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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
DOE OSTI2019

Limits of special material detectability fundamental to idealized dual-energy radiographic systems

Analysis of dual-energy radiographic approaches to the detection of “special” material, i.e. contraband, in otherwise innocuous scenes, such as maritime cargo containers encountered at ports of entry, reveals fundamental limitations of data obtained along a single line-of-sight. The basic equations that describe idealized systems are presented and analyzed so as to identify challenges that are only exacerbated by scatter, noise, and measurement uncertainty. In the mono-energetic limit, the instrumentation and measurement methods reduce to a system of linear equations that are simple to treat: it is observed that there exists a threshold for the minimum amount of high-Z material that can be detected unambiguously (without the risk of false positive or false negative indications), even when the background materials are of finite and of well-known variety. The threshold depends on the quality of prior information about the cargo and the selection of probing energies, and can therefore be minimized by good system design practices and measurement procedures, but persists as a general challenge to security operations. In discussion of this result, it is noted that techniques incorporating other prior information, such as the geometry of cargo and potential contraband, along with data from 2D imaging, have far greater potential. For instance, a simple data analysis method capable of differentiating high-Z spheres from those of more common material is presented. This simple example demonstrates that, although simple line-of-sight transmission radiography may suffer fundamental limitations, there remains good cause to be optimistic about the potential for image analysis in radiographic material identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Could a neuroscientist understand a microprocessor?

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Furthermore, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

On the relaxation behaviors of slow and classical glitches: Observational biases and their opposite recovery trends

We study the pulsar timing properties and the data analysis methods of glitch recoveries. In some cases one first fits the times of arrival (TOAs) to obtain the 'time-averaged' frequency ν and its first derivative ν-dot , and then fits models to them. However, our simulations show that ν and ν-dot obtained in this way are systematically biased unless the time intervals between the nearby data points of TOAs are smaller than about 10{sup 4} s, which is much shorter than typical observation intervals. Alternatively, glitch parameters can be obtained by fitting the phases directly with relatively smaller biases, but the initial recovery time scale is usually chosen by eye, which may introduce a strong bias. We also construct a phenomenological model by assuming a pulsar spin-down law of ν-dot ν{sup −3}=−H{sub 0}G(t) with G(t) = 1 + κe {sup –t/τ} for a glitch recovery, where H {sub 0} is a constant and κ and τ are the glitch parameters to be found. This model can reproduce the observed data of slow glitches from B1822–09 and the giant classical glitch of B2334+61, with κ < 0 or κ > 0, respectively. We then use this model to simulate TOA data and test several fitting procedures for a glitch recovery. The best procedure is (1) to use a very high order polynomial (e.g., to 50th order) to precisely describe the phase, (2) obtain ν(t) and ν-dot (t) from the polynomial, then (3) obtain the glitch parameters from ν(t) or ν-dot (t). Finally, the uncertainty in the starting time t {sub 0} of a classical glitch causes uncertainties in some glitch parameters, but less so for a slow glitch, t {sub 0}, of which can be determined from data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1987

A method for data base management and analysis for wind tunnel data

To respond to the need for improved data base management and analysis capabilities for wind-tunnel data at the Langley 16-Foot Transonic Tunnel, research was conducted into current methods of managing wind-tunnel data and a method was developed as a solution to this need. This paper describes the development of the data base management and analysis method for wind-tunnel data. The design and implementation of the software system are discussed and examples of its use are shown.

Biser, Aileen O.↗
DOE OSTI2014

Detection of a faint fast-moving near-Earth asteroid using the synthetic tracking technique

We report a detection of a faint near-Earth asteroid (NEA) using our synthetic tracking technique and the CHIMERA instrument on the Palomar 200 inch telescope. With an apparent magnitude of 23 (H = 29, assuming detection at 20 lunar distances), the asteroid was moving at 6.°32 day{sup –1} and was detected at a signal-to-noise ratio (S/N) of 15 using 30 s of data taken at a 16.7 Hz frame rate. The detection was confirmed by a second observation 77 minutes later at the same S/N. Because of its high proper motion, the NEA moved 7 arcsec over the 30 s of observation. Synthetic tracking avoided image degradation due to trailing loss that affects conventional techniques relying on 30 s exposures; the trailing loss would have degraded the surface brightness of the NEA image on the CCD down to an approximate magnitude of 25 making the object undetectable. This detection was a result of our 12 hr blind search conducted on the Palomar 200 inch telescope over two nights, scanning twice over six (5.°3 × 0.°046) fields. Detecting only one asteroid is consistent with Harris's estimates for the distribution of the asteroid population, which was used to predict a detection of 1.2 NEAs in the H-magnitude range 28-31 for the two nights. The experimental design, data analysis methods, and algorithms are presented. We also demonstrate milliarcsecond-level astrometry using observations of two known bright asteroids on the same system with synthetic tracking. We conclude by discussing strategies for scheduling observations to detect and characterize small and fast-moving NEAs using the new technique.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Next-generation wargames

Over the past century, and particularly since the outset of the Cold War, wargames (interactive simulations used to evaluate aspects of tactics, operations, and strategy) have become an integral means for militaries and policy-makers to evaluate how strategic decisions are made related to nuclear weapons strategy and international security. Furthermore, these methods have also been applied beyond the military realm, to examine phenomena as varied as elections, government policy, international trade, and supply-chain mechanics. Today, a renewed focus on wargaming combined with access to sophisticated and inexpensive drag-and-drop digital game development frameworks and new cloud computing architectures have democratized the ability to enable massive multiplayer gaming experiences. With the integration of simulation tools and experimental methods from a variety of social science disciplines, a science-based experimental gaming approach has the potential to transform the insights generated from gaming by creating human-derived, large-n datasets for replicable, quantitative analysis. In the following, we outline challenges associated with contemporary simulation and wargaming tools, investigate where scholars have searched for game data, and explore the utility of new experimental gaming and data analysis methods in both policy-making and academic settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Interlaboratory Reproducibility of Contour Method Data in a High Strength Aluminum Alloy

The contour method for residual stress measurement has seen significant development, but an experimental reproducibility study utilizing physical samples has not been published. A double-blind reproducibly study is reported, having scope beginning with EDM cutting and ending with residual stress calculation. A reinforced I-beam sample geometry is identified for its unique residual stress profile when extracted from residual stress bearing quenched aluminum bar (7050-T74). Contour measurements are prescribed on a midplane of symmetry with dimensions 24.0 mm by 50.0 mm. Fourteen identically prepared samples are fabricated from a single long bar with well characterized and uniform residual stress. Five samples throughout the bar are identified for planning measurements to validate sample uniformity and overall suitability of the residual stress field. The planning measurements employ a range of techniques: contour method, neutron diffraction, and hole-drilling. Eight samples are distributed to an international group of participants to execute their standard measurement practice. A double-blind process is followed to provide anonymity. Results are provided by eight participants: six being self-similar and two being quite different, the latter set aside as outliers. An average residual stress field is established from non-outlying results and the spatial distribution of reproducibility standard deviation is determined. The average stress field ranges from -60 to 70 MPa and the reproducibility standard deviation averages 8.1 MPa on the measurement plane. The average reproducibility standard deviation is about 3 × larger for points within 1.0 mm of plane boundaries (17.6 MPa) than for the remaining points (6.1 MPa). Reproducibility standard deviation (among different labs) for contour method residual stress measurement is found to be very similar to repeatability standard deviation (in a single lab) reported in prior work. The reproducibility observed here, for the entire measurement process, is also similar to that found in a prior reproducibility study limited to contour method data analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2016

First hydrogen operation of NIO1: Characterization of the source plasma by means of an optical emission spectroscopy diagnostic

NIO1 (Negative Ion Optimization 1) is a compact and flexible radio frequency H{sup −} ion source, developed by Consorzio RFX and INFN-LNL. The aim of the experimentation on NIO1 is the optimization of both the production of negative ions and their extraction and beam optics. In the initial phase of its commissioning, NIO1 was operated with nitrogen, but now the source is regularly operated also with hydrogen. To evaluate the source performances, an optical emission spectroscopy diagnostic was installed. The system includes a low resolution spectrometer in the spectral range of 300-850 nm and a high resolution (50 pm) one, to study, respectively, the atomic and the molecular emissions in the visible range. The spectroscopic data have been interpreted also by means of a collisional-radiative model developed at IPP Garching. Besides the diagnostic hardware and the data analysis methods, the paper presents the first plasma measurements across a transition to the full H mode, in a hydrogen discharge. The characteristic signatures of this transition in the plasma parameters are described, in particular, the sudden increase of the light emitted from the plasma above a certain power threshold.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Electric Motor Thermal Management R&D. Annual Report

With the push to reduce component volumes, lower costs, and reduce weight without sacrificing performance or reliability, the challenges associated with thermal management increase for power electronics and electric motors. Thermal management for electric motors will become more important as the automotive industry continues the transition to more electrically dominant vehicle propulsion systems. The transition to more electrically dominant propulsion systems leads to higher-power duty cycles for electric drive systems. Thermal constraints place significant limitations on how electric motors ultimately perform, and as thermal management improves, there will be a direct trade-off between motor performance, efficiency, cost, and the sizing of electric motors to operate within the thermal constraints. The goal of this research project is to support broad industry demand for data, analysis methods, and experimental techniques to improve and better understand motor thermal management. Work in FY15 focused on two areas related to motor thermal management: passive thermal performance and active convective cooling. Passive thermal performance emphasized the thermal impact of materials and thermal interfaces among materials within an assembled motor. The research tasks supported the publication of test methods and data for thermal contact resistances and direction-dependent thermal conductivity within an electric motor. Active convective cooling focused on measuring convective heat-transfer coefficients using automatic transmission fluid (ATF). Data for average convective heat transfer coefficients for direct impingement of ATF jets was published. Also, experimental hardware for mapping local-scale and stator-scale convective heat transfer coefficients for ATF jet impingement were developed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Scattering Calorimeter FY24 Deliverable Report

A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1982

Static calibration for measurement of loads in wind tunnel tests on Shuttle surface tiles

A description is given of the procedures used for the static calibrations of the Coe (1981) sensor array to determine normal force, pitching moment, and rolling moment from the ensemble of sensor outputs. The use of independent data to confirm the validity of the calibration is also described. Two methods are used in calibrating the Coe sensors. In the first, calibration loads and readings are arranged in matrix form and are assumed to be related in a linear fashion. In the second, each Coe sensor reading is regarded as a sum of contributions from each of the calibration loads. It is shown that the Coe load sensors, in conjunction with either of two data analysis methods, can be used to determine the forces and moments experienced by a Shuttle TPS tile.

Rummler, D. R.↗
DOE OSTI2015

Performance of internal covariance estimators for cosmic shear correlation functions

Data re-sampling methods such as the delete-one jackknife are a common tool for estimating the covariance of large scale structure probes. In this paper we investigate the concepts of internal covariance estimation in the context of cosmic shear two-point statistics. We demonstrate how to use log-normal simulations of the convergence field and the corresponding shear field to carry out realistic tests of internal covariance estimators and find that most estimators such as jackknife or sub-sample covariance can reach a satisfactory compromise between bias and variance of the estimated covariance. In a forecast for the complete, 5-year DES survey we show that internally estimated covariance matrices can provide a large fraction of the true uncertainties on cosmological parameters in a 2D cosmic shear analysis. The volume inside contours of constant likelihood in the $\Omega_m$-$\sigma_8$ plane as measured with internally estimated covariance matrices is on average $\gtrsim 85\%$ of the volume derived from the true covariance matrix. The uncertainty on the parameter combination $\Sigma_8 \sim \sigma_8 \Omega_m^{0.5}$ derived from internally estimated covariances is $\sim 90\%$ of the true uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

XANES and EXAFS of dilute solutions of transition metals at XFELs

This work has demonstrated that X-ray absorption spectroscopy (XAS), both Mn XANES and EXAFS, of solutions with millimolar concentrations of metal is possible using the femtosecond X-ray pulses from XFELs. Mn XAS data were collected using two different sample delivery methods, a Rayleigh jet and a drop-on-demand setup, with varying concentrations of Mn. Here, a new method for normalization of XAS spectra based on solvent scattering that is compatible with data collection from a highly variable pulsed source is described. The measured XANES and EXAFS spectra of such dilute solution samples are in good agreement with data collected at synchrotron sources using traditional scanning protocols. The procedures described here will enable XFEL-based XAS on dilute biological samples, especially metalloproteins, with low sample consumption. Details of the experimental setup and data analysis methods used in this XANES and EXAFS study are presented. This method will also benefit XAS performed at high-repetition-rate XFELs such as the European XFEL, LCLS-II and LCLS-II-HE.

Chatterjee, Ruchira (ORCID:000000020865061X)↗
DOE OSTI2021

A composite likelihood approach for inference under photometric redshift uncertainty

ABSTRACT Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

(cosmology:) large-scale structure of Universe↗
NASA NTRS2007

Hybrid Automated Diagnosis of Discrete/Continuous Systems

A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.

Park, Han↗
DOE OSTI2017

Prediction of thyroid C-cell carcinogenicity after chronic administration of GLP1-R agonists in rodents

Increased incidence of C-cell carcinogenicity has been observed for glucagon-like-protein-1 receptor (GLP-1r) agonists in rodents. It is suggested that the duration of exposure is an indicator of carcinogenic potential in rodents of the different products on the market. Furthermore, the role of GLP-1-related mechanisms in the induction of C-cell carcinogenicity has gained increased attention by regulatory agencies. This study proposes an integrative pharmacokinetic/pharmacodynamic (PKPD) framework to identify explanatory factors and characterize differences in carcinogenic potential of the GLP-1r agonist products. PK models for four products (exenatide QW (once weekly), exenatide BID (twice daily), liraglutide and lixisenatide) were developed using nonlinear mixed effects modelling. Predicted exposure was subsequently linked to GLP-1r stimulation using in vitro GLP-1r potency data. A logistic regression model was then applied to exenatide QW and liraglutide data to assess the relationship between GLP-1r stimulation and thyroid C-cell hyperplasia incidence as pre-neoplastic predictor of a carcinogenic response. The model showed a significant association between predicted GLP-1r stimulation and C-cell hyperplasia after 2 years of treatment. The predictive performance of the model was evaluated using lixisenatide, for which hyperplasia data were accurately described during the validation step. The use of a model-based approach provided insight into the relationship between C-cell hyperplasia and GLP-1r stimulation for all four products, which is not possible with traditional data analysis methods. It can be concluded that both pharmacokinetics (exposure) and pharmacodynamics (potency for GLP-1r) factors determine C-cell hyperplasia incidence in rodents. Our work highlights the pharmacological basis for GLP-1r agonist-induced C-cell carcinogenicity. The concept is promising for application to other drug classes. - Highlights: • An integrative PKPD model is applied to study GLP-1r agonist carcinogenicity. • C-cell carcinogenicity is impacted by both pharmacokinetics and pharmacodynamics. • The relation of GLP-1r stimulation and C-cell hyperplasia appears drug-independent. • Understanding carcinogenic risk needs a pharmacological basis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Physical Interpretation of Early Battery Life Prediction Models

Early battery life prediction models are most useful for R&D if they help us understand the early changes in battery electrochemical response that correspond with long-term degradation and failure. Linear regression models such as Fused lasso and Partial Least Squares can fit coefficients directly to high-dimensional electrochemical data like capacity-voltage and ΔV–state-of-charge, i.e., Q(V) and ΔV(SOC) curves, learning coefficients that can be physically interpreted. We leverage the ISU-ILCC battery aging data set to learn high-dimensional coefficients for early battery life prediction from traditional slow-rate capacity check data, demonstrating learning on Q(V), d Q· d V −1 , and ΔV(SOC) curves. A thorough study on the dependence of coefficient values on train/test size and data preprocessing methods is made, demonstrating the reliability of high-dimensional regression approaches unless very small amounts of data are used for model training. For this data set, coefficients from Q(V) and d Q· d V −1 models highlight changes in electrode stoichiometry due to lithium loss, while ΔV(SOC) coefficients highlight changes in positive electrode diffusivity due to particle cracking as well as electrode stoichiometry shifts. By directly interpreting the coefficients of a regression model, we make physical insights into battery degradation mechanisms without requiring the assumptions of traditional battery data analysis methods.

25 ENERGY STORAGE↗
DOE OSTI2013

Development of a Rubber-Based Product Using a Mixture Experiment: A Challenging Case Study

Many products used in daily life are made by blending two or more components. The properties of such products typically depend on the relative proportions of the components. Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Each step of the study is discussed, including: 1) identifying the objective of the study and requirements for properties of the o-ring, 2) selecting the components to vary and specifying the component constraints, 3) constructing a mixture experiment design, 4) measuring the responses and assessing the data, 5) developing property-composition models, 6) selecting the new product formulation, and 7) confirming the selected formulation in manufacturing. The case study includes some challenging and new aspects, which are discussed in the article.

Full-cubic mixture model↗