Download or read book Effective Formulations of Optimization Under Uncertainty for Aerospace Design written by Laurence William Cook and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aerospace System Analysis and Optimization in Uncertainty written by Loïc Brevault and published by Springer Nature. This book was released on 2020-08-26 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spotlighting the field of Multidisciplinary Design Optimization (MDO), this book illustrates and implements state-of-the-art methodologies within the complex process of aerospace system design under uncertainties. The book provides approaches to integrating a multitude of components and constraints with the ultimate goal of reducing design cycles. Insights on a vast assortment of problems are provided, including discipline modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range of topics covered include areas of current open research. This Work is destined to become a fundamental reference for aerospace systems engineers, researchers, as well as for practitioners and engineers working in areas of optimization and uncertainty. Part I is largely comprised of fundamentals. Part II presents methodologies for single discipline problems with a review of existing uncertainty propagation, reliability analysis, and optimization techniques. Part III is dedicated to the uncertainty-based MDO and related issues. Part IV deals with three MDO related issues: the multifidelity, the multi-objective optimization and the mixed continuous/discrete optimization and Part V is devoted to test cases for aerospace vehicle design.

Download or read book Efficient Uncertainty Quantification in Aerospace Analysis and Design written by Yi Zhang and published by . This book was released on 2013 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The main purpose of this study is to apply a computationally efficient uncertainty quantification approach, Non-Intrusive Polynomial Chaos (NIPC) based stochastic expansions, to robust aerospace analysis and design under mixed (aleatory and epistemic) uncertainties and demonstrate this technique on model problems and robust aerodynamic optimization. The proposed optimization approach utilizes stochastic response surfaces obtained with NIPC methods to approximate the objective function and the constraints in the optimization formulation. The objective function includes the stochastic measures which are minimized simultaneously to ensure the robustness of the final design to both aleatory and epistemic uncertainties. For model problems with mixed uncertainties, Quadrature-Based and Point-Collocation NIPC methods were used to create the response surfaces used in the optimization process. For the robust airfoil optimization under aleatory (Mach number) and epistemic (turbulence model) uncertainties, a combined Point-Collocation NIPC approach was utilized to create the response surfaces used as the surrogates in the optimization process. Two stochastic optimization formulations were studied: optimization under pure aleatory uncertainty and optimization under mixed uncertainty. As shown in this work for various problems, the NIPC method is computationally more efficient than Monte Carlo methods for moderate number of uncertain variables and can give highly accurate estimation of various metrics used in robust design optimization under mixed uncertainties. This study also introduces a new adaptive sampling approach to refine the Point-Collocation NIPC method for further improvement of the computational efficiency. Two numerical problems demonstrated that the adaptive approach can produce the same accuracy level of the response surface obtained with oversampling ratio of 2 using less function evaluations."--Abstract, page iii.

Download or read book Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications written by Massimiliano Vasile and published by Springer Nature. This book was released on 2022-01-27 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2020 International Conference on Uncertainty Quantification & Optimization gathered together internationally renowned researchers in the fields of optimization and uncertainty quantification. The resulting proceedings cover all related aspects of computational uncertainty management and optimization, with particular emphasis on aerospace engineering problems. The book contributions are organized under four major themes: Applications of Uncertainty in Aerospace & Engineering Imprecise Probability, Theory and Applications Robust and Reliability-Based Design Optimisation in Aerospace Engineering Uncertainty Quantification, Identification and Calibration in Aerospace Models This proceedings volume is useful across disciplines, as it brings the expertise of theoretical and application researchers together in a unified framework.

Download or read book Optimization Under Uncertainty with Applications to Aerospace Engineering written by Massimiliano Vasile and published by Springer Nature. This book was released on 2021-02-15 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.

Download or read book Uncertainty Management for Robust Industrial Design in Aeronautics written by Charles Hirsch and published by Springer. This book was released on 2018-07-21 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers cutting-edge findings related to uncertainty quantification and optimization under uncertainties (i.e. robust and reliable optimization), with a special emphasis on aeronautics and turbomachinery, although not limited to these fields. It describes new methods for uncertainty quantification, such as non-intrusive polynomial chaos, collocation methods, perturbation methods, as well as adjoint based and multi-level Monte Carlo methods. It includes methods for characterization of most influential uncertainties, as well as formulations for robust and reliable design optimization. A distinctive element of the book is the unique collection of test cases with prescribed uncertainties, which are representative of the current engineering practice of the industrial consortium partners involved in UMRIDA, a level 1 collaborative project within the European Commission's Seventh Framework Programme (FP7). All developed methods are benchmarked against these industrial challenges. Moreover, the book includes a section dedicated to Best Practice Guidelines for uncertainty quantification and robust design optimization, summarizing the findings obtained by the consortium members within the UMRIDA project. All in all, the book offers a authoritative guide to cutting-edge methodologies for uncertainty management in engineering design, covers a wide range of applications and discusses new ideas for future research and interdisciplinary collaborations.

Download or read book A Recourse based Solution Approach to the Design of Fuel Cell Aeropropulsion Systems written by Taeyun Paul Choi and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few decades have witnessed a growing interest in the engineering communities to approach the handling of imperfect information from a quantitatively justifiable angle. In the aerospace engineering domain, the movement to develop creative avenues to nondeterministically solving engineering problems has emerged in the field of aerospace systems design. Inspired by statistical data modeling and numerical analysis techniques that used to be relatively foreign to the designers of aerospace systems, a variety of strategies leveraging upon the probabilistic treatment of uncertainty has been, and continue to be, reported. Although each method differs in the sequence in which probabilistic analysis and numerical optimization are performed, a common motif in all of them is the lack of any built-in provisions to compensate for infeasibilities that occur during optimization. Constraint violations are either strictly prohibited or striven to be held to an acceptable probability threshold, implying that most hitherto developed probabilistic design methods promote an avoid-failure approach to developing aerospace systems under uncertainty. It is the premise of this dissertation that such a dichotomous structure of addressing imperfections is hardly a realistic model of how product development unfolds in practice. From a time-phased view of engineering design, it is often observed that previously unknown parameters become known with the passing of each design milestone, and their effects on the system are realized. Should these impacts happen to be detrimental to critical system-level metrics, then a compensatory action is taken to remedy any unwanted deviations from the target or required bounds, rather than starting the process completely anew. Anecdotal accounts of numerous real-world design projects confirm that such remedial actions are commonly practiced means to ensure the successful fielding of aerospace systems. Therefore, formalizing the remedial aspect of engineering design into a new methodological capability would be the next logical step towards making uncertainty handling more pragmatic for this generation of engineers. In order to formulate a nondeterministic solution approach that capitalizes on the practice of compensatory design, this research introduces the notion of recourse. Within the context of engineering an aerospace system, recourse is defined as a set of corrective actions that can be implemented in stages later than the current design phase to keep critical system-level figures of merit within the desired target ranges, albeit at some penalty. The terminology is inspired by the concept of the same name in the field of statistical decision analysis, where it refers to an action taken by a decision maker to mitigate the unfavorable consequences caused by uncertainty realizations. Recourse programs also introduce the concept of stages to optimization formulations, and allow each stage to encompass as many sequences or events as determined necessary to solve the problem at hand. Together, these two major premises of classical stochastic programming provide a natural way to embody not only the remedial, but also the temporal and nondeterministic aspects of aerospace systems design. A two-part strategy, which partitions the design activities into stages, is proposed to model the bi-phasal nature of recourse. The first stage is defined as the time period in which an a priori design is identified before the exact values of the uncertain parameters are known. In contrast, the second stage is a period occurring some time after the first stage, when an a posteriori correction can be made to the first-stage design, should the realization of uncertainties impart infeasibilities. Penalizing costs are attached to the second-stage corrections to reflect the reality that getting it done right the first time is almost always less costly than fixing it after the fact. Consequently, the goal of the second stage becomes identifying an optimal solution with respect to the second-stage penalty, given the first-stage design, as well as a particular realization of the random parameters. This two-stage model is intended as an analogue of the traditional practice of monitoring and managing key Technical Performance Measures (TPMs) in aerospace systems development settings. Whenever an alarmingly significant discrepancy between the demonstrated and target TPM values is noted, it is generally the case that the most cost-effective recourse option is selected, given the available resources at the time, as well as scheduling and budget constraints. One obvious weakness of the two-stage strategy as presented above is its limited applicability as a forecasting tool. Not only cannot the second stage be invoked without a first-stage starting point, but also the second-stage solution differs from one specific outcome of uncertainties to another. On the contrary, what would be more valuable given the time-phased nature of engineering design is the capability to perform an anticipatory identification of an optimum that is also expected to incur the least costly recourse option in the future. It is argued that such a solution is in fact a more balanced alternative than robust, probabilistically maximized, or chance-constrained solutions, because it represents trading the design optimality in the present with the potential costs of future recourse. Therefore, it is further proposed that the original two-stage model be embedded inside a larger design loop, so that the realization of numerous recourse scenarios can be simulated for a given first-stage design. The repetitive procedure at the second stage is necessary for computing the expected cost of recourse, which is equivalent to its mathematical expectation as per the strong law of large numbers. The feedback loop then communicates this information to the aggregate-level optimizer, whose objective is to minimize the sum total of the first-stage metric and the expected cost of future corrective actions. The resulting stochastic solution is a design that is well-hedged against the uncertain consequences of later design phases, while at the same time being less conservative than a solution designed to more traditional deterministic standards. As a proof-of-concept demonstration, the recourse-based solution approach is presented as applied to a contemporary aerospace engineering problem of interest - the integration of fuel cell technology into uninhabited aerial systems. The creation of a simulation environment capable of designing three system alternatives based on Proton Exchange Membrane Fuel Cell (PEMFC) technology and another three systems leveraging upon Solid Oxide Fuel Cell (SOFC) technology is presented as the means to notionally emulate the development process of this revolutionary aeropropulsion method. Notable findings from the deterministic trade studies and algorithmic investigation include the incompatibility of the SOFC based architectures with the conceived maritime border patrol mission, as well as the thermodynamic scalability of the PEMFC based alternatives. It is the latter finding which justifies the usage of the more practical specific-parameter based approach in synthesizing the design results at the propulsion level into the overall aircraft sizing framework. The ensuing presentation on the stochastic portion of the implementation outlines how the selective applications of certain Design of Experiments, constrained optimization, Surrogate Modeling, and Monte Carlo sampling techniques enable the visualization of the objective function space. The particular formulations of the design stages, recourse, and uncertainties proposed in this research are shown to result in solutions that are well compromised between unfounded optimism and unwarranted conservatism. In all stochastic optimization cases, the Value of Stochastic Solution (VSS) proves to be an intuitively appealing measure of accounting for recourse-causing uncertainties in an aerospace systems design environment.

Download or read book Computational Approaches for Aerospace Design written by Andy Keane and published by John Wiley & Sons. This book was released on 2005-08-05 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last fifty years, the ability to carry out analysis as a precursor to decision making in engineering design has increased dramatically. In particular, the advent of modern computing systems and the development of advanced numerical methods have made computational modelling a vital tool for producing optimized designs. This text explores how computer-aided analysis has revolutionized aerospace engineering, providing a comprehensive coverage of the latest technologies underpinning advanced computational design. Worked case studies and over 500 references to the primary research literature allow the reader to gain a full understanding of the technology, giving a valuable insight into the world’s most complex engineering systems. Key Features: Includes background information on the history of aerospace design and established optimization, geometrical and mathematical modelling techniques, setting recent engineering developments in a relevant context. Examines the latest methods such as evolutionary and response surface based optimization, adjoint and numerically differentiated sensitivity codes, uncertainty analysis, and concurrent systems integration schemes using grid-based computing. Methods are illustrated with real-world applications of structural statics, dynamics and fluid mechanics to satellite, aircraft and aero-engine design problems. Senior undergraduate and postgraduate engineering students taking courses in aerospace, vehicle and engine design will find this a valuable resource. It will also be useful for practising engineers and researchers working on computational approaches to design.

Download or read book Needs and Opportunities for Uncertainty Based Multidisciplinary Design Methods for Aerospace Vehicles written by and published by . This book was released on 2002 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aircraft Aerodynamic Design written by András Sóbester and published by John Wiley & Sons. This book was released on 2014-09-23 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal aircraft design is impossible without a parametric representation of the geometry of the airframe. We need a mathematical model equipped with a set of controls, or design variables, which generates different candidate airframe shapes in response to changes in the values of these variables. This model's objectives are to be flexible and concise, and capable of yielding a wide range of shapes with a minimum number of design variables. Moreover, the process of converting these variables into aircraft geometries must be robust. Alas, flexibility, conciseness and robustness can seldom be achieved simultaneously. Aircraft Aerodynamic Design: Geometry and Optimization addresses this problem by navigating the subtle trade-offs between the competing objectives of geometry parameterization. It beginswith the fundamentals of geometry-centred aircraft design, followed by a review of the building blocks of computational geometries, the curve and surface formulations at the heart of aircraft geometry. The authors then cover a range of legacy formulations in the build-up towards a discussion of the most flexible shape models used in aerodynamic design (with a focus on lift generating surfaces). The book takes a practical approach and includes MATLAB®, Python and Rhinoceros® code, as well as ‘real-life’ example case studies. Key features: Covers effective geometry parameterization within the context of design optimization Demonstrates how geometry parameterization is an important element of modern aircraft design Includes code and case studies which enable the reader to apply each theoretical concept either as an aid to understanding or as a building block of their own geometry model Accompanied by a website hosting codes Aircraft Aerodynamic Design: Geometry and Optimization is a practical guide for researchers and practitioners in the aerospace industry, and a reference for graduate and undergraduate students in aircraft design and multidisciplinary design optimization.

Download or read book Global and Robust Optimization for Engineering Design written by Berk Öztürk and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a need to adapt and improve conceptual design methods through better optimization, in order to address the challenge of designing future engineered systems. Aerospace design problems are tightly-coupled optimization problems, and require all-at-once solution methods for design consensus and global optimality. Although the literature on design optimization has been growing, it has generally focused on the use of gradient-based and heuristic methods, which are limited to local and low-dimensional optimization respectively. There are significant benefits to leveraging structured mathematical optimization instead. Mathematical optimization provides guarantees of solution quality, and is fast, scalable, and compatible with using physics-based models in design. More importantly perhaps, there has been a wave of research in optimization and machine learning that provides new opportunities to improve the engineering design process. This thesis capitalizes on two such opportunities. The first opportunity is to enable efficient all-at-once optimization over constraints and objectives that use arbitrary mathematical primitives. This work proposes a constraint sampling and learning approach for global optimization, leveraging developments in machine learning and mixed-integer optimization. More specifically, the feasible space of intractable constraints is sampled using existing and novel design of experiments methods, and learned using optimal classification trees with hyperplanes (OCT-Hs). OCT-Hs describe union-of-polyhedra approximations of intractable constraints, which are solved efficiently using commercial solvers to find near-feasible and near-optimal solutions to the global optimization problem. The constraints are then checked and the solution is repaired using projected gradient methods, ensuring feasibility and local optimality. The method is first tested on synthetic examples, where it finds the global optima for 9 out of 11 benchmarks, and high-performing solutions otherwise. Then it is applied to two real-world problems from the aerospace literature, and especially to a satellite on-orbit servicing problem that cannot be addressed via other global optimization methods. These applications demonstrate that decision tree driven optimization provides efficient, practical and optimal solutions to difficult global optimization problems present in aerospace design as well as other domains, regardless of the form of the underlying constraints. The second opportunity is to optimize designs affected by parametric uncertainty in a tractable and deterministic manner, while providing guarantees of constraint satisfaction. Inspired by the wealth of literature on robust optimization, and specifically on robust geometric programming, this thesis proposes and implements robust signomial programming to solve engineering design problems under uncertainty. The methods are tested on a conceptual aircraft design problem, demonstrating that robust signomial programs are sufficiently general to address engineering design problems, solved efficiently by commercial solvers, and result in designs that protect deterministically against uncertain parameter outcomes from predefined sets. In addition, robust designs are found to be less conservative than designs with margins; robust aircraft demonstrate 9% better average performance than aircraft designed with margins over the same scenarios, while providing guarantees of constraint feasibility. In anticipation of future aerospace design problems becoming increasingly coupled, complex and risky, this thesis provides a new perspective for dealing with design challenges using structured mathematical optimization. The proposed methods inject mathematical rigor into engineering design methods while keeping practical concerns for conceptual design in focus.

Download or read book Investigation of Robust Optimization and Evidence Theory with Stochastic Expansions for Aerospace Applications Under Mixed Uncertainty written by Harsheel R. Shah and published by . This book was released on 2015 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: "One of the primary objectives of this research is to develop a method to model and propagate mixed (aleatory and epistemic) uncertainty in aerospace simulations using DSTE. In order to avoid excessive computational cost associated with large scale applications and the evaluation of Dempster Shafer structures, stochastic expansions are implemented for efficient UQ. The mixed UQ with DSTE approach was demonstrated on an analytical example and high fidelity computational fluid dynamics (CFD) study of transonic flow over a RAE 2822 airfoil. Another objective is to devise a DSTE based performance assessment framework through the use of quantification of margins and uncertainties. Efficient uncertainty propagation in system design performance metrics and performance boundaries is achieved through the use of stochastic expansions. The technique is demonstrated on: (1) a model problem with non-linear analytical functions representing the outputs and performance boundaries of two coupled systems and (2) a multi-disciplinary analysis of a supersonic civil transport. Finally, the stochastic expansions are applied to aerodynamic shape optimization under uncertainty. A robust optimization algorithm is presented for computationally efficient airfoil design under mixed uncertainty using a multi-fidelity approach. This algorithm exploits stochastic expansions to create surrogate models utilized in the optimization process. To reduce the computational cost, output space mapping technique is implemented to replace the high-fidelity CFD model by a suitably corrected low-fidelity one. The proposed algorithm is demonstrated on the robust optimization of NACA 4-digit airfoils under mixed uncertainties in transonic flow"--Abstract, page iv.

Download or read book Engineering Design Optimization written by Joaquim R. R. A. Martins and published by Cambridge University Press. This book was released on 2021-11-18 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.

Download or read book New Approaches to Optimization in Aerospace Conceptual Design written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-07-18 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks. Gage, Peter J. Unspecified Center AEROSPACE ENGINEERING; DESIGN ANALYSIS; GENETIC ALGORITHMS; MATHEMATICAL PROGRAMMING; AERODYNAMIC CONFIGURATIONS; ALGORITHMS; CALCULUS; CONVERGENCE; DRAG REDUCTION; SPACECRAFT TRAJECTORIES; STRUCTURAL DESIGN; TRAJECTORY OPTIMIZATION; WEIGHT REDUCTION...

Download or read book Optimization Techniques written by George Leitmann and published by Academic Press. This book was released on 1962-01-01 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decade there has been a remarkable growth of interest in problems of systems optimization and of optimal control. And with this interest has come an increasing need for methods useful for rendering systems optimum. Rising to meet this challengc there have sprung up various “schools, often championing onc method and regarding it superior to all others. Long experience has shown that life is not so simple, that the picture is not all white and black. In short, one may expect that a particular method is superior to others for the solution of some problems-rarely for all problems. Furthermore, since the basic mathematical formulation of optimization problems is often essentially the same in many approaches, it is not unreasonable to expect that there may be a great deal of similarity among various methods, a similarity - often, indeed, an identity-which is obscured by dissimilarities in language and notation. To help the uncommitted in his search for and rhoice of the optimum optimization technique is the fundamental aim of this volume. To accomplish this aim there are assembled in one book ten chapters dealing &h the various methods currently espoused for the solution of problems in systems optimization and optimal control. The choice of authors has been dictated solely by a consideration of an author’s interest and expertiless in a particular method. With the advantages of such an eclectic approach and the ensuing multiple authorship there comes some loss of smoothness of over - all presentation, for which the Editor must take the sole blame. On the one hand, correlation between the various chapters has been achieved by cross-referencing; on the other hand, each chapter can be read as a separate entity setting forth the technique championed by a particular “School. While each of the ten chapters dealing with methods includes simple examples, primarily for didactic purposes, it has been thought useful to present four additional chapters dealing with applications alone. Of these, the first three, Chapters 11-13, cover specific optimization problems, and the final chapter contains a discussion of problems in the optimization of a complete system, in this case a nuclear propulsion system.

Download or read book High Performance and Optimum Design of Structures and Materials III written by W. P. De Wilde and published by WIT Press. This book was released on 2018-12-03 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Papers presented at the 2018 International Conference on High Performance and Optimum Design of Structures and Materials are contained in this volume. These papers address issues involving advanced types of structures, particularly those based on new concepts or new materials and their system design. The use of novel materials and new structural concepts nowadays is not restricted to highly technical areas like aerospace, aeronautical applications or the automotive industry, but affects all engineering fields including those such as civil engineering and architecture. Most high performance structures require the development of a generation of new materials, which can more easily resist a range of external stimuli or react in a non-conventional manner. Particular emphasis is placed on intelligent structures and materials as well as the application of computational methods for their modelling, control and management. Optimisation problems discussed in this book involve those related to size, shape and topology of structures and materials. Optimisation techniques have much to offer to those involved in the design of new industrial products. The development of new algorithms and the appearance of powerful commercial computer codes with easy to use graphical interfaces has created a fertile field for the incorporation of optimisation in the design process in all engineering disciplines. The latest developments in design, optimisation, manufacturing and experimentation are highlighted in this book.

Download or read book Optimization of Structural and Mechanical Systems written by Jasbir S. Arora and published by World Scientific. This book was released on 2007 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a discussion of the general impact of WTO membership on both sides of the Taiwan Strait, and addresses the political and economic impact on cross-Strait relations of common membership. The book begins with an introduction which analyzes the state of cross-Strait economic and political relations on the eve of dual accession to the WTO and briefly introduces the chapters which follow. The first chapter discusses the concessions made by both sides in their accession agreements and is followed by two chapters which describe the manner in which the Taiwan economy was reformed to achieve compliance as well as the specific, restrictive trade regime that was put into place to manage mainland trade. The next two chapters deal with the implications of that restrictive trade regime for the Taiwan economy in Asia and with the nature of the interactions between the two sides within the WTO. The final four chapters of the volume examine the impact of membership on four sectors of the economy: finance; agriculture; electronics and automobiles. There is a post-script which briefly covers developments since the chapters were completed.