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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Shielded-Twisted-Pair Cable Model for Chafe Fault Detection via Time-Domain Reflectometry

This report details the development, verification, and validation of an innovative physics-based model of electrical signal propagation through shielded-twisted-pair cable, which is commonly found on aircraft and offers an ideal proving ground for detection of small holes in a shield well before catastrophic damage occurs. The accuracy of this model is verified through numerical electromagnetic simulations using a commercially available software tool. The model is shown to be representative of more realistic (analytically intractable) cable configurations as well. A probabilistic framework is developed for validating the model accuracy with reflectometry data obtained from real aircraft-grade cables chafed in the laboratory.

Schuet, Stefan R.↗
DOE OSTI2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification

With increased adoption of supervised deep learning methods for work with cosmological survey data, the assessment of data perturbation effects (that can naturally occur in the data processing and analysis pipelines) and the development of methods that increase model robustness are increasingly important. In the context of morphological classification of galaxies, we study the effects of perturbations in imaging data. In particular, we examine the consequences of using neural networks when training on baseline data and testing on perturbed data. We consider perturbations associated with two primary sources: (a) increased observational noise as represented by higher levels of Poisson noise and (b) data processing noise incurred by steps such as image compression or telescope errors as represented by one-pixel adversarial attacks. We also test the efficacy of domain adaptation techniques in mitigating the perturbation-driven errors. We use classification accuracy, latent space visualizations, and latent space distance to assess model robustness in the face of these perturbations. For deep learning models without domain adaptation, we find that processing pixel-level errors easily flip the classification into an incorrect class and that higher observational noise makes the model trained on low-noise data unable to classify galaxy morphologies. On the other hand, we show that training with domain adaptation improves model robustness and mitigates the effects of these perturbations, improving the classification accuracy up to 23% on data with higher observational noise. Domain adaptation also increases up to a factor of ${\approx}2.3$ the latent space distance between the baseline and the incorrectly classified one-pixel perturbed image, making the model more robust to inadvertent perturbations. Successful development and implementation of methods that increase model robustness in astronomical survey pipelines will help pave the way for many more uses of deep learning for astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗
DOE OSTI2023

Amino Acid Residues Controlling Domain Interaction and Interdomain Electron Transfer in Cellobiose Dehydrogenase

The function of cellobiose dehydrogenase (CDH) in biosensors, biofuel cells, and as a physiological redox partner of lytic polysaccharide monooxygenase (LPMO) is based on its role as an electron donor. Before donating electrons to LPMO or electrodes, an interdomain electron transfer from the catalytic FAD-containing dehydrogenase domain to the electron shuttling cytochrome domain of CDH is required. This study investigates the role of two crucial amino acids located at the dehydrogenase domain on domain interaction and interdomain electron transfer by structure-based engineering. The electron transfer kinetics of wild-type Myriococcum thermophilum CDH and its variants M309A, R698S, and M309A/R698S were analyzed by stopped-flow spectrophotometry and structural effects were studied by small-angle X-ray scattering. The data show that R698 is essential to pull the cytochrome domain close to the dehydrogenase domain and orient the heme propionate group towards the FAD, while M309 is an integral part of the electron transfer pathway – its mutation reducing the interdomain electron transfer 10-fold. Structural models and molecular dynamics simulations pinpoint the action of these two residues on the domain interaction and interdomain electron transfer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors

Abstract Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.

Computer Science↗
NASA NTRS2021

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS2017

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗
DOE OSTI2023

Defects in RbF - Treated Cu(InxGal-x)Se2 Solar Cells and Their Impact on Voc

Cu(In,Ga)Se2 solar cell efficiency is limited by VOC due in large part to bulk defects limiting lifetime, but alkali treatments such as RbF recover some of the VOC loss. In this work, defects in RbF-treated and untreated CIGS were quantitatively characterized using DLTS and DLOS, and three main defects were identified in each sample. The RbF-PDT resulted in a large decrease in the mid-gap trap concentration, which was accompanied by a large improvement in minority carrier lifetime. This lifetime improvement combined with a change in doping accounted for a significant portion of the VOC improvement in the RbF CIGS.

charge carrier lifetime↗
DOE OSTI2022

Normalization of ZZ instanton amplitudes in minimal string theory

We use insights from string field theory to analyze and cure the divergences in the cylinder diagram in minimal string theory with both boundaries lying on a ZZ brane. We focus on theories with worldsheet matter consisting of the (2, p) minimal model plus Liouville theory, with total central charge 26, together with the usual bc-ghosts. The string field theory procedure gives a finite, purely imaginary normalization constant for non-perturbative effects in minimal string theory, or doubly non-perturbative effects in JT gravity. We find precise agreement with the prediction from the dual double-scaled one-matrix integral. We also make a few remarks about the extension of this result to the more general (p', p) minimal string.

2D gravity↗
NASA NTRS1999

Modeling Studies of PVT Growth of ZnSe: Current Status and Future Course

Bulk growth of wide band gap II-VI semiconductors by physical vapor transport (PVT) has been developed and refined over the past several years at NASA Marshall Space Flight Center. Results from a modeling study of PVT crystal growth of ZnSe are reported in this paper. The PVT process is numerically investigated using a two-dimensional formulation of the governing equations and associated boundary conditions. Both the incompressible Boussinesq approximation and a compressible model are tested to determine the influence of gravity on the process and to discern the differences between the two approaches. The influence of a residual gas is included in the models. The results show that both the incompressible and compressible approximations provide comparable results and the presence of a residual gas tends to measurably reduce the mass flux in the system. Detailed flow, thermal and concentration profiles are provided. The simulations show that the Stefan flux dominates the system flow field and the subtle gravitational effects can be gauged by subtracting this flux from the calculated profiles. Shear flows, due to solutal buoyancy, of the order of 50 microns/s for the liorizont,-d growth orientation and 10 microns/s for the vertical orientation are predicted. Whether these flows can fully account for the observed gravity related growth morphological effects and inhomogeneous solute and dopant distributions is a matter of conjecture. A template for future modeling efforts in this area is suggested which incorporates a mathematical approach to the tracking of the growth front based on energy of formation concepts.

Ramachandran, N.↗
DOE OSTI2024

Fire weather compromises forestation-reliant climate mitigation pathways

Forestation can contribute to climate change mitigation. However, increasing frequency and intensity of climate extremes are posed to have profound impact on forests and consequently on the mitigation potential of forestation efforts. In this perspective, we critically assess forestation-reliant climate mitigation scenarios from five different integrated assessment models (IAMs) by showcasing the spatially explicit exposure of forests to fire weather and the simulated increase in global annual burned area. We provide a detailed description of the feedback from climate change to forest carbon uptake in IAMs. Few IAMs are currently accounting for feedback mechanisms like loss from fire disturbance. Consequently, many forestation areas proposed by IAM scenarios will be exposed to fire-promoting weather conditions and without costly prevention measures might be object to frequent burning. We conclude that the actual climate mitigation portfolio in IAM scenarios is subject to substantial uncertainty and that the risk of overly optimistic estimates of negative emission potential of forestation should be avoided. As a way forward we propose how to integrate more detailed climate information when modeling climate mitigation pathways heavily relying on forestation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

Case-based approach to handling aircraft malfunctions

Reasoning about physical systems in operation is a difficult task, and any attempt to automate the process must overcome the problems of modeling normal behavior, diagnosing faults, and predicting future behavior. This paper describes a prototypical case-based reasoner (CBR) that operates in the domain of in-flight fault diagnosis and prognosis of aviation subsystems, particularly jet engines. The reasoner operates on the observation that the ability of a CBR program to reason about physical systems can be significantly enhanced by the addition to the CBR program of a model of the physical system to describe the system's structural, functional, and causal behavior.

Karamouzis, Stamos T.↗
DOE OSTI2022

Identification of Critical Material Attributes in Lignin Streams Based on Pseudomonas putida Performance

Variability in chemical composition of corn stover feedstocks has been suggested to play a role in biocatalyst performance during the conversion of lignocellulosic biomass to value-added compounds. In previous studies, we investigated the performance of Pseudomonas putida CJ781 - an engineered bacterium that converts aromatic compounds to muconate - on various lignin streams produced from the deacetylation of corn stover, and we found significant differences on muconate production. To better understand the origin of these differences, we down selected twenty-two compounds from literature - that had previously been detected as extractives in lignin streams - and we analyzed their concentrations in 12 lignin streams generated from different feedstocks. P. putida CJ781 was then cultivated in mock lignin streams supplemented with various concentrations of these compounds. Bacterial growth was tracked in microtiter plates and the performance was measured by comparing maximum growth rates among conditions. At maximum concentrations that may be found in lignin streams, sodium was the material attribute that limited growth rate in a greater extent, with a reduction in growth rate by 8 to 37%, depending on the counter ion, with sodium nitrate being the most inhibitory, followed by sodium acetate, sodium chloride, and sodium sulfate. Ammonium acetate was also found to be inhibitory at average concentrations of ammonium in lignin streams, reducing maximum growth rate by 18%. Overall, the data from this study has allowed to down select critical material attributes in lignin streams and process parameters that significantly affect the performance of P. putida and will be used as input to predictive models that aim to reduce risks attributed to feedstock variability in lignocellulosic biorefineries.

biocatalyst↗
DOE OSTI2023

Recreating the California New Year's Flood Event of 1997 in a Regionally Refined Earth System Model

Abstract The 1997 New Year's flood event was the most costly in California's history. This compound extreme event was driven by a category 5 atmospheric river that led to widespread snowmelt. Extreme precipitation, snowmelt, and saturated soils produced heavy runoff causing widespread inundation in the Sacramento Valley. This study recreates the 1997 flood using the Regionally Refined Mesh capabilities of the Energy Exascale Earth System Model (RRM‐E3SM) under prescribed ocean conditions. Understanding the processes causing extreme events informs practical efforts to anticipate and prepare for such events in the future, and also provides a rich context to evaluate model skill in representing extremes. Three California‐focused RRM grids, with horizontal resolution refinement of 14 km down to 3.5 km, and six forecast lead times, 28 December 1996 at 00Z through 30 December 1996 at 12Z, are assessed for their ability to recreate the 1997 flood. Planetary to synoptic scale atmospheric circulations and integrated vapor transport are weakly influenced by horizontal resolution refinement over California. Topography and mesoscale circulations, such as the Sierra barrier jet, are better represented at finer horizontal resolutions resulting in better estimates of storm total precipitation and storm duration snowpack changes. Traditional time‐series and causal analysis frameworks are used to examine runoff sensitivities state‐wide and above major reservoirs. These frameworks show that horizontal resolution plays a more prominent role in shaping reservoir inflows, namely the magnitude and time‐series shape, than forecast lead time, 2‐to‐4 days prior to the 1997 flood onset.

54 ENVIRONMENTAL SCIENCES↗