Due to the closure of the FSM borders during the COVID 19 pandemic, the project team was unable to visit Chuuk until November 2022. At this time work began between JMAS and MPF to improve the procedures for removing oil from the PPW in Chuuk and also to undertake the technical survey of the target wrecks.

While plans were being developed to further enhance the JMAS work their withdrawal from Chuuk in June 2023 has required a redesign of the project. Subsequent feldwork by MPF in Chuuk in November 2023 focused on assessing the practicality of resuming oil removal operations and continuing with the technical survey of the wrecks. Signifcantly, the FSM WWII Shipwreck Pollution Mitigation Project is currently the only work being undertaken proactively on legacy PPW in the Pacifc. The intention is for this project to provide a best practice template that can be utilised by other Pacifc nations in their management of PPW within their waters.

### **8.11 Lessons and Conclusions**

The threat that PPW pose to the Pacifc has been recognised since at least the late 1990s with subsequent research focusing on identifying the scale of the threat (3855 wrecks), and the potential timing of their collapse (imminent). Organisations such as SPREP have become acutely aware of the limited capacity for Pacifc Island countries and Territories to respond to spills from PPW and note the impacts of these spills as being particularly devastating in a region so heavily intertwined with the ocean.

Despite repeated and urgent calls from the Pacifc, both the U.S. (with 10% of the total PPW) and Japan (with 86%) remain committed to a reactive approach to this issue. When forced, the U.S. Government has invested substantial funds and expertise in removing oil from three PPWs in the region, but it has yet to adopt a systematic proactive approach to dealing with its remaining PPW. Similarly, the funding provided by the Japanese Government for work on their PPW in Palau and Chuuk falls far short of what is needed, especially in light of their large number of PPW across the Pacifc Region.

Despite limited progress in addressing the PPW threat in the Pacifc, several key issues have become apparent. Most legacy PPW fall under the principle of 'sovereign immunity,' belonging to the government in control of the vessel at the time of its sinking (Monfls et al., 2006). However, what remains unclear is who is responsible or authorised to remove pollutants from these wrecks, a question that has yet to be satisfactorily answered in the Pacifc. Another challenge is what to do with the pollutants once they are removed. Pacifc Island countries, including the Federated States of Micronesia, Solomon Islands, Republic of the Marshall Islands, and Papua New Guinea, already struggle with waste oil, and this situation would be greatly exacerbated by the addition of pollutants from PPW. Additionally, there is a signifcant cost associated with exporting waste oil from these countries for proper disposal, along with the need to ensure compliance with the Basel and Waigani Conventions regarding the export and import of hazardous waste.

The threat posed by PPW to the marine ecosystems, cultures, and livelihoods of the Pacifc is evident and growing more pressing each day. The sheer scale of the problem and the complex challenges it presents necessitate a multilateral solution. Countries responsible for PPW must collaborate with impacted nations to secure the funding and expertise required to mitigate the impact of the region's PPW and safeguard the Blue Pacifc for future generations.

### **References**

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# **Chapter 9 Satellite Detection and the Discovery of** *Bloody Marsh*

**Michael L. Brennan, Geoffrey Thiemann, and William Jeffery**

### **9.1 Introduction**

Assessment and mitigation of potentially polluting wrecks in deeper water is a more challenging endeavor due to limitations of divers and operating pumping equipment at depth, but additionally because locating these wrecks is harder. While wrecks in deep water are more out of sight and out of mind, even when leaking, than those near shore, they are safer from damage by dredges, trawls or other anthropogenic activities. The wreck of the tanker SS *Bloody Marsh*, reportedly sunk off South Carolina on July 2, 1943 in 560 m of water, was considered a lower risk in NOAA's PPW study due to its location in deep water, which the NOAA Screening Level Risk Assessment Packages typically considered as less risk: 'deepwater shipwrecks tend to settle upright on the bottom, and is supported by the conclusions made by the U.S. Coast Guard in 1967 that oil will likely escape from a wreck's vents and piping long before its hull plates corrode' (NOAA, 2013b: 6). This, however, is a conclusion that needs to be reconsidered. *Bloody Marsh* was carrying a cargo of 106,496 barrels of bunker C heavy fuel oil, which is one of the largest cargoes among the vessels on the PPW list. In reviewing the 87 wrecks on the list, we selected *Bloody Marsh* as a high priority because of its large cargo and the fact that it was struck with two torpedoes and reportedly broke in half while sinking. Only ships with intact hulls would settle upright on the seabed, and therefore presumed *Bloody Marsh* did not.

M. L. Brennan (\*)

SEARCH Inc., Jacksonville, FL, USA e-mail<EMAIL_ADDRESS>
G. Thiemann · W. Jeffery CGG Services, Crawley, UK

© The Author(s) 2024 117 M. L. Brennan (ed.), *Threats to Our Ocean Heritage: Potentially Polluting Wrecks*, SpringerBriefs in Underwater Archaeology, https://doi.org/10.1007/978-3-031-57960-8\_9

This observation comes from a Coast Guard report from 1967 that indicates that wrecks that settle upright on the seabed will lose their oil through vents, and that ships that sink in deep water tend to settle upright (NOAA, 2013b: 6). While this is often the case due to the streamlined design of a vessel's hull, and hence a postulated hydrodynamic glide to the seabed, and some ships that have been sunk by torpedoes and lie in deep water have been found to settle upright, for example that of SS *Coast Trader* off Vancouver (Delgado et al., 2018), the assumption here is that vessels remained intact. *Coast Trader* was struck by a single torpedo and remained intact. *Bloody Marsh* was struck by two torpedoes and witness accounts indicated it broke in half on the surface. Therefore, when reviewing the list of PPW wrecks, we suspected that *Bloody Marsh* would be in sections on the seabed like *Coimbra* and *Munger T. Ball* (Brennan et al., 2023), and likely not upright. Another tanker wreck that illustrates this sinking pattern is that of RFA *Darkdale*, a British ship sunk of St. Helena island in the South Atlantic in 1941, which was broken into two halves, the bow inverted, and the stern section lying on its port side (Liddell & Skelhorn, 2012; Hill et al., Chap. 6 and Lawrence et al., Chap. 11, this volume).

We were able to locate *Bloody Marsh* at a depth of 465 m off South Carolina due to a fortunate survey of opportunity and that it was at a depth where hull-mounted multibeam sonar could detect it. This linked with reports of oil slicks on the surface nearby directed us to where to survey, which will be discussed in more detail herein. This wreck was also important to fnd due to its large amount of cargo (>106,000 barrels), and location near the Gulf Stream where a catastrophic leak could oil the shoreline from north Florida to Delaware (NOAA, 2013b: 31). However, due to the assumption about ships in deep water, the PPW study concluded: 'this is more likely a shipwreck to be aware of and not one considered for in-water assessment… it is unlikely that signifcant amounts of oil remain on the wreck' (2013b: 6).

Writing off wrecks in deep water due to the assumptions discussed above is premature, as the case of *Bloody Marsh* indicates. Numerous vessels were struck by multiple torpedoes and could lie in sections on the seabed, on their sides or inverted, positions in which oil would not escape through vents and piping. This example furthers the need for increased ocean exploration efforts to locate and assess potentially polluting wrecks and determine the exact state of the wreck site to progress past the desktop review initially put forth in the PPW study.

### **9.2 SS** *Bloody Marsh*

SS *Bloody Marsh* was a T2-SE-A1 oil tanker built in Chester, Pennsylvania by the Sun Shipbuilding and Dry Dock Company in 1943 (Fig. 9.1). The T2 class tankers were a pre-fabricated commercial design that started production in 1940 by Sun Shipbuilding for the Standard Oil Company. These tankers were designed with standard dimensions and commonly available machinery to fast-track their construction. The T2-SE-A1 tanker was an 'oceangoing, single screw oil tanker of about 500 feet waterline length that had turboelectric propulsion, carried less than twelve

**Fig. 9.1** *Bloody Marsh* (U.S. National Archives)

passengers, and had a deadweight of 16,000 tons (approximately 141,000 barrels)' (Spyrou, 2006: 3). Following the attack on Pearl Harbor in December 1941, the U.S. Maritime Commission ordered additional tankers to supply the war effort and replace those being lost from U-boat attacks. A total of 536 T2 tankers were built of three types, and 525 were nearly identical T2-SE-A1 vessels. This basic type vessel was based on the standard ship designed and built by the private commercial oil company in response to the establishment of an emergency tanker program, which was in response to the signing of the Lend-Lease Act in March 1941 to provide aid to Britain (Sawyer & Mitchell, 1974). The hulls of these tankers were all welded, which was a relatively new method introduced in the late 1930s. Some of these tankers developed hull fractures due to the electric welds and quality of the mild steel used for the hulls in cold temperatures that made the crystalline structure of the metal brittle (Spyrou, 2006). Notable instances of these tankers breaking in half include *Schenectady* in January 1943 and SS *Pendleton*, which sank in a storm off Cape Cod in February 1952 and inspired the novel and flm, *The Finest Hours*. *Bloody Marsh* was sunk in warm summer waters off South Carolina on its maiden voyage, so the structure of its hull did not have the chance to be tested.

*Bloody Marsh* was loaded in Houston with 106,496 barrels of Navy fuel with specifc gravity 13, and departed for New York under Master Albert Barnes operating for the Cities Service Oil Company. The tanker was not completely full; reports indicate tanks 2–8 were full as were wing tanks 3–8, and wing tank #2 was approximately ¾ full. Not sailing with a convoy, the tanker sailed from Houston in a zigzag pattern through the Gulf of Mexico and around Florida, as was common antisubmarine defense procedure. About 75 min before the attack, the tanker stopped this pattern and ran a straight course (Burch, 1943). The frst torpedo from U-66 struck the port quarter at the engine room, causing the ship to immediately begin to settle by the stern, and the ship sunk until the gun platform was 'nearly awash' when the second torpedo struck amidships at the #3 tank, breaking the ship in two. The stern sank almost immediately while the bow foated free for 3–5 min before sinking (Burch, 1943: 2–3). The torpedo indicator went off about 30 s prior to when the frst torpedo struck. The ship turned hard to port and was swinging in that direction as the torpedo hit. The bridge issued a distress signal 'SOS SSSS SOS BLOODY MARSH 31.33 N 78.55 W TORPEDOED' two or three times following the frst strike, which was the only transmission the tanker sent during its entire voyage (Burch, 1943: 6). The course steadied after the explosion and gradually slowed, then proceeded at about two knots until the ship was abandoned.

The crew consisted of 50 merchant crew and 28 armed military personnel. By the time the second torpedo struck, all surviving crew had abandoned the ship in lifeboats with the exception of the Commander of the Armed Guard Unit and three enlisted men at the stern gun, who joined the crew after the second explosion. The crew spotted the U-boat before the fring of the second torpedo when it surfaced and moved toward the ship and lifeboats. Two rounds were fred from the submarine's deck gun at a 5 s interval directly after the release of the second torpedo, but it is not known if that was directed at the sinking tanker or the survivors (Burch, 1943: 4). Following the second torpedo, the submarine struck the stern of the No. 1 lifeboat, which raised it up from the water and knocked several survivors out, one of whom landed on the submarine before falling into the water. The submarine reportedly stayed in the area for 15–20 min but did not open fre on or attempt to capture any survivors. Survivors described the submarine based on their quick glimpses in the dark and a sketch was produced based on their observations (Fig. 9.2). A total of three crew were killed in the attack likely from the frst explosion: third Assistant Engineer, Robert T. Winslow; Fireman, James B. Mitchell; and Oiler, Frank B. Robuck, all of whom were on duty in the engine room at the time of the attack (Moore, 1983). The 75 survivors were picked up by SC 1049 and brought to

**Fig. 9.2** Sketch of U-66 based on descriptions of survivors (U.S. National Archives)

Charleston, South Carolina the following morning. This attack is compared to U-66's sinking of SS *Esso Gettysburg* the month before off the east coast of Florida, a tanker that was traveling the same route as *Bloody Marsh*.

### **9.3 Initial Expedition**

In 2018, NOAA Ship *Okeanos Explorer* published its planned mapping expedition location off the southeastern US and the frst author submitted *Bloody Marsh* as a potential mapping target. Previously, the Kongsberg EM302 multibeam sonar was run over the wrecks of *Gulfoil* and *Gulfpenn* in the Gulf of Mexico from exploration vessel (E/V) *Nautilu*s. Each wreck is at about 500 m depth and this was a test of the detection capability of the hull-mounted sonar over large oil tanker wrecks; they were visible but only as small bumps on the landscape. However, this indicated that the wreck of *Bloody Marsh* could be detected with hull mounted sonar. Multibeam expert Gary Fabian reviewed the data collected from *Okeanos Explorer* and found a target approximately the right size for the tanker, however when the ROV dived on it, it was determined to be a natural rock outcrop (Brennan, 2019).

Following this result, the geoscience company CGG reached out to maritime archaeologists at SEARCH through a mutual colleague at the Bureau of Ocean Energy Management (BOEM). CGG had previously licensed BOEM with an offshore natural oil seepage study across the US East Coast, which included satellitedetected oil slicks around the documented site of the *Bloody Marsh* recorded over several decades. It was hoped this specifc oil slick dataset could help refne the search area for future explorations for the wreck.

### **9.4 Satellite Detection of Sea Surface Oil Slicks**

The detection of oil slicks from sunken shipwrecks, and the usage of those oil slicks in the subsequent locating of a vessel is not in of itself a new technique. Following the loss of the bulk carrier MV *Derbyshire* in 1980, oil slicks were reported by patrol aircraft of the Japanese Maritime Safety Agency a week after the vessel's disappearance. These oil slick records, paired with ocean current models, allowed the successful discovery of the wreck location with side-scan sonar and an ROV dive in 1994 (Mearns, 1995).

The detection of the presence of oil slicks by satellite imagery is also not a new occurrence. Indeed, CGG were the frst to extensively test new satellite systems in the early 1990s, partnering with the British National Space Centre (BNSC) and several oil companies at the time to test theories of oil slick detection. Since then, many new satellites have been launched, adding to the archive of satellite imagery capable of recording oil slicks. CGG has utilised this dataset to build a global database of oil slicks around the world.

The original BOEM natural oil seepage mapping study provided by CGG follows oil slick mapping and classifcation techniques frst developed to document spatially repeating oil slicks across a satellite imagery stack over multiple imaging dates (Press & Lawrence, 1995). By observing a large imagery stack over a location across multiple dates, features can be observed that may be infrequent/ephemeral, whilst allowing for false positive features that may be misidentifed on single imaging occurrences (e.g., oil slicks sourced from shipping) to be removed.

In the region of the proposed *Bloody Marsh* site, the study utilised 76 satellite images recorded from 1992 to 2019, of which 16 documented notable oil slicks (see Table 9.1 and Fig. 9.3). This imagery, a mixture of Synthetic Aperture Radar (SAR)

**Table 9.1** Slicks observed across satellite imagery

Note: Two parallel slicks with potential affliation to the Bloody Marsh were observed on the Landsat-8 image acquired on the 24th May 2019 and shown in Fig. 9.3

**Fig. 9.3** Oil slicks mapped across 16 satellite images from 1992 to 2019, compared to the (imprecise) historically documented location of the *Bloody Marsh* wreck site. Whilst the majority of slicks originate from the southwest within a relatively constrained region with a radius of ~1.5 km, two notable outlier slicks are documented approximately 10 km away from this repeat location (imaged on 4th December 2008 and 24th May 2019). These outliers may refect signifcantly different currents within the water column at the time of imaging or additional seabed oil sources

and multispectral, was sourced and processed from the Open Access archives of the European Space Agency (ERS and Sentinel-1), Canadian Space Agency (Radarsat-1), Japanese Space Agency (ALOS-1) and the United States Geological Survey (Landsat-8).

### **9.5 Oil Slick Evidence Towards** *Bloody Marsh* **Wreck Location**

While only 20% of images used in the BOEM study documented oil slicks in the region, the reoccurrence of slicks across 27 years was highly indicative of a persistent fxed seafoor origin of the surface oil (see Fig. 9.3). Recent studies of other fxed point oil release sites around the world, at varying depths, carried out by CGG and others, resulted in the conclusion that these slicks showed strong spatial correlation to a single point source.

Typically, sea surface oil slicks fed from seabed sources (natural or anthropogenic) tend to develop curved 'corkscrew' morphologies as the overlying sea surface rotates due to near-inertial oscillation drift. This is due to most satellite scenes that observe oil slicks being acquired at low wind speeds, due to the requirement of

relatively calm conditions for the slicks to form. However, the slicks observed in the *Bloody Marsh* region were observed to drift in the strong Gulf Stream currents off the coast of South Carolina. These currents, averaging 10.3 km/h, act to drift the surfacing oil slicks rapidly away from surfacing location, leading to long linear slicks ranging from approximately 5–110 km. Crucially, the surfacing location of these slicks (origination point) where observed in the same location and the long drifting slicks showed no sign of fragmentation before evaporation. This strongly suggested that the release of oil from the wreck was likely continuous, and those images in CGG's archive that did not record an oil slick where likely to be due to other mitigating met-ocean conditions. When utilising the multispectral data in particular, that images oil directly, thicker components of the oil slick could be observed at the southwestern end of the slick, in keeping with the theory of a subsurface release, before thinning and drifting in the currents (Fig. 9.4).

Importantly, the site of the recurring oil slicks mapped by CGG was 12 km southwest of the historically documented location of SS *Bloody Marsh* and previous surveys. Following on from these observations, 3D models of oil plumes in the water column were created based on the prevailing currents in the region. These allowed backtracking of the oil source from the sea surface slick observation locations towards a clear target area on the seabed.

**Fig. 9.4** Contrast enhanced Landsat-8 image of a sea surface oil slick (linear feature running *s*outhwest to northeast) acquired on 27th June 2014. The origin point of the oil slick can be determined as the southwestern end by the presence of thicker oil (silver/metallic appearance) which disperses and thins out into a sheen as currents move the oil slick away from the source point. Landsat-8 image courtesy of the U.S. Geological Survey

### **9.6 Discovery**

An additional survey request was made to NOAA, and a target was detected only a few miles from the downstream limit of the oil slicks. The target measured shorter than the length of the tanker, and was a single target, where the reports of *Bloody Marsh*'s sinking have it breaking in half at the surface. However, the target was located in a relatively fat area of seabed two miles directly downstream of the oil slick origins on the surface, so was a promising target.

On October 28, 2021, ROVs *Deep Discoverer* and *Seirios* were launched from *Okeanos Explorer* to locate and identify the multibeam sonar target. Maritime archaeologists participated in the dive in real-time through telepresence capability on board the ship through NOAA's Ocean Explorer website and directed the dive remotely (Brennan et al., 2018). The ROV approached the target at 465 m depth and frst came upon a debris feld that was the remains of the destroyed stern and engine room. Immediately adjacent to this was the prominent hulk of the oil tanker completely inverted on the seabed (Fig. 9.5). A small amount of hull remained from the engine room, and a bulkhead between that space and the aft tanks appeared intact. Corroded holes were visible in the hull, but only those over machinery spaces. Like the *Coimbra* wreck, corrosion was more visible in areas of hull that had seawater on both sides; areas of hull that appeared to contain intact tanks had less corrosion (Brennan et al., 2023). Moving southeast forward along the wreck, the hull plate joinery indicated welded seams, which, along with the location, helped to positively identify the wreck as *Bloody Marsh*.

The main hulk of the wreck had few visible features, as the ship was completely turtled and the superstructure and decks buried in sediment. Biologists viewing the stream live commented that the wreck was colonised by what appeared to be a single species of gorgonian coral all of a similar size, indicating a single colonisation

**Fig. 9.5** ROV image of the broken stern end of *Bloody Marsh* at the joinery between the engine room and cargo tanks (NOAA Ocean Exploration)

event. The ROV documented the starboard side of the wreck, but was unable to move around to the east-facing port side due to a strong current, therefore if any superstructure remains or debris lie on the seabed on that side, it was unable to be seen during this dive. When the ROV reached the forward end of the wreck, the measurement of the hull section indicated approximately 300 feet of hull. Subtracting the destroyed engine room, this would suggest that another 100 feet or so of hull remains. However, the bow section was not visible beyond the wreck and the current prevented further exploration in the area. The break in the hull, based on this measurement, appears to be at Tank #3, which is consistent with historic accounts. Therefore, the bow section could contain intact tanks #1 and 2 as well the as Deep and Fore Peak tanks forward. Future exploration in this area would be needed to locate and document this section.

### **9.7 Discussion and Conclusion**

We had initially suspected *Bloody Marsh* could be a greater pollution risk than the PPW assessment projected due to its large cargo and the incident of its sinking. Had the vessel settled upright on the seabed, as the PPW report suggests is likely for wrecks in deep water, oil cargo would have escaped through the vents over time (NOAA, 2013a, b). This was the case for *Coast Trader* off the northwest Pacifc coast (Delgado et al., 2018), as well as tanker wrecks in the Gulf of Mexico including *Virginia*, *GulfOil* and *GulfPenn* (Church & Warren, 2008), all of which sank intact in one piece. However, other oil tanker wrecks, such as *Coimbra* and *Munger T. Ball,* illustrate that ships sunk by torpedoes that break into multiple sections do not settle evenly on the seabed (Brennan et al., 2023). While those wrecks lie in shallower water, this proves to be the case for *Bloody Marsh* as well, and potentially indicates that other tankers sunk in deep water that remain undiscovered should also be considered high pollution potential as they may not have righted as they sank, especially if broken. This case study also serves as a proof of concept for utilising surface oil slicks as indicators of leaking oil tankers if oceanographic modeling can assist in back-calculating the wrecks' locations. As many of the PPW wrecks that remain to be discovered are in deeper water, this presents a promising method for locating other sites, especially those with cargos that are in danger of releasing.

The discovery of *Bloody Marsh* illustrates the complexity of locating shipwrecks in deep water. The size of the tanker and the depth at which it sank allowed for multibeam sonar to detect it once the satellite data redirected the search to a new area. This work shows the importance of technological advancements and data review to detect leaking wrecks and its potential to locate undiscovered sites. Additional survey in the area of *Bloody Marsh* is, however, still needed, as the 100-foot bow section remains missing. The second parallel slick identifed in the satellite data could be this section, which is large enough to have some of the cargo tanks intact and still

containing cargo. Further survey may locate this section potentially downstream of that second slick. The overturned hull of the tanker appeared stable, suggesting large amounts of oil could remain inside, and this site could be one to be considered for ROV-based mitigation in the near future.

**Acknowledgements** We would like to thank Pam Orlando and Frank Cantelas with NOAA for providing research materials from the National Archives, Kasey Cantwell, Matt Dornback and Derek Sowers from NOAA Ocean Exploration for coordinating the mapping and ROV dives, and Gary Fabian and Matt Horn for data review and advice.

### **References**

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# **Chapter 10 Searching for a Lost PPW: SS** *William Rockefeller*

**John Detlie**

### **10.1 Introduction**

Possibly the most unfortunate legacy of the Battle of the Atlantic is the great number of wrecks lying in coastal and marine waters that still contain oil, unexploded ordnance, and other pollution or safety hazards. This has become an increasingly pressing issue in recent years, as these wrecks are now entering their eighth decade underwater and many are experiencing signifcant structural degradation due to natural corrosion and anthropogenic causes. While some of these potentially polluting wrecks have been located and steps taken to mitigate their pollution risk, many more remain missing, particularly those which sank in deep water (NOAA, 2013a, b; Symons et al., 2014; Hoyt et al., 2021; Brennan, Chap. 1, this volume).

This chapter discusses a potential method for locating these missing wrecks, using as a case study the oil tanker *William Rockefeller*. *Rockefeller* was a twinscrew, steel-hulled oil tanker, owned and operated by the Standard Oil Company of New Jersey. It was 554 feet long with a 75-foot beam and a gross tonnage of 14,054 tons. Its cargo capacity was 22,390 deadweight tons, or approximately 146,745 barrels of oil, carried in eight tanks amidships divided by 13 oil-tight bulkheads. When launched in 1921, *Rockefeller* and its sibling ship *John D. Archbold* were the largest oil tankers in the world. *Rockefeller* operated in the Gulf and Pacifc oil trades for most of its career, though with the advent of World War II it began taking on cargo from international ports (Newport News Shipping and Dry Dock Company, 1920:9–20; Standard Oil, 1946:320–321).

© The Author(s) 2024 129

J. Detlie (\*)

East Carolina University, Greenville, NC, USA e-mail<EMAIL_ADDRESS>
M. L. Brennan (ed.), *Threats to Our Ocean Heritage: Potentially Polluting Wrecks*, SpringerBriefs in Underwater Archaeology, https://doi.org/10.1007/978-3-031-57960-8\_10

On 28 June 1942, *Rockefeller* was sailing past Cape Hatteras en route from Aruba to New York with a cargo of heavy fuel oil when it was ambushed by the German submarine *U-701*. A single torpedo caught *Rockefeller* amidships, breaching one of its storage tanks, spraying oil across the deck, and setting the ship on fre. After its crew abandoned ship, *Rockefeller* was left to drift with the currents and wind before fnally going down sometime later. There are several versions of *Rockefeller*'s sinking; contemporary accounts indicate that it either sank on its own or after *U-701* hit it with a second torpedo almost 12 h after the attack, while some secondary sources record a claim that it was sunk the following morning by the Coast Guard as a hazard to navigation (Fig. 10.1) (Degen, 1942; Standard Oil, 1946:321–323; Hoyt et al., 2021:7–278).

When it went down, *Rockefeller* was carrying 136,647 barrels (5,739,174 gallons or 21,725,136 liters) of heavy fuel oil, excluding its bunkered fuel. Some of this oil was spilled or burned off by *U-701*'s torpedoes, but it is probable that a signifcant

**Fig. 10.1** Attack locations and possible sinking locations derived from various sources on *Rockefeller*'s loss. From bottom to top: the point at which *Rockefeller*'s known course diverged from prescribed convoy routes; attack location as given by uboat.net; attack location as given in the Offce of the Chief of Naval Operations' (OCNO) supplemental statement to the summary of events given by *Rockefeller*'s crew; sinking location as given by uboat.net; attack location as given by *Rockefeller*'s master William Stewart; sinking location based on OCNO's coordinates, given a sinking time just before midnight of 29 June; sinking location based on Captain Stewart's account, given the above sinking time; sinking location based on OCNO's statement given an approximate sinking time in the early morning of 29 June; sinking location based on Captain Stewart's account, given the ship sinking on the morning of 29 June. (OCNO, 1942b, c; uboat.net 2021; map drawn by the author)

amount remains in the wreck (OCNO, 1942a, c; Standard Oil, 1946:321; NOAA, 2013b:13). Because of this, it is one of the 87 wrecks listed in the RULET database given the potential it poses for severe pollution of the Eastern seaboard. Since the wreck has not yet been located and its condition is unknown, NOAA's risk assessment screening package has recommended conducting surveys of opportunity to locate the vessel, determine its condition, and judge whether it is an imminent hazard (NOAA, 2013b:16–22, 38–39; Symons et al., 2014).

Since *Rockefeller* sank after drifting for at least 11 h, possibly more, and the only claimed eyewitness to its sinking did not give coordinates for its last resting place in his narrative of events, establishing a search area for the wreck has proven problematic (see Fig. 10.2). Some estimates have suggested that a search would encompass up to 750 square nautical miles (NOAA, 2011, 2013b:6). As this area would require signifcant outlay of time and effort to fully cover, this chapter discusses a means by which this potential search box may be shrunk to a more manageable size using Bayesian search theory, a method that has been tested and proven in multiple maritime searches. If successful in locating *Rockefeller*, this methodology may be useful in the creation of search models for other potentially polluting shipwrecks lost under similar circumstances.

### **10.2 Why Bayesian Search?**

A shipwreck is typically a high-stress event involving imminent risk to life and limb, with accompanying repercussions for the thought processes, emotions, and memories of those involved (Gibbs, 2002:72–76). Even if someone thinks to record a sinking ship's last coordinates in the heat of the moment, it is very possible that these coordinates will be mistaken, or later misremembered. One has only to look at the records of past wreck search expeditions to see this problem in action: numbers are transposed, latitudes and longitudes are scrambled, and in some cases the coordinates given are simply wrong. Possibly the most notorious example of this phenomenon is that of the RMS *Titanic.*  Subsequent search expeditions took this position data at face value and based their efforts on it, only to come away empty-handed. It was not until Dr. Robert Ballard reevaluated the problem, concluded that the positional data must be in error, and expanded the search area that *Titanic* was relocated in 1985, 13 nautical miles from the position given by Bride and Phillips (Ballard, 1987:23, 26, 66, 83).

The problem for the archaeologist or historian is how to sift through these disparate or sparse sets of information in such a way as to maximise their chances of completing a successful search. Then comes the second issue, which is equally important: selecting a theoretical framework/model into which this data can be fed to generate a search plan. All this is done with an eye toward optimising the search parameters so as to produce the highest chance of success with the least expenditure

of money, time, and effort. Dr. Lawrence Stone refers to this as the basic problem of optimal search (Stone, 1975:32). There have been a variety of methods proposed for the solution of this problem, but Bayesian search theory offers a method that accounts for all possible scenarios while still allowing researchers and archaeologists to focus their efforts on a smaller, high-priority search area. It has been successfully employed in multiple maritime search efforts, including the recovery of an H-bomb lost off the coast of Spain in 1966 and locating the wrecks of USS *Scorpion*, SS *Central America*, and Air France Flight 447 (Richardson & Stone, 1971:141–144; Stone, 1992:42–53; Sontag et al., 1998:58–60, 104–106; Craven, 2001:167–170, 173–174, 213; Frost & Stone, 2001:3–4; Stone, 2011:21, 23; Stone et al., 2014:72–80).

Bayesian search theory is based on the statistical models of eighteenth-century English statistician and philosopher Thomas Bayes (Bayes & Price, 1763). Put simply, Bayesian statistics operate on a defnition of probability wherein 'probability' expresses a degree of belief in the occurrence of a given event. This belief may be based on prior knowledge of the event, whether derived from personal experience or historical records, or it may be based on one's own theories or beliefs about said event. The probabilities are expressed as part of an equation which is used for a given purpose, in this case searching for a lost shipwreck.

Bayesian theory as applied to maritime search is a relatively straightforward concept. The researcher must form as many reasonable hypotheses as possible about what may have happened to their target object, based either on hard data or their own beliefs. These hypotheses are used to generate a probability density function for the object's location, which calculates the probability of a random variable (in this case, the location of a submerged object) falling within a particular range of values (Stone, 2011:23).

After this, a second function is constructed which expresses the likelihood that the target object will be found at a given location, *if it is really in that location*. This information is used to generate a probability map, which gives the probability of fnding the target object in a given location for all possible locations within the projected search area. After this, a search grid and path is devised that covers the entire area from highest to lowest areas of probability. During the search, the probabilities must be continually revised according to the fndings. For example, if the object is believed to have fragmented before sinking, and fragments are not found in the areas where they are most likely to be according to the map, then the fragmentation hypothesis becomes less probable and should be revised or discarded accordingly (Stone, 2011:23–24).

As new data is gathered, it is fed into the model to update the probabilities contained therein. The model, of course, is only as good as the data that is used to make it, so someone who employs Bayesian search theory must be sure that they are collecting and using data that is as accurate as possible. Given the problems mentioned at the beginning of this section, this is not always an easy task. Such proved to be the case when applying the principles of Bayesian search to the problem of fnding *William Rockefeller*.

### **10.3 Searching for** *Rockefeller*

In the case of *William Rockefeller*, there existed several eyewitness accounts of the attack on the tanker, including its master William Stewart and Kapitänleutnant Horst Degen, the captain of *U-701*, who was captured and interrogated after his submarine was sunk in the vicinity of Cape Hatteras on 7 July 1942. These accounts form the basis of most of the research done on the tanker's loss; while they are in general agreement as to *Rockefeller*'s last hours afoat, there were some discrepancies that had to be accounted for. Most of these discrepancies could be put down to the stress of the sinkings and the unreliability of human memory, though there were indications of deliberate obfuscation or selective recall, especially when comparing the initial accounts of the attack to those set down years or decades later (Degen, 1942; OCNO, 1942a, c; Standard Oil, 1946; Offey, 2014). The accounts were used to construct a series of scenarios for *Rockefeller*'s loss, with the aim of covering all the possibilities as to the tanker's fate. They may be summarised as follows:

As is obvious, the scenarios cannot all be correct, so what weight is to be given to each of them? This is a task requiring subjective probability analysis; in plain language, this analysis involves a person looking at all the information they have gathered and deciding what they believe to be the most reliable. This is a part of the Bayesian method that is meant to quantify the otherwise unquantifable human factors of intuition, gut feelings, and hunches. This is not to say that the process is unscientifc, for it requires the person or persons conducting the analysis to carefully study the available data and evidence when making their decisions, but it contains an element of uncertainty since it is based on subjective opinions (Stone, 1992:45–46; Sontag et al., 1998:59, 104–105; Craven, 2001:167–168). In this case, the author decided that Scenario 2 was the most likely, since it tracked closely with what is generally accepted about *Rockefeller*'s last hours and Degen provided a persuasive account of his claimed second attack on the submarine (USONI, 1942; Offey, 2014). Scenario 1 overlaps in most particulars with Scenario 2; it may even be the case that Degen's second attack on *Rockefeller* was seen and processed as the tanker sinking on its own. These two scenarios were therefore weighted as being equally likely. The third scenario is not well-supported by the primary sources and appears mainly in secondary sources; it was therefore rated as the least likely of the three.

With the scenarios devised and weighted, a probability map was created using ArcGIS and SAROPS, a software package developed for the US Coast Guard that employs Bayesian mathematics and Markov chain Monte Carlo simulations to generate probability maps for maritime search-and-rescue efforts (United States Coast Guard, 2008; Kratzke et al., 2010:1–2).

Monte Carlo simulations are used to calculate the results of a scenario with numerous variables, expressing the outcome as a probability distribution showing the range of possible outcomes according to the likelihood of their occurrence. However, a standard Monte Carlo simulation is not suitable for more complex problems, since it relies on the assumption that the values for which it calculates results are independent of each other and may be drawn independently. The solution to this problem is to use a Markov chain, which calculates each successive variable based on the value of the last variable generated, creating a stochastic chain that allows for greater fexibility in generating the fnal probability density (Brownlee, 2019).

SAROPS uses Markov chain Monte Carlo simulations to generate a probability density function by sequentially generating random variables based on the data that is fed into the program. For a typical SAR scenario, this data is acquired in real time, which enables the production of highly accurate maps (Roylance, 2007:4D). In this case the simulation had to rely on historical data, which added a greater degree of uncertainty to the outcome. The two main variables were the currents and wind speed prevailing during the attack; a combination of interpretations and contemporary data had to be employed to reconstruct them.

The attack occurred within the Gulf Stream, meaning that *Rockefeller*'s drift after being abandoned would have been infuenced by this relatively strong and predictable current. Its precise speed on 28 June 1942 is not known, but the Coast Guard casualty report for *Rockefeller* indicates the ship was drifting at 1.5 kt when abandoned (USCG, 1944b). Data obtained from a 1942 Coast and Geodetic Survey publication indicated that the Gulf Stream was then known to fow strongly northeastward during the summer months, peaking in strength during July. The monthly average of the Gulf Stream in June as measured by the Diamond Shoals lightship from 1919 to 1928 was 0.66 kt (Haight, 1942:24–25, 52). It is therefore probable that the Stream was pushing *Rockefeller* northeast at low speed. Similar examples of Gulf-infuenced drift can be seen in the cases of the merchant ship *Papoose* and *U-701*. *Papoose* was torpedoed approximately 15 miles southwest of Cape Lookout, North Carolina, and drifted north with the Stream for 2 days before sinking off Oregon Inlet, and the survivors of *U-701* were carried northeast with the current for 49 h before being recovered by the Coast Guard (USCG, 1944a; USONI, 1942:1; Hickam, 1989:278–282; NOAA, 2022).

Wind speed is another variable for which assumptions and estimates had to be made, though in this case more solid data was available. *Rockefeller* was being escorted by a Coast Guard cutter that logged weather data at 4-h intervals, noting general conditions, barometric pressure, cloud cover, visibility, and wind speed. At noon, 16 min before *Rockefeller* was attacked, the cutter logged the following weather data: barometric pressure 3001, winds from the southwest at Beaufort Force 1 (1–3 mph/1–3 kt), blue skies with scattered cumulonimbus clouds, visibility 7 miles (USCG, 1942:2). Given that *Rockefeller* was drifting at about 1.5 kt when it was abandoned, it may be presumed that the wind was very light at this time, possibly not more than 1 kt, therefore both wind and current would have been exerting force against the tanker's hull.

These estimates were added to a data package which also included events, times, *Rockefeller*'s speed (known or estimated), *Rockefeller*'s position, general weather conditions, and compass bearings. The package was then sent to the Coast Guard to be input into SAROPS. Senior Chief Petty Offcer Ian Brown, an experienced SAROPS technician, was given the task of creating the SAROPS model. He consulted with oceanographer Dr. Cristina Forbes, who helped him format the data for SAROPS, calculated possible wind and current speeds, and proposed that he create three different scenarios based on possible weather conditions at the time. After this consultation, Chief Brown fed the resulting data into the SAROPS simulator. He explained to the author that the maximum vessel length that could be input into the program was 300 feet, since the program is tailored toward searching for lost individuals and small craft, not large vessels. As *Rockefeller* was 554 ft. in length, this meant that he had to split the simulated vessel into two parts and recombine the results later. He also input the estimated current, wind, and drift speeds from the historical data and his consultations with Dr. Forbes. All times in the program were recorded in Greenwich Mean Time (GMT) and were then adjusted into Eastern War Time (EWT) (Ian Brown 2022, pers. comm.).

To account for the uncertainty of wind speeds, Chief Brown ran multiple iterations of the scenario. For the frst iteration, he used a wind speed of 0.87 kt and a current speed of 0.66 kt until time index 1700 GMT (1300 EWT), representing the likely point at which *Rockefeller* would have been in the middle of the Gulf Stream and experiencing its full strength, which he calculated at 1.5 kt. For the second iteration of the scenario, he used a wind speed of 1.74 kt and the same current estimates as in the frst iteration, with *Rockefeller* entering the middle of the Gulf Stream at time index 1700 GMT/1300 EWT. For the third iteration, he again used the same current estimates and a wind speed of 2.6 kt. Each of these iterations produced a probability density cloud illustrating potential sinking locations for *Rockefeller* as based on the estimates fed into the program. For each stage of the scenarios, he placed a ring around the density cloud to indicate the general size of the area of potential drift, given in square nautical miles (Ian Brown 2022, pers. comm.).

These density clouds were added to an ArcGIS map containing the sinking locations from the historical records and a drift analysis created by the author to produce a fnal probability density map (see Fig. 10.2). A search grid was imposed over the area of highest density with cells measuring 16 square nautical miles each; this grid covers a total of 384 square nautical miles. The potential search area has thus been almost halved from NOAA's original estimate of 750 nautical miles. If sectioned into a grid of 4 by 4 nm segments, this gives 24 cells in which to search within this box (see Fig. 10.3). The question that follows is how to further prioritise the search area to maximise the chances of success. According to Bayesian methods, the

**Fig. 10.2** Combined density cloud containing data points from the author's GIS work and the SAROPS simulations. (Map created by the author and Senior Chief Ian Brown)

**Fig. 10.3** Calculated sinking locations with priority search grid overlaid. (Map drawn by the author)

factors that must be considered here are the following: the *prior distribution* of information, the *subjective probabilities* of the occurrence of given events, and *posterior distribution* of data obtained from previous search efforts (Stone, 2011; Stone et al., 2014; Rossmo et al., 2019).

When speaking of maritime search, the *prior distribution* consists of any data collected prior to the current operation. As an example, we may consider the prior distribution of the 2011 search for Air France Flight 447's black box, which was conducted by Dr. Lawrence Stone using Bayesian methods. In that case, the prior distribution consisted of the last GPS ping received from Flight 447 before its disappearance, the estimated distance the plane might have traveled from its last known position based on the cessation of signal data, and the recovery locations of debris and victims from the wreck, which was used to plot a reverse-drift scenario to estimate the crash location (Stone et al., 2014:72–75).

In the context of the search for *Rockefeller*, the prior distribution consists of the historical and spatial data assembled regarding *Rockefeller*'s loss and the maps and models created from this data. The balance of the data suggests strongly that *Rockefeller* drifted slowly northeastward after being abandoned, probably not more than 17 nm and almost certainly no more than 25 nm. There is some margin of error here; *Rockefeller*'s given drift speed of 1.5 kt is only an approximation based on the Coast Guard casualty report, and it is possible that the winds may have shifted, pushing it in another direction. This factor was accounted for in the Coast Guard's SAROPS probability maps, which posited three different wind speeds and applied different current speeds as well throughout the scenario.

The next factor to be considered is the *probability of events occurring*. This is a subjective, not objective factor, since in this case the probability is based on what the person conducting the study knows or believes to be true. As stated previously, this study has accepted KptLt Degen's account of sinking *Rockefeller* as the most probable scenario with allowance for the fact that the tanker may also have sunk on its own around the same time, as stated in Scenario 1. The third scenario, in which *Rockefeller* was scuttled by the Coast Guard, is regarded as less probable and has been weighted accordingly. Each scenario was given a percentage, all of which added to 100: Scenario 1 = 45%, Scenario 2 = 45%, Scenario 3 = 10%. If a search is undertaken, these probability percentages can be fed into the basic Bayesian probability equation, which runs as follows:

$$P\left(\left.\mathcal{A}\right|B\right) =\_{P(B)}^{P(B|\mathcal{A})P(\mathcal{A})}$$

where P (A|B) is the conditional probability of event A given event B; P (B|A) is the conditional probability of event B given event A; P(A) is the probability of Event A;

P(B) is the probability of Event B (Rossmo et al., 2019:45).

In this case, there are three events to solve for, those being the scenarios described previously. Event A may be given as Scenario 1 (*Rockefeller* sinking on its own), Event B as Scenario 2 (Degen sinking *Rockefeller* with a second attack), and Event C as Scenario 3 (*Rockefeller* being scuttled by the Coast Guard). Some of these equations are zero-sum games. Degen's account and the scuttling scenario cannot both be true, thus the conditional probability of Event B given Event C would be zero, and vice versa. The only way to know for sure is to go and look. When a search operation is launched, this equation and its derivatives may be used to update the probabilities according to the search fnds, with the results fed into the predictive model in ArcGIS to create an updated search map.

The *posterior distribution* of information is assembled from all data acquired during previous search efforts. In the case of AF Flight 447, the posterior distribution included various unsuccessful searches for the plane's wreckage in 2009 and 2010, which Dr. Stone and his colleagues factored into their probability maps (Stone et al., 2014:75–79). In the context of this study, there is no posterior distribution to consider, as there have been no searches conducted for *Rockefeller*'s remains. It may be the case, of course, that this study's conclusions are in error and a search based on them fails to locate *Rockefeller*'s wreck. In this case, a posterior distribution can be created from the data obtained in this search and used to refne the search area for the next expedition.

In the context of the initial search for *Rockefeller*'s wreck, the areas of greatest coordinate density are the four cells in the center of the grid and the two cells at its lower left edge. Focusing the search on these cells further reduces the priority search area from 384 square nautical miles to 96 sq. nm. Searching these grid cells is therefore the logical place to begin. Should the ship not be found in these areas, the remainder of the grid can be covered in descending level of priority, either in the same expedition or a follow-up search.

### **10.4 Conclusion**

This chapter has presented a method for locating lost potentially polluting shipwrecks in American waters, using Bayesian search theory and computer modeling to calculate the potential drift of an abandoned ship prior to its sinking. The initial results have produced a more manageable search box that can be further subdivided into smaller search areas based on the time and resources available. Furthermore, these search areas can be easily covered by existing underwater search technologies such as side-scan sonar and autonomous underwater vehicles. Should this method prove successful in locating the wreck of *William Rockefeller*, it can be repeated for other missing potentially polluting wrecks, provided suffcient data is available.

**Acknowledgments** The author gratefully acknowledges the cooperation and contributions of Ole Varmer and the United States Coast Guard in this study.

### **References**

Ballard, R. D. (1987). *The discovery of the Titanic*. Warner Books.

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# **Chapter 11 Assessment Methodologies for Potentially Polluting Wrecks: The Need for a Common Approach**

**Mark Lawrence, Stuart Leather, and Simon Burnay**

### **11.1 Introduction**

There are believed to be more than 8500 Potentially Polluting Wrecks (PPW) lying on the seabed around the world, including many oil tankers, which potentially still contain very large quantities of oil. With many of these wrecks having been submerged for nearly 80 years (and sometimes more), the condition of their hulls is continuing to deteriorate, which combined with the increase in the frequency of severe weather events, means that the risk of signifcant pollution is increasing, particularly for wrecks in shallower waters.

The release of large quantities of oil from the catastrophic collapse of these wrecks is therefore an increasing risk. The resulting major pollution incidents would cause signifcant damage to the ocean environment, biodiversity and blue economies. The impact on the Global South coastal states, where there is a higher reliance on fshing communities and ocean economies, would be acute, as there is very limited capacity to deal with these events in those areas.

To understand the risk of pollution emanating from any wreck, the wreck must be assessed to determine its condition, the rate of deterioration, the likely pollutants remaining on board, the impact of any pollution and what methods might be feasible for preventing a release of pollutants into the ocean environment. From this assessment, viable management plans and intervention strategies for each wreck can be developed. The management and intervention of wrecks can then be prioritised according to the risk they present.

© The Author(s) 2024 143

M. Lawrence (\*) · S. Leather (\*) · S. Burnay

Waves Group Ltd., London, UK

e-mail<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>
M. L. Brennan (ed.), *Threats to Our Ocean Heritage: Potentially Polluting Wrecks*, SpringerBriefs in Underwater Archaeology, https://doi.org/10.1007/978-3-031-57960-8\_11

### **11.2 Current Status of Wreck Assessment Methods**

A number of nations have developed methods for the risk assessment and management of PPW, including comparison between different wrecks in order to prioritise the need for intervention, according to the risk of the wreck releasing hydrocarbons and the potential environmental impact of a release.1

However, the methods developed to date are considered to be limited in certain areas and lack key components when evaluated against an international standard on risk management (e.g., ISO 31000: 2009). Few methods are considered to take into account the uncertain nature of many of these wrecks, or the risk of continuous low levels of oil release into the marine environment and there is little in the way of standardisation in terms of the methodology. The existing methods have tended to be national or regional only, and their deployment to actual wreck management and intervention projects has been sporadic. In our view, this is primarily due to budget constraints and the challenges of cross-border responsibility.

There is an absence of common standards and protocols for the assessment and prioritisation of PPW which can inhibit proactive risk management. This also inhibits funding for the management and intervention of PPW. Proactive management and intervention of PPW will reduce, and aims to eliminate, the risk of serious pollution incidents from PPW. This also signifcantly reduces costs; the cost of proactively removing pollutants from a wreck can be orders of magnitude less than dealing with an emergency pollution clean-up and response, let alone the environmental and socio-economic impacts of spills.

This chapter outlines the experience that we have gained at Waves Group in the assessment of PPW and illustrates how the technologies and methodologies used for assessment can be effective and can be standardised but are also readily adapted.

### **11.3 Our Experience in the Assessment of Potentially Polluting Wrecks**

The assessment of PPW requires a range of technical disciplines, including a combination of high-resolution survey data acquisition, naval architecture, marine engineering, modern ship salvage and pollution expertise, together with maritime archaeology expertise to address the pollution risks and the cultural heritage aspects. We have integrated this combination of expertise, regularly deploying it on modern, commercial salvage and wreck removal projects. Removal of pollutants and managing pollution risks is at the heart of modern ship salvage and so the techniques used are directly applicable to PPW and therefore provide a proven, state-of-the-art capability to meet the PPW challenge. Applying adaptions of proven commercial

<sup>1</sup>Particular examples include VRAKA (Sweden), NOAA (USA), South Pacifc Regional Environment Program (SPREP), SWERA (Finland).

technology, such as non-intrusive sampling for hydrocarbons, has enabled the development of methods that considerably reduce the risks of the destabilisation of the wreck and the unintended release of hydrocarbons into the marine environment.

We are working internationally with Governments and their Agencies, together with other stakeholders and experts in the PPW feld, and have built experience across PPW projects in UK, US, Finnish and Pacifc Island waters, and modern salvage projects worldwide, including many environmentally and socioeconomically sensitive regions from the high Arctic to South Pacifc islands. This includes both planned PPW assessments and emergency response interventions. Our experiences to date have enabled us to consider what is 'best practice' for the management of PPW and the technologies and methodologies used for their assessment, and also highlight the gaps and future needs for proactive wreck management and intervention. Here, we summarise some of the aspects of the methodologies that we have deployed and experienced.

The approach to the assessment of PPW is driven by the need to achieve the best possible certainty, whilst having the lowest environmental risk, and to ensure that the assessment can be conducted cost-effectively. The stakeholders to any PPW require a clear and accurate understanding of the risk presented by the wreck to justify the intervention strategy. The decisions required to be made are signifcant and clear, accurate data underpins this.

For a planned (i.e., proactive) wreck assessment, a comprehensive desktop scoping exercise is undertaken before any feldwork. This includes detailed archival research to source all available technical data and documentation for the wreck (e.g., plans and drawings), details of the voyage and events surrounding the sinking, location specifc information, including ocean data, environmentally sensitive areas near the wreck and geological information on the nature of the surrounding seabed. Any previously available data that may have been acquired is also integrated to this assessment, which is then used to assess the nature of the assets and equipment best suited to undertake the offshore elements of the assessment, safely and cost effectively.

To assess the potential for oil (or other pollutants) to remain in a wreck, it is critical to be able to identify the internal compartments of the wreck and to assess those that would be holding the pollutants. Using a combination of the archival research and state-of-the-art 3D digital models derived from vessel plans and lines drawings, with expert Naval Architect input, the internal arrangement and compartments of the vessel can be modeled and used to identify the potential sources of pollutants. Figure 11.1 shows the digital model of SS *Derbent* assessed on behalf of the UK MOD (see Hill et al., Chap. 6, this volume). The model has been derived from ships plans of the vessel class of tanker. The model clearly defnes the internal structure of the vessel and the location of the cargo holds.

**Fig. 11.1** Digital model of SS *Derbent* showing internal cargo tank structure

**Fig. 11.2** High-resolution multibeam bathymetry data of the *Derbent* wreck. (Hill et al., Chap. 6, this volume)

High-resolution geospatial surveys are used to obtain an accurate representation of the wreck in three dimensions *in situ* on the seabed. A combination of subsea data acquisition techniques, including side-scan sonar, multibeam sonar and photogrammetry is used to obtain the data and integrated to create a high-resolution 3D model of the wreck (Fig. 11.2). Other measurements, such as hull thickness, can be used to determine the residual dimensions of the shell plating to help assess the potential for further structural degradation and hence the risk of pollutant release.

To produce the model, high-resolution survey data and hull thickness measurements are then integrated into a 3D digital environment to provide a better understanding of the wreck on the seabed and the likely locations of the pollutants within the wreck. This enables a 'virtual' structural inspection of the wreck, which can identify breaches in the hull and the presence of potential egress points for any pollutants. Figure 11.3 shows the integration of the digital model of the *Derbent* wreck highlighting the internal structure of the wreck and the locations of the cargo tanks. The integration of the data is critical to understanding the structural collapse that can be seen at the stern, noting that the structural failure is in line with the transverse bulkheads.

The integration of all these data provides a qualitative assessment, from which a range of possibilities of oil volumes remaining in the wreck can be estimated. To determine the oil volumes remaining within a wreck, some form of sampling regime is necessary, which means either intrusive or non-intrusive sampling must be undertaken. The 3D virtual model of the wreck also allows detailed planning of sample points for quantifying the pollutants remaining in the wreck.

Non-intrusive sampling uses specialised systems such as a Neutron Backscatter System (NBS), which can identify the level of hydrocarbons contained within a compartment, therefore enabling an assessment of the volume and location of hydrocarbons remaining in a wreck. The successful application of such systems, typically with an ROV, depends on the condition and orientation of the wreck, and it must be calibrated against known compartment conditions to provide results of suffcient veracity. Being non-intrusive, this method greatly reduces the risk of oil spills during the wreck assessment phase (therefore negating costly clean-up

**Fig. 11.3** Image of the *Derbent* showing the digital model integrated with the multibeam sonar data

**Fig. 11.4** NBS sampling regime and results overlaid on the integrated data model of the *Derbent*

resources and response) and has no impact on the structure of the wreck. Figure 11.4 shows the NBS readings on the wreck of SS *Derbent* (Hill et al., Chap. 6, this volume). The sampling regime has been designed to identify the water/oil interface within cargo tanks that have been identifed as potentially containing hydrocarbons from the structural assessment.

Intrusive sampling requires tanks to be drilled and physically sampled. This can be helpful for any eventual oil removal operation, as valves can be installed that will provide samples and, if oil is identifed, can then be used for the oil removal. Alternatively, for assessing the PPW, smaller scale sampling techniques can be used drilling small holes to 'tap off' relatively small volumes of oil from the tank, which are then sealed after sampling. Any intrusive sampling has a higher impact on the hull of the wreck, increasing the risk of an uncontrolled release of oil. The advantage of intrusive sampling is that the results provide positive, visual, confrmation of the existence of pollutants and samples collected can be sent for analysis to inform the intervention planning.

To help understand the application of the assessment methodology in practice, here we summarise two case studies for PPW assessments that we have carried out. Please also see the summaries of the assessments of the SS *Derbent* wreck and the RFA *War Mehtar* wreck by Hill and colleagues earlier in this volume (Chap. 6).

### **11.4 Case Study: Tug** *Simson*

The tug *Simson* sank in the Finnish archipelago in Baltic Sea in 1978, after striking a submerged rock whilst towing a rock barge. The assessment of the *Simson* wreck was part of the PPW management programme being undertaken by the Finnish Environment Institute. The wreck was classifed as potentially polluting as it contained an estimated 1000 litres of diesel fuel, and the wreck site is located within the Finnish Archipelago which is a conservation area protected under Finnish and European law. It was chosen as a test case to apply the proposed methodology, being smaller in size, accessible and with a lower intervention risk than other larger wrecks.

Waves Group undertook the wreck assessment to inform the future management plan and assess whether remediation of the wreck was necessary. On initial survey, it was found that the wreck had sunk into the mud in an upright position and was buried up to its gunwales. It was therefore not possible to collect high-resolution imagery of the hull and as such, the methodology had to be adapted, whilst on site.

The 3D wreck model, built using derived plans for the vessel and the initial survey data, became the data reference point. Instrumental in this was also interviews with the surviving Chief Engineer!

Detailed video footage of the wreck was fused into the 3D model to create an immersive model from which the above-seabed features of the wreck could be interrogated and assessed. Water and sediment samples were also taken to assess whether any diesel was leeching into the seabed or water column. Using this methodology, we were able to assess the condition of the wreck and assess whether the wreck was leaking hydrocarbon and the viability of further remediation measures. Figure 11.5 shows a view of the combined 3D model.

Based on these adapted data, the survey concluded there was likely to be only small amounts of the diesel oil remaining in the wreck. The methodology adopted demonstrates how the integration of data with the relevant salvage experience can be adapted and used rapidly to produce results with high confdence to inform the future management plan for the wreck.

**Fig. 11.5** Tug *Simson* composite 3D model comprising multibeam sonar data and aligned solid modelling of the internal layout

**Fig. 11.6** Multibeam sonar image of unidentifed vessel

### *11.4.1 Case Study: Emergency Response Assessment*

It is, of course, preferred to conduct assessments of PPW in a proactive and planned manner. However, there are, and will be, occasions where a wreck starts to release pollutants before the planned assessment has been conducted.

Waves Group recently conducted a PPW assessment as an emergency response after signifcant oil was observed on the surface in a busy shipping area. Due to the rapid response required, the normal scoping phase could not be fully completed and mobilisation to site was conducted 'blind' with the consequence that the survey methodology had to be developed on site and evolved as fndings were obtained.

The surface oil was traced to a wreck which was charted but unidentifed (Fig.11.6). Temporary patching was installed to stop the release of oil and the wreck was surveyed using high-resolution multibeam sonar and combined with photo and video footage to create the 3D wreck model. An investigation was then undertaken to identify the vessel type, using archival data to compare and match key features to the survey data. Based on this, the vessel type was identifed and the internal structural arrangement and compartments were incorporated into the 3D model (Fig 11.7). An analysis of the structural condition of the wreck was then

**Fig. 11.7** Composite model comprising multibeam point cloud data a digital model of unidentifed wreck showing internal compartments

conducted. Non-intrusive sampling of the oil was planned but could not be undertaken due to the poor condition of the wreck structure which could have resulted in the signifcant unintended release of oil.

An assessment of the risk of future release of hydrocarbons was then conducted, considering a range of factors. This assessment considered the potential volume of hydrocarbons in each tank (and their maximum capacity), the volumes reported in the pollution reports, the potential for material volumes to be recovered in the event of a further release and the condition of each compartment and whether it was already breached (i.e., was any oil already lost to sea). With the potential volume of oil remaining, an intervention strategy was recommended.

Emergency responses operations like this serve to highlight the need for a more proactive approach in the future, where PPW can be assessed, and the risks identifed in a planned campaign. By using the similarities between vessel designs, assessments can be made with good confdence, even in rapid response cases without the time to plan the assessment. At the core of this, is the ability to adapt the assessment methodology.

### **11.5 Wreck Assessment Methodologies—The Future**

The work that Waves Group has completed on PPW has brought a standardised approach to the assessment of PPW that has enabled stakeholders to obtain a clear understanding of the risks presented by a wreck, providing increased certainty on the risks it presents, and the intervention and management strategy needed. This methodology has proven to be readily adaptable between planned wreck assessments and rapid (or emergency) response cases. Figure 11.8 below sets out this methodology.

Phase one is typically a desk-based study undertaken to create a wreck inventory that identifes all the known PPW in the area of concern, followed by an appraisal of risk to prioritise further work on specifc wrecks. Phase two is the assessment of the wrecks to establish whether the risk identifed at the desk-based phase is appropriate. This phase will include the onsite survey work and is where our methodology has been effectively utilised. Phase three is the management and intervention phase which may include pollutant removal operations, containment, monitoring and the ongoing management of the cultural heritage, noting that many PPW are designated war graves.

As outlined here, there are a number of PPW risk assessment methodologies being utilised by different nations, with some regional approaches also in existence. However, the approaches between them differ, in terms of prioritisation of the wrecks, data acquisition and analysis for wreck assessments, and in intervention strategies. Moreover, there is no common approach between nations (and in particular, between those that have responsibility for the majority of PPW) on how to deal with the increasing pollution risk arising from PPW and who pays for it.

As the condition of PPW continues to deteriorate, there is an increasing need for a common approach to reduce the risk of serious marine pollution from PPW, with the potentially devastating effects that this will have on the ocean environment, as well as the socio-economic impacts.

Proactive management of PPW will require funding. Presently, even developed nations have limited budgets for managing PPWs and despite the increased awareness of the growing risk, are still reactive in dealing with those wrecks that are their responsibility. The wreck management programs that do exist are budget limited and so, are constrained in their ability to proactively manage the number of wrecks necessary.

Therefore, opening up pathways for alternative sources of funding will be critical to enabling the proactive management of PPW. For funding to become available, there will need to be certainty of the outcome; that is, what are the costs and what do the funders get for their money?

An international standardised methodology for the assessment and management of PPW, supported by appropriate international standards and guidelines, will provide that certainty and the confdence that the methodology being used represents best practice. That is, it enhances the due diligence for the funding. It allows the costs of PPW assessments to be more easily predicted and reduced (e.g., by sharing resources and undertaking assessments in campaigns, to a standard methodology). A standardised methodology will also support the aims of international treaties and regulations (e.g., the Nairobi Wreck Removal Convention 2007) and is directly linked to international treaties and targets such as:

**Fig. 11.8** Potentially polluting wreck assessment methodology

• The UN High Seas Treaty (BBNJ), ratifed in June 2023, which aims to protect the biodiversity of the ocean, through the creation of Marine Protected Areas (30% of the High Seas by 2030).

It is our goal to see the increased awareness of the PPW problem catalyse global action to develop an international standard and appropriate methodologies, drawing on existing international expertise, experience, and bringing technological innovation to help solve the problem. As we write this action has already commenced with the start of a project with Lloyd's Register Foundation, The Ocean Foundation and Waves Group called "*A Global Framework for the Near and Long Term Assessment, Intervention and Sharing of Data for Potentially Polluting Wrecks*".

### **References**

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

# **Chapter 12 Concluding Statement**

### **Joao Sousa, Benjamin Ferrari, Michael L. Brennan, and Ole Varmer**

The grim reality of potentially polluting legacy wrecks presents a multifaceted threat that extends far beyond the decaying hulks on the ocean foor. These wrecks serve as silent sentinels of a bygone era, leaking toxic substances that indiscriminately poison marine life and disrupt the intricate web of oceanic relationships. From the smallest plankton to the largest apex predators, no organism remains untouched by the effects of these pollution sources.

The toxicity seeping from these underwater time bombs endangers the delicate balance of biodiversity in our oceans. It also poses a profound threat to the safety of people and ocean infrastructure. It jeopardises the resilience and livelihoods of communities that depend on these marine ecosystems. Coastal communities, fshing industries, and tourism sectors all bear the brunt of this environmental degradation, facing economic and social consequences that will resonate for generations. What is more, polluting legacy wrecks pose a material risk to planned strategic investment in protection and restoration of ecosystems through fnancial mechanisms such as Blue Bonds (a subset of the green, social and sustainable bonds), and management tools such as MPAs.

J. Sousa International Union for Conservation of Nature, Gland, Switzerland

B. Ferrari Lloyd's Register Foundation, Bath, UK

M. L. Brennan (\*) SEARCH Inc., Jacksonville, FL, USA e-mail<EMAIL_ADDRESS>
O. Varmer The Ocean Foundation, Washington, DC, USA

© The Author(s) 2024 157 M. L. Brennan (ed.), *Threats to Our Ocean Heritage: Potentially Polluting Wrecks*, SpringerBriefs in Underwater Archaeology, https://doi.org/10.1007/978-3-031-57960-8\_12

There are substantial barriers that must be overcome in order to move away from the current reliance on emergency response interventions to a more strategic approach that delivers assurance of long-term safety and effcient use of resources. In terms of governance there is a lack of clarity regarding responsibility and liability. While many legacy wrecks have been located, many have yet to be found and particular challenges will be posed by those in deep water where remediation efforts become even more challenging. Regardless of location, historic preservation law and policy must be factored in. That may also call for sensitivity of grave sites and mitigation to avoid or minimise adverse impacts to cultural heritage. The heritage should be identifed, considered in EIAs, and addressed in planning and management. A survey should be completed and mitigation considered before intrusive research and/or recovery. For PPWs that are also grave sites, a memorial service or a plaque may be appropriate. In addressing the duty to protect our heritage and the marine environment, it is understood that priority be given to a clean ocean particularly for those livelihoods so dependent upon it. If it is not safe for life, property, and the marine environment, it is not sustainable. A lack of widely accepted technical standards and protocols inhibits engineering intervention and strategic planning. In the absence of such standards, it is also harder to advocate for action to aggregate the necessary fnancial and multi-lateral agency support for change.

It is evident that a proactive and comprehensive approach is needed. It is essential for governments, industries, and environmental organisations to collaborate on strategies for identifying, assessing, and mitigating the risks associated with polluting wrecks. Whether through the removal of hazardous materials, the implementation of protective measures, the development of sustainable restoration initiatives or creating a relief fund to support lost livelihoods, there is a collective responsibility to safeguard our oceans and the life they support.

Public awareness and engagement are also vital components of any successful solution. Communities that rely on marine resources must be informed and empowered to advocate for the preservation of their environment. Education campaigns, research efforts, international cooperation and policy development will be instrumental in addressing the multifaceted challenges posed by polluting wrecks.

The urgency of addressing this impending crisis cannot be overstated. New resources are required—especially in the Global South—to boost resilience and manage risk. We believe that these resources, technical and fnancial, will only become available at the level required once there is a clear and widely accepted roadmap to better governance and optimised interventions. To this end, at the time of publication, Lloyd's Register Foundation is supporting partner organisations to establish an evidence base, including this volume, that will underpin advocacy for strategic action. The Ocean Foundation and Waves Group will coordinate a series of international expert workshops to forge consensus on the change that we need. The IUCN and ICOMOS are also involved and will be instrumental in enhancing cooperation with the UN family of agencies in order to marshal support for new international regulations and protocols.

In the face of this ecological and socio-economic challenge, our responsibility is clear. By prioritising the protection of our oceans and the preservation of the myriad species that call it home, we can not only safeguard biodiversity but also ensure the safety and sustainability of livelihoods that depend on these precious marine resources. The time to act is now, for the sake of our planet, its inhabitants, and the generations to come.

**Open Access** This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.


**3. Stability Analysis**

According to Nasir et al., [28] and Rana et al., [25], we need to introduce the unsteady form of Equations (6)–(8) in order to perform stability test,

$$u\frac{\partial u}{\partial t} + u\frac{\partial u}{\partial x} + v\frac{\partial u}{\partial y} = \left(\mathfrak{d} + \frac{\kappa}{\rho}\right)\frac{\partial^2 u}{\partial y^2} + \frac{\kappa}{\rho}\frac{\partial \mathcal{N}}{\partial y} \tag{17}$$

$$u\frac{\partial \mathbf{N}}{\partial t} + u\frac{\partial \mathbf{N}}{\partial \mathbf{x}} + v\frac{\partial \mathbf{N}}{\partial y} = \frac{\gamma}{\rho j}\frac{\partial^2 \mathbf{N}}{\partial y^2} - \frac{\kappa}{\rho j} \left(2\mathbf{N} + \frac{\partial u}{\partial y}\right) \tag{18}$$

$$\frac{\partial T}{\partial t} + u \frac{\partial T}{\partial \mathbf{x}} + v \frac{\partial T}{\partial y} = \frac{k^\*}{\rho c\_p} \frac{\partial^2 T}{\partial y^2} \tag{19}$$

where time is denoted by *t*. The similarity transformations are written according to Ro¸sca and Pop [30], as,

$$\begin{split} \psi = \sqrt{2\mathcal{S}La}e^{\frac{\pi}{2L}}f(\eta,\tau); \ N = ae^{\frac{2\pi}{2L}}\sqrt{\frac{a}{2\mathcal{S}L}}h(\eta,\tau); \Theta(\eta,\tau) = \frac{(T-T\_{\infty})}{(T\_w-T\_{\infty})};\\ \eta = \mathcal{Y}\sqrt{\frac{a}{2\mathcal{S}L}}e^{\frac{\pi}{2L}}; \ \tau = \frac{a}{2L}e^{\frac{\pi}{2}}.\end{split} \tag{20}$$

By applying these similarity transformations, we reduced our Equations (17)–(19) into the following form

$$(1+K)\frac{\partial^3 f}{\partial \eta^3} + f \frac{\partial^2 f}{\partial \eta^2} - 2\left(\frac{\partial f}{\partial \eta}\right)^2 + K \frac{\partial \hbar}{\partial \eta} - \frac{\partial^2 f}{\partial \tau \partial \eta} = 2\pi \left(\frac{\partial f}{\partial \eta} \frac{\partial^2 f}{\partial \eta \partial \mathbf{x}} - \frac{\partial^2 f}{\partial \eta^2} \frac{\partial f}{\partial \mathbf{x}}\right) \tag{21}$$

$$\left(1+\frac{\mathrm{K}}{2}\right)\frac{\partial^2 \mathrm{h}}{\partial \eta^2} + f\frac{\partial \mathrm{h}}{\partial \eta} - 3\mathrm{h}\frac{\partial f}{\partial \eta} - 2\mathrm{K}\mathrm{h} - \mathrm{K}\frac{\partial^2 f}{\partial \eta^2} - \frac{\partial \mathrm{h}}{\partial \tau} = 2\pi \left(\frac{\partial f}{\partial \eta}\frac{\partial \mathrm{h}}{\partial \mathbf{x}} - \frac{\partial \mathrm{h}}{\partial \eta}\frac{\partial f}{\partial \mathbf{x}}\right) \tag{22}$$

$$\left(\frac{1}{Pr}\frac{\partial^2 \theta}{\partial \eta^2} + f\frac{\partial \theta}{\partial \eta} - \theta\frac{\partial f}{\partial \eta} - \frac{\partial \theta}{\partial \tau} = 2\pi \left(\frac{\partial f}{\partial \eta}\frac{\partial \theta}{\partial x} - \frac{\partial \theta}{\partial \eta}\frac{\partial f}{\partial x}\right) \tag{23}$$

with the following boundary conditions

$$f(0,\tau) = \text{S; } \frac{\partial f(0,\tau)}{\partial \eta} = -1; \ h(0,\tau) = -m \frac{\partial^2 f(0,\tau)}{\partial \eta^2}; \ \theta(0,\tau) = 1$$

$$\frac{\partial f(\eta,\tau)}{\partial \eta} \to 0; \ h(\eta,\tau) \to 0; \ \theta(\eta,\tau) \to 0 \qquad \text{as } \eta \to \infty$$

and then we applied perturbed with the disturbance (see Ro¸sca and Pop [30]) in Equations (21)–(24) with the following functions

$$\begin{cases} f(\eta,\tau) = f\_0(\eta) + e^{-\varepsilon\tau} F(\eta,\tau) \\ h(\eta,\tau) = h\_0(\eta) + e^{-\varepsilon\tau} G(\eta,\tau) \\ \theta(\eta,\tau) = \theta\_0(\eta) + e^{-\varepsilon\tau} H(\eta,\tau) \end{cases} \tag{25}$$

where *F*(η, τ), *G*(η, τ), and *H*(η, τ) are small relative to *f*0(η), *h*0(η), and θ0(η), respectively. Further, ε is the unknown eigenvalue. By substituting Equation (25) in Equations (21)–(23) by keeping τ = 0, we have following the linearized eigenvalue problems

$$(1+K)F\_{0}^{\prime\prime} + f\_{0}F\_{0}^{\prime\prime} + F\_{0}f\_{0}^{\prime\prime} - 4f\_{0}^{\prime}F\_{0}^{\prime} + KG\_{0}^{\prime} + \varepsilon F\_{0}^{\prime} = 0\tag{26}$$

$$\left(1+\frac{K}{2}\right)G\_0^{\prime\prime} + f\_0G\_0^{\prime} + F\_0h\_0^{\prime} - 3h\_0F\_0^{\prime} - 3h\_0F\_0^{\prime} - 2KG\_0 - KF\_0^{\prime\prime} + \varepsilon G\_0 = 0\tag{27}$$

*Crystals* **2020**, *10*, 283

$$\frac{1}{Pr}H\_0'' + f\_0 H\_0' + F\_0 \theta\_0' - f\_0' H\_0 - F\_0' \theta\_0 + \varepsilon H\_0 = 0\tag{28}$$

With the boundary conditions

$$\begin{array}{cccc} F\_0(0) = 0, & F\_0'(0) = 0, & G\_0(0) = -nF\_0''(0), & H\_0(0) = 0\\ F\_0'(\eta) \to 0, & G\_0(\eta) \to 0, & H\_0(\eta) \to 0, & \text{as} \ \eta \to \infty \end{array} \tag{29}$$

We have to solve above linearized Equations (10)–(13) with new relax boundary conditions in order to find the values of smallest eigenvalue. In this particular problem, we have relaxed *H*0(η) → 0 as η → ∞ into *H*0 0 (0) = 1, see [31–33].


This work was partially supported from MECESUP2 Postdoctoral program and Regular Project 100710 3/R of the University of Bio-Bio, Chile; and the Spanish Government under Research Program Consolider Ingenio 2010: MIPRCV (CSD2007-00018) and Project TIN2011-

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[2] Harless T, Wagner F, Steele P, Taylor F, Yadama V, McMillin C (1991) Methodology for locating defect within hardwood logs and determining their impact on lumber value

[3] Sandoz J (1993) Moisture content and temperature effect on ultrasound timber grading,

[4] Martin P, Collet P, Barthelemy P, Roussy G (1987) Evaluation of wood characteristics: internal scanning off the material by microwaves, Wood Science and Technology 21:

[5] King R (1991) Measurement of basic weight and moisture content of composite board using microwave, VIII Int. Symp. On non-destructive testing osf wood 1: 21-32. [6] Gapp V, Mallick G, (1995) Capteur intelligent pour la mesure de la humdité dans le matériau par technique micro-ondes, Journées Nationales Micro-ondes 73: 53-57. [7] Baradit E, Aedo R, Correa J (2006) Knot detection in Wood using microwaves, Wood

[8] Lundgren N, Brännström M, Hagman O, Oja J (2007) Predicting the Strength of Norway Spruce by Microwave Scanning: A Comparison with Other Scanning Techniques, Wood

[9] Thomas L, Mili L (2006) Defect Detection on Hardwood Logs Using Laser Scanning,

[10] Funt B, Bryant E (1987) Detection of internal log defects by automatic interpretation of

[11] Zhu D, Conners R, Schmoldt D, Araman P, (1996) A prototype Vision System for Analyzing CT Imagery of Hardwood Logs. IEEE Transactions on Systems, Man and

[12] Rojas G, Hernández R, Condal A, Verret D, Beauregard R (2005): Exploration of the Physical Properties of Internal Characteristics of Sugar Maple Logs and Relationships

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344.

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**Acknowledgement**

25606.

**6. References**

361-371.

**Figure 13.** Evolution of an initial contour around a knot with interference from growth rings; (a) greedy algorithm; (b) simulated annealing algorithm

## **5. Conclusions**

From the experimental results presented above, we can conclude that the proposed method is a very good alternative for knot segmentation. The use of SA allows much more precise segmentation of knots with greater irregularities in the images. Nonetheless, the initial position of the deformable contour is of vital importance for a good identification. We can also use the results obtained to infer that both excessive humidity content in the logs and growth rings present inconveniences. The latter presents a great challenge since the knot shows up in the images obtained with X-rays both in isolation and confused with other objects. In the second case, additional information, for example morphological information on the knots, can be incorporated into the contour's energy function that describes the force of the image, offering a very good alternative. The cases examined correspond to segmentation by X-ray computerized tomography for logs having distortions mainly due to their storage; this causes the density of the material to increase, which then has an effect on the images. This case is of great interest for the wood industry. However, this technique can also be used in other situations such as the study of other defects in logs. The authors are currently developing 3D techniques and a way to reduce the method's computerization costs that was not considered in this first study.

## **Author details**

Cristhian A. Aguilera *Dept. Electrical and Electronic Engineering, University of Bio-Bio, Concepción, Chile*

Mario A. Ramos *Dept. Wood Engineering, University of Bio-Bio, Concepción, Chile*

Angel D. Sappa *Computer Vision Center, Autonomous University of Barcelona, Barcelona, Spain*

## **Acknowledgement**

102 Simulated Annealing – Advances, Applications and Hybridizations

algorithm; (b) simulated annealing algorithm

costs that was not considered in this first study.

*Dept. Electrical and Electronic Engineering, University of Bio-Bio, Concepción, Chile*

*Computer Vision Center, Autonomous University of Barcelona, Barcelona, Spain*

*Dept. Wood Engineering, University of Bio-Bio, Concepción, Chile*

**5. Conclusions**

**Author details**

Mario A. Ramos

Angel D. Sappa

Cristhian A. Aguilera

**Figure 13.** Evolution of an initial contour around a knot with interference from growth rings; (a) greedy

(a) (b)

From the experimental results presented above, we can conclude that the proposed method is a very good alternative for knot segmentation. The use of SA allows much more precise segmentation of knots with greater irregularities in the images. Nonetheless, the initial position of the deformable contour is of vital importance for a good identification. We can also use the results obtained to infer that both excessive humidity content in the logs and growth rings present inconveniences. The latter presents a great challenge since the knot shows up in the images obtained with X-rays both in isolation and confused with other objects. In the second case, additional information, for example morphological information on the knots, can be incorporated into the contour's energy function that describes the force of the image, offering a very good alternative. The cases examined correspond to segmentation by X-ray computerized tomography for logs having distortions mainly due to their storage; this causes the density of the material to increase, which then has an effect on the images. This case is of great interest for the wood industry. However, this technique can also be used in other situations such as the study of other defects in logs. The authors are currently developing 3D techniques and a way to reduce the method's computerization This work was partially supported from MECESUP2 Postdoctoral program and Regular Project 100710 3/R of the University of Bio-Bio, Chile; and the Spanish Government under Research Program Consolider Ingenio 2010: MIPRCV (CSD2007-00018) and Project TIN2011- 25606.

## **6. References**

	- [14] Sarigul E, Abbott L, Schmoldt D (2001) Nondestructive rule-based defect detection and indentification system in CT images of hardwood logs, Review of Progress in Nondestructive Evaluation 20: 1936-1943.

**Chapter 6**

© 2012 Huang et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2012 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

**Applications of Simulated Annealing-Based**

In the last decade, many heuristic methods have evolved for solving optimization problems that were previously difficult or impossible to solve. These methods include simulated annealing (SA), tabu search (TS), genetic algorithm (GA), differential evolution (DE), evolutionary programming (EP), evolutionary strategy (ES), ant colony optimization (ACO), and particle swarm optimization (PSO). This chapter reviews papers in international

The numerical simulation of physical phenomena has become a major issue in the design phase or optimization of many systems. The complexity of the phenomena demands that multi-scale and multi-physical aspects are considered. In recent years, many researchers are concerned with the development, study, and implementation of efficient numerical methods that can be used in applications in engineering, natural and other sciences. They also focus on numerical methods for solving highly complex and CPU-time problems using highperformance computing. For the advancement of computing schemes that improve the efficiency and even optimize calculation processes, researchers must be able to generate novel systematic methods for solving multi-physical problems. The applications of SA-

This chapter reviews various SA-based methods (including SA and other meta-heuristics methods) for the planning, operation, and optimization of power systems, including relevant recent and historical developments. Relevant publications in international journals that cover a broad range of applications of SA methods to solving power system problems are reviewed. As is well known among power engineers, many kinds of combinatorial optimization problems arise in the planning and operation of power systems. The generation and transmission expansion planning, generator maintenance scheduling and unit commitment, reactive power planning, load forecasting and economic dispatch, and

and reproduction in any medium, provided the original work is properly cited.

journals that present the SA-based methods for electric power system applications.

**Approaches to Electric Power Systems**

Yann-Chang Huang, Huo-Ching Sun and Kun-Yuan Huang

Additional information is available at the end of the chapter

based methods for electric power systems are surveyed.

distribution systems planning and operation are typical problems.

http://dx.doi.org/10.5772/50388

**1. Introduction**