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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams

Situational awareness data is a prototypical example of structured heterogeneous streaming data with asynchronous timing that can quickly scale beyond the cognitive power of a human analyst. We present deep learning methods that can train in real time from unlabeled streams and provide probabilistic anomaly scores. We compare our novel deep and recurrent neural network models to three baseline systems using threat detection recall on the CERT Insider Threat Dataset v6.2. In our experiments, our deep neural network and our recurrent neural network systems outperformed all baselines, and we found that using aggregated activity count features yielded the best performance. Our best model produces on average an anomaly score of 95.53 percentile for the day, suggesting it can facilitate a great reduction in analyst workload. Our models are also interpretable, in that they break down the anomaly score into individual features of user behavior, which could further aid analysts in reviewing potential cases of insider threat.

Tuor, Aaron R.↗
DOE OSTI2025

Unraveling membrane electrode assembly design for electrochemical conversion of carbon dioxide to formate/formic acid

This work presents a one-dimensional continuum modeling approach to investigate various cell architectures used for electrochemical conversion of CO 2 to formate/formic acid. Ion transport is simulated by a system of generalized modified Poisson–Nernst–Planck (GMPNP) equations that reflect the reactive transport phenomena including steric effects as the electrolyte solutions become concentrated. In the cathode catalyst layer, ionic current contributions from both the supporting electrolyte and solid-state ionomer are considered. Voltage and CO 2 utilization breakdowns are utilized to deconvolute the impacts of the cell architecture. The origins of (bi)carbonate formation in the cathode are explored, as the subsequent decrease in CO 2 availability is a key reason for low faradaic efficiencies to formate/formic acid. In addition, the role of a supporting electrolyte (KOH) is investigated to understand its tradeoffs: while the K + ions can improve both conductivity and electrochemically active surface area in the cathode, the presence of OH − ions raises the pH and leads to deleterious formation of (bi)carbonates. To this end, we also present parametric studies on the concentration and flow rate of supplied KOH to the cell, to establish a path towards eliminating the need for a supporting electrolyte.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

An evaluation of in vivo models for toxicokinetics of hexavalent chromium in the stomach

Hexavalent chromium (Cr6) is a drinking water contaminant that has been detected in most of the water systems throughout the United States. In 2-year drinking water bioassays, the National Toxicology Program (NTP) found clear evidence of carcinogenic activity in male and female rats and mice. Because reduction of Cr6 to trivalent chromium (Cr3) is an important detoxifying step in the gastrointestinal (GI) tract prior to systemic absorption, models have been developed to estimate the extent of reduction in humans and animals. The objective of this work was to use a revised model of ex vivo Cr6 reduction kinetics in gastric juice to analyze the potential reduction kinetics under in vivo conditions for mice, rats and humans. A published physiologically-based pharmacokinetic (PBPK) model was adapted to incorporate the new reduction model. This paper focuses on the toxicokinetics of Cr6 in the stomach compartment, where most of the extracellular Cr6 reduction is believed to occur in humans. Within the range of doses administered by the NTP bioassays, neither the original nor revised models predict saturation of stomach reducing capacity to occur in vivo if applying default parameters. However, both models still indicate that mice exhibit the lowest extent of reduction in the stomach, meaning that a higher percentage of the Cr6 dose may escape stomach reduction in that species. Similarly, both models predict that humans exhibit the highest extent of reduction at low doses. - Highlights: • We outline a new in vivo model for hexavalent chromium reduction in the stomach. • We examine in vivo reduction for mice, rats, and humans under varying conditions. • Species differences in toxicokinetics may explain susceptibility. • We show that a simplified stomach reduction model is adequate for extrapolation. • Internal dose uncertainties still exist.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Experimental and numerical evaluations of the energy savings potential of thermally anisotropic composites

Previous numerical studies conducted in FY 17 showed that the application of thermally anisotropic composites (TACs) coupled with a heat sink/source can re-direct and reduce unwanted heat flows through exterior building walls, with associated reductions in envelope-generated heating and cooling loads in buildings. The numerical analyses included two-dimensional finite element models (FEM) of wall assemblies and whole-building modeling to estimate the annual reductions in wall-generated heating and cooling loads, and associated energy consumption. The FY17 study used combined FEM and EnergyPlus (E+) simulations of a typical two-story, single-family DOE prototype residential building model.1 We studied performance of several configurations of walls containing exterior continuous insulation and thermally anisotropic composites on the wall exterior. The study showed that annual energy cost savings of up to $270 are possible under Phoenix and Baltimore weather conditions, by retrofitting a baseline wall with an anisotropic composite. In the cases considered, the TAC consisted of three layers of aluminum foil-faced foam boards. In general, it was found that the anisotropic composites were effective in reducing cooling loads; more investigation on heating loads is needed. During FY 18, ORNL performed a series of laboratory tests of anisotropic composites and appropriate heat sink/source, validated the FEMs used for the FY17 numerical study using experimental data, and revisited the whole-building modeling. Wall prototypes were created and tested in ORNL’s large scale climate simulator (LSCS) under variable conditions approximating summer and winter time periods.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Forest response to increased disturbance in the central Amazon and comparison to western Amazonian forests

Uncertainties surrounding vegetation response to increased disturbance rates associated with climate change remains a major global change issue for Amazonian forests. Additionally, turnover rates computed as the average of mortality and recruitment rates in the western Amazon basin are doubled when compared to the central Amazon, and notable gradients currently exist in specific wood density and aboveground biomass (AGB) between these two regions. This study investigates the extent to which the variation in disturbance regimes contributes to these regional gradients. To address this issue, we evaluated disturbance–recovery processes in a central Amazonian forest under two scenarios of increased disturbance rates using first ZELIG-TROP, a dynamic vegetation gap model which we calibrated using long-term inventory data, and second using the Community Land Model (CLM), a global land surface model that is part of the Community Earth System Model (CESM). Upon doubling the mortality rate in the central Amazon to mirror the natural disturbance regime in the western Amazon of ~2% mortality, the two regions continued to differ in multiple forest processes. With the inclusion of elevated natural disturbances, at steady state, AGB significantly decreased by 41.9% with no significant difference between modeled AGB and empirical AGB from the western Amazon data sets (104 vs. 107 Mg C ha -1 , respectively). However, different processes were responsible for the reductions in AGB between the models and empirical data set. The empirical data set suggests that a decrease in wood density is a driver leading to the reduction in AGB. While decreased stand basal area was the driver of AGB loss in ZELIG-TROP, a forest attribute that does not significantly vary across the Amazon Basin. Further comparisons found that stem density, specific wood density, and basal area growth rates differed between the two Amazonian regions. Last, to help quantify the impacts of increased disturbances on the climate and earth system, we evaluated the fidelity of tree mortality and disturbance in CLM. Similar to ZELIG-TROP, CLM predicted a net carbon loss of 49.9%, with an insignificant effect on aboveground net primary productivity (ANPP). Decreased leaf area index (LAI) was the driver of AGB loss in CLM, another forest attribute that does not significantly vary across the Amazon Basin, and the temporal variability in carbon stock and fluxes was not replicated in CLM. Our results suggest that (1) the variability between regions cannot be entirely explained by the variability in disturbance regime, but rather potentially sensitive to intrinsic environmental factors; or (2) the models are not accurately simulating all tropical forest characteristics in response to increased disturbances.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

How does increasing horizontal resolution in a global climate model improve the simulation of aerosol-cloud interactions?

The Community Atmosphere Model Version 5 is run at horizontal grid spacing of 2, 1, 0.5, and 0.25 degrees, with the meteorology nudged towards the Year Of Tropical Convection analysis, and cloud simulators and the collocated A-Train satellite observations are used to explore the resolution dependence of aerosol-cloud interactions. The higher-resolution model produces results that agree better with observations, showing an increase of susceptibility of cloud droplet size, indicating a stronger first aerosol indirect forcing (AIF), and a decrease of susceptibility of precipitation probability, suggesting a weaker second AIF. The resolution sensitivities of AIF are attributed to those of droplet nucleation and precipitation parameterizations. The annual average AIF in the northern hemisphere mid-latitudes (where most anthropogenic emissions occur) in the 0.25° model is reduced by about 1 W m⁻² (-30%) compared to the 2° model, leading to a 0.26 W m⁻² reduction (-15%) in the global annual average AIF.

Ma, Po -Lun↗
DOE OSTI2022

Measurements of atoms and metastable species in N 2 and H 2 –N 2 nanosecond pulse plasmas

We report time-resolved, absolute number densities of metastable N 2 (A 3 Σ u + , v = 0, 1) molecules, ground state N 2 and H atoms, and rotational–translational temperature have been measured by tunable diode laser absorption spectroscopy and two-photon absorption laser-induced fluorescence in diffuse N 2 and N 2 –H 2 plasmas during and after a nanosecond pulse discharge burst. Comparison of the measurement results with the kinetic modeling predictions, specifically the significant reduction of the N 2 (A 3 Σ u + ) populations and the rate of N atom generation during the burst, suggests that these two trends are related. The slow N atom decay in the afterglow, on a time scale longer than the discharge burst, demonstrates that the latter trend is not affected by N atom recombination, diffusion to the walls, or convection with the flow. This leads to the conclusion that the energy pooling in collisions of N 2 (A 3 Σ u + ) molecules is a major channel of N 2 dissociation in electric discharges where a significant fraction of the input energy goes to electronic excitation of N 2 . Additional measurements in a 1% H 2 –N 2 mixture demonstrate a further significant reduction of N 2 (A 3 Σ u + , v = 0, 1) populations, due to the rapid quenching by H atoms accumulating in the plasma. Comparison with the modeling predictions suggests that the N 2 (A 3 Σ u + ) molecules may be initially formed in the highly vibrationally excited states. The reduction of the N 2 (A 3 Σ u + ) number density also diminishes the contribution of the energy pooling process into N2 dissociation, thus reducing the N atom number density. The rate of N atom generation during the burst also decreases, due to its strong coupling to N 2 (A 3 Σ u + , v) populations. On the other hand, the rate of H atom generation, produced predominantly by the dissociative quenching of the excited electronic states of N 2 by H 2 , remains about the same during the burst, resulting in a nearly linear rise in the H atom number density. Comparison of the kinetic model predictions with the experimental results suggests that the yield of H atoms during the quenching of the excited electronic state of N 2 by molecular H 2 is significantly less than 100%. The present results quantify the yield of N and H atoms in high-pressure H 2 –N 2 plasmas, which have significant potential for ammonia generation using plasma-assisted catalysis

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Study on Magnetization Losses in Soldered-Stacked-Square (3S) HTS Wires with 1 mm Width

Magnetization loss of high-temperature superconducting (HTS) wires is usually considered as a critical issue in power applications. In order to reduce magnetization loss, a narrow soldered-stacked-square (3S) HTS wire with 1 mm width is firstly proposed by our group. And as a novel HTS wire type, its magnetization loss should be significantly understood before applied in further application. In this study, we fabricate the 1-mm-wide 3S wires with 2+4c, 4+2c, and 6+0c structures, and evaluate their magnetization loss experimentally and numerically. In the fabrication process of the 3S wires, a newly suggested technology, laser cutting, is adopted. The results show that the magnetization loss in (4+2c)-wire is independent of the frequency under perpendicular field but dependent on the frequency under parallel field. This may be considered that both eddy current loss and coupling loss are contained in the case of parallel field, besides hysteresis loss. Moreover, the different structures of the 3S wires will not affect the magnetization loss under perpendicular fields, but influence the magnetization loss under parallel fields. And these numerical results for parallel field have larger deviations compared with measured magnetization loss because only hysteresis loss is considered in the numerical model. Finally, a considerable reduction of the magnetization loss in the 3S wire is observed in the comparison with that in the original tape.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Enhancing Interpretability in Generative Modeling: Statistically Disentangled Latent Spaces Guided by Generative Factors in Scientific Datasets

This study addresses the challenge of statistically extracting generative factors from complex, high-dimensional datasets in unsupervised or semi-supervised settings. We investigate encoder-decoder-based generative models for nonlinear dimensionality reduction, focusing on disentangling low-dimensional latent variables corresponding to independent physical factors. Introducing Aux-VAE, a novel architecture within the classical Variational Autoencoder framework, we achieve disentanglement with minimal modifications to the standard VAE loss function by leveraging prior statistical knowledge through auxiliary variables. These variables guide the shaping of the latent space by aligning latent factors with learned auxiliary variables. We validate the efficacy of Aux-VAE through comparative assessments on multiple datasets, including astronomical simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Kinetic Modeling of the Reaction Rate for Quartz and Carbon Black Pellet

The kinetic modeling for the carbothermal reduction reaction rate in quartz and carbon black pellets is studied at different temperatures, under varying CO partial pressures in ambient atmosphere, varying carbon contents, different quartz particle sizes, and different crucible opening areas. Carbon black is produced by the cracking of natural gas. The activation energy of the SiC-producing step was determined to be 594 kJ/mol. The averaged pre-exponential factor A obtained from 1898 K, 1923 K, and 1948 K (1625 °C, 1650 °C, and 1675 °C) is 2.62E+16 min -1 . The reaction rate of the gas-solid interface factor, fix-C content (X fix-C ), temperature (T), and CO partial pressure (X CO ) can be expressed as follows:((d pct)/(dt))=(1-0.40×X fix-C -0.86 ×pct)×2.62×10 16 ×exp(-(594000/(RT)))×(2.6-0.015×X co ).

36 MATERIALS SCIENCE↗
DOE OSTI2019

Intelligent load pattern modeling and denoising using improved variational mode decomposition for various calendar periods

This paper proposes a novel approach to identify the load patterns considering calendar impact and denoising process, which advances the state of art of load identification and load forecasting to a more flexible and adaptive extent by revealing the correlation between load profile and the substantial influence factors. With the rapid development and the promising application of energy intemet and grid modernization, the accurate load modeling and forecasting especially by load pattern modeling (LPM) have become more and more critical to observe and estimate load profile so as to optimize the operation efficiency of the power grid. Traditional methods mostly focus on the static LPM itself which are unable to account the non-linear and highly dynamic load fluctuations in order to balance the demand of the power grid during various calendar period (VCP) scheduling. In this paper, a load pattern modeling method for power grid considering the impact of typical calendar effects is proposed using a combination of improved variational mode decomposition (IVMD) and deep belief network (DBN) algorithm. Firstly, an index of load curve curvature (LCC) is proposed to improve the selection of value K in the conventional VMD algorithm. The value K of the intrinsic modality is determined by adopting LCC to better quantify the average instantaneous frequency of the modal decomposition of the VMD and to reduce the elevated stochasticity of k. Secondly, an optimization formulation is developed based on adaptive segmented loop decomposition of the typical correlation coefficient to suppress the edge effect in VMD decomposition, which would enable the reconstructed curve to incorporate the variabilities from the initial data. Finally, the IVMD and DBN algorithms are jointly implemented to optimize the accuracy of VCP load pattern modeling curve regression. Numerical examples have been performed with the results proving that the proposed method significantly outperforms the state-of-art in reducing the modeling error of VCP load curve, improving the overall forecasting accuracy, and reducing load dispatching cost.

deep belief network↗
DOE OSTI2023

Evaluation of dual-weighted residual and machine learning error estimation for projection-based reduced-order models of steady partial differential equations

Projection-based reduced-order models (pROMs) show great promise as a means to accelerate many-query applications such as forward error propagation, solving inverse problems, and design optimization. In order to deploy pROMs in the context of high-consequence decision making, accurate error estimates are required to determine the region(s) of applicability in the parameter space. The following paper considers the dual-weighted residual (DWR) error estimate for pROMs and compares it to another promising pROM error estimate, machine learned error models (MLEM). Here, we show how DWR can be applied to ROMs and then evaluate DWR on two partial differential equations (PDEs): a two-dimensional linear convection–reaction–diffusion equation, and a three-dimensional static hyper-elastic beam. It is shown that DWR is able to estimate errors for pROMs extrapolating outside of their training set while MLEM is best suited for pROMs used to interpolate within the pROM training set.

42 ENGINEERING↗
DOE OSTI2021

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction

Here, we put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements. Toward emerging applications of digital twins in aviation, the proposed approach allows for constructing a realtime predictive tool for wake-vortex transport and decay systems. We build on the fact that in realistic application, there are uncertainties in initial and boundary conditions, model parameters, as well as measurements. Moreover, conventional nonlinear ROMs based on Galerkin projection (GROMs) suffer from imperfection and solution instabilities, especially for advection-dominated flows with slow decay in the Kolmogorov n-width. In the presented LSTM nudging (LSTM-N) approach, we fuse forecasts from a combination of imperfect GROM and uncertain state estimates, with sparse Eulerian sensor measurements to provide more reliable predictions in a dynamical data assimilation framework. We illustrate our concept by solving the two-dimensional vorticity transport equation. We investigate the effects of measurements noise and state estimate uncertainty on the performance of the LSTM-N behavior. We also demonstrate that it can sufficiently handle different levels of temporal and spatial measurement sparsity, and offer a huge potential in developing next-generation digital twin technologies for aerospace applications.

42 ENGINEERING↗
DOE OSTI2025

Experiments on a vapor compression air conditioner with liquid desiccants for efficient dehumidification

Buildings require air conditioning systems that not only cool and dehumidify supply air but also provide sufficient ventilation to ensure indoor air quality and occupant comfort. However, standard recirculation systems-which introduce about a 10 % to 20 % fraction of outdoor air-often fail to deliver air that is precisely cooled and dry, particularly because 80-90 % of the ventilation cooling load is latent. Mixing humid ventilation air with recirculated indoor air increases the energy and costs required to condition the air to comfortable levels. Dedicated outdoor air systems (DOASs) are designed to handle this latent dominated ventilation load and thus need to have efficient humidity removal. Many cooling cycles can perform this task. Here we describe a liquid desiccant DOAS, which combines a vapor compression cycle and a liquid desiccant absorber and desorber pair. We present its performance at 26 operating conditions and a thermodynamic model which can accurately predict the moisture removal efficiency. The model's performance predictions have a mean percentage error of 2.5 % and a coefficient of variation of the root mean square error of 7.5 %. We also compare the performance of this vapor-compression-coupled liquid desiccant system with a standard vapor compression system with the same components but no liquid desiccant. For the 26 conditions tested in this study, this comparison shows that adding liquid desiccants lowers the required evaporator cooling load by 21 %, allows for 25 % lower compressor volumetric capacity, and 25 % lower electricity use. Future work will leverage this model to quantify the reduction in annual electricity use across different climates, including the need for a standard vapor compression system to reheat the air during some of the year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Persistent high PM 2.5 pollution driven by unfavorable meteorological conditions during the COVID-19 lockdown period in the Beijing-Tianjin-Hebei region, China

Lockdown measures to curtail the COVID-19 pandemic in China halted most nonessential activities on January 23, 2020. Despite significant reductions in anthropogenic emissions, the Beijing-Tianjin-Hebei (BTH) region still experienced high air pollution concentrations. In this work, employing two emissions reduction scenarios, the Community Multiscale Air Quality (CMAQ) model was used to investigate the PM 2.5 concentrations change in this region. The model using the scenario (C3) with greater traffic reductions performed better compared to the observed PM 2.5 . Compared with the no reductions base-case (scenario C1), PM 2.5 reductions with scenario C3 were 2.70, 2.53, 2.90, 2.98, 3.30, 2.81, 2.82, 2.98, 2.68, and 2.83 µg/m 3 in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai, respectively. During high-pollution days in scenario C3, the percentage reductions in PM 2.5 concentrations in Beijing, Tianjin, Shijiazhuang, Baoding, Cangzhou, Chengde, Handan, Hengshui, Tangshan, and Xingtai were 3.76, 3.54, 3.28, 3.22, 3.57, 3.56, 3.47, 6.10, 3.61, and 3.67%, respectively. However, significant increases caused by unfavorable meteorological conditions counteracted the emissions reduction effects resulting in high air pollution in BTH region during the lockdown period. This study shows that effective air pollution control strategies incorporating these results are urgently required in BTH to avoid severe pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Depolymerization of corn stover lignin with bulk molybdenum carbide catalysts

Depolymerization of lignin into aromatic compounds in high yield for production of fuels and chemicals is vital to realize an economically competitive biorefinery. In this study, undoped and nickel-doped bulk molybdenum carbides were synthesized and evaluated in reductive depolymerization of lignin model compound and corn stover lignin in the presence of hydrogen. The highest lignin monomer yield of 37.3% was obtained with Ni-Mo 2 C and ethanol/water solvent. Nickel doping promoted the depolymerization performance of Mo 2 C, by increasing the number of metallic sites while decreasing that of acidic sites. This change in active site distribution mitigated CC coupling reactions and coking. Ethanol addition to the water solvent also significantly suppressed CC coupling. Mixing carbides with zeolites decreased monomer yields, presumably due to excessive repolymerization of reactive intermediates over the acidic zeolite. This work highlights the feasibility of developing effective lignin depolymerization catalysts by fine-tuning the properties of molybdenum carbide catalysts and solvent systems.

09 BIOMASS FUELS↗