Results for “Experiment Data” — Page 71

NASA NTRS1985

Measurement of damping of graphite epoxy materials

The design of an experiment to measure the damping of a cylindrical graphite-epoxy specimen with a three point support and a knife edge support is described as well as equipment used in tests conducted to determine the influence of the support at the two ends of the specimen and to simulate an idealized free-free boundary condition at the two edges. A curve fitting technique is being used to process the frequency response data obtained. Experiments conducted on the thin plate specimen also reveal the influence of the end support condition on the damping ratio of the specimen. The damping ratio values measured for both specimens appear to be strongly influenced by the shape of the specimen and appear to depend on length and fiber orientation as well as the presence of discontinuities such as sharp bends, corners, and notches.

Crocker, M. J.↗

NASA NTRS1991

On the estimation of climatological Z-R relationships

A statistical framework for climatological Z-R parameter estimation is developed and simulation experiments are conducted to examine sampling properties of the estimators. Both parametric and nonparametric models are considered. For parametric models, it is shown that Z-R parameters can be estimated by maximum likelihood, a procedure with optimal large sample properties. A general nonparametric framework for climatological Z-R estimation is also developed. Nonparametric procedures are attractive because of their flexibility in dealing with certain types of measurement errors common to radar data. Simulation experiments show that even under favorable assumptions on error characteristics of radar and raingages, large datasets are required to obtain accurate Z-R parameter estimates. Another important conclusion is that estimation results are generally quite sensitive to radar and raingage measurement thresholds. For fixed sample size, the simulation results can be used to provide quantitative assessments of the accuracy of Z-R model parameter estimates. These results are particularly useful for error analysis of precipitation products that are derived using climatological Z-R relations. One example is the large-area rainfall estimates derived using the height-area rainfall threshold (HART) technique.

Krajewski, Witold F.↗

NASA NTRS2002

Pathology effects at radiation doses below those causing increased mortality

Mortality data from experiments conducted at the Argonne National Laboratory (ANL) on the long-term effects of external whole-body irradiation on B6CF(1) mice were used to investigate radiation-induced effects at intermediate doses of (60)Co gamma rays or fission-spectrum neutrons either delivered as a single exposure or protracted over 60 once-weekly exposures. Kaplan-Meier analyses were used to identify the lowest dose in the ANL data (within radiation quality, pattern of exposure, and sex) at which radiation-induced mortality caused by primary tumors could be detected (approximately 1-2 Gy for gamma rays and 10-15 cGy for neutrons). Doses at and below these levels were then examined for radiation-induced shifts in the spectrum of pathology detected at death. To do this, specific pathology events were pooled into larger assemblages based on whether they were cancer, cardiovascular disease or non-neoplastic diseases detected within the lungs and pleura, liver and biliary tract, reproductive organs, or urinary tract. Cancer and cardiovascular disease were further subdivided into categories based on whether they caused death, contributed to death, or were simply observed at death. Counts of how often events falling within each of these combined pathology categories occurred within a mouse were then used as predictor variables in logistic regression to determine whether irradiated mice could be distinguished from control mice. Increased pathology burdens were detected in irradiated mice at doses lower than those causing detectable shifts in mortality-22 cGy for gamma rays and 2 cGy for neutrons. These findings suggest that (1) models based on mortality data alone may underestimate radiation effects, (2) radiation may have adverse health consequences (i.e. elevated health risks) even when mortality risks are not detected, and (3) radiation-induced pathologies other than cancer do occur, and they involve multiple organ systems.

Non-NASA Center↗

NASA NTRS1973

Two concepts for the reduction of payload attitude slewing times.

The concepts presented are particularly valuable in sounding rocket applications, where experiment data-gathering time above the atmosphere is measured in minutes per flight. One concept is a practical nonlinear control law for slewing a payload in one axis, with performance that approaches time-optimal as the uncertainty in angular acceleration approaches zero. The second concept is a practical transformation-of-coordinates system allowing slewing about an axis not coincident with any of the three control axes of the payload, so that the payload experiment axis may move along the great circle arc containing the initial and terminal target points. Implementation of both concepts is facilitated by the availability of variable-thrust cold-gas thrustors. Both concepts can result in significant reductions in slewing times compared with more conventional systems.

Riley, D. C.↗

DOE OSTI2022

Studying the Richtmyer–Meshkov instability in convergent geometry under high energy density conditions using the Decel platform

The “Decel” platform at Sandia National Laboratories investigates the Richtmyer–Meshkov instability (RMI) in converging geometry under high energy density conditions [Knapp et al., Phys. Plasmas 27, 092707 (2020)]. In Decel, the Z machine magnetically implodes a cylindrical beryllium liner filled with liquid deuterium, launching a converging shock toward an on-axis beryllium rod machined with sinusoidal perturbations. The passage of the shock deposits vorticity along the Be/D2 interface, causing the perturbations to grow. Here, we present platform improvements along with recent experimental results. To improve the stability of the imploding liner to the magneto Rayleigh–Taylor instability, we modified its acceleration history by shortening the Z electrical current pulse. Next, we introduce a “split rod” configuration that allows two axial modes to be fielded simultaneously in different axial locations along the rod, doubling our data per experiment. We then demonstrate that asymmetric slots in the return current structure modify the magnetic drive pressure on the surface of the liner, advancing the evolution on one side of the rod by multiple ns compared to its 180° counterpart. This effectively enables two snapshots of the instability at different stages of evolution per radiograph with small deviations of the cross-sectional profile of the rod from the circular. Using this platform, we acquired RMI data at 272 and 157 μm wavelengths during the single shock stage. Finally, we demonstrate the utility of these data for benchmarking simulations by comparing calculations using ALEGRA MHD and RageRunner.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Retrieving functional pathways of biomolecules from single-particle snapshots

Abstract A primary reason for the intense interest in structural biology is the fact that knowledge of structure can elucidate macromolecular functions in living organisms. Sustained effort has resulted in an impressive arsenal of tools for determining the static structures. But under physiological conditions, macromolecules undergo continuous conformational changes, a subset of which are functionally important. Techniques for capturing the continuous conformational changes underlying function are essential for further progress. Here, we present chemically-detailed conformational movies of biological function, extracted data-analytically from experimental single-particle cryo-electron microscopy (cryo-EM) snapshots of ryanodine receptor type 1 (RyR1), a calcium-activated calcium channel engaged in the binding of ligands. The functional motions differ substantially from those inferred from static structures in the nature of conformationally active structural domains, the sequence and extent of conformational motions, and the way allosteric signals are transduced within and between domains. Our approach highlights the importance of combining experiment, advanced data analysis, and molecular simulations.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1974

A new method for satellite orbit determination using an operational worldwide transponder network

The method utilizes computer programs developed for the forthcoming ATS-F/NIMBUS-F tracking and data relay experiment where the basic tracking measurements are multiple path round-trip propagation times and rates. This method of orbit computation has recently been successfully evaluated by tracking a geostationary satellite (ATS-3) using an existing VHF (150 MHz) network of automatic transponders. A master station sequentially interrogates each transponder via the ATS-3. The master site is located at Schenectady, N. Y. and four automatic transponders were located at Shannon, Reykajavik, Buenos Aires, and Seattle respectively. Data at hourly intervals were collected during a 24 hour period on April 18-19, 1973. After correcting this data for known systematic errors it was provided as input to an orbit determination program where all satellite motions during signal propagation are rigorously accounted for. The resulting estimated ATS-3 orbit yielded observational residuals on the order of 100 meters. By using more than one satellite the present scheme is further capable of accurately locating several stationary or mobile terminals as part of the overall orbital solution.

Lynn, J. J.↗

NASA NTRSDate not supplied

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

Enhancing CRTM All-Sky Simulations and Implementation of A New Active Sensor Module

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

CRTM Microwave Cloud Scattering Lookup Tables and Radar Simulator

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

Community Radiative Transfer Model: Implementing A New Cloud Scattering Database and Developing the Forward Radar Module

The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promises in calculating the scattering properties of particles with different shapes in the microwave frequencies. The goal of the research was to enhance the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. Given that such optical properties cannot be practically calculated on the fly, pre-computed look-up tables need to be implemented into the fast RT models to calculate the scattering properties of these particles using the DDA technique and the inputs provided by the users. Therefore, we implemented such pre-computed DDA databases into CRTM. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system will be used to evaluate the scattering improvements. Additionally, we used the backscattering information from the DDA database to implement a radar simulator into CRTM. The radar operators takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

NASA NTRSDate not supplied

Evaluation of TAO Observation System on ENSO Predictions from the GMAO S2S Forecast System

Since the early 1990’s, the Tropical Atmosphere Ocean (TAO) mooring array has been instrumental for observing Kelvin and Rossby wave propagation which is key for El Nino/Southern Oscillation (ENSO) prediction. However, recent funding and programmatical issues have highlighted the need to rigorously assess the impact of the TAO observing system on ENSO predictions. Therefore, we evaluate the TAO using data assimilation observation denial experiments (also known as Observing System Evaluation or OSE experiments). This presentation will evaluate the TAO observing impact on both reanalyses and prediction of the big 2015 El Nino. We have completed reanalyses for July 2014-Dec 2015 for both the CONTROL experiment (that assimilates all available data) and the NOTAO experiment (that is identical to the CONTROL but withholds all TAO observations) using the best available NASA GEOS-S2S V3 seasonal prediction system. Validation of these reanalyses shows that TAO assimilation generally improves comparisons of temperature and salinity versus gridded in situ observations. Temperature is universally improved above the thermocline near the equator, but the biggest improvement is found in the eastern Pacific, just below the thermocline, where the variation of the thermocline defines ENSO events. In addition, a surprising result is that even with relatively few observations, salinity is improved throughout the equatorial region except near 120oW near the surface. ENSO forecasts were performed that were initialized from these CONTROL and NOTAO reanalyses. For the 9-month forecasts which were initialized in January, July, and October 2015, the NINO3.4 SST shows that the CONTROL forecasts are warmer and closer to observations than the NOTAO forecasts. We will show that upwelling and shoaling of the mixed layer amplifies the ENSO signal due to TAO assimilation. Prior to (after) April 2015, this upwelling is caused by relatively stronger Rossby (Kelvin) waves in the CONTROL than in the NOTAO experiments.

E. Hackert↗

NASA NTRS2020

Improved Groundwater Table and L-Band Brightness Temperature Estimates for Northern Hemisphere Peatlands Using New Model Physics and SMOS Observations in a Global Data Assimilation Framework

There is an urgent need to include northern peatland hydrology in global Earth system models to better understand land-atmosphere interactions and sensitivities of peatland functions to climate change, and, ultimately, to improve climate change predictions. In this study, we introduced for the first time peatland-specific model physics into an assimilation scheme for L-band brightness temperature (Tb) data from the Soil Moisture Ocean Salinity (SMOS) mission to improve groundwater table estimates. We conducted two sets of model-only and data assimilation experiments using the Catchment Land Surface Model (CLSM), applying (over peatlands only) in one of them a peatland-specific adaptation (PEATCLSM). The evaluation against in-situ measurements of peatland groundwater table depth indicates the superiority of PEATCLSM model physics and additionally improved performance after assimilating SMOS Tb observations. The better performance of PEATCLSM over nearly all Northern Hemisphere peatlands is further supported by the better agreement between SMOS Tb observations and Tb estimates from the model-only and data assimilation runs. Within the data assimilation scheme, PEATCLSM reduces Tb observation-minus-forecast residuals and leads to reduced data assimilation updates of water storage components and, thus, reduced water budget imbalances in the assimilation system.

SMOS↗

DOE OSTI2024

Extracting halo independent information from dark matter electron scattering data

Direct detection experiments and the interpretation of their results are sensitive to the velocity structure of the dark matter in our galactic halo. Here we extend the formalism that deals with such astrophysics-driven uncertainties, originally introduced in the context of dark-matter-nuclear scattering, to include dark-matter-electron scattering interactions. Using mock data, we demonstrate that the ability to determine the correct dark matter mass and velocity distribution is depleted for recoil spectra which only populate a few low-lying bins, such as models involving a light mediator. We also demonstrate how this formalism allows one to test the compatibility of existing experimental data sets (e.g. SENSEI and EDELWEISS), as well as make predictions for possible future experiments (e.g. GaAs-based detectors).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1982

Operational performance of the photovoltaic-powered grain mill and water pump at Tangaye, Upper Volta

The first two years of operation of a stand alone photovoltaic (PV) power system for the village of Tangaye, Upper Volta in West Africa are described. The purpose of the experiment was to demonstrate that PV systems could provide reliable electrical power for multiple use applications in remote areas where local technical expertise is limited. The 1.8 kW (peak) power system supplies 120-V (d.c.) electrical power to operate a grain mill, a water pump, and mill building lights for the village. The system was initially sized to pump a part of the village water requirements from an existing improved well, and to meet a portion of the village grain grinding requirements. The data, observations, experiences, and conclusions developed during the first two years of operation are discussed. Reports of tests of the mills used in the project are included.

Martz, J. E.↗

NASA NTRS2006

The Scientific and Societal Need for Accurate Global Remote Sensing of Marine Suspended Sediments

Population pressure, commercial development, and climate change are expected to cause continuing alteration of the vital oceanic coastal zone environment. These pressures will influence both the geology and biology of the littoral, nearshore, and continental shelf regions. A pressing need for global observation of coastal change processes is an accurate remotely-sensed data product for marine suspended sediments. The concentration, delivery, transport, and deposition of sediments is strongly relevant to coastal primary production, inland and coastal hydrology, coastal erosion, and loss of fragile wetland and island habitats. Sediment transport and deposition is also related to anthropogenic activities including agriculture, fisheries, aquaculture, harbor and port commerce, and military operations. Because accurate estimation of marine suspended sediment concentrations requires advanced ocean optical analysis, a focused collaborative program of algorithm development and assessment is recommended, following the successful experience of data refinement for remotely-sensed global ocean chlorophyll concentrations.

Acker, James G.↗

NASA NTRS1992

The EGRET data products

We describe the Energetic Gamma Ray Experiment Telescope (EGRET) data products which we anticipate will suffice for virtually all guest and archival investigations. The production process, content, availability, format, and the associated software of each product is described. Supplied here is sufficient detail for each researcher to do analysis which is not supported by extant software.

Mattox, J. R.↗

DOE OSTI2024

Toward machine-learning-assisted PW-class high-repetition-rate experiments with solid targets

We present progress in utilizing a machine learning (ML) assisted optimization framework to study the trends in a parameter space defined by spectrally shaped, high-intensity, petawatt-class (8 J, 45 fs) laser pulses interacting with solid targets and give the first simulation-based overview of predicted trends. A neural network (NN) incorporating uncertainty quantification is trained to predict the number of hot electrons generated by the laser–target interaction as a function of pulse shaping parameters. The predictions of this NN serve as the basis function for a Bayesian optimization framework to navigate this space. For post-experimental evaluation, we compare two separate neural network (NN) models. One is based solely on data from experiments, and the other is trained only on ensemble particle-in-cell simulations. Reviewing the predicted and observed trends across the experiment-capable laser parameter search space, we find that both ML models predict a maximal increase in hot electron generation at a level of approximately 12%–18%; however, no statistically significant enhancement was observed in experiments. On direct comparison of the NN models, the average discrepancy is 8.5%, with a maximum of 30%. Since shot-to-shot fluctuations in experiments affect the observations, we evaluate the behavior of our optimization framework by performing virtual experiments that vary the number of repeated observations and the noise levels. Here, we discuss the implications of such a framework for future autonomous exploration platforms in high-repetition-rate experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗