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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Flow assisted anti-fouling geometries for compact heat exchangers

A header for a heat exchanger and method for cleaning a heat exchanger in a loop without disconnecting loop components is provided. The header is in flow communication with the heat exchanger for distributing fluid through a plurality of adjacent channels. The header is connected between a main heat exchanger inlet nozzle and a channel flow distributor. A filter element is disposed within the header between the nozzle and channel flow distributor. Under normal operation, the filter element removes particulates and fouling material from the main flow stream before it enters the heat exchanger channels. During the cleaning process, fluid is injected on or through the filter element to remove particulates and fouling material through at least one outlet port. The header arrangement allows the filter element to be ‘cleaned in place’ without draining the system and disconnecting the heat exchanger or other components from the flow loop.

Carlson, Matthew David↗
DOE OSTI2024

Searching for Strongly-Interacting Dark Matter with the Heavy Photon Search Experiment

The Heavy Photon Search Experiment (HPS) is a fixed-target experiment at Jefferson Lab’s Hall B, designed to explore a hidden sector (HS) of particles containing dark matter and a new force mediator known as the “heavy photon” (A'). The A' is a massive spin-1 gauge boson associated with a new U (1)D symmetry in the HS that kinetically mixes with the Standard Model () photon with a weak coupling strength parameterized by ¿, with ¿2 ~ 10-2 -10-10. HPS utilizes a high-intensity electron beam on a thin tungsten target to produce heavy photons in the MeV-GeV mass range via “dark bremsstrahlung,” a process analogous to SM bremsstrahlung but suppressed by ¿2. The A' can decay resonantly to SM leptons, allowing HPS to conduct both mass resonance searches for prompt decays (large ¿) and displaced vertex searches for long-lived particles (small ¿). In addition to the minimal A' model, HPS probes more complex extensions such as the QCD-like strongly-interacting massive particles (SIMPs) HS containing “dark” pions (pD) and vector mesons (VD), with pD as dark matter candidates. These particles introduce new thermal dark matter freeze- out scenarios and visible signals through long-lived VD decays to SM leptons, which are accessible to HPS. This analysis conducted a displaced vertex search for VD ¿ e-e+ in the mass range 30 MeV to 124 MeV and ¿ between 10-6 < ¿ < 10-2 using data from the 2016 Engineering Run (10.753 nb-1) at 2.3 GeV. Unlike the minimal A' search, SIMP signal kinematics required new approaches to signal normalization and SM background rejection. The strongest signal evidence was a local p-value of 0.01317 for mVD = 119 MeV, corresponding to a global significance of 0.9s. Although no signal was found, this search excluded a region of the SIMP parameter space at 90 % confidence. This work demonstrates HPS’s competitive capability to probe SIMP sectors within cosmologically significant parameters and introduces a new method for HPS displaced vertex searches using track vertical impact parameter cuts

Spellman, Alic [Univ. of California, Santa Cruz, C↗
DOE OSTI2024

Revisiting a Drag Partition Model For Canopy-Like Roughness Elements

Turbulent flows over a large surface area (S) covered by n obstacles experience an overall drag due to the presence of the ground and the protruding obstacles into the flow. The drag partition between the roughness obstacles and the ground is analyzed using an analytical model proposed by Raupach (Boundary-Layer Meteorol 60:375-395, 1992) and is hereafter referred to as R92. The R92 is based on the premise that the wake behind an isolated roughness element can be described by a shelter area A and a shelter volume V. The individual sizes of A and V without any interference from other obstacles can be determined from scaling analysis for the spread of wakes. To upscale from an individual roughness element to n/S elements where wakes may interact, R92 adopted a background stress re-normalizing instead of reducing A or V with each element addition. This work demonstrates that R92’s approach results in a linear background stress reduction in A and V only when the ratio of n/S is small, due to a low probability of wake interactions. This probabilistic nature suggests that up-scaling from individual to multiple roughness elements can be re-formulated using stochastic averaging methods proposed here. The two approaches are shown to recover R92 under plausible conditions. An alternative scaling for the shelter volume is also proposed here using thermodynamic arguments of work and dissipation though the final outcome remains similar to R92. Comparisons between R92 and available data spanning more than two decades after R92 on blocks and vegetation-like roughness elements confirm the practical utility of R92. The agreement between R92 and this updated databases of experiments and simulations confirm the potential use of R92 in large-scale models provided that the relevant parameters accommodate certain features of the roughness element type (cube versus vegetation-like) and, to a lesser extent, their configuration throughout S. Last, a comparison between R92 and models based on first-order closure principles with constant mixing length suggests that R92 can outperform such models when evaluated across a wide range of roughness densities.

canopy turbulence↗
DOE OSTI2021

Quasi-periodic travelling gravity–capillary waves

We present a numerical study of spatially quasi-periodic travelling waves on the surface of an ideal fluid of infinite depth. This is a generalization of the classic Wilton ripple problem to the case when the ratio of wavenumbers satisfying the dispersion relation is irrational. We propose a conformal mapping formulation of the water wave equations that employs a quasi-periodic variant of the Hilbert transform to compute the normal velocity of the fluid from its velocity potential on the free surface. We develop a Fourier pseudo-spectral discretization of the travelling water wave equations in which one-dimensional quasi-periodic functions are represented by two-dimensional periodic functions on the torus. This leads to an overdetermined nonlinear least-squares problem that we solve using a variant of the Levenberg–Marquardt method. We investigate various properties of quasi-periodic travelling waves, including Fourier resonances, time evolution in conformal space on the torus, asymmetric wave crests, capillary wave patterns that change from one gravity wave trough to the next without repeating and the dependence of wave speed and surface tension on the amplitude parameters that describe a two-parameter family of waves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Implicit and coupled fluid plasma solver with adaptive Cartesian mesh and its applications to non-equilibrium gas discharges

In this work, we present a new fluid plasma solver with adaptive Cartesian mesh (ACM) based on a full-Newton (nonlinear, implicit) scheme for non-equilibrium gas discharge plasma. The electrons and ions are described using drift-diffusion approximation coupled to Poisson equation for the electric field. The electron-energy transport equation is solved to account for electron thermal conductivity, Joule heating, and energy loss of electrons in collisions with neutral species. The rate of electron-induced ionization is a function of electron temperature and could also depend on electron density (important for plasma stratification). The ion and gas temperature are kept constant. The transport equations are discretized using a non-isothermal Scharfetter-Gummel scheme to resolve possible large temperature gradients in the sheaths. We demonstrate the new solver for simulations of direct current (DC) and radiofrequency (RF) discharges. The implicit treatment of the coupled equations allows using large time steps. The full-Newton method (FNM) enables fast nonlinear convergence at each time step, offering significantly improved simulation efficiency. We discuss the selection of time steps for solving different plasma problems. The new solver enables solving several problems we could not solve before with existing software: two- and three-dimensional structures of the entire DC discharges including cathode and anode regions, electric field reversals and double-layer formation, the normal cathode spot and an anode ring, moving striations in diffuse and constricted DC discharges, and standing striations in RF discharges. The developed FNM-ACM technique offers many benefits for tackling the disparity of gas discharge plasma systems' time scales and nonlinearity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Anomaly Detection in Seismic Data with Deep Learning: Application for Instrument Failure Detection and Forecasting

Seismic data quality assessment (QA) is the first and one of the most important steps before conducting any further data analysis. Traditional methods involve checking various metrics, such as spike detection and power spectral density, by setting strict thresholds or comparing data against synthetic benchmarks. However, these approaches often rely on pre-existing knowledge and assumptions about data anomalies, leading to potential misclassification of unusual cases. Here, in this study, we propose a deep autoencoder model, an unsupervised learning approach that evaluates data quality without making assumptions about normal and anomalous data, which can be used to identify deviations in recorded data that may indicate nascent instrument failure. We test the model with the U.S. International Monitoring System (IMS) seismic stations and demonstrate the capability of detecting anomalies on a monthly scale. This could prompt station operators to examine potential problems early, allowing sufficient time for instrument maintenance to prevent data outages. In addition, we use a new manually selected testing dataset to compare our model performance against two supervised machine learning (ML) approaches and a standard QA package, as baseline models. When applied to the dataset containing known data anomalies, performance of the supervised and unsupervised ML approaches is similar, with an accuracy of 88.1% for our model compared to ∼90% for the supervised ML approach and 78.2% for the standard QA package. Our model outperforms the baseline models when applied to new stations, where new types of data anomalies can be station-specific and not included in the training dataset. Finally, we show model transferability by training the model with data from the Global Seismograph Network only and applying it to the IMS network data. The results suggest that our model is generalizable and can be applied to new stations with good accuracy.

Lin, Jiun-Ting [Lawrence Livermore National Labora↗
DOE OSTI2025

Formation of hydrided Pt-Ce-H sites in efficient, selective oxidation catalysts

Single-atom site catalysts can improve the rates and selectivity of many catalytic reactions. For this work, we have modified Pt 1 /CeO 2 single sites by combining them with molecular groups and with oxygen vacancies of the support. The new sites include hydrided (Pt 2+ -Ce 3+ Hδ) and hydroxylated (Pt 2+ -Ce 3+ OH) sites that exhibit higher reactivity and selectivity to previous single sites for several reactions, including a ninefold increase in the reaction rate for carbon monoxide (CO) oxidation, and a 2.3-fold improvement of propylene selectivity for oxidative dehydrogenation of propane. The atomic structure and reaction steps of these sites were determined with in situ and ex situ spectroscopy techniques and theoretical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗
DOE OSTI2026

Modeling a generic TRISO-fueled heat pipe microreactor using SCALE: Depletion, transportation criticality, and shielding

This paper demonstrates the applicability of the SCALE code system to tristructural-isotropic (TRISO)-fueled heat pipe microreactors through depletion, transportation criticality, and shielding analyses of a generic reference design. The study conducted supports US Nuclear Regulatory Commission code readiness efforts for advanced non–light-water reactor technologies and is intended as a code capability demonstration rather than as an optimization of a specific microreactor design. The modeled reactor employs high-assay low-enriched uranium (HALEU) uranium oxycarbide (UCO) TRISO fuel and beryllium oxide (BeO) reflectors and operates at 7.5 MWth with a nominal lifetime of about 3 effective full power years. Representative cases for fresh and irradiated cores were selected to exercise SCALE methods relevant to reactor operation and post-irradiation transport. The discharged-core decay heat is approximately 6% of operating power immediately after shutdown. Transportation criticality calculations show that internal water ingress is the dominant reactivity effect, with fully flooded fresh core and irradiated core configurations remain above the subcriticality criterion, even with the available control mechanisms. Shielding calculations for a simplified transportation package indicate that normal-condition dose rates are governed mainly by shielding thickness and cooling time, whereas the breached hypothetical accident case is governed primarily by cooling time. Overall, the study shows that SCALE supports depletion, transportation criticality, and shielding evaluations efficiently for TRISO-fueled heat pipe microreactors within a single code system.

Criticality↗
DOE OSTI2026

Modulating surface acoustic wave generation through superconductivity

Surface acoustic waves (SAWs), with their five orders-of-magnitude slower propagation velocity, allow for considerably shorter wavelengths at the same frequency compared to electromagnetic waves. The short wavelengths allow for device miniaturization and on-chip integration. The generic design of these devices involves piezoelectric substrates with comb-like arrays of Al or Au electrodes known as interdigitated transducers (IDTs) deposited on the surface. However, Al and Au both have shortcomings at the cryogenic temperatures required for quantum applications, namely, the formation of two-level systems and the lack of superconductivity perpetuating Ohmic losses, respectively. In this work, SAWs are generated in the high-MHz to low-GHz range using niobium nitride (NbN) interdigitated transducers and Bragg reflectors. We demonstrate the fabrication of acoustic devices through photolithography and reactive ion etching. The sharp transition between superconducting and normal states and the corresponding change in SAW transmission allows for fine control of the “on” (superconducting) and “off” (normal) states of NbN, with a ΔT = 1 K separating the transmission minimum and maximum. We demonstrate a 16× difference in transmission between the “on” and “off” states of the device. The SAW transmission behavior mirrors the change in resistance of NbN at its T c . These findings open up new possibilities for the integration of NbN SAW resonators into existing quantum architectures based on NbN and a method for adjusting transmission properties independent of applied voltage.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Estimating Atmospheric Parameters of DA White Dwarf Stars with Deep Learning

The determination of atmospheric parameters of white dwarf stars (WDs) is crucial for researches on them. Traditional methodology is to fit the model spectra to observed absorption lines and report the parameters with the lowest χ 2 error, which strongly relies on theoretical models that are not always publicly accessible. In this work, we construct a deep learning network to model-independently estimate T eff and log g of DA stars (DAs), corresponding to WDs with hydrogen-dominated atmospheres. The network is directly trained and tested on the normalized flux pixels of full optical wavelength range of DAs spectroscopically confirmed in the Sloan Digital Sky Survey. Experiments in test yield that the rms error for T eff and log g approaches 900 K and 0.1 dex, respectively. This technique is applicable for those DAs with T eff from 5000 to 40,000 K and log g from 7.0 to 9.0 dex. Furthermore, the applicability of this method is verified for the spectra with degraded resolution of ~200. So it is also practical for the analysis of DAs that will be detected by the Chinese Space Station Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Validating methods for modeling composition gradients in planar shock experiments

An interface is Rayleigh–Taylor (RT) unstable when acceleration pushes a less dense material into a more dense one, and the growth of the instability is governed partly by the Atwood number gradient. Double-shell inertial confinement fusion capsules have a foam spacer layer pushing on an inner capsule composed of a beryllium tamper and high-Z inner shell, and so have RT unstable interfaces that require benchmarking. To this end, the results of a planar shock experiment with beryllium/tungsten targets are presented. One target had the normal bilayer construction of beryllium and tungsten in two distinct layers; the second target had the beryllium grading into tungsten with a quasi-exponential profile, motivated by the potential for reduced RT growth with the gradient profile. Simulations mimic the shock profiles for both targets and match the shock velocity to within 5%. These results validate the ability of our simulations to model double-shell capsules with bilayer or graded layer Be/W inner shells, which are needed to design future experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Actinium purification from elemental components of stainless steel and aluminum

Radioisotopes of actinium are valuable because of their potential use in the medical industry. Actinium-225 shows promise for treating disease—like cancer—via targeted alpha therapy (TAT), and the longer-lived actinium-227 is the parent of two radionuclides with potential application in TAT radiopharmaceuticals, thorium-227 and radium-223. Continuing progress in the development of these medical applications requires robust and diverse methods for extracting and purifying actinium from a wide range of matrices. Further, to define the strengths and limitations of separation methods commonly employed in actinium processing, we characterized the performance of ion exchange and extraction chromatographic steps for removing contaminants found in stainless steel (chromium, iron, nickel, and silicon) and aluminum from actinium-227. While AG-MP1 anion exchange resin with HCl (aq) successfully removed iron, cation exchanger AG 50W-X8 removed most other contaminants. The most persistent contaminant was aluminum, which was removed using a DGA Normal extraction resin. These results are presented within the context of applying that methodology toward actinium purification strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Generation of a controllable TNSA deuteron beam using deuterated metal targets

This study investigated the feasibility of using deuterated titanium targets for the generation of a target normal sheath acceleration (TNSA) deuteron beam. Commercial 25-μm-thick titanium foil was cut into 500 x 500-μm 2 squares and subsequently deuterated using different approaches. The spectra and total yields of all emitted ions were measured using a Thomson parabola ion spectrometer. It was found that a 24-h exposure to 1 atm of D 2 gas at 400°C is the most-efficient deuteration method, producing yields in the mid-10 11 deuterons per shot. The deuteron energy spectra changed from an exponential shape at low ion yields to exponentially modified Gaussians at higher yields. Simulations suggest that this effect is due to increased Coulomb interactions between the ions, which suppress the low energies. Separate campaigns will utilize the presented approach to produce a TNSA triton beam. Furthermore, two such targets will be used in a pitcher/catcher configuration to study the tritium–tritium reaction T(t, 2n)α.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Testing of Fusion Machine Components Against Cryogenic Pellet Impacts

Shattered pellet injection (SPI), currently the most effective method of disruption mitigation, is currently implemented on tokamaks worldwide for experimental purposes. Cryogenic pellets are formed and fired into an angled surface before entering the plasma. The impact with the angled surface causes the pellets to fragment into a cloud of particles with the purpose of increasing the surface area for ablation. As pellets traverse guide tubes, depending on design, there is a chance of an off-normal pellet impact. Pellet impacts are also, depending on design, possible in the plasma chamber if not fully ablated and assimilated, or if the fragment plume is not directed in the proper direction. This paper outlines a series of pellet impact tests on various tiles and components relevant to the ITER, JET, and ASDEX Upgrade SPI systems. In conclusion, testing was done to assess the potential damage from pellet and fragment plume impacts through high-speed imaging and the visual inspection of components.

Cryogenic pellets↗
DOE OSTI2023

Modeled production, oxidation, and transport processes of wetland methane emissions in temperate, boreal, and Arctic regions

Abstract Wetlands are the largest natural source of methane (CH 4 ) to the atmosphere. The eddy covariance method provides robust measurements of net ecosystem exchange of CH 4 , but interpreting its spatiotemporal variations is challenging due to the co‐occurrence of CH 4 production, oxidation, and transport dynamics. Here, we estimate these three processes using a data‐model fusion approach across 25 wetlands in temperate, boreal, and Arctic regions. Our data‐constrained model—iPEACE—reasonably reproduced CH 4 emissions at 19 of the 25 sites with normalized root mean square error of 0.59, correlation coefficient of 0.82, and normalized standard deviation of 0.87. Among the three processes, CH 4 production appeared to be the most important process, followed by oxidation in explaining inter‐site variations in CH 4 emissions. Based on a sensitivity analysis, CH 4 emissions were generally more sensitive to decreased water table than to increased gross primary productivity or soil temperature. For periods with leaf area index (LAI) of ≥20% of its annual peak, plant‐mediated transport appeared to be the major pathway for CH 4 transport. Contributions from ebullition and diffusion were relatively high during low LAI (<20%) periods. The lag time between CH 4 production and CH 4 emissions tended to be short in fen sites (3 ± 2 days) and long in bog sites (13 ± 10 days). Based on a principal component analysis, we found that parameters for CH 4 production, plant‐mediated transport, and diffusion through water explained 77% of the variance in the parameters across the 19 sites, highlighting the importance of these parameters for predicting wetland CH 4 emissions across biomes. These processes and associated parameters for CH 4 emissions among and within the wetlands provide useful insights for interpreting observed net CH 4 fluxes, estimating sensitivities to biophysical variables, and modeling global CH 4 fluxes.

Ueyama, Masahito↗
DOE OSTI2021

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to advance geothermal exploration and safe geothermal energy production. As part of the project, this submission provides data arrays for 149 microearthquakes between the year 2012 and 2013 at the Newberry EGS Site for use with the Deep Learning Algorithm that has been developed. The data provided includes raw waveform data, location data, normalized waveform data, and processed waveform data. Penn State Geothermal Team has shared the following files from the project: - 149 microearthquakes (MEQs) between 2012 and 2013 at Newberry EGS sites, 'Normalized Waveform Inputs.npz' are normalized waveforms. - labels of 149 MEQs: Processed Waveform Inputs.npz - location labels of 149 MEQs: Location Data.npz Note: .npz is the python file format by NumPy that provides storage of array data.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Algorithm to extract direction in 2D discrete distributions and a continuous Frobenius norm

In this study, we present a novel algorithm for determining directionality in 2D distributions of discrete data. We compare a reference dataset with a known direction to a measured dataset with an unknown direction by the Frobenius norm of the difference (FND) to find the unknown direction. To generalize this concept, we develop a continuous Frobenius norm of the difference (CFND) as a continuous analog of the FND and derive its analytical expression. By relating fitted and normalized 2D Gaussian distributions, we show that the CFND approximates the FND, and we validate this relationship with computer simulations. We find that a first-order approximation of the CFND between two similar Gaussian distributions takes the form of an absolute sine function, offering a simple analytical form with potential for specialized applications in segmented inverse beta decay (IBD) neutrino detectors, astronomy, machine learning, and more. Although this method may easily extend to 3D scalar fields, our focus here is on 2D real-valued fields as it directly applies to directionality. Our methodology consists of modeling a 2D Gaussian distribution, binning the data into a histogram, and encoding it as a square matrix. Rotating this matrix around its geometric center and comparing it to a measured dataset using the FND gives us rotational data that we fit with an absolute sine function. The location of the minimum of this fit is the angle closest to the true angle of the direction in the measured dataset. We present the derivation and discuss initial applications of the CFND in our novel algorithm, demonstrating its success in approximating directionality in 2D distributions.

Data Analysis, Statistics and Probability (physics↗