Risk-Based Integrity and Inspection Modeling (RBIIM) of Process Components/System

Process plants deal with hazardous (highly flammable and toxic) chemicals at extreme conditions of temperature and pressure. Proper inspection and maintenance of these facilities is paramount for the maintenance of safe and continuous operation. This article proposes a risk-based methodology for integrity and inspection modeling (RBIIM) to ensure safe and fault-free operation of the facility. This methodology uses a gamma distribution to model the material degradation and a Bayesian updating method to improve the distribution based on actual inspection results. The method deals with the two cases of perfect and imperfect inspections. The measurement error resulting from imperfect inspections is modeled as a zero-mean, normally distributed random process. The risk is calculated using the probability of failure and the consequence is assessed in terms of cost as a function of time. The risk function is used to determine an optimal inspection and replacement interval. The calculated inspection and replacement interval is subsequently used in the design of an integrity inspection plan. Two case studies are presented: the maintenance of an autoclave and the maintenance of a pipeline segment. For the autoclave, the interval between two successive inspections is found to be 19 years. For the pipeline, the next inspection is due after 5 years from now. Measurements taken at inspections are used in estimating a new degradation rate that can then be used to update the failure distribution function.     

Risk Management of Domino Effects Considering Dynamic Consequence Analysis

Domino effects are low‐probability high‐consequence accidents causing severe damage to humans, process plants, and the environment. Because domino effects affect large areas and are difficult to control, preventive safety measures have been given priority over mitigative measures. As a result, safety distances and safety inventories have been used as preventive safety measures to reduce the escalation probability of domino effects. However, these safety measures are usually designed considering static accident scenarios. In this study, we show that compared to a static worst‐case accident analysis, a dynamic consequence analysis provides a more rational approach for risk assessment and management of domino effects. This study also presents the application of Bayesian networks and conflict analysis to risk‐based allocation of chemical inventories to minimize the consequences and thus to reduce the escalation probability. It emphasizes the risk management of chemical inventories as an inherent safety measure, particularly in existing process plants where the applicability of other safety measures such as safety distances is limited.     

Response shrinkage estimation in multinomial logit models

A shrinkage estimation method for multinomial logit models is developed. The proposed method is based on shrinking the responses for each category towards the underlying probabilities. The estimator is also used in combination with Pregibon's resistant fitting. The resulting estimator can also be used to control the over-estimation of Pregibon's resistant estimator. The proposed method handles not only the problem of separation in multinomial logit models but estimates also exist when the number of covariates is large relative to the sample size. Estimates exist even when the MLE does not exist. Estimates can be easily computed with all commonly used statistical packages supporting the fitting procedures with weights. Estimates are compared with the usual MLE and Firth's bias reduction technique in a simulation study and an application.     

Subsea Release of Oil from a Riser: An Ecological Risk Assessment

This study illustrates a newly developed methodology, as a part of the U.S. EPA ecological risk assessment (ERA) framework, to predict exposure concentrations in a marine environment due to underwater release of oil and gas. It combines the hydrodynamics of underwater blowout, weathering algorithms, and multimedia fate and transport to measure the exposure concentration. Naphthalene and methane are used as surrogate compounds for oil and gas, respectively. Uncertainties are accounted for in multimedia input parameters in the analysis. The 95th percentile of the exposure concentration (EC_95%) is taken as the representative exposure concentration for the risk estimation. A bootstrapping method is utilized to characterize EC_95% and associated uncertainty. The toxicity data of 19 species available in the literature are used to calculate the 5th percentile of the predicted no observed effect concentration (PNEC_5%) by employing the bootstrapping method. The risk is characterized by transforming the risk quotient (RQ), which is the ratio of EC_95% to PNEC_5%, into a cumulative risk distribution. This article describes a probabilistic basis for the ERA, which is essential from risk management and decision‐making viewpoints. Two case studies of underwater oil and gas mixture release, and oil release with no gaseous mixture are used to show the systematic implementation of the methodology, elements of ERA, and the probabilistic method in assessing and characterizing the risk.     

Knowledge and attitudes towards AIDS: a comparison between Arab and Jewish professionals living in Israel

This paper investigates similarities and differences between Arab and Jewish professionals living in Israel regarding their knowledge and attitudes about AIDS. Although AIDS in Israel is not considered to be a pressing crisis, the aim of the research is to document and analyse what professionals in the helping professions – Arabs and Jews alike – know and how they feel about AIDS. The study also explores thoughts and feelings concerning AIDS–related education and training. This is the first scholarly attempt to compare Israeli and Arab professionals' attitudes and knowledge about such a stigmatised topic as the AIDS epidemic. The study sample consists of 350 professionals, including 218 Jews and 132 Arabs, working in various social and health–care agencies providing services to the Arab population. Professionals include social workers, nurses, occupational therapists, psychologists, and special education teachers and counsellors. Results indicate that Jewish professionals scored significantly higher on both knowledge and attitude scales than did their Arab counterparts. Two regression models predicting both knowledge and attitudes are presented, and their implications are discussed using several frameworks: the status of the disease, including perception of the threat; perception of adequacy of training; educational environment; and the socialisation process of Arab professionals in Israel     

Participation in leisure activities by Arab adults with intellectual disabilities living in the community

Azaiza F, Rimmerman A, Croitoru T, Naon D. Participation in leisure activities by Arab adults with intellectual disabilities living in the community Int J Soc Welfare 2011: 20: 97–103 © 2009 The Author(s), Journal compilation © 2009 Blackwell Publishing Ltd and the International Journal of Social Welfare. The present research study examined factors affecting participation in leisure activities of Arab adults with intellectual disabilities living in the community, via the conceptual frame of the ICF (International Classification of Functioning Disability and Health). The research was based on a secondary analysis of data taken from a nationwide survey, thus being the first of its kind. The factors examined were bodily functions (health condition, physical functioning and cognitive functioning); activities (activities of daily living, instrumental activities of daily living); participation in employment; and the environmental factor of service utilisation (N= 153). The findings reveal interesting patterns regarding the roles of physical functioning and cognitive functioning in participation in leisure activities. These findings are discussed in relation to previous findings and cultural characteristics with reference to socio‐economic disparities.     

Structural social work and the compatibility of NGO approaches: a case analysis of Bangladesh Rural Advancement Committee (BRAC)

This article offers a comparative analysis between the ideological orientation of structural social work (SSW) and the programmatic orientation of the Bangladesh Rural Advancement Committee (BRAC). SSW sees social problems as arising from specific socio-economic contexts rather than from the failings of individuals. This perspective recognises that patriarchy is a central feature of life in Bangladesh. BRAC analyses poverty, broadly defined, from a perspective that is political, making use of feminist principles. By assessing SSW as it pertains to the programme coverage of BRAC, this article presents the consistencies and inconsistencies of the approaches. Yet, SSW and BRAC share a common objective of shifting the locus of power to facilitate the empowerment of marginalised communities.     

Textual data transformations using natural language processing for risk assessment

Underlying information about failure, including observations made in free text, can be a good source for understanding, analyzing, and extracting meaningful information for determining causation. The unstructured nature of natural language expression demands advanced methodology to identify its underlying features. There is no available solution to utilize unstructured data for risk assessment purposes. Due to the scarcity of relevant data, textual data can be a vital learning source for developing a risk assessment methodology. This work addresses the knowledge gap in extracting relevant features from textual data to develop cause–effect scenarios with minimal manual interpretation. This study applies natural language processing and text-mining techniques to extract features from past accident reports. The extracted features are transformed into parametric form with the help of fuzzy set theory and utilized in Bayesian networks as prior probabilities for risk assessment. An application of the proposed methodology is shown in microbiologically influenced corrosion-related incident reports available from the Pipeline and Hazardous Material Safety Administration database. In addition, the trained named entity recognition (NER) model is verified on eight incidents, showing a promising preliminary result for identifying all relevant features from textual data and demonstrating the robustness and applicability of the NER method. The proposed methodology can be used in domain-specific risk assessment to analyze, predict, and prevent future mishaps, ameliorating overall process safety.     

Risk Analysis of Dust Explosion Scenarios Using Bayesian Networks

In this study, a methodology has been proposed for risk analysis of dust explosion scenarios based on Bayesian network. Our methodology also benefits from a bow‐tie diagram to better represent the logical relationships existing among contributing factors and consequences of dust explosions. In this study, the risks of dust explosion scenarios are evaluated, taking into account common cause failures and dependencies among root events and possible consequences. Using a diagnostic analysis, dust particle properties, oxygen concentration, and safety training of staff are identified as the most critical root events leading to dust explosions. The probability adaptation concept is also used for sequential updating and thus learning from past dust explosion accidents, which is of great importance in dynamic risk assessment and management. We also apply the proposed methodology to a case study to model dust explosion scenarios, to estimate the envisaged risks, and to identify the vulnerable parts of the system that need additional safety measures.     

Development of Economic Consequence Methodology for Process Risk Analysis

A comprehensive methodology for economic consequence analysis with appropriate models for risk analysis of process systems is proposed. This methodology uses loss functions to relate process deviations in a given scenario to economic losses. It consists of four steps: definition of a scenario, identification of losses, quantification of losses, and integration of losses. In this methodology, the process deviations that contribute to a given accident scenario are identified and mapped to assess potential consequences. Losses are assessed with an appropriate loss function (revised Taguchi, modified inverted normal) for each type of loss. The total loss is quantified by integrating different loss functions. The proposed methodology has been examined on two industrial case studies. Implementation of this new economic consequence methodology in quantitative risk assessment will provide better understanding and quantification of risk. This will improve design, decision making, and risk management strategies.