Search NASA⌕ Search

SEARCH · Search NASA

Results for “physical samples”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

In situ saxs characterization of thermoresponsive behavior of a poly(ethylene glycol)-graft-(poly(vinyl caprolactam)-co-poly(vinyl acetate)) amphiphilic graft copolymer

In this work, we report the thermoresponsive assembly and rheology of an amphiphilic thermosensitive graft copolymer, poly(ethylene glycol)-graft-(poly(vinyl caprolactam)-co-poly(vinyl acetate)) (commercial name Soluplus ® ), which has been investigated for potential biomedical applications. It has received attention due to is ability to solubilize hydrophobic drugs and for its thickening behavior close to body temperature. Through use of the synchrotron at Brookhaven National Lab, and collaboration with the department of energy, the nanoscale structure and properties can be probed in greater detail. Soluplus ® undergoes two structural changes as temperature is increased; the first, a concentration independent change where samples become turbid at 32 °C. Increasing the temperature further causes the formation of physically associated hydrogels. This sol-gel transition is concentration dependent and occurs at 32 °C for 40 wt% samples, and increases to 42 °C for 10 wt% samples. From variable temperature SAXS characterization micelles of 20–25 nm in radius can be seen and maintain their size and packing below 32 °C. A gradual increase in the aggregation of micelles corresponding to a thickening of the material is also observed. Close to and above the gelation temperature, micelles collapse and form a physically associated 3D network. A model is proposed to explain these physical effects, where the poly(vinyl caprolactam) group transitions from the hydrophilic corona at room temperature to the hydrophobic core as temperature is increased.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Viking Landers and remote sensing

Thermal and radar remote sensing signatures of the materials in the lander sample fields can be crudely estimated from evaluations of their physical-mechanical properties, laboratory data on thermal conductivities and dielectric constants, and theory. The estimated thermal inertias and dielectric constants of some of the materials in the sample field are close to modal values estimated from orbital and earth-based observations. This suggests that the mechanical properties of the surface materials of much of Mars will not be significantly different that those of the landing sites.

Moore, H. J.↗
NASA NTRS2001

Predictability of the California Current System

The physical and biological oceanography of the Southern California Bight (SCB), a highly productive subregion of the California Current System (CCS) that extends from Point Conception, California, south to Ensenada, Mexico, continues to be extensively studied. For example, the California Cooperative Oceanic Fisheries Investigations (CalCOFI) program has sampled this region for over 50 years, providing an unparalleled time series of physical and biological data. However, our understanding of what physical processes control the large-scale and mesoscale variations in these properties is incomplete. In particular, the non-synoptic and relatively coarse spatial sampling (70km) of the hydrographic grid does not completely resolve the mesoscale eddy field (Figure 1a). Moreover, these unresolved physical variations exert a dominant influence on the evolution of the ecosystem. In recent years, additional datasets that partially sample the SCB have become available. Acoustic Doppler Current Profiler (ADCP) measurements, which now sample upper-ocean velocity between stations, and sea level observations along TOPEX tracks give a more complete picture of the mesoscale variability. However, both TOPEX and ADCP are well-sampled only along the cruise or orbit tracks and coarsely sampled in time and between tracks. Surface Lagrangian drifters also sample the region, although irregularly in time and space. SeaWiFS provides estimates of upper-ocean chlorophyll-a (chl-alpha), usually giving nearly complete coverage for week-long intervals, depending on cloud coverage. Historical ocean color data from the Coastal Zone Color Scanner (CZCS) has been used extensively to determine phytoplankton patterns and variability, characterize the primary production across the SCB coastal fronts, and describe the seasonal and interannual variability in pigment concentrations. As in CalCOFI, these studies described much of the observed structures and their variability over relatively large space and time scales.

Miller, Arthur J.↗
NASA NTRS2013

The Komplast Experiment: Space Environmental Effects after 12 Years in LEO (and Counting)

The Komplast materials experiment was designed by the Khrunichev State Research and Production Space Center, together with other Russian scientific institutes, and has been carried out by Mission Control Moscow since 18. Komplast panels fitted with material samples and sensors were located on the International Space Station (ISS) Functional Cargo Block (FGB) module exterior surface. Within the framework of this experiment, the purpose was to study the effect of the low earth orbit (LEO) environment on exposed samples of various materials. The panels were sent into orbit with the FGB when it launched on November 20, 1998. Panels #2 and #10 were retrieved during Russian extravehicular activity in February 2011 and sealed within cases to temporarily protect the samples from exposure to air until they could be studied on the ground. Panel #2 contained an experiment to detect micrometeoroid and orbital debris (MMOD) impacts, radiation and UV sensors, several pieces of electrical cable, and samples made from elastomeric and fluoroplastic materials. Panel #10 contained a temperature sensor, and both carbon composite and adhesive-bonded samples. A figure shows the location of panels #2 and #10 on the FGB module aft endcone. The panels were subsequently returned to Earth by Space Shuttle Discovery on the STS-133/ULF-5 mission after 12 years of LEO exposure and opened in an argon chamber at the Institute of Nuclear Physics at Moscow State University in July 2011. Based on the results of analyzing the readings from sensors located on Komplast panels and in studying material samples from the panels, the comprehensive effect of spaceflight factors on the FGB (at the locations of Panels #2 and #10) was evaluated. Total solar exposure was determined to be 960 +/- 200 kJ/square cm or 21,000 equivalent solar hours. Because of location of these two panels and the ISS flight attitude, atomic oxygen (AO) fluence was relatively low for such a long duration exposure, approximately 1.5x10 (exp 21) O atoms/sq. cm. Most of the AO fluence occurred during the early phase of ISS assembly. Temperatures ranged from a maximum of 107 C to a minimum of -80 C. The MMOD environment was determined, as is shown. Interestingly, the distribution of craters and low-velocity impact particles observed in the 5-50 micron size range was approx 2-3 orders of magnitude higher than that predicted by the ORDEM2000 model of natural and artificial origin microparticles in the ISS orbit. Contamination observations were also made, through the evaluation of optical properties on thermal control coatings and by the examination of visible deposits located near several samples on the panels, primarily from elastomeric samples. These elastomer samples were extensively investigated for their physical property changes and sealing capability. In addition, 16 samples of adhesive-bonded joints using three types of epoxy adhesive were evaluated studying fracture toughness, failure surface, and adhesive volume properties. Both rubber and adhesive-bonded specimens also underwent additional (post-flight) ground-based exposures to simulate a total 30 years in LEO prior to their evaluation. Overall, results indicate that space environmental effects will not adversely impact the service life of the FGB through 2028. Our investigation is complete and a summary of the results obtained from this uniquely long-duration exposure experiment will be presented.

Shaevich, S. K.↗
DOE OSTI2024

Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Efficient many-jet event generation with flow matching

We apply for the first time, to the best of our knowledge, the flow matching method to the problem of phase-space sampling for event generation in high-energy collider physics. By training the model to remap the random numbers used to generate the momenta and helicities of the scattering matrix elements as implemented in the portable partonic event generator pepper, we find substantial efficiency improvements in the studied processes. We focus our study on the highest final-state multiplicities in Drell-Yan and top-antitop pair production used in simulated samples for the Large Hadron Collider, which computationally are the most relevant ones. We find that the unweighting efficiencies improve by factors of 184 and 25, respectively, when compared to the standard approach of using a vegas-based optimization. We also compare continuous normalizing flows trained with flow matching against the previously studied normalizing flows based on coupling layers and find that the former leads to better results, faster training and a better scaling behavior across the studied multiplicity range, while the latter evaluate faster. When combining the advantages of both methods using the regflow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest final-state multiplicities.

Bothmann, E. [CERN; Gottingen U.] (ORCID:000000016↗
DOE OSTI2022

Adaptive Conformer Sampling for Property Prediction Using the Conductor-like Screening Model for Real Solvents

The valorization of lignocellulose-derived bioproducts requires effective separation from excessive water. Liquid–liquid extraction is a promising low-energy separation technology, but effective extraction requires solvent selection based on the thermodynamic properties of the bioproduct and solvent components. We propose a computational framework for predicting such properties by developing an adaptive conformer selection approach for use with COSMO-RS (conductor-like screening model for real solvents) calculations. In this framework, molecular dynamics simulations are used to generate many molecular structures (conformers) at representative temperatures in varying solvent environments. Conformers are then clustered based on structural metrics in a low-dimensional space and selected using a mixed-integer quadratic programming problem to iteratively insert a sampled conformer. At each iteration, we determine bioproduct properties using COSMO-RS. Here, we demonstrate the capability of the proposed framework on representative bioproducts to show convergence of the adaptive sampling toward experimentally measured properties with fewer calculations than required by random conformer sampling, enabling the improved screening of solvent systems for liquid-phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Quantifying the unknown impact of segmentation uncertainty on image-based simulations

Abstract Image-based simulation, the use of 3D images to calculate physical quantities, relies on image segmentation for geometry creation. However, this process introduces image segmentation uncertainty because different segmentation tools (both manual and machine-learning-based) will each produce a unique and valid segmentation. First, we demonstrate that these variations propagate into the physics simulations, compromising the resulting physics quantities. Second, we propose a general framework for rapidly quantifying segmentation uncertainty. Through the creation and sampling of segmentation uncertainty probability maps, we systematically and objectively create uncertainty distributions of the physics quantities. We show that physics quantity uncertainty distributions can follow a Normal distribution, but, in more complicated physics simulations, the resulting uncertainty distribution can be surprisingly nontrivial. We establish that bounding segmentation uncertainty can fail in these nontrivial situations. While our work does not eliminate segmentation uncertainty, it improves simulation credibility by making visible the previously unrecognized segmentation uncertainty plaguing image-based simulation.

42 ENGINEERING↗
DOE OSTI2023

Millimeter-Thick Liquid Crystalline Elastomer Actuators Prepared by-Surface-Enforced Alignment

Here, liquid crystalline elastomers (LCE) are thermally cyclable, compliant actuators with compelling mechanical properties. The large and programmable deformation of LCE has led to numerous functional examinations spanning optics, medical devices, and robotics. A well-established method to prepare complex LCE actuators is to utilize surface-enforced photoalignment. Herein, a facile and scalable approach is reported to circumvent the physical limits of surface-enforced alignment (e.g., samples that are 50 µm or less) to amplify the achievable force output in LCE. Applying an approach termed direct layering, the thermomechanical response of LCE elements prepared with +1 disclination patterns in a range of compositions and thicknesses is contrasted. The design and preparation of +1 disclination patterns and arrays is explored to assess the contribution of sample geometry and overlap to deformation and force output. The methodology detailed in this contribution allows for the preparation of elements ≈1 mm in thickness that are capable of actuating large objects. Furthermore, the fabrication of these elements uniquely enables the realization of mechanical instabilities to hasten the actuation rate in response to thermal change and to enable leaping.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A random-sampling method as an efficient alternative to variational Monte Carlo for solving Gutzwiller wavefunctions

Abstract We present a random-sampling (RS) method for evaluating expectation values of physical quantities using the variational approach. We demonstrate that the RS method is computationally more efficient than the variational Monte Carlo method using the Gutzwiller wavefunctions applied on single-band Hubbard models as an example. Non-local constraints can also been easily implemented in the current scheme that capture the essential physics in the limit of strong on-site repulsion. In addition, we extend the RS method to study the antiferromagnetic states with multiple variational parameters for 1D and 2D Hubbard models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Xu, Kun [Pennsylvania U.; Durham U., ICC; Tsung-Da↗
DOE OSTI2025

Suppression of the valence transition in solution-grown single crystals of Eu 2 Pt 6 Al 15

Here, the study of Eu intermetallic compounds has allowed the exploration of valence fluctuations and transitions in 4⁢𝑓 electron systems. Recently, a Eu 2 ⁢Pt 6 ⁢Al 15 phase synthesized by arc-melting followed by a thermal treatment was reported M. Radzieowski et al. [J. Am. Chem. Soc. 140, 8950 (2018)], which undergoes a transition upon cooling below 45 K that was interpreted as a valence transition from Eu 2+ to Eu 3+ . In this paper, we present the discovery of another polymorph of Eu 2 ⁢Pt 6 ⁢Al 15 obtained by high temperature solution growth, which presents different physical properties than the arc-melted polycrystalline sample. Despite the similarities in crystal structure and chemical composition, the Eu valence transition is almost fully suppressed in the solution-grown crystals, allowing the moments associated with the Eu 2+ state to order antiferromagnetically at around 14 K. A detailed analysis of the crystal structure using single crystal x-ray diffraction reveals that, although the solution grown crystals are built from the same constituent layers as the arc-melted samples, these layers present a different stacking. The effect of different thermal treatments is also studied. Different anneal procedures did not result in significant changes in the intrinsic properties, and only by arc-melting and quenching the crystals we were able to convert them into the previously reported polymorph.

Schmidt, Juan [Ames Laboratory, and Iowa State Uni↗
DOE OSTI2024

Cone beam neutron interferometry: From modeling to applications

Phase-grating moiré interferometers (PGMIs) have emerged as promising candidates for the next generation of neutron interferometry, enabling the use of a polychromatic beam and manifesting interference patterns that can be directly imaged by existing neutron cameras. However, the modeling of the various PGMI configurations is limited to cumbersome numerical calculations and backward propagation models which often do not enable one to explore the setup parameters. Here we generalize the Fresnel scaling theorem to introduce a k -space model for PGMI setups illuminated by a cone beam, thus enabling an intuitive forward propagation model for a wide range of parameters and experimental setups. The interference manifested by a PGMI is shown to be a special case of the Talbot effect, and the optimal fringe visibility is shown to occur at the moiré location of the Talbot distances. We derive analytical expressions for the contrast and the propagating intensity profiles in various conditions and provide the first analysis of the PGMI dark-field imaging signal when considering sample characterization. The model's predictions are compared to experimental measurements and good agreement is found between them. Last, we propose and experimentally verify a method to recover contrast at typically inaccessible PGMI autocorrelation lengths. The presented work provides a toolbox for analyzing and understanding existing PGMI setups and their future applications, for example extensions to two-dimensional PGMIs and characterization of samples with nontrivial structures. Published by the American Physical Society 2024

Sarenac, D. (ORCID:0000000185753367)↗
DOE OSTI2021

A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery

Physical and budget constraints often result in inadequate sampling for accurate subsurface imaging. Preprocessing approaches, such as missing trace interpolation, are typically employed to enhance seismic data in such cases. The compressed sensing (CS) framework has been applied for modeling missing seismic data, which is estimated by sparsity-based computational algorithms. While existing work mainly focuses on recovering missing traces resulting from receiver subsampling, source subsampling has greater economical advantages, as sources are more expensive than receivers. Moreover, stronger image models different from sparsity have not been explored for source recovery. This work presents a consensus equilibrium (CE) approach to recover missing seismic shots, which enables to incorporate various regularization operators modeling different data priors. Here, simulation results from a real 3-D land seismic dataset demonstrate that the CE approach provides more accurate estimations of the linear and hyperbolic events in the recovered shots, compared with pure sparsity-based reconstructions.

58 GEOSCIENCES↗
DOE OSTI2023

Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach

Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging. Preprocessing approaches, such as missing trace or shot interpolation, are typically employed to enhance seismic data in such cases. Recently, deep learning has been used to address the trace interpolation problem at the expense of large amounts of training data to adequately represent typical seismic events. Nonetheless, most research in this area has focused on trace reconstruction, with little attention having been devoted to shot interpolation. Furthermore, existing methods assume regularly spaced receivers/sources failing in approximating seismic data from real (irregular) surveys. This work presents a novel shot gather interpolation approach which uses a continuous coordinate-based representation of the acquired seismic wavefield parameterized by a neural network. The proposed unsupervised approach, which we call coordinate-based seismic interpolation (CoBSI), enables the prediction of specific seismic characteristics in irregular land surveys without using external data during neural network training. Importantly, experimental results on real and synthetic 3-D data validate the ability of the proposed method to estimate continuous smooth seismic events in the time-space and frequency-wavenumber domains, improving sparsity or low-rank-based interpolation methods.

58 GEOSCIENCES↗
DOE OSTI2020

¬¬Integration of Quantification of Margins and Uncertainties Methodology into Parallel Discrete Event Simulator Framework

Parallel Discrete Events Simulation (PDES) is becoming increasingly important to lab efforts in security and intelligence. It is used to model complex asynchronous systems such as computer networks, satellite systems, vehicular traffic, and human performance. Uncertainty Quantification (UQ) techniques have become a mainstay of Verification and Validation (V&V) efforts on physics simulations. However, PDES models are very different from traditional physics simulations, and research into UQ techniques for PDES is in its infancy. It is not clear which traditional UQ techniques can be applied to PDES, or what new techniques will need to be developed. The goal of this project was to identify existing UQ techniques that can be applied to PDES, and to develop new techniques as necessary. The project implemented or developed techniques to handle issues that do not appear in traditional physics simulations, but are common among PDES, including sampling techniques for high-dimensional homogenous inputs, response surfaces for high-variance heteroskedastic output, and characterization of skewed output distributions. These are foundational UQ techniques that must be used in any complete UQ analysis (Tong 2018).

97 MATHEMATICS AND COMPUTING↗