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At least 1,063 records · Page 59

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NASA NTRS2006

Role of Process Control in Improving Space Vehicle Safety A Space Shuttle External Tank Example

Developing a safe and reliable space vehicle requires good design and good manufacturing, or in other words "design it right and build it right". A great design can be hard to build or manufacture mainly due to difficulties related to quality. Specifically, process control can be a challenge. As a result, the system suffers from low quality which leads to low reliability and high system risk. The Space Shuttle has experienced some of those cases, but has overcome these difficulties through extensive redesign efforts and process enhancements. One example is the design of the hot gas temperature sensor on the Space Shuttle Main Engine (SSME), which resulted in failure of the sensor in flight and led to a redesign of the sensor. The most recent example is the Space Shuttle External Tank (ET) Thermal Protection System (TPS) reliability issues that contributed to the Columbia accident. As a result, extensive redesign and process enhancement activities have been performed over the last two years to minimize the sensitivities and difficulties of the manual TPS application process.

Safie, Fayssal M.↗

NASA NTRS2005

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors: Theoretical Concept - Part I

Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

Liu, Xu↗

NASA NTRS2006

Aquarius: A Mission to Monitor Sea Surface Salinity from Space

Aquarius is a combination radiometer and scatterometer (radar) operating at L-band (1.413 GHz for the radiometer and 1.26 GHz for the scatterometer). The primary instrument for measuring salinity is the radiometer. The scatterometer will provide a correction for surface roughness (waves) which is one of the largest potential sources of error in the retrieval. Unique features of the sensor are the large reflector (2.5 meter offset fed reflector with three feeds), polarimetric operation, and the tight thermal control. The three feeds produce three beams arranged to image in pushbroom fashion looking to the side of the orbit away from the sun to avoid sunglint. Polarimetric operation is included to assist in correcting for Faraday rotation which can be important at L-band. The tight thermal control is necessary to meet stability requirements (less than 0.12K drift over 7 days) which have been imposed to assist in meeting the science requirements for the retrieval of surface salinity (0.2 psu). The sensor will be in a sun-synchronous orbit at about 650 km with equatorial crossings of 6ad6pm (ascending at 6 pm). The objective is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean. To accomplish this, the measurement goals are a spatial resolution of 100 km and retrieval accuracy of 0.2 psu globally on a monthly basis. Aquarius is being developed by NASA and is a partnership between JPL and the Goddard Space Flight Center. The SAC-D mission is being developed by CONAE and will include the spacecraft and several additional instruments, including visible and infrared cameras and a microwave radiometer to monitor rain and wind velocity over the oceans, and sea ice.

LeVine, D. M.↗

NASA NTRS2010

Combining Modis and Quikscat Data to Delineate Surface and Near-Surface Melt on the Greenland Ice Sheet

Over the last two decades, increasing melt has been measured on the Greenland Ice Sheet, along with mass loss as determined from satellite data, Monitoring the state of the Greenland Ice Sheet becomes critical especially because it is actively losing mass, and the ice sheet has a sea-level rise potential of 7 in. However measurement of the extent of surface melt varies depending on the sensor used, whether it is passive or active microwave or visible or thermal infrared. We have used remote-sensing data products to study surface and near-surface melt characteristics of the Greenland Ice Sheet. We present a blended MODIS-QS melt daily product for 2007 [1]. The products, including Moderate Resolution Imaging Spectroradiometer (MODIS) daily land-surface temperature (LST) and a special daily melt product derived from the QuikSCAT (QS) scatterometer [2,3] show consistency in delineating the melt boundaries on a daily basis in the 2007 melt season [I], though some differences are identified. An assessment of maximum melt area for the 2007 melt shows that the QSCAT product detects a greater amount of melt (862,769 square kilometers) than is detected by the MODIS LST product (766,184 square kilometers). The discrepancy is largely because the QS product can detect both surface and near-surface melt and the QS product captures melt if it occurred anytime during the day while the MODIS product is obtained from a point in time on a given day. However on a daily bases, other factors influence the measurement of melt extent. In this work we employ the digital-elevation model of Bamber et al. [4] along with the National Centers for Environmental Prediction (NCEP) data to study some areas and time periods in detail during the 2007 melt season. We focus on times in which the QS and MODIS LST products do not agree exactly. We use NCEP and elevation data to analyze the atmospheric factors forcing the melt process, to gain an improved understanding of the conditions that lead to melt and melt persistence, and our ability to capture surface melt accurately using MODIS and QS data.

Hall, Dorothy K.↗

NASA NTRS2009

Multiplexing of Hot-Electron Nanobolometers Using Microwave SQUIDs

We have obtained the first data on the multiplexed operation of titanium hot-electron bolometers (HEB). Because of their low thermal conductance and small electron heat capacity nanobolometers are particularly interesting as sensors for far-infrared spectroscopy and mid- and near-IR calorimetry. However, the short time constant of these devices (approximately microseconds at 300-400 mK) makes time domain or audio-frequency domain multiplexing impractical. The Microwave SQUID (MSQUID) approach pursued in this work uses dc SQUIDs coupled to X-band microresonators which are, in turn, coupled to a transmission line. We used a 4-element array of Ti HEBs operated at 415 mK in a He3 dewar with an optical fiber access. The microwave signal exhibited 10-MHz wide resonances at individual MSQUD frequencies between 9 GHz and 10 GHz. The resonance depth is modulated by the current through the bolometer via a change of the SQUID flux state. The transmitted signal was amplified by a cryogenic amplifier and downconverted to baseband using an IQ mixer. A 1-dB per ??/2 responsivity was sufficient for keeping the system noise at the level of ~ 2 pA/Hz1/2. This is more than an order of magnitude smaller than phonon noise in the HEB. The devices were able to detect single near- IR photons (1550 nm) with a time constant of 3.5 ?s. Follow-on work will scale the array to larger size and will address the microwave frequency signal generation and processing using a digital transceiver.

microwave readout↗

NASA NTRS2016

Highly Uniform 150 mm Diameter Multichroic Polarimeter Array Deployed for CMB Detection

The Advanced Atacama Cosmology Telescope Polarimeter is an upgraded receiver for the Atacama Cosmology Telescope, which has begun making measurements of the small angular scale polarization anisotropies in the Cosmic Microwave Background using the first of four new multichroic superconducting detector arrays. Here, we review all details of the optimization and characterization of this first array, which features 2012 AlMn transition edge sensor bolometers operating at 150 and 230 GHz. We present critical temperatures, thermal conductivities,saturation powers, time constants, and sensitivities for the array. The results show high uniformity across the 150 mm wafer and good performance in the field.

Ho, Shuay-Pwu Patty↗

NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗

NASA NTRSDate not supplied

Laser Beam Welding Benchmark Experiments Performed in Reduced Gravity and Vacuum

Laser beam welding (LBW) is affected by the extreme temperatures, reduced pressure, and reduced gravity present in space environments. Gravity and pressure especially influence its melt pool and solidification dynamics. A compact, modular vacuum chamber adaptable to flight platforms from parabolic to orbital currently hosts an experiment to investigate the combined influence of reduced gravity and pressure on LBW. A swappable cartridge contains a rotating platen on which customizable workpieces can be welded under vacuum, greatly increasing experimental throughput. Instrumentation includes weld and thermal cameras observing the process, thermocouples placed on workpieces, accelerometers, and vacuum sensors. Experimental data gathered during the welding process will be combined with post-flight nondestructive evaluation, metallography, and mechanical testing to provide validation datasets for computational modeling. Phase I of this effort involves a parabolic flight campaign in low gravity while an anticipated Phase II would proceed to in-space demonstration to access extended duration microgravity.

in-space welding↗

NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗

NASA NTRSDate not supplied

Exploration Extravehicular Mobility Unit (xEMU) 11 Foot Vacuum Chamber Upgrades Test Results

The Exploration Extravehicular Mobility Unit (xEMU) uncrewed 11 foot vacuum chamber testing evaluated the capabilities of the 11 foot vacuum chamber facility to support advanced spacesuit testing. The government reference design xEMU spacesuit provided a high-fidelity test article to demonstrate 11 foot vacuum chamber capabilities which included: gas loading of the chamber at varying simulated metabolic rates and open loop suit abort operations, Intravehicular Activity (IVA) vacuum access, consumables recharge, IVA vehicle-provided thermal loop cooling, and IVA vehicle-provided power. To demonstrate the xEMU airlock operations transitioning from IVA to EVA conditions without a test subject in the suit, test support equipment was developed to remotely actuate both the Exploration, Servicing, and Cooling Umbilical (ESCU) and the vacuum access umbilical. This test also evaluated the performance of the Exploration Portable Life Support System (xPLSS) at vacuum conditions. Data was collected and analyzed for carbon dioxide (CO2) scrubbing performance of the Rapid Cycle Amine (RCA) swingbed, for thermal regulation performance of the Suit Water Membrane Evaporator (SWME), and for sensor performance across the xPLSS. This paper will detail the findings of the testing performed with these upgrades which discussed previously laid out in ICES-2025-342.

Robert F Marsch↗

NASA NTRSDate not supplied

Exploration Extravehicular Mobility Unit 11 Foot Vacuum Chamber Upgrades Test Results

Robert Marsch↗

DOE OSTI2021

Spectral Near-Infrared and Thermal Infrared Imaging for Advanced Estimation of Thermal and Geochemical Soil-Plant-Water Properties

Explore the source record for details and available documents.

09 BIOMASS FUELS↗

DOE OSTI2023

Physics-constrained fault diagnosis framework for monitoring a multi-component thermal hydraulic system

A method for diagnosing faults includes receiving a system description of a thermal hydraulic system, the system description indicating a plurality of components and sensors. The method also includes constructing, based on physical conservations laws and using the system description, a plurality of physics-based models for the plurality of components, each of the plurality of physics-based models including unknown parameters. The method further includes receiving historical measurements and calibrating the physics-based models by calculating the unknown parameters of each of the physics-based models using the historical measurements to produce calibrated models. The method also includes receiving sensor measurements of the sensors, and calculating residuals corresponding to differences between measurements predicted by the plurality of calibrated models and the sensor measurements. The method also includes determining, based on the calculated residuals, a fault of a component or a sensor, and generating an alert indicating the fault.

Nguyen, Tat Nghia↗

NASA NTRS1989

Solid state lasers for use in non-contact temperature measurements

The last decade has seen a series of dramatic developments in solid state laser technology. Prominent among these has been the emergence of high power semiconductor laser diode arrays and a deepening understanding of the dynamics of solid state lasers. Taken in tandem these two developments enable the design of laser diode pumped solid state lasers. Pumping solid state lasers with semiconductor diodes relieves the need for cumbersome and inefficient flashlamps and results in an efficient and stable laser with the compactness and reliability. It provides a laser source that can be reliably used in space. These new coherent sources are incorporated into the non-contact measurement of temperature. The primary focus is the development and characterization of new optical materials for use in active remote sensors of the atmosphere. In the course of this effort several new materials and new concepts were studied which can be used for other sensor applications. The general approach to the problem of new non-contact temperature measurements has had two components. The first component centers on passive sensors using optical fibers; an optical fiber temperature sensor for the drop tube was designed and tested at the Marshall Space Flight Center. Work on this problem has given insight into the use of optical fibers, especially new IR fibers, in thermal metrology. The second component of the effort is to utilize the experience gained in the study of passive sensors to examine new active sensor concepts. By active sensor are defined as a sensing device or mechanism which is interrogated in some way be radiation, usually from a laser. The status of solid state lasers as sources for active non-contact temperature sensors are summarized. Some specific electro-optic techniques are described which are applicable to the sensor problems at hand. Work on some of these ideas is in progress while other concepts are still being worked out.

Buoncristiani, A. M.↗

DOE OSTI2020

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗

DOE OSTI2021

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Reannealed Fiber Bragg Gratings Demonstrated High Repeatability in Temperature Measurements

Fiber Bragg gratings (FBGs) are formed by periodic variations of the refractive index of an optical fiber. These periodic variations allow an FBG to act as an embedded optical filter, passing the majority of light propagating through a fiber while reflecting back a narrow band of the incident light. The peak reflected wavelength of the FBG is known as the Bragg wavelength. Since the period and width of the refractive index variation in the fiber determines the wavelengths that are transmitted and reflected by the grating, any force acting on the fiber that alters the physical structure of the grating will change the wavelengths that are transmitted and reflected by it. Both thermal and mechanical forces acting on the grating will alter its physical characteristics, allowing the FBG sensor to detect both the temperature variations and the physical stresses and strains placed upon it. This ability to sense multiple physical forces makes the FBG a versatile sensor. To assess the feasibility of using Bragg gratings as temperature sensors for propulsion applications, researchers at the NASA Glenn Research Center evaluated the performance of Bragg gratings at elevated temperatures for up to 300 C. For these purposes, commercially available polyimide-coated high-temperature gratings were used that were annealed by the manufacturer to 300 C. To assure the most thermally stable gratings at the operating temperatures, we reannealed the gratings to 400 C at a very slow rate for 12 to 24 hr until their reflected optical powers were stabilized. The reannealed gratings were then subjected to periodic thermal cycling from room temperature to 300 C, and their peak reflected wavelengths were monitored. The setup shown is used for reannealing and thermal cycling the FBGs. Signals from the photodetectors and the spectrum analyzer were fed into a computer equipped with LabVIEW software. The software synchronously monitored the oven/furnace temperature and the optical spectrum analyzer as well as processed the data. Experimental results presented in the following graph show typical wavelength versus temperature dependence of a reannealed FBG through six thermal cycles (80 hr). The average standard deviation of the temperature-to-wavelength relationship ranged from 1.86 to 2.92 C over the six thermal cycles each grating was subjected to. This is an error of less than 1.0 percent of full scale throughout the entire evaluation temperature range from ambient to 300 C.

Adamovsky, Grigory↗

NASA NTRS2024

On-Orbit Spatial Performance Characterization for Thermal Infrared Imagers of Landsat 7, 8, and 9, ECOSTRESS and CTI

In this analysis of the spatial resolving power of thermal imagery products we focus on four satellite instruments that are used in research and applications, for example to monitor land surface temperature and derive evapotranspiration. These are thermal imagers on Landsat 7, Landsat 8, and Landsat 9, as well as the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). We compiled sets of close-in-time, day-time images of bridges surrounded by open water bodies, captured by each of the satellite imagers during cloud-free moments. Where possible, we also included some images captured by the Compact Thermal Imager (CTI), a technology demonstrator that was co-located with ECOSTRESS on the International Space Station in 2019. Bridges were found to provide a sufficient thermal contrast with the water surface to quantify the line-spread function of satellite-based thermal products. The full-width-at-half-max of a gaussian beam model fitted to this transect quantifies the on-orbit spatial resolution of different imagers. The results show some loss of spatial resolving power in the final product delivered to end-users as compared to the at-sensor characterization of spatial resolution. For Landsat 7, 8 and 9, the spatial resolution of the thermal bands is 1.5 times the ground sampling distance of 60 m and 100 m respectively. For the ECOSTRESS the difference is up to twice the sampling distance of 78 by 69 m2. Since spatial resolution is a main driver for instrument design it is important to understand and communicate this discrepancy between pre-flight design parameters and the characteristics of the surface imagery delivered to the user community. The goal of this research is to facilitate an improved fusion of current and future satellite observations into harmonized products with superior temporal and spatial characteristics.

thermal infrared↗