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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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DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Quantifying concentration distributions in redox flow batteries with neutron radiography

Abstract The continued advancement of electrochemical technologies requires an increasingly detailed understanding of the microscopic processes that control their performance, inspiring the development of new multi-modal diagnostic techniques. Here, we introduce a neutron imaging approach to enable the quantification of spatial and temporal variations in species concentrations within an operating redox flow cell. Specifically, we leverage the high attenuation of redox-active organic materials (high hydrogen content) and supporting electrolytes (boron-containing) in solution and perform subtractive neutron imaging of active species and supporting electrolyte. To resolve the concentration profiles across the electrodes, we employ an in-plane imaging configuration and correlate the concentration profiles to cell performance with polarization experiments under different operating conditions. Finally, we use time-of-flight neutron imaging to deconvolute concentrations of active species and supporting electrolyte during operation. Using this approach, we evaluate the influence of cell polarity, voltage bias and flow rate on the concentration distribution within the flow cell and correlate these with the macroscopic performance, thus obtaining an unprecedented level of insight into reactive mass transport. Ultimately, this diagnostic technique can be applied to a range of (electro)chemical technologies and may accelerate the development of new materials and reactor designs.

Science & Technology - Other Topics↗

DOE OSTI2021

From noise to information: The transfer function formalism for uncertainty quantification in reconstructing the nuclear density

The neutron distribution of neutron-rich nuclei provides critical information on the structure of finite nuclei and neutron stars. Parity violating experiments—such as PREX and CREX—provide a clean and largely model-independent determination of neutron densities. Such experiments, however, are challenging and expensive, which is why sound statistical arguments are required to maximize the information gained. We introduce a new framework, the “transfer function formalism,” aimed at uncertainty quantification, model selection, and experimental design in the context of neutron densities. The transfer functions (TFs) are built analytically by expressing the linear response of the objective function (e.g., χ2) to small perturbations of the data. Using the TF formalism, we are able to analyze the expected overall uncertainty—quantified in terms of bias and variance—of the mean square radius and interior density of 48 Ca and 208 Pb. Using relativistic mean field models as a proxy for the weak-charge density—and assuming that a total of five measurements could be performed on the weak form factor of 48 Ca and 208 Pb—we identify the optimal models and experimental locations that minimize the uncertainty in the extraction of the radius and interior density. We also explore the use of the TF formalism to understand the influence of prior distributions for the model parameters, as well as the optimization of model hyperparameters not constrained by the data. Here,we establish how the choice of experimental locations and the model that is used can have a significant impact on the final uncertainties of the extracted quantities of interest. For challenging experiments such as CREX and PREX, a proper quantification of such uncertainties is critical. We have demonstrated how the TF formalism provides several advantages for this type of analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1979

Performance characteristics of a slagging gasifier for MHD combustor systems

The performance of a two stage, coal combustor concept for magnetohydrodynamic (MHD) systems was investigated analytically. The two stage MHD combustor is comprised of an entrained flow, slagging gasifier as the first stage, and a gas phase reactor as the second stage. The first stage was modeled by assuming instantaneous coal devolatilization, and volatiles combustion and char gasification by CO2 and H2O in plug flow. The second stage combustor was modeled assuming adiabatic instantaneous gas phase reactions. Of primary interest was the dependence of char gasification efficiency on first stage particle residence time. The influence of first stage stoichiometry, heat loss, coal moisture, coal size distribution, and degree of coal devolatilization on gasifier performance and second stage exhaust temperature was determined. Performance predictions indicate that particle residence times on the order of 500 msec would be required to achieve gasification efficiencies in the range of 90 to 95 percent. The use of a finer coal size distribution significantly reduces the required gasifier residence time for acceptable levels of fuel use efficiency. Residence time requirements are also decreased by increased levels of coal devolatilization. Combustor design efforts should maximize devolatilization by minimizing mixing times associated with coal injection.

Smith, K. O.↗

DOE OSTI2023

Smoothing tool design and performance during subaperture glass polishing

During subaperture tool grinding and polishing, overlaps of the tool influence function can result in undesirable mid-spatial frequency (MSF) errors in the form of surface ripples, which are often corrected using a smoothing polishing step. Here, in this study, flat multi-layer smoothing polishing tools are designed and tested to simultaneously (1) reduce or remove MSF errors, (2) minimize surface figure degradation, and (3) maximize the material removal rate. A time-dependent convergence model in which spatial material removal varies with a workpiece-tool height mismatch, combined with a finite element mechanical analysis to determine the interface contact pressure distribution, was developed to evaluate various smoothing tool designs as a function of tool material properties, thicknesses, pad textures, and displacements. An improvement in smoothing tool performance is achieved when the gap pressure constant, $\overline{h}$ (which describes the inverse rate at which the pressure drops with a workpiece-tool height mismatch), is minimized for smaller spatial scale length surface features (namely, MSF errors) and maximized for large spatial scale length features (i.e., surface figure). Five specific smoothing tool designs were experimentally evaluated. A two-layer smoothing tool using a thin, grooved IC1000 polyurethane pad (with a high elastic modulus, E pad =360 MPa ), thicker blue foam (with an intermediate modulus, E foam =5.3 MPa ) underlayer, and an optimized displacement (d t =1 mm ) provided the best overall performance (namely, high MSF error convergence, minimal surface figure degradation, and high material removal rate).

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Effects of composition and morphology on the hydrogen storage properties of transition metal hydrides: Insights from PtPd nanoclusters

Transition metal hydride nanoparticles are promising hydrogen storage materials as they store and release hydrogen at near-ambient conditions. Their storage capacities can be modulated by adjusting their size, shape, morphology, and composition. It is however unclear why these factors influence hydrogen storage properties. Here, we present a first-principles study on six 55-atom PtPd nanoclusters to elucidate the effects of nanoparticle morphology and composition on the hydrogen storage characteristics of small nanoclusters. We employ the cluster expansion methodology to analyze how the spatial distribution and energetics of hydrogen adsorption and absorption evolve as a function of hydrogen loading. Our results reveal that at near-ambient pressures and above, hydrogen is actively stored in both the surface—top sites on Pt, and bridge sites on Pd—and the subsurface. The hydrogen storage capacity is controlled by the binding strength of hydrogen, itself influenced by two factors: i) the interaction energy between hydrogen atoms, which dictates how binding strength varies with increasing loading; and ii) the intrinsic binding affinity of a metal cluster for hydrogen, which dictates the magnitude of the nearly-uniform offsets in binding strength across all hydrogen loadings. Bimetallic clusters with alloyed shells and core-shell morphologies modulate these factors by tuning the distribution of hydrogen binding strengths on the surface and subsurface respectively. We shed light on the factors that affect hydrogen storage in clusters and provide insights for the rational design of metal clusters with maximal hydrogen storage capacities.

08 HYDROGEN↗

DOE OSTI2024

Synthesizing realistic sand assemblies with denoising diffusion in latent space

Abstract The shapes and morphological features of grains in sand assemblies have far‐reaching implications in many engineering applications, such as geotechnical engineering, computer animations, petroleum engineering, and concentrated solar power. Yet, our understanding of the influence of grain geometries on macroscopic response is often only qualitative, due to the limited availability of high‐quality 3D grain geometry data. In this paper, we introduce a denoising diffusion algorithm that uses a set of point clouds collected from the surface of individual sand grains to generate grains in the latent space. By employing a point cloud autoencoder, the three‐dimensional point cloud structures of sand grains are first encoded into a lower‐dimensional latent space. A generative denoising diffusion probabilistic model is trained to produce synthetic sand that maximizes the log‐likelihood of the generated samples belonging to the original data distribution measured by a Kullback‐Leibler divergence. Numerical experiments suggest that the proposed method is capable of generating realistic grains with morphology, shapes and sizes consistent with the training data inferred from an F50 sand database. We then use a rigid contact dynamic simulator to pour the synthetic sand in a confined volume to form granular assemblies in a static equilibrium state with targeted distribution properties. To ensure third‐party validation, 50,000 synthetic sand grains and the 1542 real synchrotron microcomputed tomography (SMT) scans of the F50 sand, as well as the granular assemblies composed of synthetic sand grains are made available in an open‐source repository.

Vlassis, Nikolaos N.↗

DOE OSTI2025

Advancing the understanding of coastal disturbances with a network-of-networks approach

Coastal ecosystems are at the nexus of many high priority challenges in environmental sciences, including predicting the influences of compounding disturbances exacerbated by climate change on biogeochemical cycling. Extreme events such as hurricanes, flooding, landslides, and wildfires influence biogeochemical cycling in these systems. However, while research in coastal science is fundamentally transdisciplinary – as drivers of biogeochemical and ecological processes often span scientific and environmental domains – traditional place-based approaches are still often employed to understand coastal ecosystems. In this perspective, we argue that integration among distributed research sites from a macrosystem perspective is crucial to understand how compounding disturbances affect coastal ecosystems. We identify a roadmap for the implementation of an integrated network-of-networks framework that leverages existing research network sites in coastal ecosystems to advance continental-scale process understanding for studying extreme events and global change. We also identify specific ways that existing research efforts can maximize mutual benefit, and where additional infrastructure investments might increase return-on-investment along the coast, using the coastal continental US as a case study.

Myers-Pigg, Allison N. [BATTELLE (PACIFIC NW LAB)]↗

DOE OSTI2022

High-efficiency, anode-free lithium–metal batteries with a close-packed homogeneous lithium morphology

Anode-free lithium–metal batteries (LMBs) are ideal candidates for high-capacity energy storage as they eliminate the need for a conventional graphite electrode or excess lithium–metal anode. Current anode-free LMBs suffer from low Coulombic efficiency (CE) due to poor lithium stripping efficiency. Advanced electrolyte development is a promising route to maximize lithium plating and stripping CE and minimize capacity fade. However, a poor understanding of the mechanisms by which advanced electrolytes improve performance hampers progress in the practical development of anode-free LMBs. Here, we use synchrotron techniques and other tools to analyze the influence of three commercially available electrolytes on the composition, heterogeneity, kinetics, morphology, and electrochemistry of anode-free LMBs. Advanced electrolytes improve the electrochemical performance of anode-free LMBs by forming much denser and better-packed Li morphologies on a Cu current collector than on the conventional electrolyte. Li plates uniformly over the electrode area with the advanced electrolytes rather than in a few active sites. Inactive crystalline Li with heterogeneous distribution dominates the capacity degradation of anode-free cells, especially with the conventional electrolyte, indicating that reducing the amount of “dead” crystalline Li will significantly improve the cycling stability of anode-free cells. Finally, the understanding of the Li plating and stripping process obtained from this work will accelerate the development of anode-free LMBs with high efficiency.

25 ENERGY STORAGE↗

NASA NTRS2011

Gravity and Rossby Wave Signatures in the Tropical Troposphere and Lower Stratosphere Based on Southern Hemisphere Additional Ozonesondes (SHADOZ), 1998-2007

Prior investigations attempted to determine the relative influence of advection and convective processes on ozone and water vapor distributions in the tropical tropopause layer (TTL) through analyses of tracers, related physical parameters (e.g., outgoing long-wave radiation, precipitable water, and temperature), or with models. In this study, stable laminae in Southern Hemisphere Additional Ozonesonde Network (SHADOZ) ozone profIles from 1998 to 2007 are interpreted in terms of gravity waves (GW) or Rossby waves (RW) that are identified with vertical and quasi-horizontal displacements, respectively. Using the method of Pierce and Grant (1998) as applied by Thompson et al. (2007a, 2007b, 2010, 2011), amplitudes and frequencies in ozone laminae are compared among representative SHADOZ sites over Africa and the Pacific, Indian, and Atlantic oceans. GW signals maximize in the TTL and lower stratosphere. Depending on site and season, GW are identified in up to 90% of the soundings. GW are most prevalent over the Pacific and eastern Indian oceans, a distribution consistent with vertically propagating equatorial Kelvin waves. Ozone laminae from RW occur more often below the tropical tropopause and with lower frequency 20%). Gravity wave and Rossby wave indices (GWI, RWI) are formulated to facilitate analysis of interannual variability of wave signatures among sites. GWI is positively correlated with a standard ENSO (El Nino-Southern Oscillation) index over American Samoa (14degS, 171degW) and negatively correlated at Watukosek, Java (7.5degS, 114degE), Kuala Lumpur (3degN, 102degE), and Ascension Island (80degS, 15degW). Generally, the responses of GW and RW to ENSO are consistent with prior studies.

Thompson, Anne M.↗

DOE OSTI2021

Future Automotive Systems Technology Simulator (FASTSim) Validation Report - 2021

The National Renewable Energy Laboratory's Future Automotive Systems Technology Simulator (FASTSim) captures the most important factors influencing vehicle power demands and performs large-scale fuel efficiency calculations very quickly. These features make FASTSim well suited to evaluate a representative distribution of real-world fuel efficiency over a large quantity of in-use driving profiles, which have become increasingly available in recent years owing to incorporation of Global Positioning System data collection into various travel surveys and studies. In addition, by being open source, computationally lightweight, freely available, and free from expensive third-party software requirements, analyses conducted using FASTSim may be easily replicated and critiqued in an open forum. This is highly desirable for situations in which technical experts seek to reach consensus over questions about what vehicle development plans or public interest strategies could maximize fuel savings and minimize adverse environmental impacts with an evolving vehicle fleet. While FASTSim continues to be refined and improved on an ongoing basis, this report compiles available runs using versions of the tool from the past few years to provide illustrative comparisons of the model results against measured data.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

DOE OSTI2020

Quantifying the Influence of Jupiter on the Earth’s Orbital Cycles

A wealth of Earth-sized exoplanets will be discovered in the coming years, providing a large pool of candidates from which the targets for the search for life beyond the solar system will be chosen. The target selection process will require the leveraging of all available information in order to maximize the robustness of the target list and make the most productive use of follow-up resources. Here, we present the results of a suite of n-body simulations that demonstrate the degree to which the orbital architecture of the solar system impacts the variability of Earth’s orbital elements. By varying the orbit of Jupiter and keeping the initial orbits of the other planets constant, we demonstrate how subtle changes in solar system architecture could alter the Earth’s orbital evolution—a key factor in the Milankovitch cycles that alter the amount and distribution of solar insolation, thereby driving periodic climate change on our planet. The amplitudes and frequencies of Earth’s modern orbital cycles fall in the middle of the range seen in our runs for all parameters considered—neither unusually fast nor slow, neither large nor small. This finding runs counter to the “Rare Earth” hypothesis, which suggests that conditions on Earth are so unusual that life elsewhere is essentially impossible. Our results highlight how dynamical simulations of newly discovered exoplanetary systems could be used as an additional means to assess the potential targets of biosignature searches, and thereby help focus the search for life to the most promising targets.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1993

Hemodynamic and hormonal responses to lower body negative pressure in men with varying profiles of strength and aerobic power

Hemodynamic, cardiac, and hormonal responses to lower-body negative pressure (LBNP) were examined in 24 healthy men to test the hypothesis that responsiveness of reflex control of blood pressure during orthostatic challenge is associated with interactions between strength and aerobic power. Subjects underwent treadmill tests to determine peak oxygen uptake (VO2max) and isokinetic dynamometer tests to determine knee extensor strength. Based on predetermined criteria, subjects were classified into one of four fitness profiles of six subjects each, matched for age, height, and body mass: (a) low strength/average aerobic fitness, (b) low strength/high aerobic fitness, (c) high strength/average aerobic fitness, and (d) high strength/high aerobic fitness. Following 90 min of 0.11 rad (6 degrees) head-down tilt (HDT), each subject underwent graded LBNP to -6.7 kPa or presyncope, with maximal duration 15 min, while hemodynamic, cardiac, and hormonal responses were measured. All groups exhibited typical hemodynamic, hormonal, and fluid shift responses during LBNP, with no intergroup differences between high and low strength characteristics. Subjects with high aerobic power exhibited greater (P < 0.05) stroke volume and lower (P < 0.05) heart rate, vascular peripheral resistance, and mean arterial pressure during rest, HDT, and LBNP. Seven subjects, distributed among the four fitness profiles, became presyncopal. These subjects showed greatest reduction in mean arterial pressure during LBNP, had greater elevations in vasopressin, and lesser increases in heart rate and peripheral resistance. Neither VO2max nor leg strength were associated with fall in arterial pressure or with syncopal episodes. We conclude that interactions between aerobic and strength fitness characteristics do not influence responses to LBNP challenge.

Norepinephrine/blood↗

NASA NTRS1999

Cooperation and Coordination Between Fuzzy Reinforcement Learning Agents in Continuous State Partially Observable Markov Decision Processes

Successful operations of future multi-agent intelligent systems require efficient cooperation schemes between agents sharing learning experiences. We consider a pseudo-realistic world in which one or more opportunities appear and disappear in random locations. Agents use fuzzy reinforcement learning to learn which opportunities are most worthy of pursuing based on their promise rewards, expected lifetimes, path lengths and expected path costs. We show that this world is partially observable because the history of an agent influences the distribution of its future states. We consider a cooperation mechanism in which agents share experience by using and-updating one joint behavior policy. We also implement a coordination mechanism for allocating opportunities to different agents in the same world. Our results demonstrate that K cooperative agents each learning in a separate world over N time steps outperform K independent agents each learning in a separate world over K*N time steps, with this result becoming more pronounced as the degree of partial observability in the environment increases. We also show that cooperation between agents learning in the same world decreases performance with respect to independent agents. Since cooperation reduces diversity between agents, we conclude that diversity is a key parameter in the trade off between maximizing utility from cooperation when diversity is low and maximizing utility from competitive coordination when diversity is high.

Berenji, Hamid R.↗

NASA NTRS1985

Diurnal tide in the equatorial middle atmosphere as seen in LIMS temperatures

The distribution of day-night temperature differences in the middle atmosphere determined by the Nimbus 7 LIMS experiment is described. Day-night differences maximize at and are approximately symmetric about the equator. Successive centers of opposite sign increase in amplitude with altitude, the pattern having a vertical wavelength of approximately 25 km. Profiles of rocket meridional wind at Kwajalein (8.7 deg N) and Ascension Island (8.0 deg S) taken near local noon and averaged over the LIMS data period, exhibit maxima which support the tidal interpretation of the equatorial temperature pattern. These characteristics are in general agreement with previous observational and theoretical results for the solar driven diurnal tide. Substantial time variations in amplitude and in location of the temperature maxima are observed. The diurnal tide near the equatorial stratopause appears to be influenced by the phase of the semiannual oscillation.

Hitchman, M. H.↗

NASA NTRS1993

Influence of heat transfer rates on pressurization of liquid/slush hydrogen propellant tanks

A multi-dimensional computational model of the pressurization process in liquid/slush hydrogen tank is developed and used to study the influence of heat flux rates at the ullage boundaries on the process. The new model computes these rates and performs an energy balance for the tank wall whereas previous multi-dimensional models required a priori specification of the boundary heat flux rates. Analyses of both liquid hydrogen and slush hydrogen pressurization were performed to expose differences between the two processes. Graphical displays are presented to establish the dependence of pressurization time, pressurant mass required, and other parameters of interest on ullage boundary heat flux rates and pressurant mass flow rate. Detailed velocity fields and temperature distributions are presented for selected cases to further illuminate the details of the pressurization process. It is demonstrated that ullage boundary heat flux rates do significantly effect the pressurization process and that minimizing heat loss from the ullage and maximizing pressurant flow rate minimizes the mass of pressurant gas required to pressurize the tank. It is further demonstrated that proper dimensionless scaling of pressure and time permit all the pressure histories examined during this study to be displayed as a single curve.

Sasmal, G. P.↗

DOE OSTI2023

Structure-Driven Liquid Microjunction Surface-Sampling Probe Mass Spectrometry

The rhizosphere is the narrow region of soil surrounding the roots of plants that is influenced by root exudates, root secretions, and associated microbial communities. This region is crucial to plant growth and development and plays a critical role in nutrient uptake, disease resistance, and soil transformation. Understanding the function of exogenous compounds in the rhizosphere starts with determining the spatiotemporal distribution of these molecular components. Using liquid microjunction surface-sampling probe mass spectrometry (LMJ-SSP-MS) and microfluidic devices with attached microporous membranes enables in situ, nondisruptive, and nondestructive spatiotemporal measurement of exogenous compounds from plant roots. However, long imaging times (>2 h) can negatively affect plant heath and limit temporal studies. Here, we present a novel strategy to optimize the number and location of sampling sites on these microporous membrane-covered microfluidic devices. In conclusion, this novel, “structure-driven” sampling workflow takes into consideration the channel structure of the microfluidic device to maximize sampling from the channels and minimize acquisition time (~4× less time in some cases while providing similar chemical image accuracy), thus reducing stress on plants during in situ LMJ-SSP-MS analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗