Advanced Modeling and Simulation in Engineering Sciences最新文献_第3页

Physics-informed two-tier neural network for non-linear model order reduction. 用于减少非线性模型阶次的物理信息双层神经网络。

IF 2

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2024-01-01 Epub Date: 2024-11-14 DOI: 10.1186/s40323-024-00273-3

Yankun Hong, Harshit Bansal, Karen Veroy

{"title":"Physics-informed two-tier neural network for non-linear model order reduction.","authors":"Yankun Hong, Harshit Bansal, Karen Veroy","doi":"10.1186/s40323-024-00273-3","DOIUrl":"10.1186/s40323-024-00273-3","url":null,"abstract":"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, expensive, full-order solutions as the training data. Furthermore, in state-of-the-art methods, neural networks trained by a small amount of training data cannot be expected to generalize sufficiently well, and the training phase often ignores the underlying physical information when it is applied with MOR. Moreover, state-of-the-art MOR techniques that ensure an efficient online stage, such as hyper reduction techniques, are either intrusive or entail high offline computational costs. To resolve these challenges, inspired by recent developments in physics-informed and physics-reinforced neural networks, we propose a non-intrusive, physics-informed, two-tier deep network (TTDN) method. The proposed network, in which the first tier achieves the regression of the unknown quantity of interest and the second tier rebuilds the physical constitutive law between the unknown quantities of interest and derived quantities, is trained using pretraining and semi-supervised learning strategies. To illustrate the efficiency of the proposed approach, we perform numerical experiments on challenging non-linear and non-affine problems, including multi-scale mechanics problems.","PeriodicalId":37424,"journal":{"name":"Advanced Modeling and Simulation in Engineering Sciences","volume":"11 1","pages":"20"},"PeriodicalIF":2.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11564392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A consistent diffuse-interface model for two-phase flow problems with rapid evaporation. 快速蒸发两相流问题的一致扩散界面模型。

IF 2

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2024-01-01 Epub Date: 2024-11-13 DOI: 10.1186/s40323-024-00276-0

Magdalena Schreter-Fleischhacker, Peter Munch, Nils Much, Martin Kronbichler, Wolfgang A Wall, Christoph Meier

{"title":"A consistent diffuse-interface model for two-phase flow problems with rapid evaporation.","authors":"Magdalena Schreter-Fleischhacker, Peter Munch, Nils Much, Martin Kronbichler, Wolfgang A Wall, Christoph Meier","doi":"10.1186/s40323-024-00276-0","DOIUrl":"10.1186/s40323-024-00276-0","url":null,"abstract":"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 orders of magnitude, leading to high velocity and pressure jumps across the liquid-vapor interface, along with dynamically changing interface topologies. To this end, we integrate an incompressible Navier-Stokes solver combined with a conservative level-set formulation and a regularized, i.e., diffuse, representation of discontinuities into a matrix-free adaptive finite element framework. The achievements are three-fold: First, we propose mathematically consistent definitions for the level-set transport velocity in the diffuse interface region by extrapolating the velocity from the liquid or gas phase. They exhibit superior prediction accuracy for the evaporated mass and the resulting interface dynamics compared to a local velocity evaluation, especially for strongly curved interfaces.Second, we show that accurate prediction of the evaporation-induced pressure jump requires a consistent, namely a reciprocal, density interpolation across the interface, which satisfies local mass conservation. Third, the combination of diffuse interface models for evaporation with standard Stokes-type constitutive relations for viscous flows leads to significant pressure artifacts in the diffuse interface region. To mitigate these, we propose to introduce a correction term for such constitutive model types. Through selected analytical and numerical examples, the aforementioned properties are validated. The presented model promises new insights in simulation-based prediction of melt-vapor interactions in thermal multiphase flows such as in laser-based powder bed fusion of metals.","PeriodicalId":37424,"journal":{"name":"Advanced Modeling and Simulation in Engineering Sciences","volume":"11 1","pages":"19"},"PeriodicalIF":2.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11561015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-world application of a discrete feedback control system for flexible biogas production 离散反馈控制系统在柔性沼气生产中的实际应用

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-11-27 DOI: 10.1186/s40323-023-00251-1

Lingga Aksara Putra, Bernhard Huber, Matthias Gaderer

{"title":"Real-world application of a discrete feedback control system for flexible biogas production","authors":"Lingga Aksara Putra, Bernhard Huber, Matthias Gaderer","doi":"10.1186/s40323-023-00251-1","DOIUrl":"https://doi.org/10.1186/s40323-023-00251-1","url":null,"abstract":"Using renewable energy is increasingly prevalent as part of a global effort to safeguard the environment, with a reduction in $${mathrm{CO}}_{2}$$ being one of the primary objectives. A biogas plant provides an opportunity to produce green energy, but its profitability prevents it from being utilized more frequently. A suitable response to this economic issue would be flexible biogas production to exploit fluctuating energy prices. Nevertheless, the complex nature of the anaerobic digestion process that proceeds within the biogas plant and the wide range of substrates that may be utilized as the plant’s feeds make it challenging to achieve flexible biogas production truly. Most plant operators will rely on their experience and intuition to run the plant without knowing exactly how much biogas they will produce with the feed substrate. This work combines a system model estimation and feedback controller to provide an intuitive yet precise feedback control system. The system model estimation represents the biogas plant mathematically, and a total of six distinct approaches have been compared and evaluated. A PT1 model most accurately approximated the step-down and the step-up by the time percentage method, with the Akaike Information Criterion as the primary evaluation criterion for selecting the best model. The downward model was controlled by a discrete PI controller modified with the Root Locus Method and an Anti-Windup scheme, and the upward model was controlled by a state space controller. The quality of the controller was evaluated in both simulation and at the actual biogas plant in Grub, and the controller was able to reduce the biogas production rate approaching the setpoint in the expected period. Furthermore, the developed feedback control system is effortless enough to be installed in many biogas plants.","PeriodicalId":37424,"journal":{"name":"Advanced Modeling and Simulation in Engineering Sciences","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138529347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Classification and analysis of common simplifications in part-scale thermal modelling of metal additive manufacturing processes 金属增材制造过程局部热建模中常见简化方法的分类与分析

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-11-08 DOI: 10.1186/s40323-023-00253-z

Rajit Ranjan, Matthijs Langelaar, Fred Van Keulen, Can Ayas

{"title":"Classification and analysis of common simplifications in part-scale thermal modelling of metal additive manufacturing processes","authors":"Rajit Ranjan, Matthijs Langelaar, Fred Van Keulen, Can Ayas","doi":"10.1186/s40323-023-00253-z","DOIUrl":"https://doi.org/10.1186/s40323-023-00253-z","url":null,"abstract":"Abstract Computational process modelling of metal additive manufacturing has gained significant research attention in recent past. The cornerstone of many process models is the transient thermal response during the AM process. Since deposition-scale modelling of the thermal conditions in AM is computationally expensive, spatial and temporal simplifications, such as simulating deposition of an entire layer or multiple layers, and extending the laser exposure times, are commonly employed in the literature. Although beneficial in reducing computational costs, the influence of these simplifications on the accuracy of temperature history is reported on a case-by-case basis. In this paper, the simplifications from the existing literature are first classified in a normalised simplification space based on assumptions made in spatial and temporal domains. Subsequently, all types of simplifications are investigated with numerical examples and compared with a high-fidelity reference model. The required numerical discretisation for each simplification is established, leading to a fair comparison of computational times. The holistic approach to the suitability of different modelling simplifications for capturing thermal history provides guidelines for the suitability of simplifications while setting up a thermal AM model.","PeriodicalId":37424,"journal":{"name":"Advanced Modeling and Simulation in Engineering Sciences","volume":"78 S344","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135342543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solving multiphysics-based inverse problems with learned surrogates and constraints 用学习到的代理和约束求解基于多物理场的逆问题

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-10-11 DOI: 10.1186/s40323-023-00252-0

Ziyi Yin, Rafael Orozco, Mathias Louboutin, Felix J. Herrmann

{"title":"Solving multiphysics-based inverse problems with learned surrogates and constraints","authors":"Ziyi Yin, Rafael Orozco, Mathias Louboutin, Felix J. Herrmann","doi":"10.1186/s40323-023-00252-0","DOIUrl":"https://doi.org/10.1186/s40323-023-00252-0","url":null,"abstract":"Abstract Solving multiphysics-based inverse problems for geological carbon storage monitoring can be challenging when multimodal time-lapse data are expensive to collect and costly to simulate numerically. We overcome these challenges by combining computationally cheap learned surrogates with learned constraints. Not only does this combination lead to vastly improved inversions for the important fluid-flow property, permeability, it also provides a natural platform for inverting multimodal data including well measurements and active-source time-lapse seismic data. By adding a learned constraint, we arrive at a computationally feasible inversion approach that remains accurate. This is accomplished by including a trained deep neural network, known as a normalizing flow, which forces the model iterates to remain in-distribution, thereby safeguarding the accuracy of trained Fourier neural operators that act as surrogates for the computationally expensive multiphase flow simulations involving partial differential equation solves. By means of carefully selected experiments, centered around the problem of geological carbon storage, we demonstrate the efficacy of the proposed constrained optimization method on two different data modalities, namely time-lapse well and time-lapse seismic data. While permeability inversions from both these two modalities have their pluses and minuses, their joint inversion benefits from either, yielding valuable superior permeability inversions and CO 2 plume predictions near, and far away, from the monitoring wells.","PeriodicalId":37424,"journal":{"name":"Advanced Modeling and Simulation in Engineering Sciences","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

On the flow conditions requiring detailed geometric modeling for multiscale evaluation of coastal forests 沿海森林多尺度评价中需要详细几何建模的流动条件

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-08-24 DOI: 10.1186/s40323-023-00250-2

Reika Nomura, S. Takase, Shuji Moriguchi, K. Terada

引用次数: 0

Compatible interface wave–structure interaction model for combining mesh-free particle and finite element methods 无网格粒子与有限元相结合的兼容界面波-结构相互作用模型

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-07-26 DOI: 10.1186/s40323-023-00248-w

N. Mitsume

引用次数: 0

Scalable block preconditioners for saturated thermo-hydro-mechanics problems 饱和热流体力学问题的可伸缩块预处理器

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-06-26 DOI: 10.1186/s40323-023-00245-z

A. Ordoñez, N. Tardieu, C. Kruse, Daniel Ruiz, S. Granet

引用次数: 0

Sensitivity-guided iterative parameter identification and data generation with BayesFlow and PELS-VAE for model calibration 基于BayesFlow和PELS-VAE的灵敏度导向迭代参数识别和数据生成模型标定

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-06-24 DOI: 10.1186/s40323-023-00246-y

Yi Zhang, Lars Mikelsons

引用次数: 2

Numerical modelling of the process chain for aluminium Tailored Heat-Treated Profiles 铝定制热处理型材工艺链的数值模拟

Advanced Modeling and Simulation in Engineering Sciences Pub Date : 2023-06-12 DOI: 10.1186/s40323-023-00247-x

Hannes Fröck, Matthias Graser, M. Reich, M. Lechner, M. Merklein, O. Kessler

引用次数: 0