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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Grand-scale Atmospheric Imaging Apparatus (GAIA) and Wind LiDAR Multi-scale Measurements in the Atmospheric Surface Layer

Understanding the organization and dynamics of turbulence structures in the atmospheric surface layer (ASL) is important for fundamental and applied research in different fields, including weather prediction, snow settling, particle and pollutant transport, and wind energy. The main challenges associated with probing and modeling turbulence in the ASL are: i) the broad range of turbulent scales associated with the different eddies present in high Reynolds-number boundary layers ranging from the viscous scale ($\mathcal{O}$(mm)) up to large energy-containing structures ($\mathcal{O}$(km)); ii) the non-stationarity of the wind conditions and the variability associated with the daily cycle of the atmospheric stability; iii) the interactions among eddies of different sizes populating different layers of the ASL, which contribute to momentum, energy, and scalar turbulent fluxes. Creative and innovative measurement techniques are required to probe near-surface turbulence by generating spatio-temporally-resolved data in the proximity of the ground and, at the same time, covering the entire ASL height with large enough streamwise extent to characterize the dynamics of larger eddies evolving aloft. To this aim, the U.S. National Science Foundation sponsored the development of the Grand-scale Atmospheric Imaging Apparatus (GAIA) enabling super-large snow particle image velocimetry (SLPIV) in the near-surface region of the ASL. This inaugural version of GAIA provides a comprehensive measuring system by coupling SLPIV and two scanning Doppler LiDARs to probe the ASL at an unprecedented resolution. A field campaign performed in 2021–2022 and its preliminary results are presented herein elucidating new research opportunities enabled by the GAIA measuring system.

17 WIND ENERGY↗
DOE OSTI2024

Employing artificial intelligence to steer exascale workflows with colmena

Computational workflows are a common class of application on supercomputers, yet the loosely coupled and heterogeneous nature of workflows often fails to take full advantage of their capabilities. We created Colmena to leverage the massive parallelism of a supercomputer by using Artificial Intelligence (AI) to learn from and adapt a workflow as it executes. Colmena allows scientists to define how their application should respond to events (e.g., task completion) as a series of cooperative agents. In this paper, we describe the design of Colmena, the challenges we overcame while deploying applications on exascale systems, and the science workflows we have enhanced through interweaving AI. The scaling challenges we discuss include developing steering strategies that maximize node utilization, introducing data fabrics that reduce communication overhead of data-intensive tasks, and implementing workflow tasks that cache costly operations between invocations. These innovations coupled with a variety of application patterns accessible through our agent-based steering model have enabled science advances in chemistry, biophysics, and materials science using different types of AI. In conclusion, our vision is that Colmena will spur creative solutions that harness AI across many domains of scientific computing.

Workflows↗
DOE OSTI2020

Opinion: Lighting Research During and After the Pandemic

For many lighting researchers, the recent restrictions related to COVID-19 have paused most in-person laboratory or field experiments. In certain countries, regulatory institutions have allowed such experiments to resume but issued safety recommendations like pre-checking participants for disease symptoms and excluding those that are especially vulnerable. To avoid potential complications and delays, researchers are likely to resort to other research designs that enable remote research — eliminating the need for the experimenter and subjects to be in the same room. While unanticipated, this shift to remote research methods is an opportunity to revisit and further develop remote experimental techniques, which can have beneficial long-lasting implications on lighting research during and after the pandemic. Perhaps the most common type of remote research is online experiments; which can greatly benefit from improved techniques to allow for greater control or characterization of experimental conditions, like those proposed by Villa and Labayrade . These techniques require validation specific to the type of response collected and context, e.g. space type and attributes. New research techniques continue to emerge and will enable remote collection of objective measures such as gaze direction and high dynamic range images (HDRIs) without specialized equipment. In fact, many of these methods and techniques are commonly used in other disciplines, like vision science and psychology, and can be adapted for lighting research. Not all lighting studies can be conducted online, but in the age of ubiquitous and connected technologies, there is a largely missed opportunity to utilize crowdsourced responses to lighting conditions in real environments where people live and go about their daily lives without the research being limited to a certain time and laboratory locations. For instance, outdoor street luminaires can be rated by passersby using ecological momentary assessments on mobile phones. While this approach does not provide laboratory-level control over experimental conditions, it can provide more contextual responses resulting from ‘normal’ dynamic gaze, behavior, and interactions. Further, it can also reduce bias related to the experimental setting. Further development of remote research methods and their use in lighting research can improve the quality of lighting research. Given that sample sizes in most lighting research are relatively small, remote research can substantially increase sample sizes, reduce research costs, and shorten study duration, all while reducing interaction between experimenter and subjects. Another benefit is reaching a wider audience and including under-represented individuals who typically are not reachable using common recruitment methods. The pandemic has set back our plans for in-lab experiments, but can it inspire us to think of new and creative ways to expand lighting research?

Abboushi, Belal K.↗
DOE OSTI2020

Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS

The continental flood inundation mapping (CFIM) framework is a high-performance computing (HPC)-based computational framework for the Height Above Nearest Drainage (HAND)-based inundation mapping methodology. Using the 10m Digital Elevation Model (DEM) data produced by U.S. Geological Survey (USGS) 3DEP (the 3-D Elevation Program) and the NHDPlus hydrography dataset produced by USGS and the U.S. Environmental Protection Agency (EPA), a hydrological terrain raster called HAND is computed for HUC6 units in the conterminous U.S. (CONUS). The value of each raster cell in HAND is an approximation of the relative elevation between the cell and its nearest water stream. Derived from HAND, a hydraulic property table is established to calculate river geometry properties for each of the 2.7 million river reaches covered by NHDPlus (5.5 million kilometers in total length). This table is a lookup table for water depth given an input stream flow value. Such lookup is available between water depth 0m and 25m at 1-foot interval. The flood inundation map is then computed by using HAND and this lookup table based on the near real-time water forecast from the National Water Model (NWM) at the National Oceanic and Atmospheric Administration (NOAA). HAND and the Hydraulic Property Table version 0.2. is created to correspond to data updates in the USGS 1/3 arcsec DEM, the USGS National Hydrography Dataset, including its Water Boundary Dataset, and the NHDPlus medium resolution dataset. This dataset comprises 331 HUC6 units for CONUS (excluding the five great lakes units), each is a downloadable zip file. Version 0.1 was computed at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urban-Champaign in 2016 and is currently hosted at the Texas Advanced Computing Center (TACC). Please cite this data DOI and the following publications and data DOIs when you use HAND and the hydraulic property table: Liu, Yan Y., David R. Maidment, David G. Tarboton, Xing Zheng, and Shaowen Wang. 'A CyberGIS integration and computation framework for high-resolution continental-scale flood inundation mapping.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 770-784. DOI: 10.1111/1752-1688.12660 Zheng, Xing, David G. Tarboton, David R. Maidment, Yan Y. Liu, and Paola Passalacqua. 'River channel geometry and rating curve estimation using height above the nearest drainage.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 785-806. DOI: 10.1111/1752-1688.12661 Liu, Y. (2018). Height Above Nearest Drainage (HAND) for CONUS - v0.1, HydroShare, https://doi.org/10.4211/hs.69f7d237675c4c73938481904358c789 LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS - Version 0.21 (20200601)

The continental flood inundation mapping (CFIM) framework is a high-performance computing (HPC)-based computational framework for the Height Above Nearest Drainage (HAND)-based inundation mapping methodology. Using the 10m Digital Elevation Model (DEM) data produced by U.S. Geological Survey (USGS) 3DEP (the 3-D Elevation Program) and the NHDPlus hydrography dataset produced by USGS and the U.S. Environmental Protection Agency (EPA), a hydrological terrain raster called HAND is computed for HUC6 units in the conterminous U.S. (CONUS). The value of each raster cell in HAND is an approximation of the relative elevation between the cell and its nearest water stream. Derived from HAND, a hydraulic property table is established to calculate river geometry properties for each of the 2.7 million river reaches covered by NHDPlus (5.5 million kilometers in total length). This table is a lookup table for water depth given an input stream flow value. Such lookup is available between water depth 0m and 25m at 1-foot interval. The flood inundation map is then computed by using HAND and this lookup table based on the near real-time water forecast from the National Water Model (NWM) at the National Oceanic and Atmospheric Administration (NOAA). HAND and the Hydraulic Property Table version v0.21 is an upgrade to v0.2. Version 0.21 applies NHD HR etching to DEMs for all HUC6 units before running the HAND workflow. This new version also fixed the issue of void areas along HUC boundary. This dataset comprises 331 HUC6 units for CONUS (excluding the five great lakes units), each is a downloadable zip file. Version 0.1 was computed at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urban-Champaign in 2016 and is currently hosted at the Texas Advanced Computing Center (TACC). Please cite this data DOI and the following publications and data DOIs when you use HAND and the hydraulic property table: Liu, Yan Y. Height Above Nearest Drainage (HAND) and Hydraulic Property Table for CONUS - Version 0.2. (20200301). Oak Ridge Leadership Computing Facility. (2020). DOI: 10.13139/ORNLNCCS/1608331 Liu, Yan Y., David R. Maidment, David G. Tarboton, Xing Zheng, and Shaowen Wang. 'A CyberGIS integration and computation framework for high-resolution continental-scale flood inundation mapping.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 770-784. DOI: 10.1111/1752-1688.12660 Zheng, Xing, David G. Tarboton, David R. Maidment, Yan Y. Liu, and Paola Passalacqua. 'River channel geometry and rating curve estimation using height above the nearest drainage.' JAWRA Journal of the American Water Resources Association 54, no. 4 (2018): 785-806. DOI: 10.1111/1752-1688.12661 Liu, Y. (2018). Height Above Nearest Drainage (HAND) for CONUS, HydroShare, https://doi.org/10.4211/hs.69f7d237675c4c73938481904358c789 LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Road Lidar Dataset for the TxDOT Austin District

This is a road lidar data collection for developing road elevation models and road inundation mapping methodologies, a joint work between ORNL and The University of Texas at Austin. This dataset is generated as part of the flood transportation infrastructure, partly funded by the NOAA CIROH project. ORNL is a project partner for high-performance computing-empowered flood inundation mapping methodology R&D. The dataset is computed using a GPU-accelerated lidar data processing workflow developed at ORNL. The lidar data source is from TxGIO, the state lidar data collection site. The output dataset is in two formats: laz and copc. It is organized by TxDOT's maintenance sections, covering the Austin District. Data size: 3.86 billion road lidar points, 1.67% of the entire lidar data input Projection: EPSG:32614 (WGS84/UTM zone 14N) Website: https://web.corral.tacc.utexas.edu/nfiedata/road3d/austin_district/AustinMaintenanceSections_H_epsg6343_V_epsg5703/ LICENSE FOR USE -- MAPS AND DATA DISCLAIMER This resource is shared under the Creative Commons Attribution CC BY, http://creativecommons.org/licenses/by/4.0/ MAPS AND DATA DISCLAIMER The Oak Ridge National Laboratory (ORNL) shall not be held liable for improper or incorrect use of the data described or information contained on this map or associated series of maps. The data and related map graphics are not legal, land survey or engineering documents and are not intended to be used as such. ORNL gives no warranty, express or implied, as to the accuracy, reliability, utility or completeness of this information. The user of these maps and data assumes all responsibility and risk for the use of the maps and data. ORNL disclaims all warranties, representations or endorsements either express or implied, with regard to the information contained in this map product, including, but not limited to, all implied warranties of merchantability, fitness for a particular purpose or non-infringement. This preliminary map product is for research and review purposes only. It is not intended to be used for emergency management operational or life safety decisions at the local or regional governmental level or by the general public. Users requiring information regarding hazardous conditions or meteorological conditions for specific geographic areas should consult directly with their city or county emergency management office.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Back to Basics: First Principles of HRA

Human Reliability Analysis (HRA) continues to suffer from a myriad of technical gaps in its foundations. Core issues have been widely discussed but remain largely unaddressed, although the path taken to this point was paved with good intentions. Now, while this characterization may seem dramatic it is not intended to throw doubt onto HRA as a discipline or to diminish the value it has on increasing safety and resilience in nuclear power. Rather, it is intended to communicate that HRA has some serious challenges and is desperately in need of a critical evaluation. To quote Dougherty [1], “the misrepresentations that will undoubtedly arise may serve to provoke the necessary creativity.” What bears noting is that in the last thirty years since Alan Swain declared that “no adequate HRA had ever been done,” there has been little effort to correct the issues he highlighted. Human factors practice is still poorly implemented, many complex systems are fundamentally incompatible with reliable human performance, and there remains poor foundational support for many of the assumptions within HRA. We propose three categories of issues in HRA, philosophical, theoretical, and empirical and potential solutions to these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Conserved HA-peptide NG34 formulated in pCMV-CTLA4-Ig reduces viral shedding in pigs after a heterosubtypic influenza virus SwH3N2 challenge

Swine influenza viruses (SIVs), the causal agents of swine influenza, are not only important to control due to the economic losses in the swine industry, but also can be pandemic pathogens. Vaccination is one of the most relevant strategies to control and prevent influenza infection. Current human vaccines against influenza induce strain-specific immunity and annual update is required due to the virus antigenic shift phenomena. Previously, our group has reported the use of conserved hemagglutinin peptides (HA-peptides) derived from H1-influenza virus as a potential multivalent vaccine candidate. Immunization of swine with these HA-peptides elicited antibodies that recognized and neutralized heterologous influenza viruses in vitro and demonstrated strong hemagglutination-inhibiting activity. In the present work, we cloned one HA-peptide (named NG34) into a plasmid fused with cytotoxic T lymphocyte-associated antigen (CTLA4) which is a molecule that modifies T cell activation and with an adjuvant activity interfering with the adaptive immune response. The resulting plasmid, named pCMV-CTLA4-Ig-NG34, was administered twice to animals employing a needle-free delivery approach. Two studies were carried out to test the efficacy of pCMV-CTLA4-Ig-NG34 as a potential swine influenza vaccine, one in seronegative and another in seropositive pigs against SIV. The second one was aimed to evaluate whether pCMV-CTLA4-Ig-NG34 vaccination would overcome maternally derived antibodies (MDA). After immunization, all animals were intranasally challenged with an H3N2 influenza strain. A complete elimination or significant reduction in the viral shedding was observed within the first week after the challenge in the vaccinated animals from both studies. In addition, no challenged heterologous virus load was detected in the airways of vaccinated pigs. Overall, it is suggested that the pCMV-CTLA4-Ig-NG34 vaccine formulation could potentially be used as a multivalent vaccine against influenza viruses. © 2019 Sisteré-Oró et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

An analysis and metric of reusable data licensing practices for biomedical resources

Data are the foundation of science, and there is an increasing focus on how data can be reused and enhanced to drive scientific discoveries. However, most seemingly “open data” do not provide legal permissions for reuse and redistribution. The inability to integrate and redistribute our collective data resources blocks innovation and stymies the creation of life-improving diagnostic and drug selection tools. To help the biomedical research and research support communities (e.g. libraries, funders, repositories, etc.) understand and navigate the data licensing landscape, the (Re)usable Data Project (RDP) assesses the licensing characteristics of data resources and how licensing behaviors impact reuse. We have created a ruleset to determine the reusability of data resources and have applied it to 56 scientific data resources (e.g. databases) to date. Here, the results show significant reuse and interoperability barriers. Inspired by game-changing projects like Creative Commons, the Wikipedia Foundation, and the Free Software movement, we hope to engage the scientific community in the discussion regarding the legal use and reuse of scientific data, including the balance of openness and how to create sustainable data resources in an increasingly competitive environment.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Evaluating and Explaining Natural Language Generation with GenX

Current methods for evaluation of natural language generation models focus on measuring text quality but fail to probe the model creativity, i.e., its ability to generate novel but coherent text sequences not seen in the training corpus. We present the GenX tool which is designed to enable interactive exploration and explanation of natural language generation outputs with a focus on the detection of memorization. We demonstrate the utility of the tool on two domain-conditioned generation use cases - phishing emails and ACL abstracts.

Duskin, Kayla R.↗
DOE OSTI2018

Implementation of ISO 50001 at Marine Corps Air Station Beaufort

The ISO 50001 implementation demonstration at U.S. Marine Corps Air Station (MCAS) Beaufort proved the feasibility of integrating an ISO 50001-conforming EnMS into existing command structures. The approach of leveraging external experts in gap analysis, EnMS training, and technical assistance were effective. In addition, strong leadership commitment and personnel resources were critical for success. Addressing typical personnel rotations by training newly rotated personnel and partnering key leadership positions in the EnMS structure with civilian counterparts can ensure program continuity. The project team brought forward many creative solutions that address the unique challenges for the Marine Corps and has paved the way for future Marine Corps EnMS implementations with example strategies and work products. Implementation of an ISO 50001 EnMS at additional Marine Corps facilities could provide for integration of base energy-related data systems and standardized energy reporting, using meaningful metrics for energy performance improvement. Beyond the energy performance improvement benefits of ISO 50001, widespread adoption of the standard at Marine Corps facilities would provide the communication and integration basis on which to reduce energy resiliency concern and could integrate energy service cyber security protections base wide. High levels of energy consumption, aggressive mandates from multiple sources, complex organizational structures, and constant personnel rotation make ISO 50001 a uniquely attractive proposition for the Marine Corps in support of the DoD’s overall energy strategy. The recently launched Energy Ethos and Unit Energy Manager (UEM) programs offer dynamic action-based programs over which ISO 50001 based business management can provide integrated governance of the Marine Corps installations’ energy programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

High Efficiency Cost Optimized - Spark Ignited Natural Gas Engines (HECO-SING) (Final Report)

The abundance of relatively low cost natural gas in the North American market, along with energy independence, makes natural gas attractive as an alternate fuel. Natural gas also has an advantage over diesel engines in low NOx emissions production. Natural gas does however have some technical challenges in its lower efficiency due to natural gas energy content in comparison to diesel or gasoline, which is also a partial factor in its vehicle storage capacity limitations and thus driving range. In order to address these challenges, the HECO-SING (High-Efficiency Cost-Optimized, Spark Ignited Natural Gas) project was undertaken. The goal was to increase engine efficiency (fuel economy), while still meeting future emissions, in a cost effective manner. In order to achieve these goals, high dilution combustion will be used with focus on advanced ignition systems, optimized aftertreatment selection, and creative engine controls are applied.

03 NATURAL GAS↗
DOE OSTI2019

2018 Annual Report Laboratory Directed Research and Development at Pacific Northwest National Laboratory

A national laboratory must establish and maintain an environment in which creativity and innovation are encouraged and supported in order to fulfill its missions and remain viable in the long term. As such, multiprogram laboratories are given discretion to allocate a percentage of their operating budgets to support research and development projects that align to PNNL’s and DOE’s missions and support the missions of other federal agencies, including DHS, DOD, and others. Individual project reports comprise the bulk of this LDRD report. The Laboratory focuses its LDRD research on scientific assets that often address more than one scientific discipline.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2019

Literature Review of Generalized Two-Dimensional Correlation Spectroscopy (2D-COS)

Generalized two-dimensional correlation spectroscopy (2D-COS) is a technique that has improved on traditional spectroscopic techniques by exposing samples to a variable amount of an external perturbation before they have been probed spectroscopically through IR, UV, Raman, etc. These perturbed signals are plotted over a second independent wavenumber axis and after mathematical manipulation, a dynamic spectrum is created that shows the synchronous and asynchronous spectra. The dynamic spectrum shows the way spectral changes in the material are correlated to each other, and a mechanism of material degradation can be proposed through a set of rules that Noda proposed. This technique is important to spectroscopic studies because of improved spectral resolution and the identification of complex or overlapping bands that cannot be distinguished in traditional analytical methods. This technique has been widely utilized since its inception, and has developed towards protein studies, as well as even wine chemistry, because of the advanced capabilities of band separation. Two-dimensional hetero-spectral correlation analysis has also been developed to find correlations in spectra with different spectroscopic probes. 2D-COS as an analytical technique has increasing avenues of expansion, and can be creatively used in many other fields in the future.

2D-COS↗
DOE OSTI2019

Accelerate Performance (Final Technical Report)

Encouraging commercial building owners to set measurable energy goals before design begins can drive design and contractor teams to develop innovative energy efficiency solutions within conventional building budgets. A federal building owner piloted this technique and created a large-scale zero-energy office building on a budget comparable to local market construction rates. The successes and lessons learned from this performance-based project formed the basis of Accelerate Performance, an expanded program using utilities as the primary outreach channel to replicate the approach. Four utilities partnered with Slipstream, a not-for-profit program implementer, to develop pilot incentive offerings to focus building owners on the whole building rather than on individual building components and systems. The original performance-based procurement process and its successful implementation in a federal building project informed all these efforts. The experiences and lessons learned in different new construction markets led to further process adaptations as well as the development of templates and tools to streamline outreach and technical support efforts. The approach can be adapted to utility new construction programs and is a powerful tool for engaging many building owners early in the project planning process as they make critical energy decisions that impact the performance of the building. The approach has led to real energy savings in building projects by encouraging cost-effective, low-risk, and creative design solutions. The performance-based approach was tested in a variety of applications including different building types and owner types, with many owners adopting performance-based procurement techniques, some with variations, but all maintaining the same core principles. Over the course of the project, nearly 100 building projects were impacted and additional projects will continue to be supported through ongoing program offerings with three leading utilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Advancing Science Through Computation at NDSU (Final Report)

The Center for Computationally Assisted Science and Technology (CCAST), a research unit within the Office for the Vice President for Research and Creative Activity, is in its build-out phase at North Dakota State University (NDSU). CCAST is developing high-performance computing (HPC) capabilities, designed to support existing HPC-oriented NDSU programs as well as to support its own research program which will initially concentrate, but not be limited to, application of theory and computation toward development of high-value functional materials and systems for renewable energy and energy efficiency. The following initial priorities for the Center were established: (1) reconstruct the NDSU HPC hardware and software infrastructure, (2) define CCAST research focus, (3) hire research and HPC support staff, (4) fit-out CCAST computer rooms to ensure continuation and growth of the Center’s HPC activities and, (5) support the NDSU existing thrust in chemo- and bio-informatics (as applied to the high-throughput combinatorial chemistry, biology, and genomics). These priorities are subject to change as the Center grows and evolves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

An August boost for key roles in Weapons Production

In August, the Associate Laboratory Directorate of Weapons Production (ALDWP) hosted two virtual hiring events and welcomed the first cohort of a new college pipeline program. With hiring steadily on the increase in support of the national security mission, creative methods like these have been key to finding successful candidates.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

2020 LLNL Nuclear Science and Security Summer Internship Program

The Lawrence Livermore National Laboratory (LLNL) Nuclear Science and Security Summer Internship Program (NS 3 IP) is designed to give graduate students an opportunity to come to LLNL for 8–10 weeks of hands-on research. Students conduct research under the supervision of a staff scientist, attend a weekly lecture series, interact with other students, and present their work in poster format at the end of the program. Students also have the opportunity to meet staff scientists one-on-one, participate in LLNL facility tours (e.g., the National Ignition Facility and Center for Accelerator Mass Spectrometry), and gain a better understanding of the various science programs at LLNL. Due to the travel and access restrictions imposed by the COVID-19 pandemic, the 2020 NS 3 IP was organized as an “all-virtual” internship program. With LLNL’s extensive institutional support, students accessed the laboratory’s cyberinfrastructure through a secure virtual desktop environment and all seminars, mentor interactions, summer presentations, and laboratory tours were performed remotely. While this virtual internship format did not allow for hands-on laboratory research projects, both the interns and their mentors constructed creative research projects that maximized student exposure to nuclear science research that is relevant to DTRA and LLNL interests in nuclear security.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗