Classification and Moral Evaluation of Uncertainties in Engineering Modeling

Murphy, Colleen; Gardoni, Paolo; Harris, Charles E.

doi:10.1007/s11948-010-9242-2

Cited by 52 publications

(24 citation statements)

References 23 publications

(21 reference statements)

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“…When modeling earthquake risk, one must be aware of the large amount of uncertainties related mainly to the hazard and to the vulnerability (Ordaz 2000;Grossi 2004;Murphy et al 2011;Marulanda et al 2013;Salgado-Gálvez et al 2014b;Salgado-Gálvez et al 2015a). …”

Section: Probabilistic Seismic Risk Assessmentmentioning

confidence: 99%

Probabilistic estimation of annual lost economic production due to premature deaths because of earthquakes

Salgado‐Gálvez

Bernal

Barbat

et al. 2015

Human and Ecological Risk Assessment: An International Journal

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This is an Accepted Manuscript of an article published by Taylor & Francis Group in Human and Ecological Risk Assessment: An International Journal on 2016, available online at: http://www.tandfonline.com/10.1080/10807039.2015.1095072A methodology to estimate, in a probabilistic way, the annual cost to society of premature deaths because of earthquakes is proposed in this article. The methodology makes use of results obtained by means of prospective and probabilistic seismic risk assessments where expected deaths caused by the collapse of buildings are obtained. Those results, combined with demographic and macroeconomic indicators such as the age distribution, life expectancy at birth, and per capita gross domestic product, are used to estimate the cost to society in terms of lost productivity due to premature mortality because of earthquakes. The proposed methodology does not attempt to estimate nor assign a cost to human lives at any stage, but the one associated to lost productivity at the societal level. One of the descriptors of the methodology is part of the components of the disability adjusted life year, a widely used metric in the public health field that estimates the burden of diseases based mostly on historical data. As an example, the methodology is applied to Medellin, the second largest city of Colombia, finding that the cost of lost productivity due to premature mortality because of earthquakes has a similar order of magnitude to the direct physical losses in the public and private building stock calculated in a previous probabilistic seismic risk assessment.Peer ReviewedPostprint (author's final draft

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Section: Probabilistic Seismic Risk Assessmentmentioning

confidence: 99%

Probabilistic estimation of annual lost economic production due to premature deaths because of earthquakes

Salgado‐Gálvez

Bernal

Barbat

et al. 2015

Human and Ecological Risk Assessment: An International Journal

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“…Essential components of uncertainty analysis include physical system-based uncertainties that mainly affect the community robustness (e.g., stemming from performance of individual facilities, building portfolios and infrastructure systems as a whole) and socioeconomic uncertainties that affect the extent of societal impact and community recovery (e.g., those associated with social, economic and political institutions within the community, human responses and available external resources.) Such socioeconomic uncertainties will be considered (Murphy et al 2011).…”

Section: Treatment Of Interdependency Aging Infrastructure and Uncementioning

confidence: 99%

Computational environment for modeling and enhancing community resilience: Introducing the center for risk-based community resilience planning

Lindt¹,

Ellingwood²,

McAllister³

et al. 2015

Proceedings of the Second International Conference on Performance-Based and Life-Cycle Structural Engineering (PLSE 2015)

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The resilience of a community is defined as its ability to prepare for, withstand, recover from and adapt to the effects of natural or human-caused disasters, and depends on the performance of the built environment and on supporting social, economic and public institutions that are essential for immediate response and long-term recovery and adaptation. The performance of the built environment generally is governed by codes, standards, and regulations, which are applicable to individual facilities and residences, are based on different performance criteria, and do not account for the interdependence of buildings, transportation, utilities and other infrastructure sectors. The National Institute of Standards and Technology recently awarded a new Center of Excellence (NIST-CoE) for Risk-Based Community Resilience Planning, which is headquartered at Colorado State University and involves nine additional universities. Research in this Center is focusing on three major research thrusts: (1) developing the NIST-Community Resilience Modeling Environment known as NIST-CORE, thereby enabling alternative strategies to enhance community resilience to be measured quantitatively; (2) developing a standardized data ontology, robust data architecture and data management tools in support of NIST-CORE; and (3) performing a comprehensive set of hindcasts on disasters to validate the data architecture and NIST-CORE.

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“…We talk about probability of occurrence because of the lack of a certain outcomes due to the presence of uncertainties. The two primary classes of uncertainties are endodoxastic and metadoxastic uncertainties …”

Section: Definition Of Riskmentioning

confidence: 99%

“…Epistemic uncertainties are often a product of limits of our knowledge. Sources of uncertainty include possible simplifications made in the process of constructing models to estimate the probabilities, mistaken assumptions in developing a model, measurement errors or sparseness of data when calibrating a model, and human errors in applying a model . Such uncertainties are in principle reducible, for example, by the use of improved models, the acquisition of more accurate measurements, and the collection of larger samples.…”

Section: Definition Of Riskmentioning

confidence: 99%

A Scale of Risk

Gardoni

Murphy

2013

Risk Analysis

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This article proposes a conceptual framework for ranking the relative gravity of diverse risks. This framework identifies the moral considerations that should inform the evaluation and comparison of diverse risks. A common definition of risk includes two dimensions: the probability of occurrence and the associated consequences of a set of hazardous scenarios. This article first expands this definition to include a third dimension: the source of a risk. The source of a risk refers to the agents involved in the creation or maintenance of a risk and captures a central moral concern about risks. Then, a scale of risk is proposed to categorize risks along a multidimensional ranking, based on a comparative evaluation of the consequences, probability, and source of a given risk. A risk is ranked higher on the scale the larger the consequences, the greater the probability, and the more morally culpable the source. The information from the proposed comparative evaluation of risks can inform the selection of priorities for risk mitigation.

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Classification and Moral Evaluation of Uncertainties in Engineering Modeling

Cited by 52 publications

References 23 publications

Probabilistic estimation of annual lost economic production due to premature deaths because of earthquakes

Probabilistic estimation of annual lost economic production due to premature deaths because of earthquakes

Computational environment for modeling and enhancing community resilience: Introducing the center for risk-based community resilience planning

A Scale of Risk

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