Decision optimal

In optimization using a modular process simulator, certain restrictions apply on the choice of decision variables. For example, if the location of column feeds, draws, and heat exchangers are selected as decision variables, the rate or heat duty cannot also be selected. For an isothermal flash both the temperatures and pressure may be optimized, but for an adiabatic flash, on the other hand, the temperature is calculated in a module and only the pressure can be optimized. You also have to take care that the decision (optimization) variables in one unit are not varied by another unit. In some instances, you can make alternative specifications of the decision variables that result in the same optimal solution, but require substantially different computation time. For example, the simplest specification for a splitter would be a molar rate or ratio. A specification of the weight rate of a component in an exit flow stream from the splitter increases the computation time but yields the same solution. 

Thermoeconomics needs to flourish in order to avoid misconceptions and erroneous statistics which would lead to bad mistakes by engineers involved in design and operating decisions, and by managers and politicians who are involved with "energy" use and development in the private and government sectors. Thermoeconomics needs to flourish not only to avoid bad decisions, but also in order to make good decisions — optimally. 

In the process of utilising risk assessment in a more structured manner in electricity distribution, it is our opinion that one should try to establish better analysis approaches for each of the risk aspects before jumping to the aggregation of risks into on common measure with the aim to perform a full optimization - emphasising to provide decision support rather than decision optimization. 

It should be emphasized that these recommendations for the initial settings of the reactor conversion will almost certainly change at a later stage, since reactor conversion is an extremely important optimization variable. When dealing with multiple reactions, selectivity is maximized for the chosen conversion. Thus a reactor type, temperature, pressure, and catalyst are chosen to this end. Figure 2.10 summarizes the basic decisions which must be made to maximize selectivity. ... 

Two implementation decisions could be made immediately. First, DPMTA is based on the PVM message-passing library [11] and therefore it was necessary to base NAMD on PVM as well. All communication done by NAMD, however, would use an intermediate interface to allow communications to be easily retargeted to MPI [12] or other standards, and to simplify later implementation of communication optimizations such as combining messages destined for the same processor. Second, after much debate C++ was selected... 

Chemoinformati.cs is involved in the drug discovery process in both the lead finding and lead optimization steps. Artificial neural networks can play a decisive role of various stages in this process cf. Section 10.4.7.1). 

Optimization of Cycle Times. In batch filters, one of the important decisions is how much time is allocated to the different operations such as filtration, displacement dewatering, cake washing, and cake discharge, which may involve opening of the pressure vessel. Ah. of this has to happen within a cycle time /. which itself is not fixed, though some of the times involved may be defined, such as the cake discharge time. 

A hierarchical design procedure for process synthesis can be used in conjunction with a flow-sheeting program to analyze, evaluate, and optimize the options (60). The emphasis is on starting with the simplest possible models that will give answers to a particular question quickly so that the questions to be asked at the next decision level can be formulated. At each stage, it is necessary to ensure that the level of detail in the model is sufficient to give rehable information. 

Catalyst Selection. The choice of catalyst is one of the most important design decisions. Selection is usually based on activity, selectivity, stabiUty, mechanical strength, and cost (31). StabiUty and mechanical strength, which make for steady, long-term performance, are the key characteristics. The basic strategy in process design is to minimize catalyst deactivation, while optimizing pollutant destmction. 

D. A. Sofge and D. A. White, "Neural Network Based Process Optimization and Control," in Proceedings of the 29th Conference on Decision and Control,... 

Optimization should be viewed as a tool to aid in decision making. Its purpose is to aid in the selection of better values for the decisions that can be made by a person in solving a problem. To formulate an optimization problem, one must resolve three issues. First, one must have a representation of the artifact that can be used to determine how the artifac t performs in response to the decisions one makes. This representation may be a mathematical model or the artifact itself. Second, one must have a way to evaluate the performance—an objective function—which is used to compare alternative solutions. Third, one must have a method to search for the improvement. This section concentrates on the third issue, the methods one might use. The first two items are difficult ones, but discussing them at length is outside the scope of this sec tion. 

All filters require a filter medium to retain solids, whether the filter is for cake filtration or for filter-medium or depth filtration. Specification of a medium is based on retention of some minimum parficle size at good removal efficiency and on acceptable hfe of the medium in the environment of the filter. The selection of the type of filter medium is often the most important decision in success of the operation. For cake filtration, medium selection involves an optimization of the following factors ... 

In the development of new products, optimization of the fermentation medium for titer only often ignores the consequences of the medium properties on subsequent downstream processing steps such as filtration and chromatography. It is imperative, therefore, that there be effective communication and understanding between workers on the upstream and downstream phases of the produc t development if rational trade-offs are to be made to ensure overall optimahty of the process. One example is to make the conscious decision, in collaboration with those responsible for the downstream operations, whether to produce a protein in an unfolded form or in its native folded form the purification of the aggregated unfolded proteins is simpler than that of the native protein, but the refolding process itself to obtain the product in its final form may lack scalabihty. 

Analysts must recognize that the end use as well as the uncertainty determines the value of measurements. While the operators may pay the most attention to one set of measurements in making their decisions, another set may be the proper focus for model development and parameter estimation. The predilec tion is to focus on those measurements that the operators Believe in or that the designers/con-trollers originally believed in. While these may not be misleading, they are usually not optimal, and analysts must consciously expand their vision to include others. 

Once the highest steam level is set, then intermediate levels must be established. This involves having certain turbines exhaust at intermediate pressures required of lower pressure steam users. These decisions and balances should be done by in-house or contractor personnel having extensive utility experience. People experienced in this work can perform the balances more expeditiously than people with primarily process experience. Utility specialists are experienced in working with boiler manufacturers on the one hand and turbine manufacturers on the other. They have the contacts as well as knowledge of standard procedures and equipment size plateaus to provide commercially workable and optimum systems. At least one company uses a linear program as an aid in steam system optimization. 

The last-mentioned property of a synthetic process, i.e. versatility, is frequently an important consideration in research on optimally effective therapeutic agents in which the synthesis of a large series of structural analogs from a single intermediate is desirable. This aspect of the problem-solving environment can play a decisive role in synthetic design. 

When optimizing industrial ventilation, the real consequences for the environment due to decisions made are of interest. Therefore, the marginal effect on the whole energy system is what is required. This is of course difficult. Many practitioners use electricity produced from coal processes as marginal, but some use natural-gas-fired power plants. It depends mainly on the area and time frame that is being considered. 

Rossiter and Douglas (1986) state that the first step in process design is to generate a basic structure for the flowsheet i.e. the choice of unit operations and interconnections which can be analysed, refined and costed, and then compared to alternatives. Thus, the generation of an industrial crystallization flowsheet gives rise to a number of optimization problems for which a systematic hierarchical decision process for particulate systems was proposed ... 

The initial aim of the procedure is to generate a reasonable base case design that can be used for preliminary economic evaluation of the process. This can subsequently be optimized and/or compared with any process alternatives that are identified. The complete process is always considered at each decision level, but additional fine detail is added to the structure of the flowsheet at any stage. Established heuristics and equipment selection procedures are used together with new process synthesis insights to guide each flowsheet decision. 

The analytical tools to accomplish laminate design are at least twofold. First, the invariant laminate stiffness concepts developed by Tsai and Pagano [7-16 and 7-17] used to vary laminate stiffnesses. Second, structural optimization techniques as described by Schmit [7-12] can be used to provide a decision-making process for variation of iami-nate design parameters. This duo of techniques is particularly well suited to composite structures design because the simultaneous possibility and necessity to tailor the material to meet structural requirements exists to a degree not seen in isotropic materials. 

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