Search NASA⌕ Search

SEARCH · Search NASA

Results for “sensor data analytics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Ultra-Pure, High Endurance Liquid Bladder with Volume Sensor for Space Applications

The NASA Portable Life Support System (PLSS) for the Exploration Extravehicular Mobility Unit (xEMU) incorporates a Feedwater Supply Assembly (FSA) to store consumable cooling water. The FSA accepts pure water prior to each Extra-Vehicular Activity (EVA), then supplies this water to a membrane evaporator at ambient suit pressure during the eight hour EVA. The FSA must function reliably for hundreds of EVAs over 15 years of service without introducing contamination that may accumulate and foul the membrane. We present a unique design that combines the benefits of a flexible fluoropolymer bladder with the strength and convenience of a rigid tank, providing an ultra-pure, ambient-pressure reservoir with fill-drain cycle life exceeding 3000, internal pressure tolerance exceeding 100 psi, high volumetric efficiency, near-zero dead volume, optical transparency for visual inspection, simplified mounting, and very low mass. We also incorporate a novel volume sensor suitable for both microgravity and arbitrarily accelerated environments and capable of real-time monitoring with accuracy on the order of 2.5% full scale. Analytical predictions are supported by experimental test data from a mature subscale prototype.

PLSS Portable Life Support System FSA Feedwater Su↗

Analytical and experimental study of mean flow and turbulence characteristics inside the passages of an axial flow inducer

The inviscid and viscid effects existing within the passages of a three bladed axial flow inducer operating at a flow coefficient of 0.065 are investigated. The blade static pressure and blade limiting streamline angle distributions were determined and the three components of mean velocity, turbulence intensities, and turbulence stresses were measured at locations inside the inducer blade passage utilizing a rotating three sensor hotwire probe. Applicable equations were derived for the hotwire data reduction analysis and solved numerically to obtain the appropriate flow parameters. The three dimensional inviscid flow in the inducer was predicted by numerically solving the exact equations of motion, and the three dimensional viscid flow was predicted by incorporating the dominant viscous terms into the exact equations. The analytical results are compared with the experimental measurements and design values where appropriate. Radial velocities are found to be of the same order as axial velocities within the inducer passage, confirming the highly three dimensional characteristic of inducer flow. Total relative velocity distribution indicate a substantial velocity deficiency near the tip at mid-passage which expands significantly as the flow proceeds toward the inducer trailing edge. High turbulence intensities and turbulence stresses are concentrated within this core region. Considerable wake diffusion occurs immediately downstream of the inducer trailing edge to decay this loss core. Evidence of boundary layer interactions, blade blockage effects, radially inward flows, annulus wall effects, and backflows are all found to exist within the long, narrow passages of the inducer.

Gorton, C. A.↗

Application of Geostatistical Simulation to Enhance Satellite Image Products

With the deployment of Earth Observing System (EOS) satellites that provide daily, global imagery, there is increasing interest in defining the limitations of the data and derived products due to its coarse spatial resolution. Much of the detail, i.e. small fragments and notches in boundaries, is lost with coarse resolution imagery such as the EOS MODerate-Resolution Imaging Spectroradiometer (MODIS) data. Higher spatial resolution data such as the EOS Advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER), Landsat and airborne sensor imagery provide more detailed information but are less frequently available. There are, however, both theoretical and analytical evidence that burn scars and other fragmented types of land covers form self-similar or self-affine patterns, that is, patterns that look similar when viewed at widely differing spatial scales. Therefore small features of the patterns should be predictable, at least in a statistical sense, with knowledge about the large features. Recent developments in fractal modeling for characterizing the spatial distribution of undiscovered petroleum deposits are thus applicable to generating simulations of finer resolution satellite image products. We will present example EOS products, analysis to investigate self-similarity, and simulation results.

Hlavka, Christine A.↗

Near Real-Time Flood Monitoring and Impact Assessment Systems

Floods are the costliest natural disaster, causing approximately 6.8 million deaths in the twentieth century alone. Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD. Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries. Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change. Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assess flooding and extend analytical methods to estimate impacted population and infrastructure. Measuring flood extent in situ is generally impractical, time consuming, and can be inaccurate. Remotely sensed imagery acquired from space-borne and airborne sensors provides a viable platform for consistent and rapid wall-to-wall monitoring of large flood events through time. Terabytes of freely available satellite imagery are made available online each day by NASA, ESA, and other international space research institutions. Advances in cloud computing and data storage technologies allow researchers to leverage these satellite data and apply analytical methods at scale. Repeat-survey earth observations help provide insight about how natural phenomena change through time, including the progression and recession of floodwaters. In recent years, cloud-penetrating radar remote sensing techniques (e.g., Synthetic Aperture Radar) and high temporal resolution imagery platforms (e.g., MODIS and its 1-day return period), along with high performance computing infrastructure, have enabled significant advances in software systems that provide flood warning, assessments, and hazard reduction potential. By incorporating social and economic data, researchers can develop systems that automatically quantify the socioeconomic impacts resulting from flood disaster events.

Ahamed, Aakash↗

Experimental and analytical determination of vibration characteristics of corrugated, flexibly supported, heat-shield panels

Experimental and analytical natural frequencies, nodal patterns, and typical modal displacements for a corrugated, flexibly supported, heat-shield panel are discussed. Good correlation was found between the experimental data and NASTRAN analytical results for the corrugated panel over a relatively wide frequency spectrum covered in the investigation. Of the two experimental techniques used for mode shape and displacement measurements (a noncontacting displacement sensor system and a holographic technique using a helium-neon, continuous-wave laser), the holographic technique was found, in the present investigation, to be faster and better suited for determining a large number of complex nodal patterns of the corrugated panel.

Carden, H. D.↗

Applications of Skylab data to land use and climatological analysis

The author has identified the following significant results. Skylab study in Central Atlantic Regional Ecological Test Site encompassed two separate but related tasks: (1) evaluation of photographic sensors S190A and B as sources of land use data for planning and managing land resources in major metropolitan regions, and (2) evaluation of the multispectral scanner S192 used in conjunction with associated data and analytical techniques as a data source on urban climates and the surface energy balance. Photographs from the Skylab S190B earth terrain camera were of greatest interest in the land use analysis task; they were of sufficiently high resolution to identify and map many level 2 and 3 land use categories. After being corrected to allow for atmosphere effects, output from thermal and visible bands of the S192 was employed in constructing computer map plots of albedo and surface temperature.

Alexander, R. H.↗

Development and Flight Testing of an Adaptive Vehicle Health-Monitoring Architecture

On going development and testing of an adaptable vehicle health-monitoring architecture is presented. The architecture is being developed for a fleet of vehicles. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle, and, a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained expert system. The expert system is parameterized, which makes it adaptable to be trained to both a user's subject reasoning and existing quantitative analytic tools. Communication between all levels is done with wireless radio frequency interfaces. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear. The flight tests were performed to validate the following: the wireless radio frequency communication capabilities of the system, the hardware design, command and control; software operation and, data acquisition, storage and retrieval.

Woodard, Stanley E.↗

NASA’s Prototype Spectral Water Inversion Processor and Emulator (SWIPE): Towards Global Coastal and Inland Water Quality and Algal Biodiversity Monitoring

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will provide updates on NASA’s prototype open-source aquatic modeling platform, Spectral Water Inversion Processor and Emulator (SWIPE), which is a comprehensive, multi-faceted modeling platform for both forward and inverse modeling of diverse aquatic ecosystems from the benthos to top-of-atmosphere (TOA). SWIPE provides a cohesive application which leverages recent advancements in particle modeling, Big Data analytics, and machine learning to develop a high-fidelity synthetic training ground for sensitivity studies and algorithm development for multispectral or upcoming hyperspectral missions. Some of the prominent features of SWIPE to be discussed include: 1. Advanced hyperspectral modeling of globally diverse algal and non-algal particles using a novel two-layer coated sphere scattering model and radiative transfer modeling, 2. Massive, highly detailed synthetic spectral libraries of Analysis-Ready-Data (ARD) which include spectral libraries of particle microphysics, water biogeophysical and optical properties, as well as surface and TOA reflectances at 1 nm resolution, 3. An ensemble of pre-built analytic, machine learning, and deep learning inversion algorithms for various water quality and biodiversity related retrieval parameters and uncertainty quantification, 4. Sensor-agnostic water quality inversion at wide ranging spatial and spectral resolutions including a codebase for seamless application in the Google Earth Engine and NASA Earth Exchange (NEX) for planetary scale analysis. SWIPE will be a fully open-source platform based in python with comprehensive documentation, tutorials, and options for distributed computing on high performance computing clusters or on single, local machines. Further, we will discuss how we envision SWIPE contributing towards a global analysis of coastal and inland water quality dynamics.

top-of-atmosphere (TOA)↗

GPR Imaging for Deeply Buried Objects: A Comparative Study Based on FDTD Models and Field Experiments

Conventional use of Ground Penetrating Radar (GPR) is hampered by variations in background environmental conditions, such as water content in soil, resulting in poor repeatability of results over long periods of time when the radar pulse characteristics are kept the same. Target objects types might include voids, tunnels, unexploded ordinance, etc. The long-term objective of this work is to develop methods that would extend the use of GPR under various environmental and soil conditions provided an optimal set of radar parameters (such as frequency, bandwidth, and sensor configuration) are adaptively employed based on the ground conditions. Towards that objective, developing Finite Difference Time Domain (FDTD) GPR models, verified by experimental results, would allow us to develop analytical and experimental techniques to control radar parameters to obtain consistent GPR images with changing ground conditions. Reported here is an attempt at developing 20 and 3D FDTD models of buried targets verified by two different radar systems capable of operating over different soil conditions. Experimental radar data employed were from a custom designed high-frequency (200 MHz) multi-static sensor platform capable of producing 3-D images, and longer wavelength (25 MHz) COTS radar (Pulse EKKO 100) capable of producing 2-D images. Our results indicate different types of radar can produce consistent images.

Tilley, roger↗

Failure detection and isolation experiments with the Langley Mini-Mast

A report is presented on experiments to demonstrate failure detection and isolation (FDI) using the flexible truss facility Mini-Mast at the NASA Langley Research Center. Two techniques are selected for study because they are applicable both to sensor and actuator failures and because they do not depend on hypotheses about the forms of possible failures. These two are the method of generalized parity relations and the failure detection filter. These methods utilize the concept of analytical redundancy and therefore their performance depends on the fidelity of the model of the dynamics of the system being monitored. Results are given for sensor FDI using generalized parity relations and input-output data collected during operation of the Mini-Mast. component failures are simulated in the data. The dependence of the performance of the methods on choices of the parameters in their implementation is explored.

Vander Velde, Wallace E.↗

Multi Sensor Approach to Address Sustainable Development

The main objectives of Earth Science research are many folds: to understand how does this planet operates, can we model her operation and eventually develop the capability to predict such changes. However, the underlying goals of this work are to eventually serve the humanity in providing societal benefits. This requires continuous, and detailed observations from many sources in situ, airborne and space. By and large, the space observations are the way to comprehend the global phenomena across continental boundaries and provide credible boundary conditions for the mesoscale studies. This requires a multiple sensors, look angles and measurements over the same spot in accurately solving many problems that may be related to air quality, multi hazard disasters, public health, hydrology and more. Therefore, there are many ways to address these issues and develop joint implementation, data sharing and operating strategies for the benefit of the world community. This is because for large geographical areas or regions and a diverse population, some sound observations, scientific facts and analytical models must support the decision making. This is crucial for the sustainability of vital resources of the world and at the same time to protect the inhabitants, endangered species and the ecology. Needless to say, there is no single sensor, which can answer all such questions effectively. Due to multi sensor approach, it puts a tremendous burden on any single implementing entity in terms of information, knowledge, budget, technology readiness and computational power. And, more importantly, the health of planet Earth and its ability to sustain life is not governed by a single country, but in reality, is everyone's business on this planet. Therefore, with this notion, it is becoming an impractical problem by any single organization/country to bear this colossal responsibility. So far, each developed country within their means has proceeded along satisfactorily in implementing their Earth observing needs but it has left a big void in the developing world who have very limited resources to invest in the space measurements. This paper gives some serious thoughts in what options are there in undertaking this tremendous challenge. The problem is multi-dimensional in terms of budget, technology availability, environmental legislations, public awareness, and communication limitations. Some of these issues are introduced, discussed and possible implementation strategies are provided in this paper to move out of this predicament. A strong emphasis is placed on international cooperation and collaboration to see a collective benefit for this effort

Habib, Shahid↗

Aircraft electric field measurements: Calibration and ambient field retrieval

An aircraft locally distorts the ambient thundercloud electric field. In order to determine the field in the absence of the aircraft, an aircraft calibration is required. In this work a matrix inversion method is introduced for calibrating an aircraft equipped with four or more electric field sensors and a high-voltage corona point that is capable of charging the aircraft. An analytic, closed form solution for the estimate of a (3 x 3) aircraft calibration matrix is derived, and an absolute calibration experiment is used to improve the relative magnitudes of the elements of this matrix. To demonstrate the calibration procedure, we analyze actual calibration date derived from a Lear jet 28/29 that was equipped with five shutter-type field mill sensors (each with sensitivities of better than 1 V/m) located on the top, bottom, port, starboard, and aft positions. As a test of the calibration method, we analyze computer-simulated calibration data (derived from known aircraft and ambient fields) and explicitly determine the errors involved in deriving the variety of calibration matrices. We extend our formalism to arrive at an analytic solution for the ambient field, and again carry all errors explicitly.

Koshak, William J.↗

Restructuring Big Data to Improve Data Access and Performance in Analytic Services Making Research More Efficient for the Study of Extreme Weather Events and Application User Communities

By developing and enhancing various services and tools, the GES DISC provides users with the capability to access and visualize data, and to make comparisons of data from multiple sensor and models via a number of cross-discipline projects. Discovering Data via Faceted Web Interface Web interface to data products and services Search and Download mechanisms Dataset Landing Pages Accessing Data through Interoperable Services: GDS – GrADS Data Server OPeNDAP - Open-source Project for a Network Data Access Protocol WMS – OGC service GIS connector – allowing IS tools to access data easier (coming soon) HTTPS -- direct online access Downloading Data Basics: Subset and egridding Service – Parameter, Spatial, Time, Vertical, Mean averaging, format conversion, and regridding for L3/L4 gridded data Swath Data Subsetter – Parameter, spatial subset of L2 /L1 data. Visualizing Data Online: Giovanni –Visualization and Analysis L3/L4 gridded data AIRS NRT Viewer – AIRS near-real-time DQVis – L2 data quality visualization

data cube↗

Temperature Knowledge and Model Correlation for the Soil Moisture Active and Passive (SMAP) Reflector Mesh

NASA's Earth observing Soil Moisture Active & Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 km near-polar, sun synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its 3 year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 rpm, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within 3 days. In order to make the necessary precise surface emission measurements from space, a temperature knowledge of 60 deg C for the mesh reflector is required. In order to show compliance, a thermal vacuum test was conducted using a portable solar simulator to illuminate a non flight, but flight-like test article through the quartz window of the vacuum chamber. The molybdenum wire of the antenna mesh is too fine to accommodate thermal sensors for direct temperature measurements. Instead, the mesh temperature was inferred from resistance measurements made during the test. The test article was rotated to five separate angles between 10 deg and 90 deg via chamber breaks to simulate the maximum expected on-orbit solar loading during the mission. The resistance measurements were converted to temperature via a resistance versus temperature calibration plot that was constructed from data collected in a separate calibration test. A simple thermal model of two different representations of the mesh (plate and torus) was created to correlate the mesh temperature predictions to within 60 deg C. The on-orbit mesh temperature will be predicted using the correlated analytical thermal model since direct measurements from in-situ flight thermal sensors are not possible.

Mikhaylov, Rebecca↗

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Mannino, Antonio↗

Data Collection and Analysis Software Development for Rotor Dynamics Testing in Spin Laboratory

Gas turbine engine components undergo high rotational loading another complex environmental conditions. Such operating environment leads these components to experience damages and cracks that can cause catastrophic failure during flights. There are traditional crack detections and health monitoring methodologies currently being used which rely on periodic routine maintenances, nondestructive inspections that often times involve engine and components dis-assemblies. These methods do not also offer adequate information about the faults, especially, if these faults at subsurface or not clearly evident. At NASA Glenn research center, the rotor dynamics laboratory is presently involved in developing newer techniques that are highly dependent on sensor technology to enable health monitoring and prediction of damage and cracks in rotor disks. These approaches are noninvasive and relatively economical. Spin tests are performed using a subscale test article mimicking turbine rotor disk undergoing rotational load. Non-contact instruments such as capacitive and microwave sensors are used to measure the blade tip gap displacement and blade vibrations characteristics in an attempt develop a physics based model to assess/predict the faults in the rotor disk. Data collection is a major component in this experimental-analytical procedure and as a result, an upgrade to an older version of the data acquisition software which is based on LabVIEW program has been implemented to support efficiently running tests and analyze the results. Outcomes obtained from the tests data and related experimental and analytical rotor dynamics modeling including key features of the updated software are presented and discussed.

Rotor Dynamics↗

Remote measurements of water pollution with a lidar polarimeter

This paper examines a dual polarization laser backscatter system as a method for remote measurements of certain water quality parameters. Analytical models for describing the backscatter from turbid water and oil on turbid water are presented and compared with experimental data. Laser backscatter field measurements from natural waterways are presented and compared with simultaneous ground observations of the water quality parameters: turbidity, suspended solids, and transmittance. The results of this study show that the analytical models appear valid and that the sensor investigated is applicable to remote measurements of these water quality parameters and oil spills on water.-

Sheives, T. C.↗

Analytical Redundancy Using Kalman Filters for Rocket Engine Sensor Validation

The use of sensor redundancy is crucial in aerospace systems to maintain safe, reliable operation. While hardware redundancy is more common in application, analytical redundancy can provide a viable alternative in systems where the installation of multiple redundant sensors is not viable. To this end, the use of Kalman filters to analytically validate sensor measurements within rocket engines was explored. First, a dynamic model of the RS 25 engine, a derivative of the Space Shuttle Main Engine (SSME), was reduced to a subset of relations, focused around the main combustion chamber pressure. These relations were used within the Kalman filter algorithm to generate an estimate of sensor measurements to be compared with true measurements for data validation purposes. By using a bank of Kalman filters, the residuals between the estimated and true measurements were used to detect and isolate sensor faults. Through fault simulations, the sensor validation performance of this Kalman filter bank design was compared to a hardware redundancy check. Sensor bias and drift faults of various magnitudes were injected into nominal RS 25 engine test data. Results for both approaches show comparable fault detection with most bias faults found nearly instantaneously by both algorithms. Drift fault detection results show certain cases where one algorithm is faster than the other. The key advantage of the Kalman filter algorithm is shown in fault isolation performance where it can isolate faults between two redundant sensors while the hardware redundancy comparisons cannot.

sensors↗