Understanding the dynamics of agricultural basins has been difficult for decision-makers when developing cost-effective plans. An uncertainty analysis evaluates the impact of information gaps on hydrologic model’s output and performance. The Agricultural Policy/Environmental Extender (APEX v1501) was used to predict runoff, crop yield, sediment load, total phosphorus, and total nitrogen from agricultural fields in the Mississippi Delta to investigate the impact of using different input variables (climate, soils, and management practices) on mechanistic models. Results indicated that the use of surrogate information such as weather data from close weather stations, a predominant soil series, and simulated irrigation schedules, could be considered when available in situ information is restricted. Overall results provided information on model setup and output interpretation that may be useful to Mississippi Delta decision-makers.

Quantitative risk analysis (QRA) is widely applied in several industries as a tool to improve safety, as part of design, licensing or operational processes. Nevertheless, there is much less academic research on the validity and validation of QRA, despite their importance both for the science of risk analysis and with respect to its practical implication for decision-making and improving system safety. In light of this, this paper presents a review focusing on the validity and validation of QRA in a safety context. Theoretical, methodological and empirical contributions in the scientific literature are reviewed, focusing on three questions. Which theoretical views on validity and validation of QRA can be found? Which features of QRA are useful to validate a particular QRA, and which frameworks are proposed to this effect? What kinds of claims are made about QRA, and what evidence is available for QRA being valid for the stated purposes? A discussion follows the review, focusing on the available evidence for the validity of QRA and the effectiveness of validation methods.

An investigation was conducted to assess the usefulness of anti-optimization in the process of validating of aerodynamic codes. Anti-optimization is defined here as the intentional search for regions where the computational and experimental results disagree. Maximizing such disagreements can be a useful tool in uncovering errors and/or weaknesses in both analyses and experiments. The codes chosen for this investigation were an airfoil code and a lifting line code used together as an analysis to predict three-dimensional wing aerodynamic coefficients. The parameter of interest was the maximum lift coefficient of the three-dimensional wing, CL max. The test domain encompassed Mach numbers from 0.3 to 0.8, and Reynolds numbers from 25,000 to 250,000. A simple rectangular wing was designed for the experiment. A wind tunnel model of this wing was built and tested in the NASA Langley Transonic Dynamics Tunnel. Selection of the test conditions (i.e., Mach and Reynolds numbers) were made by applying the techniques of response surface methodology and considerations involving the predicted experimental uncertainty. The test was planned and executed in two phases. In the first phase runs were conducted at the pre-planned test conditions. Based on these results additional runs were conducted in areas where significant differences in CL max were observed between the computational results and the experiment — in essence applying the concept of anti-optimization. These additional runs were used to verify the differences in CL max and assess the extent of the region where these differences occurred. The results of the experiment showed that the analysis was capable of predicting CL max to within 0.05 over most of the test domain. The application of anti-optimization succeeded in identifying a region where the computational and experimental values of CL max differed by more than 0.05, demonstrating the usefulness of anti-optimization in process of validating aerodynamic codes. This region was centered at a Mach number of 0.55 and a Reynolds number of 34,000. Including considerations of the uncertainties in the computational and experimental results confirmed that the disagreement was real and not an artifact of the uncertainties. / Ph. D.

Die zentralen Fragestellungen der Arbeit sind, wie die Insolvenzwahrscheinlichkeiten von Unternehmen prognostiziert und wie sie durch zielgerichtetes Handeln beeinflusst werden können. Hierzu gibt der Autor zunächst einen ausführlichen Überblick über die derzeit in Wissenschaft und Praxis verwendeten Ansätze zur Prognose von Unternehmensinsolvenzen, Schätzgütemaßen von Insolvenzprognosen sowie Datenquellen, die für die Prognose von Unternehmensinsolvenzen zur Verfügung stehen. Anschließend entwickelt er ein kausales Unternehmensmodell, das er mit stochastischen Simulationsverfahren analysiert. Das Modell wird validiert und mit Benchmarkverfahren verglichen. Abschließend zeigt der Autor, wie das Modell zur Ableitung von Handlungsempfehlungen zur Beeinflussung der individuellen Insolvenzwahrscheinlichkeit von Unternehmen herangezogen werden kann.

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This master's thesis deals with development of a module for a data mining system, which is being developed on FIT. The first part describes the general knowledge discovery process and cluster analysis including cluster validation; it also describes Oracle Data Mining including algorithms, which it uses for clustering. At the end it deals with the system and the technologies it uses, such as NetBeans Platform and DMSL. The second part describes design of a clustering module and a module used to compare its results. It also deals with visualization of cluster analysis results and shows the achievements.

This paper presents a mathematical model to predict the distribution of yarn tension and the balloon shape as a function of spindle speed in the ring spinning process. The dynamic yarn path from the delivery rollers to the winding point on the cop has been described with a non-linear differential equation system. These equations have been integrated with a Runge–Kutta method using MATLAB software. Since the numerical solution of the equations strongly depends on initial values, an algorithm of sensitivity analysis has been developed to predict the right choice of initial values in order to find a stable solution. For model validation purposes, the yarn tension has been measured between delivery rollers and yarn guide. Furthermore, a high-speed camera has been used to capture the balloon shape at different spindle angular velocities in order to compare the theoretically determined balloon shape with the one that actually occurs on the machine.