Quantification of the upstream‐to‐downstream influence in the Muskingum method and implications for speedup in parallel computations of river flow
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Cédric H. David↗
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Results for “quantification”
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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Performance of Airborne Imaging Spectrometers for Carbon Dioxide Detection and Emission Quantification
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Jinsol Kim↗
Spatial and Temporal Quantification of Subaerial Volcanism From 1980 to 2019: Solid Products, Masses, and Average Eruptive Rates
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Federico Galetto↗
MRI-based quantification of posterior ocular globe flattening during 60 days of strict 6° head-down tilt bed rest with and without daily centrifugation
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Stuart H. Sater↗
A Virtual Solar Wind Monitor at Mars With Uncertainty Quantification Using Gaussian Processes
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A. R. Azari↗
Quantification of arterial, venous, and cerebrospinal fluid flow dynamics by magnetic resonance imaging under simulated micro-gravity conditions: a prospective cohort study
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Arslan M. Zahid↗
MRI-based quantification of ophthalmic changes in healthy volunteers during acute 15° head-down tilt as an analogue to microgravity
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Stuart H. Sater↗
Quantification of endospores in ancient permafrost using time-resolved terbium luminescence
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S.J. Lalla↗
A protein switch sensing system for the quantification of sulfate
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Krystal Teasley Hamorsky↗
Material State Awareness for Composites Part II: Precursor Damage Analysis and Quantification of Degraded Material Properties Using Quantitative Ultrasonic Image Correlation (QUIC)
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Subir Patra↗
Empirical Quantification of Topobathymetric Lidar System Resolution Using Modulation Transfer Function
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K. W. Sacca↗
Discrimination and quantification of Fe and Ni abundances in Genesis solar wind implanted collectors using X-ray standing wave fluorescence yield depth profiling with internal referencing
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Y. Choi↗
Quantification of Precipitation Asymmetries of Tropical Cyclones Using 16‐Year TRMM Observations
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Yongxian Pei↗
Novel incubation‐free approaches to determine phytoplankton net primary productivity, growth, and biomass based on flow cytometry and quantification of ATP and NAD(H)
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Bethan M. Jones↗
Uncertainty quantification of measured quantities for a HCCI engine: mass-average quantities and perofrmances
UQHCCI_2 propagates the uncertainties of mass-average quantities (temperature, heat capacity ratio) and the output performances (IMEP, heat release, CA50 and RI) of a HCCI engine test bench using the pressure trace, and intake and exhaust molar fraction and IVC temperature distributions, as inputs (those inputs may be computed using another code UQHCCI_2, or entered independently).
Petitpas, Guillaume↗
Uncertainty quantification of measured quantities for a HCCI engine: composition or temperatures
UQHCCI_1 computes the measurement uncertainties of a HCCI engine test bench using the pressure trace and the estimated uncertainties of the measured quantities as inputs, then propagating them through Bayesian inference and a mixing model.
Petitpas, Guillaume↗
Demand Response Resource Quantification with Detailed Building Energy Models
Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Image processing tool for automatic feature recognition and quantification
A system for defining structures within an image is described. The system includes reading of an input file, preprocessing the input file while preserving metadata such as scale information and then detecting features of the input file. In one version the detection first uses an edge detector followed by identification of features using a Hough transform. The output of the process is identified elements within the image.
36 MATERIALS SCIENCE↗
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