Multi-Objective Stochastic Optimization for Preventive Maintenance Planning

PresentationMaintenance is an essential part of mechanical integrity programs and aims to prevent the occurrence of process safety incidents and costly unplanned shutdowns. Maintenance can increase the reliability of equipment in productive systems and effective preventive maintenance programs enable maintenance activities to be planned proactively. However, maintenance planning is subject to resource scarcity and is rendered nontrivial due to system complexity, reliability model nonlinearity, and parametric uncertainty. Multi-objective stochastic mixed-integer nonlinear programming is well suited to addressing these challenges and is adopted here to optimize the time intervals in which to perform maintenance on different pieces of equipment. Following presentation of an optimal maintenance planning framework, a model is formulated and optimized accounting for: the effect of imperfect repair using an effective age model, equipment failure behavior using a Weibull reliability model, endogenous uncertainty in reliability model parameters, and the simultaneous need to satisfy the competing objectives of cost minimization and reliability maximization using the ε-constraint method. The results of the research consist of optimal maintenance plans, plots of resultant equipment and system reliability over time, and a Pareto frontier of optimal solutions from which the decision maker can select. The approach adopted here is illustrated with a case study and can be extended to improving the overall availability, effectiveness, and resilience of a variety of productive systems

Buckets to Disaster: What to Avoid in Making Critical Decisions

PresentationThis paper offers an approach to the development of techniques and tools to teach risk-based decision analysis and complex decision analysis to minimize the disastrous outcomes of critical decisions taking in the worlds of plant operations and engineering. Risk Based Decision Management (RBDM) and critical decision analyses are not taught in the curricula of the engineering programs at any major university. Engineers and other technical staff are promoted based on their abilities and the assumption that their experience will guide them to make robust decisions when needed particular in the heat of the moment when time is of the essence. The historical incident record brings this assumption into question. Decisions made by individuals or teams on behalf of companies can lead to disastrous outcomes and significant consequences that have the potential to cause significant losses. This paper proposes a basis for the development of materials to prepare curricula to teach RBDM as part of undergraduate and graduate courses in a very structured and logical manner. RBDM techniques draw on the sports world in which elite teams have developed programs to teach decision making based on reading and reacting in game situations to enhance the chances of positive outcomes. These high-performing teams learn, through many hours of focused practice, how to apply risk-reward paradigms to take decisions in very dynamic and stressful game situations. We all can learn from the sports techniques and processes and apply them in other fields. Based on the analyses of several incidents with disastrous outcomes, the common themes that reoccur in decision making are identified as “buckets” which must be avoided to reduce the possibility of negative outcomes from decisions. The definition and rationale behind these buckets provide the basis of an approach to assist decision makers in taking more rational decisions during engineering projects or operations. Another benefit of analyzing incidents through the eyes of risk (i.e. the decisions implicated in the disastrous consequences) is a better understanding of “what went wrong” and hence an improved ability to more effectively learn from past incidents. Learning from incidents in a global sense has not proven to be effective in the past

Safety-centered process control design based on dynamic safe set

PresentationDespite significant efforts to make operation of chemical plants safer, the occurrence of incidents clearly indicates the need for better design approaches. Studies to identify the root causes of incidents in hydrocarbon industries reveal that poor design and inadequate control systems contribute to more than 20% of the offshore incidents[1] and 30% of the thermal runaway incidents [2] analyzed. Characterizing and quantifying process safety performance is a complex problem. Traditional control engineers used the concept of phase margin and gain margin to measure the stability of single feedback loops. Although it can be viewed as a measure of safety, the method does not account for multiloop interactions and the presence of constraints in the system. More recently, researchers have used model predictive control (MPC) theory to address safety concerns. The objective of the MPC optimization problem is maximization of cost and other performance metrics, where safety is modelled as a set of additional constraints that must be enforced. The approach is not adequate as there is not a clear method to quantify the safety performance for application in design. Process safety engineering concepts emerge from cause-effect based analysis like HAZOP analysis, fault trees and event trees. These methods do not account for multivariable and non-linear interactions. The objective of this research is to develop an approach for the process control problem with safety as the primary target. In this paper, the concept of dynamic safe set (DSS) is formulated. The DSS is a set of states of the process that guarantee enforcement of safety critical constraints, in the presence of bounded safety threatening disturbances. Already existing mathematical concepts from the systems literature, namely maximal output admissible sets [3, 4] and the reference governor theory[5, 6] are used for evaluating the DSS. The DSS is calculated around a steady-state operating point. It is safe in the sense that if the initial state belongs to the DSS, then for all modeled disturbances the closed-loop system is guaranteed to not violate the constraints at any time in the future. The safety threatening disturbances that can increase the possibility of safety constraint violation by pushing the system to a risky operation zone are also modeled while calculating the DSS. A method to quantify the size of the DSS is also proposed by defining the concept dynamic safety margin (DSM). It is defined as the minimum distance of the steady-state operating point from the boundary of DSS. The DSM margin is relevant and important because it is not possible to model all possible disturbances. That is, a DSS with larger DSM will be able to handle unmodeled random disturbances that push the states away from the steady-state. This will be used as a safety performance metric for control system design. This will lead to designing processes with safety as the primary objective and all other performance metrics are treated as secondary considerations. The DSS approach is also extended to applications in abnormal event management. Under upset scenarios, there is often a need for sudden and large set-point changes. To safely respond to those changes, control strategies need to be designed to stay away from the safety critical constraints. For this purpose, the concept of reference governor is used. The reference governor is a supervisory nonlinear control scheme that works along with an existing closed-loop system. The DSS approach is tested on an exothermic process in a CSTR. The approach helped in selecting the operating condition of the process by identifying steady-states that are relatively safer. The closed loop process design was studied under proportional (P) and proportional- integral (PI) control strategies. It showed that the controller parameters played a significant role on the DSM of the process. The trade-off between control and safety performance can be analyzed using the DSM concept. The effect of maximum available control input on the system’s safety performance was also investigated. The reference governor was also implemented to the CSTR. The dynamic responses of the process under large disturbances, demonstrate significantly superior control performance when compared to the process without reference governor

Probabilistic Methods of Quantitative Risk Analysis: A Case Study with Bayesian Networks and Petri Nets Approach

PresentationConventional risk assessment methods such as Bow Ties have been incapable of capturing the dynamic nature of a system and hence have failed to properly predict the time dependent failure of barriers. Modifications made to incorporate time dependencies in such methods have not found wide application yet. Rapidly changing physical parameters necessitate techniques capable of considering the dynamic aspects of a system throughout its lifetime. The present work is aimed at demonstrating the applicability of Bayesian Networks and Petri Nets to capture the time dependencies of systems to carry out a quantitative risk analysis. A case study is to be carried out using both Bayesian Network and Petri Nets to provide an insight into the pros and cons of using each method to model the system. This insight is to provide a starting point for the development of a model that will enable us to conduct a quantitative risk analysis considering all factors that can lead to an incident

Analysis of enhanced flame speed in the transition droplet sizes for n-alkane aerosols generated by electrospray

PresentationFire and explosion incidents related to aerosol occur occasionally throughout the industries. However, its hazards are relatively overlooked due to the misconception of that liquids are safe below their flash point. As well as scarcity of data stems from the difficulty of aerosol generation by a well-controlled manner. In this research, n-alkane aerosols were produced from an improved electrospray device, and their flame speeds were measured to verify the transition range. When droplet sizes fell into this range, the flame speed would be enhanced and pose greater threats to people and surroundings. Theoretic simulation and empirical equation were performed to predict the trend of flame propagation. Application of convective droplet evaporation improved the theoretic simulation but still failed to recognize the transition range. On the other hand, the empirical equation provided a good fitting and explained possible reason for the trend. It should notice that the transition droplet size range is not a fixed range for aerosols. Therefore, process design and operation should consider the potential generation of aerosol size and location of transition range to reduce the hazards. By understanding the flammability of aerosol, the associated risk can be managed to an acceptable level

Heat transfer modeling of high expansion foam application for vapor risk mitigation of Liquefied Natural Gas (LNG) spills

PresentationThe consumption of natural gas is expected to increase significantly over the next few decades due to much less carbon dioxide emission per unit of energy, when compared to other sources like oil or coal. This has also been facilitated by availability of a large number of reserves and improvements in fracking technologies. Liquefaction of natural gas enables ease of storage and transportation because of a high ratio of liquid to vapor density, especially over long distances when constructing pipelines is economically infeasible. While presenting many advantages, there are several safety concerns involved in the handling of LNG. A spill of cryogenic LNG can absorb heat from the surroundings and form a vapor cloud which has the potential to ignite and presents an asphyxiation hazard. In addition, this vapor cloud can migrate downwind near ground level because of a density greater than air. The National Fire Protection Association suggests application of high expansion foam to mitigate LNG vapor risk. Foam blocks the effects of convection and radiation on an LNG pool and warms rising LNG vapors. Understanding the heat transfer mechanisms between the applied foam and LNG is important to quantify its mitigation effect and determine the amount of foam to be applied for effective vapor risk mitigation. This work aims to address some of the gaps observed in previous efforts towards heat transfer modeling of foam applied on LNG spills

A Strategy Based on Aspen Plus for Venting and Leaks from Vessels

PresentationSevere accidents have occurred when vessels release their contained material either accidentally or intentionally to prevent further catastrophic accidents. Several models have been developed to deal with simulating these events where rigorous thermodynamic procedures are used to improve the estimation. The approach developed in this work takes advantage of the commercial software Aspen Plus to estimate all required thermodynamic properties including estimation of sonic releases. The procedure is developed in the Excel environment where the strategy is programmed to call and run an Aspen Plus file, while keeping control on the integration to solve a quasi-steady-state model. The simple Euler method is applied to solve the dynamic release model. Physical characteristics of the vessel can easily be incorporated to detect the releasing phase. The releasing behavior is modelled with the internal models for valves include in Aspen Plus, where sonic estimation is already implemented. Estimation takes advantage of the simulation package and results are in good agreement with experimental data reported in the literature

Roles of Contractors in Process Safety

PresentationProcess safety starts at the conceptual phase and continues throughout the entire life cycle of an asset. From process selection to de-commissioning, various process safety elements govern the safety and reliability of the total system. Contractors play a crucial role in project execution including detailed design, technology selection, plant layout, commissioning, start-up, and further expansion, modification and maintenance activities. The interface/interaction of the contractor with the operator/owner often defines the importance of process safety throughout this life cycle. Undoubtedly, these are the most critical phases of a plant life cycle which could trigger an unexpected or uncontrolled situation leading to a catastrophic incident. This paper discusses the impact of the contractors’ role during major process safety events including the Phillips explosion in Pasadena (1989), Sonat vessel failure (1998), Texas City Refinery explosion (2005), T2 Laboratories explosion (2007) and a few others. Lessons from past incidents are highlighted and an in-depth analysis is conducted to identify essential process safety components for different groups of contractors and for the different phases of projects. Different aspects of process safety functional elements are presented and discussed for both greenfield and brownfield projects. A Comprehensive understanding of process safety and risk management is required by all levels of contractors to ensure risk-based decision making and hazard mitigation. Besides the process safety expertise needed by the contractors, the necessity of having a consistent and harmonized interaction between the operators/owners and the contractors is also emphasized

Modeling the blanketing and warming effect of high expansion foam used for LNG vapor risk mitigation

PresentationNatural Gas is a cleaner energy when compared to other sources like oil or coal. Its consumption has been drastically increasing over the past few years and is projected to increase further. Liquefying natural gas is an effective way of easily storing and transporting it because of the high ratio of liquid to vapor densities. However, a leak of liquefied natural gas (LNG) can result in the formation of a huge vapor cloud, which poses a potential risk. This cryogenic vapor cloud has the potential to ignite and can migrate downwind near ground level because of a density greater than air. NFPA recommends the use of high expansion foam to mitigate the vapor hazard due to LNG. The primary objective of this paper is to study the effects of heat transfer mechanisms like convection and radiation on foam breakage to be able to accurately quantify the amount of foam required to mitigate the vapor risk of LNG spills