Probabilistic Optimisation Of Composite Structures: Machine Learning For Design Optimisation

— —

Kwangkyu Alex Yoo (Imperial College London, Uk & Deep Meta, Uk) Omar Bacarreza Nogales (Imperial College London, Uk & Orca Computing, Uk)

Probabilistic Optimisation Of Composite Structures

Machine Learning For Design Optimisation

Kwangkyu Alex Yoo (Imperial College London, Uk & Deep Meta, Uk), Omar Bacarreza Nogales (Imperial College London, Uk & Orca Computing, Uk), M H Ferri Aliabadi (Imperial College London, Uk)

$203.95 $163.52

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

World Scientific Europe Ltd
17 April 2025

Plastics & polymers technology; Mechanical engineering

Series: Computational and Experimental Methods in Structures

Summary
Details

This book introduces an innovative approach to multi-fidelity probabilistic optimisation for aircraft composite structures, addressing the challenge of balancing reliability with computational cost. Probabilistic optimisation pursues statistically reliable and robust solutions by accounting for uncertainties in data, such as material properties and geometry tolerances. Traditional approaches using high-fidelity models, though accurate, are computationally expensive and time-consuming, especially when using complex methods such as Monte Carlo simulations and gradient calculations.

For the first time, the proposed multi-fidelity method combines high- and low-fidelity models, enabling high-fidelity models to focus on specific areas of the design space, while low-fidelity models explore the entire space. Machine learning technologies, such as artificial neural networks and nonlinear autoregressive Gaussian processes, fill information gaps between different fidelity models, enhancing model accuracy. The multi-fidelity probabilistic optimisation framework is demonstrated through the reliability-based and robust design problems of aircraft composite structures under a thermo-mechanical environment, showing acceptable accuracy and reductions in computational time.

By: Kwangkyu Alex Yoo (Imperial College London Uk & Deep Meta Uk), Omar Bacarreza Nogales (Imperial College London, Uk & Orca Computing, Uk), M H Ferri Aliabadi (Imperial College London, Uk)
Imprint: World Scientific Europe Ltd
Country of Publication: United Kingdom
Volume: 15
ISBN: 9781800616844
ISBN 10: 1800616848
Series: Computational and Experimental Methods in Structures
Pages: 208
Publication Date: 17 April 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Hardback
Publisher's Status: Active