Quantitative Model of Optimization on Non-Oil Based Fuel Alternative Energy

Research of “Quantitative Model of Optimization On Non-Oil Based Fuel Alternative Energy” is using goal programing method approach which will generate comprehensive mathematic models to determine policy on alternative energy field beside oil based fuel. The result of the research is sensitivity analytic model and optimization model of nonoil based fuel alternative energy. Developed model is goal programing to optimise alternative energy beside oil based fuel. Model implementation conducted on alternative energy are coal, nature gas and hydro. And the calculation result using Expert Choice Version 9.0 is obtained that coal as alternative energy has relative priority value of 36,8% at overall consistency index 0,04 or 4%. Optimization implemented model conducted at alternative oil based energy plan using calculation of Quantitative System 3.0 program conclude that coal = 9.809274, gas = 0.8409028, hydro = 0. Minimal objective = 18.69225

Neutronic analysis of fuel pin design for the long-life core in a pressurized water reactor

This work presents the neutronic analysis of fuel design for a long-life core in a pressurized water reactor (PWR). In order to achieve a high burnup, a high enrichment U-235 is traditionally considered without special constraints against proliferation. To counter the excess reactivity, Erbium was selected as a burnable poison due to its good depletion performance. Calculations based on a standard fuel model were carried out for the PWR type core using SRAC code system. A parametric study was performed to quantify the neutronically achievable burnup at a number of enrichment levels and for a numerous geometries covering a wide design space of lattice pitch. The fuel temperature and coolant temperature reactivity coefficients as well as the small and large void reactivity coefficients are also investigated. It was found that it is possible to achieve sufficient criticality up to 100 GWd/tHM burnup without compromising the safety parameters.

Mapping Forest Fire Risk—A Case Study in Galicia (Spain)

The optimization of forest management in roadsides is a necessary task in terms of wildfire prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing a decision-making support about vegetation management for firefighting. In this study, nine relevant parameters: elevation, slope, aspect, road distance, settlement distance, fuel model types, normalized difference vegetation index (NDVI), fire weather index (FWI), and historical fire regimes, were considered as indicators of the likelihood of a forest fire occurrence. The parameters were grouped in five categories: topography, vegetation, FWI, historical fire regimes, and anthropogenic issues. This paper presents a novel approach to forest fire risk mapping the classification of vegetation in fuel model types based on the analysis of light detection and ranging (LiDAR) was incorporated. The criteria weights that lead to fire risk were computed by the analytic hierarchy process (AHP) and applied to two datasets located in NW Spain. Results show that approximately 50% of the study area A and 65% of the study area B are characterized as a 3-moderate fire risk zone. The methodology presented in this study will allow road managers to determine appropriate vegetation measures with regards to fire risk. The automation of this methodology is transferable to other regions for forest prevention planning and fire mitigation.