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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Utah FORGE: Sanvean Technologies Drilling Data from Well 16B(78)-32

Included here is Sanvean Technologies bit sensor data amalgamated with data from National Oilwell Varco's (NOV) BlackBox tool for Reed Hycalog bits used during drilling of Well 16B(78)-32. The dataset contains information collected at the bit while drilling including rate of penetration (ROP), top drive torque, and bit box temperature. The data was recorded at the bit box and top sub of the motor. RPM was measured by onboard gyro recording continuously in each sensor, and shock levels were also recorded on X, Y and Z axis. This data was merged with EDR in time format and saved in file sets (the zipped files) then output into CSV files. Please note: fields in the CSV files, such as the date field, may need to be formatted to display properly. There is an additional zipped folder in each dataset that is password protected. Sanvean GameChanger Viewer software must be used to view this password protected data. Information on how to use and download this free software is also included here.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Camp Fire processed Landsat 8 images, pre-fire, during-fire, post-fire

The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. GEE acquires L8 data products from USGS that include Real-Time Tier 1 DN values, representing scaled, calibrated at-sensor radiance, and Level-1 Precision Terrain (L1TP) processing. We carried out additional processing on the pre- and post-fire images, including an illumination correction to account for effects of steep topography, and radiometric normalization to ensure homogeneity between images. We also identified and processed high-quality images for both the pre-fire condition(25 Oct 2013), and the post-fire burn scar (26 Dec 2018). Using the tools we provided in the paper, we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management. A visualization app (sliderApp) that includes pre-fire, active fire, and post-fire images: https://caralyngorman.users.earthengine.app/view/camp-fire-sliding-map-3-9-19

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AmeriFlux US-MWW Allegan Wetland

This is the AmeriFlux version of the carbon flux data for the site US-MWW Allegan Wetland. Site Description - Privately owned and managed wetland along the Rabbit River, a tributary to the Kalamazoo River. Land owner controls water level at site. Sensors are at the edge of open water and emergent vegetation, with wet forests surrounding the wetland. Site was chosen to represent managed wetlands along the Kalamazoo River watershed.

Chen, Jiquan↗
NASA NTRS1977

Magnetic field experiment for Voyagers 1 and 2

The magnetic field experiment to be carried on the Voyager 1 and 2 missions consists of dual low field (LFM) and high field magnetometer (HFM) systems. The dual systems provide greater reliability and, in the case of the LFM's, permit the separation of spacecraft magnetic fields from the ambient fields. Additional reliability is achieved through electronics redundancy. The wide dynamic ranges of plus or minus 0.5G for the LFM's and plus or minus 20G for the HFM's, low quantization uncertainty of plus or minus 0.002 gamma in the most sensitive (plus or minus 8 gamma) LFM range, low sensor RMS noise level of 0.006 gamma, and use of data compaction schemes to optimize the experiment information rate all combine to permit the study of a broad spectrum of phenomena during the mission. Planetary fields at Jupiter, Saturn, and possibly Uranus; satellites of these planets; solar wind and satellite interactions with the planetary fields; and the large-scale structure and microscale characteristics of the interplanetary magnetic field are studied. The interstellar field may also be measured.

Behannon, K. W.↗
NASA NTRS1978

Monitoring systems for community water supplies

Water monitoring system includes equipment and techniques for waste water sampling sensors for determining levels of microorganisms, oxygen, chlorine, and many other important parameters. System includes data acquisition and display system that allows computation of water quality information for real time display.

Taylor, R. E.↗
NASA NTRS1987

Evaluation of a dual processor implementation for a fault inferring nonlinear detection system

The design of a modified fault inferring nonlinear detection system (FINDS) algorithm for a dual-processor configured flight computer is described. The algorithm was changed in order to divide it into its translational dynamics and rotational kinematics and to use it for parallel execution on the flight computer. The FINDS consists of: (1) a no-fail filter (NFF), (2) a set of test-of-mean detection tests, (3) a bank of first order filters to estimate failure levels in individual sensors, and (4) a decision function. NFF filter performance using flight recorded sensor data is analyzed using a filter autoinitialization routine. The failure detection and isolation capability of the partitioned algorithm is evaluated. A multirate implementation for the bias-free and bias filter gain and covariance matrices is discussed.

Godiwala, P. M.↗
NASA NTRS1987

The sensing and perception subsystem of the NASA research telerobot

A useful space telerobot for on-orbit assembly, maintenance, and repair tasks must have a sensing and perception subsystem which can provide the locations, orientations, and velocities of all relevant objects in the work environment. This function must be accomplished with sufficient speed and accuracy to permit effective grappling and manipulation. Appropriate symbolic names must be attached to each object for use by higher-level planning algorithms. Sensor data and inferences must be presented to the remote human operator in a way that is both comprehensible in ensuring safe autonomous operation and useful for direct teleoperation. Research at JPL toward these objectives is described.

Wilcox, B.↗
NASA NTRS2005

Semiautomated, Reproducible Batch Processing of Soy

A computer-controlled apparatus processes batches of soybeans into one or more of a variety of food products, under conditions that can be chosen by the user and reproduced from batch to batch. Examples of products include soy milk, tofu, okara (an insoluble protein and fiber byproduct of soy milk), and whey. Most processing steps take place without intervention by the user. This apparatus was developed for use in research on processing of soy. It is also a prototype of other soy-processing apparatuses for research, industrial, and home use. Prior soy-processing equipment includes household devices that automatically produce soy milk but do not automatically produce tofu. The designs of prior soy-processing equipment require users to manually transfer intermediate solid soy products and to press them manually and, hence, under conditions that are not consistent from batch to batch. Prior designs do not afford choices of processing conditions: Users cannot use previously developed soy-processing equipment to investigate the effects of variations of techniques used to produce soy milk (e.g., cold grinding, hot grinding, and pre-cook blanching) and of such process parameters as cooking times and temperatures, grinding times, soaking times and temperatures, rinsing conditions, and sizes of particles generated by grinding. In contrast, the present apparatus is amenable to such investigations. The apparatus (see figure) includes a processing tank and a jacketed holding or coagulation tank. The processing tank can be capped by either of two different heads and can contain either of two different insertable mesh baskets. The first head includes a grinding blade and heating elements. The second head includes an automated press piston. One mesh basket, designated the okara basket, has oblong holes with a size equivalent to about 40 mesh [40 openings per inch (.16 openings per centimeter)]. The second mesh basket, designated the tofu basket, has holes of 70 mesh [70 openings per inch (.28 openings per centimeter)] and is used in conjunction with the press-piston head. Supporting equipment includes a soy-milk heat exchanger for maintaining selected coagulation temperatures, a filter system for separating okara from other particulate matter and from soy milk, two pumps, and various thermocouples, flowmeters, level indicators, pressure sensors, valves, tubes, and sample ports

Thoerne, Mary↗
NASA NTRS2016

In-Flight Calibration Methods for Temperature-Dependent Offsets in the MMS Fluxgate Magnetometers

During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection↗
NASA NTRS2017

In-Flight Calibration of the MMS Fluxgate Magnetometers

We present an overview of the approach to in-flight calibration, which is a coordinated effort between the University of California Los Angeles (UCLA), Space Research Institute, Graz, Austria (IWF) and the NASA Goddard Space Flight Center (GSFC). We present details of the calibration effort at GSFC. During the first dayside season of the Magnetospheric Multiscale (MMS) mission, the in-flight calibration process for the Fluxgate magnetometers (FGM) implemented an algorithm that selected a constant offset (zero-level) for each sensor on each orbit. This method was generally able to reduce the amplitude of residual spin tone to less than 0.2 nT within the region of interest. However, there are times when the offsets do show significant short-term variations. These variations are most prominent in the nighttime season (phase 1X), when eclipses are accompanied by offset changes as large as 1 nT. Eclipses are followed by a recovery period as long as 12 hours where the offsets continue to change as temperatures stabilize. Understanding and compensating for these changes will become critical during Phase 2 of the mission in 2017, when the nightside will become the focus of MMS science. Although there is no direct correlation between offset and temperature, the offsets are seen for the period of any given week to be well-characterized as function of instrument temperature. Using this property, a new calibration method has been developed that has proven effective in compensating for temperature-dependent offsets during phase 1X of the MMS mission and also promises to further refine calibration quality during the dayside season.

Magnetic field reconnection↗
NASA NTRS2020

A Simulation Framework for Precision Landing and Hazard Avoidance Technology Assessments

To meet NASA’s challenge to return humans to the Moon in 2024 and establish a sustainable presence in 2028 requires advances in autonomous spacecraft navigation. The Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project, which leverages previous work at NASA to develop multi-mission precision landing and hazard avoidance technologies, is using a multi-faceted approach to achieve the advanced landing requirements. In addition to increasing the technology readiness level of key sensors and developing high performance space computing, SPLICE uses simulations to determine navigation requirements and evaluate sensor performance. The effort evaluates various precision landing concepts of operations, not only for the lunar human and robotic missions, but also for potential missions to other solar system destinations. This paper summarizes the six degree-of-freedom high fidelity simulation framework, trajectory design methodology, and sensor models being considered for a variety of precision lander missions. Initial results of the navigation sensor performance for a human Mars mission are presented. Finally, trade and sensitivity studies are outlined for future work to fully characterize sensor performance assumptions and modifications required to achieve precision landing and hazard avoidance.

Alicia Dwyer Cianciolo↗
DOE OSTI2020

Completion design improvement using a deep convolutional network

Maximizing stimulated natural and hydraulic fracture network is one of the primary hydraulic fracturing concerns for economic production from a horizontal shale gas well. Geomechanical facies and preexisting fractures in each stage are identified based on similarities in formation characteristics to optimize the locations of perforation clusters. This often requires analyzing large volumes of drilling, Logging While Drilling (LWD) and Measurement While Drilling (MWD) data. In this paper, we develop a methodology that calculates the mechanical specific energy (MSE) using real-time drill string acceleration signals directly from its definition. High resolution vibration signals have been collected using a tri-axial accerlometer, which was an auxiliary tool included in acoustic borehole imager. This technique provides a cost-efficient solution for engineered completion design. Furthermore, we adopt deep Convolutional Neural Network (CNN) with signal processing to build a data pipeline that effectively extracts patterns from dynamic acceleration signals for rock lateral MSE classification. First, we apply discrete wavelet transform and Short-Time Fourier Transform (STFT) for signal denoising and pattern recognition. Then we construct an image dataset using multi-scale image fusion at pixel level from 3 sensor channels, including axial, lateral acceleration spectrograms and zero-padded revolutions per minute (RPM). The resulted RGB image dataset includes 4,000 images of 5 MSE ranges with various rock strength conditions. Our results demonstrate that the proposed deep learning model can achieve more than 90% classification accuracy. The deep learning results, as a reference source, were applied in selected Marcellus Shale Energy and Environmental Lab (MSEEL) wells engineered completion located in the Marcellus shale gas site.

03 NATURAL GAS↗
NASA NTRS2010

Fiber-Optic Continuous Liquid Sensor for Cryogenic Propellant Gauging

An innovative fiber-optic sensor has been developed for low-thrust-level settled mass gauging with measurement uncertainty <0.5 percent over cryogenic propellant tank fill levels from 2 to 98 percent. The proposed sensor uses a single optical fiber to measure liquid level and liquid distribution of cryogenic propellants. Every point of the sensing fiber is a point sensor that not only distinguishes liquid and vapor, but also measures temperature. This sensor is able to determine the physical location of each point sensor with 1-mm spatial resolution. Acting as a continuous array of numerous liquid/vapor point sensors, the truly distributed optical sensing fiber can be installed in a propellant tank in the same manner as silicon diode point sensor stripes using only a single feedthrough to connect to an optical signal interrogation unit outside the tank. Either water or liquid nitrogen levels can be measured within 1-mm spatial resolution up to a distance of 70 meters from the optical interrogation unit. This liquid-level sensing technique was also compared to the pressure gauge measurement technique in water and liquid nitrogen contained in a vertical copper pipe with a reasonable degree of accuracy. It has been demonstrated that the sensor can measure liquid levels in multiple containers containing water or liquid nitrogen with one signal interrogation unit. The liquid levels measured by the multiple fiber sensors were consistent with those virtually measured by a ruler. The sensing performance of various optical fibers has been measured, and has demonstrated that they can survive after immersion at cryogenic temperatures. The fiber strength in liquid nitrogen has also been measured. Multiple water level tests were also conducted under various actual and theoretical vibration conditions, and demonstrated that the signal-to-noise ratio under these vibration conditions, insofar as it affects measurement accuracy, is manageable and robust enough for a wide variety of spacecraft applications. A simple solution has been developed to absorb optical energy at the termination of the optical sensor, thereby avoiding any feedback to the optical interrogation unit

Xu. Wei↗
NASA NTRS2012

Dynamic Range and Sensitivity Requirements of Satellite Ocean Color Sensors: Learning from the Past

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

chlorophyll fluorescence↗
NASA NTRS1990

Flight test results of failure detection and isolation algorithms for a redundant strapdown inertial measurement unit

Flight test results for two sensor fault-tolerant algorithms developed for a redundant strapdown inertial measurement unit are presented. The inertial measurement unit (IMU) consists of four two-degrees-of-freedom gyros and accelerometers mounted on the faces of a semi-octahedron. Fault tolerance is provided by edge vector test and generalized likelihood test algorithms, each of which can provide dual fail-operational capability for the IMU. To detect the wide range of failure magnitudes in inertial sensors, which provide flight crucial information for flight control and navigation, failure detection and isolation are developed in terms of a multi level structure. Threshold compensation techniques, developed to enhance the sensitivity of the failure detection process to navigation level failures, are presented. Four flight tests were conducted in a commercial transport-type environment to compare and determine the performance of the failure detection and isolation methods. Dual flight processors enabled concurrent tests for the algorithms. Failure signals such as hard-over, null, or bias shift, were added to the sensor outputs as simple or multiple failures during the flights. Both algorithms provided timely detection and isolation of flight control level failures. The generalized likelihood test algorithm provided more timely detection of low-level sensor failures, but it produced one false isolation. Both algorithms demonstrated the capability to provide dual fail-operational performance for the skewed array of inertial sensors.

Morrell, F. R.↗
NASA NTRS2011

Intelligent Wireless Sensor Networks for System Health Monitoring

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.

networks↗
DOE OSTI2025

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Investigation into the Development and Testing of a Simplex Capacitance Sensor for Rotor Tip Clearance Measurement in Turbo Machinery

The rotor tip clearance is a vital parameter to characterize turbomachinery performance. It is an essential measurement during engine development and testing. The efficiency of the major modules like fan, compressor and turbine depends on the optimum running clearances. The capacitive sensor is preferred for tip clearance measurements because of various inherent advantages. They are fabricated through complex processes for turbomachinery application and are expensive. These sensors are exposed to harsh engine environments and are likely to exhibit degraded performance. Insulation failure at sensing head, connector contamination and micro-cracks in the MI (Mineral Insulated) cable leads to noise in the signal output. Frequent mechanical failures are also seen due to work hardening of MI cables, lead connector detachments and failure of micro fins at interconnects. Fault fixing of these is tedious and very expensive. This paper presents the concerted effort in developing a simple capacitance sensor addressing potential sensor failure issues. The design features include simple construction, ease of sensor assembly, component realization and troubleshooting. The design also addresses all safety requirements. The sensor has a large sensing area (7.6 mm diameter) producing very stable, high-level signal. The developed sensor produces output that varies from 1 V{sub P-P} to 11 V{sub P-P} for blade-tip gaps between 3 mm to 0.4 mm respectively. Blade pass simulation studies across the sensor, display almost flat response at minimum clearance. This feature results in very minimal data acquisition errors. The sensor along with RC (Resistance-Capacitance) conditioning electronics was successfully used for clearance measurement on fan stage of gas turbine engine. Test results are in line with the predictions. Extensive tip clearance measurements on the engine validate the design. The current work provides an insight into the development of a simplex capacitance sensor for tip clearance measurement.

42 ENGINEERING↗