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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 253 records · Page 14

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-ofattack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Suh, Peter M.↗

NASA NTRS2013

Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors

A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-of-attack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.

Modal Filter↗

NASA NTRS1994

TOPEX/POSEIDON microwave radiometer performance and in-flight calibration

Results of the in-flight calibration and performance evaluation campaign for the TOPEX/POSEIDON microwave radiometer (TMR) are presented. Intercomparisons are made between TMR and various sources of ground truth, including ground-based microwave water vapor radiometers, radiosondes, global climatological models, special sensor microwave imager data over the Amazon rain forest, and models of clear, calm, subpolar ocean regions. After correction for preflight errors in the processing of thermal/vacuum data, relative channel offsets in the open ocean TMR brightness temperatures were noted at the approximately = 1 K level for the three TMR frequencies. Larger absolute offsets of 6-9 K over the rain forest indicated a approximately = 5% gain error in the three channel calibrations. This was corrected by adjusting the antenna pattern correction (APC) algorithm. AS 10% scale error in the TMR path delay estimates, relative to coincident radiosondes, was corrected in part by the APC adjustment and in part by a 5% modification to the value assumed for the 22.235 FGHz water vapor line strength in the path delay retrieval algorithm. After all in-flight corrections to the calibration, TMR global retrieval accuracy for the wet tropospheric range correction is estimated at 1.1 cm root mean square (RMS) with consistent peformance under clear, cloudy, and windy conditions.

Ruf, C. S.↗

NASA NTRS1986

The National Transonic Facility

The National Transonic Facility, NTF, is a high Reynolds Number facility where the increase in Reynolds Number is obtained by operating at high pressures and low temperatures. Liquid nitrogen is allowed to vaporize, making gaseous nitrogen the test medium with temperatures extending down to approximately 100 degrees Kelvin. These factors have created unique, new challenges to those developing sensors and instrumentation. Pressure vessels, thermal enclosures or elaborate temperature compensations schemes, are needed for environmental protection and special materials are needed for sensors and model fabrication. The need for a new measurement, model deformation, was also created. An extensive program to develop the unique sensors and instrumentation was initiated. The data acquisition system and systems to measure aerodynamic forces and pressures, model attitude, and model deformation, are discussed.

Holmes, H. K.↗

NASA NTRS1979

Wind-tunnel investigation of the flow correction for a model-mounted angle of attack sensor at angles of attack from -10 deg to 110 deg

A preliminary wind tunnel investigation was undertaken to determine the flow correction for a vane angle of attack sensor over an angle of attack range from -10 deg to 110 deg. The sensor was mounted ahead of the wing on a 1/5 scale model of a general aviation airplane. It was shown that the flow correction was substantial, reaching about 15 deg at an angle of attack of 90 deg. The flow correction was found to increase as the sensor was moved closer to the wing or closer to the fuselage. The experimentally determined slope of the flow correction versus the measured angle of attack below the stall angle of attack agreed closely with the slope of flight data from a similar full scale airplane.

Moul, T. M.↗

DOE OSTI2025

Designing an Optimal Sensor Network via Minimizing Information Loss

Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the placement of sensors to monitor spatiotemporal processes, explicitly accounting for the temporal dimension in our modeling and optimization. We observe that recent advancements in computational sciences often yield large datasets based on physics-based simulations, which are rarely leveraged in experimental design. We introduce a novel model-based sensor placement criterion, along with a highly-efficient optimization algorithm, which integrates physics-based simulations and Bayesian experimental design principles to identify sensor networks that “minimize information loss” from simulated data. Our technique relies on sparse variational inference and (separable) Gauss-Markov priors, and thus may adapt many techniques from Bayesian experimental design. We validate our method through a case study monitoring air temperature in Phoenix, Arizona, using state-of-the-art physics-based simulations. Our results show our framework to be superior to random or quasi-random sampling, particularly with a limited number of sensors. We conclude by discussing practical considerations and implications of our framework, including more complex modeling tools and real-world deployments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Miniature flow-direction and airspeed sensor for airplanes and radio controlled models in spin studies

A miniature flow direction and airspeed sensor was developed for use on 1/10- to 1/15 scale models and on full-scale airplanes engaged in spin research. The range of flow angles encountered in spinning flight (+ or - 120 degrees in angle of attack and + or - 55 degrees in sideslip) is larger than that of normal flight. These angles, along with an effective airspeed range of 9 to 90 m/sec, were measured with static accuracies of + or - 0.35 degrees for angle of attack, + or - 0.25 degrees for sideslip angle, and + or - 1 m/sec for airspeed. The dynamic accuracy is adequate to measure the rapidly changing flow angles and airspeed without singificant distortion. The sensor is rugged enough to withstand both the airplane environment and that of the radio-controlled, unpowered models.

Kershner, D. D.↗

DOE OSTI2024

Machine learning models of intermittent operation of RO wellhead water treatment for salinity reduction and nitrate removal

Machine learning models were developed for intermittent multi-mode operation of a wellhead reverse osmosis water purification and desalination system to predict salt passage, nitrate passage, and permeate flux. The models, based on long short-term memory (LSTM) recurrent neural network (RNN) architecture, included an attention mechanism to increase model performance in proximity of the regulatory limit for nitrate. Training and testing of the models for the Startup, Production, Shutdown and Flushing operational modes were based on operational data (consisting of 22 process variables per data sample) acquired every 2–5 s over a six-month period. The significant sets of model input attributes for the different operational modes were assessed via Spearman ranking correlation, Self-Organizing Map (SOM) analysis and feed forward feature selection (FFFS). Although the variability of nitrate passage, salt passage and permeate flux was significant over the four operational modes, prediction performance for the three outcomes were with R2 and Average Absolute Relative Error (AARE) of 0.78–0.95 and 2.96–6.16 %, respectively. Model updates post membrane elements replacement demonstrated similar levels of prediction accuracy. The study results suggest that there is merit in exploring the utility of multi-mode models for sensor fault detection, data imputation, and for potential use in model-predictive control.

Intermittent RO operation↗

DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than non-detonating engines. To understand the high-speed heat transfer dynamics inside an RDE, a novel, high-frequency heat flux gage is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Sensor bench testing is performed using a hot plate as a heat source, and the sensor response is compared to a finite-element analysis (FEA) model. The sensor response is then tested inside a water-cooled RDE and the wall heat flux is compared to calorimetry data.

rotating detonation engines↗

NASA NTRS1988

In-situ measurement of processing properties during fabrication in a production tool

Progress is reported on the use of frequency-dependent electromagnetic measurements (FDEMs) as a single, convenient technique for continuous in situ monitoring of polyester cure during fabrication in a laboratory and manufacturing environment. Preliminary FDEM sensor and modeling work using the Loss-Springer model in order to develop an intelligent closed-loop, sensor-controlled cure process is described. FDEMs using impedance bridges in the Hz to MHz region is found to be ideal for automatically monitoring polyester processing properties continuously throughout the cure cycle.

Kranbuehl, D. E.↗

DOE OSTI2025

Novel Design and Fabrication of a High Frequency Transient Heat Flux Sensor for Use in an RDE

rotating detonation engines↗

NASA NTRS2002

Effect of surface roughness on liquid property measurements using mechanically oscillating sensors

The resonant frequency and quality factor Q of a liquid immersed magnetoelastic sensor are shown to shift linearly with the liquid viscosity and density product. Measurements using different grade oils, organic chemicals, and glycerol-water mixtures show that the surface roughness of the sensor in combination with the molecular size of the liquid play important roles in determining measurement sensitivity, which can be controlled through adjusting the surface roughness of the sensor surface. A theoretical model describing the sensor resonant frequency and quality factor Q as a function of liquid properties is developed using a novel equivalent circuit approach. Experimental results are in agreement with theory when the liquid molecule size is larger than the average surface roughness. However, when the molecular size of the liquid is small relative to the surface roughness features molecules are trapped, and the trapped molecules act both as a mass load and viscous load; the result is higher viscous damping of the sensor than expected. c2002 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗

NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗

DOE OSTI2022

AOI.1 Application of Artificial Intelligence techniques enabling coal fired power plants the ability to achieve higher efficiency, improved availability, and increased reliability of their operations (Final Report)

During this effort, SparkCognition with support from the Electric Power Research Institute (EPRI) was tasked with applying artificial intelligence (AI) to improve the reliability, efficiency, and safety of operations at a coal-fired plant. By implementing AI techniques, like machine learning (ML), it is believed that operators can leverage existing data sources to gain more insights such as advanced warning of machine degradation. With enough lead time, a reliability engineer can take action to minimize, or even avoid, impact to production. To complete this work effort, SparkCognition developed and refined an ML-based model using sensor data for a Steam Turbine unit at a host site. The models were deployed in an online, web-based solution that allows users to visualize model outputs and supporting data. The final solution, based on SparkCognition’s proprietary software platform called SparkPredict®, was shared with EPRI who completed an online evaluation of results to determine the solution’s ability to detect actionable events.

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS1987

A vector-based failure detection and isolation algorithm for a dual fail-operational redundant strapdown inertial measurement unit

A vector-based failure detection and isolation technique for a skewed array of two degree-of-freedom inertial sensors is developed. Failure detection is based on comparison of parity equations with a threshold, and isolation is based on comparison of logic variables which are keyed to pass/fail results of the parity test. A multi-level approach to failure detection is used to ensure adequate coverage for the flight control, display, and navigation avionics functions. Sensor error models are introduced to expose the susceptibility of the parity equations to sensor errors and physical separation effects. The algorithm is evaluated in a simulation of a commercial transport operating in a range of light to severe turbulence environments. A bias-jump failure level of 0.2 deg/hr was detected and isolated properly in the light and moderate turbulence environments, but not detected in the extreme turbulence environment. An accelerometer bias-jump failure level of 1.5 milli-g was detected over all turbulence environments. For both types of inertial sensor, hard-over, and null type failures were detected in all environments without incident. The algorithm functioned without false alarm or isolation over all turbulence environments for the runs tested.

Morrell, Frederick R.↗

NASA NTRS1990

Spanwise measurements of vertical components of atmospheric turbulence

Correlation and spectrum magnitude estimates are computed for vertical gust velocity measurements at the nose and wing tips of a NASA B-57B aircraft for six level flight, low speed and low altitude runs and are compared with those of the von Karman atmospheric turbulence model extended for spanwise relationships. The distance between the wing tips was 62.6 ft. Airspeeds ranged from about 330 to 400 ft/sec, heights above the ground ranged from near ground level to about 5250 ft. and gust velocity standard deviations ranged from 4.10 to 8.86 ft/sec. Integral scale lengths, determined by matching measured autocorrelation estimates with those of the model, ranged from 410 to 2050 ft. Digital signals derived from piezoelectric sensors provided continuous pressure and airspeed measurements. Some directional acceleration sensitivity of the sensors was eliminated by sensor orientation, and their performance was spectrally verified for the higher frequencies with supplemental onboard piezoresistive sensors. The model appeared to satisfactorily predict the trends of the measured cross-correlations and cross-spectrum magnitudes, particularly between the nose and wing tips. However, the measured magnitude estimates of the cross-spectra between the wing tips exceeded the predicted levels at the higher frequencies. Causes for the additional power across the wing tips were investigated. Vertical gust velocity components evaluated along and lateral to the flight path implied that the frozen-turbulence-field assumption is a suitable approximation.

Sleeper, Robert K.↗

NASA NTRS2011

Continued Development of Meandering Winding Magnetometer (MWM (Register Trademark)) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of Composite Overwrapped Pressure Vessels

Composite Overwrapped Pressure Vessels (COPVs) are used in essentially all NASA spacecraft, launch. vehicles and payloads to contain high-pressure fluids for propulsion, life support systems and science experiments. Failure of any COPV either in flight or during ground processing would result in catastrophic damage to the spacecraft or payload, and could lead to loss of life. Therefore, NASA continues to investigate new methods to non-destructively inspect (NDE) COPVs for structural anomalies and to provide a means for in-situ structural health monitoring (SHM) during operational service. Partnering with JENTEK Sensors, engineers at NASA, Kennedy Space Center have successfully conducted a proof-of-concept study to develop Meandering Winding Magnetometer (MWM) eddy current sensors designed to make direct measurements of the stresses of the internal layers of a carbon fiber composite wrapped COPV. During this study three different MWM sensors were tested at three orientations to demonstrate the ability of the technology to measure stresses at various fiber orientations and depths. These results showed good correlation with actual surface strain gage measurements. MWM-Array technology for scanning COPVs can reliably be used to image and detect mechanical damage. To validate this conclusion, several COPVs were scanned to obtain a baseline, and then each COPV was impacted at varying energy levels and then rescanned. The baseline subtracted images were used to demonstrate damage detection. These scans were performed with two different MWM-Arrays. with different geometries for near-surface and deeper penetration imaging at multiple frequencies and in multiple orientations of the linear MWM drive. This presentation will include a review of micromechanical models that relate measured sensor responses to composite material constituent properties, validated by the proof of concept study, as the basis for SHM and NDE data analysis as well as potential improvements including design changes to miniaturize and make the sensors durable in the vacuum of space

Russell, Richard↗

NASA NTRS1995

Fixture For Mounting A Pressure Sensor

Fixture for mounting pressure sensor in aerodynamic model simplifies task of removal and replacement of sensor in event sensor becomes damaged. Makes it unnecessary to dismantle model. Also minimizes any change in aerodynamic characteristics of model in event of replacement. Removable pressure sensor installed in fixture in wall of model. Wires from sensor pass through channel under surface.

Cagle, Christopher M.↗