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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data for Influence of Particle Size on NIR Spectroscopic Characterization of Sorghum Biomass for the Biofuel Industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

Biomass Analytics↗
NASA NTRS1972

The performance of a noncoherent FSK receiver preceded by a bandpass limiter.

Many applications of the bandpass limiter involve either coherent or noncoherent demodulation following the limiter. In this paper we study the performance of a noncoherent frequency-shift keying (FSK) receiver when it is preceded by a bandpass limiter. In particular, we obtain expressions for signal suppression factor, output signal-to-noise ratio (SNR), and error probability from which one can assess the degradation in performance of the receiver due to the presence of the limiter.

Simon, M. K.↗
DOE OSTI2020

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Improvements to CTF for Modeling of Boiling Water Reactor Geometry and Operating Conditions

This report documents work done to improve CTF modeling of boiling water reactor (BWR) designs during FY 2020. Several improvements were made to the geometry modeling capabilities, including adding support for modeling of inlet flow orifices, axially varying large water rods, channel boxes with large corner round radii, and quarter symmetry models. Work was also done to improve on the numerical stability and run-time performance of CTF in Virtual Environment for Reactor Applications (VERA) for core-scale BWR problems. An outer iteration loop was implemented that ensures mass and energy are conserved before moving on to the next time step in the solution. The ability to use a direct solver for the pressure matrix was also added, which reduces the matrix solution error and improves code stability and run-time performance. Improvements to the pressure balance iteration loop were needed to allow CTF to be used in a coupled VERA solution of a model of Hatch that was developed. Finally, various improvements have led to a 2×reduction in the total VERA walltime for the Hatch model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1974

Optical range and range rate estimation for teleoperator systems

Range and range rate are crucial parameters which must be available to the operator during remote controlled orbital docking operations. A method was developed for the estimation of both these parameters using an aided television system. An experiment was performed to determine the human operator's capability to measure displayed image size using a fixed reticle or movable cursor as the television aid. The movable cursor was found to yield mean image size estimation errors on the order of 2.3 per cent of the correct value. This error rate was significantly lower than that for the fixed reticle. Performance using the movable cursor was found to be less sensitive to signal-to-noise ratio variation than was that for the fixed reticle. The mean image size estimation errors for the movable cursor correspond to an error of approximately 2.25 per cent in range suggesting that the system has some merit. Determining the accuracy of range rate estimation using a rate controlled cursor will require further experimentation.

Shields, N. L., Jr.↗
DOE OSTI2025

Leveraging transfer learning and leaf spectroscopy for leaf trait prediction with broad spatial, species, and temporal applicability

Accurate and reliable prediction of leaf traits is crucial for understanding plant adaptations to environmental variation, monitoring terrestrial ecosystems, and enhancing comprehension of functional diversity and ecosystem functioning. Currently, various approaches (e.g., statistical, physical models) have been developed to estimate leaf traits through hyperspectral remote sensing and leaf spectroscopy. However, the absence of high-performing, transferable, and stable models across various domains of space, plant functional types (PFTs) and seasons hinder our ability to quantify and comprehend spatiotemporal variations in leaf traits. This study proposes robust and highly transferable models for better predicting leaf traits with hyperspectral reflectance. Initially, three datasets were assembled, pairing common leaf traits — chlorophyll (Chla+b), carotenoids (Ccar), leaf mass per area (LAM), equivalent water thickness (EWT) — with leaf spectra measurements collected across diverse geographic locations in the U.S. and Europe, PFTs, and seasons. Measurements were acquired using spectroradiometers (e.g., ASD FieldSpec 3/4/Pro and SVC HR-1024i) with integrating spheres, leaf clips, and contact probes. Here, we then developed transfer learning-based hybrid models that incorporated the domain knowledge of radiative transfer models (RTMs) through pretraining processes and were well-constrained by fine-tuning with field measurements. Through comparison with other state-of-the-art statistical models, including partial-least squares regression (PLSR) and Gaussian Process Regression (GPR), as well as pure physical models, we found that the proposed transfer learning models achieved better predictive performance and higher transferability. Specifically, compared to other statistical models and pure RTMs, the transfer learning model exhibited higher coefficient of determination (R 2 ) values with range of 0.01 to 0.79, lower normalized root mean square error (NRMSE) with range of 0.06 % to 33.25 % in model performance. Additionally, the models exhibited improved transferability, with higher R 2 values range from 0.04 to 0.32, lower NRMSE range from 0.08 % to 30.81 %. The findings underscore that transfer learning models through integrating domain knowledge from RTMs and limited observations, can harness the advantages of both RTMs and statistical models and serve as a promising approach for effectively predicting leaf traits.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1999

Principal Investigator-in-a-Box

Human performance in orbit is currently limited by several factors beyond the intrinsic awkwardness of motor control in weightlessness. Cognitive functioning can be affected by such factors as cumulative sleep loss, stress and the psychological effects of long-duration small-group isolation. When an astronaut operates a scientific experiment, the performance decrement associated with such factors can lead to lost or poor quality data and even the total loss of a scientific objective, at great cost to the sponsors and to the dismay of the Principal Investigator. In long-duration flights, as anticipated on the International Space Station and on any planetary exploration, the experimental model is further complicated by long delays between training and experiment, and the large number of experiments each crew member must perform. Although no documented studies have been published on the subject, astronauts report that an unusually large number of simple errors are made in space. Whether a result of the effects of microgravity, accumulated fatigue, stress or other factors, this pattern of increased error supports the need for a computerized decision-making aid for astronauts performing experiments. Artificial intelligence and expert systems might serve as powerful tools for assisting experiments in space. Those conducting space experiments typically need assistance exactly when the planned checklist does not apply. Expert systems, which use bits of human knowledge and human methods to respond appropriately to unusual situations, have a flexibility that is highly desirable in circumstances where an invariably predictable course of action/response does not exist. Frequently the human expert on the ground is unavailable, lacking the latest information, or not consulted by the astronaut conducting the experiment. In response to these issues, we have developed "Principal Investigator-in-a-Box," or [PI], to capture the reasoning process of the real expert, the Principal Investigator, and combine that with real-time data available in space in order to advise the astronaut about how to proceed in real time. [PI] advises the astronaut during the progress of an experiment in much the same way a real Principal Investigator might do while looking over the astronaut's shoulder. In its original application, [PI] mimicked several of the tasks of the Principal Investigator, including data quality monitoring, troubleshooting, prescheduling, protocol management and "interesting data" detection. The proposed research focuses on the efficacy of this technique as applied to the data quality monitoring and troubleshooting aspects of [PI].

Young, Laurence R.↗
NASA NTRS1992

A prototype automatic phase compensation module

The growing demands for high gain and accurate satellite communication systems will necessitate the utilization of large reflector systems. One area of concern of reflector based satellite communication is large scale surface deformations due to thermal effects. These distortions, when present, can degrade the performance of the reflector system appreciable. This performance degradation is manifested by a decrease in peak gain, and increase in sidelobe level, and pointing errors. It is essential to compensate for these distortion effects and to maintain the required system performance in the operating space environment. For this reason the development of a technique to offset the degradation effects is highly desirable. Currently, most research is direct at developing better material for the reflector. These materials have a lower coefficient of linear expansion thereby reducing the surface errors. Alternatively, one can minimize the distortion effects of these large scale errors by adaptive phased array compensation. Adaptive phased array techniques have been studied extensively at NASA and elsewhere. Presented in this paper is a prototype automatic phase compensation module designed and built at NASA Lewis Research Center which is the first stage of development for an adaptive array compensation module.

Terry, John D.↗
DOE OSTI2022

DMC-ICE13 : Ambient and high pressure polymorphs of ice from diffusion Monte Carlo and density functional theory

Ice is one of the most important and interesting molecular crystals, exhibiting a rich and evolving phase diagram. Recent discoveries mean that there are now 20 distinct polymorphs; a structural diversity that arises from a delicate interplay of hydrogen bonding and van der Waals dispersion forces. This wealth of structures provides a stern test of electronic structure theories, with Density Functional Theory (DFT) often not able to accurately characterize the relative energies of the various ice polymorphs. Thanks to recent advances that enable the accurate and efficient treatment of molecular crystals with Diffusion Monte Carlo (DMC), we present here the DMC-ICE13 dataset; a dataset of lattice energies of 13 ice polymorphs. This dataset encompasses the full structural complexity found in the ambient and high-pressure molecular ice polymorphs, and when experimental reference energies are available, our DMC results deliver sub-chemical accuracy. Using this dataset, we then perform an extensive benchmark of a broad range of DFT functionals. Of the functionals considered, revPBE-D3 and RSCAN reproduce reference absolute lattice energies with the smallest error, while optB86b-vdW and SCAN+rVV10 have the best performance on the relative lattice energies. Our results suggest that a single functional achieving reliable performance for all phases is still missing, and that care is needed in the selection of the most appropriate functional for the desired application. The insights obtained here may also be relevant to liquid water and other hydrogen-bonded and dispersion-bonded molecular crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Performance analysis of digital FM demodulators for fading channels in the threshold region

The quasi-optimum digital FM demodulators for fading channels reported earlier (1975) reflected the system performance accurately under high signal to noise ratio conditions. In this paper, the prediction of the system performance for low SNR values is considered. A new set of error variance algorithms is developed from the filter algorithm assuming a Gaussian distribution for the state estimation errors and taking the effect of high frequency terms into consideration. Simulation analysis for an FM system with Rician fading channel shows that these algorithms predict the system performance accurately in the threshold region.

Dharamsi, M. T.↗
NASA NTRS1990

Development of a validation model for the defense meteorological satellite program's special sensor microwave imager

The Defence Meteorological Space Program's (DMSP) Special Sensor Microwave/Imager (SSM/I), an operational wind speed algorithm was developed. The algorithm is based on the D-matrix approach which seeks a linear relationship between measured SSM/I brightness temperatures and environmental parameters. D-matrix performance was validated by comparing algorithm derived wind speeds with near-simultaneous and co-located measurements made by off-shore ocean buoys. Other topics include error budget modeling, alternate wind speed algorithms, and D-matrix performance with one or more inoperative SSM/I channels.

Swift, C. T.↗
NASA NTRSDate not supplied

Update on Tbird on-Orbit Experiments and Performance Results

The TeraByte Infrared Delivery (TBIRD) mission has successfully demonstrated 200-Gbps laser communication downlinks from a 6U CubeSat in low-Earth orbit (LEO), delivering up to 4.8 terabytes (TB) error-free in a 5-minute pass. In total 65 passes were performed from May 2022 through May 2023. This paper presents an overview of the results of two experimental campaigns during that year of operations.

TBIRD↗
DOE OSTI2025

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

CH 4 Activation over Perovskite Catalysts: True Density and Reactivity of Active Sites

The high thermal stability of perovskites has drawn attention toward their applications for catalytic CH 4 activation and conversion, typically occurring at high temperatures. The reaction rates of perovskite catalysts for CH 4 combustion, however, trail behind those of noble metal catalysts. Ways to optimize the performance of perovskite catalysts are destined to trial-and-error approaches unless their complex reconstructed surfaces are correlated with fundamental kinetic parameters. Discerning the intrinsic activity of surface catalytic sites and the density of those sites is crucial to rationally envision complex metal oxides with enhanced catalytic performance. Here, the present work presents a detailed kinetic analysis of catalytic CH 4 combustion over a set of seven perovskites (SrTiO 3 , SrZrO 3 , SrFeO 3 , LaFeO 3 , LaInO 3 , LaCoO 3 , LaMnO 3 ) with various surface terminations. Steady-state isotopic transient kinetic analysis was employed to measure turnover frequency (TOF) and density of surface intermediates (N) under operando conditions. Top surface characterization elucidated performance-structure relationships between near-monolayer surface composition and intrinsic reactivity of the catalysts. By using a chemical etching procedure to expose Fe-sites at the top surface of LaFeO 3 (LaFeO 3 , HNO 3 ), its TOF was increased 4-fold, compared with the unmodified sample, although N on the surface of LaFeO 3 , HNO 3 decreased. Density functional theory simulations corroborated that surface Fe-termination and La-Fe termination offer lower energetic barriers for CH 4 activation when compared with La-termination. In general, surface reconstruction is shown as a tool to tune TOF and N to improve reaction rates. This work fills a gap in current kinetic studies of perovskites through a careful assessment and discussion of the density and intrinsic reactivity of active sites for methane combustion over well-characterized reconstructed perovskite surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

High accuracy radiation efficiency measurement techniques

The relatively large antenna subarrays (tens of meters) to be used in the Solar Power Satellite, and the desire to accurately quantify antenna performance, dictate the requirement for specialized measurement techniques. The error contributors associated with both far-field and near-field antenna measurement concepts were quantified. As a result, instrumentation configurations with measurement accuracy potential were identified. In every case, advances in the state of the art of associated electronics were found to be required. Relative cost trade-offs between a candidate far-field elevated antenna range and near-field facility were also performed.

Kozakoff, D. J.↗
NASA NTRS2000

Testing New Programming Paradigms with NAS Parallel Benchmarks

Over the past decade, high performance computing has evolved rapidly, not only in hardware architectures but also with increasing complexity of real applications. Technologies have been developing to aim at scaling up to thousands of processors on both distributed and shared memory systems. Development of parallel programs on these computers is always a challenging task. Today, writing parallel programs with message passing (e.g. MPI) is the most popular way of achieving scalability and high performance. However, writing message passing programs is difficult and error prone. Recent years new effort has been made in defining new parallel programming paradigms. The best examples are: HPF (based on data parallelism) and OpenMP (based on shared memory parallelism). Both provide simple and clear extensions to sequential programs, thus greatly simplify the tedious tasks encountered in writing message passing programs. HPF is independent of memory hierarchy, however, due to the immaturity of compiler technology its performance is still questionable. Although use of parallel compiler directives is not new, OpenMP offers a portable solution in the shared-memory domain. Another important development involves the tremendous progress in the internet and its associated technology. Although still in its infancy, Java promisses portability in a heterogeneous environment and offers possibility to "compile once and run anywhere." In light of testing these new technologies, we implemented new parallel versions of the NAS Parallel Benchmarks (NPBs) with HPF and OpenMP directives, and extended the work with Java and Java-threads. The purpose of this study is to examine the effectiveness of alternative programming paradigms. NPBs consist of five kernels and three simulated applications that mimic the computation and data movement of large scale computational fluid dynamics (CFD) applications. We started with the serial version included in NPB2.3. Optimization of memory and cache usage was applied to several benchmarks, noticeably BT and SP, resulting in better sequential performance. In order to overcome the lack of an HPF performance model and guide the development of the HPF codes, we employed an empirical performance model for several primitives found in the benchmarks. We encountered a few limitations of HPF, such as lack of supporting the "REDISTRIBUTION" directive and no easy way to handle irregular computation. The parallelization with OpenMP directives was done at the outer-most loop level to achieve the largest granularity. The performance of six HPF and OpenMP benchmarks is compared with their MPI counterparts for the Class-A problem size in the figure in next page. These results were obtained on an SGI Origin2000 (195MHz) with MIPSpro-f77 compiler 7.2.1 for OpenMP and MPI codes and PGI pghpf-2.4.3 compiler with MPI interface for HPF programs.

Jin, H.↗
NASA NTRS1971

Space Trajectories Error Analysis (STEAP) Programs. Volume 1: Analytic manual, update

Manual revisions are presented for the modified and expanded STEAP series. The STEAP 2 is composed of three independent but related programs: NOMAL for the generation of n-body nominal trajectories performing a number of deterministic guidance events; ERRAN for the linear error analysis and generalized covariance analysis along specific targeted trajectories; and SIMUL for testing the mathematical models used in the navigation and guidance process. The analytic manual provides general problem description, formulation, and solution and the detailed analysis of subroutines. The programmers' manual gives descriptions of the overall structure of the programs as well as the computational flow and analysis of the individual subroutines. The user's manual provides information on the input and output quantities of the programs. These are updates to N69-36472 and N69-36473.

Source record↗
DOE OSTI2024

New Measurements of the Lyα Forest Continuum and Effective Optical Depth with LyCAN and DESI Y1 Data

Abstract We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form τ ( z ) = τ 0 ( 1 + z ) γ to our measurements and find τ 0 = (2.46 ± 0.14) × 10 −3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

79 ASTRONOMY AND ASTROPHYSICS↗