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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Cooling efficiency of a spot-type personalized air-conditioner

Here, this study defined Cooling Efficiency ( CE ) of a Spot-type Personalized Air-Conditioning (SPAC) device as the ratio of the additional sensible heat removal from human body induced by SPAC and the device's cooling capacity. CE enabled the investigation of SPAC performance on the occupant's sensible heat loss (Q s ) and thermal sensation by its quantitative relation with the change of PMV level ( ΔPMV ). Three round nozzles with the diameter of 0.08 m, 0.105 m, and 0.128 m, respectively, discharged air jets at airflow rates from 11.8 L s –1 to 59.0 L s –1 , toward the chest of a seated or standing human body with a clothing of 0.48 clo. This study developed a validated CFD model coupled with the Fanger's thermoregulation model, to calculate Q s in a room of 26 °C ventilated at a rate of 3 ACH. According to the results, Q s , CE and draft risk ( DR ) at face had significant positive linear correlation with the SPAC device's supply airflow rates (R2 >0.96), and a negative linear correlation for ΔPMV. With DR = 20% at face, CE was always under 0.3, and ΔPMV was around -1.0–1.1. Interestingly, both CE and ΔPMV had the least favorable values for the air jet produced by the nozzle with the diameter of 0.105 m independent of body posture. In conclusion, although SPAC could lead to additional Q s by sending air at a higher airflow rate from a smaller nozzle, the improvement in cooling efficiency and thermal sensation had a limit due to draft risk.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Long-term carbon emission reduction potential of building retrofits with dynamically changing electricity emission factors

Buildings account for approximately 36% of the United States' total carbon emissions and building retrofits have great potential to reduce carbon emissions. Current research adopts a constant electricity emission factor although it changes over time due to the increase of renewable energy generation. Here, to accurately predict emission reduction potential of building retrofits, this study develops a novel method by using dynamically changing electricity emission factors. Using medium office buildings as an example, we predicted emission reduction of eight building retrofit measures from 2020 to 2050 in five locations in the U.S. with distinct climates and renewable adoption rates. To evaluate emission reduction potential sensitivity to the compositions of electricity generation, five scenarios for renewable energy adoptions are investigated. The results reveal several new phenomena on emission reduction potential of building retrofits for medium offices in the U.S.: (1) it decreases from 2026 to 2050; (2) it has the same trend with coal usage; and (3) it reaches the maximum under the high renewable cost scenario. Based on the results, it is recommended that building retrofits should focus on 1) improving lighting and equipment efficiency; 2) locations with higher coal usage rate, and 3) buildings under the high renewable cost scenario. The new method can also be used for predicting emission reduction potential of the building sector in the U.S. by applying to other building types and regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Intrinsic kinetics of water-inhibited ultra-lean methane oxidation over PtPd-Mg/ θ -Al 2 O 3 catalyst

Here, this study develops intrinsic methane oxidation kinetics for ultra-lean methane conditions in the presence of water over a highly active and stable PtPd–Mg/θ-Al 2 O 3 catalyst. Comprehensive laboratory experiments were conducted over a wide range of methane concentrations (150–1200 ppm CH 4 ), water contents (1–5% H 2 O), and industrially relevant space velocities (80,000 ≤ GHSV ≤ 160,000 h -1 ). These systematic experiments informed a two-dimensional, axisymmetric, multiscale reactor model that was used to develop and validate methane oxidation kinetics under practically relevant conditions, including non-isothermal operation and high conversion regimes. Combined experimental and modeling results revealed significant intraparticle diffusion resistance and transport-induced reaction exotherm at elevated temperatures, which limited catalyst utilization despite high intrinsic activity. These transport effects were explicitly incorporated into the reactor model, enabling accurate estimation of intrinsic kinetic parameters without reliance on conventional effectiveness-factor corrections. The resulting kinetic model successfully captured both kinetically controlled and mass-transfer-limited regimes and reliably predicted CH 4 conversion across broad ranges of temperature, methane concentration, and water content

Heat and mass transfer limitations↗
DOE OSTI2025

A cradle-to-grave life-cycle-assessment of dry-processed Li-ion batteries for electric vehicles

Maxwell-type dry processing has emerged as a promising manufacturing technology for high-areal-loading Li-ion battery electrodes, offering a significant advantage by eliminating the use of the toxic and costly NMP solvent. This study developed a cradle-to-grave life-cycle-assessment model to evaluate the environmental impacts of this innovative technology, benchmarking the results against the conventional NMP-based technique for a configured 42 kWh NMC622-graphite battery pack. Furthermore, the findings reveal that the dry-processing method merits a 4.8% lower energy consumption and achieves environmental impacts up to 47.5% lower in 12 out of 13 categories, highlighting its environmental benefits compared with the NMP-based manufacturing processes.

Electrode↗
DOE OSTI2023

Advances and prospects to achieve high-performing and durable proton-exchange-membrane unitized regenerative fuel cells

Proton-exchange-membrane unitized regenerative fuel cell (PEM-URFC) is a promising energy storage and conversion device for large-scale and long-term applications. Previous research has primarily focused on materials development studies, with performance and durability not evaluated at relevant conditions. Such an approach becomes insufficient for making URFC technology commercially competitive. In this review, we highlight recent progress on high-performing PEM-URFCs, focusing on electrode engineering, key components, and operating approaches that take realistic operating conditions into consideration. Key components of a membrane electrode assembly (MEA), including catalyst layer, diffusion media, and membrane, which require different optimization strategies, are discussed in this review.

25 ENERGY STORAGE↗
DOE OSTI2016

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on renewable power energy sources. Biomass supply chain design and operational planning models are often formulated and studied using deterministic mathematical models. While these models are beneficial for making decisions, their applicability to real world problems may be limited because they do not capture all the complexities in the supply chain, including uncertainties in the parameters. This study develops a statistically robust quantile-based approach for stochastic optimization under uncertainty, which builds upon scenario analysis. We apply and evaluate the performance of our approach to address the problem of analyzing competing biomass supply chains subject to stochastic demand and supply. Finally, the proposed approach was found to outperform alternative methods in terms of computational efficiency and ability to meet the stochastic problem requirements.

09 BIOMASS FUELS↗
DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Damage progression and failure of SiC/SiC composite tubes under hard-contact radial expansion

The response of silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composite cladding to mechanical interaction with fissile fuel is a knowledge gap that must be overcome to design and assess SiC-based cladding systems for advanced nuclear applications. This study developed the relevant mechanical testing capability and identified the failure behavior and the critical microstructural features and processing defects. Sections of SiC composite tube were subjected to a modified expansion-due-to-compression (EDC) test in an X-ray computed tomography microscope: a polyurethane plug pressed surrogate Al 2 O 3 into the inner walls of the SiC/SiC composite tubes to achieve hard contact. A pure EDC test with just a polyurethane plug was also performed as a reference. Through the use of displacement fields, digital volume correlation revealed inhomogeneous deformation fields in the tubes, even for pure EDC, which was related to the inherent defects in the structure. Deep learning–aided segmentation and systematic data analysis revealed that the presence of inhomogeneous deformation applied by the hard contact was exaggerated by the presence of inner surface imperfections left behind from the matrix densification process. In conclusion, the findings provide insights into the applications, highlighting the necessity for improvements in inner surface roughness and the incorporation of localized contacts in pellet–cladding mechanical interaction computational models.

Composites↗
DOE OSTI2022

Typological representation of the offshore oceanographic environment along the Alaskan North Slope

Erosion and flooding impacts to Arctic coastal environments are intensifying with nearshore oceanographic conditions acting as a key environmental driver. Robust and comprehensive assessment of the nearshore oceanographic conditions require knowledge of the following boundary conditions: incident wave energy, water level, incident wind energy, ocean temperature and salinity, bathymetry, and shoreline orientation. The number of offshore oceanographic boundary conditions can be large, requiring a significant computational investment to reproduce nearshore conditions. This present study develops location-independent typologies to reduce the number of boundary conditions needed to assess nearshore oceanographic environments in both a Historical (2007–2019) and Future (2020–2040) timespan along the Alaskan North Slope. We used WAVEWATCH III® and Delft3D Flexible Mesh model output from six oceanographic sites located along a constant ~50 m bathymetric line spanning the Chukchi to Beaufort Seas. K-means clustering was applied to the energy-weighted joint-probability distribution of significant wave height (H s ) and peak period (T p ). Distributions of wave and wind direction, wind speed, and water level associated with location-independent centroids were assigned single values to describe a reduced order, typological rendition of offshore oceanographic conditions. Reanalysis data (e.g., ASRv2, ERA5, and GOFS) grounded the historical simulations while projected conditions were obtained from downscaled GFDL-CM3 forced under RCP8.5 conditions. Location-dependence for each site is established through the occurrence joint-probability distribution in the form of unique scaling factors representing the fraction of time that the typology would occupy over a representative year. As anticipated, these typologies show increasingly energetic ocean conditions in the future. They also enable computationally efficient simulation of the nearshore oceanographic environment along the North Slope of Alaska for better characterization of coastal processes (e.g., erosion, flooding, or sediment transport).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Long-term carbon intensity reduction potential of K-12 school buildings in the United States

School buildings have a great potential for carbon emission reduction since their annual emission is about 72 million metric tons. Currently, more than 30% of school buildings were built before 1960 and are underperforming. To effectively reduce carbon emissions via school building retrofits, it is critical for policymakers to understand the carbon intensity reduction potential of retrofitting school buildings in different regions. Hence, this study develops a method to comprehensively assess the long-term carbon intensity reduction potential of aggregated commercial buildings on a county-by-county basis in the continental U.S. We apply this method to the K-12 school buildings including primary and secondary school buildings. Here, this paper predicts the carbon intensity reduction potential of K-12 school buildings with eight building retrofit measures from 2022 to 2050 in the continental U.S. The results reveal several interesting findings: (1) In the approximately 3,000 counties of the U.S. from 2022 to 2050, the carbon intensity reduction potential of retrofitting K-12 school buildings in each county ranges from 0.41 kg/m 2 to 40.00 kg/m 2 . (2) Even in the same climate zone, the trends of carbon intensity reduction potential from 2022 to 2050 are different depending on their electricity sources. For example, in a hot and humid climate zone, the carbon intensity reduction potential in Florida will decrease from 2044 to 2048. However, in Mississippi, the carbon intensity reduction potential from 2044 to 2046 will increase due to the termination of the nuclear energy usage. (3) Generally, reducing lighting power density leads to more carbon intensity reduction in most states, but it might not be applicable for states with high clean energy penetration, such as Washington.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Active multi-mode data analysis to improve fault diagnosis in AHUs

Faults in heating, ventilation and air conditioning systems can lead to increased energy consumption, occupant comfort issues, and reduced equipment lifetime. Commercial fault detection and diagnosis (FDD) tools has been increasingly deployed in U.S. commercial buildings. While they are helping to achieve energy efficiency and operational reliability, there remain gaps in their fault diagnostic capabilities. The diagnostic results often contain multiple distinct candidate root causes (CRCs) or offer no insight into CRCs. This study developed a novel active rule-based multi-mode data analysis method to enhance diagnostic resolution by applying proven rule sets and additional new rules to data from multiple known operational modes. The proposed method was demonstrated using enhanced air handling unit performance assessment rule sets and validated with the simulated data of two air handling units. New metrics, namely, reduced number of CRCs and improvement ratio, were developed to quantify the improvement of fault diagnostic resolution. The validation results showed that the proposed method effectively reduced the number of CRCs in contrast to analyzing data solely for a single mode of operation. It achieved a median improvement ratio of 80% in 19 test cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Optimizing district energy systems by integrating Borehole Thermal Energy Storage Using a Mixed-Integer Linear Programming g-function framework with a Multi-Timescale Rolling Horizon method

Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution: two borefields comprising 382 boreholes can meet 8.0 % and 6.6 % of the total campus heating and cooling demand, respectively, at an average energy rate of 0.70–0.77 USD/kWh and carbon intensity of 0.54 kg-CO2/kWh. Short-term analysis reveals a 35%–65% decline in BTES energy flow after 3–6 months of continuous heating/cooling operation, while long-term simulation shows that annual energy production of BTES can vary by up to 12.0 % after four years before stabilizing. Overall, this study develops a novel optimization framework that couples physics-based g-function method with MILP optimization framework, thereby advancing methodological development for shallow-geothermal integration and providing actionable guidance for BTES deployment in district-energy systems.

Yang, Jiahui↗
DOE OSTI2025

Sparse chronology strategy for integrating seasonal energy storage in capacity expansion models

Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Soil porous microstructure control over soil organic matter mobility: A multimethod workflow for understanding chemistry-dependent organic matter binding in soil

Soil organic matter (SOM) has attracted a great deal of interest; particularly for its potential to mitigate human derived CO 2 emissions. Studies have demonstrated that SOM plays a critical role in carbon storage and CO 2 sequestration. However, the sorption properties of SOM, which influence its transport in pore water and stabilization within the soil, remain poorly understood. This study develops a workflow to: (1) examine compound-specific advective and diffusive transport and desorption behaviors, (2) quantify desorption rates through stop-flow and continuous-flow column experiments, and (3) evaluate the impact of soil microporosity on SOM mobility using high-resolution imaging and extractions. Intact core column experiments were conducted on Uncultivated (Natural) and Cultivated soil samples, both were arid soils, collected in Washington State. X-ray computed tomography was employed to measure porosity and pore connectivity, while Fourier-transform ion cyclotron resonance mass spectrometry was used to analyze SOM composition. The findings revealed that cultivation increased total carbon and nitrogen levels due to irrigation and fertilization, enhancing carbon capture potential in arid soils. In contrast, the Natural soil, characterized by higher porosity and connectivity, contained more oxidized carbon. Pore network analysis indicated that soil compaction in the Cultivated soil may lead to longer diffusion pathways, significantly influencing SOM transport and stability.

Hydraulic Properties↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2025

A green degumming approach for lignocellulosic kenaf bast using ethanolamine deep eutectic solvent

Traditional chemical degumming methods for lignocellulosic bast fibers pose substantial challenges, especially when dealing with kenaf bast, which has a high lignin content. Here, these challenges include severe pollution and low efficiency, etc. Therefore, this study developed a novel, green, and efficient degumming approach for lignocellulosic kenaf bast, leveraging choline chloride-ethanolamine (ChCl-ETA) alkaline deep eutectic solvent (DES). The efficacy of the ChCl-ETA DES based degumming method was validated through comprehensive chemical composition analysis, scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TG), and two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy. Subsequently, the optimal degumming conditions, with a choline chloride to ethanolamine ratio of 1:6 and a degumming temperature of 120 °C, were determined based on the results of the residual gum content. Significantly, the recycled ChCl-ETA DES mixtures could maintain a degumming capacity (revealed by the residual gum content of degummed fibers) comparable to that of the conventional double-boiling method for at least five degumming cycles without purification. Given its low-pollution process and high efficiency, this developed method holds great potential for industrial-scale applications of lignocellulosic bast fibers.

Choline chloride↗
DOE OSTI2021

Thermodynamic modeling of hydrogen fueling process from high-pressure storage tank to vehicle tank

This study develops a hydrogen fueling station (HFS) thermodynamic model that simulates the actual fueling process in which hydrogen is supplied from a high-pressure (HP) storage tank into a fuel cell electric vehicle (FCEV) tank. To make the model as accurate as possible, we use the same components and specifications as in actual HFSs, such as a pressure control valve, a pre-cooling system, and an FCEV tank. After the components and their specifications are set, pressure and temperature profiles are set as the HP tank supply conditions. Based on the pressure and temperature profiles, the model solves for the temperature, pressure, and mass flow rate of hydrogen at each downstream position, including the inside of the vehicle tank. The values predicted by the model are compared with experimental data, and we show that the developed model makes it possible to accurately simulate those values at any position during the fueling process.

08 HYDROGEN↗
DOE OSTI2017

Analysis of the Factors Contributing to Vertebral Compression Fractures After Spine Stereotactic Radiosurgery

Purpose: To determine our institutional vertebral compression fracture (VCF) rate after spine stereotactic radiosurgery (SRS) and determine contributory factors. Methods and Materials: Retrospective analysis from 2001 to 2013 at a single institution was performed. With institutional review board approval, electronic medical records of 1905 vertebral bodies from 791 patients who were treated with SRS for the management of primary or metastatic spinal lesions were reviewed. A total of 448 patients (1070 vertebral bodies) with adequate follow-up imaging studies available were analyzed. Doses ranging from 10 Gy in 1 fraction to 60 Gy in 5 fractions were delivered. Computed tomography and magnetic resonance imaging were used to evaluate the primary endpoints of this study: development of a new VCF, progression of an existing VCF, and requirement of stabilization surgery after SRS. Results: A total of 127 VCFs (11.9%; 95% confidence interval [CI] 9.5%-14.2%) in 97 patients were potentially SRS induced: 46 (36%) were de novo, 44 (35%) VCFs progressed, and 37 (29%) required stabilization surgery after SRS. Our rate for radiologic VCF development/progression (excluding patients who underwent surgery) was 8.4%. Upon further exclusion of patients with hematologic malignancies the VCF rate was 7.6%. In the univariate analyses, females (hazard ratio [HR] 1.54, 95% CI 1.01-2.33, P=.04), prior VCF (HR 1.99, 95% CI 1.30-3.06, P=.001), primary hematologic malignancies (HR 2.68, 95% CI 1.68-4.28, P<.001), thoracic spine lesions (HR 1.46, 95% CI 1.02-2.10, P=.02), and lytic lesions had a significantly increased risk for VCF after SRS. On multivariate analyses, prior VCF and lesion type remained contributory. Conclusions: Single-fraction SRS doses of 16 to 18 Gy to the spine seem to be associated with a low rate of VCFs. To the best of our knowledge, this is the largest reported experience analyzing SRS-induced VCFs, with one of the lowest event rates reported.

62 RADIOLOGY AND NUCLEAR MEDICINE↗