[{"author":"","categories":[],"content":"Operator confirmation required This notice describes the data flows visible in the website source. Before treating it as final, the responsible operator must confirm and complete the items marked Operator action below. In particular, the repository does not identify the controller’s legal entity, hosting provider, processor contracts, or configured retention periods.\nController and privacy contact The website currently identifies this operator contact:\nInstitute for Risk and Reliability\nCallinstr. 34\n30167 Hannover, Germany\nTelephone: +49 511 762 - 5981\nEmail: beer@irz.uni-hannover.de Operator action: Confirm the full legal name and contact details of the controller under Article 4(7) GDPR. Confirm whether a data-protection officer has been appointed and, if so, add the officer’s direct contact details here.\nVisiting the website The site is delivered as static files. To send a requested page or file, the hosting system necessarily processes connection data such as the requesting IP …","date":"2026-07-24","permalink":"https://jures-test.ilses-lan.de/privacy/","section":"","summary":"Information about personal data processed when this website is visited or its contact address is used.","tags":[],"title":"Privacy Notice"},{"author":"","categories":[],"content":"Legal Disclosure Provider information pursuant to § 5 DDG Institute for Risk and Reliability Callinstr. 34 30167 Hannover Tel. +49 511 762 - 5981 Fax +49 511 762 - 4756 https://irz.uni-hannover.de Represented by Prof. Dr.-Ing. Michael Beer beer@irz.uni-hannover.de Disclaimer Accountability for content The contents of our pages have been created with the utmost care. However, we cannot guarantee the contents’ accuracy, completeness or topicality. We are responsible for our own content on these web pages in accordance with applicable law. There is no general obligation to monitor transmitted or stored third-party information or to investigate circumstances indicating illegal activity. Obligations to remove or block access to information under generally applicable laws remain unaffected.\nAccountability for links Responsibility for the content of external links (to web pages of third parties) lies solely with the operators of the linked pages. No violations were evident to us at the time …","date":"2026-07-24","permalink":"https://jures-test.ilses-lan.de/legal/","section":"","summary":"Publisher contact information, legal disclosure, copyright notice, and website disclaimer.","tags":[],"title":"Legal Disclosure"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Fuel cells are a vital component of renewable energy warranting significant consideration and ever-increasing applications. With the increase in the application of these systems, the need for safety analysis also increases. These systems can fail due to several reasons that can result in economic losses and catastrophes. Increasing the life expectancy of fuel cells is an important aspect that needs substantial attention. Hence, to avoid sudden failures and achieve better life expectancy the discovery, identification, and implementation of enhanced health indicators for effective diagnosis and prognosis is critical.\nIncorporation of AI methods can aid these approaches. In particular, reliability analysis, diagnostics, and prognostics of fuel cells using AI-based uncertainty quantification, and data-driven or physics-based deep learning methods can be implemented. This special issue is focused on holistic approaches for reliability, safety analyses, uncertainty …","date":"2024-06-02","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-06-02_si065b/","section":"Posts","summary":"Call for fuel-cell reliability, safety, uncertainty quantification, diagnostics, and prognostics research.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI065B: Reliability and Safety Analysis, Uncertainty …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Background This Special Collection (SC) aims to gather contributions to advance the state-of-the-art methods and applications of uncertainty propagation in high-dimensional stochastic systems. Effective uncertainty propagation is critical for rational decision-making, risk assessment, and optimization of engineering systems. Particularly, high-dimensional stochastic systems represent a significant class of problems encountered in various domains. Nevertheless, uncertainty propagation in high-dimensional settings poses significant challenges due to the “curse of dimensionality”. Traditional methods often become computationally prohibitive. Consequently, there is a growing need for advanced techniques to handle the complexity of high-dimensional systems accurately and efficiently. This SC focuses on efficient analytical, data-driven, and computational methods for uncertainty propagation, novel control techniques for stochastic systems, and advanced optimization approaches. …","date":"2024-09-26","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-09-27_si069a/","section":"Posts","summary":"Call for efficient methods and engineering applications for uncertainty propagation in high-dimensional stochastic systems.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC069A: Advanced Numerical Techniques and Engineering …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground Bayesian inference provides a fundamental probabilistic framework to quantify uncertainty, incorporate evolving information, and make informed decisions. Over the years it has attracted ever-growing interest in various fields of science and engineering. In structural health monitoring (SHM) the approach has been explored for addressing challenges in extracting actionable information from data for structural identification, load estimation, damage diagnosis and prognosis, and remaining useful life prediction, for unknown and potentially changing structure and environment. Amidst emerging technologies such as artificial intelligence, machine learning, and digital twin, there are opportunities for exploring Bayesian techniques along deep learning methods to better account for modeling errors and uncertainties. This special collection aims to create a collaborative research platform for academics and practitioners worldwide to …","date":"2025-02-09","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-02-09_si072a/","section":"Posts","summary":"Archived call on advances in Bayesian inference for structural health monitoring.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC072A: Advances in Bayesian Inference for Structural Health …"},{"author":"Torsten Ilsemann","categories":[],"content":"We are delighted to announce the recipients of the 2024 Bilal M. Ayyub Research Award and Research Prize for Risk and Uncertainty in Engineering Systems, recognizing the best papers published in our journal in 2024. The awards highlight outstanding scholarly contributions to the advancement of risk and uncertainty analysis in engineering systems.\n📰 Best Paper in Part A: Civil Engineering Title: Risk Tolerance, Aversion, and Economics of Energy Utilities in Community Resilience to Wildfires Authors: Bilal M. Ayyub, Ramsay Sawaya, David T. Butry, Jennifer Helgeson, Yumi Oum, Vincent Loh\nPublished: June 2024 DOI: 10.1061/AJRUA6.RUENG-1254 This paper presents an insightful and timely study on how energy utilities’ economic behaviors, influenced by risk tolerance and aversion, affect community resilience against wildfires. The contribution stands out for its interdisciplinary integration of economics, risk modeling, and civil infrastructure resilience.\n📰 Best Paper in Part B: Mechanical …","date":"2025-05-15","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-05-15/","section":"Posts","summary":"The 2024 winning papers for the Bilal M. Ayyub Research Award and Research Prize in Parts A and B.","tags":["Announcements","Awards","Part B","Part A"],"title":"2024 Bilal M. Ayyub Research Award Winners Announced"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Description Reliability is a key aspect of safety-critical structures and systems such as bridges, aircrafts, dams, and nuclear structural facilities. For this reason, the performance of such structures and systems needs to be assessed via reliability analysis, to ensure they operate safely and, in turn, protect lives.\nGiven that reliability analysis is data-driven in nature, a significant challenge is the limited information availability, such as: 1) component reliability data; and 2) model-form certainty over the structure/system. These introduce uncertainty in the analysis, which is present in real-world engineering problems. Hence, the reliability analysis is often accompanied by an uncertainty analysis, which can be performed via the Bayesian approach.\nThe Special Collection builds on the previous efforts looking at uncertainty quantification in engineering, with the objective of creating a collection of state-of-the-art Bayesian methodologies, and cutting-edge …","date":"2025-08-25","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-08-25_si076a/","section":"Posts","summary":"Call for Bayesian reliability-updating research for safety-critical structures and systems with limited data.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC076A: Advances in Bayesian Approaches for Reliability …"},{"author":"Journal Editorial Board","categories":[],"content":"Submit Paper » About this joint special collection This multi-journal ASCE special collection brings together research, applied case studies, and forward-looking perspectives on engineering solutions for climate adaptation and infrastructure resilience. Topics include risk modeling, performance-based and life-cycle engineering, adaptive design, resilient infrastructure planning, digital twins, artificial intelligence, and decision-making under deep uncertainty.\nThe ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering is one of the participating journals. Authors should select the participating journal that best matches their manuscript’s aims and scope.\nDeadline Paper submission deadline: January 5, 2027\nTarget completion: June 30, 2027, or according to the journal review process\nSubmission guidance Read the complete publisher call for papers , then submit to Part A through its Editorial Manager site. In the submission questions, indicate that the …","date":"2026-01-05","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-01-05_climate-adaptation-resilience/","section":"Posts","summary":"Joint ASCE call for research and practice on climate adaptation and resilience for buildings and infrastructure.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"Joint ASCE: Climate Adaptation and Resilience for Buildings …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Description This Special Collection (SC) aims to provide a dedicated space for the in-depth exploration and dissemination of advancements in reliability-based, risk-based, and uncertainty-informed decision-making. The primary goal of this SC is to showcase emerging developments that address reliability and risk management to enhance the resilience and sustainability of our infrastructure systems and built environment. Contributions are expected to present key ideas, concepts, and technologies for solving significant challenges posed by the high complexity and multidisciplinary nature of problems as well as the comprehensive quantification, efficient processing, and management of induced uncertainties. By establishing this SC, we aim to foster a collaborative environment that encourages researchers to share insights and innovations in the multifaceted fields of risk, uncertainty, and decision-making within infrastructure systems.\nTopics Recent advances in reliability and …","date":"2026-02-20","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-02-20_si078a/","section":"Posts","summary":"Call for advances in reliability, risk, resilience, and uncertainty-informed infrastructure decision-making.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC078A: Reliability and Risk Management of Infrastructure …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Description The digital era is reshaping geotechnical uncertainty quantification (UQ) and reliability analysis through modern sensing, continuous monitoring, high-performance computing, and digital-twin ecosystems. Practice is increasingly data-rich, yet still challenged by sparse/biased data, nonstationarity, and complex ground–structure interactions. Meanwhile, the rapid integration of machine learning with physics-based and probabilistic models raises new demands for rigor, transparency, data efficiency, and deployability. This Special Collection seeks original research and practice-oriented advances that (i) separate, represent, propagate, and reduce uncertainty from site characterization and design to construction and operation, and (ii) translate uncertainty into decision-ready reliability and risk metrics. Contributions featuring verification/validation, uncertainty-aware interpretability, and reproducible workflows or well-documented datasets/case studies are …","date":"2026-02-24","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-02-24_si077a/","section":"Posts","summary":"Call for digital-era methods and applications in geotechnical uncertainty quantification and reliability analysis.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC077A: Geotechnical Uncertainty Quantification and …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Description The rapid advancement of sensing technologies, structural health monitoring (SHM), and intelligent data analytics has significantly enhanced the ability to detect damage and diagnose faults in engineering systems. From bridges and tunnels to energy facilities and transportation networks, large volumes of monitoring data are continuously collected through distributed sensors, imaging systems, and inspection platforms. Meanwhile, advances in signal processing, machine learning, and deep learning have enabled increasingly accurate and automated condition assessment.\nHowever, a critical gap remains between intelligent condition monitoring and risk assessment in engineering systems. While data-driven diagnostic methods can identify damage or anomalies, their outputs are often not systematically integrated into probabilistic reliability analysis, risk quantification, or decision-making frameworks. Uncertainties arising from measurement noise, environmental …","date":"2026-04-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-04-01_si080a/","section":"Posts","summary":"Call for research linking intelligent condition monitoring with reliability, risk assessment, and decision support.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC080A: Integrating Intelligent Condition Monitoring with …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submit Paper » Modern engineering systems, from vibration-sensitive mechanical devices and safety-critical structures to aerospace, transportation, industrial, and energy applications, are increasingly equipped with advanced sensing, modeling, and control technologies to enhance safety, serviceability, and resilience. However, assessing and predicting their performance are inevitably affected by multiple sources of uncertainty, including variability in material and geometric properties, modeling simplifications, measurement noise, environmental effects, and the stochastic nature of external excitations.\nRecent advances in health monitoring of engineering systems, system identification, and robust control offer new opportunities to address these challenges. Yet, a unified framework that consistently integrates modeling, identification, and control under uncertainty is still lacking. In this regard, the emphasis is on methodologies that not only quantify uncertainty, but actively …","date":"2026-06-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-06-01_si079b/","section":"Posts","summary":"Call for uncertainty-aware modeling, system identification, and control of engineering systems.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI079B: Modeling, Identification, and Control of Engineering …"},{"author":"Eleni Chatzi","categories":[],"content":"Archive note (July 13, 2026): This newsletter is preserved as published. For a concise, deadline-sorted view of active opportunities, see Open Calls for Papers .\nASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message I thank you all very much for your invaluable support of the journal in various ways, which has helped tremendously with the …","date":"2026-07-10","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-07-10_newsletter_july_2026/","section":"Posts","summary":"July 2026 journal newsletter with current calls for papers, conference news, awards, and editorial updates.","tags":["Announcements","Newsletter"],"title":"Newsletter July 2026 📩"},{"author":"","categories":[],"content":"Purpose ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering disseminates research findings, best practices and concerns, and discussion and debate on risk and uncertainty related issues. The journal reports on the full range of risk and uncertainty analysis state-of-art and state-of-practice relating to mechanical engineering, including but not limited to risk quantification based on hazard identification, scenario development and rate quantification, consequence assessment, valuations, perception, communication, risk-informed decision making, design for resilience, uncertainty analysis and modeling, and other related areas.\nScope Risk and reliability analysis methods; Uncertainty analysis and quantification; Resilience assessment and design for resilience, Optimization under uncertainty; Computational methods; Applications areas including every aspect of mechanical engineering systems, such as mechanical assets and infrastructure, materials …","date":"2026-07-13","permalink":"https://jures-test.ilses-lan.de/part_b/","section":"","summary":"Scope, submission information, journal metrics, and editorial board for Part B: Mechanical Engineering.","tags":[],"title":"Part B: Mechanical Engineering"},{"author":"","categories":[],"content":"Aims \u0026amp; Scope The journal will meet the needs of the researchers and engineers to address risk, disaster and failure-related challenges due to many sources and types of uncertainty in planning, design, analysis, construction, manufacturing, operation, utilization, and life-cycle management of existing and new engineering systems. Challenges abound due to increasing complexity of engineering systems, new materials and concepts, and emerging hazards (both natural and human caused). The journal will serve as a medium for dissemination of research findings, best practices and concerns, and for the discussion and debate on risk and uncertainty related issues. The journal will report on the full range of risk and uncertainty analysis state-of-the-art and state-of-the-practice relating to civil and mechanical engineering including but not limited to:\nRisk quantification based on hazard identification, Scenario development and rate quantification, Consequence assessment, Valuations, perception, …","date":"2026-07-13","permalink":"https://jures-test.ilses-lan.de/part_a/","section":"","summary":"Scope, submission information, journal metrics, and editorial board for Part A: Civil Engineering.","tags":[],"title":"Part A: Civil Engineering"},{"author":"","categories":[],"content":"","date":"2026-07-13","permalink":"https://jures-test.ilses-lan.de/open-calls/","section":"","summary":"Current calls for papers for Parts A and B of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems.","tags":[],"title":"Open Calls for Papers"},{"author":"","categories":[],"content":"Contact Online Editing Torsten Ilsemann jrues.managing.editor@gmail.com","date":"2026-07-13","permalink":"https://jures-test.ilses-lan.de/contact/","section":"","summary":"Contact the journal’s online managing editor.","tags":[],"title":"Contact"},{"author":"","categories":[],"content":"Journal Awards Established in 2019, the Editor’s Award is given annually to one paper in Part A appearing in the preceding volume year. Starting from 2022, the Editor’s Award for Part A was named “Bilal M. Ayyub Research Award” in recognition of the outstanding professional leadership of the founding Editor-in-Chief, Professor Bilal M. Ayyub, Dist. M. ASCE and Hon. M. ASME.\nThe awarded papers are made freely available from the ASCE Library for one year to anyone interested once registered and logged in to download.\nBilal M. Ayyub Research Award The former Best Paper Award is selected by a committee of the journal editorial board members. Congratulations to the authors for their work and contributions to the journal and the profession.\n2024 Winner Risk Tolerance, Aversion, and Economics of Energy Utilities in Community Resilience to Wildfires by Bilal M. Ayyub, Ramsay Sawaya, David T. Butry, Jennifer Helgeson, Yumi Oum, and Vincent Loh (2024) Previous Winners Experimental Study on the …","date":"2026-07-13","permalink":"https://jures-test.ilses-lan.de/awards/","section":"","summary":"Award-winning papers and reviewer recognition for Parts A and B of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems.","tags":[],"title":"Awards and Reviewer Recognition"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message It’s my great pleasure to announce that the fundraising for the Bilal M. Ayyub Research Award for Risk and Uncertainty in Engineering Systems has been finalized successfully, and ASCE has agreed to implement this award as an ASCE Society Award with effect from 2026. At this point, I would …","date":"2026-04-02","permalink":"https://jures-test.ilses-lan.de/posts/post-2026-04-02_newsletter_april_2026/","section":"Posts","summary":"April 2026 journal newsletter with active calls for papers, conference news, awards, and editorial updates.","tags":["Announcements","Newsletter"],"title":"Newsletter April 2026 📩"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message The trajectory of our journal is going upwards in a robust and sustainable manner. The impact factors have increased for both parts of the journal, now being 2.7 for Part A and 2.3 for Part B. Both parts of the journal are ranked in Q2. Part A is ranked 68/183 in Civil Engineering, which …","date":"2025-11-04","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-11-03_newsletter_okt_2025/","section":"Posts","summary":"November 2025 journal newsletter with calls for papers, awards, events, and editorial updates.","tags":["Announcements","Newsletter"],"title":"Newsletter November 2025 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nDescription The emergence of large language models (LLMs) and multimodal foundation models has revolutionized traditional approaches to risk assessment and predictive maintenance in engineering systems. These AI systems demonstrate unprecedented capabilities in processing heterogeneous data streams - from textual maintenance logs and equipment manuals to time-series sensor data and visual inspection reports - enabling comprehensive fault diagnosis across civil infrastructure (e.g., bridges, dams, power grids) and mechanical systems (e.g., rotating machinery, HVAC systems, industrial robots). However, the deployment of LLMs in safety-critical engineering applications introduces profound challenges that demand urgent research attention. First, the probabilistic nature of LLMs leads to inherent epistemic uncertainty in fault diagnosis, compounded by issues of model hallucination when interpreting sparse or noisy field data. Second, the …","date":"2025-08-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-08-01_si075a/","section":"Posts","summary":"Archived call for reliable, explainable large language models in engineering fault diagnosis, risk analysis, and predictive maintenance.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC075A: Large Language Models for Engineering Risk and …"},{"author":"Torsten Ilsemann","categories":[],"content":"The ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering is pleased to announce the launch of a new cycle of its Early Career Editorial Board (ECEB). Following the great success of the previous two cycles, this initiative continues to provide a unique opportunity for early career researchers to contribute to editorial leadership while gaining invaluable insight into the scholarly publishing process.\nThe ECEB program is designed to support researchers within 1–3 years of earning their doctoral degree who have demonstrated excellence in scholarship and a commitment to advancing the journal’s mission. Selected members participate in a range of editorial tasks under the mentorship of the journal’s associate editors and leadership team.\n🎯 ECEB Objectives and Responsibilities ECEB members play a vital role in the journal’s operations and outreach, including:\nProviding peer reviews for submitted manuscripts. Identifying potential reviewers. Acting as …","date":"2025-07-07","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-07-07/","section":"Posts","summary":"Announcement of Part A’s new Early Career Editorial Board cycle, its eligibility criteria, responsibilities, and professional-development benefits.","tags":["Announcements","ECEB","Part A"],"title":"🌟 Welcome to the New Cycle of the Early Career Editorial …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message The Bilal M. Ayyub Research Award for Risk and Uncertainty in Engineering Systems for the Best Paper in Part A of the Journal goes to Bilal M. Ayyub, Ramsay Sawaya, David T. Butry, Yumi Oum and Vincent Loh for their paper “Risk Tolerance, Aversion, and Economics of Energy Utilities in …","date":"2025-05-26","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-05-26_newsletter_may_25/","section":"Posts","summary":"May 2025 journal newsletter with the 2024 awards, calls for papers, conferences, and editorial news.","tags":["Announcements","Newsletter"],"title":"Newsletter May 2025 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nThe rapid evolution of mechanical systems and increasing industrial complexity have driven the need for advanced predictive maintenance strategies. Cognitive Digital Twins (CDTs), integrating AI, real-time data analytics, and cognitive computing, have emerged as a transformative solution. Unlike traditional digital twins, CDTs can learn, reason, and adapt, enabling more accurate and dynamic predictive maintenance. However, their reliability is challenged by modeling uncertainties, sensor noise, environmental variability, and unforeseen operational conditions.\nThese challenges highlight the need for robust uncertainty quantification and risk analysis frameworks tailored to CDTs. This special issue focuses on the intersection of cognitive digital twins, predictive maintenance, and risk analysis, exploring how CDTs can enhance decision-making under uncertainty, improve system reliability, and optimize maintenance strategies. It emphasizes …","date":"2025-03-10","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-03-10_si074b/","section":"Posts","summary":"Archived call for cognitive digital twins that support predictive maintenance through uncertainty quantification and risk-informed decisions.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI074B: Cognitive Digital Twins for Predictive Maintenance: …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nIndustrial equipment, such as engine, robot, machine tool, energy harvester, vehicle, etc., plays a pivotal role in enhancing production efficiency, ensuring product quality, and reducing labor expenses. However, the randomness of structural parameters and external excitations can potentially threaten the operation and safety of industrial equipment. Consequently, structural reliability, which can quantify the given performance and safety level of system under various uncertainties, is essential to ensure the quality of industrial equipment.\nCurrently, there are still some challenges to be studied further in identification of failure modes, efficient uncertainty quantification, rare failure probability assessment for industrial equipment, and measures of enhancing equipment quality and lengthening its life. The purpose of this special issue is to present the latest advancements in the field of reliability assessment and quality assurance …","date":"2025-03-08","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-03-08_si073b/","section":"Posts","summary":"Archived call for reliability assessment, failure analysis, quality assurance, and life extension of industrial equipment.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI073B: Reliability Assessment and Quality Assurance of …"},{"author":"Eleni Chatzi","categories":[],"content":"Image Source: vanderbilt.edu\nOn behalf of the ASCE-ASME Journal of Risk and Uncertainty in Engineering, we congratulate Professor Sankaran Mahadevan on receiving the 2025 Alfredo Ang Award on Risk Analysis and Management of Civil Infrastructure.\nEMI Past-President, Sankaran Mahadevan , Ph.D., F.EMI, M.ASCE, is the 2025 recipient of the Alfredo Ang Award on Risk Analysis \u0026amp; Management of Civil Infrastructure.\nProf. Mahadevan has contributed extensively to risk and reliability analysis, uncertainty quantification, and decision-making for engineered systems. As a former Managing Editor of the journal, he played a key role in advancing research and its dissemination in these areas.\nThe Alfredo Ang Award, presented by ASCE, recognizes contributions to risk analysis in civil infrastructure. The award was established to honor Alfredo H.S. Ang, Ph.D., S.E., Hon.M.ASCE, NAE, the developer of practical and effective methods of risk and reliability approaches to engineering safety-and-design …","date":"2025-02-15","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-02-15_award/","section":"Posts","summary":"Journal congratulations to Professor Sankaran Mahadevan, the 2025 recipient of ASCE’s Alfredo Ang Award for civil-infrastructure risk analysis.","tags":["Announcements","Awards"],"title":"Congratulations to Prof. Sankaran Mahadevan on Receipt of …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message On behalf of the ASCE-ASME Journal family, we wish you a Happy and Prosperous New Year. I would like to express my particular thanks to the journal managing and editorial team, which has made an outstanding contribution to promote the journal and to maintain and to increase quality. The …","date":"2025-01-27","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-01-28_newsletter_januar_25/","section":"Posts","summary":"January 2025 journal newsletter with calls for papers, awards, editorial updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter January 2025 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground Uncertainty Quantification (UQ) focuses on identifying, characterizing, and managing uncertainties in computational models and real-world systems. These uncertainties are classified into aleatory and epistemic types. Aleatory uncertainty, arising from inherent variability in natural systems, is irreducible, such as fluctuations in material properties. Epistemic uncertainty results from incomplete knowledge or assumptions in the modeling process and can be reduced with better information or models. Both types often coexist in practical problems, and quantifying them is essential for reliable predictions in various scientific and engineering disciplines. Forward Uncertainty Quantification (FUQ) is a specialized area within UQ that predicts how uncertain inputs affect model outputs, considering both aleatory and epistemic uncertainties. This process is vital for developing robust models that reflect real-world behavior under …","date":"2025-01-10","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-01-10_si071a/","section":"Posts","summary":"Archived call for engineering methods, tools, and applications in forward quantification of aleatory and epistemic uncertainty.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC071A: Forward Uncertainty Quantification for Aleatory \u0026 …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nLarge-scale systems are prevalent across critical infrastructure, manufacturing, offshore, automotive, aerospace, energy, and other sectors. These systems are inherently complex, and are characterized by the interactions among various components within the system and between the system and its environment. These systems are plagued with uncertainties stemming from various sources including incomplete or unreliable information, lack of data, and partially known physics. There is a growing demand for advanced techniques that can efficiently manage large-scale system complexity and result in robust and reliable design solutions with limited computational resources, ultimately minimizing failures with catastrophic consequences.\nThis special issue aims to bridge the gap between the theoretical frameworks and their real-world implementations with an emphasis on showcasing the effective implementation of safe design practices for large-scale …","date":"2025-01-08","permalink":"https://jures-test.ilses-lan.de/posts/post-2025-01-08_si068b/","section":"Posts","summary":"Archived call for practical, uncertainty-aware design methods for reliable large-scale systems across critical engineering sectors.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI068B: Design of Large-scale Complex Systems under …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message The impact factors for our journal show a robust consolidation at 2.3 for Part A and at 1.8 for Part B. This result is matching the average impact factors of journals in the respective areas, while the ranking is in Q2 for both parts. Based on the increased number of submissions in both …","date":"2024-09-27","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-09-27_newsletter_september_24/","section":"Posts","summary":"September 2024 journal newsletter with calls for papers, awards, editorial updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter September 2024 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground Engineering systems and structures are often subject to a wide range of uncertainties arising from material properties, environmental conditions, manufacturing tolerances, operational fluctuations, etc. Probabilistic analysis is usually applied to describe these uncertainties, although more often than not they also involve epistemic uncertainties arising from modelling the randomness under insufficient information, and/or a lack of modelling details of the physical processes with computational simulators. Accurately quantifying these uncertainties is critical for designing robust and reliable engineering solutions. This Special Issue aims to highlight the latest developments and innovative approaches in the field of uncertainty quantification tailored specifically for engineering applications.\nTopics Relevant topics may include but not limited to:\nUncertainty characterization and inference methods for spatial/temporal quantities …","date":"2024-09-26","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-09-27_si070a/","section":"Posts","summary":"Archived call for numerical and experimental methods to characterize, propagate, and reduce uncertainty in engineering systems.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC070A: Advances in Numerical and Experimental Methods for …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nAims \u0026amp; Scope This Special Collection (SC) aims to provide a dedicated space for in-depth exploration and dissemination of advancements in uncertainty modeling and quantification of numerical methods in geotechnical engineering. The primary goal of this SC is to feature emerging developments, which address the calibration of soil or rock constitutive models developed in recent time, data-driven and physics-informed models for soil or rock constitutive relations, database assessment of the variability in geotechnical numerical predictions, and benchmark exercises for geotechnical analyses by commercial software. The contributions are supposed to provide a deeper insight into the calibration and verification of numerical models in geotechnics, as well as the quantification of variability in numerical predictions of geo-structural response (e.g., deformation, capacity or stability). By establishing this SC, we aim to foster a collaborative …","date":"2024-07-02","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-07-02_si066a/","section":"Posts","summary":"Archived call for uncertainty modeling, calibration, verification, and data-informed numerical methods in geotechnical engineering.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC066A: Uncertainty Modeling and Quantification of Numerical …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nEngineering systems are increasingly complex. They need to meet advanced requirements for mission-critical fields with a low failure tolerance. As unexpected failures during the designed lifespan of a system may lead to catastrophic consequences, their reliability modeling and assessment are of utmost importance. The reliability modeling should achieve the assessment at a reasonable confidence level to help decision-makers arrive at sound decisions in practice.\nHowever, the modeling and assessment of real engineering systems often face an environment with a mixed uncertainty, due to either the inherent randomness (aleatory uncertainty) or a lack of knowledge (epistemic uncertainty). Particularly, available information for reliability modeling is often imperfect, arising from insufficient accumulated knowledge, biased prior information, limited field test data, etc. This makes reliability assessment considering imperfect information and …","date":"2024-06-08","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-06-08_si067b/","section":"Posts","summary":"Archived call for reliability modeling and assessment of complex engineering systems affected by aleatory and epistemic uncertainty.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI067B: Reliability Modelling and Assessment of Complex …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message It’s my great pleasure to report that the best paper awards for the 2023 cycle have been determined. The Bilal M. Ayyub Research Award for Risk and Uncertainty in Engineering Systems for the Best Paper in Part A of the Journal goes to Jinju Tao and Jianbing Chen for their paper “Experimental …","date":"2024-05-07","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-05-07_newsletter_may_24/","section":"Posts","summary":"May 2024 journal newsletter with award news, calls for papers, editorial updates, and events.","tags":["Announcements","Newsletter"],"title":"Newsletter May 2024 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground This Special Collection (SC) aims to provide a dedicated space for in-depth exploration and dissemination of advancements in vulnerability analysis, risk management, and uncertainty modeling. The primary goal of this SC is to feature emerging developments, which address hazards, risks and respective mitigation strategies towards resilience and sustainability of our infrastructure systems and the built environment. The contributions are supposed to provide key ideas, concepts and technologies to solve major challenges concerned with the high complexity and the multi-disciplinary character of the problems as well as with the comprehensive quantification, efficient processing and management of the involved uncertainties. By establishing this SC, we aim to foster a collaborative environment that encourages researchers to contribute high-quality works, sharing insights and innovations in the multifaceted fields of risk, uncertainty, …","date":"2024-05-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-05-01_si064a/","section":"Posts","summary":"Archived call for advances in vulnerability analysis, risk management, uncertainty modeling, and resilient infrastructure decisions.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC064A: Vulnerability Analysis, Risk Management, and …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message The previous year has been very exciting in several respects. Our best paper awards were named after our Founding Editor in Chief, Professor Bilal M. Ayyub. The awards were given in the closing session of the ASCE INSPIRE conference in November 2023, which has promoted both the awards and our …","date":"2024-01-14","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-01-15_newsletter_january_24/","section":"Posts","summary":"January 2024 journal newsletter with calls for papers, editorial updates, awards, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter January 2024 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground The reliability of civil engineering structures is paramount for sustainable and resilient infrastructure. Ensuring robust behavior, particularly in the face of extreme events, is crucial for longevity and adaptability. This Special Collection focuses on a pivotal aspect of structural resilience: the control of vibrations, specifically addressing uncertainties. Scholars are invited to contribute original research papers exploring the nuanced interplay between vibration control and broader resilient civil engineering structures. This thematic issue serves as a guide for risk and reliability analysis, emphasizing the vital role of vibration control devices in reinforcing stability amidst uncertainty.\nTopics The collection spans topics such as advanced risk and reliability analysis methods, transformative vibration control technologies, case studies validating techniques, vulnerability assessments, and strategies for enhancing …","date":"2024-01-03","permalink":"https://jures-test.ilses-lan.de/posts/post-2024-01-4_si063a/","section":"Posts","summary":"Archived call for risk and reliability methods that improve the resilience of civil structures through vibration-control devices.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC063A: Risk and Reliability Analysis of Resilient Civil …"},{"author":"Torsten Ilsemann","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Please contact the Editor or the Managing Editors by email if you have an interest to guest edit a special collection (Part A) or a special issue (Part B). Both Part A and Part B are listed in the Emerging Sources Citation Index by Clarivate Analytics , formerly Thomson Reuters, with Part A being indexed since …","date":"2023-09-08","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-09-08_toc/","section":"Posts","summary":"Archived September 2023 journal contents and editorial newsletter.","tags":["Announcements","Newsletter","TOC"],"title":"Table of Content: September 2023 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nBackground Understanding the data and reaching accurate conclusions are of paramount importance in the present era of Big Data. Machine learning has been widely used in academia and industry to analyze voluminous and intricate datasets to uncover hidden patterns and reach incisive insights. Whilst machine learning approaches have extraordinary potential and are increasingly employed to aid in various complicated tasks, their results are not wholly reliable due to the challenges introduced by data uncertainty (aleatory uncertainty) and model uncertainty (epistemic uncertainty). It is essential to accommodate uncertainties and provide uncertainty estimates to uncover beneficial information for a better decision-making process. To this end, the development and application of novel uncertainty quantification methods in tandem with different machine-learning-enhanced techniques are crucial to yield useful information and amplify the …","date":"2023-07-31","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-07-31_si062a/","section":"Posts","summary":"Archived call for uncertainty quantification that improves the reliability, interpretability, and engineering use of machine learning.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC062A: Uncertainty Quantification for Machine Learning in …"},{"author":"Torsten Ilsemann","categories":[],"content":"Submissions for this archived call are closed.\nIn recent decades, fault diagnostics and failure prognostics have demonstrated their great potential for health monitoring and risk management of complex engineering systems, including smart factories, power plants, space systems, and heavy equipment. The credibility and applicability of fault diagnostics and failure prognostics, however, are significantly affected by various uncertainties, such as model uncertainty, data uncertainty, process uncertainty, environmental uncertainty, and the inherent uncertainty of engineered systems. Therefore, accurately quantifying the effects of these uncertainties is essential and one of the most widely-held concerns to ensure trustworthy decision-making based on diagnostic and prognostic results. The purpose of this special issue is to present the latest advancements in the field of uncertainty-aware diagnostics and prognostics for the health management of engineered systems.\nTopic Areas THE SCOPE OF …","date":"2023-07-18","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-07-17_si061b/","section":"Posts","summary":"Archived call for uncertainty-aware fault diagnosis and failure prognosis for health monitoring and risk management of engineered systems.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI061B: Uncertainty-Aware Diagnostics and Prognostics for …"},{"author":"Eleni Chatzi","categories":[],"content":"ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message Part B of our journal has received an Impact Factor of 2.2, which is a tremendous success for the initial allocation. The Impact Factor for Part A has experienced a slight drop to 2.5, which is a result of a significant increase of the denominator of the assessment equation. In overall, this …","date":"2023-07-12","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-07-12_newsletter_july_23/","section":"Posts","summary":"Archived July 2023 journal newsletter with calls for papers, journal updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter July 2023 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Hi there,\nhere is the current table of content. Click to download the PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Please contact the Editor or the Managing Editors by email if you have an interest to guest edit a special collection (Part A) or a special issue (Part B). Both Part A and Part B are listed in the Emerging Sources Citation Index by …","date":"2023-05-18","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-05-19_toc/","section":"Posts","summary":"Archived June 2023 journal contents and editorial newsletter.","tags":["Announcements","Newsletter","TOC"],"title":"Table of Content: June 2023 📩"},{"author":"Eleni Chatzi, Sofi Alba","categories":[],"content":"Hi there,\nhere is the current newsletter. Click to download the PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message Our journal is gaining expanded exposure in the international community. This exposure is related to the global links built around the ASCE Infrastructure Resilience Division (IRD) and the ASME Safety Engineering \u0026amp; Risk …","date":"2023-04-10","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-04-10_newsletter_apr_23/","section":"Posts","summary":"Archived April 2023 journal newsletter with calls for papers, journal updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter April 2023 📩"},{"author":"Eleni Chatzi, Sofi Alba","categories":[],"content":"Hi there,\nhere is the current table of content. Click to download the PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Please contact the Editor or the Managing Editors by email if you have an interest to guest edit a special collection (Part A) or a special issue (Part B). Both Part A and Part B are listed in the Emerging Sources Citation Index by …","date":"2023-02-15","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-02-15_toc/","section":"Posts","summary":"Archived February 2023 journal contents and editorial newsletter.","tags":["Announcements","Newsletter","TOC"],"title":"Table of Content: Feb 2023 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Collection on Non-Deterministic Model Updating and Structural Health Monitoring for Existing Structures.\nClick to download the CFP Submissions for this archived call are closed.\nGuest Editors Masaru Kitahara, Assistant Professor, Department of Civil Engineering, The University of Tokyo, kitahara@bridge.t.u-tokyo.ac.jp Sifeng Bi, Lecturer, Department of Mechanical and Aerospace Engineering, University of Strathclyde, sifeng.bi@strath.ac.uk Matteo Broggi, Deputy Head, Institute for Risk and Reliability, Leibniz University Hannover, broggi@irz.uni-hannover.de Takayuki Shuku, Associate Professor, Architecture, Civil Engineering and Environmental Management Program, Okayama University, shuku@cc.okayama-u.ac.jp Aims \u0026amp; Scope This Special Collection (SC) aims to gather contributions presenting the state-of-the-art on uncertainty analysis in model updating and structural health monitoring (SHM) for existing structures. Over the past few …","date":"2023-01-18","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-01-18_sc059a/","section":"Posts","summary":"Archived call for non-deterministic model updating and uncertainty-aware structural health monitoring of existing infrastructure.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC059A: Non-Deterministic Model Updating and Structural …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Collection on Resilience of Power Infrastructure System.\nClick to download the CFP Guest Editors Wei Zhang, Associate Professor, University of Connecticut, wzhang@uconn.edu Ge (Gaby) Ou, Assistant Professor, University of Florida, gaby.ou@essie.ufl.edu Youngjib Ham, Associate Professor, Texas A\u0026amp;M University, yham@tamu.edu Zongjie Wang, Assistant Professor, University of Connecticut, zongjie.wang@uconn.edu Aims \u0026amp; Scope Extreme weather events, such as hurricanes, droughts, and flooding, are expected to be more “common” under a more variable climate system. With threats from stronger hurricanes, wildfires, snowstorms, etc., power infrastructure systems are experiencing critical threats, leading to many community residents and industrial facilities without power for days, weeks or longer. With the interdependency with other infrastructure systems, such as the communication, water, and transportation systems, the damages or failures …","date":"2023-01-17","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-01-17_sc058a/","section":"Posts","summary":"Archived call for research strengthening power-infrastructure resilience to extreme weather, cascading failures, and lifecycle risks.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC058A: Resilience of Power Infrastructure System"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Collection on New Technologies in Risk Assessment of Maritime Transport.\nClick to download the CFP Guest Editors Qing Yu, Jimei University, China, qing.yu@jmu.edu.cn Jakub Montewka, Gdansk University of Technology, jakub.montewka@pg.edu.pl Floris Goerlandt, Dalhousie University, Canada, floris.goerlandt@dal.ca Chengpeng Wan, Wuhan University of Technology, Wuhan, China, cpwan@whut.edu.cn Zhisen Yang, Shenzhen Technology University, Shenzhen, China, yangzhisen@sztu.edu.cn Zaili Yang, Liverpool John Moores University, UK, z.yang@ljmu.ac.uk Aims \u0026amp; Scope Motivated by the transition of trading demands in context of ongoing economic developments, the shipping industry is of rising importance from both national and international perspectives. However, maritime transport still suffers various risks due to emerging technological development (e.g., autonomous ships), new hazards/threats (e.g., climate change, cybersecurity, and COVID-19), …","date":"2023-01-16","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-01-16_sc057a/","section":"Posts","summary":"Archived call for emerging technologies and methods that improve risk assessment, safety, and resilience in maritime transport.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC057A: New Technologies in Risk Assessment of Maritime …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Issue on Probabilistic Digital Twins in Additive Manufacturing.\nClick to download the CFP Guest Editors Zequn Wang, Assistant Professor, Michigan Technological University, USA, zequnw@mtu.edu Zhen Hu, Assistant Professor, University of Michigan-Dearborn, USA, zhennhu@umich.edu Moon Seung Ki, Associate Professor, Nanyang Technological University, Singapore, skmoon@ntu.edu.sg Hong-Zhong Huang, Professor, University of Electronic Science and Technology of China, China, hzhuang@uestc.edu.cn Qi Zhou, Associate Professor, Huazhong University of Science and Technology, China, qizhou@hust.edu.cn Aims \u0026amp; Scope Additive manufacturing (AM) has made enormous progress over the past decade, as it is capable of producing complex parts with significantly less fabrication constraints compared to existing manufacturing technologies over a broad dimensional scale. Complicated AM process variability is one of the greatest obstacles in performance …","date":"2023-01-15","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-01-15_si060b/","section":"Posts","summary":"Archived call for probabilistic digital twins, uncertainty quantification, reliability, and process control in additive manufacturing.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI060B: Probabilistic Digital Twins in Additive …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Issue on Modeling and Analysis of Inspection Uncertainties in Structural Health Monitoring.\nClick to download the CFP Guest Editors Yi Zhang, Associate Professor, School of Civil Engineering, Tsinghua University, China, zhang-yi@tsinghua.edu.cn Chul-Woo Kim, Professor, Department of Civil and Earth Resources Engineering, Kyoto University, Japan, kim.chulwoo.5u@kyoto-u.ac.jp Yan-Gang Zhao, Professor, Department of Architecture, Kanagawa University, Japan, zhao@kanagawa-u.ac.jp Pei-Pei Li, Postdoctoral Research Fellow, School of Civil Engineering, Tsinghua University, China, lipeipei626@gmail.com Aims \u0026amp; Scope In recent years, structural health monitoring (SHM) technology has developed rapidly and is now gradually applied to civil, mechanical, automobile, and aerospace engineering practices. One of the most widely-held concerns is to utilize useful information provided by SHM for quantitative assessment of structural health and …","date":"2023-01-14","permalink":"https://jures-test.ilses-lan.de/posts/post-2023-01-14_si059b/","section":"Posts","summary":"Archived call for methods that model inspection and measurement uncertainty in structural health monitoring and model updating.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI059B: Modeling and Analysis of Inspection Uncertainties in …"},{"author":"Eleni Chatzi, Sofi Alba","categories":[],"content":"Hi there,\nhere is the current newsletter. Click to download the PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message Over the past year our journal has featured Special Collections and Special Issues on emerging technologies and cross-cutting topics of current interest, which attracted significant attention not only through their scientific …","date":"2022-12-31","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-12-31_newsletter_dez_22/","section":"Posts","summary":"Archived December 2022 journal newsletter with calls for papers, journal updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter December 2022 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Issue on Digital Twins: A New Frontier in Critical Infrastructure Protection and Resilience.\nClick to download the CFP Update: Submissions are open until January 31, 2023. Guest Editors Nii Attoh-Okine, PhD, University of Delaware, USA, okine@udel.edu Yaw Adu-Gyamfi, PhD, University of Missouri, USA, adugyamfiy@missouri.edu Aims \u0026amp; Scope A digital twin is a computational model (or set of coupled) that evolves over time to persistently represent the critical structure, its components, system or process. Digital twin underpins intelligent automation by supporting data-driven decision making and enabling asset specific analysis and system behavior. Within the contexts of critical Infrastructure systems, the digital twins represent the flow of information among connected platforms. In the future, as many agencies turn to digital twin capabilities, they have to migrate towards continuous real-time performance models and calibrate by …","date":"2022-11-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-06-28_si053b/","section":"Posts","summary":"Archived call for research on digital twins for real-time monitoring, failure prediction, protection, and resilience of critical infrastructure.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI053B: Digital Twins: A New Frontier in Critical …"},{"author":"Eleni Chatzi, Sofi Alba","categories":[],"content":"Hi there,\nhere is the current newsletter. Click to download the PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message Our journal has just recruited the new team of Early Career Editorial Board (ECEB) members. The ECEB was introduced as a mechanism to bring onboard young members serving as “ambassadors” for the journal to increase its …","date":"2022-11-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-11-01_newsletter_sept_22/","section":"Posts","summary":"Archived September 2022 journal newsletter with calls for papers, journal updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter September 2022 📩"},{"author":"Eleni Chatzi, Sofi Alba","categories":[],"content":"Click to download the newsletter as PDF ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems - Call for Papers Part A: Civil Engineering, and Part B. Mechanical Engineering\nThe Editorial Board of the ASCE-ASME Journal invites contributions presenting state-of-the-art research and best practices for addressing risk, disaster and failure-related challenges arising from uncertainty. We particularly welcome emerging research relating to availability and processing of big data, including data driven decision support, machine learning and further computational intelligence tools relating to risk and uncertainty.\nHow to submit:\nPart A: https://ascelibrary.org/journal/ajrua6 Part B: ASME Digital Collection - Part B Editorial Message We are proud to receive an Impact Factor of 3.084 for Part A of our journal. Simultaneously, we experience an upward trend for Part B and anticipate a respective reflection in an impact factor in the next cycle. This success is based upon a team effort …","date":"2022-10-19","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-07-15_newsletter_july_22/","section":"Posts","summary":"Archived July 2022 journal newsletter with calls for papers, journal updates, and community news.","tags":["Announcements","Newsletter"],"title":"Newsletter July 2022 📩"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Issue on Uncertainty Quantification \u0026amp; Management in Nonlinear Dynamical Systems in Aerospace and Mechanical Engineering.\nClick to download the CFP Guest Editors Jie Yuan, University of Strathclyde, United Kingdom, jie.yuan@strath.ac.uk Jinglang Feng, University of Strathclyde, United Kingdom, jinglang.feng@strath.ac.uk Enora Denimal, INRIA Institut National de Recherche en Informatique et en Automatique, France, enora.denimal@inria.fr Quan Hu, Beijing Institute of Technology, China, huquan2690@bit.edu.cn Sifeng Bi, University of Strathclyde, United Kingdom, sifeng.bi@strath.ac.uk Alice Cicirello, Delft University of Technology, The Netherlands, A.Cicirello@tudelft.nl Aims \u0026amp; Scope The study of aerospace systems is becoming an increasingly critical challenge due to the presence of a wide range of nonlinearities (such as large structural deformations, joints, fluid-structure interaction, electro-mechanical interaction, etc.), and …","date":"2022-10-13","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-10-14_si058b/","section":"Posts","summary":"Archived call for uncertainty quantification and management in nonlinear dynamical systems across aerospace and mechanical engineering.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI058B: Uncertainty Quantification \u0026 Management in Nonlinear …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Collection Advances in Efficient Methods in Random Fields Modeling and Analysis.\nClick to download the CFP Guest Editors Zhenhao Zhang, Changsha University of Science \u0026amp; Technology, zhangzhenhao@csust.edu.cn De-Cheng Feng, Southeast University, dcfeng@seu.edu.cn You Dong, The Hong Kong Polytechnic University, you.dong@polyu.edu.hk Emilio Bastidas-Arteaga, La Rochelle University, ebastida@univ-lr.fr Aims \u0026amp; Scope Spatial and temporal variability widely exists in practical engineering and has a significant influence on structural performance. Generally, it is modeled by the random field/process methods which typically transfer the field into a set of random variables, then it can be implemented in conventional uncertainty analysis framework. Efficient random field modeling and analysis usually involves three aspects, the adopted mathematical representation method, the accurate reflection of the geometric correlations, and the …","date":"2022-09-30","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-09-30_sc056a/","section":"Posts","summary":"Archived call for efficient random-field modeling, sampling, uncertainty analysis, and data-driven methods for engineering applications.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC056A: Advances in Efficient Methods in Random Fields …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Issue on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies.\nClick to download the CFP Guest Editors Cao Wang, University of Wollongong, Australia, wangc@uow.edu.au Matthias G.R. Faes, TU Dortmund University, Germany, matthias.faes@tu-dortmund.de Michael Beer, Leibniz University Hannover, Germany, beer@irz.uni-hannover.de Enrico Zio, Politecnico di Milano, Italy, enrico.zio@polimi.it John W. van de Lindt, Colorado State University, USA, jwv@engr.colostate.edu Aims \u0026amp; Scope Many types of disruptive events, such as earthquakes, tropical cyclones, floods, wildfires, and remarkably the coronavirus (COVID-19) pandemic, have threatened communities around the world with dramatic consequences. With respect to this, society is asking justified questions: how resilient is our community against disruptive events? How can we use resilience approaches to counteract disruptive events? What lessons …","date":"2022-08-09","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-08-09_si055b/","section":"Posts","summary":"Archived call for models, analyses, lessons learned, and case studies on community resilience before and after disruptive events.","tags":["Announcements","Special Collection/Issue","Part B","Call for Papers"],"title":"SI055B: Community Resilience to Disruptive Events: Models …"},{"author":"Torsten Ilsemann","categories":[],"content":"Dear colleagues, it is a great pleasure to announce the launch of our new website. You will find here the newsletter of the journals, additional information and links.","date":"2022-08-04","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-08-04/","section":"Posts","summary":"Announcement of the journal’s redesigned website and its resources for authors and readers.","tags":["Announcements"],"title":"Our New Website is Online 🎉"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the Call for Papers for the Special Collection on Extreme Damage Mechanics for Lifecycle Fatigue Resilience of Infrastructure Systems.\nClick to download the CFP Guest Editors Xuhong Zhou, Chongqing University, zxh@cqu.edu.cn Yongtao Bai, Chongqing University, bai.yongtao@cqu.edu.cn Frédéric Ragueneau, Paris‐Saclay University, frederic.ragueneau@ens‐paris‐saclay.fr Julio Florez‐Lopez, Chongqing University, j.florezlopez@cqu.edu.cn Aims \u0026amp; Scope This Special Collection aims to gather prestigious contributions presenting the state‐of‐the‐art breakthroughs on extreme damage mechanicsfor the lifecycle fatigue resilience of infrastructure systems. Since the 19th century, when the use of steels in civil engineering began to increase, it has been recognized that structural components and systems subjected to repetitive load cycles may fail in service life. This type of failure is well known as “fatigue” due to the formation and propagation of crack damages caused by …","date":"2022-08-01","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-08-01_sc054a/","section":"Posts","summary":"Archived call for research coupling damage mechanics and probabilistic methods to improve lifecycle fatigue resilience of infrastructure systems.","tags":["Announcements","Special Collection/Issue","Part A","Call for Papers"],"title":"SC054A: Extreme Damage Mechanics for Lifecycle Fatigue …"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the general Call for Papers for Part B: Mechanical Engineering.\nClick to download the CFP","date":"2022-06-29","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-06-29_cfp_part_b/","section":"Posts","summary":"General invitation to submit mechanical engineering research on risk, reliability, resilience, and uncertainty to the journal’s Part B.","tags":["Announcements","Part B","Call for Papers"],"title":"General Call for Papers for Part B: Mechanical Engineering"},{"author":"Torsten Ilsemann","categories":[],"content":"Please find attached the general Call for Papers for Part A: Civil Engineering.\nClick to download the CFP","date":"2022-06-29","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-06-29_cfp_part_a/","section":"Posts","summary":"General invitation to submit civil engineering research on risk, reliability, resilience, and uncertainty to the journal’s Part A.","tags":["Announcements","Part A","Call for Papers"],"title":"General Call for Papers for Part A: Civil Engineering"},{"author":"Torsten Ilsemann","categories":[],"content":"Dear colleagues, you are cordially invited to subscribe our quarterly newsletter for the latest updates on the ASCE-ASME Journal JRUES – both Part A and Part B.\nClick here to sign up","date":"2022-04-06","permalink":"https://jures-test.ilses-lan.de/posts/post-2022-04-06_newsletter_subscription/","section":"Posts","summary":"Subscribe to the quarterly JRUES newsletter for calls for papers, journal announcements, awards, and updates from Parts A and B.","tags":["Announcements","Newsletter"],"title":"Newsletter Subscription 📩"}]