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Results for “specific yield”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Determination of Scopolamine in Human Saliva Using Solid Phase Extraction and LC/MS/MS

Purpose: Scopolamine is the preferred treatment for motion sickness during space flight because of its quick onset of action, short half-life and favorable side-effect profile. The dose administered depends on the mode of administration and usually ranges between 0.1 and 0.8 mg. Such small doses make it difficult to detect concentrations of scopolamine in biological fluids by using conventional HPLC methods. To measure scopolamine in saliva and thereby to evaluate the pharmacokinetics of scopolamine, we developed an LC/MS/MS method using off-line solid phase extraction. Method: Samples (0.5mL) were loaded onto Waters Oasis HLB co-polymer cartridges (10 mg, 1 mL) and eluted with 0.5 mL methanol without evaporation and reconstitution. HPLC separation of the eluted sample was performed using an Agilent Zorbax SB-CN column (50 x 2.1 mm) at a flow rate of 0.2 mL/min for 4 minutes. The mobile phase for separation was 90:10 (v/v) methanol: ammonium acetate (2 mM) in water, pH 5.0 +/- 0.1. Concentrations of scopolamine were determined using a Micromass Quattro Micro(TM) mass spectrometer with electrospray ionization (ESI). ESI mass spectra were acquired in positive ion mode with multiple reaction monitoring for the determination of scopolamine m/z = 304.2 yields 138.1 and internal standard (IS) hyoscyamine m/z = 290.2 yields 124.1. Results: The method is rapid, reproducible, specific and has the following parameters: scopolamine and the IS are eluted at 1.7 and 3.2 min respectively. The linear range is 50-5000 pg/mL for scopolamine in saliva with correlation coefficients > 0.99 with a CV < 0.5 %. The intra-day and inter-day CVs are < 15 % for quality control samples with concentrations of 75, 300, 750 and 3000 pg/mL of scopolamine in human saliva. Conclusion: Solid phase extraction allows more rapid sample preparation and greater precision than liquid extraction. Furthermore, we increased the sensitivity and specificity by adjusting the LC mobile phase and using an MS/MS detector.

Wang, Zuwei↗
NASA NTRS1978

System-state and operating condition sensitive control method and apparatus for electric power delivery systems

This invention provides a method and apparatus for determining a precise switching sequence for the power switching elements of electric power delivery systems of the on-off switching type and which enables extremely fast transient response, precise regulation and highly stable operation. The control utilizes the values of the power delivery system power handling network components, a desired output characteristic, a system timing parameter, and the externally imposed operating conditions to determine where steady state operations should be in order to yield desired output characteristics for the given system specifications. The actual state of the power delivery system is continuously monitored and compared to a state-space boundary which is derived from the desired equilibrium condition, and from the information obtained from this comparison, the system is moved to the desired equilibrium condition in one cycle of switching control. Since the controller continuously monitors the power delivery system's externally imposed operating conditions, a change in the conditions is immediately sensed and a new equilibrium condition is determined and achieved, again in a single cycle of switching control.

Burns, III, William Wesley↗
NASA NTRS2012

A Model for Simulating the Response of Aluminum Honeycomb Structure to Transverse Loading

A 1-dimensional material model was developed for simulating the transverse (thickness-direction) loading and unloading response of aluminum honeycomb structure. The model was implemented as a user-defined material subroutine (UMAT) in the commercial finite element analysis code, ABAQUS(Registered TradeMark)/Standard. The UMAT has been applied to analyses for simulating quasi-static indentation tests on aluminum honeycomb-based sandwich plates. Comparison of analysis results with data from these experiments shows overall good agreement. Specifically, analyses of quasi-static indentation tests yielded accurate global specimen responses. Predicted residual indentation was also in reasonable agreement with measured values. Overall, this simple model does not involve a significant computational burden, which makes it more tractable to simulate other damage mechanisms in the same analysis.

Ratcliffe, James G.↗
NASA NTRS2017

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Ozone variables↗
NASA NTRS2011

Ground-Laboratory to In-Space Atomic Oxygen Correlation for the Polymer Erosion and Contamination Experiment (PEACE) Polymers

The Materials International Space Station Experiment 2 (MISSE 2) Polymer Erosion and Contamination Experiment (PEACE) polymers were exposed to the environment of low Earth orbit (LEO) for 3.95 years from 2001 to 2005. There were 41 different PEACE polymers, which were flown on the exterior of the International Space Station (ISS) in order to determine their atomic oxygen erosion yields. In LEO, atomic oxygen is an environmental durability threat, particularly for long duration mission exposures. Although spaceflight experiments, such as the MISSE 2 PEACE experiment, are ideal for determining LEO environmental durability of spacecraft materials, ground-laboratory testing is often relied upon for durability evaluation and prediction. Unfortunately, significant differences exist between LEO atomic oxygen exposure and atomic oxygen exposure in ground-laboratory facilities. These differences include variations in species, energies, thermal exposures and radiation exposures, all of which may result in different reactions and erosion rates. In an effort to improve the accuracy of ground-based durability testing, ground-laboratory to in-space atomic oxygen correlation experiments have been conducted. In these tests, the atomic oxygen erosion yields of the PEACE polymers were determined relative to Kapton H using a radio-frequency (RF) plasma asher (operated on air). The asher erosion yields were compared to the MISSE 2 PEACE erosion yields to determine the correlation between erosion rates in the two environments. This paper provides a summary of the MISSE 2 PEACE experiment; it reviews the specific polymers tested as well as the techniques used to determine erosion yield in the asher, and it provides a correlation between the space and ground laboratory erosion yield values. Using the PEACE polymers asher to in-space erosion yield ratios will allow more accurate in-space materials performance predictions to be made based on plasma asher durability evaluation.

Stambler, Arielle H.↗
NASA NTRS1977

Impurity concentrations and surface charge densities on the heavily doped face of a silicon solar cell

Increased solar cell efficiencies are attained by reduction of surface recombination and variation of impurity concentration profiles at the n(+) surface of silicon solar cells. Diagnostic techniques are employed to evaluate the effects of specific materials preparation methodologies on surface and near surface concentrations. It is demonstrated that the MOS C-V method, when combined with a bulk measurement technique, yields more complete concentration data than are obtainable by either method alone. Specifically, new solar cell MOS C-V measurements are combined with bulk concentrations obtained by a successive layer removal technique utilizing measurements of sheet resistivity and Hall coefficient.

Weinberg, I.↗
NASA NTRS1972

Electrothermal hydrazine thruster development.

Results of testing of several electrically-heated, thermal-decomposition hydrazine thrustors in the 5- to 70-mlb thrust range. Propellant supply pressures are compatible with those typical of larger catalytic thrustors. With a 5-W power input, pulsed specific impulse varies from about 165 to 215 sec, depending on duty cycle. The thrustors yield highly reproducible 1-mlb-sec impulse bits with 50-msec command pulse widths. The steady-state specific impulse exceeds 230 sec for thrust levels above 10 mlb.

Murch, C. K.↗
NASA NTRSDate not supplied

Use of Design of Experiments and Rule-Based Inference in Determining Neural Network Architectures for Loss of Control Detection

In this work, we describe methods for selecting the neural network architectures and input spaces to implement belief state inference on generic commercial transport aircraft. First, we highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). We present a structured method that can be used in a number of aerospace applications, to optimize the structure and training parameters of the CVAE for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from a NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications. While theoretically, we could create a single CVAE with an input space the size of all measurable flight variables and environmental dynamics, it becomes intractable to use such a neural network in an in-situ intelligent multi-agent system. Using the recommendations from our case study, we introduce a technical approach for feasibly describing the belief space by (1) identifying significant statistical relationships among flight variables using rule induction, (2) using a set of rules that cover all features to define the input space of multiple CVAEs, and (3) forming a belief space based on the joint probability density of their collective latent spaces. This results in a series of relatively small matrix multiplications that can be performed in real time, as opposed to large matrix computations in a single CVAE. We demonstrate the application of this approach on the T-2 flight loss-of control experiments, using the architecture and hyperparameter recommendations from the case study. We compare the utilities of an individual CVAE trained on all flight variables and multiple CVAEs defined on subsets of flight variables for detecting qualitative changes in flight. We demonstrate that the use of multiple CVAEs with smaller input spaces permits the CVAE to capture more granular relationships in the latent space, permitting better state space characterization and loss-of-control detection.

Design of experiments↗
NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

Loss of Control↗
NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T 2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

Loss of Control↗
NASA NTRSDate not supplied

Use of Design of Experiments in Determining Neural Network Architectures for Loss of Control Detection

Abstract—We describe empirical methods for selecting a neural network architecture to implement belief state inference on generic commercial transport aircraft. We highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). Our main contribution is the application of a structured method that can be used for machine learning in many aerospace applications. This method optimizes the structure and training parameters of a neural network for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE analysis was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from the NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications.

neural networks↗
NASA NTRS2000

Photochemical Phenomenology Model for the New Millenium

This project tackles the problem of conversion of validated a priori physics-based modeling capabilities, specifically those relevant to the analysis and interpretation of planetary atmosphere observations, to application-oriented software for use in science and science-support activities. The software package under development, named the Photochemical Phenomenology Modeling Tool (PPMT), has particular focus on the atmospheric remote sensing data to be acquired by the CIRS instrument during the CASSINI Jupiter flyby and orbital tour of the Saturnian system. Overall, the project has followed the development outline given in the original proposal, and the Year 1 design and architecture goals have been met. Specific accomplishments and the difficulties encountered are summarized in this report. Most of the effort has gone into complete definition of the PPMT interfaces within the context of today's IT arena: adoption and adherence to the CORBA Component Model (CCM) has yielded a solid architecture basis, and CORBA-related issues (services, specification options, development plans, etc.) have been largely resolved. Implementation goals have been redirected somewhat so as to be more relevant to the upcoming CASSINI flyby of Jupiter, with focus now being more on data analysis and remote sensing retrieval applications.

Bishop, James↗
NASA NTRS2015

Development and Characterization of a Rate-Dependent Three-Dimensional Macroscopic Plasticity Model Suitable for Use in Composite Impact Problems

Several key capabilities have been identified by the aerospace community as lacking in the material/models for composite materials currently available within commercial transient dynamic finite element codes such as LS-DYNA. Some of the specific desired features that have been identified include the incorporation of both plasticity and damage within the material model, the capability of using the material model to analyze the response of both three-dimensional solid elements and two dimensional shell elements, and the ability to simulate the response of composites composed with a variety of composite architectures, including laminates, weaves and braids. In addition, a need has been expressed to have a material model that utilizes tabulated experimentally based input to define the evolution of plasticity and damage as opposed to utilizing discrete input parameters (such as modulus and strength) and analytical functions based on curve fitting. To begin to address these needs, an orthotropic macroscopic plasticity based model suitable for implementation within LS-DYNA has been developed. Specifically, the Tsai-Wu composite failure model has been generalized and extended to a strain-hardening based orthotropic plasticity model with a non-associative flow rule. The coefficients in the yield function are determined based on tabulated stress-strain curves in the various normal and shear directions, along with selected off-axis curves. Incorporating rate dependence into the yield function is achieved by using a series of tabluated input curves, each at a different constant strain rate. The non-associative flow-rule is used to compute the evolution of the effective plastic strain. Systematic procedures have been developed to determine the values of the various coefficients in the yield function and the flow rule based on the tabulated input data. An algorithm based on the radial return method has been developed to facilitate the numerical implementation of the material model. The presented paper will present in detail the development of the orthotropic plasticity model and the procedures used to obtain the required material parameters. Methods in which a combination of actual testing and selective numerical testing can be combined to yield the appropriate input data for the model will be described. A specific laminated polymer matrix composite will be examined to demonstrate the application of the model.

Impact↗
NASA NTRSDate not supplied

Regional and Model-Specific Response Types in A Global Gridded Crop Model Ensemble

Crop models are often employed to project crop yields under changing conditions such as global warming and associated management change for adaptation. Multi-model ensembles are promoted to enhance the robustness of projections, but questions remain on what causes often large differences between projections of individual models. Global Gridded Crop Models (GGCMs) are especially exposed to this question when applied for assessing climate change impacts, adaptation, environmental impacts of agricultural production, because their results are used in downstream analyses, such as in integrated assessment or economic modeling for projecting future land-use change. Even though global gridded crop models are often based on detailed field-scale models or have implemented similar modeling principles in other ecosystem models, global-scale models are subject to substantial uncertainties from both model structure and parametrization as well as from calibration and input data quality. AgMIP’s Global Gridded Crop Model Intercomparison (GGCMI) has thus set out to intercompare GGCMs in order to evaluate model performance, describe model uncertainties, identify inconsistencies within the ensemble and underlying reasons, and to ultimately improve models and modeling capacities. In phase 2 of the GGCMI activities, 12 modeling groups followed a modeling protocol that asked for up to 1404 31-year global simulations at 0.5 arc-degree spatial resolution to assess models’ sensitivities to changes in carbon dioxide (C; 4 different levels) temperature (T; 7 different offset levels), water supply (W; 9 levels), and nitrogen (N; 3 levels), the so-called CTWN experiment (Franke et al. 2020; http://dx.doi.org/10.5194/gmd-13-2315-2020). We here present analyses of model response types using impact response surfaces along the C, T, W, and N dimensions, respectively and collectively. Doing so, we can understand differences in simulated responses per driver rather than aggregated changes in yields. We find that models’ sensitivities to the individual driver dimensions are substantially different and often more different across models than across regions. A cluster analysis finds regional and model-specific patterns. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response type clusters across models suggests that models need to undergo further scrutiny. We suggest establishing standards in model process evaluation not only against historical dynamics but also against dedicated experiments across the CTWN dimensions.

crop models↗
NASA NTRS1974

Investigation of the ionospheric Faraday rotation for use in orbit corrections

The possibility of mapping the Faraday factors on a worldwide basis was examined as a simple method of representing the conversion factors for any possible user. However, this does not seem feasible. The complex relationship between the true magnetic coordinates and the geographic latitude, longitude, and azimuth angles eliminates the possibility of setting up some simple tables that would yield worldwide results of sufficient accuracy. Tabular results for specific stations can easily be produced or could be represented in graphic form.

Llewellyn, S. K.↗
NASA NTRS1977

General purpose film plotting system

The general purpose film plotting system which is a plot program design to handle a majority of the data tape formats presently available under OS/360 was discussed. The convenience of this program is due to the fact that the user merely describes the format of his data set and the type of data plots he desires. It processes the input data according to the given specifications. The output is generated on a tape which yields data plots when processed by the selected plotter. A summary of each job is produced on the printer.

Mcquillan, C.↗
NASA NTRS1985

Reassignment of the Iron (3) Absorption Bands in the Spectra of Mars

Absorption features in the near-infrared and visible region reflectance spectra of Mars have been assigned to specific Fe (3+) crystal-field and o(2-) yields Fe(3+) charge transfer transitions. Recently, near-ultraviolet absorption spectra of iron oxides were obtained and the energies of o(2-) yields Fe(3+) charge-transfer (LMCT) transitions were determined from accurate SCF-X # alpha-SW molecular orbital calculations on (FeO6)(9-) and (FeO4)(5-) clusters. Both the theoretical and experimental results, together with existing data in the literature, show that some of the previous Fe(3+) band assignments in the spectra of Mars need to be revised. The theory of Fe(3+) spectra in minerals is discussed and applied to the spectrum of Mars.

Sherman, D. M.↗