ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
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EISSN:2332-9025|ISSN:2332-9017|Disc:The 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, uncertainty analysis and modeling, and other related areas|Priority:4|Publisher:American Society of Mechanical Engineers|
Recent Submissions
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Uncertainty Quantification in Fault and Degradation Analysis of Rolling Element Bearings
(The American Society of Mechanical Engineers (ASME), 2025)This study presents an innovative framework for deriving degradation models of rolling element bearings through uncertainty quantification. Natural open-source run-to-failure experimental datasets, XJTU-SY and PRONOSTIA, ... -
Influence of Potential Parameters on the Bistable Energy Harvester Under Random Excitation
(The American Society of Mechanical Engineers (ASME), 2025) -
Probabilistic Deep Learning With Bayesian Networks for Predicting Complex Engineering Systems' Remaining Useful Life: A Case Study of Unmanned Surface Vessel
(The American Society of Mechanical Engineers (ASME), 2025)Remaining useful life (RUL) serves as a key indicator of system health, and its accurate and timely prediction supports informed decision-making for efficient operation and maintenance. This is essential for complex ... -
A Flexible Distribution Based on L-Moments and Its Application in Structural Reliability
(The American Society of Mechanical Engineers (ASME), 2025)The distribution information of random variables is essential for reliability engineering analysis. Distribution characteristics are generally described by traditional central moments (C-moments). However, C-moments may ... -
Propagation of Systematic Sensor Uncertainty Into the Frequency Domain
(The American Society of Mechanical Engineers (ASME), 2025)When it comes to the identification of dynamic system parameters, like stiffness and damping, the systematic measurement uncertainty is mostly ignored in the frequency domain because of its complicated and elaborate ... -
Multi-State Reliability Modeling and Assessment for Corrosion of Organic Coating-Substrate Structure
(The American Society of Mechanical Engineers (ASME), 2024)The organic coating-substrate structure suffers from corrosion reaction between the substrate material and water molecules during the storage stage. Multiphysics simulation is a promising tool for corrosion modeling and ... -
Associate Editor's Recognition
(The American Society of Mechanical Engineers (ASME), 2025)The Editors-in-Chief and Associate Editors of the ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering would like to thank all the Associate Editors for their expertise and time ... -
Reviewer's Recognition
(The American Society of Mechanical Engineers (ASME), 2025)The Editor and Editorial Board of the ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering would like to thank all the reviewers for volunteering their expertise and time reviewing ... -
Adaptative Kriging for Reliability Analysis of Sequential Simulation Models of Fatigue-Loaded Systems
(The American Society of Mechanical Engineers (ASME), 2025)Sequential numerical model chains are often used in industrial analyses. For example, structural durability analysis involves first finite element simulations followed by fatigue postprocessing. The prohibitive computational ... -
Balancing Interpretability and Uncertainty in Prognostic Models: A TOPSIS-Based Comparative Analysis of N-CMAPSS DS02 Methods
(The American Society of Mechanical Engineers (ASME), 2025)Prognostic models are vital for predictive maintenance, enabling accurate prediction of remaining useful life (RUL) in complex systems. However, balancing model interpretability, accuracy, and robust uncertainty quantification ... -
Mixed Uncertainty Analysis in Pressure Systems Inspection Applications
(The American Society of Mechanical Engineers (ASME), 2025)Pressure systems contain hazardous fluids within industrial processes. Inspection plays a vital role in managing the reliability of these safety-critical systems. It allows engineers to identify, characterize, and manage ... -
Heuristic-Based Recommendation System for Dealing With Abnormal Situations in Industrial Applications
(The American Society of Mechanical Engineers (ASME), 2025)The effective management of process deviations and abnormal events depends on operational actions in providing the appropriate responses to each situation. Applications with requirements focused on the provision of resources ... -
Survival Signature-Based Structural Importance Analysis of Multistate System With Binary-State Components
(The American Society of Mechanical Engineers (ASME), 2025)System reliability analysis aims to identify a system’s weaknesses or critical components and quantify their failures’ impact. Analyzing the influence of system components on system failure is a common problem in reliability ... -
Special Section on Reliability Modeling and Assessment of Complex Engineering Systems with Mixed Uncertainty
(The American Society of Mechanical Engineers (ASME), 2025)Engineering systems are becoming increasingly complex. They need to meet advanced requirements, especially in mission-critical fields with a low failure tolerance. As unexpected failures during the designed lifespan of a ... -
Harnessing Bayesian Deep Learning to Tackle Unseen and Uncertain Scenarios in Diagnosis of Machinery Systems
(The American Society of Mechanical Engineers (ASME), 2024)Direct inverse analysis of faults in machinery systems such as gears using first principle is intrinsically difficult, owing to the multiple time- and length-scales involved in vibration modeling. As such, data-driven ... -
Uncertainty Quantification in Fault and Degradation Analysis of Rolling Element Bearings
(The American Society of Mechanical Engineers (ASME), 2025)This study presents an innovative framework for deriving degradation models of rolling element bearings through uncertainty quantification. Natural open-source run-to-failure experimental datasets, XJTU-SY and PRONOSTIA, ... -
Influence of Potential Parameters on the Bistable Energy Harvester Under Random Excitation
(The American Society of Mechanical Engineers (ASME), 2025)- -
Probabilistic Deep Learning With Bayesian Networks for Predicting Complex Engineering Systems' Remaining Useful Life: A Case Study of Unmanned Surface Vessel
(The American Society of Mechanical Engineers (ASME), 2025)Remaining useful life (RUL) serves as a key indicator of system health, and its accurate and timely prediction supports informed decision-making for efficient operation and maintenance. This is essential for complex ... -
A Flexible Distribution Based on L-Moments and Its Application in Structural Reliability
(The American Society of Mechanical Engineers (ASME), 2025)The distribution information of random variables is essential for reliability engineering analysis. Distribution characteristics are generally described by traditional central moments (C-moments). However, C-moments may ... -
Propagation of Systematic Sensor Uncertainty Into the Frequency Domain
(The American Society of Mechanical Engineers (ASME), 2025)When it comes to the identification of dynamic system parameters, like stiffness and damping, the systematic measurement uncertainty is mostly ignored in the frequency domain because of its complicated and elaborate ...