• Proceedings of the Korean Geotechical Society Conference
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• 2001.10b
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• pp.1-18
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• 2001

Recently advanced composite materials have been successfully used in the civil infrastructure application due to its many advantages such as light weight, high strength, corrosion resistance. Demand for longer service life, increased durability and reduced maintenance have prompted such developments. In this article, characteristics of composite materials, fabrication process, case studies for various field and future of advanced composite materials for civil infrastructures is presented.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.641-659
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• 2010

Structural Health Monitoring (SHM) gradually becomes a technique for ensuring the health and safety of civil infrastructures and is also an important approach for the research of the damage accumulation and disaster evolving characteristics of civil infrastructures. It is attracting prodigious research interests and the active development interests of scientists and engineers because a great number of civil infrastructures are planned and built every year in mainland China. In a SHM system the sheer number of accompanying wires, fiber optic cables, and other physical transmission medium is usually prohibitive, particularly for such structures as offshore platforms and long-span structures. Fortunately, with recent advances in technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensor technique has been developing rapidly and is being used gradually in the SHM of civil engineering structures. In this paper, some recent advances in the research, development, and implementation of wireless sensors for the SHM of civil infrastructures in mainland China, especially in Dalian University of Technology (DUT) and Harbin Institute of Technology (HIT), are introduced. Firstly, a kind of wireless digital acceleration sensors for structural global monitoring is designed and validated in an offshore structure model. Secondly, wireless inclination sensor systems based on Frequency-hopping techniques are developed and applied successfully to swing monitoring of large-scale hook structures. Thirdly, wireless acquisition systems integrating with different sensing materials, such as Polyvinylidene Fluoride(PVDF), strain gauge, piezoresistive stress/strain sensors fabricated by using the nickel powder-filled cement-based composite, are proposed for structural local monitoring, and validating the characteristics of the above materials. Finally, solutions to the key problem of finite energy for wireless sensors networks are discussed, with future works also being introduced, for example, the wireless sensor networks powered by corrosion signal for corrosion monitoring and rapid diagnosis for large structures.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1032-1039
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• 2022

Evaluating infrastructure's impact on social equity is an emerging area of research in transportation construction engineering. Transportation agencies have been trying to include sustainable development. The three components of sustainable development are environmental protection, social equity, and economic development. Although social equity is one of the essential components of sustainable development, most transportation agencies do not consider this component. The research publications in this area are limited. The principal objective of this study is to synthesize existing studies related to the impact of transportation infrastructures on social equity. This study will also identify social equity indicators, the correlation between social equity and transportation infrastructures and their services, and the impact of transportation infrastructures' on social equity. In addition, this study will identify current issues of social equity and will provide some recommendations. This synthesis study revealed that transportation infrastructures impacted social equity in various ways. Some effects are positive, such as new job creation on the market. Other effects are adverse, such as diminishing socio-economic and environmental degradation. Studies also showed that the current practices evaluated infrastructures' impact on a case-by-case basis. The authors recommend adopting a multi-disciplinary holistic for assessing infrastructure's effects on social equity. The multi-disciplinary fields of study include civil engineers, construction engineers/managers, public policy researchers, environmentalists, and social scientists.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.725-730
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• 2007

A framework of multi layered database is proposed for the integrated operation of civil infrastructure information in this study. The multi-layered database is a logically integrated database composed of standardized information layers. The framework of multi-layered database is defined by three axes, national assets, lifetime, and data levels. The axis of national assets indicates civil infrastructures such as bridges, dams, tunnels and power plants that can be considered as national key structures. The axes of lifetime and data levels indicate the standardized information layers generated from the life-phase of civil infrastructure and the priority of data in the information layers, respectively. The standardized information layers are basically composed of reusable data sets defined by information models. A prototype of standard database for steel bridges is constructed based on the framework as a proof of concept. Demonstration examples such as data consistency check and automatic generation of a FEA model show that the proposed concept can assure the sustainable interoperability of civil infrastructure information as well as design information of steel bridges.

• Structural Engineering and Mechanics
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• v.25 no.5
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• pp.577-596
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• 2007

Recent development of fiber optic sensor technology has provided an excellent choice for civil engineers for performance monitoring of civil infrastructures. Fiber optic sensors have the advantages of small dimensions, good resolution and accuracy, as well as excellent ability to transmit signal at long distances. They are also immune to electromagnetic and radio frequency interference and may incorporate a series of interrogated sensors multiplexed along a single fiber. These advantages make fiber optic sensors a better method than traditional damage detection methods and devices to some extent. This paper provides a review of recent developments in fiber optic sensor technology as well as some applications of fiber optic sensors to the performance monitoring of civil infrastructures such as buildings, bridges, pavements, dams, pipelines, tunnels, piles, etc. Existing problems of fiber optic sensors with their applications to civil structural performance monitoring are also discussed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.77-86
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• 2017

Industry Foundation Classes(IFC) is the core product schema for ensuring the interoperability of information in Building Information Modeling(BIM) environment. However, since current IFC is mainly focused on building structure. there are limitations in the generation of functional information of components when applied to civil infrastructures. Previous studies have proposed IFC-based new entities for the civil infrastructures, it takes long time to support them in BIM authoring software packages. In this study, we proposed practical rules to apply IFC-based information modeling using BIM authoring software and additional new entities for the civil infrastructure through attributes and information mapping. The availabilities of proposed method were examined using the rail and sleeper information models based on an extended IFC data schema for the railway infrastructures.

• Smart Structures and Systems
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• v.5 no.2
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• pp.173-191
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• 2009

Civil infrastructures are always subjected to various types of hazard and deterioration. These conditions require systematic efforts to assess the exposure and vulnerability of infrastructure, as well as producing strategic countermeasures to reduce the risks. This paper describes the needs for and concept of advanced sensor technologies for risk assessment of civil infrastructure in Japan. Backgrounds of the infrastructure problems such as natural disasters, difficult environment, limited resource for maintenance, and increasing requirement for safety are discussed. The paper presents a concept of risk assessment, which is defined as a combination of hazard and structural vulnerability assessment. An overview of current practices and research activities toward implementing the concept is presented. This includes implementation of structural health monitoring (SHM) systems for environment and natural disaster prevention, improvement of stock management, and prevention of structural failure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.2
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• pp.666-674
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• 2010

There is a few problems in the preliminary seismic performance evaluation procedure of subway infrastructures, such as cut-and-cover tunnel structures and bridge structures, recently because the characteristics of subway infrastructures are not properly considered in the procedure. In particular, the evaluation procedure of vehicular bridge structures is applied to subway bridges without any modification. Moreover, the present evaluation procedure is lack of both theoretical and empirical backgrounds, which makes the evaluation less reliable. This paper presents problems in the existing preliminary evaluation procedure and proposes possible modification(revision) to the procedure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.150-156
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• 2004

Though the concept of Life-Cycle Cost (LCC) itself is not new, its effectiveness for planning, design, rehabilitation and maintenance/management of civil infrastructures is becoming increasingly recognized. For the decision problems as in the case of the LCC of plant facilities, equipments, bridge decks, pavements, etc., the Life-Cycle Cost Analysis (LCCA) is relatively simple, and thus its practical implementation is rather straightforward. However, when it comes to major infrastructures such as bridge, tunnels, underground facilities, etc., the LCCA problem becomes extremely complex because lack of cost data associated with various direct and indirect losses, and the absence of uncertainty data available for the assessment as well. As a result, the LCC studies have been largely limited only to those relatively simple LCCA problems of planning or conceptual design for making decisions. Accordingly, in the recent years, the researchers have pursued extensive studies on the LCC effectiveness mostly related to LCC models and frameworks for civil infrastructures. Moreover, recently the demand on the practical application of LCC effective decisions in design and maintenance is rapidly growing unprecedently in civil engineering practice. Indirction cost is very important on LCC formulation. But that is very difficult and complicate the estimation every LCC. The objective of this paper is to suggest efficient regression model for the estimation of indirect cost approach to the practical application of LCC for the design and rehabilitation of civil. infrastructures considering traffic, traffic network, detour condition, and workzone condition. In this paper, it performed the sensitivity analysis and correlation analysis of parameter for development of regression model of inflection cost.