• Smart Structures and Systems
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• v.31 no.4
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• pp.311-323
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• 2023

Ever since ancient times, earthquakes have been a major threat to the civil infrastructures and the safety of human beings. The majority of casualties in earthquake disasters are caused by the damaged civil infrastructures but not by the earthquake itself. Therefore, the efficient and accurate post-earthquake assessment of the conditions of structural damage has been an urgent need for human society. Traditional ways for post-earthquake structural assessment rely heavily on field investigation by experienced experts, yet, it is inevitably subjective and inefficient. Structural response data are also applied to assess the damage; however, it requires mounted sensor networks in advance and it is not intuitional. As many types of damaged states of structures are visible, computer vision-based post-earthquake structural assessment has attracted great attention among the engineers and scholars. With the development of image acquisition sensors, computing resources and deep learning algorithms, deep learning-based post-earthquake structural assessment has gradually shown potential in dealing with image acquisition and processing tasks. This paper comprehensively reviews the state-of-the-art studies of deep learning-based post-earthquake structural assessment in recent years. The conventional way of image processing and machine learning-based structural assessment are presented briefly. The workflow of the methodology for computer vision and deep learning-based post-earthquake structural assessment was introduced. Then, applications of assessment for multiple civil infrastructures are presented in detail. Finally, the challenges of current studies are summarized for reference in future works to improve the efficiency, robustness and accuracy in this field.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.51-69
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• 2016

Monitoring the performance and estimating the remaining useful life of aging civil infrastructure in the United States has been identified as a major objective in the civil engineering community. Structural health monitoring has emerged as a central tool to fulfill this objective. This paper presents a review of the major structural monitoring programs that have been recently implemented in the United States, focusing on the integrity and performance assessment of large-scale structural systems. Applications where response data from a monitoring program have been used to detect and correct structural deficiencies are highlighted. These applications include (but are not limited to): i) Post-earthquake damage assessment of buildings and bridges; ii) Monitoring of cables vibration in cable-stayed bridges; iii) Evaluation of the effectiveness of technologies for retrofit and seismic protection, such as base isolation systems; and iv) Structural damage assessment of bridges after impact loads resulting from ship collisions. These and many other applications show that a structural health monitoring program is a powerful tool for structural damage and condition assessment, that can be used as part of a comprehensive decision-making process about possible actions that can be undertaken in a large-scale civil infrastructure system after potentially damaging events.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.10-24
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• 2015

This study introduces a fatigue assessment procedure using mesh-insensitive structural stress method based on the Common Structural Rules for Bulk Carriers by considering important factors, such as mean stress and thickness effects. The fatigue assessment result of mesh-insensitive structural stress method have been compared with CSR procedure based on equivalent notch stress at major hot spot points in the area near the ballast hold for a 180 K bulk carrier. The possibility of implementing mesh-insensitive structural stress method in the fatigue assessment procedure for ship structures is discussed.

• Geomechanics and Engineering
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• v.28 no.6
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• pp.573-584
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• 2022

Water inrush may occur during seaside urban tunnel excavation. Various factors affect the water inrush, and the water inrush mechanism is complex. In this study, nine evaluation indices having potential effects on water inrush were analysed. Specifically, the geographic and geomorphic conditions, unfavourable geology, distance from the tunnel to sea, strength of the surrounding rock, groundwater level, tidal action, cyclical footage, grouting pressure, and grouting reinforced region were analysed. Furthermore, a two-step interval risk assessment method for water inrush management during seaside urban tunnel excavation was developed by a multi-index system and interval risk assessment comprised of an interval analytic hierarchy process, fuzzy comprehensive evaluation, and relative superiority analysis. The novel assessment method was applied to the Haicang Tunnel successfully. A preliminary interval risk assessment method for water inrush was performed based on engineering geological conditions. As a result, the risk level fell into a risk level IV, which represents a section with high risk. Subsequently, a secondary interval risk assessment method was performed based on engineering geological conditions and construction conditions. The risk level of water inrush is reduced to a risk level II. The results agreed with the current tunnel situation, which verified the reliability of this approach.

• Geomechanics and Engineering
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• v.9 no.1
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• pp.57-81
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• 2015

Water inrush and mud outburst always restricts the tunnel constructions in mountain area, which becomes a major geological barrier against the development of underground engineering. In view of the complex disaster-causing mechanism and difficult quantitative predictions of water inrush and mud outburst, several theoretical methods are adopted to realize dynamic assessment of water inrush in the progressive process of tunnel construction. Concerning both the geological condition and construction situation, eleven risk factors are quantitatively described and an assessment system is developed to evaluate the water inrush risk. In the static assessment, the weights of eight risk factors about the geological condition are determined using Analytic Hierarchy Process (AHP). Each factor is scored by experts and the synthesis scores are weighted. The risk level is ultimately determined based on the scoring outcome which is derived from the sum of products of weights and comprehensive scores. In the secondary assessment, the eight risk factors in static assessment and three factors about construction situation are quantitatively analyzed using fuzzy evaluation method. Subordinate levels and weight of factors are prepared and then used to calculate the comprehensive subordinate degree and risk level. In the dynamic assessment, the classical field of the eleven risk factors is normalized by using the extension evaluation method. From the input of the matter-element, weights of risk factors are determined and correlation analysis is carried out to determine the risk level. This system has been applied to the dynamic assessment of water inrush during construction of the Yuanliangshan tunnel of Yuhuai Railway. The assessment results are consistent with the actual excavation, which verifies the rationality and feasibility of the software. The developed system is believed capable to be back-up and applied for risk assessment of water inrush in the underground engineering construction.

• Structural Engineering and Mechanics
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• v.89 no.4
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• pp.399-409
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• 2024

Assessment of existing concrete bridges is a challenge for owners. It has greater economic impact when compared to designing new bridges. When using conventional linear analyses, judgment of the engineer is required to understand the behavior of redundant structures after the first element in the structural system reaches its ultimate capacity. The alternative is to use a predictive tool such as advanced nonlinear finite element analyses (ANFEA) to assess the overall structural behavior. This paper proposes a new reliability framework for the assessment of existing bridge structures using ANFEA. A general framework defined in previous works, accounting for material uncertainties and concrete model performance, is adapted to the context of the assessment of existing bridges. A "shifted" reliability problem is defined under the assumption of quasi-deterministic dead load effects. The overall exercise is viewed as a progressive pushover analysis up to structural failure, where the actual safety index is compared at each event to a target reliability index.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.5
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• pp.435-444
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• 2011

This paper deals with the structural assessment of metallic and non-metallic stiffened/monocoque plated marine structures under a lateral pressure load to identify appropriate combination of material and section configuration, especially at the preliminary marine structural design stage. A generic rectangular plated structure is exemplified from the metallic superstructure of a marine vessel and its structural topology is varied for the structural assessment. In total 13 different structural topologies are proposed and assessed using appropriate elastic solutions in conjunction with a set of stress and deflection limits obtained from practice. The geometry dimensions and weights of the structural topologies are calculated, and subsequently, the costs of the materials used in the structural topologies are reviewed to discuss the cost-effectiveness of the materials. Finally, conclusions are made with the aim of suggesting suitable structural topology for the marine structural member considered in this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.161-168
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• 2004

This study describes the behavior and failure probability of basic structural member in case of fire for the research of safety assessment on onshore structure. Fire safety assessment can be done by comparing fire resistance of members with fire severity of heat load For more Practical applications, the commercial structural analysis program is linked with the in-house code and gets the limiting temperature by analyzing structural strength of member with elasto-plastic analysis and large deflection analysis. AFOSM method is utilized to obtain the failure probability against the fire. The examples of rather simple structures such as beams and plates are applied to explain and verify the procedure of fire safety assessment.

• Smart Structures and Systems
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• v.6 no.2
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• pp.135-146
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• 2010

This paper presents the perspective of the Structural Mechanics program of the Air Force Office of Scientific Research (AFOSR) on the damage assessment of structures for the period 2006-2009 when the author was serving as Program Manager at AFOSR. It is found that damage assessment of structures plays a very important role in assuring the safety and operational readiness of US Air Force fleet. The current fleet has many aging aircraft, which poses a considerable challenge for the operators and maintainers. The nondestructive evaluation technology is rather mature and able to detect damage with considerable reliability during the periodic maintenance inspections. The emerging structural health monitoring methodology has great potential, because it will use on-board damage detection sensors and systems, will be able to offer on-demand structural health bulletins. Considerable fundamental and applied research is still needed to enable the development, implementation, and dissemination of structural health monitoring technology.

• Smart Structures and Systems
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• v.24 no.3
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• pp.319-332
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• 2019

Structural health monitoring (SHM) is of great importance to super high-rise buildings. The Shanghai Tower is currently the tallest building in China, and a complete SHM system was simultaneously constructed at the beginning of the construction of the tower. Due to the variety of sensor types and the large number of measurement points in the SHM system, an online automatic structural health assessment method with few computations and no manual intervention is needed. This paper introduces a structural health assessment method for the Shanghai Tower that uses the coefficients of an autoregressive (AR) time series model as structural state indicators. An analysis of collected data indicates that the coefficients of the AR model are affected by environmental factors, and the principal component analysis method is used to remove the influence of environmental factors. Finally, the control chart method is used to track the changes in structural state indicators, and a plan for online automatic structure health state evaluation is proposed. This method is applied to long-term acceleration and inclination data from the Shanghai Tower and successfully identifies the changes in the structural state. Overall, the structural state indicators of the Shanghai Tower are stable, and the structure is in a healthy state.