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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Dempsey, Paula J.↗
NASA NTRS2023

Direct Measurement of the Cosmic-Ray Helium Spectrum from 40 GeV to 250 TeV with the Calorimetric Electron Telescope on the International Space Station

We present the results of a direct measurement of the cosmic-ray helium spectrum with the CALET instrument in operation on the International Space Station since 2015. The observation period covered by this analysis spans from October 13, 2015, to April 30, 2022 (2392 days). The very wide dynamic range of CALET allowed for the collection of helium data over a large energy interval, from ∼40 GeV to ∼250 TeV, for the first time with a single instrument in low Earth orbit. The measured spectrum shows evidence of a deviation of the flux from a single power law by more than 8σ with a progressive spectral hardening from a few hundred GeV to a few tens of TeV. This result is consistent with the data reported by space instruments including PAMELA, AMS-02, and DAMPE and balloon instruments including CREAM. At higher energy we report the onset of a softening of the helium spectrum around 30 TeV (total kinetic energy). Though affected by large uncertainties in the highest energy bins, the observation of a flux reduction turns out to be consistent with the most recent results of DAMPE. A double broken power law is found to fit simultaneously both spectral features: the hardening (at lower energy) and the softening (at higher energy). A measurement of the proton to helium flux ratio in the energy range from 60 GeV=n to about 60 TeV=n is also presented, using the CALET proton flux recently updated with higher statistics.

O Adriani↗
NASA NTRSDate not supplied

Adjusting a Full Body Model to Mitigate Inverse Kinematics Artifacts in Opensim

BACKGROUND: In support of Vibration Isolation and Stabilization (VIS) system development for Human Health Countermeasures (HHC) exercise systems in space, such as the European Enhanced Exploration Exercise Device (E4D) [1], dynamic quantities required to model the response of a proposed VIS while considering the effect of VIS motion on the forces between the human and VIS platform were obtained using motion capture data [2]. On occasion, large-amplitude oscillatory spikes were found in the subject’s linear and angular momentum derivatives, affecting analyses that depend on forces and moments derived from motion capture. The purpose of this investigation was to identify causes of these artifacts and techniques for their resolution. METHODS AND RESULTS: To obtain the required human dynamic quantities to drive the VIS simulation, motion capture data was collected containing recorded trajectories of passive retroreflective markers on body landmarks of an exercising subject. Since the full body Rajagopal model [3] was originally used to enhance gait analysis, upper body joints did not require large Ranges of Motion (ROM). We thus modified the Rajagopal model [4, 5] to allow it to be used for upper body intensive exercises like those common to the E4D. OpenSim Inverse Kinematics (IK) [6] was performed using these scaled subject models to generate the joint angles throughout the exercise while minimizing marker error. At times, the arms were observed to ‘snap’ from one configuration to another, causing spike artifacts. Following IK, a custom OpenSim plugin [7] was used to determine the required dynamic quantities including the rates of change of the linear and angular momenta of the human. Since motion capture is recorded at a larger time step than required by the VIS simulation, the human center of mass location was fit with splines and a second derivative taken to obtain the momentum derivative, allowing the VIS simulation to maintain conservation of momentum when appropriate. In a few cases during this stage, artifacts much larger than the expected noise of the second derivatives were introduced. Investigation of cases containing artifacts revealed several modifications that could be made to the OpenSim model to improve IK results. Since OpenSim models use Euler angles and rotation sequences, ‘gimbal lock’ would be encountered in the arms when raised 90 degrees to the side (e.g., T-pose, some hang clean exercise, etc.). This was resolved by reorienting the horizontal axes at the shoulder joint by 45 degrees, placing ‘gimbal lock’ outside common arm ROM, with the arm ROMs adjusted following this change. Elbow and wrist ROMs could also be adjusted to allow realistic motion while at the same time limiting the likelihood of unrealistic orientations. On occasion, the arms flipped backwards when raised above the head. This was prevented by using medial elbow markers in scaling and IK. When medial markers were not available, the acromial joint location in the unscaled model was shifted before model scaling to better align the arm with available markers. Lastly, artifacts which became apparent after taking the second derivatives of spline-fit data were found to occur in cases when the pelvis rotation limit prevented the full range of motion of an exercise. These issues were resolved by unclamping the pelvis rotation limit. Through this investigation, an understanding of conditions leading to IK artifacts was acquired allowing the automation of artifact detection. These artifact detection and mitigation techniques can be applied toward modeling of upper body motions in aerospace and other fields for improved IK results.

C A Bell↗
NASA NTRS2015

Post-Flight Aerodynamic and Aerothermal Model Validation of a Supersonic Inflatable Aerodynamic Decelerator

NASA's Low Density Supersonic Decelerator Program is developing new technologies that will enable the landing of heavier payloads in low density environments, such as Mars. A recent flight experiment conducted high above the Hawaiian Islands has demonstrated the performance of several decelerator technologies. In particular, the deployment of the Robotic class Supersonic Inflatable Aerodynamic Decelerator (SIAD-R) was highly successful, and valuable data were collected during the test flight. This paper outlines the Computational Fluid Dynamics (CFD) analysis used to estimate the aerodynamic and aerothermal characteristics of the SIAD-R. Pre-flight and post-flight predictions are compared with the flight data, and a very good agreement in aerodynamic force and moment coefficients is observed between the CFD solutions and the reconstructed flight data.

Supersonic Flight Dynamics Test↗
NASA NTRS1998

Advanced Data Format (ADF) Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial. Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its 1/0 software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The ADF is a generic database manager with minimal intrinsic capability. It was written for the purpose of storing large numerical datasets in an efficient, platform independent manner. To be effective, it must be used in conjunction with external agreements on how the data will be organized within the ADF database such defined by the SIDS. There are currently 34 user callable functions that comprise the ADF Core library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Smith, Matthew↗
DOE OSTI2016

NSLS-II biomedical beamlines for micro-crystallography, FMX, and for highly automated crystallography, AMX: New opportunities for advanced data collection

We present the final design of the x-ray optics and experimental stations of two macromolecular crystallography (MX) beamlines at the National Synchrotron Light Source-II. The microfocusing FMX beamline will deliver a flux of ∼5×10{sup 12} ph/s at 1 Å into a 1 – 20 µm spot, its flux density surpassing current MX beamlines by up to two orders of magnitude. It covers an energy range from 5 – 30 keV. The highly automated AMX beamline is optimized for high throughput, with beam sizes from 4 – 100 µm, an energy range of 5 – 18 keV and a flux at 1 Å of ∼10{sup 13} ph/s. A focus in designing the beamlines lay on achieving high beam stability, for example by implementing a horizontal bounce double crystal monochromator at FMX. A combination of compound refractive lenses and bimorph mirror optics at FMX supports rapid beam size changes. Central components of the in-house developed experimental stations are horizontal axis goniometers with a target sphere of confusion of 100 nm, piezo-slits for dynamic beam size changes during diffraction experiments, dedicated secondary goniometers for data collection from specimen in crystallization plates, and next generation pixel array detectors. FMX and AMX will support a broad range of biomedical structure determination methods from serial crystallography on micron-sized crystals, to structure determination of complexes in large unit cells, to rapid sample screening and room temperature data collection of crystals in trays.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

An automated platform for in situ serial crystallography at room temperature

Direct observation of functional motions in protein structures is highly desirable for understanding how these nanomachineries of life operate at the molecular level. Because cryogenic temperatures are non-physiological and may prohibit or even alter protein structural dynamics, it is necessary to develop robust X-ray diffraction methods that enable routine data collection at room temperature. We recently reported a crystal-on-crystal device to facilitate in situ diffraction of protein crystals at room temperature devoid of any sample manipulation. Here an automated serial crystallography platform based on this crystal-on-crystal technology is presented. A hardware and software prototype has been implemented, and protocols have been established that allow users to image, recognize and rank hundreds to thousands of protein crystals grown on a chip in optical scanning mode prior to serial introduction of these crystals to an X-ray beam in a programmable and high-throughput manner. This platform has been tested extensively using fragile protein crystals. We demonstrate that with affordable sample consumption, this in situ serial crystallography technology could give rise to room-temperature protein structures of higher resolution and superior map quality for those protein crystals that encounter difficulties during freezing. This serial data collection platform is compatible with both monochromatic oscillation and Laue methods for X-ray diffraction and presents a widely applicable approach for static and dynamic crystallographic studies at room temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Optimal Power Flow Pursuit

Past works that focused on addressing power-quality and reliability concerns related to renewable energy resources (RESs) operating with business-as-usual practices have looked at the design of Volt/VAr and Volt/Watt strategies to regulate real or reactive powers based on local voltage measurements, so that terminal voltages are within acceptable levels. These control strategies have the potential of operating at the same time scale of distribution-system dynamics, and can therefore mitigate disturbances precipitated fast time-varying loads and ambient conditions; however, they do not necessarily guarantee system-level optimality, and stability claims are mainly based on empirical evidences. On a different time scale, centralized and distributed optimal power flow (OPF) algorithms have been proposed to compute optimal steady-state inverter setpoints, so that power losses and voltage deviations are minimized and economic benefits to end-users providing ancillary services are maximized. However, traditional OPF schemes may offer decision making capabilities that do not match the dynamics of distribution systems. Particularly, during the time required to collect data from all the nodes of the network (e.g., loads), solve the OPF, and subsequently dispatch setpoints, the underlying load, ambient, and network conditions may have already changed; in this case, the DER output powers would be consistently regulated around outdated setpoints, leading to suboptimal system operation and violation of relevant electrical limits. The present work focuses on the synthesis of distributed RES-inverter controllers that leverage the opportunities for fast feedback offered by power-electronics interfaced RESs. The overarching objective is to bridge the temporal gap between long-term system optimization and real-time control, to enable seamless RES integration in large scale with stability and efficiency guarantees, while congruently pursuing system-level optimization objectives. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. The proposed controllers enable an update of the power outputs at a time scale that is compatible with the underlying dynamics of loads and ambient conditions, and continuously drive the system operation towards OPF-based solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Synoptic NO3 in Slate River Watershed, Colorado (2022)

The synoptic nitrate (NO3) dataset in the Slate River Watershed, Colorado consists of NO3 data collected at 19 locations three times during the summer of 2022. Stream samples were collected in early summer (early July), mid summer (late August), and late summer (late September). The samples include mainstem, tributary, and point source input water samples. These data were collected to evaluate spatiotemporal variability in stream NO3 during the summer, and evaluate anthropogenic controls on stream NO3 dynamics. This data package contains: (1) a csv of all NO3 samples and (2) a csv of locations for each sampling site. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > FRESHWATE↗
DOE OSTI2023

Exploring the determinants of organic matter bioavailability through substrate-explicit thermodynamic modeling

Microbial decomposition of organic matter (OM) in river corridors is a major driver of nutrient and energy cycles in natural ecosystems. Recent advances in omics technologies enabled high-throughput generation of molecular data that could be used to inform biogeochemical models. With ultrahigh-resolution OM data becoming more readily available, in particular, the substrate-explicit thermodynamic modeling (SXTM) has emerged as a promising approach due to its ability to predict OM degradation and respiration rates from chemical formulae of compounds. This model implicitly assumes that all detected organic compounds are bioavailable, and that aerobic respiration is driven solely by thermodynamics. Despite promising demonstrations in previous studies, these assumptions may not be universally valid because OM degradation is a complex process governed by multiple factors. To identify key drivers of OM respiration, we performed a comprehensive analysis of diverse river systems using Fourier-transform ion cyclotron resonance mass spectrometry OM data and associated respiration measurements collected by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium. In support of our argument, we found that the incorporation of all compounds detected in the samples into the SXTM resulted in a poor correlation between the predicted and measured respiration rates. The data-model consistency was significantly improved by the selective use of a small subset (i.e., only about 5%) of organic compounds identified using an optimization method. Through a subsequent comparative analysis of the subset of compounds (which we presume as bioavailable) against the full set of compounds, we identified three major traits that potentially determine OM bioavailability, including: (1) thermodynamic favorability of aerobic respiration, (2) the number of C atoms contained in compounds, and (2) carbon/nitrogen (C/N) ratio. We found that all three factors serve as “filters” in that the compounds with undesirable properties in any of these traits are strictly excluded from the bioavailable fraction. This work highlights the importance of accounting for the complex interplay among multiple key traits to increase the predictive power of biogeochemical and ecosystem models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Shock compression of vanadium at extremes: Theory and experiment

Here, the equation of state (EOS) and shock compression of bulk vanadium were investigated using canonical ab initio molecular dynamic simulations, with experimental validation to 865 GPa from shock data collected at Sandia's Z Pulsed Power Facility. In simulations the phase space was sampled along isotherms ranging from 3000 K to 50 000 K, for densities between ρ = 3 and 15 g / cm 3 , with a focus on the liquid regime and the body-centered-cubic phase in the vicinity of the melting limit. The principal Hugoniot predicted from first principles is overall consistent with shock data, while it showed that current multiphase SESAME-type EOS for vanadium needed revision in the liquid regime. A more accurate SESAME EOS was developed using constraints from experiments and simulations. This work emphasizes the need to use a combined theoretical and experimental approach to develop high-fidelity EOS models for extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure

Highlights: • A year's worth of RF-EMF data is collected in an urban sensor network is analysed. • A full spatio-temporal model of the RF-EMF exposure in the study area is built. • Short-term variations of the RF-EMF exposure are collected in temporal profiles. • Models using data collected at different instants are improved by adjusting for time. As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio-temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42 dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Investigation of the yielding transition in concentrated colloidal systems via rheo-XPCS

We probe the microstructural yielding dynamics of a concentrated colloidal system by performing creep/recovery tests with simultaneous collection of coherent scattering data via X-ray Photon Correlation Spectroscopy (XPCS). This combination of rheology and scattering allows for time-resolved observations of the microstructural dynamics as yielding occurs, which can be linked back to the applied rheological deformation to form structure–property relations. Under sufficiently small applied creep stresses, examination of the correlation in the flow direction reveals that the scattering response recorrelates with its predeformed state, indicating nearly complete microstructural recovery, and the dynamics of the system under these conditions slows considerably. Conversely, larger creep stresses increase the speed of the dynamics under both applied creep and recovery. The data show a strong connection between the microstructural dynamics and the acquisition of unrecoverable strain. By comparing this relationship to that predicted from homogeneous, affine shearing, we find that the yielding transition in concentrated colloidal systems is highly heterogeneous on the microstructural level.

42 ENGINEERING↗
NASA NTRS2011

Three-Dimensional Model for Preservation and Restoration of Architectural Heritage

Thc aim of the research will be to create a model, three-dimensional mathematical. implementation. consultation and assistance to "large" restoration projects that will assist the structural analysis, allowing easier display of dynamic strain. analysis and lighting noise. It could also be a valuable tool for decision support. therefore. may simulate several possible scenarios for intervention, This model appears therefore an excellent support for recovering. ordering and monitoring information about materials and data (stage of restoration. photographs. sampling points. results of diagnostic tests, etc.) collected dynamically during the "life" of the cultural heritage. allowing to document its complete history

Marchis, Elena↗
DOE OSTI2022

Bayesian-based response expansion and uncertainty quantification using sparse measurement sets

Systems subjected to dynamic loads often require monitoring of their vibrational response, but limitations on the total number and placement of the measurement sensors can hinder the data-collection process. Here, we present an indirect approach to estimate a system’s full-field dynamic response, including all uninstrumented locations, using response measurements from sensors sparsely located on the system. This approach relies on Bayesian inference that utilizes a system model to estimate the full-field response and quantify the uncertainty in these estimates. By casting the estimation problem in the frequency domain, this approach utilizes the modal frequency response functions as a natural, frequency-dependent weighting scheme for the system mode shapes to perform the expansion. This frequency-dependent weighting scheme enables an accurate expansion, even with highly correlated mode shapes that may arise from spatial aliasing due to the limited number of sensors, provided these correlated modes do not have natural frequencies that are closely spaced. Furthermore, the inherent regularization mechanism that arises in this Bayesian-based procedure enables the utilization of the full set of system mode shapes for the expansion, rather than any reduced subset. This approach can produce estimates when considering a single realization of the measured responses, and with some modification, it can also produce estimates for power spectral density matrices measured from many realizations of the responses from statistically stationary random processes. A simply supported beam provides an initial numerical validation, and a cylindrical test article excited by acoustic loads in a reverberation chamber provides experimental validation.

42 ENGINEERING↗
DOE OSTI2026

Fast and accurate calculation of EXAFS Debye-Waller factors in U⁢O2 using the dynamical matrix method

Theoretical modeling of bonding dynamics in metal oxides is required for predicting their thermal conductivity, catalytic activity, and mechanical properties. A primary challenge is the scarcity of experimental methods for validating theoretical predictions of these atomic-scale dynamics. This work presents a workflow that uses experimental extended x-ray absorption fine structure (EXAFS) data collected at high temperatures to validate an interatomic force field for uranium dioxide (UO2), an important model material. The validated force field is then used to drive computationally intensive molecular dynamics (MD) simulations and as input for the much faster dynamical matrix Debye-Waller (DMDW) method. The predicted values of the Debye-Waller factors from the DMDW calculations are in good agreement with those obtained from the MD simulations, with residual pair-specific differences attributable to quantum zero-point motion at low temperatures and lattice anharmonicity at high temperatures. We further show that theoretical EXAFS spectra constructed directly from DMDW-derived Debye-Waller factors reproduce the experimental data (at relatively low temperatures) with accuracy comparable to full MD-EXAFS, providing an additional validation of the choice of the potential. This study establishes a validated, rapid computational pathway for modeling bond dynamics, naturally incorporating quantum nuclear\\\\r\\\\nstatistics absent in classical simulations, which are essential for the mechanistic understanding of complex oxide materials.

58 GEOSCIENCES↗
DOE OSTI2020

Dynamic compressed sensing for real-time tomographic reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by ~3-fold while also reducing its error by 27% for a Au/SrTiO 3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within ~33% of completion and fine details are visible as early as ~66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, we report reconstruction parameters that tune data fidelity can be manipulated throughout the computation without re-running the entire process.

47 OTHER INSTRUMENTATION↗