A Simplified Methodology for Rapidly Analyzing the Effect of Multi-Hazard Scenario on Atmospheric Storage Tanks

Natural hazard events that trigger technical emergencies (Natech events), as a typical type of multi-hazard, have become a matter of growing concern. In particular, the occurrence of Natech events in industrial areas triggered a number of severe accidents. The present research aims at introducing a sound but simplified methodology to quickly and flexibly assess the vulnerability of atmospheric storage tanks to multiple natural disasters in Natech events. This method consists of 8 steps, relying on the simplified physical models of tank damage caused by natural disasters. The models of wind overturning tank and tank buckling caused by hail are proposed. In addition, the assessment process of tank vulnerability is demonstrated from two aspects: deterministic analysis and probabilistic analysis. The uncertain parameter set (UPS) proposed in the method and the Monte Carlo simulation method can help to purposefully analyze the impact of various parameters and this method is also a general method, which is also applicable to Natech events including other natural disasters or other types of storage tanks.

A longitudinal analysis of collapsibility with predictions over the southeastern Loess Plateau in China

Loess presents very unique collapsible behaviour due to its special under-compactness, weak cementation and porousness. Many environmental issues and geological hazards including subgrade subsidences, slope collapses or failures, building cracking and so on are directly caused by the collapsible deformation of loess. Such collapsible behaviour may also severe accidents due to sinkholes, underground caves or loess gullies. Moreover, with the increasing demand of construction and development in the loess areas, an in-depth research towards effective evaluation of loess collapsibility is urged. Currently no studies have made attempts to explore a rather complete and representative area of Loess Plateau. This paper thus provides a novel approach on spatial modelling over Jin-Shan Loess Plateau as an extension to experimental studies. The in-lab experiment results have shown that shown that the porosity ratio and collapsibility follow a Gaussian distribution and a Gamma distribution respectively for both sampling areas: Yan’an and Lv Liang. This establishes the prior intuition towards spatial modelling which provides insights of potential influential factors on loess collapsibility and further sets a potential direction of the loess studies by considering an extra dimension of spatial correlation. Such modelling allows robust predictions taken into account of longitudinal information as well as structural parameters and basic physical properties. Water contents, dry densities, pressure levels and elevations of samples are determined to be statistically significant factors which affect the loess collapsibility. All regions in Lv Liang area are at risk of high collapsibility with average around 0.03, out of which roughly a third of them are predicted to be at high risk. Clear spatial patterns of higher expected collapsibility in the southwest comparing to the northeast are shown adjusting for influential covariates. On reference guidelines for potential policy makings, county-level regions with the highest expected loess collapsibility are also identified.

A Framework for Identification, Assessment and Prioritization of Climate Change Adaptation Measures for Roads and Railways

Severe accidents and high costs associated with weather-related events already occur in today’s climate. Unless preventive measures are taken, the costs are expected to increase in future due to ongoing climate change. However, the risk reduction measures are costly as well and may result in unwanted impacts. Therefore, it is important to identify, assess and prioritize which measures are necessary to undertake, as well as where and when these are to be undertaken. To be able to make such evaluations, robust (scientifically based), transparent and systematic assessments and valuations are required. This article describes a framework to assess the cause-and-effect relationships and how to estimate the costs and benefits as a basis to assess and prioritize measures for climate adaptation of roads and railways. The framework includes hazard identification, risk analysis and risk assessment, identification, monetary and non-monetary evaluation of possible risk reduction measures and a step regarding distribution-, goal- and sensitivity analyses. The results from applying the framework shall be used to prioritize among potential risk reduction measures as well as when to undertake them.

Construction Safety during Pandemics: Learning from the Xinjia Express Hotel Collapse during COVID-19 in China

Many construction accidents occur in China each year, leading to a large number of deaths, injures, and property losses. Due to the outbreak of COVID-19, little attention is paid to construction safety, resulting in severe accidents. To prevent construction accidents and learn to how address safety issues in future pandemics, this study proposed an improved STAMP (Systems Theoretic Accident Modeling and Processes) model to analyze the collapse accident of the Xinjia Express Hotel used for COVID-19 quarantine in China. Through the application of the STAMP approach, the causes of the construction accident and the relationship between various causal factors are analyzed from a systematic perspective. The identified causes are divided into five categories: contractors, management of organizations, technical methods, participants, and interactive feedback. Finally, safety recommendations are drawn from this study to improve construction safety and safety management in pandemics.