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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

On Mixed-Integer Programming Formulations for the Unit Commitment Problem

We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.

97 MATHEMATICS AND COMPUTING↗

Light Water Reactor Sustainability Program Materials Research Pathway Technical Program Plan

The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Approximating Two-Stage Chance-Constrained Programs with Classical Probability Bounds

We consider a joint-chance constraint (JCC) as a union of sets, and approximate this union using bounds from classical probability theory. When these bounds are used in an optimization model constrained by the JCC, we obtain corresponding upper and lower bounds on the optimal objective function value. We compare the strength of these bounds against each other under two different sampling schemes, and observe that a larger correlation between the uncertainties tends to result in more computationally challenging optimization models. We also observe the same set of inequalities to provide the tightest upper and lower bounds in our computational experiments.

97 MATHEMATICS AND COMPUTING↗

Texture analysis of AGR program matrix materials

We report the fuel form for high-temperature gas-cooled reactors consists of tristructural isotropic (TRISO) particles embedded in a matrix of graphite flake and carbonized resin. The process of overcoating particles prior to compacting yields a circumferential orientation of the graphite flake surrounding the TRISO particles, which is modified to varied extents when overcoated particles are pressed into the final fuel form. As graphite is highly anisotropic, the texture may impact the properties and performance of the fuel. Ellipsometry was used to measure the texture of the matrix for fueled compacts and unfueled “matrix-only” samples. Results indicated local texture related to the spherical particles in compacts associated with overcoating versus a more linear layered structure in “matrix-only” samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Scalable Programming Workflows for Validation of Quantum Computers

Hybrid quantum-classical workflows have become standard methods for executing variational algorithms and other quantum simulation techniques, which are key applications for noisy intermediate scale quantum (NISQ) computers. Validating these simulations is an important task which helps gauge the progress of quantum computer development, and classical simulation can serve as a tool to this end. Both exact and more scalable approximate methods with quantifiable error bounds can be used in validation tasks where the applicable metrics include the distance from a calculable ground truth, the quality of an error model fit to data, etc. Here we present a library extension that includes methods for validation of quantum simulations based on scalable hybrid workflows executable on high performance computers. We provide examples that use approximate methods based on tensor networks and stabilizer simulators to bound the error of quantum simulations on NISQ hardware.

Nguyen, Thien↗

JACC: Leveraging HPC Meta-Programming and Performance Portability with the Just-in-Time and LLVM-based Julia Language

We present JACC (Julia for Accelerators), the first high-level, and performance-portable model for the just-in-time and LLVM-based Julia language. JACC provides a unified and lightweight front end across different back ends available in Julia, enabling the same Julia code to run efficiently on many HPC CPU and GPU targets. We evaluated the performance of JACC for common HPC kernels as well as for the most computationally demanding kernels used in applications, HPCCG, a supercomputing benchmark test for sparse domains, and HARVEY, a blood flow simulator to assist in the diagnosis and treatment of patients suffering from vascular diseases. We carried out the performance analysis on the most advanced US DOE supercomputers: Aurora, Frontier, and Perlmutter. Overall, we show that JACC has a negligible overhead versus vendor-specific solutions, reporting GPU speedups with no extra cost to programmability.

Valero-Lara, Pedro↗