A dynamic HAZOP case study using the Texas City refinery explosion

© 2016 Elsevier Ltd. The catastrophic explosion that occurred at Texas City on 23 March 2005 during the start-up of the raffinate splitter resulted in an estimated 15 deaths and 180 injuries. Since the incident, several studies have investigated the root causes of the disaster. Some contributing factors to the incident include wider organisational, process safety management, and human elements. There have also been some attempts to model the sequence of events before the incident, and the consequences of the resulting fires and explosions. This study provides a dynamic model of the sequence of events leading up to the incident and replicates the reported process variables during the isomerisation unit start-up on the day of the incident. The resulting simulation model is used as the framework for a dynamic hazard and operability (HAZOP) study

Diseño para operabilidad: Una revisión de enfoques y estrategias de solución

In the last decades the chemical engineering scientific research community has largely addressed the design-foroperability problem. Such an interest responds to the fact that the operability quality of a process is determined by design, becoming evident the convenience of considering operability issues in early design stages rather than later when the impact of modifications is less effective and more expensive. The necessity of integrating design and operability is dictated by the increasing complexity of the processes as result of progressively stringent economic, quality, safety and environmental constraints. Although the design-for-operability problem concerns to practically every technical discipline, it has achieved a particular identity within the chemical engineering field due to the economic magnitude of the involved processes. The work on design and analysis for operability in chemical engineering is really vast and a complete review in terms of papers is beyond the scope of this contribution. Instead, two major approaches will be addressed and those papers that in our belief had the most significance to the development of the field will be described in some detail.En las últimas décadas, la comunidad científica de ingeniería química ha abordado intensamente el problema de diseño-para-operabilidad. Tal interés responde al hecho de que la calidad operativa de un proceso esta determinada por diseño, resultando evidente la conveniencia de considerar aspectos operativos en las etapas tempranas del diseño y no luego, cuando el impacto de las modificaciones es menos efectivo y más costoso. La necesidad de integrar diseño y operabilidad esta dictada por la creciente complejidad de los procesos como resultado de las cada vez mayores restricciones económicas, de calidad de seguridad y medioambientales. Aunque el problema de diseño para operabilidad concierne a prácticamente toda disciplina, ha adquirido una identidad particular dentro de la ingeniería química debido a la magnitud económica de los procesos involucrados. El trabajo sobre diseño y análisis para operabilidad es realmente vasto y una revisión completa en términos de artículos supera los alcances de este trabajo. En su lugar, se discutirán los dos enfoques principales y aquellos artículos que en nuestra opinión han tenido mayor impacto para el desarrollo de la disciplina serán descriptos con cierto detalle.Fil: Blanco, Anibal Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Applications of dynamic simulations in the process industries : a safety case study using Texas City refinery explosion

Although process safety performance in petroleum refineries is much better today compared to several decades ago, major accidents still occur occasionally. The explosion and fires at Texas City refinery on 23 March 2005 is regarded as one of the worst industrial accidents in US history to date. Dynamic process simulation provides an effective means to collect, collate and analyze data from previous incidents and offer recommendations of good practice to further improve process safety outcomes.A simulation of the sequence of events that led to the catastrophic explosions at Texas City refinery is presented in Aspen HYSYS. An initial steady state simulation of the operation of the raffinate splitter column at Texas City forms the basis for a subsequent dynamic simulation of the filling of the distillation column from 0213hrs until 1313hrs when the explosion occurred. A PID (proportional, integral, derivative) control scheme is implemented with appropriate tuning parameters.The dynamic simulation of the overall tower filling dynamics from 1000hrs to 1320hrs when the explosion occurred revealed that the feed to the column vaporised at approximately 1310 hrs. This happened as a result of the additional heat input into the column through the feed-product heat exchanger. Subsequently, thermal expansion of the liquid in the column led to the filling of the overhead vapour line with hydrocarbon liquids and an increase in pressure as a result of the hydrostatic liquid head. Flammable hydrocarbon vapours subsequently flowed from the overhead line through the collection headers into the blowdown drum. An alternative accident pathway is presented as the basis for a quantitative hazard and operability study, HAZOP

Framework for operability assessment of production facilities: an application to a primary unit of a crude oil refinery

This work focuses on the development of a methodology for the optimization, control and operability of both existing and new production facilities through an integrated environment of different technologies like process simulation, optimization and control systems. Such an integrated environment not only creates opportunities for op¬erational decision making but also serves as training tool for the novice engineers. It enables them to apply engineering expertise to solve challenges unique to the process industries in a safe and virtual environment and also assist them to get familiarize with the existing control systems and to understand the fundamentals of the plant operation. The model-based methodology proposed in this work, starts with the implementation of first principle models for the process units on consideration. The process model is the core of the methodology. The state of art simulation technologies have been used to model the plant for both steady state and dynamic state conditions. The models are validated against the plant operating data to evaluate the reliability of the models. Then it is followed by rigorously posing a multi-optimization problem. In addition to the basic economic variables such as raw materials and operating costs, the so-called “triple-bottom-line” variables related with sustainable and environmental costs are incorporated into the objective function. The methodologies of Life Cycle Assessment (LCA) and Environmental Damage Assessment (EDA) are applied within the optimization problem. Subsequently the controllability of the plant for the optimum state of conditions is evaluated using the dynamic state simulations. Advanced supervisory control strategies like the Model Predictive Control (MPC) are also implemented above the basic regulatory control. Finally, the methodology is extended further to develop training simulator by integrating the simulation case study to the existing Distributed Control System (DCS). To demonstrate the effectiveness of the proposed methodology, an industrial case study of the primary unit of the crude oil refinery and a laboratory scale packed distillation unit is thoroughly investigated. The presented methodology is a promising approach for the operability study and optimization of production facilities and can be extended further for an intelligent and fully-supportable decision making

Model Based Mission Assurance: NASA's Assurance Future

Model Based Systems Engineering (MBSE) is seeing increased application in planning and design of NASAs missions. This suggests the question: what will be the corresponding practice of Model Based Mission Assurance (MBMA)? Contemporaneously, NASAs Office of Safety and Mission Assurance (OSMA) is evaluating a new objectives based approach to standards to ensure that the Safety and Mission Assurance disciplines and programs are addressing the challenges of NASAs changing missions, acquisition and engineering practices, and technology. MBSE is a prominent example of a changing engineering practice. We use NASAs objectives-based strategy for Reliability and Maintainability as a means to examine how MBSE will affect assurance. We surveyed MBSE literature to look specifically for these affects, and find a variety of them discussed (some are anticipated, some are reported from applications to date). Predominantly these apply to the early stages of design, although there are also extrapolations of how MBSE practices will have benefits for testing phases. As the effort to develop MBMA continues, it will need to clearly and unambiguously establish the roles of uncertainty and risk in the system model. This will enable a variety of uncertainty-based analyses to be performed much more rapidly than ever before and has the promise to increase the integration of CRM (Continuous Risk Management) and PRA (Probabilistic Risk Analyses) even more fully into the project development life cycle. Various views and viewpoints will be required for assurance disciplines, and an over-arching viewpoint will then be able to more completely characterize the state of the project/program as well as (possibly) enabling the safety case approach for overall risk awareness and communication

Fuzzy Logic Modeling and Observers Applied to Estimate Compositions in Batch Distillation Columns

In this chapter, the analysis and design of a fuzzy observer based on a Takagi-Sugeno model of a batch distillation column are presented. The observer estimates the molar compositions and temperatures of the light component in the distillation column considering a binary mixture. This estimation aims to allow monitoring the physical variables in the process to improve the quality of the distillated product as well as to detect failures that could affect the system performance. The Takagi-Sugeno fuzzy model is based on eight linear subsystems determined by three premise variables: the opening percentage of the reflux valve and the liquid molar composition of the light element of the binary mixture in the boiler and in the condenser. The stability analysis and the observer gains are obtained by linear matrix inequalities (LMIs). The observer is validated by MATLAB® simulations using real data obtained from a distillation column to verify the observer’s convergence and analyze its response under system disturbances

Molecular modeling for physical property prediction

Multiscale modeling is becoming the standard approach for process study in a broader framework that promotes computer aided integrated product and process design. In addition to usual purity requirements, end products must meet new constraints in terms of environmental impact, safety of goods and people, specific properties. This chapter adresses the use of molecular modeling tools for the prediction of physical property usefull for chemical engineering practice