39 research outputs found
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CADS:Cantera Aerosol Dynamics Simulator.
This manual describes a library for aerosol kinetics and transport, called CADS (Cantera Aerosol Dynamics Simulator), which employs a section-based approach for describing the particle size distributions. CADS is based upon Cantera, a set of C++ libraries and applications that handles gas phase species transport and reactions. The method uses a discontinuous Galerkin formulation to represent the particle distributions within each section and to solve for changes to the aerosol particle distributions due to condensation, coagulation, and nucleation processes. CADS conserves particles, elements, and total enthalpy up to numerical round-off error, in all of its formulations. Both 0-D time dependent and 1-D steady state applications (an opposing-flow flame application) have been developed with CADS, with the initial emphasis on developing fundamental mechanisms for soot formation within fires. This report also describes the 0-D application, TDcads, which models a time-dependent perfectly stirred reactor
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Aria 1.5 : user manual.
Aria is a Galerkin finite element based program for solving coupled-physics problems described by systems of PDEs and is capable of solving nonlinear, implicit, transient and direct-to-steady state problems in two and three dimensions on parallel architectures. The suite of physics currently supported by Aria includes the incompressible Navier-Stokes equations, energy transport equation, species transport equations, nonlinear elastic solid mechanics, and electrostatics as well as generalized scalar, vector and tensor transport equations. Additionally, Aria includes support for arbitrary Lagrangian-Eulerian (ALE) and level set based free and moving boundary tracking. Coupled physics problems are solved in several ways including fully-coupled Newton's method with analytic or numerical sensitivities, fully-coupled Newton-Krylov methods, fully-coupled Picard's method, and a loosely-coupled nonlinear iteration about subsets of the system that are solved using combinations of the aforementioned methods. Error estimation, uniform and dynamic h-adaptivity and dynamic load balancing are some of Aria's more advanced capabilities. Aria is based on the Sierra Framework
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Modeling pore corrosion in normally open gold- plated copper connectors.
The goal of this study is to model the electrical response of gold plated copper electrical contacts exposed to a mixed flowing gas stream consisting of air containing 10 ppb H{sub 2}S at 30 C and a relative humidity of 70%. This environment accelerates the attack normally observed in a light industrial environment (essentially a simplified version of the Battelle Class 2 environment). Corrosion rates were quantified by measuring the corrosion site density, size distribution, and the macroscopic electrical resistance of the aged surface as a function of exposure time. A pore corrosion numerical model was used to predict both the growth of copper sulfide corrosion product which blooms through defects in the gold layer and the resulting electrical contact resistance of the aged surface. Assumptions about the distribution of defects in the noble metal plating and the mechanism for how corrosion blooms affect electrical contact resistance were needed to complete the numerical model. Comparisons are made to the experimentally observed number density of corrosion sites, the size distribution of corrosion product blooms, and the cumulative probability distribution of the electrical contact resistance. Experimentally, the bloom site density increases as a function of time, whereas the bloom size distribution remains relatively independent of time. These two effects are included in the numerical model by adding a corrosion initiation probability proportional to the surface area along with a probability for bloom-growth extinction proportional to the corrosion product bloom volume. The cumulative probability distribution of electrical resistance becomes skewed as exposure time increases. While the electrical contact resistance increases as a function of time for a fraction of the bloom population, the median value remains relatively unchanged. In order to model this behavior, the resistance calculated for large blooms has been weighted more heavily
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Foam process models.
In this report, we summarize our work on developing a production level foam processing computational model suitable for predicting the self-expansion of foam in complex geometries. The model is based on a finite element representation of the equations of motion, with the movement of the free surface represented using the level set method, and has been implemented in SIERRA/ARIA. An empirically based time- and temperature-dependent density model is used to encapsulate the complex physics of foam nucleation and growth in a numerically tractable model. The change in density with time is at the heart of the foam self-expansion as it creates the motion of the foam. This continuum-level model uses an homogenized description of foam, which does not include the gas explicitly. Results from the model are compared to temperature-instrumented flow visualization experiments giving the location of the foam front as a function of time for our EFAR model system
Computational thermal, chemical, fluid, and solid mechanics for geosystems management.
This document summarizes research performed under the SNL LDRD entitled - Computational Mechanics for Geosystems Management to Support the Energy and Natural Resources Mission. The main accomplishment was development of a foundational SNL capability for computational thermal, chemical, fluid, and solid mechanics analysis of geosystems. The code was developed within the SNL Sierra software system. This report summarizes the capabilities of the simulation code and the supporting research and development conducted under this LDRD. The main goal of this project was the development of a foundational capability for coupled thermal, hydrological, mechanical, chemical (THMC) simulation of heterogeneous geosystems utilizing massively parallel processing. To solve these complex issues, this project integrated research in numerical mathematics and algorithms for chemically reactive multiphase systems with computer science research in adaptive coupled solution control and framework architecture. This report summarizes and demonstrates the capabilities that were developed together with the supporting research underlying the models. Key accomplishments are: (1) General capability for modeling nonisothermal, multiphase, multicomponent flow in heterogeneous porous geologic materials; (2) General capability to model multiphase reactive transport of species in heterogeneous porous media; (3) Constitutive models for describing real, general geomaterials under multiphase conditions utilizing laboratory data; (4) General capability to couple nonisothermal reactive flow with geomechanics (THMC); (5) Phase behavior thermodynamics for the CO2-H2O-NaCl system. General implementation enables modeling of other fluid mixtures. Adaptive look-up tables enable thermodynamic capability to other simulators; (6) Capability for statistical modeling of heterogeneity in geologic materials; and (7) Simulator utilizes unstructured grids on parallel processing computers
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Experiments for foam model development and validation.
A series of experiments has been performed to allow observation of the foaming process and the collection of temperature, rise rate, and microstructural data. Microfocus video is used in conjunction with particle image velocimetry (PIV) to elucidate the boundary condition at the wall. Rheology, reaction kinetics and density measurements complement the flow visualization. X-ray computed tomography (CT) is used to examine the cured foams to determine density gradients. These data provide input to a continuum level finite element model of the blowing process
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Multiscale models of nuclear waste reprocessing : from the mesoscale to the plant-scale.
Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans
Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have
fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in
25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16
regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of
correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP,
while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in
Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium
(LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region.
Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant
enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the
refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa,
an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of
PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent
signals within the same regio
The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe