A2 Noradrenergic Lesions Prevent Renal Sympathoinhibition Induced by Hypernatremia in Rats

Renal vasodilation and sympathoinhibition are recognized responses induced by hypernatremia, but the central neural pathways underlying such responses are not yet entirely understood. Several findings suggest that A2 noradrenergic neurons, which are found in the nucleus of the solitary tract (NTS), play a role in the pathways that contribute to body fluid homeostasis and cardiovascular regulation. The purpose of this study was to determine the effects of selective lesions of A2 neurons on the renal vasodilation and sympathoinhibition induced by hypertonic saline (HS) infusion. Male Wistar rats (280–350 g) received an injection into the NTS of anti-dopamine-beta-hydroxylase-saporin (A2 lesion; 6.3 ng in 60 nl; n = 6) or free saporin (sham; 1.3 ng in 60 nl; n = 7). Two weeks later, the rats were anesthetized (urethane 1.2 g⋅kg−1 b.wt., i.v.) and the blood pressure, renal blood flow (RBF), renal vascular conductance (RVC) and renal sympathetic nerve activity (RSNA) were recorded. In sham rats, the HS infusion (3 M NaCl, 1.8 ml⋅kg−1 b.wt., i.v.) induced transient hypertension (peak at 10 min after HS; 9±2.7 mmHg) and increases in the RBF and RVC (141±7.9% and 140±7.9% of baseline at 60 min after HS, respectively). HS infusion also decreased the RSNA (−45±5.0% at 10 min after HS) throughout the experimental period. In the A2-lesioned rats, the HS infusion induced transient hypertension (6±1.4 mmHg at 10 min after HS), as well as increased RBF and RVC (133±5.2% and 134±6.9% of baseline at 60 min after HS, respectively). However, in these rats, the HS failed to reduce the RSNA (115±3.1% at 10 min after HS). The extent of the catecholaminergic lesions was confirmed by immunocytochemistry. These results suggest that A2 noradrenergic neurons are components of the neural pathways regulating the composition of the extracellular fluid compartment and are selectively involved in hypernatremia-induced sympathoinhibition

Dynamic Simulator for Nuclear Power Plants (DSNP)

A new simulation language DSNP (Dynamic Simulator for Nuclear Power Plants) is being developed. It is a simple block oriented simulation language with an extensive library of component and auxiliary modules. Each module is a self-contained unit of a part of a physical component to be found in nuclear power plants. Each module will be available in four levels of sophistication, the fourth being a user supplied model. A module can be included in the simulation by a single statement. The precompiler translates DSNP statements into FORTRAN statements, takes care of the module parameters and the intermodular communication blocks, prepares proper data files and I/0 statements and searches the various libraries for the appropriate component modules. The documentation is computerized and all the necessary information for a particular module can be retrieved by a special document generator. The DSNP will be a flexible tool which will allow dynamic simulations to be performed on a large variety of nuclear power plants or specific components of these plants. (auth

Level-one modules library for DSNP: Dynamic Simulator for Nuclear Power-plants

The Dynamic Simulator for Nuclear Power-plants (DSNP) is a system of programs and data sets by which a nuclear power plant or part thereof can be simulated at different levels of sophistication. The acronym DSNP is used interchangeably for the DSNP language, for the DSNP precompiler, for the DSNP libraries, and for the DSNP document generator. The DSNP language is a set of simple block oriented statements, which together with the appropriate data, comprise a simulation of a nuclear power plant. The majority of the DSNP statements will result in the inclusion of a simulated physical module into the program. FORTRAN statements can be inserted with no restrictions among DSNP statements

DSNP: a new approach to simulate nuclear power plants

The DSNP (Dynamic Simulator for Nuclear Power-plants) is a special purpose block oriented simulation language. It provides for simulations of a large variety of nuclear power plants or various parts of the power plant in a simple straightforward manner. The system is composed of five basic elements, namely, the DSNP language, the precompiler-or the DSNP language translator, the components library, the document generator, and the system data files. The DSNP library of modules includes the selfcontained models of components or physical processes found in a nuclear power plant, and various auxiliary modules such as material properties, control modules, integration schemes, various basic transfer functions etc. In its final form DSNP will have four libraries

Kinetic model of sodium-water reaction applied to dynamic simulation of leak detection in the core components test loop. [LMFBR]

A detailed model for the CCTL steam-generator leak-detection simulation was developed to predict the hydrogen- and oxygen-detector response during a series of experiments to be performed at ANL. The detailed kinetic equations for the sodium-water interaction are given, as well as the assumptions made in assessing the various reactivity rates and hydrogen-gas migration in the sodium toward a free surface in contact with the cover gas. A dynamic model was developed describing concentration changes as a result of primary and secondary sodium reactions, sodium flow through the system piping, mixing processes in various plenum elements, cold-trap operation, cover-gas pressure changes, and water leaks. A computer program CCTL-DYSP has been written in which the dynamic model was simulated to obtain the concentration of the different reaction products as functions of time for any segment of the CCTL system. A generalized approach was used in the modeling and programming procedures, so that only the input data have to be changed in order to analyze different experiments and different system configurations. With minor changes, the computer program can be adapted to simulate leak detection in the CRBR. Some representative results are included in the report, and qualitatively they are in agreement with similar results published elsewhere. Some experimental results also became available recently,and they are in good agreement with the simulated concentrations