Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Research and development plan”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗
DOE OSTI2024

Advanced Perovskite Solar Cells and Modules

The “Advanced perovskite Cells and Modules” research project was the final agreement focused on enhancing perovskite solar cell (PSC) technologies funded by the US Department of Energy's Solar Energy Technologies Office. The project was designed to address three crucial areas in PSC development: stability, manufacturability, and efficiency. The project was then structured around three main tasks, each targeting one of these strategic goals. The team of experienced researchers in these materials worked collaboratively to address the targets outlined in the technical work plan. building on existing PSC research while also exploring promising new concepts arising in the field. An overview of each primary task is summarized below: Task 1 Stability: This first task, aims to identify material characteristics and metrics that can help predict the primary degradation mechanisms impacting PSC stability. This involved developing specific device tests based on hypotheses regarding mechanisms impacting stability, including fast failure procedures to speed up PSC development and improvement. Various strategies to enhance stability, like incorporating additives, post-treatments, novel contact materials etc. were developed using this fast feedback approach. The relationships between indoor and outdoor stresses were also validated. Task 2 Manufacturability: This second task, focused on creating a scalable production process for PSCs. Initially the objective is to establish a best-known method for a 182 cm2 minimodule. However, given resource limitations, these metrics were modified to focus on the other goal of outlined in the TWP. Specifically, this task worked to demonstrate the transferability of this best-known method to another research institution. Work scope in this area was expanded to material purity and understanding of reagent/process relationships. Examination of other difficulties in PSC production and potential solutions for large-scale production were also evaluated. Given challenges observed in process transfer, work to develop data infrastructure and recording tools for processing of material and devices was then also prioritized in this task. Task 3 Efficiency: This task was focused on improvements to PCE, while still considering Task 1 and Task 2 goal. The efforts targeted a PCE greater than 22% with a T95 exceeding 1000 hours at 25°C in a nitrogen environment for lab-scale devices (approximately 0.1 cm2 devices) across a range of solar-relevant perovskite compositions, including wide-gap (around 1.7 eV) and low-gap (around 1.3 eV) materials, using standard metal contacts. This work then provides a foundation for MHP-based tandem efforts undertaken in other projects and the All-MHP tandem efforts outlined in this projects TWP. Work in this project emphasized disseminating its findings through peer-reviewed publications (PRP), conference presentations, and industrial collaborations. Significant products were produced in all these areas, over 53 peer reviewed publications, 32 conference presentations and industrial investment based on NLR assistance on precompetitive challenges. The team also developed significant intellectual property and awards for their technical excellence, innovations and leadership. The team also leveraged traditional and social media platforms to engage with stakeholders and the public.

14 SOLAR ENERGY↗
DOE OSTI2020

Overview of the MCNP6® SQA Plan and Requirements [Memorandum]

For all X Computational Physics Division (XCP) software under the Associate Laboratory Directorate for Weapons Physics (ALDX), the Weapons Research Services Secure Networks and Assurance Group (WRS-SNA) manages the software quality assurance (SQA) plan, requirements and guidance with respect to development processes and tools to meet the broader LANL SQA requirements. Each XCP software product is categorized into one of three software types: Safety Software, Non-Safety Risk Significant Software, and Non-Safety Commercially Controlled Software. In 2018, using LANL Form 2033, the MCNP6 code was categorized by the XCP division as Non-Safety Commercially Controlled Software, provided in Appendix A. Using WRSFORM- 0001U, the MCNP6 code was graded as a Medium Impact software product, provided in Appendix B. Given these determinations, the WRS-AD-0010U SQA plan is followed for all MCNP6 developments, documentation and code releases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Southwest Wind Power R&D Test Site Development at the National Wind Technology Center (CRADA CRD-12-00472 Final Report)

Southwest Windpower, Inc. (SWWP) has been designing and distributing small wind turbines for more than 22 years and is the recognized global leader in the design, manufacturing and distribution of small wind systems (400-3000 watts). The company has been a pioneer in the development of wind technology and has built and shipped more than 170,000 wind turbines to over 120 countries worldwide. Headquartered in Flagstaff AZ, SWWP has sales representatives in over 88 countries. Applications for SWWP systems include residential homes, commercial properties, micro grids, remote cabins, telecom transmitters, offshore platforms, water pumping and sailboats. In addition, U.S. Department of Defense uses SWWP’s products in Forward Operating Bases (FOB’s), USGS uses them for remote monitoring of glacier movements and the CIA uses them to provide power seismic monitoring. Today, SWWP plans development of new technologies to address distributed energy market needs and become even more aggressive in international markets. This strategy includes extensive Research, Development, Demonstration & Deployment (RDD&D) activities to improve existing production line into more simple, reliable, and cost-effective wind turbine systems. Important part of such activities is the field testing of the new systems, which should provide: (i) validation of the reliable operation of hardware and software; (ii) validation of numerical models of the system and its components; (iii) field comparison of various control and optimization strategies; (iv) customized reliability testing; (v) customized monitoring and analysis testing; and (vi) IEC certification testing (vii) filed demonstration of system performance and reliability. Such field testing facility should encompass multiple towers and appropriate data acquisition systems. SWWP is exploring to move part of the engineering department to Colorado, and execute its RDD&D strategies in this new location. Partnership with NREL will provide great insights into SWWP’s RDD&D processes and more efficient commercialization by utilizing NWTC as the field testing site, and working close with NREL personnel. NWTC is ideally suited to strain the design. NREL is very experienced with customized and IEC testing. During this project, Southwest Windpower aims to improve the value proposition of distributed renewable energy, and make it a competitive choice in the energy markets. As of today, more then 170,000 small wind turbines, manufactured in the U.S., are installed in more then 180 countries. With the improved value proposition, Southwest Windpower wants to create and address new market needs, substantially increase its sales domestically and internationally, which should have positive impact on the creation of American jobs, competitiveness of U.S. economy, export or U.S. products, and the use of renewable energy.

17 WIND ENERGY↗
DOE OSTI2023

Key Goals and Innovations Needed for a U.S. Compact Fusion Pilot (Final Technical Report)

Fusion energy offers the prospect of addressing the nation's energy needs and contributing to the transition to a low-carbon emission electrical generation infrastructure. Technology and research results from U.S. investments in the major fusion burning plasma experiment known as ITER, coupled with a strong foundation of research funded by the Department of Energy (DOE), position the United States to begin planning for its first fusion pilot plant. Strong interest from the private sector is an additional motivating factor, as the process of decarbonizing and modernizing the nation's electric infrastructure accelerates and companies seek to lead the way. At the request of DOE, Bringing Fusion to the U.S. Grid builds upon the work of the 2019 report Final Report of the Committee on a Strategic Plan for U.S. Burning Plasma Research to identify the key goals and innovations - independent of confinement concept - that are needed to support the development of a U.S. fusion pilot plant that can serve as a model for producing electricity at the lowest possible capital cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Commissioning of the IOTA Proton Injector

The IOTA Proton Injector (IPI) at the Fermilab Accelerator Science and Technology facility (FAST) is a machine capable of delivering up to 14 mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. Its construction was completed in the fall of 2025, followed by a successful commissioning run scheduled to conclude at the end of May 2026. It operates alongside the existing electron injector beamline to facilitate further beam physics research and continued development of novel accelerator technologies at the IOTA ring. This report details the current operational profile, known challenges, and future plans for the proton program development at FAST.

Romanov, A. [Fermilab] (ORCID:0000000287065709)↗
DOE OSTI2019

Basic Research Needs for High Energy Physics Detector Research & Development: Report of the Office of Science Workshop on Basic Research Needs for HEP Detector Research and Development: December 11-14, 2019

Transformative discovery in science is driven by innovation in technology. Our boldest undertakings in particle physics have at their foundation precision instrumentation. To reveal the profound connections underlying everything we see from the smallest scales to the largest distances in the Universe, to understand its fundamental constituents, and to reveal what is still unknown, we must invent, develop, and deploy advanced instrumentation. Investments in High Energy Physics (HEP) enabled by instrumentation have been richly rewarded with discoveries of the tiny masses of the neutrinos, the origin of mass itself: the enigmatic Higgs boson, and the surprising accelerating expansion of the Universe. What we have learned is remarkable, unexpected, exciting and mysterious; raising many new questions waiting to be answered. The quest to answer them drives innovation that improves the nation's health, wealth, and security, inspiring the public and drawing young people to science. Excellence and innovation come most effectively from diverse teams of people. Success, therefore, depends critically on attracting, engaging, and supporting a diverse cadre of young people to the field, and ensuring an inclusive environment at all levels. The program laid out in the 2014 Particle Physics Projects Prioritization Panel (P5) report "Building for Discovery - A Strategic Plan for U.S. Particle Physics in a Global Context" guides current and near future experiments to exploit these and other discoveries, and the instrumentation innovation they require, to push the frontiers of science into new territory. To explore this territory HEP will soon embark on planning the next generation of experiments. Realizing these experiments will require giant leaps in capabilities beyond the instrumentation of today. Accordingly, now is a pivotal moment to invest in the accelerated development of cost-effective instrumentation with greatly improved sensitivity and performance that will make measurable the unmeasurable, enabling a tool-driven revolution to open the door to future discoveries. Historic scientific opportunities await us, enabled by executing the instrumentation research plan outlined here.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Enabling Capabilities and Resources: 2024 Principal Investigator Meeting Proceedings

As a major supporter of basic genome-enabled research, BER’s Biological Systems Science Division (BSSD) fosters scientific discovery by funding - fundamental biological research across disciplines in conjunction with enabling investigational tools and computational capabilities that include world-class user facilities. The overarching goal of BSSD is to provide the necessary fundamental science to understand, predict, manipulate, and design biological systems that underpin innovations for bioenergy and bioproduct production and enhance understanding of natural, DOE-relevant environmental processes (Biological Systems Science Division Strategic Plan, 2021). To accelerate the U.S. bioeconomy, BSSD pursues innovative science underpinning advances in sustainable biofuels and bioproducts and the development of next-generation technologies and computational resources for systems biology research. The 2024 BSSD Enabling Capabilities and Resources (ECR) Principal Investigator (PI) meeting brought together PIs across the BSSD ECR portfolio to confer on shared interests and opportunities. The meeting was held concurrently with the Genomic Science program (GSP) PI meeting to optimize collaboration on research to advance bioenergy and the bioeconomy. Rick Stevens of Argonne National Laboratory gave a keynote on How Generative Artificial Intelligence Can Impact Biological Research (see Keynote: How Generative Artificial Intelligence Can Impact Biological Research, this page). Plenary presentations included several joint sessions that illuminated the integration and understanding of the larger BSSD mission. GSP’s objective is to provide systems-level understanding of plants, microbes, and their communities through its Bioenergy Research, Biosystems Design, and Environmental Microbiome Research portfolios. The objective of the ECR portfolio is to support development of computational and instrumental platforms to advance fundamental GSP research—and BER more broadly— toward the overall goal of understanding the functional principles of living systems and their response to environmental challenges.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Community Input on the Need, Scope, and Development Roadmap of a Proposed National Virtual Biosecurity for Bioenergy Crops Center (NVBBCC)

Brookhaven National Laboratory (BNL) was awarded a pilot project in FY22 under the U.S. Department of Energy (DOE) Office of Science Biopreparedness Research Virtual Environment (BRaVE) initiative, to define research priorities, needs, and requirements for a national virtual center devoted to the biosecurity of bioenergy crops. The mission of the proposed center, referred to as the National Virtual Biosecurity for Bioenergy Crop Center (NVBBCC), would be to provide the scientific basis and tools to detect, characterize, model, and mitigate biothreats to bioenergy crops. This function will be essential to ensure the projected increased US reliance over the next few decades on key plant-based energy products, such as biojet fuel. The NVBBCC is envisioned as a distributed, virtual center with multiple national laboratories at its core to maximize the use of existing unique facilities and expertise across the DOE complex. A major goal of the pilot project was to develop a roadmap for establishing NVBBCC through a series of meetings to gather community input. A total of about 150 individuals, drawn from DOE laboratories, the USDA, academia, NIH, DHS and the private sector participated in six planning meetings held in FY23. Four of the meetings were focused on specific research topics (disease detection, dispersion and disease propagation, biomolecular characterization of plant-pathogen interaction, and mitigation strategies). These four meetings were followed by a meeting that focused on computational needs to support collaborative, data-intensive research within a distributed center as well as workforce development. A final meeting focused on establishing and maintaining preparedness within NVBBCC to respond to an emerging disease within bioenergy crops and how it would collaborate and coordinate with USDA and DHS.

09 BIOMASS FUELS↗
DOE OSTI2021

Viability of Vehicles Utilizing On-Board CO 2 Capture

Although battery electric and hydrogen fuel cell vehicles hold great promise for mitigating CO 2 emissions, there are still unaddressed sectors for electrified transport, e.g., the heavy-duty and long-range global shipping industry. In this Viewpoint, we examine the viability of CO 2 -neutral transportation using hydrocarbon or alcohol fuels, in which the CO 2 product is captured on-board the vehicle. This approach takes advantage of the unparalleled energy density of carbon-based fuels as needed for these energy-intensive applications. Here, a concept is developed considering the power technologies, infrastructure, and fuels required. Storage volume and mass requirements are calculated for a wide range of vehicle types and compared with those for other CO 2 -neutral options, namely hydrogen fuel cell and battery electric vehicles, and research and development needs to implement this technology are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Research and Development Studies for Reactor Neutrino Experiments in Turkey (RNET)

The program of the Reactor Neutrino Experiments of Turkey includes a small portable Water-based liquid scintillator detector to detect neutrinos from the Akkuyu nuclear power plant, planned to begin operating in 2023. The small near-field detector will weigh about 2-3 tons and will be placed less than 100 meters from the reactor cores. The Reactor Neutrino Experiments of Turkey program also includes a medium-size 30-ton Water-based liquid scintillator detector, which will be placed 1-2 km away from the reactor cores and will be used as a far detector. Both detectors and their responses to neutrino interactions were simulated using a GEANT4-based RAT-PAC simulation package. Here, we will share the technical and physical details of both detectors, and discuss the ongoing R&D effort for neutrino studies in Turkey.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Mercury Remediation Technology Development for Lower East Fork Poplar Creek—FY 2021 Update

Mercury remediation is a high priority for the US Department of Energy (DOE) Oak Ridge Office of Environmental Management. Mercury contamination in the environment can be found at all three DOE facilities in Oak Ridge, Tennessee, but the greatest environmental risk concern relative to Hg on the Oak Ridge Reservation is likely associated with historical Hg losses at and near the Y-12 National Security Complex (Y-12). Mercury in water and fish from East Fork Poplar Creek (EFPC) downstream of Y-12 exceeds regulatory thresholds. Because of the complexities of Hg transport and fate in the aquatic environment, conventional remedial options for EFPC are highly uncertain. DOE is using a phased adaptive management approach to Hg remediation at Y-12, with a focus in the next few years on construction of the Mercury Treatment Facility (MTF) to treat the most contaminated Y-12 outfall entering EFPC (DOE 2017a; DOE 2017b). Once operational, the MTF will provide additional protection against inadvertent releases of Hg into the stream from decontamination and decommissioning of Y-12 Hg-use buildings. Although the MTF is anticipated to substantially decrease Hg water concentrations and flux in upper EFPC (UEFPC), research and technology development are needed to develop appropriate and longer-term remedial solutions for the downstream environment. Since late 2014, the Oak Ridge Office of Environmental Management and URS | CH2M Oak Ridge LLC/Restoration Services Inc. have supported DOE’s Oak Ridge National Laboratory (ORNL) Environmental Sciences Division staff in conducting field and laboratory studies to develop Hg remedial technology solutions for lower EFPC (LEFPC). Whereas previous annual reporting updates for Hg remediation technology development for LEFPC have focused on presenting detailed results from the previous fiscal year, this FY 2021 update takes a comprehensive, higher-level approach to the research and technology development activities conducted since 2014. The report is organized to be consistent with the three tasks defined in the LEFPC strategic plan

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

U.S. Offshore Wind Energy Noise Reduction Associated with Installation of Fixed-Bottom Foundations: Workshop Report

As offshore wind energy development grows in the United States, solutions are needed to reduce the underwater noise and substrate vibration generated during fixed-bottom turbine installation to help protect marine life. Monopiles are currently the main turbine foundation type installed globally and impact pile driving, the primary installation method, can be a major source of noise and vibration generation during wind farm construction. Opportunities exist to reduce the amount of noise and vibration produced during future offshore wind farm development. The use of alternative foundation types and installation methods, as well as innovative noise abatement technologies, would help reduce the potential detrimental effects on sensitive marine species. To explore these opportunities, the Department of Energy’s Wind Energy Technologies Office, in collaboration with the Bureau of Ocean Energy Management and the National Oceanic and Atmospheric Administration, funded the National Renewable Energy Laboratory and the Pacific Northwest National Laboratory to organize, host, and facilitate a virtual workshop in December 2022. The goal of the workshop was to gather input from the offshore wind energy community on noise reduction strategies for the installation of fixed-bottom offshore wind turbines in U.S. waters across multiple regions, including the U.S. Atlantic Coast, Gulf of Mexico, and Great Lakes to inform recommendations on future research. The joint lab team convened industry representatives, subject matter experts, and regulators to discuss potential pathways to reduce noise and vibration associated with fixed-bottom turbine installation, including the practicality of using alternative foundations and installation methods, the effectiveness of noise abatement technologies, as well as research and monitoring needs. In preparation for the workshop, the team invited experts to be part of a steering committee and worked with its members to help focus activities to meet the workshop goals. Additional pre-workshop activities included developing the invitee list and workshop agenda, reviewing existing Construction and Operations Plans (COP) for proposed offshore wind projects, distributing a brief questionnaire to industry representatives, and drafting the workshop discussion questions and Mural boards. In total, 128 workshop participants provided over 600 comments in response to the 17 group discussion questions used over two workshop sessions. Overarching recommendations highlighted across themes included future investments to provide data sharing, consistency, transparency, and opportunities for sharing best available science, knowledge, and expertise. The joint lab team synthesized the comments and identified four key research and development themes that could help advance the successful implementation of noise and vibration reduction strategies (see report). This report provides an overview of the workshop goals and scope, reviews the pre-workshop activities, presents brief summaries of participant feedback, and concludes with detailed research themes and recommendations for future investments. Appendix A includes the group discussion questions, Appendix B includes the results of the COP review, and Appendix C includes the results of the industry questionnaire. Overall, there was a high level of interest and engagement in the workshop. The sessions provided an opportunity for significant exchange of information between workshop participants from across sectors. Participants identified a variety of opportunities for next steps towards the noise reduction of offshore wind turbine installation in U.S. waters, including recommendations for future investments to provide certainty in the use of new technologies associated with alternative foundation types, noise abatement systems, and efficacy monitoring.

17 WIND ENERGY↗
DOE OSTI2021

Experimental Plan for the Vermiculite Study

Homes in which vermiculite, which can contain asbestos, is present are often deferred under the DOE Weatherization Assistance Program (WAP) because of uncertainty in how to safely weatherize such homes from a client and worker perspective and the potential costs associated with alternative approaches. Recognizing this situation, the Department of Energy (DOE) tasked the Oak Ridge National Laboratory (ORNL) to perform a research project that scientifically identifies the asbestos exposure risks in weatherizing homes with existing vermiculite insulation. Current approaches being used by Grantees and Subgrantees to weatherize homes with existing vermiculite insulation were identified as part of the development of this experimental plan based on a review of Grantee Health and Safety Plans and communications with weatherization program staff from seven states. Other than deferral, these approaches include the following:1.) Abating (i.e., removing) the existing vermiculite using funding sources other than WAP (e.g., state funds, utility funds, the Zonolite Attic Insulation Trust Fund, and possibly homeowner contributions) because abatement is not allowed using WAP funds per Weatherization Program Notice (WPN) 17-7. 2.) Weatherizing the house as normal after testing reveals that the vermiculite contains less than 1% asbestos. 3.) Avoiding areas of the house where vermiculite is installed and weatherizing the remaining areas of the house as normal. 4.) Encapsulating the existing vermiculite insulation in an attic by blowing cellulose or other insulation over it. 5.) Weatherizing the areas of the house where vermiculite is installed using unique/alternative approaches developed specifically for that house. Blower door testing is also impacted by the presence of vermiculite due to the concern of bringing asbestos fibers into the space. Some states address this by performing pressurized blower door tests, whereas other states prohibit blower door testing entirely when vermiculite is present. This research project will focus on gathering data on home occupant and weatherization worker exposures to asbestos before, during, and/or after the weatherization of the homes containing vermiculite insulation using five of the six approaches identified above. Abatement of the existing vermiculite insulation will not be studied because it is not allowed using WAP funding per WPN 17-7 and, thus, is not a sustainable approach for WAP.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Dataset of Generative AI Workload Power Profiles

This dataset provides a collection of high-resolution (5/10 Hz or every 0.2/0.1 seconds) power consumption profiles for generative artificial intelligence (GenAI) workloads executed on NLR's High Performance Computing (HPC) platform Kestrel. The dataset also includes examples of representative whole-facility power profiles generated using a bottom-up, event-driven, data center energy model . This dataset is designed to support research in energy modeling, infrastructure planning, energy system integration, and sustainability analysis for AI-driven computing systems. The dataset captures time-resolved electrical power measurements across a diverse set of configurations, including variations in job type (inference vs. training), workload (LLM vs. image generation), datasets, and number of compute nodes. Power traces are provided in a standardized format and include both raw/instantaneous and aggregated files. Each profile is accompanied by metadata describing workload parameters, enabling reproducibility and cross-study comparison. The dataset is intended for use in applications such as data center infrastructure planning, energy modeling, demand response and grid impact studies, and development and validation of system-level simulation tools. By making these workload-specific power profiles publicly available, this dataset aims to address the current lack of open, empirical energy data for generative AI systems and to facilitate transparent, reproducible research on the energy and environmental impacts of large-scale AI deployment. If you use this dataset, please cite the associated publication: Vercellino et al., “Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning,” arXiv:2604.07345 (2026).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Structure-Aware Unsupervised, Transformational Machine Learning for Drug Discovery (DTRA Basic Research Final Report)

The major goal of this project is to develop machine learning (ML) methods to enable improved predictive power on real drug discovery for novel targets. More specifically, we planned to demonstrate the capability and effectiveness of ML tools utilizing unlabeled large-volume protein-ligand datasets. We investigated multiple pre-training approaches for 3D protein-ligand structure-based foundation models, without relying on experimental binding data. We also addressed scenarios in which crystal structures are unavailable or binding data are limited. We also planned to develop a complete pipeline to screen novel compounds as well as to demonstrate the capability and effectiveness of the developed methods by testing on a realistic drug discovery task such as SARS-CoV-2. While the major goals and milestones remain consistent with the original proposal, certain technical details have been adjusted, based on the experimental results and related outcomes.

97 MATHEMATICS AND COMPUTING↗