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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2018

Cost-Reduction Roadmap for Residential Solar Photovoltaics (PV), 2017-2030

The installed cost of solar photovoltaics (PV) has fallen rapidly in recent years and is expected to continue declining in the future. In this report, we focus on the potential for continued PV cost reductions in the residential market. From 2010 to 2017, the levelized cost of energy (LCOE) for residential PV declined from 52 cents per kilowatt-hour (cents/kWh) to 16 cents/kWh (Fu et al. 2017). The U.S. Department of Energy's (DOE's) Solar Energy Technologies Office (SETO) recently set new LCOE targets for 2030, including a target of 5 cents/kWh for residential PV. We present a roadmap for achieving the SETO 2030 residential PV target. Because the 2030 target likely will not be achieved under business-as-usual trends (NREL 2017), we examine two key market segments that demonstrate significant opportunities for cost savings and market growth: installing PV at the time of roof replacement and installing PV as part of the new home construction process. Within both market segments, we identify four key cost-reduction opportunities: market maturation, business model integration, product innovation, and economies of scale. To assess the potential impact of these cost reductions, we compare modeled residential PV system prices in 2030 to the National Renewable Energy Laboratory's (NREL's) quarter one 2017 (Q1 2017) residential PV system price benchmark (Fu et al. 2017). We use a bottom-up accounting framework to model all component and project-development costs incurred when installing a PV system. The result is a granular accounting for 11 direct and indirect costs associated with installing a residential PV system in 2030. All four modeled pathways demonstrate significant installed-system price savings over the Q1 2017 benchmark, with the visionary pathways yielding the greatest price benefits. The largest modeled cost savings are in the supply chain, sales and marketing, overhead, and installation labor cost categories. When we translate these installed-system costs into LCOE, we find that the less-aggressive pathways achieve significant cost reductions, but may not achieve the 2030 LCOE target. On the other hand, both visionary pathways could get very close to (for roof replacement) or achieve (for new construction) the 2030 target. Our analysis has two key implications. First, because installed-system soft cost reductions account for about 65 percent of the LCOE reductions in 2030 for both visionary pathways, residential PV stakeholders may need to emphasize these soft cost reductions to achieve the 2030 target. Second, capturing these savings will likely require considerable innovation in the technologies and business practices employed by the PV industry.

14 SOLAR ENERGY↗

DOE OSTI2021

Freight Analysis Framework Version 5 (FAF5) Base Year 2017 Data Development Technical Report

The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive national picture of freight movements among states and major metropolitan areas by all modes of transportation. The latest of this data series is FAF5, which is the fifth generation FAF and is benchmarked on Commodity Flow Survey (CFS) 2017. Except for FAF1 that provided estimates for truck, rail, and water tonnage for calendar year 1998, later generations of FAF (FAF2 through FAF5) were built based on their benchmark year CFS data, for 2002, 2007, 2012, and 2017 respectively. The FAF is produced under a partnership between Bureau of Transportation Statistics (BTS) and Federal Highway Administration (FHWA). As a major data product of the FAF program, the FAF regional database provides a national picture of freight flows to, from, and within the United States (among regions and states), by commodity and mode for the base year, as well as for forecasts up to 30 years into the future in a 5-year interval. Additional FAF data products also include FAF network flows database, where truck movements are routed onto the national highway network, estimates of annual projections, and synchronized historical data series. This report is a technical document prepared to describe the data sources and methodologies applied in the process of building the FAF5 base-year 2017 regional database, released as FAF5.0 in February 2021. This report offers a description of the diverse data sources and modeling methods used in constructing the base year FAF5 regional database. The FAF5 base-year database is used as the base for development of forecasts and for assignment of truck flows on highway network. Similarly, the FAF5 base-year database will be used as the base to generate FAF5 annual estimates. In addition to this report, users are encouraged to refer to the FAF5 User’s Guide, which provides basic information of the data, including definitions of the data attributes, information on how to access the data and tool, as well as detailed data dictionary and code tables.

42 ENGINEERING↗

NASA NTRS2014

Investigating the Airspace Safety Threshold of the NAS

As self-separation systems are being developed for integration into the airspace, it is crucial to determine a standard that the systems must meet so that airspace safety does not degrade. To do this, the current level of safety of the NAS (National Airspace System) needs to be determined as a benchmark for comparison. This presentation is an overview of some of the ongoing work being done to evaluate the airspace as it is today. The research analyzes the distribution of encounter statistics of IFR-VFR (Instrument Flight Rules-Visual Flight Rules) traffic using unmodified historical flight data to account for mitigation effects present in the current NAS.

Airspace Encounters↗

DOE OSTI2025

A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part I: Model Formulation

Here, this paper formulates a new particle-in-cell method for the Vlasov–Maxwell system. Under the Lorenz gauge condition, Maxwell’s equations for the electromagnetic fields can be written as a collection of scalar and vector wave equations. The use of potentials for the fields motivates the adoption of a Hamiltonian formulation for particles that employs the generalized (conjugate) momentum. A notable advantage offered by the Hamiltonian formulation is the elimination of time derivatives in the Lorenz gauge formulation that are required by the standard Newton–Lorentz treatment of the particles. This allows the fields to retain the full time-accuracy guaranteed by the field solver. The resulting updates for particles require only knowledge of the fields and their spatial derivatives. An analytical method for constructing these spatial derivatives is presented that exploits the underlying integral solution used in the field solver for the wave equations. Moreover, these derivatives are demonstrated to converge at the same rate as the fields in both time and space. The Method of Lines Transpose field solver we consider in this work is globally first-order accurate in time and high-order accurate in space (e.g., fourth- and fifth-order) and belongs to a larger class of methods which are unconditionally stable, can address geometry, and leverage $\mathcal {O}(N)$ fast summation methods for efficiency. We demonstrate the method on several well-established benchmark problems on bounded domains, including a plasma sheath as well as a relativistic particle beam. The efficacy of the proposed formulation is established by comparing with a second-order accurate finite-difference time-domain method that employs a leapfrog time advance for particles and a charge conserving map suitable for bounded domains. The new method shows mesh-independent numerical heating properties even in cases where the plasma Debye length is smaller than the grid spacing. This is an important feature of the new method for problems defined on bounded domains, because it permits the use of coarser grids in space in the representation of the fields. Such a capability has significant implications for the simulation of plasmas in bounded domains with complex geometry, where the ratio between the largest and smallest cells can vary significantly. The use of high-order spatial approximations in the new method also means that fewer grid points are required in order to achieve a fixed accuracy. Our results also suggest that the new method can be used with fewer simulation particles per cell compared to the benchmark explicit method, which permits further computational savings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

IER 500: AWE-LLNL Measurement Campaign at DAF [Slides]

Presentation Hosted at Device Assembly Facility (DAF). Joint collaboration by Atomic Weapons Establishment (AWE) and Lawrence Livermore National Laboratory (LLNL). Multiple measurements were recorded through a two-week period with 12 unique objects measured. LLNL deployed Machine learning software program for diagnostic assessments. Current status notes the dedicated DAF team LLNL maintains. Additionally, LLNL is compiling a report on the AWE-LLNL measurements and designing security benchmark experiments. The presentation concludes with future work envisioned.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Non Accountable Sealed Radioactive Sources

Presentation describes investigation into defective 10 uCi Cs-137 "button" sources and response to potential contamination, to include radiological control measures, notifications, and awareness reports. Effort involves benchmarking of EFCOG member processes for use and handling of non-accountable sources.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

Search for minimal supersymmetric standard model Higgs Bosons H / A and for a $Z^{\prime}$ boson in the $\tau\tau $ final state produced in pp collisions at $\sqrt{s}$= 13 TeV with the ATLAS detector

A search for neutral Higgs bosons of the minimal supersymmetric standard model (MSSM) and for a heavneutral Z ' boson is performed using a data sample corresponding to an integrated luminosity of 3.2 fb - 1 from proton–proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC. The heavy resonance is assumed to decay to a τ + τ - pair with at least one τ lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2–1.2 TeV for the MSSM neutral Higgs bosons and 0.5–2.5 TeV for the heavy neutral Z ' boson. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in MSSM and Z ' benchmark scenarios. The most stringent constraints on the MSSM m A –tan β space exclude at 95 % confidence level (CL) tan β > 7.6 for m A = 200 GeV in the m$mod+\atop{h}$ MSSM scenario. For the Sequential Standard Model, a Z$'\atop{SSM}$ mass up to 1.90 TeV is excluded at 95 % CL and masses up to 1.82–2.17 TeV are excluded for a Z'$\atop{SFM}$ of the strong flavour model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production

Identifying gene targets for enhancing metabolite production in metabolic engineering is challenging due to the vast research literature and the approximation in genome-scale metabolic model (GEM) simulations. Here, to address this, we propose the Gene-Metabolite Association Prediction task, which automates gene discovery for given metabolite-gene pairs, accompanied by a benchmark dataset of 2474 metabolites and 1947 genes for Saccharomyces cerevisiae (SC) and Issatchenkia orientalis (IO). This task is complicated by incomplete metabolic graphs and metabolic heterogeneity. We introduce an Interactive Knowledge Transfer mechanism based on Metabolism Graphs (IKT4Meta) to enhance prediction accuracy by integrating cross-metabolism knowledge. Using Pretrained Language Models (PLMs) to generate inter-graph links mitigates heterogeneity issues, while intra-graph links are propagated via these anchors. Gene-metabolite predictions are then performed on the enriched graphs integrating multiple microorganisms’ knowledge. Experiments show that IKT4Meta outperforms baselines by up to 12.3% in link prediction.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗

NASA NTRS2001

On Multifunctional Collaborative Methods in Engineering Science

Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized.

Ransom, Jonathan B.↗

DOE OSTI2018

A Techno-Economic Look at SiC WBG from Wafer to Motor Drive

Techno-economic analysis helps benchmark and deliver supply chain and manufacturing insights that can be leveraged by decision-makers to inform investment strategies, policy, and other decisions to promote economic growth and competitiveness. Silicon Carbide (SiC) wide-band gap (WBG) technologies is poised to be an integral contributor to the clean energy economy. We use bottoms-up regional manufacturing cost models to show SiC power electronics, manufactured in volume, could result in final product cost parity with those manufactured with silicon. The models are further leveraged to show innovation pathways to lower cost and potentially expanded technology adoption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Energy Management Information System Powers NREL's Intelligent Campus

NREL's Intelligent Campus program leverages its own laboratory buildings as research instruments to study renewable energy, energy efficiency, and energy storage, integration, and analysis with real, quantitative measurements. At the heart of NREL's Intelligent Campus program is its Energy Management Information System (EMIS), a family of tools and services used to manage building and campus energy use. NREL's EMIS includes capabilities, such as benchmarking and monthly utility tracking, interval meter analytics, equipment fault detection and diagnostics, condition-based monitoring, and supervisory control, enabling unprecedented energy management capabilities. The system serves as a demonstration project for other federal facilities interested in learning about its design, features, and benefits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Energy Management Information System Powers NREL's Intelligent Campus

EMIS↗

DOE OSTI2024

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the Organization of Economic Cooperation and Development / Nuclear Energy Agency Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). Previous analyses as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. In this paper, we present a new RELAP5-3D model of HTTF with finer radial nodalization built to assess the impact of radial heat transfer. We describe the new model and compare it against the old one at full-power steady state and for the pressurized conduction cooldown (PCC) transient. These analyses are based on the code-to-code comparison exercise for the PCC problem of the HTGR T/H benchmark. We compare maximum block temperature as the primary figure of merit and include discussion on intracore natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2016

SU-F-T-153: Experimental Validation and Calculation Benchmark for a Commercial Monte Carlo Pencil Beam Scanning Proton Therapy Treatment Planning System in Water

Purpose: Eclipse proton Monte Carlo AcurosPT 13.7 was commissioned and experimentally validated for an IBA dedicated PBS nozzle in water. Topas 1.3 was used to isolate the cause of differences in output and penumbra between simulation and experiment. Methods: The spot profiles were measured in air at five locations using Lynx. PTW-34070 Bragg peak chamber (Freiburg, Germany) was used to collect the relative integral Bragg peak for 15 proton energies from 100 MeV to 225 MeV. The phase space parameters (σx, σθ, ρxθ) number of protons per MU, energy spread and calculated mean energy provided by AcurosPT were identically implemented into Topas. The absolute dose, profiles and field size factors measured using ionization chamber arrays were compared with both AcurosPT and Topas. Results: The beam spot size, σx, and the angular spread, σθ, in air were both energy-dependent: in particular, the spot size in air at isocentre ranged from 2.8 to 5.3 mm, and the angular spread ranged from 2.7 mrad to 6 mrad. The number of protons per MU increased from ∼9E7 at 100 MeV to ∼1.5E8 at 225 MeV. Both AcurosPT and TOPAS agree with experiment within 2 mm penumbra difference or 3% dose difference for scenarios including central axis depth dose and profiles at two depths in multi-spot square fields, from 40 to 200 mm, for all the investigated single-energy and multi-energy beams, indicating clinically acceptable source model and radiation transport algorithm in water. Conclusion: By comparing measured data and TOPAS simulation using the same source model, the AcurosPT 13.7 was validated in water within 2 mm penumbra difference or 3% dose difference. Benchmarks versus an independent Monte Carlo code are recommended to study the agreement in output, filed size factors and penumbra differences. This project is partially supported by the Varian grant under the master agreement between University of Pennsylvania and Varian.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Electronic tuning of confined sub-nanometer cobalt oxide clusters boosting oxygen catalysis and rechargeable Zn–air batteries.

Reasonable design of robust bifunctional oxygen catalysts from an electronic structure perspective is intriguing and challenging for the development of high active rechargeable zinc-air batteries (ZABs). In this study, the favorable regulation of the electronic structure of the cobalt oxide nanoclusters was firstly predicted by density functional theory (DFT) simulation, and then experimentally verified by confining sub-nanometer CoOx clusters (0.86 nm) into the small pore of ZIF-8 derived N-doped nanomaterials (PNC) using a microporous MOFs confinement strategy. The confined effect of the MOF micropores not only enhanced the stability of the subnanometer cobalt oxide clusters, but also make it coupled with Co-Nx to further regulate the electronic structure of the former, synergistic resulting in enhanced ORR/OER actives. As a result, the optimized 0.05CoOx@PNC catalyst demonstrates outstanding bifunctional oxygen performance with a smaller potential gap of 0.67 V. Moreover, the rechargeable Zn-air batteries integrated 0.05CoOx@PNC air cathode displays encouraging performance with a peak power density of 157.1 mW cm(-2), a specific capacity of 887 mAh g(Zn)(-1)at 10 mA cm(-2) and long-term cyclability for over 200 h, significantly outperforming the benchmark electrode couple consisted of Pt/C/RuO2. DFT calculation further revealed that reducing particle size and coupling with Co-N could effectively regulate the charge distribution of CoOx nanoclusters and downshift the D-band center of Co adsorption sites in CoOx nanoclusters, which reduced the reaction barrier of intermediate O-2* and OH* and ORR/ OER over potential, thus accelerating the overall ORR/OER kinetic process. This work offers a novel reference for the construction of a robust sub-nanometer cluster catalysts in the field of ZABs.

Bifunctional oxygen electrocatalysts↗

DOE OSTI2017

A Variational Nodal Approach to 2D/1D Pin Resolved Neutron Transport for Pressurized Water Reactors

A two-dimensional/one-dimensional (2D/1D) variational nodal approach is presented for pressurized water reactor core calculations without fuel-moderator homogenization. A 2D/1D approximation to the within-group neutron transport equation is derived and converted to an even-parity form. The corresponding nodal functional is presented and discretized to obtain response matrix equations. Within the nodes, finite elements in the x-y plane and orthogonal functions in z are used to approximate the spatial flux distribution. On the radial interfaces, orthogonal polynomials are employed; on the axial interfaces, piecewise constants corresponding to the finite elements eliminate the interface homogenization that has been a challenge for method of characteristics (MOC)-based 2D/1D approximations. The angular discretization utilizes an even-parity integral method within the nodes, and low-order spherical harmonics (P N ) on the axial interfaces. The x-y surfaces are treated with high-order P N combined with quasi-reflected interface conditions. Furthermore, the method is applied to the C5G7 benchmark problems and compared to Monte Carlo reference calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Barrier Function-based Reinforcement Learning for Emergency Control of Power Systems

Under voltage load shedding has been considered as a standard and effective measure to recover the voltage stability of the electric power grid under emergency and severe conditions. However, this scheme usually trips a massive amount of load which can be unnecessary and harmful to customers. Recently, deep reinforcement learning (RL) has been regarded and adopted as a promising approach that can significantly reduce the amount of load shedding. However, like most existing machine learning (ML)-based control techniques, RL control usually cannot guarantee the safety of the systems under control. In this paper, we introduce a novel safe RL method for load shedding of power systems, that can enhance the safe voltage recovery of the electric power grid after experiencing faults. Unlike standard RL method, the safe RL method integrates a Barrier function into the reward function. Consequently, the optimal control policy can render the power system to avoid the safety bounds. This method is general and can be applied to other safety-critical control problems. Numerical simulations on the 39-bus IEEE benchmark is performed to demonstrate the effectiveness of the proposed safe RL emergency control, as well as its adaptive capability to faults not seen in the training.

Vu, Thanh Long↗