Deep learning-based inverse design for engineering systems: multidisciplinary design optimization of automotive brakes
نویسندگان
چکیده
The braking performance of the brake system is a target that must be considered for vehicle development. Apparent piston travel (APT) and drag torque are most representative factors evaluating performance. In particular, as two have conflicting relationship with each other, multidisciplinary design optimization (MDO) approach required design. However, computational cost MDO increases number disciplines increases. Recent studies on inverse use deep learning (DL) established possibility instantly generating an optimal can satisfy without implementing iterative process. This study proposes DL-based (MID) simultaneously satisfies multiple targets, such APT system. Results show proposed find more efficiently compared conventional methods, backpropagation sequential quadratic programming. MID achieved similar to single-disciplinary in terms accuracy cost. A novel was derived basis results, same satisfied existing
منابع مشابه
Multidisciplinary Design Optimization of Dynamic Engineering Systems
Dynamic engineering systems are playing an increasingly important role in society, especially as active and autonomous dynamic systems become more mature and prevalent across a variety of domains. Successful design of complex dynamic systems requires multidisciplinary analysis and design techniques. While multidisciplinary design optimization has been used successfully for the development of ma...
متن کاملMultidisciplinary Design Optimization of Elastomeric Mounting Systems in Automotive Vehicles
In this paper, a design optimization problem with multidisciplinary objectives is considered for a general purpose elastomeric mounting system (EMS). The multidisciplinary design objectives include quasi-static, dynamic and stability targets. Elastic stability of the EMS is investigated for the first time with the development of a general formulation that determines the critical buckling force ...
متن کاملIncorporating Multidisciplinary Design Optimization into Spacecraft Systems Engineering
Systems Engineering (SE) and Multidisciplinary Design Optimization (MDO) are usually regarded as two different aspects of spacecraft design. This paper investigates the problem of merging these two fields for the improvement of the spacecraft system design. The SE and MDO processes are described with emphases on their principles, models and tools, followed by a detailed analysis of their relati...
متن کاملDeep learning for topology optimization design
Generative modeling techniques are being rapidly developed in the field of deep learning, and they have been applied to topology optimization. The variational autoencoder (VAE) is a generative modeling technology that extends the autoencoder to generate new images with a limited latent space. We modified the basic VAE structure to encode optimization conditions and decode latent variables for t...
متن کاملInductive learning for engineering design optimization
We applied inductive learning to a problem, engineering design optimization, for which the applicability of inductive learning is not immediately obvious. In this paper we describe how we were able to formulate two pieces of the optimization problem as inductive learning problems, and we describe some of the lessons that we learned in the process.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Structural and Multidisciplinary Optimization
سال: 2022
ISSN: ['1615-1488', '1615-147X']
DOI: https://doi.org/10.1007/s00158-022-03386-8