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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

A Network of Field-Calibrated Low-Cost Sensor Measurements of PM2.5 in Lomé, Togo, Over One to Two Years

Air pollution is a leading cause of global premature mortality and is especially prevalent in many low- and middle-income countries (LMICs). In sub-Saharan Africa, preliminary monitoring networks, satellite retrievals of air-quality-relevant species, and air quality models show ambient fine particulate matter (PM 2.5 ) concentrations that far exceed the World Health Organization guidelines, yet many areas remain largely unmonitored and understudied. Deploying a network of five low-cost PurpleAir PM 2.5 monitors over 2 years (2019–2021), we present the first multiyear ambient air pollution monitoring data results from Lomé, Togo, a major West African coastal city with a population of about 1.4 million people. The full-study time period network-wide mean measured daily PM 2.5 concentration is 23.5 μ g m –3 m –3 . The strong regional influence of the dry and dusty Harmattan wind increases the local average PM 2.5 concentration by up to 58% during December through February, but the diurnal and weekly trends in PM 2.5 are largely controlled by local influences. At all sites, more than 87% of measured days exceeded the new WHO Daily PM 2.5 guidelines; these first measurements highlight the need for air quality improvement in a rapidly growing urban metropolis.

air pollution↗
DOE OSTI2026

Local Air Quality Impacts of a Peak-Shaving Diesel Generator Unit in Waynesville, North Carolina

The Waynesville Electric Department in Waynesville, North Carolina, operates a 2,000-kW diesel generator with a 4% capacity factor, emitting less than 1 ton annually of PM2.5, VOCs, carbon monoxide (CO), and sulfur dioxide (SO2), and approximately 1.8 tons of NO. The National Laboratory of the Rockies (NLR) conducted high-resolution, near-source air-quality modeling to evaluate the generator's impacts. Results indicate minimal effects on ambient pollutant concentrations: annual PM2.5 increases are below 0.0004 microgrm/m3 for local census tracts, while CO and SO2 levels increase by less than 0.00004 ppm and 0.0002 ppb, respectively. Estimated annual premature mortality attributable to PM2.5 exposure is less than 0.001 cases across Haywood County, with an associated economic impact of approximately $12,000. This report complements a separate technoeconomic analysis to inform Waynesville's investment strategies for demand reduction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1947

Estimated Flying Qualities of the Martin Model 202 Airplane

The flying qualities of the Martin model 202 airplane have been estimated chiefly from the results of tests of an 0.0875-scale complete model with power made in the Wright Brothers tunnel at the Massachusetts Institute of Technology and from partial span wing and isolated vertical tail tests made in the Georgia Tech Nine-Foot Tunnel. These estimated handling qualities have been compared with existing Army-Navy and CAA requirements for stability and control. The results of the analysis indicate that the Martin model 202 airplane will possess satisfactory handling qualities in all respects except possibly in the following: The amount of elevator control available for landing or maneuvering in the landing condition is either marginal or insufficient when using the adjustable stabilizer linked to the flaps . Moreover, indications are that the longitudinal trim changes will be neither large nor appreciably worse with a fixed stabilizer than with the contemplated arrangement utilizing the adjustable stabilizer in an attempt to reduce the magnitude of the trim changes caused by flap deflection.

Weil, Joseph↗
DOE OSTI2026

From bulk to surface: Structure and dynamics of amorphous alumina from deep potential molecular dynamics

Understanding the atomic-scale structure and dynamics of amorphous oxide surfaces is essential for interpreting their chemical reactivity, mechanical stability, and interfacial behavior, yet direct experimental characterization remains challenging. We employ Deep Potential (DP) molecular dynamics to generate large-scale, ab initio -quality models of amorphous Al 2 O 3 bulk glasses and melt-quenched free surfaces, enabling a quantitative analysis of both structure and relaxation dynamics with statistical confidence inaccessible to direct ab initio simulation. The trained DP model reproduces experimental liquid and glass structure, captures the cooling-rate dependence of the bulk glass transition, and corrects systematic biases in the polyhedral populations predicted by widely used classical force fields. At the free surface, mass density recovers to bulk values over ~10 Å, while local coordination requires a slightly wider subsurface region to fully converge. The outermost layer is oxygen-enriched, exhibits altered polyhedral connectivity with contracted Al–O bonds, and hosts a broad population of under-coordinated motifs (notably AlO 3 and OAl 2 ) whose abundances are governed by glass stability. These under-coordinated surface motifs exhibit distinct vibrational signatures and occur as locally paired Lewis acid and Brønsted base sites consistent with bond-valence compensation, yet remain spatially dispersed rather than aggregating into extended clusters. Despite this pronounced structural heterogeneity, surface relaxation and the glass-transition temperature remain comparable to their bulk counterparts, suggesting that the disordered surface is kinetically stable once formed. Together, these results establish a molecular-level picture of amorphous alumina surfaces and demonstrate the capability of machine-learned potentials to resolve structure–property relationships in disordered oxide interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effects of residue removal and tillage on greenhouse gas emissions in continuous corn systems as simulated with RZWQM2

Agricultural production is a major source of carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) globally. The effects of conservation practices on soil CO 2 and N 2 O emissions remain a high degree of uncertainty. In this study, soil CO 2 and N 2 O emissions under different residue and tillage practices in an irrigated, continuous corn system, were investigated using the Root Zone Water Quality Model (RZWQM2). Combinations of no/high stover removal (NR and HR, respectively) and no-till/conventional tillage (NT and CT, respectively) field experiments were tested over the four crop-years (Apr. 2011–Apr. 2015). The model was calibrated using the NRCT, and validated with other treatments. The simulation results showed that soil volumetric water content (VWC) in the NR treatments (i.e., NRCT and NRNT) was 1.3%–1.9% higher than that in the HR treatments (i.e., HRCT and HRNT) averaged across the four years. A higher amount of CO 2 and N 2 O emissions were simulated in the NRCT across the four years (annual average: 7034 kg C/ha/yr for CO 2 and 3.8 kg N/ha/yr for N 2 O), and lower emissions were in the HRNT (annual average: 6329 kg C/ha/yr and 3.7 kg N/ha/yr for N 2 O). A long-term simulation (2001–2015) suggested that the CO 2 and N 2 O emissions were closely correlated with the stover removal degree (SRD), tillage, VWC, soil temperature (ST), years in management (Y), and fertilizer application. Stover and tillage practices had cumulative effects on CO 2 emissions. The simulated annual CO 2 emissions in 1st year from NRCT, NRNT, and HRCT were 7.8%, 0.0%, and 7.7% higher than that from HRNT, respectively; then the emissions in 15th year were 63.6%, 47.7%, and 29.1% higher, respectively. Meanwhile, there were no cumulative effects on N 2 O emissions. Furthermore, the results also demonstrated that the RZWQM2 is a promising tool for evaluating the long-term effects of CO 2 and N 2 O emissions on different conservation practices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Responses of gaseous sulfuric acid and particulate sulfate to reduced SO 2 concentration: A perspective from long-term measurements in Beijing

SO 2 concentration decreased rapidly in recent years in China due to the implementation of strict control policies by the government. Particulate sulfate ( p S O 4 2 - ) and gaseous H 2 SO 4 (SA) are two major products of SO 2 and they play important roles in the haze formation and new particle formation (NPF), respectively. We examined the change in p S O 4 2 - and SA concentrations in response to reduced SO 2 concentration using long-term measurement data in Beijing. Simulations from the Community Multiscale Air Quality model with a 2-D Volatility Basis Set (CMAQ/2D-VBS) were used for comparison. From 2013 to 2018, SO 2 concentration in Beijing decreased by ~81% (from 9.1 ppb to 1.7 ppb). p S O 4 2 - concentration in submicrometer particles decreased by ~60% from 2012–2013 (monthly average of ~10 μg·m - 3 ) to 2018–2019 (monthly average of ~4 μg·m - 3 ). Accordingly, the fraction of p S O 4 2 - in these particles decreased from 20–30% to <10%. Increased sulfur oxidation ratio was observed both in the measurements and the CMAQ/2D-VBS simulations. Despite the reduction in SO 2 concentration, there was no obvious decrease in SA concentration based on data from several measuring periods from 2008 to 2019. This was supported by the increased SA:SO 2 ratio with reduced SO 2 concentration and condensation sink. NPF frequency in Beijing between 2004 and 2019 remains relatively constant. Finally, this constant NPF frequency is consistent with the relatively stable SA concentration in Beijing, while different from some other cities where NPF frequency was reported to decrease with decreased SO 2 concentrations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Advances in Kriging-Based Autonomous X-Ray Scattering Experiments

Autonomous experimentation is an emerging paradigm for scientific discovery, wherein measurement instruments are augmented with decision-making algorithms, allowing them to autonomously explore parameter spaces of interest. We have recently demonstrated a generalized approach to autonomous experimental control, based on generating a surrogate model to interpolate experimental data, and a corresponding uncertainty model, which are computed using a Gaussian process regression known as ordinary Kriging (OK). We demonstrated the successful application of this method to exploring materials science problems using x-ray scattering measurements at a synchrotron beamline. Here, we report several improvements to this methodology that overcome limitations of traditional Kriging methods. The variogram underlying OK is global and thus insensitive to local data variation. We augment the Kriging variance with model-based measures, for instance providing local sensitivity by including the gradient of the surrogate model. As with most statistical regression methods, OK minimizes the number of measurements required to achieve a particular model quality. However, in practice this may not be the most stringent experimental constraint; e.g. the goal may instead be to minimize experiment duration or material usage. We define an adaptive cost function, allowing the autonomous method to balance information gain against measured experimental cost. We provide synthetic and experimental demonstrations, validating that this improved algorithm yields more efficient autonomous data collection.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. In this study, the three-dimensional electron density of a protein, as it would be determined by cryo-EM or x-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work employs the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along the chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along the reaction coordinates derived from electron densities can capture conformational transitions between known intermediates. The simulated pathways appear reversible with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein Data Bank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution density information coupled to comparatively large structural transitions. Practical considerations for probing the transitions between multiple intermediate density states are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires

In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.

O'Neill, Susan↗
DOE OSTI2022

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances—Part 3: Optical properties of black and brown carbon emissions

Residential biomass combustion is a source of carbonaceous aerosol. Inefficient combustion, particularly of solid fuels produces large quantities of black and brown carbon (BC and BrC). These particle types are important as they have noted effects on climate forcing and human health. One method of measuring these quantities is by measurement of aerosol light-absorption and scattering, which can be performed using an aethalometer and nephelometer, respectively. These instruments are widely deployed in the study of ambient air and are frequently used in air quality modeling and source apportionment studies. In this study, we will describe (1) a method for measuring primary BC and BrC emissions from two residential log-fired wood hydronic heaters and (2) the BC and BrC emission from these devices over a wide range of operating conditions, such as cold-starts, warm-starts, four different levels of output ranging from 15% to 100% maximum rated output, and periods of repeated cycling. The range in flue-gas BC concentrations, measured using an aethalometer at the 880 nanometer (nm) wavelength, were between 5.09 × 10 2 and 2.24 × 10 4 micrograms per cubic meter (µg/m 3 ) while the scattering coefficient of the flue-gas, measured by a nephelometer at 880 nm, ranged between 2.20 × 10 3 and 8.56 × 10 5 inverse megameters (Mm –1 ). The BrC concentrations, measured using the 370 nm wavelength of an aethalometer, were between 9.10 × 10 1 and 3.56 × 10 4 µg/m 3 . The calculated Angstrom Absorption Exponent (AAE) of the flue-gas aerosol ranged between 1.54 and 3.63. Performing a comparison between the measured BC concentration and an external particulate matter (PM) concentration showed that overall BC makes up roughly a quarter of the PM emitted by either of the two appliances. Further for both appliances, the cold-start and the test phase immediately following it had the highest BC and BrC concentrations, the highest measured scattering coefficient, as well as a low AAE.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Hennessy, Eleanor M. (ORCID:0000000294715765)↗
DOE OSTI2024

Mortality attributable to PM 2.5 from wildland fires in California from 2008 to 2018

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM 2.5 ), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM 2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM 2.5 estimates. We used a concentration-response function for PM 2.5 , applying ZIP code–level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM 2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $\$432$ to $\$456$ billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Scalable Federated Learning for Scientific Foundation Models on Leadership-Class Systems

Federated learning (FL) at leadership-class HPC systems remains largely unexplored, despite growing interest in deploying federated workflows on modern HPC systems. This paper provides the first system-level empirical characterization of federated fine-tuning of pretrained foundation models on an exascale supercomputer under a multi-node deployment. Using up to 96 concurrent FL clients deployed across Frontier nodes, we study the impact of client scale, model size, data heterogeneity, partial participation, and differential privacy on runtime, communication overhead, and convergence stability. Our results show that pretrained transformer models remain robust to heterogeneity, client dropout, and privacy noise, while system efficiency degrades rapidly with scale as synchronizat and orchestration dominate runtime. We further demonstrate that system-aware execution strategies, including intra-node aggregation and early aggregation, significantly reduce wall-clock time without degrading model quality. These findings establish a practical performance baseline and inform the design of communication-efficient FL systems on leadership-class HPC platforms.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
DOE OSTI2026

2000 Knoxville Urban Area Household Travel Behavior Survey

This survey, conducted by NuStats, was a comprehensive study of travel behavior in Knox and Blount counties in the Knoxville urban area. The purpose of the survey was to collect weekday travel characteristics of household members (ages five and older) in the counties during a 24-hour timeframe. The data will be used by the Knoxville Urban Area Metropolitan Planning Organization and local agencies to update transportation and air quality models and to identify transportation needs in the region. The survey was conducted between November 2000 and February 2001. In total, 2,674 households were recruited to participate in the survey. Of these, 1,538 households reported data from a one-day travel log, totaling 12,631 trips by 3,522 persons. Of all trips originating in the study area, three-fourths were made by persons residing in Knox County.

1Hz data↗
DOE OSTI2026

2008 East Tennessee Household Travel Survey

The 2008 East Tennessee Household Travel Survey, conducted by NuStats, was a comprehensive study of travel behavior in Knox, Blount, Anderson, Jefferson, Loudon, Roane, Sevier, and Union counties. The purpose of the survey was to collect weekday travel characteristics of households in the eight-county region during a 24-hour timeframe. The data will be used by the Knoxville Regional Transportation Planning Organization and local agencies to update transportation and air quality models and to identify transportation needs in the region. The survey collected demographic and travel data from a sample of 1,400 households between February and May 2008. In total, 12,012 trips were reported by 3,301 persons.

1Hz data↗
DOE OSTI2020

Improved Advanced Biomass Logistics Utilizing Woody and other Feedstocks in the Northeast and Pacific Northwest (Final Report)

Willow and poplar short rotation woody crops (SRWC) have shown promise with regards to environmental benefits and rural development but wide adoption lags due to underdeveloped markets and supply systems. High costs associated with harvesting, handling and transportation (40-60% of delivered cost) have impeded expansion. A better understanding of these systems will create opportunities to improve efficiency, reduce costs, and realize environmental benefits and impacts. The project’s goal was to lower the delivered cost of hybrid poplar in the Northwest and willow in the Northeast by optimizing harvesting and logistics supply systems while maintaining or improving biomass quality along the supply chain. Over 3,400 Mg of biomass and 300 ha of willow and poplar were monitored over a range of crop and field conditions. Feedstock quality as affected by storage and preprocessing were shown to improve or maintain feedstock quality. Modeled harvesting costs ranged from $38–61 Mg -1 dry; when including delivery and preprocessing feedstock costs ranged between $79-83 Mg -1 dry for willow and $106-116 Mg -1 dry for poplar. Costs for willow minimized when hot water extraction and high-moisture densification preprocessing were used. Models also suggest that social and regional factors could further reduce costs. Results will give guidance to feedstock growers, harvesting and logistic operations, biorefinery project developers, and policy makers developing SRWC to support a growing bioeconomy.

, biomass↗
DOE OSTI2022

Expansion of the ORNL VALID Library [Slides]

VALID continues as a library of high-quality models used for testing SCALE and nuclear data. Recent expansion of VALID was the largest impactful change in a decade. Adding 233 U experiments circa 2017 added more cases. There are a huge number of cases in the pipeline, but a lack of qualified staff and funding to complete reviews. Future plans should simplify the process and increase the availability of models and results for external users.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Expansion of the Verified, Archived, Library of Inputs and Data (VALID) [Slides]

This project dialogue provides an update on the Expansion of Verified, Archived, Library of Inputs and Data or VALID. VALID is a QA-Like (Quality Assurance) process to generate high quality models from reliable reference descriptions and make those models available to users. This presentation provides a brief project overview, a reminder of cases added in FY2021, cases currently in progress, and future plans for VALID.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗