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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 217 records · Page 12

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NASA NTRS2017

3D Material Response Analysis of PICA Pyrolysis Experiments

Primarily interested in improving ablation modeling for use in inverse reconstruction of flight environments on ablative heat shields. Ablation model is essentially a component of the heat flux sensor, so model uncertainties lead to measurement uncertainties. Non-equilibrium processes have been known to be significant in low density ablators for a long time, but increased accuracy requirements of the reconstruction process necessitates incorporating this physical effect. Attempting to develop a pyrolysis model for implementation in material response based on the PICA data produced by Bessire and Minton. Pyrolysis gas species molar yields as a function of temperature and heating rate. Several problems encountered while trying to fit Arrhenius models to the data led to further investigation of the experimental setup.

Oliver, Brandon A.↗

NASA NTRS2011

Computational Electromagnetic Modeling of SansEC(Trade Mark) Sensors

This paper describes the preliminary effort to apply computational design tools to aid in the development of an electromagnetic SansEC resonant sensor composite materials damage detection system. The computational methods and models employed on this research problem will evolve in complexity over time and will lead to the development of new computational methods and experimental sensor systems that demonstrate the capability to detect, diagnose, and monitor the damage of composite materials and structures on aerospace vehicles.

Smith, Laura J.↗

NASA NTRS1995

Deposition Of Thin-Film Sensors On Glass-Fiber/Epoxy Models

Direct-deposition process devised for fabrication of thin-film sensors on three-dimensional, curved surfaces of models made of stainless steel covered with glass-fiber/epoxy-matrix composite material. Models used under cryogenic conditions, and sensors used to detect on-line transitions between laminar and turbulent flows in wind tunnel environments. Sensors fabricated by process used at temperatures from minus 300 degrees F to 175 degrees F.

Tran, Sang Q.↗

NASA NTRS1993

Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors

A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.

Holben, Brent N.↗

NASA NTRS1996

Alpha-Particle Gas-Pressure Sensor

An approximate model was developed to establish design curves for the saturation region and a more complete model developed to characterize the current-voltage curves for an alpha-particle pressure sensor.

alpha-particle↗

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↗