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This PhD defense presentation includes how the results assessment methodology identifies physics driving behavior in simulated results using comparison with analytic and reduced-fidelity computational models.
Previous generations of scientists would make tremendous efforts to simplify non-tractable problems and generate simpler models that preserved the fundamental physics. This process involved applying assumptions and simplifications to reduce the complexity of the problem until it reached a solvable form. Each assumption and simplification was chosen and applied with the intent to preserve the essential physics of the problem, since, if the core physics of the problem were eliminated, the simplified model served no purpose. Moreover, if done correctly, solutions to the reduced model would serve as useful approximations to the original problem. In a sense, solving the simple models laid the ground-work for and provided insight into the more complex problem. Today, however, the affordability of high performance computing has essentially replaced the process for analyzing complex problems. Rather than "building up" a problem by understanding smaller, simpler models, a user generally relies on powerful computational tools to directly arrive at solutions to complex problems. As computational resources grow, users continue trying to simulate new, more complex, or more detailed problems, resulting in continual stress on both the code and computational resources. When these resources are limited, the user will have to make concessions by simplifying the problem while trying to preserve important details. In the context of the Monte Carlo N-Particle radiation transport simulation tool, simplifications typically come as reductions in geometry, or by using variance reduction techniques. Both approaches can influence the physics of the problem, leading to potentially inaccurate or non-physical results. Errors can also be introduced as a result of faulty input into a computational tool: something as simple as transposing numbers in a tally input can result in incorrect answers. In this paradigm, reduced complexity computational and analytical models still have an important purpose. The explicit form of an analytic solution is arguably the best way to understand the qualitative properties of simple models. In contrast to "building up" a complex problem through understanding simpler problems, results from detailed computational scenarios can be better explained by "building down" the complex model through simple models rooted in the fundamental or essential phenomenology. Simplified analytic and computational models can be used to 1) increase a user's confidence in the computational solution of a complex model, 2) con firm there are no user input errors, and 3) ensure essential assumptions of the simulation tool are preserved. This process of using analytic models to develop a more valuable analysis of simulation results is named the results assessment methodology. The utility of the results assessment methodology and a complimentary sensitivity analysis is exempli fied through the analysis of the neutron flux in a dry used fuel storage cask. This application was chosen due to current scientific interest in used nuclear fuel storage.
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The DARHT Weather Enclosure (WE) project provided an excellent opportunity to redesign and rebuild some of DARHT systems without introducing interruptions to normal operations. Multiple improvements were made to the facility to improve data quality and operational reliability.
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Abstract not provided.
NREL will work with the Participant to perform accelerated long-term durability and other standard durability tests for prototypes to help demonstrate the reliability of the technology for PV applications. NREL will test commercially relevant-sized prototypes under realistic environmental soiling conditions to correlate dust removal efficacy for improving the PV output under standard solar conditions. Measurements will include voltage-current characterization in solar simulators before and after dust cleaning.
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These experiments were performed by Bramblett and Czirr at UCRL (i.e., LLNL) in the late 1960s through the 1970s and evaluated by Mark Lee (LFO, retired) for the ICSBEP Handbook. Dimensions, geometry, and benchmark RSFR values are taken from the Handbook. All sample calculational results used COG 11.3 with ENDF/B-VIII.0 cross-sections. A sample input listing is provided in Appendix A.
The material was prepared as part of an independent review (Schubert Review) for the Thorium Fuel Safeguards project.
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Thiis presentation shows the character of an integral experiment. It covers the question why Godiva 4? Additionally, this presentation touches on the IER 498 benchmark quantity, activities facilitated by IER 498, proposed CED-2 test matrix, and what happened during the IER 498’s gap year.
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Advancements in quantum technology, which include quantum computing, quantum sensing, quantum communications, and associated research, continue to revolutionize various fields of study by solving challenging problems deemed too difficult or more efficient than those used for classical computers. However, as these systems become ever so complex, it is critical to secure their electromagnetic operational environments and the associated impact on quantum systems and infrastructure. The goal of this synopsis is to bring attention to the susceptibility of quantum technology facilities to potential issues related to the radio frequency (RF) environment within the broader electromagnetic context. A framework is proposed for identifying, mitigating, monitoring, and auditing these often complex operational environments. By establishing best practices in the consideration and evaluation of these criteria, one can enhance the operational integrity, resilience, and security of quantum technology systems and facilities, thereby supporting their continued development and application in research and industry.