Search NASA⌕ Search

SEARCH · Search NASA

Results for “TEST RANGE”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermal Characterization of Tl 2 LiYCl 6 :Ce (TLYC)

Tl 2 LiYCl 6 :Ce (TLYC) is a new dual-detection elpasolite scintillator that can detect and distinguish between gamma rays and neutrons using pulse shape discrimination (PSD). It has a higher density and Z -number than the more mature and well-known elpasolite Cs 2 LiYCl 6 :Ce (CLYC), causing it to have a significantly better gamma-ray stopping power. These properties make TLYC an attractive alternative to CLYC for resource-constrained applications where size and weight are important, such as space or national security applications. Such applications may be subjected to a wide range of temperatures, and therefore, TLYC's performance was characterized for the first time over a temperature range of -20 °C to +50 °C in 10 °C increments. TLYC's thermal response effects on light-output linearity with energy, gamma-ray photopeak energy resolution, detected neutron energy, pulse shapes, and figure of merit (FOM) is analyzed and reported. The light output of TLYC was found to be linear with energy over the tested temperature range and was observed to decrease with increasing temperature. The decay time of the scintillation light output was observed to decrease with decreasing temperature at short times, leading to a decreasing PSD FOM. The gamma-ray photopeak energy resolution was also observed to degrade with decreasing temperature, due to an asymmetric broadening of the photopeak at low temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments

This article describes PyOED, a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, the current version of PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to “enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.” This article provides a brief description of the PyOED layout and philosophy and provides a set of exemplary test cases and tutorials to demonstrate the potential of the package.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PYOED: AN ETENSIBLE SUITE FOR DATA ASSIMILATION AND MODEL-CONSTRAINED OPTIMAL DESIGN OF EXPERIMENTS

SF-23-005 PyOED is a highly extensible scientific package that enables developing and testing model-constrained optimal experimental design (OED) for inverse problems. Specifically, PyOED aims to be a comprehensive Python toolkit for model-constrained OED. The package targets scientists and researchers interested in understanding the details of OED formulations and approaches. It is also meant to enable researchers to experiment with standard and innovative OED technologies with a wide range of test problems (e.g., simulation models). OED, inverse problems (e.g., Bayesian inversion), and data assimilation (DA) are closely related research fields, and their formulations overlap significantly. Thus, PyOED is continuously being expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators. These pieces are added such that they can be permuted to enable testing OED methods in various settings of varying complexities. The PyOED core is completely written in Python and utilizes the inherent object-oriented capabilities; however, PyOED is meant to be extensible rather than scalable. Specifically, PyOED is developed to ``enable rapid development and benchmarking of OED methods with minimal coding effort and to maximize code reutilization.'' PyOED will be continuously expanded with a plethora of Bayesian inversion, DA, and OED methods as well as new scientific simulation models, observation error models, and observation operators.

ATTIA, AHMEDMOHAMED↗
DOE OSTI2023

Using the Shallow Strain Tensor to Characterize Deep Geologic Reservoirs

Abstract Storing and recovering water, carbon, and heat from geologic reservoirs is central to managing resources in a changing climate. We tested the hypothesis that the strain tensor caused by injecting or producing fluids can be measured at shallow depths and interpreted to advance understanding of underlying deep aquifers or reservoirs. Geodetic‐grade strainmeters were deployed at 30 m depth overlying the Bartlesville Formation, a 500‐m‐deep sandstone near Tulsa, OK. The strainmeters are 220 m east of injection well 9A completed in a permeable lens at the base of the Bartlesville Formation. Water was injected into well 9A at approximately 1.0 L/s during four tests that ranged in duration from a few hours to a few weeks. The horizontal strain increased (tension) and the circumferential strain was a few times larger than the radial strain. The vertical strain decreased (compression) during injection. Strain rates were approximately 100 nε/day during the first few hours, but the rates decreased and were approximately 10 nε/day during most of the tests. Four independent methods of poroelastic simulation and inversion predict reservoir properties and geometries that are similar to each other and consistent with independent information about the reservoir. All strain interpretations predict that a boundary to the permeable lens occurs beneath the vicinity of the strainmeters, which is consistent with core data from the site. The boundary of the permeable lens is located by matching the vertical, radial and circumferential strains, which demonstrates the value of measuring the strain tensor.

Murdoch, Lawrence C.↗
DOE OSTI2020

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy–funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor–like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD–based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 ·s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

42 ENGINEERING↗
DOE OSTI2023

Microscopic theory, analysis, and interpretation of conductance histograms in molecular junctions

Molecular electronics break-junction experiments are widely used to investigate fundamental physics and chemistry at the nanoscale. Reproducibility in these experiments relies on measuring conductance on thousands of freshly formed molecular junctions, yielding a broad histogram of conductance events. Experiments typically focus on the most probable conductance, while the information content of the conductance histogram has remained unclear. Here we develop a microscopic theory for the conductance histogram by merging the theory of force-spectroscopy with molecular conductance. The procedure yields analytical equations that accurately fit the conductance histogram of a wide range of molecular junctions and augments the information content that can be extracted from them. Our formulation captures contributions to the conductance dispersion due to conductance changes during the mechanical elongation inherent to the experiments. In turn, the histogram shape is determined by the non-equilibrium stochastic features of junction rupture and formation. The microscopic parameters in the theory capture the junction’s electromechanical properties and can be isolated from separate conductance and rupture force (or junction-lifetime) measurements. The predicted behavior can be used to test the range of validity of the theory, understand the conductance histograms, design molecular junction experiments with enhanced resolution and molecular devices with more reproducible conductance properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Normative Ranges for Oculomotor and Reaction Time Tests in U.S. Military Service Members and Veterans

AbstractBackground Oculomotor and reaction time tests are frequently used assessments of vestibular symptoms, traumatic brain injury (TBI), or other neurological disorders in both clinical and research contexts. When interpreting these tests it is important to have a reference interval (RI) as a comparison for what constitutes a typical/expected response; however, the current body of research has only limited information regarding normative ranges calculated according to established standards or for a military-specific sample.Purpose The purpose of the present study was to describe RIs for oculomotor and reaction time tests in a cohort of service members and veterans (SMVs) for use as comparators by clinicians and scientists.Research Design Descriptive.Study Sample Participants were prospectively enrolled in the Defense and Veterans Brain Injury Center-Traumatic Brain Injury Center of Excellence 15-year Longitudinal Traumatic Brain Injury Study. Only SMVs without a history of TBI or blast exposure were included in the RI calculations.Data Collection and Analysis The test paradigms included in this analysis were: smooth pursuit, prosaccades, antisaccades, saccades and reaction time, predictive saccades, optokinetic nystagmus, auditory reaction time, and visual reaction time. Nonparametric methods, based on the U.S. Food and Drug Administration's recognized consensus standards, were used to calculate 95% RIs. A comparison between the calculated RIs and those available from previously published research is provided.Results Summary statistics and RIs were calculated for 47 outcome parameters from 13 oculomotor and reaction time tests. Sample sizes and age ranges varied across outcome parameters depending on the availability of reference values for RI calculations. The sample sizes used to calculate RIs ranged from 51 to 69. The age of SMVs included in each RI ranged from 19 to 61 years with mean ages ranging from 37 to 39 years. Similarities/differences between the RIs in the present study and those in previously published research are highly dependent on the outcome parameter; however, in general, the RIs in the present study tended to be somewhat wider.Conclusion The RIs provided in this paper can serve as comparisons for clinicians and scientists who are utilizing these oculomotor and reaction time testing paradigms in similar cohorts of patients or research participants.

Audiology & Speech-Language Pathology↗
DOE OSTI2024

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Dean vortex-enhanced blood plasma separation in self-driven spiral microchannel flow with cross-flow microfilters

Point-of-care (POC) diagnostic devices have been developing rapidly in recent years, but they are mainly using saliva instead of blood as a test sample. A highly efficient self-separation during the self-driven flow without power systems is desired for expanding the point-of-care diagnostic devices. Microfiltration stands out as a promising technique for blood plasma separation but faces limitations due to blood cell clogging, resulting in reduced separation speed and efficiency. These limitations are mainly caused by the high viscosity and hematocrit in the blood flow. A small increment in the hematocrit of the blood significantly increases the pressure needed for the blood plasma separation in the micro-filters and decreases the separation speed and efficiency. Addressing this challenge, this study explores the feasibility of diluting whole blood within a microfluidic device without external power systems. This study implemented a spiral microchannel utilizing the inertial focusing and Dean vortex effects to focus the red blood cells and extract the blood with lower hematocrit. The inertial migration of the particles during the capillary flow was first investigated experimentally; a maximum of 88% of the particles migrated to the bottom and top equilibrium positions in the optimized 350 × 60 μm (cross-sectional area, 5.8 aspect ratio) microchannel. With the optimized dimension of the microchannel, the whole blood samples within the physiological hematocrit range were tested in the experiments, and more than 10% of the hematocrit reduction was compared between the outer branch outlet and inner branch outlet in the 350 × 60 μm microchannel.

Biochemistry & Molecular Biology↗
DOE OSTI2022

A Comparative Study of Compressive Effects on the Morphology and Performance of Carbon Paper and Cloth Electrodes in Redox Flow Batteries

Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression‐induced changes impact pressure drop, polarization, and mass‐transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge‐transfer, and mass‐transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade‐offs of mechanical robustness on fluid‐dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

25 ENERGY STORAGE↗
DOE OSTI2019

Kinetics of the Carbothermic Reduction of Manganese Oxide from Slag

Experiments were performed using a range of test conditions to elucidate the rate controlling step during the reaction of liquid iron-carbon droplets and slags containing manganese oxide. Four conditions were tested in the system: initial MnO content in the slag (5, 10, and 15 wt pct), initial carbon content of the metal (1, 2.5, 4.3 wt pct), initial droplet mass (0.5, 1.0, and 1.5 g), and reaction temperature (1823 K [1550 °C], 1873 K [1600 °C], and 1923 K [1650 °C]). Data were collected using the Constant Volume Pressure Increase (CVPI) technique which tracked the continuous pressure increase in the sealed furnace over time. Samples were quenched at the end of each experiment and chemistry was checked using LECO Carbon Analysis and ICP (Inductively Coupled Plasma) for manganese. The rate of reaction can be broken into a faster initial period related to internal CO formation, and a slower second reaction controlled by a complex mechanism involving transport of oxygen from slag to metal via CO{sub 2} and decomposition of the CO{sub 2} at the gas–metal interface.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows

Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR codes. In this work a novel hybrid adaptive multiresolution (HAMR) approach to AMR-based calculations is introduced to address this issue. The multiresolution (MR) smoothness indicators are used to identify regions of smoothness on the mesh where the computational cost of individual physics solvers may be decreased by replacing direct calculations with interpolation. We suggest an approach to balance the errors due to the adaptive discretization and the interpolation of physics quantities such that the overall accuracy of the HAMR solution is consistent with that of the MR-driven AMR solution. The performance of the HAMR scheme is evaluated for a range of test problems, from pure hydrodynamics to turbulent combustion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Determination of oxidation rates and volatile oxidation products for HTGR graphite matrix material exposed to steam atmospheres

High-temperature gas-cooled reactors (HTGRs) in operation use tristructural isotropic (TRISO) particles embedded in graphite and carbonized resin matrix to form the fuel element. This graphite matrix material serves as a supportive structural element, heat transfer medium, and neutron moderator. In HTGR designs, fuel compacts are exposed to helium coolant, which facilitates high outlet temperatures (750°C 2 O, 800°C 2 , and H 2 , are quantified in varied oxidant atmospheres using a coupled thermogravimetric analyzer and mass spectrometer. Furthermore, oxidation rates reported here for varied steam (H 2 O [g]) atmospheres are predominantly linear and comparable with literature values in the range of tested temperatures (800–1200°C). Changes in dominant matrix oxidation products from primarily CO to a mixture of CO, CO 2 , and H 2 were observed at higher temperatures (≥1000°C) and steam atmospheres (≥5 kPa pH 2 O). Kinetic data indicates that there was no shift in oxidation regime with chemical oxidation occurring at all temperatures and H2O (g) atmospheres tested. These data provide insight into the oxidation behavior of graphite matrix material and will inform future testing conditions, notably mixed atmospheric conditions, of HTGR fuel elements.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Joining technique for in-oven/autoclave molds manufactured by large scale polymer additive manufacturing

Large scale additive manufacturing (AM) of fiber-reinforced polymer composites has gained traction in the mold and die community over the last decade, largely due to reduced material cost and lead time. However, limitations in mold size remain present due to printer volume constraints and costs associated with large format machines. Here, this paper describes a method for producing additively manufactured polymer molds in segments with an O-ring joint design, which can be machined and subsequently assembled for autoclave applications. The developed joining mechanism allows for maintaining the vacuum integrity during the cure cycle while accounting for the anisotropic nature of the additively manufactured polymer molds. Over a range of tested temperatures, 20–200 °C, the multi-part mold joining design was able to achieve full vacuum of ∼73.7 cmHg (29 inchHg) and maintain a vacuum integrity with vacuum losses less than 1.5 cmHg/5min (0.6 inchHg).

Joining↗
DOE OSTI2023

Diffusion in intact secondary cell wall models of plants at different equilibrium moisture content

Secondary plant cell walls are composed of carbohydrate and lignin polymers, and collectively represent a significant renewable resource. Leveraging these resources depends in part on a mechanistic understanding for diffusive processes within plant cell walls. Common wood protection treatments and biomass conversion processes to create biorefinery feedstocks feature ion or solvent diffusion within the cell wall. X-ray fluorescence microscopy experiments have determined that ionic diffusion rates are dependent on cell wall hydration as well as the ionic species through non-linear relationships. In this work, we use classical molecular dynamics simulations to map the diffusion behavior of different plant cell wall components (cellulose, hemicellulose, lignin), ions (Na + , K + , Cu2 + , Cl - ) and water within a model for an intact plant cell wall at various hydration states (3-30 wt% water). From these simulations, we analyze the contacts between different plant cell wall components with each other and their interaction with the ions. Generally, diffusion increases with increasing hydration, with lignin and hemicellulose components increasing diffusion by an order of magnitude over the tested hydration range. Ion diffusion depends on charge. Positively charged cations preferentially interact with hemicellulose components, which include negatively charged carboxylates. As a result, positive ions diffuse more slowly than negatively charged ions. Measured diffusion coefficients are largely observed to best fit piecewise linear trends, with an inflection point between 10 and 15% hydration. These observations shed light onto the molecular mechanisms for diffusive processes within secondary plant cell walls at atomic resolution.

09 BIOMASS FUELS↗
DOE OSTI2021

Evaluation of Differential Peptide Loading on Tandem Mass Tag-Based Proteomic and Phosphoproteomic Data Quality

Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One major barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics—currently on the order of 25 mg wet tissue weight, depending on tissue type. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is in excess of 10 million (1E7) peripheral blood mononuclear cells (PBMCs). Throughout the course of a prospective study, this requirement will certainly exceed what is obtainable from many of the individual patients/timepoints. For this reason, we were interested in examining the impact of differential peptide loading across multiplex channels on proteomic data quality. Methods: To achieve this, we tested a range of channel loading amounts (20, 40, 100, 200, and 400 µg of tryptic peptides, or approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification reproducibility and accuracy in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, we found that fewer missing values are observed in TMT channels with higher peptide loading amounts compared to those with lower loading. Moreover, channels with lower loading amounts have greater quantitative variability than channels with higher loading amounts. Statistical analysis of the differences in means among the five loading groups showed that the 20 µg loading group was significantly different from the 400 µg loading group. However, no significant differences were detected among the 40, 100, 200 and 400 µg loading groups. Conclusions: These assessment data demonstrate the practical limits of loading differential quantities of peptides across channels in TMT multiplexes, and provide a basis for designing the optimal clinical proteomics study when specimen quantities are limited.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Technology Pathways Could Help Drive the U.S. West Coast Grid's Exposure to Hydrometeorological Uncertainty

Abstract Previous studies investigating deep decarbonization of bulk electric power systems and wholesale electricity markets have not sufficiently explored how future grid pathways could affect the grid's vulnerability to hydrometeorological uncertainty on multiple timescales. Here, we employ a grid operations model and a large synthetic weather ensemble to “stress test” a range of future grid pathways for the U.S. West Coast developed by ReEDS, a well‐known capacity planning model. Our results show that gradual changes in the underlying capacity mix from 2020 to 2050 can cause significant “re‐ranking” of weather years in terms of annual wholesale electricity prices (with “good” years becoming bad, and vice versa). Nonetheless, we find the highest and lowest ranking price years in terms of average electricity price remain mostly tied to extremes in hydropower availability (streamflow) and load (summer temperatures), with the strongest sensitivities related to drought. Seasonal dynamics seen today involving spring snowmelt and hot, dry summers remain well‐defined out to 2050. In California, future supply shortfalls in our model are concentrated in the evening and occur mostly during periods of high temperature anomalies in late summer months and in late winter; in the Pacific Northwest, supply shortfalls are much more strongly tied to negative streamflow anomalies. Under our more robust sampling of stationary hydrometeorological uncertainty, we also find that the ratio of dis‐patchable thermal (i.e., natural gas) capacity to wind and solar required to ensure grid reliability can differ significantly from values reported by ReEDS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗