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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 181 records · Page 10

Autonomous power expert system

The Autonomous Power Expert (APEX) system was designed to monitor and diagnose fault conditions that occur within the Space Station Freedom Electrical Power System (SSF/EPS) Testbed. APEX is designed to interface with SSF/EPS testbed power management controllers to provide enhanced autonomous operation and control capability. The APEX architecture consists of three components: (1) a rule-based expert system, (2) a testbed data acquisition interface, and (3) a power scheduler interface. Fault detection, fault isolation, justification of probable causes, recommended actions, and incipient fault analysis are the main functions of the expert system component. The data acquisition component requests and receives pertinent parametric values from the EPS testbed and asserts the values into a knowledge base. Power load profile information is obtained from a remote scheduler through the power scheduler interface component. The current APEX design and development work is discussed. Operation and use of APEX by way of the user interface screens is also covered.

Walters, Jerry L.↗

On Hilbert-Huang Transform Based Synthesis of a Signal Contaminated by Radio Frequency Interference or Fringes

Norden E. Huang et al. had proposed and published the Hilbert-Huang Transform (HHT) concept correspondently in 1996, 1998. The HHT is a novel method for adaptive spectral analysis of non-linear and non-stationary signals. The HHT comprises two components: - the Huang Empirical Mode Decomposition (EMD), resulting in an adaptive data-derived basis of Intrinsic Mode functions (IMFs), and the Hilbert Spectral Analysis (HSA1) based on the Hilbert Transform for 1-dimension (1D) applied to the EMD IMF's outcome. Although paper describes the HHT concept in great depth, it does not contain all needed methodology to implement the HHT computer code. In 2004, Semion Kizhner and Karin Blank implemented the reference digital HHT real-time data processing system for 1D (HHT-DPS Version 1.4). The case for 2-Dimension (2D) (HHT2) proved to be difficult due to the computational complexity of EMD for 2D (EMD2) and absence of a suitable Hilbert Transform for 2D spectral analysis (HSA2). The real-time EMD2 and HSA2 comprise the real-time HHT2. Kizhner completed the real-time EMD2 and the HSA2 reference digital implementations respectively in 2013 & 2014. Still, the HHT2 outcome synthesis remains an active research area. This paper presents the initial concepts and preliminary results of HHT2-based synthesis and its application to processing of signals contaminated by Radio-Frequency Interference (RFI), as well as optical systems' fringe detection and mitigation at design stage. The Soil Moisture Active Passive (SMAP mission (SMAP) carries a radiometer instrument that measures Earth soil moisture at L1 frequency (1.4 GHz polarimetric - H, V, 3rd and 4th Stokes parameters). There is abundant RFI at L1 and because soil moisture is a strategic parameter, it is important to be able to recover the RFI-contaminated measurement samples (15% of telemetry). State-of-the-art only allows RFI detection and removes RFI-contaminated measurements. The HHT-based analysis and synthesis facilitates recovery of measurements contaminated by all kinds of RFI, including jamming [7-8]. The fringes are inherent in optical systems and multi-layer complex contour expensive coatings are employed to remove the unwanted fringes. HHT2-based analysis allows test image decomposition to analyze and detect fringes, and HHT2-based synthesis of useful image.

Spacecraft Electronics Equipment↗

Wiener restoration of sampled image data - End-to-end analysis

The Wiener filter is formulated as a function of the basic image-gathering and image-reconstruction constraints, thereby providing a method for minimizing the mean-squared error between the (continuous-input) radiance field and its restored (continuous-output) representation. This formulation of the Wiener filter is further extended to the Wiener-characteristic filter, which provides a method for explicitly specifying the desired representation. Two specific examples of Wiener filters are presented.

Fales, Carl L.↗

A Remote Sensing/Geographic Information Systems Approach in the Selection of Mars Sites of Biological Interest

The search for extinct or extant life on Mars is the search for past or present liquid water, respectively. There are numerous signs of past liquid water on Mars in the form of dry river valleys, paleolakes, and their associated flow and sediment patterns. While some of these features are recent (Amazonian, 1.8 billion years ago to present), there is no evidence that any are currently flowing. Liquid water on the surface would only be possible at those sites with sufficiently high temperatures and pressure. The key to the selection of sites on Mars to search for evidence of life is the search for the presence of water. An approach to this problem is the use of remotely sensed data incorporated in a geographic information system (GIS). A GIS is a computer-based system capable of assembling, storing, manipulating, and displaying geographically referenced information, i.e., data identified according to their locations. In planetary studies these data are acquired from remote sensing (RS) platforms (orbiters). These data are co-registered layers and, through the use of GIS analysis functions, areas on these layers can be selected as a function of the information desired. Our work used existing data layers from the Viking and Mars Global Surveyor missions to determine where water could be possible in liquid form on the Martian surface, based on the phase diagram for water.

Lobitz, B. M.↗

Comparison of analysis and flight test data for a drone aircraft with active flutter suppression

A drone aircraft equipped with an active flutter suppression system is considered with emphasis on the comparison of modal dampings and frequencies as a function of Mach number. Results are presented for both symmetric and antisymmetric motion with flutter suppression off. Only symmetric results are given for flutter suppression on. Frequency response functions of the vehicle are presented from both flight test data and analysis. The analysis correlation is improved by using an empirical aerodynamic correction factor which is proportional to the ratio of experimental to analytical steady-state lift curve slope. The mathematical models are included and existing analytical techniques are described as well as an alternative analytical technique for obtaining closed-loop results.

Newsom, J. R.↗

Updated Performance Evaluation of the ISS Water Processor Multifiltration Beds

The ISS Water Processor Assembly (WPA) produces potable water from a waste stream containing humidity condensate and urine distillate. The primary treatment process is achieved in the Multifiltration Beds, which include adsorbent media and ion exchange resin for the removal of dissolved organic and inorganic contaminants. Two Multifiltration Beds (MF Beds) were replaced on ISS in July 2010 after initial indication of inorganic breakthrough of the first bed and an increasing Total Organic Carbon (TOC) trend in the product water. The first bed was sampled and analyzed Sept 2011 through March 2012. The second MF Bed was sampled and analyzed June 2012 through August 2012. The water resident in the both beds was analyzed for various parameters to evaluate adsorbent loading, performance of the ion exchange resin, microbial activity, and generation of leachates from the ion exchange resin. Portions of the adsorbent media and ion exchange resin were sampled and subsequently desorbed to identify the primary contaminants removed at various points in the bed in addition to microbial analysis. Analysis of the second bed will be compared to results from the first bed to provide a comprehensive overview of how the Multifiltration Beds function on orbit. New data from the second bed supplements the analysis of the first bed (previously reported) and gives a more complete picture of breakthrough compounds, resin breakdown products, microbial activity, and difficult to remove compounds. The results of these investigations and implications to the operation of the WPA on ISS are documented in this paper.

Bowman, Elizabeth M.↗

Quasi Real Time Data Analysis for Air Quality Monitoring with an Electronic Nose

Cabin Air Quality Monitoring: A) Functions; 1) Incident monitor for targeted contaminants exceeding targeted concentrations. Identify and quantify. 2) Monitor for presence of compounds associated with fires or overheating electronics. 3) Monitor clean-up process. B) Characteristics; 1) Low mass, low power device. 2) Requires little crew time for maintenance and calibration. 3) Detects, identifies and quantifies selected chemical species at or below 24 hour SMAC.

data analysis↗

Radiation Dose Assessments of Solar Particle Events with Spectral Representation at High Energies for the Improvement of Radiation Protection

For radiation dose assessments of major solar particle events (SPEs), spectral functional forms of SPEs have been made by fitting available satellite measurements up to approx.100 MeV. However, very high-energy protons (above ~500 MeV) have been observed with neutron monitors (NMs) in ground level enhancements (GLEs), which generally present the most severe radiation hazards to astronauts. Due to technical difficulties in converting NM data into absolutely normalized fluence measurements, those functional forms were made with little or no use of NM data. A new analysis of NM data has found that a double power law in rigidity (the so-called Band function) generally provides a satisfactory representation of the combined satellite and NM data from approx.10 MeV to approx.10 GeV in major SPEs (Tylka & Dietrich 2009). We use the Band function fits to re-assess human exposures from large SPEs. Using different spectral representations of large SPEs, variations of exposure levels were compared. The results can be applied to the development of approaches of improved radiation protection for astronauts, as well as the optimization of mission planning and shielding for future space missions.

Kim, Myung-Hee↗

Absorption and Attenuation Coefficients Using the WET Labs ac-s in the Mid-Atlantic Bight: Field Measurements and Data Analysis

Ocean color algorithms are based on the parameterization of apparent optical properties as a function of inherent optical properties. WET Labs underwater absorption and attenuation meters (ac-9 and ac-s) measure both the spectral beam attenuation [c (lambda)] and absorption coefficient [a (lambda)]. The ac-s reports in a continuous range of 390-750 nm with a band pass of 4 nm, totaling approximately 83 distinct wavelengths, while the ac-9 reports at 9 wavelengths. We performed the ac-s field measurements at nine stations in the Mid-Atlantic Bight from water calibrations to data analysis. Onboard the ship, the ac-s was calibrated daily using Milli Q-water. Corrections for the in situ temperature and salinity effects on optical properties of water were applied. Corrections for incomplete recovery of the scattered light in the ac-s absorption tube were performed. The fine scale of spectral and vertical distributions of c (lambda) and a (lambda) were described from the ac-s. The significant relationships between a (674) and that of spectrophotometric analysis and chlorophyll a concentration of discrete water samples were observed.

Ohi, Nobuaki↗

Analysis of structural response data using discrete modal filters

The application of reciprocal modal vectors to the analysis of structural response data is described. Reciprocal modal vectors are constructed using an existing experimental modal model and an existing frequency response matrix of a structure, and can be assembled into a matrix that effectively transforms the data from the physical space to a modal space within a particular frequency range. In other words, the weighting matrix necessary for modal vector orthogonality (typically the mass matrix) is contained within the reciprocal model matrix. The underlying goal of this work is mostly directed toward observing the modal state responses in the presence of unknown, possibly closed loop forcing functions, thus having an impact on both operating data analysis techniques and independent modal space control techniques. This study investigates the behavior of reciprocol modal vectors as modal filters with respect to certain calculation parameters and their performance with perturbed system frequency response data.

Freudinger, Lawrence C.↗

A FORTRAN program for the analysis of linear continuous and sample-data systems

A FORTRAN digital computer program which performs the general analysis of linearized control systems is described. State variable techniques are used to analyze continuous, discrete, and sampled data systems. Analysis options include the calculation of system eigenvalues, transfer functions, root loci, root contours, frequency responses, power spectra, and transient responses for open- and closed-loop systems. A flexible data input format allows the user to define systems in a variety of representations. Data may be entered by inputing explicit data matrices or matrices constructed in user written subroutines, by specifying transfer function block diagrams, or by using a combination of these methods.

Edwards, J. W.↗

The estimation of decay coefficient in pulsed transient data

The problem of estimation and interpretation of a decay coefficient in a pulsed transient signal is considered. Two methods are proposed in estimating the decay coefficient of pulsed decay transient data. The methods are derived through a spectral analysis for a parametric model of impulse response function of signal frequency. The several pulsed response data from T burner tests as well as some synthesized data are analyzed and the performance of the estimation procedures are examined. Suggestions for further research in this area are offered. The estimation procedures presented can be extended to the case of multiple frequencies in pulse response function and time dependent decay or growth coefficients.

Park, T. W.↗

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗

Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems; Workshop Report

The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.

Braverman, Amy↗

A Monte Carlo investigation of experimental data requirements for fitting polynomial functions

This report examines the extent to which sample size affects the accuracy of a low order polynomial approximation of an experimentally observed quantity and establishes a trend toward improvement in the accuracy of the approximation as a function of sample size. The task is made possible through a simulated analysis carried out by the Monte Carlo method, in which data are generated by using several transcendental or algebraic functions as models. Contaminated data of varying amounts are fitted to linear quadratic or cubic polynomials, and the behavior of the mean-squared error of the residual variance is determined as a function of sample size. Results indicate that the effect of the size of the sample is significant only for relatively small sample sizes and diminishes drastically for moderate and large amounts of experimental data.

Canavos, G. C.↗

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This paper investigates the utility of the Hilbert-Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert-Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert-Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this paper is to demonstrate the potential applications of the Hilbert-Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized/online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F/A-18 Active Aeroelastic Wing aircraft, an Aerostructures Test Wing, and pitch-plunge simulation.

Brenner, Marty↗

Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy

Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).

Neergaard, Lynn↗

Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy

Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).

Neergaard, L.↗