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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 289 records · Page 16

Non-Contact Stiffness Measurement of a Suspended Single Walled Carbon Nanotube Device

A new nanoscale electric field sensor was developed for studying triboelectric charging in terrestrial and Martian dust devils. This sensor is capable to measure the large electric fields for large dust devils without saturation. However, to quantify the electric charges and the field strength it is critical to calibrate the mechanical stiffness of the sensor devices. We performed a technical feasibility study of the Nano E-field Sensor stiffness by a non-contact stiffness measurement method. The measurement is based on laser Doppler vibrometer measurement of the thermal noise due to energy flunctuations in the devices. The experiment method provides a novel approach to acquire data that is essential in analyzing the quantitative performance of the E-field Nano Sensor. To carry out the non-contact stiffness measurement, we fabricated a new Single-Walled Carbon Nanotube (SWCNT) E-field sensor with different SWCNTs suspension conditions. The power spectra of the thermal induced displacement in the nano E-field sensor were measured at the accuracy of picometer. The power spectra were then used to derive the mechanical stiffness of the sensors. Effect of suspension conditions on stiffness and sensor sensitivty was discussed. After combined deformation and resistivity measurement, we can compare with our laboratory testing and field testing results. This new non-contact measurement technology can also help to explore to other nano and MEMS devices in the future.

Zheng, Yun↗

Summary of flight performance of the Skylab Earth Resources Experiment Package /EREP/

A group of six remote sensor systems (sensing visible, infrared, and microwave radiation) known as the Earth Resources Experiment Package (EREP) was flown on the NASA Skylab spacecraft to furnish data to numerous investigators in the earth sciences and in technology assessment. Inflight sensor performance in three categories (functional, geometric, and radiometric) was evaluated using: (1) ground measurements of surface, atmospheric, and illumination parameters; (2) ground deployment and operation of microwave receivers and transponders to monitor and excite the active EREP sensors; (3) measurement of surface and atmospheric parameters by instrumented aircraft on underflights of Skylab passes; and (4) analysis of the actual flight data. This resulted in identification and correction of anomalous sensor operation, quantization of geometric distortions or aberrations, improvement or confirmation of calibrations, and determination of sensitivity, accuracy, and stability of the sensors.

Potter, A. E.↗

NASA SPLICE Project: Development and Testing of Precision Landing GN&C Technologies

NASA's technology advancement needs for entry, descent and landing call for high-precision, high-rate sensors that can improve navigation accuracy and vehicle control performance. Higher landing accuracy is required for any future human lander missions, and likely, for most robotic missions 1,2. Sensors and algorithms that significantly reduce navigation errors and can image the local terrain will enable landing at locations of high scientific interest that would otherwise pose significant risk to the vehicle. The Safe and Precise Landing-Integrated Capabilities Evolution project, or SPLICE, is developing precision landing and hazard avoidance (PL&HA) technologies for NASA and for potential commercial space flight missions. SPLICE technologies include sensors, algorithms, advanced space flight computing capabilities, and simulation tools used to integrate and study guidance, navigation, and control (GN&C) system performance. SPLICE efforts include hardware-in-the-loop (HWIL) simulation testing, ground testing, and flight testing, including reuse of hardware from the CoOperative Blending of Autonomous Landing Technologies (COBALT) suborbital flight-test payload3,4. Two of the precise navigation sensors that are being developed and matured within SPLICE are LiDARs. Since 2006, NASA Langley has been developing a Navigation Doppler LiDAR (NDL) for precise velocity measurements, and SPLICE is building an NDL engineering test unit (ETU) that will be brought up to TRL 6 following environmental and high-speed1,2 testing. NASA Goddard is developing a Hazard Detection LiDAR (HD LiDAR) engineering development unit (EDU) for SPLICE that has relevance to future human and robotic lander missions. The HD LiDAR will be flight test and matured to TRL 5.

Restrepo, Carolina I.↗

Calibrating a 3-Axis Accelerometer Instrument with a Less Accurate Calibration Device Part 1: Mathematical Methodology

A three-axis accelerometer instrument (3xAI) can provide the angular attitude of a 3D object using the gravity vector (g) as the sole reference. Calibrating such an instrument requires placing it at known (to some accuracy plus uncertainty) angular articulations with respect to g. This paper will show a potential process for calibrating a 3xAI by using a 2-axis rotary system (calibration device) to provide these articulations. Any calibration device (CD) with such capacity will contain internal misalignments. These misalignments, even if made relatively small or approximated to zero in the kinematics model (KM), can be detrimental to the calibration of the instrument when high measurement accuracy is required. This is especially true if the selected set of articulations chosen for calibration do not include their symmetrical counterpoints (a point where the misalignment has equal magnitude but is opposite in direction to a point chosen). The consequence of not including the combination, point and counterpoint, for any misalignment involved in the calibration, results in a biased instrument. This paper will demonstrate a calibration of the instrument using symbolic math resulting in a closed-form solution of the instrument coefficients. The main objective is to show the impact of all the CD misalignments to the instrument coefficients. This process is the basis for a more sophisticated method (shown in a future paper) for obtaining the instrument coefficients while simultaneously obtaining an estimate of the calibration device internal misalignments.

Angle↗

Study of a Proposed Infrared Horizon Scanner for Use in Space-Orientation Control Systems

An attitude-sensing device for space vehicles which detects the thermal radiation discontinuity at opposite horizons of a planetary body to produce an attitude error signal is described. The planetary body may be the Earth, its Moon, Mars, or Venus. The sensor is expected to have an accuracy of 0.25 degrees for the Earth, a long continuous operating lifetime, a wide altitude range, a wide capture capability, and an inherent ability to produce signals indicating vehicle altitude. An experimental model incorporating many of the features of the proposed sensor indicates that the proposed sensor will be low in weight, volume, and power consumption. The sensor's altitude range, accuracy, lifetime, and sensitivity to radiation from the Moon and planets are discussed.

INFRARED HORIZON SCANNER↗

Improved guided-wave acoustic defect detection and localization in pipes under varying temperature conditions using deep learning

Early defect detection in pipelines is critical across industries, particularly in the oil and gas sector, where failures result in significant maintenance costs and operational disruptions. Acoustic guided-wave techniques are widely used for nondestructive evaluation of pipeline defects due to their long-distance propagation capability. However, environmental variations, sensitivity limitations, and complex signal interpretation challenges limit the effectiveness of traditional signal processing approaches with guided-wave signals. Recent advances in deep learning methods have demonstrated remarkable success in solving complex real-world problems in many fields. In particular, deep-learning-based signal processing holds substantial promise to overcome limitations and challenges of conventional signal processing. This study presents a deep learning framework for pipeline inspection using acoustic guided-wave signals under temperature varying environments. The proposed framework employs a dual-path one-dimensional convolutional autoencoder that combines defect detection, localization, and temperature prediction functions. The proposed system utilizes multi-mode and broadband acoustic waves with an optimized number of sensors that provide high accuracy while retaining practical simplicity. Experimental validation is performed on a carbon steel pipe. The results indicate exceptional defect detection accuracy and precise defect localization with a mean absolute error of 66 mm. The proposed technique also predicts the effective average temperature of the pipe with a mean absolute error of 0.2°C. Comparative analysis shows superior performance of the proposed method over a traditional method previously developed by the authors' team. These results highlight the potential of integrating deep learning methods into guided-wave pipeline inspection systems to improve reliability under varying environmental conditions.

42 ENGINEERING↗

Hydrogen Mitigation Process Testing at Nevada Solar One

The National Renewable Energy Laboratory (NREL) and Acciona Solar Power (ASP) developed and installed a process that addresses the issue of hydrogen buildup in Acciona's Nevada Solar One power plant. Our method selectively removes hydrogen from the expansion tanks of the power plant to control hydrogen levels in the circulating heat-transfer fluid (HTF). During previous work, we developed a sensor that measures hydrogen partial pressure in the expansion-tank headspace gas. We demonstrated that our sensor measures hydrogen levels over a wide range of partial pressure from 10 mbar down to 0.003 mbar. More recently, we conceived and developed an integrated process module that performs both hydrogen sensing and separating functions. The sensor/separator measures hydrogen partial pressure in the headspace gas in the same way as our original sensor design. Additionally, the integrated module separates hydrogen from the headspace gas to reduce hydrogen to the level needed to maintain the performance of receivers in the collector field. Laboratory testing at NREL showed that the sensor function had an accuracy of +/-7%, and the hydrogen extraction rate for separator function was consistent with our modeling predictions. The primary benefit of this module is its simple design, both in terms of function and incorporation into the HTF subsystem of the power plant. Most recently, NREL and ASP completed installation and initial testing of a mitigation process at ASP's Nevada Solar One power plant in Boulder City, Nevada. In this paper, we report on the completed installation, initial testing, and plans to bring the process to full automation, so that it can be operated unattended on a daily schedule.

chemical elements↗

Robust two-colour pyrometry uncertainty analysis to acquire spatially-resolved measurements

Two-colour pyrometry (2CP) has been used over several decades to study engine-relevant combustion processes, but results are generally regarded as qualitative or semi-quantitative. In many current 2CP systems, large measurement errors are introduced by parallax because the two measured wavelengths are not from the same line of sight. Here this work presents a spatially-resolved 2CP system with the objective of quantifying and reducing measurement uncertainty. An optical setup that eliminates parallax in 2CP is used together with pixel-by-pixel calibration of the camera sensor to increase measurement accuracy. Primary uncertainty terms are identified, and an error propagation analysis is performed to compute uncertainties in the final results of soot temperature, soot concentration parameter, KL, and soot mass. These methodologies are applied to investigate an auto-igniting fuel spray in a constant pressure flow rig at diesel-like conditions of high ambient pressure and temperature. Results show bias uncertainty of around 200 K (≈10%) for temperature and about 40%–60% for KL. High uncertainty was found to occur on the diffusion flame front where both optical thickness and soot concentrations are small. However, these uncertain measurement zones with relatively low soot concentrations contribute minimally to the total soot mass present in the reacting jet during the temporal evolution of the flame.

42 ENGINEERING↗

Evaluating the Accuracy of Various Irradiance Models in Detecting Soiling of Irradiance Sensors

We evaluate the feasibility of using various clear-sky models or purchased satellite data for estimating the soiling of a reference cell irradiance sensor. We find results to be more accurate for models that consider local meteorological conditions. We conclude that given the data sets considered, and depending on the requirements of the data analyst, choosing to use purchased satellite irradiance data from Solargis to estimate the soiling of a reference cell sensor tends to yield more accurate results, although there are instances where a clear-sky model performs better. The SOLIS clear-sky model in PVLIB with variable P wat provided useful soiling results, implying that the general method of using a clear-sky model with local meteorological data may provide a low-cost tool for detecting soiling of irradiance sensors.

14 SOLAR ENERGY↗

Cyber-Attack Detection for Photovoltaic Farms Based on Power-Electronics-Enabled Harmonic State Space Modeling

Here in this paper, a physics-data-based detection method is proposed to detect a variety of cyber-attacks in Photovoltaic (PV) farms using the power electronics-enabled harmonic state space (HSS) models, which, to our knowledge, is original. At the device level, HSS-based detection is developed to monitor harmonic vectors of individual PV converter with minimum sensor measurements, thus improving accuracy and robustness compared to Kalman Filter-based detection. At the system level that involves multiple PV converters, a clustering approach is developed to investigate attack propagation and accurately locate attack sources within a PV farm. The proposed approach is one of the first attempts to address PV security through interaction between the device and system, maximizing the accuracy and robustness at different levels. To verify the feasibility, a comprehensive attacks model is built, including single attack, coordinated attacks, and replay attacks. Besides, the impacts of irradiance changes are taken into consideration in the test scenarios. With the real-time data acquisition and hardware-in-the-loop testbed, comprehensive test results are provided to verify the feasibility of the proposed detection methodology.

42 ENGINEERING↗

On optimizing the sensor spacing for pressure measurements on wind turbine airfoils

This research article presents a robust approach to optimizing the layout of pressure sensors around an airfoil. A genetic algorithm and a sequential quadratic programming algorithm are employed to derive a sensor layout best suited to represent the expected pressure distribution and, thus, the lift force. The fact that both optimization routines converge to almost identical sensor layouts suggests that an optimum exists and is reached. By comparing against a cosine-spaced sensor layout, it is demonstrated that the underlying pressure distribution can be captured more accurately with the presented layout optimization approach. Conversely, a 39 %–55 % reduction in the number of sensors compared to cosine spacing is achievable without loss in lift prediction accuracy. Given these benefits, an optimized sensor layout improves the data quality, reduces unnecessary equipment and saves cost in experimental setups. While the optimization routine is demonstrated based on the generic example of the IEA 15 MW reference wind turbine, it is suitable for a wide range of applications requiring pressure measurements around airfoils.

17 WIND ENERGY↗

Study to develop gradiometer techniques

The primary goal of the current gravity gradiometer research at Stanford has been to establish the feasibility of using a gravity gradiometer with 1 E accuracy, as the primary sensor in various applications. The two applications considered here in detail are geodesy missions and inertial navigation systems. Preliminary sections on gravity models and gravity gradiometer bias estimation are also included.

Schaechter, D.↗

Studies of radiative transfer in the earth's atmosphere with emphasis on the influence of the radiation budget in the joint institute for advancement of flight sciences at the NASA-Langley Research Center

Earth and solar radiation budget measurements were examined. Sensor calibration and measurement accuracy were emphasized. Past works on the earth's radiation field that must be used in reducing observations of the radiation field were reviewed. Using a finite difference radiative transfer algorithm, models of the angular and spectral dependence of the earth's radiation field were developed.

Source record↗

Surface accuracy measurement system deployable reflector antennas

Conceptual optical sensor configurations for measuring the surface deformations of large, deployable space antennas are described. These antennas include precision deployable reflectors up to 30 meters diameter and 1000 GHz frequency and mesh deployable reflectors up to 100 meters diameter and 30 GHz frequency. For each representative antenna configuration, the surface deformation sensor provides continuous, real-time measurements at a sufficient number of sample points to be compatible with active surface control. Moreover, the sensor system does not interfere with the mechanical or microwave characteristics of either the antenna surface or the feed. For the applications considered, the sensor system consists of a central receiver ring containing six to ten long focal length, angle measuring instruments, each viewing a dedicated set of bright point targets at the antenna. The targets, either light emitting diodes or illuminated retroreflectors, are modulated to eliminate errors from spurious backgrounds. Very preliminary performance estimates indicate that the sensor system, using commerical grade components, can produce a 20th to a 30th wavelength accuracy (3 sigma).

Neiswander, R. S.↗

Programmable charge-coupled device /CCD/ correlator for pattern classification

The potential use of charge coupled device (CCD) programmable digital/analog correlators for multispectral data classification is discussed. CCD digital/analog correlator technology and the experimental evaluation of a 32-stage 4-bit test device are presented. The design of an IC for use in a multispectral classification system for 16 sensors and 8 bit accuracy is reviewed.

Mayer, D. J.↗

Three-axis attitude determination from vector observations

Two computationally efficient algorithms are presented for determining three-axis attitude from two or more vector observations. The first of these, the TRIAD algorithm, provides a deterministic (i.e., nonoptimal) solution for the attitude based on two vector observations. The second, the QUEST algorithm, is an optimal algorithm which determines the attitude that achieves the best weighted overlap of an arbitrary number of reference and observation vectors. Analytical expressions are given for the covariance matrices for the two algorithms using a fairly realistic model for the measurement errors. The mathematical relationship of the two algorithms and their relative merits are discussed and numerical examples are given. The advantage of computing the covariance matrix in the body frame rather than in the inertial frame (e.g., in terms of Euler angles) is emphasized. These results are valuable when a single-frame attitude must be computed frequently. They will also be useful to the mission analyst or spacecraft engineer for the evaluation of launch-window constraints or of attitude accuracies for different attitude sensor configurations.

Shuster, M. D.↗

The conical scanner evaluation system design

The software design for the conical scanner evaluation system is presented. The purpose of this system is to support the performance analysis of the LANDSAT-D conical scanners, which are infrared horizon detection attitude sensors designed for improved accuracy. The system consists of six functionally independent subsystems and five interface data bases. The system structure and interfaces of each of the subsystems is described and the content, format, and file structure of each of the data bases is specified. For each subsystem, the functional logic, the control parameters, the baseline structure, and each of the subroutines are described. The subroutine descriptions include a procedure definition and the input and output parameters.

Cumella, K. E.↗

LANDSAT-4 evaluation program and scientific characterization activities

The characterization objectives of the LANDSAT 4 Science Office at GSFC are to: (1) determine the accuracy and precision of sensor and spacecraft performance, image data quality, and derived information; (2) recommend LANDSAT 4 system improvements; and (3) communicate results to the research community. In-house activities are directed toward full access and utilization of the prelaunch and in-orbit engineering test data on the sensor and spacecraft. Principle scientists in remote sensing are involved as part of a major scientific characterization effort, and workshops were held for these investigative teams. A symposium is scheduled prior to turnover of the TM to NOAA.

Barker, J. L.↗