Study on explosion risk of aluminum powder under different dispersions

This paper mainly studied the influence of particle size distribution on the explosion risk of aluminum powder under the span of large particle size distribution. The measurement was carried out with the 20 L explosion ball and the Hartmann tube. The statistical analysis was used to analyze the relevance between the parameters of explosion risk and the particle size parameters. Test results showed that with the increase of particle size, the sensitivity parameter increases and the intensity parameter deceleration decreases. The effect of particle size change on MEC and MIE of small particle size aluminum powder is relatively small but greater impact on Pm and (dP/dt)m. The small particle size components greatly increasing the sensitivity of the explosion and accelerating the rate of the explosion reaction; while the large particle size component contributes to the maximum explosion pressure. D_3,2 particle size dust determines the risk of aluminum powder explosion.     

Multi-criteria decision-making considering risk and uncertainty in physical asset management

In this work we present a method for risk-informed decision-making in the physical asset management context whereby risk evaluation and cost-benefit analysis are considered in a common framework. The methodology uses quantitative risk measures to prioritize projects based on a combination of risk tolerance criteria, cost-benefit analysis and uncertainty reduction metrics. There is a need in the risk and asset management literature for a unified framework through which quantitative risk can be evaluated against tolerability criteria and trade-off decisions can be made between risk treatment options. The methodology uses quantitative risk measures for loss of life, loss of production and loss of property. A risk matrix is used to classify risk as intolerable, As Low As Reasonably Practicable (ALARP) or broadly tolerable. Risks in the intolerable and ALARP region require risk treatment, and risk treatment options are generated. Risk reduction benefit of the treatment options is quantified, and cost-benefit analysis is performed using discounted cashflow analysis. The Analytic Hierarchy Process is used to derive weights for prioritization criteria based on decision-maker preferences. The weights, along with prioritization criteria for risk reduction, tolerance criteria and project cost, are used to prioritize projects using the Technique for Order Preference by Similarity to Ideal Solution. The usefulness of the methodology for improved decision-making is illustrated using a numerical example.     

Failure mode and effect analysis using regret theory and PROMETHEE under linguistic neutrosophic context

Failure mode and effect analysis (FMEA), which aims to identify and assess potential failure modes in a system, has been widely utilized in diverse areas for improving and enhancing the performance of systems due to it is a powerful and useful risk and reliability assessment instrument. However, the conventional FMEA approach has been suffered several criticisms for it has some shortcomings, such as unable to handle ambiguous and uncertain information, neglect the relative weights of risk criteria, and without considering the psychological behaviors of decision-makers. To ameliorate these limitations, this paper aims at establishing a hybrid risk ranking model of FMEA via combing linguistic neutrosophic numbers, regret theory, and PROMETHEE (Preference ranking organization method for enrichment evaluation) approach. In the presented model, linguistic neutrosophic numbers are adopted to capture decision-makers’ evaluation regarding the failure modes on each risk criterion. A modified PROMETHEE approach based on regret theory is presented to obtain the risk priority of failure modes considering the psychological behaviors of decision-makers. Moreover, a maximizing deviation model and TOPSIS (Technique for order preference similar to ideal solution) are separately applied to derive the weights of risk criteria and decision-makers. Finally, a numerical example relating to the supercritical water gasification system is employed to implement the presented method, and the effectiveness and feasibility of the proposed model are validated by the results derived from a sensitivity and comparison analysis.     

A bibliometric study of pool fire related publications

Pool fire is a common form of fire, which is constantly investigated along with the development of fire science and is also comprehensively employed as stable fire sources in examining other fire scenarios such as building and tunnel fires. According to the records in Science Citation Index Expanded database in the Web of Science Core Collection, a total of 1073 articles or reviews related to pool fires have been published from 1966 to 2019. In order to have a better understanding of knowledge structure of this topic and further identify its development history and currently popular concerns, a bibliometric analysis of pool fire research is conducted by means of visualization software VOSviewer and CiteSpace. This work visually provides a comprehensive overview of pool fire research in terms of annual publication output, source journals, productive countries/regions, authors and their cooperation network, subject terms, and reference co-citation analysis. The analysis provides networks of co-cited references, authors, countries, subject terms, and their respective clusters, indicating their ranking in contributions to the pool fire related publications. The results can be applied to enhance the understanding of pool fire research and support further work in this area.     

System safety assessment using safety entropy

Safety assessment has a primary role in hazardous operations. Most studies on safety assessment focus on risk and accident modeling, in which safety is absent. These top-down methods are highly dependent on the occurred accidents to establish accidental scenarios, which may make the assessment approach lagging behind the evolving modern systems. Moreover, this “special to general” logic is scientifically suspect in safety assessment. There is a call for the development of safety assessment methods in the presence of system safety to complement risk-focused safety analysis. These methods should provide a framework based on a bottom-up approach to examine system safety from the operational perspective. This paper has attempted to provide a potential solution. In particular, a novel concept of safety entropy is proposed to integrate with The Functional Resonance Analysis Method (FRAM), which is used to form the qualitative understanding of a system. A formula consisted of safety entropy, functional conformability, and system complexity has been established to determine the spontaneity of the safety state-changing process. The proposed method is applied to the safety assessment of a propane feed-control system. The results show the applicability of the method. Nevertheless, the model still needs to be further improved to fulfill better support for safety-related decision problems.     

Numerical study on premixing characteristics and explosion process of starch in a vertical pipe under turbulent flow

Fire and explosion accidents are frequently caused by combustible dust, which has led to increased interest in this area of research. Although scholars have performed some research in this field, they often ignored interesting phenomena in their experiments. In this paper, we established a 2D numerical method to thoroughly investigate the particle motion and distribution before ignition. The optimal time for the corn starch dust cloud to ignite was determined in a semi-closed tube, and the characteristics of the flame propagation and temperature field were investigated after ignition inside and outside the tube. From the simulation, certain unexpected phenomena that occurred in the experiment were explained, and some suggestions were proposed for future experiments. The results from the simulation showed that 60–70 ms was the best time for the dust cloud to ignite. The local high-temperature flame clusters were caused by the agglomeration of high-temperature particles, and there were no flames near the wall of the tube due to particles gathering and attaching to the wall. Vortices formed around the nozzle, where the particle concentration was low and the flame spread slowly. During the explosion venting, particles flew out of the tube before the flame. The venting flame exhibited a “mushroom cloud” shape due to interactions with the vortex, and the flame maintained this shape as it was driven upward by the vortex.     

Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

典型铬渣简易掩埋场铬渣及土壤铬污染特征和处置分析

通过钻孔采样分析,研究了典型铬渣简易掩埋场地下铬渣及土壤铬中Cr6 、总Cr的分布特征和污染状况,结果表明,铬渣简易掩埋场铬污染程度严重,引起了周边和地下深部较大面积的土壤污染,深度达到了地下的基岩.铬含量在土壤层剖面中分布呈现规律性变化,即随土壤深度增加,Cr6 、总Cr含量逐渐下降,但绝大多数超过了危险废物毒性鉴别标准.从铬污染程度上看,总体上存在铬渣>土壤>人工填土.在此基础上,提出了铬渣及污染土壤的处置方式,为铬渣污染治理和资源化利用提供科学依据.     

多目标灰色关联度决策模型分析

本文针对多目标决策的复杂性,运用灰色系统分析方法和物元分析理论,建立了决策方案的评价体系并对评价指标进行规范化处理。以决策方案的灰色关联度作为评判准则,建立了一种目标灰色关联度决策模型。     

OPTIMAL WATER USE AND SALINITY CONTROL FOR ENERGY - UPPER COLORADO RIVER BASIN1

ABSTRACT: The Upper Colorado River Basin contains appreciable amounts of undeveloped fuel resources. Large quantities of oil shale, coal, and uranium have attracted recent economic and commercial interests. Development of these resources and subsequent conversion to alternative energy forms require an adequate supply of water. Water use for large scale energy development will place increasing demands on an already overstressed allocation of Colorado River water. Present water quality is at a concentration where increased salinity will result in economic detriments to holders of downstream water rights. The salt and water exchange in mining, processing, and spent fuel disposal processes has been incorporated as part of a two-level minimum cost linear programming algorithm. Mathematical simulation results provide an optimal use of Upper Colorado River water for levels of energy output such that salinity concentrations are maintained below predetermined levels.