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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three readers using a five point Likert scale. Results: There was no statistically significant difference between inter-reader and reader-algorithm agreement for either MAD or CCC metrics (p > 0.1). The algorithm phase was within 2% of the consensus phase in 15/21 of cases. The average absolute difference between consensus and algorithm best phases was 2.29% ± 2.47%, with a maximum difference of 8%. Average image quality scores for the algorithm chosen best phase were 4.01 ± 0.65 overall, 3.33 ± 1.27 for right coronary artery (RCA), 4.50 ± 0.35 for left anterior descending (LAD) artery, and 4.50 ± 0.35 for left circumflex artery (LCX). Average image quality scores for the consensus best phase were 4.11 ± 0.54 overall, 3.44 ± 1.03 for RCA, 4.39 ± 0.39 for LAD, and 4.50 ± 0.18 for LCX. There was no statistically significant difference (p > 0.1) between the image quality scores of the algorithm phase and the consensus phase. Conclusions: The proposed algorithm was statistically equivalent to a reader in selecting an optimal cardiac phase for CCTA exams. When reader and algorithm phases differed by >2%, image quality as rated by blinded readers was statistically equivalent. By detecting the optimal phase for CCTA reconstruction, the proposed algorithm is expected to improve coronary artery visualization in CCTA exams.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-R-39: Effects of Radiation Dose Reduction On Renal Cell Carcinoma Discrimination Using Multi-Phasic CT Imaging

Purpose: A method to discriminate different types of renal cell carcinoma (RCC) was developed using attenuation values observed in multiphasic contrast-enhanced CT. This work evaluates the sensitivity of this RCC discrimination task at different CT radiation dose levels. Methods: We selected 5 cases of kidney lesion patients who had undergone four-phase CT scans covering the abdomen to the lilac crest. Through an IRB-approved study, the scans were conducted on 64-slice CT scanners (Definition AS/Definition Flash, Siemens Healthcare) using automatic tube-current modulation (TCM). The protocol included an initial baseline unenhanced scan, followed by three post-contrast injection phases. CTDIvol (32 cm phantom) measured between 9 to 35 mGy for any given phase. As a preliminary study, we limited the scope to the cortico-medullary phase—shown previously to be the most discriminative phase. A previously validated method was used to simulate a reduced dose acquisition via adding noise to raw CT sinogram data, emulating corresponding images at simulated doses of 50%, 25%, and 10%. To discriminate the lesion subtype, ROIs were placed in the most enhancing region of the lesion. The mean HU value of an ROI was extracted and used to discriminate to the worst-case RCC subtype, ranked in the order of clear cell, papillary, chromophobe and the benign oncocytoma. Results: Two patients exhibited a change of worst case RCC subtype between original and simulated scans, at 25% and 10% doses. In one case, the worst-case RCC subtype changed from oncocytoma to chromophobe at 10% and 25% doses, while the other case changed from oncocytoma to clear cell at 10% dose. Conclusion: Based on preliminary results from an initial cohort of 5 patients, worst-case RCC subtypes remained constant at all simulated dose levels except for 2 patients. Further study conducted on more patients will be needed to confirm our findings. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant Support from: U01 CA181156.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Discovery of true electrochemical reactions for ultrahigh catalyst mass activity in water splitting

Better understanding of true electrochemical reaction behaviors in electrochemical energy devices has long been desired. It has been assumed so far that the reactions occur across the entire catalyst layer (CL), which is designed and fabricated uniformly with catalysts, conductors of protons and electrons, and pathways for reactants and products. By introducing a state-of-the-art characterization system, a thin, highly tunable liquid/gas diffusion layer (LGDL), and an innovative design of electrochemical proton exchange membrane electrolyzer cells (PEMECs), the electrochemical reactions on both microspatial and microtemporal scales are revealed for the first time. Surprisingly, reactions occur only on the CL adjacent to good electrical conductors. On the basis of these findings, new CL fabrications on the novel LGDLs exhibit more than 50 times higher mass activity than conventional catalyst-coated membranes in PEMECs. In conclusion, this discovery presents an opportunity to enhance the multiphase interfacial effects, maximizing the use of the catalysts and significantly reducing the cost of these devices.

08 HYDROGEN↗
DOE OSTI2021

Design of tough adhesive from commodity thermoplastics through dynamic crosslinking

Tough adhesives provide resistance against high debonding forces, and these adhesives are difficult to design because of the simultaneous requirement of strength and ductility. Here, we report a design of tough reversible/recyclable adhesive materials enabled by incorporating dynamic covalent bonds of boronic ester into commodity triblock thermoplastic elastomers that reversibly bind with various fillers and substrates. The spectroscopic measurements and density functional theory calculations unveil versatile dynamic covalent binding of boronic ester with various hydroxy-terminated surfaces such as silica nanoparticles, aluminum, steel, and glass. The designed multiphase material exhibits exceptionally high adhesion strength and work of debonding with a rebonding capability, as well as outstanding mechanical, thermal, and chemical resistance properties. Bonding and debonding at the interfaces dictate hybrid material properties, and this revelation of tailored dynamic interactions with multiple interfaces will open up a new design of adhesives and hybrid materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Giant piezoelectricity in oxide thin films with nanopillar structure

High-performance piezoelectric materials are critical components for electromechanical sensors and actuators. For more than 60 years, the main strategy for obtaining large piezoelectric response has been to construct multiphase boundaries, where nanoscale domains with local structural and polar heterogeneity are formed, by tuning complex chemical compositions. We used a different strategy to emulate such local heterogeneity by forming nanopillar regions in perovskite oxide thin films. We obtained a giant effective piezoelectric coefficient d 33 , f * of ~1098 picometers per volt with a high Curie temperature of ~450°C. Our lead-free composition of sodium-deficient sodium niobate contains only three elements (Na, Nb, and O). The formation of local heterogeneity with nanopillars in the perovskite structure could be the basis for a general approach to designing and optimizing various functional materials.

Science & Technology - Other Topics↗
DOE OSTI2019

Synthetic Methane-Consuming Communities from a Natural Lake Sediment

The factors and processes that influence the behavior and functionality of ecosystems inhabited by complex microbiomes are still far from being clearly understood. Synthetic microbial communities provide reduced-complexity models that allow an examination of ecological theories under defined and controlled conditions. In this study, we applied a multiphasic approach to study synthetic methane-oxidizing communities and species interactions as proxies to the natural communities. Our results confirm that, under selective pressures, natural-sediment communities of high complexity simplify rapidly, selecting for several major functional guilds, the major partners in methane oxidation being the Methylococcaceae methanotrophs and the Methylophilaceae methylotrophs, along with minor but persistent partners, members of Burkholderiales and Flavobacteriales. As a proof of concept, we established minimalist synthetic communities that were representative of the four functional guilds to demonstrate the dependency of the non-methane-utilizing species on the methanotrophs as the primary carbon-providing species. We observed that in communities consisting of multiple representatives of the key guilds, members of the same guild appeared to compete for resources. For example, when two methanotrophs of the same family were present, the two expressed similar key methanotrophy pathways and responded similarly to changing environmental conditions, suggesting that they perform a similar keystone function in situ. Similar observations were made for the Methylophilaceae. However, differences were noted in the expression of auxiliary and unique genes among strains of the same functional guild, reflecting differential adaptation and suggesting mechanisms for competition. At the same time, differences were also noted in the performances of partners with specific metabolic schemes. For example, a mutant of Methylotenera mobilis impaired in nitrate utilization behaved as a more efficient cooperator in methane consumption, suggesting that the loss of function may lead to changes in communal behavior. Overall, we demonstrate the robust nature of synthetic communities built of native lake sediment strains and their utility in addressing important ecological questions while using a simplified model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Evenly spaced columns in the Bishop Tuff (California, USA) as relicts of hydrothermal cooling

A few square kilometers of the Bishop Tuff in eastern California (USA) have evenly spaced columns that are more resistant to erosion than the surrounding tuff owing to the precipitation of mordenite, a low-temperature (100-130 °C) zeolite. We hypothesize that the columns are a result of instabilities at the liquid water and steam interface as cold water seeped into the still-cooling Bishop Tuff. We use two methods to quantitatively assess this hypothesis. First, scaling shows which hydrodynamic instabilities exist in the system. Second, to account for the effects of multiphase flow, latent heat, and the finite amplitude and temporal evolution of these instabilities we use two-dimensional numerical models of liquid water infiltrating hot tuff. These tests highlight several features of boiling hydrothermal systems. (1) The geometry of at least some convection appears to be broadly captured by linear stability theory that neglects reactive transport, heterogeneity of the host rock, and the finite amplitude of instabilities. (2) Slopes > 10% set the wavelength of convection, meaning that these columns formed somewhere with relatively gentle topography. (3) For permeabilities of > 10 -13 m 2 , the wavelength of the instability changes through time, slowing infiltration, while for permeabilities < 10 -15 m 2 , cooling is dominated by conduction. The spacing and stability of columns increase with higher vertical permeability and decrease with higher horizontal permeability. These columns are a rare window into hydrothermal processes that may be widespread.

58 GEOSCIENCES↗
DOE OSTI2015

How does the connectivity of open-framework conglomerates within multi-scale hierarchical fluvial architecture affect oil-sweep efficiency in waterflooding?

Understanding multi-phase fluid flow and transport processes within aquifers, candidate reservoirs for CO 2 sequestration, and petroleum reservoirs requires understanding a diverse set of geologic properties of the aquifer or reservoir, over a wide range of spatial and temporal scales. We focus on multiphase flow dynamics with wetting (e.g., water) and non-wetting (e.g., gas or oil) fluids, with one invading another. This problem is of general interest in a number of fields and is illustrated here by considering the sweep efficiency of oil during a waterflood. Using a relatively fine-resolution grid throughout a relatively large domain in these simulations and probing the results with advanced scientific visualization tools (Reservoir Visualization Analysis [RVA]/ ParaView software) promote a better understanding of how smaller-scale features affect the aggregate behavior at larger scales. We studied the effects on oil-sweep efficiency of the proportion, hierarchical organization, and connectivity of high-permeability open-framework conglomerate (OFC) cross-sets within the multi-scale stratal architecture found in fluvial deposits. We further analyzed oil production rate, water breakthrough time, and spatial and temporal distribution of residual oil saturation. As expected, the effective permeability of the reservoir exhibits large-scale anisotropy created by the organization of OFC cross-sets within unit bars, and the organization of unit bars within compound- bars. As a result, oil-sweep efficiency critically depends on the direction of the pressure gradient. However, contrary to expectations, the total amount of trapped oil due to the effect of capillary trapping does not depend on the magnitude of the pressure gradient within the examined range. Hence the pressure difference between production and injection wells does not affect sweep efficiency; although the spatial distribution of oil remaining in the reservoir depends on this value. Whether or not clusters of connected OFC span the domain affects only the absolute rate of oil production—not sweep efficiency.

58 GEOSCIENCES↗
DOE OSTI2019

Effect of Ion (Ar{sup +}) Irradiation on Cluster Magnetism and Magnetic Interactions in Fe{sub 67}Cr{sub 18}B{sub 15} Amorphous Alloy

The comparison of the resonance magnetic absorption spectra with the data on structure and magnetic properties of Fe{sub 67}Cr{sub 18}B{sub 15} amorphous samples has shown that a randomly inhomogeneous medium of amorphous alloy is multiphase. Two types of samples with the same chemical composition, but with a different clusterized structure, and the use of (Ar{sup +}) ion irradiation in the experiment made it possible to separate four basic phases with different magnetic properties. The basic phase α-(Fe,Cr) contains large clusters of D < 400 Å in size with a tendency to phase separation of iron (α-Fe) and chromium (α-Cr), which under irradiation, enhances the competing FM and AFM magnetic interactions and increases the intensity of the resonance magnetic absorption lines associated with α-Fe and α-Cr. The phase Fe{sub 3}B (D < 100 Å) is detected by independent line in the resonance absorption spectra only when its groupings are isolated from the α-(Fe,Cr) metal phase clusters. The fourth phase contains precluster groupings and disappears when the sample is irradiated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Discrete models of fluids: spatial averaging, closure and model reduction

We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.

Multiscale modeling, discrete models, fluid flow↗
DOE OSTI2019

Efficient Operator-Coarsening Multigrid Schemes for Local Discontinuous Galerkin Methods

An efficient hp-multigrid scheme is presented for local discontinuous Galerkin (LDG) discretizations of elliptic problems, formulated around the idea of separately coarsening the underlying discrete gradient and divergence operators. We show that traditional multigrid coarsening of the primal formulation leads to poor and suboptimal multigrid performance, whereas coarsening of the flux formulation leads to essentially optimal convergence and is equivalent to a purely geometric multigrid method. The resulting operator-coarsening schemes do not require the entire mesh hierarchy to be explicitly built, thereby obviating the need to compute quadrature rules, lifting operators, and other mesh-related quantities on coarse meshes. We show that good multigrid convergence rates are achieved in a variety of numerical tests on two-dimensional and three-dimensional uniform and adaptive Cartesian grids, as well as for curved domains using implicitly defined meshes and for multiphase elliptic interface problems with complex geometry. Extensions, e.g., to non-LDG discretizations and fully unstructured meshes, are briefly discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Mechanistic and Mitigation-Strategy Insights into NaCl and CaCl 2 Contamination of Proton-Exchange-Membrane Water Electrolysis Using Continuum Modeling

Cationic contaminants are detrimental to proton-exchange-membrane water electrolyzers (PEMWEs). To obtain insight, a 1-D, nonisothermal, multiphase continuum cell model including cationic contamination is developed. Simulations of steady-state cell performance predict decreased performance due to an increase in kinetic overpotential associated with the hydrogen-evolution reaction, which was attributed to decreased protonic-activity within the cathode catalyst layer from proton supplantation with contaminant cations. The accumulation and extent of cation exchange in the cathode catalyst layer depends on the operating current density due to migration. Simulations of cell recovery of potential suggest that a contaminated cell can recover approximately 78% (450 mV) with 24 h of constant current density operation at 2 A cm –2 , with higher current densities accelerating reduced recovery times. Parametric studies show that anode-side acidification at lower current densities inhibit cation contaminant adsorption, and cathode-side acidification at larger current densities facilitate the expulsion of adsorbed cations; for a cathode-side pH of 6 and 5, the cell can recover an additional 10% and 100% performance, respectively. Overall, the model serves as a framework for modeling other aspects of PEMWE systems to address durability and performance aspects, which can assist in improving the viability of the technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Elucidating Performance Limitations in Alkaline-Exchange- Membrane Fuel Cells

Water management is a serious concern for alkaline-exchange-membrane fuel cells (AEMFCs) because water is a reactant in the alkaline oxygen-reduction reaction and hydroxide conduction in alkaline-exchange membranes is highly hydration dependent. Here in this article, we develop and use a multiphysics, multiphase model to explore water management in AEMFCs. We demonstrate that the low performance is mostly caused by extremely non-uniform distribution of water in the ionomer phase. A sensitivity analysis of design parameters including humidification strategies, membrane properties, and water transport resistance was undertaken to explore possible optimization strategies. Furthermore, the strategy and issues of reducing bicarbonate/carbonate buildup in the membrane-electrode assembly with CO 2 from air is demonstrated based on the model prediction. Overall, mathematical modeling is used to explore trends and strategies to overcome performance bottlenecks and help enable AEMFC commercialization.

25 ENERGY STORAGE↗
DOE OSTI2016

Understanding Impacts of Catalyst-Layer Thickness on Fuel-Cell Performance via Mathematical Modeling

In this article, a two-dimensional, multiphase, transient model is introduced and used to explore the impact of catalyst-layer thickness on performance. In particular, the tradeoffs between water production and removal through transport or evaporation are highlighted, with a focus on low-temperature performance. For the latter, a case study of an ultra-thin catalyst layer is undergone to explore how various material properties alter the steady-state and startup performance of a cell. The findings provide understanding and guidance to optimize fuel-cell performance with thin electrodes.

25 ENERGY STORAGE↗
DOE OSTI2020

(Invited) Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO 2 R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. We specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

42 ENGINEERING↗
DOE OSTI2020

Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO2R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. Here, we specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

(Invited) Continuum Mathematical Modeling of Water Electrolysis: A Tutorial

Widespread use of hydrogen energy is contingent on the development of reliable and economical sources of hydrogen. Electrolysis from renewably-derived low-carbon electricity is a potentially viable method of hydrogen generation. Prime among the electrolysis technologies are those utilizing ion-conducting polymers (ionomers) including proton-exchange-membrane water electrolyzer (PEMWE). However, these technologies need to exhibit increased efficiency, performance, and durability to become commercially viable. Like most electrochemical devices, PEMWEs involve multiple components (e.g., catalyst, ionomer, transport layers, membrane, plates) and multiple phases, with phenomena occurring across different time and length scales. Furthermore, it is difficult to experimentally probe many of the species and phenomena during operation. Thus, mathematical modeling at the continuum level has been an invaluable aid in exploring, understanding, and optimizing PEMWE cell and components. Furthermore, this is especially true in the highly coupled and complex physics and chemistries that occur with the membrane-electrode assembly (MEA). The physics in a typical volume-averaged non-isothermal model include multiphase transport in porous media, concentrated-solution theory, Ohm's Law, and Butler-Volmer kinetics, and ion, gas, and water transport in the ionomer.

Dizon, Arthur↗
DOE OSTI2015

Cantera and Cantera Electrolyte Thermodynamics Objects

Cantera is a suite of object-oriented software tools for problems involving chemical kinetics, thermodynamics, and/or transport processes. It is a multi-organizational effort to create and formulate high quality 0D and 1D constitutive modeling tools for reactive transport codes.Institutions involved with the effort include Sandia, MIT, Colorado School of Mines, U. Texas, NASA, and Oak Ridge National Labs. Specific to Sandia's contributions, the Cantera Electrolyte Thermo Objects (CETO) packages is comprised of add-on routines for Cantera that handle electrolyte thermochemistry and reactions within the overall Cantera package. Cantera is a C++ Cal Tech code that handles gas phase species transport, reaction, and thermodynamics. With this addition, Cantera can be extended to handle problems involving liquid phase reactions and transport in electrolyte systems, and phase equilibrium problemsinvolving concentrated electrolytes and gas/solid phases. A full treatment of molten salt thermodynamics and transport has also been implemented in CETO. The routines themselves consist of .cpp and .h files containing C++ objects that are derived from parent Cantera objects representing thermodynamic functions. They are linked unto the main Cantera libraries when requested by the user. As an addendum to the main thermodynamics objects, several utility applications are provided. The first is multiphase Gibbs free energy minimizer based on the vcs algorithm, called vcs_cantera. This code allows for the calculation of thermodynamic equilibrium in multiple phases at constant temperature and pressure. Note, a similar code capability exists already in Cantera. This version follows the same algorithm, but gas a different code-base starting point, and is used as a research tool for algorithm development. The second program, cttables, prints out tables of thermodynamic and kinetic information for thermodynamic and kinetic objects within Cantera. This program serves as a "Get the numbers out" utility for Cantera, and as such it is very useful as a verification tool. These add-on utilities are encapsulated into a directory structure named cantera_apps, whose installation uses autoconf and also utilizes Cantera's application environment (i.e., they utilize Cantera as a library).

John Hewson, HarryMoffat↗