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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 793 records · Page 44

Nb 3 Sn Superconducting RF Cavities: R&D Progress at Fermilab and Opportunities

Nb 3 Sn becomes superconducting at twice as high temperature as our standard SRF material niobium. This allows us to efficiently operate Nb 3 Sn cavities at 4.4 K instead of the usual 2 K. This reduces cryogenic costs and even makes it possible to use a cryocooler instead of a large, complex cryogenic plant. The superheating field H sh of Nb 3 Sn is twice that of niobium. H sh is thought to be the ultimate limit for a defect-free superconductor. Nb 3 Sn cavities being made today are still about a factor of 4 away from this ultimate limit, but R&D has been leading to substantial progress towards this goal.

43 PARTICLE ACCELERATORS↗

Nb 3 Sn Superconducting RF Cavities: R&D Progress at Fermilab and Opportunities [Poster]

Nb 3 Sn becomes superconducting at twice as high temperature as our standard SRF material niobium. This allows us to efficiently operate Nb 3 Sn cavities at 4.4 K instead of the usual 2 K. This reduces cryogenic costs and even makes it possible to use a cryocooler instead of a large, complex cryogenic plant. The superheating field Hsh of Nb 3 Sn is twice that of niobium. Hsh is thought to be the ultimate limit for a defect-free superconductor. Nb 3 Sn cavities being made today are still about a factor of 4 away from this ultimate limit, but R&D has been leading to substantial progress towards this goal

43 PARTICLE ACCELERATORS↗

Crystalline Disposal R&D at LBNL: FY20 Progress Report

Within the Spent Fuel & Waste Science and Technology (SFWST) Program, research work continues further with the goal to better understand long-term performance of disposal systems in three main geologic rock types: clay/shale, salt, and crystalline rock. This report documents LBNL’s research activities related to investigations of crystalline host rock according to the scope of two work packages: SF-20LB01030207 “Crystalline International Collaborations – LBNL,” and SF-20LB01030203 “Crystalline Disposal R&D – LBNL.” These research activities correspond are related to key Features, Events, and Processes (FEPs), ranked in importance from medium to high, as listed in Table 7 of the Used Fuel Disposition Campaign Disposal Research and Development Roadmap (FCR&D-USED-2011-000065 REV0) (Nutt, 2011). Specifically, these research activities address FEP 2.2.01, Excavation Disturbed Zone (EZD). The results of these research activities provide important insights into understanding and predicting flow and transport processes that could occur in low-permeability crystalline rocks, in which fractures might serve as main conduits for fluid flow and radionuclide transport. The evolution of the EDZ during the excavation of the tunnel as well as the evolution of microcrack growth within the EDZ after the emplacement of backfill are critical for predicting the long- term behavior of the EDZ. A number of factors including stress, temperature, water activity, capillary pressure, chemistry, and mineralogy can affect the rock evolution, which require advanced experimental tools to study it.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

International Collaborations Activities on Disposal in Argillite R&D: Bentonite Barrier Characterization Studies and Modeling Investigations

This interim report is an update of the report Jove Colon et al. (2019; M4SF-19SN010301091) describing international collaboration activities pertaining to FEBEX-DP and DECOVALEX19 Task C projects. Although work on these two international repository science activities is no longer continuing by the international partners, investigations on the collected data and samples is still ongoing. Descriptions of these underground research laboratory (URL) R&D activities are given in Jové Colón et al. (2018; 2019) but will repeated here for completeness. The 2019 status of work conducted at Sandia National Laboratories (SNL) on these two activities is summarized along with other international collaboration activities in Birkholzer et al. (2019).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrating Applied Energy and BER Smart Data Capabilities to Develop a DOE Data Fabric for Energy-Water R&D

Focal Area(s): 1) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization, unsupervised learning (including deep learning), and hardware-related efforts involving AI (e.g., edge computing). Science Challenge: DOE R&D, including DOE’s Basic Energy Research (BER)’s Environmental Systems Science Division (EESSD) program and DOE’s applied energy research (AER) programs (EERE, FE, and NE) are producers and consumers of Earth systems datasets. This white paper focuses on the first topic area from the call in relation to how crosscutting resources and innovations from DOE’s EESSD and AER can be brought to bear to mutual benefit and more efficient energy-water, Earth system data resources through improved. The overarching challenge posed by this call focuses on how DOE can directly leverage artificial intelligence (AI) to engineer a substantial (paradigm-changing) improvement in Earth System Predictability? While stemming from DOE BER’s EESSD program, this is a challenge that is faced and also being addressed by DOE’s AER programs. Over the past decade plus, FE, EERE, and NE programs have made important strides towards addressing this need. These strides are in many ways highly complementary to EESSD’s MODEX efforts. Energy water systems spanning metocean to groundwater to surface water systems all are data driven whether for basic energy or applied energy. These are remote, multi-variate, complex natural, and in many cases engineered, systems. Key needs and challenges of both EESSD and AER include developing data-focused tools to enhance data search and discovery to fill in knowledge gaps (address sparse data challenge), and rapidly transform datasets, including disparate and multi-source data. Leveraging DOE on-premise computing (HPC, exascale) infrastructure supports the computing-intensive algorithms required to execute these data acquisition and transformation processes to derive enriched knowledge and data, driving AI/ML and big data analytics for these systems. The opportunity lies in combining BER and AER efforts to provide a more robust, advanced, efficient and complete computing data fabric to address energy-water data acquisition and assimilation needs which currently pose significant impediments to AI/ML predictions and research.

54 ENVIRONMENTAL SCIENCES↗

International Collaborations Activities on Disposal in Argillite R&D: Characterization Studies and Modeling Investigations

This interim report is an update of ongoing experimental and modeling work on bentonite material described in Jové Colón et al. (2019, 2020) from past international collaboration activities. As noted in Jové Colón et al. (2020), work on international repository science activities such as FEBEX-DP and DECOVALEX19 is either no longer continuing by the international partners. Nevertheless, research activities on the collected sample materials and field data are still ongoing. Descriptions of these underground research laboratory (URL) R&D activities are described elsewhere (Birkholzer et al. 2019; Jové Colón et al. 2020) but will be explained here when needed. The current reports recent reactive-transport modeling on the leaching of sedimentary rock.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

R-CERT Project Analysis Report

The R-CERT project aims to determine if PBX 9501 will experience a deflagration to detonation transition (DDT) while in a high pressure environment. Combined efforts in design and analysis between multiple groups at Los Alamos National Laboratory (LANL) were required to finalize the test design. The proposed design of the case assembly (i.e. the pressure vessel that would contain the high explosive) was analyzed and iteratively modified until modeling efforts predicted the case would maintain pressure up to 5000 psi under quasi-static conditions. To prevent the case from being excessively robust beyond its design requirement, grooves were added to the case geometry with depths and radii of 4 mm, thus weakening the case while maintaining much of the mass of the proposed design.

42 ENGINEERING↗

Nonproliferation and Arms Control Research and Development (NPAC R&D) [Slides]

NPAC R&D focus areas include: Advancing U.S. capabilities to detect and characterize nuclear weapon development activities globally, including material production, the movement of special nuclear materials and nuclear weapons, and the testing or use of nuclear weapons, Supporting the development and testing of policy options and technical capabilities for international nuclear safeguards, arms control / treaty verification, nuclear export controls, and nonproliferation initiatives consistent with U.S. Government goals and objectives to enable monitoring and verification, Utilizing uranium, lithium, and high explosives (HE) materials expertise to support national-level activities in nuclear forensics and nuclear detection technology testing and evaluation, Providing unique training and capacity-building programs, particularly with the Nuclear Detection and Sensor Testing Center (NDSTC), and Engaging internationally to promote nonproliferation and arms control norms and best practices through bilateral and multilateral work.

36 MATERIALS SCIENCE↗

Key Pandemic Response R&D Contributions by Los Alamos National Laboratory

New research goals, mitigation successes, and beneficial collaborations burgeoned from the early critical days of 2020 when LANL (Los Alamos National Laboratory) pivoted to help respond to the pandemic. By applying its considerable capabilities in the fields of science, technology, and engineering (STE), LANL responded to the coronavirus infectious disease (COVID-19) pandemic. This report documents representative examples of that response. Through significant investments in COVID-19 mitigations and ongoing research and development (R&D), important advancements were made to address the pandemic that not only benefited the global population affected by the pandemic, but also protected our staff and collaborators as we executed our Lab’s mission.

59 BASIC BIOLOGICAL SCIENCES↗

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report: FY19-FY22)

This is the final technical report for the FY19-FY21 research program "R&D to Ensure a Scientific Basis for Qualification Tests and Standards." This research was performed because project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. This program advances PV module reliability of commercial products through identification of reliability needs, characterization that provides scientific understanding of targeted degradation mechanisms, and translation of those data into practical and predictive test protocols and standards. This report describes program scope, results, milestones, and accomplishments over the three-year period of performance.

14 SOLAR ENERGY↗

Preliminary Implementation of Two-Dimensional Cartesian Solver in CTF-R

Sub-channel codes are one of the the modeling and simulation tools used for thermal-hydraulic analysis of nuclear reactors. A few examples of such sub-channel codes are the COolant Boiling in Rod Arrays (COBRA) family of codes. The approximations that are used to simplify the fluid conservation equations into sub-channel form, mainly that of axially-dominated flow, lead to noticeable limitations on sub-channels solvers for problems with significant flow in lateral directions. In this report, a two-dimensional Cartesian solver is developed and implemented within CTF-R, which is the residual solver in the North Carolina State University version of COBRA-TF (CTF). The new solver will enable CTF to simulate flow that is not axially-dominated. The appropriate Cartesian forms of the conservation equations are derived and implemented in the solver. Once the conservation equations are established, the process of constructing the matrix system was altered to solve a two-dimensional staggered grid system. A simple case was used to test that the two-dimensional Cartesian solver is accurate. The test problem does not include any source terms or flow in the lateral direction. The results show that the solver was able to run the simple case and converge to a steady-state solution. Future work will focus on testing existing capabilities by using test cases that include transients and equation cross-terms. Future work will also include adding additional capabilities such as enabling the solver to include cases with source terms and three dimensional cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Computational Modeling and Simulation for Nonproliferation: The History (and Present) of Monte Carlo and the MCNP(R) Code at Los Alamos [Slides]

The emergence of the Monte Carlo method as a research tool springs from work done at Los Alamos in the 1940s.Monte Carlo and the MCNP Code have been and continue to be developed at Los Alamos for many decades. From basic science in support of understanding nuclear interaction physics to global security applications, application uses of the code are extensive. Recent R&D projects and code modernization efforts make the MCNP code a great tool for nuclear nonproliferation applications. In collaboration with nuclear safeguards experts, new training has just recently been developed to help new practitioners learn how to use the code for nuclear safeguards applications.

97 MATHEMATICS AND COMPUTING↗

Advanced Serpentine Heat Exchangers to Minimize Number of Joints and Leakage in HVAC&R Systems

Refrigerant leakage has a significant impact on heating, ventilation, air conditioning and refrigeration (HVAC&R) industries in terms of both greenhouse gas (GHG) emissions and lost efficiency of the systems themselves. One of the major causes of refrigerant leakage is braze joints within a vapor compression system. The brazing process is often inconsistent and almost always imperfect. As a result, braze joints are left vulnerable to leaks and can be weaker than non-brazed tubing. Conventional tube-fin heat exchangers are manufactured using one brazed joint per tube. An alternative to the conventional approach is the use of a single continuous serpentine tube. An Advanced Serpentine Heat Exchanger was developed to provide a heat transfer solution that meets or exceeds performance while also significantly reducing the number of joints and, consequently, the potential for refrigerant leakage. The developed serpentine heat exchanger not only delivers on performance, but is also cost competitive with conventional heat exchangers on the market.

30 DIRECT ENERGY CONVERSION↗

Modernization efforts for the R-Matrix code SAMMY [Slides]

This presentation details modernization efforts for the R-Matrix code SAMMY. It provides an overview of SAMMY, modernization and maintenance goals, modernization accomplishments, covariance data, SAMMY API development, as well as future plans.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Nuclear Safety and Regulatory Research R&D [Slides]

Included are slides for a MIT nuclear engineering department invited seminar. The talking points are: (1) Current R&D at INL in safety, risk, and reliability; (2) Technical focus; and (3) Future directions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗