So, although logic should have tip the balance towards the utilization of structure-based methods, there is a bias towards screening of libraries of chemical compounds by high throughput methods looking for whole-cell or "in vitro" enzyme inhibition.

## **7. Summary**

There are several reviews in the literature that describe the mechanisms of action of antitubercular drugs currently in clinical use, and also a large number of publications summarizing the quest for new drugs and the nature of the novel compounds that may be added to the anti-tubercular treatment in short time. The objective of this review is different from that, and although I have offered a brief account of the recent developments in the field, commenting on the two main approaches (broad screening *vs* structure-based design) for anti-tubercular drug development, I have chosen to focus on few compounds to

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demonstrate that there are drugs already produced at pharmaceutical industry levels (namely azole drugs, verapamil, reserpine, and thioridazine) with a large history of use in humans –therefore providing rich information on adverse effects, pharmacokinetics, pharmacology, etc- which are effective on *M. tuberculosis*, not only on pan-susceptible strains but also on MDR-TB as well as on XDR-TB strains; moreover, the effect of some of those drugs reaches as far as the latent population of this pathogen. The fact that the mentioned compounds have already been approved for human use by regulatory agencies shortens the time for the evaluation of their new uses as many aspects have already been addressed. Thus we have a unique opportunity to seize, concentrating effort at academic laboratories to increase our understanding on mechanisms of action of these compounds as well as learning about the ensuing mechanisms of resistance in mycobacteria, testing drug –drug interactions and generating the comprehensive body of knowledge needed to incorporate these drugs to the anti-tubercular portfolio. On a personal basis, I strongly believe that coordinated effort on those compounds by research groups may produce at last the addition of the mentioned drugs to clinical treatment, helping to stop the spreading of human tuberculosis. It is possible that by taking a bold decision on those issues, we will reach our El Dorado: new drugs to defeat tuberculosis.

#### **8. Acknowledgements**

HRM is a carreer member of Consejo de Investigaciones, UNR, Argentina. This work was funded by grants from ANPCyT and UNR.

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**5**

*Brazil*

**An Approach to the Search for**

**New Drugs Against Tuberculosis**

Fernando R. Pavan1,\*, Daisy N. Sato1 and Clarice Q.F. Leite1,\* *1School of Pharmacy, São Paulo State University, Araraquara, SP,*

The history of *Mycobacterium tuberculosis* (MTB) as the main agent of tuberculosis (TB) goes back a very long time. Fragments of the spinal column of Egyptian mummies from 2400 BCE (Before Common Era) show definite pathological signs of tubercular decay (Tripathi, Tewari *et al.*, 2005). From that time to the present day millions have died of the disease and only a few drugs are active against the bacilli. Current data show an ancient disease more prevalent in the world today than at any other time in human history (Koul, Arnoult *et al.*, 2011). Annually, TB is responsible for the death of two to three million people worldwide and global economic losses around \$ 12 billion (Ma, Lienhardt *et al.*, 2010). Approximately a third of the world's population is estimated to be infected with MTB, giving rise to 9.4 million new cases of active TB disease each year (Zwerling, Behr *et al.*, 2011). In addition, the highly resistant Multi-Drug-resistant (MDR) and Extensively-Drug-Resistant (XDR) MTB organisms are virtually untreatable in immunocompetent patients. So when these bacteria enter into contact with highly immunocompromised HIV-infected populations, the mortality rate reaches 100% within a few weeks of infection (Gandhi, Nunn *et al.*, 2010).

No new specific drug against MTB has been developed since 1960 and the emergence of MDR-TB and XDR-TB highlights the ineffectiveness of current treatment (Lalloo e Ambaram, 2010). An effective new drug against TB could: (i) reduce the duration of the treatment, (ii) be active against resistant strains, (iii) not interfere with antiretroviral drugs and (iv) be active against latent bacilli (Ma, Lienhardt *et al.*, 2010). According to Koul et al (2011), the key questions are: how vigorous are current strategies to discover new TB drugs and what measures could be taken to shorten the protracted clinical development of new drugs (Koul, Arnoult *et al.*, 2011). In this chapter we describe a successfully working pipeline being developed at the "Dr. Hugo David" Laboratory, which is based on the responses that a new drug has to provide, ordered into a sequence of lead-optimization stages that go from initial screening hits to the

The lack of new anti-TB drugs since 1960, when rifampicin (RMP) was added to the therapeutic together with the failure of current treatment against MDR and XDR-TB and

final *in vitro* and *in vivo* preclinical assays of candidate drugs.

**2. Rational pipeline: Phenotypic or genotypic?**

**1. Introduction**

 \*

Corresponding authors


Meet the editors

Igor Loboda received his MS and PhD degrees in Aircraft Engine Engineering from the Kharkov Aviation Institute (Ukraine) in 1979 and 1994, respectively. He was an investigator, lecturer, and assistant professor at the Kharkov Aviation Institute from 1992 to 2001. Since 2001 he has been an assistant professor and investigator at the National Polytechnic Institute of Mexico. His research interests are in the areas of simulation and condition

monitoring of gas turbines and the common theory of pattern recognition. Particular issues of interest are gas turbine thermodynamic models (static and dynamic), model identification, analysis of real data (gas path variables), fault identification techniques, and neural network application to gas path diagnostics.

Professor Sergiy Yepifanov is a Professor (2003) and a Doctor of Sc., Eng. (2001) and the Head of the Aircraft Engine Design Department of the National Aerospace University "Kharkiv Aviation Institute" (Ukraine). He is an Honored Worker of Science of Ukraine. He has supervised 10 PhD dissertations. He is the co-author of 7 monographs and textbooks, as well as 33 scientific articles in indexed journals (SCOPUS) and more than

300 other publications. He is the chief organizer of the Engine Engineering Congress (every year since 1996). He is the lead lecturer of the education disciplines "Construction of Aircraft Engines", "Dynamics and Strength of Aircraft Engines", "Automatic Control Systems of Aircraft Engines", "Diagnostics of Aircraft Engines", "On-ground Application of Aircraft Turbine Engines", "Cooling Systems and Thermal Strength of Aircraft Turbine Engines", and "Life-time Designing of Aircraft Turbine Engines". His research interests are in the areas of turbine engine simulation, automatic control, and health management. He supervised and participated in creation of onboard and on-ground engine diagnosing systems of several aircrafts and engines that were developed in Ukraine and Russia.

Contents

**Section 1**

*by Igor Loboda*

of Gas Capacities

**Section 3**

*and Maha Khanfara*

Turbine Engine Starting Simulation *by Sergiy Yepifanov and Feliks Sirenko*

*by Sergiy Yepifanov and Roman Zelenskyi*

*by Cristhian Maravilla and Sergiy Yepifanov*

Based on a Doubly Fed Induction Generator

*by Imane Idrissi, Houcine Chafouk, Rachid El Bachtiri*

**Section 2**

**Preface III**

Introduction **1**

**Chapter 1 3**

Gas Turbines **11**

**Chapter 2 13**

**Chapter 3 31**

**Chapter 4 59**

Wind Turbines **77**

**Chapter 5 79**

Introductory Chapter: Gas and Wind Turbines and Their Models

Gas Turbine Simulation Taking into Account Dynamics

Parameters in an Engine Lifetime Monitoring System

A New Approach for Model Developing to Estimate Unmeasured

Modeling and Simulation of the Variable Speed Wind Turbine

## Contents

Preface

This book is devoted to the issue of modeling and simulation of turbomachines, namely gas turbines and wind turbines. Gas turbines are the main engines for power generation and transportation, and wind turbines present an increasingly growing sector of renewable energy production. The design of these complex machines and,

The book consists of three sections that include five chapters. Section 1 consists of the introductory chapter (Chapter 1), which introduces the area of modeling of gas and wind turbines and explains the demand for further model development.

Section 2 unites three chapters that offer particular improvements in gas turbine modeling. A novel methodology for the modeling of engine starting is presented in Chapter 2. Chapter 3 performs a thorough theoretical comparative analysis of models for the simulation of gas capacities between engine components, and offers practical recommendations on model applications, in particular for engine control purposes. In Chapter 4, the reader interested in gas turbine diagnostics can find the answer to how to compute important unmeasured parameters. Multiple algorithms for calculating these parameters are proposed and compared. The best algorithms

In section 3, the field of wind turbine modeling is presented in Chapter 5. It introduces a general-purpose model that describes both aerodynamic and electric parts of a wind power plant. Such a detailed physics-based model helps with the development of more accurate control and diagnostic systems that will result in

In this way, the book includes four new studies in the area of gas and wind turbine modeling. These studies are interesting and useful for specialists in turbine engine

**Igor Loboda**

México

Ciudad de México,

**Sergiy Yepifanov**

Kharkiv, Ukraine

Instituto Politécnico Nacional,

National Aerospace University – Kharkiv Aviation Institute,

in particular, the development of control and diagnostic systems rely on

mathematical modeling.

allow accurate prognostics of engine lifetime.

more effective electricity production.

control and diagnostics.


Diffusion Phenomena Numerical Analysis

**References**

Springer, 2013

2004

109-128

Algorithms; 2008

**112**

University Press; 2013

Element Method: Theory,

[1] Trangenstein J. Numerical Solution of Elliptic and Parabolic Partial Differential Equations. Cambridge

*Recent Advances in Numerical Simulations*

[2] M. Larson, F. Bengzon, The Finite

Implementation, and Applications,

[3] Ern A, Guermond J. Theory and Practice of Finite Elements. Springer;

ed. John Wiley & Sons; 2013

[5] Edelsbrunner H. Geometry and Topology for Mesh Generation. Cambridge University Press; 2001

[7] Notay Y. Aggregation-based algebraic multigrid for convectiondiffusion equations. SIAM J. Sci. Comput. 2012;**34**:A2288-A2316

[8] Akbari H, Pereira F. An algebraic multiscale solver with local Robin boundary value problems for flows in high-contrast media. Journal of Engineering Mathematics. 2020;**123**:

[9] Zienkiewicz OC, Taylor RL, Nithiarasu P. The Finite Element Method for Fluid Dynamics. 7th ed. Butterworth-Heinemann; 2013

[10] Hesthaven J, Warburton T. Nodal Discontinuous Galerkin Methods. Analysis, and Applications, Springer:

[6] Saad Y. Iterative methods for sparse linear systems. Second ed. SIAM; 2000

[4] Frey P, George PL. Mesh Generation: Application to Finite Elements. second

**Chapter 7**

**Abstract**

**1. Introduction**

**115**

Equations

*Gerald Tendayi Marewo*

A Modified Spectral Relaxation

Method for Some Emden-Fowler

In this chapter, we present a modified version of the spectral relaxation method for solving singular initial value problems for some Emden-Fowler equations. This study was motivated by the several applications that these equations have in Science. The first step of the method of solution makes use of linearisation to solve the model problem on a small subinterval of the problem domain. This subinterval contains a singularity at the initial instant. The first step is combined with using the spectral relaxation method to recursively solve the model problem on the rest of the problem domain. We make use of examples to demonstrate that the method is reliable, accurate and computationally efficient. The numerical solutions that are obtained in this chapter are in good agreement with other solutions in the literature.

**Keywords:** Emden-Fowler equations, Lane-Emden equations, singular initial value

*dx* þ *r x*ð Þ¼ , *y s x*ð Þ, 0 <*x*, *γ* >0

(1)

*dx* ð Þ¼ 0 0, *m* ∈ (2)

*dx* ð Þ¼ 0 0, *α* ∈

for the Lane-Emden Eq. (1) models several phenomena such as the thermal behaviour of a spherical cloud of gas acting under the mutual attraction of its molecules [1], the temperature variation of a self gravitating star, the kinetics of combustion [2], thermal explosion in a rectangular slab [3] and the density distribution in isothermal gas spheres [4]. Moreover, Eq. (1) has been used many a time

A particular case of Eq. (1) is the Emden-Fowler equation of the first kind:

As mentioned in [5], Eq. (2) represents the dimensionless form of the governing equation for the gravitational potential of a Newtonian self-gravitating, spherically

*dx* þ *ym* ¼ 0, *y*ð Þ¼ 0 1, *dy*

problem, spectral relaxation method, numerical method

*y*ð Þ¼ 0 *α*,

*dy*

The singular initial value problem

as a benchmark for new methods.

*d*2 *y dx*2 þ

2 *x dy*

*d*2 *y dx*2 þ *γ x dy* **Chapter 7**