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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

CEC Quest: Long Duration Energy Storage Impact Analysis Tool

SAND2025-14389O CEC Quest is a Python tool with a user interface designed to analyze the greenhouse gas impacts of long-duration energy storage projects in California. The tool automates data collection from public sources and uses an Application Programming Interface (API) to enable users to download photovoltaic resource availability, marginal operating emissions rate, and utility rate data. It guides users in inputting parameters for a battery energy storage model and uploading site electrical load data, while also prompting for relevant analysis parameters like timestep and grid limits. CEC Quest performs monthly optimization of one year of data to assess impacts on the site’s electrical bill and the grid’s greenhouse gas emissions. Finally, it conducts a lifecycle analysis to evaluate changes over a defined quantification period, with results aggregated through automated report generation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rosewater, David [Sandia National Lab. (SNL-CA), L↗
NASA NTRS2006

Human Bone-Forming Chondrocytes Cultured in the Hydrodynamic Focusing Bioreactor Retain Matrix Proteins: Similarities to Spaceflight Results

Fracture healing, crucial to a successful Mars mission, involves formation of a cartilaginous fracture callus which differentiates, mineralizes, ossifies and remodels via the endochondral process. Studies of spaceflown and tailsuspended rats found that, without loading, fracture callus formation and cartilage differentiation within the callus were minimal. We found delayed differentiation of chondrocytes within the rat growth plate on Cosmos 1887, 2044, and Spacelab 3. In the current study, differentiation of human bone-forming chondrocytes cultured in the hydrodynamic focusing bioreactor (HFB) was assessed. Human costochondral chondrocytes in suspension were aggregated overnight, then cultured in the HFB for 25 days. Collagen Type II, aggrecan and unsulfated chondroitin were found extracellularly and chondroitin sulfates 4 and 6 within the cell. Lack of secretion was also found in pancreatic cells of spaceflown rats, and in our SL3 studies. The HFB can be used to study cartilage differentiation in simulated microgravity.

Duke, P. J.↗
DOE OSTI2022

ORPC RivGen 2.0 at Igiugig, AK Operational Data 2019 and 2020

Information enclosed includes operational data from the ORPC RivGen 2.0 deployed at Igiugig, AK in 2019 and 2020. Flow velocities and device performance metrics are recorded along with a report detailing flow speed characterization where Igiugig river flow data is aggregated into a single flow velocity.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Identification of engine oil-derived ash nanoparticles and ash formation process for a gasoline direct-injection engine

Engine oil-derived ash particles emitted from internal combustion (IC) engines are unwanted by-products, after oil is involved in in-cylinder combustion process. Since they typically come out together with particulate emissions, no detail has been reported about their early-stage particles other than agglomerated particles loaded on aftertreatment catalysts and filters. To better understand ash formation process during the combustion process, here differently formulated engine oils were dosed into a fuel system of a gasoline direct injection (GDI) engine that produces low soot mass emissions at normal operating conditions to increase the chances to find stand-alone ash particles separated from soot aggregates in the sub-20-nm size range. In addition to them, ash/soot aggregates in the larger size range were examined using scanning transmission electron microscopy (STEM)-X-ray electron dispersive spectroscopy (XEDS) to present elemental information at different sizes of particles from various oil formulations. The STEM-XEDS results showed that regardless of formulated oil type and particle size, Ca, P and C were always contained, while Zn was occasionally found on relatively large particles, suggesting that these elements get together from an early stage of particle formation. The S, Ca and P K-edge X-ray absorption near edge structure (XANES) analyses were performed for bulk soot containing raw ash. The linear combination approach & cross-checking among XANES results proposed that Ca 5 (OH)(PO 4 ) 2 , Ca 3 (PO 4 ) 2 and Zn 3 (PO 4 ) 2 are potentially major chemical compounds in raw ash particles, when combined with the STEM-XEDS results. Despite many reports that CaSO 4 is a major ash chemical when ash found in DPF/GFP systems was examined, it was observed to be rarely present in raw ashes using the S K-edge XANES analysis, suggesting ash transformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services

A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.

Olama, Mohammed [Oak Ridge National Lab. (ORNL), O↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2022

Solvent selection criteria for temperature-resilient lithium–sulfur batteries

All-climate temperature operation capability and increased energy density have been recognized as two crucial targets, but they are rarely achieved together in rechargeable lithium (Li) batteries. Herein, we demonstrate an electrolyte system by using monodentate dibutyl ether with both low melting and high boiling points as the sole solvent. Its weak solvation endows an aggregate solvation structure and low solubility toward polysulfide species in a relatively low electrolyte concentration (2 mol L −1 ). These features were found to be vital in avoiding dendrite growth and enabling Li metal Coulombic efficiencies of 99.0%, 98.2%, and 98.7% at 23 °C, −40 °C, and 50 °C, respectively. Pouch cells employing thin Li metal (50 μm) and high-loading sulfurized polyacrylonitrile (3.3 mAh cm −2 ) cathodes (negative-to-positive capacity ratio = 2) output 87.5% and 115.9% of their room temperature capacity at −40 °C and 50 °C, respectively. This work provides solvent-based design criteria for a wide temperature range Li-sulfur pouch cells.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Performance Optimization Methods for a Memory-Bound, Unstructured-Grid CFD Application on Massively Parallel GPU Platforms

Computational performance of the FUN3D unstructured-grid computational fluid dynamics (CFD) application on massively parallel GPU environments is memory-bound and highly dependent upon efficient reads from and atomic updates to the irregular cell-, edge-, and node-based data structures. In this talk, we present recent efforts into optimizing select performance-critical kernels on NVIDIA Tesla V100 and A100 GPUs and AMD CDNA MI100 GPUs. A novel use of L2 cache residency controls and asynchronous loads into on-chip shared memory are explored on the A100 GPU for the sparse iterative solver, which is dominated by mixed-precision, sparse matrix vector multiplication. Demonstrations show that these methods improve global memory bandwidth utilization by 13.5% on the A100 GPU. Several techniques are also presented that use registers and/or shared memory to facilitate array transposition and aggregation which combine to reduce the frequency and increase the cache efficiency of floating-point atomic updates to the irregular data structures. These methods are demonstrated to improve the kernel throughput by nearly 500% on select kernels on the AMD MI100 over atomic updates directly to global memory. Overall, both V100 and A100 GPUs outperformed the MI100 GPU on kernels dominated by double-precision atomic updates; however, the techniques demonstrated here reduced the performance gap and improved the MI100 performance.

GPU CPU unstructured CFD memory↗
DOE OSTI2021

Origins of Clustering of Metalate–Extractant Complexes in Liquid–Liquid Extraction

Effective and energy-efficient separation of precious and rare metals is very important for a variety of advanced technologies. Liquid-liquid extraction (LLE) is a relatively less energy intensive separation technique, widely used in separation of lanthanides, actinides, and platinum group metals (PGMs). In LLE, the distribution of an ion between an aqueous phase and an organic phase is determined by enthalpic (coordination interactions) and entropic (fluid reorganization) contributions. The molecular scale details of these contributions are not well understood. Preferential extraction of an ion from the aqueous phase is usually correlated with the resulting fluid organization in the organic phase, as the longer-range organization increases with metal loading. However, it is difficult to determine the extent to which organic phase fluid organization causes, or is caused by, metal loading. In this study, we demonstrate that two systems with the same metal loading may impart very different organic phase organizations and investigate the underlying molecular scale mechanism. Small-angle X-ray scattering shows that the structure of a quaternary ammonium extractant solution in toluene is affected differently by the extraction of two metalates (octahedral PtCl 6 2- and square-planar PtCl 6 2- ), although both are completely transferred into the organic phase. The aggregates formed by the metalate-extractant complexes (approximated as reverse micelles) exhibit a more long-range order (clustering) with PtCl 6 2- compared to that with PtCl 6 2- . Vibrational sum frequency generation spectroscopy and complementary atomistic molecular dynamics simulations on model Langmuir monolayers indicate that the two metalates affect the interfacial hydration structures differently. Furthermore, the interfacial hydration is correlated with water extraction into the organic phase. Overall, these results support a strong relationship between the organic phase organizational structure and the different local hydration present within the aggregates of metalate-extractant complexes, which is independent of metalate concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2023

Grid Services Load Shift Baseline Degradation Analysis Methodology v1

As demand flexibility becomes more common, the mix and frequency of a range of demand flexibility strategies will introduce potential biases into baselines, i.e., the time period immediately prior to a LS event may include other LS or DF events. Baseline degradation assessment provides an approach to quantify how these biases begin to compromise predictive accuracy. Heatmaps, based on each month of the year provides a granular view of a given model's predictive capability. However, for comparing multiple algorithms, separately for weekdays and weekends, aggregating results to seasons provides a simpler means of comparison while still allowing for review of variations by time of day and time of year

Fernandes, Samuel↗
DOE OSTI2020

Effect of Natural Organic Matter on the Fate of Cadmium During Microbial Ferrihydrite Reduction

Natural organic matter (NOM) is known to affect the microbial reduction and transformation of ferrihydrite, but its implication toward cadmium (Cd) associated with ferrihydrite is not well-known. In this work, we investigated how Cd is redistributed when ferrihydrite undergoes microbial reduction in the presence of NOM. Incubation with Geobacter sulfurreducens showed that both the rate and the extent of reduction of Cd-loaded ferrihydrite were enhanced by increasing concentrations of NOM (i.e., C/Fe ratio). Furthermore, without NOM, only 3–4% of Fe(III) was reduced, but around 61% of preadsorbed Cd was released into solution due to ferrihydrite transformation to lepidocrocite. At high C/Fe ratio (1.6), more than 35% of Fe(III) was reduced, as NOM can facilitate bioreduction by working as an electron shuttle and decreased aggregate size, but only a negligible amount of Cd was released into solution, thus decreasing Cd toxicity and prolonging microbial Fe(III) reduction. No ferrihydrite transformation was observed at high C/Fe ratios using Mössbauer spectroscopy and X-ray diffraction, and X-ray absorption spectroscopy indicated the proportion of Cd-OM bond increased after microbial reduction. This study shows that the presence of NOM leads to less mobilization of Cd under reducing condition possibly by inhibiting ferrihydrite transformation and recapturing Cd through Cd-OM bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2008

Modeling and Optimization for Morphing Wing Concept Generation II: Morphing Wing Modeling and Structural Sizing Techniques - Part 1

This report documents a series of investigations to develop an approach for structural sizing of various morphing wing concepts. For the purposes of this report, a morphing wing is one whose planform can make significant shape changes in flight - increasing wing area by 50% or more from the lowest possible area, changing sweep 30 or more, and / or increasing aspect ratio by as much as 200% from the lowest possible value. These significant changes in geometry mean that the underlying load-bearing structure changes geometry. While most finite element analysis packages provide some sort of structural optimization capability, these codes are not amenable to making significant changes in the stiffness matrix to reflect the large morphing wing planform changes. The investigations presented here use a finite element code capable of aeroelastic analysis in three different optimization approaches -a "simultaneous analysis" approach, a "sequential" approach, and an "aggregate" approach.

Skillen, Michael D.↗
DOE OSTI2025

Linking structural and rheological memory in disordered soft materials

Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.

Kamani, Krutarth M. [Univ. of Illinois at Urbana-C↗
DOE OSTI2020

In-situ X-ray Evaluation of Traumatic Brain Injury Dynamic Impacts (Final Report)

The goal of this project was to create an in-situ model of traumatic brain injury that allows for analysis of chronic traumatic encephalopathy (CTE) development. CTE is a neurodegenerative disease that occurs as a result of traumatic brain injuries. The resulting neurodegeneration and atrophying of cortical brain tissue develop as tau proteins build-up around small blood vessels and at the base of cortical sulci. Aggregation of tau proteins results in blood vessel damage and neurological function loss, leading to cortical tissue atrophy. This occurs only at some neuronal junctions in the brain after trauma. It has been conjectured that the geometrical distribution of force along neurons is responsible for initiation of tau deposition. However, to assess the validity of this proposition, it is necessary to analyze the mechanical response under dynamic loading associated with brain trauma in-situ

42 ENGINEERING↗
NASA NTRS1996

Soot and Radiation Measurements in Microgravity Jet Diffusion Flames

The subject of soot formation and radiation heat transfer in microgravity jet diffusion flames is important not only for the understanding of fundamental transport processes involved but also for providing findings relevant to spacecraft fire safety and soot emissions and radiant heat loads of combustors used in air-breathing propulsion systems. Our objectives are to measure and model soot volume fraction, temperature, and radiative heat fluxes in microgravity jet diffusion flames. For this four-year project, we have successfully completed three tasks, which have resulted in new research methodologies and original results. First is the implementation of a thermophoretic soot sampling technique for measuring particle size and aggregate morphology in drop-tower and other reduced gravity experiments. In those laminar flames studied, we found that microgravity soot aggregates typically consist of more primary particles and primary particles are larger in size than those under normal gravity. Comparisons based on data obtained from limited samples show that the soot aggregate's fractal dimension varies within +/- 20% of its typical value of 1.75, with no clear trends between normal and reduced gravity conditions. Second is the development and implementation of a new imaging absorption technique. By properly expanding and spatially-filtering the laser beam to image the flame absorption on a CCD camera and applying numerical smoothing procedures, this technique is capable of measuring instantaneous full-field soot volume fractions. Results from this technique have shown the significant differences in local soot volume fraction, smoking point, and flame shape between normal and reduced gravity flames. We observed that some laminar flames become open-tipped and smoking under microgravity. The third task we completed is the development of a computer program which integrates and couples flame structure, soot formation, and flame radiation analyses together. We found good agreements between model predictions and experimental data for laminar and turbulent flames under both normal and reduced gravity. We have also tested in the laboratory the techniques of rapid-insertion fine-wire thermocouples and emission pyrometry for temperature measurements. These techniques as well as laser Doppler velocimetry and spectral radiative intensity measurement have been proposed to provide valuable data and improve the modeling analyses.

Ku, Jerry C.↗
DOE OSTI2026

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗
DOE OSTI2025

Influence of Pore Water on the Fracture of Silica Sand at Particle Scale

The fracture of particles has a significant influence on the engineering behavior of granular materials. There are no reported conclusive answers in the literature to explain the influence of pore water on the fracture of sand, gravel, railroad ballast rock, aggregates, rockfill, and so on. Here, in this paper, two novel techniques were adopted to investigate the influence of pore water on the fracture of natural silica sand at the particle scale. The three-dimensional (3D) synchrotron microcomputed tomography (SMT) imaging technique was used to acquire and analyze multiple 3D images of specimens composed of wetted silica sand that were subjected to confined one-dimensional (1D) compression loading up to the fracture stage. A few representative particles were identified and digitally separated from the liquid water and gas phases. The 3D SMT images offer clear experimental evidence of the phase transition of water from liquid to gas within the opening cracks. In addition, a computational fluid dynamics numerical simulation framework for water flow into an opening crack was adopted and the results show that the fast opening of the crack induced cavitation, water phase transition, and water hammer effects. The results of the numerical simulations agree with the confined 1D compression experiments where the onset of the bubbles (gas phase) within the crack is mainly generated during the secondary cavitation stage, and the generated bubble near the crack mouth opening resulted from the primary cavitation, which was directly caused by the crack expansion. The results reported in this paper present a new cavitation phenomenon that occurs during particle fracture, which offers a physics-based explanation of why water-wetted sand fractures at smaller stresses than dry and can pave the way for more in-depth future studies on the fracture of water-wetted sand.

cavitation↗