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At least 847 records · Page 47

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DOE OSTI2015

An integrated QSAR-PBK/D modelling approach for predicting detoxification and DNA adduct formation of 18 acyclic food-borne α,β-unsaturated aldehydes

Acyclic α,β-unsaturated aldehydes present in food raise a concern because the α,β-unsaturated aldehyde moiety is considered a structural alert for genotoxicity. However, controversy remains on whether in vivo at realistic dietary exposure DNA adduct formation is significant. The aim of the present study was to develop physiologically based kinetic/dynamic (PBK/D) models to examine dose-dependent detoxification and DNA adduct formation of a group of 18 food-borne acyclic α,β-unsaturated aldehydes without 2- or 3-alkylation, and with no more than one conjugated double bond. Parameters for the PBK/D models were obtained using quantitative structure–activity relationships (QSARs) defined with a training set of six selected aldehydes. Using the QSARs, PBK/D models for the other 12 aldehydes were defined. Results revealed that DNA adduct formation in the liver increases with decreasing bulkiness of the molecule especially due to less efficient detoxification. 2-Propenal (acrolein) was identified to induce the highest DNA adduct levels. At realistic dietary intake, the predicted DNA adduct levels for all aldehydes were two orders of magnitude lower than endogenous background levels observed in disease free human liver, suggesting that for all 18 aldehydes DNA adduct formation is negligible at the relevant levels of dietary intake. The present study provides a proof of principle for the use of QSAR-based PBK/D modelling to facilitate group evaluations and read-across in risk assessment. - Highlights: • Physiologically based in silico models were made for 18 α,β-unsaturated aldehydes. • Kinetic parameters were determined by in vitro incubations and a QSAR approach. • DNA adduct formation was negligible at levels relevant for dietary intake. • The use of QSAR-based PBK/D modelling facilitates group evaluations and read-across.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Dynamic Modeling of Aerobic Growth of Shewanella oneidensis. Predicting Triauxic Growth, Flux Distributions and Energy Requirement for Growth

A model-based analysis is conducted to investigate metabolism of Shewanella oneidensis MR-1 strain in aerobic batch culture, which exhibits an intriguing growth pattern by sequentially consuming substrate (i.e., lactate) and by-products (i.e., pyruvate and acetate). A general protocol is presented for developing a detailed network-based dynamic model for S. oneidensis based on the Lumped Hybrid Cybernetic Model (LHCM) framework. The L-HCM, although developed from only limited data, is shown to accurately reproduce exacting dynamic metabolic shifts, and provide reasonable estimates of energy requirement for growth. Flux distributions in S. oneidensis predicted by the L-HCM compare very favorably with 13C-metabolic flux analysis results reported in the literature. Predictive accuracy is enhanced by incorporating measurements of only a few intracellular fluxes, in addition to extracellular metabolites. The L-HCM developed here for S. oneidensis is consequently a promising tool for the analysis of intracellular flux distribution and metabolic engineering.

ATP requirement for growth↗

DOE OSTI2018

Non-equilibrium approach to prediction of microstructure evolution for metals undergoing severe plastic deformation

Highlights: • New consistent physically-based model of dynamic recrystallization. • The model is based on evolution of fraction of high-angle grain boundaries. • Possibility to predict the evolution of dislocation cells and grain boundaries. • The model is implemented for FEM simulations. • Results demonstrate inhomogeneous distribution of strain within the sample. - Abstract: Available models of dynamic recrystallization have a number of disadvantages that in most cases make them inapplicable for practical predictions of material microstructure evolution. Both the microstructural and the empirically based approaches do not reflect physical processes leading to evolution of material defect structure in the process of plastic deformation. This work presents an attempt to develop a consistent physically-based model of dynamic recrystallization. This model, accounting for physical nature of processes of material defect structure evolution, should provide a possibility to predict evolution of several different experimentally measurable parameters of material microstructure without introduction of big number of fitting parameters. It is suggested that such a model should be based on equation for evolution of fraction of high-angle grain boundaries (HAGBs) in the process of deformation. It is shown, that the new model gives a possibility to predict the evolution of dislocation cells and grain boundaries in copper-based alloys providing good coincidence with experimental observations. Full 3-dimensional numerical simulation of multidirectional forging of copper is performed utilizing the developed dynamic recrystallization model. The same 3D simulations demonstrate new noteworthy effects connected to inhomogeneous distribution of plastic strain within the bulk of the material and material strain hardening.

36 MATERIALS SCIENCE↗

DOE OSTI2015

A thermodynamic and kinetic model for paste–aggregate interactions and the alkali–silica reaction

A new conceptual model is developed for ASR formation based on geochemical principles tied to aqueous speciation, silica solubility, kinetically controlled mineral dissolution, and diffusion. ASR development is driven largely by pH and silica gradients that establish geochemical microenvironments between paste and aggregate, with gradients the strongest within the aggregate adjacent to the paste boundary (i.e., where ASR initially forms). Super-saturation of magadiite and okenite (crystalline ASR surrogates) occurs in the zone defined by gradients in pH, dissolved silica, Na{sup +}, and Ca{sup 2} {sup +}. This model provides a thermodynamic rather than kinetic explanation of why quartz generally behaves differently from amorphous silica: quartz solubility does not produce sufficiently high concentrations of H{sub 4}SiO{sub 4} to super-saturate magadiite, whereas amorphous silica does. The model also explains why pozzolans do not generate ASR: their fine-grained character precludes formation of chemical gradients. Finally, these gradients have interesting implications beyond the development of ASR, creating unique biogeochemical environments.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Development of a General Form CO 2 and Brine Flux Input Model

The National Risk Assessment Partnership (NRAP) project is developing a science-based toolset for the quantitative analysis of the potential risks associated with changes in groundwater chemistry from CO 2 injection. In order to address uncertainty probabilistically, NRAP is developing efficient, reduced-order models (ROMs) as part of its approach. These ROMs are built from detailed, physics-based process models to provide confidence in the predictions over a range of conditions. The ROMs are designed to reproduce accurately the predictions from the computationally intensive process models at a fraction of the computational time, thereby allowing the utilization of Monte Carlo methods to probe variability in key parameters. This report presents the procedures used to develop a generalized model for CO 2 and brine leakage fluxes based on the output of a numerical wellbore simulation. The resulting generalized parameters and ranges reported here will be used for the development of third-generation groundwater ROMs.

58 GEOSCIENCES↗

DOE OSTI2017

WTFgenes: What's The Function of these genes? Static sites for model-based gene set analysis

A common technique for interpreting experimentally-identified lists of genes is to look for enrichment of genes associated with particular ontology terms. The most common test uses the hypergeometric distribution; more recently, a model-based test was proposed. These approaches must typically be run using downloaded software, or on a server. We develop a collapsed likelihood for model-based gene set analysis and present WTFgenes, an implementation of both hypergeometric and model-based approaches, that can be published as a static site with computation run in JavaScript on the user's web browser client. Apart from hosting files, zero server resources are required: the site can (for example) be served directly from Amazon S3 or GitHub Pages. A C++11 implementation yielding identical results runs roughly twice as fast as the JavaScript version. WTFgenes is available from https://github.com/evoldoers/wtfgenes under the BSD3 license. A demonstration for the Gene Ontology is usable at https://evoldoers.github.io/wtfgo.

Mungall, Christopher J.↗

DOE OSTI2014

Sci—Thur AM: YIS - 06: An EPID-based 3D patient dose verification method for SBRT-VMAT delivery

Purpose: Stereotactic body radiation therapy (SBRT) delivered via volumetric modulated arc therapy (VMAT) can strongly benefit from an in vivo patient dose verification due to the large doses per fraction. Electronic portal imaging devices (EPIDs) can be utilized as a patient dose dosimeter. In this work we present a physics-based model which utilizes on-treatment EPID images to reconstruct the dose delivered to an anthropomorphic phantom during SBRT-VMAT delivery. Methods: An SBRT linac beam was modeled using Monte Carlo methods and verified with measured data. Our dose reconstruction model back-projects EPID measured focal fluence upstream of the patient and adds a predicted extra-focal fluence component. This fluence is forward projected onto the patient's density matrix and convolved with dose kernels to calculate dose. The model was validated for two prostate, three lung, and two spine SBRT-VMAT treatments. Results were compared to the treatment planning system's calculation. Results: 2%/2 mm chi comparison calculations gave pass rates for the whole volume, infield, and high dose region respectively, and no lower than: 98%, 95%, 99% for the prostate plans, 99%, 92%, 85% for the lung plans, and 91%, 85%, 81% for the spine plans. A 3%/3mm calculation gave pass rates no lower than 99%, 94%, and 90% for all dose regions for the prostate, lung, and spine respectively. Conclusions: We have developed a physics-based model which calculates delivered dose to phantom (or patient) for SBRT-VMAT delivery using on treatment EPID images. The accuracy of the results has allowed us to test this model clinically.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Manufacturing of Fabric Electrodes using a High-Throughput Screening Platform for Redox Flow Batteries

The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.

25 ENERGY STORAGE↗

DOE OSTI2018

Hydropower Development Opportunities for Alaska Native Villages

This report consolidates efforts among Oak Ridge National Laboratory (ORNL), the United States Department of Energy's (DOE) Office of Indian Energy Policy and Programs, and the Alaska Energy Authority (AEA) to evaluate opportunities for hydropower development among 171 Alaska Native villages. This research builds upon new stream -reach development (NSD) research [3] conducted by DOE/ORNL and geospatial modelling provided by the Bureau of Indian Affairs (BIA) [ 2 ]. Based on that information, ORNL has developed a model that evaluates village diesel (gallons) consumption, cost, price per gallon, and kilowatt-hours produced and purchased [4], in conjunction with the past analyses of DOE and BIA, to identify potential benefits of diesel offset from hydropower development on a yearly and 50-year (assumed hydro project lifespan) basis.

13 HYDRO ENERGY↗

DOE OSTI2023

Middleware for a Heterogeneous CAV Fleet

This paper introduces CAN to ROS, a model-based code generation tool used in development, testing, and deployment of a heterogeneous fleet of vehicles with robotic sensing in ROS. Code generation supports two main features: (1) self-configuration for deployment in a heterogeneous vehicle fleet, and (2) quick iteration for testing and development of reading vehicle sensors and robotic control. This tool features the ability to detect the vehicle it is in and regenerate and rebuild itself at runtime to provide the proper two-way bridge between ROS and the sensed on-board vehicle sensor network. Code generation relies on a per-model defined JSON to map a CAN database (DBC) to the desired ROS topic names and message types. The live ROS publishing of CAN messages allows for instant feedback, and the code regeneration allows for adjustments in DBC or vehicle JSON to iteratively hone in on new vehicle signals. Generated ROS nodes are written in C++ for runtime use in lightweight embedded computers. This has been tested in vehicles from three different Original Equipment Manufacturers (OEMs), and can be extended to support a wide array of vehicles. By using a unifying ROS specification, a heterogeneous set of vehicles can be unified into a fleet with abstracted model-specific details; this opens the door for developing cross-model software applications for vehicle control, connected vehicle applications, or fleet monitoring systems.

42 ENGINEERING↗

DOE OSTI2025

Solar Decarbonization of Paraffin Dehydrogenation Through Particle Heat Carriers (Final Technical Report)

This project focuses on solutions to decarbonize high-temperature catalytic processes using solar thermal heat. The primary project goal is to show the validity of a moving packed bed reactor for propane dehydrogenation using catalyst particles as the heat carrier for the reaction, which can be heated by concentrated solar energy in a particle receiver. This concept, if further developed, may provide a cost-effective pathway for converting lower value gases to important chemical precursors for industrial materials using only renewable energy. The project was divided into six tasks. In Task 1, DFT calculations were performed to understand the role of Pt and Sn in the catalytic dehydrogenation reaction. In Task 2 chemical kinetics measurements were made for several catalyst formulations at high temperatures. In Task 3, the solar absorptance of catalyst particles was compared to the absorptance of commonly used materials in particle receivers. In Task 4, numerical models were developed which could predict performance of the complete system and predict specific temperatures in the system. In Task 5, a prototype system was designed, fabricated, and tested to show the validity of the concept. Task 6 concerned project management activities. Experiments with the prototype showed repeatable thermal performance at temperatures targeted for the reaction. A limited set of tests were done with active catalyst and propane dehydrogenation, showing conversion of propane to propylene with a range of conversions and selectivities. The results are promising, and the prototype designed was reliable during testing, and the team expects that further development of the prototype would yield improved results. A numerical model framework based on coupled fluid and particle mechanics was developed with high computational efficiency using GPU calculations. The model may prove highly useful for evaluating other high-temperature particle systems. However, it was determined that simpler porous media models were good fits for the needs of the current moving packed bed concept. Data showing strong solar absorption of the particles validates the plan of using existing solar particle receivers with only a change in the particle type. Catalyst investigation showed that Pt 1 Sn 3 is the most viable candidate for developing PtSn catalysts for high temperature propane dehydrogenation, considering the balance of activity, selectivity, and deactivation. This project completed an initial study of various factors needed to incorporate a moving bed catalytic reactor for propane dehydrogenation into a concentrated solar thermal particle system. Future developments may allow this technology to be scaled up and help to use solar thermal energy to decarbonize not only the propane dehydrogenation reaction, but other gas-solid catalytic reactions at similar temperatures.

14 SOLAR ENERGY↗

DOE OSTI2015

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Preliminary Model Comparison Results From the Sim-SEQ Project Using TOUGH2, STOMP, Eclipse, and VESA Approach

Sim-SEQ is an international initiative on model comparison for geologic carbon sequestration (GCS), with an objective to understand and, if possible, quantify model uncertainties. Model comparison efforts in Sim-SEQ are initially limited to one specific field test site, hereafter referred to as the Sim-SEQ Study site (or S-3 site). Within Sim-SEQ, different modeling teams are developing conceptual models of CO2 injection at the S-3 site. One of the conceptual models, developed by the LBNL team, is based on TOUGH2/EOS7C. In this paper, we present some preliminary model predictions of the S-3 site using the TOUGH2/EOS7C simulator. We also compare the predictions of the TOUGH2 simulator with three other conceptual models, developed by three different organizations, of the S-3 site.

carbon sequestration↗

DOE OSTI2022

3D simulations of inertial confinement fusion implosions part 1: inline modeling of polarized cross beam energy transfer and subsequent drive anomalies on OMEGA and NIF

Inertial confinement fusion experiments are sensitive to cross-beam energy transfer (CBET), a laser-plasma instability that redistributes laser energy in the coronal plasma through self-generated ion acoustic wave (IAW) gratings. The detailed CBET coupling depends on the polarization state of the crossing wavefields. CBET itself can also scramble the beam polarizations by inducing ellipticity through the IAW grating, and rotating the seed polarization toward that of the pump. We develop a ray-based model that describes the polarized CBET coupling and that is compatible with the framework of 3D inline radiative hydrodynamics simulations. The model is implemented in the ASTER/IFRIIT code and verified against an academic test case and an offline polarized CBET post-processor. It is then applied to the detailed configuration of the distributed polarization rotator system on OMEGA, where results highlight how polarized CBET induces significant low modes in the collisional absorption source term. Finally, the modeling is applied to a simple indirect-drive configuration, comparing CBET calculations with 96 unpolarized or polarized beams with 24 unpolarized quads. It is shown that these cases produce similar power amplification per cone of beams grouped with similar polar angles. However, the 96 beam geometry itself is found to reduce azimuthal variations in quad power after the interaction and favors beams with larger polar angles within the cones, an effect that is amplified by the polarized CBET. Application of the model to inline calculations of OMEGA implosions are presented in a companion paper.

3D inline modeling↗

DOE OSTI2020

Predicting boron coordination in multicomponent borate and borosilicate glasses using analytical models and machine learning

Accurate prediction of boron coordination in multicomponent glasses is critical in glass science and technology as it strongly affects the properties of borate and borosilicate glasses. We have collected a dataset containing 657 glasses from literature with boron coordination values and developed models using analytical functions based on the well accepted Dell, Xiao and Bray model. Good prediction of boron coordination with a R 2 value higher than 0.8 was obtained. The large variation of boron coordination from experiments, originated from sample preparations and characterizations, led to difficulties in obtaining models with better prediction performance. Various machine learning (ML) algorithms were evaluated and slightly better prediction performance was observed; however, interpretation of the ML models is less straight forward. In conclusion, this study developed various models capable of providing quantitative boron coordination predictions, providing insights into its structural roles in multi-component glasses, and suggesting fruitful areas for future research.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Can Single-Walled Carbon Nanotube Diameter Be Defined by Catalyst Particle Diameter?

The need of designing and controlling single-walled carbon nanotube (SWCNT) properties is a challenge in a growing nanomaterials-related industry. Recently, great progress has been made experimentally to selectively control SWCNT diameter and chirality. However, there is not yet a complete understanding of the synthesis process, and there is a lack of mathematical models that explain nucleation and diameter selectivity of stable carbon allotropes. Here, in situ analysis of chemical vapor deposition SWCNT synthesis confirms that the nanoparticle-to-nanotube diameter ratio varies with the catalyst particle size. It is found that the tube diameter is larger than that of the particle below a specific size (dc ≈ 2 nm) and above this value is smaller than particle diameters. Additionally, to explain these observations, we develop a statistical mechanics based model that correlates possible energy states of a nascent tube with the catalyst particle size. This model incorporates the equilibrium distance between the nucleating SWCNT layer and the metal catalyst (e.g., Fe, Co, and Ni) evaluated with density functional theory (DFT) calculations. The theoretical analysis explains and predicts the observed correlation between tube and solid particle diameters during growth of supported SWCNTs. This work also brings together previous observations related to the stability condition for SWCNT nucleation. Tests of the model against various published data sets and our own experimental results show good agreement, making it a promising tool for evaluating SWCNT synthesis processes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Estimation of constituent properties of concrete materials with an artificial neural network based method

Multi-scale models are developed for heterogeneous concrete materials to estimate their macroscopic mechanical properties in terms of micro-structural data. One crucial challenge of those models is the identification of local properties of constituent phases. In this paper, we present an efficient method based on Artificial Neural Networks (ANN). Typical concrete materials are taken as example. A macroscopic analytical strength criterion is established from three steps of nonlinear homogenization procedure. The macroscopic strength of materials is determined as a function of the frictional coefficient and cohesion of solid cement particles at nanometer scale, intra-particle pores, inter-particle pores and aggregates (inclusions). The objective is to identify the nanoscopic frictional coefficient and cohesion of cement particle from measured macroscopic values of uniaxial compression and tensile strengths. For this purpose, a numerical method based on the ANN is developed. With the analytical macroscopic strength criterion, sensitivity studies are first realized to identify the most important micro-structural parameters influencing the macroscopic strength of concrete. A simplified analytical macroscopic strength criterion is then proposed. A large dataset is further constructed through the inversion of the analytical strength criterion by using the aggregates volume fraction, porosity, macroscopic uniaxial tensile and compressive strengths as input variables and the frictional coefficient and cohesion of cement particles as output unknowns. An ANN model containing four hidden layers and 100 neurons in each layer is constructed and trained by using this dataset. Various types of validation of the ANN model are performed. It is found that the proposed ANN based model can effectively predict the frictional coefficient and cohesion of porous cement paste at the microscopic scale with a very good accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Moving Bed Chemical Looping Combustion Fuel Reactor Modeling and Sensitivity Analysis

Chemical looping combustion (CLC) is a novel, coal-based power generation technology that has currently achieved only small-scale, non-integrated development status, with the fuel reactor being the key developmental component in the CLC process. Both circulating fluidized bed (CFB) and moving bed fuel reactors have been the subjects of ongoing development campaigns. The objective of the effort described in this report is to characterize a moving bed fuel reactor by applying more detailed, reaction kinetics-based models that represent the nature of this reactor with a more fundamental foundation than has previously been reported by developers. This report describes the modeling basis, and a “base” fuel reactor’s design and performance characteristics resulting from the model. A major focus of the evaluation has been placed on studies of the sensitivity of the base moving bed fuel reactor performance, design, and CLC power plant cost implications to the key parameters.

20 FOSSIL-FUELED POWER PLANTS↗