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Colin Judge: Testing structural materials in Idaho’s newest hot cell facility
Idaho National Laboratory’s newest facility—the Sample Preparation Laboratory (SPL)—sits across the road from the Hot Fuel Examination Facility (HFEF), which started operating in 1975. SPL will host the first new hot cells at INL’s Materials and Fuels Complex (MFC) in 50 years, giving INL researchers and partners new flexibility to test the structural properties of irradiated materials fresh from the Advanced Test Reactor (ATR) or from a partner’s facility.
Materials meant to withstand extreme conditions in fission or fusion power plants must be tested under similar conditions and pushed past their breaking points so performance and limitations can be understood and improved. Once irradiated, materials samples can be cut down to size in SPL and packaged for testing in other facilities at INL or other national laboratories, commercial labs, or universities. But they can also be subjected to extreme thermal or corrosive conditions and mechanical testing right in SPL, explains Colin Judge, who, as INL’s division director for nuclear materials performance, oversees SPL and other facilities at the MFC.
SPL won’t go “hot” until January 2026, but Judge spoke with NN staff writer Susan Gallier about its capabilities as his team was moving instruments into the new facility.
M. J. R. Chowdhury, M. A. R. Sarkar (BUET)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 867-871
Generation Expansion Planning (GEP) is one of the significant modules in power system planning studies performed for next 10 to 30 years. Generation expansion planning, deciding on types and sizes of generating plants should be brought into a power system, is of fundamental importance to electric utilities. Here load is forecasted and it helps in prediction on types of loads. Optimal Generation Expansion Planning (OGEP) is a non-linear and limited optimization problem. All solutions are compared to each other to reach final optimal solution. This paper presents an optimization model and its application to a generation expansion planning problem in Bangladesh for the year 2016 to 2030 and prediction of generation capacity and energy demand up to year 2060 by regression analysis. Due to high growth of electricity demand of 10.8% per annum Bangladesh needs large scale units of power generation units using different types of fuel such as- coal, natural gas, hydro power and nuclear power in future. The diversification of existing energy resources and exploration of new sources specially nuclear power is an important aspect to be considered in order to have a sustainable power development and its implementation in the country. In this model the existing and candidate plants are presented for the feasible simulation to obtain optimum solution of generation unit configuration. In this paper, WASP IV, a well-known software for power expansion planning is used to optimize generation expansion planning of Bangladesh. WASP uses probabilistic simulation and for optimization planning dynamic programming method is used. Repetition of input data, execution of the modules and review of the WASP outputs until an expansion plan is identified, which is optimal within the constraints such as heat used for generation limitation, emission limitation etc. imposed by the user.