ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Browse by
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
-
The Safety Assessment of Civil Ships Against Capsizing Based on the Probability Analysis of Multiple Threshold-Crossings of Stochastic Sea Waves
(The American Society of Mechanical Engineers (ASME), 2024)This paper investigates the impact of threshold-crossing events on ship capsizing through a probabilistic model that predicts random wave heights. Utilizing statistical data from wave height observations, this paper proposes ... -
A FMEA Optimization Method Based on TODIM and Best Worst Method-Water Filling Theory in Pythagorean Fuzzy Language Environment for Reliability Assessment of Industrial Robot
(The American Society of Mechanical Engineers (ASME), 2024)In view of the shortcomings of traditional failure modes and effects analysis (FMEA) in risk evaluation language, weight information, risk priority number (RPN), this paper proposes an FMEA optimization method. First, using ... -
Identification of Crashworthy Designs Combining Active Learning and the Solution Space Methodology
(The American Society of Mechanical Engineers (ASME), 2024)This study introduces a novel methodology for vehicle development under crashworthiness constraints. We propose coupling the solution space method (SSM) with active learning reliability (ALR) to map global requirements, ... -
Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems
(The American Society of Mechanical Engineers (ASME), 2024)Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of ... -
Innovative Bearing Fault Diagnosis Method: Combining Swin Transformer Deep Learning and Acoustic Emission Technology
(The American Society of Mechanical Engineers (ASME), 2024)Wind power generation, as a paragon of clean energy, places great importance on the reliability of its equipment. Bearings, in particular, as the core components of wind turbines, have a direct correlation with the stable ... -
On the Efficacy of Sparse Representation Approaches for Determining Nonlinear Structural System Equations of Motion
(The American Society of Mechanical Engineers (ASME), 2025)A sparsity-based optimization approach is presented for determining the equations of motion of stochastically excited nonlinear structural systems. This is done by utilizing measured excitation-response realizations in the ... -
A Novel Unsupervised Domain Adaptation Transformation Reconstructed Gated Recurrent Unit Framework Considering Prediction Uncertainty for Machinery Prognostics Under Variable Lubrication Conditions
(The American Society of Mechanical Engineers (ASME), 2024)As critical components in industrial application scenarios, high-precision and high-confidence health assessment of rolling bearings attract more and more attention. Currently, predictive maintenance obtains outstanding ... -
An Efficient Statistical Inference Approach for Model Calibration Using Griddy Gibbs Sampling
(The American Society of Mechanical Engineers (ASME), 2025)Model calibration is a critical step in many fields to ensure that decisions are made based on models that best capture the behavior of the physical system. Typically, an estimation of the uncertainty of the model is also ... -
A Novel Active Learning Kriging-Based Reliability Analysis Method for Aero-Engine Gear
(The American Society of Mechanical Engineers (ASME), 2025)This paper proposes the active learning Kriging (ALK)-based reliability method for high-cycle fatigue reliability analysis of aero-engine gears. Uncertainties to affect the reliability of aero-engine gears are quantified ... -
Uncertainty Quantification of Additively Manufactured Architected Cellular Materials for Energy Absorption Applications
(The American Society of Mechanical Engineers (ASME), 2024)With advances in additive manufacturing (AM), the technology has significantly increased the applications in a wide range of industrial sectors. For example, stereolithography (SLA) has become a promising candidate for the ... -
On the Consistent Classification and Treatment of Uncertainties in Structural Health Monitoring Applications
(The American Society of Mechanical Engineers (ASME), 2024)In this paper, we provide a comprehensive definition and classification of various sources of uncertainty within the fields of structural dynamics, system identification, and structural health monitoring (SHM), with a ... -
Data-Informed Risk Analysis of Power Grids: Application of Method for Managing Heterogeneous Datasets
(The American Society of Mechanical Engineers (ASME), 2024)Power utilities are continuously under high pressure to ensure the best performance of their grid. Nevertheless, power outages continue to be periodically observed. This paper assesses the applicability and implications ... -
Daily Engine Performance Trending Using Common Flight Regime Identification
(The American Society of Mechanical Engineers (ASME), 2024)Accurate flight regime identification is critical for enhancing aircraft efficiency and safety. Traditionally, predictive models for aircraft operation have relied on complex, black-box machine learning techniques that ... -
Data Augmentation Based on Image Translation for Bayesian Inference-Based Damage Diagnostics of Miter Gates
(The American Society of Mechanical Engineers (ASME), 2024)Structural health monitoring (SHM) data is the essential foundation for any SHM structural integrity assessment, including large civil infrastructure such as the miter gate application in this work. For some applications, ... -
Statistical Approaches for the Reduction of Measurement Errors in Metrology
(The American Society of Mechanical Engineers (ASME), 2024)Metrology is extensively used in the manufacturing industry to determine whether the dimensions of parts are within their tolerance interval. However, measurement errors cannot be avoided. Metrology experts are of course ... -
Optimizing Battery Maintenance and Reliability in Ground Control Station for Tethered High-Altitude Platforms
(The American Society of Mechanical Engineers (ASME), 2025)This paper presents an integrated system for ensuring uninterrupted power supply to tethered high-altitude platform systems (HAPS) by strategically managing the repair and replenishment of batteries in a k-out-of-n:G, COLD ... -
Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes
(The American Society of Mechanical Engineers (ASME), 2024)Despite the substantive literature on remaining useful life (RUL) prediction, less attention is paid to the influence of epistemic uncertainty and aleatory uncertainty in multiple failure behaviors in the accuracy of RUL. ... -
A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty
(The American Society of Mechanical Engineers (ASME), 2024)Inverse uncertainty quantification commonly uses the well established Bayesian framework. Recently, alternative interval methodologies have been introduced. However, in their current state of the art implementation, both ... -
Random Dynamic Responses of Two Parallel Interfacial Cracks Between a Functionally Graded Material Strip and Two Dissimilar Elastic Strips
(The American Society of Mechanical Engineers (ASME), 2024)An analytical approach is presented in this article for the random dynamic study of two parallel interfacial cracks in a functionally graded material (FGM) strip that is bonded between two distinct elastic strips. One of ... -
Stochastic Modeling of Crack Growth and Maintenance Optimization for Metallic Components Subjected to Fatigue-Induced Failure
(The American Society of Mechanical Engineers (ASME), 2024)The degradation of metallic systems under cyclic loading is subject to significant uncertainty, which affects the reliability of residual lifetime predictions and subsequent decisions on optimum maintenance schedules. This ...