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Thermodynamic analysis of a two-stage binary-fluid ejector heat pump water heater
Ejector heat pump water heaters (EHPWHs) could significantly increase the thermal efficiency of domestic water heating and reduce greenhouse gas emissions. This study addresses two major technical barriers to using EHPWHs in domestic water heating—low heating cycle coefficient of performance (COP) and low condensation temperatures—using binary fluid pairs as a working fluid in a two-stage ejector system. A comprehensive, geometry-free model of binary-fluid ejectors was built and validated to predict the entrainment ratios of binary-fluid ejectors. A thermodynamic model of a two-stage binary-fluid ejector EHPWH was built to predict the heating cycle COP of EHPWHs. The performance of the EHPWH was theoretically evaluated using HFE7000 and Novec649 as primary fluids and R600 and R1234ze(Z) as secondary fluids. HFE7000/R600 gave the highest heating cycle COP (i.e., 1.356) in producing domestic hot water at 60.0 °C. An optimum evaporation temperature of the primary fluid was identified for the maximum effective entrainment ratio and effective pressure lift ratio of two-stage ejectors. Here, the effective entrainment ratio of the two-stage ejector dominated the heating cycle COP of the EHPWH. Primary fluids with lower latent heats of evaporation and/or secondary fluids with higher latent heats of evaporation yielded higher heating cycle COPs of EHPWHs.
Phase diagram to demarcate supercritical, transcritical, and continuous phase regimes for binary fluid equilibrium mixing relevant to combustion applications
Here, a robust methodology to develop phase diagrams of binary fluid mixtures at fixed thermo dynamic conditions (pressure, temperature, and mole fraction) as well as of two initially separated fluids undergoing mixing near critical conditions are presented for fluids and con ditions relevant to rockets, gas turbines, and diesel engine applications. Phase equilibria of mixtures is first examined to provide insight into the continuous-phase mixing behavior (including but not limited to supercritical behavior), and to develop a broadly applicable phase-diagram for binary fluid mixtures at fixed conditions. Next, adiabatic mixing theory and reduced Helmholtz equations of state are used to predict the thermodynamic conditions required to attain continuous-phase binary fluid mixing near critical conditions. Then, a 3D surface diagram (P,T fuel ,T amb ) separating single and two-phase regions is constructed by varying the ambient pressure and the initial temperatures of the two fluids. Polynomial fits of the 3D surfaces for 10 different binary mixtures are tabulated for nitrogen-alkane and methane-oxygen blends relevant to air-breathing and propellant based engines, respectively.
Searching for Suitable Binary Fluid for an Ejector Heat Pump for Domestic Water Heating
Water heating is a major source of energy consumption in the U.S. residential sector. Heat pumps can significantly increase the energy efficiency of water heating. An ejector heat pump (EHP) is a novel, thermally driven heat pump that uses an ejector as a thermocompressor. Choosing suitable working fluids is critical in developing high-performance EHPs. Therefore, this research screens binary fluid pairs (BFPs) for EHPs to produce domestic hot water at a high coefficient of performance (COP). The criteria for screening BFP candidates for EHP water heaters (EHPWHs) are established, and BFP candidates are shortlisted. This study identifies HFE7000, Novec649, HFE7100, HFE7200, and HFE7500 for the primary fluids and RE170, R600a, R600, and R1234ze(Z) for the secondary fluids. The thermodynamic model is employed to investigate the performance of EHPWHs using the shortlisted BFPs under various operating parameters, including the evaporation pressure of the primary working fluid in the high-temperature evaporator and the condensation temperature. In conclusion, the highest heating-cycle COP of 1.328 is achieved by an EHPWH operating with HFE7000/R600 at a condenser temperature of 50 °C and a pressure of 1.69 MPa in the high-temperature evaporator.
Machine Learning-Based Upscaling of Finite-Size Molecular Dynamics Diffusion Simulations for Binary Fluids
Molecular diffusion coefficients calculated using molecular dynamics (MD) simulations suffer from finite-size (i.e., finite box size and finite particle number) effects. Results from finite-sized MD simulations can be upscaled to infinite simulation size by applying a correction factor. For self-diffusion of single-component fluids, this correction has been well-studied by many researchers including Yeh and Hummer (YH); for binary fluid mixtures, a modified YH correction was recently proposed for correcting MD-predicted Maxwell–Stephan (MS) diffusion rates. In this study we use both empirical and machine learning methods to identify improvements to the finite-size correction factors for both self-diffusion and MS diffusion of binary Lennard-Jones (LJ) fluid mixtures. Using artificial neural networks (ANNs), the error in the corrected LJ fluid diffusion is reduced by an order of magnitude versus existing YH corrections, and the ANN models perform well for mixtures with large dissimilarities in size and interaction energies where the YH correction proves insufficient.
Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks
Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.
Foot-scale Evaluation of CO2-Responsive Polymer and CO2 Binary Fluid as an Alternative Fracturing Fluid for Enhanced Geothermal Systems
A foot-scale high-temperature true-triaxial fracturing apparatus was used to conduct hydraulic fracture tests on rock samples. The fracturing tests used different fluids including water, CO2, CO2 with water, and CO2 with a 1% polyallylamine (PAA)/water solution. The tests were conducted with both constant pressure injection and constant flow rate injection modes. CO2-based fracturing fluids were found to produce higher breakdown pressures, high transient flow rates, and produce higher-conductivity fractures as compared to water-based fracturing fluids. Additionally, faster pressurization rates with CO2-based fracturing fluids (obtained when fracturing at constant flow rate mode) are found to be associated with higher fracture conductivities. When fracturing with CO2-based fluids in the presence of a PAA aqueous solution, for example if the rock is saturated with 1wt% PAA in water, the volume expansion caused by CO2-induced crosslinking of PAA leads to a faster pressure increase due to the associated volume expansion and increase in viscosity. It was also found that CO2 as a fracturing fluid injected in hot dry rock (HDR) attain the highest fracture conductivity only when injected at very high flow rates, followed very closely by the CO2/PAA fracturing fluid system that generates fractures with, on average, similarly high conductivity values though independently of injection flow rate and using 1/6 of the mass of CO2 as compared to CO2 in HDR. Breakdown pressures were also similar for CO2 stimulation in HDR and CO2/PAA fluid system under identical injection flow rates. Finally, the well-known low viscosity of CO2 phase prevents the efficient transport of proppants while the reacted CO2/PAA fluid system is known to form a high viscosity binary fracturing fluid system with the potential to carry proppant in addition of being a fine fracturing fluid.
Learning Coarse-Grained Potentials for Binary Fluids
Even though atomistic and CG models have been used to simulate liquid nanodroplets in vapor, very few rigorous studies of the liquid-liquid interface structure are available, and most of them are limited to planar interfaces. In this work, we evaluate several existing force fields (FF)s, including two atomistic and three CG FFs, with respect to modeling the interface structure and thermodynamic properties of the water-hexane interface. Both atomistic FFs are able to quantitatively reproduce the interfacial tension and the coexisting densities of the experimentally-observed planar interface. We use the atomistic FFs to model water droplets in hexane and use these simulations to test the CG FFs. We found that the tested CG FFs cannot reproduce the interfacial tensions of planar and/or curved interfaces. Finally, we propose a new approach for learning coarse-grained (CG) potentials within the CG SDK (Shinoda-DeVane- Klein) FF framework from atomistic simulation data. We demonstrate that the new potential significantly improves the prediction of both the interfacial tension and structure of water-hexane planar and curved interfaces.
Exploration of Heat-Driven Ejector High-Temperature Heat Pumps
Heat-driven ejector heat pumps use a supersonic ejector as a thermo-compressor to replace the mechanical compressor. Supersonic ejectors have many advantages in high-temperature heat pump (HTHP) applications, including high operating temperature tolerance, no need for lubrication, low maintenance, and low cost. The coefficient of performance of ejector HTHPs could be improved by selecting binary fluids with unique thermodynamic properties. Although supersonic ejectors have been widely used in refrigeration systems, their application in spaces and water heating is limited. This study explores the theoretical potential of ejector HTHPs with a sink temperature of 100°C–130°C and a lift temperature of 10°C–30°C. Ejector HTHPs were evaluated with single-fluid ejectors (SFEs) and binary-fluid ejectors (BFEs). A comprehensive, geometry-free theoretical model of BFEs was developed to predict the theoretical maximum entrainment ratios. HFE7500 and R718 (water) were selected as working fluids for SFEs and BFEs. SFEs operating with R718 provided a higher coefficient of performance of ejector HTHPs than SFEs operating with HFE7500 and BFEs. This study preliminarily demonstrates the technical potential of ejector HTHP applications in recovering moderate-temperature heat sources
Experiments on the Capillary Condensation/Evaporation Hysteresis of Pure Fluids and Binary Mixtures in Cylindrical Nanopores
Here, a new experimental method, i.e., isochoric cooling/heating cycle measurement using differential scanning calorimeter (DSC), is applied to investigate the hysteretic phenomenon of pure components and mixtures confined in two different types of cylindrical nanopores (SBA-15 and KIT-6). The capillary condensation/evaporation hysteresis end point (T he ) for a specific system is determined by performing a series of measurements with different densities by increasing initial temperature and pressure. We confirm that for a pure component, T he is lower when confined in smaller nanopores, whereas T he for CH 4 /CO 2 and CH 4 /C 2 H 6 mixtures at the specific composition investigated are higher than that of pure CO 2 and C 2 H 6 , respectively, when confined in the same nanopores. To the best of our knowledge, this is the first time that T he of fluid mixture is experimentally studied, which further demonstrates that binary mixtures behave similarly to pure fluids when confined in nanoporous media. At low temperatures where hysteresis is observed, the shape as well as the duration of the exothermic peak (due to capillary condensation) and endothermic peak (due to capillary evaporation) indicate that capillary condensation, rather than capillary evaporation, takes place at/near a thermodynamic equilibrium. Within the accuracy of the measurements, we find that the total heat of capillary condensation is identical to that of capillary evaporation for all systems examined, regardless of the presence of hysteresis. By comparing the heat per unit volume among different systems, we also find that the heat per unit volume of the phase transition of confined pure fluid is lower than that of bulk, which further demonstrates that the molar density of confined pure liquid is less than that of bulk pure liquid at saturation.
Lattice Boltzmann method for diffusion-limited partial dissolution of fluids
A lattice Boltzmann model for two partially miscible fluids is developed. By partially miscible, we mean that although there is a definite interfacial region separating the two fluids with a surface tension force acting at all points of the transition region, each fluid can nonetheless accept molecules from the other fluid up to a set solubility limit. We allow each fluid to diffuse into the other with the solubility and diffusivity in each fluid being input parameters. The approach is to define two regions within the fluid. One interfacial region having finite width, across which most of the concentration change occurs, and in which a surface tension force and color separation step are allowed for. And one miscible fluid region where the concentration of the binary fluids follows an advection-diffusion equation and the mixture as a whole obeys the Navier-Stokes incompressible flow equations. Numerical examples are presented in which the algorithm produces results that are quantitatively compared to exact analytical results as well as qualitatively examined for their reasonableness. The model has the ability to simulate how bubbles of one fluid flow through another while dissolving their contents as well as to a range of practical invasion problems such as injecting supercritical CO 2 into a porous material saturated with water for sequestration purposes.
Thermal performance of an absorption-assisted two-stage ejector air-to-water heat pump
In this work, a gas-fired air-to-water ejector heat pump (EHP) for domestic hot water production is proposed and analyzed thermodynamically. The COP of the EHP is improved by using binary fluids (HFE7500 and water), and the high backpressure in the primary ejector (first-stage) is actively controlled by either a second-stage ejector and/or a LiBr-H 2 O absorption subsystem. A thermodynamic model is established for analysis and performance evaluation. A case study shows the backpressure of the first-stage ejector is reduced by 53.5%, and the backpressure control using the second-stage ejector increases the system COP by 21.0% compared with that using LiBr-H 2 O absorption. Parametric studies are conducted to investigate the roles of the first-stage ejector, the second-stage ejector, and the LiBr-H 2 O absorption subsystem. The first-stage ejector plays a dominant role in the EHP system performance. The EHP’s heating COP can reach 2.0 with an entrainment ratio of 0.12 in the first-stage ejector. EHP performance can be improved with a high entrainment ratio and a low-temperature primary working fluid in the first-stage and second-stage ejectors, a low condensation temperature in the first-stage ejector, and a high generating temperature and a low concentration of the LiBr-H 2 O solution.
Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations
Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely-resolved (e.g. molecular dynamics) and coarse-grained (e.g. continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 84115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics (SDPD). An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.
Ephemeral antibubbles: Spatiotemporal evolution from direct numerical simulations
Antibubbles, which consist of a shell of a low-density fluid inside a high-density fluid, have several promising applications. We show, via extensive direct numerical simulations (DNSs), in both two and three dimensions, that the spatiotemporal evolution of antibubbles can be described naturally by the coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations for a binary fluid. Our DNSs capture elegantly the gravity-induced thinning and breakup of an antibubble via the time evolution of the Cahn-Hilliard scalar-order-parameter field $\phi$, which varies continuously across interfaces, so we do not have to enforce complicated boundary conditions at the moving antibubble interfaces. To ensure that our results are robust, we supplement our CHNS simulations with sharp-interface volume-of-fluid DNSs. We track the thickness of the antibubble and calculate the dependence of the lifetime of an antibubble on several parameters; we show that our DNS results agree with various experimental results; in particular, the velocity with which the arms of the antibubble retract after breakup scales as σ 1/2 , where σ is the surface tension.
A mass-conserving lattice Boltzmann method with dynamic grid refinement for immiscible two-phase flows
A mass-conserving lattice Boltzmann method (LBM) for multiphase flows is presented in this paper. The proposed LBM improves a previous model (Lee and Liu, 2010 [21]) in terms of mass conservation, speed-up, and efficiency, and also extends its capabilities for implementation on non-uniform grids. The presented model consists of a phase-field lattice Boltzmann equation (LBE) for tracking the interface between different fluids and a pressure-evolution LBM for recovering the hydrodynamic properties. In addition to the mass conservation property and the simplicity of the algorithm, the advantages of the current phase-field LBE are that it is an order of magnitude faster than the previous interface tracking LBE proposed by Lee and Liu (2010) [21] and it requires less memory resources for data storage. Meanwhile, the pressure-evolution LBM is equipped with a multi-relaxation-time (MRT) collision operator to facilitate attainability of small relaxation rates thereby allowing simulation of multiphase flows at higher Reynolds numbers. Additionally, we reformulate the presented MRT-LBM on nonuniform grids within an adaptive mesh refinement (AMR) framework. Various benchmark studies such as a rising bubble and a falling drop under buoyancy, droplet splashing on a wet surface, and droplet coalescence onto a fluid interface are conducted to examine the accuracy and versatility of the proposed AMR-LBM. The proposed model is further validated by comparing the results with other LB models on uniform grids. A factor of about 20 in savings of computational resources is achieved by using the proposed AMR-LBM. As a more demanding application, the Kelvin–Helmholtz instability (KHI) of a shear-layer flow is investigated for both density-matched and density-stratified binary fluids. The KHI results of the density-matched fluids are shown to be in good agreement with the benchmark AMR results based on the sharp-interface approach. When a density contrast between the two fluids exists, a typical chaotic structure in the flow field is observed at a Reynolds number of 10000, which indicates that the proposed model is a promising tool for direct numerical simulation of two-phase flows.
Fluctuating hydrodynamics and the Rayleigh–Plateau instability
The Rayleigh–Plateau instability occurs when surface tension makes a fluid column become unstable to small perturbations. At nanometer scales, thermal fluctuations are comparable to interfacial energy densities. Consequently, at these scales, thermal fluctuations play a significant role in the dynamics of the instability. These microscopic effects have previously been investigated numerically using particle-based simulations, such as molecular dynamics (MD), and stochastic partial differential equation–based hydrodynamic models, such as stochastic lubrication theory. In this paper, we present an incompressible fluctuating hydrodynamics model with a diffuse-interface formulation for binary fluid mixtures designed for the study of stochastic interfacial phenomena. An efficient numerical algorithm is outlined and validated in numerical simulations of stable equilibrium interfaces. We present results from simulations of the Rayleigh–Plateau instability for long cylinders pinching into droplets for Ohnesorge numbers of Oh = 0.5 and 5.0. Both stochastic and perturbed deterministic simulations are analyzed and ensemble results show significant differences in the temporal evolution of the minimum radius near pinching. Short cylinders, with lengths less than their circumference, were also investigated. As previously observed in MD simulations, we find that thermal fluctuations cause these to pinch in cases where a perturbed cylinder would be stable deterministically. Finally, we show that the fluctuating hydrodynamics model can be applied to study a broader range of surface tension–driven phenomena.
Unveiling the Dynamics of KRAS4b on Lipid Model Membranes
Abstract Small GTPase proteins are ubiquitous and responsible for regulating several processes related to cell growth and differentiation. Mutations that stabilize their active state can lead to uncontrolled cell proliferation and cancer. Although these proteins are well characterized at the cellular scale, the molecular mechanisms governing their functions are still poorly understood. In addition, there is limited information about the regulatory function of the cell membrane which supports their activity. Thus, we have studied the dynamics and conformations of the farnesylated KRAS4b in various membrane model systems, ranging from binary fluid mixtures to heterogeneous raft mimics. Our approach combines long time-scale coarse-grained (CG) simulations and Markov state models to dissect the membrane-supported dynamics of KRAS4b. Our simulations reveal that protein dynamics is mainly modulated by the presence of anionic lipids and to some extent by the nucleotide state (activation) of the protein. In addition, our results suggest that both the farnesyl and the polybasic hypervariable region (HVR) are responsible for its preferential partitioning within the liquid-disordered (Ld) domains in membranes, potentially enhancing the formation of membrane-driven signaling platforms. Graphic Abstract
Systematic Mapping of Binary Nanocrystal Superlattices: The Role of Topology in Phase Selection
The self-assembly of two sizes of spherical nanocrystals has revealed a surprisingly diverse library of structures. To date, at least 15 distinct binary nanocrystal superlattice (BNSL) structures have been identified. The stability of these binary phases cannot be fully explained using the traditional conceptual framework treating the assembly process as entropy-driven crystallization of rigid spherical particles. Such deviation from hard sphere behavior may be explained by the soft and deformable layer of ligands that envelops the nanocrystals, which contributes significantly to the overall size and shape of assembling particles. In this work, we describe a set of experiments designed to elucidate the role of the ligand corona in shaping the thermodynamics and kinetics of BNSL assembly. Using hydrocarbon-capped Au and PbS nanocrystals as a model binary system, we systematically tuned the core radius ( R ) and ligand chain length ( L ) of particles and subsequently assembled them into binary superlattices. The resulting database of binary structures enabled a detailed analysis of the role of effective nanocrystal size ratio, as well as softness expressed as L/R , in directing the assembly of binary structures. This catalog of superlattices allowed us to not only study the frequency of different phases but to also systematically measure the geometric parameters of the BNSLs. Furthermore, this analysis allowed us to evaluate new theoretical models treating the cocrystallization of deformable spheres and to formulate new hypotheses about the factors affecting the nucleation and growth of the binary superlattices. Among other insights, our results suggest that the relative abundance of the binary phases observed may be explained not only by considerations of thermodynamic stability, but also by a postulated preordering of the binary fluid into local structures with icosahedral or polytetrahedral symmetry prior to nucleation.