Optimal Plant Design Research Articles

Optimal MSF plant design

The aim of this paper is to present a rigorous model for Multi-Stage Flash Evaporation System (MSF). The MSF system is represented as a No Linear Programming (NLP) model. The model incorporates a high number of non-linear restrictions; so the achievement of the global optimum is difficult. Here, the study of an algorithm for the system optimisation is presented.

Thermodynamic Optimization of the Operative Parameters for the Heat Recovery in Combined Power Plants

For the combined power plants, the optimization of the heat recovery steam generator (HRSG) is of particular interest in order to improve the efficiency of the heat recovery from turbine exhaust gas and to maximize the power production in the steam cycle. The thermodynamic optimization is the first step of a power plant design optimization process. The aim of this paper is to provide thermodynamic tools for the optimal selection of the operative parameters of the HRSG, starting from which a detailed optimization of its design variables can be carried out. For the thermodynamic analysis, the selected objective is the minimization of thermal exergy losses, taking into account only the irreversibility due to the temperature difference between the hot and cold streams. Various HRSG configurations have been analyzed, from the simpler, a single evaporator to the common configuration of two-pressure steam generator with five different sections. This paper was presented at the ECOS'00 Conference in Enschede, July 5-7, 2000

Genetic algorithms and Monte Carlo simulation for optimal plant design

Abstract We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown–Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance.

Optimal design and operation of heat exchangers under milk fouling

AbstractThis article presents a procedure for the simultaneous optimization of the design and operation of heat exchangers under milk fouling. This scheme is based on a highly accurate dynamic model described by integral, partial differential, and algebraic equations. Design and operating parameters determined by the dynamic optimization include the length and diameter of the exchanger, the control policy, and the timing of the key operating steps. An economic objective function is used to account for the important factors related to milk heat treatment, and many operating constraints are imposed. Three heat exchanger configurations are considered to study the effect of fouling on the optimal plant design. Optimization indicates that the cost factor due to the interruption of production is dominant, while an increase in energy consumption due to fouling is not very important. The constant wall temperature configuration proved to be the most economical. The economic impact of different control structures was also explored.

Phosphate removal in real anaerobic supernatants: modelling and performance of a fluidized bed reactor

Phosphate removal in anaerobic supernatant coming from a centrifugation sludge station of an A2O process is studied. A fluidized bed reactor is employed to crystallize phosphate as hydroxyapatite or struvite using only air stripping to reach the supersaturation pH. The classic composition of supernatant (alkalinity 3550 mgCaCO3/l, PO4 139 mg/l, Mg 24 mg/l) does not require any addition of chemicals for phosphate removal. Seventeen runs are performed in a bench scale FBR obtaining very high conversion and removal efficiency and phosphate loss in the effluent ≤3.5%. The use of Ca or Mg enriched supernatant has no meaningful influence on efficiency, but it determines the prevalent salt formed between MAP or HAP. Efficiency can be related to pH and sand contact time in a double saturational model. The half efficiency constants: 0.075 h for t and 7.75 pH, have an important role in the process knowledge and optimization of plant design. Exhaust sand analysis indicates the same composition at the top, bottom and mean of the sand bed (39% mol MAP and 61% mol HAP). This result together with the high half efficiency constant for contact time indicate that the phosphate growth on the bed is not competitive. Finally, the phosphate release from the plant is studied. Results show a weak release rate, equivalent to 2.8-10% d−1 phosphate as MAP, obtained at an operative pH range of 8.1-8.4.

Phosphate removal in real anaerobic supernatants: Modelling and performance of a fluidized bed reactor

Phosphate removal in anaerobic supernatant coming from a centrifugation sludge station of an A2O process is studied. A fluidized bed reactor is employed to crystallize phosphate as hydroxyapatite or struvite using only air stripping to reach the supersaturation pH. The classic composition of supernatant (alkalinity 3550 mgCaCO3/l, PO4 139 mg/l, Mg 24 mg/l) does not require any addition of chemicals for phosphate removal. Seventeen runs are performed in a bench scale FBR obtaining very high conversion and removal efficiency and phosphate loss in the effluent ≤3.5%. The use of Ca or Mg enriched supernatant has no meaningful influence on efficiency, but it determines the prevalent salt formed between MAP or HAP. Efficiency can be related to pH and sand contact time in a double saturational model. The half efficiency constants: 0.075 h for t and 7.75 pH, have an important role in the process knowledge and optimization of plant design. Exhaust sand analysis indicates the same composition at the top, bottom and mean of the sand bed (39% mol MAP and 61% mol HAP). This result together with the high half efficiency constant for contact time indicate that the phosphate growth on the bed is not competitive. Finally, the phosphate release from the plant is studied. Results show a weak release rate, equivalent to 2.8–10% d−1 phosphate as MAP, obtained at an operative pH range of 8.1–8.4.

Consideration on safety research strategy toward commercialization of FBRs

The situation of FBR enters upon development stage expecting to commercialize upto 2030's and has not yet established the concept of commercialized FBR plant. The primary subject is remarkable improvement of economy which can be accomplished through higher performance of plant systems, reduction of the amount of materials of the plant due to simplification of the plant systems and maximization of plant availability. This subject can be solved by development of foresighted plant design through full utilization of the inherent safety characteristics of FBR's. The secondary subject is acquirement of public confidence of FBR safety. If recriticality accident can be eliminated from the safety analysis for licensing of future FBRs with firm experimental evidences, then safety logic for the FBRs will more simple and thus friendly to the public. Then the public will be quite confident of safety securement of the FBR system and will be free from any anxiety. Discrepancy of the confidence level of FBR safety between the experts and the public will be significantly improved by showing experimental evidence of elimination of recriticality accidents. In addition, an optimized plant design for further reduction of the plant construction cost can be accomplished by elimination of recriticality accidents in an FBR plant design. In order to realize the above experiments and clarify these phenomena with a subassembly scale, development of new in-pile experimental facility using real materials in an FBR core is essential. Considering requirements of prototypicality or objectives for demonstration, it is concluded that the new in-pile experimental facility should be built early in the next century. The tertiary subject is reinforcement of FBR safety and reliability technologies in a more broad sense developed by the industry's voluntary safe-ensuring activities. These requirements have been realized through lessons learned from the sodium leak incident in the secondary heat transport system of Monju occurred on December 8th, 1995. For acquirement of social confidence on FBR safety by the public, significant amount of sodium leakage should be precluded, even if spilled sodium is non-radioactive and thus gives no radiological consequence to the public. Countermeasures for prevention and mitigation against such sodium leakage should be reinforced not as regulation-based activities but as the voluntary safe-ensuring activities by the utilities/development organizations. It thus appears that development of rules, standards and guidelines made by the industries in addition to reinforcement of wide range of sodium-related fundamental technology are essential for the future commercialization of FBRs. In order to solve the above-mentioned subjects, it is essential to optimize and clarify the roles between the government and industries, to execute safety researches based on the well-organized long-term plan and to make the most use of international cooperation.

A novel approach to circuit synthesis in mineral processing

Traditional plant design procedures seldom produce the optimum design for given plant parameters. Non-optimum design is due to a variety of factors including, amongst others, a poorly structured approach, reluctance to undertake time consuming iterative design, lack of equipment knowledge and the bias of design due to personal preferences. This paper presents details of a new technique for mineral processing plant synthesis. Using an approach incorporating various aspects of Artificial Intelligence, including Learning Classifier Systems, the idea is to create self-contained plant units that possess knowledge of applicability from within. The process objects then bid for an appropriate position in the plant. As a processing plant is a multi-component process the Intelligent Process Plant Object (IPPO) is used to advise on possible plant interactions during the bidding process. Using this approach it is believed that the proposed technique will use up-to-date knowledge and resources in a more efficient manner than conventional methods. As part of the development of the synthesis technique the paper describes a case study comprising of a three stage crushing and screening circuit used in the quarrying industry. The new synthesis technique is applied to the manual plant design in order to determine if the approach is capable of replicating the original circuit. The result of this analysis is presented. The idea of intelligent objects representing the plant and the subsequent synthesis of a circuit via bidding and competition has great potential for the minerals' industry. It is hoped that this procedure will save the design engineer considerable time, reducing design expenses, and thus allowing the user to get closer to the goal of optimum plant design for given input and product requirements.

Discussion of “ Optimal Water Treatment Plant Design ” by Mark R. Wiesner, Charles R. O'Melis, and Jared L. Cohon (June, 1987, Vol. 113, No. 3)

Discussion of “ <i>Optimal Water Treatment Plant Design</i> ” by Mark R. Wiesner, Charles R. O'Melis, and Jared L. Cohon (June, 1987, Vol. 113, No. 3)

Rule‐Based Model of Design Judgment about Sludge Bulking

The use of a rule‐based approximate reasoning modeling technique is illustrated in the context of wastewater treatment plant design. Sludge bulking is a poorly understood problem in activated sludge wastewater treatment plants. An engineer must use judgment gained from experience to design a plant to prevent bulking and the attendant plant failure. An attempt was made to use fuzzy logic to model that judgment. Results from the literature were formulated in a rulebased model that relates design variable values to the likelihood of a design experiencing bulking problems. The model was calibrated and checked for consistency against an experienced engineer's evaluation of two sets of 15 plant designs. The model of judgment could be used to evaluate the bulking potential of any design. The model was also incorporated into a plant design optimization model, and the tradeoff between cost and the likelihood of bulking was examined for a typical problem.

Optimal Water Treatment Plant Design

The identification of a least cost design and configuration of unit processes for particle removal in water treatment is formulated as a nonlinear optimization program. Simulation models describing changes in particle size and concentration enter into the formulation as constraints. Contact and direct filtration are found to be optimal treatment configurations at particle concentrations less than 15–20 mg/L. Reducing the number of unit processes in a water treatment plant does not always result in a decrease in cost. Results indicate that filter design traditionally relies on low filtration rates rather than pretreatment to ensure filtrate quality.

Particles, Pretreatment, and Performance in Water Filtration

Relationships among raw water quality, pretreatment facilities, and the design of packed bed filters are presented and applied. The particle size, particle concentration, particle surface characteristics, and solution chemistry in the raw water supply have important and predictable effects on filter design. An integrative approach to water treatment plant design, from raw water quality to filter bed performance, will facilitate process evaluation and has the potential for providing a basis for optimal plant design.

Model building in complex catalytic reaction systems

Catalytic rate-modelling forms an integral part of Process Development and Design as well as providing insight into the underlying reaction mechanisms. Industrial reactions are usually complex, involving several simultaneous and consecutive reactions, leading to a variety of products. In petro-chemical applications, in particular, the reactions often occur in the presence of continuous deactivation of the catalyst—a complex process which must also be modelled if an optimum plant design and operating policy are to be realized. This paper describes an approach to model building of such systems which requires a multi-step strategy of experimentation and analysis, using different types of laboratory reactor. The approach is applied to the kinetic modelling of simultaneous isomerisation and disproportionation of a mixture of xylenes over a silica-alumina catalyst which is subject to continuous coking.

Utilization of plant operating experience in new plant designs: A consultant's viewpoint

One specific area which should be considered in the transfer of nuclear technology to countries beginning development of a nuclear industry is the utilization and transfer of existing operating plant experience. No other single area can assist in developing a level of useful knowledge more rapidly than the systematic comparison of existing new plant designs with older plants and their associated performance data. With the advent of the Rasmussen Study (WASH-1400, 1975), a methodology now exists that can provide the systematic review of the plant design and quantify its probability of being an optimum system. Generally, the most important criteria for definition of the optimum system would be initial capital cost, projected maintenance costs, and plant availability. The fault tree analysis methodology used on the Rasmussen study allows system availability to be placed on a firm numerical footing. The area of each plant system contributing most to its unavailability is readily identifiable. Once identified, various methods for system improvement can be analyzed to determine which will provide the best results at lowest cost. The actual costs of the improvements vs the resultant savings from improved plant availability can be calculated, thus optimizing the solution (Lintner, 1976). Simple financial considerations of initial capital costs, escalation, and overall nuclear plans provide the final loop in the iteration to establish the optimum plant design. Since the most unfamiliar and most difficult part of the solution is the fault-tree construction and utilization, most attention will be paid to its discussion.

The impact of twenty years of noise research on nuclear power plant design, instrumentation and control

Some twenty years have elapsed since the first technical papers began to appear in a general field which can be loosely described as the statistical nature of the nuclear fission reaction and its influence on the criticality and dynamics of nuclear power systems. A few years subsequently, the first zero energy “neutron noise” measurements were reported in the scientific literature. These investigations clearly demonstrated that the time constants and the dynamic characteristics of low energy nuclear systems could be elegantly determined by the correlation or spectral analysis of fluctuating signals from ion chambers and proportional counters. The analyses of the time series information and the multi-filtering operations in the frequency domain were time consuming and tedious projects due to the non-availability of suitable data processing equipment. During the last decade, the significant advances in the field were the recognition of the advantages of the two-channel cross-correlation technique and the realisation that the dynamic behaviour of nuclear power plant at power could be monitored and studied in depth by the cross-correlation of mechanical, thermal and hydrodynamic signals with neutronic information. The former concept gave the spur to the development of theoretical models for spatial and energy dependent noise fields within a nuclear system. The latter technology, in principle at any rate, opened a floodgate of potential advances in nuclear power plant design optimization, control and safety instrumentation, and control and safety diagnostic systems. The present decade has seen the interaction of workers in the reactor noise field with workers investigating general vibrational phenomena and the structural mechanics of nuclear power plant. Despite this, it is sobering to reflect in retrospect that neither design, nor instrumentation and control concepts arising from noise research, have found any great measure of practical acceptance in current nuclear technology. This paper explores the reasons for this unsatisfactory situation, surveys the few available practical examples of accepted noise technology, and makes some definitive proposals with regard to the future implementation of nuclear power plant design, instrumentation, and control procedures, based on the concept of stochastic models and noise analysis.

Dynamics Analysis of a Nuclear Boiler

A dynamics analysis of a nuclear boiler based on a steam-generating, pressure-tube, heavy-water-moderated design is presented. In effect the plant is very similar to a La Mont recirculating cycle. A detailed mathematical model to represent plant dynamics (linearized, full power) is discussed with special reference to the boiling channel, steam drum, and recirculating loop. A simplified model is derived for analogue computer studies. Dynamic performance is discussed in terms of: (1) boiler only (no reactivity feedbacks): influence of pressure feedbacks, steam drum design, subcooling, recirculating delay; (2) complete plant (including reactor): as above but including influence of void coefficient. The two most important results are: (1) the strong dependence of plant behaviour/stability on the degrees of float allowed to pressure; (2) the possibility of designing an inherently stable and self-regulating plant with a small positive void coefficient. Finally, conclusions are drawn on the complete dynamic analysis under the heads: (1) optimal plant design; (2) control system design; (3) development of analytical/computing methods; (4) research into two-phase physics.

Optimum Plant Design for Seasonal Production

A systematic optimization procedure is developed for the design of a plant which is subject to uncertain, seasonal production. Based on a generalized seasonal production model, the present value of the cash flows associated with production by means of a combination of alternates is expressed in terms of the unknown capacities. On the basis of the derived solution, a systematic procedure is presented which yields optimum designs without reference to the involved mathematics. Finally, the more important assumptions are removed and suggestions are given with respect to the modifications that are required in order to extend the method to more complex problems.