Building Resilience in Civil Infrastructure Systems: System-Level Biomimicry to Address Complex Managerial Challenges

The transcendent technologies include nanotechnology, microelectronics, information technology and biotechnology as well as the enabling and supporting civil infrastructure systems and materials. These technologies are the primary drivers of the twenty first century and the new economy. Mechanics and materials are essential elements in all of the transcendent technologies. Research opportunities, education and challenges in mechanics and materials, including nanomechanics, carbon nano-tubes, bio-inspired materials, coatings, fire-resistant materials as well as improved engineering and design of materials are presented and discussed in this paper.

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Signal Processing for Sensing and Monitoring of Civil Infrastructure Systems

Intelligent Sensor Networks ◽

10.1201/b14300-14 ◽

2012 ◽

pp. 267-304 ◽

Cited By ~ 2

Author(s):

Mustafa Gul ◽

F. Necati Catbas

Keyword(s):

Signal Processing ◽

Civil Infrastructure ◽

Infrastructure Systems

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Adaptive decision-making for civil infrastructure systems and communities exposed to evolving risks

Structural Safety ◽

10.1016/j.strusafe.2018.05.001 ◽

2018 ◽

Vol 75 ◽

pp. 1-12 ◽

Cited By ~ 5

Author(s):

Ji Yun Lee ◽

Henry V. Burton ◽

David Lallemant

Keyword(s):

Decision Making ◽

Civil Infrastructure ◽

Infrastructure Systems ◽

Adaptive Decision Making

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Knowledge Management in Civil Infrastructure Systems

Encyclopedia of Communities of Practice in Information and Knowledge Management ◽

10.4018/978-1-59140-556-6.ch049 ◽

2011 ◽

pp. 286-292

Author(s):

Hyung Seok Jeong ◽

Dolphy M. Abraham ◽

Dulcy M. Abraham

Keyword(s):

Knowledge Management ◽

Social Issues ◽

Modern Society ◽

Well Being ◽

Data Availability ◽

Civil Infrastructure ◽

Research And Practice ◽

Infrastructure Systems ◽

Conflicting Objectives ◽

Oil Gas

This article reviews current research and practice of knowledge management (KM) in the management of Civil infrastructure systems. Civil infrastructure systems, such as energy systems (electric power, oil, gas), telecommunications, and water supply, are critical to our modern society. The economic prosperity and social well being of a country is jeopardized when these systems are damaged, disrupted, or unable to function at adequate capacity. The management of these infrastructure systems has to take into account critical management issues such as (Lemer, Chong & Tumay, 1995): • the need to deal with multiple, often conflicting objectives; • the need to accommodate the interests of diverse stakeholders; • the reliance of decision making on uncertain economic and social issues; • the constraints in data availability; and • the limitations posed by institutional structure.

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Spatially dependent flood probabilities to support the design of civil infrastructure systems

Hydrology and Earth System Sciences ◽

10.5194/hess-23-4851-2019 ◽

2019 ◽

Vol 23 (11) ◽

pp. 4851-4867 ◽

Cited By ~ 1

Author(s):

Phuong Dong Le ◽

Michael Leonard ◽

Seth Westra

Keyword(s):

Flood Risk ◽

Integrated Approach ◽

Design Flow ◽

Civil Infrastructure ◽

Infrastructure Systems ◽

Railway Infrastructure ◽

Single Location ◽

System Risk ◽

Intensity Duration Frequency ◽

Evacuation Routes

Abstract. Conventional flood risk methods typically focus on estimation at a single location, which can be inadequate for civil infrastructure systems such as road or railway infrastructure. This is because rainfall extremes are spatially dependent; to understand overall system risk, it is necessary to assess the interconnected elements of the system jointly. For example, when designing evacuation routes it is necessary to understand the risk of one part of the system failing given that another region is flooded or exceeds the level at which evacuation becomes necessary. Similarly, failure of any single part of a road section (e.g., a flooded river crossing) may lead to the wider system's failure (i.e., the entire road becomes inoperable). This study demonstrates a spatially dependent intensity–duration–frequency (IDF) framework that can be used to estimate flood risk across multiple catchments, accounting for dependence both in space and across different critical storm durations. The framework is demonstrated via a case study of a highway upgrade comprising five river crossings. The results show substantial differences in conditional and unconditional design flow estimates, highlighting the importance of taking an integrated approach. There is also a reduction in the estimated failure probability of the overall system compared with the case where each river crossing is treated independently. The results demonstrate the potential uses of spatially dependent intensity–duration–frequency methods and suggest the need for more conservative design estimates to take into account conditional risks.

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