Article
Engineering, Industrial
Rui Teixeira, Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor
Summary: This study discusses an innovative approach to metamodeling in reliability by using a field-transversal rationale. The proposed complement-basis method of using multiple metamodels or techniques for reliability analysis shows potential in improving efficiency. Further transversal research may enhance metamodeling in reliability analysis.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Computer Science, Interdisciplinary Applications
D. Rossat, J. Baroth, M. Briffaut, F. Dufour
Summary: In this paper, a Bayesian inversion approach combining adaptive Polynomial Chaos Kriging surrogate models and Subset Simulation rare event estimation method is proposed. The approach enables accurate approximation of posterior distributions and exhibits high sampling efficiency in dealing with multi-modal posteriors.
JOURNAL OF COMPUTATIONAL PHYSICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Xinxin Yue, Jian Zhang, Weijie Gong, Min Luo, Libin Duan
Summary: The novel PCE-HDMR algorithm proposed in this article integrates PCE with Cut-HDMR to provide simple and explicit approximations for a wide range of high-dimensional problems efficiently. Comprehensive comparisons on various mathematical functions and engineering examples show that PCE-HDMR has superior accuracy and robustness in terms of both global and local error metrics.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Acoustics
Juliette Dreau, Benoit Magnain, Alain Batailly
Summary: This article focuses on the stochastic modeling of nonlinear systems with discontinuous response surfaces. It proposes a method to improve the efficiency of multi-element polynomial chaos expansion by automating the detection of discontinuities and representing them as B-spline curves. The proposed methodology provides a more accurate and computationally efficient approximation of the discontinuous responses compared to classical polynomial chaos and multi-element polynomial chaos expansions.
JOURNAL OF SOUND AND VIBRATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Qiu-Jing Pan, Rui-Feng Zhang, Xin-Yu Ye, Zheng-Wei Li
Summary: This paper proposes an efficient algorithm that combines PCK and ARBIS for reliability analysis, updating both models adaptively. By sequentially updating the PCK model based on an active learning function and updating the fl-sphere in iterations until the optimal sphere is found, the algorithm demonstrates high accuracy and efficiency in five representative examples.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Construction & Building Technology
Deepthi Mary Dilip, G. L. Sivakumar Babu
Summary: Recognizing the importance of sustainable and durable structures, reliability-based designs are increasingly being adopted in pavement engineering. This study proposes the Reliability Based Design Optimization (RBDO) to create cost-effective flexible pavements considering uncertainties. Two meta-modelling techniques, second-order adaptive Response Surface Model (RSM) and adaptive Polynomial-Chaos based Kriging (PC-Kriging), are considered. The study highlights the need for adaptive meta-modelling approaches to address epistemic uncertainties. The proposed System Reliability Based Design Optimization (SRBDO) method integrates economic analysis and the Mechanistic-Empirical procedure to optimize pavement layer thicknesses and moduli.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Computer Science, Artificial Intelligence
A. Amini, A. Abdollahi, M. A. Hariri-Ardebili, U. Lall
Summary: This paper discusses time-dependent reliability and sensitivity analysis, comparing the superior efficiency and accuracy of the polynomial chaos Kriging meta-model with two other state-of-the-art methods. It examines aging dam issues, adaptive reliability approaches, and the significance of considering nonlinear dependency between random variables in reliability and sensitivity concepts.Overall, the paper highlights the potential of using PCK meta-model in uncertainty quantification and establishing accurate meta-models for reliability analysis in structural UQ.
APPLIED SOFT COMPUTING
(2021)
Article
Mathematics, Interdisciplinary Applications
Florian Bourgey, Emmanuel Gobet, Clement Rey
Summary: This article proposes a comprehensive comparison of polynomial chaos expansion (PCE) for indicator functions, providing tight estimates for the resulting truncation of PCE and analyzing the theoretical and numerical accuracy when extra transforms are applied. Different optimal choices are revealed based on the value of the threshold parameter.
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
(2022)
Article
Engineering, Industrial
Tong Zhou, Yongbo Peng
Summary: In this paper, an efficient reliability method called APCK-PDEM is developed, which combines adaptive Polynomial-Chaos Kriging and probability density evolution method. By proposing the notation of region of interest, this method can accurately estimate the failure probability and has high computational efficiency.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Automation & Control Systems
Mohammad Amin Hariri-Ardebili, Golsa Mahdavi
Summary: This paper proposes three surrogate modeling techniques (polynomial chaos expansion, Kriging, and canonical low-rank approximation) for concrete compressive strength regression analysis. With a benchmark database of high-performance concrete, various sources of uncertainties in surrogate modeling are quantified. The Kriging-based surrogate models outperform the existing predictive models and show more stable results. The selection of a proper optimization algorithm is the most important factor in surrogate modeling.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Multidisciplinary
Yicheng Zhou, Zhenzhou Lu, Kai Cheng
Summary: The Adaboost-PCE method proposed in this study is a novel polynomial chaos expansion surrogate modeling technique based on Adaboost algorithm, which can reduce the impact of outliers effectively and has the advantages of estimating ensemble weights and conducting adaptive sampling.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Industrial
Aghatise Okoro, Faisal Khan, Salim Ahmed
Summary: A tradeoff between cost and safety is essential in the reliability-based design of offshore support structures. This study proposes a dependence-based double-loop optimization framework for complex structural systems in uncertain harsh environments. It demonstrates the importance of multivariate dependence modeling and optimal copula selection, as well as the efficiency provided by the adaptive Polynomial Chaos Kriging (PCK) metamodel. The method described in this paper provides a road map for a dependency-based optimal design of complex ocean structures, allowing for strategic decision-making under uncertainty, considering cost and safety.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Engineering, Mechanical
H. C. Xie, D. H. Liao
Summary: This paper proposes a new time-dependent reliability analysis method based on a two-level meta-models technique for problems with interval variables, to efficiently obtain upper and lower bounds of reliability indexes of structures within a given design lifetime period. The method includes steps such as parameter transformation, polynomial chaos expansion, and meta-model construction, and its effectiveness is verified through three numerical examples.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Biswarup Bhattacharyya
Summary: An adaptive Bayesian polynomial chaos expansion method is proposed for uncertainty quantification and reliability analysis, utilizing automatic relevance determination and variational Bayesian inference to achieve highly sparse PCE models. The leave one out error is used to obtain the adaptive BPCE model, which can simultaneously select the optimal number of model evaluations and PCE degree, predicting accurate results with few model evaluations. Further, distribution parameters of the predicted response quantity are obtained by the VB inference, helping compute the confidence interval of predicted response quantities.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Multidisciplinary
Lukas Novak, Miroslav Vorechovsky, Vaclav Sadilek, Michael D. Shields
Summary: This paper introduces a novel adaptive sequential sampling method for constructing Polynomial Chaos Expansion surrogate models. The technique aims to obtain an optimal sample at each stage by extending the experimental design one by one. The strategy selects candidate points proportionally to their local variance contribution, balancing the exploitation of the surrogate model and exploration of the design domain.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Engineering, Industrial
Rui Teixeira, Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor
Summary: This study discusses an innovative approach to metamodeling in reliability by using a field-transversal rationale. The proposed complement-basis method of using multiple metamodels or techniques for reliability analysis shows potential in improving efficiency. Further transversal research may enhance metamodeling in reliability analysis.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Energy & Fuels
Rocio de la Torre, Bhakti S. Onggo, Canan G. Corlu, Maria Nogal, Angel A. Juan
Summary: Efforts are being made to instill key concepts such as circular economy and sustainable energy in higher education institutions to raise awareness among future professionals and managers about the importance of energy optimization. Despite successful implementation in favoring active student learning, there is still a need for more widespread use, particularly in serious games, to incorporate circular economy concepts into higher education degrees. Currently, there are challenges in integrating these concepts at the university management level.
Article
Chemistry, Analytical
Tian Peng, Maria Nogal, Joan R. Casas, Jose Turmo
Summary: The inverse problem of structural system identification is prone to ill-conditioning issues, and uncertainty quantification analysis is necessary to evaluate its impact on estimated parameters. The dynamic constrained observability method can compensate for the shortcomings of existing methods, and its correct performance and applicability are demonstrated through the analysis of a real bridge. The optimal sensor placement should consider not only the accuracy of sensors, but also the unknown structural part as epistemic uncertainty is removed with increasing knowledge of the structure.
Article
Construction & Building Technology
Omar Kammouh, Maria Nogal, Ruud Binnekamp, A. R. M. Rogier Wolfert
Summary: The paper introduces the 3C concept for managing infrastructure interventions, which optimizes activities and leads to cost savings. The approach formalizes a mathematical model to account for interactions between infrastructure networks and stakeholders, accommodating different types of interventions.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Construction & Building Technology
Tian Peng, Maria Nogal, Joan R. Casas, Jose Turmo
Summary: This paper highlights the importance of reducing estimation errors in Structural Health Monitoring (SHM) strategy and Structural System Identification (SSI) analysis, introducing a new method based on the constrained observability method and decision trees. The effectiveness of this method is validated using numerical models and a real bridge case, indicating the significant insights it provides for decision-making in optimal SHM + SSI strategy.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Construction & Building Technology
Omar Kammouh, Maria Nogal, Ruud Binnekamp, A. R. M. (Rogier) Wolfert
Summary: Probabilistic Monte Carlo simulations are commonly used to determine project completion times at specific probability levels. However, schedule changes can negatively impact the probability of timely completion, necessitating a manual trial and error approach to find effective mitigation measures.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2021)
Review
Engineering, Civil
Yue Shang, Maria Nogal, Haoyu Wang, A. R. M. (Rogier) Wolfert
Summary: Performance evaluation and maintenance planning are becoming increasingly important for ageing rail infrastructure and increasing demand for track safety and continuous availability. Discrete railway assets, such as bridges and level crossings, along with extended track sections, comprise the main railway network infrastructure. These assets have significant implications for train safety, riding comfort, operating expenditures, and effective network capacity. The heterogeneity of asset features and operating environments also presents challenges for efficient maintenance planning. This review focuses on level crossings and synthesizes different perspectives on their maintenance management. The integration of a systems thinking approach and two levels of asset management (micro- and macro-level) provide a structured synthesis that is interdependent and synergistic. The review also compares mechanistic and data-driven modeling approaches and identifies limitations in existing studies, with directions for future research aimed at improving the inspection and diagnosis process and moving towards a system-level maintenance approach for multiple level crossings.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Environmental Sciences
Luka Vucinic, David O'Connell, Rui Teixeira, Catherine Coxon, Laurence Gill
Summary: Microbial pollution of aquifers is a global water quality problem that poses significant risks to public health. This study utilized flow cytometric analysis and fecal indicator bacteria to assess the potential of providing faster and more descriptive information on microbial pollution in karst aquifers. The study also evaluated the use of turbidity as a proxy indicator for fecal groundwater contamination. The findings suggest that flow cytometry can provide additional insights into fecal pollution sources and its fate and transport in karst catchments.
WATER RESOURCES RESEARCH
(2022)
Article
Engineering, Civil
Rui Teixeira, Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor
Summary: This study explores the application of metamodels in recovery and adaptation modeling and proposes a sequential global metamodeling technique. The results show that metamodeling-based metaheuristics enable fast engineering analysis of traffic recovery and adaptation, which may change the way decisions are made.
SUSTAINABLE AND RESILIENT INFRASTRUCTURE
(2022)
Article
Engineering, Electrical & Electronic
Yukun Fang, Haigen Min, Xia Wu, Xiaoping Lei, Shixiang Chen, Rui Teixeira, Xiangmo Zhao
Summary: In order to ensure the safety and reliability of autonomous driving applications, a fault diagnosis framework tailored to autonomous vehicles is essential. This study discusses the interpretability issue in fault diagnosis for autonomous vehicles from the perspective of sensor data analytics. The impact of the environment on sensor data is evaluated using noise energy as a measure. A signal quality indicator and online denoising techniques are proposed to mitigate the impact and enhance data quality. An adversarial learning neural network, ALDSAE, is constructed for sensor data anomaly detection. An explanation model specific to ALDSAE is employed to interpret the anomaly detection results. Experiments with real test field data show that ALDSAE has higher performance than traditional anomaly detectors in terms of area under the ROC curve (AUC_ROC), and the explanation accuracy of the residual explainer is comparable to the widely used kernel Shapley additive explanation (SHAP) with significantly reduced response time.
IEEE SENSORS JOURNAL
(2023)
Article
Environmental Sciences
Rui Teixeira, Beatriz Martinez-Pastor, Luka Vucinic, Alan O'Connor
Summary: Floods are a major challenge for human societies, and effective flood adaptation decision-making is crucial. The study proposes a new approach, called expectation-quantile-investment (EQI) evaluation, that considers expectations, probability quantiles, and investments to assess robust adaptation decisions. The results show that EQI-informed decisions can determine optimality in seemingly competitive measures.
JOURNAL OF FLOOD RISK MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Haigen Min, Yukun Fang, Xia Wu, Xiaoping Lei, Shixiang Chen, Rui Teixeira, Bing Zhu, Xiangmo Zhao, Zhigang Xu
Summary: Fault diagnosis for autonomous vehicles is important to provide information about the vehicle's operation status and avoid potential risks. This study proposes a fault diagnosis framework with sensor self-diagnosis, using a residual consistency checking algorithm and a denoising shrinkage autoencoder (DSAE) for anomaly detection. Experimental results show that the proposed algorithm effectively detects and isolates failed sensors, and the DSAE achieves the best anomaly detection performance compared to other machine learning methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Civil
A. R. Ibrahim, D. A. Makhloof
Summary: The unavoidable heterogeneity in the mechanical characteristics of concrete is crucial to consider in the design of high-rise buildings. This study investigates the spatial variability of material properties and proposes a framework to capture the stochastic response and assess the reliability of structural components. The results demonstrate the importance of accounting for material uncertainty in ensuring the safety of high-rise buildings.
Article
Engineering, Civil
Zhiqiang Wan
Summary: This paper emphasizes the importance of global sensitivity analysis for stochastic dynamical systems with multiple uncertain parameters and proposes a global sensitivity index suitable for this purpose. The research findings demonstrate that the proposed approach exhibits high efficiency and accuracy.
Article
Engineering, Civil
Max Ehre, Iason Papaioannou, Daniel Straub
Summary: Reliability sensitivity analysis is a method to measure the influence of uncertain input parameters on the probability of failure in a system. Statistically dependent inputs pose challenges in computing and interpreting sensitivity indices. This study introduces a separation of effects between the probabilistic model and computational model to compute the independent and full contributions of all inputs. By using hierarchically structured isoprobabilistic transformations, the full set of variance-based sensitivity indices can be computed with a single set of failure samples obtained from a rare event estimation method.
Article
Engineering, Civil
Ze Yuan, Quanwang Li, Kefei Li
Summary: This paper proposes a method to determine a measurement plan for durability assessment of concrete structures, by calibrating the models using Bayesian updating and linear fitting in order to achieve the required accuracy. The paper establishes probabilistic time-dependent models for surface chloride concentration and chloride diffusion coefficient, and discusses the key factors affecting the accuracy of the models.
Article
Engineering, Civil
Ziqi Wang
Summary: This study addresses the fundamental limitation of equivalent linearization methods in nonlinear random vibration analysis, proposing a method to construct an estimator that converges on the nonlinear system solution using a limited number of nonlinear system simulations and optimizing the equivalent linear system to approach the nonlinear system solution quickly, especially for rare event probabilities.
Article
Engineering, Civil
Min Li, Srinivasan Arunachalam, Seymour M. J. Spence
Summary: This paper presents a multi-fidelity approach for computing small failure probabilities in engineering systems. By integrating information from different levels of model fidelity, the required number of high-fidelity model runs is reduced while maintaining accuracy in estimating failure probabilities.
Article
Engineering, Civil
Aritra Chatterjee, Trisha Chakravorty, Baidurya Bhattacharya
Summary: This paper presents a methodology to determine the system reliability of commonly used steel moment connections that have been designed according to current element based procedures. A general expression is derived to modify element resistance factors and meet specified system reliability targets.
Article
Engineering, Civil
Yuanqin Tao, Kok-Kwang Phoon, Honglei Sun, Jianye Ching
Summary: This study derives theoretical and approximate variance reduction functions (VRFs) for a potential inclined slip line in a spatially variable soil. The study investigates one-dimensional (1D) VRFs and proposes approximate VRFs for the one-dimensional Whittle-Mate 'rn (WM) model and the one-dimensional cosine Whittle-Mate 'rn (CosWM) model. The paper also derives theoretical scales of fluctuation and VRFs for commonly used two-dimensional autocorrelation models and proposes general approximations for the VRF over an inclined line.
Article
Engineering, Civil
Amir H. Khodabakhsh, Seid H. Pourtakdoust
Summary: The Fokker-Plank-Kolmogorov (FPK) equation is a crucial model for understanding and improving the performance of engineering systems. However, its solution is challenging due to its high dimensionality. This study introduces FPK-DP Net, a physics-informed network that can effectively solve high-dimensional FPK equations and demonstrates its applicability and accuracy through numerical implementations on benchmark problems.
Article
Engineering, Civil
Wouter Jan Klerk, Vera van Bergeijk, Wim Kanning, Rogier Wolfert, Matthijs Kok
Summary: This paper examines the reliability of flood defence systems under shock-based degradation and compares different maintenance concepts. The results show that the current maintenance concept fails to meet the reliability requirements for revetment failure. Additional inspections and targeted interventions can significantly reduce total cost and improve the robustness of flood defence systems.
Article
Engineering, Civil
Xuejing Wang, Xin Ruan, Joan R. Casas, Mingyang Zhang
Summary: This paper proposes a probabilistic Gaussian mixture model for simulating heavy vehicle scenarios on long-span bridges under free-flow conditions. The study utilizes a non-stationary Poisson process to simulate the uneven occurrence of heavy vehicles in different lanes, considering the correlation of gross vehicle weights within close range. The results show that the correlation and stationarity of vehicle distribution location significantly affect the structural responses.
Article
Engineering, Civil
Jianhua Xian, Ziqi Wang
Summary: This study presents an importance sampling formulation based on adaptively relaxing parameters, providing a unified framework for various existing variance reduction techniques and laying the foundation for creating new importance sampling strategies. It proposes two importance sampling strategies for low-dimensional and high-dimensional problems, which are crucial for fragility analysis in performance-based engineering.
Article
Engineering, Civil
Chi Xu, Jun Chen, Jie Li
Summary: This study proposes a new algorithm to determine the probability distributions of the live load duration and compares the results with Monte Carlo simulation. The algorithm allows the exact determination of design live loads based on a predefined exceeding probability, providing guidance for engineering design.
Article
Engineering, Civil
Hongyuan Guo, You Dong, Emilio Bastidas-Arteaga
Summary: This paper presents a general reliability assessment framework for RC structures based on a Mixed Bayesian network, taking into account environmental parameters, chloride transport, and concrete crack inspection. The case study reveals that early detection of large cracks may lead to an overestimation of failure probability by about 500%.
Article
Engineering, Civil
Changle Peng, Cheng Chen, Tong Guo, Weijie Xu
Summary: Reliability Analysis (RA) is critical in structural design and performance evaluation. This study proposes a novel learning function, SEUR, for surrogate model-assisted RA to improve efficiency and accuracy. The SEUR function is demonstrated to be more effective and efficient in dealing with nonlinear problems, small probabilities, and complex limit states.