Journals in Numerical methods in engineering
Journals in Numerical methods in engineering
- ISSN: 0266-8920
Probabilistic Engineering Mechanics
This journal provides a forum for scholarly work dealing primarily with probabilistic and statistical approaches to contemporary solid/structural and fluid mechanics problems encountered in diverse technical disciplines such as aerospace, civil, marine, mechanical, and nuclear engineering. The journal aims to maintain a healthy balance between general solution techniques and problem-specific results, encouraging a fruitful exchange of ideas among disparate engineering specialities.From time to time, review papers will be published to provide research and development oriented readers with state-of-the-art analyses of various areas of current interest. In addition, occasional papers of tutorial nature help enhance practice oriented readers' knowledge of the basic probabilistic and statistical techniques that are essential in present-day engineering practice design.In consultation with the editors, distinguished members of the probabilistic mechanics community may serve as guest editors for a special issue dedicated to a particular theme.Fields Covered:Aerospace engineering: • Damage-tolerant and durability design of aircraft • Load spectra characterisation • Random vibration of aerospace structuresCivil engineering: • Geotechnical applications • Natural hazards such as earthquakes, hurricanes, and waves • Stochastic fluid mechanics/hydrology • Structural response/control under natural hazardsMarine engineering: • Offshore structures response to wind-induced waves • Ship motion in a random seaMechanical engineering: • Fatigue design • Mechanical systems response/control • Vehicle vibration • Vibration isolationNuclear engineering: • Probabilistic risk assessment • Structural and equipment response to accidental loadsCommon to all disciplines: • Composite materials • Damage mechanics • Monte Carlo simulation • Random fields • Stochastic finite elements • Stochastic optimization • System reliability.
- ISSN: 0955-7997
Engineering Analysis with Boundary Elements
Aim of the JournalEngineering analysis with boundary elements is dedicated to the latest developments of engineering analysis with boundary elements, mesh reduction, and other related innovative and emerging numerical methods. The journal founded in 1984 was originally focused on the development of the Boundary Element Method. Its scope has since been expanded to include the emerging mesh reduction and meshless methods. The aim of the journal is to promote the use of non-traditional, innovative, and emerging computational methods for the analyses of modern engineering problems.ScopeEngine... Analysis with Boundary Elements publishes topics including: • Boundary Element Methods • Method of Fundamental Solutions and Related Methods • Radial Basis Function Collocation Methods • Other Mesh Reduction and Meshless Methods • Particle Methods • Other Emerging and Non-Traditional Numerical Methods • Advanced Engineering Analyses and Applications
- ISSN: 0167-4730
Structural Safety
An International Journal on Integrated Risk Assessment for Constructed FacilitiesStructural Safety is an international journal devoted to integrated risk assessment for a wide range of constructed facilities such as buildings, bridges, earth structures, offshore facilities, dams, lifelines and nuclear structural systems. Its purpose is to foster communication about risk and reliability among technical disciplines involved in design and construction, and to enhance the use of risk management in the constructed environment. All aspects of quantitative safety assessment are of interest:• Loads and environmental effects; • Material properties; • Prediction of response and performance; • Treatment of human error and engineering judgment; • Quality assurance/control; and • Techniques of decision analysis and risk management.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center
- ISSN: 0925-5273
International Journal of Production Economics
The International Journal of Production Economics focuses on topics treating the interface between engineering and management. All aspects of the subject in relation to manufacturing and process industries, as well as production in general are covered. The journal is interdisciplinary in nature, considering whole cycles of activities, such as the product life cycle - research, design, development, test, launch, disposal - and the material flow cycle - supply, production, distribution.The ultimate objective of the journal is to disseminate knowledge for improving industrial practice and to strengthen the theoretical base necessary for supporting sound decision making. It provides a forum for the exchange of ideas and the presentation of new developments in theory and application, wherever engineering and technology meet the managerial and economic environment in which industry operates. In character, the journal combines the high standards of a traditional academic approach with the practical value of industrial applications.Article... accepted need to be based on rigorous sound theory and contain an essential novel scientific contribution. Tracing economic and financial consequences in the analysis of the problem and solution reported, belongs to the central theme of the journal. Submissions should strictly follow the Guide for Authors of the journal.We are interested in publishing high quality survey and review papers in relevant domains. However, we stress that the hurdles for consideration of such papers are high. They must demonstrate a strong need, show that they are well-executed, and generate valuable insights. Survey and review papers must position themselves clearly in relation to existing related reviews and surveys in the field. Systematic reviews that merely describe publication patterns in a particular field are unlikely to be sent out for review for IJPE. All survey and review papers must show valuable critique of the field and new insights. Such papers will normally require author(s) with sufficient experience in the field to make appropriate judgements.Benefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center
- ISSN: 0045-7825
Computer Methods in Applied Mechanics and Engineering
The development of computational methods for the solution of scientific and engineering problems governed by the laws of mechanics was one of the great scientific and engineering achievements of the second half of the 20th century, with a profound impact on science and technology. This is accomplished through advanced mathematical modeling and numerical solutions reflecting a combination of concepts, methods and principles that are often interdisciplinary in nature and span several areas of mechanics, mathematics, computer science and other scientific disciplines as well. The continued staggering developments of the 21st century have now enabled simulation capabilities that are leading to tangible technological achievements for the clear betterment of mankind. Computer Methods in Applied Mechanics and Engineering was founded over five decades ago, providing a platform for the publication of papers in this important field of computational science and engineering. The range of appropriate contributions is very wide. It covers any type of computational method for the simulation of complex physical problems leading to the analysis and design of engineering products and systems. This includes theoretical development and rational applications of mathematical models and numerical algorithms related to finite elements, boundary elements, finite differences, finite volumes, meshless discretization methods, isogeometric methods, molecular dynamics, ab-initio calculations, physically-based machine-learning methods and digital-twin technologies, in the following fields of simulation-based engineering science: Solid and structural mechanics Fluid mechanics Mechanics of materials Heat transfer Dynamics Geomechanics Acoustics Biomechanics NanomechanicsAtomist... Molecular dynamics Quantum mechanics Electromagneticsand also includes virtual design, multiscale phenomena, from nanoscale to macroscale, multiphysics problems, parallel computing, optimization, machine learning, probabilistic and stochastic approaches.CMAME publishes original papers at the forefront of modern research describing significant developments of computational methods in solving problems of applied mechanics and engineering.CMAME does not publish review or survey papers.
- ISSN: 0266-352X
Computers and Geotechnics
The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged. The application of newly proposed numerical methods and techniques to complex geotechnical engineering problems or to well-documented case studies are of interest. However, submissions that predominantly report results from proprietary codes, describe computer modelling of laboratory tests, field monitoring, or case histories, or develop new design approaches are only welcome if they demonstrate novel user-implemented computational methods. Mining, petroleum, or transportation engineering topics are usually discouraged as they align more closely with other journals. Since the journal is willing to accept longer papers if justified, authors are asked to avoid two-part submissions.Original contributions in the emerging areas of Machine Learning and Data Science are now welcome. Submissions should have a focus on geotechnical engineering problems and should provide either i) advances in foundational algorithms and computational frameworks or ii) innovative applications of physics-informed AI/ML techniques. Research results are sought that leverage the integration of observational data, fundamental physical laws and our domain knowledge in geomechanics and geotechnical engineering to offer new physical insights, uncover hidden intrinsic physical laws, and create new knowledge for both geotechnical researchers and practitioners.
- ISSN: 0965-9978
Advances in Engineering Software
Aerospace • Civil • Environmental • Mechanical and Structural EngineeringIncluding Computing Systems in EngineeringThe objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving.The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliabilityThe journal publishes research papers, survey papers on key application areas, short communications and technical notes, discussions, software reviews and book reviews. A conference calendar is also included – entries welcome.Related conferences are listed under 'Related publications'.
- ISSN: 0377-2217
European Journal of Operational Research
Published in collaboration with the Association of European Operational Research Societies (EURO)The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making. EJOR contains the following types of papers:• Invited Reviews, explaining to the general OR audience the developments in an OR topic over the recent years • Innovative Applications of OR, describing novel ways to solve real problems • Theory and Methodology Papers, presenting original research results contributing to the methodology of OR and to its theoretical foundations, • Short Communications, if they correct important errors found in papers previously published in EJORThe Theory and Methodology Papers are classified into one of the seven headings:• Continuous Optimization • Discrete Optimization • Production, Manufacturing and Logistics • Stochastics and Statistics • Decision Support • Computational Intelligence and Information Management • Interfaces with Other DisciplinesBenefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center
- ISSN: 0167-6377
Operations Research Letters
Operations Research Letters (ORL) is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. ORL welcomes pure methodological papers and applied papers with firm methodological grounding. All articles are restricted to at most eight journal pages, with the option to relegate proofs and additional material to an online appendix. The main criteria for the papers to be published are quality, originality, relevance, and clarity. The journal's traditional strength is in methodology, including theory, modelling, algorithms, and computational studies. Please find below a full description of the areas covered by the journal.Area EditorsApproximation Algorithms for Combinatorial Optimization Problems Area Editor: Leah Epstein Associate Editors: M. Chrobak, K. Elbassioni, M. Feldman, J. Hurink, N. Olver, J. Sgall, J. Verschae The area covers all issues relevant to the development of efficient approximate solutions to computationally difficult problems. This includes worst case analysis or competitive analysis of approximation algorithms, and complexity results.Submissions can be articles consisting of theoretical work in the area, or articles combining significant theoretical contributions of mathematical flavor with computational investigations of heuristic approaches. Articles in the area of discrete optimization that do not belong to the scope of other areas may be submitted to this area as well.Computational Social Science Area Editor: Vianney Perchet Associate Editors: A. Drutsa, P. Mertikopoulos, R. Smorodinsky This area publishes papers focusing on data-driven procedures, either from a theoretical or an applied perspective, in operation research, games, economics and other social science. The scope includes: sample/computational complexity of mechanisms, learning in games/OR/social science, empirical solutions with AI algorithms (such as, but not limited to, deep learning techniques) of complex problems, etc. Continuous Optimization Area Editor: Hector Ramirez Associate Editors: M.F. Anjos, L.M. Briceno, D. Dadush, G. Eichfelder, D. Jiang, D. Orban, F. Schoen Papers in all fields of continuous optimization that are relevant to operations research are welcome. These areas include, but are not restricted to, linear programming, nonlinear programming (constrained or unconstrained, convex or nonconvex, smooth or nonsmooth, finite or infinite-dimensional... complementarity problems, variational inequalities, bilevel programming, and mathematical programs with equilibrium constraints. Financial Engineering Area Editor: Ning Cai Associate Editors: X. He, D. Mitchell Financial engineering utilizes methodologies of optimization, simulation, decision analysis and stochastic control to analyse the effectiveness and efficiency of financial markets. This area is interested in papers that innovate in terms of methods or that develop new models which guide financial practices. Examples include but are not limited to Fintech, financial networks, market microstructure, derivative pricing and hedging, credit and systemic risk, energy markets, portfolio selection. Game Theory Area Editor: Tristan Tomala Associate Editors: S. Beal, V. Ihele, D.W.K. Yeung, G. Zaccour This area publishes papers which use game theory to analyze operations research models or make theoretical contributions to the theory of games. The scope includes (but is not limited to): cooperative and non-cooperative games, dynamic games, mechanism and market design, algorithmic game theory, games on networks, games of incomplete information. Graphs & Networks Area Editor: Gianpaolo Oriolo Associate Editors: F. Bonomo, Y. Faenza, Z. Friggstad, L. Sanita The area seeks papers that apply, in original and insightful ways, discrete mathematics to advance the theory and practice of operations research, as well as those reporting theoretical or algorithmic advances for the area. Of particular, but not exclusive, interest are papers devoted to novel applications, telecommunications and transportation networks, graphs and web models and algorithms. Inventory and Supply Chain Optimization Area Editor: Sean Zhou Associate Editors: H. Abouee Mehrizi, A. Burnetas, X. Gong, Q. Li, J. Yang The area welcomes innovative papers focused on inventory control and supply management. Examples of topics include, but are not limited to, optimal sourcing, inventory and assortment selection, pricing and inventory optimization, capacity planning, multi-item/echelon systems, algorithms and bounds, near-optimal or asymptotic optimal solutions, and incentive design. Mixed Integer Optimization Area Editor: Marc Pfetsch Associate Editors: R. Fukasawa, L. Liberti, J.P. Vielma, G. Zambelli All submissions advancing the theory and practice of mixed integer (linear or nonlinear) programming like novel techniques and algorithmic approaches in convex relaxations, branch and cut, polyhedral combinatorics and theory driven heuristics are welcome. Case studies may be considered if they contribute to the general methodology. Operations Management Area Editor: Mahesh Nagarajan Associate Editors: L. Chu, Y. Ding, N. Golrezaei, T. Huh, R. Roet-Green, D. Saban, C. Shi, L. Zhu The OM department aims to publish short, focused high quality research in the area of operations management, broadly the field of operations research applied to management problems. We welcome papers that use a wide variety of methodologies, both descriptive as well as prescriptive in nature including optimization, applied probability, simulation, and game theory. Scheduling Area Editor: Marc Uetz Associate Editors: B. Moseley, E. Pesch, R. Van Stee We seek original and significant contributions to the analysis and solution of sequencing and scheduling problems. This includes structural and algorithmic results, in particular optimization, approximation and online algorithms, as well as game theoretic modeling. All results are welcome as long as the relevance of a problem and significance of the contribution is made compellingly clear. Stochastic Models and Data Science Area Editor: Henry LamAssociate Editors: H. Bastani, J. Dong, K. Murthy, I. Ryzhov, Y. Zhou The area seeks papers broadly on the interplay between operations research and machine learning and statistics where stochastic variability and uncertainty play a crucial role. The area values both papers that develop or utilize stochastic analysis and computation in data science problems, including but not limited to reinforcement learning, stochastic iterative algorithms for model estimation or training, probabilistic analysis of statistical and machine learning tools, sampling and Monte Carlo methods, and also papers that integrate learning or statistical techniques into stochastic modeling to enhance prediction or decision-making for a wide variety of systems. Stochastic Networks and Queues Area Editor: Harsha HonnappaAssociate Editors: E. Ozkan, W. Wang, Y. ZhaoThe area seeks papers that contribute to the modeling, analysis or innovative application of stochastic networks or queues. Work submitted should propose original models and develop novel analytical or computational methods more than incremental extensions. Examples of relevant application areas include but are not limited to supply chain management, manufacturing, financial engineering, healthcare, revenue management, service operations, telecommunications, sharing economy, online markets and public sector operations research. Application-oriented papers should demonstrate direct practical impact and have a strong methodological component as well.Stochastic Optimization and Machine Learning Area Editor: Angelos Georghiou Associate Editors: M. Bodur, M. Claus, E. Feinberg, P. Vayanos The Stochastic Optimization and Machine Learning area of Operations Research Letters solicits original articles that generate novel insights into problems that arise in optimization under uncertainty and in machine learning. The focus is broad and encompasses, among others, stochastic (dynamic) programming, (distributionally) robust optimization, data-driven optimization as well as the interface of machine learning with traditional areas of operations research. Successful submissions in this area are expected to make a clear and meaningful academic contribution, which may be through the study of new problems, models, solution techniques, performance analysis and convincing and reproducible numerical evaluations.
- ISSN: 0267-7261
Soil Dynamics and Earthquake Engineering
The journal aims to encourage and enhance the role of mechanics and other disciplines as they relate to earthquake engineering by providing opportunities for the publication of the work of applied mathematicians, engineers and other applied scientists involved in solving problems closely related to the field of earthquake engineering and geotechnical earthquake engineering.Emphasis is placed on new concepts and techniques and case histories are considered only if they enhance the presentation and understanding on new technical concepts associated with analysis.Fields Covered:Seismology and Geology relevant to earthquake engineering problems with emphasis on modeling and methodologies and consideration of their effects on the analysis and design of structures.Wave propagation, wave scattering and dynamic crack propagation in soils and rocks under elastic or inelastic material behavior.Dynamic constitutive behavior of materials.Dynamic interaction problems (soil-structure interaction, fluid-structure interaction and tsunamis if only related to its geotechnical and structural systems).Seismic analysis and design of steel and reinforced concrete structures, retaining walls, dams, slopes.Effect of moving loads on bridges and pavements and vibration isolation in geotechnical structures.Inverse problems, identification and structural health monitoring in earthquake engineering.Instrume... and experimental methods in earthquake engineering.Applied mathematical methods and artificial intelligence for earthquake engineering analysis and design.Performance-b... seismic design of structures.Probabili... methods in earthquake engineering including risk analysis and reliability Earthquake case histories and lessons learned from catastrophic ground motions.Earthquake case histories and lessons learned from catastrophic ground motions only if they include modeling and geotechnical/structu... analysis.