Issues affecting advanced passive light-water reactor safety analysis

Next generation commercial reactor designs emphasize enhanced safety by means of improved safety system reliability and performance. These objectives are achieved via safety system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet, the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs will necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing U.S. advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes may require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.     

Using neural networks to select wavelet features for breast cancerdiagnosis

This study focuses on improving microcalcification classification by establishing an efficient computer-aided diagnosis system that extracts Daubechies-4 and biorthogonal wavelet features. These wavelets were chosen because they have been used in military target recognition and fingerprint recognition research with images characterized by low contrast, similar to mammography. Feature selection techniques are employed to further increase classification performance. The artificial neural network feature selection techniques are complemented by a conventional decision boundary-based feature selection method. The results using the wavelet features are compared to more conventional measures of image texture, angular second moment, and Karhunen Loeve coefficients. The use of alternative signal processing to compare wavelet and neural techniques allows for a measure of the problem difficulty. It is concluded that advances and contributions have been made with the introduction of two novel feature extraction methods for breast cancer diagnosis, wavelets and eigenmasses. Additionally, feature selection techniques are demonstrated, compared, and validated, transforming adequate discrimination power into promising classification results     

Caring for dying children: nurses' experiences

Interviews with 25 nurses in this grounded theory study show that when nurses recognized that a child's death was inevitable, they struggled with both grief distress and moral distress. Their distress occurred within the context of the nurse-patient relationship. Nurses employed a range of strategies to manage their distress. Several conditions facilitated or constrained nurses' strategies, and resulted in far-reaching implications both professionally and personally.     

MERLIN: a device diagnosis system based on analytic models

An approach to computer-aided interpretation of parametric test data for integrated circuit process-problem diagnosis is presented. In contrast to a conventional expert system, which reasons with a knowledge base consisting of rules acquired from human experts, the system presented centers its knowledge around analytic device equations. By using equations as the basis of the system knowledge, a more universal, well-organized, and concise level of knowledge is encoded. With the use of objects to present this knowledge, a great deal of useful information outside that described by only the symbolic expressions can be represented, and extension to qualitative or numeric models should be straightforward. The result is an expressive, well-organized, easily built, and easily maintained knowledge base. The authors describe the system's interactive graphical displays and the automatic data interpretation algorithms. Examples evaluating n-channel metal oxide semiconductor (NMOS) parameter variations, interconnect parameter variations, and interconnect yields are used for illustration