scholarly journals Validation of Methodology to Evaluate Risk Reduction in Tank Car Derailments

2018 ◽  
Author(s):  
Francisco Gonzalez ◽  
Anand Prabhakaran ◽  
Graydon F. Booth ◽  
Florentina M. Gantoi ◽  
Arkaprabha Ghosh
Keyword(s):  
Risk Reduction ◽  
Mitigation Strategies ◽  
Impact Loads ◽  
Data Sets ◽  
Global Risk ◽  
Operating Environment ◽  
Design Changes ◽  
Unique Outcome ◽  
Chaotic Nature ◽  
Detailed Computer

Critical derailment incidents associated with crude oil and ethanol transport have led to a renewed focus on improving the performance of tank cars against the potential for puncture under derailment conditions. Proposed strategies for improving accident performance have included design changes to tank cars, as well as, operational considerations such as reduced speeds. In prior publications, the authors have described the development of a novel methodology for quantifying and characterizing the reductions in risk that result from changes to tank car designs or the tank car operating environment. The methodology considers key elements that are relevant to tank car derailment performance, including variations in derailment scenarios, chaotic derailment dynamics, nominal distributions of impact loads and impactor sizes, operating speed differences, and variations in tank car designs, and combines these elements into a consistent framework to estimate the relative merit of proposed mitigation strategies. The modeling approach involves detailed computer simulations of derailment events, for which typical validation techniques are difficult to apply. Freight train derailments are uncontrolled chain events, which are prohibitively expensive to stage and instrument; and their chaotic nature makes the unique outcome of each event extremely sensitive to its particular set of initial and bounding conditions. Furthermore, the purpose of the modeling was to estimate the global risk reduction expected in the U.S. from tank car derailments, not to predict the outcome of a specific derailment event. These challenges call into question which validation techniques are most appropriate, considering both the modeling intent as well the availability and fidelity of the data sets available for validation. This paper provides an overview of the verification and validation efforts that have been used to enhance confidence in this methodology.

Evaluation of Risk Reduction From Tank Car Design and Operations Improvements: An Extended Study

2016 ◽  
Author(s):  
Francisco Gonzalez ◽  
Anand Prabhakaran ◽  
Graydon F. Booth ◽  
Florentina M. Gantoi
Keyword(s):  
Crude Oil ◽  
Mitigation Strategies ◽  
Impact Loads ◽  
Probabilistic Framework ◽  
Operating Environment ◽  
Component Level ◽  
Extended Study ◽  
Train Derailment ◽  
Design Changes ◽  
Objective Methodology

Critical derailment incidents associated with crude oil and ethanol transport have led to a renewed focus on improving the performance of tank cars against the potential for puncture under derailment conditions. Proposed strategies for improving puncture performance have included design changes to tank cars as well as operational considerations, such as reduced speeds and upgraded brake systems. In a prior paper on this topic, the authors conceptualized a novel and objective methodology for quantifying and characterizing the reductions in risk that result from changes to tank car design or to the tank car operating environment. This paper describes an extension of that effort to include additional derailment cases, additional operating speeds, considerations for alternate train configurations, such as Distributed Power (DP) and Electrically Controlled Pneumatic (ECP) brakes, as well as options for component level studies. In essence, the developed methodology considers key elements that are relevant to tank car derailment performance and combines these elements into a consistent probabilistic framework to estimate the relative merit of proposed mitigation strategies. The relevant elements considered include variations in the derailment scenarios, chaotic derailment dynamics, the distribution of impact loads and impactor sizes, various operating speeds, brake system differences, and variations in tank car design. The paper also provides an overview of the validation efforts which suggest that the gross dynamics of a tank car train derailment, and the resulting puncture performance of the tank cars, are captured well by this methodology.

Mitigating Strategies for Hazardous Material Trains: Evaluating the Risk Reduction

2015 ◽  
Author(s):  
Francisco Gonzalez ◽  
Anand Prabhakaran ◽  
Graydon F. Booth ◽  
Florentina M. Gantoi ◽  
Anand R. Vithani
Keyword(s):  
Impact Load ◽  
Operating Conditions ◽  
Mitigation Strategies ◽  
The North ◽  
Load Distributions ◽  
Design Changes ◽  
Safety Improvement ◽  
North American Market ◽  
Chaotic Nature ◽  
Objective Methodology

There is a significant increase in the transportation by rail of hazardous materials such as crude oil and ethanol in the North American market. Several derailment incidents associated with such transport have led to a renewed focus on improving the performance of tank cars against the potential for puncture under derailment conditions. Proposed strategies for improving puncture resistance have included design changes to tank cars, as well as, operational considerations such as reduced speeds. Given the chaotic nature of derailment events, it has been difficult to quantify globally, the overall ‘real-world’ safety improvement resulting from any given proposed change. A novel and objective methodology for quantifying and characterizing reductions in risk that result from changes to tank car designs or the tank car operating environment is outlined in this paper. The proposed methodology captures several parameters that are relevant to tank car derailment performance, including multiple derailment scenarios, derailment dynamics, impact load distributions, impactor sizes, operating conditions, tank car designs, etc., and combines them into a consistent probabilistic framework to estimate the relative merit of proposed mitigation strategies.

scholarly journals Robust Estimation of Infection Fatality Rates during the Early Phase of a Pandemic

2020 ◽  
Author(s):  
Perikles Simon
Keyword(s):  
Robust Estimation ◽  
Case Fatality ◽  
Mitigation Strategies ◽  
Global Burden ◽  
Data Sets ◽  
Serological Testing ◽  
Time Data ◽  
Age Cohorts ◽  
Spanish Influenza ◽  
And Control

AbstractDuring a pandemic, robust estimation of case fatality rates (CFRs) is essential to plan and control suppression and mitigation strategies. At present, estimates for the CFR of COVID-19 caused by SARS-CoV-2 infection vary considerably. Expert consensus of 0.1–1% covers in practical terms a range from normal seasonable Influenza to Spanish Influenza. In the following, I deduce a formula for an adjusted Infection Fatality Rate (IFR) to assess mortality in a period following a positive test adjusted for selection bias.Official datasets on cases and deaths were combined with data sets on number of tests. After data curation and quality control, a total of IFR (n=819) was calculated for 21 countries for periods of up to 26 days between registration of a case and death.Estimates for IRFs increased with length of period, but levelled off at >9days with a median for all 21 countries of 0.11 (95%-CI: 0.073–0.15). An epidemiologically derived IFR of 0.040 % (95%-CI: 0.029%– 0.055%) was determined for Iceland and was very close to the calculated IFR of 0.057% (95%-CI: 0.042– 0.078), but 2.7–6-fold lower than CFRs. IFRs, but not CFRs, were positively associated with increased proportions of elderly in age-cohorts (n=21, spearman’s ρ=.73, p =.02).Real-time data on molecular and serological testing may further displace classical diagnosis of disease and its related death. I will critically discuss, why, how and under which conditions the IFR, provides a more solid early estimate of the global burden of a pandemic than the CFR.

Considering the impacts of simultaneous perils

2019 ◽  
Vol 28 (6) ◽  
pp. 823-837 ◽  
Author(s):  
Mario Ordaz ◽  
Mario Andrés Salgado-Gálvez ◽  
Benjamín Huerta ◽  
Juan Carlos Rodríguez ◽  
Carlos Avelar
Keyword(s):  
Risk Assessment ◽  
Latin America ◽  
Risk Model ◽  
Disaster Risk ◽  
Data Sets ◽  
Global Risk ◽  
Content Type ◽  
Hazard Risk ◽  
Resolution Level ◽  
Hazard Risk Assessment

Purpose The development of multi-hazard risk assessment frameworks has gained momentum in the recent past. Nevertheless, the common practice with openly available risk data sets, such as the ones derived from the United Nations Office for Disaster Risk Reduction Global Risk Model, has been to assess risk individually for each peril and afterwards aggregate, when possible, the results. Although this approach is sufficient for perils that do not have any interaction between them, for the cases where such interaction exists, and losses can be assumed to occur simultaneously, there may be underestimation of losses. The paper aims to discuss these issues. Design/methodology/approach This paper summarizes a methodology to integrate simultaneous losses caused by earthquakes and tsunamis, with a peril-agnostic approach that can be expanded to other hazards. The methodology is applied in two relevant locations in Latin America, Acapulco (Mexico) and Callao (Peru), considering in each case building by building exposure databases with portfolios of different characteristics, where the results obtained with the proposed approach are compared against those obtained after the direct aggregation of individual losses. Findings The fully probabilistic risk assessment framework used herein is the same of the global risk model but applied at a much higher resolution level of the hazard and exposure data sets, showing its scalability characteristics and the opportunities to refine certain inputs to move forward into decision-making activities related to disaster risk management and reduction. Originality/value This paper applies for the first time the proposed methodology in a high-resolution multi-hazard risk assessment for earthquake and tsunami in two major coastal cities in Latin America.

scholarly journals Indigenous knowledge for disaster risk reduction: An African perspective

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Nnamdi G. Iloka
Keyword(s):  
Climate Change ◽  
Indigenous Knowledge ◽  
Risk Reduction ◽  
Disaster Risk Reduction ◽  
Disaster Risk ◽  
Mitigation Strategies ◽  
Local People ◽  
Contributing Factors ◽  
Policy Makers ◽  
Future Challenges

Indigenous knowledge is valuable knowledge that has helped local communities all over the world survive for generations. This knowledge originates from the interaction between members of the community and the environment in which they live. Although much has been written about indigenous knowledge, its documentation in the area of disaster risk reduction and climate change in Africa has been very limited. The wealth of this knowledge has not been well-recognised in the disaster risk reduction field, as policy-makers still rely on mitigation strategies based on scientific knowledge. Colonialism and lack of proper documentation of indigenous knowledge are some of the contributing factors to this. Ignoring the importance of understanding adaptive strategies of the local people has led to failed projects. Understanding how local people in Africa have managed to survive and adapt for generations, before the arrival of Western education, may be the key to developing sustainable policies to mitigate future challenges. Literature used in this article, obtained from the books, papers and publications of various experts in the fields of disaster risk reduction, climate change, indigenous knowledge and adaptation, highlight the need for more interest to be shown in indigenous knowledge, especially in the developing country context. This would lead to better strategies which originate from the community level but would aim for overall sustainable development in Africa.

scholarly journals Potential of semi-structural and non-structural adaptation strategies to reduce future flood risk: case study for the Meuse

2012 ◽  
Vol 12 (11) ◽  
pp. 3455-3471 ◽  
Author(s):  
J. K. Poussin ◽  
P. Bubeck ◽  
J. C. J. H. Aerts ◽  
P. J. Ward
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Risk Reduction ◽  
Flood Risk ◽  
Local Level ◽  
Mitigation Strategies ◽  
Policy Implications ◽  
Mitigation Measures ◽  
Reduction Capacity ◽  
Flood Prone Areas

Abstract. Flood risk throughout Europe has increased in the last few decades, and is projected to increase further owing to continued development in flood-prone areas and climate change. In recent years, studies have shown that adequate undertaking of semi-structural and non-structural measures can considerably decrease the costs of floods for households. However, there is little insight into how such measures can decrease the risk beyond the local level, now and in the future. To gain such insights, a modelling framework using the Damagescanner model with land-use and inundation maps for 2000 and 2030 was developed and applied to the Meuse river basin, in the region of Limburg, in the southeast of the Netherlands. The research suggests that annual flood risk may increase by up to 185% by 2030 compared with 2000, as a result of combined land-use and climate changes. The independent contributions of climate change and land-use change to the simulated increase are 108% and 37%, respectively. The risk-reduction capacity of the implementation of spatial zoning measures, which are meant to limit and regulate developments in flood-prone areas, is between 25% and 45%. Mitigation factors applied to assess the potential impact of three mitigation strategies (dry-proofing, wet-proofing, and the combination of dry- and wet-proofing) in residential areas show that these strategies have a risk-reduction capacity of between 21% and 40%, depending on their rate of implementation. Combining spatial zoning and mitigation measures could reduce the total increase in risk by up to 60%. Policy implications of these results are discussed. They focus on the undertaking of effective mitigation measures, and possible ways to increase their implementation by households.

scholarly journals Automated image processing to support the analysis of between-year transmission of Leptosphaeria maculans in field conditions

2018 ◽  
Author(s):  
Lydia Bousset ◽  
Marcellino Palerme ◽  
Melen Leclerc ◽  
Nicolas Parisey
Keyword(s):  
Image Processing ◽  
Oilseed Rape ◽  
Leptosphaeria Maculans ◽  
Large Data ◽  
Stem Canker ◽  
Epidemiological Studies ◽  
Mitigation Strategies ◽  
Plant Diseases ◽  
Data Sets ◽  
Growing Period

Understanding the transmission of inoculum between periods where the host plants are present is central for predicting the development of plant diseases and optimising mitigation strategies. However, the production at the end of the growing period, the survival during the intercrop period, and the emergence or emission of inoculum after sowing or planting can be highly variable, difficult to assess and generally inferred indirectly from symptoms data. As a result, there is a lack of large data sets which is a major brake for the study of these epidemiological processes. Here we focus on Leptosphaeria maculans that causes the black leg of oilseed rape. After having infected leaves, at early stages of the plant, and migrating into the stem, it causes a basal stem canker before harvest. It then survives on stubble left in the field from which ascospores are emitted at the beginning of the next growing period. In this study we first developed an image processing framework to estimate the density of fruiting bodies produced on stubble. Then, we used this framework to analyse automatically a large number of stems collected in oilseed rape fields among a cultivated area. Having performed a quality assessment of the processing chain we used the output data to investigate how the potential level of inoculum may change with the source field, the considered year and the stem canker severity at harvest. Besides the insights gain into the blackleg of oilseed rape, this work shows how image-based phenotyping may support epidemiological studies by increasing substantially the precision of high throughput disease data.

scholarly journals Geospatial input data for the PALM model system 6.0: model requirements, data sources, and processing

2020 ◽  
Author(s):  
Wieke Heldens ◽  
Cornelia Burmeister ◽  
Farah Kanani-Sühring ◽  
Björn Maronga ◽  
Dirk Pavlik ◽  
...  
Keyword(s):  
Input Data ◽  
Open Data ◽  
Local Environment ◽  
Model System ◽  
Urban Environments ◽  
Mitigation Strategies ◽  
Data Sources ◽  
Data Sets ◽  
Simulation Scenario ◽  
German Cities

Abstract. The PALM model system 6.0 is designed to simulate micro- and mesoscale flow dynamics in realistic urban environments. The simulation results can be very valuable for various urban applications, for example to develop and improve mitigation strategies related to heat stress or air pollution. For the accurate modelling of urban environments, realistic boundary conditions need to be considered for the atmosphere, the local environment, and the soil. The local environment with its geospatial components is described in the static driver of the model and follows a standardized, hereafter called PALM input data standard. The main input parameters describe surface type, buildings and vegetation. Depending on the desired simulation scenario and the available data, the local environment can be described at different levels of detail. To compile a complete static driver describing a whole city, various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. This manuscript shows how input data sets for three German cities can be derived. Based on these data sets, the static driver for PALM can be generated. As the collection and preparation of input data sets is tedious, prospective research aims at the development of a semi-automated processing chain to support users in formatting their geospatial data.

scholarly journals Effects of ozone on agriculture, forests and grasslands

2020 ◽  
Vol 378 (2183) ◽  
pp. 20190327 ◽  
Author(s):  
Lisa Emberson
Keyword(s):  
Risk Assessment ◽  
Food Supply ◽  
Land Surface ◽  
Large Body ◽  
Coastal Region ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Global Risk ◽  
Gangetic Plain ◽  
Surface Exchange

The damage and injury that ground level ozone (O 3 ) causes vegetation has become increasingly evident over the past half century with a large body of observational and experimental evidence demonstrating a variety of effects at ambient concentrations on crop, forest and grassland species and ecosystems. This paper explores the use of experimental data to develop exposure-response relationships for use in risk assessment studies. These studies have typically identified the USA mid-West, much of Europe, the Indo Gangetic Plain in South Asia and the Eastern coastal region of China as global regions where O 3 is likely to threaten food supply and other ecosystems. Global risk assessment modelling estimates yield losses of staple crops between 3 to 16% causing economic losses of between US$14 to 26 billion in the year 2000. Changes in anthropogenic emissions of O 3 precursors in recent decades have modified O 3 concentration profiles (peaks versus background O 3 ) and global distributions with the Northern Hemisphere seeing increases in O 3 levels of between 1 and 5 ppb/decade since the 1950s and the emergence of Asia as the region with the highest O 3 concentrations. In the future, O 3 mitigation could focus on methane (CH 4 ) and nitrogen oxide (NOx) emissions; these will differentially influence global and local/regional O 3 concentrations and influence daily and seasonal profiles. The consequent effects on vegetation will in part depend on how these changes in O 3 profile alter the exceedance of detoxification thresholds for plant damage. Adaptation options may play an important role in enhancing food supply while mitigation strategies are being implemented. An improved understanding of the mechanisms by which O 3 affects plants, and how this might influence detoxification thresholds and interactions with other environmental variables such as water stress and nutrients, would help develop O 3 deposition and impact models to support the development of crop, land-surface exchange and ultimately earth system models for holistic assessments of global change. This article is part of a discussion meeting issue ‘Air quality, past present and future’.

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