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Results for “Sample 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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Image reconstruction of IRAS survey scans

The IRAS survey data can be used successfully to produce images of extended objects. The major difficulties, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds is presented, using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spacial resolutions, at different wavelengths. Data estimates of the physical parameters, temperature, density and composition, can be made from the data without prior image (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

Bontekoe, Tj. Romke↗
NASA NTRS1990

Image construction from the IRAS survey and data fusion

The IRAS survey data can be used successfully to produce images of extended objects. The major difficulty, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds, is presented using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spatial resolutions, at different wavelengths. Direct estimates of the physical parameters, temperature, density and composition, can be made from the data without prior images (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

Bontekoe, Tj. R.↗
NASA NTRS1991

Image construction from the IRAS survey

IRAS survey data can be used successfully to produce images of extended objects. The major difficulties, i.e., nonuniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, have been resolved. The results of three different image construction techniques are compared: coaddition, constrained least-squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arcsecods, using 60 microns survey data is presented. This exceeds the telescope diffraction limit of about 1 minute of arc at this wavelength.

Bontekoe, T. R.↗
DOE OSTI2023

Nanolamellar phase transition in an additively manufactured eutectic high-entropy alloy under high pressures

Much is unknown about how phase transitions link to micro-/nano-structures in high-entropy systems, especially under extreme pressure and temperature conditions. This work studies the evolution of dual-phase nanolamellar eutectic high-entropy alloy phases of AlCoCrFeNi 2.1 generated by laser powder-bed fusion (L-PBF) for pressures up to 42 GPa. We compare quasi-hydrostatic high pressure synchrotron x-ray diffraction studies on L-PBF printed cylindrical samples up to 5.5 GPa (large-volume Paris–Edinburgh cell) to those carried out on an L-PBF printed foil in a diamond anvil cell where the pressure reached 42 GPa. Our results show that the initially alternating face-centered cubic (FCC) and body-centered cubic (BCC) nanolamellar structure of AlCoCrFeNi 2.1 transformed into single-phase FCC nanolamellae under high pressure with BCC–FCC phase transformation completion at 21 ± 3 GPa. Our results indicate a diffusionless BCC–FCC transformation in this additively manufactured far-from-equilibrium microstructure and demonstrate that the FCC phase is stable up to very high pressures. The measured equation of state for the FCC phase of AlCoCrFeNi 2.1 is presented up to 42 GPa and shows excellent agreement between the data obtained in large-volume press and diamond anvil cell experiments.

36 MATERIALS SCIENCE↗
NASA NTRS1994

The heat capacity of titanium disilicide

The heat capacity of TiSi2 has been measured in the temperature range 105-500 K. The heat capacity of TiSi2 varies monotonically between temperatures of 100 and 500 K with a reference value of 22.0 +/- 0.2 J/g atom K at 298.15 K. Based upon our heat capacity data, the standard molar entropy of TiSi2 at 298.15 K estimated to be 22.2 +/- 0.8 J/g atom K. Our data support estimates of the higher temperature heat capacity of TiSi2 based upon previously measured heat capacities of different, but similar, substances. A number of TiSi2 samples were prepared by rapidly quenching (greater than 10(exp 5) K/s) from the melt. The structure and the measured heat capacity of these samples were similar to those of well annealed samples, underscoring the thermal stability of this material.

Sylla, W. K.↗
DOE OSTI2019

Magnetocaloric Effect and Critical Behavior Investigations in La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} Manganite Oxide

Structural, magnetic, and magnetocaloric effect (MCE) properties and the critical behavior of the La{sub 0.45}Pr{sub 0.2}Sr{sub 0.35}MnO{sub 3} sample prepared by the sol–gel method have been investigated. The X-ray diffraction characterization reveals that our sample crystallizes in the orthorhombic structure with Pnma space group. Magnetization versus temperature measurement shows that our compound exhibits a ferromagnetic–paramagnetic transition. The Curie temperature is found to be 348 K. Close to this temperature, the maximum values of the magnetic entropy change (ΔS{sub M}) and the relative cooling power (RCP) are found to be 2.84 J/kg/K and 230 J/K under µ{sub 0}H = 5 T, respectively. The Arrott plots revealed that this compound exhibits a second-order magnetic phase transition at T{sub C}. The critical behavior has been investigated by several techniques which are the modified Arrott plot method, the Kouvel–Fisher method, and the critical isotherm analysis. The obtained critical exponents β, γ, and δ are consistent with those predictions of the mean-field model. Their reliability was confirmed by Widom’s scaling relation, as well as the universal scaling hypothesis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Predicting Thermochemical Equilibria with Interacting Defects: Sr 1 − x Ce x Mn O 3 − δ Alloys for Water Splitting

Solar thermochemical hydrogen is one of the few potential routes towards direct fuel production from renewable energy sources, but the thermodynamic boundary conditions for efficient and economic energy conversion are challenging. Success or failure of a given oxide working material depends on the subtle balance between enthalpy and entropy contributions in the redox processes. Developing a mechanistic understanding of the behavior of materials on the basis of atomistic models and first-principles calculations is an important part of advancing the technology. One challenge is to quantitatively predict thermochemical equilibria at high concentrations when the redox-active defects start to interact with each other, thereby impeding the formation of additional defects. This problem is of more general importance to applications that rely on high levels of off-stoichiometry or doping, including, for example, batteries, thermoelectrics, and ceramic fuel cells. To account for such repulsive defect interactions, we introduce a statistical mechanics approach, defining an expression for the free energy of defect interaction based on limited sampling of defect configurations in density functional theory supercell calculations. The parameterization of this energy contribution as a function of defect concentration and temperature allows on-the-fly simulation of thermochemical equilibria. The approach consistently incorporates finite temperature effects by including the leading contributions to the temperature-dependent free energy for the case at hand, i.e., the ideal gas and configurational enthalpies and entropies. We demonstrate the capability and utility of the approach by simulating the water splitting redox processes for Sr 1 − x Ce x Mn O 3 − δ alloys. Published by the American Physical Society 2024

08 HYDROGEN↗
DOE OSTI2015

Design and Validation Testing of TruckScan to Assay Large Sacks of Fukushima Radioactive Debris on a Truck

As a result of the March 2011 earthquake and resulting tsunami in Japan, there was a serious accident at the Fukushima Dai-ichi Nuclear Power Plant. This accident has contaminated soil and vegetation in a wide area around the plant. Decontamination projects over the last 4 years have resulted in large numbers of 1 cubic meter canvas bags of debris, commonly called Super Sacks [SS]. These are currently stored nearby where they were generated, but starting in 2015, they will be moved to various Interim Storage Facilities [ISF]. Trucks will typically carry 8-20 of these SSs. When the trucks arrive at the ISF they need to be rapidly sorted into groups according to radioactivity level, for efficient subsequent processing. Canberra Industries, Inc. [CI] has designed a new truck monitoring system 'TruckScan' for use at these ISFs. The TruckScan system must measure the entire truck loaded with multiple closely packed SSs, and generate a nuclide specific assay report showing the radioactivity in each individual SS. The Canberra-Japan office, along with Obayashi Corporation have performed validation testing to demonstrate to the regulatory authorities that the proposed technique was sufficiently accurate. These validation tests were conducted at a temporary storage area in Fukushima prefecture. Decontaminated waste of various representative types and of various levels of radioactivity was gathered and mixed to create homogeneous volumes. These volumes were sampled multiple times and assayed with laboratory HPGe detectors to determine the reference concentration of each pile. Multiple SSs were loaded from each pile. Some of the SSs were filled 50% full, others 75% full, and others 100% full, to represent the typical loading configuration of the existing SSs in the field. The content of the SSs are either sand, soil, or vegetation with densities ranging from 0.3 g/cc - 1.6 g/cc. These SSs with known concentrations of Cs-134 and Cs-137 were then loaded onto trucks in a variety of configurations, typical of how they might be on the real trucks. A partial system was installed at the site and used to assay these trucks with the various loading configurations. Whereas the full system will have 8 collimated 3 x 3'' NaI detectors, the test system only had two detectors; therefore the truck was moved and counted 4 times. The data were acquired and analyzed with the Canberra Genie software to determine the peak counts for both Cesium nuclides. That data was then analyzed with a prototype version of a Maximum Entropy algorithm, to determine the individual SS activity. The goal of the validation tests was to demonstrate that the system could detect 1000 Bq/kg in 15 seconds, and to determine how accurately it could quantify individual SSs. The validation tests demonstrated that the product would perform as predicted. The TruckScan results were consistent with the sample assay results [y = 1.0029 x, R{sup 2} = 0.914]. The Total Propagated Uncertainty, including both uncertainties from these tests and others that were estimated but not tested was 16.6% percent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds

A minimax estimator has the minimum possible error (“risk”) in the worst case. Here we construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O (1/$\sqrt{N}$ ) —in contrast to that of classical probability estimation, which is O (1/N) —where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. Lastly, this makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Microstructure and Mechanical Behavior of High-Entropy Alloys

High entropy alloys (HEA) have generated interest in recent years due to their unique positioning within the alloy world. By incorporating a number of elements in high proportion, usually of equal atomic percent, they have high configurational entropy, and thus, they hold the promise of interesting and useful properties such as enhanced strength and alloy stability. The present study investigates the mechanical behavior, fracture characteristics and microstructure of two singlephase FCC high-entropy alloys (HEA's) CoCrFeNi and CoCrFeNiMn with some detailed attention given to melting, homogenization and thermo-mechanical processing. Ingots approaching 8 kg in mass were made by vacuum induction melting (VIM) to avoid the extrinsic factors inherent to small scale laboratory button samples. A computationally based homogenization heat treatment was given to both alloys in order to eliminate any solidification segregation. The alloys were then fabricated in the usual way (forging, followed by hot rolling) with typical thermo-mechanical processing parameters employed. Transmission electron microscopy (TEM) was subsequently used to assess the single phase nature of the alloys prior to mechanical testing. Tensile specimens (ASTM E8) were prepared with tensile mechanical properties obtained from room temperature through 800°C. Material from the gage section of selected tensile specimens was extracted to document room and elevated temperature deformation within the HEA's. Fracture surfaces were also examined to note fracture failure modes. The tensile behavior and selected tensile properties were compared with results in the literature for similar alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Synthesis of the p-type semiconducting ternary oxide CuAlO{sub 2} using the Pechini method

Graphical abstract: - Highlights: • We have prepared single-phase samples of the semiconducting oxide CuAlO{sub 2} using the Pechini method. • Reaction times are reduced relative to conventional solid-state synthesis. • Products have high surface area suitable for ceramic processing. • Product composition is dictated by thermodynamic control; CuAl{sub 2}O{sub 4} is obtained preferentially at lower temperature. - Abstract: The synthesis of the delafossite phase CuAlO{sub 2} using the Pechini method was investigated. Powder X-ray diffraction data showed that pure, single-phase samples were obtained after only 3 h heating at 1100 °C. CuAl{sub 2}O{sub 4}, which contains Cu(II) rather than Cu(I), was the dominant phase between 700 and 1100 °C. Conversion to CuAlO{sub 2} is promoted by the positive entropy change associated with the evolution of oxygen. No mixed Cu–Al oxide was formed below 700 °C.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Simplified Digital Subband Coders And Decoders

Simplified digital subband coders and decoders developed for use in converting digitized samples of source signals into compressed and encoded forms that maintain integrity of source signals while enabling transmission at low data rates. Examples of coding methods used in subbands include coarse quantization in high-frequency subbands, differential coding, predictive coding, vector quantization, and entropy or statistical coding. Encoders simpler, less expensive and operate rapidly enough to process video signals.

Glover, Daniel R.↗
DOE OSTI2024

Effects of electron beam irradiation on CrMnV and CrMnTiV high entropy alloys: Nano-mechanical, structural, and thermodynamic perspectives

Beam exit windows are crucial components of any particle accelerator as they provide an interface between the beamline vacuum and target material at atmospheric media. For high beam power machines, special materials and designs are required to withstand high radiation and mechanical loads, while minimizing energy loss during transition and maximizing window lifetime. This research investigates the impact of electron beam exposure to bulk CrMnV and CrMnTiV high entropy alloys (HEAs) with the primary goal of identifying suitable candidate materials for the design of robust and durable exit window settings. The selection criteria include intrinsic characteristics, power dissipation, and mechanical responses. According to the thermodynamic calculations, both equiatomic CrMnV and the addition of 7% of Ti with equiatomic CrMnV yield solid-solutions phases. The structural and mechanical properties of CrMnV and CrMnTiV samples were tested using field emission scanning electron microscopy, atomic force microscopy, scanning electron microcopy with energy dispersive x-ray spectroscopy, x-ray diffraction, and nanoindentation before and after exposure to a dose of ~66 kGy from a 10 MeV e-beam accelerator. Despite exhibiting beam transmission characteristics comparable to Cr and V, the indentation hardness of HEAs exceeded that of the Cr and V samples by five to six times. The examination of the CrMnTiV irradiated samples revealed organized deformation patterns depicting new features, which we suspect twinning and twin boundaries due to the addition of Ti to CrMnV. Ti, a hexagonal-close-packed crystal structure, is commonly known for deformation twinning behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model-free estimation of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Abstract An accurate description of information is relevant for a range of problems in atomistic machine learning (ML), such as crafting training sets, performing uncertainty quantification (UQ), or extracting physical insights from large datasets. However, atomistic ML often relies on unsupervised learning or model predictions to analyze information contents from simulation or training data. Here, we introduce a theoretical framework that provides a rigorous, model-free tool to quantify information contents in atomistic simulations. We demonstrate that the information entropy of a distribution of atom-centered environments explains known heuristics in ML potential developments, from training set sizes to dataset optimality. Using this tool, we propose a model-free UQ method that reliably predicts epistemic uncertainty and detects out-of-distribution samples, including rare events in systems such as nucleation. This method provides a general tool for data-driven atomistic modeling and combines efforts in ML, simulations, and physical explainability.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The effect of submicron grain size on thermal stability and mechanical properties of high-entropy carbide ceramics

(Hf 0.2 Zr 0.2 Ta 0.2 Nb 0.2 Ti 0.2 )C high-entropy ceramics (HEC) with a submicron grain size of 400 to 600 nm were fabricated by spark plasma sintering using a two-step sintering process. Both X-ray and neutron diffractions confirmed the formation of single-phase with rock salt structure in the as-fabricated (Hf 0.2 Zr 0.2 Ta 0.2 Nb 0.2 Ti 0.2 )C samples. The effect of submicron grain size on the thermal stability and mechanical properties of HEC was investigated. The grain growth kinetics in the fine-grained HEC was small at 1300 and 1600°C, suggesting high thermal stability that was possibly related to the compositional complexity and sluggish diffusion in HEC. Compared to the coarse-grain HEC with a grain size of 16.5 µm, the bending strength and fracture toughness of fine-grained HEC were 25% and 20% higher respectively. The improvement of mechanical properties in fine-grained HEC may be attributed to micromechanistic mechanisms such as crack deflection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Experimental investigation of thermal conductivity of high entropy ceramics

In this talk, we will present the experimental investigation of thermal conductivity of high entropy carbides (HEC) and borides (HEB) with different compositions. Thermal conductivity determines the capability of a material to transport thermal energy and is considered as one critical physical property, specially in the energy industry. Due to the presences of disordered cation sublattice, it is expected that thermal conductivity of high entropy ceramics is lower than the counterparts with simpler compositions, but the experimental studies are relatively few. Using laser-based spatial-domain and frequency-domain thermoreflectance technique, we measured thermal conductivity of HECs and HEBs in a temperature range from 77K to 773K. Furthermore, by focusing the laser using an objective lens, we were able to perform the thermal property mapping on samples with the spatial resolution of micrometer. Such measurements could reveal important microstructure information in a rapid and efficient way without using scanning electron microscopy. The high spatial resolution also enables thermal conductivity measurements on ion-irradiated HECs with the damage layer of merely 1.1µm. These measurements can provide valuable information to predict the performances of HECs and HEBs with different compositions and from different manufacturing processes, and in the extreme environments such as nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2022

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE). A novel density estimator recently developed by Farmer and Jacobs offers an alternative high-throughput automated approach to univariate nonparametric density estimation based on maximum entropy and order statistics, improving accuracy over univariate KDE. This article presents an extension of the single variable case to multiple variables. The univariate estimator is used to recursively calculate a product array of one-dimensional conditional probabilities. In combination with interpolation methods, a complete joint probability density estimate is generated for multiple variables. Good accuracy and speed performance in synthetic data are demonstrated by a numerical study using known distributions over a range of sample sizes from 100 to 10 6 for two to six variables. Performance in terms of speed and accuracy is compared to KDE. The multivariate density estimate developed here tends to perform better as the number of samples and/or variables increases. As an example application, measurements are analyzed over five filters of photometric data from the Sloan Digital Sky Survey Data Release 17. The multivariate estimation is used to form the basis for a binary classifier that distinguishes quasars from galaxies and stars with up to 94% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗