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ORNL has established a program with four complementary subprograms to meet its LDRD objectives and to fulfill the particular needs of the laboratory. A provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel ideas with scientific and technological merit will be recognized and supported.
Deuterium-tritium fusion reactors cannot operate for a significant period without a closed tritium fuel cycle, according to a recent National Academies of Sciences (NAS) report on bringing fusion reactors to the US electrical grid. This fact places breeder blankets as one of the foundational systems for self-sustained fusion reactor operation. The typical functional requirements for a breeder blanket system include producing tritium, absorbing kinetic energy, transporting thermal energy, and being environmentally attractive. State-of-the-art research on liquid blankets has converged to primarily focus on (LiF) 2 and BeF 2 (FLiBe) molten salts and a metallic eutectic of lead and lithium (PbLi), but “virtually all of the technologies related to the tritium fuel cycle are at a low technological readiness level”. This work sought to explore optimum blanket configurations as it aligned with the Oak Ridge National Laboratory (ORNL) FY 2023 Laboratory Directed Research and Development Program’s research priority of developing and expanding the current understanding of fusion blanket science and technology. This purpose of this work was to address ORNL research priorities and NAS recommendations by investigating novel liquid blanket materials that could provide self-sustaining operation and draw on experience from research on molten salts used for advanced fission reactors, concentrated solar, and thermal energy storage. The hypothesis when proposing this research was that there could be chloride-based blanket designs that can exceed the tritium breeding ratios of (FLiBe) molten salt blankets while reducing the use of Be (FLiBe), avoiding the generation of HF (FLiBe), and minimizing magnetohydrodynamic (MHD)-perturbed flow fields (PbLi). The fastest and most cost-effective path to deploying liquid fusion breeder blankets could be from maximizing the synergistic technological overlap between fusion, fission, concentrated solar, and thermal energy storage industries.
The project summaries are organized by Capability Pillar – Complex Natural and Engineered Systems, Information Science and Technology, Materials for the Future, Nuclear and Particle Futures, Science of Signatures, and Weapons Systems. Project summaries for continuing projects appear first, followed by project summaries and technical outcomes for projects that ended in FY23.
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The President’s Council of Advisors on Science and Technology (PCAST) is the sole body of advisors from outside the federal government charged with making science, technology, and innovation policy recommendations to the President and the White House. Established by Executive Order, it is an independent Federal Advisory Committee comprised of distinguished individuals from industry, academia, and non-profit organizations with a range of perspectives and expertise. On December 5, 2024, PCAST sent a report to the President with recommendations to strengthen and improve the NITRD program and its activities to provide an even greater positive impact for the Nation.
Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.
The Biological and Environmental Research (BER) program advances fundamental research and scientific user facilities to support Department of Energy (DOE) missions in scientific discovery and innovation, energy security, and environmental responsibility. BER seeks to understand the biological, biogeochemical, and physical principles needed to predict a continuum of processes occurring across scales, from molecular and genomics-controlled mechanisms at the smallest scales to environmental and Earth system change at the largest scales.
The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.
This is the final technical report from the grant "A membrane-based approach to medical isotope purification" which was awarded by the Isotope Research and Development Program through the early career research program to Christine Duval at Case Western Reserve University. The project developed adsoprtive membranes with covalently bound diglycolamide-derived ligands for the purification of Ac-225 and benchmarked them against the current state of the art adsorbent materials.
The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.
On June 28–29, 2021, the US Department of Energy’s (DOE’s) Advanced Scientific Computing Research (ASCR) program in the Office of Science convened a workshop with the Energy Efficiency and Renew able Energy (EERE) program offices to assess the future need for advanced computing resources in the areas of clean energy and advanced manufacturing. In part, this discussion served as an update to earlier workshops and townhalls. ASCR is guided by DOE mission needs as it develops research programs, computers, and networks at the leading edge of technologies. As the exascale computing era dawns, technology changes are creating new opportunities for those who must use high-performance computing (HPC) and data systems effectively. The ASCR computing facilities are augmenting their strategy to adapt to changing science needs and emerging technologies and to leverage the utility of exascale computing across the federal government.
On October 15, 2021, the U.S. Department of Energy Solar Energy Technologies Office (SETO) released the Performance Targets for Perovskite Photovoltaic Research, Development, and Demonstration Programs Request for Information (RFI) for public response and comment. The RFI sought feedback from industry, academia, research laboratories, government agencies, and other stakeholders on efficiency, stability and replicability performance targets for perovskite (PVSK) photovoltaic devices that could be utilized to align community efforts, ensure relevance of potential future funding programs, and accelerate technical and commercial development and de-risking of perovskite technologies. The RFI included the following proposed target matrix for power conversion efficiency (PCE), area, stability, and sample sizes, and included questions on relevance, completeness, and challenges.
Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.There are 252 mean change files represented in this dataset (12 months * 3 future time periods * 7 variables ). The mean change is calculated by taking the mean of the differences between the future projected average (e.g., 2046-2065) and the climate model baseline (e.g., 1979-1999). The differences were calculated for each downscaled GCM and then averaged across all models to obtain the mean change. This mean of the differences was calculated for each month, each future time period, and each variable.
Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.These grid files were created from data collected using a Riegl 3-D laser scanner. Millions of x, y, and z points from the F2 Washover Fan on Onslow Beach were processed using the MARS software package to define a bare-earth model. Grid files were imported into Golden Software Surfer version 19 for editing and exported from that application as .grd files. Files can be opened in Surfer or ArcMap, but the coordinate system information will be lost if opened in ArcMap. These data were collected to quantify the morphological changes that occur on a washover fan through time.
This note summarizes our research activities within the TEAM project between October 2019 and November 2020, funded by the ASCR Advanced Research in Quantum Computing program. Three research efforts have begun during the review period. The first effort, resulting in the JuQBox software, implemented a novel algorithm for optimal control in closed quantum systems based on symplectic time integration and exact calculations of the gradient of the discretized objective function. In our second effort, resulting in a code called Quandary, we consider the optimal control problem for open quantum systems. Here the evolution of the quantum system is modeled by the Lindblad master equation. In this code, we are considering both the realization of quantum gates as well as the optimal reset problem in which a general mixed quantum state is driven towards its ground state. In our third research effort we have begun the development of computational software for what we call Lindblad learning, i.e. the process of characterizing the equations governing our quantum computing hardware.
The vortex on this issue’s cover represents the sense of uncertainty experienced by scientists in the initial stages of exploring a new research path. The article beginning on p. 4 introduces research projects of higher technical risk conducted under Lawrence Livermore’s Disruptive Research (DR) Program, a component of the Laboratory Directed Research and Development Program. If successful, DR projects yield order-of-magnitude rewards. If DR projects fail to meet stated goals, they offer different rewards by shaping future research and investment
The promotional schedule to advertise the NRC Research Associateship Programs included the following: 1) attending meetings of major scientific and engineering professional societies; 2) advertising in society meeting programs as well as their online career centers; 3) emailing program announcements to the heads of appropriate science and engineering departments of U.S. academic institutions that grant doctoral degrees in STEM fields; 4) posting announcements on online job and career sites and ResearchGate; 5) advertising print ads in Science magazine; and 6) maintaining a presence on the program’s Twitter and Facebook pages.
Throughout this year’s report, we highlight how the LDRD program invests in ideas that make the world a safer place. We review key accomplishments and performance indicators, and we share snapshots of some of our talented staff. I also encourage you to visit our LDRD website and learn more about the 244 projects that we supported during fiscal year 2020. Looking to the future, I am confident that LDRD investments will continue to help LLNL remain at the forefront of innovative research.