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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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32 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Clacc: OpenACC for C/C++ in Clang

The Clacc project has developed OpenACC compiler, runtime, and profiling interface support for C/C++ by extending Clang and LLVM. A key Clacc design feature is that it translates OpenACC to OpenMP to leverage the OpenMP offloading support that is actively being developed for Clang and LLVM. A benefit of this design is support for two compilation modes: traditional compilation mode produces a binary, and source-to-source mode produces OpenMP source. Clacc has been deployed on Oak Ridge National Laboratory’s (ORNL’s) Frontier, on which Clacc is the only OpenACC implementation for C/C++. Clacc supports x86_64, POWER9, AMD GPUs, and NVIDIA GPUs. Clacc’s OpenACC profiling interface support has been integrated with TAU, which is also deployed on Frontier. While Clacc has always supported C as a base language, Clacc also has increasing C++ support, including support for Kokkos’s OpenACC back end. Clacc itself is hosted publicly on GitHub. In this paper, we describe Clacc’s design and mapping from OpenACC directives to OpenMP. We also present a performance evaluation on ORNL’s Frontier (AMD MI250x GPU offload) and Argonne National Laboratory’s (ANL’s) Polaris (NVIDIA A100 GPU offload) for various SPEC ACCEL and Kokkos OpenACC back end benchmarks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Detector Response and Battery Reliability

The Sandia National Laboratories (SNL) Material Control and Accountability (MC&A) measurements team performs confirmation measurements of Special Nuclear Material (SNM) at different locations around Sandia. The measurement team has access to two High purity Germanium (HPGe) detectors, the AEGIS (Model: AEGIS-BEGE5030), and the ORTEC (Model: trans-SPEC-DX-100). These two can operate purely on battery power, but the response of the detectors while on battery power is not well documented. To enhance our knowledge with these detectors the team wants to investigate the detectors response to changes in battery range, wall charging, and mid operation battery swaps (Hot Swaps).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Low-Temperature Plasma-Based Metrology of Lithium-Ion Battery Electrode Materials (CRADA Final Report)

As part of the Cyclotron Road program, SirenOpt Inc. evaluated its low-temperature plasma-based metrology sensor prototype for measuring multiple critical properties of lithium-ion battery electrode materials in parallel and in real-time. Cost-effective, minimal-waste manufacturing of high-performance battery electrode materials will be vital for achieving society’s net-zero carbon emission goals. Because existing electrode metrology sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products and detect problems. When manufacturers perform these offline tests, they typically only test a small portion of the manufactured products. Current electrode manufacturing thus often yields many low-quality products, or off-spec products that must be thrown away all together. For example, at least 6% of the total lithium-ion battery manufacturing cost (i.e., over $250 million/year for the average gigafactory) is devoted to processing defective electrodes that are not scrapped until performance tests are failed during late-stage quality control checks. Electrode variability also leads manufacturers to build extra cells into battery packs to reduce the risk of poor performance. For example, many electric vehicle (EV) manufacturers include up to 10% more cells than needed, which substantially increases the cost and weight of the final EV product. The SirenOpt sensor can potentially enable early detection of poorly manufactured electrodes and allow them to be removed earlier from manufacturing lines, which can save battery manufacturers (hundreds of) millions of dollars per year. The sensor can further be used to improve product quality by accelerating R&D and process optimization, improving quality control, and enabling real-time process control. Overall, a real-time, in-situ metrology strategy can create unprecedented opportunities for implementation of smart manufacturing practices and advanced quality and process control solutions to realize higher battery electrode throughput and performance.

25 ENERGY STORAGE↗
DOE OSTI2026

Laboratory Testing of Portable Air Cleaner Products for Energy Efficiency and Clean Air Performance at Various Fan Settings [Slides]

This document contains the results of a product review and laboratory testing experiment of portable air cleaning devices (PACs). Thirty-four commercially available PACs were reviewed, and from those, 7 products were purchased and underwent AHAM AC-7 clean air delivery rate (CADR) testing. The following research questions were explored: 1) What is the relationship between clean air delivery rate (CADR) and energy across a range of products and what is the general decrement in CADR as a result of operating at lower fan speeds? 2) How might the multiple units at lower power compare to fewer, larger units at full power in terms of energy efficiency and total cost? 3) How do the measured CADR, power, and efficiency compare to the manufacturer specs? 4) Are there product attributes that can be identified that might contribute to better CADR/W performance?

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Calibration of the Nonlinear Viscoelastic SPECtacular Model for 828-CTBN/DEA/GMB and 828/Z/AlOx

Nonlinear viscoelastic model calibrations are developed for two filled epoxies: an adduct of Epon 828 DGEBA and CTBN cross-linked with diethanolamine (DEA) filled with glass microballoons, called 828-CTBN/DEA/GMB, and Epon 828 DGEBA cross-linked with Ancamine Z and filled with alumina, called 828/Z/AlOx. The thermo-mechanical responses of these materials are represented using the SPECtacular constitutive model, an extension of the Simplified Potential Energy Clock (SPEC) model. The model couples

Cundiff, Kenneth Noel [Sandia National Laboratorie↗
DOE OSTI2024

Upcycling of Mixed Aluminum Alloy Shredder Scrap using Shear Processing

Conservation of critical materials is an increasing area of focus in the Unites States. In 2023, aluminum was added to the US Department of Energy Final Critical Materials List which has spurred public and private research into sustainable management of these resources. Additionally, efficiency in manufacturing and conservation of natural resources are growing concerns with targets to lower global carbon emissions, as primary aluminum alloy production is energy intensive, requiring 14 MWh of electricity plus 0.4 tonnes of CO2 per tonne of Al. Due to these factors, is essential that more sustainable manufacturing methods for aluminum alloys are developed going forward. To this end, much research is ongoing on the topic of more efficient utilization and recovery. However, most of this research still requires primary aluminum in the production process. Here, it will be attempted to bypass the use of primary aluminum and produce useful material recycled from 100% post-consumer scrap. Even considering recent developments in recycling of Al scrap, there is still a large amount of post-consumer scrap that is underutilized due to high impurity content, and that amount will increase significantly as more and more aluminum alloys are utilized in vehicles. This “scrap wave” is expected to cover 80% of the demand for automotive aluminum alloys by 2050 . A challenge to be addressed before the coming scrap wave can be fully utilized is that the tolerance of manufacturing techniques to impurities or off-spec alloy compositions must be increased. Particularly, in 5000-and 6000-series alloys (the most common wrought alloys in durable products), excess iron, copper, and silicon create brittle intermetallics during casting that remain in the extruded microstructure which limit the formability, ductility, and corrosion resistance of the alloy. Concerningly, many of the highest-volume post-consumer aluminum scrap streams such as automotive shredder scrap contain a mix of alloys including both wrought and cast alloys. Their compositions can vary widely depending on geography and the time of year. Because they are mixed, they often contain high content of multiple alloying elements such as Si and Cu in higher concentrations than are found in typical wrought alloys. They may also be contaminated with non-Al alloys from fasteners that get mixed in and often have high content of unwanted elements such as Fe. As a method for utilizing these underused scrap streams that are high in tramp elements, an emerging extrusion technology is being developed at the Pacific Northwest National Laboratory (PNNL) that aims to upcycle 100% post-consumer aluminum scrap directly into extruded components without the addition of primary aluminum . This new technology, called Shear Assisted Processing and Extrusion (ShAPE), is enabling a shift away from today’s recycling paradigm by reaching deeper into lower-value scrap streams, using shredder scrap as the extrusion billet material. Sometimes referred to as Twitch or Tweak, these scrap streams result from shredding and sorting of automobiles, building materials, appliances, and consumer goods. ShAPE combines the linear axis of conventional extrusion with a rotating extrusion die. This rotating die applies large strain to the material during extrusion, which breaks up large impurity-containing intermetallic particles, reducing their deleterious effects. This has been demonstrated for 6063 machining scrap spiked with excess Fe, and Twitch scrap high in Fe, Si and Cu where strength and ductility were retained for both feedstock compositions. Additionally, the extreme plastic deformation during ShAPE enables extrusion of billets with high Si that are too brittle for processing by conventional extrusion. By using 100% post-consumer shedder scrap as feedstock, ShAPE has the potential to slash embodied energy and carbon in extruded components by >80% compared to conventional extrusion of primary aluminum alloys.

Milligan, Brian K.↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗
DOE OSTI2024

LSAFE: a Lightweight Static Analysis Framework for binary Executables

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

Qu, Guangzhi↗
DOE OSTI2025

Future TRISO fuel irradiations in the Advanced Test Reactor

AGR-5/6/7 was thought to be the last experiment in the AGR series and the last experiment directly sponsored by DOE. Over the last five years three developments have caused a reevaluation of that assumption. First is that interest in TRISO fueled reactors has spiked dramatically. Virtually all of the new reactor designs are for SMRs or micro-reactors . Some of these reactors use new fuel designs with higher concentrations of U235. This results in changes to the particle design and even fuel pellet design. Second, a design flaw in AGR-5/6/7 Capsule 1 produced a large number of particle failures which resulted in the loss of data from Capsule 1. An additional irradiation could fill in this lost data set. Thirdly, many reactor developers have decided to use AGR spec fuel but different irradiation goals have been identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

SimPoint++: Less Simulation Points

We propose SimPoint++, which replaces the BIC method by combining WCSS and Silhouette to find the optimal cluster. The new Python framework of SimPoint++ provides a dimension reduction pipeline for effective clustering and supports multi-thread application analysis. We evaluate SimPoint++ with Spec CPU 2017 benchmarks. SimPoint++ achieves comparable or higher accuracy with significantly fewer simulation points, resulting in a 5x speed-up in simulation time compared to state-of-the-art solutions.

Chen, Si↗
DOE OSTI2026

Developing a Digital Twin for SRF Cavity Assembly at Fermilab

When assembling Superconducting Radio Frequency (SRF) Cavities, maintaining an environment devoid of particulates like dust and other small particles is essential. If a single spec of dust enters the cavity a significant degradation of performance can occur. To avoid a cavity failure Fermilab assembles the SRF cavities within a ISO-4 (Class 10) environment. This environment though is still susceptible to foreign contaminants when technicians enter and new components are added to the cleanroom. To reduce the risk even more Fermilab has introduced a cobot manipulator into the cleanroom environment to speed up the assembly time which will reduce the time that the technicians operate in the cleanroom. But, this still leaves the potential of contaminants to enter the cleanroom if new components need to be tested within the cleanroom. This project aims to lay the groundwork to develop a Digital Twin environment of the cleanroom to aid in manufacturing processes and testing. In its simplest form, a digital twin is a bidirectional link between a physical system and its digital counterpart or twin. NVIDIA Isaac Sim is used as the digital twin foundation for the digital representation of the cleanroom, specifically for the UR16e assembly area. A simulated UR16e was used to validate the performance of Isaac Sim as a testing environment by comparing the tool center points (TCP) positional data between the simulated and digital representation of the UR16e. Due to a new vision based robotic assembly process being introduced to the cleanroom a digital representation of the physical camera was tested and validated to ensure that it will produce close to the same outcome as the physical environment. The TCP comparison results showed a peak translational error of approximately 0.1mm and rotational errors of up to 8 between the simulated and digital UR16es. While the camera validation performed with high repeatability across multiple runs, it still requires minor tuning before it can accurately replicate a physical camera.

Imburgia, Joseph [Northern Illinois U.]↗
DOE OSTI2025

On the Role of Airborne Ice Nucleating Particles in Primary and Secondary Ice Formation Processes in Convective Midlatitude Clouds

Abstract Formation of ice in mixed-phase clouds may proceed via primary nucleation and secondary ice production (SIP). Primary nucleation involves the presence of ice nucleating particles (INPs), while SIP follows primary nucleation, resulting in ice crystal number concentrations N ice exceeding the number of INPs. The ice formation pathways in young congestus clouds are not well understood nor are the environmental conditions favorable for the onset of SIP. Coincident airborne measurements of INPs and N ice collected during the Secondary Production of Ice in Cumulus Experiment (SPICULE) campaign over the U.S. central Great Plains are reported for young congestus clouds. Number concentrations of INPs and N ice at temperatures between −10° and −20°C were used to categorize whether SIP was active in each analyzed cloud pass. Observational data suggested that fragmentation of freezing droplets (FFDs) was occurring and the most likely SIP mechanism for ice enhancement during the early stages of the sampled clouds, where higher cloud-base temperatures and stronger updrafts produced conditions favorable for the onset of FFD. Simple model simulations of a congestus cloud were used to compare predictions of N ice from newly implemented SIP mechanisms (including FFD) alongside those from the existing Hallett–Mossop (HM) mechanism. Although predicted N ice , when all SIP mechanisms were active, was in good agreement with observations, the dominant SIP mechanism in the model was predicted to be HM. The rate of heterogeneous freezing in raindrops was likely inhibiting realistic FFD rates in the simulated cloud. These discrepancies between the observations and simulations underscore the need for extended laboratory studies to formulate improved model representations of SIP in convective clouds.

Patnaude, Ryan J. [Department of Atmospheric Scien↗
DOE OSTI2025

Unveiling the Mechanism of Mn Dissolution Through a Dynamic Cathode‐Electrolyte Interphase on LiMn2O4

Abstract Understanding the formation and evolution of the cathode‐electrolyte interphase (CEI), which forms at the interface between the cathode and electrolyte, is crucial for revealing degradation mechanisms in cathode materials, especially for developing strategies to stabilize the interphase in the strongly oxidizing conditions that evolve at high operating voltages in next‐generation Li‐ion batteries. However, The present understanding of the CEI is challenged by its complex and dynamic nature. In this work, near‐edge X‐ray absorption fine structure spectroscopy, electrochemical characterization, and reactive molecular dynamics simulations are combined to reveal a mechanism for CEI formation and evolution above model LiMn 2 O 4 (LMO) thin‐film electrodes in contact with conventional carbonate‐based electrolytes. It is found that Mn dissolution from LMO can be understood in terms of repetitive Mn 3 O 4 formation and dissolution behavior during cycling, which is closely connected to electrolyte decomposition and a key aspect of the CEI formation and growth. The behavior of the CEI in this model system offers detailed insight into the dynamic chemistry of the interphase, underscoring the important role of electrolyte composition and cathode surface structure in interphase degradation.

Ou, Wenhan↗
DOE OSTI2025

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗