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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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113 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Medium- and Heavy-Duty Truck Duty Cycles

This dataset provides second-by-second duty cycle data for Class 6 and Class 8 diesel trucks in Texas, including key vehicle metrics, engine-related data, and GPS data (excluding GPS latitude and longitude to ensure confidentiality). The data were collected via tablets installed on the trucks and organized into daily datasets, each associated with a unique vehicle ID and date. There are 12 daily datasets for Class 6 diesel trucks (three unique vehicle IDs) and 43 daily datasets for Class 8 diesel trucks (six unique vehicle IDs). The units associated with each column are included in the name. The engine performance data include columns such as engine speed, engine percent torque, and engine fuel rate. Road grade (%/100) was estimated using the GPS altitude and wheel-based vehicle speed, which is used as an input for FASTSim. Cumulative distance was also calculated using the wheel-based vehicle speed. Additional columns include: - Engine Speed (RPM): Removed inaccurate readings and used to calculate angular velocity (radians/second). - Torque (N·m): Calculated using engine percent torque, nominal friction percent torque, and engine reference torque values (those columns were removed from dataset), then normalized to express as torque (%). - Flywheel Power (%): Calculated using the angular velocity and torque (in kW), then normalized as a percentage of the maximum value. - Engine Fuel Rate (%) and Torque (%): Both metrics were normalized by dividing by their respective maximum values within each dataset to express them as percentages. The datasets were analyzed to assess the energy impact of various driving behaviors, simulate energy efficiency, and recommend optimal routes for diesel trucks using NLR’s tool called RouteE. For driver coaching, factors like speed and acceleration limits were considered, and idle periods were reduced (assuming the engine was off during idling) to adjust each drive cycle. These adjusted drive cycles were then simulated in FASTSim to evaluate their effect on fleet energy consumption and estimate potential energy savings. The original cycles are available for download on this page ![image](CoVaR_Image_for_Data_Page_Kenworth_Truck.jpg)

1Hz↗
NASA NTRS2011

Further Constraints and Uncertainties on the Deep Seismic Structure of the Moon

The Apollo Passive Seismic Experiment (APSE) consisted of four 3-component seismometers deployed between 1969 and 1972, that continuously recorded lunar ground motion until late 1977. The APSE data provide a unique opportunity for investigating the interior of a planet other than Earth, generating the most direct constraints on the elastic structure, and hence the thermal and compositional evolution of the Moon. Owing to the lack of far side moonquakes, past seismic models of the lunar interior were unable to constrain the lowermost 500 km of the interior. Recently, array methodologies aimed at detecting deep lunar seismic reflections found evidence for a lunar core, providing an elastic model of the deepest lunar interior consistent with geodetic parameters. Here we study the uncertainties in these models associated with the double array stacking of deep moonquakes for imaging deep reflectors in the Moon. We investigate the dependency of the array stacking results on a suite of parameters, including amplitude normalization assumptions, polarization filters, assumed velocity structure, and seismic phases that interfere with our desired target phases. These efforts are facilitated by the generation of synthetic seismograms at high frequencies (approx. 1Hz), allowing us to directly study the trade-offs between different parameters. We also investigate expected amplitudes of deep reflections relative to direct P and S arrivals, including predictions from arbitrarily oriented focal mechanisms in our synthetics. Results from separate versus combined station stacking help to establish the robustness of stacks. Synthetics for every path geometry of data were processed identically to that done with data. Different experiments were aimed at examining various processing assumptions, such as adding random noise to synthetics and mixing 3 components to some degree. The principal stacked energy peaks put forth in recent work persist, but their amplitude (which maps into reflector impedance contrast) and timing (which maps into reflector depth) depend on factors that are not well constrained -- most notably, the velocity structure of the overlying lunar interior. Thus, while evidence for the lunar core remains strong, the depths of imaged reflectors have associated uncertainties that will require new seismic data and observations to constrain. These results strongly advocate further investigations on the Moon to better resolve the interior (e.g., Selene missions), for the Moon apparently has a rich history of construction and evolution that is inextricably tied to that of Earth.

Lin, Pei-Ying Patty↗
NASA NTRS1994

Rarefield-Flow Shuttle Aerodynamics Flight Model

A model of the Shuttle Orbiter rarefied-flow aerodynamic force coefficients has been derived from the ratio of flight acceleration measurements. The in-situ, low-frequency (less than 1Hz), low-level (approximately 1 x 10(exp -6) g) acceleration measurements are made during atmospheric re-entry. The experiment equipment designed and used for this task is the High Resolution Accelerometer Package (HiRAP), one of the sensor packages in the Orbiter Experiments Program. To date, 12 HiRAP re-entry mission data sets spanning a period of about 10 years have been processed. The HiRAP-derived aerodynamics model is described in detail. The model includes normal and axial hypersonic continuum coefficient equations as function of angle of attack, body-flap deflection, and elevon deflection. Normal and axial free molecule flow coefficient equations as a function of angle of attack are also presented, along with flight-derived rarefied-flow transition bridging formulae. Comparisons are made between the aerodynamics model, data from the latest Orbiter Operational Aerodynamic Design Data Book, applicable computer simulations, and wind-tunnel data.

Blanchard, Robert C.↗
DOE OSTI2025

NERSC_Lightweight Distributed Metric Service (NERSC_LDMS) v4.4.2

Miscellany This LDMS Loftsman/Helm Chart horizontally scales LDMS daemons in order to achieve a 1Hz sample rate from over 5,000 nodes, collecting 38k metrics per minute on Perlmutter. This LMDS Configuration relies on already running `ldmsd` producers running on nodes, which produce metrics via sampler plugins. The Helm chart distributes the collection of metrics from producer acrross many aggregator and storage `ldmsd` daemons, ensuring no damon is overloaded and data loss is avoided.

Stile, John [Lawrence Berkeley National Laboratory↗
NASA NTRS2006

Multi-Wavelength Dielectrometer (MWD) Sensor For Planetary Subsurface Exploration

NASA's mission to Moon, Mars, and Beyond envisions landing of a light weight measurement platform on the planetary surface. The Multi-Wavelength Dielectrometer (MWD) on-board consists of essential electronics and metallic plates acting as electrodes attached to the body of such platform. An electric signal applied to one of the electrodes acting as a cathode sets up electric field pattern (in the soil medium) between the cathode and other electrodes acting as anodes. The electrodes are swept through multiple wavelengths (1Hz-1MHz) and the electric current drawn by the electrodes is measured at each frequency. The measured current whose amplitude and phase depend upon electrode spacing, dielectric constant of the subsurface soil, and the frequency is then used to estimate electrical properties of the soil. In this paper the MWD sensor that will measure the dielectric properties of Moon/Mars s soil is presented. A procedure to process the MWD measured data for extracting the soil properties is also described. Assuming the subsurface soil structure as multilayer strata having varying electric properties, an electric equivalent circuit of the multiple electrodes configuration placed on a multi-layer soil sample is obtained. The current drawn by the equivalent circuit from the low frequency signal generator is then calculated. By minimizing the difference between the model s estimated current and measured MWD data the electric properties of soil samples are extracted. Experimental and simulated results will be presented to validate the proposed procedure for extracting soil properties.

Deshpande, Manohar↗