Search-to-Extraction: A reinforcement learning approach for structural reliability analysis

The paper presents a hybrid active-learning approach for structural reliability analysis via adaptive Kriging surrogate models. The quasi first-order reliability method is first proposed for characteristic truncation point of a structural performance function. This is used to define a truncation boundary via the joint probability distribution function of input random variables. To reduce simulation time for new training samples, a U-function based criterion is further implemented to refine the candidate sample set. Since the reliability-based expected improvement function and U functions are combined together to evaluate new training samples, it finalizes a hybrid active-learning Kriging (HALK) to develop adaptive surrogate models for the structural reliability analysis. Several numerical examples are presented to demonstrate potential applications of the proposed HALK algorithm. Compared to benchmark results provided by the brutal force Monte-Carlo simulation method, the effectiveness of the HALK approach has been justified by dealing with various structural reliability problems.

Structural reliability analysis based on improved wolf pack algorithm AK-SS

The paper presents a semi-empirical based response surface approach for structural reliability analysis of steel plates with non-uniform corrosion represented by random fields. The approach consists of using a semi-empirical design equation as simplified response surface model, which is then calibrated iteratively by means of the results of non-linear finite element analyses at the design points calculated by the First Order Reliability Method. This technique has been successfully applied to problems formulated in terms of discrete random variables and is now applied to problems involving spatial variability of structural parameters represented by random fields. The approach is first illustrated with an example of the ultimate strength of plates with random imperfections and material properties and then applied to plates with random fields of corrosion discretized using the Expansion Optimal Linear Estimation method. The results obtained by the semi-empirical based response surface approach and by coupling directly the First Order Reliability Method and the finite element code are compared.

A New Approach for Structural Reliability Analysis of Offshore Drilling Riser System

The study and analysis of repairable systems is an important topic in reliability. Analytical techniques become very complicated and unrealistic especially for modern complex systems. There have been attempts in the literature to evolve more realistic techniques using simulation approach for reliability analysis of systems. The purpose of this paper is to develop a novel Markov system dynamics (MSD) simulation framework for the reliability modeling and analysis of a repairable system. This paper proposes a hybrid approach called as MSD approach which combines the Markov approach with system dynamics simulation approach for reliability modeling. This approach will have the advantages of both Markov as well as system dynamics methodologies. The proposed framework is illustrated for a repairable two component system. The results of the simulation obtained in this work when compared with that obtained by traditional Markov analysis clearly validate that this novel MSD approach is an alternative approach for reliability modeling and analysis.

Smart transmitters are increasingly being deployed in safety critical systems. Although the processing and diagnostic features provided by digital systems are advantageous, it introduces additional complexity in reliability modelling of systems. The conventional Fault Tree Analysis (FTA) method for system reliability analysis has its shortcomings in modelling digital systems, to incorporate its dynamic system interaction and failure modes in detail. This is because some of the failure modes may arise due to the dynamic interactions between the modules of the system. Dynamic Flowgraph Methodology (DFM) was identified as one of the optimistic approaches to handle these interactions. DFM approach combines multi‐valued logic modelling and analysis capabilities to handle systems consisting of components that have multiple degraded states and exhibit dynamic behaviour. However, only few DFM tools have been developed and some of them are not available in public domain. The DFM approach relies heavily on development and implementation of its decision tables. The logic information present within the decision tables can be meticulously implemented using Petri Nets. Also, there are plenty of free Petri Nets tools available online. Thus, the idea of DFM was used in this work to capture the dynamic interactions by developing decision tables. The decision tables were transformed into the Petri Net models to perform the analysis. The paper demonstrates the potential of the hybrid DFM – Petri Net approach for dynamic reliability analysis of smart transmitter.

Due to the existing of various kinds of uncertainties, predicting structural performance is always a great challenge in practical applications. The reliability of structure under the probabilistic uncertainty has been well studied in the past decade. However, the randomness is not the only attribute of reality. This paper attempts to investigate approach for the structural reliability analysis via the fuzzy safety state which is defined by state variable and fuzzy random allowable interval. The fuzziness of safety criterion, the fuzziness and randomness of generalized stress and generalized strength are considered in the limit state models, and the membership function of the fuzzy structural reliability are derived by the defined fuzzy safety state.

The accelerated lifetime test is a widely used and effective approach in reliability analysis because of its shorter testing duration. In this study, product lifetimes are assumed to follow the Gompertz distribution. This article primarily focuses on performance comparisons between the linear model and the inverse power-law model, both of which are utilized to characterize the relationship between the shape parameter and stress levels. To test model robustness, we also generate data from the Sine-Modified Power Gompertz distribution, a more flexible alternative. We conduct Monte Carlo simulations using four estimation methods: the maximum likelihood method, the least squares method, the maximum product of spacing method, and the Cramér-von Mises method, for small, medium, and large sample sizes. The comparison of mean squared error serves as a critical indicator for evaluating the performance of different methods and models. Additionally, the shape parameter and reliability function are obtained based on the estimation results. Finally, a real dataset is analyzed to demonstrate the most suitable accelerated life model, and the Akaike Information Criterion is used to further assess model fit. Furthermore, we employ leave-one-out cross-validation (LOOCV) to prove this model’s generalizability.

This paper proposes an analytical approach for reliability analysis of structures with moderate to low level reliabilities (e.g., not larger than 0.99). In this approach, the primary statistical moments of a multi-dimensional performance function are estimated using the univariate dimension-reduction (DR) methodology based on additive decomposition of the performance function. Thus, complicated equations involving the evaluation of multidimensional integrals are transformed into simplified formulae requiring the solutions of multiple uni-dimensional integrals. The estimated statistical moments are then used to evaluate the unknown parameters associated with the extended generalized lambda distribution (EGLD). By minimizing the error between the moments of EGLD and those of the performance function as predicted by DR, the probability distribution of the performance function is estimated, and then the probability of failure is calculated. To evaluate the accuracy and efficiency of the proposed DR+EGLD approach, five example problems involving nonlinear limit state functions with low to moderate sets of random variables are examined. With direct Monte Carlo simulation and the first-order reliability method (FORM) as benchmark approaches, the effectiveness of the proposed approach is evaluated.

Seismic reliability analysis of bridge structures during and succeeding an earthquake event is of significant importance. The more accurate and robust approach of seismic reliability analysis is based on direct Monte Carlo simulation technique. But it is computationally challenging due to the requirement of large number of nonlinear time history analyses. The response surface method–based metamodeling approach is a viable alternative in such situation. This study explores the advantage of moving least squares method–based adaptive response surface method compared to the usually applied least squares method–based response surface method for improved seismic reliability analysis of multi-span bridge pier. The nonlinear time history analyses of the bridge pier are performed in the OpenSees with fibre sections considering a ground motion bin corresponding to the specified hazard level of the bridge site. The seismic reliability analysis results obtained by the usual least squares method and the proposed moving least squares method–based response surface method are compared with that of obtained by more accurate direct Monte Carlo simulation technique to elucidate the effectiveness of the proposed approach.

Reliability analysis based on the simulation model could be wrong if the simulation model were not validated. Various model bias correction approaches have been developed to improve the model credibility by adding the identified model bias to the baseline simulation model. However, little research has been conducted for simulation models with dynamic system responses. This paper presents such a framework for model bias correction of dynamic system responses for reliability analysis by addressing three technical components including: i) a validation metric for dynamic system responses, ii) an effective approach for dynamic model bias calibration and approximation, and iii) reliability analysis considering the dynamic model bias. Two case studies including a thermal problem and a corroded beam problem are employed to demonstrate the proposed approaches for simulation-based reliability analysis.

Purpose — Analysis of nonprismatic members has received a great deal attention from designers and engineers due to their ability in satisfaction of architectural and aesthetic necessities. Using these structural members in complex structures such as aircrafts, turbine blades and space vehicles, exact static and dynamic analyses of these members become more significant. Based on structural/mechanical principles, the purpose of this paper is to present a new method to evaluate exact structural matrices for nonprismatic Euler‐Bernoulli beam elements. Design/methodology/approach — Through introducing the concept of basic displacement functions (BDFs), it is shown that exact shape functions are derived in terms of BDFs. BDFs and their derivatives have structural interpretations; therefore, they are obtained via application of flexibility method. Unlike the conventional methods, which are almost categorized as displacement‐based methods, the flexibility basis of the method ensures the true satisfaction of equilibrium equations at any interior point of the element. Findings — The exact shape functions and consequently structural matrices are derived for general nonprismatic beam elements. Numerical examples are carried out to determine static deflection and natural frequencies, and the results are highly competent with the other methods in literature. Research limitations/implications — The method can be extended to structural analysis of curved beams, plates and shells as well. Moreover, it is possible to derive exact dynamic shape functions via BDFs by solving the governing equation for transverse vibration of beams. Theoretically, the method faces limitation in analysis of nonprismatic beams that converge to a point where cross‐sectional area and moment of inertia are equal to zero. Practical implications — The development of this idea, i.e. BDFs seems to lead to promotive novel approaches for structural analysis and could be a breaking point for developing new elements for plates and shells as it was shown for beam elements. Originality/value — The paper's introduction of special functions, namely BDFs and their application, in both static and dynamic analyses of structures, could be a breaking point in analysis procedures.

A cellular framework for structural analysis and optimization

The effective implementation of drug precursor legislation has driven the innovation and design of new alternative substances. The application of 1,3-dicarbonyl precursors as alternative precursors for the synthesis of 1-phenyl-2-propanone (P2P) and 3,4-methylenedioxyphenyl-2-propanone (MDP2P) has created new challenges to legal control. Their 1,3-dicarbonyl structure allows the precursors to exist as an equilibrium mixture of the tautomeric diketo and keto-enolic forms during the nuclear magnetic resonance (NMR) analysis. In this study, the keto-enol tautomerism of four 1,3-dicarbonyl drug pre-precursors, α-phenylacetoacetamide (APAA), methyl α-phenylacetoacetate (MAPA), ethyl α-phenylacetoacetate (EAPA), and methyl 2-(benzo[d][1,3]dioxol-5-yl)-3-oxobutanoate (MAMDPA) were investigated through NMR. One-dimensional (1D) and 2D NMR were combined to assign signals for the diketo and keto-enolic tautomers. Results showed that the keto-enol tautomerism was solvent-dependent but was also influenced by the substituent present in the molecule. Further, the analysis results indicated that majority of substances existed mainly in the diketo form. The enol-keto equilibrium constant (Keq) was stable in dimethyl sulfoxide-d6 and chloroform-d, while unstable for some compounds in acetone-d6 and deuterated methanol. The presence of impurities in the seized sample may disrupt the equilibrium between keto-enol tautomers in 1,3-dicarbonyl precursors. After the optimization of several key quantitative parameters, a quantitative NMR method for the quantification of 1,3-dicarbonyl drug precursors were also developed to facilitate their quantitative analysis. This is the first study to investigate the keto-enol tautomerism and quantification of 1,3-dicarbonyl drug precursors by NMR, providing a new approach for structure analysis and quantification of new precursor analogues.

Coupled ship simulation in hydrodynamics and structural dynamics provides a comprehensive approach to understanding the dynamic behavior of ships under wave-induced loads. Improvements in computer power have made it much easier to create coupled simulation methods that combine structural and hydrodynamics analyses. A literature review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 is used to look at future trends in this literature review. We have filtered 1440 articles in PRISMA 2020, including 93 articles for analysis. The bibliographic analysis reveals that China emerged as the first according to the first authors due to significant industrial and funding support. Based on 93 articles, computational methods can be grouped by the coupling method (one-way and two-way), the hydrodynamic analysis approach (potential flow and CFD), the structural analysis approach (FEM, TMM, and DMB), the hydrodynamics element type (2D and 3D), and the structural element type (1D and 3D). As an outcome of the review, it can be concluded that the most common approach is a two-way connection of the potential flow and FEM methods, which both use 3D elements for structural and hydrodynamic analyses. Future trends of this research should be explored based on the application of variables, reducing computational resources, and using artificial intelligence.