Prediction Of Structural Damage Research Articles

Construct validity and reliability of ultrasound disease activity score in assessing joint inflammation in RA: comparison with DAS-28

To investigate the construct validity and reliability of US DAS compared with 28-joint DAS (DAS-28) in assessing joint inflammation and in prediction of structural damage in patients with RA. Ninety patients with active RA were prospectively recruited and followed up during the 6 months of treatment. The patients underwent clinical, laboratory and X-ray assessment, along with blinded power Doppler US (PDUS) and grey-scale (GS) US (GSUS) examination at baseline and 6 months. A subgroup of 25/90 randomly assigned patients underwent MRI examination of their hands at baseline. A PDUS examination of 22 joints and GSUS examination for effusion/hypertrophy (E/H) of 28 joints were performed by two independent examiners, blinded to clinical findings. E/H was qualitatively assessed as absent or present, and PD signal was semi-quantitatively graded from 0 to 3. PDUS score for synovitis in 22 joints and GS score for E/H in 28 joints were included in US DAS calculation. Clinical scoring, PDUS and GSUS inter-observer reliability were evaluated. Strong correlation was found between US DAS and standard assessment of disease activity such as the DAS-28, ESR and CRP levels. Correlation between US DAS and patients' and physicians' visual analogue scale of activity was moderate, whereas correlations of US DAS with Health Assessment Questionnaire - Disability Index (HAQ-DI) and Short Form 36 Health Survey (SF-36) were weak to moderate. US DAS correlated with X-ray, MRI and US parameters and rates of joint damage. US DAS better anticipated future joint damage than standard DAS-28.

Vibration-Based Damage Identification Method Using Modified Back-Propagation Neural Networks

This paper presents a damage detection method using a combination of global (changes in natural frequencies) and local (displacement mode shapes) vibration-based analysis data as input in neural networks for location and severity prediction of structural damage. The necessary features for damage detection have been selected by performing sensitivity analyses. In order to check the robustness of the input used in the analysis and to simulate the numberical errors, artificial random noise has been generated numerically and added to noise-free data during the training of the neural networks. Furthermore, a modified back-propagation neural networks with the dynamic steepest descent (DSD) algorithm as training algorithm is used to improve the training efficiency. With those as basis, the neural networks can assess damage condition (locaiton and severity) with very good accuracy.

Energy Infrastructure Damage Analysis for Hurricane Rita

In 2005, Hurricane Rita caused significant damage to the in the Gulf of Mexico region. In the context of this investigation, the energy infrastructure refers to the offshore oil platforms, refineries, and gasoline supply stations in the region, often referred to as the petroleum infrastructure, the natural gas supply lines, and the delivery of electric power. In this paper, we examine the structural damage to the networks as defined by restoration, resilience, and fragility with a focus on the analysis of the electric power delivery disruptions. Our concern is not on the evaluation of risk, but rather to provide those who assess hurricane risk with relevant structural damage prediction models. We provide correlations of hurricane wind speed data with outages. We conclude that high winds alone can create significant damage to the system.

Review and Recommendations for Lifeline Recovery and Reconstruction

In the Great Hanshin Earthquake, the severing of lifelines – utilities and infrastructures systems – heavily inconvenienced victims and caused serious rifts in emergency activities and medical and firefighting operations right after the earthquake, all of which are critical to life. We review lifelines in terms of damage, recovery that took almost three months, and reconstruction taking 10 years, and recommend ordinary and emergency actions, including reinforcement of frameworks for emergencies, structural damage prediction, and the preparation of improvement guidelines.

Inverse damage prediction in structures using nonlinear dynamic perturbation theory

A non-linear perturbation theory which furnishes an exact relationship between the perturbation of structural parameters and the perturbation of modal parameters is presented. A system of governing equations is derived, where the information about incomplete modal data can be directly adopted. The Direct Iteration and the Gauss–Newton Least Squares techniques for an inverse prediction of structural damage are discussed, where both the location and the extent of structural damage can be correctly determined using only a limited amount of incomplete modal measurements data. Structural damage is assumed to be associated with a proportional reduction of the original element stiffness matrix or with a proportional reduction of the contribution of a Gauss point to the element stiffness matrix, which characterises a structure at an element level or at a Gauss point level. Finally, a damaged cantilever beam is considered using different model problems to demonstrate the effectiveness of the proposed techniques.

Assessment of damage in continuum structures based on incomplete modal information

An identification technique based on the characteristic equations for structural dynamic systems is developed to assess damage in continuum structures, where the information about incomplete modal data can be directly utilised. The structural damage model is assumed to be associated with a reduction of a contribution to the element stiffness matrix emanating from a given Gauss point, equivalent to a scalar reduction of the material modulus, which characterises material at the Gauss point level. The incomplete mode shapes for the damaged structure can be expanded into complete mode shapes by using the actual measured modal readings and assuming the unknown modal data for the remaining dimension. A computational technique based on the Gauss–Newton Least Squares technique is developed for the inverse prediction of structural damage, where both the location and the extent of structural damage can be correctly determined using only a limited amount of measurements of incomplete modal data. Finally, numerical examples for continuum structures, restricted here to a plane stress model problem and plate bending model problem, are utilised to demonstrate the effectiveness of the proposed approach.

Development of response spectra techniques for prediction of structural damage from open-pit blasting vibrations : Walker, S; Young, P A; Davey, P M Trans Inst Min Metall (Sect A Min Ind), V91, April 1982, PA55–A62

Development of response spectra techniques for prediction of structural damage from open-pit blasting vibrations : Walker, S; Young, P A; Davey, P M Trans Inst Min Metall (Sect A Min Ind), V91, April 1982, PA55–A62