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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Software reliability: Additional investigations into modeling with replicated experiments

The effects of programmer experience level, different program usage distributions, and programming languages are explored. All these factors affect performance, and some tentative relational hypotheses are presented. An analytic framework for replicated and non-replicated (traditional) software experiments is presented. A method of obtaining an upper bound on the error rate of the next error is proposed. The method was validated empirically by comparing forecasts with actual data. In all 14 cases the bound exceeded the observed parameter, albeit somewhat conservatively. Two other forecasting methods are proposed and compared to observed results. Although demonstrated relative to this framework that stages are neither independent nor exponentially distributed, empirical estimates show that the exponential assumption is nearly valid for all but the extreme tails of the distribution. Except for the dependence in the stage probabilities, Cox's model approximates to a degree what is being observed.

Nagel, P. M.↗
NASA NTRS2022

A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes

Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state’s risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CI(cyano)). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CI(cyano) detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CI(cyano) was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.

remote sensing↗
DOE OSTI2024

A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution

Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.

Chemistry↗
DOE OSTI2023

The miniJPAS survey quasar selection – II. Machine learning classification with photometric measurements and uncertainties

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of a larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a machine learning-based method that employs convolutional neural networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg 2 of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established machine learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars, and unresolved galaxies. Our results are a proof of concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Protein-ligand binding affinity prediction using multi-instance learning with docking structures

Recent advances in 3D structure-based deep learning approaches demonstrate improved accuracy in predicting protein-ligand binding affinity in drug discovery. These methods complement physics-based computational modeling such as molecular docking for virtual high-throughput screening. Despite recent advances and improved predictive performance, most methods in this category primarily rely on utilizing co-crystal complex structures and experimentally measured binding affinities as both input and output data for model training. Nevertheless, co-crystal complex structures are not readily available and the inaccurate predicted structures from molecular docking can degrade the accuracy of the machine learning methods. We introduce a novel structure-based inference method utilizing multiple molecular docking poses for each complex entity. Our proposed method employs multi-instance learning with an attention network to predict binding affinity from a collection of docking poses. We validate our method using multiple datasets, including PDBbind and compounds targeting the main protease of SARS-CoV-2. The results demonstrate that our method leveraging docking poses is competitive with other state-of-the-art inference models that depend on co-crystal structures. This method offers binding affinity prediction without requiring co-crystal structures, thereby increasing its applicability to protein targets lacking such data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

A transient response analysis of the space shuttle vehicle during liftoff

A proposed transient response method is formulated for the liftoff analysis of the space shuttle vehicles. It uses a power series approximation with unknown coefficients for the interface forces between the space shuttle and mobile launch platform. This allows the equation of motion of the two structures to be solved separately with the unknown coefficients at the end of each step. These coefficients are obtained by enforcing the interface compatibility conditions between the two structures. Once the unknown coefficients are determined, the total response is computed for that time step. The method is validated by a numerical example of a cantilevered beam and by the liftoff analysis of the space shuttle vehicles. The proposed method is compared to an iterative transient response analysis method used by Martin Marietta for their space shuttle liftoff analysis. It is shown that the proposed method uses less computer time than the iterative method and does not require as small a time step for integration. The space shuttle vehicle model is reduced using two different types of component mode synthesis (CMS) methods, the Lanczos method and the Craig and Bampton CMS method. By varying the cutoff frequency in the Craig and Bampton method it was shown that the space shuttle interface loads can be computed with reasonable accuracy. Both the Lanczos CMS method and Craig and Bampton CMS method give similar results. A substantial amount of computer time is saved using the Lanczos CMS method over that of the Craig and Bampton method. However, when trying to compute a large number of Lanczos vectors, input/output computer time increased and increased the overall computer time. The application of several liftoff release mechanisms that can be adapted to the proposed method are discussed.

Brunty, J. A.↗
NASA NTRS2008

On the Development of Parameterized Linear Analytical Longitudinal Airship Models

In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.

aerobot↗
NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Wind tunnel experiments will continue to be a primary source of validation data for many types of mathematical and computational models in the aerospace industry. The increased emphasis on accuracy of data acquired from these facilities requires understanding of the uncertainty of not only the measurement data but also any correction applied to the data. One of the largest and most critical corrections made to these data is due to wall interference. In an effort to understand the accuracy and suitability of these corrections, a statistical validation process for wall interference correction methods has been developed. This process is based on the use of independent cases which, after correction, are expected to produce the same result. Comparison of these independent cases with respect to the uncertainty in the correction process establishes a domain of applicability based on the capability of the method to provide reasonable corrections with respect to customer accuracy requirements. The statistical validation method was applied to the version of the Transonic Wall Interference Correction System (TWICS) recently implemented in the National Transonic Facility at NASA Langley Research Center. The TWICS code generates corrections for solid and slotted wall interference in the model pitch plane based on boundary pressure measurements. Before validation could be performed on this method, it was necessary to calibrate the ventilated wall boundary condition parameters. Discrimination comparisons are used to determine the most representative of three linear boundary condition models which have historically been used to represent longitudinally slotted test section walls. Of the three linear boundary condition models implemented for ventilated walls, the general slotted wall model was the most representative of the data. The TWICS code using the calibrated general slotted wall model was found to be valid to within the process uncertainty for test section Mach numbers less than or equal to 0.60. The scatter among the mean corrected results of the bodies of revolution validation cases was within one count of drag on a typical transport aircraft configuration for Mach numbers at or below 0.80 and two counts of drag for Mach numbers at or below 0.90.

Walker, Eric Lee↗
NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Wind tunnel experiments will continue to be a primary source of validation data for many types of mathematical and computational models in the aerospace industry. The increased emphasis on accuracy of data acquired from these facilities requires understanding of the uncertainty of not only the measurement data but also any correction applied to the data. One of the largest and most critical corrections made to these data is due to wall interference. In an effort to understand the accuracy and suitability of these corrections, a statistical validation process for wall interference correction methods has been developed. This process is based on the use of independent cases which, after correction, are expected to produce the same result. Comparison of these independent cases with respect to the uncertainty in the correction process establishes a domain of applicability based on the capability of the method to provide reasonable corrections with respect to customer accuracy requirements. The statistical validation method was applied to the version of the Transonic Wall Interference Correction System (TWICS) recently implemented in the National Transonic Facility at NASA Langley Research Center. The TWICS code generates corrections for solid and slotted wall interference in the model pitch plane based on boundary pressure measurements. Before validation could be performed on this method, it was necessary to calibrate the ventilated wall boundary condition parameters. Discrimination comparisons are used to determine the most representative of three linear boundary condition models which have historically been used to represent longitudinally slotted test section walls. Of the three linear boundary condition models implemented for ventilated walls, the general slotted wall model was the most representative of the data. The TWICS code using the calibrated general slotted wall model was found to be valid to within the process uncertainty for test section Mach numbers less than or equal to 0.60. The scatter among the mean corrected results of the bodies of revolution validation cases was within one count of drag on a typical transport aircraft configuration for Mach numbers at or below 0.80 and two counts of drag for Mach numbers at or below 0.90.

Walker, Eric L.↗
DOE OSTI2017

Calibration of AGN Reverberation Distance Measurements

In Yoshii et al., we described a new method for measuring extragalactic distances based on dust reverberation in active galactic nuclei (AGNs), and we validated our new method with Cepheid variable stars. In this Letter, we validate our new method with Type Ia supernovae (SNe Ia) that occurred in two of the AGN host galaxies during our AGN monitoring program: SN 2004bd in NGC 3786 and SN 2008ec in NGC 7469. Their multicolor light curves were observed and analyzed using two widely accepted methods for measuring SN distances, and the distance moduli derived are μ=33.47±0.15 for SN 2004bd and 33.83 ± 0.07 for SN 2008ec. These results are used to obtain independently the distance measurement calibration factor, g. The g value obtained from the SN Ia discussed in this Letter is g{sub SN}=10.61±0.50, which matches, within the range of 1σ uncertainty, g{sub DUST}=10.60, previously calculated ab initio in Yoshii et al. Having validated our new method for measuring extragalactic distances, we use our new method to calibrate reverberation distances derived from variations of Hβ emission in the AGN broad-line region, extending the Hubble diagram to z≈0.3 where distinguishing between cosmologies is becoming possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Fast Algorithm for Evaluating Critical Current of High-Temperature Superconducting Pancake Coil

Second-generation (2G) high-temperature superconducting (HTS) tapes are now capable of carrying very high transport current and promising for a wide range of applications. The critical current of HTS coils is important for applications, such as superconducting electric machines, superconducting magnetic energy storage, and superconducting magnets. Therefore, precisely and quickly calculating critical current of HTS coils is very important for designing HTS devices. This paper provides a fast algorithm for evaluating critical current of HTS pancake coil. The fast algorithm is realized through a stationary model, which is based on finite element method (FEM) software. The stationary model means that the model is solved by stationary study instead of time-dependent study. To validate this method, a pancake HTS coil was wound and its critical current was measured. Meanwhile, an axial symmetric stationary model was built according to the geometry of the measured HTS coil. By comparing measured and calculated results, the effectiveness of the stationary model was demonstrated. Moreover, the stationary model is compared with H formulation model. The calculated results by the two models are nearly the same. However, by using stationary calculation, the stationary model can remarkably speed up the computational process. Due to the advantage of calculating speed, the stationary model can be used to characterize and design large-scale HTS applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Assessing time-of-flight signal-to-noise ratio gains within the myocardium and subsequent reductions in administered activity in cardiac PET studies

Background: Time-of-flight (TOF) is known to increase signal-to-noise ratio (SNR) and facilitate reductions in administered activity. Established measures of SNR gain are derived from areas of uniform uptake, which is not applicable to the heterogeneous uptake in cardiac PET images using fluoro-deoxyglucose (FDG). This study aimed to develop a technique to quantify SNR gains within the myocardium due to TOF. Methods: Reference TOF SNR gains were measured in 88 FDG oncology patients. Phantom data were used to translate reference SNR gains and validate a method of quantifying SNR gains within the myocardium from parametric images produced from multiple replicate images. This technique was applied to 13 FDG cardiac viability patients. Results: Reference TOF SNR gains of +23% ± 8.5% were measured in oncology patients. Measurements of SNR gain from the phantom data were in agreement and showed the parametric image technique to be sufficiently robust. SNR gains within the myocardium in the viability patients were +21% ± 2.8%. Conclusion: A method to quantify SNR gains from TOF within the myocardium has been developed and evaluated. SNR gains within the myocardium are comparable to those observed by established methods. This allows guidance for protocol optimization for TOF systems in cardiac PET.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Three-dimensional traction microscopy accounting for cell-induced matrix degradation

Tractions exerted by cells on the extracellular matrix (ECM) are critical in many important physiological and pathological processes such as embryonic morphogenesis, wound healing, and cancer metastasis. Three-dimensional Traction Microscopy (3DTM) is a tool to quantify cellular tractions by first measuring the displacement field in the ECM in response to these tractions, and then using this measurement to infer tractions. Most applications of 3DTM have assumed that the ECM has spatially-uniform mechanical properties, but cells secrete enzymes that can locally degrade the ECM. In this work, a novel computational method is developed to quantify both cellular tractions and ECM degradation. In particular, the ECM is modeled as a hyperelastic, Neo-Hookean solid, whose material parameters are corrupted by a single degradation parameter. The feasibility of determining both the traction and the degradation parameter is first demonstrated by showing the existence and uniqueness of the solution. An inverse problem is then formulated to determine the nodal values of the traction vector and the degradation parameter, with the objective of minimizing the difference between a predicted and measured displacement field, under the constraint that the predicted displacement field satisfies the equation of equilibrium. The inverse problem is solved by means of a gradient-based optimization approach, and the gradient is computed efficiently using appropriately derived adjoint fields. The computational method is validated in-silico using a geometrically realistic neuronal cell model and synthetic traction and degradation fields. It is found that the method accurately recovers both the traction and degradation fields. Moreover, it is found that neglecting ECM degradation can yield significant errors in traction measurements. Finally, our method can extend the range of context where tractions can be appropriately measured.

42 ENGINEERING↗
NASA NTRS2003

Strain Gage Measurement System to Determine Cryogenic Propellant Tank Level

Measurement of tank level, particularly for cryogenic propellants, has proven to be a difficult proposition. Current methods based on differential pressure, capacitance sensors, temperature sensors, etc.; do not provide sufficiently accurate or robust measurements, especially at run time. This paper describes a simple, but effective method to determine propellant volume by measuring very small deformations of the structure supporting the tank. Results of a laboratory study to validate the method, and experimental data from a deployed system are presented. A comparison with an existing differential pressure sensor shows that the strain gage system provides a very good quality signal even during pressurization.

Figueroa, Fernando↗
NASA NTRS2004

Fiber-Optic Strain-Gage Tank Level Measurement System for Cryogenic Propellants

Measurement of tank level, particularly for cryogenic propellants, has proven to be a difficult problem. Current methods based on differential pressure, capacitance sensors, temperature sensors, etc.; do not provide sufficiently accurate or robust measurements, especially at run time. These methods are designed to measure tank-level, but when the fluids are in supercritical state, the liquid-gas interface disappears. Furthermore, there is a need for a non-intrusive measurement system; that is, the sensors should not require tank modifications and/or disturb the fluids. This paper describes a simple, but effective method to determine propellant mass by measuring very small deformations of the structure supporting the tank. Results of a laboratory study to validate the method, and experimental data from a deployed system are presented. A comparison with an existing differential pressure sensor shows that the strain gage system provides a much better quality signal across all regimes during an engine test. Experimental results also show that the use of fiber optic strain gages (FOSG) over classic foil strain gages extends the operation time (before the system becomes uncalibrated), and increases accuracy. Finally, a procedure is defined whereby measurements from the FOSG mounted on the tank supporting structure are compensated using measurements of a FOSG mounted on a reference plate and temperature measurements of the structure. Results describing the performance of a deployed system that measures tank level during propulsion tests are included.

Figueroa, Fernando↗
NASA NTRSDate not supplied

Three-Dimensional Instantaneous Flow-field Reconstruction Using Planar Spectral Proper Orthogonal Decomposition

A novel method for three-dimensional flowfield reconstruction is presented that utilizes spectral proper orthogonal decomposition (SPOD). The time-resolved PIV data are acquired in multiple two-dimensional spanwise planes, with adequate streamwise spacing to resolve the out-of-plane wavelength. Knowledge of the out-of-plane phase speed is also required, and for the present case this value was obtained using instantaneous hot-wire measurements. The method is validated by comparing phase-averaged results acquired with a forcing signal to the SPOD reconstructed results using the same data. The method is also applied to data with no forcing applied, and the results are shown to be similar to the forced case. This method is particularly useful for cases in which there are multiple frequencies of interest, or cases in which the phenomena occur over a broad range of frequencies. This method allows reconstruction of the frequencies of interest without the need for a forcing signal, so the flow can be studied in its natural (undisturbed) state.

boundary-layer transition↗
DOE OSTI2019

Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks

Land cover datasets are essential for modeling and analysis of Arctic ecosystem structure and function and for understanding land–atmosphere interactions at high spatial resolutions. However, most Arctic land cover products are generated at a coarse resolution, often limited due to cloud cover, polar darkness, and poor availability of high-resolution imagery. A multi-sensor remote sensing-based deep learning approach was developed for generating high-resolution (5 m) vegetation maps for the western Alaskan Arctic on the Seward Peninsula, Alaska. The fusion of hyperspectral, multispectral, and terrain datasets was performed using unsupervised and supervised classification techniques over a ~343 km 2 area, and a high-resolution (5 m) vegetation classification map was generated. An unsupervised technique was developed to classify high-dimensional remote sensing datasets into cohesive clusters. We employed a quantitative method to add supervision to the unlabeled clusters, producing a fully labeled vegetation map. We then developed convolutional neural networks (CNNs) using the multi-sensor fusion datasets to map vegetation distributions using the original classes and the classes produced by the unsupervised classification method. To validate the resulting CNN maps, vegetation observations were collected at 30 field plots during the summer of 2016, and the resulting vegetation products developed were evaluated against them for accuracy. Our analysis indicates the CNN models based on the labels produced by the unsupervised classification method provided the most accurate mapping of vegetation types, increasing the validation score (i.e., precision) from 0.53 to 0.83 when evaluated against field vegetation observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Accurate and Sensitive Analytical Strategy for the Determination of Antimony: Hydrogen Assisted T-Shaped Slotted Quartz Tube-Atom Trap-Flame Atomic Absorption Spectrometry

Antimony is known to have some adverse health effects on human health. Flame atomic absorption spectrometry (FAAS) is a widely used instrumental for the determination of antimony and other metals. However, it lacks the sensitivity to determine these metals at trace levels. This study was aimed at overcoming this setback by using hydrogen assisted T-shaped slotted quartz tube technique to preconcentrate and determine antimony by FAAS. All the system parameters were optimized to enhance the detection power of the system. Under the optimum experimental conditions, the limits of detection and quantification were found to be 0.75 and 2.49 µg L{sup −1}, respectively with R{sup 2} value of 0.9999. Accuracy of the developed method was validated by experimental results agreeing to the certified value of a standard reference material. Recovery studies were also carried out to determine the method’s applicability to tap and mineral water samples, and the results obtained were appreciable.

54 ENVIRONMENTAL SCIENCES↗