Fuel Cell Model Research Articles

A numerical investigation of operating condition effects on unitized regenerative fuel cells with elliptically shallow channel during mode switching

ABSTRACT In this study, a two-dimensional, two-phase, non-isothermal, and un-steady state unitized regenerative fuel cell model is established. The effect of various operating conditions on the variation trend of parameters and cell performance during mode switching from fuel cell to electrolytic cell mode is studied when using an elliptically shallow flow channel. Three operating parameter conditions are discussed, including inlet gas velocity, electrolytic cell voltage and water supply velocity. The effects of various operating conditions on cell performance and parameters are compared. The results show that different operating conditions have different effects on cell performance. When switching from fuel cell mode to electrolytic cell mode, changing the stoichiometric ratio of inlet gas velocity does not affect the cell performance after mode switching. The cell performance can be improved gradually with the increase in electrolytic cell voltage. Increasing the flow rate of liquid water can effectively speed up the stabilization time, however, the cell performance is slightly reduced, and it is easy to accumulate oxygen at the outlet.

Wall-function method used to simplify the solid oxide fuel cell model

Numerical model is a powerful tool in the solid oxide fuel cell (SOFC) study, but its application is seriously restricted by the tremendous demand of computational resources and time due to the high aspect ratio of functional layers. In this paper, the wall-function method widely used in turbulent flow model is introduced to simplify the SOFC model. By analyzing the similarity in SOFC functional layers to the viscous flow nearby wall, a set of wall functions is developed to calculate the generating current in functional layers instead of the traditional complex partial differential equations. Compared with traditional full 3D model, the simplified model based on wall-function method shows similar accuracy but uses only about one third mesh elements and spends less than a half of solution time. Numerical results show that there are two important advantages for the wall-function method: 1) it allows a coarse mesh which can significantly reduce the computational storage and time; 2) it allows the introduction of other information in wall-functions and uses denser points in thickness direction which can considerably improve the accuracy of model.

Parameter Identification of Proton Exchange Membrane Fuel Cell Based on Hunger Games Search Algorithm

This paper presents a novel minimum seeking algorithm referred to as the Hunger Games Search (HGS) algorithm. The HGS is used to obtain optimal values in the model describing proton exchange membrane fuel cells (PEMFCs). The PEMFC model has many parameters that are linked in a nonlinear manner, as well as a set of constraints. The HGS was used with the aforementioned model to test its performance against nonlinear models. The main aim of the optimization problem was to obtain accurate values of PEMFC parameters. The proposed heuristic algorithm was used with two commercial PEMFCs: the Ballard Mark V and the BCS 500 W. The simulation results obtained using the HGS-based model were compared to the experimental results. The effectiveness of the proposed model was verified under various temperature and partial pressure conditions. The numerical output results of the HGS-based fuel cell model were compared with other optimization algorithm-based models with respect to their efficiency. Moreover, the parametric t-test and other statistical analysis methods were employed to check the robustness of the proposed algorithm under various independent runs. Using the proposed HGS-based PEMFC model, a model with very high precision could be obtained, affecting the operation and control of the fuel cells in the simulation analyses.

A comparison of various universally applicable power distribution strategies for fuel cell hybrid trains utilizing component modeling at different levels of detail: From simulation to test bench measurement

A comparative study of energy management strategies for fuel cell hybrid trains, which focuses merely on universally applicable power distribution strategies, is presented in this contribution. These scalable strategies include a load follower strategy, an adaptive rule-based strategy, and adaptive Pontryagin's minimum principle (APMP)-based strategies with or without considering the relaxation process in batteries. For the load follower strategy, information about the characteristic consumption curves of the fuel cell system and the equivalent circuit of the batteries is not required. The adaptive rule-based strategy exploits the fuel cell system's characteristic consumption curves to maintain the fuel cell power close to its mean value. For the APMP-based strategies, in addition to the fuel cell modeling, the battery modeling with and without relaxation process in batteries is considered separately. In order to fairly compare the different scalable energy management strategies regarding hydrogen efficiency, Pontryagin's minimum principle-based strategy is used as the reference strategy, which considers the relaxation process in batteries. The comparison of the four strategies in terms of fuel economy is firstly based on the simulative analysis. For the different strategies, the additional hydrogen consumption amounts to 1.6%, 0.7%, 0.6%, and 0.6% respectively, compared to the reference strategy under a typical all-day regional train driving cycle. Then, in the RWTH Aachen University's Center for Mobile Propulsion, the hydrogen consumption is measured experimentally using the different strategies for a short driving cycle. The APMP strategy considering the relaxation process in batteries, consumes the least hydrogen per kilometer travel of 161.9 g/km, with charge sustaining maintained, which is the most energy-efficient energy management strategy. The simulation and experimental results show that the strategy should be selected based on the level of detail to utilize the modeling accuracy of components. Furthermore, due to the scalability of the strategies, they can be further transferred to other applications without enormous tuning effort.

Improving Water Management and Performance of an Air-Cooled Fuel Cell System Using Pressurized Air for Aviation Applications

Air-cooled fuel cell systems feature a light-weight and simple design and are thus recognized as a suitable technology for drone and aviation applications. As compared to liquid-cooled fuel cell systems, however, they suffer from low specific power per unit volume and unstable performance due to severe electrolyte dehydration and nonuniform profiles of current density and temperature inside a fuel cell stack. Here, we present a high-pressure air-cooled fuel cell system in which atmospheric air is pre-compressed by a compressor and then fed into the fuel cell stack. To minimize the compressor power consumption, the system is designed to recirculate the exhaust air from the fuel cell stack. A three-dimensional two-phase fuel cell model is implemented with a high-pressure air-cooled fuel cell system mainly consisting of an air-cooled fuel cell stack, compressor, air chamber and duct, and heat exchanger and is used to predict superior fuel cell performances under various high-pressure conditions. Simulation results show that the fuel cell operation at 2 atm allows an increase of up to two times the stack power and 1.5 times the net system power compared to a 1-atm fuel cell operation.

Numerical Investigation of Mass Transfer in PEM Fuel Cell with Straight Gas Flow Channels using CFD

Interest in PEM fuel cells has grown rapidly in recent years because of its possible applications. The performance of PEM fuel cells is strongly affected by various physical factors, such as the flow of reactant gas, thermal management and water management. The performance and characteristics of a PEM fuel cell have been analysed through the development of a 3D model and numerical simulation. The result obtained from the computational model shows details of species movement, charge Transport and mass transfer phenomena. This paper also investigates the influence of input parameters on the output of the PEM fuel cell model. The result from the analytical study is compared with experimental results to check the accuracy of the model.

Damage Modeling of Solid Oxide Fuel Cells Accounting for Redox Effects

This paper applies a multiscale mechanistic damage model developed for porous brittle ceramics and implemented in finite element analysis (FEA) packages [1] to study progressive damage in solid oxide fuel cells (SOFC) subjected to thermomechanical loading under operating and shutdown states. The damage model captures the micromechanics of stiffness reduction due to material porosity change and microcracking and integrates the as-obtained stiffness reduction law into a continuum damage mechanics (CDM) formulation for the evolution of microcracks up to fracture. An Eshelby-Mori-Tanaka approach (EMTA) [2-3] is first used to model the ceramic containing pores and aligned microcracks regarded as inclusions with negligible stiffness. The stiffness of the actual porous ceramic is obtained from the EMTA solution averaged over all possible microcrack orientations using an orientation averaging method. The evolution of microcracking damage is described by a CDM formulation derived from our previous model [4]. Apart from the operating and shutdown states, additional damage that may occur due to reduction and re-oxidation (redox cycling) of Ni/YSZ anodes is also studied. The reduction of NiO into Ni leads to changes in volume and porosity of the anode layer that consequently change its physical and thermomechanical properties. The volume change or volumetric “swelling” during redox cycling may affect the structural integrity of the anode and may cause fracture of the electrolyte under high tensile stresses leading to operational failure for SOFCs. In the constitutive relations, volumetric swelling is treated in a similar way to thermal expansion using the models developed in Refs [5-6] for fusion energy ceramic materials. However, while thermal expansion vanishes if temperature change tends to zero, swelling is irreversible and significantly contributes to degrade SOFC stacks during redox cycling.This damage model was implemented in the commercial FEA software ABAQUS© and ANSYS© via user subroutines. First, it has been validated through predictions of strength and stress-strain response for the typical SOFC ceramic materials. Figs 1(a) and 1(b) show the predicted stress-strain responses as a function of temperature for dense NiO/YSZ and Ni/YSZ, respectively. These figures also illustrate the predicted responses at 750°C with prescribed initial values of porosity. The damage model predicts significant reductions in strength and elastic modulus with higher initial porosity and higher temperatures, and the predicted trends are in good agreement with the experimental findings [7-8].Next, the damage model was applied to predict the potential for degradation in a generic planar SOFC stack with large active area cells modeled in ANSYS. Stack models with single and multi-cells were simulated in both co-flow and counter-flow configurations. The thermomechanical loads representing the operating and shutdown conditions were simulated. The realistic thermal gradients that occur in an operating stack were imposed in the models by solving the electrochemistry under various operating conditions using the in-house SOFC multiphysics code (SOFC MP-3D) [9-10]. In addition to the operating and shutdown conditions, a constant temperature redox cycle was also simulated to capture overall cell electrode damage due to volumetric swelling of the Ni/YSZ anode in the anode supported cells. The results from single cell stack models showed little damage at operating and shutdown conditions which could be attributed to enough out-of-plane support for the PEN assembly. The results from the multicell stacks (Fig. 2) showed higher damage in counter-flow configuration. Within the stack, the top cells experienced the highest damage and the middle cells experienced the lowest. Overall, no significant damage that may lead to total failure of the cells was observed in the multicell stack models with the operating conditions considered in this study.

A Simplified Model for Reversible Solid Oxide Fuel Cells

: Butler-Volmer Equations based on a first order approximation of global redox reaction kinetics have been used in the past successfully for design analysis of solid oxide fuel cells. Such a model forms the backbone of the widely used multidimensional code, DREAM-SOFC originally developed at West Virginia University and currently being used by the fuel cell research team at the US DOE lab, National Energy Technology Laboratory (NETL). Recent interest in using solid oxide cells (SOCs) for hydrogen production has prompted the question as to whether the Butler-Vomer Model (BVM) empirically calibrated and used in DREAM-SOFC would be appropriate for simulation of reversible fuel cells as well. To this end we have simulated anode supported Ni/YSZ/LSCF button cells in reversible mode and found that the BVM is not capable of reproducing the trends observed in experiments performed at various applied steam, hydrogen and oxygen concentrations, even if some key parameters such as effective bulk diffusivity and exchange current density are treated as calibration parameters and adjusted freely. To bridge this gap, we modified the oxygen electrode model using a simplified version of the single pathway oxygen reduction reaction equations originally put forth by Svensson et al. [1]. In the simplified model, it is assumed that the adsorbed oxygen concentration remains close to its equilibrium value in most of the oxygen electrode active layer. This assumption eliminates the need to solve the more difficult, stiff surface coverage transport equation leaving only the oxygen ion vacancy concentration to be solved for, thus simplifying the model greatly. This paper presents the mathematical model, and an in-depth analysis of the results from this model applied to button cells with LSCF and LSM electrodes. Figure 1 shows the comparison between the simulated and experimental polarization curves. As shown, good agreement is achieved between simulations and experiments for fuel cell and electrolysis modes. We conclude that by extending the BVM only by adding the vacancy concentration transport equation, leads to a simple yet sufficient model with which one can perform very fast calibration and design analysis of reversible SOCs with minimal computation time.Reference:[1] A.M. Svensson, et al., J. Electrochem. Soc., 145(4), 1390 (1998) doi: 10.1149/1.1838471 Figure 1

Revised Zero-Dimensional Model for a Solid Oxide Fuel Cell with Mo-Doped Ceria Anode Using Syngas as Fuel

A zero-dimensional model was implemented to simulate the performance of a solid oxide fuel cell (SOFC) with Mo-doped ceria (CMO) anode using humidified (3%v/v water) hydrogen or syngas (50%v/v H2 – 50%v/v CO) as fuel. The model was validated preliminarily through experimental data generated at 800ºC using a SOFC with coated electrodes supported in the electrolyte (a 20 mm diameter yttria-stabilized zirconia, YSZ, disc) with a 14 mm diameter CMO|CMO-YSZ anode and a 14 mm diameter LSM-YSZ|LSM (lanthanum strontium manganite) cathode. Polarization (cell voltage vs current density, ΔEcell vs j) and power density (power density vs current density, Pelec vs j) curves were generated via linear sweep voltammetry connecting the SOFC to a Gamry Reference 3000 potentiostat/galvanostat/ZRA using platinum mesh and wires.The open circuit voltage (OCV) of the SOFC operating with humidified hydrogen was modelled directly using Nernst equations for the electrochemical hydrogen oxidation and oxygen reduction reactions. For the case of the SOFC operating with humidified syngas, the electrochemical hydrogen and carbon monoxide oxidation reactions occur simultaneously at the anode. Hence, the Nernst equation was corrected by each anodic reaction selectivity determined solving mass balances coupled to an electrochemical kinetics model.Figure 1.a shows the fitted polarization and power density curves. Maximum SOFC power densities of ca. 1295 W m-2 (at 0.53 V and 2434 A m-2) and ca. 1084 W m-2 (at 0.52 V and 2106 A m-2) are predicted for the cell operating with humidified hydrogen and humidified syngas as fuel, respectively. These values are 2 and 5% lower than the experimental values. The OCVs calculated are ca. 1.10 V and 1.01 V, respectively, which are 5 and 8% higher/lower than the experimental values. The differences observed are attributed to the non-ideality of the gases due to their interaction with the electrode surfaces, and the possible infiltration of air into the anodic chamber [1,2].The SOFC ohmic losses calculated represent ca. 72% of the total voltage losses when operating at the maximum power density, which are attributed to the low electrical conductivities of the CMO|CMO-YSZ anode (CMO electrical conductivity is ca. 0.501 S m-1 at 800ºC [3]) and the thick electrolyte (ca. 2.203 S m-1 at 800ºC [4]). Improvements are being introduced to the anode material by including nickel, which will contribute to increase the hydrogen oxidation kinetics while CMO protects the electrode from carbon deposition when syngas is used as fuel. Presently, activation losses represent ca. 28% of the total voltage losses at the maximum power density. It has been reported that for SOFCs using syngas as fuel, the anode active sites are more occupied by carbon monoxide molecules due to their slower oxidation kinetics in comparison with hydrogen. Nevertheless, carbon monoxide is also susceptible to undergo a surface reforming process via the water-gas shift reaction. Such phenomenon becomes more relevant at high carbon monoxide concentrations, which was the case in this study (50% v/v CO), thus favoring the electricity generation through hydrogen oxidation at the anode surface [2].For the SOFC using humidified syngas as fuel, the model assumes that the desorption equilibrium pressure of hydrogen (pH2 *) on the surface of molybdenum in the CMO|CMO-YSZ anode is equal to that reported for humidified hydrogen on the surface of nickel in Ni-YSZ anodes (0.09 atm) [5]. Figure 1.b shows the results obtained for the sensitivity analysis of the model as a function of pH2 *, which indicates that unless its value is increased by ca. 220% over 0.09 atm the exchange current density for carbon monoxide oxidation (j0,CO) does not go below its lower confidence limit. It is unlikely that this parameter reaches such level of discrepancy because it implies that hydrogen adsorption at the anode surface is strongly diminished, thus electrochemical oxidation kinetics decrease considerably which is not consistent with the experimental observations.Future work includes the analysis of the kinetic parameters dependence on the temperature and the fuels partial pressures.

Modeling and experimental parameterization of an electrically controllable PEM fuel cell

Optimized integration of fuel cells into grids or on-board power supplies is necessary to facilitate replacement of conventional energy producers by a reliable and plannable power generation technology. Due to the interdependency between fuel cell current and voltage, integration of fuel cells requires a power conditioning system, which increases integration weight and cost. For this reason, integration of electric field modifier electrodes into the setup of proton exchange membrane fuel cells is a new approach to control the output voltage in order to minimize the subsequent power conditioning system. This approach considers the physics of proton transport through the electrolyte membrane and could offer a lever to control the ohmic resistance. In this paper, a fuel cell model is implemented in MATLAB and extended by electric field modifier electrodes, allowing control of the ohmic resistance through an externally applied voltage. The concept of boosting and attenuating fuel cell voltage is presented along with different setups to enable this behavior. Furthermore, an electrical equivalent circuit for electrically controllable fuel cells is developed and implemented in MATLAB/Simulink. A method to parameterize the developed MATLAB and Simulink models by first experimental results is presented.

Proton Exchange Membrane Fuel Cells Modeling Using Chaos Game Optimization Technique

For the precise simulation performance, the accuracy of fuel cell modeling is important. Therefore, this paper presents a developed optimization method called Chaos Game Optimization Algorithm (CGO). The developed method provides the ability to accurately model the proton exchange membrane fuel cell (PEMFC). The accuracy of the model is tested by comparing the simulation results with the practical measurements of several standard PEMFCs such as Ballard Mark V, AVISTA SR-12.5 kW, and 6 kW of the Nedstack PS6 stacks. The complexity of the studied problem stems from the nonlinearity of the PEMFC polarization curve that leads to a nonlinear optimization problem, which must be solved to determine the seven PEMFC design variables. The objective function is formulated mathematically as the total error squared between the laboratory measured terminal voltage of PEMFC and the estimated terminal voltage yields from the simulation results using the developed model. The CGO is used to find the best way to fulfill the preset requirements of the objective function. The results of the simulation are tested under different temperature and pressure conditions. Moreover, the results of the proposed CGO simulations are compared with alternative optimization methods showing higher accuracy.

Revised Zero-Dimensional Model for a Solid Oxide Fuel Cell with Mo-Doped Ceria Anode Using Syngas as Fuel

A zero-dimensional model was implemented to simulate the performance of a solid oxide fuel cell (SOFC) with Mo-doped ceria (CMO) anode using humidified (3%v/v water) syngas (50%v/v H2 – 50%v/v CO) as fuel. The model was validated preliminarily using polarization data (cell voltage vs current density, ΔEcell vs j, curves) generated experimentally at 800ºC using a SOFC supported on the electrolyte (a 20 mm diameter, 250 μm thickness yttria-stabilized zirconia, YSZ, disc) with a 14 mm diameter CMO-YSZ|CMO anode and a 14 mm diameter LSM (lanthanum strontium manganite)|LSM-YSZ cathode, that was connected to a Gamry Reference 3000 potentiostat/galvanostat/ZRA using platinum mesh and wires. Open circuit voltage was modeled using a Nernst equation corrected by H2 and CO electrooxidation reactions selectivity at the anode, which was determined through the resolution of relevant mass balances as a function of the SOFC thermodynamics and kinetics.

A Simplified Model for Reversible Solid Oxide Fuel Cells

A simplified reversible steady-state solid oxide cell model is formulated and solved analytically with only a few calibration parameters to match experimental performance data. A Butler-Volmer type model is used for the hydrogen electrode while a two-step single pathway reduced-order oxygen reduction reaction model is applied in the oxygen electrode. It is shown that this simple model is capable of accurately predicting the trends of V-I data produced experimentally at various gas concentrations in both fuel cell and electrolysis modes.

A family of high gain fuel cell front-end converters with low input current ripple for PEMFC power conditioning systems

Since the output voltage of the proton exchange membrane fuel cell (PEMFC) is relatively low and load-dependent, a high-performance fuel cell front-end converter is required to achieve boost and power regulation in PEMFC systems. In response, a novel family of high gain fuel cell front-end converters with low input current ripple is proposed. The proposed topologies can substantially improve the voltage gain through the expansion and combination of active switched-inductor networks and passive switched-capacitor units. The introduced interleaved parallel structure is convenient to limit the current ripple on the input side to prevent accelerated aging of fuel cells, which is another prominent advantage. Meanwhile, the converters can achieve the automatic current sharing between parallel inductors and the low voltage stress on active switches and diodes. In this paper, the fuel cell model and topology derivation of the high gain fuel cell front-end converters are first analyzed. Then, it further describes the operating mode and steady-state performance of converters under the inductor current continuous conduction mode. The comparison with other converters shows that this converter is suitable for connecting the PEMFC to the high voltage DC bus. Finally, a 200 W, 20/180 V converter prototype is implemented, and the simulation and experiment prove the theoretical correctness and validate the superior performances of the proposed converters.

A reduced‐dimension dynamic model of a proton‐exchange membrane fuel cell

The existing models of proton-exchange membrane fuel cells, such as computational fluid dynamics and lumped-parameter models, cannot provide a comprehensive description of mass-transport mechanisms without incurring a high computational load. This paper proposes a reduced-dimension dynamic model of fuel cells that considers main mass-transport mechanisms, including two-phase flow in the gas diffusion layer. Under the quasi-steady-state assumption, the distributions of liquid water and gas species in the through-plane direction are calculated through analytical expressions. Thus, the reduced-dimension fuel-cell model can obtain a similar output to a one-dimensional model without needing to solve partial differential equations. The reduced-dimension model was validated on steady state and transient experimental data. The computational load of the reduced-dimension model was only 1/60 that of a one-dimensional model. To simulate the transient behavior of the fuel-cell system, the reduced-dimension fuel-cell model was integrated with a comprehensive balance-of-plant model. The system model could execute long-time-scale transient simulations and evaluate the internal states of the fuel cell while minimizing the computing resources. Finally, the contradiction between the power response rate and oxygen starvation under the load-delay strategy was analyzed with the system model, and the delay duration was optimized. Results verify the potential of the reduced-dimension model in control-oriented applications. Novelty statement The existing models of proton-exchange membrane fuel cells, such as computational fluid dynamics and lumped-parameter models, cannot provide a comprehensive description of mass-transport mechanisms without incurring a high computational load. This work proposes a reduced-dimension dynamic model of fuel cells that considers main mass-transport mechanisms, including two-phase flow in the gas diffusion layer. Under the quasi-steady-state assumption, the distributions of liquid water and gas species in the through-plane direction are calculated through analytical expressions. Thus, the reduced-dimension fuel-cell model can obtain a similar output to a one-dimensional model without needing to solve partial differential equations. The computational load of the reduced-dimension model was only 1/60 that of a one-dimensional model.

Model identification of Solid Oxide Fuel Cell using hybrid Elman Neural Network/Quantum Pathfinder algorithm

In this research, a new efficient method is introduced for model assessment of Solid Oxide Fuel Cell (SOFC) model using a new hybrid Elman Neural Network (ENN). The main purpose of this research is to minimize the Mean Squared Error (MSE) between empirical data and modeling data of the fuel cell output voltage using the suggested hybrid ENN. The designed ENN is indeed a combination of this network with an improved metaheuristic, called Quantum Pathfinder (QPF) algorithm to give an optimal model. The proposed QPF-ENN model is then performed in a SOFC case study to show its efficiency. The results of the suggested method are validated by the reference voltage and also two other methods to show the higher minimum value of the Mean Squared Error (MSE) toward the others. Simulation results are analyzed the mean squared error value of the methods for 5000 samples, where, the voltage is limited between 320 V and 361 V. The results show that the mean square error for the QPF-Elman method, GWO-RHNN method, and PF-Elman method are 0.0014, 0.0017, and 0.0018, respectively. This indicates that the proposed QPF-Elman delivers the minimum value of the mean square error.

Development of a Typical Distribution Function of Relaxation Times Model for Polymer Electrolyte Membrane Fuel Cells and Quantifying the Resistance to Proton Conduction within the Catalyst Layer

In recent decades, polymer electrolyte membrane fuel cell (PEMFC) technologies have attracted research attention as promising candidates for next-generation energy conversion systems. This work deals with the effect of operating conditions and the construction of a typical model for PEMFCs, using electrochemical impedance spectroscopy (EIS) and distribution of relaxation times analysis. In operando EIS measurements were carried out on PEMFCs under different operating conditions. The measurements were analyzed using a genetic algorithm to obtain the distribution function of relaxation times (DFRT) models as analytical functions. The obtained model consists of four peak functions that fit the four main physical processes known to occur within the fuel cell during operation: proton conduction within the membrane, proton conduction within the catalyst layer (CL), oxygen reduction reaction’s charge transfer, and oxygen mass transfer within the CL and the gas diffusion layer. In addition, this method enabled examining each physical process’s response to operating conditions (such as temperature, humidity, and output current) and quantifying each process’s effective resistance. In particular, we were able to quantify the resistance to proton conduction within the CL, a process known to have a low contribution to the overall impedance, hence many times eclipsed by other processes. The resulting model can be further used in, for example, PEMFC degradation research, owing again to the fact that the model’s analytical form is stable while its parameters change as the cell degrades.

A mathematical model of two-stage Solid Oxide Fuel Cell, SOFC, stacks for dynamic simulation of Combined Heat and Power system fed by natural gas

Abstract Zero-dimensional two-stage SOFC stacks dynamic model was developed to investigate the effect of operating parameters on stacks performance. The model resolves spatially thermal and thermo-electrochemical behaviour for electrochemical reactions, Catalytic Partial Oxidation and Steam Reforming processes. Design variables and thermo-electrochemical properties were obtained from in-house-fabricated SOFCs carried out by project partners. The completed SOFCs based Combined Heat and Power, CHP, system model was validated by data 18 and numerical results obtained at steady-state mode showing its high-fidelity. A parametric study with respect to key operating parameters including changes in fuel utilization, lambda number and current density values was conducted. The global CHP system dynamic response, in term of the current/voltage delivered by two-stage SOFC stacks, under a fixed fuel utilization, has been determined resulting in greater variations in the voltage of a single cell in the first stack in comparison to the corresponding values in the second stack.

(Invited) Multi-Scale Analysis of Transport in Dry and Partially-Saturated Porous Media

Improvements in imaging techniques, such as micro- and nano-computer tomography (CT) and focus ion beam scanning electron microscopy (FIB-SEM), have enabled the reconstruction of complex porous media that can then be analyzed by computer simulation to estimate effective transport properties, e.g., ref. [1, 2]. Experimental setups have also been developed to measure dry and partially-saturated gas diffusivity and permeability of gas diffusion layers (GDLs) and catalyst layer (CLs), e.g., ref. [3, 4]. Based on the available literature, a comparison between micro-scale simulation results and experimental data must be performed to assess the accuracy of direct numerical simulation CT image analysis for dry and partially-saturated transport property estimation. In the later case, the validity of computational methods to predict water intrusion, such as full morphology/morphological image opening [1] and watershed segmentation [5], should also be assessed by comparing mercury intrusion experiments to numerical predictions, and by direct comparison of numerical results to CT images. Finally, these transport properties should be integrated into complete fuel cell models where volume-averaging techniques are used to properly estimate channel-porous media interactions. Such interactions however are seldom studied in literature.The proposed contribution aims at first studying the validity of two popular methods for numerical estimation of effective transport properties from three-dimensional reconstructed porous media, i.e., direct numerical simulation (DNS) and pore network modeling (PNM). Two fuel cell gas diffusion media and an electrolyzer porous transport layer are analyzed by CT and characterized by measuring mercury intrusion porosimetry (MIP), and dry permeability and diffusivity. A comparison of numerical and experimental results shows that DNS tools in OpenFCST [6] are capable of accurately predicting intrusion, and transport properties without using any fitting parameters. Accurate predictions are also achieved with the PNM implementation in OpenPNM [7] when the inscribed diameter method is used to estimate the pore size distribution, and the equivalent diameter is used to estimate pore transport properties. These tools open an avenue for computational design of porous materials.Effective transport properties must be integrated into volume-averaged fuel cell models where porous media-channel interactions are of paramount importance. These interactions however, as well as the method used for volume averaging fuel cell equations, are seldom studied in detail. Therefore, the second contribution of the talk aims at analyzing channel-porous media interactions by developing a compressible volume-averaged channel-porous media model in OpenFCST, and validating it with respect to permeability and diffusion bridge experiments in the literature. Comparison of numerical and experimental results show that, depending on the volume-averaging methodology used, experimentally obtained transport properties do not correspond to the input parameters needed in volume-averaged models. Finally, the numerical model is used to estimate flow by-pass in serpentine and inter-digitated channels, as well as compressibility effects [8].

Second-order slip effect on bio-convectional viscoelastic nanofluid flow through a stretching cylinder with swimming microorganisms and melting phenomenon

The uses of nanofluid in cooling technology is growing. The nanofluid is made up of metallic and nonmetallic particles that are distributed in a base fluid. This research provides a summary of fuel cell models, uses, and how they function. Researchers have made significant contributions in the following era due to the importance of bioconvection in nanotechnology and a variety of biological systems. The idea of the recent work is to evaluate the aspects of the Cattaneo–Christov (C–C) heat and mass flux model, the second-order boundary with melting phenomenon on the bioconvective flow of viscoelastic nanofluid across a cylinder. The nature of the activation energy, thermal conductivity is also taken into account. Appropriate similarity transformations are utilized to reframe the PDEs of the modeled system into a system of ODEs. The governing equations for the renovated system of ODEs are treated by a shooting function. Here bvp4c built-in function computational tool MATLAB is used. The two-dimensional flow has ceased application in several areas, such as polymer industry, material synthesis technology, nano-biopolymer computer graphics processing, industry, mechanical engineering, airplane structures, and scientific research, which is much more useful in nanotechnology. The results of emerging important flow-field parameters are investigated with the aid of graphs and numerical results.