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At least 1,423 records · Page 79

Improved Regression Analysis of Temperature-Dependent Strain-Gage Balance Calibration Data

An improved approach is discussed that may be used to directly include first and second order temperature effects in the load prediction algorithm of a wind tunnel strain-gage balance. The improved approach was designed for the Iterative Method that fits strain-gage outputs as a function of calibration loads and uses a load iteration scheme during the wind tunnel test to predict loads from measured gage outputs. The improved approach assumes that the strain-gage balance is at a constant uniform temperature when it is calibrated and used. First, the method introduces a new independent variable for the regression analysis of the balance calibration data. The new variable is designed as the difference between the uniform temperature of the balance and a global reference temperature. This reference temperature should be the primary calibration temperature of the balance so that, if needed, a tare load iteration can be performed. Then, two temperature{dependent terms are included in the regression models of the gage outputs. They are the temperature difference itself and the square of the temperature difference. Simulated temperature{dependent data obtained from Triumph Aerospace's 2013 calibration of NASA's ARC-30K five component semi{span balance is used to illustrate the application of the improved approach.

wind tunnel testing↗

Measuring and Modeling Shared Visual Attention

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval.We present two methods for comparing sequences of this sort, one based on computing the time varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions.We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of activities, each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. Using these criteria, we have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Gontar Hoermann, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Mulligan, Jeffrey B.↗

Conducting the NASP ground test program

The National Aero-Space Plane (NASP) program has recently entered a new phase of the program known as Phase 2D. During this period, five aerospace companies and the Government have formed a National Team. This team has focused on developing a single experimental (X-30) vehicle design and are pursuing a technology validation and demonstration program to prove out the design concepts and design tools. This paper presents an overview of the Phase 2D round testing being conducted to validate the X-30 design and to demonstrate the critical technologies needed to build and fly a research vehicle during Phase 3 of the program. The Phase 2D exit criteria are discussed to identify how they provide top-level guidance for developing the ground test program. An overview of major test facility modifications being performed in support of the test program is also presented. Emphasis is placed on propulsion and structures testing since these are felt to be the primary areas requiring technologies beyond the current state-of-the-art. Also discussed is the use of uncertainty analysis as a method to account for uncertainties in test data. In addition, this paper addresses the use of these uncertainties to develop qualitative indicators of how well the design and technology developed during Phase 2 have matured.

Airframes↗

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), has typically limited machine learning (ML) in space studies and further study of radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNAseq) data from 6 mouse liver GeneLab datasets (GLDS) with a total of 113 spaceflight and ground-control samples to determine top features relevant to spaceflight including the effect of radiation exposure. Data was normalized within each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. The top MRMR features were used to predict spaceflight vs. ground-control samples using a Random Forest (RF) classifier with 5-fold cross validation (CV). The ML-based gene sets were further compared against differential gene expression results from individual GLDS. CV training using the top 100 MRMR genes show averages of 86% accuracy and 0.95 AUC value on the validation set over 5 folds (Figure 1A). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 811 or 68 DEGs overlapping between at least 2 or 3 studies, respectively (Figure 1B). Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism. Set analysis between the MRMR features and the DEGs showed 60 or 8 genes overlapping with at least 1 or 2 studies, respectively. MRMR feature selection and ensemble ML methods (e.g. RF) improve performance relative to a Naïve Bayes classifier when NGS data sets are analyzed. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise ratio. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from RNASeq analysis. Non-intersecting sets introduce opportunity to explore spaceflight relevant genes and implementing ML methods across existing NGS datasets may overcome sample size limitations. ML coupled with existing analytical methods enhances understanding of disease by revealing common underlying pathways across datasets.

Machine Learning↗

Local Lunar Gravity Field Analysis over the South Pole-aitken Basin from SELENE Farside Tracking Data

We present a method with which we determined the local lunar gravity field model over the South Pole-Aitken (SPA) basin on the farside of the Moon by estimating adjustments to a global lunar gravity field model using SELENE tracking data. Our adjustments are expressed in localized functions concentrated over the SPA region in a spherical cap with a radius of 45deg centered at (191.1 deg E, 53.2 deg S), and the resolution is equivalent to a 150th degree and order spherical harmonics expansion. The new solution over SPA was used in several applications of geophysical analysis. It shows an increased correlation with high-resolution lunar topography in the frequency band l = 40-70, and admittance values are slightly different and more leveled when compared to other, global gravity field models using the same data. The adjustments expressed in free-air anomalies and differences in Bouguer anomalies between the local solution and the a priori global solution correlate with topographic surface features. The Moho structure beneath the SPA basin is slightly modified in our solution, most notably at the southern rim of the Apollo basin and around the Zeeman crater

Lunar Gravity↗

Research analysis of Space Shuttle Orbiter entry aerothermodynamic flight data at the NASA Langley Research Center

The methods used to analyze the aerothermodynamic data gathered from the Shuttle protoflights are reviewed. Trajectory and atmospheric reconstruction allow an accurate definition of the freestream environment through which the Shuttle has flown. The reconstructions, combined with aerodynamic coefficient and convective heating rate determinations, provide predictive capability for comparison with future flights. Data are acquired by operational instrumentation (12,000 parameters), development flight instrumentation (4500 measurements), and Orbiter experiments instrumentation; tracking and meteorological data are also included in the analyses. The aerothermodynamic and aerodynamic technology base for large, winged, lifting body entry vehicles is being expanded by the analysis efforts. Sensor locations on the Shuttle and data management techniques are described.

Throckmorton, D. A.↗

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton–proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13 TeV. Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20 pb –1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An investigation of error characteristics and coding performance

The first year's effort on NASA Grant NAG5-2006 was an investigation to characterize typical errors resulting from the EOS dorn link. The analysis methods developed for this effort were used on test data from a March 1992 White Sands Terminal Test. The effectiveness of a concatenated coding scheme of a Reed Solomon outer code and a convolutional inner code versus a Reed Solomon only code scheme has been investigated as well as the effectiveness of a Periodic Convolutional Interleaver in dispersing errors of certain types. The work effort consisted of development of software that allows simulation studies with the appropriate coding schemes plus either simulated data with errors or actual data with errors. The software program is entitled Communication Link Error Analysis (CLEAN) and models downlink errors, forward error correcting schemes, and interleavers.

Ebel, William J.↗

Transonic propulsion system integration analysis at McDonnell Aircraft Company

The technology of Computational Fluid Dynamics (CFD) is becoming an important tool in the development of aircraft propulsion systems. Two of the most valuable features of CFD are: (1) quick acquisition of flow field data; and (2) complete description of flow fields, allowing detailed investigation of interactions. Current analysis methods complement wind tunnel testing in several ways. Herein, the discussion is focused on CFD methods. However, aircraft design studies need data from both CFD and wind tunnel testing. Each approach complements the other.

Cosner, Raymond R.↗

Application of satellite data in variational analysis for global cyclonic systems

The research goal was a variational data assimilation method that incorporates as dynamical constraints, the primitive equations for a moist, convectively unstable atmosphere and the radiative transfer equation. Variables to be adjusted include the three-dimensional vector wind, height, temperature, and moisture from rawinsonde data, and cloud-wind vectors, moisture, and radiance from satellite data. This presents a formidable mathematical problem. In order to facilitate thorough analysis of each of the model components, four variational models that divide the problem naturally according to increasing complexity are defined. Each model is summarized.

Achtemeier, G. L.↗

How to determine spiral bevel gear tooth geometry for finite element analysis

An analytical method was developed to determine gear tooth surface coordinates of face milled spiral bevel gears. The method combines the basic gear design parameters with the kinematical aspects for spiral bevel gear manufacturing. A computer program was developed to calculate the surface coordinates. From this data a 3-D model for finite element analysis can be determined. Development of the modeling method and an example case are presented.

Handschuh, Robert F.↗

A Parallel Computing Infrastructure for Building Energy Simulation

In order to study grid-interactive efficient buildings, Pacific Northwest National Laboratories (PNNL) needs an infrastructure for urban-scale building energy modeling. Such an infrastructure should be fast, scalable, and easy-to-use. Given a set of data from the Energy Information Administration’s Commercial Building Energy Consumption Survey (CBECS) and tool to translate survey data into simulation inputs, this project aimed to conduct the simulation of the entire dataset in parallel. Before running the simulations, the necessary software was bundled into a container for use on the PNNL supercomputing network. Then, the parallel simulation workflow was designed using GNU Make, a file creation software, and submitted to a supercomputing partition which could run hundreds of simulations simultaneously. The EnergyPlus simulations output hourly electric meter data for each CBECS sample, which represents the electricity consumption of similar commercial buildings across the United States. Analyzing and visualizing the meter data is important to the future of the work, and this project wrote code to make common analysis methods simple, fast, and accessible. Moving forwards, the model will need to be expanded to include data from other sources and its accuracy will need to be improved and eventually validated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Using feature importance as an exploratory data analysis tool on Earth system models

Abstract. Machine learning (ML) models are commonly used to generate predictions, but these models can also support the discovery of new science. Generating accurate predictions necessitates that a model captures the structure of the underlying data. If the structure is properly extracted, ML could be a useful exploratory and evidential tool. In this paper, we present a case study that demonstrates the use of ML for exploratory data analysis (EDA) in the climate space. We apply the ML explainability method of spatiotemporal zeroed feature importance (stZFI) to understand how climate-variable associations evolve over space and time. Our analyses focus on data from ensembles of Earth system models (ESMs) which provide data on different climate states and conditions. We elect to work with ESM ensembles since they allow us to compare feature importance across alternative scenarios not available with observed data. The ensembles also account for natural variability so that we can distinguish between signal and noise due to natural climate variability when computing feature importance. The use of perturbed initial condition ensembles introduces variability mimicking the natural variability in the atmosphere; thus the signals emerging using feature importance (FI) can be evaluated against the natural variability in the climate system. For our analyses, we consider the 1991 volcanic eruption of Mount Pinatubo, which was a large stratospheric aerosol injection. We explore the climate pathway associated with the eruption from aerosols to radiation to temperature at both the near-surface and stratospheric levels. In addition to applying the method to data generated from two different ESMs, we apply stZFI to reanalysis data to compare the associations identified by stZFI. We show how stZFI tracks the importance of aerosol optical depth over time on forecasting temperatures. This case study illustrates usefulness of an ML tool (stZFI) for EDA on a well-studied climate exemplar.

Ries, Daniel (ORCID:0000000250294647)↗

Calculations for interpretation of solar vector magnetograph data

Computer techniques for data analysis of sunspot observations are presented. Photographic spectra were converted to digital form and analyzed. Methods of determining magnetic field strengths, i.e., the Zeeman effect, are discussed. Errors originating with telescope equipment and the magnetograph are treated. Flow charts of test programs and procedures of the data analysis are shown.

Dunn, A. R.↗

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗

Nonlinear aerodynamics and the design of wing tips

This report describes results of research conducted from April 1991 through March 1992. The general objective was to improve an existing wing optimization method, and apply the method to specific problems of interest. The method, while a valuable tool for wing tip design studies, can be applied to more general problems, and has been applied to some of these other problems during its development. Specific goals that were accomplished are listed and explained in more detail in the report. First, improvements were made to the portability and control flow of the existing code. The major iteration loop dealing with structural design was sped up and an alternate approach, using the optimizer to do structural sizing, was studied. Second, analysis methods were improved in the areas of structural and high lift modeling. The structural method was revised to give total wing weight and verified against data for particular commercial aircraft. The high lift analysis was improved to provide reasonable estimates of C(sub L max) in the flaps down condition. These improvements enabled making wing area a design variable, where it had been a fixed variable in the original method. Third, the method was applied to the design of wings for a Learjet. Rough studies were done to determine the effects of laminar flow design on wing shape. Finally, studies on wingtip shape were begun.

Kroo, Ilan↗

Hanford Site Composite Analysis Data Package: Exposure Scenarios and Radionuclide Specific Dose Conversion Factors.

This data package summarizes the exposure assumptions, equations, and methods used to calculate radionuclide-specific unit dose factors and the radiological doses for both groundwater and atmospheric pathways as a part of the revised Hanford Site Composite Analysis. An All-Pathways Representative Person exposure scenario is considered to evaluate exposure via both groundwater and atmospheric transport pathways. The radiological dose assessments for both groundwater and atmospheric pathways are included in the performance assessments for various Waste Management Areas at the Hanford Site. This data package calculates exposure route-specific and total unit dose factors for composite-analysis-specific radionuclides of concern based on the exposure assumptions used in the composite analysis and performance assessments. This data package presents the results and comparison of the radionuclide-specific unit dose factors based on the exposure assumptions used in the revised composite analysis and various performance assessments.

61 RADIATION PROTECTION AND DOSIMETRY↗

A Methodology for Flight-Time Identification of Helicopter-Slung Load Frequency Response Characteristics Using CIFER

Helicopter slung load operations are common in both military and civil contexts. The slung load adds load rigid body modes, sling stretching, and load aerodynamics to the system dynamics, which can degrade system stability and handling qualities, and reduce the operating envelope of the combined system below that of the helicopter alone. Further, the effects of the load on system dynamics vary significantly among the large range of loads, slings, and flight conditions that a utility helicopter will encounter in its operating life. In this context, military helicopters and loads are often qualified for slung load operations via flight tests which can be time consuming and expensive. One way to reduce the cost and time required to carry out these tests and generate quantitative data more readily is to provide an efficient method for analysis during the flight, so that numerous test points can be evaluated in a single flight test, with evaluations performed in near real time following each test point and prior to clearing the aircraft to the next point. Methodology for this was implemented at Ames and demonstrated in slung load flight tests in 1997 and was improved for additional flight tests in 1999. The parameters of interest for the slung load tests are aircraft handling qualities parameters (bandwidth and phase delay), stability margins (gain and phase margin), and load pendulum roots (damping and natural frequency). A procedure for the identification of these parameters from frequency sweep data was defined using the CIFER software package. CIFER is a comprehensive interactive package of utilities for frequency domain analysis previously developed at Ames for aeronautical flight test applications. It has been widely used in the US on a variety of aircraft, including some primitive flight time analysis applications.

Sahai, Ranjana↗