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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Commercial Building Energy Asset Score

This software (Asset Scoring Tool) is designed to help building owners and managers to gain insight into the as-built efficiency of their buildings. It is a web tool where users can enter their building information and obtain an asset score report. The asset score report consists of modeled building energy use (by end use and by fuel type), building systems (envelope, lighting, heating, cooling, service hot water) evaluations, and recommended energy efficiency measures. The intended users are building owners and operators who have limited knowledge of building energy efficiency. The scoring tool collects minimum building data (~20 data entries) from users and build a full-scale energy model using the inference functionalities from Facility Energy Decision System (FEDS). The scoring tool runs real-time building energy simulation using EnergyPlus and performs life-cycle cost analysis using FEDS. An API is also under development to allow the third-party applications to exchange data with the web service of the scoring tool.

Source record↗
DOE OSTI2026

Reasoning4PDEs

Towards Reasoning for PDE Foundation Models: A Reward-Model-Driven Inference-Time-Scaling Algorithm

Mansingh, Siddharth↗
DOE OSTI2020

General Bayesian Inference over the Stiefel Manifold via the Givens Transform

We introduce here an approach based on the Givens representation for posterior inference in statistical models with orthogonal matrix parameters, such as factor models and probabilistic principal component analysis (PPCA). We show how the Givens representation can be used to develop practical methods for transforming densities over the Stiefel manifold into densities over subsets of Euclidean space. We demonstrate how to deal with issues arising from the topology of the Stiefel manifold and how to inexpensively compute the change-of-measure terms. We introduce an auxiliary parameter approach that limits the impact of topological issues. We provide both analysis of our methods and numerical examples demonstrating the effectiveness of the approach. We also discuss how our Givens representation can be used to define general classes of distributions over the space of orthogonal matrices. We then give demonstrations on several examples showing how the Givens approach performs in practice in comparison with other methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Kronecker-structured covariance models for multiway data

Many applications produce multiway data of exceedingly high dimension. Modeling such multi-way data is important in multichannel signal and video processing where sensors produce multi-indexed data, e.g. over spatial, frequency, and temporal dimensions. We will address the challenges of covariance representation of multiway data and review some of the progress in statistical modeling of multiway covariance over the past two decades, focusing on tensor-valued covariance models and their inference. We will illustrate through a space weather application: predicting the evolution of solar active regions over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Microanalysis of carbonate cement δ 18 O in a CO 2 -storage system seal: Insights into the diagenetic history of the Eau Claire Formation (Upper Cambrian), Illinois Basin

Oxygen isotope (δ 18 O) zonation in carbonate mineral cements is often employed as a proxy record (typically with millimeter-scale resolution) of changing temperature regimes during different stages of sediment diagenesis. Recent advances in secondary ion mass spectrometry allow for highly precise and accurate determinations of cement δ 18 O values to be made in situ on a micrometer scale, thus significantly increasing the spatial resolution available to studies of diagenesis in sandstone–shale and carbonate systems. Chemo-isotopically zoned dolomite–ankerite cements within shaly sandstone beds of the predominantly silty–shaly Eau Claire Formation (Cambrian, Illinois Basin) were investigated, revealing the following: with increasing depth of burial (from <0.5 to ~2 km [<1500 to 6500 ft]), cement δ 18 O values decrease from a high of approximately 24‰ down to approximately 14‰ (on the Vienna standard mean ocean water [VSMOW] scale, equivalent to -6.5‰ to -16.5‰ on the Vienna Peedee belemnite [VPDB] scale). The observed cross-basin trend is largely consistent with cements having formed in response to progressive sediment burial and heating. Within the context of independent burial and thermal history models for the Illinois Basin, cementation began soon after deposition and continued intermittently into the mid-Permian. Finally, however, temperatures in excess of burial model predictions are inferred at the time of latest ankerite cement precipitation, which we propose overlapped in time with conductive heating of the Eau Claire Formation (a closed system) from under- and overlying sandstone aquifers that channeled the flow of hot, Mississippi Valley–type mineralizing brines during the mid-Permian (ca. 270 Ma).

58 GEOSCIENCES↗
DOE OSTI2025

Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation

Low-rank methods have shown success in accelerating simulations of a collisionless plasma described by the Vlasov equation, but still rely on computationally costly linear algebra every time step. We propose a data-driven factorization method using artificial neural networks, specifically with convolutional layer architecture, that trains on existing simulation data. At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. Numerical experiments show that the method achieves comparable reconstruction accuracy for interpolation tasks, generalizing to unseen test data in a manner beyond just memorizing training data; patterns in factorization also inherently followed the same numerical trend as those within algebraic methods (e.g., truncated singular-value decomposition). However, when training on the first 70% of a time-series data and testing on the remaining 30%, the method fails to meaningfully extrapolate. Despite this limiting result, the technique may have benefits for simulations in a statistical steady-state or otherwise showing temporal stability. These results suggest that while the model offers a computationally efficient alternative for datasets with temporal stability, its current formulation is best suited for interpolation rather than for predicting future states in time-evolving systems. This study thus lays the groundwork for further refinement of neural network-based approaches to low-rank matrix factorization in high-dimensional plasma simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Sythesis of MCMC and Belief Propagation

Markov Chain Monte Carlo (MCMC) and Belief Propagation (BP) are the most popular algorithms for computational inference in Graphical Models (GM). In principle, MCMC is an exact probabilistic method which, however, often suffers from exponentially slow mixing. In contrast, BP is a deterministic method, which is typically fast, empirically very successful, however in general lacking control of accuracy over loopy graphs. In this paper, we introduce MCMC algorithms correcting the approximation error of BP, i.e., we provide a way to compensate for BP errors via a consecutive BP-aware MCMC. Our framework is based on the Loop Calculus (LC) approach which allows to express the BP error as a sum of weighted generalized loops. Although the full series is computationally intractable, it is known that a truncated series, summing up all 2-regular loops, is computable in polynomial-time for planar pair-wise binary GMs and it also provides a highly accurate approximation empirically. Motivated by this, we first propose a polynomial-time approximation MCMC scheme for the truncated series of general (non-planar) pair-wise binary models. Our main idea here is to use the Worm algorithm, known to provide fast mixing in other (related) problems, and then design an appropriate rejection scheme to sample 2-regular loops. Furthermore, we also design an efficient rejection-free MCMC scheme for approximating the full series. The main novelty underlying our design is in utilizing the concept of cycle basis, which provides an efficient decomposition of the generalized loops. In essence, the proposed MCMC schemes run on transformed GM built upon the non-trivial BP solution, and our experiments show that this synthesis of BP and MCMC outperforms both direct MCMC and bare BP schemes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Conditional Generative Adversarial Networks for Solving Heat Transfer Problems

Generative Adversarial Networks (GANs) have been used as a deep learning approach to solving physics and engineering problems. Using deep learning for these problems is attractive in that reasonably accurate models can be inferred from only raw data, eliminating the need to define the exact physical equations governing a problem. We expand on previous work using GANs to generate steady-state solutions to the two-dimensional heat equation. Using a basic conditional GAN (cGAN), we generate accurate solutions for rectangular domains conditioned on four edge boundary conditions (MAE < 0.5%). For finding steady-state solutions over arbitrary two-dimensional domains (not constrained to rectangles), we use a cGAN designed for image-to-image translation. We train this GAN on various types of geometric domains (circles, squares, triangles, shapes with one circular or rectangular hole), achieving accurate results on test data made up of geometries similar to those in training (MAE < 1%). For both of these GANs, we experiment with different loss function terms, showing that a term using the gradients of solution images significantly improves the basic cGAN but not the image-to-image GAN. Lastly, we show that the image-to-image GAN performs poorly when applied to two-dimensional geometries that vary in structure from training data (MAE < 8% for shapes with multiple holes or different shaped holes). This demonstrates the cGAN's lack of generalizability. While the cGAN is an accurate and computationally efficient method when trained and tested on similarly structured data, it is a much less reliable method when applied to data that is slightly different in structure from the training data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Real-time neutron multiplicity and source localization for criticality safety during fuel debris removal

Advancing neutron detection and analysis techniques for complex radiation environments is an ongoing focus in nuclear instrumentation and monitoring. This proposal presents research and development of a generalized real-time neutron monitoring and analysis system, applicable to any detector capable of producing time-tagged neutron count data. While the work is demonstrated using the Neutron Multiplication Analysis Detector (NoMAD), a modular 15-tube helium-3 (He-3) array, due to its availability, spatial resolution, and flexible deployment, the methods developed are extensible to other systems, including organic scintillators and fast digital detectors. This research investigates two complementary analytical techniques for real-time characterization of neutron emitting sources: neutron multiplicity estimation based on the Hage-Cifarelli formalism and spatial localization using supervised machine learning applied to spatial count rate patterns. These methods are designed to operate under dynamic, evolving conditions such as fuel debris retrieval or reactor startup, where neutron-emitting material geometries may be partially unknown or changing over time. By integrating statistical neutron emission data with spatial localization, this research aims to develop and evaluate methods for real time neutron monitoring, source characterization, and material verification. Key contributions include implementation of a low-latency data pipeline for continuous neutron multiplicity analysis, development and validation of machine learning models for spatial inference, and experimental evaluation of system performance under variable measurement conditions. The outcomes are intended to support applications in nuclear safeguards, verification, emergency response, and reactor startup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2

Severe acute respiratory syndrome coronavirus 2 is the causative agent of the ongoing coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6–7 days and a basic reproductive number (R 0 ) of 2.2–2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period (4.2 days). We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3–3.3 days. Assuming a serial interval of 6–9 days, we calculated a median R0 value of 5.7 (95% CI 3.8–8.9). Here, we further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SGR A* and its environment: low-mass star formation, the origin of X-ray gas and collimated outflow

We present high-resolution multiwavelength radio continuum images of the region within 150″ of Sgr A*, revealing a number of new extended features and stellar sources in this region. First, we detect a continuous 2″ east–west ridge of radio emission, linking Sgr A* and a cluster of stars associated with IRS 13 N and IRS 13E. The ridge suggests that an outflow of east–west blob-like structures is emerging from Sgr A*. In particular, we find arc-like radio structures within the ridge with morphologies suggestive of photoevaporative protoplanetary disks. We use infrared K{sub s} and L′ fluxes to show that the emission has similar characteristics to those of a protoplanetary disk irradiated by the intense radiation field at the Galactic center. This suggests that star formation has taken place within the S-cluster 2″ from Sgr A*. We suggest that the diffuse X-ray emission associated with Sgr A* is due to an expanding hot wind produced by the mass loss from B-type main sequence stars, and/or the disks of photoevaporation of low mass young stellar objects (YSOs) at a rate of ∼10{sup −6} M{sub ⊙} yr{sup −1}. The proposed model naturally reduces the inferred accretion rate and is an alternative to the inflow–outflow style models to explain the underluminous nature of Sgr A*. Second, on a scale of 5″ from Sgr A*, we detect new cometary radio and infrared sources at a position angle PA ∼ 50° which is similar to that of two other cometary sources X3 and X7, all of which face Sgr A*. In addition, we detect a striking tower of radio emission at a PA ∼ 50°–60° along the major axis of the Sgr A East supernova remnant shell on a scale of 150″ from Sgr A*. We suggest that the cometary sources and the tower feature are tracing interaction sites of a mildly relativistic jet from Sgr A* with the atmosphere of stars and the nonthermal Sgr A East shell at a PA ∼ 50°–60° with M-dot ∼1×10{sup −7} M{sub ⊙} yr{sup −1}, and opening angle 10°. Lastly, we suggest that the east–west ridge of radio emission traces an outflow that is potentially associated with past flaring activity from Sgr A*. The position angle of the outflow driven by flaring activity is close to −90°.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

WHAT IS CONTROLLING THE FRAGMENTATION IN THE INFRARED DARK CLOUD G14.225–0.506?: DIFFERENT LEVELS OF FRAGMENTATION IN TWIN HUBS

We present observations of the 1.3 mm continuum emission toward hub-N and hub-S of the infrared dark cloud G14.225–0.506 carried out with the Submillimeter Array, together with observations of the dust emission at 870 and 350 μm obtained with APEX and CSO telescopes. The large-scale dust emission of both hubs consists of a single peaked clump elongated in the direction of the associated filament. At small scales, the SMA images reveal that both hubs fragment into several dust condensations. The fragmentation level was assessed under the same conditions and we found that hub-N presents 4 fragments while hub-S is more fragmented, with 13 fragments identified. We studied the density structure by means of a simultaneous fit of the radial intensity profile at 870 and 350 μm and the spectral energy distribution adopting a Plummer-like function to describe the density structure. The parameters inferred from the model are remarkably similar in both hubs, suggesting that density structure could not be responsible for determining the fragmentation level. We estimated several physical parameters, such as the level of turbulence and the magnetic field strength, and we found no significant differences between these hubs. The Jeans analysis indicates that the observed fragmentation is more consistent with thermal Jeans fragmentation compared with a scenario in which turbulent support is included. The lower fragmentation level observed in hub-N could be explained in terms of stronger UV radiation effects from a nearby H ii region, evolutionary effects, and/or stronger magnetic fields at small scales, a scenario that should be further investigated.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Kiloparsec mass/light offsets in the galaxy pair-Lyα emitter lens system SDSS J1011+0143

We report the discovery of significant mass/light offsets in the strong gravitational lensing system SDSS J1011+0143. We use the high-resolution Hubble Space Telescope (HST) F555W- and F814W-band imaging and Sloan Digital Sky Survey (SDSS) spectroscopy of this system, which consists of a close galaxy pair with a projected separation of ≈4.2 kpc at z{sub lens} ∼ 0.331 lensing an Lyα emitter (LAE) at z{sub source} = 2.701. Comparisons between the mass peaks inferred from lens models and light peaks from HST imaging data reveal significant spatial mass/light offsets as large as 1.72 ± 0.24 ± 0.34 kpc in both filter bands. Such large mass/light offsets, not seen in isolated field lens galaxies and relaxed galaxy groups, may be related to the interactions between the two lens galaxies. The detected mass/light offsets can potentially serve as an important test for the self-interacting dark matter model. However, other mechanisms such as dynamical friction on spatially differently distributed dark matter and stars could produce similar offsets. Detailed hydrodynamical simulations of galaxy–galaxy interactions with self-interacting dark matter could accurately quantify the effects of different mechanisms. The background LAE is found to contain three distinct star-forming knots with characteristic sizes from 116 to 438 pc. It highlights the power of strong gravitational lensing in probing the otherwise too faint and unresolved structures of distance objects below subkiloparsec or even 100 pc scales through its magnification effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

IMAGING OBSERVATIONS OF THE HYDROGEN COMA OF COMET 67P/CHURYUMOV–GERASIMENKO IN 2015 SEPTEMBER BY THE PROCYON/LAICA

The water production rate of a comet is one of the fundamental parameters necessary to understand cometary activity when a comet approaches the Sun within 2.5 au, because water is the most abundant icy material in the cometary nucleus. Wide-field imaging observations of the hydrogen Lyα emission in comet 67P/Churyumov–Gerasimenko were performed by the Lyman Alpha Imaging Camera (LAICA) on board the 50 kg class micro spacecraft, the Proximate Object Close Flyby with Optical Navigation (PROCYON), on UT 2015 September 7.40, 12.37, and 13.17 (corresponding to 25.31, 30.28, and 31.08 days after the perihelion passage of the comet, respectively). We derive the water production rates, Q{sub H{sub 2O}}, of the comet from Lyα images of the comet by using a 2D axi-symmetric Direct Simulation Monte-Carlo model of the atomic hydrogen coma; (1.46 ± 0.47) × 10{sup 28}, (1.24 ± 0.40) × 10{sup 28}, and (1.30 ± 0.42) × 10{sup 28} molecules s{sup −1} on 7.40, 12.37, and 13.17 September, respectively. These values are comparable to the values from in situ measurements by the Rosetta instruments in the 2015 apparition and the ground-based and space observations during the past apparitions. The comet did not show significant secular change in average water production rates just after the perihelion passage for the apparitions from 1982 to 2015. We emphasize that the measurements of absolute Q{sub H{sub 2O}} based on the wide field of view (e.g., by the LAICA/PROCYON) are so important to judge the soundness of the coma models used to infer Q{sub H{sub 2O}} based on in situ measurements by spacecraft, like the Rosetta.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Excitation and Depletion of the Asteroid Belt in the Early Instability Scenario

Containing only a few percentages of the mass of the moon, the current asteroid belt is around three to four orders of magnitude smaller than its primordial mass inferred from disk models. Yet dynamical studies have shown that the asteroid belt could not have been depleted by more than about an order of magnitude over the past ∼4 Gyr. The remainder of the mass loss must have taken place during an earlier phase of the solar system’s evolution. An orbital instability in the outer solar system occurring during the process of terrestrial planet formation can reproduce the broad characteristics of the inner solar system. Here, we test the viability of this model within the constraints of the main belt’s low present-day mass and orbital structure. Although previous studies modeled asteroids as massless test particles because of limited computing power, our work uses graphics processing unit acceleration to model a fully self-gravitating asteroid belt. We find that depletion in the main belt is related to the giant planets’ exact evolution within the orbital instability. Simulations that produce the closest matches to the giant planets’ current orbits deplete the main belt by two to three orders of magnitude. These simulated asteroid belts are also good matches to the actual asteroid belt in terms of their radial mixing and broad orbital structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Relativistic Magnetic Reconnection in Electron–Positron–Proton Plasmas: Implications for Jets of Active Galactic Nuclei

Magnetic reconnection is often invoked to explain the nonthermal radiation of relativistic outflows, including jets of active galactic nuclei (AGNs). Motivated by the largely unknown plasma composition of AGN jets, we study reconnection in the unexplored regime of electron–positron–proton (pair-proton) plasmas with large-scale two-dimensional particle-in-cell simulations. We cover a wide range of pair multiplicities (lepton-to-proton number ratio κ = 1–199) for different values of the all-species plasma magnetization (σ = 1, 3, and 10) and electron temperature (${{\rm{\Theta }}}_{e}\equiv {{kT}}_{e}/{m}_{e}{c}^{2}=0.1\mbox{--}100$). We focus on the dependence of the post-reconnection energy partition and lepton energy spectra on the hot pair plasma magnetization ${\sigma }_{e,h}$ (i.e., the ratio of magnetic to pair enthalpy densities). We find that the post-reconnection energy is shared roughly equally between magnetic fields, pairs, and protons for ${\sigma }_{e,h}$ gsim 3. We empirically find that the mean lepton Lorentz factor in the post-reconnection region depends on σ, Θ e , and ${\sigma }_{e,h}$ as $\langle {\gamma }_{e}-1\rangle \approx \sqrt{\sigma }(1+4{{\rm{\Theta }}}_{e})\left(1+{\sigma }_{e,h}/30\right)$, for σ ≥ 1. The high-energy part of the post-reconnection lepton energy distributions can be described by a power law, whose slope is mainly controlled by ${\sigma }_{e,h}$ for κ gsim 3–6, with harder power laws obtained for higher magnetizations. We finally show that reconnection in pair-proton plasmas with multiplicities κ ~ 1–20, magnetizations σ ~ 1–10, and temperatures Θ e ~ 1–10 results in particle power-law slopes and average electron Lorentz factors that are consistent with those inferred in leptonic models of AGN jet emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

SAGAbg. I. A Near-unity Mass-loading Factor in Low-mass Galaxies via Their Low-redshift Evolution in Stellar Mass, Oxygen Abundance, and Star Formation Rate

Measuring the relation between star formation and galactic winds is observationally difficult. In this work we make an indirect measurement of the mass-loading factor (the ratio between the mass outflow rate and star formation rate) in low-mass galaxies using a differential approach to modeling the low-redshift evolution of the star-forming main sequence and mass–metallicity relation. We use Satellites Around Galactic Analogs (SAGA) background galaxies, i.e., spectra observed by the SAGA Survey that are not associated with the main SAGA host galaxies, to construct a sample of 11,925 spectroscopically confirmed low-mass galaxies from 0.01 ≲ z ≤ 0.21 and measure auroral line metallicities for 120 galaxies. The crux of the method is to use the lowest-redshift galaxies as the boundary condition of our model, and to infer a mass-loading factor for the sample by comparing the expected evolution of the low-redshift reference sample in stellar mass, gas-phase metallicity, and star formation rate against the observed properties of the sample at higher redshift. We infer a mass-loading factor of η m = $0.92^{+1.76}_{-0.74}$, which is in line with direct measurements of the mass-loading factor from the literature despite the drastically different sets of assumptions needed for each approach. While our estimate of the mass-loading factor is in good agreement with recent galaxy simulations that focus on resolving the dynamics of the interstellar medium, it is smaller by over an order of magnitude than the mass-loading factor produced by many contemporary cosmological simulations.

79 ASTRONOMY AND ASTROPHYSICS↗