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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Calculating Free Energy Changes in Continuum Solvation Models

We recently showed for a large dataset of pK a s and reduction potentials that free energies calculated directly within the SMD continuum model compares very well with corresponding thermodynamic cycle calculations in both aqueous and organic solvents (Phys. Chem. Chem. Phys. 2015, 17, 2859). In this paper, we significantly expand the scope of our study to examine the suitability of this approach for the calculation of general solution phase kinetics and thermodynamics, in conjunction with several commonly used solvation models (SMDM062X, SMD-HF, CPCM-UAKS, and CPCM-UAHF) for a broad range of systems and reaction types. This includes cluster-continuum schemes for pK a calculations, as well as various neutral, radical and ionic reactions such as enolization, cycloaddition, hydrogen and chlorine atom transfer, and bimolecular SN2 and E2 reactions. On the basis of this benchmarking study, we conclude that the accuracies of both approaches are generally very similar – the mean errors for Gibbs free energy changes of neutral and ionic reactions are approximately 5 kJ mol -1 and 25 kJ mol -1 respectively. In systems where there are significant structural changes due to solvation, as is the case for certain ionic transition states and amino acids, the direct approach generally afford free energy changes that are in better agreement with experiment. The results indicate that when appropriate combinations of electronic structure methods are employed, the direct approach provides a reliable alternative to the thermodynamic cycle calculations of solution phase kinetics and thermodynamics across a broad range of organic reactions.

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

Automated Design-for-Reliability of a Power Electronics Module

The design of a power electronics module is a multiphysics problem and involves electrical, thermal, and reliability targets and constraints. Although the electrical and thermal design consider multiple aspects such as materials, geometry, and energy losses, reliability design is often limited to the selection of the attachment materials and electrical interconnect types. In this paper, we incorporate reliability metrics in the design phase by investigating the impact of package geometry on the thermomechanical behavior of the die-attachment material. To this end, we conducted thermal and power cycling simulations of a commercial six-pack power module with silicon carbide devices to compute junction temperature and strain energy density per cycle, respectively. We performed multiple simulations with different geometric dimensions and established a correlation between input features and output variables using subspace-based dimension reduction. The machine learning-based dimension reduction method serves as a surrogate model, which can be employed to identify the optimal module design from a thermal and reliability standpoint.

design-for-reliability↗
DOE OSTI2020

CheKiPEUQ Intro 2: Harnessing Uncertainties from Data Sets, Bayesian Design of Experiments in Chemical Kinetics**

When choosing experimental conditions, Bayesian statistical tools can predict the experimental choices which will yield the highest information gain. Experimental choices could be temperature, pressure, reaction time, number of measurements, reactor volume, etc.. Three example analyses are presented here, each using the software Chemical Kinetics Parameter Estimation and Uncertainty Quantification (CheKiPEUQ). Information gain is a measure of reduction of uncertainty in a model's parameters. The three chemical system examples presented each illustrate Bayesian Design of Experiments using information gain. In the first chemical example, temperature selection impacts the information gain for the free energy of reaction in a two-component equilibrium reaction. In the second example, temperature and pressure are explored for a competitive adsorption Langmuir replacement reaction system. Finally, the third example is a catalytic membrane reactor which is a culmination of the previous examples. The catalytic membrane reactor has a complex and nonlinear response in the observables which is solved by numerical evaluation. In the three examples, the experimental conditions are treated as design variables for maximizing information gain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Using the apparent diffusion coefficient to identifying MGMT promoter methylation status early in glioblastoma: importance of analytical method

Accurate knowledge of O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter subtype in patients with glioblastoma (GBM) is important for treatment. However, this test is not always available. Pre-operative diffusion MRI (dMRI) can be used to probe tumour biology using the apparent diffusion coefficient (ADC); however, its ability to act as a surrogate to predict MGMT status has shown mixed results. We investigated whether this was due to variations in the method used to analyse ADC. We undertook a retrospective study of 32 patients with GBM who had MGMT status measured. Matching pre-operative MRI data were used to calculate the ADC within contrast enhancing regions of tumour. The relationship between ADC and MGMT was examined using two published ADC methods. A strong trend between a measure of ‘minimum ADC’ and methylation status was seen. An elevated minimum ADC was more likely in the methylated compared to the unmethylated MGMT group (U = 56, P = 0.0561). In contrast, utilising a two-mixture model histogram approach, a significant reduction in mean measure of the ‘low ADC’ component within the histogram was associated with an MGMT promoter methylation subtype (P < 0.0246). This study shows that within the same patient cohort, the method selected to analyse ADC measures has a significant bearing on the use of that metric as a surrogate marker of MGMT status. Thus for dMRI data to be clinically useful, consistent methods of data analysis need to be established prior to establishing any relationship with genetic or epigenetic profiling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Plasma Treatment of Onychomycosis

We report on the use of three “cold” atmospheric plasma (CAP) devices in treating model nails that have been coated on the backside of the nail with either Escherichia coli ( E. coli ) bacteria or Trichophyton rubrum ( T. rubrum ) fungus. We tested a helium plasma jet; a surface microdischarge plasma device; and a floating electrode dielectric barrier discharge. All of the devices, acting through the model nail, showed significant log reductions of bacterial and fungal targets in several tens of minutes. CAP technology appears to offer promise as a safe, effective, and inexpensive therapy for fungal nail infection treatment.

Xiong, Zilan↗
DOE OSTI2015

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological Impact

Light absorbing particles (LAP, e.g., black carbon, brown carbon, and dust) influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance (a.k.a., surface darkening), which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice (LAPSI) has been identified as one of major forcings affecting climate change, e.g. in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, andclimatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

light absorbing particles↗
DOE OSTI2018

Electroelastic investigation of drying rate in the direct contact ultrasonic fabric dewatering process

Ultrasonic vibrations, used to atomize liquids into a fine mist, are a promising solution for the future of efficient clothes drying technology. The world’s first ultrasonic dryer—demonstrated by researchers at Oak Ridge National Laboratory—successfully applies the scientific principles behind ultrasonic drying, and several working prototypes have been demonstrated. This technology is based on direct mechanical coupling between mesh piezoelectric transducers and wet fabric. During the atomization process, vertical oscillations of a contained liquid, called Faraday excitations, result in the formation of standing waves on the liquid surface. At increasing amplitudes and frequencies of oscillation, wave peaks become extended and form “necks” connecting small secondary droplets to the bulk liquid. When the oscillation reaches an acceleration threshold, the droplet momentum is sufficient to break the surface tension of the neck and enable the droplets to travel away from the liquid. In this work, we investigate the atomization process using an ultrasonic transducer as it pertains to moisture retained within a fabric. An experimentally validated electromechanical analytical-numerical model is proposed. This model bridges the vibrations of a piezoelectric mesh transducer to the critical acceleration needed for fabric drying to occur. Then, the drying rate model is developed, consisting of an initial nonlinear region due to atomization, followed by a linear thermal evaporation region. The models developed identify the influence of key parameters on ultrasonic drying and will aid in improving atomizer design for efficient, timely fabric drying. This study is the first proposed model for the ultrasonic atomization of fabrics saturated with water, applicable to any type of transducer. The results present a non-dimensional equation for the ultrasonic dewatering of fabrics, dependent only on transducer acceleration and the surface area of the cloth. Furthermore, the development of this technology using the proposed physical models will allow for global reductions in electrical demand related to clothes drying.

42 ENGINEERING↗
DOE OSTI2022

An optimization framework for the network design of advanced district thermal energy systems

In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Additionally, modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21-25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A class of three-dimensional gyroviscous magnetohydrodynamic models

A Hamiltonian and action principle formalism for deriving three-dimensional gyroviscous magnetohydrodynamic models is presented. The uniqueness of the approach in constructing the gyroviscous tensor from first principles and its ability to explain the origin of the gyromap and the gyroviscous terms are highlighted. The procedure allows for the specification of free functions, which can be used to generate a wide range of gyroviscous models. Through the process of reduction, the noncanonical Hamiltonian bracket is obtained and briefly analysed.

Physics↗
DOE OSTI2020

Absolute Templating of M(111) Cluster Surrogates by Galvanic Exchange

The precise preparation of monodisperse nanomaterials is among the most fundamental tasks in inorganic synthesis and materials science. Achieving this goal by galvanic exchange is hardly predictable, and often results in major structural changes and polydisperse mixtures. Here, taking advantage of the enhanced stability imparted by ambiphilic carbenes, we report and rationalize the absolute templating — the complete exchange of metals in a template — of group 11 clusters across the entire coinage metal family by means of galvanic exchange. We further delineate that these species provide a molecular model for better understanding the reduction of CO 2 at M(111) coinage metal surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

New Evidence for the Importance of Non-Stomatal Pathways in Ozone Deposition During Extreme Heat and Dry Anomalies

Dry deposition could partially explain the observed response in ambient ozone to extreme hot and dry episodes. We examine the response of ozone deposition to heat and dry anomalies using three long-term co-located ecosystem-scale carbon dioxide, water vapor and ozone flux measurement records. We find that, as expected, canopy stomatal conductance generally decreases during days with dry air or soil. However, during hot days, concurrent increases in non-stomatal conductance are inferred at all three sites, which may be related to several temperature-sensitive processes not represented in the current generation of big-leaf models. This may offset the reduction in stomatal conductance, leading to smaller net reduction, or even net increase, in total deposition velocity. We find the response of deposition velocity to soil dryness may be related to its impact on photosynthetic activity, though considerable variability exists. Our findings emphasize the need for better understanding and representation of non-stomatal ozone deposition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Internal climate variability and projected future regional steric and dynamic sea level rise

Observational evidence points to a warming global climate accompanied by rising sea levels which impose significant impacts on island and coastal communities. Studies suggest that internal climate processes can modulate projected future sea level rise (SLR) regionally. It is not clear whether this modulation depends on the future climate pathways. Here, by analyzing two sets of ensemble simulations from a climate model, we investigate the potential reduction of SLR, as a result of steric and dynamic oceanographic affects alone, achieved by following a lower emission scenario instead of business-as-usual one over the twenty-first century and how it may be modulated regionally by internal climate variability. Results show almost no statistically significant difference in steric and dynamic SLR on both global and regional scales in the near-term between the two scenarios, but statistically significant SLR reduction for the global mean and many regions later in the century (2061–2080). However, there are regions where the reduction is insignificant, such as the Philippines and west of Australia, that are associated with ocean dynamics and intensified internal variability due to external forcing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery

The solvation free energy of organic molecules is a critical parameter in determining emergent properties such as solubility, liquid-phase equilibrium constants, and pKa and redox potentials in an organic redox flow battery. In this work, we present a machine learning (ML) model that can learn and predict the aqueous solvation free energy of an organic molecule using Gaussian process regression method based on a new molecular graph kernel. To investigate the performance of the ML model on electrostatic interaction, the nonpolar interaction contribution of solvent and the conformational entropy of solute in solvation free energy, three data sets with implicit or explicit water solvent models, and contribution of conformational entropy of solute are tested. We demonstrate that our ML model can predict the solvation free energy of molecules at chemical accuracy with a mean absolute error of less than 1 kcal/mol for subsets of the QM9 dataset and the Freesolv database. To solve the general data scarcity problem for a graph-based ML model, we propose a dimension reduction algorithm based on the distance between molecular graphs, which can be used to examine the diversity of the molecular data set. It provides a promising way to build a minimum training set to improve prediction for certain test sets where the space of molecular structures is predetermined.

25 ENERGY STORAGE↗
DOE OSTI2026

Feasibility Study on Implementing a Staggered-Grid Finite Volume Method for System Analysis Code Development Under the MOOSE Framework

Here, this work summarizes a feasibility study on testing numerical algorithms that are suitable and efficient for advanced system analysis code development under the mutli-physics framework, MOOSE. The key to the test bed is the implementation of high-order one-dimensional staggered-grid finite volume method (SG-FVM), and its direct interaction with the linear/nonlinear solver, PETSc. The test bed utilized a more flexible code structure to enable the finite volume method implementation and direct interacting with the solver package, instead of using the natively supported finite element method by the framework. Using a suite of selected test problems with different problem sizes and levels of complexity, the implemented SG-FVM demonstrated superior performance improvement against a direct finite element method implementation through MOOSE. On two computer systems, the speedup was observed to be significant, with at least one order of magnitude of solving time reduction. For a complex reactor model, transient simulation was performed using the newly developed finite volume method code, the results of which agree very well with the reference results from the finite element method code. Overall, this study demonstrates a successful feasibility study on the proposed numerical algorithms and software structure to support advanced system analysis tool development.

MOOSE↗
DOE OSTI2021

Disruption thermal load mitigation with shattered pellet injection on the Joint European Torus (JET)

Disruption mitigation remains a critical, unresolved challenge for ITER. To aid in addressing this challenge, a shattered pellet injection (SPI) system was installed on JET and experiments conducted at a range of thermal energy fractions and stored energies in excess of 7 MJ. The primary goals of these experiments were to investigate the efficacy of the SPI on JET and the ability of the plasma to assimilate multiple pellets. Single pellet injections produced a saturation in total radiated energy (Wrad) with increasing injected neon content, suggesting total radiation of stored thermal energy. Further increases in injected neon quantities resulted in reduced cooling times and current quench (CQ) durations, indicating higher impurity assimilation. No significant variation in CQ duration or W rad was observed when varying the deuterium content at fixed neon quantities. Additionally, higher assimilation, inferred by shorter CQ durations, was measured when a mechanical punch was used to launch the pellets and this was attributed to a lower pellet velocity leading to higher solid content in the pellet plume and larger fragments penetrating deeper into the plasma. Radiation asymmetries averaged over the cooling time were inferred from Emis3D and ranged from 1.6 to 1.9. Asymmetries averaged over the entire disruption sequence were found to increase at higher thermal energy fractions. The radiated energy fractions decreased with increasing thermal energy fractions but this trend was eliminated when toroidal asymmetries were accounted for with Emis3D. Pure deuterium pellets were able to produce cooling times of up to 75 ms with a gradual loss in thermal stored energy of up to 80%. Experiments with multiple pellet injection indicated W rad can be increased through pellet superposition and density can be increased with an additional D2 injection without a reduction in W rad . KPRAD modelling accurately reproduced the cooling times and the CQ duration at high thermal energies. Assimilation estimates from KPRAD indicated CQ rates scale strongly whilst W rad scales weakly and saturates with assimilated neon content. Comparable W rad can be achieved with lower assimilated neon quantities as longer cooling times are attained. Thus reduced neon content can be preferential in a thermal load mitigation scheme as it may reduce radiation asymmetries and prevent flash melting.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Interpretive modeling of tungsten divertor leakage during experiments with neon gas seeding

Abstract Many existing and future tokamaks with tungsten divertors operate, or will operate, with low- Z impurity seeding, but the direct effect of these seeded impurities on tungsten Scrape-off-Layer (SOL) transport has not been explored in detail. This paper reports on a DIII-D experiment designed to test how tungsten divertor leakage from the Small-Angle Slot V-Shaped, tungsten-coated divertor is impacted by neon seeding at a variety of injection rates and poloidal injection locations. Measurements from the experiment show an inverse relationship between the neon injection rate and the tungsten core penetration factor. Interpretive modeling is performed with a combination of the SOLPS-ITER and DIVIMP codes to assess the underlying tungsten behavior. The modeling results show that the reduction in tungsten divertor leakage is driven by both an increase in the divertor collisionality as well as a reduction in the ion temperature gradient near the divertor target. Collisions between low- Z impurities and tungsten impurities are found to have a significant impact on the tungsten SOL transport, such that ignoring the low- Z impurity collisional effects on the tungsten transport can result in an overestimate of the divertor leakage by an order-of-magnitude. Given the importance of these localized interactions, neon seeding from the closed, slot-like divertor has a clear advantage in being able to reduce tungsten divertor leakage without the high levels of neon core contamination that occur when seeding from other poloidal locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Novel functional and distributed approaches to data analysis available in ROOT

The bright future of particle physics at the Energy and Intensity frontiers poses exciting challenges to the scientific software community. The traditional strategies for processing and analyzing data are evolving in order to (i) offer higher-level programming model approaches and (ii) exploit parallelism to cope with the ever increasing complexity and size of the datasets. This contribution describes how the ROOT framework, a cornerstone of software stacks dedicated to particle physics, is preparing to provide adequate solutions for the analysis of large amount of scientific data on parallel architectures. The functional approach to parallel data analysis provided with the ROOT TDataFrame interface is then characterized. The design choices behind this new interface are described also comparing with other widely adopted tools such as Pandas and Apache Spark. The programming model is illustrated highlighting the reduction of boilerplate code, composability of the actions and data transformations as well as the capabilities of dealing with different data sources such as ROOT, JSON, CSV or databases. Details are given about how the functional approach allows transparent implicit parallelization of the chain of operations specified by the user. The progress done in the field of distributed analysis is examined. In particular, the power of the integration of ROOT with Apache Spark via the PyROOT interface is shown. In addition, the building blocks for the expression of parallelism in ROOT are briefly characterized together with the structural changes applied in the building and testing infrastructure which were necessary to put them in production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Direct Visualization of Surface Spin-Flip Transition in MnBi 4 Te 7

Here, we report direct visualization of spin-flip transition of the surface layer in antiferromagnet MnBi 4 Te 7 , a natural superlattice of alternating MnBi 2 Te 4 and Bi 2 Te 3 layers, using cryogenic magnetic force microscopy (MFM). The observation of magnetic contrast across domain walls and step edges confirms that the antiferromagnetic order persists to the surface layers. The magnetic field dependence of the MFM images reveals that the surface magnetic layer undergoes a first-order spin-flip transition at a magnetic field that is lower than the bulk transition, in excellent agreement with a revised Mills model. Our analysis suggests no reduction of the order parameter in the surface magnetic layer, implying robust ferromagnetism in the single-layer limit. The direct visualization of surface spin-flip transition not only opens up exploration of surface metamagnetic transitions in layered antiferromagnets, but also provides experimental support for realizing quantized transport in ultrathin films of MnBi 4 Te 7 and other natural superlattice topological magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗