Archives of Computational Methods in Engineering最新文献

{"title":"Finite Element Model Updating for Material Model Calibration: A Review and Guide to Practice","authors":"Bin Chen,&nbsp;Bojan Starman,&nbsp;Miroslav Halilovič,&nbsp;Lars A. Berglund,&nbsp;Sam Coppieters","doi":"10.1007/s11831-024-10200-9","DOIUrl":"10.1007/s11831-024-10200-9","url":null,"abstract":"<div><p>Finite element model updating (FEMU) is an advanced inverse parameter identification method capable of identifying multiple parameters in a material model through one or a few well-designed material tests. The method has become more mature thanks to the widespread use of full-field measurement techniques, such as digital image correlation. Proper application of FEMU requires extensive expertise. This paper offers a review of FEMU and a guide to practice. It also presents FEMU-DIC, an open-source software package. We conclude by discussing the challenges and opportunities in this field with the intent of inspiring future research.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 4","pages":"2035 - 2112"},"PeriodicalIF":12.1,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11831-024-10200-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145168834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Residual-Based Stabilized Reduced-Order Models of the Transient Convection–Diffusion–Reaction Equation Obtained Through Discrete and Continuous Projection","authors":"Eric Parish,&nbsp;Masayuki Yano,&nbsp;Irina Tezaur,&nbsp;Traian Iliescu","doi":"10.1007/s11831-024-10197-1","DOIUrl":"10.1007/s11831-024-10197-1","url":null,"abstract":"<div><p>Galerkin and Petrov–Galerkin projection-based reduced-order models (ROMs) of transient partial differential equations are typically obtained by performing a dimension reduction and projection process that is defined at either the spatially continuous or spatially discrete level. In both cases, it is common to add stabilization to the resulting ROM to increase the stability and accuracy of the method; the addition of stabilization is particularly common for convection-dominated systems when the ROM is under-resolved. While continuous and discrete approaches can be equivalent in certain settings, a plethora of different techniques have emerged for each approach. However, to the best of our knowledge, a thorough comparison of these techniques is currently missing. In this work, we take a first, foundational step and provide an in-depth review of seven commonly used residual-based ROM stabilization strategies within the setting of finite element method (FEM) discretizations using the convection-dominated convection–diffusion–reaction (CDR) equation, an established testbed for stabilization methods. We present the formulations in a unified setting, highlight connections between the strategies, and numerically assess the strategies. In the spatially continuous case, we examine the Galerkin, streamline upwind Petrov–Galerkin (SUPG), Galerkin/least-squares (GLS), and adjoint (ADJ) stabilization methods. For the GLS and ADJ methods, we examine formulations constructed from both the “discretize-then-stabilize” technique and the space–time technique. In the spatially discrete case, we examine the Galerkin, least-squares Petrov–Galerkin (LSPG), and adjoint Petrov–Galerkin (APG) methods. We summarize existing analyses for these methods and provide numerical experiments, comparing competing methods for the first time in the literature and assessing the impact of stabilization parameters and time step sizes. Our numerical experiments demonstrate that residual-based stabilized methods developed via continuous and discrete processes yield substantial improvements over standard Galerkin methods when the underlying FEM model is under-resolved. We find that SUPG, space–time GLS, and space–time ADJ are the best continuous stabilization techniques considered. For discrete ROMs, we find that APG is more accurate than LSPG at the expense of a smaller region of stability with respect to the stabilization parameter. The combination of an APG ROM constructed on top of a SUPG FEM is the overall best performing method. The review, discussion, and numerical inter-comparison of the seven stabilizations strategies using the CDR equations serves as a stepping stone toward a comprehensive investigation and further development of stabilization methods for more challenging problems.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1885 - 1929"},"PeriodicalIF":9.7,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atomistic-Scale Simulations on Grain Boundary Migration Mechanisms Involved in Metals and Alloys: A Critical Review","authors":"Nitin Kishore Rawat,&nbsp;Naman Jain,&nbsp;Abhishek Kumar Mishra,&nbsp;Akarsh Verma","doi":"10.1007/s11831-024-10201-8","DOIUrl":"10.1007/s11831-024-10201-8","url":null,"abstract":"<div><p>The mechanical properties of a material are affected by the kinetics and thermodynamics of the grain boundaries (GBs) present in their domain. Various research works, both experimental and simulation-based, have been undertaken to explore the relation between GBs and mechanical characteristics of materials, however, the underlying mechanism of GB growth or migration is still not well understood and requires additional research. Experimentally, the tracking of micro-evolution in GBs is a challenging task and to resolve this, atomistic-scale based molecular dynamics (MD) based simulations have emerged as a prominent tool for investigating the structure, kinetics, and thermal behaviour of GBs. Here in, the authors present a comprehensive overview of the research conducted on GB migration using MD based simulations. First, we discussed the various driving force (DF) methods utilised in MD simulations to cause GB migration. This includes artificial DF, curvature driven method, elastic DF, thermal gradient DF, Peach-Koehler DF method and random walk method. The concepts and underlying principles of each approach are then unveiled in detail. Next, a thorough examination of the principal discoveries of prior works conducted based on these approaches is showcased. The influence of grain boundary (GB) energy, faceted structure, grain growth, the type of driving force applied, temperature, and other relevant parameters has been thoroughly analyzed. The advantages and limitations of various approaches for studying GB migration are also pondered over. Finally, a summary of methods is given in conjunction with potential future directions.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1931 - 1968"},"PeriodicalIF":9.7,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State-of-the-Art Review of Continuum Mechanics-Based Modelling of Soil Surface Erosion","authors":"Hang Feng,&nbsp;Zhen-Yu Yin,&nbsp;Maozhu Peng,&nbsp;Qimeng Guo","doi":"10.1007/s11831-024-10198-0","DOIUrl":"10.1007/s11831-024-10198-0","url":null,"abstract":"<div><p>Soil surface erosion can shape the morphography of rivers and estuaries in the natural environment and induce high potential risks to structures in engineering. Numerical simulations based on continuum mechanics theory can provide reliable assessments of the evolution of surface erosion from the perspective of a large-scale view. However, current studies on continuum mechanics-based modelling are still limited. This paper comprehensively reviews such numerical simulations of soil surface erosion. This review begins by discussing the fundamental physical mechanisms of surface erosion. Subsequently, it explores the basic physics-based conservation equations controlling soils and fluids in surface erosion. Then, the empirical formulae depicting the different stages of surface erosion are presented. Building on these mathematical foundations, this paper reviews various numerical methods for surface erosion modelling from a continuum mechanics perspective. Finally, this paper discusses the advantages and limitations of the numerical methods. This work can provide researchers convenience for using numerical models on surface erosion simulations.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 4","pages":"1969 - 1995"},"PeriodicalIF":12.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11831-024-10198-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145162461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review on Data-Driven Constitutive Laws for Solids","authors":"Jan N. Fuhg,&nbsp;Govinda Anantha Padmanabha,&nbsp;Nikolaos Bouklas,&nbsp;Bahador Bahmani,&nbsp;WaiChing Sun,&nbsp;Nikolaos N. Vlassis,&nbsp;Moritz Flaschel,&nbsp;Pietro Carrara,&nbsp;Laura De Lorenzis","doi":"10.1007/s11831-024-10196-2","DOIUrl":"10.1007/s11831-024-10196-2","url":null,"abstract":"<div><p>This review article highlights state-of-the-art data-driven techniques to discover, encode, surrogate, or emulate constitutive laws that describe the path-independent and path-dependent response of solids. Our objective is to provide an organized taxonomy to a large spectrum of methodologies developed in the past decades and to discuss the benefits and drawbacks of the various techniques for interpreting and forecasting mechanics behavior across different scales. Distinguishing between machine-learning-based and model-free methods, we further categorize approaches based on their interpretability and on their learning process/type of required data, while discussing the key problems of generalization and trustworthiness. We attempt to provide a road map of how these can be reconciled in a data-availability-aware context. We also touch upon relevant aspects such as data sampling techniques, design of experiment, verification, and validation.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1841 - 1883"},"PeriodicalIF":9.7,"publicationDate":"2024-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Image-Based Hemodynamic and Rheological Study of Patient’s Diseased Arterial Vasculatures Using Computational Fluid Dynamics (CFD) and Fluid–Structure Interactions (FSI) Analysis: A review","authors":"Abdulgaphur Athani,&nbsp;Nik Nazri Nik Ghazali,&nbsp;Irfan Anjum Badruddin,&nbsp;Abdullah Y. Usmani,&nbsp;Mohammad Amir,&nbsp;Digamber Singh,&nbsp;Sanan H. Khan","doi":"10.1007/s11831-024-10193-5","DOIUrl":"10.1007/s11831-024-10193-5","url":null,"abstract":"<div><p>Vascular diseases, such as aneurysms and stenosis, significantly impact hemodynamic parameters and disrupt the structural integrity of the arterial layer. Computational Fluid Dynamics (CFD) simulations in realistic arteries with wall interactions can detect stenosis formation by identifying altered flows and variations in wall shear stresses. This review article aims to highlight the significance of CFD simulations in finding the evolution of arterial diseases based on CT (Computed tomography) scan images of actual patient data. Each article was evaluated based on various hemodynamic parameters, inflow pulsatile waveform nature, and blood rheological models, including Newtonian and Non-Newtonian. The review provides the outcomes of studies involving fluid and structure interactions. The challenges of CFD and Fluid–Structure Interaction (FSI) simulations are discussed using results derived from patient-specific CT scan data. Different anatomical vessels reconstructed using medical images, and various inflow and outflow boundary conditions being applied to simulate the flow in these models and wall interaction with the fluid domain have been reported to analyze the flow behavior and predict arterial wall diseases. The article will be helpful to researchers and surgeons in analyzing diseased patient and developing a non-invasive-based system. The study emphasizes the potential of CFD simulations for identifying vascular diseases and predicting their evolution based on CT scan images of actual patient data. Additionally, the article highlights the need for more research to address the challenges associated with CFD and FSI simulations.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1427 - 1457"},"PeriodicalIF":9.7,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Aided Modeling of Granular Materials: A Review","authors":"Mengqi Wang,&nbsp;Krishna Kumar,&nbsp;Y. T. Feng,&nbsp;Tongming Qu,&nbsp;Min Wang","doi":"10.1007/s11831-024-10199-z","DOIUrl":"10.1007/s11831-024-10199-z","url":null,"abstract":"<div><p>Artificial intelligence (AI) has become a buzzy word since Google’s AlphaGo beat a world champion in 2017. In the past five years, machine learning as a subset of the broader category of AI has obtained considerable attention in the research community of granular materials. This work offers a detailed review of the recent advances in machine learning-aided studies of granular materials from the particle-particle interaction at the grain level to the macroscopic simulations of granular flow. This work will start with the application of machine learning in the microscopic particle-particle interaction and associated contact models. Then, different neural networks for learning the constitutive behaviour of granular materials will be reviewed and compared. Finally, the macroscopic simulations of practical engineering or boundary value problems based on the combination of neural networks and numerical methods are discussed. We hope readers will have a clear idea of the development of machine learning-aided modelling of granular materials via this comprehensive review work.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 4","pages":"1997 - 2034"},"PeriodicalIF":12.1,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11831-024-10199-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145171700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review of Technologies and Challenges for Integrated Modeling Analysis","authors":"Laurence Sigler,&nbsp;Pere-Andreu Ubach,&nbsp;Javier Mora,&nbsp;Eugenio Oñate","doi":"10.1007/s11831-024-10187-3","DOIUrl":"10.1007/s11831-024-10187-3","url":null,"abstract":"<div><p>The natural and built environment form a complex system, comprised of many interrelated subsystems, each interacting in multiple nexus. Manifestations of these interactions can be seen in complex events. Climate change, natural disasters, military conflicts, pandemics, and other such events require accurate preparation, preparedness, and response planning, in a fast, ever changing context. With exascale (<span>(10^{18})</span> floating point operations per second) computational levels reached, computing power gives us the capability to model and simulate complex scenarios. This capability gives decision makers tools to game possibilities and enact preparatory and preventative measures to build resilience. There has been a trend of development of decision support, risk assessment, and operational forecasting systems to address this issue, aggregating diverse data sources onto unified platforms. Nonetheless, the majority of such platforms focus on the aggregation of just data and not models, and remain in silos of disciplines. What is needed to prepare and plan for disruptive events is a move towards decision support based on holistic, integrated, model-based analysis. While modeling individual systems has been done for many years, modeling in holistic analysis presents additional challenges. This paper presents an overview of the challenges and advances present for a move to a model-based holistic analysis, and an evaluation of some platforms currently in development and operation. The present work signals gaps in research to be addressed. Finally, we formulate base requirements for the development of systems to perform holistic model-based analysis, and discuss future plans for the development of such a platform.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1733 - 1762"},"PeriodicalIF":9.7,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11831-024-10187-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reviews on Load Flow Methods in Electric Distribution Networks","authors":"Attia A. El-Fergany","doi":"10.1007/s11831-024-10191-7","DOIUrl":"10.1007/s11831-024-10191-7","url":null,"abstract":"<div><p>In power system studies, load flow (LF) analysis is one of the most crucial tools. It is the most important and required method of looking at issues with power system design and operation. A series of nonlinear algebraic equations make up the LF issue, which needs to be mathematically solved by iterative numerical methods. In the current modern distribution systems (DSs) field, the most significant criterion that is heavily influenced by the DS’s size—which keeps growing—is the convergence of the solution. This paper gives readers an overview of recent research that has used both classical and artificial intelligence-based methods to handle LF-related issues with particular attention to DSs. The impacts of high R/X ratio of DSs along with various load models are discussed. Various standard and non-standard test feeders used for investigating LF algorithms are addressed. It also offers suggestions for future paths for this field of study. The types of examined LF problems are used to categorize the surveyed literature.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1619 - 1633"},"PeriodicalIF":9.7,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11831-024-10191-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Review on Multi-objective Optimization Techniques of Wire Electrical Discharge Machining","authors":"Devendra Pendokhare,&nbsp;Shankar Chakraborty","doi":"10.1007/s11831-024-10195-3","DOIUrl":"10.1007/s11831-024-10195-3","url":null,"abstract":"<div><p>In the present-day manufacturing environment, wire electrical discharge machining (WEDM) has become one of the most efficient non-conventional material removal processes to generate complicated 2D and 3D profiles on many of the difficult-to-cut engineering materials. Although the material removal rate of this process is comparatively low, but it can provide high dimensional accuracy and tolerance along with excellent surface integrity. To explore its maximum potential, it is advised to operate this process at the optimal combination of its various input parameters, which can only be derived using some optimization tools. The past researchers have already applied several multi-objective optimization techniques to resolve the issue. This paper comprehensively reviews and documents applications of four major multi-objective optimization tools, i.e. desirability function approach, grey relational analysis (GRA), multi-criteria decision making methods and metaheuristic algorithms considered for parametric optimization of WEDM processes. It also extracts information regarding type of the experimental design plan, work and wire materials, dielectric utilized, and WEDM parameters and responses considered. It is observed that Taguchi’s <i>L</i>₂₇ orthogonal array has been the most commonly deployed design plan, while medium and high carbon steels, and brass have been the most prevalent work and wire materials, respectively. Most of the researchers have preferred deionized water as the dielectric and GRA as the multi-objective optimization technique. During WEDM experiments, pulse-on time and pulse-off time have appeared as the two most significant input parameters; and surface roughness has been the most important response, followed by material removal rate. The outcome of this review paper would help the future researchers to have an idea regarding initial settings of different WEDM parameters and achievable response values. It would also act as a data support for subsequent utilization in developing machine learning-based prediction models.</p></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"32 3","pages":"1797 - 1839"},"PeriodicalIF":9.7,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143769831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}