Using Resilience in Risk-Based Asset Management Plans

2020 ◽  
Vol 2674 (4) ◽  
pp. 178-192
Author(s):  
YuanChi Liu ◽  
Sue McNeil
Keyword(s):  
Asset Management ◽  
Transportation Networks ◽  
Management Plan ◽  
Extreme Weather Events ◽  
Risk And Resilience ◽  
Technical Performance ◽  
Weather Events ◽  
Management Plans ◽  
Robeson County ◽  
Transportation Asset Management

Each state in the U.S.A. is required to develop and maintain a risk-based transportation asset management plan for the National Highway System (NHS) to improve or preserve the condition of the assets and the performance of the system. Awareness of natural hazards and extreme weather events has also increased with recent catastrophic hurricanes, such as Matthew (October, 2016) and Harvey (August, 2017), which caused significant inland floods in Robeson County, North Carolina, and Houston, Texas, respectively. These recent events and the damage to transportation infrastructure has also focused attention on the resilience of transportation networks. However, an integrated, consistent, well-understood method to assess or quantify the resilience of transportation networks is still lacking. This paper reviews the relevant concepts, legislative requirements that link asset management, risk and resilience, and tools available to support risk-based asset management. Based on a review of the transportation asset management plans developed by 49 state departments of transportation in 2018 and 2019, the paper summarizes the approaches to the risk management section of these asset management plans and the role resilience plays. Opportunities to better integrate resilience into the risk-based asset management plans are then identified. Examples are presented that demonstrate the role of resilience-related technical performance measures that reflect decisions related to flooding in the various stages of the disaster cycle (preparedness, response, recovery, and mitigation).

scholarly journals A Risk Management Database Framework Implementation for Transportation Asset Management

CivilEng ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 193-213
Author(s):  
Inya Nlenanya ◽  
Omar Smadi
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Asset Management ◽  
Risk Mitigation ◽  
Application Programming Interface ◽  
Management Plan ◽  
Management Program ◽  
Risk Modeling ◽  
Transportation Asset Management ◽  
Management Database

A 2017 survey of the state of practice on how agencies are developing their risk-based asset management plan shows that state highway agencies are increasingly adapting the way they do business to include explicit considerations of risks. At the moment, this consideration of risk is not linked to data. Hence, there is a lack of integration of risk management in driving strategic cross-asset programming and decision-making. This paper proposes and implements a risk management database framework as the missing piece in the full implementation of a risk-based transportation asset management program. This risk management database framework utilizes Geographic Information Systems (GIS) and Application Programming Interface (API) to implement a risk management database of all the relevant variables an agency needs for risk modeling to improve risk monitoring, risk register updates, and decision-making. This approach allows the use of existing enterprise as well as legacy data collection systems, which eliminates the need for any capital-intensive implementation cost. Furthermore, it provides transportation agencies with the ability to track risk in quantitative terms, a framework for prioritizing risk, and the development of an actionable plan for risk mitigation. In this paper, the implementation of the fully integrated GIS-enabled risk management database employs the Iowa department of transportation (DOT) data and risk register.

An Integrated Critical Infrastructure Risk and Resilience Concept in the Context of Extreme Weather Events and Global Change

2016 ◽  
Vol 03 (04) ◽  
pp. 1650015 ◽  
Author(s):  
Maria Schwab ◽  
Claudia Berchtold ◽  
Anna Goris
Keyword(s):  
Risk Management ◽  
Critical Infrastructure ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Practical Implementation ◽  
Risk And Resilience ◽  
Integrative Framework ◽  
Weather Events ◽  
Management Concepts ◽  
Set Up

A review of risk assessment research in the context of extreme weather events (EWE) reveals that conceptual approaches addressing the risk of critical infrastructures (CI) focus primarily on single components and factors of CI that are at risk. The objective of the paper is to introduce an integrative framework that considers the complex set-up of CI and links it to newer conceptualizations of risk management and adaptation. Drawing on existing risk and resilience approaches, this paper brings together aspects of the engineering community, which currently dominate CI-related research, and of disaster risk reduction research communities, resilience and adaptation research in the context of natural hazards. The paper thereby presents an adapted approach that particularly addresses interdependencies of infrastructures as well as future dynamics. The risk concept applied is based on the IPCC framework and considers the manifold impacts of CI failures upon society, economy and environment. Recommendations for risk management regimes are thereby formulated in the context of EWE. Based on a more holistic socio-ecological systems’ perspective, the approach covers the dynamic transformation of a system’s resilience state. The framework provides a tool and concept to improve the understanding of the multitude factors determining the risks of EWE for CI. Additional research is required for the further operationalization of the conceptual framework, such as the development of indicators, in order to enable the practical implementation for the support of risk management concepts.

scholarly journals Element-Based Multi-Objective Optimization Methodology Supporting a Transportation Asset Management Framework for Bridge Planning and Programming

2021 ◽  
pp. 036119812110413
Author(s):  
Karim Naji ◽  
Erin Santini-Bell ◽  
Kyle Kwiatkowski
Keyword(s):  
Asset Management ◽  
Optimization Problems ◽  
Leading Edge ◽  
Management Plan ◽  
Bridge Management ◽  
Multi Objective Optimization ◽  
Element Level ◽  
Management Framework ◽  
Multi Objective ◽  
Transportation Asset Management

The U.S. Moving Ahead for Progress in the 21st Century Act (MAP-21) mandates the development of a risk-based transportation asset management plan and the use of a performance-based approach in transportation planning and programming. This paper introduces a systematic element-based multi-objective optimization (EB-MOO) methodology integrated into a goal-driven transportation asset management framework to improve bridge management and support state departments of transportation with their transition efforts to comply with these MAP-21 requirements. The methodology focuses on the bridge asset class and is structured around five modules: data processing, improvement, element-level optimization, bridge-level optimization, and network-level optimization modules. It relies on a leading-edge forecasting model, three separate screening processes (i.e., the element deficiency, alternative feasibility, and solution superiority screening processes) to overcome computer memory and processing time limitations, and a simulation arrangement to generate life-cycle alternatives (series of improvement actions). Additionally, the EB-MOO methodology consists of three levels of optimization assessment based on the Pareto optimality concept: element-level, bridge-level, and network-level (following either a top-down or bottom-up approach). A robust metaheuristic genetic algorithm handles the different multi-objective optimization problems. A prototyping tool was developed for the implementation of the methodology through several examples of unconstrained and constrained (by budget, performance, or both) scenarios. Results reveal the capability of the methodology to generate Pareto optimal or near-optimal solutions, predict performance, and determine funding requirements and short- and long-term intervention strategies detailed at the bridge-element level for planning and programming. The EB-MOO methodology can also be expanded to accommodate other asset classes or modes.

Forecasting Federal Transportation Performance Management Bridge Condition Measures for Bridge Management

2021 ◽  
pp. 036119812110152
Author(s):  
Paul D. Thompson
Keyword(s):  
Performance Management ◽  
Long Range ◽  
Asset Management ◽  
Capital Budgeting ◽  
Time Frame ◽  
Bridge Management ◽  
Novel Approach ◽  
Management Plans ◽  
Transportation Asset Management ◽  
Condition State

Many common processes of bridge management can benefit from network-level analysis of long-term costs and condition, on a time frame of about 10 years. Such processes include development and implementation of Transportation Asset Management Plans, long-range needs analysis, capital budgeting and programming, and policy analysis. The ability to forecast federal Transportation Performance Management (TPM) condition measures would provide managers with a way of evaluating the possible outcomes of funding, programming, and policy decisions. A model for this purpose has been developed as a part of StruPlan, an open-source spreadsheet for long-range renewal planning for transportation structures. Element condition state data are found to be highly exponential in distribution, while the federal measures “Percent Good” and “Percent Poor” are categorical when applied to specific bridges. Element data, providing more detail about the type, severity, and extent of defects, are valuable for deterioration modeling, while the TPM measures are simpler for reporting to stakeholders. A set of models was developed to bridge the gap between these measures. Thus far, the models have been calibrated and pilot tested using Idaho, South Dakota, and Kentucky data. The model is a novel approach that has not been attempted elsewhere, that may simplify important parts of bridge management and provide some valuable new ideas for researchers and developers.

Modelling the Bioclimatic Niche of a Cohort of Selected Mite Species (Acari, Acariformes) Associated with the Infestation of Stored Products

2019 ◽  
Vol 53 (5) ◽  
pp. 399-416
Author(s):  
V. M. Tytar ◽  
Ya. R. Oksentyuk
Keyword(s):  
Potential Evapotranspiration ◽  
Species Distribution Modeling ◽  
Mite Species ◽  
Extreme Weather Events ◽  
Stored Products ◽  
Weather Events ◽  
Moisture Regimes ◽  
Bioclimatic Variables ◽  
Contemporary Climate ◽  
Future Management

Abstract In this study an attempt is made to highlight important variables shaping the current bioclimatic niche of a number of mite species associated with the infestation of stored products by employing a species distribution modeling (SDM) approach. Using the ENVIREM dataset of bioclimatic variables, performance of the most robust models was mostly influenced by: 1) indices based on potential evapotranspiration, which characterize ambient energy and are mostly correlated with temperature variables, moisture regimes, and 2) strong fluctuations in temperature reflecting the severity of climate and/or extreme weather events. Although the considered mite species occupy man-made ecosystems, they remain more or less affected by the surrounding bioclimatic environment and therefore could be subjected to contemporary climate change. In this respect investigations are needed to see how this will affect future management targets concerning the safety of food storages.

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