Engineering Papers⌕ Search

SEARCH · Engineering Papers

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

Gill, Roger↗
DOE OSTI2025

Benchmarking image processing techniques for porosity measurement in polymer additive manufacturing: Review and experimental analysis

An image processing workflow is proposed for porosity measurement in polymer additive manufacturing. Various techniques, including global and local thresholding, region growing, and K-means clustering, were applied to microscopic images of carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and benchmarked for their ability to accurately measure porosity. Global methods included Otsu, minimum error, iterative, and entropy-based thresholding, while local methods included Niblack, Bernsen, Sauvola, and Bradley-Roth algorithms. Artificial uneven illumination was introduced to test local adaptive thresholds. Results showed significant differences in porosity values across methods. Otsu, region growing, and K-means clustering excelled under uniform illumination, while Sauvola and Bradley-Roth performed better with uneven illumination. Comparison with X-ray computed tomography (XCT) revealed slightly lower porosity values (2.55 %) than optimized methods (2.73–2.79 %) due to XCT's lower resolution excluding smaller pores. While XCT offers finer pore detection, it limits sample volume and underestimates porosity due to spatial variation. Validation using artificial grayscale images with 5 % porosity confirmed that Otsu, Bradley-Roth, region growing, and Sauvola algorithms produced accurate results. Although tested on a single material system, these methods can be adapted to others with optimization. In conclusion, given XCT's high computational and time costs, this study highlights suitable image processing techniques as cost-effective alternatives for porosity analysis in polymer composites.

Additive manufacturing↗
DOE OSTI2019

Effect of Isovalent Cation Substitution on the Thermal, Caloric, and Magnetocaloric Properties of the (La{sub 1 –} {sub y}Eu{sub y}){sub 0.7}Pb{sub 0.3}MnO{sub 3} Manganites

Crystalline samples of the (La{sub 1 –} {sub y}Eu{sub y}){sub 0.7}Pb{sub 0.3}MnO{sub 3} (y = 0, 0.2, 0.4, 0.5, 0.6, and 0.8) manganite solid solutions have been grown. Temperature dependences of the specific heat, thermal expansion, and high-intensity magnetocaloric effect have been investigated. A comparative analysis of the effect of isovalent cationic substitution on the thermal and caloric parameters of the ferromagnetic phase transition has been made. It has been shown that the growth of the Eu atom concentration leads to a decrease in the phase transition entropy and an increase in the baric coefficient dT/dp. Field and temperature dependences of the magnetocaloric effect have been established. It is demonstrated that, varying the ratio of cations, one can obtain the solid solutions with the maximum magnetocaloric effect value in fields of up to 6 kOe in a temperature range of 90–340 K. Owing to the similar reduced relative cooling powers, the investigated solid solutions can be used as reference solid-state cooling media in designing the cascade cooling systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Structure–Activity Relationships in Ether-Functionalized Solid-State Metal–Organic Framework Electrolytes

The structure–property relationships of metal–organic framework (MOF)-based solid-state electrolytes are not well understood. Herein, a systematic investigation of 12 Zr(IV)-based UiO-66 MOFs with varying ether-chain functional groups was carried out to elucidate the critical microscopic interactions that facilitate improved solid-state electrolyte performance. Enhanced sampling molecular dynamics (MD) simulations were employed and revealed a three-tier ion hopping mechanism: linker–linker hopping, linker-counterion hopping, and counterion-counterion hopping. Detailed structural analysis of the MD trajectories revealed that the chemistry and morphology of the linker groups affect the relative stability and population distribution of the electrolyte components, such that crown-ether-based linker groups enhance the probability of extended, low-barrier ion percolation pathways. As a result, we were able to tune the ionic conductivities by rationally manipulating the counterion distributions, linker binding strengths, and the configurational entropy (multivariability of the linkers). The resulting performance of these MOF-based solid-state electrolytes was significantly enhanced, with a methoxy-functionalized framework (UiO-66-L1 100 ) achieving high ionic conductivities of 2.32 × 10 –4 S/cm and 2.07 × 10 –3 S/cm at 30 °C and 90 °C, respectively, an order of magnitude greater than other all-solid-state MOF electrolyte systems. The electrolyte stability was evaluated with LiIn|LPSCl|MOF:LiTFSI|LPSCl|LiIn symmetric cells, showing excellent Li plating/stripping processes for over 2 months.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Experimental X-ray Charge-Density Studies–A Suitable Probe for Superconductivity? A Case Study on MgB 2

Case studies of 1T-TiSe 2 and YBa 2 Cu 3 O 7-δ have demonstrated that X-ray diffraction (XRD) studies can be used to trace even subtle structural phase transitions which are inherently connected with the onset of superconductivity in these benchmark systems. However, the utility of XRD in the investigation of superconductors like MgB 2 lacking an additional symmetry-breaking structural phase transition is not immediately evident. Nevertheless, high-resolution powder XRD experiments on MgB 2 in combination with maximum entropy method analyses hinted at differences between the electron density distributions at room temperature and 15 K, that is, below the T c of approx. 39 K. The high-resolution single-crystal XRD experiments in combination with multipolar refinements presented here can reproduce these results but show that the observed temperature-dependent density changes are almost entirely due to a decrease of atomic displacement parameters as a natural consequence of a reduced thermal vibration amplitude with decreasing temperature. Our investigations also shed new light on the presence or absence of magnesium vacancies in MgB 2 samples–a defect type claimed to control the superconducting properties of the compound. Here, we propose that previous reports on the tendency of MgB 2 to form non-stoichiometric Mg 1–x B 2 phases (1 – x ~ 0.95) during high-temperature (HT) synthesis might result from the interpretation of XRD data of insufficient resolution and/or usage of inflexible refinement models. Indeed, advanced refinements based on an Extended Hansen–Coppens multipolar model and high-resolution X-ray data, which consider explicitly the contraction of core and valence shells of the magnesium cations, do not provide any significant evidence for the formation of non-stoichiometric Mg 1–x B 2 phases during HT synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reducing the Parameter Dependency of Phase-Picking Neural Networks with Dice Loss

Training a neural network for picking seismic phase arrivals has been commonly posed as a segmentation problem. It is a highly imbalanced segmentation problem in the sense that the background vastly dominates the foreground because we are trying to pick the optimal single sample point that represents the arrival of a seismic phase in a many seconds long time window. Here, we test the Dice loss, which is a preferred loss function for highly imbalanced image segmentation problems. We show that phase-picking neural networks trained on the Dice loss behave in a binary fashion for which the prediction output is almost always either nearly 1 or nearly 0. This feature removes the strong dependence of data processing workflows on the prediction score threshold, which is an otherwise critical parameter to determine when using neural networks trained on the cross-entropy loss. When strategically used, models trained on the Dice loss can reduce the parameter dependency of machine learning-based seismic monitoring.

58 GEOSCIENCES↗
DOE OSTI2025

Selective Oxidation and Cr Segregation in High-Entropy Oxide Thin Films

High-entropy oxides (HEOs) offer exceptional compositional flexibility and structural stability, making them promising materials for energy and catalytic applications. Here, in this study, we investigate Sr doping effects on B-site cation oxidation states, local composition, and structure in epitaxial La 1–x Sr x (Cr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 )O 3 thin films. X-ray spectroscopies reveal that Sr doping preferentially promotes Cr oxidation from Cr 3+ to Cr 6+ , partially oxidizes Co and Ni, while leaving Mn 4+ and Fe 3+ unchanged. Atomic-resolution scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy shows pronounced Cr segregation, with depletion at the interface and enrichment at the surface, along with partial amorphization in heavily Sr-doped samples. This segregation is likely driven by oxidation-induced migration of smaller, high-valence Cr cations during growth. These findings highlight the critical interplay between charge compensation, local strain, and compositional fluctuations in HEOs, indicating that precise control over growth conditions is critical for tuning their surface composition and electronic structure toward more robust electrocatalyst design.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Magnetic properties and transformation of crystal structure in the ErFe{sub 2}-ErAl{sub 2} system

The modification of structural properties and magnetic behaviour of the ErFe{sub 2−x}Al{sub x} Laves phase intermetallic compounds have been studied while changing the Al content in the range 0.36 ≤ x ≤ 1.5. Powder X-ray diffraction study at room temperature showed the formation of the cubic C15 structure, in the samples with Al content of 0.36 ≤ x < 0.75 and 1.4 ≤ x ≤ 2.0. For the intermediate compositions with 0.75 ≤ x ≤ 1.4, the hexagonal C14 structure is observed. Magnetic and magnetocaloric properties of polycrystalline ErFe{sub 2−x}Al{sub x} intermetallic compounds were investigated experimentally using magnetic and heat capacity measurements. The Curie temperature T{sub C} decreases from 275 to 28 K as the Al content increases from x = 0.36 to x = 1.5, respectively. Magnetization measurements in strong magnetic fields showed the complex mechanism of magnetic saturation in the studied compounds. Under an external field change from 0 to 2 T, the maximum entropy change is 6 J/kg K at T = 28 K for the composition with x = 1.5. The minimum in the concentration dependence of the magnetic entropy change is observed in the vicinity of x equal to 1.25. Regularities of variations of magnetocaloric properties of ErFe{sub 2−x}Al{sub x} intermetallic compounds with increasing Al content are discussed from the point of view of their both structural and magnetic states.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Multiphonon: Phonon Density of States tools for Inelastic Neutron Scattering Powder Data

The multiphonon python package calculates phonon density of states, a reduced representation of vibrational property of condensed matter (see, for example, Section “Density of Normal Modes” in Chapter 23 “Quantum Theory of the Harmonic Crystal” of (Ashcroft and Mermin 2011)), from inelastic neutron scattering (see, for example (B. Fultz et al. 2006–2016)) spectrum from a powder sample. Inelastic neutron spectroscopy (INS) is a probe of excitations in solids of vibrational or magnetic origins. In INS, neutrons can lose(gain) energy to(from) the solid in the form of quantized lattice vibrations – phonons. Measuring phonon density of states is usually the first step in determining the phonon properties of a material experimentally. Phonons play a very important role in understanding the physical properties of a solid, including thermal conductivity and electrical conductivity. Hence, INS is an important tool for studying thermoelectric materials (Budai et al. 2014, Li et al. (2015)), where low thermal conductivity and high electrical conductivity are desired. Study of phonon entropy also made important contributions to the research of thermal dynamics and phase stability of materials (B. Fultz 2010, bogdanoff2002phonon, swan2006vibrational).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mechanism of Stoichiometrically Governed Titanium Oxide Brownian Tree Formation on Stepped Au(111)

Previously observed formation of substoichiometric titanium oxide dendritic structures across terraces of Au(111) is computationally studied and shown to follow the classical fractal formation mechanism of diffusion-limited aggregation (DLA). Globally optimized gas-phase oxide cluster structures are sampled in a variety of landing formations on gold surfaces and shown to favor isomers driving polymerization to Brownian tree fractal structures. Mobility of Ti 3 O 5 monomers is shown to be extremely high, with diffusion barriers of 0.21 eV or less. Through bonding stabilization, polymerization of these monomers is energetically favorable and irreversible on the 111 terrace but geometrically impossible to propagate along the step edge. Simulated scanning tunneling microscopy (STM) images show strong similarity to experiment. By contrast, observation of Ti 3 O 6 aggregating as wires along step edges is explained by the affinity of oxygen to step edges and statistical arguments for aggregation entropy at the step, in addition to low barriers for monomer diffusion and polymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2015

FCRD Transmutation Fuels Handbook 2015

Transmutation of minor actinides such as Np, Am, and Cm in spent nuclear fuel is of international interest because of its potential for reducing the long-term health and safety hazards caused by the radioactivity of the spent fuel. One important approach to transmutation (currently being pursued by the DOE Fuel Cycle Research & Development Advanced Fuels Campaign) involves incorporating the minor actinides into U-Pu-Zr alloys, which can be used as fuel in fast reactors. It is, therefore, important to understand the properties of U-Pu-Zr alloys, both with and without minor actinide additions. In addition to requiring extensive safety precautions, alloys containing U and Pu are difficult to study for numerous reasons, including their complex phase transformations, characteristically sluggish phase-transformation kinetics, tendency to produce experimental results that vary depending on the histories of individual samples, and sensitivity to contaminants such as oxygen in concentrations below a hundred parts per million. Many of the experimental measurements were made before 1980, and the level of documentation for experimental methods and results varies widely. It is, therefore, not surprising that little is known with certainty about U-Pu-Zr alloys, and that general acceptance of results sometimes indicates that there is only a single measurement for a particular property. This handbook summarizes currently available information about U, Pu, Zr, and alloys of two or three of these elements. It contains information about phase diagrams and related information (including phases and phase transformations); heat capacity, entropy, and enthalpy; thermal expansion; and thermal conductivity and diffusivity. In addition to presenting information about materials properties, it attempts to provide information about how well the property is known and how much variation exists between measurements. Although the handbook includes some references to publications about modeling, its primary focus is experimental data. Most of the data has been published elsewhere (although scattered throughout numerous references, some quite obscure); however, some data is presented here for the first time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2022

Mars Terrain Segmentation with Less Labels

Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain segmentation methods rely on supervised learning which is very data hungry and difficult to train where only a small number of labeled samples are available. Moreover, the semantic classes are defined differently for different applications (e.g., rover traversal vs. geological) and as a result the network has to be trained from scratch each time, which is an inefficient use of resources. This research proposes a semi-supervised learning framework for Mars terrain segmentation where a deep segmentation network trained in an unsupervised manner on unlabeled images is transferred to the task of terrain segmentation trained on few labeled images. The network incorporates a backbone module which is trained using a contrastive loss function and an output atrous convolution module which is trained using a pixel-wise cross-entropy loss function. Evaluation results using the metric of segmentation accuracy show that the proposed method with contrastive pre-training outperforms plain supervised learning by 2%-10%. Moreover, the proposed model is able to achieve a segmentation accuracy of 91.1% using only 161 training images (1% of the original dataset) compared to 81.9% with plain supervised learning.

Wilson, Brian D↗
DOE OSTI2016

A New CE TSUNAMI-3D Capability for Calculating Undersampling Metrics and Biases

This study investigates the viability of several statistical metrics for predicting the undersampling biases in continuous-energy (CE) Monte Carlo transport simulation tally estimates. Undersampling is a phenomenon in which a Monte Carlo simulation fails to use enough particles per generation to adequately sample fission points in all regions of a problem, resulting in biases in tally estimates that are much larger than the statistical uncertainties, potentially leading to erroneous conclusions regarding system performance and safety. Previous work found that biases due to undersampling could be as large as several hundred per cent mille (pcm) for eigenvalue estimates and up to tens or hundreds of percent for flux tally estimates. This paper documents the encapsulation of undersampling metrics within CE TSUNAMI-3D in the SCALE code system and examines the correlation between the various undersampling metric scores and the magnitude of various undersampling biases. Of the metrics examined, the RHW metric, the Tally Entropy metric, and the uncertainty in the scores for these metrics produce scores that correlated well with the fraction of the undersampling biases in various eigenvalue, flux, and energy-integrated reaction rate tallies in an infinitely reflected model of a PWR fuel assembly. The average number of nonzero scores per generation encountered by a tally was also found to show promise at predicting the magnitude of undersampling biases, and it also found use in detecting and filtering extremely undersampled tallies in the application of the other metrics. Future work will strengthen these conclusions by improving the degree of convergence for the examined tally and undersampling bias estimates, apply these metrics to a more broad variety of systems, and investigate variance reduction approaches for mitigating undersampling in Monte Carlo tally estimates. (authors)

42 ENGINEERING↗
DOE OSTI2018

Effects of non-hydrostaticity and grain size on the pressure-induced phase transition of the CoCrFeMnNi high-entropy alloy

Recently, an irreversible polymorphic transition from face-centered cubic to hexagonal close-packing was surprisingly observed under high pressure in the prototype CoCrFeMnNi high-entropy alloys (HEAs) by various research groups. This unexpected phase transition brings new insights into the stability of HEAs, and its irreversibility stimulates exploration for new HEAs via high-pressure compression synthesis. However, the onset pressure for the phase transition was reported to fluctuate over a vast range from ~7 to above 49 GPa in the reported experiments. The reason for this inconsistency remains unclear and puzzles the HEA community. To address this problem, this work systematically investigates the effects of non-hydrostaticity and grain size. Our results demonstrate that larger deviatoric stress induced by the non-hydrostaticity of the pressure medium and larger grain size of the initial sample can both promote a phase transition and, therefore, considerably depress the onset pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heat capacity and thermodynamic functions of transition metal ion (Cu 2+ , Fe 2+ , Mn 2+ ) exchanged, partially dehydrated zeolite $\mathrm{A}$ ($\mathrm{LTA}$)

Here we have measured the heat capacity from 1.8 to 300 K of partially dehydrated zeolite A (LTA), fully exchanged with Cu 2+ , Fe 2+ , and Mn 2+ ions. The samples have a broad excess heat capacity contribution centered around 4 K, which we attribute to local electric fields splitting the magnetic moments of the cations. The excess heat capacity is modelled using a sum of several Schottky anomalies. From these models, we conclude that the cations in the Cu 2+ zeolite reside in at least four distinct coordination environments, and that some of the coordination environments in all three zeolites are highly asymmetric. We also report theoretical fits of the heat capacity data, and values of the standard thermodynamic functions C P,m , Δ 0K T S m ° , Δ 0K T H m ° , and Φ m ° at smooth temperatures. The standard molar entropies at 298.15 K are 71.8 J·K -1 ·mol -1 for Cu-zeolite A (Cu 0.22 Al 0.49 Si 0.51 O 2 1.04 H 2 O), 71.1 J·K -1 ·mol -1 for Fe-zeolite A (Na 0.01 Fe 0.23 Al 0.50 Si 0.51 O 2 ∙0.77 H 2 O), and 66.0 J·K -1 ·mol -1 for Mn-zeolite A (Mn 0.26 Al 0.49 Si 0.50 O 2 ∙0.53 H 2 O).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

Sloshing of the Magnetized Cool Gas in the Cores of Galaxy Clusters

X-ray observations of many clusters of galaxies reveal the presence of edges in surface brightness and temperature, known as "cold fronts". In relaxed clusters with cool cores, these edges have been interpreted as evidence for the "sloshing" of the core gas in the cluster's gravitational potential. The smoothness of these edges has been interpreted as evidence for the stabilizing effect of magnetic fields "draped" around the front surfaces. To check this hypothesis, we perform high-resolution magnetohydrodynamics simulations of magnetized gas sloshing in galaxy clusters initiated by encounters with subclusters. We go beyond previous works on the simulation of cold fronts in a magnetized intracluster medium by simulating their formation in realistic, idealized mergers with high resolution ((Delta)x approx. 2 kpc). Our simulations sample a parameter space of plausible initial magnetic field strengths and field configurations. In the simulations, we observe strong velocity shears associated with the cold fronts amplifying the magnetic field along the cold front surfaces, increasing the magnetic field strength in these layers by up to an order of magnitude, and boosting the magnetic pressure up to near-equipartition with thermal pressure in some cases. In these layers, the magnetic field becomes strong enough to stabilize the cold fronts against Kelvin-Helmholtz instabilities, resulting in sharp, smooth fronts as those seen in observations of real clusters. These magnetic fields also result in strong suppression of mixing of high and low-entropy gas in the cluster, seen in our simulations of mergers in the absence of a magnetic field. As a result, the heating of the core due to sloshing is very modest and is unable to stave off a cooling catastrophe.

ZuHone, J. A.↗