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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 OSTI2016

Computational modeling predicts simultaneous targeting of fibroblasts and epithelial cells is necessary for treatment of pulmonary fibrosis

Pulmonary fibrosis is pathologic remodeling of lung tissue that can result in difficulty breathing, reduced quality of life, and a poor prognosis for patients. Fibrosis occurs as a result of insult to lung tissue, though mechanisms of this response are not well-characterized. The disease is driven in part by dysregulation of fibroblast proliferation and differentiation into myofibroblast cells, as well as pro-fibrotic mediator-driven epithelial cell apoptosis. The most well-characterized pro-fibrotic mediator associated with pulmonary fibrosis is TGF-β1. Excessive synthesis of, and sensitivity to, pro-fibrotic mediators as well as insufficient production of and sensitivity to anti-fibrotic mediators has been credited with enabling fibroblast accumulation. Available treatments neither halt nor reverse lung damage. In this study we have two aims: to identify molecular and cellular scale mechanisms driving fibroblast proliferation and differentiation as well as epithelial cell survival in the context of fibrosis, and to predict therapeutic targets and strategies. We combine in vitro studies with a multi-scale hybrid agent-based computational model that describes fibroblasts and epithelial cells in co-culture. Within this model TGF-β1 represents a pro-fibrotic mediator and we include detailed dynamics of TGFβ1 receptor ligand signaling in fibroblasts. PGE 2 represents an anti-fibrotic mediator. Using uncertainty and sensitivity analysis we identify TGF-β1 synthesis, TGF-β1 activation, and PGE 2 synthesis among the key mechanisms contributing to fibrotic outcomes. We further demonstrate that intervention strategies combining potential therapeutics targeting both fibroblast regulation and epithelial cell survival can promote healthy tissue repair better than individual strategies. Combinations of existing drugs and compounds may provide significant improvements to the current standard of care for pulmonary fibrosis. In conclusion, a two-hit therapeutic intervention strategy may prove necessary to halt and reverse disease dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Computational Modeling, Simulation and Analysis of the RPI Walthousen Reactor Critical Facility (RCF)

The Walthousen Reactor Critical Facility (RCF), located in Schenectady, New York, is currently owned and operated by Rensselaer Polytechnic Institute (RPI). The facility was originally constructed by the American Locomotive Company (ALCO) for the research and development of small, portable reactors. Originally designed for highly-enriched uranium fuel, the prototype reactor first came online in August 26, 1956, and was transferred to RPI ownership in 1963. Several changes to the reactor's design and operation have been made, the most notable of which was the conversion from high-enriched uranium to low-enriched uranium fuel. The RCF is an open-pool critical assembly that operates at a low power with a license limit of less than 100 watts. This low operating power permits a much greater flexibility in configuration and operation as compared to other research reactors. Because of this, experiments may be designed that would be unfeasible for research reactors that operate at much higher powers. The RCF's functional capabilities provide opportunities to perform several reactor experiments and measurements, such as: core criticality experiments, differential and integral rod worth measurements, moderator temperature coefficient of reactivity calculations, critical rod height and critical water height measurements, etc.. These experiments are regularly performed in conjunction with RPI course-work education and Senior Reactor Operator (SRO) training. The unique capabilities and experiments that may be performed in the RCF are particularly useful for validating certain aspects of computational analysis codes. A computational model of the RCF reactor has been previously generated and validated using the Monte Carlo N-Particle (MCNP) code. For the purpose of future experiments, this model is also being adapted for use with the SHARP Toolset, which includes the PROTEUS neutronics code, the Nek5000 fluid dynamics code, and the Diablo structural mechanics code. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Synthesis, characterization, and computational modeling of 6,6'-(((2-hydroxyethyl)azanediyl)bis(methylene))bis(2,4-di-tert-butylphenol) modified group 4 metal alkoxides

The coordination behavior of the tridentate alkoxy ligand 6,6'-(((2-hydroxyethyl)azanediyl)bis(methylene)) bis(2,4-di-tert-butylphenol) (termed H 3 -AM-DBP 2 ) with group 4 metal alkoxides ([M(OR) 4 ]) in a 1:1 ratio was previously found to generate [(ONep)Ti(κ 4 (O,O’,O”,N)-AM-DBP2)] and [(OR)Zr(κ 4 (μ-O,O’,O”,N)-AM-DBP 2 )] 2 (M = Zr, Hf). Additional studies revealed that increasing the stoichiometric ratio to 1:2 H3-AM-DBP 2 :[M(OR) 4 ] led to the isolation of [(ONep)Ti(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-ONep)Ti(ONep) 3 ] (1)•tol, [(OBu t)Zr(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-OBu t)Zr(OBu t )3] (2) and [(OBu t)Hf(κ 4 (μ-O,O’,O”,N)-AM-DBP2)(μ-OBu t )Hf(OBu t ) 3 ] (3). The asymmetric dinuclear complexes of 1-3 resemble the chelation of a [M(OR) 4 ] moiety to a “(OR)M(κ 4 (O,O’,O”,N)-AM-DBP 2 )” fragment. The metal complexed by the AM-DBP 2 ligand has a pseudo octahedral geometry while the other metal adopts an intermediate trigonal bipyramidal (TBP-5)/square base pyramidal (SBP-5) geometry for 1 but a distorted SBP-5 for both 2 and 3. The structure and properties of 1-3 were analyzed by computational modeling and fully characterized by standard analytical methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Ion Exchange Distribution Coefficient Tests and Computer Modeling at High Ionic Strength Supporting Technetium Removal Resin Maturation

The primary treatment of the tank waste at the DOE Hanford site will be done in the Waste Treatment and Immobilization Plant (WTP) that is currently under construction. The baseline plan for this facility is to treat the waste, splitting it into High Level Waste (HLW) and Low Activity Waste (LAW). Both waste streams are then separately vitrified as glass and poured into canisters for disposition. The LAW glass will be disposed onsite in the Integrated Disposal Facility (IDF). There are currently no plans to treat the waste to remove technetium, so its disposition path is the LAW glass. Due to the water solubility properties of pertechnetate and long half-life of 99 Tc, effective management of 99 Tc is important to the overall success of the Hanford River Protection Project mission. To achieve the full target WTP throughput, additional LAW immobilization capacity is needed, and options are being explored to immobilize the supplemental LAW portion of the tank waste. Removal of 99 Tc, followed by off-site disposal, would eliminate a key risk contributor for the IDF Performance Assessment (PA) for supplemental waste forms, and has potential to reduce treatment and disposal costs. Washington River Protection Solutions (WRPS) is developing some conceptual flow sheets for supplemental LAW treatment and disposal that could benefit from technetium removal. One of these flowsheets will specifically examine removing 99 Tc from the LAW feed stream to supplemental immobilization. To enable an informed decision regarding the viability of technetium removal, further maturation of available technologies is being performed. This report contains results of experimental ion exchange distribution coefficient testing and computer modeling using the resin SuperLig ® 639 a to selectively remove perrhenate from high ionic strength simulated LAW. It is advantageous to operate at higher concentration in order to treat the waste stream without dilution and to minimize the volume of the final wasteform. This work examined the impact of high ionic strength, high density, and high viscosity if higher concentration LAW feed solution is used. Perrhenate (ReO 4 - ) has been shown to be a good nonradioactive surrogate for pertechnetate in laboratory testing for this ion exchange resin, and the performance bias is well established. Equilibrium contact testing with 7.8 M [Na + ] average simulant concentrations indicated that the SuperLig ® 639 resin average perrhenate distribution coefficient was 368 mL/g at a 100:1 phase ratio. Although this indicates good performance at high ionic strength, an equilibrium test cannot examine the impact of liquid viscosity, which impacts the diffusivity of ions and therefore the loading kinetics. To get an understanding of the effect of diffusivity, modeling was performed, which will be followed up with column tests in the future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

SST-GPU: An Execution -Driven CUDA Kernel Scheduler and Streaming-Multiprocessor Compute Model

Programmable accelerators have become commonplace in modern computing systems. Advances in programming models and the availability of massive amounts of data have created a space for massively parallel acceleration where the context for thousands of concurrent threads are resident on-chip. These threads are grouped and interleaved on a cycle-by-cycle basis among several massively parallel computing cores. The design of future supercomputers relies on an ability to model the performance of these massively parallel cores at scale. To address the need for a scalable, decentralized GPU model that can model large GPUs, chiplet-based GPUs and multi-node GPUs, this report details the first steps in integrating the open-source, execution driven GPGPU-Sim into the SST framework. The first stage of this project, creates two elements: a kernel scheduler SST element accepts work from SST CPU models and schedules it to an SM-collection element that performs cycle-by-cycle timing using SSTs Mem Hierarchy to model a flexible memory system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Computational models of direct and indirect X‐ray breast imaging detectors for in silico trials

Abstract Background To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers are needed. Purpose The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of their systems. Methods We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open‐source GPU‐accelerated Monte Carlo x‐ray imaging simulation code (MC‐GPU). We build on the previous version of the MC‐GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)‐approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x‐ray photon till its first interaction within the x‐ray detector. On the other hand, the signal spread in the x‐ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron–hole pairs or optical photons) using analytical equations in the detector. The analytical optical spread model for the indirect detector includes the depth‐dependent spread and collection of optical photons and relies on a pre‐computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x‐ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measured data. Results We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with direct detectors. Conclusions We have presented computational models of three commercially available FDA‐approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC‐GPU codes that can be used to replicate three systems are available in open source format through GitHub.

Sengupta, Aunnasha↗
DOE OSTI2014

Computer Modeling of Violent Intent: A Content Analysis Approach

We present a computational approach to modeling the intent of a communication source representing a group or an individual to engage in violent behavior. Our aim is to identify and rank aspects of radical rhetoric that are endogenously related to violent intent to predict the potential for violence as encoded in written or spoken language. We use correlations between contentious rhetoric and the propensity for violent behavior found in documents from radical terrorist and non-terrorist groups and individuals to train and evaluate models of violent intent. We then apply these models to unseen instances of linguistic behavior to detect signs of contention that have a positive correlation with violent intent factors. Of particular interest is the application of violent intent models to social media, such as Twitter, that have proved to serve as effective channels in furthering sociopolitical change.

Sanfilippo, Antonio P.↗
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↗