Structural Safety Analysis Research Articles

A refined empirical model of steady-state downburst based on high-resolution wind speed data obtained from wind tunnel tests

A slice of research pertinent to the analytical or empirical models of downburst winds was available, but the current validation was usually based on sampled wind velocities at several typical positions in the experimental measurements rather than the whole-flow domain information. Therefore, the capability of existing analytical or empirical models to reproduce the whole development of downbursts at different stages remains questionable. This paper aims to refine the empirical model of downbursts based on high-resolution wind speed data obtained from wind tunnel tests, which renders the well-established empirical model to simulate the maximum wind speed of the vortex ring and to obtain the more accurate wind profiles in the outflow regime. To overcome the bottleneck problem that lay in the lack of experimental results for whole-flow domain information, a comprehensive experimental study based on the impinging jet simulator was conducted and the spatial variations of downburst winds were systematically measured. Then, the empirical model considering the nonlinear growth of boundary layer thickness is refined according to the experimental results, so that two new empirical functions, which could rationally represent the spatial variation of horizontal wind velocities in the whole-flow domain, have been proposed. The refined empirical model can be used to facilitate the safety analysis of structures and buildings under downburst winds with a higher confidence level.

Inversion study of dam incidence angle under oblique incidence of seismic waves

Determination of seismic wave incidence angle is a critical step in performing seismic oblique incidence analysis of dams. However, for structures with complex dynamic responses, such as dams, it is difficult to derive the incident angle by traditional mathematical methods. For this reason, this paper proposes a method for determining the seismic wave incidence angle based on the dynamic response of the dam. The model calculates the dynamic response of the dam under different incidence angles of seismic waves, establishes the mapping relationship between the dynamic response and the incidence angle by using a hybrid particle network, and performs feature screening to obtain the optimal inversion features by the SHAP method, and then constructs the optimal inversion model. The results show that there is a significant correlation between the dynamic response of the dam body and the incident angle, the correlation coefficients of the model are all greater than 0.96, and the average absolute percentage errors are less than 5 %, which proves that the model can effectively invert the incident angle. The method can also be applied to the seismic safety analysis of other structures, providing a new way to determine the seismic wave incidence angle.

Analysis of Structural Safety of Structures when Accounting Processes of Progressive Destruction

Analysis of Structural Safety of Structures when Accounting Processes of Progressive Destruction

Structural safety and failure analysis of buried jointed high-density polyethylene corrugated pipelines subjected to blast vibration

The reliability of buried jointed high-density polyethylene (HDPE) corrugated pipelines under urban blast vibration loading needs to be emphasized. This study combines field blasting tests on directly buried single-section pipelines and numerical simulations to investigate the mechanical performance of jointed HDPE corrugated pipelines under complex blasting conditions. Intelligent prediction models based on genetic algorithm (GA), particle swarm optimization (PSO), and white shark optimization (WSO) combined with extreme learning machine (ELM) are proposed, namely GA-ELM, PSO-ELM, and WSO-ELM models, respectively. The numerical model is established using the orthogonal experimental principle to supplement the predicted sample data. By comparing the predictions of RPPV (resultant peak particle velocity) and RPPD (resultant peak particle displacement) for the pipelines under various working conditions using the four optimized ELM models, the results indicate that the WSO-ELM model is the best intelligent model for predicting the pipeline response characteristics. By combining the pipeline deflection criterion with the WSO-ELM prediction model, adjustments to the field blast parameters can be made to ensure the safety of the pipeline while improving construction efficiency.

Multilayer heterostructure inhomogeneous model for the functionally graded spherical shell with rotation effect for arbitrarily varying material properties

With the development of functionally graded materials (FGMs) composite technology, structural safety analysis related to FGMs has been widely concerned. An innovative multilayer heterostructure power-law inhomogeneous (MHPI) model is taken to solve the rotating FGMs hollow spherical shell with arbitrarily varying material properties (elastic modulus and density) along the radial direction. The basic idea of MHPI model is that the rotating FGMs spherical shell is divided into multiple sublayers, and two power functions approximate the elastic modulus and density of each sublayer respectively. For each single sublayer, the analytical solutions include two undetermined constants, which can be obtained from the boundary and continuity conditions. Many numerical examples of the rotating FGMs spherical shell are discussed, involving seven property profiles gradient laws assumptions, three boundary conditions, and nine volume fraction gradient models. Finally, this study further discusses the rotating FGMs spherical shell optimization design. The greatest advantage of this study is that the elastic response of the rotating FGMs spherical shell under various gradient assumptions is completely discussed. The numerical results show that the MHPI model can solve the problem of circumferential stress oscillation well and have good convergence and high accuracy. For many numerical examples, the error of the MHPI model results is about 5‰ when sublayer number reaches 15.

A mixed uncertain structural reliability analysis method considering random and convex set variables with correlation

AbstractIn this paper, a mixed model reliability analysis method is put forward for the problem of assessing the reliability of complex engineering structures containing both random and convex aggregate variables. By integrating the ellipsoidal model with correlation and the interval model, the uncertainty region characterized by the ellipsoidal model with correlation is optimized with full consideration of the limited amount of engineering structure sample data, and the risk region represented by the reliability model is redefined, a new mixed reliability assessment criterion is established, and the minimum safe nonprobability reliability index of the structure is built. A key reference is offered by the safety limit diagram of constant reliability indexes set for the first time for the optimal design of engineering structure reliability. The proposed mixed reliability model is compared and analyzed with three classical models. The sensitivity of nonprobability reliability indexes, influenced by random variable parameters and correlation coefficients, is analyzed. This verification confirms that the new reliability model not only provides an accurate assessment of engineering structures' reliability but also lowers the computational demands of engineering design. In this paper, aero‐engine blades and wind turbine blades are taken as examples to expound the validity of the reliability model built using this method and its importance to the structural safety analysis of actual engineering.

Seismic Safety Analysis of Dam Appurtenant Structures in Northern Thailand

Seismic Safety Analysis of Dam Appurtenant Structures in Northern Thailand

A new method for long-term safety analysis of marine structures

This paper proposes to utilise a new adaptive kernel density estimation (KDE) method based on a linear diffusion process for fitting the significant wave height data in order to calculate the sea state parameter distribution tails more accurately, particularly the higher, more extreme values. The accuracy of the proposed method has been demonstrated based on fittings to two measured ocean wave datasets. This proposed method has subsequently been utilised for deriving accurate 50-year and 500-year environmental contour lines. The advantages of using a more reliable contour line derived from using the proposed new method for long-term safety analysis of marine structures have been substantiated.

Determination of Multiple-target Equivalent Static Wind Load of Large-span Roof Structures based on Clustering Analysis Techniques

Spatial structures in modern society exhibit a city’s distinguishing features and show its strength in building technology. Large-span roof structures are mostly seen among spatial structures for various activities. Large-span roof structures are usually sensitive to wind loads due to their lightness in materials and curved geometric appearance. However, spatial structures are generally designed with many structural members, making it challenging to determine adequate load distributions for structural safety analysis. This paper intends to introduce the concept of the multiple-target equivalent static wind loads and to demonstrate how to reduce the heavy computational burden when the structural designer needs to consider multiple loading effects of the target structure. The wind tunnel test of an elliptical-shaped stadium structure with a flat roof is first conducted to show the fundamental aerodynamic characteristics. The methodologies of the background-component wind force based on the load-response-correlation (LRC) method and the resonant-component wind force based on the inertial force method are then introduced for the specification of single-target equivalent static wind loads. Finally, the clustering analysis technique is adopted to explain the concept of the multiple-target equal static wind loads. A decay index is proposed to indicate how the clustering technique improves the specification of equivalent static wind loads.

Developing data science for structural safety analysis and pre- warning in civil engineering

The development of data science in civil engineering has benefited from the rapid advances in sensor technology as well as data acquisition and storage. In contrast to traditional analysis and evaluation based on periodic inspection and full-scale test, the structural safety analysis and pre-warning can be achieved directly through the analysis of the design data of the newly built bridge and the monitoring data & test data of the bridge in service. Specifically, structural geometric data (length and cross-sectional area etc.), physical response data like displacement and stress, and vibration response data, such as acceleration and frequency, as well as the influence of the environment, e.g., temperature and humidity, must all be taken into account. Furthermore, the different sensitivity of different response data, which in turn affects structural safety analysis and pre-warning accuracy, is one of the current frontier sciences, i.e., the problem of multi-source (different response) data. It is expected that the development of data science will have very important theoretical research value and engineering practice significance for safety analysis and pre-warning in civil engineering, and is expected to bring new prospects for academia and industry.

Bayes Inference of Structural Safety under Extreme Wind Loads Based upon a Peak-Over-Threshold Process of Exceedances

In the present paper, the process of estimating the important statistical properties of extreme wind loads on structures is investigated by considering the effect of large variability. In fact, for the safety design and operating conditions of structures such as the ones characterizing tall buildings, wind towers, and offshore structures, it is of interest to obtain the best possible estimates of extreme wind loads on structures, the recurrence frequency, the return periods, and other stochastic properties, given the available statistical data. In this paper, a Bayes estimation of extreme load values is investigated in the framework of structural safety analysis. The evaluation of extreme values of the wind loads on the structures is performed via a combined employment of a Poisson process model for the peak-over-threshold characterization and an adequate characterization of the parent distribution which generates the base wind load values. In particular, the present investigation is based upon a key parameter for assessing the safety of structures, i.e., a proper safety index referred to a given extreme value of wind speed. The attention is focused upon the estimation process, for which the presented procedure proposes an adequate Bayesian approach based upon prior assumptions regarding (1) the Weibull probability that wind speed is higher than a prefixed threshold value, and (2) the frequency of the Poisson process of gusts. In the last part of the investigation, a large set of numerical simulations is analyzed to evaluate the feasibility and efficiency of the above estimation method and with the objective to analyze and compare the presented approach with the classical Maximum Likelihood method. Moreover, the robustness of the proposed Bayes estimation is also investigated with successful results, both with respect to the assumed parameter prior distributions and with respect to the Weibull distribution of the wind speed values.

Structural analysis and optimization of steel truss bridge based on finite element method

In view of the defects of the current mainstream structural safety analysis method of Truss bridge, the safety analysis method at the component level should be further developed. Therefore, it is necessary to carry out the overall safety analysis and structural optimization at the structural level. Based on the concrete data of the actual steel truss beam bridge, this paper uses ABAQUS and MIDAS finite element software to model the truss structure. First of all, the static analysis is carried out, and then the structural analysis and optimization of the steel truss beam bridge is carried out with the elastic modulus reduction method. Based on the linear elastic finite element method, the bearing state of each component is solved, and the ultimate bearing capacity of the whole structure is calculated iteratively. Thus, the limitation of incremental nonlinear finite element method is overcome, and higher calculation accuracy and efficiency are realized.

Experimental investigation of failure modes and ultimate strength of GFRP structure members under longitudinal compression

Due to the higher strength and lightweight of glass fiber reinforced polymer (GFRP), its application in ship structures is becoming increasingly prevalent. However, the mechanical properties of GFRP are affected by many factors, such as fabrication techniques and structural connection designs. The true safety margin of the GFRP structure is necessary to investigate in engineering applications. This study carries out experimental investigations of the ultimate strength and failure modes for three typical GFRP structural members, including stringer, longitudinal stiffener and hard corner, which constitute the cross section of the hull girder. The three kinds of structure members exhibit different failure modes: the stringer exhibits yielding failure, the longitudinal stiffener exhibits buckling and interlayer delamination, and the hard corner presents buckling and debonding. Finally, the finite element analysis is validated by the experimental results to assess the ultimate strength of the GFRP structure. The foam core effectively enhances the structural strength of the stringer and longitudinal stiffener, while the hard corners require a change in the connection method to increase the connection strength. The conclusions can be used as guidance for safety analysis of GFRP structures in ships.

Reducing inconsistencies of FAHP in structural safety assessment of diversion tunnels

The Fuzzy Analytic Hierarchy Process (FAHP) is an effective method for assessing risks and has great potential for assessing the structural safety of diversion tunnels. However, this type of professional assessment can become more complicated due to the presence of multiple factors that influence the safety of the tunnel. This complexity not only necessitates the establishment of a comprehensive index system but also introduces uncertainties related to inconsistencies in expert judgments and unknown expert weights in group decision-making process. To address these issues, this study proposed an improved FAHP method for the structural safety assessment of diversion tunnels. This method incorporates a proposed comprehensive index system and incorporates a preceding ordering process before pairwise comparisons in the questionnaire to enhance the consistency in expert judgment. The consistency and compatibility of expert judgment matrices are quantified using a distance vector rather than a single number, and a reasonable comprehensive weight is calculated based on the Dempster–Shafer (D–S) evidence theory. We applied this method to the structure safety assessment of the Houziyan hydropower station diversion tunnel and found an overall low risk for the tunnel, but significant issues were identified regarding lining crack. Furthermore, we conducted a comparative evaluation of the proposed method against other related methods, thereby demonstrating its high quality. The study contributes an improved FAHP method for the structural safety analysis of diversion tunnels and encourages the wider application of FAHP in more complicated systems.

A Review on Wind Speed Extreme Values Modeling and Bayes Estimation for Wind Power Plant Design and Construction

Rapid growth of the use of wind energy calls for a more careful representation of wind speed probability distribution, both for identification and estimation purposes. In particular, a key point of the above identification and estimation aspects is representing the extreme values of wind speed probability distributions, which are of great interest both for wind energy applications and structural tower reliability analysis. The paper reviews the most adopted probability distribution models and estimation methods. In particular, for reasons which are properly discussed, attention is focused on the evaluation of an opportune “safety index” related to extreme values of wind speeds or gusts. This topic has gained increasing attention in recent years in both wind energy generation assessment and also in risk and structural reliability and safety analysis. With regard to wind energy generation, there is great sensitivity in the relationship between wind speed extreme upper quantiles and the corresponding wind energy quantiles. Concerning the risk and reliability analysis of structures, extreme wind speed value characterization is useful for a proper understanding of the destructive wind forces that may affect structural tower reliability analysis and, consequently, the proper choice of the cut off wind speed value; therefore, the above two kinds of analyses are somewhat related to each other. The focus is on the applications of the Bayesian inference technique for estimating the above safety index due to its effectiveness and usefulness.

Integrating Energy-Based Limit State Functions to Optimize Target Reliability of Bridge Pile for Seismic Events

The target reliability index is a safety and economic measure used to stipulate the optimal reliability level for structural elements. The conventional load and resistance factor design (LRFD) philosophy is premised on limit state functions that ignore structural performance by disregarding the structural stored energy capacity. Indeed, two significant concerns have yet to be adequately addressed within structural failure and safety analysis. The first pertains to the careful consideration of failure modes. The second involves the relationship between target reliability and hazard intensity. The main goal of this research is to propose a new energy-based limit state function to incorporate the performance-based design and LRFD philosophies concerning the target reliability of bridge substructure systems, including piles. The proposed energy-based limit state function can thoroughly examine a structure’s behavior in the presence of a natural disaster. This study’s reliability analysis corresponds to the seismic performance levels. The elastic and plastic energy resistance of pile elements is quantified concerning the various performance levels subjected to the loading scenarios. The uncertainties of soil and structural resistance and the structure’s dynamic response are considered and a new energy-based limit state function established. To validate the proposed limit state function, several finite element method models are examined to capture the probability energy distribution for structural resistance and loading conditions. Finally, the structural target reliability indices for the bridge piles are delineated using the proposed optimization approaches.

BIM–based time-varying system reliability analysis for buildings and infrastructures

In recent decades, building information modelling (BIM) technology has been rapidly developed and applied widely in the building industry. Although BIM technology is crucial for the whole design, construction, operation, and maintenance life cycle of building structures, BIM-based infrastructure time effect analysis still has limitless potential. Nevertheless, the current BIM-based study on time effect focuses mostly on cost and schedule analyses for buildings. The assessment of infrastructure places greater emphasis on component level evaluation and ignores how components affect system safety. In this paper, a BIM-reliability integrated technology for time-varying and system analysis of structural safety is developed. In the developed framework, parameters information for calculating component reliability are first extracted from the BIM model. The BIM model is then transformed into a topology structure and based on the transformed structure, the risk assessment is conducted through stochastic approaches. The suggested framework is demonstrated using two different cases: a long-term corrosion impact analysis example of an underground pipeline network and a short-term seismic load analysis instance of a four-layer frame. In the short-term analysis, the structural analysis is performed by integrating REVIT-Dynamo and OpenSees, taking into account the randomness of the material properties and the fabrication size. The design optimization can be carried out by comparing the reliability of inter-storey displacement under seismic load in different design schemes, and the system failure probability is more sensitive to the changes in the failure probability of each floor. In the long-term analysis, the time-varying reliability and importance index of each pipe during its lifetime are calculated using the transformed topology algorithm and the stochastic corrosion model. It is found that the BIM-reliability integrated technology can effectively evaluate the impact of time effect on the safety of the structures and is of great significance for structures with unknown working environment and working conditions.

Fiber Optic Sensing Technology and Vision Sensing Technology for Structural Health Monitoring.

Structural health monitoring is currently a crucial measure for the analysis of structural safety. As a structural asset management approach, it can provide a cost-effective measure and has been used successfully in a variety of structures. In recent years, the development of fiber optic sensing technology and vision sensing technology has led to further advances in structural health monitoring. This paper focuses on the basic principles, recent advances, and current status of applications of these two sensing technologies. It provides the reader with a broad review of the literature. It introduces the advantages, limitations, and future directions of these two sensing technologies. In addition, the main contribution of this paper is that the integration of fiber optic sensing technology and vision sensing technology is discussed. This paper demonstrates the feasibility and application potential of this integration by citing numerous examples. The conclusions show that this new integrated sensing technology can effectively utilize the advantages of both fields.

Structural Safety Analysis of Battery Housing for Electric Vehicles According to the Horizontal Cross-Member Structure

Structural Safety Analysis of Battery Housing for Electric Vehicles According to the Horizontal Cross-Member Structure

Structural failure assessment system exemplified by dumbbell-shaped CFST arch

The study of structural failure law is the basis of structural safety assessment, but engineering structures present complex nonlinearities and diversity, which make it difficult to analyze the failure laws of structures. However, the failure of ductile structure is a process of quantitative cumulation to qualitative change, and this turning point is the key to structural failure analysis. Based on this view, we propose a new system for structural failure assessment, which includes the identification of mutation locations, strain data visualization, structural internal force estimation, and finite element stochastic simulation, etc. Moreover, every new method is compared and validated. Experimental data of a dumbbell CFST arch model are used throughout the paper for illustration. Finally, the time-varying failure probability of the whole structure is evaluated. In summary, this paper organically combines experiment, simulation and engineering practice to provide a new approach to structural safety analysis, structural health monitoring and structural design.