Design methods data requirements

While many methods for parameter estimation have been proposed, experience has shown some to be more effective than others. Since most phenomenological models are nonlinear in their adjustable parameters, the best estimates of these parameters can be obtained from a formalized method which properly treats the statistical behavior of the errors associated with all experimental observations. For reliable process-design calculations, we require not only estimates of the parameters but also a measure of the errors in the parameters and an indication of the accuracy of the data. 

Table A.4, taken from the CCPS Guidelines for Chemical Reactivity Evaluation and Application to Process Design, shows the questions which need to be asked regarding the safety of the proposed reaction, the data required to answer those questions and some selected methods of investigation. The experimental analysis is extremely specialized, and companies should consider outsourcing the tests if they do not have specialists in this area.

Crystallization proeess systems design and operation is a eomplex matter requiring extensive data for systematie evaluation. Whilst simplified design methods and heuristies are available, the simple faet remains that the more and better the data input, the better the final design and reliability of the plant. Ideally, amongst the data required are the following ... 

Where values cannot be found, the data required will have to be measured experimentally or estimated. Methods of estimating (predicting) the more important physical properties required for design are given in this chapter. A physical property data bank is given in Appendix C. 

This efficient statistical test requires the minimum data collection and analysis for the comparison of two methods. The experimental design for data collection has been shown graphically in Chapter 35 (Figure 35-2), with the numerical data for this test given in Table 38-1. Two methods are used to analyze two different samples, with approximately five replicate measurements per sample as shown graphically in the previously mentioned figure. 

The goal of assessing risk is to build on the knowledge of chemical reactivity hazards, to understand how the hazard properties may lead to loss scenarios in the facility context, and to determine whether existing safeguards are adequate. Therefore, the assessment of risk can be performed at any stage of facility design, development, operation, or alteration. Of course, the more that is known about the facility and its equipment and operation, the more detailed the risk assessment can be. Methods used to determine chemical reaction risks are varied, as are their objectives and data requirements. 

In an attempt to provide this focus, forty-seven active receptor model users from government, university, consulting and industry met for 2 1/2 days in February 1980 it. They addressed the models and the information required to use them in six separate task forces 1) Chemical Element Balance Receptor Models, 2) Multivariate Receptor Models, 3) Microscopic Identification Receptor Models, 4) Field Study Design and Data Management, 5) Source Characterization, and 6) Analytical Methods. The objectives of these interrelated task forces were to ... 

The measurements required for the present receptor models Include particulate matter composition, size and variability for both source and receptor. Obtaining these data requires attention to field study design and data management, source characterization, and analytical methods. 

The first two of the above disadvantages of fixed design methods can be overcome by the use of iterative designs. These are methods in which an initial design that contains a minimum number of data points is used, then the results are investigated and the results of that investigation are used to conclude whether or not one or more new experiments are required, as well as where these additional experiments should be located in the parameter space. 

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