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Experimental Validation of a Prognostic Health Management System for Electro-Mechanical Actuators

The work described herein is aimed to advance prognostic health management solutions for electro-mechanical actuators and, thus, increase their reliability and attractiveness to designers of the next generation aircraft and spacecraft. In pursuit of this goal the team adopted a systematic approach by starting with EMA FMECA reviews, consultations with EMA manufacturers, and extensive literature reviews of previous efforts. Based on the acquired knowledge, nominal/off-nominal physics models and prognostic health management algorithms were developed. In order to aid with development of the algorithms and validate them on realistic data, a testbed capable of supporting experiments in both laboratory and flight environment was developed. Test actuators with architectures similar to potential flight-certified units were obtained for the purposes of testing and realistic fault injection methods were designed. Several hundred fault scenarios were created, using permutations of position and load profiles, as well as fault severity levels. The diagnostic system was tested extensively on these scenarios, with the test results demonstrating high accuracy and low numbers of false positive and false negative diagnoses. The prognostic system was utilized to track fault progression in some of the fault scenarios, predicting the remaining useful life of the actuator. A series of run-to-failure experiments were conducted to validate its performance, with the resulting error in predicting time to failure generally lesser than 10% error. While a more robust validation procedure would require dozens more experiments executed under the same conditions (and, consequently, more test articles destroyed), the current results already demonstrate the potential for predicting fault progression in this type of devices. More prognostic experiments are planned for the next phase of this work, including investigation and comparison of other prognostic algorithms (such as various types of Particle Filter and GPR), addition of new fault types, and execution of prognostic experiments in flight environment.

TRMM Ground Validation Radar Site 3D Reflectivity L2 1 hour V7 (TRMM_2A55UW) at GES DISC

This dataset is part of the University of Washington TRMM Ground Validation products. Multiple-level cartesian grid containing output of NCAR SPRINT interpolation of CZ and VR fields of 1C51UW. Horizontal extent is 150x150km and resolution is 2km. Vertical range is 2-15km and resolution is 1km. Unlike other products, 2A55UW is not created for every volume but only for volumes of interest. These are defined as volumes within +/-15 minutes of overpass times and volumes with significant rainfall (areal rainfall rate greater or equal 0.15mm/hr). A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products. The four primary GV sites are: + Darwin, Australia; + Houston, Texas; + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida. A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers. DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers.

Development of a Mobile Robot Test Platform and Methods for Validation of Prognostics-Enabled Decision Making Algorithms

As fault diagnosis and prognosis systems in aerospace applications become more capable, the ability to utilize information supplied by them becomes increasingly important. While certain types of vehicle health data can be effectively processed and acted upon by crew or support personnel, others, due to their complexity or time constraints, require either automated or semi-automated reasoning. Prognostics-enabled Decision Making (PDM) is an emerging research area that aims to integrate prognostic health information and knowledge about the future operating conditions into the process of selecting subsequent actions for the system. The newly developed PDM algorithms require suitable software and hardware platforms for testing under realistic fault scenarios. The paper describes the development of such a platform, based on the K11 planetary rover prototype. A variety of injectable fault modes are being investigated for electrical, mechanical, and power subsystems of the testbed, along with methods for data collection and processing. In addition to the hardware platform, a software simulator with matching capabilities has been developed. The simulator allows for prototyping and initial validation of the algorithms prior to their deployment on the K11. The simulator is also available to the PDM algorithms to assist with the reasoning process. A reference set of diagnostic, prognostic, and decision making algorithms is also described, followed by an overview of the current test scenarios and the results of their execution on the simulator.

GPM Ground Validation NEXRAD Level III KMPX IFloodS V1

The GPM Ground Validation NEXRAD Level III KMPX IFloodS dataset contain precipitation products derived from selected NEXt Generation Weather RADar system (NEXRAD) radars in operation during the Iowa Flood Studies (IFloodS) field campaign to help support the ground validation of the Global Precipitation Measurement (GPM). NEXRAD is a network of 160 stationary S-Band radars dispersed throughout the United States and select locations abroad. Data were gathered from four NEXRAD stations in the vicinity of the IFloodS campaign during March 29, 2013 through June 18, 2013. This dataset contains data files of digital instantaneous precipitation rate (DPR) and storm total accumulation estimates (DTA) in NIDS binary format.

GPM Ground Validation CXSI Radar Imagery OLYMPEX V1

The GPM Ground Validation CXSI Radar Imagery OLYMPEX dataset contains radar reflectivity and precipitation rate images obtained from Environment and Climate Change Canada (ECCC)’s weather radar network during the GPM Ground Validation Olympic Mountain Experiment (OLYMPEX), which was conducted to validate rain and snow measurements in mid latitude frontal systems as they move from ocean to coast to mountains and to determine how remotely sensed measurements of precipitation by GPM can be applied to a range of hydrologic, weather forecasting, and climate data. These data are available as GIF images for November 19, 2015 through December 31, 2015.

GPM Ground Validation NEXRAD Level III KARX IFloodS V1

The GPM Ground Validation NEXRAD Level III KARX IFloodS dataset contain precipitation products derived from selected NEXt Generation Weather RADar system (NEXRAD) radars in operation during the Iowa Flood Studies (IFloodS) field campaign to help support the ground validation of the Global Precipitation Measurement (GPM). NEXRAD is a network of 160 stationary S-Band radars dispersed throughout the United States and select locations abroad. Data were gathered from four NEXRAD stations in the vicinity of the IFloodS campaign during March 29, 2013 through June 18, 2013. This dataset contains data files of digital instantaneous precipitation rate (DPR) and storm total accumulation estimates (DTA) in NIDS binary format.

Remote-sensing-derived particulate organic carbon (POC) validation

Measurements taken for the purpose of validating remote-sensing-derived particulate organic carbon.

GPM GROUND VALIDATION NOAA S-BAND PROFILER RAW DATA NETCDF FORMAT MC3E V1

The GPM Ground Validation NOAA S-Band Profiler Raw Data NetCDF Format MC3E dataset was gathered during the Midlatitude Continental Convective Clouds Experiment (MC3E) in Oklahoma April 8, 2011 to June 7, 2011 and consists of uncalibrated Doppler velocity spectra data in units of relative power return. The overarching goal was to provide the most complete characterization of convective cloud systems, precipitation, and the environment that has ever been obtained, providing constraints for model cumulus parameterizations and space-based rainfall retrieval algorithms over land that had never before been available. The S-band 2.8 GHz profiler points vertically and measures the backscattered power from raindrops and ice particles as precipitating cloud systems pass overhead. The profiler processes radar pulses during a 7-second dwell before calculating and saving uncalibrated Doppler velocity spectra at each range gate that were separated by 60-meters vertically. Data collected during each hour are saved in two files. All precipitation mode profiles are saved in one hourly data file and all attenuated mode profiles are saved in another hourly data file. Calibrated data can be obtained from the S-band Original Dwell and Minute datasets.

GPM GROUND VALIDATION CONICAL SCANNING MILLIMETER-WAVE IMAGING RADIOMETER (COSMIR) MC3E V1

The GPM Ground Validation Conical Scanning Millimeter-wave Imaging Radiometer (COSMIR) MC3E dataset used the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR), which was utilized during the Midlatitude Continental Convective Clouds Experiment (MC3E) served as an airborne high-frequency simulator of the GPM Microwave Imager (GMI), which launched in 2014. The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team. The dataset provides well-calibrated radiometric data from 9 channels between 50-183 GHz with the accuracy on the order of +-1K. All channels besides the 89 and 165.5 GHz are horizontally polarized.

Autonomous Radiometric Validation of PACEâs OCI in the Gulf of Mexico

Validate PACEâs OCI remote sensing reflectance using uncrewed autonomous vessel measuring water-leaving radiance with two methods along with inherence optical properties in the Gulf of Mexico.

GPM Ground Validation Duke Micro Rain Radar (MRR) IPHEx V1

The GPM Ground Validation Duke Micro Rain Radar (MRR) IPHEx dataset was gathered during the Global Precipitation Measurement (GPM) Ground Validation Integrated Precipitation and Hydrology Experiment (IPHEx) in North Carolina from May 1, 2014 through June 15, 2014. The dataset contains measured and derived data from three MRR instruments placed in separate locations within the study region. The MRR is a Biral/Metek 24 GHz (K-band) vertically oriented Frequency Modulated Continuous Wave (FM-CW) radar that measures signal backscatter from which Doppler spectra, radar reflectivity, Doppler velocity, drop size distribution, rain rate, liquid water content, and path integrated attenuation are derived. Data files are available in ASCII data format.

GPM Ground Validation NEXRAD Level III KDMX IFloodS V1

The GPM Ground Validation NEXRAD Level III KDMX IFloodS dataset contain precipitation products derived from selected NEXt Generation Weather RADar system (NEXRAD) radars in operation during the Iowa Flood Studies (IFloodS) field campaign to help support the ground validation of the Global Precipitation Measurement (GPM). NEXRAD is a network of 160 stationary S-Band radars dispersed throughout the United States and select locations abroad. Data were gathered from four NEXRAD stations in the vicinity of the IFloodS campaign during March 29, 2013 through June 18, 2013. This dataset contains data files of digital instantaneous precipitation rate (DPR) and storm total accumulation estimates (DTA) in NIDS binary format.

Ocean color calibration and validation measurements off the New Jersey and New York coasts

Measurements made off the New Jersey and New York coasts between 2005 and 2009.

Rodent Research-1 (RR1) NASA Validation Flight: Mouse soleus muscle transcriptomic and epigenomic data

NASA's Rodent Research (RR) project is playing a critical role in advancing biomedical research on the physiological effects of space environments. Due to the limited resources for conducting biological experiments aboard the International Space Station (ISS), it is imperative to use crew time efficiently while maximizing high-quality science return. NASA's GeneLab project has as its primary objectives to 1) further increase the value of these experiments using a multi-omics, systems biology-based approach, and 2) disseminate these data without restrictions to the scientific community. The current investigation assessed viability of RNA, DNA, and protein extracted from archived RR-1 tissue samples for epigenomic, transcriptomic, and proteomic assays. During the first RR spaceflight experiment, a variety of tissue types were harvested from subjects, snap-frozen or RNAlater-preserved, and then stored at least a year at -80C after return to Earth. They were then prioritized for this investigation based on likelihood of significant scientific value for spaceflight research. All tissues were made available to GeneLab through the bio-specimen sharing program managed by the Ames Life Science Data Archive and included mouse adrenal glands, quadriceps, gastrocnemius, tibialis anterior, extensor digitorum longus, soleus, eye, and kidney. We report here protocols for and results of these tissue extractions, and thus, the feasibility and value of these kinds of omics analyses. In addition to providing additional opportunities for investigation of spaceflight effects on the mouse transcriptome and proteome in new kinds of tissues, our results may also be of value to program managers for the prioritization of ISS crew time for rodent research activities.

Rodent Research-1 (RR1) NASA Validation Flight: Mouse tibialis anterior muscle transcriptomic, proteomic, and epigenomic data

GPM GROUND VALIDATION CONICAL SCANNING MILLIMETER-WAVE IMAGING RADIOMETER (COSMIR) GCPEX V1

The GPM Ground Validation Conical Scanning Millimeter-wave Imaging Radiometer (COSMIR) GCPEx dataset used the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR), which was utilized for the GPM Cold-season Precipitation Experiment (GCPEx) as an airborne high-frequency simulator of the GPM Microwave Imager (GMI), which was launched in 2014. The CoSMIR was modified with a new scan mode to acquire both conical and cross-track scan data simultaneously in a given flight satisfying the requirements of the Precipitation Measurement Mission (PMM) algorithm development team. The dataset provides well-calibrated radiometric data from 9 channels between 50-183 GHz with the accuracy on the order of +-1K. All channels besides the 89 and 165.5 GHz are horizontally polarized.

Tackling Verification and Validation for Prognostics

Verification and validation (V&V) has been identified as a critical phase in fielding systems with Integrated Systems Health Management (ISHM) solutions to ensure that the results produced are robust, reliable, and can confidently inform about vehicle and system health status and to support operational and maintenance decisions. Prognostics is a key constituent within ISHM. It faces unique challenges for V&V since it informs about the future behavior of a component or subsystem. In this paper, we present a detailed review of identified barriers and solutions to prognostics V&V, and a novel methodological way for the organization and application of this knowledge. We discuss these issues within the context of a prognostics application for the ground support equipment of space vehicle propellant loading, and identify the significant barriers and adopted solution for this application.

GPM Ground Validation Composite Satellite Overpasses OLYMPEX V4

The GPM Ground Validation Composite Satellite Overpasses OLYMPEX dataset provides brightness temperature, precipitation, and total column water vapor estimates from multiple satellite overpasses including DMSP F16-19, GCOM-W1, GPM, MetOp, NOAA, and NPP for the OLYMPEX field campaign. The OLYMPEX field campaign took place between November, 2015, and January, 2016, with additional ground sampling continuing through February, on the Olympic Peninsula in the Pacific Northwest of the United States. This field campaign provides ground-based validation support of the findings resulting from the Global Precipitation Measurement (GPM) Core Observatory satellite. Data files are available from November 1, 2015 thru May 1, 2016 in HDF-5 format.

GPM Ground Validation National Mosaic and Multi-Sensor QPE (NMQ) System IPHEx V1

The GPM Ground Validation National Mosaic and Multi-Sensor QPE (NMQ) System IPHEx dataset consists of six different data products: precipitation rate, hourly rainfall accumulation, daily rainfall accumulation, hybrid scan reflectivity, three-dimensional reflectivity, and vertically integrated liquid content estimates. These data products were created using the NOAA NMQ System which ingests Weather Surveillance Radar 88 Doppler (WSR-88D) radar data, Rapid Update Cycle (RUC) model analysis fields, and Hydrometeorological Automated Data Systems (HADS) gauge data. The files provided in this dataset are from system output during the GPM Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign that occurred in the Southern Appalachians, spanning into the Piedmont and Coastal Plain regions of North Carolina. These data are available in ASCII and netCDF-4 formats for dates between April 30, 2014 through June 16, 2014.

GPM Ground Validation Duke Parsivel IPHEx V1

The GPM Ground Validation Duke Parsivel IPHEx dataset were collected during the GPM Ground Validation Integrated Precipitation and Hydrology Experiment (IPHEx) field campaign which was held in the Southern Appalachian region, including the Piedmont and Coastal Plain regions, of North Carolina. OTT laser-based Parsivel instruments operated from May 1, 2014 through June 30, 2014. The IPHEx campaign was designed to characterize warm season orographic precipitation regimes and determine the relationship between precipitation regimes and hydrologic processes in regions of complex terrain. The parsivel data are available in ASCII-csv format for each of the parsivel locations and contain precipitation intensity and drop parameters.