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2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

Department of Energy Office of Science Graduate Student Research (SCGSR) Program Mid-Award Project Report

Three-quarters of the total mass of the universe is believed to be ”dark”, meaning that it does not interact with light; it’s presence has only been inferred through astrophysical observations. Because this so-called dark matter has never been observed directly, the question of its identity has become one of the most prominent unresolved mysteries in physics. With many answers ruled out, a direct observation of dark matter is certain to uncover new physics beyond the Standard Model, making it an enticing area of study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Lawrence Graduate Research Scholar, Allegra Mayer, 2021 (Final Report)

Carbon storage in tropical forest soil depends on the balance between large C inputs from high rates of productivity, and high rates of soil C loss due to rapid decomposition rates. Disturbances to tropical forests, including severe hurricanes, could result in globally significant fluxes of C either to or from forest soils. Severe hurricane events are increasing in frequency in the tropics, yet the vulnerability of soil carbon to a frequent severe hurricane regime is unknown. By constraining a model with samples from before and after three major hurricanes within thirty years, this study examines the cycling of C between soil pools and with depth, under conditions marked by sudden organic matter pulses, rapid shifts in forest structure, and fast decomposition rates.

54 ENVIRONMENTAL SCIENCES↗

Graduate Fellowships [Slides]

All fellowship awards and their corresponding internships must be approved by LANL management. Awards and corresponding internship assignments are not guaranteed, even if student has management support.

99 GENERAL AND MISCELLANEOUS↗

LANL-TAMUS Graduate Fellowship Report

The goal of this project is to conduct analysis of 147 Sm neutron transmission (n,tot) data at DICER alongside previously collected neutron capture (n,γ) data and report updated resonance parameters and spins. Measurement and analysis of neutron-capture data, without neutron transmission data, has been conducted before and showed that the gamma widths, Γ γ , and neutron widths, Γn, both deviate from the distributions predicted by well-established theory. Γ γ is expected to follow a narrow Gaussian distribution independent of energy but instead a broadening of the distribution around 350 eV incident neutron energy was observed (P. E. Koehler et al. Phys. Rev. C 108, 142502 (2012)). Γ n is predicted to follow a chi-squared distribution with one degree of freedom known as the Porter-Thomas distribution but this prediction also failed above 350 eV incident neutron energy (P. E. Koehler et al. Phys. Rev. C 76, 025804 (2007)). This project seeks to reassess this past measurement by including neutron transmission data and simultaneously analyzing them alongside the neutron capture data to extract the most accurate measure of Γ γ and Γ n ever taken for the resonances of 147 Sm and see if theory holds or fails under a more refined measurement with newer data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Studies to Improve the Sensitivity to Low Energy Interactions in Dual-Phase Xenon Dark Matter Detectors. Department of Energy Office of Science Graduate Student Research (SCGSR) Program, Final project report

Noble liquid time projection chambers (TPCs) are some of the most sensitive particle detectors ever developed. They see use in searches for new physics with neutrinos, or for new particles like dark matter. They work by sensing light and charge signals left behind by particle interactions in a volume of liquified xenon or argon. TPCs are so sensitive that even a single electron liberated in an interaction can be readily detected. However this sensitivity to signals comes with a sensitivity to background noise, with one example being single electrons that arrive long after the signals from a true particle interaction. This type of noise has been the subject of multiple studies, which have concluded that single electron backgrounds are well correlated with prior events in the TPC, as well as impurities in the detection medium. At Lawrence Livermore National Laboratory (LLNL), the XeNu TPC is a testbed for a novel study of these backgrounds by generating data with new components made of aluminum and Shapal--the latter being an exotic ceramic which can be machined using standard tools. These materials were selected to replace plastic components which introduce impurities in the TPC during operation. Without plastic, the hope is that electron backgrounds will be reduced, leaving new opportunities for studying their origins and dependence on impurities. The SCGSR fellowship served as a springboard to help meet these objectives. Over the course of a year, the new components were designed, fabricated, and installed in XeNu. Following their installation, data was taken for use in a future study that will enable the electron background contributions from plastic components to be studied directly. In the interim, preliminary analysis results indicate that electron backgrounds with the new components are roughly 50% lower. This has established the efficacy of Shapal as a low-background replacement for plastic components where electrical and thermal stability are needed

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗