Uncertainty aspects in process safety analysis

Uncertainties of input data as well as of simulation models used in process safety analysis (PSA) are key issues in the application of risk analysis results. Mostly, it is connected with an incomplete and uncertain identification of representative accident scenario (RAS) and other vague and ambiguous information required for the assessment of particular elements of risk, especially for determination of frequency as well as severity of the consequences of RAS. The authors discuss and present the sources and types of uncertainties encountered in PSA and also methods to deal with them. There are different approaches to improve such analysis including sensitivity analysis, expert method, statistics and fuzzy logic. Statistical approach uses probability distribution of the input data and fuzzy logic approach uses fuzzy sets. This paper undertakes the fuzzy approach and presents a proposal for fuzzy risk assessment. It consists of a combination of traditional part, where methods within the process hazard analysis (PHA) are used, and “fuzzy part”, applied quantitatively, where fuzzy logic system (FLS) is involved. It concerns frequency, severity of the consequences of RAS and risk evaluation. In addition, a new element called risk correction index (RCI) is introduced to take into account uncertainty concerned with the identification of RAS. The preliminary tests confirmed that the final results on risk index are more precisely and realistically determined.     

Factors affecting conviction rates of intoxicated driver patients in two large trauma centers

Objective: Outcomes from previous studies report the driving under the influence (DUI) conviction rates for trauma patients in several cities within Canada and the United States over the last 2 decades. This study reports charge, conviction, and prosecution rates for trauma patients at 2 level I trauma centers servicing a large metropolitan city.

Methods: A retrospective review of the trauma databases was completed to identify patients meeting inclusion criteria. Four hundred sixty patients were identified and their records were compared with the district attorney's records for DUI charges and convictions.

Results: The conviction rate for this study was 8.7%, demonstrating continued low rates of conviction despite growing interest and public awareness of drinking and driving.

Conclusions: We discuss legal considerations that providers should consider when treating patients who have been drinking and driving.     

Integration studies on a two-stage fermentation process for the production of biohydrogen

Fermentation of biomass residues and second generation biomasses is potentially a way to enable a sustainable production of hydrogen. Simulation models which calculate mass and energy balances, developed with Aspen Plus^®, are used to integrate the process steps necessary to produce pure hydrogen from biomass in a 2-stage fermentation process. Process and heat integration are introduced to reduce the high water and heat demand of the process, connected to the low substrate concentrations in the involved process streams. The results show that the recirculation of process effluents, together with the use of properly designed heat exchangers, can reduce the water and heat demand up to 90% from a non-integrated process, but is also subject to restrictions due to an increase in osmolality in the system.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

The implementation of the SEVESO II legislation in the Polish major hazard industry

The paper presents the implementation of the SEVESO II Directive in Poland. Particularly, a systematic approach to the realization of MAPP, Safety Report and Emergency Plan is shown. It takes into account the real technical and organizational standards of the Polish major hazard industry as well. The impact of the implementation of SEVESO II Legislation on safety performance changes in particular major hazard companies was assessed using the questionnaires method of data collection. The fundamental question of that survey was: did that exercise improve safety performance or was it just a ‘paper work’? The majority of survey reported more positive than negative comments. The conclusions were drawn and some suggestions were made to improve major accident control in Poland.     

Fuzzy logic for piping risk assessment (pfLOPA)

This paper explores the application of the fuzzy logic for risk assessment of major hazards connected with transportation of flammable substances in long pipelines. As a basis for risk assessment, the framework of the fuzzy Layer of Protection Analysis (fLOPA) was used. fLOPA presents a new approach to risk assessment based on two assumptions: 1. different effects of the layer of protection functions on particular elements of the risks (frequency and severity of consequence), and 2. the application of fuzzy logic system (FLS) composed of three elements: fuzzification, inference process and defuzzification. A further calculation follows LOPA methodology with the use of fuzzy logic system where fuzzy risk matrix is used for risk assessment. A typical case study comprising section of a long pipeline failure is performed and a comparison between the classical LOPA approach and fuzzy approach is made.     

Application of fuzzy logic to explosion risk assessment

Safety and health of workers potentially being at risk from explosive atmospheres are regulated by separate regulations (ANSI/AIHA in USA and ATEX in the European Union). The ANSI/AIHA does not require risk assessment whereas it is compulsory for ATEX. There is no standard method to do that assessment. For that purpose we have applied the explosion Layer of Protection Analysis (ExLOPA), which enables semi-quantitative risk assessment for process plants where explosive atmospheres occur. The ExLOPA is based on the original work of CCPS for LOPA taking into account an explosion accident scenario at workplace. That includes typical variables appropriate for workplace explosion like occurrence of the explosive atmosphere, the presence of effective ignition sources, activity of the explosion prevention and mitigation independent protection layers as well as the severity of consequences. All those variables are expressed in the form of qualitative linguistic categories and relations between them are presented using expert based engineering knowledge, expressed in the form of appropriate set of rules. In this way the category of explosion risk may be estimated by the semi-quantitative analysis. However, this simplified method is connected with essential uncertainties providing over or under estimation of the explosion risk and may not provide real output data.In order to overcome this problem and receive more detailed quantitative results, the fuzzy logic system was applied. In the first stage called fuzzification, all linguistic categories of the variables are mapped by fuzzy sets. In the second stage, the number of relation between all variables of analysis are determined by the enumerative combinatorics and the set of the 810 fuzzy rules “IF-THEN” is received. Each rule enables determination of the fuzzy risk level for a particular accident scenario. In the last stage, called defuzzification, the crisp value of final risk is obtained using a centroid method. The final result of the risk presents a contribution of each risk category represented by the fuzzy sets (A, TA, TNA and NA) and is therefore more precise and readable than the traditional approach producing one category of risk only. Fuzzy logic gives a possibility of better insights into hazards and safety phenomena for each explosion risk scenario. It is not possible to receive such conclusions from the traditional ExLOPA calculation results. However it requires the application of computer-aided analyses which may be partially in conflict with a simplicity of ExLOPA.The practical example provides a comparison between the traditional results obtained by ExLOPA and by fuzzy ExLOPA methods.     

Estimation of energy demand of fermentation-based hydrogen production

The paper is concerned with estimation of heat and power consumption in a conceptual plant to produce hydrogen from sucrose-containing or starchy biomass by fermentation. A hydrogen plant connected with a sugar factory is regarded as the basic option; the sugar factory serves as a source of sucrose-containing thick juice for the hydrogen plant, where this feedstock is processed to hydrogen. As another option, a stand-alone hydrogen plant in which starch must initially be converted to fermentable glucose solution is considered. The values of key process parameters are assumed on the basis of preliminary experimental data. For both options of the hydrogen plant, heat consumption is estimated taking heat recovery in a heat exchanger network into account. Power consumption is estimated by calculating power needed for pumping of liquid and gaseous process media.