Determination of Anisotropic Yield Coefficients by a Data-Driven Multiobjective Evolutionary and Genetic Algorithm
TL;DR: In this article, a robust multiobjective optimization based on evolutionary algorithm is proposed to minimize the error in yield stress and plastic strain ratio simultaneously and thereby overcomes the limitations in the approaches used before.
Abstract: The texture induced anisotropy of yield strength in cold rolled sheet metals is modeled using anisotropic yield criteria. The classical and other optimization methods used so far to determine the yield coefficients are limited by fixed set of experimental data, initial guess values, and pre-determined weight factors. A robust multiobjective optimization based on evolutionary algorithm proposed in this paper minimizes the error in yield stress and plastic strain ratio simultaneously and thereby overcomes the limitations in the approaches used before. The new approach is tested using Hill48 and Barlat89 yield criteria for five different materials from literature. The new approach is observed to improve the prediction capability of yield coefficients when compared to earlier approaches. The Pareto frontier obtained in the new approach can serve as a comparative tool to evaluate the accuracy of different yield criteria.
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TL;DR: In this article, the authors distinguish fracture porosity and matrix porosity in coalbed methane reservoirs through a novel approach which is the joint usage of NMR transverse relaxation (T2) measurements and rock physics modeling based on Levenberg-Marquardt (LM) algorithm.
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TL;DR: In this paper, the authors considered a common metallurgical problem associated with the phase transformation of steel during heating where austenite grain tends to grow in size with time and results in poor mechanical properties in the final stages.
Abstract: This study considers a common metallurgical problem associated with the phase transformation of steel during heating where austenite grain tends to grow in size with time and results in poor mechanical properties in the final stages. This investigation was performed using a Cellular Automata model for dual-phase steel developed in house. Data-driven metamodels for a biobjective optimization problem involving minimizing average austenite grain size along with the maximizing of time of heating were constructed using Evolutionary Neural Network (EvoNN) and Biobjective Genetic Programming (BioGP). The input variables selected for this task were (i) heating rate, (ii) pearlite percentage, (iii) nucleation density of austenite, and (iv) the finish temperature of austenite formation. The analyses of the results led to the fact that heating rate is the most influencing factor and it needs to be large during transformation to obtain a refined microstructure. The comparison of Pareto front between EvoNN and BioGP r...
27 citations
TL;DR: In this article, a genetic algorithm combined with principal components analysis (PCA) coupled Grey Relational Analysis (GRA) is employed to improve the straight turning process of MMCs.
Abstract: The metal matrix composites (MMCs) have gained acceptance in an extensive range of applications owing to their high strength to mass ratio. Machining of such complex MMCs is often challenging. It is essential to optimize the controllable machining parameters to simultaneously attain manifold objectives. In the current work, response surface design is created for experiments, and Genetic algorithm (GA) combined with Principal Components Analysis (PCA) coupled Grey Relational Analysis (GRA) is employed to improve the straight turning process of MMCs. The procedure is demonstrated by machining aluminum-based MMC with 25% SiC particulates. The procedure aims at identifying optimal combination of machining parameters to obtain high surface quality at lower cutting force without increasing the specific power consumption. PCA is helpful in providing the individual uncorrelated quality characteristics called as quality indices that do not have any influence on other responses. Individual quality indices h...
22 citations
Cites methods from "Determination of Anisotropic Yield ..."
...Design and optimization of semi-conductors [38,39], optimization of laser cladding process [40], optimization of machining parameters and tooling geometry for Ti alloys [41], optimization of turning process in nickel alloy based on residual stress distribution [42], design and development of new alloys [43] and identification of material constants in anisotropic yield criteria [44], and optimization of the solid state fermentation process are some of the applications where conflicting multiple objectives were optimized using evolutionary multiobjective optimization (MOO) algorithms [45]....
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TL;DR: In this paper, an architectured multifunctional battery-structure material system, namely the Cellular Battery Assembly (CBA), is introduced, which is composed of cylindrical battery cells surrounded by hollow tubes.
19 citations
TL;DR: In this article, a steel plant flow sheet containing a top gas recycling blast furnace is simulated and subjected to multi-objective optimization through an evolutionary approach, which allows optimizing a large number of objectives in an evolutionary way, which is difficult to do by other methods.
Abstract: A steel plant flow sheet containing a top gas recycling blast furnace is simulated and subjected to multi-objective optimization through an evolutionary approach. A recently proposed k-optimality criterion is used, which allows optimizing a large number of objectives in an evolutionary way, which is difficult to do by other methods. A number of promising optimum results, showing the optimum tradeoffs between several cost factors are identified and analyzed. The results appear to be very significant in the context of CO2 reduction challenges faced by the steel industries today.
14 citations
References
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Book•
01 Jan 2001
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Abstract: From the Publisher:
Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. · Comprehensive coverage of this growing area of research · Carefully introduces each algorithm with examples and in-depth discussion · Includes many applications to real-world problems, including engineering design and scheduling · Includes discussion of advanced topics and future research · Features exercises and solutions, enabling use as a course text or for self-study · Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
12,134 citations
Book•
30 Jun 2002
TL;DR: This paper presents a meta-anatomy of the multi-Criteria Decision Making process, which aims to provide a scaffolding for the future development of multi-criteria decision-making systems.
Abstract: List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.
5,994 citations
Book•
26 Sep 2011
TL;DR: This paper is concerned with the development of methods for dealing with the role of symbols in the interpretation of semantics.
Abstract: Preface. Acknowledgements. Notation and Symbols. Part I: Terminology and Theory. 1. Introduction. 2. Concepts. 3. Theoretical Background. Part II: Methods. 1. Introduction. 2. No-Preference Methods. 3. A Posteriori Methods. 4. A Priori Methods. 5. Interactive Methods. Part III: Related Issues. 1. Comparing Methods. 2. Software. 3. Graphical Illustration. 4. Future Directions. 5. Epilogue. References. Index.
4,976 citations
"Determination of Anisotropic Yield ..." refers methods in this paper
...The objective functions used in the study, namely error in yield stress and plastic strain ratio, are conflicting with each other and optimizing both of them simultaneously will lead to a typical Pareto-optimality condition [26, 27]....
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TL;DR: In this article, a theory is suggested which describes the yielding and plastic flow of an anisotropic metal on a macroscopic scale and associated relations are then found between the stress and strain-increment tensors.
Abstract: A theory is suggested which describes, on a macroscopic scale, the yielding and plastic flow of an anisotropic metal. The type of anisotropy considered is that resulting from preferred orientation. A yield criterion is postulated on general grounds which is similar in form to the Huber-Mises criterion for isotropic metals, but which contains six parameters specifying the state of anisotropy. By using von Mises' concept (1928) of a plastic potential, associated relations are then found between the stress and strain-increment tensors. The theory is applied to experiments of Korber & Hoff (1928) on the necking under uniaxial tension of thin strips cut from rolled sheet. It is shown, in full agreement with experimental data, that there are generally two, equally possible, necking directions whose orientation depends on the angle between the strip axis and the rolling direction. As a second example, pure torsion of a thin-walled cylinder is analyzed. With increasing twist anisotropy is developed. In accordance with recent observations by Swift (1947), the theory predicts changes in length of the cylinder. The theory is also applied to determine the earing positions in cups deep-drawn from rolled sheet.
3,426 citations
"Determination of Anisotropic Yield ..." refers background or methods or result in this paper
...Hill48 is proved to be satisfactory for a wide range of materials, especially steels [32–35]....
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...The Pareto front estimated using both Hill48 and Barlat89 are compared for all the materials in Fig....
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...The anisotropic yield coefficients for Hill48 and Barlat89 yield criteria can be determined either based on stress (r0, r45, r90, rb) or ‘‘r’’ values (r0, r0, r45, r90)....
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...Of historical importance is the Hill’s quadratic yield function [3] (referred henceforth as Hill48), which is essentially a modification of the von Mises isotropic yield criterion [4]....
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...Similarly, Hill48 is better than Barlat89 for AA5182-O....
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TL;DR: In this article, a plane stress yield function that well describes the anisotropic behavior of sheet metals, in particular, aluminum alloy sheets, was proposed, which was introduced in the formulation using two linear transformations on the Cauchy stress tensor.
1,374 citations
"Determination of Anisotropic Yield ..." refers methods in this paper
...Depending upon the complexity of the yield function, numerical iterations like Newton–Raphson method [9, 10] and optimization techniques are commonly used to identify the anisotropic coefficients [14, 15]....
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...Features Numerical iterations and optimization [9, 10, 14, 15] Single objective genetic algorithm [19, 20] Multiobjective optimization of hill criterion [21] Present methodology...
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...method [9, 10] are employed for this purpose....
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...This is expedient particularly during employing the methodology for advanced yield criteria [9, 10, 14, 38] where calculation of objective functions for each individual over several generations is computationally expensive....
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