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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

On the Five-Moment Hamburger Maximum Entropy Reconstruction

We consider the Maximum Entropy Reconstruction (MER) as a solution to the five-moment truncated Hamburger moment problem in one dimension. In the case of five monomial moment constraints, the probability density function (PDF) of the MER takes the form of the exponential of a quartic polynomial. This implies a possible bimodal structure in regions of moment space. An analytical model is developed for the MER PDF applicable near a known singular line in a centered, two-component, third- and fourth-order moment (μ{sub 3}, μ{sub 4}) space, consistent with the general problem of five moments. The model consists of the superposition of a perturbed, centered Gaussian PDF and a small-amplitude packet of PDF-density, called the outlying moment packet (OMP), sitting far from the mean. Asymptotic solutions are obtained which predict the shape of the perturbed Gaussian and both the amplitude and position on the real line of the OMP. The asymptotic solutions show that the presence of the OMP gives rise to an MER solution that is singular along a line in (μ{sub 3}, μ{sub 4}) space emanating from, but not including, the point representing a standard normal distribution, or thermodynamic equilibrium. We use this analysis of the OMP to develop a numerical regularization of the MER, creating a procedure we call the Hybrid MER (HMER). Compared with the MER, the HMER is a significant improvement in terms of robustness and efficiency while preserving accuracy in its prediction of other important distribution features, such as higher order moments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Study of the Thermomechanical Performance of FR-4 Laminates During the Reflow Process

The behavior of FR4 laminates for printed circuit boards (PCBs) during a double reflow process and the main factors associated with warpage are discussed. The microstructure, glass transition temperature (T{sub g}), decomposition temperature (T{sub d}), coefficient of thermal expansion (CTE), time to delamination and % water absorption were characterized, and the temperature profiles in the board during its pass through the reflow oven were recorded. Bow and twist measurements were taken on a set of 30 PCBs. Both T{sub d} and T{sub g} were found to be below their nominal values. The CTE is highly anisotropic and vary at different locations, and it is more than three times higher in the through thickness middle section with respect to the bottom and top locations. Temporary temperature gradients of more than 50 degrees between different locations were detected at the start of the reflow step as a result, the bow values were found to be strongly anisotropic, particularly after the first reflow, in which different sides can present bow values up to more than six times higher than others, with maxima values of 0.47 mm. The anisotropy of the CTE appears to affect only slightly the twist values. Compared with the first reflow, the bow and twist values are lower, exhibit less dispersion and are more homogeneous for the second reflow. The histograms of both bow and twist do not seem to follow a normal distribution, possibly as a result of the combined effect of spatial variations and anisotropy of properties as well as the temperature gradients during reflow.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The method of imbedded Lagrangian element to estimate wave power absorption by some submerged devices

A simple approach is described to estimate the wave power absorption potential of submerged devices known to cause wave focusing and flow enhancement. In particular, the presence of a flow-through power take-off (PTO) system, such as low-head turbines, can be accounted for. The wave radiation characteristics of an appropriately selected Lagrangian element (LE) in the fluid domain are first determined. In the limit of a vanishing mass, the LE reduces to a patch of distributed normal dipoles. Here, the hydrodynamic coefficients of this virtual object are then input in a standard equation of motion where the effect of the PTO can be represented, for example, as a dashpot damping term. The process is illustrated for a class of devices recently proposed by Carter and Ertekin (2011), although in a simplified form. Favorable wave power absorption is shown for large ratios of the LE wave radiation coefficient over the LE added mass coefficient. Under optimal conditions, the relative flow reduction from the PTO theoretically lies between 0.50 and 1/√2≈ 0.71, with lower values corresponding to better configurations. Wave power capture widths, the sensitivity of results to PTO damping and sample spectral calculations at a typical site in Hawaiian waters are proposed to further illustrate the versatility of the method.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

Tannic Acid: a Novel Calibrator for Facile and Accurate Mass Measurement of Electrospray Ionization Mass Spectrometry

Accurate mass calibration is beneficial to the identification of the unknown compounds quickly and accurately. The ESI mass spectrum of tannic acid (TA) tends to a normal distribution of the cluster ion peaks in m/z range from 371.0368 to 1739.1169. Based on the interesting result, we reported the use of TA, a natural plant polyphenol, as a novel calibrator for electrospray ionization mass spectrometry (ESI MS), which has the following three advantages, including (1) easy preparation, (2) the calibration range of m/z 200~2000, and (3) the calibration error is around 3.00 ppm in positive ion mode, which is less than the use of sodium formate (SF) and Prod #88323 calibrators. This TA calibrator has great potential for the wide applications in biological, chemical, and pharmacal analysis. .

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Efficient computation of basic sums for random polydispersed composites

The main goal of the paper was to develop algorithms and methods for computation of basic sums, the mathematical objects of great importance in computational materials science having applications to description of the representative volume element (RVE) and to the effective properties of 2D composites. The previously used algorithm had the exponential complexity. We propose a linearly complex algorithm. All the presented algorithms can be easily implemented in modern scientific computing packages, while maintaining both efficient calculations and a high level of abstraction. The proposed approach is applied to derivation of a polynomial approximation of the effective conductivity formula for 2D random material with non-overlapping circular inclusions with normally distributed radii. The obtained formulas are applied to the optimal packing problem of disks on the plane.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Disordered crystals from first principles I: Quantifying the configuration space

This work represents the first chapter of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures. We are interested in the range of temperatures, where most electronic components operate, that is, room temperature and above. The aim is a predictive first-principle formalism that combines ab-initio molecular dynamics and a finite-temperature Kubo-formula for homogeneous thermodynamic phases. The input for this formula is the ergodic dynamical system (Ω,G,dP) defining the thermodynamic crystalline phase, where Ω is the configuration space for the atomic degrees of freedom, G is the space group acting on Ω and dP is the ergodic Gibbs measure relative to the G-action. The present work develops an algorithmic method for quantifying (Ω,G,dP) from first principles. Using the silicon crystal as a working example, we find the Gibbs measure to be extremely well characterized by a multivariate normal distribution, which can be quantified using a small number of parameters. The latter are computed at various temperatures and communicated in the form of a table. Using this table, one can generate large and accurate thermally-disordered atomic configurations to serve, for example, as input for subsequent simulations of the electronic degrees of freedom.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Genetics of osteoporosis

Highlights: • Single-nucleotide polymorphisms (SNPs) associated with osteoporosis were identified. • SNPs mapped close to or within VDR and ESR1 are associated with bone mineral density. • WNT signaling pathway plays a pivotal role in regulating bone mineral density. • Genetic studies will be useful for identification of new therapeutic targets. - Abstract: Osteoporosis is a skeletal disease characterized by low bone mineral density (BMD) and microarchitectural deterioration of bone tissue, which increases susceptibility to fractures. BMD is a complex quantitative trait with normal distribution and seems to be genetically controlled (in 50–90% of the cases), according to studies on twins and families. Over the last 20 years, candidate gene approach and genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with low BMD, osteoporosis, and osteoporotic fractures. These SNPs have been mapped close to or within genes including those encoding nuclear receptors and WNT-β-catenin signaling proteins. Understanding the genetics of osteoporosis will help identify novel candidates for diagnostic and therapeutic targets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗
DOE OSTI2023

A new approach to model geomaterials with heterogeneous properties in thermo-hydro-mechanical coupled problems

The main objective of this article is to present a new approach to model coupled thermo-hydro-mechanical problems considering geomaterials with heterogeneous properties. This approach has been implemented in the software CODE_BRIGHT and it provides the possibility of considering geomaterials with a spatially correlated heterogeneous field of porosity, following a normal distribution. This spatial correlation can be isotropic or anisotropic. An important feature of this approach is that material properties such as intrinsic permeability, thermal conductivity, diffusivity, retention curve, elastic modulus or cohesion are defined as a function of porosity and, thus, they become heterogeneous with spatial correlation and, eventually, anisotropic. A validation exercise and other basic numerical examples have been carried out to illustrate the possibilities of the proposed approach. The results, which have been compared with a homogeneous case, show that considering heterogeneous fields can be relevant in different modelling problems, especially coupled thermo-hydro-mechanical problems.

42 ENGINEERING↗
DOE OSTI2019

A probabilistic perspective on thermodynamic parameter uncertainties: Understanding aqueous speciation of mercury

Speciation plays an important role in determining the fate and transport of metals in terrestrial surface and subsurface systems. Equilibrium speciation modeling in aqueous systems relies on thermodynamic constants (log K values) of complexes, which are subject to uncertainties. In this study, using Monte Carlo (MC) simulations with Latin hypercube sampling (LHS) we systematically analyze the propagation of thermodynamic constant uncertainty through speciation modeling of an inorganic mercury-sulfide-chloride-water system. We find that seemingly small variances of the input log K normal distributions can lead to output species concentrations spanning multiple orders of magnitude, with highly skewed probability distributions. When equilibrium with mineral metacinnabar (β-HgS(s)) is neglected, the relative uncertainty of each output species is strongly positively correlated with the skewness of its concentration probability distribution, i.e., the lowest uncertainty occurs when the species concentration probability distribution is the most negatively skewed as its concentration approaches the total element concentration limit. The highest uncertainty in the identity of dominant species is located around species equivalence points. For cases where the mineral equilibrium is included, we derive analytical probability density functions for the log concentrations of all major species in the system. The mineral log K uncertainty is found to be an important contributor to all output concentration uncertainties. The analysis of combined effects of both pH and total sulfide concentration on output concentration uncertainties shows that high concentration uncertainties occur under highly sulfidic alkaline conditions and low uncertainties at low pH and sulfide concentrations. Finally, an analysis as presented here can distinguish between conditions that require a full uncertainty analysis and those for which the classical deterministic speciation modeling suffices.

58 GEOSCIENCES↗
DOE OSTI2023

Determining the tensile strength of fuel surrogate TRISO-coated particle buffer, IPyC, and buffer-IPyC interlayer regions

A novel micro tensile sample fabrication technique for determining the tensile strength of the buffer, IPyC, and buffer -IPyC interlayer regions of surrogate (ZrO2) TRISO fuel particle layers was refined and implemented. Copper micro tensile samples served as baseline materials to verify the methods used. Tensile tests performed in this study, while limited in number, were analyzed using standard and Weibull statistics. As expected, the buffer layer was weakest, with an average ultimate tensile strength of 138.70 MPa, and the IPyC layer samples, were strongest, with an average ultimate tensile strength of 189.74 MPa. In the buffer -IPyC interface samples, all breaks occurred in the buffer region, though the average ultimate tensile strength of the samples, 159.80 MPa, was between the pure buffer and IPyC samples. These results suggest the interlayer region has unique properties, perhaps associated with pyrocarbon infiltration into the buffer layer during particle coating. All interlayer samples fractured within the buffer side; however, the stress strain behavior of some of these samples resembled the behavior of the IPyC layer samples. Here, the buffer and IPyC layer strengths had a normal distribution under Weibull analysis, while the interlayer region had a Rayleigh distribution. Further testing is needed to clarify both the standard and Weibull statistical results

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Production and cross-sectional characterization of aligned co-electrospun hollow microfibrous bulk assemblies

The development of co-electrospun (co-ES) hollow microfibrous assemblies of an appreciable thickness is critical for many practical applications, including filtration membranes and tissue-mimicking scaffolds. In this study, thick uniaxially aligned hollow microfibrous assemblies forming fiber bundles and strips were prepared by co-ES of polycaprolactone (PCL) and polyethylene oxide (PEO) as shell and core materials, respectively. Hollow microfiber bundles were deposited on a fixed rotating disc, which resulted in non-controllable cross-sectional shapes on a macroscopic scale. In comparison, fiber strips were produced with tuneable thickness and width by additionally employing an x–y translation stage in co-ES. Scanning electron microscopy (SEM) images of cross-sections of fiber assemblies were analyzed to investigate the effects of production time (from 0.5 h to 12 h), core flow rate (from 0.8 mL/h to 2.0 mL/h) and/or translation speed (from 0.2 mm/s to 5 mm/s) on the pores and porosity. We observed significant changes in pore size and shape with core flow rate but the influence of production time varied; five strips produced under the same conditions had reasonably good size and porosity reproducibility; pore sizes didn't vary significantly from strip bottom to surface, although the porosity gradually decreased and then returned to the initial level. - Highlights: • Hollow microfibrous assemblies based on co-electrospinning are demonstrated. • The thickness and width of co-electrospun strips were controllable. • Cross-sections of fibres had non-normally distributed pore sizes and shapes. • Cross-sections were significantly influenced by production time and flow rate. • Co-electrospun strips had reasonably good reproducible cross-sections.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning

Accurate prediction of the optimal catalytic temperature ( T opt ) of enzymes is vital in biotechnology, as enzymes with high T opt values are desired for enhanced reaction rates. Recently, a machine learning method (temperature optima for microorganisms and enzymes, TOME) for predicting T opt was developed. TOME was trained on a normally distributed data set with a median T opt of 37 °C and less than 5% of T opt values above 85 °C, limiting the method’s predictive capabilities for thermostable enzymes. Due to the distribution of the training data, the mean squared error on T opt values greater than 85 °C is nearly an order of magnitude higher than the error on values between 30 and 50 °C. Here, we apply ensemble learning and resampling strategies that tackle the data imbalance to significantly decrease the error on high T opt values (>85 °C) by 60% and increase the overall R 2 value from 0.527 to 0.632. The revised method, temperature optima for enzymes with resampling (TOMER), and the resampling strategies applied in this work are freely available to other researchers as Python packages on GitHub.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Surface Morphology and Electrical Properties of Cu 3 BTC 2 Thin Films Before and After Reaction with TCNQ

HKUST-1 or Cu 3 BTC 2 (BTC = 1,3,5-benzenetricarboxylate) is a prototypical metal–organic framework (MOF) that holds a privileged position among MOFs for device applications, as it can be deposited as thin films on various substrates and surfaces. Recently, new potential applications in electronics have emerged for this material when HKUST-1 was demonstrated to become electrically conductive upon infiltration with 7,7,8,8-tetracyanoquinodimethane (TCNQ). However, the factors that control the morphology and reactivity of the thin films are unknown. Here, we present a study of the thin-film growth process on indium tin oxide and amorphous Si prior to infiltration. From the unusual bimodal, non-log-normal distribution of crystal domain sizes, we conclude that the nucleation of new layers of Cu 3 BTC 2 is greatly enhanced by surface defects and thus difficult to control. We then show that these films can react with methanolic TCNQ solutions to form dense films of the coordination polymer Cu(TCNQ). This chemical conversion is accompanied by dramatic changes in surface morphology, from a surface dominated by truncated octahedra to randomly oriented thin platelets. The change in morphology suggests that the chemical reaction occurs in the liquid phase and is independent of the starting surface morphology. The chemical transformation is accompanied by 10 orders of magnitude change in electrical conductivity, from <10 –11 S/cm for the parent Cu 3 BTC 2 material to 10 –1 S/cm for the resulting Cu(TCNQ) film. In conclusion, the conversion of Cu 3 BTC 2 films, which can be grown and patterned on a variety of (nonplanar) substrates, to Cu(TCNQ) opens the door for the facile fabrication of more complex electronic devices.

2D nucleation↗
DOE OSTI2020

Parameterizing Subgrid Variations of Land Surface Heat Fluxes to the Atmosphere Improves Boreal Summer Land Precipitation Simulation With the NCAR CESM1.2

Subgrid horizontal variations of land surface heat fluxes to the atmosphere resulting from subgrid land cover heterogeneity are important in land-atmosphere interaction in global climate models (GCMs). To incorporate it, a parameterization using stochastic sampling based on truncated normal distributions diagnosed from the land model and internal ensemble mean of multiple calls to the planetary boundary layer and deep convection schemes is developed. After its implementation in the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.2 (CESM1.2), large changes of simulated land precipitation are found to occur in regions where large subgrid variations of surface heat fluxes exist. The simulated precipitation is improved in boreal summer, especially over eastern China and the coastal areas of the Bay of Bengal. The improved precipitation is mainly a result of improved large-scale moisture convergence and advection by altered vertical diffusion and convection.

58 GEOSCIENCES↗
DOE OSTI2014

Reconstruction 3-dimensional image from 2-dimensional image of status optical coherence tomography (OCT) for analysis of changes in retinal thickness

Optical Coherence Tomography is often used in medical image acquisition to diagnose that change due easy to use and low price. Unfortunately, this type of examination produces a two-dimensional retinal image of the point of acquisition. Therefore, this study developed a method that combines and reconstruct 2-dimensional retinal images into three-dimensional images to display volumetric macular accurately. The system is built with three main stages: data acquisition, data extraction and 3-dimensional reconstruction. At data acquisition step, Optical Coherence Tomography produced six *.jpg images of each patient were further extracted with MATLAB 2010a software into six one-dimensional arrays. The six arrays are combined into a 3-dimensional matrix using a kriging interpolation method with SURFER9 resulting 3-dimensional graphics of macula. Finally, system provides three-dimensional color graphs based on the data distribution normal macula. The reconstruction system which has been designed produces three-dimensional images with size of 481 × 481 × h (retinal thickness) pixels.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Financial derivative pricing under probability operator via Esscher transfomation

The problem of pricing contingent claims has been extensively studied for non-Gaussian models, and in particular, Black- Scholes formula has been derived for the NIG asset pricing model. This approach was first developed in insurance pricing{sup 9} where the original distortion function was defined in terms of the normal distribution. This approach was later studied6 where they compared the standard Black-Scholes contingent pricing and distortion based contingent pricing. So, in this paper, we aim at using distortion operators by Cauchy distribution under a simple transformation to price contingent claim. We also show that we can recuperate the Black-Sholes formula using the distribution. Similarly, in a financial market in which the asset price represented by a stochastic differential equation with respect to Brownian Motion, the price mechanism based on characteristic Esscher measure can generate approximate arbitrage free financial derivative prices. The price representation derived involves probability Esscher measure and Esscher Martingale measure and under a new complex valued measure φ (u) evaluated at the characteristic exponents φ{sub x}(u) of X{sub t} we recuperate the Black-Scholes formula for financial derivative prices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗