A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.     

Does ICT lessen CO2 emissions for fast-emerging economies? An application of the heterogeneous panel estimations

Environmental Science and Pollution Research - This study examines the effects of electricity consumption, financial development, economic growth, trade and ICT on CO2 emissions in the...     

Risk-based asset integrity indicators

Asset integrity is a major concern of process facilities. Monitoring and assessing asset integrity is a challenging task due to the involvement of various dependent and independent parameters. Monitoring and assessing asset performance through indicators is one easily doable option. Lack of an appropriate set of indicators quantification technique and measurement cohesion limits the use of an indicator system. To overcome this, in the present paper a hierarchical framework is prepared to for asset integrity monitoring and assessment. The hierarchical structure is used to characterize the asset and relate it to an organization’s strategic goal. The hierarchical structure is based on three major areas of asset integrity, namely: mechanical, personnel and process. Further, it provides an opportunity to follow a bottom-up perspective for identifying multilevel level indicators. The proposed approach uses a risk metric to classify asset integrity through the integration of leading and lagging indicators’ outcome. The analytical hierarchy process is used to determine the weights, or for prioritization of each level indicator and for the aggregation of the indicators to classify risk. To test the proposed model, a benchmark study is conducted. The estimated asset integrity index value provides a tangible asset’s performance index. The system of indicators and their integration provide a comprehensive view of the process facility’s status and also reveal which sections of the facility need more attention.     

Handling data uncertainties in event tree analysis

Event tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.     

TOPHAZOP: a knowledge-based software tool for conducting HAZOP in a rapid, efficient yet inexpensive manner

Hazard and operability (HAZOP) studies constitute an essential step in the risk analysis of any chemical process industry and involve systematic identification of every conceivable abnormal process deviation, its causes and abnormal consequences. These authors have recently proposed optHAZOP as an alternative procedure for conducting HAZOP studies in a shorter span of time than taken by conventional HAZOP procedure, with greater accuracy and effectiveness [Khan, F. I. and Abassi, S. A., optHAZOP. An effective and efficient technique for hazard identification and assessment Journal of Loss Prevention in the Process Industries, 1997, 10, 191–204]. optHAZOP consists of several steps, the most crucial one requires use of a knowledge-based software tool which would significantly reduce the requirement of expert man-hours and speed up the work of the study team. TOPHAZOP (Tool for OPTmizing HAZOP) has been developed to fulfil this need.

The TOPHAZOP knowledge-base consists of two main branches: process-specific and general. The TOPHAZOP framework allows these two branches to interact during the analysis to address the process-specific aspects of HAZOP analysis while maintaining the generality of the system. The system is open-ended and modular in structure to make easy implementation and/or expansion of knowledge. The important features of TOPHAZOP and its performance on an industrial case study are described.     

Fugitive emissions in chemical processes: The assessment and prevention based on inherent and add-on approaches

Fugitive emissions are among the major concerns of industrial process releases. The emissions cause problem to various aspects including the environment, health, and economic. Early evaluation of process hazards is beneficial because process can be made inherently benign at lower cost. This paper discusses two important aspects of fugitive emissions assessment during process design – the quantification and the prevention strategies.For the quantification part, three methods are presented for fugitive emissions estimation during the process design. They are tailored to data available in simple process flow diagram (PFD), detailed PFD, and piping & instrumentation diagram (PID). Such methods are needed as early emissions estimation allows production routes and process designs with lower emissions to be selected. The fugitive emissions estimation and methods to abatement are demonstrated on a benzene process case study. Valves are found to be the major emission source with 50% of fugitive emissions of process area in a base case of petrochemical process, in which no fugitive emission reductions are yet made. Pumps without mechanical seals come second with 30% and flanges with 8% of emissions. Inherently safer design keywords can be applied to prevent fugitive emissions in the process plants. Substitution is the most applicable keyword in fugitive emission reduction of existing plants.The emission rate calculations together with estimation of health risk give a sound background for the decision making on elimination of emissions at source through equipment and piping changes. The case study presented reveals that by substituting emission prone components by inherently low-leaking ones, the plant emissions can be reduced over 90% in practice. This is created mainly by replacing rising stem valves with ball valves, installing double mechanical pump seals or hermetic pumps and making changes in sampling and relief systems. Ideally by also changing flanges to welded connections, which is not viable for various reasons, the emissions could be reduced nearly to zero.     

The effectiveness of the e-money incentive mechanism in promoting separation of recyclables at source in Malaysia

Journal of Material Cycles and Waste Management - A new concept of a reward system by two e-money-incentive systems aimed at improving separation at source toward reducing residual waste generation...     

Proposed formulation of surface water quality and modelling using gene expression,machine learning,and regression techniques

Environmental Science and Pollution Research - The rising water pollution from anthropogenic factors motivates further research in developing water quality predicting models. The available models...