**5. Impact of genetic identification on justice**

At the present time. genetic testing using DNA has wide applicability to the field of justice, this method being used for the following:

**•** Identification of certain probes for medical testing (tissue for histology testing, blood alcohol content testing, other toxicological tests).


*4.1. Comparison of Natural Fundamental Periods*

In this part, the period values obtained according to the eigenvalue analyses were compared with the empirical ones predicted for each country. The time required for the undamped system to complete one vibration cycle is called the natural vibration period of the system. The more rigid one of the same mass with a single degree of freedom system will have a shorter natural period and a higher natural frequency. Similarly, of two structures of the same stiffness, the heavier (greater mass) has a lower natural frequency and a longer natural period. This value can be obtained both with approximate formulas and as a result of numerical analysis [143–146]. The empirical relations and explanations stipulated in the corresponding design code for each country are given in Table 16. The comparison of these periods with the ones obtained from structural analyses is shown in Table 16. The empirical formulas used in Table 16 are directly taken from the seismic design codes currently used by countries.

**Table 16.** Comparison of the natural fundamental periods for selected countries.

The fundamental periods obtained from the structural analyses for all countries were constant since the structural characteristics of the sample RC buildings models did not change. Empirically, the smallest period values were obtained for Albania, while the highest periods were obtained for Türkiye. The empirical periods suggested for Albania were lower than the periods obtained from the structural analysis. For the other five countries, the empirically suggested period values were higher than the period values obtained from the structural analyses.

### *4.2. Comparisons of Limit States*

In this study, the target displacement values for the different number of storeys were obtained from the structural analyses for each country, considering the limit states in Eurocode 8 for six different countries. The comparison of target displacements of sample RC models for Albania is given in Table 17.

**Table 17.** The obtained target displacements of sample RC models for Albania.

The target displacements suggested by the seismic design code for the first three earthquakes in Albania provide target displacements in which the acceleration values measured in earthquakes are taken into account. However, the target displacements predicted for the structure for the last two earthquakes and the target displacements obtained under the effect of the earthquake were exceeded. This suggests that the target displacements are adequately represented for some earthquakes, while it is not sufficient for others.

The comparison of target displacements of sample RC models for Bosnia and Herzegovina is given in Table 18.

**Table 18.** The obtained target displacements of sample RC models for Bosnia and Herzegovina.

The target displacements suggested by the seismic design code for the first three earthquakes in Bosnia and Herzegovina do not provide target displacements in which the acceleration values measured in earthquakes are taken into account. However, the target displacements predicted for the structure for the last two earthquakes and the target displacements obtained under the effect of the earthquake were not exceeded. This suggests that the target displacements are adequately represented for some earthquakes, while it is not sufficient for others.

The comparison of target displacements of sample RC models for Croatia is given in Table 19.

**Table 19.** The comparison of target displacements of sample RC models for Croatia.

The target displacements suggested by the seismic design code for all earthquakes in Croatia provide target displacements in which the acceleration values measured in earthquakes are taken into account. It shows that the seismic hazard is adequately taken into account in the structural analysis for all the selected earthquakes.

The comparison of target displacements of sample RC models for Serbia is given in Table 20.

The target displacements suggested by the seismic design code for all earthquakes in Serbia provide target displacements in which the acceleration values measured in earthquakes are taken into account. It shows that the seismic hazard is adequately taken into account in the structural analysis for all selected earthquakes.

The comparison of target displacements of sample RC models for Türkiye is given in Table 21. As seen in Table 21, the target displacements suggested by the seismic design code for the first, second, and fifth earthquakes for Türkiye provide target displacements in which the acceleration values measured in earthquakes are taken into account. However, the target displacements predicted for the other earthquakes for these structures were exceeded. This suggests that the target displacements are adequately represented for some earthquakes, while it is not sufficient for others.

**Table 20.** The obtained target displacements of sample RC models for Serbia.

**Table 21.** The obtained target displacements of sample RC models for Türkiye.

The comparison of target displacements of sample RC models for Iran is shown in Table 22.

The target displacements suggested by the seismic design code for the first two earthquakes for Iran provide target displacements in which the acceleration values measured in earthquakes are taken into account. However, the target displacements predicted for the structure for the last three earthquakes and the target displacements obtained under the effect of the earthquake were exceeded. This suggests that the target displacements are adequately represented for some earthquakes, while it is not sufficient for others.

In addition to the structural analysis according to the number of stories, the local soil class change was taken into account. The structural analyzes were carried out only for the four-storey RC building model since it is aimed to reveal the soil class effects. In the previous structural analyses, the ZD soil class envisaged in Eurocode-8 was taken into account. In this section, structural analyzes were made separately for each earthquake by choosing the ZA class in the same code. The recommended properties in the code for these two soil types are given in Table 23. The target displacements for selected earthquakes for each country for the ZA soil class type were given in Table 24.

**Table 22.** The obtained target displacements of sample RC models for Iran.

**Table 23.** The characteristics of local soil types considered in this study [147].

### **Table 24.** Comparison of target displacements for the ZA soil class type.

Another parameter chosen in order to put the effect of different structural conditions in common was the importance class of the structure. While the IV class was selected in the previous analysis, it was considered as the II class in the new analysis. The only difference in the initial analysis is the building importance class, all other features remained the same. Selected building importance class characteristics are given in Table 25. The target displacements for selected earthquakes for each country for the II class were given in Table 26.

**Table 25.** Selected importance classes for buildings [147].

**Table 26.** Comparison of target displacements for building important class II.

In addition to all these different structural conditions, the concrete class is also considered as a variable. While previous analyzes were performed for the C20 concrete class, new structural analyzes considered the C12 concrete class with lower properties for all load-bearing elements. The target displacements for selected earthquakes for each country for the C12 concrete class were given in Table 27.

72

**Table 27.** Comparison of target displacements for the C12 concrete class.

### *4.3. Evaluation of Existing Building Stocks*

### 4.3.1. Albania

According to the Albanian Institute of Statistics (INSTAT) 2001, the Albanian building stock primarily consists of four typologies, namely brick and stone, prefabricated, wood, and other building materials. However, when referring to the recent census of 2011 (IN-STAT), information on building materials is not included and houses are classified based on their heights and construction period. Table 28 presents a summary of the Albanian building stock based on existing information (INSTAT 2001) [148]. Accordingly, the 'RC and masonry' type represents the biggest part of the current building stock.

**Table 28.** Albanian building stock [147].

According to the Albanian Institute of Statistics (INSTAT) 2011, one-storey buildings account for 85% of the total building stock corresponding to the accommodation of the half population of the country. They were mostly built with unreinforced masonry and reinforced concrete frames with infill walls. However, the total number of multi-storey houses in Albania is significantly lower compared to one-storey houses, but they shelter the remaining half of the population. During the recent earthquake sequences in 2019, multistorey buildings were significantly affected, resulting in higher damage in the stricken areas. While the available data given in Table 24 is outdated, they highlight an important indicator (design code) on the construction year of the housings. An important portion of the current building stock was built before 1990 showing a lack of adequacy to the modern code requirements [17]. Therefore, it is likely that there were deficiencies affecting the seismic performance of buildings constructed in this time period.

### 4.3.2. Bosnia and Herzegovina

According to the available data for Bosnia and Herzegovina (CBS 2013) [149], it is noted that, from the total of 1,078,156 buildings, 60.72% are structures made of brick, stone, and concrete, 35.08% of reinforced concrete and steel frames and only 4.20% of wood and light material [73]. The majority of the structures are either confined masonry buildings or RC buildings constructed according to the regulations from 1981 (35%), considering age distribution from 1981–1990. Since 1991 Prestandards (ENV) have been applied and this accounts for 18.9% of all buildings being either RC buildings or confined masonry buildings. The application of Eurocode 8 started after 2006 accounting for 2.0% of all buildings (as well as RC buildings or confined masonry buildings). Masonry structures with rigid floors were mainly constructed in the period from 1971 to 1980, amounting to 33.6% of all structures built in Bosnia and Herzegovina. Brick masonry structures with rigid RC slabs were built in the period from 1946 to 1970, amounting to 6.6% of all the structures built in Bosnia and Herzegovina. The remaining 4% is devoted to stone masonry buildings with wooden floors constructed before 1945. Seismic vulnerability assessment of structures in Bosnia and Herzegovina is mainly done by individual researchers [150–153]. At the moment, Bosnia and Herzegovina does not have a well-organized and efficient database of structures and building's typologies. Several studies were conducted to determine the vulnerability of buildings in several cities of Bosnia and Herzegovina, like Banja Luka and Sarajevo [74]), Visoko [154], and Tuzla [155]. For the first time, the specific site and its influence on the vulnerability were taken into consideration in the Tuzla region [155]. Currently, 700 structures in the city of Sarajevo are being examined and a database is being created [156]. Based on all this preliminary analysis, it is clear that most of the existing building stock in Bosnia and Herzegovina does not possess sufficient resistance to ground motions that may be expected in this region. It is necessary to construct a detailed database taking into account all the data required to conduct adequate seismic assessments and perform a seismic risk assessment. Without this database and conducted calculations, it is not possible to construct an effective disaster management plan.

### 4.3.3. Croatia

According to the 2011 Census, the total number of dwellings in Croatia by year of construction was 1,496,558. Of that, 13.2% were built before 1945, which means that they did not follow any building codes. Building design and construction in Croatia did not follow earthquake-resistant building rules until 1948 [157].

Masonry houses used timber floor constructions until 1920. Most of these structures were constructed between 1860 and 1920 and are now part of Croatia's historic town centers, most of which are categorized as historical heritage. These structures were not intended to withstand significant horizontal ground motions (e.g., earthquakes). After 1930, the first semi-prefabricated RC floors were installed, followed by monolithic RC floors in 1964. After the Skopje earthquake in 1963, the first seismic building codes were developed and later modified. In addition, following the earthquake in Skopje in 1963, masonry structures throughout the former Yugoslavia were erected systematically using horizontal tie-beams and vertical tie-columns to achieve confined masonry. The load-bearing system in reinforced concrete structures (RC frames and RC shear walls) was built in accordance with

the seismic regulations enacted in 1964 (following the 1963 Skopje earthquake) and 1981 (following the 1979 Montenegro (coast) earthquake). Eurocodes were gradually adopted as voluntary structural design norms between 1992 and 1998. Due to the challenges associated with the harmonization of new standards with old national legislation at the time, they kept a pre-standards status (ENV label). The final version was introduced in 1998, with the European standard (EN label), but the ultimate implementation began in 2005 with the adoption of the technical standards for concrete buildings (NN 101/05). Eurocodes were ultimately made a requirement in official usage in 2011, however, pre-standards were still used until the end of 2012 [147].

Predominant structural systems for the buildings in one of the Croatian cities (Osijek) can be summarized as follows [147]: Unreinforced masonry buildings made of old bricks with flexible floors, unreinforced masonry structures with rigid floors, confined masonry structures, RC frame structures, RC shear walls, and RC dual structures. For RC structures, the level of earthquake resistance design should be taken into account.

On December 29, 2020, an earthquake of magnitude 6.4 MW hit Sisak-Moslavina county with an epicentre 3 km southwest of the Croatian city of Petrinja. In the preliminary report on the consequences of the earthquake, a detailed description of the damage to residential low-rise and multi-family residential buildings is presented [158]. The following are the primary sources of damage and failure in low-rise residential buildings: Excessive lateral displacements of flexible timber flooring caused out-of-plane damage or failure of exterior masonry walls at the upper/top levels of older URM structures (built before World War II). Recent masonry structures have rigid floors, but they also suffered damage owing to the lack of vertical reinforcement at the bottom floor level. Due to the extremely high seismic demand, the in-plane damage pattern took the form of diagonal tension cracks in the walls. The major tensile stresses in the walls created by the earthquake surpassed the masonry tensile strength, resulting in the formation of inclined cracks (diagonal tension cracks). In certain situations, the quality of masonry materials and construction appeared to be poor, which was also a source of damage. The primary sources of damage and failure in multi-family residential buildings can be summarized as follows: Excessive lateral displacements of flexible timber flooring caused out-of-plane damage or failure of exterior masonry walls at the upper/top levels of older URM structures (built before World War II). In general, the failure process in low-rise and mid-rise structures is relatively similar.

Many older URM buildings were not properly maintained, and as a result, their condition was poor before the earthquake [159]. The level of damage is thought to have been impacted by the degradation of building materials and components (such as wooden floors and roofing) as well as the use of weak mortar.

Due to extremely high seismic demand, masonry structures with rigid floors built in the 1960s developed in-plane shear cracking at the building's base. The major tensile stresses in the walls created by the earthquake surpassed the masonry tensile strength, resulting in the formation of inclined cracks (diagonal tension cracks). The earthquake caused no structural damage to RC structures; nevertheless, minor damage to non-structural components such as chimneys occurred in several buildings.

### 4.3.4. Serbia

According to the 2011 Serbian Census of population, household, and dwellings, 85% of all dwellings in Serbia were constructed after 1945, i.e., in the period when there were at least some seismic design codes. Before 2019, the seismic design codes created and implemented in the former Yugoslavia were used. The first seismic design code was published in 1948, but it lacked detailed detailing guidelines for RC and masonry construction. The disastrous earthquakes that struck Skopje in 1963 and Montenegro in 1979 served as turning points in the creation of Yugoslavian seismic design codes. Following the 1963 Skopje Earthquake, the first complete seismic design code was published in 1964. Two years after the 1979 Montenegro earthquake, a new, much more advanced code was published. The seismic design of new structures in Serbia must comply with Eurocode 8—Part 1 [147]

as of 2019 [160]. However, although most buildings were constructed after 1945, a recent moderate-size Mw = 5.5 2010 Kraljevo earthquake revealed the vulnerability of the Serbian building stock. It should be noted that reinforced-concrete structures accounted for only 10% of the building stock in the affected area. As expected, buildings with unreinforced brick masonry walls and flexible diaphragms sustained notable damages while properly constructed modern confined masonry buildings remained undamaged. However, numerous one- or two-storey masonry buildings with rigid RC floors and horizontal ring beams suffered severe damage and/or partial collapse due to the inadequate design and construction and/or low-quality building materials and many multi-storey masonry buildings were damaged due to poorly planned and executed renovations and extensions [161]. These findings call for increased efforts toward a more realistic estimation of the vulnerability of the existing building stock in Serbia if one would like to obtain a realistic estimate of the seismic risk.

### 4.3.5. Türkiye

Most of the existing building stock in Türkiye does not have sufficient resistance to earthquakes. This is clearly seen from the observed damage caused by the recent earthquakes in Türkiye. Earthquake regulations are renewed over time and put into effect, especially after the large-scale loss of life and property [162–164]. Insufficient structural features of the existing building stock play an active role in losses in earthquakes. For this reason, these uninspected buildings, which constitute the majority of the building stock, should be examined, some of them should be strengthened and others should be evaluated within an urban transformation project. The need for low-cost housing as a result of unplanned urbanization due to population growth and migration to big cities in Türkiye has caused both the shift from residential areas to areas with high earthquake hazards and the growth of building stock with weak earthquake safety. Knowing the characteristics of both new buildings and relatively old buildings with weak earthquake safety is of great importance in order to make accurate earthquake risk and loss calculations of settlements. To reduce the damage caused by earthquakes and for effective disaster management, the earthquake risks of existing structures should be calculated realistically. In this context, it is of great importance to know the properties of the building stock that affect the earthquake behavior well, to make the risk and loss calculations correctly. In this respect, examining the Turkish building stock in terms of time and space is of great importance in earthquake risk calculations.

### 4.3.6. Iran

After the 1990 Manjil mega-earthquake, one of the biggest and most fatal incidents in the seismic history of Iran that claimed the lives of more than 40,000 people, several investigations were initiated by many researchers on the analysis of the damages and vulnerability of the building stocks in the similar earthquake-stricken areas. The catastrophe caused a turning point in the analysis and design approaches of buildings and several modifications to the Iranian Code of Practice for Earthquake Resistant Design of Buildings, Standard 2800, and the definition of many research programs [165]. A study was conducted on three earthquakes in Iran, including the 2003 Bam earthquake, the 2005 Zarand earthquake, and the 2006 Silakhor earthquake by Mahdi and Mahdi [166]. The Bam earthquake has been the biggest earthquake with the highest rate of fatalities in the country after the 1990 Manjil earthquake, in which more than 53,000 buildings were destroyed while the remaining structures were severely damaged [167]. Damage analysis of buildings after the 2003 Bam earthquake by Mostafaei and Kabeyasawa [168] showed that building stock in this city at the time of the earthquake was comprised of adobe, masonry (reinforced and unreinforced), steel, and concrete buildings. As shown in this study, the major building system type has been unreinforced masonry (for around 68% of the buildings), and only 24% of the buildings in the city had been designed seismic-resistant, having a structural system as per the Iranian seismic design code of practice. This is while even the remaining steel or

reinforced concrete (RC) damaged buildings suffered from inappropriate structural design, low-quality construction practices, and insufficient implementation controls. Buildings that have been destroyed or heavily damaged in the other two earthquakes have been mostly adobe or unreinforced masonry buildings, while inadequate seismic-resistant structural systems or unsuitable construction practices were recognized as the main reason for damages. According to the 2016 national census conducted by the Statistical Centre of Iran (SCI) on the residential building stock and different building types, it is understood that the five main types of building systems, i.e., concrete, steel, masonry, adobe, and wooden, could be recognized in Iran. The census shows that masonry, steel, and concrete structures contain 39%, 30%, and 27% of the building stock, respectively. The remaining building types were either wooden or adobe, with 0.14% and 4%, respectively, while the remaining 0.26% had no recognizable system [169]. The study by Bastami et al. [169] which proposes new seismic vulnerability models for building stocks in Iran, shows a considerable change in newer versions of the Iranian Code of Practice for Earthquake Resistant Design of Buildings, Standard 2800, in terms of response factor for calculating base shear in the equivalent static method. These revisions as well as other stricter regulations and modifications for the design and construction of seismic-resistant buildings are in line with the above-mentioned started programs and initiatives for more protection of structures in Iran.

### **5. Results and Conclusions**

Both the seismic parameters and the expected target displacements from the structures have been obtained by considering five earthquakes that occurred in six different countries with different seismic risks within the scope of the study. The highest PGA value for all considered earthquakes was obtained in the 2003 Bam (Iran) earthquake and is 0.970 g. The lowest measured PGA was obtained as 0.01 g for the Serbian earthquakes. While the measured PGA's for Croatia and Serbia provided the recommended PGA's, the recommended PGA values for Türkiye, Bosnia and Herzegovina, Iran and Albania were exceeded. PGA values were compared, considering the standard design earthquake with a 10% exceedance of probability in 50 years (repetition period of 475 years). Therefore, it is possible that these values can be met with the consideration of earthquakes with a larger repetition period. Considering the largest earthquake data as the ground motion level in regions with high seismicity risk means that the seismicity risk can be adequately represented.

The selected earthquake range in Albania is between 5.4–6.9. Medium-sized earthquakes are mostly in the range of 0.1–0.2 g. However, the acceleration of the 5.4 magnitude earthquake that occurred in Tirana in 1988 was recorded as very high (0.4 g), exceeding the expected acceleration value (0.28–0.3 g). Two earthquakes, one moderate (5.7) and the other large (6.9) were selected in Bosnia and Herzegovina. The first selected earthquake exceeded the expected acceleration value (0.17 g) at nearby stations and took values in the range of 0.29–0.43 g. However, the 6.9 magnitude earthquake created an acceleration value (0.01–0.4 g) far below the expected acceleration value (0.18–0.26 g) at stations approximately 200 km away. In three different earthquakes selected in Croatia, a small (4.9) earthquake, however, close to the recording station (6.4 km) created an acceleration of 0.0 g. The acceleration value created by the 6.4 magnitude earthquake 60 km away from the station was 0.04 g. The 6.9 magnitude earthquake that occurred in Montenegro in 1979 had an acceleration of 0.08 g in Dubrovnik, 105 km away, and 0.04 g in Makarska, 208 km away. All of the recorded accelerations are considerably lower than the expected acceleration values. The earthquakes considered in Serbia are medium-sized, and the distances of the earthquakes to the acceleration stations are also high. Moreover, the places where the stations are located are rocky. For this reason, the acceleration values formed were quite low. The lowest of the five earthquakes selected that occurred in Türkiye is 6.3 and the highest is 7.4. It is quite interesting that three earthquakes greater than 7 produce very different accelerations from each other. The lowest acceleration was recorded in Van (Mw= 7.2) with 0.182 g and Düzce (Mw = 7.2) with 0.823 g. However, very high accelerations were observed in Erzincan (Mw = 6.8) earthquakes in 1992 and Bingöl (Mw = 6.3) earthquakes in 2003 (Bingöl 0.511 g

and Erzincan 0.485 g). One of the main factors in recording very high acceleration values is the proximity of the recording station to the earthquake focus and the other is ground conditions. It is seen that very high acceleration values were recorded in three different earthquakes in Iran. The 7.37 magnitude earthquake that occurred in Manjil in 1990 was recorded differently at different stations. Accordingly, the acceleration value of 0.13 g in Qazvin, 0.086 g in Rudsar, and 0.538 g at the other station in Rudsar show how different geological conditions affect the acceleration value. The acceleration of the 7.35 magnitude earthquake that occurred in Tabas in 1978 was recorded as 0.64 g, and the acceleration of the 6.6 magnitude earthquake that occurred in Bam in 2003 was recorded as an extraordinarily large 0.97 g. It is clear that the very loose soil structure of the city of Bam played the most important role in such magnification of the acceleration value.

The highest loss of life/damaged buildings ratio was found as 0.24 for 17.08.1999 Türkiye (˙Izmit) and the lowest value was determined as 0.0006 for 26.11.2019 Albania (Durrës). While the highest loss of life among all earthquakes was 17,480 in the 17.08.1999 Türkiye (˙Izmit) earthquake, the most building damage occurred in the Albania (Durrës) earthquake of 26.11.2019 with ~90000 buildings.

In order to reveal the effect of different structural conditions within the scope of this study, the number of storeys, local soil class, building importance class, and concrete class were chosen as variables. There is complete agreement between the target displacements obtained for all variables. The target displacements increased for three different limit conditions as the number of storeys in the building increased. In the case of weak local soil properties, the target displacements were obtained larger. The values obtained for ZA are lower than the values obtained for ZD. At the same time, target displacements were found to be larger in buildings that were required to be used after the earthquake. The displacements obtained for the building importance class IV are larger than those obtained for the II. class. As the strength of the concrete decreased, the target displacements expected from the structure increased. This once again reveals that buildings with weak earthquake vulnerability require larger displacements.

However, it was examined whether the seismic risks taken into account for different countries are adequately represented. In this context, since the seismicity elements of each country differ, the losses resulting from the earthquakes vary. Therefore, it is obvious that the realistic determination of the seismic risk will result in a more realistic result with the performance levels expected from the structures. In this respect, the building stock characteristics and local ground conditions also directly affect the losses. The vulnerability of the existing building stock increases the structural damage.

 Loose layers near the surface cannot be a source of earthquakes in this sense. However, since such areas are areas of weakness, they allow the incoming tremor to reach the surface easily and stand out because they are geologically highly impacted areas. In this study, it is observed that the earthquakes selected in countries other than Bosnia and Herzegovina and Croatia occur under the influence of geological conditions. Selected earthquakes in Albania are mostly in Durres, Shkoder, and Tirana. The depression areas formed with the neotectonic uplift that started in the Pliocene period in Albania led to the formation of Quaternary lakes and plains. In these grabens, the thickness of which reaches 200 m, unstable soil formations at the swamp level cause earthquakes to be more effective [170]. In Serbia, mainly earthquakes occurred in Kraljevo. This area is in the current alluvial and Tertiary flysch structure. The second important earthquake zone is the Pec zone, which is also the flysch zone. Therefore, it can be said that earthquakes occurring in these regions are based on weak geological conditions. Almost all the earthquakes selected in Türkiye have occurred in the current alluvial areas (Erzincan, Kocaeli, Düzce, Bingöl, Van). Plain regime areas created by very thick alluvial structures and active tectonism continue to be sources of earthquakes. The Bam and Manjil earthquakes, which were selected from the earthquakes that occurred in Iran, were effective in the current alluvial basin-type areas. The reason for the occurrence of earthquakes in these areas can be considered as specific geological conditions.

Buildings constructed in loose and unstable ground conditions are the most vulnerable to earthquakes. For this purpose, it is necessary to choose the soil-building interaction correctly. Almost all the earthquakes selected in this article, which are considered important in the country where they occurred due to the damage caused, have resulted in severe damage due to incompatibility. One of the main purposes of this study is to show that the damages caused by earthquakes without borders are based on similar faults.

It is important to construct buildings in accordance with earthquake-resistant building design guidelines in earthquake-prone regions against the possibility of the recurrence of earthquakes that cause significant damage. This depends on the correct application of earthquake-resistant building design principles during the design and construction stages. The application of earthquake-resistant building design principles together with adequate supervision can be seen as the first step in minimizing the problems, both during the project and construction phases. In addition, the existing building stock should be determined quickly and reliably, and then strengthening and demolition procedures should be decided in buildings that do not have sufficient earthquake performance. At this point, the number of weak buildings under the effect of earthquakes should be minimized by utilizing urban transformation.

**Author Contributions:** Conceptualization, E.I., M.H.-N., H.B., N.A., A.B., E.H., B.B., H.B.Ö. and S.E.A.H.; methodology, E.H., S.E.A.H., E.I., A.B. and E.H.; software, E.I., N.A., H.B. and M.H.-N.; validation, E.H., A.B., H.B.Ö. and S.E.A.H.; formal analysis, B.B.; investigation, E.I., M.H.-N., H.B., N.A., A.B., E.H., B.B., H.B.Ö. and S.E.A.H.; resources, E.I., M.H.-N., H.B., N.A., A.B., E.H., B.B., H.B.Ö. and S.E.A.H.; data curation, E.I., M.H.-N., H.B., N.A., A.B., E.H., B.B., H.B.Ö. and S.E.A.H.; writing—original draft preparation, N.A., A.B., E.I., B.B. and M.H.-N.; writing—review and editing, S.E.A.H., N.A., M.H.-N., E.I. and E.H.; visualization, H.B.; supervision, E.I., N.A., M.H.-N. and B.B.; project administration, E.I.; funding acquisition, M.H.-N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data sharing is not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


*2.3. Climatic Conditions*

The monthly temperature, precipitation, and humidity were recorded by the State Meteorology Station for Antalya (Table S3) and Isparta (Table S4). For 2018–2019 and 2019–2020, there were similar trends for temperatures, with the lowest temperatures occurring in January and February and the highest in June at Antalya. The highest rainfall was recorded in December. Additionally, there was less rainfall in 2018–2019 than in 2019–2020 in all growing seasons except for January, April and June. Similarly, the highest rainfall

was observed in December and January in Isparta (highland), however at least 40% total rainfall was recorded compared to Antalya. The coldest month in highland is January, with 5.2 (◦C), followed by February and March (Table S4).


Response Surface Methodology Optimization in Asphalt Mixtures: A Review

*Aliyu Usman, Muslich Hartadi Sutanto, Madzlan Bin Napiah and Nura Shehu Aliyu Yaro*

#### **Abstract**

The application of statistical modeling and optimization approaches such as response surface methodology (RSM) is important for the excellent potential to tackle different constraints and goals and the analysis of the relationships between independent factors influencing a particular response. This chapter provides a simple yet detailed literature review on the utilization of RSM for the design of experiments, modeling, and optimization of virgin and alternative materials into asphalt binder and mixtures for sustainability. Meanwhile, an in-depth analysis based on the literature reviewed in terms of asphalt binder modification employing RSM with various independent parameters were summarized. Also, a critical review of the application of RSM to optimize the engineering and mechanical performance characteristics of asphalt concrete mixtures is presented in this chapter. The current chapter concluded that the use of RSM statistical analysis in a highway materials perspective provides a broader understanding of the factors that control pavement performance throughout the pavement service life.

**Keywords:** asphalt binder, asphalt concrete mixture, response surface methodology, prediction, optimization

#### **1. Introduction**

In order to get the most benefits from a process and maximize its efficiency, optimization of the process is needed. Optimization refers to picking the ideal factor from a collection of potential solutions (independent variables). In certain applications, the value of the variable is enough to achieve the optimal output or best possible outcome. The common practice used to assess optimum design parameters is to evaluate the effect of each variable independently on the response [1, 2]. In this process, interactive effects among parameters are not regarded. Consequently, this approach does not display the full impact of these variables on the outcome. Another primary disadvantage of this method is the increase in the overall number of tests needed for the investigation, leading to an increase in costs and materials, and time [3, 4]. Owing to these drawbacks, researchers have been exploring alternative approaches. For the past decades, response surface methodology (RSM) is among the most effective approaches used for modeling and optimization. Myers, et al. [5] defined response surface methodology (RSM)

as a statistical method that is commonly used to optimize engineering design and operations. The majority of RSM applications require multiple response variables. In a typical RSM analysis, the experimenter will create an empirical model like the second-order model to every response using these models to evaluate the configuration of the design variables that generate optimum or at least appropriate response values [2, 6]. RSM has great relevance in the design, development, and introduction of new material and the enhancement of material designs. RSM describes the influence of independent variables, either alone or in synergetic effect, during the process. It also helps in evaluating the influence of independent variables, this experimental approach produces a statistical model that explains the mechanism and processes [2, 5, 7]. While RSM has several benefits, it can be concluded that it applies to all modeling and optimization analyses of various aspect of engineering, RSM has now been commonly and successfully used to optimize asphalt binder and asphaltic concrete mixtures to maximize their performances and promote sustainability. The current research examined the application of RSM for modeling and optimization in asphalt pavement studies. In this chapter, several recently published RSM studies have been examined to have an overview and access the application of RSM in the pavement industry.

#### **2. Design of experiment (DoE)**

Design-Expert is a software for experimental design, statistical analysis, modeling, and optimization. It provides a variety of programs such as fractional factorial design, surface response, full factorial, mixing, and D-optimal designs [1, 2, 8]. RSM experimental designs are developed using the Design-Expert program. The program is also utilized to analyze the data obtained. Regression is applied to data obtained where the measured variable (response) is estimated based on a functional relationship between the predicted input variables. Experimental values that can be altered independently of one another are referred to as factors or independent variables [2, 9]. Variable levels are the various stages of the factors at which the experiments are to be performed. After conducting the experiment, the data obtained are called responses or dependent variables. While residual is the discrepancy between the experimental and predicted values for the determined range of experimental criteria also model with low residual values indicates a strong fitting of the experimental data [8, 9].

#### **3. Response surface methodology (RSM)**

Box and Wilson [10] introduced RSM in 1951 and they proposed using a seconddegree polynomial model. RSM has recently been used for process parameter optimization. RSM can be considered as a systematic calculation technique for the optimization problem. This method provides an appropriate experimental method that incorporates all the independent variables and utilizes the experiment's input data to subsequently create a set of equations that can offer an output's theoretical value [11]. The findings are achieved from a well-designed regression analysis that examines the relationship between independent variables'-controlled values. Based on the new values of independent variables, the dependent variable can then be forecast [11]. RSM is an effective statistical tool for both the modeling and optimization of multiple variables with a minimum number of experiments to forecast the optimum performance parameters [7, 12]. By employing the RSM technique in the optimization process, the testing of all the variables relating to the product assessment requires just a short time, making the laboratory test stage more efficient [11]. *Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

Furthermore, the estimation of parameters that profoundly influence the model can determine which allows researchers to concentrate on those specific variables to improve the performance of the process [11]. In a set of experimental designs, one factor or process variable can depend strongly on or be dependent on another variable. In an attempt to discover the output–input relationship, understanding the interaction between the variables is critical, that is why taking a single factor at a time approach is seldom used to evaluate interrelationships between parameters. RSM can determine the relationship as well as interactions between the multiple parameters using quantitative data by creating a model equation. In RSM implementation, there are three steps; (i) experiment design, i.e., Box Behnken (BBD) and Central Composite Design (CCD); (ii) statistical and regression analysis to build model equations that describe the modeling of the response surface; and (iii) optimization of parameters/variables carried out via model Equation [13]. A statistical experimental design is presented in RSM. Different experimental designs could be carried out based on the special criteria and the choice of experimental points and numbers. In addition to randomizing the experimental error to every experimental point, operating with a statistical experimental design often implies the distributions of experimental points in the examined set of independent variables. These improve the reliability of the model Equation [5].

#### **3.1 Central composite design (CCD)**

The most widely and frequently employed and effective design technique is central composite design (CCD). A minimum of two numerical inputs is required and varied in the CCD approach at a range of alpha (α) over three (−1, 0, +1) or five (−α, −1, 0, +1, +α) stages. Three features are contained in the CCD model: (i) a complete factorial or fractional factor design; (ii) an additional design, mainly a star design with experimental points from the centre at alpha; and (iii) a central point. There are various ways to CCD depending on the alpha (α)-value, such as face-centred central composite (FCCD), rotational, spherical, orthogonal quadratic, and practical. Five levels are utilized for the rotational and spherical approaches depending on the number of variables. The value of alpha (a) for the FCCD is always unity. This means that the axial points are not positioned on the spheres, but rather on the centre of the faces, so only three variants of each parameter are involved [2]. **Figure 1**(**a** and **b**) illustrate the full factorial central composite model for two and three parameters optimization.

**Figure 1.**

*Optimization of two and three parameters using CCD (a) two parameters (X1 and X2) where alpha (*α*) = 1.41 (b) three parameters (X1, X2, and X3) where alpha (*α*) = 1.68 [12].*

#### **3.2 Box Behnken design (BBD)**

Box–Behnken Design (BBD) suggested how to select points from a three-level parameter model to permit the first- and second-level coefficients of the statistical model to be effectively assessed. In this way, these designs, especially for many variables, are more efficient and cost-effective than their respective 3k design models. A minimum of three numerical factors are required in BBD and vary across three levels. In Box–Behnken models, the experimental points are situated on a hypersphere spaced uniformly from the central point. BBD's key characteristics are: (1) it requires an experimental number depending on the Eq. N = 2 k (k − 1) + cp, where k is the number of variables and (cp) the number of central points; (2) it is appropriate to change all factor levels at three levels only (−1, 0, + 1) with intervals spaced equally. BBD has been used successfully as a physical and chemical technique for different optimization processes. Other RSM design techniques, such as one factor, optimal design, miscellaneous design, user-defined, and historical data designs, are available [2].

#### **3.3 Motivation for the chapter**

Due to the challenges facing the conventional pavement materials such as asphalt binder and mixtures and the paradigm shifts towards green and sustainable construction. The application of RSM is one of the promising ways used by pavements engineers as it has shown to be of great importance in the design, development, and incorporation of alternative green materials for the improvement of the pavement material design. Modeling and optimization of the synergetic impact of different parameters that affect the engineering properties and performance output of the asphalt binder and mixtures utilization help to provide more insight into the influences of the various variables. This experimental method generates a numerical method that helps elaborate on the mechanism and procedures that involve a lesser

**Figure 2.** *General RSM design flow chart.*

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

number of experimental runs. Thus, the utilization of RSM is of pivotal use for pavement engineers.

RSM is an effective instrument for engineering new bituminous blends. By forecasting the response of the materials on the basis of experimental plans drawn up with a scientific and statistical method [14]. Also, another RSM's key goal is to evaluate the optimal settings for control variables that lead to the maximum or minimum output over a certain area of study. The generated equations can be used for interpolation to obtain the maximum (or minimum) predictable results within the levels of the analyzed variables [14–16].

The general design flow chart of the RSM statistical technique framework is presented in **Figure 2**.

#### **4. Asphalt mixing process for incorporating new materials**

Three methods are employed to incorporate new sustainable materials into asphalt binders and mixtures for optimization. These methods are selected based on the type and properties of the new material to be incorporated. These methods are wet process, dry process, and modified dry process.

#### **4.1 Wet process**

The wet method comprises blending the newly added material with the heated asphalt binder to form the modified asphalt binder, The optimization is commonly done on the mixing parameters or the conventional properties of the mixes and the mixture is formed by blending hot aggregates with the modified asphalt binder. This method is suitable for materials having low melting points such as low-density polyethylene (LDPE), and polypropylene (PP). This method requires a high-shear mixer and sufficient time for blending the newly added material and asphalt binder [15].

#### **4.2 Dry process**

In the dry method, before adding asphalt binder to the mixture, the new sustainable green material is initially incorporated into the heated aggregates and mixed [16]. In this technique, some of the filler is lost as dust when blending the new material with the aggregates, which is not suitable [15]. This method is suitable for materials with a higher melting point above the asphalt mixture mixing temperatures such as polyethylene terephthalate (PET) and high-density polyethylene (HDPE). The optimization process using involves the mixing process and mechanical properties of the asphalt mixtures.

#### **4.3 Modified dry process**

In the modified dry method, new added sustainable green materials are incorporated while the heated asphalt binder and aggregates are thoroughly mixed [17]. The added new materials particles are ensured to be well coated by the asphalt binder. It is hypothesized that minor changes in the shape and properties of added waste materials during mixing will result from the modified dry process [15, 18]. Some experts modified the blending techniques to obtain a good distribution of the waste materials particles in the modified blends. The optimization process using involves the mixing process and mechanical properties of the asphalt mixtures.

#### **5. Utilization of RSM optimization techniques in asphalt binder modification**

RSM has been utilized in the modification of asphalt binder and optimization of the modification mixing parameters to enhance sustainability and improve performance of various bitumen modifiers using different dependent and independent variables associated with the bitumen, modification process, and performance of the bitumen. Assessment and investigation of the interactive effects on the response of process variables can thus be studied and analyzed using RSM. The model equation also quickly clarifies the effects with the various combination of the independent parameters. In this section the application of RSM for the modification of asphalt binder utilizing several types of alternative materials. Most of the prior study includes studies of the mixing conditions of asphalt binder and its conventional properties are discussed below.

A study conducted by Liu, et al. [19] evaluated the effects of mixing variables parameters such as mixing speed, time, temperature, and the modifier (diatomite and crumb rubber) on modified asphalt binder properties (penetration, softening point, penetration index, viscosity, elastic recovery, and ductility) were examined and optimization using RSM. The findings showed that with the increase in crumb rubber concentration, softening points, viscosity, elastic recovery, and penetration index increased, while penetration and ductility decreased. With the rise in diatomite concentration, the softening points, viscosity, and penetration index increase, while penetration and ductility decrease, which has little effect on elastic binder recovery. The shear temperature has had major impacts on penetration, ductility, softening point, and viscosity. Because of its similar mechanism of action, shear velocity, shear duration, and storage time have similar influences on binder properties. The optimum speed, time, and temperature of mixing were achieved at 55 min and 5300 rpm, 55 minutes, and 183 °C, respectively, based on the optimization. The effects of the various mixing parameters on the convention properties of the diatomite and crumb rubber modified bitumen is illustrated in the 3D surface plots in **Figures 3-5**.

Recently, the effects of various crumb rubber (CR) contents and their interactions with high-temperature ranges on the rheological activity of asphalt binder were also studied by Badri, et al. [20] At temperatures ranging from 46 °C to 82 °C, a temperature sweep test was performed using a dynamic shear rheometer (DSR) on modified binders with 5, 7, 10, 12 and 15% crumb rubber content. Based on central composite design (CCD) and considering the rheological parameters complex modulus (G\*) and phase angle (δ) as response variables, RSM statistical analysis was performed. The outcome of the ANOVA test showed that rheological parameters were significantly affected by temperature and rubber content with p less than 0.05. Independent effects of temperature and rubber content were analyzed, and the results showed that both responses were affected by the interaction of both independent variables but were more impacted by rubber content than temperature as depicted in the synergetic effect of the variables on the CR modified bitumen are shown in the 2D and 3D contour diagrams in **Figures 6** and **7**. It can therefore be inferred that RSM is an efficient tool for investigating rheological characteristics. For all responses, a percentage error of <5% was achieved, suggesting that the optimization process by RSM is a very efficient and effective technique.

Also, the RSM was used to evaluate both the volumetric and mechanical properties of asphalt mixtures after modifying the mix variables. A study conducted by Nassar, et al. [21] optimize the design mix variables, namely bitumen emulsion content (BEC), pre-wetting water content (PWC), and curing temperature (CT), the Response Surface Methodology (RSM) was used. The purpose of this work was

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

**Figure 3.**

*Response surface plots for the preparation parameters on penetration values (a) shear time and diatomite (b) shear temperature and crumb rubber and for softening point. (c) shear time and diatomite content, (d) shear speed and crumb rubber content [19].*

to evaluate the relationship influence on the mechanical and volumetric properties of cold bitumen emulsion (CBEMs) between these parameters. To determine the mechanical response, indirect tensile strength (ITS) and indirect tensile stiffness modulus (ITSM) tests were performed while air voids and dry density were calculated to obtain volumetric responses. Besides, the total fluid content was used in the typical mix design technique, the individual effects of BEC and PWC are significant. The findings show a lower CBEM strength/stiffness at the same overall fluid content and with varying ratios of BEC/PWC. The stiffness modulus assessment of the CBEM after 10 days is anticipated to provide the designer with sufficient information to optimize the CBEM mix model in a reasonable period. The overall 3D surface plots showing the interaction between the three autonomous factors on the output parameters.

Another research by Varanda, et al. [22] utilized RSM in the formulation of bitumen mixtures from the refining process of base oils utilizing asphaltic residue, vacuum residue, and three aromatic extracts (by-products). The asphaltic residue (A), vacuum residue (B), and the three different aromatic extracts (hereafter denoted by Extract-1 (C), Extract-2 (D) and Extract-3 (E)) from base oil refining, all derived from the same crude oil source (Arabian Light), To control bitumen formulation, a constrained mixture methodology was employed. The projected and calculated responses show that both models are reliable with average deviations of just 4.67% and 1.53% respectively for the penetration and the softening stage. Mixture design has been shown to be an effective and important instrument for bitumen formulation in general especially if a significant number of components are included in the blends. In general, in contrast to aromatic extracts, both asphaltic and vacuum residues impart greater stability to bitumen, which ensures that the

**Figure 4.**

*Response surface plots for the preparation parameters on Ductility. (a) Shear time and diatomite (b) shear speed and Crumb rubber content and Viscosity values on (c) shear temperature and diatomite (d) shear time and crumb rubber [19].*

softening point increases while penetration reduces. The asphaltic residue, however, transmits more difficult properties to bitumen n vacuum residue.

Wang and Fan [23] utilize Box–Behnken model RSM was to obtain the optimum values of process parameters for calcium sulphate whisker (CSW) modified bitumen. To access the mechanism of modification, three input variables, stirring time, stirring temperature, and production temperature was chosen. Three performances were evaluated as reactions by testing in the, including high-temperature efficiency, low-temperature efficiency, and deformation resistance related to the bitumen properties. The study found that mixing time of 32 min, mixing temperature of 175 °C, and production temperature of 175 °C were the optimum process parameters within the range of this analysis, with accurate precision compared to actual experimental results. In contrast, the influence of three process parameters on bitumen properties was also investigated, and stirring time was found to have a more important impact on the softening point, penetration, and ductility. CSW has a reasonable dispersion in the bitumen matrix under the optimization process parameters and has been shown to increase the physical performance of the bitumen.

del Barco Carrión, et al. [14] use RSM to develop a modified bitumen with a mixture of Liquid Rubber (LR), a uniform mix of 50–70% pre-processed Recycled Tyre Rubber (RTR) in conjunction with wax and heavy oils blend. To forecast the response of different combinations of LR and Ethylene Bis Stearamide (EBS) in terms of temperature (high and low) properties and expenses, the RSM was used to optimize both conventional and rheological properties of Polymer Modified Bitumen (PMBs) commonly utilized in bitumen blends and roofing membranes. Both two modifiers show improve bitumen elasticity and stiffness, thus complementing each other. In general, the LR oils decrease the stiffness of the neat bitumen whereas the EBS has been shown to increase the stiffness and elasticity of

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

#### **Figure 5.**

*Response surface plots for the preparation parameters on Elastic recovery. (a) Diatomite and crumb rubber (b) storing time and shearing speed and PI values of (c) Shearing time and diatomite content (d) shear temperature and crumb rubber content [19].*

**Figure 6.**

*Effects of input factors on phase angle (a) 2D contour for the synergistic influence of rubber content and temperature (b) 3D surface diagram for the synergistic influence of rubber content and temperature.*

the blends significantly, thus enabling the use of higher LR quality to comply with disadvantages. LR contents in the range of 30–40% by weight of neat bitumen are the optimum composition of blends, thus reducing the need for virgin bitumen in terms of overall modification for both pavement and roofing.

Recently, Memon, et al. [24] utilizes RSM for modeling and optimizing the bitumen physical characterization, the mixing conditions of petroleum sludge modified bitumen (PSMB) using the penetration, softening point, penetration index, and

#### **Figure 7.**

*Simultaneous effect of input parameters on complex modulus (a) Plot of 2D contour on the synergistic influence of rubber content and temperature (b) 3D plot for the synergistic influence of rubber content and temperature.*

#### **Table 1.**

*Summary of previous works of literature on the utilization of RSM for asphalt binder optimization.*

storage stability. The findings show that the stiffness of PSMB was strengthened by the synergistic effects of mixing temperature and speed, whereas the mixing time initially reduces and then increases the stiffness of PSMB. The PSMB met the *Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

storage stability and the penetration index requirements for bitumen modification under optimum mixing conditions. This enhancement in stiffness at higher mixing conditions is due to the increased ratio of maltenes to asphaltenes in PSMB. While at high mixing conditions, the softening point influences were reduced, whereas it was noted that the lightweight oil component of the PS was also responsible for the softening point decline of the PSMB. The mixing time, speed, and temperature for PSMB were evaluated to be 53 min, 1292 rpm, and 149 °C, respectively, based on the RSM optimization. The overview of prior works on the optimization of various autonomous parameters on bitumen conventional properties is displayed in **Table 1**.

#### **6. Application of RSM in modeling and optimization of materials for asphalt mixtures modification**

Several RSM studies have been published, this study emphasizes the utilization of RSM for optimizing virgin or waste materials as alternative asphaltic mixtures materials for sustainability. In this section, the application of RSM for the optimization of the virgin as well as waste secondary materials will be discussed depending on the work of existing literature.

The application of Response Surface Methodology (RSM) for the prediction of Marshal volumetric properties is being explored by Bala, et al. [34] Polyethylene and nanosilica were used as the independent factors in the analysis, while the air

**Figure 8.**

*2D and 3D RSM contour plots for the optimization of nanosilica and binder content (a-b) Air void (c-d) Stability (e-f) Flow [34].*

#### **Figure 9.**

*RSM 3D contour for the optimization of irradiated PET fiber and binder content (a) Density (b) Air void (c) VFB (d) Stability (e) Marshall flow [35].*

void, flow, and Marshall stability were the responses. Findings show that RSMbased statistical analysis confirms that it is possible to use a quadratic model built with a high degree of correlation and predictive capacity to predict the Marshal volumetric properties of the mixture. **Figure 8(a)** and **(b)** demonstrates that the binder content has more impact on the air void than the nanosilica content, whereas **Figure 8(c)** and **(d)** illustrates that both independent factors have an influential effect on the Marshall stability of the asphalt mixture. On the Marshall flow values for the nanosilica modified asphalt blend, a combined effect of both variables was noted but the binder content has a more pronounced impact on the flow values as presented in **Figure 8(e)** and **(f )**.

Recently, Usman, et al. [35] optimize irradiated waste PET fiber and binder contents utilizing RSM on the volumetric and strength properties of fiberreinforced asphalt mixes. **Figure 9(a-e)** illustrates the interactive impacts of the mixture design parameters on the dependent variables. It was hinted that both independent factors have a significant positive effect on the bulk specific density (BSD), Marshall stability, and the Marshall flow values for the fiber-reinforced asphalt mixes. However, on the air void (AV) and voids filled with bitumen (VFB), the asphalt binder content has a more pronounced influence compared to the irradiated waste PET fiber content. The investigation concluded that the use of fibers in asphalt mixture production improves the strength and performance characteristics of asphalt mixes and based on multi-objective optimization analysis, 5.25% and 0.53% as the optimized contents for binder and irradiated waste PET, respectively.

Likewise, in 2020, Omranian, et al. [36] investigate the effects of short-term aging on asphalt concrete mixture compactibility and volumetric characteristics. Three independent parameters, including aging temperature, aging period, and duration in humidity and ultraviolent chambers, were considered in this analysis, while the compaction energy index (CEI) and volumetric characteristics, were considered as responses. Significant impacts of aging temperature and duration on compactibility, air voids (AV), mineral aggregate voids (WMA), and asphalt filled voids (WFA) are revealed in the research findings. However, duration in the environment chamber did not exhibit any significant effect on responses, as shown in **Figure 10(a-d)**. Finally, the analysis shows the ability of the RSM to predict

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

**Figure 10.** *Graphical representation of RSM 3D contour (a) CEI (b) Va (c) VMA (d) WFA [36].*

changes from mathematical equation responses that correlate with the empirical findings with good precision. This finding concluded that to achieve the desired requirements, pavement designers should use RSM statistical technique to predict the pavement density and adjust pressure as well as the number of rolling passes.

Khan, et al. [37] explore the applicability of utilizing RSM to investigate the relationship between autonomous and dependent parameters for the formulation of cementitious grout. In the study, regular and irradiated waste PET and fly ash contents were optimized. A high coefficient of determination (R2 ) with an adequate precision (AP) of greater than 4 from the analysis of variance was reported. It was further revealed that gamma irradiation exposure of waste PET resulted in the usage of a higher percentage of the waste PET in comparison to the regular waste PET without compromising the properties considered in the study. Moreover, the investigation concluded that waste PET treatment with gamma rays could be an innovative and effective way to recycle waste PET in the formulation of cementitious grout for semi-flexible pavement application as cement replacement material and can be an important advancement to attaining the zero-waste plastic goal of the united nation sustainable development.

The permanent deformation property of asphalt concrete incorporating various concentrations of recycled asphalt pavement (RAP) and quantities of the waste engine and cooking oil was evaluated by Taherkhani and Noorian [38] using response surface methodology. The study substituted 25, 50, and 75% of total aggregates with RAP and rejuvenated each with 5, 10, and 15 percent (by total binder weight) of waste engine oil (WEO) and waste cooking oil (waste cooking oil) (WCO). A polynomial quadratic model was reported to be accurate to predict the permanent strain employing RSM in the Design-Expert software. RAP and oil content, squared oil content, and oil types were significant terms for the prediction of permanent strain. Results show that with increasing RAP content, permanent strain decreases, but for each RAP content, the lowest permanent strain is reached at a specific oil content amount. The finding concluded that through RSM optimization, the concentration of oils was obtained to achieve asphalt mixture with a comparable control mix deformation property.

#### **Table 2.**

*Summary of previous works of literature on the utilization of RSM for asphalt mixtures optimization.*

Bala, et al. [39] employed RSM to optimize two independent parameters, namely nanosilica and binder content effects on the response factors VMA, Marshall stability, flow, fatigue life, and indirect tensile strength (ITS). It was observed that VMA decreases substantially for binder content from 4–5%, beyond that it experiences a decreasing trend for mixtures fabricated with binder content between 5–6%. The findings also reported that nanosilica content has less influence on the VMA compared to the binder content. Also, the contour plot revealed that on the Marshall stability, the nanosilica particles have a marginal effect than the binder content. For the flow, fatigue life, and ITS, both nanosilica and binder contents have significant impacts on the nanocomposite modified asphalt mixes. The finding concluded that 2.67% and 4.65% as the optimized nanosilica and binder contents for an improved mixture performance property.

Several studies have been performed on the effect of different alternative materials on asphalt concrete mixtures [19, 40–48]. **Table 2** presents the summary of some selected work done utilizing RSM for different independent factors on several mechanical performance properties of asphalt concrete mixes.

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

#### **7. Conclusions**

RSM has effectively been utilized for various applications in the pavement industry. The current book chapter provides an overview of RSM applications for bitumen, asphaltic mixture modification, and performance properties. From the review, it was observed that RSM has many benefits in improving the knowledge about the synergetic effect of various modification variables on the bitumen performance. RSM technique provides an in-depth understanding of the influence of other responses with the variability each mix design factor would have on the asphalt mixture performance. RSM also has shown the benefit of analyzing various autonomous variables concurrently. For several optimization research, the implementation of RSM to achieve optimum dependent variable outcome leads to considerably reduced costs of running experiments while at the same time optimizing the performance properties of both the bitumen and asphaltic mixtures. Thus, with the need to optimized mix design, RSM plays a crucial role in the pavement industry to establish a performance-based mix design about the above criteria. Generally, RSM can also be regarded as an effective alternative to optimize and understand the pavement mix design parameters effectively to produce optimal mixtures with less cost and sample runs. It was shown in this chapter that the RSM exhibits the great ability to determine the compactness and mechanical efficiency properties of asphalt binder and mixtures under different conditions quickly and accurately. With appropriate precision, the model developed by the RSM always fits into the experimental observations. This means that in predicting the effects of the autonomous parameters on the response variables, these models are accurate and realistic. RSM's proposed models can be used by the highway industry as a valuable and effective way to controlling and preparing the construction method to achieve the best pavement performance characteristics, which can significantly increase pavement performance and longevity.

#### **Acknowledgements**

The authors would like to appreciate the support provided by Universiti Teknologi PETRONAS for carrying out this review.

#### **Conflict of interest**

The authors declare no conflict of interest.

#### **Author details**

Aliyu Usman\*, Muslich Hartadi Sutanto, Madzlan Bin Napiah and Nura Shehu Aliyu Yaro Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Bandar Seri-Iskandar, Malaysia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. 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, and reproduction in any medium, provided the original work is properly cited.

*Response Surface Methodology Optimization in Asphalt Mixtures: A Review DOI: http://dx.doi.org/10.5772/intechopen.95994*

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#### **Chapter 7**