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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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DOE OSTI2023

Potential of the Julia Programming Language for High Energy Physics Computing

Research in high energy physics (HEP) requires huge amounts of computing and storage, putting strong constraints on the code speed and resource usage. To meet these requirements, a compiled high-performance language is typically used; while for physicists, who focus on the application when developing the code, better research productivity pleads for a high-level programming language. A popular approach consists of combining Python, used for the high-level interface, and C++, used for the computing intensive part of the code. A more convenient and efficient approach would be to use a language that provides both high-level programming and high-performance. The Julia programming language, developed at MIT especially to allow the use of a single language in research activities, has followed this path. In this paper the applicability of using the Julia language for HEP research is explored, covering the different aspects that are important for HEP code development: runtime performance, handling of large projects, interface with legacy code, distributed computing, training, and ease of programming. The study shows that the HEP community would benefit from a large scale adoption of this programming language. The HEP-specific foundation libraries that would need to be consolidated are identified.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Receiver willingness to participate in off-hour service programs

Service trips, a frequently overlooked segment of urban traffic, represent a disproportionately large share of the negative impacts associated with commercial activity. The reason is that although service trips are less frequent than freight trips, they often take longer and thus occupy a significant share of commercial parking. Demand management programs seeking to move service trips off-hours can potentially reduce congestion and emissions but they have been understudied. Here, this paper describes research conducted to investigate receivers’ willingness to participate in off-hour programs for planned service activity. The research reported in this paper analyzes results from a survey of 189 business establishments in New York City and the Capital Region in New York State using descriptive analyses of the data, and by estimating a discrete choice model to gain insight into how business characteristics influence willingness to participate in off-hour services. To assess the impacts of a hypothetical off-hour services program, the authors applied the discrete choice model, together with service trip attraction models, to quantify the hours of daytime parking that could be eliminated by the proposed program in certain ZIP Codes in New York City and the Albany area. The research conducted led to the identification of numerous policy implications that will help policymakers understand and maximize the potential benefits of implementing off-hour service programs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Chemical classification program synthesis using generative artificial intelligence

Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEBI) database. These programs can be used for efficient deterministic run-time classification of SMILES structures, with natural language explanations. The programs themselves constitute an explainable computable ontological model of chemical class nomenclature, which we call the ChEBI Chemical Class Program Ontology (C3PO). We validated our approach against the ChEBI database, and compared our results against deep learning models and a naive SMARTS pattern based classifier. C3PO outperforms the naive classifier, but does not reach the performance of state of the art deep learning methods. However, C3PO has a number of strengths that complement deep learning methods, including explainability and reduced data dependence. C3PO can be used alongside deep learning classifiers to provide an explanation of the classification, where both methods agree. The programs can be used as part of the ontology development process, and iteratively refined by expert human curators.

Artificial Intelligence↗
DOE OSTI2015

On-Going International Research Program on Irradiated Concrete Conducted by DOE, EPRI and Japan Research Institutions. Roadmap, Achievements and Path Forward

The Joint Department of Energy (DOE)-Electric Power Research Institute (EPRI) Program (Light Water Reactor Sustainability (LWRS) Program–Material Pathway–Concrete and Long-Term Operation (LTO) Program) and US Nuclear Regulatory Commission (NRC) research studies aim at understanding the most prominent degradation modes and their effects on the long-term operation of concrete structures to nuclear power generation. Based on the results of the Expanded Materials Degradation Analysis (EMDA), (NUREG/CR-7153, ORNL/TM-2011/545), irradiated concrete and alkali-silica reaction (ASR)-affected concrete structures are the two prioritized topics of on-going research. This report focuses specifically on the topic of irradiated concrete and summarizes the main accomplishments obtained by this joint program, but also provides an overview of current relevant activities domestically and internationally. Possible paths forward are also suggested to help near-future orientation of this program.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

2016 Nuclear Energy Voucher Pilot Program Final Summary

In March 2016, the Department of Energy Office of Nuclear Energy (DOE-NE) Gateway for Accelerated Innovation in Nuclear (GAIN) initiative launched the NE Voucher pilot program for small businesses that develop advanced nuclear technologies. The intent of this program is to provide access to unique physical and intellectual capital that exists within the DOE National Laboratory complex for private-sector developers of innovative nuclear energy technologies. Vouchers allow recipients to have work performed on their behalf at select DOE laboratory facilities. The work is funded by DOE-NE and must be completed within approximately 12 months of the award date. Awards for the pilot had values of $50,000–300,000 each, depending on the complexity of the task requested. The program requires a 20% cost share by voucher recipients. In addition to providing the technical assistance sought by the awardees, the 2016 pilot award cycle showed that the program fosters relationships between these businesses and DOE laboratory staff, serving the GAIN mission to develop a private-public partnership framework that will enable accelerated commercialization of innovative concepts. For the inaugural voucher program, DOE-NE made a total of $2M available. In total, twenty-nine proposals were received and eight (Table 1) were chosen for award based on several criteria, including technical quality, level of innovation, commercialization potential, and relevance to the DOE-NE mission. After the review process, cooperative agreements were finalized, and work on all eight vouchers started in September 2016 and all but one were completed by the end of September, 2017. The single exception was completed in December, 2017.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

NCSP Training and Education Program [Slides]

The mission of the Nuclear Criticality Safety Program is to provide sustainable expert leadership, direction and the technical infrastructure necessary to develop, maintain, and disseminate the essential technical tools, training, and data required to support safe, efficient fissionable material operations within DOE; the vision of the program is a Continually improving, adaptable, and transparent program that communicates and collaborates globally to incorporate technology, practices, and programs to be responsive to the essential technical needs of those responsible for developing, implementing, and maintaining nuclear criticality safety. Training and education topics for the program include a 1-week Manager/Criticality Safety Officer Course and a 2-week NCS Engineer Hands-on Training Course.

42 ENGINEERING↗
DOE OSTI2023

ES4SE Technical Assistance Program Evaluation

Technical assistance (TA) programs can provide organizations and communities with the information, tools, and resources needed to support their development and resilience goals. The Energy Storage for Social Equity (ES4SE) TA program sought to empower undeserved communities through co-development of energy storage pathways and solutions to address community-defined challenges and needs. Evaluating the design, implementation, and outcomes of TA programs like ES4SE is critical to understanding whether program and participant goals were accomplished and how to adjust the TA approach to better meet participant needs. This evaluation explores the experiences and perceptions of community participants in the ES4SE TA program.

25 ENERGY STORAGE↗
DOE OSTI2026

Classical-Quantum Algorithm for Solving Stochastic Programs

Stochastic programming provides a rigorous mathematical framework for making decisions under uncertainty in a risk-aware manner. Two-stage stochastic programming is, perhaps, the simplest form of this framework. Here the first-stage variables represent decisions that must be made "here and now" in the face of uncertainty, while the second-stage variables are decisions made after uncertain events. However, the broad adoption of stochastic programming has been hindered by computational challenges caused by the two-stage stochastic programming formulation which requires solving an ensemble of optimization problems. Using quantum amplitude estimation (QAE), quantum computers have shown the theoretic ability to compute expectations with Monte-Carlo methods with quadratically fewer samples than classical methods. In this work, we present a quantum algorithm for computing the expectation term using QAE for given first-stage decisions. Further, we detail methods of computing gradient information from the quantum calculation enabling the application of classical gradient-based optimization techniques. The result is a classical-quantum hybrid method of solving two-stage stochastic programs. These techniques are demonstrated with computational experiments based an engineering optimization problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Developing extensible lattice-Boltzmann simulationsfor general-purpose graphics-programming units

Lattice-Boltzmann methods are versatile numerical modeling techniques capable of reproducing a wide variety of fluid-mechanical behavior. These methods are well suited to parallel implementation, particularly on the single-instruction multiple data (SIMD) parallel processing environments found in computer graphics processing units (GPUs). Although more recent programming tools dramatically improve the ease with which GPU programs can be written, the programming environment still lacks the flexibility available to more traditional CPU programs. In particular, it may be difficult to develop modular and extensible programs that require variable on-device functionality with current GPU architectures. This paper describes a process of automatic code generation that overcomes these difficulties for lattice-Boltzmann simulations. It details the development of GPU-based modules for an extensible lattice-Boltzmann simulation package - LBHydra. The performance of the automatically generated code is compared to equivalent purpose written codes for both single-phase, multiple-phase, and multiple-component flows. The flexibility of the new method is demonstrated by simulating a rising, dissolving droplet in a porous medium with user generated lattice-Boltzmann models and subroutines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Exploiting first-class arrays in Fortran for accelerator programming

Emerging architectures for high performance computing often are well suited to a data parallel programming model. This paper presents a simple programming methodology based on existing languages and compiler tools that allows programmers to take advantage of these systems. We will work with the array features of Fortran 90 to show how this infrequently exploited, standardized language feature is easily transformed to lower level accelerator code. Our transformations are based on a mapping from Fortran 90 to C++ code with OpenCL extensions. The sheer complexity of programming for clusters of many or multi-core processors with tens of millions threads of execution make the simplicity of the data parallel model attractive. Furthermore, the increasing complexity of todays applications (especially when convolved with the increasing complexity of the hardware) and the need for portability across hardware architectures make a higher-level and simpler programming model like data parallel attractive. The goal of this work has been to exploit source-to-source transformations that allow programmers to develop and maintain programs at a high-level of abstraction, without coding to a specific hardware architecture. Furthermore these transformations allow multiple hardware architectures to be targeted without changing the high-level source. It also removes the necessity for application programmers to understand details of the accelerator architecture or to know OpenCL.

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

Experiences with High-Level Programming Directives for Porting Applications to GPUs

HPC systems now exploit GPUs within their compute nodes to accelerate program performance. As a result, high-end application development has become extremely complex at the node level. In addition to restructuring the node code to exploit the cores and specialized devices, the programmer may need to choose a programming model such as OpenMP or CPU threads in conjunction with an accelerator programming model to share and manage the difference node resources. This comes at a time when programmer productivity and the ability to produce portable code has been recognized as a major concern. In order to offset the high development cost of creating CUDA or OpenCL kernels, directives have been proposed for programming accelerator devices, but their implications are not well known. In this paper, we evaluate the state of the art accelerator directives to program several applications kernels, explore transformations to achieve good performance, and examine the expressiveness and performance penalty of using high-level directives versus CUDA. We also compare our results to OpenMP implementations to understand the benefits of running the kernels in the accelerator versus CPU cores.

43 PARTICLE ACCELERATORS↗
DOE OSTI2011

Global Arrays Parallel Programming Toolkit

The two predominant classes of programming models for parallel computing are distributed memory and shared memory. Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in modern computers this characteristic can have a negative impact on performance and scalability. Careful code restructuring to increase data reuse and replacing fine grain load/stores with block access to shared data can address the problem and yield performance for shared memory that is competitive with message-passing. However, this performance comes at the cost of compromising the ease of use that the shared memory model advertises. Distributed memory models, such as message-passing or one-sided communication, offer performance and scalability but they are difficult to program. The Global Arrays toolkit attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed by the programmer. This management is achieved by calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be specified by the programmer and hence managed. GA is related to the global address space languages such as UPC, Titanium, and, to a lesser extent, Co-Array Fortran. In addition, by providing a set of data-parallel operations, GA is also related to data-parallel languages such as HPF, ZPL, and Data Parallel C. However, the Global Array programming model is implemented as a library that works with most languages used for technical computing and does not rely on compiler technology for achieving parallel efficiency. It also supports a combination of task- and data-parallelism and is available as an extension of the message passing (MPI) model. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. Virtually all the scalable architectures possess non-uniform memory access characteristics that reflect their multi-level memory hierarchies. These hierarchies typically comprise processor registers, multiple levels of cache, local memory, and remote memory. Over time, both the number of levels and the cost (in processor cycles) of accessing deeper levels has been increasing. It is important for any scalable programming model to address memory hierarchy since it is critical to the efficient execution of scalable applications.

ARMCI↗
DOE OSTI2014

The Role of Awards Programs in Stimulating Energy Efficient Behavior: A Study of Award Winners

The value of formal awards programs may be principally in gaining wider recognition for achievements in energy efficiency. But how do these programs contribute to the goal that is presumably behind this value, i.e., stimulating further energy efficient behavior, beyond publicizing the awards ceremonies and describing the projects via websites, posters, and the like? Interviews with 22 individuals and teams of award winners under the Department of Energy Federal Energy Management Program (DOE FEMP) yield insights on the roles that awards programs can play in stimulating energy efficient behavior, especially with regard to institutional dimensions of such behavior. Award winners identified institutional facilitators and barriers in their projects and programs as well as factors in their implementation processes, thus providing information that can guide other efforts. Although only one of the interviewees affirmed that winning an award was a motivating factor, awards do validate often-hard-won achievements through recognition and, in some cases, additional resources, thus stimulating both the winners themselves and those who see the achievements to further energy-saving activities. Finally, award winners’ responses demonstrated the importance of behavioral and institutional change in energy efficiency.

awards programs↗
DOE OSTI2017

Consolidated Nuclear Security, LLC, Excess Facility Disposition Program - 17289

Consolidated Nuclear Security, LLC (CNS), the management and operating contractor for the Y-12 National Security Complex (Y-12) in Oak Ridge, Tennessee, and the Pantex Plant (Pantex) in Amarillo, Texas, has developed an integrated strategy to address badly deteriorating excess facilities presenting risks to people, the environment, and the National Nuclear Security Administration (NNSA) mission. The comprehensive, integrated Excess Facilities Disposition Program (EFDP) incorporates NNSA scope for excess facility risk reduction, preparation of facilities to be transferred to the U.S. Department of Energy (DOE) Office of Environmental Management (EM) for demolition, and demolition of non-process contaminated facilities. The Program has been developed using the NNSA Office of Safety, Infrastructure, and Operations (NA-50) Program Management Plan as a guide. The Program has undertaken actions to address the most immediate risks associated with CNS excess facilities. At Y-12, new foam roofs have been installed on Buildings 9201-5 (Alpha 5), 9204-4 (Beta 4), and 9206 to minimize further facility degradation. Tanks and dikes outside of Alpha 5 and Beta 4 are also being disconnected, drained, and filled with concrete. In addition, Beta 4 will be getting a new electrical system as its Manhattan Project-era system will be replaced by a temporary 'construction power' setup that will provide as-needed electricity to the building that is safer, more reliable, and will ease demolition activities in the future. The EFDP is also focusing on the basement of Alpha 5 and is planning to remove the water from the aging facility's flooded basement, which in some areas contains up to 54 inches of water. The EFDP is also planning several efforts to remove excess materials from Alpha 5 and Beta 4, de-inventory the Alpha 5 Mercury House System and numerous transformers, and de-inventory Beta 4 hydraulic pumps and systems. Efforts are also underway to deactivate and decommission non-process-contaminated facilities at Y-12 and at Pantex. The EFDP has prioritized the performance of work to reduce risk while at the same time supporting the preparation of process-contaminated Y-12 facilities for transfer to EM. The Program aligns with the EM goal to have the NNSA scope completed in Alpha 5 and Beta 4 by the end of FY 2020, and Building 9206 completed by the end of FY 2024. These dates and project sequencing will support the Y-12-related DOE EM cleanup initiatives. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

DOE nuclear safety research and development program - 15413

A corporate Nuclear Safety Research and Development (NS R and D) Program has been established by the U.S. Department of Energy (DOE), managed by the Office of Nuclear Safety in DOE's Office of Environment, Health, Safety and Security (EHSS). Among the objectives of the program are the identification, support, and dissemination of the results of R and D to address cross-cutting nuclear safety issues relevant to the design, construction, and operation of DOE civilian and defense nuclear facilities. Most of the projects supported by the NSR and D Program are selected from responses to an annual Call for Proposals, which is distributed to the National Nuclear Security Administration (NNSA) and DOE Program Offices, and to the contractors operating DOE and NNSA nuclear facilities. Additional NSR and D projects have been initiated by the Office of Nuclear Safety to support the Office's mission of developing DOE nuclear safety policy. The Office of Nuclear Safety continues to work closely with NNSA and DOE program offices to expand the number and scope of NSR and D projects, and to look for opportunities to collaborate with other organizations to identify and study nuclear safety issues relevant to DOE's nuclear facilities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Managing Hanford's Direct Feed Low Activity Waste Program - 20002

The Office of River Protection (ORP) is responsible for the management and completion of the River Protection Project (RPP) mission, which comprises both the Hanford Site tank farms operations and the completion and operation of the Waste Treatment and Immobilization Plant Project. The RPP mission is to safely retrieve, treat, and immobilize Hanford's high-level and low-activity tank waste and close the tank farms to protect the Columbia River. The Direct-Feed Low-Activity Waste (DFLAW) Program is a major subset of the overall RPP mission, providing disposition of low-activity waste. The scope is to retrieve, treat, and immobilize the low-activity waste at the Low-Activity Waste Facility. DFLAW will begin operations no later than December 2023. The DFLAW Program overarches a suite of individual projects, activities, and infrastructure upgrades. The major projects and activities include multiple contractors under both ORP and the Richland Operations Office, underscoring the need for effective integration, coordination, and collaboration. The objectives of the DFLAW Program leadership team are to: - Effectively coordinate and integrate the projects that comprise the DFLAW Program - Manage the interfaces between the projects so that the integrated DFLAW Program is completed successfully - Ensure the DFLAW portfolio of projects operate as required without gaps or conflicts at the interfaces. DOE is accomplishing these objectives through a newly established leadership model that integrates the DOE and contractor work streams and promotes a teamwork model to enable collaborative success. Long considered one of the most formidable cleanup challenges at Hanford, the Department of Energy and its contractors are on the verge of achieving a cleanup commitment that has been decades in the making. DOE is preparing to vitrify (turn to glass) Hanford's chemical and radioactive tank waste using the DFLAW process. The Modified Consent Decree milestone for completing hot commissioning of the Hanford Site's Low- Activity Waste Facility is Dec. 31, 2023. While this milestone may seem distant under normal project management circumstances, it is a relatively short period of time for the operational and cultural transformation necessary to successfully begin treating tank waste at Hanford. Direct feed means separating the waste at a tank farm to remove the more radioactive portion (i.e., solids and cesium) so that the resulting low-activity (less radioactive) waste can be fed directly to the Waste Treatment and Immobilization Plant's Low-Activity Waste Facility. Starting DFLAW will require a singular, intensive leadership focus, along with a sustained, collective commitment to excellence and teamwork by the Department and its contractors. Major upgrades to Hanford's infrastructure will occur prior to startup. Supporting DFLAW operations requires significant integration between the DFLAW facilities - the Waste Treatment Plant, Hanford's tank farms, effluent treatment facilities, disposal facilities - and between all of the site contractors to achieve success. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Department of Energy Hydrogen Program Plan

The DOE Hydrogen Program Plan provides a strategic view of how the Department conducts and coordinates hydrogen research, development, and demonstration (RD&D) activities under the DOE Hydrogen Program. With participation from the Offices of Energy Efficiency and Renewable Energy, Fossil Energy, Nuclear Energy, Electricity, Science, and ARPA-E, the DOE Hydrogen Program is a coordinated Departmental effort to advance the affordable production, transport, storage, and use of carbon-neutral hydrogen across different sectors of the economy. This version of the Plan updates and expands upon previous versions, including the Hydrogen Posture Plan and the DOE Hydrogen and Fuel Cells Program Plan, and provides a coordinated high-level summary of hydrogen-related activities across DOE.

08 HYDROGEN↗
DOE OSTI2021

Capturing the legacy of the U.S.-China EcoPartnerships program

Under the Ten Year Framework for Cooperation on Energy and Environment between the Governments of the United States and China, the two countries implemented a highly successful U.S.-China EcoPartnerships program . The program helped to grow 45 U.S.-China subnational partnerships and accelerate breakthroughs in technology and policy to achieve shared goals in clean air, clean water, and waste reduction. Following the culmination of the U.S.-China EcoPartnerships program in January 2021, this article captures the legacy of this impressive program by providing insights into its unique structure; the diverse set of projects that comprised U.S.-China EcoPartnerships; its commercial and environmental impacts; and the lessons that can be applied to future bilateral and multilateral subnational environmental programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗