Simplifications and theoretical assumptions are usually incorporated into the numerical modeling of structures. However, these assumptions may reduce the accuracy of the simulation results. This problem has led to the development of model-updating te...
The modal parameters of tooltip vibrations are crucial for determining chatter-free machining conditions. However, conventional methods often depend on measurements taken when the machine is not operating under real cutting conditions or require mult...
Categorical variables are common in spatial data analysis. Traditional analytical methods for deriving probabilities of class occurrence, such as kriging-family algorithms, have been hindered by the discrete characteristics of categorical fields. To...
To establish a high-fidelity model of engineering structures, this paper introduces an improved Bayesian model updating method for stochastic dynamic models based on frequency response functions (FRFs). A novel validation metric is proposed first wit...
Quantifying the vulnerability of buildings is fundamental to seismic risk mitigation, and fragility curves are among the most widely used tools for this purpose. With the growing availability and access to post-earthquake damage data from reconnaissa...
A Bayesian framework is presented for finite element model-updating using experimental modal data. A novel likelihood formulation is proposed regarding the inclusion of the mode shapes, based on a probabilistic treatment of the MAC value between the...
Finite element (FE) models are widely used in structural health monitoring to represent real structures and assess their condition, but discrepancies often arise between numerical and actual structural behavior due to simplifying assumptions, uncerta...
We focus on a Bayesian inference framework for finite element (FE) model updating of a long-span cable-stayed bridge using long-term monitoring data collected from a wireless sensor network (WSN). A robust Bayesian inference method is proposed which...
Ultrasonic non-destructive characterization is an appealing technique for identifying the microstructures of materials in place of destructive testing. However, the existing ultrasonic characterization techniques do not have sufficient long-term gage...
In levee system reliability, the length effect is the term given to the phenomenon that the longer the levee, the higher the probability that it will have a weak spot and fail. Quantitatively, it is the ratio of the segment failure probability to the...
Mechanics-based dynamic models are commonly used in the design and performance assessment of structural systems, and their accuracy can be improved by integrating models with measured data. This paper provides an overview of hierarchical Bayesian mod...
A novel probabilistic approach for model updating based on approximate Bayesian computation with subset simulation (ABC-SubSim) is proposed for damage assessment of structures using modal data. The ABC-SubSim is a likelihood-free Bayesian approach in...
Offshore wind turbine support structures are in harsh and unsteady marine environments, and their dynamic characteristics could change gradually after long-term service. To better understand the status and improve remaining life estimation, it is ess...
It is important to determine the soil–water characteristic curve (SWCC) for analyzing landslide seepage under varying hydrodynamic conditions. However, the SWCC exhibits high uncertainty due to the variability inherent in soil. To this end, a B...
In this study, we investigate inventory allocation and pricing strategies for retailers by incorporating demand information into the issue of inventory allocation during the presale period. In a presale system, retailers offer presale goods at a pric...
This paper proposes a Bayesian RC-frame finite element model updating (FEMU) and damage state estimation approach using the nonlinear acceleration time history based on nested sampling. Numerical RC-frame finite element model (FEM) parameters are sel...
Bayesian model updating has received considerable attention and has been extensively used in structural damage detection. It provides a rigorous statistical framework for realizing structural system identification and characterizing uncertainties ass...
Bayesian structural model updating (SMU) is among the most powerful methods for estimating the bending stiffness and modal damping of high-speed railway (HSR) bridges and predicting their bridge-response-based resonance responses. Although studies in...
In this work, we present an up-scaling framework in a multi-scale setting to calibrate a stochastic material model. In particular with regard to application of the proposed method, we employ Bayesian updating to identify the probability distribution...
Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-ba...
Analyzing the seismic vulnerability of bridge structures is of great significance in assessing the sustainable capacity of bridges. However, previous seismic vulnerability analysis of bridge structures was based on theoretical simulation or experimen...
The Bayesian model updating approach (BMUA) benefits from identifying the most probable values of structural parameters and providing uncertainty quantification. However, the traditional BMUA is often used to update stiffness only with the assumption...
We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the M...
Crest cracking is one of the most common damage types for high earth-rockfill dams. Cracking risk of dam crest is closely related to the duration of abnormal deformation state. In this paper, a methodology for dynamic risk evaluation and early warnin...
This paper presents a dynamic model for full-power converter permanent magnet synchronous wind turbines based on Physics-Informed Neural Networks (PINNs). The model integrates the physical dynamics of the wind turbine directly into the loss function,...
Bayesian update is widely used in data fusion. However, the information quality is not taken into consideration in classical Bayesian update method. In this paper, a new Bayesian update with information quality under the framework of evidence theory...
Importance sampling is used to approximate Bayes’ rule in many computational approaches to Bayesian inverse problems, data assimilation and machine learning. This paper reviews and further investigates the required sample size for importance sa...
In the construction process of large-scale bridges, there are uncertainties and time-varying factors in the environment and construction loads. It is difficult to make accurate estimates of the theoretical calculation models of construction control i...
Aiming at the problem that the performance of adaptive Kalman filter estimation will be affected when the statistical characteristics of the process and measurement of the noise matrices are inaccurate and time-varying in the linear Gaussian state-sp...
Background/Objectives: This study presents and explores the potential of Updated Bayesian Deduction (UBD) using colorectal cancer (CRC) detection and prioritisation as a case example. Colorectal cancer (CRC) is a leading cause of cancer-related morta...
The forecasting demand for new technology for which few historical data observations are available is difficult but essential to sustainable development. The current study suggests an alternative forecasting methodology based on a hazard rate model u...
Real-time anomaly detection in large, dynamic graph networks is crucial for real-world applications such as network intrusion prevention, fraud transaction identification, fake news detection in social networks, and uncovering abnormal communication...
Tie rods play a crucial role in civil engineering, particularly in controlling lateral thrusts in arches and vaults, and enhancing the structural integrity of masonry buildings, both historic and contemporary. Accurately assessing the tensile axial f...
An accurate seismic response simulation of civil structures requires accounting for the nonlinear soil response behavior. This, in turn, requires understanding the nonlinear material behavior of in situ soils under earthquake excitations. System iden...
This study develops a mathematical optimization framework to determine optimal inspection policies for imperfect production systems subject to stochastic deterioration. System degradation is modeled using a Weibull power law process, which captures t...
In recent years, structural health monitoring, starting from accelerometric data, is a method which has become widely adopted. Among the available techniques, machine learning is one of the most innovative and promising, supported by the continuously...
This paper presents a systematic and general method for Lamb wave-based crack size quantification using finite element simulations and Bayesian updating. The method consists of construction of a baseline quantification model using finite element simu...
Finite Element Model Updating (FEMU) is a common approach to model-based Non-Destructive Evaluation (NDE) and Structural Health Monitoring (SHM) of civil structures and infrastructures. Its application can be further utilized to produce effective dig...
Many masonry buildings exist worldwide. Safety assessments are crucial for renovation and upgrading. On-site testing reveals material properties and historic loads, enabling updates to structural resistance models for more accurate evaluations. (1) T...
This study introduces a Bayesian model updating approach for analyzing the long-term performance of steel–concrete composite beams (SCBs). Two nominally identical SCBs (SCB-1 and SCB-2) were designed, fabricated, and subjected to modal testing....
Monitoring and interpreting structural response using structural-identification methodologies improves understanding of civil-infrastructure behavior. New sensing devices and inexpensive computation has made model-based data interpretation feasible i...
When it is acknowledged that all candidate parameterised statistical models are misspecified relative to the data generating process, the decision maker (DM) must currently concern themselves with inference for the parameter value minimising the Kull...
Pipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly...
This paper is a review of a particular approach to the method of maximum entropy as a general framework for inference. The discussion emphasizes pragmatic elements in the derivation. An epistemic notion of information is defined in terms of its relat...
In order to enhance the streamflow forecast skill, seasonal/sub-seasonal streamflow forecasts can be post-processed by incorporating new information, such as climate signals. This study proposed a simple yet efficient approach, the “Bivar_updat...
This paper presents a Bayesian-based finite element model updating method that integrates static displacement measurements and dynamic modal data to simultaneously identify structural mass and stiffness parameters. By leveraging Bayesian inference, a...
This study develops a Bayesian parameter identification framework that uses static strain measurements to update pipeline structural models under complex boundary conditions. Because strain responses are directly linked to internal stress states and...
The fatigue reliability assessment of deepwater risers plays an important role in the safety of oil and gas development. Physical-based models are widely used in riser fatigue reliability analyses. However, these models present some disadvantages in...
The practice of the assessment of the safety of existing masonry structures is related to the safety of people’s lives and property. However, the current assessment method, described in “GB50292-2015 Standard for appraisal of reliability...
The paper presents a survey on selected models of opinion dynamics. Both discrete (more precisely, binary) opinion models as well as continuous opinion models are discussed. We focus on frameworks that assume non-Bayesian updating of opinions. In the...
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