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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

High Performance Computing Modeling Advances Accelerator Science for High-Energy Physics

The development and optimization of particle accelerators are essential for advancing our understanding of the properties of matter, energy, space, and time. Particle accelerators are complex devices whose behavior involves many physical effects on multiple scales. Therefore, advanced computational tools utilizing high-performance computing are essential for accurately modeling them. In the past decade, the US Department of Energy's SciDAC program has produced accelerator-modeling tools that have been employed to tackle some of the most difficult accelerator science problems. The authors discuss the Synergia framework and its applications to high-intensity particle accelerator physics. Synergia is an accelerator simulation package capable of handling the entire spectrum of beam dynamics simulations. Our authors present Synergia's design principles and its performance on HPC platforms.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

A unified RANS–LES model: Computational development, accuracy and cost

Large eddy simulation (LES) is computationally extremely expensive for the investigation of wall-bounded turbulent flows at high Reynolds numbers. A way to reduce the computational cost of LES by orders of magnitude is to combine LES equations with Reynolds-averaged Navier–Stokes (RANS) equations used in the near-wall region. A large variety of such hybrid RANS–LES methods are currently in use such that there is the question of which hybrid RANS-LES method represents the optimal approach. The properties of an optimal hybrid RANS–LES model are formulated here by taking reference to fundamental properties of fluid flow equations. It is shown that unified RANS–LES models derived from an underlying stochastic turbulence model have the properties of optimal hybrid RANS–LES models. The rest of the paper is organized in two parts. First, a priori and a posteriori analyses of channel flow data are used to find the optimal computational formulation of the theoretically derived unified RANS–LES model and to show that this computational model, which is referred to as linear unified model (LUM), does also have all the properties of an optimal hybrid RANS–LES model. Second, a posteriori analyses of channel flow data are used to study the accuracy and cost features of the LUM. The following conclusions are obtained. (i) Compared to RANS, which require evidence for their predictions, the LUM has the significant advantage that the quality of predictions is relatively independent of the RANS model applied. (ii) Compared to LES, the significant advantage of the LUM is a cost reduction of high-Reynolds number simulations by a factor of 0.07Re{sup 0.46}. For coarse grids, the LUM has a significant accuracy advantage over corresponding LES. (iii) Compared to other usually applied hybrid RANS–LES models, it is shown that the LUM provides significantly improved predictions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Review of the synergies between computational modeling and experimental characterization of materials across length scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends in which predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure–property relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to “simply” support experimental work. This is illustrated by examples from several application areas on structural materials. In conclusion this manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.

3-D microstructure characterization↗
DOE OSTI2014

Programming Non-Trivial Algorithms in the Measurement Based Quantum Computation Model

We provide a set of prescriptions for implementing a quantum circuit model algorithm as measurement based quantum computing (MBQC) algorithm1, 2 via a large cluster state. As means of illustration we draw upon our numerical modeling experience to describe a large graph state capable of searching a logical 8 element list (a non-trivial version of Grover's algorithm3 with feedforward). We develop several prescriptions based on analytic evaluation of cluster states and graph state equations which can be generalized into any circuit model operations. Such a resulting cluster state will be able to carry out the desired operation with appropriate measurements and feed forward error correction. We also discuss the physical implementation and the analysis of the principal 3-qubit entangling gate (Toffoli) required for a non-trivial feedforward realization of an 8-element Grover search algorithm.

Alsing, Paul↗
DOE OSTI2017

Interfacial Structure and Electric Field Probed by in Situ Electrochemical Vibrational Stark Effect Spectroscopy and Computational Modeling

Interfacial electric fields play crucial roles in electrochemistry, catalysis, and solar energy conversion. Understanding of the interfacial electric field effects has been hindered by the lack of a direct spectroscopic method to probe of the interfacial field at the molecular level. Here, we report the characterization of the field and interfacial structure at Au/diisocyanide/aqueous electrolyte interfaces, using a combination of in situ electrochemical vibrational sum frequency generation (SFG) spectroscopy, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. For 1,4-phenylene diisocyanide (PDI), 4,4'-biphenyl diisocyanide (BPDI), and 4,4"-p-terphenyl diisocyanide (TPDI), our results reveal that the frequency of the gold-bound NC stretch mode of the diisocyanide self-assembled monolayer (SAM) increases linearly with the applied potential, suggesting that SFG can be an in situ probe of the strength of the electric field at electrode/electrolyte interfaces. Using DFT-computed Stark tuning rates of model complexes, the electric field strength at the metal/SAM/electrolyte interfaces is estimated to be 108–109 V/m. The linear dependence of the vibrational frequency (and field) with applied potential is consistent with an electrochemical double-layer structure that consists of a Helmholtz layer in contact with a diffused layer. The Helmholtz layer thickness is approximately the same as the molecular length for PDI, suggesting a well-ordered SAM with negligible electrolyte penetration. For BPDI and TPDI, we found that the Helmholtz layer is thinner than the monolayer of molecular adsorbates, indicating that the electrolyte percolates into the SAM, as shown by molecular dynamics simulations of the Au/PDI/electrolyte interface. The reported analysis demonstrates that a combination of in situ SFG probes and computational modeling provides a powerful approach to elucidate the structure of electrochemical interfaces at the detailed molecular level.

Ge, Aimin↗
DOE OSTI2014

Computational modeling and analysis of thermoelectric properties of nanoporous silicon

In this paper, thermoelectric properties of nanoporous silicon are modeled and studied by using a computational approach. The computational approach combines a quantum non-equilibrium Green's function (NEGF) coupled with the Poisson equation for electrical transport analysis, a phonon Boltzmann transport equation (BTE) for phonon thermal transport analysis and the Wiedemann-Franz law for calculating the electronic thermal conductivity. By solving the NEGF/Poisson equations self-consistently using a finite difference method, the electrical conductivity σ and Seebeck coefficient S of the material are numerically computed. The BTE is solved by using a finite volume method to obtain the phonon thermal conductivity k{sub p} and the Wiedemann-Franz law is used to obtain the electronic thermal conductivity k{sub e}. The figure of merit of nanoporous silicon is calculated by ZT=S{sup 2}σT/(k{sub p}+k{sub e}). The effects of doping density, porosity, temperature, and nanopore size on thermoelectric properties of nanoporous silicon are investigated. It is confirmed that nanoporous silicon has significantly higher thermoelectric energy conversion efficiency than its nonporous counterpart. Specifically, this study shows that, with a n-type doping density of 10{sup 20} cm{sup –3}, a porosity of 36% and nanopore size of 3 nm × 3 nm, the figure of merit ZT can reach 0.32 at 600 K. The results also show that the degradation of electrical conductivity of nanoporous Si due to the inclusion of nanopores is compensated by the large reduction in the phonon thermal conductivity and increase of absolute value of the Seebeck coefficient, resulting in a significantly improved ZT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Computational modeling of phononic pseudocrystal isolators

Methods for the efficient computational prediction of the performance of phononic pseudocrystals (structured materials capable of blocking extraordinary ranges of frequency) in COMSOL and other comparable finite element method codes are set forth. These methods include boundary conditions that make possible halving the size of the computational domain. Also included is an introduction of elastic energy density methods for assessing the extinction of elastic waves within the patterned region.

Swift, Stephen Hales↗
DOE OSTI2015

A UNIFIED COMPUTATIONAL MODEL FOR SOLAR AND STELLAR FLARES

We present a unified computational framework that can be used to describe impulsive flares on the Sun and on dMe stars. The models assume that the flare impulsive phase is caused by a beam of charged particles that is accelerated in the corona and propagates downward depositing energy and momentum along the way. This rapidly heats the lower stellar atmosphere causing it to explosively expand and dramatically brighten. Our models consist of flux tubes that extend from the sub-photosphere into the corona. We simulate how flare-accelerated charged particles propagate down one-dimensional flux tubes and heat the stellar atmosphere using the Fokker–Planck kinetic theory. Detailed radiative transfer is included so that model predictions can be directly compared with observations. The flux of flare-accelerated particles drives return currents which additionally heat the stellar atmosphere. These effects are also included in our models. We examine the impact of the flare-accelerated particle beams on model solar and dMe stellar atmospheres and perform parameter studies varying the injected particle energy spectra. We find the atmospheric response is strongly dependent on the accelerated particle cutoff energy and spectral index.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Comprehensive computer model for magnetron sputtering. II. Charged particle transport

Discharges for magnetron sputter thin film deposition systems involve complex plasmas that are sensitively dependent on magnetic field configuration and strength, working gas species and pressure, chamber geometry, and discharge power. The authors present a numerical formulation for the general solution of these plasmas as a component of a comprehensive simulation capability for planar magnetron sputtering. This is an extensible, fully three-dimensional model supporting realistic magnetic fields and is self-consistently solvable on a desktop computer. The plasma model features a hybrid approach involving a Monte Carlo treatment of energetic electrons and ions, along with a coupled fluid model for thermalized particles. Validation against a well-known one-dimensional system is presented. Various strategies for improving numerical stability are investigated as is the sensitivity of the solution to various model and process parameters. In particular, the effect of magnetic field, argon gas pressure, and discharge power are studied.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computational Modeling of a 3D Printed Recuperator and Subsequent Experimental Loop for Supercritical Carbon Dioxide Cycles

Oak Ridge National Laboratory (ORNL), in collaboration with mechanical-thermal energy storage (mTES) provider EarthEn, a US Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) recipient at ORNL’s Innovation Crossroads 2023, is utilizing a state-of-the-art patented 3D printing technique to design an additively manufactured (AM) supercritical CO2 (sCO2) recuperator (REC) for EarthEn’s charge/discharge cycle. The AM REC will be printed at ORNL’s Manufacturing Demonstration Facility using Inconel Alloy 718 and tested on a closed-loop, ∼100 kW scale experimental facility that is under construction. The testing will compare the printed design against a commercial-off-the-shelf Printed Circuit Heat Exchanger (PCHE) REC. The design of the sCO2 facility is guided by a Modelica-based system model which is primarily dependent on the open-source TRANSFORM library developed at ORNL and uses the open-source CoolProp library for thermophysical properties of sCO2 via the External Media library. It is envisioned that an iterative process will be followed between the physical loop and the system model wherein the initial experimental data will be used to tune the model, which in turn will be used to guide future loop operation. Simultaneously, the AM REC is being designed using computer-aided design models, and it is also being analyzed for hydraulic and thermomechanical response using commercial computational fluid dynamics software, Simcenter STAR-CCM+, on highperformance computing resources.1

See, Nate [ORNL] (ORCID:0000000178581202)↗
DOE OSTI2018

Efficient Computational Modeling of Human Ventricular Activation and Its Electrocardiographic Representation: A Sensitivity Study

Patient-specific models of the ventricular myocardium, combined with the computational power to run rapid simulations, are approaching the level where they could be used for personalized cardiovascular medicine. A major remaining challenge is determining model parameters from available patient data, especially for models of the Purkinje-myocardial junctions (PMJs): the sites of initial ventricular electrical activation. There are no non-invasive methods for localizing PMJs in patients, and the relationship between the standard clinical ECG and PMJ model parameters is underexplored. Thus, this study aimed to determine the sensitivity of the QRS complex of the ECG to the anatomical location and regional number of PMJs. The QRS complex was simulated using an image-based human torso and biventricular model, and cardiac electrophysiology was simulated using Cardioid. The PMJs were modeled as discrete current injection stimuli, and the location and number of stimuli were varied within initial activation regions based on published experiments. Results indicate that the QRS complex features were most sensitive to the presence or absence of four “seed” stimuli, and adjusting locations of nearby “regional” stimuli provided finer tuning. Decreasing number of regional stimuli by an order of magnitude resulted in virtually no change in the QRS complex. Thus, a minimal 12-stimuli configuration was identified that resulted in physiological excitation, defined by QRS complex feature metrics and ventricular excitation pattern. In conclusion, overall, the sensitivity results suggest that parameterizing PMJ location, rather than number, be given significantly higher priority in future studies creating personalized ventricular models from patient-derived ECGs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties

Calibration parameters in deterministic computer experiments are those attributes that cannot be measured or available in physical experiments. Here, an approach to estimate them by using data from physical experiments and computer simulations. A theoretical framework is given which allows us to study the issues of parameter identifiability and estimation. We define the L 2 -consistency for calibration as a justification for calibration methods. It is shown that a simplified version of the original KO method leads to asymptotically L 2 -inconsistent calibration. This L 2 -inconsistency can be remedied by modifying the original estimation procedure. A novel calibration method, called the L 2 calibration, is proposed and proven to be L 2 -consistent and enjoys optimal convergence rate. Furthermore a numerical example and some mathematical analysis are used to illustrate the source of the L 2 -inconsistency problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Computer Modeling of Transport of Oxidizing Species in Grain Boundaries during Zirconium Corrosion

Zirconium (Zr) based alloys are widely used as the cladding materials in light-water reactors. The water-side corrosion of these alloys degrades their structural integrity and poses serious safety concerns. During the Zr corrosion process, a thin Zr oxide (ZrO2) layer forms on the alloy surface and serves as a barrier layer for further corrosion. The majority of the oxide has the monoclinic phase. At the transition region between the oxide and the metal, the oxide contains a thin layer of stabilized tetragonal phase. It is found that the texture of the tetragonal layer determines the protectiveness of the oxide for corrosion. The transport of oxidizing species, such as anion defects, cation defects, and electron through the tetragonal oxide layer could be the rate limiting step of the corrosion. The defect diffusion can be affected by the growing stresses and microstructures such as grain boundaries and dislocations. In this work molecular dynamics simulations are used to investigate the anion and cation diffusion in bulk and at grain boundaries in tetragonal ZrO2. The results show that defect diffusion at grain boundaries is complex and the behavior strongly depends on the grain boundary type. For most of the grain boundaries studied the defect diffusion are much slower than in the bulk, implying that grain boundaries may not be fast defect transport paths during corrosion. The connection between the modeling results and published experimental work will also be discussed. This work is funded by the Laboratory Directed Research and Development (LDRD) program at Idaho National Laboratory.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High Performance Computational Models of Synthetic Jet Actuators for Step Change Improvements in Freight Efficiency

The project presents results of a computational fluid dynamics (CFD) model developed by the Oak Ridge National Laboratory team for a synthetic jet produced by an actuator. Numerical results were compared against experimental data provided by Actasys, Inc. Three CFD packages were used for this work that are Star-CCM+, Nek5000 and OpenFOAM. A sensitivity analysis was performed with Star-CCM+ and provided more insights on how to optimize the design of the actuator. Nek5000 was used to obtain a high-resolution solution of the synthetic jet. In a exploratory stage, a CFD model of the actuator was also developed in OpenFOAM. All CFD models were able to capture the main flow features.

42 ENGINEERING↗
DOE OSTI2025

Combining computational modeling and experimental library screening to affinity-mature VEEV-neutralizing antibody F5

Engineered monoclonal antibodies have proven to be highly effective therapeutics in recent viral outbreaks. However, despite technical advancements, an ability to rapidly adapt or increase antibody affinity and by extension, therapeutic efficacy, has yet to be fully realized. We endeavored to stand-up such a pipeline using molecular modeling combined with experimental library screening to increase the affinity of F5, a monoclonal antibody with potent neutralizing activity against Venezuelan Equine Encephalitis Virus (VEEV), to recombinant VEEV (IAB) E1E2 antigen. We modeled the F5/E1E2 binding interface and generated predictions for mutations to improve binding using a Rosetta-based approach and dTERMen, an informatics approach. The modeling was complicated by the fact that a high-resolution structure of F5 is not available and the H3 loop of F5 exceeds the length for which current modeling approaches can determine a unique structure. A subset of the predicted mutations from both methods were incorporated into a phage display library of scFvs. This library and a library generated by error-prone PCR were screened for binding affinity to the recombinant antigen. Results from the screens identified favorable mutations which were incorporated into 12 human-IgG1 variants. The best variant, containing eight mutations, improved KD from 0.63 nM (parental) to 0.01 nM. While this did not improve neutralization or therapeutic potency of F5 against IAB, it did increase cross-reactivity to other closely related VEEV epizootic and enzootic strains, demonstrating the potential of this method to rapidly adapt existing therapeutics to emerging viral strains.

affinity-maturation↗
DOE OSTI2023

DFO Computational Modeling Project - Catalytic Upgrading of Bio-based Furfural to 1,5-Pentanediol: A New Renewable Monomer for the Coatings Industry (Final Report)

This report summarizes the results of a collaborative effort between Oak Ridge National Laboratory (ORNL) and Pyran™ Inc. to utilize modeling capabilities developed by the CCPC (Consortium for Computational Physics and Chemistry) to assist Pyran in scaling up its proprietary process for thermocatalytic conversion of furfural to 1,5 pentanediol (PDO). Pyran’s bio-based PDO is a direct replacement for petroleum-based PDO and 1,6 hexanediol (HDO) currently used in polymers, additives, coatings, adhesives and sealants. The current market is in excess of $\$$1B/yr. According to Pyran, their production process results in 95+% reduction in fossil CO 2 at lower production costs compared to the existing petroleum-based routes for PDO & HDO. Other chemicals based on intermediates from this process have current markets in excess of $\$$10B/yr.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Comparison of realistic and idealized breathing patterns in computational models of airflow and vapor dosimetry in the rodent upper respiratory tract

Abstract Context: Computational fluid dynamics (CFD) simulations of airflows coupled with physiologically based pharmacokinetic (PBPK) modeling of respiratory tissue doses of airborne materials have traditionally used either steady-state inhalation or a sinusoidal approximation of the breathing cycle for airflow simulations despite their differences from normal breathing patterns. Objective: Evaluate the impact of realistic breathing patterns, including sniffing, on predicted nasal tissue concentrations of a reactive vapor that targets the nose in rats as a case study. Materials and methods: Whole-body plethysmography measurements from a free-breathing rat were used to produce profiles of normal breathing, sniffing and combinations of both as flow inputs to CFD/PBPK simulations of acetaldehyde exposure. Results: For the normal measured ventilation profile, modest reductions in time- and tissue depth-dependent areas under the curve (AUC) acetaldehyde concentrations were predicted in the wet squamous, respiratory and transitional epithelium along the main airflow path, while corresponding increases were predicted in the olfactory epithelium, especially the most distal regions of the ethmoid turbinates, versus the idealized profile. The higher amplitude/frequency sniffing profile produced greater AUC increases over the idealized profile in the olfactory epithelium, especially in the posterior region. Conclusions: The differences in tissue AUCs at known lesion-forming regions for acetaldehyde between normal and idealized profiles were minimal, suggesting that sinusoidal profiles may be used for this chemical and exposure concentration. However, depending upon the chemical, exposure system and concentration and the time spent sniffing, the use of realistic breathing profiles, including sniffing, could become an important modulator for local tissue dose predictions.

dosimetry↗