scholarly journals Generalized graphic-analytical model for evaluation of the fatality / structural collapse production mechanism on a building affected by an explosion

2022 ◽  
Vol 354 ◽  
pp. 00033
Author(s):  
Gabriel Vasilescu ◽  
Attila Kovacs ◽  
Ciprian Jitea ◽  
Doru Anghelache ◽  
Florian Stoian

The paper highlights the generalized grapho-analytical model of analysis and evaluation of the mechanism of occurrence of the event scenario for the production of fatality/structural collapse in the case of a building affected by explosion. This mathematical model is based on research results in the field of civil explosives for the technological/occupational risks estimation and assessment, as well as threats to the security of protected areas that may be vulnerable through acts of malice. The process of quantitative risk assessment associated with explosion phenomena as a result of the detonation of an explosive charge, allows estimating result indicators based on the use of algorithms and models specific to associated hazards, in order to model the effects and consequences of event scenarios.

Author(s):  
N. M. Meshchakova

Advanced approach to assessment of not cancerogenic professional risks at workers of chemical productions which basis are calculations of exposition chemical loadings for the entire period of an exposition and the indicators of incidence and quantitative risk assessment of the main all-pathological syndromes associated with them is presented.


2013 ◽  
Vol 19 (3) ◽  
pp. 521-527 ◽  
Author(s):  
Song YANG ◽  
Shuqin WU ◽  
Ningqiu LI ◽  
Cunbin SHI ◽  
Guocheng DENG ◽  
...  

1997 ◽  
Vol 35 (11-12) ◽  
pp. 29-34 ◽  
Author(s):  
P. Teunis ◽  
A. Havelaar ◽  
J. Vliegenthart ◽  
G. Roessink

Shellfish are frequently contaminated by Campylobacter spp, presumably originating from faeces from gulls feeding in the growing or relaying waters. The possible health effects of eating contaminated shellfish were estimated by quantitative risk assessment. A paucity of data was encountered necessitating many assumptions to complete the risk estimate. The level of Campylobacter spp in shellfish meat was calculated on the basis of a five-tube, single dilution MPN and was strongly season-dependent. The contamination level of mussels (<1/g) appeared to be higher than in oysters. The usual steaming process of mussels was found to completely inactivate Campylobacter spp so that risks are restricted to raw/undercooked shellfish. Consumption data were estimated on the basis of the usual size of a portion of raw shellfish and the weight of meat/individual animal. Using these data, season-dependent dose-distributions could be estimated. The dominant species in Dutch shellfish is C. lari but little is known on its infectivity for man. As a worst case assumption, it was assumed that the infectivity was similar to C. jejuni. A published dose-response model for Campylobacter-infection of volunteers is available but with considerable uncertainty in the low dose region. Using Monte Carlo simulation, risk estimates were constructed. The consumption of a single portion of raw shellfish resulted in a risk of infection of 5–20% for mussels (depending on season; 95% CI 0.01–60%). Repeated (e.g. monthly) exposures throughout a year resulted in an infection risk of 60% (95% CI 7–99%). Risks for oysters were slightly lower than for mussels. It can be concluded that, under the assumptions made, the risk of infection with Campylobacter spp by eating of raw shellfish is substantial. Quantitative risk estimates are highly demanding for the availability and quality of experimental data, and many research needs were identified.


Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Pete Burnap ◽  
Omar Santos

AbstractThe Internet-of-Things (IoT) triggers data protection questions and new types of cyber risks. Cyber risk regulations for the IoT, however, are still in their infancy. This is concerning, because companies integrating IoT devices and services need to perform a self-assessment of its IoT cyber security posture. At present, there are no self-assessment methods for quantifying IoT cyber risk posture. It is considered that IoT represent a complex system with too many uncontrollable risk states for quantitative risk assessment. To enable quantitative risk assessment of uncontrollable risk states in complex and coupled IoT systems, a new epistemological equation is designed and tested though comparative and empirical analysis. The comparative analysis is conducted on national digital strategies, followed by an empirical analysis of cyber risk assessment approaches. The results from the analysis present the current and a target state for IoT systems, followed by a transformation roadmap, describing how IoT systems can achieve the target state with a new epistemological analysis model. The new epistemological analysis approach enables the assessment of uncontrollable risk states in complex IoT systems—which begin to resemble artificial intelligence—and can be used for a quantitative self-assessment of IoT cyber risk posture.


Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Carlos Carvalhais ◽  
Micaela Querido ◽  
Cristiana C. Pereira ◽  
Joana Santos

BACKGROUND: The COVID-19 global pandemic brought several challenges to occupational safety and health practice. One of these is the need to (re)assess the occupational risks, particularly, biological risks. OBJECTIVE: The purpose of this work is to promote guidance to occupational safety and health practitioners when conducting a biological risk assessment in this context. METHODS: The main steps of the biological risk assessment are explained with some inputs regarding the novelty posed by SARS-CoV-2 and an example of a qualitative risk assessment method is presented. Also, its application to two different activities was exemplified. RESULTS: In both cases, the assessment considered that vulnerable workers were working from home or in medical leave. The results showed low or medium risk level for the assessed tasks. For medium risk level, additional controls are advised, such maintain social distancing, sanitize instruments/equipment before use, use proper and well-maintained PPE (when applicable), and promote awareness sessions to spread good practices at work. Employers must be aware of their obligations regarding biological risk assessment and OSH practitioners must be prepared to screen and link the abundance of scientific evidence generated following the outbreak, with the technical practice. CONCLUSIONS: This paper could be an important contribution to OSH practice since it highlights the need to (re)assess occupational risks, especially biological risk, to ensure a safe return to work, providing technical guidance.


2021 ◽  
Vol 11 (11) ◽  
pp. 5208
Author(s):  
Jianpo Liu ◽  
Hongxu Shi ◽  
Ren Wang ◽  
Yingtao Si ◽  
Dengcheng Wei ◽  
...  

The spatial and temporal distribution of tunnel failure is very complex due to geologic heterogeneity and variability in both mining processes and tunnel arrangement in deep metal mines. In this paper, the quantitative risk assessment for deep tunnel failure was performed using a normal cloud model at the Ashele copper mine, China. This was completed by considering the evaluation indexes of geological condition, mining process, and microseismic data. A weighted distribution of evaluation indexes was determined by implementation of an entropy weight method to reveal the primary parameters controlling tunnel failure. Additionally, the damage levels of the tunnel were quantitatively assigned by computing the degree of membership that different damage levels had, based on the expectation normalization method. The methods of maximum membership principle, comprehensive evaluation value, and fuzzy entropy were considered to determine the tunnel damage levels and risk of occurrence. The application of this method at the Ashele copper mine demonstrates that it meets the requirement of risk assessment for deep tunnel failure and can provide a basis for large-scale regional tunnel failure control in deep metal mines.


2021 ◽  
Vol 420 ◽  
pp. 129893
Author(s):  
Zijian Liu ◽  
Wende Tian ◽  
Zhe Cui ◽  
Honglong Wei ◽  
Chuankun Li

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