56 research outputs found
Real-fluid simulation of ammonia cavitation in a heavy-duty fuel injector
The reduction of greenhouse gases (GHG) emitted into the earth's atmosphere,
such as carbon dioxide, has obviously become a priority. Replacing fossil fuels
with cleaner renewable fuels (such as ammonia) in internal combustion engines
for heavy-duty vehicles is one promising solution to reduce GHG emissions. This
paper aims to study the cavitation formation in a heavy-duty injector using
ammonia as fuel. The simulation is carried out using a fully compressible
two-phase multi-component real-fluid model (RFM) developed in the CONVERGE CFD
solver. In the RFM model, the thermodynamic and transport properties are stored
in a table which is used during the run-time. The thermodynamic table is
generated using the in-house Carnot thermodynamic library based on vapor-liquid
equilibrium calculations coupled with a real-fluid equation of state. The RFM
model allows to consider the effects of the dissolved non-condensable gas such
as nitrogen on the phase change process. The obtained numerical results have
confirmed that the model can tackle the phase transition phenomenon under the
considered conditions. In contrast to previous numerical studies of the
cavitation phenomenon using hydrocarbon fuels, the formed cavitation pockets
were found to be primarily composed of ammonia vapor due to its high vapor
pressure, with minimal contribution of the dissolved non-condensable nitrogen.Comment: 32nd European Conference on Liquid Atomization & Spray Systems, ILASS
Europe, Sep 2023, Napoli, Ital
A non-additive repulsive contribution in an equation of state: The development for homonuclear square well chains equation of state validated against Monte Carlo simulation
International audienceThis work consists of the adaptation of a non-additive hard sphere theory inspired by Malakhov and Volkov, Polym. Sci. Ser. A. 2007;49(6):745-756 to a square-well chain. Using the thermodynamic perturbation theory, an additional term is proposed that describes the effect of perturbing the chain of square well spheres by a non-additive parameter. In order to validate this development, NPT Monte Carlo simulations of thermodynamic and structural properties of the non-additive square well (NASW) for a pure chain and a binary mixture of chains are performed. Good agreements are observed between the compressibility factor originating from the theory and those from molecular simulations
Modeling of mixed-solvent electrolyte systems
International audienceModels for mixed-solvent strong electrolytes, using an equation of state (EoS) are reviewed in this work. Through the example of ePPC-SAFT (that includes a Born term and ionic association), the meaning and the effect of each contribution to the solvation energy and the mean ionic activity coefficient are investigated. The importance of the dielectric constant is critically reviewed, with a focus on the use of a salt-concentration dependent function. The parameterization is performed using two adjustable parameters for each ion: a minimum approach distance () and an association energy (). These two parameters are optimized by fitting experimental activity coefficient and liquid density data, for all alkali halide salts simultaneously, in the range 298K to 423K. The model is subsequently tested on a large number of available experimental data, including salting out of Methane/Ethane/CO 2 /H 2 S. In all cases the deviations in bubble pressures were below 20% AADP. Predictions of vapor-liquid equilibrium of mixed solvent electrolyte systems containing methanol, ethanol are also made where deviations in bubble pressures were found to be below 10% (AADP)
HMOE: Hypernetwork-based Mixture of Experts for Domain Generalization
Due to domain shift, machine learning systems typically fail to generalize
well to domains different from those of training data, which is what domain
generalization (DG) aims to address. Although various DG methods have been
developed, most of them lack interpretability and require domain labels that
are not available in many real-world scenarios. This paper presents a novel DG
method, called HMOE: Hypernetwork-based Mixture of Experts (MoE), which does
not rely on domain labels and is more interpretable. MoE proves effective in
identifying heterogeneous patterns in data. For the DG problem, heterogeneity
arises exactly from domain shift. HMOE uses hypernetworks taking vectors as
input to generate experts' weights, which allows experts to share useful
meta-knowledge and enables exploring experts' similarities in a low-dimensional
vector space. We compare HMOE with other DG algorithms under a fair and unified
benchmark-DomainBed. Our extensive experiments show that HMOE can divide
mixed-domain data into distinct clusters that are surprisingly more consistent
with human intuition than original domain labels. Compared to other DG methods,
HMOE shows competitive performance and achieves SOTA results in some cases
A-UNIFAC modelling of binary and multicomponent phase equilibria of fatty esters+water+methanol+glycerol
The production of methyl and ethyl esters of fatty acids is of great industrial interest,
considering the direct application of these esters as biodiesel. For biodiesel purification and by-products recovery processes design and optimization, the prediction of the phase behaviour of mixtures containing fatty esters, alcohols, glycerol and water is of utmost importance. In this work we show the capability of a A-UNIFAC to correlate and predict phase behaviour of these mixtures. This GE model is an extension of UNIFAC that explicitly
includes association effects between groups based on the statistical Wertheim theory [1].
For the water-esters binary systems, the residual and association parameters have been
previously estimated using low pressure VLE data [1]. The use of these parameters to
predict liquid-liquid equilibrium results in good agreement with experimental information on binaries of water with acetic, octanoic or dodecanoic acids methyl esters.
The association effect in methanol and glycerol are represented with the same hydrogen bonding hydroxyl groups (OH) with two associating sites, one group in methanol and three in glycerol. For the residual contribution, both molecules are considered as molecular groups (CH3OH and C3H8O3). The residual interaction parameters between CH3OH and C3H8O3 were obtained by fitting isothermal liquid-liquid equilibrium data on the ternary system dodecanoic acid methyl ester-methanolâglycerol [2]. The glycerol/paraffin (C3H8O3/CH2) and
glycerol/ester (C3H8O3/CCOO) interaction parameters were estimated by fitting experimental data on liquid-liquid equilibrium and infinite dilution activity coefficients of the binary systems
dodecanoic acid methyl ester-glycerol and hexanoic acid methyl ester-glycerol between 320-438 K [2].
A-UNIFAC with the final set of parameters is able to predict with good agreement
experimental data on binary and ternary liquid-liquid equilibria of glycerol + methanol + fatty esters as well as infinite dilution activity coefficient for this system.
References
[1] O. Ferreira, E.A. Macedo, S.B. Bottini, Fluid Phase Equilib. 227 (2005) 165-176.
[2] F.M. Korgitzsch, Study of Phase Equilibria as a Fundament for the Refinement of Vegetable and Animal Fats and Oils. Ph.D. Dissertation, TU Berlin, 1993
A multi-layered view of chemical and biochemical engineering
The contents of this article are based on the results of discussions the corresponding author has had since 2015 with the co-authors, who are members of academia and industry in Europe, on the scope and significance of chemical and biochemical engineering as a discipline. The result is a multi-layered view of chemical and biochemical engineering where the inner-layer deals with the fundamental principles and their application; the middle-layer deals with consolidation and expansion of the principles through a combination of science and engineering, leading to the development of sustainable technologies; and the outer-layer deals with integration of knowledge and collaboration with other disciplines to achieve a more sustainable society. Through this multi-layered view several important issues with respect to education, research and practice are highlighted together with current and future challenges and opportunities
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