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Data-Driven Evolutionary Modeling in Materials Technology

2022-09-15 Technology & Engineering
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Release : 2022-09-15
Genre : Technology & Engineering
Kind : eBook
Book Rating : 864/5 ( reviews)

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Book Synopsis Data-Driven Evolutionary Modeling in Materials Technology by : Nirupam Chakraborti

Download or read book Data-Driven Evolutionary Modeling in Materials Technology written by Nirupam Chakraborti. This book was released on 2022-09-15. Available in PDF, EPUB and Kindle. Book excerpt: Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are used in learning and modeling especially with the advent of big data related problems. This book presents the algorithms and strategies specifically associated with pertinent issues in materials science domain. It discusses the procedures for evolutionary multi-objective optimization of objective functions created through these procedures and introduces available codes. Recent applications ranging from primary metal production to materials design are covered. It also describes hybrid modeling strategy, and other common modeling and simulation strategies like molecular dynamics, cellular automata etc. Features: Focuses on data-driven evolutionary modeling and optimization, including evolutionary deep learning. Include details on both algorithms and their applications in materials science and technology. Discusses hybrid data-driven modeling that couples evolutionary algorithms with generic computing strategies. Thoroughly discusses applications of pertinent strategies in metallurgy and materials. Provides overview of the major single and multi-objective evolutionary algorithms. This book aims at Researchers, Professionals, and Graduate students in Materials Science, Data-Driven Engineering, Metallurgical Engineering, Computational Materials Science, Structural Materials, and Functional Materials.

Materials Science and Engineering

2013-07-10 Technology & Engineering
Download Materials Science and Engineering PDF Online Free

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Release : 2013-07-10
Genre : Technology & Engineering
Kind : eBook
Book Rating : 354/5 ( reviews)

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Book Synopsis Materials Science and Engineering by : Nirupam Chakraborti

Download or read book Materials Science and Engineering written by Nirupam Chakraborti. This book was released on 2013-07-10. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) and genetic programming (GP) have already emerged as two very effective computing strategies for constructing data-driven models for systems of scientific and engineering interest. However, coming up with accurate models or meta-models from noisy real-life data is often a formidable task due to their frequent association with high degrees of random noise, which might render an ANN or GP model either over- or underfitted. This problem has recently been tackled in two emerging algorithms, Evolutionary Neural Net (EvoNN) and Bi-objective Genetic Programming (BioGP), which utilize the concept of Pareto tradeoff and apply a bi-objective genetic algorithm (GA) in the basic framework of both ANNs and GP. These concepts are elaborated in detail in this chapter.

Data-Driven Evolutionary Modeling in Materials Technology

2022-09-15 Technology & Engineering
Download Data-Driven Evolutionary Modeling in Materials Technology PDF Online Free

Author :
Release : 2022-09-15
Genre : Technology & Engineering
Kind : eBook
Book Rating : 821/5 ( reviews)

GET EBOOK


Book Synopsis Data-Driven Evolutionary Modeling in Materials Technology by : Nirupam Chakraborti

Download or read book Data-Driven Evolutionary Modeling in Materials Technology written by Nirupam Chakraborti. This book was released on 2022-09-15. Available in PDF, EPUB and Kindle. Book excerpt: Due to efficacy and optimization potential of genetic and evolutionary algorithms, they are used in learning and modeling especially with the advent of big data related problems. This book presents the algorithms and strategies specifically associated with pertinent issues in materials science domain. It discusses the procedures for evolutionary multi-objective optimization of objective functions created through these procedures and introduces available codes. Recent applications ranging from primary metal production to materials design are covered. It also describes hybrid modeling strategy, and other common modeling and simulation strategies like molecular dynamics, cellular automata etc. Features: Focuses on data-driven evolutionary modeling and optimization, including evolutionary deep learning. Include details on both algorithms and their applications in materials science and technology. Discusses hybrid data-driven modeling that couples evolutionary algorithms with generic computing strategies. Thoroughly discusses applications of pertinent strategies in metallurgy and materials. Provides overview of the major single and multi-objective evolutionary algorithms. This book aims at Researchers, Professionals, and Graduate students in Materials Science, Data-Driven Engineering, Metallurgical Engineering, Computational Materials Science, Structural Materials, and Functional Materials.

Springback Assessment and Compensation of Tailor Welded Blanks

2022-12-27 Science
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Release : 2022-12-27
Genre : Science
Kind : eBook
Book Rating : 943/5 ( reviews)

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Book Synopsis Springback Assessment and Compensation of Tailor Welded Blanks by : Ab Abdullah

Download or read book Springback Assessment and Compensation of Tailor Welded Blanks written by Ab Abdullah. This book was released on 2022-12-27. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on techniques developed to evaluate the forming behaviour of tailor welded blanks (TWBs) in sheet metal manufacturing, this edited collection details compensation methods suited to mitigating the effects of springback. Making use of case studies and in-depth accounts of industry experience, this book gives a comprehensive overview of springback and provides essential solutions necessary to modern-day automotive engineers. Sheet metal forming is a major process within the automotive industry, with advancement of the technology including utilization of non-uniform sheet metal in order to produce light or strengthened body structures. This is critical in the reduction of vehicle weight in order to match increased consumer demand for better driving performance and improved fuel efficiency. Additionally, increasingly stringent international regulations regarding exhaust emissions require manufacturers to seek to lighten vehicles as much as possible. To aid engineers in optimizing lightweight designs, this comprehensive book covers topics by a variety of industry experts, including compensation by annealing, low-power welding, punch profile radius and tool-integrated springback measuring systems. It ends by looking at the future trends within the industry and the potential for further innovation within the field. This work will benefit car manufacturers and stamping plants that face springback issues within their production, particularly in the implementation of TWB production into existing facilities. It will also be of interest to students and researchers in automotive and aerospace engineering.

Data-driven Modeling Implementation Within Materials Development and Manufacturing Systems

2023
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Release : 2023
Genre :
Kind : eBook
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Book Synopsis Data-driven Modeling Implementation Within Materials Development and Manufacturing Systems by : Allen Jonathan Roman

Download or read book Data-driven Modeling Implementation Within Materials Development and Manufacturing Systems written by Allen Jonathan Roman. This book was released on 2023. Available in PDF, EPUB and Kindle. Book excerpt: Predicting polymeric material behavior during processing and predicting final part properties continues to be a strong research focus within the scientific community as it involves taking into consideration a wide range of time-dependent variables. By use of data-driven modeling, the materials development process can be accelerated, and the highly predictive modeling techniques can facilitate the development of smart manufacturing systems. This dissertation worked on solving polymer engineering problems by use of data-driven modeling techniques. The first strategy was using data-driven modeling to provide a predictive model with statistical insights of the injection molding process to ensure part quality is maximized for a highly viscoelastic material blend. By injection molding highly viscoelastic materials, the probability of part defects is increased, therefore, it was crucial to use advanced computational techniques to understand the nuances of this highly non-linear process and to predict the outcome before creating material waste from faulty trials. The second strategy was in the use of data-driven modeling for reverse engineering purposes, specifically within materials development. By combining experimental characterization and data-driven modeling, algorithms were developed and compared to prove how highly predictive models can be used as reverse engineering toolboxes. This ultimately informed users of the optimal formulation which would reach the specified target material properties. The final strategy explored using data-driven modeling to validate the high influence of viscous heating within the pressure melt removal process, therefore, work was done in implementing a viscous heating system within a fused filament fabrication (FFF) 3D printer to accelerate the 3D printing process. The instrumented FFF 3D printer proved capable of accelerating print speeds and improving mechanical performance of 3D printed parts, working towards solving two of the largest bottlenecks within additive manufacturing: lead times and part quality. Given the unique capabilities of the data-driven modeling, the novel 3D printer was tested and evaluated via data-driven modeling to provide statistical information regarding which processing parameters were the most influential for improving overall performance of the 3D printing system. The results of this work provide a basis for future research endeavors related to combining data-driven modeling and polymer science, such as in optimizing the newly developed viscous heating 3D printer.

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