Chemical Processing Plant Research Articles

Modeling and experimental analysis of packed column for SO2 emission control process

Sulfur dioxide (SO2) emissions from chemical process plants are increasing at an alarming rate. It is necessary to implement the best methodology to reduce the SO2 emissions. This paper presents physical modeling, computational fluid dynamics (CFD) analysis, and experimental analysis of a packed column used for flue gas desulfurization (FGD) process to reduce SO2 emission at a greater extent. The packed column parameters such as liquid/gas (L/G) ratio, diameter, packed height and total height were determined using physical modeling with two–film gas–liquid absorption theory. Simulation model of the packed column is developed by GAMBIT 2.2.30 and analysis is carried out by FLUENT 6.2.16. In CFD analysis, hydrogen peroxide (H2O2) (with different concentrations) was used as an absorbent. CFD simulation result ensures that when H2O2 is used as a reactant, better removal efficiency is obtained. Based on the physical modeling and CFD analysis, a lab scale packed column was developed. Experimental result showed that 95% SO2 removal efficiency is achieved for 0.1M H2O2 as a reactant. Experimental results agreed excellently with the developed CFD model and can be used for designing industrial packed columns.

An Experimental Study on Three General Interface Layout Designs for Chemical Process Plants

AbstractThe human‐machine interface design is not a new problem; however, existing knowledge appears to be focused either on interface conceptual design, which determines what information at what time needs to be displayed, or on interface detailed design, which determines the form of display elements. This article presents a study on interface layout design. Three interface layout designs were proposed based on the proximity compatibility priniciple, which were on the same interface conceptual design. In particular, the first interface layout design is with the highest degree of proximity cognition and the second and third with a reduced degree of proximity cognition. They are called sophisticated, semisophisticated, and nonsophisticated interfaces, respectively. An experiment with a simple process plant was conducted to understand user behaviors on the three interfaces. It is noted that in order to provide an unbiased comparative evaluation of these interfaces the same application problem and similar look‐and‐feel forms of interfaces were designed. In the experiment, three general classes of tasks were considered, namely, normal control operation, fault detection (or monitoring), and fault diagnosis. Two categories of measures were used: the performance measure and the subjective measure. The major results obtained from the experiment are 1) the nonsophisticated interface is the best for fault detections in terms of performance measure; besides, this interface has the lowest mental workload for fault detection; 2) the sophisticated interface is the best for normal operation in terms of performance measure; 3) there appears no significant difference for fault diagnosis in terms of performance measures for all these three interfaces; 4) for normal operation and fault diagnosis, the mental workloads for the three interfaces have no significant difference. Overall, the experiment suggests that the nonsophisticated interface be used in practice with additional two reasons: 1) most of time in the chemical process plant today is the fault detection or operation monitoring task, and 2) it is relatively easier for the nonsophisticated interface to adapt to changes in the chemical process plant design, which are common in today's manufacturing environments.

Wind Energy Facility Siting: Learning from Experience and Guides for Moving Forward

Renewable energy technologies, like wind turbines, solar arrays, and biomass (and biogas) plants, and carbon reduction technologies, such as carbon storage and sequestration (CSS), will be a critical part of future energy supplies as the United States and other countries seek ways to reduce carbon emissions. Renewable energy technologies can be perceived as hazardous and undesirable, much to the surprise of some. Siting failures can be high and unexpected. Broad, general support for renewable energy can give way to more polarization about specific proposals. While a growing literature exists about the formation of public support and opposition to wind and other renewable energy technologies, lessons relevant to the wind industry can be found from past experiences relating to hazardous technologies, including chemical processing plants, nuclear waste facilities, nuclear power plants, incinerators, and hazardous and municipal landfills, and locally unwanted land uses, such as airports, transmission lines, schools, and housing developments. There has been little direct application of this broad source of knowledge to wind or other renewable energy siting literature. We review this literature to identify factors that contribute to public support and opposition. Substantial increases in the contribution of wind energy to the US energy mix will require leadership at both the federal and state levels. We end by proposing several strategies for improving future wind energy siting efforts.

Incident investigation in Pakistan's fertilizer industry—Common safety management system failures and issues

The learning from operational incidents plays a key role in improving the performance and safety of the chemical process plants. In this article, the incidents occurred during January 2011 to April 2012 in different sections, that is, Ammonia, Urea, and Utility Units of fertilizer sector in Pakistan have been analyzed using Why Tree analysis. The aim is to identify the failures in the safety management system to prevent the incidents. One thousand and fifteen, root and contributing causes identified in investigations strongly assert that improvement in safety management systems could have prevented or mitigated the intensity of many of the occurred incidents/accidents. The flaws in mechanical integrity, maintenance procedures and operating procedures, and job risk assessment are the most common recurrent as root cause failures of safety management system. © 2014 American Institute of Chemical Engineers Process Saf Prog 33: 399–404, 2014

Heat Transfer and Turbulent Fluid Flow over Vertical Double Forward-Facing Step

Abstract — Numerical study of heat transfer and fluid flow over vertical double forward facing step were presented. The k-w model with finite volume method was employed to solve continuity, momentum, and energy equations. Different step heights were adopted for range of Reynolds number varied from 10000 to 40000, and range of temperature varied from 310K to 340 K. The straight side of duct is insulated while the side of double forward facing step is heated. The result shows augmentation of heat transfer due to the recirculation region created after and before steps. Effect of step length and Reynolds number observed on increase of local Nusselt number particularly at recirculation regions. Contour of streamline velocity is plotted to show recirculation regions after and before steps. Numerical simulation in this paper done by used ANSYS FLUENT 14. Keywords — Turbulent flow, Double forward, Heat transfer, Separation flow.I. I NTRODUCTION HE crises of energy in global has been encourage researchers to look for new techniques which improve of thermal performance. One of common method to increase efficiency of energy system equipment is by change the design geometry of channel. The fluid flow over forward or backward-facing step found in many practical applications such as heat exchangers, chemical process, turbine blades, and power plants. There are many experimental and numerical study of effect separation flow at forward or backward-facing step on increase of enhancement heat transfer rate. Heat transfer to fluid flow over single and double forward-facing step experimentally studied by Shakouchi and Kajino [1] with using laser Doppler anemometer where the results appeared that the reattachment region by a new heat flux probe, and Oyakawa et al. [2], [3] used jet discharge. Saldana and Anand [4] performed numerical study of laminar fluid flow over a horizontal forward-facing step in three dimensions. They showed that the increase of Reynolds number leads to increase of reattachment length and average Nusselt number.

Non-Constant Prediction-Step MPC for Processes with Multi-Scale Dynamics

Motivated by applications in minerals processing, a novel model predictive control scheme is presented with non-constant prediction step size. In the proposed scheme, the sampling rate of the prediction and control horizons changes, with nearer steps having a shorter sampling period than ones in the more distant future. This approach allows for fine tuning of the control trajectory over the near horizon, whilst still allowing for long prediction and control horizons to account for slow dynamics. This may find application in many chemical and minerals processing plants where process units have multiple time-scale dynamics. Extensions to decentralized control of process networks are presented. The approach is illustrated using an industrial case study.

Economic plantwide control: Automated controlled variable selection for a reactor-separator-recycle process

A systematic plantwide control design procedure was proposed in [Skogestad, 2000]. The main goal of this procedure is, to design an optimal control structure for a complete chemical plant based on steady state plant economics, also known as economic plantwide control. In this work, we automated a key step of this procedure, which is the selection of controlled variables, based on quantitative local methods. We applied the economic plantwide control design procedure to a typical chemical plant process, which consists of a reactor, a separator and a recycle stream with purge. We evaluated the economic performance of the designed control structures for various disturbances and found that, although the automatic selection of the controlled variables was based on local methods, the control structures performed quite well, even for large disturbances.

Steady states for chemical process plants: A legacy code, time‐stepping approach

Given a legacy dynamic simulator of a chemical process plant, we construct a computational procedure that can be “wrapped around” the simulator to compute its steady states (both stable and unstable) and their dependence on input parameters. We apply this approach to the Tennessee Eastman (TE) challenge problem presented by Downs and Vogel, who also provided a FORTRAN process model. Using the FORTRAN simulator as a black‐box input‐output map, we enable it to systematically converge to isolated solutions and study their stability and parametric dependence within the equation‐free framework. The presence of neutrally stable modes in TE problem (due to so‐called inventories), their interplay with the problem formulation and the convergence of the solution procedure is explored and rationalized. Interestingly, our time‐stepper formulation can automatically take advantage of separation of time scales, when present, to enhance computational convergence. The approach enables legacy dynamic simulators to calculate several dynamic problem characteristics useful for controller design and/or process optimization. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3308–3321, 2013

Profit optimization for chemical process plant based on a probabilistic approach by incorporating material flow uncertainties

This paper reports how the economic performance of a chemical process plant is affected by material flow uncertainties from the plant inlet and outlet. Two chance-constrained optimization models were proposed. The models were tested using case studies of an existing gas processing plant. Profit optimization for the case studies was made with respect to the reliability of holding the process constraints at a certain confidence level [0.5, 1]. The optimal profit change for uncertainty from the plant inlet within the confidence interval [0.96, 1] was 86%. On the other hand, the optimal profit change for uncertainty from the plant outlet was only 2% for the same confidence level interval considered. This suggests that the uncertainty from the plant inlet has a major impact on the overall economic performance of the plant. Sensitivity analysis showed how uncertain parameters from both plant sides can affect the overall profit significantly.

Framework methodology for increased energy efficiency and renewable feedstock integration in industrial clusters

Energy intensive industries, such as the bulk chemical industry, are facing major challenges and adopting strategies to face these challenges. This paper investigates options for clusters of chemical process plants to decrease their energy and emission footprints. There is a wide range of technologies and process integration opportunities available for achieving these objectives, including (i) decreasing fossil fuel and electricity demand by increasing heat integration within individual processes and across the total cluster site; (ii) replacing fossil feedstocks with renewables and biorefinery integration with the existing cluster; (iii) increasing external utilization of excess process heat wherever possible. This paper presents an overview of the use of process integration methods for development of chemical clusters. Process simulation, pinch analysis, Total Site Analysis (TSA) and exergy concepts are combined in a holistic approach to identify opportunities to improve energy efficiency and integrate renewable feedstocks within such clusters. The methodology is illustrated by application to a chemical cluster in Stenungsund on the West Coast of Sweden consisting of five different companies operating six process plants. The paper emphasizes and quantifies the gains that can be made by adopting a total site approach for targeting energy efficiency measures within the cluster and when investigating integration opportunities for advanced biorefinery concepts compared to restricting the analysis to the individual constituent plants. The holistic approach applied highlights the significant potential improvement to energy and emissions footprints that can be achieved when applying a total site approach.

Understanding the Impacts of Indirect Stakeholder Relationships Stakeholder Value Network Analysis and Its Application to Large Engineering Projects

In order to understand the strategic implications of indirect stakeholder relationships on large engineering projects, this research develops a qualitative/quantitative network approach, namely the Stakeholder Value Network analysis, to model the multiple relationships between stakeholders as value exchanges. With theoretical support from the Social Exchange Theory, this approach unifies both social and economic relationships into a common framework and also defines network statistics to effectively measure indirect stakeholder influence in a “Network” model as against a more traditional “Hub-and-Spoke” model. The usefulness of this approach and the strategic implications of these network statistics are then demonstrated by a retrospective case study for a large real-world engineering project, with improved understanding of relationships management for various stakeholders. The retrospective case is conducted on a multi-billion dollar, 5-year upgrade and turnaround of a major chemical processing plant for a Global 500 firm. In addition, we discuss the synergy between the Stakeholder Value Network approach and Strategic Issue Management, and outline a feasible plan to integrate these two approaches as an important extension of the original framework of the Stakeholder Value Network analysis.

Semi-Markov processes with semi-regenerative states for the availability analysis of chemical process plants with storage units

Design to capacity is an engineering principle that is increasingly applied in chemical industry, among others owing to increasing plant sizes and associated investments. This principle aims to reduce over-capacity, over-sized buffers and excessive redundancy. Concurrently, a high level of availability is targeted over the entire production chain. The consequences of unavailability of highly interconnected chemical process plants can be significant because a technical disruption in one plant is able to spread over the entire production network. In chemical process plants not only technical equipment determines the availability, but also storage units, which are able to bridge times of planned or unplanned interruptions of production. To find a balance between the principle of design to capacity and high production availability, the influence of different design parameters, such as capacity of production units, redundancy concept and the size of storage units, have to be evaluated and integrated in the design process. In this article, we present an analytical method for availability evaluation based on extending Semi-Markov processes integrating storage units and multiple production lines. Semi-regenerative states are used to capture the characteristics of storage units, and an approach is proposed in this work to assign distributions for the remaining holding times in these states. The proposed modelling and analysis are demonstrated on two case studies.

A novel graph-based partitioning algorithm for large-scale dynamical systems

In this paper, a novel graph-based system partitioning approach is proposed to facilitate the design of distributed or decentralised control in large-scale dynamical systems. In large-scale dynamical systems, a decomposition method is required to determine a suitable set of distributed subsystems and their relevant variables. In the proposed approach, a decomposition algorithm starts to generate an overall graph representation of the system model in the form of a new weighted digraph on the basis of a sensitivity analysis concept to quantify the coupling strengths among the system variables in terms of graph edge weights. The produced weighted digraph and its structural information are then used to partition the system model. All the potential system control inputs are first characterised as the main graph vertices, representing fixed subsystems centres. Then, the remaining vertices, representing system states or outputs, are assigned to the created subgraphs. Once the initial grouping is accordingly formed, a merging routine is automatically conducted to merge the small subgraphs in other subgraphs in an iterative searching way to find the smaller cut sizes. Each time a merging occurs, the total cost of the merged configuration, being defined in terms of an averaged linear quadratic regulator (LQR) metric, is used as a novel dynamic performance metric versus total group number reduction to terminate the algorithm for the best grouping result. A chemical industrial process plant is used as a benchmark to assess performance of the proposed methodology to fulfil the system partitioning objective. The output result of the algorithm is then comparatively used for a decentralised non-linear model-based predictive control methodology to demonstrate its ultimate merits.

Plant-Wide Control System Design of an Alkylation Process Using Integrated Framework of Simulation, Heuristics, and Optimization

In recent years, increasing concern of process economics, strict product specifications, and stringent safety and environmental regulations has resulted in increased use of material recycle and energy integration in chemical process plants. These highly integrated plants need effective control systems for smooth and optimal operation. This has led researchers to propose plant-wide control (PWC) system design methodologies. The present contribution considers the application of one such recently proposed methodology, the integrated framework of simulation, heuristics, and optimization (IFSHO) [Vasudevan, S.; Rangaiah, G. P. Integrated Framework Incorporating Optimization for Plant-Wide Control of Industrial Processes. Ind. Eng. Chem. Res.2011, 50, 8122–8137]. This framework is applied to the autorefrigerated alkylation process for the production of high-octane C8 components, which is important in petroleum refining. The step-by-step application of IFSHO is discussed. The performance of the resulting control...

Optimal Layout of a Chemical Process Plant to Minimize the Risk to Humans

The process layout of chemical plants is usually designed in a compact configuration for economic efficiency. However, most of the chemical process units are vulnerable to accidents such as fires and explosions, and these accidents can cause severe damage to humans. In this study, direct risks to humans from such hazards were quantitatively assessed as individual risk and converted into safety distances for each piece of process equipment. Then, a process layout optimization problem was formulated with risk zones constructed using those safety distances. Boundary factors accounting for land uses around the process site and protection factors from additional protective devices were also considered. A case study for an ethylene oxide plant was conducted. With the proposed methodology, a cost-efficient and inherently safe layout can be provided in the early stage of the design of a process plant.

Simple Parametric Model for Quick Assessment of IGCC Performance

Abstract Even though almost all components of an integrated gasification combined cycle (IGCC) power plant are proven and mature technologies, the sheer number of them, the wide variety of competing technologies (e.g., gasifiers, gas clean-up systems, heat recovery options), and system integration options (e.g., cryogenic air separation unit and the gas turbine), including the recent addition of carbon capture and sequestration (CCS) with its own technology and integration options, render fundamental IGCC performance analysis a monumental task. Almost all published studies utilize highly complex chemical process and power plant heat balance software, including commercially available packages and in-house proprietary codes. This makes an objective assessment of comparable IGCC plant designs, performance (and cost), and other perceived advantage claims (IGCC versus other technologies, too) very difficult, if not impossible. This paper develops a coherent simplified parametric model based on fully physics-based grounds to be used for quick design performance assessment of a large variety of IGCC power plants with and without CCS. Technology parameters are established from complex model runs and supplemented by extensive literature search. The model is tested using published data to establish its confidence interval and is satisfactory to carry conceptual design analysis at a high level to identify promising alternatives and development areas and assess the realism in competing claims.

A New Comprehensive Sensor Network Design Methodology for Complex Nonlinear Process Plants

This paper presents an optimal integrated instrumentation sensor network design methodology for complex nonlinear chemical process plants using a Combinatorial Particle Swarm Optimiazation (CPSO) engine. No comprehensive sensor network design approach has been addressed yet in the literature to simultaneously incorporate cost, precision and reliability requirements for nonlinear plants. The presented approach attempts to accomplish this objective via enhancement of the estimation accuracy of the aimed instrumentation sensor network subject to desired cost, reliability and redundancy constraints. An Unscented Kalman Filter (UKF)-based data reconciliation algorithm has been developed to present evaluating measures through comparisions of the estimated and real variables in terms of Modified Root Mean Squared of Error (MRMSE), while CPSO maintains the provisions of the Network Fault Tolerence (NFT) including sensor netowrk reilability (R), strong and weak redundancy degrees (i.e., SRD and WRD). The developed CPSO engine searches in a diverse variety of possible sensor networks to adopt the most fitted one based on the imposed NFT and cost design constraints. The effective capabilities of the proposed design methodology has been illustrated in a simulated nonlinear Continuous Stirred Tank Reactor (CSTR) as a complex process plant benchmark.

History of the process plant safety symposium: 20 years, 1992-2012

The first Process Plant Safety Symposium (PPSS) was a regional conference held in 1992 in Houston, TX, which has the largest concentration of chemical process plants in North America. The symposium was organized to provide perspectives, methods, and tools that could be readily practiced at the plant level. The first conference was organized by the South Texas Section of the American Institute of Chemical Engineers (AIChE) and cosponsored by the AIChE Center for Chemical Process Safety and a number of other engineering and scientific organizations. The PPSS has evolved to an international symposium, part of the Global Congress on Process Safety, held annually in conjunction with the AIChE Spring Meeting. This article is a brief history of the PPSS. © 2012 American Institute of Chemical Engineers Process Saf Prog, 2012

Using layer of protection analysis to understand necessary safeguards for steam boiler operation

Most chemical process plants, petrochemical facilities, and electrical power utilities rely on steam boilers to provide motive power, electricity, and process steam for operations. Safe operation, startup, and shutdown of these boilers require many levels of operational/controls safeguards. The design and selection of safeguards is often guided by the original design of the boiler, equipment manufacturers, internal company standards, and recognized authoritative standards. In the United States, the National Fire Protection Association (NFPA) has promulgated NFPA 85 Boiler and Combustion Systems Hazards Code. This prescriptive code identifies necessary safeguards along with “listing” and “labeling” requirements for some components used as safeguards; however, the Safety Integrity Levels for the multiple safeguard systems have not been quantified. In this article, we use Layer of Protection Analysis methods along with generally accepted probabilities and frequencies of failures to provide a quantitative framework for an owner, operator, or manufacturer to use in designing or evaluating the multiple safeguards necessary for safe steam boiler operation. As part of the analysis, we have provided case studies of boiler failures with a discussion of how additional layers of protection may be either ineffective or missing. © 2012 American Institute of Chemical Engineers Process Saf Prog, 2012

Robust Controller Design using Quantitative Feedback Theory (QFT)

of the practical systems are characterized by high uncertainty which makes it difficult to maintain good stability margins and performance properties for closed loop system. In case of conventional control, if plant parameter changes we cannot assure about the system performance hence it is necessary to design robust control for uncertain plant. Among the various strategies proposed to tackle this problem, Quantitative Feedback Theory (QFT) has proved its superiority especially in the face of significant parametric uncertainty. The feature of QFT is that it can take care of large parametric uncertainty along with phase information. For the purpose of QFT, the feedback system is normally described by the two-degrees-of freedom structure. A chemical system common to many chemical processing plants, known as a continuous stirred tank reactor (CSTR).For an isothermal CSTR the product concentration can be controlled by manipulating the feed flow rate,which changes the residence time. Keywords—