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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Introduction to Focus Issue: Rhythms and Dynamic Transitions in Neurological Disease: Modeling, Computation, and Experiment

Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Computational modeling of the N-terminus of the human dopamine transporter and its interaction with PIP 2 -containing membranes: Modeling of DAT N-Terminus/PIP 2 Interactions

The dopamine transporter (DAT) is a transmembrane protein belonging to the family of neurotransmitter:sodium symporters (NSS). Members of the NSS are responsible for the clearance of neurotransmitters from the synaptic cleft, and for their translocation back into the presynaptic nerve terminal. The DAT contains long intracellular N- and C-terminal domains that are strongly implicated in the transporter function. The N-terminus (N-term), in particular, regulates the reverse transport (efflux) of the substrate through DAT. Currently, the molecular mechanisms of the efflux remain elusive in large part due to lack of structural information on the N-terminal segment. Here we report a computational model of the N-term of the human DAT (hDAT), obtained through an ab initio structure prediction, in combination with extensive atomistic molecular dynamics (MD) simulations in the context of a lipid membrane. Our analysis reveals that whereas the N-term is a highly dynamic domain, it contains secondary structure elements that remain stable in the long MD trajectories of interactions with the bilayer (totaling >2.2 μs). Combining MD simulations with continuum mean-field modeling we found that the N-term engages with lipid membranes through electrostatic interactions with the charged lipids PIP 2 (phosphatidylinositol 4,5-Biphosphate) or PS (phosphatidylserine) that are present in these bilayers. We identify specific motifs along the N-term implicated in such interactions and show that differential modes of N-term/membrane association result in differential positioning of the structured segments on the membrane surface. These results will inform future structure-based studies that will elucidate the mechanistic role of the N-term in DAT function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination

Mycobacterium tuberculosis (Mtb), the causative infectious agent of tuberculosis (TB), kills more individuals per year than any other infectious agent. Granulomas, the hallmark of Mtb infection, are complex structures that form in lungs, composed of immune cells surrounding bacteria, infected cells, and a caseous necrotic core. While granulomas serve to physically contain and immunologically restrain bacteria growth, some granulomas are unable to control Mtb growth, leading to bacteria and infected cells leaving the granuloma and disseminating, either resulting in additional granuloma formation (local or non-local) or spread to airways or lymph nodes. Dissemination is associated with development of active TB. It is challenging to experimentally address specific mechanisms driving dissemination from TB lung granulomas. Herein, we develop a novel hybrid multi-scale computational model, MultiGran, that tracks Mtb infection within multiple granulomas in an entire lung. MultiGran follows cells, cytokines, and bacterial populations within each lung granuloma throughout the course of infection and is calibrated to multiple non-human primate (NHP) cellular, granuloma, and whole-lung datasets. We show that MultiGran can recapitulate patterns of in vivo local and non-local dissemination, predict likelihood of dissemination, and predict a crucial role for multifunctional CD8+ T cells and macrophage dynamics for preventing dissemination.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Unraveling the Mechanics: Computational Modeling of Residual Stresses in U10Mo Fuel with Aluminum Cladding

LEU (Low Enriched Uranium) plate-type fuel elements consist of a high-density, low-enrichment U–Mo alloy-based fuel foil encapsulated in an aluminum cladding and is fabricated through the Hot Isostatic Pressing (HIP) technique. Understanding the mechanism of possible failure modes of nuclear fuel is critical to mitigate potential consequences. One of the major contributing factors in various failure modes is stress and it greatly affects the integrity under temperature, pressure, and irradiation. These stresses could originate from various sources, including manufacturing, and operation, and can lead to deformation, cracking, or even complete failure of fuel elements. This study focuses on the development of a computational model that accurately predicts the residual stresses generated in the U10Mo fuel during fabrication. It has been observed that cladding creep has a substantial impact on the residual stresses in the U10Mo fuel post the HIP fabrication process. Furthermore, during the HIP bonding process the fuel plate system is heated to a temperature of 560 oC and as a result, the aluminum cladding transitions from (Al 6061-T6 to -O). This presents a challenge in capturing the change in material properties accurately. Therefore, a temperature dependent creep model such as hyperbolic sine creep model is considered to estimate the creep properties of the Aluminum cladding. The proposed calibrated creep model accurately predicts the residual stresses in the U10Mo fuel foil and agrees well with the experiments.

42 ENGINEERING↗
DOE OSTI2019

Multiscale Computational Model for Particle Size Evolution during Coprecipitation of Li-Ion Battery Cathode Precursors

Next generation lithium ion batteries require higher energy and power density, which can be achieved by tailoring the cathode particle morphology, such as particle size, size distribution, and internal porosity. All these morphological features are determined during the cathode synthesis process, which consists of two steps, (i) coprecipitation and (ii) calcination. Transition metal hydroxide precursors are synthesized during the coprecipitation process, whereas their oxidation and lithiation occur during calcination. The size and size distribution of crystalline primary and aggregated secondary particles and their internal porosity are determined during coprecipitation. Operating conditions of the chemical reactor, such as solution pH, ammonia concentration, and stirring speed control the final morphological features. Here, a multiscale computational model has been developed to capture the nucleation and growth of crystalline primary particles and their aggregation into secondary transition metal hydroxide precursor particles. The simulations indicate that increasing solution pH and decreasing ammonia concentration lead to smaller sizes of the secondary particles. Finally, a phase map has been developed that can help identify the synthesis conditions needed for a specified particle size and size distribution.

25 ENERGY STORAGE↗
DOE OSTI2014

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Establishing a clostridia foundry for biosystems design by integrating computational modeling, systems-level analyses, and cell-free engineering technologies (Final Report)

Rapid population growth, a rise in global living standards, and economic competitiveness have intensified the need for sustainable, low-cost biofuels and bioproducts production. Industrial biotechnology using microbial cell factories – and waste and/or renewable feedstocks – is one of the most attractive approaches for addressing this need, particularly when large-scale chemical synthesis is untenable. Unfortunately, designing, building, and optimizing biosynthetic pathways in cells remains a complex challenge. With support from the Department of Energy, we worked to address this challenge in a new interdisciplinary venture that established the world’s first clostridial Foundry for Biosystems Design (cBioFAB). Working both in vitro (cell-free) and in vivo, the goal of this project was to interweave and advance state-of-the-art computational modeling, genome editing, omics measurements, systems-biology analyses, and cell-free technologies to expand the set of platform organisms that meet DOE bioenergy goals. Specifically, we manufactured fuel and chemical intermediates via existing and de novo pathways. This report covers the outcomes of our research project.

09 BIOMASS FUELS↗
DOE OSTI2015

Swelling In Light Water Reactor Internal Components: Insights from Computational Modeling

A modern cluster dynamics model has been used to investigate the materials and irradiation parameters that control microstructural evolution under the relatively low-temperature exposure conditions that are representative of the operating environment for in-core light water reactor components. The focus is on components fabricated from austenitic stainless steel. The model accounts for the synergistic interaction between radiation-produced vacancies and the helium that is produced by nuclear transmutation reactions. Cavity nucleation rates are shown to be relatively high in this temperature regime (275 to 325°C), but are sensitive to assumptions about the fine scale microstructure produced under low-temperature irradiation. The cavity nucleation rates observed run counter to the expectation that void swelling would not occur under these conditions. This expectation was based on previous research on void swelling in austenitic steels in fast reactors. This misleading impression arose primarily from an absence of relevant data. The results of the computational modeling are generally consistent with recent data obtained by examining ex-service components. However, it has been shown that the sensitivity of the model s predictions of low-temperature swelling behavior to assumptions about the primary damage source term and specification of the mean-field sink strengths is somewhat greater that that observed at higher temperatures. Further assessment of the mathematical model is underway to meet the long-term objective of this research, which is to provide a predictive model of void swelling at relevant lifetime exposures to support extended reactor operations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational Modeling, Simulation, and Potential Applications of Optical Stochastic Cooling

With the rising demand for intense particles beams, much research is being conducted in the area of particle beam cooling. One of these methods, called Stochastic Cooling (SC) (developed at CERN in the 1970's), delivered a feedback method to improve the quality and lifetime of circulating proton beams by reducing their 6D phase-space and has been widely implemented in a number of hadron machines. However, traditional stochastic cooling schemes are limited by the bandwidth of microwave frequency systems. Optical Stochastic Cooling (OSC) is a promising extension of the stochastic cooling beam cooling technique. OSC instead uses optical wavelengths which allows for improved control and increased cooling but creates its own technical challenges. This lays out work conducted toward the experimental demonstration of OSC at Fermilab's Integrable Optics Test Accelerator (IOTA) storage ring. This includes the design and characterization of parts of the optical delay system, the development and validation of a high-fidelity computational model of the OSC process, and the investigations into possible applications of the OSC mechanism to advanced beam manipulations.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Computational modeling and validation of a modified Marple cascade impactor

Oak Ridge National Laboratory (ORNL) is investigating respirable aerosol fractions from failed high-burnup (HBU) commercial spent nuclear fuel (CSNF) rods (Montgomery et al., 2022). The work aims to characterize the source term of radioactive aerosols that could result from mechanical failure and handling of failed fuel rods during storage and/or transportation. The experiment involves capturing and characterizing aerosols from a four-point bending experiment of fueled rod segments at ORNL’s Irradiated Fuels Examination Laboratory (IFEL). For this, a Marple cascade impactor (Series 290) with the ability to collect particles up to aerodynamic equivalent diameters of ~15 μm was tested for feasibility. The commercially available Marple cascade impactor design was modified for the experiment, where the cascade inlet was replaced with a 3D printed inlet nozzle. Collection efficiency curves were then generated with the modified impactor, and the cascade’s performance was tested using ISO dust capture experiments followed by SEM analysis of the collection and computational modeling. The current work highlights the performance testing and experimental validation of this modified Marple Impactor for spent nuclear fuel aerosol collection.

Kumar, Vineet↗
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.↗