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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

EPA and Idaho National Laboratory create first of its scale

Advancing the science and engineering of decontaminating water distribution systems and safely disposing of high-volumes of contaminated water are high priorities for the EPA. To help address these science gaps, EPA homeland security researchers have developed the first-of-its-scale Water Security Test Bed (WSTB). Water is an important component of everyday life. We rely on safe, clean water for our health and the health of the environment. Protecting this vital resource is critical to living safely and securely. The U.S. Environmental Protection Agency is responsible for working with water utilities to protect water systems from contamination and to clean up systems that become contaminated. Purposeful or inadvertent distribution system contamination can result in large amounts of infrastructure and water that must be cleaned. Water distribution systems contamination can be caused by, for example, natural disasters such as Superstorm Sandy or by individuals hoping to cause harm. The WSTB, constructed at the Department of Energy’s (DOE) Idaho National Laboratory, replicates a section of a typical municipal drinking water system including a piping system with roughly 445 feet of pipe and two fire hydrants laid out in an “L” shape using 40-year-old, eight-inch cement mortar lined, ductile iron pipes, excavated after twenty years of use for water conveyance. Researchers built the WSTB above ground for easy access during experiments, and to facilitate fast leak detection. Over the next several years, EPA and partner researchers will conduct experiments using simulants of various biological, chemical, and radioactive materials that simulate high toxic versions of these agents. At this “full” sized system, researchers will demonstrate approaches to contamination detection, sensor and model testing, infrastructure decontamination, water treatment and cyber testing developed at lab and pilot scale. Researchers are also able to verify if laboratory results that were effective in controlled conditions are as effective in full-scale testing. Having the ability to conduct bench scale studies in a real world setting can help address specific research gaps, and help water researchers understand conditions in which real world drinking water systems operate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Occupant thermal comfort inference using body shape information

Occupant thermal comfort may be inferred and improved using body shape information. Height, weight, and shoulder circumference of an occupant of a room may be obtained using a depth sensor. A model may be utilized that is trained on a dataset including information reflecting of occupant comfort within the room versus temperature, the model receiving, as inputs, the height, the weight, and the shoulder circumference of the occupant and environmental information and outputting a comfort class. A temperature set-point for is identified which the room occupant is identified by the model as having the comfort class being indicative of user comfort. Heating, ventilation, and air conditioning (HVAC) controls are adjusted for the room to the identified temperature set-point.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

Sensor Radiance for a Midlatitude Atmospheric Model

The Herman radiative transfer code which iteratively traces solar radiance through a discrete number of scattering angles and many atmospheric layers was transferred to a personnal computer to reduce time in recompiling the source code. The code was then used to predict what ground reflectance would saturate the TM sensor output given a standard midlatitude atmospheric model. Output radiance is tabulated for the first four bands. Plots show radiance at the sensor as a function of solar zenith angle from a visibility of 40 km; solar zenith angle as a function of time of year for four latitudes over a typical portion of the descending node of a LANDSAT orbit; and values of ground reflectance required to saturate the TM sensor from three different aerosol loading conditions (corresponding to about 20 km, 40 km. and greater than 100 km visibility).

Source record↗
NASA NTRS1989

A model for atmospheric brightness temperatures observed by the special sensor microwave imager (SSM/I)

A closed-form mathematical model for the atmospheric contribution to microwave the absorption and emission at the SSM/I frequencies is developed in order to improve quantitative interpretation of microwave imagery from the Special Sensor Microwave Imager (SSM/I). The model is intended to accurately predict upwelling and downwelling atmospheric brightness temperatures at SSM/I frequencies, as functions of eight input parameters: the zenith (nadir) angle, the integrated water vapor and vapor scale height, the integrated cloud water and cloud height, the effective surface temperature, atmospheric lapse rate, and surface pressure. It is shown that the model accurately reproduces clear-sky brightness temperatures computed by explicit integration of a large number of radiosonde soundings representing all maritime climate zones and seasons.

Petty, Grant W.↗
NASA NTRS2012

End-to-end Coronagraphic Modeling Including a Low-order Wavefront Sensor

To evaluate space-based coronagraphic techniques, end-to-end modeling is necessary to simulate realistic fields containing speckles caused by wavefront errors. Real systems will suffer from pointing errors and thermal and motioninduced mechanical stresses that introduce time-variable wavefront aberrations that can reduce the field contrast. A loworder wavefront sensor (LOWFS) is needed to measure these changes at a sufficiently high rate to maintain the contrast level during observations. We implement here a LOWFS and corresponding low-order wavefront control subsystem (LOWFCS) in end-to-end models of a space-based coronagraph. Our goal is to be able to accurately duplicate the effect of the LOWFS+LOWFCS without explicitly evaluating the end-to-end model at numerous time steps.

coronagraphs↗
NASA NTRSDate not supplied

Medium-Fidelity CFD Modeling of Multicopter Wakes for Airborne Sensor Measurements

A steady-state multicopter simulation capability leveraging automated Cartesian grid generation and a blade element source term rotor model was used to investigate multi-rotor aerodynamics in and out of ground effect. Simulations demonstrated that this model is able to predict reasonably accurate thrust in ground effect for both single and multiple propeller cases. The method yielded accurate lift and drag predictions for a commercial quadcopter when compared to recent wind tunnel test data. This aircraft was then simulated in a variety of flight conditions, including both hover and edgewise forward flight, to determine if generalized guidelines for airborne sensor placement could be developed. Velocity perturbation magnitudes showed large regions of affected air upstream of the vehicle at low speeds, which contracted as the vehicle’s speed was increased. Placing the sensors more than one characteristic length ahead of or above the aircraft reduces errors from rotor-induced flow at higher speeds. For low-speed forward flight, the entrainment of flow into the propeller wakes introduces significant flow turning above the aircraft, suggesting that a forward location, with more moderate perturbations, could be advantageous for these conditions.

ARMD↗
NASA NTRS1993

Textile composite processing science

A multi-dimensional model of the Resin Transfer Molding (RTM) process was developed for the prediction of the infiltration behavior of a resin into an anisotropic fiber preform. Frequency dependent electromagnetic sensing (FDEMS) was developed for in-situ monitoring of the RTM process. Flow visualization and mold filling experiments were conducted to verify sensor measurements and model predictions. Test results indicated good agreement between model predictions, sensor readings, and experimental data.

Loos, Alfred C.↗
DOE OSTI2022

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗
NASA NTRS1982

Atmospheric Correction for Remote Sensor Data

Mathematical model based on radiative transfer theory as applied to plane parallel, horizontally spatially homogeneous, isotropic atmosphere. Model includes effects of multiple scattering by gases and aerosols, and effects of absorption by ozone in near ultraviolet and visible parts of spectrum.

Turner, R. E.↗
NASA NTRS2005

Passive Millimeter-wave Signatures of Ice Particles in Hurricane Erin

Observations of Hurricane Erin (2001) taken during the Fourth Convection and Moisture Experiment (CAMEX-Q) are used to elucidate relationships between measurements and models. Measurements include active and passive microwave sensors, and dropsondes. Models used in the analysis include radiative transfer (RT) models, mesoscale models (MM5), and particle parameterizations. Various combinations of the models and observational constraints are used in the RT model to provide calculated brightness temperatures to compare to the passive observations. In order to match the wide frequency range 10 to 183±10 GHg model modifications were needed. The 55.5 GHz channel provided insight to the tropospheric temperature profile, while the 10 GHz channel provided knowledge of (near) ocean surface conditions. The channels less than ~90 GHz are mostly responsive to liquid in the cloud, while higher frequencies respond to ice particles in the cloud.

Ice clouds↗
NASA NTRS2021

Gravity Wave Observations by the Mars Science Laboratory REMS Pressure Sensor and Comparison with Mesoscale Atmospheric Modeling with MarsWRF

Surface pressure measurements on Mars have revealed a wide variety of atmospheric phenomena. The Mars Science Laboratory Rover Environmental Monitoring Station pressure sensor dataset is now the longest duration record of surface pressure on Mars. We use the first 2580 martian sols, nearly 4 Mars years,of measurements to identify atmospheric pressure waves with periods of tens of minutes to hours using wavelet analysis on residual pressure after the tidal harmonics are removed. We find these waves have a clear diurnal cycle with strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Ls= 180-360°). The strongest such waves of the entire mission occurred during the Mars Year 34 global dust storm. Comparable atmospheric waves are identified using atmospheric modeling with the MarsWRF general circulation model in a “nested” high spatial resolution mode. With the support of the modeling, we find these waves best fit the expected properties of inertia-gravity waves with horizontal wavelengths of O(100s) of km. PLAIN LANGUAGE SUMMARY Measuring air pressure from the surface of Mars has revealed a wide variety of atmospheric phenomena. The Curiosity rover's record or surface air pressure is now the longest yet made on Mars.We use the first ~8 years of Curiosity's pressure observations to look for atmospheric waves with periods of tens of minutes to hours. We find these waves have a clear pattern in their daily behavior with the strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Northern hemisphere fall and winter). The strongest such waves occurred in 2018 during a global dust storm. We find comparable waves in atmospheric modeling. With the support of modeling, we find these waves best fit the expected properties of buoyancy waves forced by airflow over topography with horizontal wavelengths of 100-1000 km.

Scott D Guzewich↗