Hot Zero and Full Power Validation of PHISICS RELAP-5 Coupling

PHISICS is a reactor analysis toolkit developed over the last 3 years at the Idaho National Laboratory. It has been coupled with the reactor safety analysis code RELAP5-3D. PHISICS is aimed at providing an optimal trade off between needed computational resources (in the range of 10~100 computer processors) and accuracy. In fact, this range has been identified as the next 5 to 10 years average computational capability available to nuclear reactor design and optimization nuclear reactor cores. Detailed information about the individual modules of PHISICS can be found in [1]. An overview of the modules used in this study is given in the next subsection. Lately, the Idaho National Laboratory gained access plant data for the first cycle of a PWR, including Hot Zero Power (HZP) and Hot Full Power (HFP). This data provides the opportunity to validate the transport solver, the interpolation capability for mixed macro and micro cross section and the criticality search option of the PHISICS pack

ExoMol line lists XXVIII: The rovibronic spectrum of AlH

A new line list for AlH is produced. The WYLLoT line list spans two electronic states $X\,{}^1\Sigma^+$ and $A\,{}^1\Pi$. A diabatic model is used to model the shallow potential energy curve of the $A\,{}^1\Pi$ state, which has a strong pre-dissociative character with only two bound vibrational states. Both potential energy curves are empirical and were obtained by fitting to experimentally derived energies of the $X\,{}^1\Sigma^+$ and $A\,{}^1\Pi$ electronic states using the diatomic nuclear motion codes Level and Duo. High temperature line lists plus partition functions and lifetimes for three isotopologues $^{27}$AlH, $^{27}$AlD and $^{26}$AlH were generated using ab initio dipole moments. The line lists cover both the $X$--$X$ and $A$--$X$ systems and are made available in electronic form at the CDS and ExoMol databases

Analysis of combined low-level indicators for the hot-season performance of roof components

A single performance indicator, the solar transmittance factor (STF), has been proposed in previous works, together with the derived solar transmittance index (STI). It is aimed at evaluating the summer performance of the roofing system and allowing the selection of the most effective mix of surface and mass properties. It is easily calculated from low-level indicators such as U-value, module of periodic thermal transmittance, and solar reflectance. In the present work, the correlation between STF and the cooling energy demand, integrated over a reference period, was studied, as well as the peak of ceiling temperature increase with respect to the indoor temperature, relevant for thermal comfort. In particular, the thermal behavior of different roof types with variable insulation was calculated numerically by TRNSYS 17 for a wide set of locations and environmental conditions. Unlike other commonly used indicators, to which the analysis has been extended, a strong correlation with STF was found for both cooling energy demand and ceiling temperature rise

A Storm of Feasibility Pumps for Nonconvex MINLP

One of the foremost difficulties in solving Mixed Integer Nonlinear Programs, either with exact or heuristic methods, is to find a feasible point. We address this issue with a new feasibility pump algorithm tailored for nonconvex Mixed Integer Nonlinear Programs. Feasibility pumps are algorithms that iterate between solving a continuous relaxation and a mixed-integer relaxation of the original problems. Such approaches currently exist in the literature for Mixed-Integer Linear Programs and convex Mixed-Integer Nonlinear Programs: both cases exhibit the distinctive property that the continuous relaxation can be solved in polynomial time. In nonconvex Mixed Integer Nonlinear Programming such a property does not hold, and therefore special care has to be exercised in order to allow feasibility pumps algorithms to rely only on local optima of the continuous relaxation. Based on a new, high level view of feasibility pumps algorithms as a special case of the well-known successive projection method, we show that many possible different variants of the approach can be developed, depending on how several different (orthogonal) implementation choices are taken. A remarkable twist of feasibility pumps algorithms is that, unlike most previous successive projection methods from the literature, projection is "naturally" taken in two different norms in the two different subproblems. To cope with this issue while retaining the local convergence properties of standard successive projection methods we propose the introduction of appropriate norm constraints in the subproblems; these actually seem to significantly improve the practical performances of the approach. We present extensive computational results on the MINLPLib, showing the effectiveness and efficiency of our algorithm