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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

O'Hare Airport roadway traffic prediction via data fusion and Gaussian process regression

This study proposes an approach of leveraging information gathered from multiple traffic data sources at different resolutions to obtain approximate inference on the traffic distribution of Chicago's O'Hare Airport area. Specifically, it proposes the ingestion of traffic datasets at different resolutions to build spatiotemporal models for predicting the distribution of traffic volume on the road network. Due to its good adaptability and flexibility for spatiotemporal data, the Gaussian process (GP) regression was employed to provide short-term forecasts using data collected by loop detectors (sensors) and supplemented by telematics data. The GP regression is used to make predictions of the distribution of the proportion of sensor data traffic volume represented by the telematics data for each location of the sensors. Consequently, the fitted GP model can be used to determine the approximate traffic distribution for a testing location outside of the training points. Policymakers in the transportation sector can find the results of this work helpful for making informed decisions relating to current and future transportation conditions in the area.

42 ENGINEERING↗
DOE OSTI2024

Managing Subsurface Pressure Buildup and Interference in Commercial-Scale CO 2 Storage Project with Proximal Injection Wells

Large-scale decarbonization using carbon capture and storage (CCS) is likely to involve many commercial-scale CO 2 storage projects located in close proximity to each other. This close proximity raises concerns over pressure interference among the storage projects. Pressure interference between injection and storage efforts can reduce the practicable CO 2 storage resource and force wells to inject CO 2 at a lower rate to avoid the fracture pressure thresholds per United States Environmental Protection Agency (EPA) Class VI well regulations to preserve injection and confining zone integrity and potentially mitigate against inducing seismic activity. These analyses employ numerical full-physics reservoir modeling to evaluate how pressure buildup fronts and CO 2 plumes evolve under commercial-scale injection volumes of CO 2 in which multiple storage sites located in close proximity occur in tandem. The simulation models mimic injection at pseudo basin-scale and assume homogeneous saline formation(s) as storage targets with a pair of upper and lower homogeneous seal layer/s. These analyses specifically investigate the efficacy of two basin-wide reservoir pressure management strategies in addressing the technical challenges associated with pressure buildup and CO 2 plume commingling. The strategies explored include: 1) enlarging the area of injection well spacing (WS) and 2) storing CO 2 in a stacked sequence (SSS) of saline formations compared to a single formation. The storage and confining zones properties assumed were held common across the scenarios, unless specified otherwise. Analyses results show that after injecting 4 million tons per year for 30 years using 4 separate wells (each injecting 1 million metric tons per year), the radius of CO 2 plume extends to a mere 3 km or less from injection wells. Meanwhile, the radius of pressure buildup ranges on the order of tens to a few hundreds of kilometers, depending on the magnitude of pressure buildup threshold that one would use to define the front. CO 2 plume commingling from different injection wells appears to occur 50 years post-injection, especially under scenarios with narrowly spaced (i.e., < 5 km apart) injection well locations. Findings from sensitivity cases on the well spacing suggest that storage formations modeled would require different well spacing to avoid fracture pressure thresholds. For instance, modeled storage formations with high fracture gradients (i.e., 0.8 psi/ft) would need less than 5–km well spacing, whereas those with lower fracture gradients (i.e., 0.7 psi/ft) would need approximately 20–km well spacing, based on assumed modeling parameters. Under stacked injection, the pressure challenges (described above) still exist but are more alleviated due to distributing the same injection volume across more available reservoir volume. These analyses demonstrate that stacked-sequence storage can effectively address the challenges, while still providing the same target CO 2 storage volumes and allowing a large number of storage projects to be deployed in the same basin by better utilizing the available storage resource across different reservoir depths. Among cases modeled, the resulting pressure buildup front is most suppressed when each storage project distributes injection volumes over several wells, each of which injects a portion of the total CO 2 across the stacked sequence. This strategy results in the smallest CO 2 aerial footprint amongst scenarios evaluated but also shows the largest reduction in the pressure buildup at the top of perforation at the injection wells (upwards of approximately 42 percent compared to the commercial-scale single-formation storage), the result of which is crucial to maintain caprock integrity. The findings presented by this research draw attention to the importance of greater coordination among storage operators and regulatory stakeholders to foster the upscaling and deployment of CCS. These analyses provide insights into required decision-making when considering multi-project deployment in a shared basin. Because these analyses evaluate a very specific geologic situation, they bear further investigations across other geologic situations.

42 ENGINEERING↗
DOE OSTI2021

Are you using the right probe molecules for assessing the textural properties of metal–organic frameworks?

Textural properties—such as the surface area, pore size distribution, and pore volume—are at the forefront of characterization for porous materials. Therefore, it is essential to accurately and reproducibly report a material's textural properties as they could ultimately dictate its applicability. This work aims to provide insightful and comprehensive studies of textural properties for a set of metal–organic frameworks (MOFs), a class of porous materials, using various gases to equip researchers in the field with a helpful guide and reference. Here, we selected a series of nine MOFs with different surface areas, pore sizes, shapes, and chemical environments to represent a wide range of materials. We probed the textural properties of these MOFs using traditional and distinctive gases: N 2 , Kr and O 2 at 77 K, Ar at 87 K, and CO 2 at 195 and 273 K. With regard to surface area, we discuss the validity and challenges associated with the current BET method, the importance of utilizing the Rouquerol et al. consistency criteria to ensure accuracy and reproducibility, and the recommended gas probes for certain materials. For pore size distribution, we discuss the efficacy of each probe for determining the pore sizes within a porous material relative to the calculated distribution from its crystal structure, the limitations of current computational kernels used to calculate pore size distributions, and the need for advanced kernels to envelope the diversity of porous materials. Finally, for pore volume, we discuss the use of the Gurvich rule to obtain the total pore volume in comparison with calculated values from crystal structures and its consistency as a metric for porous materials. Ultimately, we hope that this article will aid researchers in characterizing the textural properties of porous materials and encourage the development of new kernels capable of encompassing the complexity of MOFs and other porous materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Using 3D position sensitivity to reveal response non-uniformities in CdZnTe, TlBr, and CsPbBr 3 detectors

Position sensitivity enables the correction of response non-uniformities in room-temperature semiconductor detectors caused by crystal defects and other factors. It can also be used to pinpoint the exact location of crystal defects responsible for the response variations. This work describes a technique for revealing and visualizing the detector regions affecting the charge collection efficiency in CdZnTe (CZT), TlBr, and CsPbBr 3 detectors configured as position-sensitive virtual Frisch-grid (VFG) devices. The technique correlates the photopeak events in energy spectra with their spatial distributions inside the detectors using the position information. By selecting the events from narrow energy intervals within a photopeak, we can visualize the detector volumes with particular charge collection efficiencies, which, in turn, correlate with the locations of electrode and crystal defects. Here, we demonstrate this technique in several examples. Columnar structures in the volume plots (position distribution maps) are consistent with signal losses near or at the anode in selected samples of CZT and TlBr. Structures exhibiting a distinct depth dependence are consistent with grain boundaries or other crystal defects.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations

In this work, an intercomparison of raindrop mean diameter frequency distribution (RDFD) is performed for numerical simulations of precipitating cloud systems using an array of models and microphysics schemes. This includes results from the Regional Atmospheric Modeling System (RAMS) double-moment microphysics, the Hebrew University Cloud Model bin microphysics (HUCM) interfaced to the RAMS parent model, and the Weather Research and Forecasting (WRF) Model with the Thompson, Morrison, double-moment 6-class (WDM6), and National Severe Storms Laboratory (NSSL) double-moment schemes. Simulations are examined with respect to the raindrop size distribution (DSD) volume-number mean diameter (D m ) and intercept parameter (N w ). When compared to a suite of disdrometer observations, the RDFD resulting from each microphysics scheme exhibits varying degrees of mean drop size constraints and peaks in the frequency distribution of D m . A more detailed investigation of the peaked RDFD from the RAMS simulations suggests that the parameterization of raindrop collisional breakup can impose strong limitations on the evolution of simulated drop growth. As such, a summary and comparison of the drop breakup parameterizations among the aforementioned microphysics schemes is presented. While some drop breakup parameterizations are adjusted toward the observations by modifying the threshold diameter for the onset of breakup, this study explores the use of a modified maximum breakup efficiency. This method permits the parameterization to retain its threshold breakup diameter, while limiting the strength of drop breakup and permitting a broader range of drop sizes. As a result, the simulated mean drop sizes are in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of fracture diagnostic methods for fluid distribution based on quantitative interpretation of distributed acoustic sensing and distributed temperature sensing

Multistage hydraulic fracturing design on horizontal wells has significantly evolved with larger fluid volume, more fracturing stages, and tighter perforation cluster spacing to efficiently stimulate unconventional reservoirs. From the published field observations, the recent fracturing design results in complex fracture networks or swarm of fractures. Fracture treatment evaluation is extremely challenging in such a case because of the large amount of variables in well completion and stimulation design. Combined measurements from different technologies can help in fracture diagnosis. Fluid distribution, either during fracture injection or during production, directly relates to the stimulation efficiency at the cluster level and at the stage level. Because it is unlikely in the real world to distribute the injected fluid uniformly among all the clusters, we need diagnostic techniques to generate the flow profile along a lateral. Fiber-optic measurements, such as distributed acoustic sensing (DAS) and distributed temperature sensing (DTS), are currently used to diagnose downhole flow conditions. This technology allows us to qualitatively confirm the fluid flow profile and other issues occurring downhole during fracturing such as leakage through plugs. For optimizing a fracturing design, we also need to understand how the design parameters are correlated with the stimulation efficiency. In this study, we combine two sets of models of DAS and DTS data interpretation for injected fluid volume distribution. The DAS is interpreted based on an empirical correlation between fluid flow rates and frequency band energy from the acoustic signals. The DTS is interpreted by performing temperature history match-based thermal energy conservation. Because of the completely different physics behind the interpretations, the confirmation of two interpretations provides confidence in fluid distribution.

Geochemistry & Geophysics↗
DOE OSTI2026

3D Gaussian Splatting for Volume Compression

This codebase uses machine learning to train a collection of 3D Gaussian distributions to approximate scientific volume data. Because this collection uses less memory than the original dataset, it can be used as a compressed model of the original data for applications such as visualization.

Dyken, Landon↗
DOE OSTI2020

Excluded-volume model for quarkyonic matter. II. Three-flavor shell-like distribution of baryons in phase space

We extend the excluded-volume model of isospin symmetric two-flavor dense quarkyonic matter [Phys. Rev. C 101, 035201 (2020)] including strange particles and address its implications for neutron stars. The effective sizes of baryons are defined from the diverging hard-core potentials in the short interdistance regime. Around the hard-core density, the repulsive core between baryons at short distances leads to a saturation in the number density of baryons and generates perturbative quarks from the lower phase space, which leads to the shell-like distribution of baryons by the Pauli exclusion principle. The strange-quark Fermi sea always appears at high densities but the Λ hyperon shell only appears when the effective size of the Λ hyperon is smaller than the effective size of nucleons. We find that the pressure of strange quarkyonic matter can be large enough to support neutron stars with two times solar mass and can have a large sound speed, $c^2_s ≃ 0.7$. Finally, the fraction of the baryon number carried by perturbative quarks is about 30% at the inner core of most massive neutron stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Advanced Interactive 3D Visualization Tool for Customizable Analyses of Tomography Datasets in Material Science

Current methods for visualizing and analyzing 3D tomography datasets in materials science often lack the interactivity and depth required for detailed structural insights. This limitation restricts a researchers' ability to accurately interpret complex data, which is critical for advancing material innovations and understanding structural properties. To address this issue, we have developed a novel, web-based interactive 3D visualization and analysis tool from the Trame framework that offers customizable features to enhance data interpretability. The tool allows users to adjust parameters such as visible range, slice planes, data rotation, and layering, providing a more detailed and dynamic view of complex structures. Its user-friendly web interface increases the accessibility and ease of use for both novice and experienced researchers, to visualize large volumetric datasets. The tool supports a diverse range of data formats, making it versatile for various research applications. Unique capabilities include real-time data manipulation, automated feature detection, context-sensitive feedback, and real-time volume calculations and distributions per sliced region or layer, alongside the ability to quickly generate high-quality screenshots and videos for presentations and reports. These advancements offer a comprehensive solution for enhanced 3D data exploration, significantly improving the analysis process and communication of results in materials science.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Energy system analysis of cutting off Russian gas supply to the European Union

The reduction of European Union's pipeline gas imports from Russia as a consequence of the Russian war against Ukraine has had severe economy-wide implications for the EU. Using a multisector integrated assessment model (GCAM), we find that a potential complete cut-off of Russian pipeline gas exports to the EU unevenly impacts the energy mix, prices, and trade flows of different subregions within the EU, depending on their access to alternative gas pipelines and LNG infrastructure. Moreover, there are also large changes in the volume and geographical distribution of global gas infrastructure capacity additions and stranded assets. Our results show that by significantly reducing demand for natural gas, the EU Fit-for-55 policy framework already improves resilience against a complete and persistent cut-off of Russian pipeline gas. However, further improvements in energy efficiency and renewable targets could further soften impacts, while bringing climate objectives closer in sight.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Modeling Ti–6Al–4V using crystal plasticity, calibrated with multi-scale experiments, to understand the effect of the orientation and morphology of the α and β phases on time dependent cyclic loading

Classically, crystal plasticity modeling has used a range of constitutive equations, in which the incorporation of additional physics-based relationships typically results in additional model parameters. These additional parameters need to be reliably calibrated, which often necessitates the use of a range of experimental data acquired at multiple length scales. In this work, a crystal plasticity based finite element (CPFE) model for a dual-phase Titanium alloy, Ti–6Al–4V, is developed. The α and β phases of the microstructure are explicitly modeled. The model is calibrated using a systematic optimization routine and experimental data that consist of macroscopic stress-strain curves coupled with lattice strains on different crystallographic planes for the two phases. These experimental data were obtained from in situ high energy X-ray diffraction experiments for multiple material pedigrees, with varying crystallographic orientation distribution and β volume fractions. Depending on the thermomechanical-processing route and the heat treatment used to manufacture the alloy, Ti–6Al–4V can exist in a wide number of microstructural forms, which often results in the α and β phases either having well aligned slip systems (following the Burgers orientation relationship (BOR)) or possessing no alignment of the slip systems across the interphase boundary (not following the BOR). In this study, the fully-calibrated CPFE model is used to gain a comprehensive understanding of the deformation behavior of Ti–6Al–4V, specifically, the effect of microstructures that follow the BOR (or not) on time-dependent cyclic loading (including the effects of dwell hold times).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tuning gas separation performance of polyimide membranes with macrocyclic crown ether units

Membrane-based gas separation is an energy-efficient alternative to conventional thermally-driven separation processes. However, polymer membranes face the permeability-selectivity trade-off challenge, which stems from the broad size distribution of free volume voids. Here, this study reports a molecular design strategy to address this challenge through incorporating macrocyclic crown ether (CE) moieties into the backbone of Matrimid® polyimide, a commercial gas separation membrane. A series of CE-containing Matrimid®-like copolyimides were synthesized with systematically varied CE molar contents ranging from 3 to 20%. These copolyimides formed ductile, defect-free thin films suitable for membrane fabrication. Gas permeation tests revealed a non-monotonic relationship between permeability/selectivity and CE content. Notably, the copolyimide with only 5% CE demonstrated a 61% increase in CO 2 /CH 4 selectivity and a 13% increase in CO 2 permeability relative to pristine Matrimid®. Higher CE contents did not yield further performance improvements, which is likely due to the competing effects of chain packing disruption and π–π interactions among CE moieties at high content. This hypothesis was supported by wide-angle X-ray scattering (WAXS) analysis, density measurements, and fractional free volume calculations. These findings highlight the potential of macrocyclic crown ether incorporation strategies in fine tuning the microstructure of commercial polyimide gas separation membranes to surpass the traditional permeability-selectivity trade-off.

CO2 separation↗
DOE OSTI2025

Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography

Obtaining high-quality 3D reconstructions from electron tomography of crystalline particles embedded in lighter support elements is crucial for various material systems such as catalysts for fuel cell applications. However, significant challenges arise due to the limited tilt range, sparse and low signal-to-noise ratio of the measurements. In addition, small metal particles can cause strong streaking and shading artifacts in the 3D reconstructions when using conventional reconstruction algorithms due to the presence of Bragg diffraction and the large scattering cross-section difference between the materials of the particles and the background support regions. These artifacts lead to errors in the downstream characterization affecting extraction of critical features such as the size of the metal particles, their distribution and the volume of the lighter support regions. In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. Our approach yields high-quality 3D reconstructions compared to traditional algorithms, accurately capturing both the metal particles as well as the background support. We demonstrate the effectiveness of our algorithm through simulated and experimental bright-field electron tomography data, showing significant improvements in reconstruction quality compared to traditional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Sparse thermal data for cellular automata modeling of grain structure in additive manufacturing

Grain growth in the wake of the melt pool formed during alloy-based additive manufacturing (AM) is complex and multifaceted, depending on parameters governing heat transport, fluid flow, and solidification itself. Cellular automata (CA) models have proven effective in providing computationally efficient and physically sound predictions of grain structure for several AM problems, but their efficiency is tied to the performance of heat transport models. CA models use only a small portion of the problem's temperature data (near the moving melt pool boundary), and much of the CA calculations do not affect the final result due to re-melting of material. Coupling of and communication between heat transport and solidification models, and eliminating operations irrelevant towards final grain structure prediction, will be necessary for using these methods for efficient simulation of large parts. In this work, we introduce a procedure of decoupling the CA from temperature field simulation, using files of relevant temperature data written by the heat transport model. This approach is validated against the standard coupling approach using data obtained through the computational fluid dynamics software OpenFOAM. Negligible differences are seen in grain size, volume, and texture distributions for multilayer simulation of test problems, while the quantity of temperature data for these test problems was reduced by four orders of magnitude (from 100s of GB to 10s of MB) and the code performance sped up by a factor of around 50. Furthermore, variability in microstructure as a function of cell size, substrate, time step, and nucleation parameters is studied, and it is found that cell sizes less than or equal to 1.67 μm and sufficiently small time steps yield Αstatistically equivalent microstructures. Finally, a potential use case for this CA approach—the layer-wise convergence in grain structure starting from extremes in initial grain size—is examined. This approach's ability to simulate expected trends in nucleation and epitaxial grain growth for large regions of microstructure, simulated independently of heat transport models themselves, should prove useful for investigation of various microstructure uncertainties and prediction of part-scale experimental results.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dose Coefficients for Internal Dose Assessments for Exposure to Radioactive Fallout

This paper presents values as well as the bases for calculating internal dose coefficients suitable for estimating organ doses from the exposure to radioactive fallout that could result from the detonation of a nuclear fission device. The 34 radionuclides discussed are the same as those given in a priority list of radionuclides for fallout dose assessments presented in a companion overview paper. The radionuclides discussed are those that are believed to account for a preponderance of the organ doses that might be received by intake by persons of all ages (including in utero and via breast feeding for infants) following exposure to radioactive fallout. The presented dose coefficients for ingestion account for age and include modifications for variations in solubility with distance as discussed previously in the literature, and those for inhalation similarly account for age, solubility, and particle sizes that would be relevant at various distances of exposure as discussed in a companion paper on ingestion dose methods. The proposed modifications peculiar to radioactive fallout account for systematic changes in solubility and particle sizes with distance from the site of detonation, termed here as the region of “local fallout” and the region “beyond local fallout.” Brief definitions of these regions are provided here with more detailed discussion in a companion paper on estimating deposition of fallout radionuclides. This paper provides the dose coefficients for ingestion and inhalation (for particle sizes of 1 μm, 5 μm, 10 μm, and 20 μm) for the region “local fallout.” These dose coefficients for “local fallout” are specific for particles formed in a nuclear explosion that can be large and have radionuclides, particularly the more refractory ones, distributed throughout the volume where the radionuclide has reduced solubility. The dose coefficients for the region “beyond local fallout” are assumed to be the ones published by the International Commission on Radiological Protection (ICRP) in 1995. Comparisons of the presented dose coefficients are made with values published by the ICRP.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2025

Relaxation times for disoriented isospin condensates in high energy heavy ion collisions

Fluctuations between charged and neutral kaons measured by the ALICE Collaboration in Pb-Pb collisions at the CERN Large Hadron Collider (LHC) exceed conventional explanations. Previously it was shown that if the scalar condensate is accompanied by an electrically neutral isospin-1 field then the combination can produce large equilibrium fluctuations where ⟨$\overline{𝑢}$ ⁢𝑢⟩≠⟨ $\overline{𝑑}$𝑑⟩. Hadronizing strange and antistrange quarks might then strongly fluctuate between charged ($\overline{𝑢}$⁢𝑠 or $\overline{𝑠}$⁢𝑢) and neutral (𝑑⁢$\overline{𝑠}$⁢ or 𝑠⁢$\overline{𝑑}$) kaons. Here, we estimate the times for the condensates to achieve their equilibrium probability distributions within causal volumes in high energy heavy ion collisions. This is achieved by modeling the temperature dependence of the condensates, mesonic collective excitations, decay rates of the associated fields, and employing the Langevin and Fokker-Planck equations. Within this model, we find that the equilibration times are short compared with the expansion time, making disoriented isospin condensates a viable explanation for the anomalous fluctuations observed at the LHC.

Quark-gluon plasma↗
DOE OSTI2021

Updated MiniBooNE neutrino oscillation results with increased data and new background studies

The MiniBooNE experiment at Fermilab reports a total excess of $638.0 \pm 132.8$ electron-like events ($4.8 \sigma$) from a data sample corresponding to $18.75 \times 10^{20}$ protons-on-target in neutrino mode, which is a 46% increase in the data sample with respect to previously published results, and $11.27 \times 10^{20}$ protons-on-target in antineutrino mode. The additional statistics allow several studies to address questions on the source of the excess. First, we provide two-dimensional plots in visible energy and cosine of the angle of the outgoing lepton, which can provide valuable input to models for the event excess. Second, we test whether the excess may arise from photons that enter the detector from external events or photons exiting the detector from $\pi^0$ decays in two model independent ways. Beam timing information shows that almost all of the excess is in time with neutrinos that interact in the detector. The radius distribution shows that the excess is distributed throughout the volume, while tighter cuts on the fiducal volume increase the significance of the excess. We conclude that models of the event excess based on entering and exiting photons are disfavored.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Voltage Support With PV Inverters in Low-Voltage Distribution Networks: An Overview

Large solar photovoltaic (PV) penetration using inverters in low voltage (LV) distribution networks may pose several challenges, such as reverse power flow and voltage rise situations. These challenges will eventually force grid operators to carry out grid reinforcement to ensure continued safe and reliable operations. However, smart inverters with reactive power control capability enable PV systems to support voltage quality in the distribution network better. Here, this paper gives an overview of the current state-of-the-art control strategies for handling voltage problems through PV inverters and other devices. In addition, the (control) technical issues of PV systems integrated into the LV distribution network are considered from a control point of view. By comparing the control issues of PV integration into the grid, the paper aims to help distribution system operators to expand the volume of PV generation in the distribution system in an efficient and safe manner. Additionally, it will help control engineers and researchers select proper control strategies for PV systems as well as other distributed renewable sources.

42 ENGINEERING↗