Multidisciplinary Design Optimization and Its Application in Deep Manned Submersible Design

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Release : 2020-08-28
Genre : Technology & Engineering
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Book Rating : 558/5 ( reviews)

Multidisciplinary Design Optimization and Its Application in Deep Manned Submersible Design - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multidisciplinary Design Optimization and Its Application in Deep Manned Submersible Design write by Binbin Pan. This book was released on 2020-08-28. Multidisciplinary Design Optimization and Its Application in Deep Manned Submersible Design available in PDF, EPUB and Kindle. This book investigates Reliability-based Multidisciplinary Design Optimization (RBMDO) theory and its application in the design of deep manned submersibles (DMSs). Multidisciplinary Design Optimization (MDO) is an effective design method for large engineering systems like aircraft, warships, and satellites, which require designers and engineers from various disciplines to cooperate with each other. MDO can be used to handle the conflicts that arise between these disciplines, and focuses on the optimal design of the system as a whole. However, it can also push designs to the brink of failure. In order to keep the system balanced, Reliability-based Design (RBD) must be incorporated into MDO. Consequently, new algorithms and methods have to be developed for RBMDO theory. This book provides an essential overview of MDO, RBD, and RBMDO and subsequently introduces key algorithms and methods by means of case analyses. In closing, it introduces readers to the design of DMSs and applies RBMDO methods to the design of the manned hull and the general concept design. The book is intended for all students and researchers who are interested in system design theory, and for engineers working on large, complex engineering systems.

Multidisciplinary Design Optimization

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Release : 1997-01-01
Genre : Design
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Book Rating : 596/5 ( reviews)

Multidisciplinary Design Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multidisciplinary Design Optimization write by Natalia M. Alexandrov. This book was released on 1997-01-01. Multidisciplinary Design Optimization available in PDF, EPUB and Kindle. Multidisciplinary design optimization (MDO) has recently emerged as a field of research and practice that brings together many previously disjointed disciplines and tools of engineering and mathematics. MDO can be described as a technology, environment, or methodology for the design of complex, coupled engineering systems, such as aircraft, automobiles, and other mechanisms, the behavior of which is determined by interacting subsystems.

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering

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Release : 2017-05-08
Genre : Technology & Engineering
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Book Rating : 099/5 ( reviews)

Multidisciplinary Design Optimization Supported by Knowledge Based Engineering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multidisciplinary Design Optimization Supported by Knowledge Based Engineering write by Jaroslaw Sobieszczanski-Sobieski. This book was released on 2017-05-08. Multidisciplinary Design Optimization Supported by Knowledge Based Engineering available in PDF, EPUB and Kindle. Multidisciplinary Design Optimization supported by Knowledge Based Engineering supports engineers confronting this daunting and new design paradigm. It describes methodology for conducting a system design in a systematic and rigorous manner that supports human creativity to optimize the design objective(s) subject to constraints and uncertainties. The material presented builds on decades of experience in Multidisciplinary Design Optimization (MDO) methods, progress in concurrent computing, and Knowledge Based Engineering (KBE) tools. Key features: Comprehensively covers MDO and is the only book to directly link this with KBE methods Provides a pathway through basic optimization methods to MDO methods Directly links design optimization methods to the massively concurrent computing technology Emphasizes real world engineering design practice in the application of optimization methods Multidisciplinary Design Optimization supported by Knowledge Based Engineering is a one-stop-shop guide to the state-of-the-art tools in the MDO and KBE disciplines for systems design engineers and managers. Graduate or post-graduate students can use it to support their design courses, and researchers or developers of computer-aided design methods will find it useful as a wide-ranging reference.

Multidisciplinary Design Optimization: An Emerging New Engineering Discipline

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Release : 1993
Genre :
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Book Rating : /5 ( reviews)

Multidisciplinary Design Optimization: An Emerging New Engineering Discipline - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multidisciplinary Design Optimization: An Emerging New Engineering Discipline write by . This book was released on 1993. Multidisciplinary Design Optimization: An Emerging New Engineering Discipline available in PDF, EPUB and Kindle.

Multidisciplinary Design Optimization of Complex Structures Under Uncertainty

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Release : 2024-09-02
Genre : Technology & Engineering
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Book Rating : 516/5 ( reviews)

Multidisciplinary Design Optimization of Complex Structures Under Uncertainty - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Multidisciplinary Design Optimization of Complex Structures Under Uncertainty write by Debiao Meng. This book was released on 2024-09-02. Multidisciplinary Design Optimization of Complex Structures Under Uncertainty available in PDF, EPUB and Kindle. In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potential of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance. The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field. Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization.