Computation-Effective Structural Performance Assessment Using Gaussian Process-Based Finite Element Model Updating and Reliability Analysis

Structural identification (St-Id) using finite element models for optimum sensor configuration and uncertainty quantification

Probabilistic seismic performance assessment of aqueduct structures considering different sources of uncertainty

Effects of changes in the structural parameters of bionic straw sandwich concrete beetle elytron plates on their mechanical and thermal insulation properties

Introduction. Malfunctions of the elements of the fuel injection system lead to a deterioration in the performance of diesel engines. The largest proportion of faults that occur during the operation of battery injection systems are electro-hydraulic injectors. For the timely detection of malfunctions, the injectors are diagnosed. The most accurate determination of the technical condition of the injectors can be made using specialized diagnostic stands with their removal from the engine. As a rule, the diagnosis is a conclusion about the general technical condition of the injector. To ensure high quality and reduce the complexity of repairs, it is necessary to use new methods and tools that allow for in-depth diagnostics of injectors with the identification of specific defects. The purpose of the presented work is to identify possible differences in the change in the set of diagnostic parameters when changing individual structural parameters in order to be able to determine specific defects in injectors during their diagnosis.Materials and methods. The hydrodynamic processes occurring in the electro-hydraulic injector during its operation were described by a system of differential equations of the first order. Numerical experiments were carried out to study the influence of changes in structural parameters on diagnostic parameters. The calculations using the software environment for mathematical calculations Mathcad were carried out. The calculations at different combinations of pressures in the fuel accumulator and the duration of the control pulse corresponding to certain engine operating modes were carried out.Results. The paper presents the graphs of the dependences of the cyclic supply, the average fuel consumption in the drain line, the delay in the start of the needle lift, the duration of the needle lift and landing, the duration of the injection and the sensitivity of these diagnostic parameters on the gaps in the interfaces ‘needle guide spray body’, ‘plunger multiplier – sleeve’, from the magnitude of the leakage of the control valve.Discussion and conclusion. As a result of numerical experiments, differences in the change in the set of diagnostic parameters with a change in individual structural parameters were found.

A method of structural damage identification using harmonic excitation force is presented. It considers the effects of both measurement and modelling errors in the baseline finite element model. Damage that accompanies changes in structural parameters can be estimated for a damaged structure from the change between measured vibration responses and ones calculated from the analytical model of the intact structure. In practice, modelling errors exist in the analytical model due to material and geometric uncertainties and a reduction in the degrees of freedom as well as measurement errors, making identification difficult. To surmount these problems, bootstrap hypothesis testing, which enables statistical judgment without information about these errors, was introduced. The method was validated by numerical simulation using a three-dimensional frame structure and real vibration data for a three-storey steel frame structure. Copyright © 2005 John Wiley & Sons, Ltd.

Energy research of three-adjacent structures connected by Kelvin-type dampers based on power flow

The paper presents the assessment results of changes in the structural, strength and thermal parameters of cer-cer composite ceramics based on oxide compounds to radiation damage caused by high-temperature irradiation with heavy Kr15+ and Xe23+ ions. During the studies conducted, relationships between changes in structural parameters caused by deformation distortion of the crystalline structure and an increase in its volume, with the assessment results of the degradation of strength and thermal parameters, were established. It was determined that an elevation in the irradiation fluence leads to a cumulative effect of degradation of the properties of ceramics, while in the case of irradiation with heavy Xe23+ ions, the effect of structural disordering and degradation of strength and thermal parameters is more pronounced than in the case of irradiation with Kr15+ ions. This phenomenon is caused by differences in the value of ionization losses of incident ions, as well as the size of damaged areas that arise as a result of the interaction of incident ions with the crystalline structure of the damaged layer. At the same time, the most stable to radiation-stimulated softening processes are two-phase Al2O3 – ZrO2 ceramics, in which the presence of interphase boundaries leads to a growth in resistance to softening and destruction under high-dose irradiation. The presence of interphase boundaries acting as barriers that stop the diffusion of point and vacancy defects and reduce the degree of structural disorder of the damaged layer is considered as a mechanism for containing radiation damage in the case of two-phase ceramics.

This article presents a novel strategy for finite element model updating of flexural structures. The method is based on modal parameters extracted from dynamic distributed macro-strain responses. The objective function that comprised low-order modal macro-strain and frequency was established first, while local bending stiffness, density, and boundary conditions of structures can be selected as the design variables. Both numerical simulation and experiment were conducted to verify the effectiveness of the proposed method. The long-gauge macro-strain sensors chosen in this article are first addressed, and the fundamental sensing properties of the macro-strain sensors confirm great dynamic measurement capacity. Simulation and experimental results show that both the local parameter (bending stiffness) and the global parameters (mass density and rotational stiffness of support) can be well identified. Notably, the updated finite element model can predict local response modal macro-strain and global response (frequency and displacement mode) because the local information-sensitive index and global information-sensitive index are included in the objective function. Therefore, the proposed finite element model updating strategy constitutes a new alternative in performance assessment of flexural structures.

The paper discusses non-probabilistic approaches for uncertainty treatment in structure reliability analysis. Based on rough set theory,the uncertain parameters of structures are expressed by rough variables,the structure reliability index is computed by rough function and metric. This new methodology for structural reliability is proved to be valid and efficient using theory analysis and examples of practical application.

13 - A hybrid strategy for parameter identification of plated structures

Optimal condition monitoring, maintenance and management of the existing civil infrastructure have been identified as a critical factor in ensuring and raising the economic productive capacity. Direct in-service structural health monitoring and vibration behaviour measurement data are essential to provide more accurate performance assessment and capacity estimation. The main focus of this special issue, organised by Australian Network of Structural Health Monitoring (ANSHM), is to present recent developments and applications of innovative techniques for structural modelling, structural identification with uncertainties, data interpretation for structural performance prediction and reserve capacity evaluation.

To improve the vibration isolation performance of suspensions, various new structural forms of suspensions have been proposed. However, there is uncertainty in these new structure suspensions, so the deterministic research cannot reflect the performance of the suspension under actual operating conditions. In this paper, a quasi-zero stiffness isolator is used in automotive suspensions to form a new suspension−quasi-zero stiffness air suspension (QZSAS). Due to the strong nonlinearity and structural complexity of quasi-zero stiffness suspensions, changes in structural parameters may cause dramatic changes in suspension performance, so it is of practical importance to study the effect of structural parameter uncertainty on the suspension performance. In order to solve this problem, three suspension structural parameters d0, L0 and Pc0 are selected as random variables, and the polynomial chaos expansion (PCE) theory is used to solve the suspension performance parameters. The sensitivity of the performance parameters to different structural parameters was discussed and analyzed in the frequency domain. Furthermore, a multi-objective optimization of the structural parameters d0, L0 and Pc0 of QZSAS was performed with the mean and variance of the root-mean-square (RMS) acceleration values as the optimization objectives. The optimization results show that there is an improvement of about 8%−10% in the mean value and about 40%−55% in the standard deviation of acceleration (RMS) values. This paper verifies the feasibility of the PCE method for solving the uncertainty problem of complex nonlinear systems, which provide a reference for the future structural design and optimization of such suspension systems.

Effect of size and aspect ratio on structural parameters and evidence of shape transition in zinc oxide nanostructures

Stochastic boundary element method for reliability analysis of plate and beams composite structures

A structural parametric identification strategy based on neural networks algorithms using dynamic macro-strain measurements in time domain from a long-gage strain sensor by fiber optic sensing technique such as Fiber Bragg Grating (FBG) sensor is developed. An array of long-gage sensors is bounded on the structure to measure reliably and accurately macro-strains. By the proposed methodology, the structural parameter of stiffness can be identified. A beam model with known mass distribution is considered as an object structure. Without any eigenvalue analysis or optimization computation, the structural parameter of stiffness can be identified. First an emulator neural network is presented to identify the beam structure in current state. Free vibration macro-strain responses of the beam structure are used to train the emulator neural network. The trained emulator neural network can be used to forecast the free vibration macro-strain response of the beam structure with enough precision and decide the difference between the free vibration macro-strain responses of other assumed structure with different structural parameters and those of the original beam structure. The root mean square (RMS) error vector is presented to evaluate the difference. Subsequently, corresponding to each assumed structure with different structural parameters, the RMS error vector can be calculated. By using the training data set composed of the structural parameters and RMS error vector, a parametric evaluation neural network is trained. A beam structure is considered as an existing structure, based on the trained parametric evaluation neural network, the stiffness of the beam structure can be forecast. It is shown that the parametric identification strategy using macro-strain measurement from long-gage sensors has the potential of being a practical tool for a health monitoring methodology applied to civil engineering structures.