Synthesis of Rice Processing Plants. III. Sensitivity Analysis

Abstract

An optimal process flowsheet for a rice processing plant has been developed. The optimization problem was formulated as a Mixed-Integer Nonlinear Programme, MINLP, consisting of a vector of binary and continuous variables. The set of optimum decision variables including the number of drying, cooling, and tempering units, temperature and relative humidity of drying air, drying time, cooling time, and tempering time were determined as the solution of the MINLP problem. Six objective functions were investigated as performance criteria. A sensitivity analysis of each model parameter was conducted to determine its influence on the optimal flowsheet. The MINLP approach is an efficient tool for optimization and the simplified models were adequate for use at the synthesis stage. The solution is insensitive to uncertainty in the models. However, due to the nonconvex nature of MINLPs, the solution was found to depend on the initial starting values, especially for the maximum profit flowsheet.     

Synthesis of Rice Processing Plants. I. Development of Simplified Models

Abstract

This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.     

Synthesis of Rice Processing Plants. I. Development of Simplified Models

This article, the first of three articles on the synthesis of rice processing plants, focuses on the development of simplified mathematical models necessary for use in optimizing rice processing plants. The second concentrates on the optimal synthesis of a rice plant and the third on the sensitivity of the optimization to uncertainty in model parameters. Existing models for rice processing unit operations are not suitable for flowsheet optimization and new models need to be developed to overcome numerical difficulties that occur in optimization applications, specifically in mixed integer nonlinear programming (MINLP) applications. Simplified models of the drying, cooling, and tempering units are developed. In addition head rice yield models, used as a quality indicator, energy consumption, and economic models were also developed. Naturally, the new models exhibit some mismatch with respect to the existing models from which they were developed. However, a sensitivity analysis, presented in Part III, has shown that the optimal flowsheet structure was not sensitive to a lack of fit between the simplified and complex models. The simplified models were found adequate to be appropriate for use at the synthesis stage.     

Synthesis of Rice Processing Plants. II. MINLP Optimization

Abstract

A systematic design approach was applied to develop the optimal process flowsheet for a rice processing plant. The optimization problem was formulated as a Mixed-Integer NonLinear Programme, MINLP, consisting of vectors of binary and continuous variables. A superstructure flowsheet comprising all serial structures of drying, cooling, and tempering units in the process was postulated. The set of optimum decision variables including the number of drying, cooling, and tempering units, temperature and relative humidity of drying air, drying time, cooling time, and tempering time were determine as the solution of the corresponding MINLP. Six objective functions were investigated as possible performance criteria: production time, number of the operating units, energy consumption, total operating cost, head rice yield, and the profit. The choice of objective function was found to have a significant effect on the optimal solution. Comparison with typical design and operating conditions, the MINLP results showed that a 22% reduction in energy consumption was possible along with a 2.4% increase in head rice yield. These savings, if applied to the world-wide rice industry, translate into more than $3 billion dollars/year increase in profit.     

Synthesis of Rice Processing Plants. II. MINLP Optimization

A systematic design approach was applied to develop the optimal process flowsheet for a rice processing plant. The optimization problem was formulated as a Mixed-Integer NonLinear Programme, MINLP, consisting of vectors of binary and continuous variables. A superstructure flowsheet comprising all serial structures of drying, cooling, and tempering units in the process was postulated. The set of optimum decision variables including the number of drying, cooling, and tempering units, temperature and relative humidity of drying air, drying time, cooling time, and tempering time were determine as the solution of the corresponding MINLP. Six objective functions were investigated as possible performance criteria: production time, number of the operating units, energy consumption, total operating cost, head rice yield, and the profit. The choice of objective function was found to have a significant effect on the optimal solution. Comparison with typical design and operating conditions, the MINLP results showed that a 22% reduction in energy consumption was possible along with a 2.4% increase in head rice yield. These savings, if applied to the world-wide rice industry, translate into more than $3 billion dollars/year increase in profit.     

Analysis and Optimization of Drying of Green Bricks in a Tunnel Dryer

One way to avoid the risk of condensation in a tunnel dryer for drying of green bricks is to use higher air flow rates. However, higher air flow rates accelerate the drying rate and thus cause damages. It is necessary to determine the optimal values of the hot and outdoor air mass flow rates and optimum stack temperature to avoid the condensation. Four different temperatures, (?5, 10, 20, and 30°C) and three different relative humidities (40, 60, and 80%) for the outdoor air were selected. Optimal operation parameters and the required stack temperature to avoid condensation for different cases were computed.     

Multiperiod Optimization for Production Planning of Petroleum Refineries

Production planning has been the focus of many articles in the mathematical programming literature. In particular, successful operation of oil companies depends on systematic decisions over complex logistics. The present article focuses on the decision-making process involved in petroleum production planning. The proposed model is based on a nonlinear programming formulation that was developed to plan production over a single period. First, the model incorporates multiple planning periods and the selection of different crude oil types. Uncertainty related to petroleum and product prices as well as demand is then included as a set of discrete probabilities. Finally, crude oil handling constraints are added. The resulting models are mixed integer nonlinear programs (MINLP), which were successfully applied to a real-world case at the Petrobras REVAP refinery. Problems of up to 19 time periods and up to five scenarios were solved to optimality.     

Design of memetic algorithms for the efficient optimization of chemical process synthesis problems with structural restrictions

In Urselmann et al., 2011a, Urselmann et al., 2011b we presented a memetic algorithm (MA) for the design optimization of reactive distillation columns. The MA is a combination of a problem-specific evolutionary algorithm (EA) that optimizes the design variables and a mathematical programming (MP) method that solves the continuous sub-problems with fixed discrete decisions which are proposed by the EA to local optimality. In comparison to the usual superstructure formulation, the search space of the MA is significantly reduced without excluding feasible solutions. The algorithm computes many different local optima and can handle structural restrictions and discontinuous cost functions. In this contribution, a systematic procedure to modify the MA to solve more complex design problems is described and demonstrated using the example of a reactive distillation column with an optional side- or pre-reactor with structural restrictions on the number of streams. New concepts to handle connected and optional unit operations are proposed.     

MINLP synthesis of optimal cooling networks

A mixed-integer nonlinear programming (MINLP) algorithm for the synthesis of cooling networks is presented. As opposed to previous models in which the minimization of utility consumption has been formulated, the algorithm considers simultaneously the capital cost for the coolers and the utility costs. The strategy is based on a superstructure that allows bypass and splitting of utility streams. Also, the superstructure considers a combination of arrangements in series and in parallel that allows for an efficient use of cooling streams. The typical arrangement of cooling networks in parallel usually conducts to higher total costs. Also, it is shown that the use of minimum amounts of cold utilities does not necessarily conduct to the minimum total cost. Three case studies are used to show the application of the proposed method.     

Multiperiod Optimization for Production Planning of Petroleum Refineries

Production planning has been the focus of many articles in the mathematical programming literature. In particular, successful operation of oil companies depends on systematic decisions over complex logistics. The present article focuses on the decision-making process involved in petroleum production planning. The proposed model is based on a nonlinear programming formulation that was developed to plan production over a single period. First, the model incorporates multiple planning periods and the selection of different crude oil types. Uncertainty related to petroleum and product prices as well as demand is then included as a set of discrete probabilities. Finally, crude oil handling constraints are added. The resulting models are mixed integer nonlinear programs (MINLP), which were successfully applied to a real-world case at the Petrobras REVAP refinery. Problems of up to 19 time periods and up to five scenarios were solved to optimality.     

A generalized methodology for optimal configurations of hybrid distillation-pervaporation processes

The aim of this work is to illustrate the structural and parametric optimization of continuous hybrid distillation-pervaporation process with different configurations such as series, parallel, and series-parallel arrangement of pervaporation modules in the pervaporation network, and to propose a generalized methodology for difficult separations. A superstructure representation of hybrid process is considered and the process is modeled and optimized using an MINLP approach. The optimization strategy is to obtain the desired degree of either the retentate or the distillate purity without violating the composition constraints of products and heat exchange policy which minimizes the required membrane area by increasing the flux through the membrane. The structural and operating parameters such as number of trays required, feed tray location, reflux ratio, retentate recycle location, permeate recycle location, membrane feed location, number of pervaporation modules required, target composition (which is directly related to membrane area), and membrane selectivity are optimized for each configuration by minimizing the total annual cost (TAC) for the separation system. The optimization studies have been carried out with General Algebraic Modeling System software (GAMS/SBB/CONOPT) and the results of different configurations have been compared on the basis of TAC required for the separation. A total of three industrial case studies have been dealt with. The separation of isopropanol-water as an azeotropic mixture, propylene-propane as a close boiling mixture (system with a low relative volatility) and acetone-water as a tangent pinch mixture have been studied as representative examples.     

Optimal design of hybrid RO/MSF desalination plants Part III: Sensitivity analysis

This is the last paper in a series of three parts entitled “Optimal design of hybrid RO/MSF desalination plants”. This research is concerned with exploring the feasibility of hybridization of multi-stage flash (MSF) and reverse osmosis (RO) technologies in order to improve the performance characteristics and process economics ofthe conventional MSF process. The research project involved an optimization study where the water cost perunit product is minimized subject to a number of constraints. In the first part, the design and cost models were presented, the optimization problem formulated and solutions for a number of cases were outlined. In the second part, results were presented and discussed. In this paper we discuss the sensitivity of water cost from the alternative plant designs to variations in some cost elements and operating conditions. In general, it is concluded that, for the same desalting capacity, hybrid RO/MSF plants can produce desalted water at a lower cost than brine recycle MSF plants, while hybrid plants are characterized, by lower specific capital costs and higher water recovery fractions. Reduction in steam cost allows MSF to compete more with hybrid RO/MSF plants. This result explains the advantage of coupling MSF plants and steam power plants where the exhaust steam from the back pressure turbine represents a relatively cheaper source of heat for the MSF process. Results showed that the RO technology exceeds all other designs over the whole range of energy, chemicals and membrane costs studied here. However, water cost of the RO process was the most sensitive to variations in membrane and electricity costs compared to other hybrid configurations.     

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm☆

Synthesis and optimization of utility system usual y involve grassroots design, retrofitting and operation optimi-zation, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal configuration and operation conditions of the sys-tem. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of configuration and improves computational efficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.     

Optimization of hydrogen networks with multiple impurities and impurity removal

To explore the effect of removing different impurities to hydrogen networks, an MINLP model is proposed with all matching possibilities and the trade-off between operation cost and capital cost is considered. Furthermore, the impurity remover, hydrogen distribution, compressor and pipe setting are included in the model. Based on this model, the impurity and source(s) that are in higher priority for impurity removal, the optimal targeted concentration, and the hydrogen network with the minimum annual cost can be identified. The efficiency of the proposed model is verified by a case study.     

Sensitivity Analysis of the Reaction Engineering Approach to Modeling Spray Drying of Whey Proteins Concentrate

Whey proteins concentrate (WPC) powder is an important protein source for humans and is commonly produced from whey using a spray-drying technique. Predicting several drying parameters as well as the parameters that govern the quality of the product is essential before manufacturing WPC in industries. Drying kinetics is an essential tool for predicting the drying rate and various parameters that are rate dependent. However, there have been only a few studies published previously on both modeling WPC drying and dryer-wide simulations using different computational tools. In this article we review the application of a reaction engineering approach (REA) to model the droplet drying process. Results based on dryer-wide simulations using the REA are presented. More importantly, a sensitivity analysis of the REA using drying of WPC and skim milk droplets is reported. This analysis will be helpful to select an appropriate drying kinetics model and forms a benchmark for the future WPC drying modeling work.     

A Small-Scale Pneumatic Conveying Dryer of Rough Rice

This article studies the possibility of reducing the high initial moisture content of wet rough rice using a small-scale low-cost pneumatic conveying dryer as a first stage dryer. The parameters investigated are final moisture content, surface temperature of rough rice, head rice yield, drying rate, power consumption per unit mass of evaporated water, and physical characteristics of rice. Parametric effects of the following variables are examined: velocity of drying air from 20 to 30 m/s, feed rate of rough rice from 150 to 350 kg/h, initial moisture content from 22 to 26% (wet basis), and drying air temperature from 35 to 70°C. From the experimental results, it is found that this drying method can be used for fresh rough rice with an initial moisture content of over 24% (wet basis). The drying process is able to lead to very rapid drying without any grain quality problems such as cracks in the rice kernel. The moisture content can be reduced to approximately 18% (wet basis) or about 5-6% of the initial moisture content within 3-4 s. The optimal drying air temperature is in the range of 50 to 60°C. A comparison of pneumatic conveying drying data obtained from the present study with fluidized bed drying data reported in the open literature is also discussed.     

A Small-Scale Pneumatic Conveying Dryer of Rough Rice

This article studies the possibility of reducing the high initial moisture content of wet rough rice using a small-scale low-cost pneumatic conveying dryer as a first stage dryer. The parameters investigated are final moisture content, surface temperature of rough rice, head rice yield, drying rate, power consumption per unit mass of evaporated water, and physical characteristics of rice. Parametric effects of the following variables are examined: velocity of drying air from 20 to 30 m/s, feed rate of rough rice from 150 to 350 kg/h, initial moisture content from 22 to 26% (wet basis), and drying air temperature from 35 to 70°C. From the experimental results, it is found that this drying method can be used for fresh rough rice with an initial moisture content of over 24% (wet basis). The drying process is able to lead to very rapid drying without any grain quality problems such as cracks in the rice kernel. The moisture content can be reduced to approximately 18% (wet basis) or about 5–6% of the initial moisture content within 3–4 s. The optimal drying air temperature is in the range of 50 to 60°C. A comparison of pneumatic conveying drying data obtained from the present study with fluidized bed drying data reported in the open literature is also discussed.     

Modeling Equilibrium Moisture Content of γ-Ray Irradiated Rough Rice

Experimental studies show that gamma irradiation dose affects the values of equilibrium moisture content of grain at the same relative humidity and temperature of ambient. Values of the equilibrium moisture content decreased with increasing dose of γ-ray irradiation during both adsorption and desorption. Factor of irradiation dose was included in three widely used models for equilibrium moisture content; the parameters in the models were estimations from experimental data. Based on the correlation coefficient, mean relative error, and standard error of moisture, the modified Chung-Pfost equation and the modified Henderson equation were found to fit the desorption and adsorption isotherms for rough rice in the range of experimental conditions studied.     

16.5万t/a煤焦油加工装置分析

介绍了16.5万t/a煤焦油加工装置的工艺流程、技术特点及设备装备,分析了各项实用技术,具有节能、环保和自动化程度高的特点,分析比较了各项生产指标,可以得出16.5万t/a煤焦油加工装置的产品质量好,能耗较低,是我国煤焦油加工的适用技术之一。     

Optimization of Vapor Compression for Cost Savings in Drying Processes

Energy saving from vapor compression entails additional costs for the vapor compressors and larger heating surfaces of the drier. Thus, they are offset to a certain degree. An analytically solvable mathematical model is presented for determining the maximum cost savings with the optimum pressure ratio of the compression. According to this, the maximum cost savings depends only on five parameters, namely, the specific cost ratios of drier to fuel and compressors to fuel, the price ratio of power and fuel, the difference between the moisture contents of the inlet and outlet of the drier and the pressure level inside the drier. Above dy = 1 kg_H2O/kg_DS (DS – dry substance) the specific cost ratio of drier to fuel proves to be dominant and thus decisively determines the optimum pressure ratio. Hence, one can explain why, e.g., in the case of brown coal drying higher pressure ratios are required than in the case of sludge drying and here again higher ones than in the case of evaporization processes for liquids.