Two-stage ROM: a hybrid reduced order model for offline and online efficiency [0.03%]
两阶段ROM：一种混合型降阶模型以提高离线和在线效率
Rahul Dhopeshwar,Harshit Bansal,Karen Veroy
Rahul Dhopeshwar
Physics-based reduced-order models are one of the key enablers for improving the predictive capabilities of digital twins, offering a balance between computational efficiency and physical fidelity. However, their efficiency for nonlinear pr...
Hybrid machine learning and physical modeling of feedstock deformation during robotic 3D printing of continuous fiber thermoplastic composites [0.03%]
基于机器人3D打印连续纤维热塑性复合材料的料丝变形的混合机器学习和物理建模方法研究
Chady Ghnatios,Kazem Fayazbakhsh
Chady Ghnatios
Feedstock deformation during 3D printing of continuous fiber composites is a critical challenge in path planning and a main driver in the generation of manufacturing defects. The proposed work addressed the feedstock deformation during the ...
Arvan Sedighzadeh,Matteo Torzoni,Alberto Corigliano
Arvan Sedighzadeh
Truss design is a highly constrained problem due to mechanical requirements and practical limitations related to fabrication and assembly. This study formulates truss design synthesis as a discrete Markov decision process, in which grammar-...
Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder [0.03%]
基于 Proper Orthogonal Decomposition 和卷积自编码器的激光选区熔化成型过程的数据驱动非侵入式降阶模型预测方法研究
Shubham Chaudhry,Azzedine Abdedou,Azzeddine Soulaïmani
Shubham Chaudhry
This study proposes and compares two data-driven, non-intrusive reduced-order models (ROMs) for additive manufacturing (AM) processes: a combined proper orthogonal decomposition-artificial neural network (POD-ANN) and a convolutional autoen...
Response estimation and system identification of dynamical systems via physics-informed neural networks [0.03%]
基于物理信息神经网络的动态系统响应估计与系统辨识
Marcus Haywood-Alexander,Giacomo Arcieri,Antonios Kamariotis et al.
Marcus Haywood-Alexander et al.
The accurate modelling of structural dynamics is crucial across numerous engineering applications, such as Structural Health Monitoring (SHM), structural design optimisation, and vibration control. Often, these models originate from physics...
A segregated reduced-order model of a pressure-based solver for turbulent compressible flows [0.03%]
基于压力的湍流可压缩流动求解器的一种分离的降阶模型
Matteo Zancanaro,Valentin Nkana Ngan,Giovanni Stabile et al.
Matteo Zancanaro et al.
This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing...
Discovering non-associated pressure-sensitive plasticity models with EUCLID [0.03%]
用EUCLID发现非关联的压力敏感塑性模型
Haotian Xu,Moritz Flaschel,Laura De Lorenzis
Haotian Xu
We extend (EUCLID Efficient Unsupervised Constitutive Law Identification and Discovery)-a data-driven framework for automated material model discovery-to pressure-sensitive plasticity models, encompassing arbitrarily shaped yield surfaces w...
Pierre Ladevèze,Ludovic Chamoin
Pierre Ladevèze
Prior to any numerical development, the paper objective is to answer first to a fundamental question: what is the mathematical form of the most general data-driven constitutive model for stable materials, taking maximum account of knowledge...
Physics-informed two-tier neural network for non-linear model order reduction [0.03%]
基于物理知识的两层神经网络非线性模型降阶方法
Yankun Hong,Harshit Bansal,Karen Veroy
Yankun Hong
In recent years, machine learning (ML) has had a great impact in the area of non-intrusive, non-linear model order reduction (MOR). However, the offline training phase often still entails high computational costs since it requires numerous,...
A consistent diffuse-interface model for two-phase flow problems with rapid evaporation [0.03%]
一种一致的扩散界面模型用于两相流问题及快速蒸发问题
Magdalena Schreter-Fleischhacker,Peter Munch,Nils Much et al.
Magdalena Schreter-Fleischhacker et al.
We present accurate and mathematically consistent formulations of a diffuse-interface model for two-phase flow problems involving rapid evaporation. The model addresses challenges including discontinuities in the density field by several or...