AIMS Testing Results and Discussion

Data collection was performed with Agilents GC ChemStation software revision A.06.03. Although ChemStation software is in-use at DuPont, the MARS units typically used more traditional Laboratory Information Management Systems (LIMS) for GC data management. 

The raw GC data was converted into compositional data using the internal standard method with either N2 or Kr as the reference species. Once the species compositions were determined, values for the reactant conversion, product selecti-vities, and product yields were evaluated using the standard expressions. Errors in these parameters were calculated by closing the mass balance on the reaction. This was done by comparing the feed gas composition with the measured product gas compositions. Large errors in the mass balance ( 5%) were indicative of physical problems with the system, which were typically attributed to leaks. Smaller errors ( 5%) were caused by uncertainties in the GC molar response factors as well as fluctuations in flow rates of the MFCs on the Feed Gas Mixing Board. 

Operating the AIMS under the reaction conditions was similar to other catalyst test systems at DuPont that utilize reactors run in parallel, such as the MARS system (Mills and Nicole, 2005). Considerable care was needed to setup the system so 

---

Until now, we have discussed group comparison or factor analysis v/iih fixed effects. Fixed effects means that the levels of our independent variables will be the same (fixed) in any attempted replication of our experiment. We have ehosen a eertain seleetion of levels that are of interest and do not attempt to generalize beyond these levels. As an example, let us consider a comparison of the impedance of electrode types. We could do a study in which the aim is to compare a certain selection of electrode types with different characteristics, and electrode type would then be a fixed factor. We could also do a study in which the aim is to assess whether the electrode type has an effect on the measured impedance in general. The electrode type would then be a random factor, and our sample of electrode types (levels) would be treated as a random selection of the overall population of possible electrode types/manufacturers. In the first case, our test result will be the explicit differences between the impedance of the selected electrode t5rpes, but for the second case the test result will be the general effect of electrode tjrpe on the impedance. In some cases. 

ABSTRACT Several EU PAMINA project partners have applied different Sensitivity Analysis (SA) techniques to analytical models as well as to a simplified, though representative, PA model. The aims of the exercise were to investigate the performance of different techniques in the presence of features such as (lack of) linearity, (lack of) monotony, interactions, etc. to check the importance of sample size to compare different options within a given S A technique to cross-compare the results obtained using different teehniques and to get a better understanding of the rationale behind every available technique and about their capabilities and shortcomings. This paper presents and discusses some results on the tests of global sensitivity analysis performed with variance-based sensitivity indicators. 

Chapter 3 offers the customer demand forecast dynamic equation model, provides the model to determine the parameters in the model and discusses the method for parametric estimation and hypothesis testing for forecasting model error aimed at the customer demand forecast issue in the formulation of supply chain logistics planning. Furthermore, in order to enhance the precision of customer demand forecast in the supply chain and obtain relatively ideal forecast results, the research... 

A case study was devised to evaluate the framework, focused on the services of the Liferay Portal, an enterprise web platform project that aims for immediate delivery of robust business solutions for organizations. This case study allowed us to demonstrate the flexibility, usability and utility of the framework. The results revealed the services under test performing quite well in the situations tested. Obviously, the quality of the tests performed depends on the testing tools used, but this discussion is out of the scope of this work, as the merits of each tool were evaluated and discussed in different works by their authors [2, 9]. 

A round robin test result was reported and discussed in the previous paper [5] using double edge notched tensile (DENT) specimens of 1mm thickness injection moulded plastics with two types of materials ABS as a semi-ductile material and PP as a ductile material, aiming at investigation of the cause of lab dependency of this method or to find possibility of improvement in reproducibility. These injection moulded specimens were... 

So far, the only approximation in our description of the FMS method has been the use of a finite basis set. When we test for numerical convergence (small model systems and empirical PESs), we often do not make any other approximations but for large systems and/or ab //i/Y/o-determined PESs (AIMS), additional approximations have to be made. These approximations are discussed in this subsection in chronological order (i.e., we begin with the initial basis set and proceed with propagation and analysis of the results). 

---