Browsing by Subject "Process Safety"
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Item Mathematical Programming Formulations for the Optimal Placement of Imperfect Detectors with Applications to Flammable Gas Detection and Mitigation Systems(2014-11-13) Benavides Serrano, Alberto J.The placement of detectors in mitigation systems is a difficult problem usually addressed in the industry via qualitative and semiquantative approaches. Simplifications are used to circumvent difficulties regarding problem size, parameter uncertainty, and lack of information concerning leak development. Given recent improvement of consequence modeling tools, the use of a stochastic Mixed-Integer Linear Programming (MILP) formulation (SP) was previously proposed to quantitatively approach this problem. This formulation minimizes the expected damage over a large set of gas leak scenarios while assuming perfect detectors. In reality gas detectors are prone to false positives and false negatives. Two solutions are usually implemented in the process industries. First, additional confirmation from several detectors (i.e., voting) is required before emergency actions are triggered in order to avoid false positives. Second, in order to avoid false negatives, the unavailability of the detectors is considered in the placement strategy. Unavailability corresponds to the probability that the detector will not be able to perform its intended function when required. In the first part of this dissertation, two problem formulations were developed and validated to address the issue of imperfect detectors: minimization of expected damage considering unavailability (SP-U) and minimization of the expected damage considering unavailability and voting (SP-UV). SP-U and SP-UV placement results were compared with those obtained assuming perfect detectors. Results demonstrate that explicit consideration of unavailability and voting effects alters the final detector placement. Quantitative risk can be significantly higher if we neglect these issues when solving for the optimal placement. Furthermore, SP-UV placement results were compared with those of four existing approaches for gas detector placement using three different performance metrics in accordance to the objectives of gas detection systems. Results provide further evidence on the effectiveness of the use of dispersion simulations, and mathematical programming, to supplement the gas detector placement problem. Formulation SP-U assumes a uniform unavailability across all detector types and locations. In the second part of this work, this assumption is relaxed via formulation SPqt, which considers non-uniform dynamic detector unavailabilities. Relaxing this assumption results in a Mixed-Integer NonLinear Programming (MINLP) formulation. SPqt, being an extension of SP-U, explicitly considers di?erent backup detection levels, allowing an approximation where the maximum degree of the nonlinear products considered can be determined by the modeler. The effect of reducing the number of detection levels was analyzed. For the problem, results shown that two detection levels are sufficient to find objective values within 1% of the optimal solution. Considering two detection levels reduces the MINLP formulation to a zero-one quadratic formulation (SPqt-Q). A solution quality comparison between SPqt-Q and approximate solution strategies previously proposed in the literature demonstrates its suitability to obtain approximate answers for the general nonlinear problem. Two exact linear reformulation strategies (SPqt-L1 and SPqt-L2) were proposed for SPqt-Q and validated from the computationally efficiency perspective. All the results presented were obtained by using four real data sets provided by Gex-Con. The data corresponds to FLACS CFD dispersion simulations including the full geometric features of an offshore facility and capturing the uncertainty in the leak characteristics. Additionally, real unavailability values were obtained from industry gas detector reliability databases. The work presented here constitutes a step forward toward the achievement of a realistic detector placement formulation that includes current industrial practice for these important safety systems.Item Methods to Improve Process Safety Performance through Flange Connection Leak Prediction and Control(2014-08-08) Nelson, JeremyProcess safety is a task of preventing leaks. Leak prevention is critical because pressure vessels and piping assets in chemical plants are fabricated from materials which have limited corrosion resistance. When corrosive compounds are processed in these assets, they may suffer degradation over time due to thinning, cracking, or loss of their material properties. This problem is partially controlled by applying a safety margin known called a corrosion allowance. The corrosion allowance is determined by predicting the asset?s expected corrosion rate and its service life. However, this fixed safety margin does not consider the inherent uncertainty in an individual asset?s degradation rate due to variability in the material?s corrosion resistance, the operating parameters of the process, and the inspection techniques used to measure the progression of corrosion damage over time. Consequently, deterministic analysis is not capable of precisely estimating an asset?s safe operating life during its design stage. One of the most likely areas for leakage to occur in process equipment is at the flange connections that join assets together. Risk analyses for planning inspections of fixed equipment and piping usually treat flanges as components of their parent asset. This thesis focuses on methods to improve prediction and control of corrosion and leakage at flange connections in particular. Flange connection seal tightness can be monitored through vibration-based Non-Destruction Testing (NDT). The data gathered from this monitoring can be used to update risk models for flange connection leakage. Hierarchical Bayesian Network methods of modeling risk are demonstrated in this thesis to be capable of predicting probability of seal failure based on the mean and variance of failure rates in a population of flange connections. This allows for prediction of the probabilities based on corrosion and leak events in the plant. The results of inspection techniques are used as inputs to this risk model, enabling probabilistic decision-making.Item Modeling of LNG Pool Spreading and Vaporization(2012-11-20) Basha, Omar 1988-In this work, a source term model for estimating the rate of spreading and vaporization of LNG on land and sea is introduced. The model takes into account the composition changes of the boiling mixture, the varying thermodynamic properties due to preferential boiling within the mixture and the effect of boiling on conductive heat transfer. The heat, mass and momentum balance equations are derived for continuous and instantaneous spills and mixture thermodynamic effects are incorporated. A parameter sensitivity analysis was conducted to determine the effect of boiling heat transfer regimes, friction, thermal contact/roughness correction parameter and VLE/mixture thermodynamics on the pool spreading behavior. The aim was to provide a better understanding of these governing phenomena and their relative importance throughout the pool lifetime. The spread model was validated against available experimental data for pool spreading on concrete and sea. The model is solved using Matlab for two continuous and instantaneous spill scenarios and is validated against experimental data on cryogenic pool spreading found in literature.Item Safety-oriented Resilience Evaluation in Chemical Processes(2012-02-14) Dinh, Linh Thi ThuyIn the area of process safety, many efforts have focused on studying methods to prevent the transition of the state of the system from a normal state to an upset and/or catastrophic state, but many unexpected changes are unavoidable, and even under good risk management incidents still occur. The aim of this work is to propose the principles and factors that contribute to the resilience of the chemical process, and to develop a systematic approach to evaluate the resilience of chemical processes in design aspects. Based on the analysis of transition of the system states, the top-level factors that contribute to Resilience were developed, including Design, Detection Potential, Emergency Response Planning, Human, and Safety Management. The evaluation framework to identify the Resilience Design Index is developed by means of the multifactor model approach. The research was then focused on developing complete subfactors of the top-level Design factor. The sub-factors include Inherent Safety, Flexibility, and Controllability. The proposed framework to calculate the Inherent Safety index takes into account all the aspects of process safety design via many sub-indices. Indices of Flexibility and Controllability sub-factors were developed from implementations of well-known methodologies in process design and process control, respectively. Then, the top-level Design index was evaluated by combining the indices of the sub-factors with weight factors, which were derived from Analytical Hierarchical Process approach. A case study to compare the resilience levels of two ethylene production designs demonstrated the proposed approaches and gave insights on process resilience of the designs.Item Stochastic Programming Approaches for the Placement of Gas Detectors in Process Facilities(2013-05-21) Legg, Sean WThe release of flammable and toxic chemicals in petrochemical facilities is a major concern when designing modern process safety systems. While the proper selection of the necessary types of gas detectors needed is important, appropriate placement of these detectors is required in order to have a well-functioning gas detection system. However, the uncertainty in leak locations, gas composition, process and weather conditions, and process geometries must all be considered when attempting to determine the appropriate number and placement of the gas detectors. Because traditional approaches are typically based on heuristics, there exists the need to develop more rigorous optimization based approaches to handling this problem. This work presents several mixed-integer programming formulations to address this need. First, a general mixed-integer linear programming problem is presented. This formulation takes advantage of precomputed computational fluid dynamics (CFD) simulations to determine a gas detector placement that minimizes the expected detection time across all scenarios. An extension to this formulation is added that considers the overall coverage in a facility in order to improve the detector placement when enough scenarios may not be available. Additionally, a formulation considering the Conditional-Value-at-Risk is also presented. This formulation provides some control over the shape of the tail of the distribution, not only minimizing the expected detection time across all scenarios, but also improving the tail behavior. In addition to improved formulations, procedures are introduced to determine confidence in the placement generated and to determine if enough scenarios have been used in determining the gas detector placement. First, a procedure is introduced to analyze the performance of the proposed gas detector placement in the face of ?unforeseen? scenarios, or scenarios that were not necessarily included in the original formulation. Additionally, a procedure for determine the confidence interval on the optimality gap between a placement generated with a sample of scenarios and its estimated performance on the entire uncertainty space. Finally, a method for determining if enough scenarios have been used and how much additional benefit is expected by adding more scenarios to the optimization is proposed. Results are presented for each of the formulations and methods presented using three data sets from an actual process facility. The use of an off-the-shelf toolkit for the placement of detectors in municipal water networks from the EPA, known as TEVA-SPOT, is explored. Because this toolkit was not designed for placing gas detectors, some adaptation of the files is necessary, and the procedure for doing so is presented.Item Well Integrity Diagnostics for Sustained Casing Pressure and Faulty Gas-Lift Valve Based on Pressure Transient Modeling(2014-10-20) Rocha-Valadez, TonyA problem frequently present in the oil and gas industry is the difficulty of measuring well integrity parameters; particularly, for high-pressure high-temperature wells. For this reason, many relevant parameters, indicators of the integrity of the well, are not directly measured but rather qualitatively estimated by testing response variables, sometimes, unfortunately, without understanding the correlation between the key parameter and the response variable. This research presents methodologies to quantitatively evaluate well integrity in wells with sustained casing pressure (SCP) and gas-lifted wells with faulty gas-lift valves (GLV). The phenomenon occurring during these well integrity issues were modeled using the thermodynamic properties and transport phenomena occurring inside the wellbore. Well integrity denotes the ability to maintain intentional isolation between the formation and the well. The consequences of not detecting and managing well integrity issues can go from the activation of rupture discs to a release of oil/gas, fire and/or explosion during a blowout. For the SCP problem, the developed analytic model has been validated against field data and compared to other numerical models showing similar performance. The SCP model allows for early time data to be used to accurately predict the leak?s severity by estimating a seepage factor, which is akin to permeability, to account for leakage occurring through the imperfect cement sheath. In comparison to current practices, the model shortens the testing time and reduces the risk from gas accumulation and pressure buildup, making it an inherently safer testing procedure. The methodology developed to assess wellbore annular integrity, during gas-lift operations, has been compared to acoustic well sounding (AWS) data from different wells. The model divides the well into small elements and estimates average properties which are used to quantify the total amount of mass and hydrostatic pressure in the annulus at any given time. This methodology accurately tracks casinghead pressure and liquid level increase. When fluid intrusion occurs mostly through the gas-lift valve, the model allows estimating the damage coefficient of the faulty GLV. This coefficient serves as a quantitative parameter for GLV replacement; being independent of acoustic well sounding devices. This methodology has the advantages of easy and quick implementation, being accurate, not requiring any specialized equipment, and providing a quantitative damage parameter for the GLV.