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NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-response Curves

NASA will soon be collecting noise-annoyance community survey data as the X-59 aircraft flies supersonically over several communities in the USA. Sparse measurements of the X-59 sonic thumps will be used together with physics-based simulations to estimate noise doses at survey participant locations. These dose estimates have associated error that affects the accuracy of modeled dose-response curves, which can result in misestimation of annoyance. The precision in dose-response curves is also a consideration in selecting the number of survey participants. To enable pretest studies of dose error and precision, simulated dose-response data were generated based on NASA’s Quiet Supersonic Flights 2018 test. The data included various degrees of dose error and sample size. Frequentist multilevel logistic regression models were fit to the true and perturbed dose-response data. Simple proportional relationships were identified between the model parameters and the perturbation standard deviation. The summary dose-response curves illustrate the impact on accuracy if dose error is not accounted for in the model. The precision in the dose-response curves is also shown as the number of participants and degree of participation is varied. Finally, sampling variability is illustrated by showing the dose-response curves for several replicates with random draws of participants and errors.

X-59↗

NASA NTRSDate not supplied

Effects of Dose Error and Sample Size on Sonic Boom Dose-Response Curves

X-59↗

NASA NTRS1980

Microwave radiometric determination of oceanographic and meteorological parameters

The thermal microwave brightness from the atmosphere over an ocean in the range 5-40 GHz is influenced primarily by the distribution of vapor and liquid water in the atmosphere and the temperature and wind speed at the sea surface. The Scanning Multichannel Microwave Radiometer (SMMR), which was carried aboard both the Nimbus-7 and Seasat satellites (both launched in 1978), measures this radiation at five frequencies to find these four parameters. A retrieval algorithm has been developed which, on simulated data, yields accuracies of 1.5 C in sea surface temperature, 0.9 m/s in wind speed, 4 mg/ sq cm of cloud liquid water content and 0.14gm/sq cm of precipitable water vapor. Results from the Seasat SMMR, while both preliminary and sparse, are consistent with these simulations.

Wilheit, T. T.↗

NASA NTRS1991

Statistical analysis of power-size-redshift distributions of extragalactic jets

This paper investigates whether a hot, sparse, yet cosmologically significant intergalactic medium is consistent with data collected from extragalactic radio sources. This is done by use of Monte Carlo simulations which employ previously run pseudohydrodynamical simulations to cover an observational parameter space. These observational parameters include the scale height, central density, and temperature of a (isothermal) galactic halo, and the power of the central engine which drives the jet. The Monte Carlo simulations generate distribution of sizes in bins of (received) power and redshift, which have been compared with observational data using Kolmogorov-Smirnov tests. Results of this analysis are consistent with the existence of an IGM with temperature and density mentioned above. In addition, this analysis suggests that the active lifetime of powerful extragalactic radio sources decreases with increasing power.

Rosen, Alexander↗

NASA NTRS2013

An Indirect System Identification Technique for Stable Estimation of Continuous-Time Parameters of the Vestibulo-Ocular Reflex (VOR)

The vestibulo-ocular reflex (VOR) is a well-known dual mode bifurcating system that consists of slow and fast modes associated with nystagmus and saccade, respectively. Estimation of continuous-time parameters of nystagmus and saccade models are known to be sensitive to estimation methodology, noise and sampling rate. The stable and accurate estimation of these parameters are critical for accurate disease modelling, clinical diagnosis, robotic control strategies, mission planning for space exploration and pilot safety, etc. This paper presents a novel indirect system identification method for the estimation of continuous-time parameters of VOR employing standardised least-squares with dual sampling rates in a sparse structure. This approach permits the stable and simultaneous estimation of both nystagmus and saccade data. The efficacy of this approach is demonstrated via simulation of a continuous-time model of VOR with typical parameters found in clinical studies and in the presence of output additive noise.

Kukreja, Sunil L.↗

NASA NTRS2017

An RFI Detection Algorithm for Microwave Radiometers Using Sparse Component Analysis

Radio Frequency Interference (RFI) is a threat to passive microwave measurements and if undetected, can corrupt science retrievals. The sparse component analysis (SCA) for blind source separation has been investigated to detect RFI in microwave radiometer data. Various techniques using SCA have been simulated to determine detection performance with continuous wave (CW) RFI.

radiometers↗

NASA NTRS2017

An RFI Detection Algorithm for Microwave Radiometers Using Sparse Component Analysis

radiometers↗

NASA NTRS2013

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Cheung, Kar-Ming↗

NASA NTRS2021

Large-scale features of Last Interglacial climate: results from evaluating the lig127k simulations for the Coupled Model Intercomparison Project (CMIP6)–Paleoclimate Modeling Intercomparison Project (PMIP4)

The modeling of paleoclimate, using physically based tools, is increasingly seen as a strong out-of-sample test of the models that are used for the projection of future climate changes. New to the Coupled Model Intercomparison Project (CMIP6) is the Tier 1 Last Interglacial experiment for 127 000 years ago (lig127k), designed to address the climate responses to stronger orbital forcing than the midHolocene experiment, using the same state-of-the-art models as for the future and following a common experimental protocol. Here we present a first analysis of a multi-model ensemble of 17 climate models, all of which have completed the CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) experiments. The equilibrium climate sensitivity (ECS) of these models varies from 1.8 to 5.6°C. The seasonal character of the insolation anomalies results in strong summer warming over the Northern Hemisphere continents in the lig127k ensemble as compared to the CMIP6 piControl and much-reduced minimum sea ice in the Arctic. The multi-model results indicate enhanced summer monsoonal precipitation in the Northern Hemisphere and reductions in the Southern Hemisphere. These responses are greater in the lig127k than the CMIP6 midHolocene simulations as expected from the larger insolation anomalies at 127 than 6 ka. New synthesis for surface temperature and precipitation, targeted for 127 ka, have been developed for comparison to the multi-model ensemble. The lig127k model ensemble and data reconstructions are in good agreement for summer temperature anomalies over Canada, Scandinavia, and the North Atlantic and for precipitation over the Northern Hemisphere continents. The model–data comparisons and mismatches point to further study of the sensitivity of the simulations to uncertainties in the boundary conditions and of the uncertainties and sparse coverage in current proxy reconstructions. The CMIP6–Paleoclimate Modeling Intercomparison Project (PMIP4) lig127k simulations, in combination with the proxy record, improve our confidence in future projections of monsoons, surface temperature, and Arctic sea ice, thus providing a key target for model evaluation and optimization.

Last Interglacial climate↗

NASA NTRS2008

Testing of Error-Correcting Sparse Permutation Channel Codes

A computer program performs Monte Carlo direct numerical simulations for testing sparse permutation channel codes, which offer strong error-correction capabilities at high code rates and are considered especially suitable for storage of digital data in holographic and volume memories. A word in a code of this type is characterized by, among other things, a sparseness parameter (M) and a fixed number (K) of 1 or "on" bits in a channel block length of N.

Shcheglov, Kirill, V.↗

NASA NTRS2000

An Assessment of Our Ability to Model the Upper Troposphere and Lower Stratosphere in Interactive Climate Models

The physics of the upper troposphere is dominated by the different phases of water, while the lower stratosphere is governed by the presence of ozone. The tropopause may be regarded as the layer which separates the regions where stratospheric and tropospheric processes dominate the physics, but it is clearly not a smooth transition level. Modelling this region in comprehensive climate models is complicated, partly because of the constraints inherent in numerical methods (such as the finite resolution used in models) and partly because of our incomplete knowledge of the physical and chemical interactions which occur (such as the phase transitions of water and the composition of aerosols). However, studies of stratospheric impacts on climate change clearly require the tropopause region to be modelled with a high degree of accuracy. This paper will examine how well we can currently model the structure and dynamics of the tropopause region; this includes some comparisons of the simulated atmospheric composition with observational estimates of these species, some studies of discrepancies between forecasts and observations in the Data Assimilation System of the Data Assimilation office, and inferences for sparsely observed quantities. The analysis will focus on meteorological quantities, physical forcing mechanisms, and the transport and interactions of trace species.

Pawson, Steven↗

NASA NTRS1997

Rhenium Rocket Manufacturing Technology

The NASA Lewis Research Center's On-Board Propulsion Branch has a research and technology program to develop high-temperature (2200 C), iridium-coated rhenium rocket chamber materials for radiation-cooled rockets in satellite propulsion systems. Although successful material demonstrations have gained much industry interest, acceptance of the technology has been hindered by a lack of demonstrated joining technologies and a sparse materials property data base. To alleviate these concerns, we fabricated rhenium to C-103 alloy joints by three methods: explosive bonding, diffusion bonding, and brazing. The joints were tested by simulating their incorporation into a structure by welding and by simulating high-temperature operation. Test results show that the shear strength of the joints degrades with welding and elevated temperature operation but that it is adequate for the application. Rhenium is known to form brittle intermetallics with a number of elements, and this phenomena is suspected to cause the strength degradation. Further bonding tests with a tantalum diffusion barrier between the rhenium and C-103 is planned to prevent the formation of brittle intermetallics.

Source record↗

NASA NTRS2002

Prediction of Aerodynamic Coefficient using Genetic Algorithm Optimized Neural Network for Sparse Data

Wind tunnels use scale models to characterize aerodynamic coefficients, Wind tunnel testing can be slow and costly due to high personnel overhead and intensive power utilization. Although manual curve fitting can be done, it is highly efficient to use a neural network to define the complex relationship between variables. Numerical simulation of complex vehicles on the wide range of conditions required for flight simulation requires static and dynamic data. Static data at low Mach numbers and angles of attack may be obtained with simpler Euler codes. Static data of stalled vehicles where zones of flow separation are usually present at higher angles of attack require Navier-Stokes simulations which are costly due to the large processing time required to attain convergence. Preliminary dynamic data may be obtained with simpler methods based on correlations and vortex methods; however, accurate prediction of the dynamic coefficients requires complex and costly numerical simulations. A reliable and fast method of predicting complex aerodynamic coefficients for flight simulation I'S presented using a neural network. The training data for the neural network are derived from numerical simulations and wind-tunnel experiments. The aerodynamic coefficients are modeled as functions of the flow characteristics and the control surfaces of the vehicle. The basic coefficients of lift, drag and pitching moment are expressed as functions of angles of attack and Mach number. The modeled and training aerodynamic coefficients show good agreement. This method shows excellent potential for rapid development of aerodynamic models for flight simulation. Genetic Algorithms (GA) are used to optimize a previously built Artificial Neural Network (ANN) that reliably predicts aerodynamic coefficients. Results indicate that the GA provided an efficient method of optimizing the ANN model to predict aerodynamic coefficients. The reliability of the ANN using the GA includes prediction of aerodynamic coefficients to an accuracy of 110% . In our problem, we would like to get an optimized neural network architecture and minimum data set. This has been accomplished within 500 training cycles of a neural network. After removing training pairs (outliers), the GA has produced much better results. The neural network constructed is a feed forward neural network with a back propagation learning mechanism. The main goal has been to free the network design process from constraints of human biases, and to discover better forms of neural network architectures. The automation of the network architecture search by genetic algorithms seems to have been the best way to achieve this goal.

Rajkumar, T.↗

NASA NTRS1993

Determination of solid/porous wall boundary conditions from wind tunnel data for computational fluid dynamics codes

A computational and experimental study has been undertaken to investigate methods of modeling solid and porous wall boundary conditions in CFD codes. The procedure utilizes experimental measurements at the walls to develop a flow field solution based on the method of singularities. This flow field solution is then imposed as a boundary condition in a CFD simulation of the internal flow field. The effectiveness of this method in describing the boundary conditions at the wind tunnel walls using only sparse experimental measurements has been investigated. Verification of the approach using computational studies has been carried out using an incompressible flow solver. The current work demonstrates this technique for low speed flows and compares the result with experimental data obtained from a heavily instrumented variable porosity test section. Position and refinement of experimental measurements required to describe porous wall boundary conditions has also been considered for application to other porous wall wind tunnels.

Beutner, Thomas J.↗

NASA NTRS1998

A New Approach to Overcoming Spatial Aliasing in Structural Damage Detection

Aircraft, reusable launch vehicles,unmanned aircraft, and other advanced structures are being built using lightweight composite materials/metals with design safety factors as low as 1.25. These advanced structures operate in uncertain and severe environments and are susceptible to damage such as delamination, fiber/matrix damage, hydrothermal strain in composite materials, and fatigue and cracking in metals. To ensure human safety and load-bearing integrity these structures must be inspected to detect and locate often invisible damage and faults before they become catastrophic. Conventional methods of non-destructive evaluation sometimes miss significant damage and are time consuming and expensive to perform. In contrast, vibrometry or vibration signature techniques are a global method of structural integrity monitoring that potentially can efficiently detect damage on large structures, including damage that is away from sensor locations, and in the interior of structures. However, a barrier problem in damage detection using vibration measurements is the need to measure the vibration response at a large number of points on the structure. Typically, model reduction or expansion procedures such as Guyan reduction or dynamic expansion are attempted to overcome the problem of insufficient measurements or spatial aliasing. These approaches depend on using information from the healthy model, and thus put error into the reduction used to represent the damaged structure. In this paper, a Frequency Response Function technique is used to detect damage to a fixed-free beam. The technique uses measured frequency response functions from the healthy structure as reference data, and then monitors vibration measurements during the life of the structure to detect damage. In an analytical simulation using a finite-element model of a beam, damage was located using only sparse measurements because the technique uses both rotation and translation measurements from the damaged structure.

Schulz, Mark J.↗

NASA NTRS1994

Determination of solid/porous wall boundary conditions from wind tunnel data for computational fluid dynamics codes

A computational and experimental study has been undertaken to investigate methods of modelling solid and porous wall boundary conditions in computational fluid dynamics (CFD) codes. The procedure utilizes experimental measurements at the walls to develop a flow field solution based on the method of singularities. This flow field solution is then imposed as a pressure boundary condition in a CFD simulation of the internal flow field. The effectiveness of this method in describing the boundary conditions at the wind tunnel walls using only sparse experimental measurements has been investigated. Verification of the approach using computational studies has been carried out using an incompressible flow solver. The current work demonstrates this technique for low speed flows and compares the result with experimental data obtained from a heavily instrumented variable porosity test section. Position and refinement of experimental measurements required to describe porous wall boundary conditions have also been considered for application to other porous wall wind tunnels. The approach developed is simple, computationally inexpensive, and does not require extensive or intrusive measurements. It may be applied to both solid and porous wall wind tunnel tests. Some consideration is given to the extension of this method to three dimensions.

Beutner, Thomas J.↗

NASA NTRS2013

Stellar Laboratories: New GeV and Ge VI Oscillator Strengths and their Validation in the Hot White Dwarf RE0503-289

State-of-the-art spectral analysis of hot stars by means of non-LTE model-atmosphere techniques has arrived at a high level of sophistication. The analysis of high-resolution and high-S/N spectra, however, is strongly restricted by the lack of reliable atomic data for highly ionized species from intermediate-mass metals to trans-iron elements. Especially data for the latter has only been sparsely calculated. Many of their lines are identified in spectra of extremely hot, hydrogen-deficient post-AGB stars. A reliable determination of their abundances establishes crucial constraints for AGB nucleosynthesis simulations and, thus, for stellar evolutionary theory. Aims. In a previous analysis of the UV spectrum of RE 0503-289, spectral lines of highly ionized Ga, Ge, As, Se, Kr, Mo, Sn, Te, I, and Xe were identified. Individual abundance determinations are hampered by the lack of reliable oscillator strengths. Most of these identified lines stem from Ge V. In addition, we identified Ge VI lines for the first time. We calculated Ge V and Ge VI oscillator strengths in order to reproduce the observed spectrum. Methods. We newly calculated Ge V and Ge VI oscillator strengths to consider their radiative and collisional bound-bound transitions in detail in our non-LTE stellar-atmosphere models for the analysis of the Ge IV-VI spectrum exhibited in high-resolution and high-S/N FUV (FUSE) and UV (ORFEUS/BEFS, IUE) observations of RE 0503-289. Results. In the UV spectrum of RE 0503-289, we identify four Ge IV, 37 Ge V, and seven Ge VI lines. Most of these lines are identified for the first time in any star. We can reproduce almost all Ge IV, GeV, and Ge VI lines in the observed spectrum of RE 0503-289 (T(sub eff) = 70 kK, log g = 7.5) at log Ge = -3.8 +/- 0.3 (mass fraction, about 650 times solar). The Ge IV/V/VI ionization equilibrium, that is a very sensitive T(sub eff) indicator, is reproduced well. Conclusions. Reliable measurements and calculations of atomic data are a prerequisite for stellar-atmosphere modeling. Our oscillator-strength calculations have allowed, for the first time, Ge V and Ge VI lines to be successfully reproduced in a white dwarf s (RE 0503-289) spectrum and to determine its photospheric Ge abundance.

Rauch, T.↗

NASA NTRS1980

First Scientific Working Group Meeting of Airborne Doppler Lidar Wind Velocity Measurement Program, appendix C

The problem is to operate on two scalar fields to produce a vector field, to produce user products from the vector field, and to establish reliability of results. Data problems encountered include sparse measurements, irregular distribution, varying quality, imperfect orthogonality, aliasing due to sampling volume, and measurements not simultaneous. Desired algorithm characteristics, solution elements, and characteristics of the model are listed. The seven simulation elements, eight algorithm steps and the required user inputs are given.

Lee, R. W.↗