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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground‐based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010‐2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

Morin, Cory↗
NASA NTRS1993

Calibration of radiation codes in climate models: Comparison of calculations with observations from the SPECtral Radiation Experiment (SPECTRE)

The primary goal of SPECTRE is to: close the loopholes by which longwave radiation models have eluded incisive comparisons with measurements. Likewise, the experimental approach was quite simple in concept, namely: accurately measure the zenith infrared radiance at high spectral resolution while simultaneously profiling the radiatively important atmospheric properties with conventional and remote sensing devices. The field phase of SPECTRE was carried out as part of FIRE Cirrus II, and detailed spectra of the down welling radiance were obtained by several interferometers simultaneous to the measurement of the optical properties of the atmosphere. We are now well along in the process of analyzing the data and calibrating radiation codes so that they may be used more effectively in climate related studies. The calibration is being done with models ranging from the most detailed (line-by-line) to the broad-band parameterizations used in climate models. This paper summarizes our progress in the calibration for clear-sky conditions. When this stage is completed, we will move on to the calibration for cirrus conditions.

Ellingson, R. G.↗
NASA NTRS1995

Spatial and Spatial Frequency Spreads Of Masking: Measurements and a Contrast-Gain-Control Model

Masked pattern detection is affected by the mask's proximity to the target in both the spatial and the spatial frequency domains. We measured contrast thresholds for detection of a Gabor patch centered in a sample of static band-pass noise with a central noise-free aperture. To examine spatial spread, target and mask frequency were identical, at either 2, 4, or 8 cycles/degree (cpd), and the radius of the aperture was 0, 1/2 or 1 cycle of the noise band's center frequency. The results suggest that the spatial spread of masking is scale invariant, with the largest radius producing little masking. To examine spatial frequency spread, a radius of 0 (no aperture) was used with all pairings of 2,4, and 8 cpd for target and mask. The results suggest that masking is asymmetrical over log frequency: 8 cpd noise masks a 2 cpd target, but 2 cpd noise does not mask an 8 cpd target. We have used these results to calibrate a model of contrast-gain-control.

Solomon, J. A.↗
DOE OSTI2025

An On-Sky Atmospheric Calibration of SPT-SLIM

We present the methodology and results of the on-sky responsivity calibration of the South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM). SPT-SLIM is a pathfinder line intensity mapping experiment utilizing the on-chip spectrometer technology, and was first deployed during the 2024-2025 Austral Summer season on the South Pole Telescope. During the two-week on-sky operation of SPT-SLIM, we performed periodic measurements of the detector response as a function of the telescope elevation angle. Combining these data with atmospheric opacity measurements from an on-site atmospheric tipping radiometer, simulated South Pole atmospheric spectra, and measured detector spectral responses, we construct estimates for the responsivity of SPT-SLIM detectors to sky loading. We then use this model to calibrate observations of the moon taken by SPT-SLIM, cross-checking the result against the known brightness temperature of the Moon as a function of its phase.

Dibert, K. R. [Chicago U., Astron. Astrophys. Ctr.↗
NASA NTRS1995

Spatial and Spatial Frequency Spreads of Masking: Measurements and A Contrast-Gain-Control Model

Masked pattern detection is affected by the mask's proximity to the target in both the spatial and the spatial frequency domains. We measured contrast thresholds for detection of a Gabor patch centered in a sample of static band-pass noise with a central noise-free aperture. To examine spatial spread, target and mask frequency were identical, at either 2, 4, or 8 cycles/degree (cpd), and the radius of the aperture was 0, 1/2 or 1 cycle of the noise band's center frequency. The results suggest that the spatial spread of masking is scale invariant, with the largest radius producing little masking. To examine spatial frequency spread, a radius of 0 (no aperture) was used with all pairings of 2, 4, and 8 cpd for target and mask. The results suggest that masking is asymmetrical over log frequency: 8 z 0 cpd noise masks a 2 cpd target, but 2 cpd noise does not mask an 8 cpd target. We have used these results to calibrate a model of contrast-gain-control.

Solomon, Joshua A.↗
DOE OSTI2026

Process‐Oriented Calibration of a Turbulence Scheme in the DOE's Global Storm‐Resolving Model Using Machine Learning

A process‐oriented calibration framework is developed for the Simplified Higher‐Order Closure (SHOC) turbulence scheme in DOE's Simple Cloud Resolving E3SM Atmospheric Model (SCREAM). This framework leverages machine learning surrogates and observational constraints to efficiently calibrate SHOC adjustable parameters across two convective regimes: clear‐sky dry convective boundary layer and fair‐weather shallow cumulus clouds from ARM observations. We use perturbed‐parameter ensembles of a doubly periodic version of SCREAM to train surrogates and apply Markov Chain Monte Carlo sampling guided by cost functions based on benchmarking large‐eddy simulations and observations to identify optimized parameter sets that perform well in both regimes. The calibrated SHOC parameters substantially improve boundary‐layer turbulence and cloud boundaries, and modeled cloud fraction and radiative effects align better with observations than the default. These results demonstrate that combining multiple process‐specific convective regimes with machine‐learning surrogates can reduce parametric uncertainties and yield a model more faithful to cloud–turbulence interactions.

58 GEOSCIENCES↗
NASA NTRS1999

Numerical Thermal Model of a 30-cm NSTAR Ion Thruster

A thermal computer model of the NSTAR (Nasa Solar Electric Propulsion Technology Applications Readiness) xenon ion thruster has been produced using a lumped parameter thermal nodal network scheme. This model contains 104 nodes on the thruster and was implemented using SINDA (Systems Improved Numerical Differencing Analyzer) and TRASYS (Thermal Radiation Analyzer System) on various UNIX workstations. The model includes radiation and conduction heat transfer, the effect of plasma interaction on the thruster, and an account for finely perforated surfaces. The model was developed in conjunction with an NSTAR thruster outfitted with approximately 20 thermocouples for thermal testing at the NASA Lewis Research Center. The results of these experiments were used to calibrate and confirm the computer model first without and then with the plasma interaction. The calibrated model was able to predict discharge chamber temperatures to within 10 C of measured temperatures. To demonstrate the ability of the model under various circumstances the heat flux was examined for a thruster operating in the environment of space.

VanNoord, Jon↗
DOE OSTI2025

Simulated effect of defect volume and location on very high cycle fatigue of laser beam powder bed fused AlSi10Mg

This study quantifies the interaction between volumetric defect location and size on the very high cycle fatigue (VHCF) of laser beam powder bed fused (LB-PBF) AlSi10Mg. Crystal plasticity finite element method (CPFEM) simulations were used to investigate the effects of defect location and size on the driving force for crack initiation. The CPFEM model was calibrated against uniaxial and cyclic experimental data of LB-PBF AlSi10Mg. Defect characteristics were informed by experimental data from the specimens produced in various geometries to create realistic representative volume elements (RVEs) with equivalent volume fractions of defects. By embedding defects of varying sizes and locations within the RVEs, fatigue indicator parameters (FIPs) were calculated to analyze the impact of defects’ characteristics on fatigue performance. Different combinations of defect volume and locations were generated for various microstructure instantiations, providing insight into extreme value fatigue responses. Larger defect volumes located on free surfaces consistently generated the highest FIPs, suggesting defect size and boundary proximity intensify stress concentration effects. RVEs with multiple smaller defects produced lower FIPs than those with single large critical defects. These findings underscore the critical role of defect characteristics on fatigue life, providing a foundation for future predictive modeling in fatigue-sensitive AM applications.

AlSi10Mg↗
DOE OSTI2026

Study of wrap mode impact on Pseudomonas aeruginosa motion in the chemotactic field of fungi

An agent-based discrete computational model biologically calibrated to Pseudomonas aeruginosa migration is used to explore the impacts of bacterial reversals and wrap mode on the efficiency of motion in different environments, both with and without chemotaxis. It is first shown that wrap mode increases the exploration of continuous multimodal chemotactic profiles such as those produced by biologically relevant fungal networks. For cells undergoing a run-reverse pattern, it is shown that the bacteria are likely to remain at the first local chemoattractant maximal production site on a hypha they find. However, with wrap mode, the bacteria can more easily escape these local sites to further explore their neighboring environment along the fungi, suggesting that wrap mode may be beneficial for migration along the fungi in liquid. In a different set of simulations of bacterial motion close to an isolated chemotactic source, wrap mode is shown to increase the ability of a bacterium to reorient toward the source while reducing the overall motion required for similar chemotactic efficiency as a run-reverse strategy, suggesting a potential metabolic benefit. In contrast, model simulations show that wrap mode can increase the rate of dispersal of P. aeruginosa in a nonchemotactic environment.

Hansen, Austin [University of California, Riversid↗
NASA NTRS2005

Consistent Large-Eddy Simulation of a Temporal Mixing Layer Laden with Evaporating Drops: A Posteriori Modelling - Part 2

Large-eddy simulation (LES) is conducted of a three-dimensional temporal mixing layer whose lower stream is initially laden with liquid drops which may evaporate during the simulation. The gas-phase equations are written in an Eulerian frame for two perfect gas species (carrier gas and vapour emanating from the drops), while the liquid-phase equations are written in a Lagrangian frame. The effect of drop evaporation on the gas phase is considered through mass, species, momentum and energy source terms. The drop evolution is modelled using physical drops, or using computational drops to represent the physical drops. Simulations are performed using various LES models previously assessed on a database obtained from direct numerical simulations (DNS). These LES models are for: (i) the subgrid-scale (SGS) fluxes and (ii) the filtered source terms (FSTs) based on computational drops. The LES, which are compared to filtered-and-coarsened (FC) DNS results at the coarser LES grid, are conducted with 64 times fewer grid points than the DNS, and up to 64 times fewer computational than physical drops. It is found that both constant-coefficient and dynamic Smagorinsky SGS-flux models, though numerically stable, are overly dissipative and damp generated small-resolved-scale (SRS) turbulent structures. Although the global growth and mixing predictions of LES using Smagorinsky models are in good agreement with the FC-DNS, the spatial distributions of the drops differ significantly. In contrast, the constant-coefficient scale-similarity model and the dynamic gradient model perform well in predicting most flow features, with the latter model having the advantage of not requiring a priori calibration of the model coefficient. The ability of the dynamic models to determine the model coefficient during LES is found to be essential since the constant-coefficient gradient model, although more accurate than the Smagorinsky model, is not consistently numerically stable despite using DNS-calibrated coefficients. With accurate SGS-flux models, namely scale-similarity and dynamic gradient, the FST model allows up to a 32-fold reduction in computational drops compared to the number of physical drops, without degradation of accuracy; a 64-fold reduction leads to a slight decrease in accuracy.

two-phase flow↗
NASA NTRS1991

Preliminary calibration plan for the Advanced Particles and Field Observatory (APAFO) magnetometer experiment

Prelaunch and postlaunch calibration plans for the APAFO magnetometer experiment are presented. A study of tradeoffs between boom length and spacecraft field is described; the results are summarized. The prelaunch plan includes: calibration of the Vector Fluxgate Magnetometer (VFM), Star Sensors, and Scalar Helium Magnetometer (SHM); optical bench integration; and acquisition of basic spacecraft field data. Postlaunch calibration has two phases. In phase one, SHM data are used to calibrate the VFM, total vector magnetic field data are used to calibrate a physical model of the spacecraft field, and both calibrations are refined by iteration. In phase two, corrected vector data are transformed into geocentric coordinates, previously undetected spacecraft fields are isolated, and initial geomagnetic field models are computed. Provided the SHM is accurate to the required 1.0 nT and can be used to calibrate the VFM to the required 3.0- nT accuracy, the tradeoff study indicates that a 12 m boom and a spacecraft field model uncertainty of 5 percent together allow the 1.0 nT spacecraft field error requirement to be met.

Voorhies, C. V.↗
DOE OSTI2026

Reservoir-scale model of geologic hydrogen production from serpentinization: Cyclic injection in a dual-permeability fracture-matrix system

Geologic hydrogen (GeoH 2 ) from serpentinization is a promising low-carbon resource, but its reservoir-scale behavior remains poorly understood. We develop a dual-permeability reactive transport model for an injector–producer well pair in ultramafic rock that couples multiphase flow, heat transfer, geochemistry, and porosity–permeability evolution. Here, the model is calibrated to olivine flow-through experiments and upscaled to two-year long simulations with continuous injection and cyclic injection with shut-in-to-injection ratios (SIR = 1, 0.5, 0.1). Olivine reacts along high-flux pathways to form lizardite and magnetite, increasing pH; H 2 (aq) and H 2 (g) peak early and then decline as exsolution and advective export outpace local generation. Continuous injection yields the highest cumulative H 2 but the lowest water-use efficiency (1.138 x 10 –6 mol/kgw). Cyclic injection increases this ratio to 1.35 x 10 –6 , 1.377 x 10 –6 , and 1.182 x 10 –6 mol/kgw for SIR = 1, 0.5, and 0.1, respectively; SIR = 0.5 provides a ~20% improvement over continuous injection and the best compromise for pilot design.

08 HYDROGEN↗
DOE OSTI2025

Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel

The long-term thermal stability of structural alloys is essential for ensuring the safe and reliable operation of nuclear reactors and other power plants. While extensive research has explored the effects of thermal aging on conventional stainless steels, the behavior of additively manufactured (AM) alloys remains less understood. This study examines the thermal aging response of laser powder bed fusion (LPBF) 316H stainless steel (SS) at temperatures ranging from 550 °C to 750 °C over durations of up to 10,000 h (approximately 1.14 years). Advanced characterization techniques, including electron microscopy and synchrotron X-ray diffraction, were used to investigate dislocation recovery and phase evolution. Based on these findings, a time-temperature-precipitation (TTP) diagram was developed for LPBF 316H SS, revealing a 10- to100-fold acceleration in precipitation kinetics compared to wrought 316H SS. A physics-informed model was calibrated using the short-term experimental data, enabling predictions of average precipitate sizes, volume fractions of M 23 C 6 and Laves phases, and changes in molybdenum solute concentration for aging up to 1 × 10⁶ h (114 years). These microstructural insights were further utilized to estimate yield strength and extrapolate strength reduction factors over the extended aging period. Despite the accelerated aging kinetics, LPBF 316H SS demonstrated superior yield strength retention compared to its wrought counterpart. In conclusion, this study establishes a framework for evaluating long-term performance using short-term experimental data and supports the accelerated qualification of AM materials for high-temperature structural applications.

Laser powder bed fusion↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗
DOE OSTI2025

Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

Batteries↗
DOE OSTI2024

A potential model study of the nucleon's charge and mass radius

We study the charge and mass distributions within a nucleon and compute the associated squared radii based on a potential model approach. Different constituent quark configurations such as Δ, Y, and quark-diquark are considered and compared, with model parameters calibrated by experimental measurements of the proton and neutron charge radius. The results suggest that while the charge radius is dictated by quark dynamics, the mass radius is strongly influenced by nonperturbative QCD contributions to a nucleon's mass that are not sensitive to the constituent quarks. As a result, the mass radius could become substantially different from the charge radius. The obtained nucleon mass distributions of different configurations are further used for simulations of the initial conditions in heavy ion collisions. Furthermore, the computed eccentricities ε 2 and ε 3 are found to demonstrate a considerable sensitivity to the input nucleon profiles, especially to the mass radius in the peripheral region as well as for systems with fewer participants.

Gallimore, Daniel [Indiana University, Bloomington↗
DOE OSTI2025

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗