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Results for “Entropy”
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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Jarzynski-like equality of nonequilibrium information production based on quantum cross-entropy
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Demon in the Machine: Learning to Extract Work and Absorb Entropy from Fluctuating Nanosystems
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Maximal Entropy Approach for Quantum State Tomography
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Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting
Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.
Visualization of higher genus carbon nanomaterials: free energy, persistent current, and entanglement entropy
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Parameterized MDPs and Reinforcement Learning Problems—A Maximum Entropy Principle-Based Framework
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Local structure of the Mg x Ni x Co x Cu x Zn x O( x =0.2) entropy-stabilized oxide: An EXAFS study
Abstract not provided
Phase stability and tensorial thermal expansion properties of single to high-entropy rare-earth disilicates
Temperature limitations in nickel-base superalloys have resulted in the emergence of SiC-based ceramic matrix composites as a viable replacement for gas turbine components in aviation applications. Higher operating temperatures allow for reduced fuel consumption but present a materials design challenge related to environmental degradation. Rare-earth disilicates (RE 2 Si 2 O 7 ) have been identified as coatings that can function as environmental barriers and minimize hot component degradation. In this work, single- and multiple-component rare-earth disilicate powders were synthesized via a sol-gel method with compositions selected to exist in the monoclinic C 2/m phase (β phase). Phase stability in multiple cation compositions was shown to follow a rule of mixtures and the C 2/m phase could be realized for compositions that contained up to 25% dysprosium, which typically only exists in a triclinic, P $\bar1$, phase. All compositions exhibited phase stability from room temperature to 1200°C as assessed by X-ray diffraction. The thermal expansion tensors for each composition were determined from high-temperature synchrotron X-ray diffraction and accompanying Rietveld refinements. It was observed that ytterbium-containing compositions had larger changes in the α 31 shear component with increasing temperature that led to a rotation of the principal axes. Principal axes rotation of up to 47° were observed for ytterbium disilicate. The results suggest that microstructure design and crystallographic texture may be essential future avenues of investigation to ensure thermo-mechanical robustness of rare-earth disilicate environmental barrier coatings.
Stochastic variational quantization and maximum entropy principle
In this note, we discuss the stochastic variational method (SVM) to derive the action principle of Schrödinger equation. In this formalism, the wave function is introduced as one of convenient ways to express the action. This work is a reformulation of Nelson—Yasue’s stochastic quantization scheme and its variational formulation by Yasue, and will furnish possible way to deal with more complicated system such as quantum field theory, suggesting an origin of quantum mechanics.
Corrosion Behavior of CoCrFeMnNi High-Entropy Alloys Under Aqueous Acidic Conditions
Presented by NETL at 231 Electrochemical Society Meeting, 05/17
Corrosion of Additively Manufactured CoCrFeMnNi High Entropy Alloy in Molten NaNO 3 -KNO 3
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High Entropy Analysis Code
This code describes the process to estimate material properties using elemental properties and machine learning.
Enhancing internet of things security using entropy-informed RF-DNA fingerprint learning from Gabor-based images
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