CFD Simulation of Ethanol Steam Reforming System for Hydrogen Production

Transcription

1 chemengineering Article CFD Simulation of Ethanol Steam Reforming System for Hydrogen Production Alon Davidy ID Israel Military Industries Ltd., Ramat Hasharon 47100, Israel; Tel.: Received: 26 May 2018; Accepted: 30 July 2018; Published: 2 August 2018 Abstract: Hydrogen could be a promising source fuel, and is often considered as a clean energy carrier as it can be produced by. The use of presents several advantages, because it is a renewable feedstock, easy to transport, biodegradable, has low toxicity, contains high hydrogen content, and easy to store and handle. Reforming steam occurs at relatively lower temperatures, compared with or hydrocarbon fuels, and has been widely studied due to high yield provided for formation of hydrogen. A new computational fluid dynamics (CFD) simulation model of steam reforming (ESR) has been developed in this work. The reforming system model is composed from an burner and a catalytic bed reactor. The liquid is burned inside firebox, n radiative heat flux from burner is transferred to catalytic bed reactor for transforming steam mixture to hydrogen and carbon dioxide. The proposed computational model is composed of two phases Simulation of burner by using Fire Dynamics Simulator software (FDS) (version 5.0) and a multi-physics simulation of steam reforming process occurring inside reformer. COMSOL multi-physics software (version 4.3b) has been applied in this work. It solves simultaneously fluid flow, heat transfer, diffusion with chemical reaction kinetics equations, and structural analysis. It is shown that heat release rate produced by burner, can provide necessary heat flux required for maintaining reforming process. It has been found out that mass fractions of hydrogen and carbon dioxide mass fraction are increased along reformer axis. The hydrogen mass fraction increases with enhancing radiation heat flux. It was shown that Von Mises stresses increases with heat fluxes. Safety issues concerning structural integrity of steel jacket are also addressed. This work clearly shows that by using which has low temperature conversion, decrease in structural strength of steel tube is low. The numerical results clearly indicate that under normal conditions of reforming (The temperature of steel is about 600 C or 1112 F), rupture time of HK-40 steel alloy increases considerably. For this case rupture time is greater than 100,000 h (more than 11.4 years). Keywords: burner; steam reformer; catalytic bed reactor; hydrogen production; fuel cell; CFD; Fire Dynamic Simulation software (FDS); Large Eddy Simulation (LES); radiative heat flux; convective heat flux; Multi-physics Simulation; Darcy Flow Equation; chemical kinetics; arrhenius coefficients; diffusion equation; heat transfer; rmal expansion; structural analysis; steel tube; HK-40 alloy; ultimate tensile strength; rupture time 1. Introduction In recent decades, re has been a continuous effort to reduce global environmental pollution and fossil oil consumption [1]. According to Akande et al. [2] demand for hydrogen has increased recently due to progress in fuel cell technologies. Fuel cells are electrochemical devices described as continuously operating batteries and are considered as a clean source of electric ChemEngineering 2018, 2, 34; doi: /chemengineering

2 ChemEngineering 2018, 2, 34 2 of 24 energy, containing high energy efficiency, and its resulting emission is just water [3]. It can be produced from different kinds of renewable feedstocks, such as. The use of as a raw material presents several advantages because it is easy to transport, biodegradable, has low toxicity, contains high hydrogen content, and easy to store and handle [4]. Furrmore, is economically, environmentally and strategically attractive as an energy source. Ethanol can be a hydrogen source for countries that lack fossil fuel resources, but have significant agricultural economy. This is feasible, because virtually any biomass can now be converted into as a result of recent advances in biotechnology [5]. These attributes have made H 2 obtained from reforming a very good energy vector, especially in fuel cells applications. Hydrogen production from has advantages compared to or H 2 production techniques, including steam reforming of m and hydrocarbons. Unlike hydrocarbons, is easier to reform and is also free of sulfur, which is a catalyst poison in reforming of hydrocarbons [6]. Also, unlike m, which is produced from hydrocarbons and has a relatively high toxicity, is completely biomass-based and has low toxicity and as such it provides less risk to population [7]. The fact that m is derived from fossil fuel resources also renders it an unreliable energy source in long run. Conclusively, amongst various processes and primary fuels that have been proposed for hydrogen production in fuel cell applications, steam reforming of is very attractive. Ethanol steam reforming (ESR) proceeds at temperatures in range of C, which is significantly lower than those required for CH 4 or gasoline reforming. This is an important consideration for improved heat integration of fuel cell vehicles. The main objective of computational fluid dynamics (CFD) modeling in this work is to analyze structural integrity and performance of an industrial ESR system with considerable modeling accuracy that can help evaluate various modeling assumptions usually employed. Extensive work has been performed on mamatical modeling development of first-principles reformer models. With dramatic increase of computing power, CFD modeling has become an increasingly important platform for reformer modeling and design, combining physical and chemical models with detailed representation of reformer geometry. When compared with first-principles modeling, CFD is a modeling technique with powerful visualization and computational capabilities to deal with various geometry characteristics, transport equations and boundary conditions. A 3D CFD simulation pioneering study of ESR in microreactors with square channels has been carried out by Uriz et al. [8]. A phenomenological kinetic model based on simple power-law rate equations and considering following reactions dehydrogenation to acetaldehyde, acetaldehyde steam reforming to H 2 and CO 2, decomposition to CO, CH 4 and H 2, and water-gas shift describes satisfactorily ESR over a Co 3 O 4 -ZnO catalyst. The CFD computational study shows that high reforming temperatures (above 625 C) should be avoided. This is because decomposition of competes effectively with dehydrogenation of alcohol to acetaldehyde, which is key intermediate of ESR process, and results in a reduced hydrogen yield and an increased content of CO in reformate stream. Their work shows that micro reactors can help to overcome se difficulties by increasing surface area-to-volume ratio and catalyst loading. By using se micro reactors, operating temperature can be reduced while increasing selectivity and maintaining level of conversion [8]. Uriz et al. [9] showed that CFD is a very useful tool for advancing in development and optimization of se technologies. The interest of CFD for assisting in understanding of behavior of hydrogen technologies is also important. Neverless, re are also limitations regarding description of chemical transformations and physics of some complex phenomena such as in multi-physics systems. Lao et al. [10] developed a CFD model of an industrial scale steam methane reforming reactor (reforming tube) used to produce hydrogen. The CFD model of an industrial-scale reforming tube has

3 ChemEngineering 2018, 2, 34 3 of 24 been developed in ANSYS Fluent (version 15.0) with realistic geometry characteristics to simulate transport and chemical reaction phenomena with approximate representation of catalyst packing. In this work a CFD simulation study of ESR system has been performed. The proposed computational work is composed of two phases simulation of burner by using fire dynamics simulator (FDS) software and a multiphysics simulation of steam reforming process occurring inside reformer. COMSOL multi-physics software has been applied in this work. It solved simultaneously fluid flow, heat transfer, diffusion with chemical reaction kinetics equations and structural analysis. It is probably first time that FDS software has been applied in order to simulate combustion processes of burner inside gas heated heat exchange reformer (GHHR). The FDS software is described in detail in Sections 2.1 and 2.2. The multiphysics reformer model is described in Section 2.3. As far as I know, this work is first coupled CFD and structural analysis study on ESR system. The structural analysis of reformer steel tube is essential in order to verify that structural integrity of tube under operating conditions of reformer is maintained. Steel tube rupture and cracks may cause release of hydrogen gas to reformer facility. Hydrogen has wide flammability limits and very low ignition energy [11]. Therefore, hydrogen present safety concerns at limited ventilation conditions because of danger of explosive mixture formation that may cause severe damage [12 14]. Diéguez et al. [12] showed examples of application of CFD to safety issues such as hydrogen leakages, hydrogen flames, detonation and application of simulation results to evaluate possible physiological injuries. They performed a CFD for simulating Hydrogen leakage Mechanism of Steam Ethanol Reforming Process The main reactions that occur during ESR process on Ni catalyst are [15]: Ethanol steam reforming: C 2 H 5 OH + 3H 2 O 2CO 2 + 6H 2 Ethanol decomposition to methane: C 2 H 5 OH CO + H 2 + CH 4 Ethanol dehydration: Ethanol dehydrogenation: C 2 H 5 OH C 2 H 4 + H 2 O C 2 H 5 OH CH 3 CHO + H 2 Ethanol decomposition to acetone: 2C 2 H 5 OH CH 3 COCH 3 + CO + 3H 2 Water-gas shift reaction: CO + H 2 O CO 2 + H Ethanol Burner Steam Reformer The reforming system described in this work is composed from burner and a catalytic bed reactor. The liquid is burned inside firebox. The heat from flue gases is transferred to catalytic bed reactor ( oretical model of reformer is described in Section 2.3) for transforming steam mixture to hydrogen and carbon dioxide. The catalyst is made from Ni/Al 2 O 3. The schematic of system is described in [16]. Burner Heat Transfer The heat produced from burning from combustion products is transferred to catalytic bed walls in by three modes (see Figure 1):

4 ChemEngineering 2018, 2, 34 4 of 24 (1) Convection ChemEngineering 2018, 2, x FOR PEER REVIEW 4 of 24 (2) Radiation (3) (2) Conduction Radiation (3) Conduction Figure Figure Heat Heat transfer transfer mechanisms in in steam steam reformer reformer [17]. [17] Convection Convection Heat is transferred through fluids in motion and between a fluid and solid surface in relative Heat is transferred through fluids in motion and between a fluid and solid surface in relative motion. When motion is produced by forces or than gravity, term forced convection is motion. When motion is produced by forces or than gravity, term forced convection is used. In engines fluid motions are turbulent. Heat is transferred by forced convection between used. In in-cylinder engines gases fluidand motions cylinder are turbulent. head, valves, Heat cylinder is transferred walls, and bypiston forcedduring convection induction, between in-cylinder compression, gases expansion and and cylinder exhaust processes head, valves, [18]. cylinder walls, and piston during induction, compression, expansion and exhaust processes [18] Radiative Heat Transfer Radiative There are Heat two Transfer sources of radiative heat transfer within burner: The high temperature burned gases and soot particles in flames. In burner, most if fuel burns in There are two sources of radiative heat transfer within burner: The high temperature burned turbulent diffusion flame as fuel and air mix toger. The flame is highly luminous, and soot gasesparticles and are soot formed particles at an in intermediate step flames. in combustion In burner, process most [18]. if fuel burns in turbulent diffusion flame as fuel and air mix toger. The flame is highly luminous, and soot particles are Conduction Heat Transfer formed at an intermediate step in combustion process [18]. Heat is transferred by molecular motion, through solids and through fluids at rest, due to temperature Conductiongradient. Heat Transfer It is transferred by conduction through reformer walls [18]. Heat 2. Materials is transferred and Methods by molecular motion, through solids and through fluids at rest, due to temperature gradient. It is transferred by conduction through reformer walls [18] Fire Dynamic Simulation Modeling of Burner 2. Materials and Methods The FDS has been developed at Building and Fire Research Laboratory (BFRL) at 2.1. Fire National Dynamic Institutes Simulation of Standards Modeling and oftechnology Burner(NIST), e.g., McGrattan et al. [19,20]. This software calculates simultaneously temperature, density, pressure, velocity, and chemical composition The within FDS each hasnumerical been developed grid cell at at each Building discrete and time Fire step. Research It also calculates Laboratory (BFRL) temperature, heat National Institutes flux, and of Standards mass loss and rate of Technology enclosed (NIST), solid surfaces. e.g., McGrattan The latter etis al. used [19,20]. in This case software where calculates fire simultaneously heat release rate temperature, is unknown. The density, major components pressure, velocity, of this software and chemical are: composition within each numerical Hydrodynamic grid cell at each Model FDS discrete time code step. is formulated It also calculates based on CFD temperature, of fire-driven heat fluid flux, flow. and The mass loss rate FDS of numerical enclosed solution solid can surfaces. be carried The out using lattereir is used a Direct in Numerical case where Simulation fire heat (DNS) release method rate is or Large Eddy Simulation (LES). The latter is relatively low Reynolds numbers and is not severely unknown. The major components of this software are:

5 ChemEngineering 2018, 2, 34 5 of 24 Hydrodynamic Model FDS code is formulated based on CFD of fire-driven fluid flow. The FDS numerical solution can be carried out using eir a Direct Numerical Simulation (DNS) method or Large Eddy Simulation (LES). The latter is relatively low Reynolds numbers and is not severely limited in grid size and time step as DNS method. In addition to classical conservation equations considered in FDS, including mass species momentum and energy, rmodynamics-based state equation of a perfect gas is adopted along with chemical combustion reaction for a library of different fuel sources. Combustion Model For most applications, FDS uses a mixture fraction combustion model. The mixture fraction is a conserved scalar quantity that is defined as fraction of gas at a given point in flow field that originated as fuel. The model assumes that combustion is mixing controlled, and that reaction of fuel and oxygen is infinitely fast. The mass fractions of all of major reactants and products can be derived from mixture fraction by means of state relations, empirical expressions arrived at by a combination of simplified analysis and measurement [21]. Radiation Transport Radiative heat transfer is included in model via solution of radiation transport equation for a non-scattering gray gas. In a limited number of cases, a wide band model can be used in place of gray gas model. The radiation equation is solved using a technique similar to a finite volume method for convective transport, thus name given to it is Finite Volume Method (FVM) [19]. FDS also has a visual post-processing image simulation program named smoke-view Governing Equations of FDS Software This section introduces basic conservation equations for mass, momentum and energy for a Newtonian fluid. These are same equations that can be found in almost any textbook on fluid dynamics or CFD Mass and Species Transport Mass conservation can be expressed eir in terms of density, ρ [19]: ρ t + ρu = ṁ b (1) where ρ is density (kg/m 3 ), and u is velocity field (m/s). In terms of individual gaseous specie, Y α : t (ρy α) + ρy α u = ρd α Y α + ṁ α + ṁ b,α (2) D α is diffusion coefficient of α component of mixture (m 2 /s) Momentum Transport The momentum equation in conservative form is written [19]: t (ρu) + ρuu + p = ρg + f b + τ ij (3) where f b is force term (Pa/m). The stress tensor, τ ij (Pa), is defined [19]: ( τ ij = µ 2S ij 2 ) 3 δ ij( u) ; δ ij = { 1 i = j 0 i = j ; S ij = 1 2 ( u i + u ) j i, j = 1, 2, 3 (4) x j x i The term S ij is symmetric rate-of-strain tensor, written using conventional tensor notation. The symbol µ is dynamic viscosity of fluid. The overall computation can eir be treated as a DNS, in which dissipative terms are computed directly, or as a LES, in which large-scale

6 ChemEngineering 2018, 2, 34 6 of 24 eddies are computed directly and subgrid-scale dissipative processes are modeled. The numerical algorithm is designed so that LES becomes DNS as grid is refined. Most applications of FDS are LES. For example, in simulating flow of smoke through a large, multi-room enclosure, it is not possible to resolve combustion and transport processes directly. However, for small-scale combustion experiments, it is possible to compute transport and combustion processes directly LES The most distinguishing feature of any CFD model is its treatment of turbulence. Of three main techniques of simulating turbulence, FDS contains only LES and DNS. There is no Reynolds-averaged Navier-Stokes (RANS) capability in FDS. LES is a technique used to model dissipative processes (viscosity, rmal conductivity, material diffusivity) that occur at length scales smaller than those that are explicitly resolved on numerical grid. This means that parameters µ, k and D in equations above cannot be used directly in most practical simulations. They must be replaced by surrogate expressions that model ir impact on approximate form of governing equations. This section contains a simple explanation of how se terms are modeled in FDS. There is a small term in energy equation known as dissipation rate, ε (Pa/s) rate at which kinetic energy is converted to rmal energy by viscosity [19]: ( [ ) 2 ( ) 2 ( ) ε = τ ij u = µ 2S ij S ij 2 3 ( u)2) = µ 2( u x + 2 v y + 2 w 2+ z ( ) 2 ( ) 2 ( ) 2 ( ) ] (5) 2 v x + u y + w y + v z + u z + w x 2 u 3 x + v y + w z Following analysis of Smagorinsky, viscosity µ is modeled: µ LES = ρ(c s ) 2 (2S ij : S ij 2 3 ( u)2 ) 1 2 (6) where C s is an empirical constant and is a length on order of size of a grid cell. The bar above various quantities denotes that se are resolved values, meaning that y are computed from numerical solution sampled on a coarse grid (relative to DNS). The or diffusive parameters, rmal conductivity and material diffusivity, are related to turbulent viscosity by [16]: k LES = µ LESc p Pr t ; (ρd) t,les = µ LES Sc t (7) The turbulent Prandtl number Pr t and turbulent Schmidt number Sc t are assumed to be constant for a given scenario. The model for viscosity, µ LES, serves two roles: Firstly, it provides a stabilizing effect in numerical algorithm, damping out numerical instabilities as y arise in flow field, especially where vorticity is generated. Second, it has appropriate mamatical form to describe dissipation of kinetic energy from flow Energy Transport The energy conservation equation is written in terms of sensible enthalpy, h s (J/kg) [19]: t (ρh s) + (ρh s u) = Dp Dt +. q. q b.q + ε (8) The sensible enthalpy (J/kg) is a function of temperature [19]: h s = Y α h s,α (9) α

7 ChemEngineering 2018, 2, 34 7 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 7 of 24 where sensible heat of each component in mixture is calculated by: where sensible heat of each component in mixture is calculated by: T T ( s,α (T) = c p,α T ) h dt (10) T T dt s, c p, (10) T 0 where where q. is q HRR is per HRR unitper volume unit volume from a chemical from a chemical reaction reaction (W/m 3 ), (W/m q. 3 ), b is q energy transferred to evaporating liquid (W/m 3 ) and q. b is energy transferred to evaporating liquid (W/m represents 3 ) and q represents conductive and conductive radiative and heat radiative fluxes heat (W/m 2 ): fluxes (W/m 2 ):. q = k T h s,a ρd a Y a + q r (11) q=k T- hs,a a Da Y+q a r (11) Equation of State Equation of State The pressure is calculated by using ideal gas equation of state ( burning occurs at atmospheric The pressure which is calculated is much by less using than ideal critical gas pressure equation of state air): ( burning occurs at atmospheric pressure which is much less than critical pressure of air): p = ρrt (12) W (12) where p is pressure in (Pa), T is temperature in (K), R is universal gas constant and W is where p is pressure in (Pa), T is temperature in (K), R is universal gas constant and W molecular mass of gaseous mixture in (J/mol). is molecular mass of gaseous mixture in (J/mol) FDS Modelling of Ethanol Burner FDS Modelling of Ethanol Burner The geometry The geometry of of burner burner model model is is shown shown in in Figure Figure T0 a p= RT W Figure Figure The The geometry of burner. burner. At At bottom bottom of of burner, burner, is is injected and ignited. ignited. The The burning burning still in still air is air is controlled by buoyancy (see Figure 3) [22]. controlled by buoyancy (see Figure 3) [22].

8 ChemEngineering 2018, 2, 34 8 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 8 of 24 Figure 3. The physics of liquid fuel burning [22]. Figure 3. The physics of liquid fuel burning [22]. It was assumed that heat of combustion of is 26,780 (kj/kg) [23]. The rmal It was assumed that heat of combustion of is 26,780 (kj/kg) [23]. The rmal conductivity of liquid is 0.17 (W/(m K)). The specific heat of liquid is 2.45 conductivity of liquid is 0.17 (W/(m K)). The specific heat of liquid is (kj/(kg K)) and its density is 787 (kg/m 3 ) [24]. There are three reasons that lead to justify this 2.45 (kj/(kg K)) assumption: and its density is 787 (kg/m 3 ) [24]. There are three reasons that lead to justify this assumption: (1) The rmal diffusivity of is low ( ratio between rmal conductivity and (1) The heat rmal capacity diffusivity multiplied of by density). is low Therefore, ( ratio between heat front penetrates rmalwithin conductivity a short and heat distance capacity inside multiplied by pool. density). Therefore, heat front penetrates within a short (2) distance The radiative inside heat flux is pool. attenuated inside liquid phase. (3) The internal flow inside liquid can be neglected (natural convection). Therefore, (2) The radiative heat flux is attenuated inside liquid phase. convective heat transfer inside liquid pool can be neglected. (3) The internal flow inside liquid can be neglected (natural convection). Therefore, convective The FDS simulation is based on lower heating values of. This model is flexible. heat transfer inside liquid pool can be neglected. There is an option to increase heat release rate (HRR) by using fuel with higher heating value The (such FDS as gasoline simulation or diesel). is based on lower heating values of. This model is flexible. There is an option to increase heat release rate (HRR) by using fuel with higher heating value (such 2.3. Multiphysics Analysis of Reformer Model as gasoline or diesel). The second part deals with numerical analysis of reformer. Figure 4 shows geometry of 2.3. Multiphysics this system. Analysis of Reformer Model The second part deals with numerical analysis of reformer. Figure 4 shows geometry of this system.

9 ChemEngineering 2018, 2, 34 9 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 9 of 24 Steel Tube Catalytic bed H2O + C2H5OH Figure 4. Figure 3D plot 4. of 3D plot reformer. of reformer. The The reformer is made is made of catalyst of catalyst bed bed material material and steel and steel tube. tube. It has Itbeen has been assumed assumed that that radius radius of of reformer is is m. m. The height of reformer is is m. m. The The thickness thickness of of steel (HK-40 steel (HK-40 alloy) alloy) tube tube is 0.01 is 0.01 m (10 m (10 mm). mm). The The reformation chemical reactions occurin in a porous catalytic bed bed where where heat is supplied through burner to drive endormal reaction system. The heat is supplied through burner to drive endormal reaction system. The reactor is reactor is enclosed with steel tube. Ethanol and steam are mixed in stoichiometric amounts and enter enclosed with steel tube. Ethanol and steam are mixed in stoichiometric amounts and enter through through inlet of catalytic reactor. COMSOL multi-physics software (version 4.3b) has been inlet of catalytic reactor. COMSOL multi-physics software (version 4.3b) has been applied applied in this work. It solved simultaneously fluid flow, heat transfer, diffusion with chemical reaction in this kinetics work. equations It solvedand simultaneously structural analysis. fluid flow, heat transfer, diffusion with chemical reaction kinetics equations and structural analysis Model Kinetics Reformer Bed Model Kinetics Reformer Bed Inside reformer, steam and react to form hydrogen and carbon dioxide: Inside reformer, steam and react to form hydrogen and carbon dioxide: C2H5OH + 3H2O 2CO 2+ 6H2 (13) C The rate constant of ESR reaction 2 H is 5 OH + 3H temperature 2 O 2CO dependent according 2 + 6H 2 (13) to [8]: The rate constant of ESR reaction = exp isetemperature k A dependent according to [8]: RT ( g k = A exp E ) R g T where A (frequency factor) is (1/s) and E (activation energy) is 65.8 (kj/mol) [15]. where A (frequency factor) is Fluid Flow Reformer Bed 5 (1/s) and E (activation energy) is 65.8 (kj/mol) [15] The flow Fluidof Flow Reformer gaseous species through Bed reformer bed is described by Darcy s Law: The flow of gaseous species through reformer bed is described by Darcy s Law: p sr =0 (15) [ ( ρ κ )] η p sr = 0 (15) (14) (14)

10 ChemEngineering 2018, 2, of 24 Here, ρ denotes gas density (kg/m 3 ), η is viscosity (Pa s) and κ is permeability of porous medium (m 2 ) and p sr is pressure inside reformer bed (Pa). All or boundaries are impervious, corresponding to condition: k η p sr n = 0 (16) Energy Transport Reformer Bed The energy transport equation is used to describe average temperature distribution in porous bed: ( ) T sr ρcp + ( k sr T sr ) + ( ) ρc p u Tsr = Q (17) t The volumetric heat capacity of bed is given by: ( ρcp )t = ε ( ρc p ) f + (1 ε)( ρc p )s (18) In above equations, indices f and s denote fluid and solid phases, respectively, and ε is volume fraction of fluid phase. Furrmore, T sr is temperature (K) and k sr is rmal conductivity of reformer bed w/(m K). Q represents a rmal source (w/m 3 ), and u is fluid velocity field (m/s). Assuming that porous medium is homogeneous and isotropic, steady-state equation becomes: ( k sr T sr ) + ( ρc p ) u Tsr = Q (19) The volumetric heat source due to reaction is calculated: Q = H r r (20) where r represents reaction rate. The steam reformation of is endormic, with an enthalpy of reaction of H r = J/mol. Equation (19) also accounts for conductive heat transfer in steel tube. As no reactions occur in this domain, description reduces to: ( k steel T sr ) = 0 (21) where k steel is rmal conductivity of steel. The temperature of gas is 700 K at inlet. At outlet, it is assumed that convective heat transport is dominant: n ( k sr T sr ) = 0 (22) The rmal properties of reformer are presented at Table 1 [9]. Table 1. Thermal properties of reformer [10]. Material Property Value rho 3960 (kg/m 3 ) Cp 880 (J/(kg C)) k 33 (w/(m C))

11 ChemEngineering 2018, 2, of Mass Transport Reformer Bed The mass-balance equations for model are Maxwell-Stefan diffusion and convection equations at steady state: ( ρω i u ρω i n j = 1 ( D ij x j + ( ) ) p x j ω j Di T p ) T T = R i (23) Here ρ denotes density (kg/m 3 ), ω i is mass fraction of species i, x j is molar fraction of species j, D ij is ij component of multicomponent Fick diffusivity (m 2 /s), Di T denotes generalized rmal diffusion coefficient (kg/(m s)), T is temperature (K), and R i is reaction rate (kg/(m 3 s)) Calculation of Binary Diffusion Coefficients Reformer Bed The diffusion coefficients of components in mixture, D ij Chapman-Enskog ory [25]: T 3 ( 1Mi + 1Mj ) are obtained from D ij = pσ 2 ij Ω ij (24) In which σ ij and Ω ij are Lennard-Jones collision diameter and collision integral between one molecule of i and one molecule of j respectively. The collision diameter is obtained from σ ij = 1/2 ( ) σ i + σ j and Ωij is taken from [26]: Ω ij = τ 2 ij exp ( τ ij ) exp ( τ ij ) exp ( τ ij ) (25) In which τ ij = kt/ε ij is dimensionless temperature, where k is Boltzmann constant and ε ij = ε i ε j is maximum attractive energy between one molecule of i and one molecule of k. The values of σ i and ε i for substances used in this work are given in Table 2 [27]. Table 2. Properties of gaseous species [27]. Lennard-Jones Collision Diameter σ i (Angstroms) Ethanol H 2 O CH CO CO H Maximum Attractive Energy between Two molecules σ i /k B (K) Ethanol H 2 O CH CO CO H The diffusion coefficients as a function of temperature are shown in Figure 5.

12 ChemEngineering 2018, 2, x FOR PEER REVIEW 12 of 24 ChemEngineering 2018, 2, of 24 The diffusion coefficients as a function of temperature are shown in Figure 5. Figure 5. The binary diffusion coefficients of main species as a function of temperature. Figure 5. The binary diffusion coefficients of main species as a function of temperature. This figure clearly shows that spreading (diffusion) gaseous species inside reformer This figure clearly shows that spreading (diffusion) gaseous species inside reformer increases with temperature. increases with temperature Structural Analysis Reformer Bed and Steel Tube Structural Analysis Reformer Bed and Steel Tube It was assumed that tube is made of Steel HK-40. HK alloy, known as HK 40, is an austenitic It Fe-Cr-Ni was assumed alloy that that has been tube a standard is madeheat of Steel resistant HK-40. material. HK alloy, With known moderately as HK high 40, temperature is an austenitic Fe-Cr-Ni strength, alloyoxidation that hasresistance, been a standard alloy heat is used resistant in a wide material. variety of With industrial moderately applications high temperature such as: strength, Ammonia, oxidation m resistance, and hydrogen alloyreformers; is used inethylene a widepyrolysis variety of coils industrial and fittings; applications steam super such as: Ammonia, heater m tubes and fittings and hydrogen [28]. The reformers; rmo-physical ethylene and pyrolysis rmomechanical coils andproperties fittings; steam of steel super are heater tubeslisted and fittings in Table [28]. 3 [10,29]. The rmo-physical and rmomechanical properties of steel are listed in Table 3 [10,29]. Table 3. Thermo-physical and rmomechanical properties of steel HK-40 [10,27]. Table 3. Thermo-physical Material and rmomechanical Property Value properties of steel HK-40 [10,27]. E (Pa) Material Property nu Value 0.3 Erho (kg/m 10 9 (Pa) 3 ) nu alpha (1/ C) rho Cp (J/(kg C)) (kg/m 3 ) alpha k (w/(m C)) 10 6 (1/ C) Cp 502 (J/(kg C)) 3. Results k (w/(m C)) This section divided into two parts. In Section 3.1 rmal results of Fire Dynamics 3. Results Simulation (FDS) software are shown. In Section 3.2 COMSOL multi-physics results for reformer are presented. This section divided into two parts. In Section 3.1 rmal results of Fire Dynamics Simulation (FDS) 3.1. software Fire Dynamics are shown. Simulator In Software Section Results 3.2 COMSOL multi-physics results for reformer are presented. One advantage of FDS simulation is that it can provide much detailed information on 3.1. Fire Dynamics burner, Simulator including Software Results local and transient gas velocity, gas temperature, species One advantage of FDS simulation is that it can provide much detailed information on burner, including local and transient gas velocity, gas temperature, species concentration, solid wall temperature, fuel burning rate, radiative heat flux, convective heat flux and HRR. The temperature field at t = 77.5 s is shown in Figure 6.

13 ChemEngineering 2018, 2, FOR PEER REVIEW 13 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 13 of 24 ChemEngineering concentration, 2018, solid 2, 34 wall temperature, fuel burning rate, radiative heat flux, convective heat flux and 13 of 24 concentration, solid wall temperature, fuel burning rate, radiative heat flux, convective heat flux and HRR. The temperature field at 77.5 is shown in Figure 6. HRR. The temperature field at t = 77.5 s is shown in Figure 6. Figure Temperature field ( C) inside burner at at t 77.5 = 77.5 s. s. Figure 6. Temperature field ( C) inside burner at t = 77.5 s. The The maximal temperature at at t 77.5 approaches to to C. C. The The velocity field field of flue of gases flue gases is The maximal temperature at t = 77.5 s approaches to 815 C. The velocity field of flue gases is is shown shown in Figure in Figure shown in Figure 7. Figure 7. Velocity field (m/s) of flue gases at 77.5 s. Figure Figure Velocity field (m/s) of of flue flue gases gases at t at = t 77.5 = 77.5 s. s. Figure shows radiation heat flux emitted by burner. Figure Figure 8 shows 8 shows radiation heat heat flux emitted by burner.

14 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 14 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 14 of 24 Figure 8. Radiation heat flux produced by burner. Figure 8. Radiation heat flux produced by burner. Figure 8 shows that maximal radiation heat flux is 100,000 (W/m2). It should be noted that 8. Radiation heat fluxheat produced burner.2 ). It should be noted that Figure 8 shows that Figure maximal radiation flux by is 100,000 (W/m FDS simulation is based on lower heating values of. This model is flexible. There FDS is based onhrr by lower heating values of heating. This model is flexible. There is 2). It as is ansimulation option 8toshows increase using fuel with higher value (such gasoline or diesel). Figure that maximal radiation heat flux is 100,000 (W/m should be noted that an option to simulation increase HRR by using fuel with higherofheating (such asisgasoline orflux diesel). As see later, HHR canvalue provide necessary heatthere we FDSshall is based on produced lower by heating values burner,. This model flexible. As we shall see later, HHR produced by burner, can provide necessary heat required for maintaining reforming process. is an option to increase HRR by using fuel with higher heating value (such as gasoline or diesel). flux required forshall maintaining HHR reforming process. As we see later, produced by burner, can provide necessary heat flux 3.2. Multi-Physics Analysis of Operation of Ethanol Steam Reformer required for maintaining reforming process Multi-Physics Analysis of Operation of Ethanol Steam Reformer A parametric study has been performed in order to analyze influence of heat flux on 3.2. Multi-Physics Analysis of Operation of Ethanol Steam Reformer reformer performance andbeen its structural integrity. numerical for heat flux of flux 95,300 A parametric study has performed in orderthe to analyze results influence of heat on 2) are presented in Section The numerical results for heat flux of 200,000 (W/m2) are (W/m A parametric study has been performed in order to analyze influence of heat flux on reformer performance and its structural integrity. The numerical results for heat flux of 95,300 (W/m2 ) presented in Section reformer performance and The its structural Theheat numerical heat 2flux 95,300 in are presented in Section numericalintegrity. results for flux of results 200,000for (W/m ) areofpresented 2) are presented in Section The numerical results for heat flux of 200,000 (W/m2) are (W/m Section Multiphysics Results for Low Heat Flux Input presented in Section Figure 9 shows 3D field Input inside reformer Multiphysics Results fortemperature Low Heat Flux Multiphysics Results for Low Heat Flux Input Figure 9 shows 3D temperature field inside reformer. Figure 9 shows 3D temperature field inside reformer. Figure 9. 3D plot of reformer temperature field. Figure 9. 3D plot of reformer temperature field. Figure 9. 3D plot of reformer temperature field.

15 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 15 of 24 As ChemEngineering can be seen from Figure 9, temperature at bottom section of reformer is lower than As can be seen 2018, 2, from x FOR Figure PEER REVIEW 9, temperature at bottom section of reformer is lower 15 of than 24 temperature at upper side. The temperature of steel is much higher than temperature temperature at upper side. The temperature of steel is much higher than temperature of catalyst. As can This be seen is from because Figure of two 9, reasons: temperature Firstly, at bottom endormic section of reactions reformer is absorb lower than of catalyst. This is because of two reasons: Firstly, endormic reactions absorb heat, and heat, and secondly, temperature catalyst is upper secondly, catalyst is much much side. thicker thicker The temperature than than steel steel of tube. tube. steel Figure Figure is much shows shows higher than mass mass temperature fractions fractions of species (, CO 2 and H 2 axis for inlet temperature of 600 of of catalyst. This is because of two reasons: Firstly, endormic reactions absorb heat, and species (, C. CO2 secondly, catalyst and is much H2O) along thicker than reformer steel axis tube. for Figure inlet temperature 10 shows of mass 600 fractions C. of species (, CO2 and H2O) along reformer axis for inlet temperature of 600 C. Figure 10. Mass fractions of species (, CO2 Figure Figure 10. Mass 10. Mass fractions of of species (, and H2O) along reformer axis. CO2 2 and H2O) H 2 O) along along reformer axis. axis. The The mass The mass mass fractions fractions of of of and steam and steam decay decay along along reformer reformer axis. The axis. axis. The The conversion is 80.3%. conversion The is is 80.3%. 80.3%. The and The steam and decays steam at decays same at slope, same and slope, according and and according to Equation to to Equation (13) amounts (13) (13) of amounts of and of steam and are proportional steam are proportional to each or. to each Similar or. values Similar have values been have have reported been been in reported in in Reference [4]. [4]. From this figure it can be seen that HRR produced by by Reference [4]. From this figure it can be seen that HRR produced by burner, can provide burner, can can provide required heat flux for maintaining reforming process. Figure shows required heat flux for maintaining reforming process. Figure 11 shows mass fractions of mass mass fractions of of along reformer axis for inlet of 400 C, 500 C and along reformer axis for inlet temperatures of 400 temperatures C, 500 of 400 C and 600 C, 500 C and C C. C. Figure 11. Mass fractions of along reformer axis for various inlet temperatures. Figure 11. Mass fractions of along reformer axis for various inlet temperatures. Figure 11. Mass fractions of along reformer axis for various inlet temperatures.

16 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 16 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 16 of 24 From this figure it can be seen that for inlet temperature of 500 From this figure it can be seen that for inlet temperature of 500 C, conversion is C, conversion is 70.0%. 70.0%. For inlet temperature For inlet temperature of 400 of 400 C, conversion is 43.8%. Thus, conversion From this figure it can C, be seen that conversion for inlet temperature is 43.8%. of Thus, 500 C, conversion increases is increases with inlet temperature. Figure 12 shows mass fractions of hydrogen along with 70.0%. inlet For temperature. inlet temperature Figure of C, shows mass conversion fractions is of 43.8%. hydrogen Thus, along reformer conversion axis. reformer axis. increases with inlet temperature. Figure 12 shows mass fractions of hydrogen along reformer axis. Figure 12. Mass fractions of H2 along reformer axis. Figure 12. Mass fractions of H 2 along reformer axis. Figure 12. Mass fractions of H2 along reformer axis. This figure clearly shows a considerable increasing of hydrogen mass fraction along This reformer figure axis. clearly The increase shows a in considerable Hydrogen mass increasing fraction of is hydrogen 89.4%. The mass sum fraction of hydrogen, along, reformer axis. carbon The This increase figure dioxide, inand Hydrogen clearly shows steam mass mass a fraction fraction considerable at is 89.4%. increasing reformer The output sum of hydrogen is of1 hydrogen, mass as expected, fraction according carbon along mass dioxide, reformer axis. The increase in Hydrogen mass fraction is 89.4%. The sum of hydrogen,, and steam conservation mass fraction law. The at 3D Von-Mises reformerstress output distribution 1 as expected of reformer according is shown in Figure mass conservation 13. law. carbon dioxide, and steam mass fraction at reformer output is 1 as expected according mass The 3D Von-Mises stress distribution of reformer is shown in Figure 13. conservation law. The 3D Von-Mises stress distribution of reformer is shown in Figure 13. Figure 13. 3D plot of reformer Von-Mises stress field. Figure 13. 3D plot of reformer Von-Mises stress field. As expected, Figure maximal 13. stress 3D plot is located of reformer at reformer Von-Mises head stress corner. field. The Von-Mises rmal stresses which is developed inside steel are much higher than Von-Mises stresses which are As expected, maximal stress is located at reformer head corner. The Von-Mises rmal developed inside catalyst material. This is because temperatures inside catalyst material As stresses expected, which is developed maximalinside stress is located steel are at much reformer higher than head Von-Mises corner. The stresses Von-Mises which rmal are stresses developed which inside is developed catalyst inside material. steel This are is because much higher temperatures than Von-Mises inside catalyst stresses material which are developed inside catalyst material. This is because temperatures inside catalyst material are much lower than temperature in steel tube (Since reforming reaction is endormic, it

17 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 17 of 24 absorbs are more much heat lower and than cools temperature of reformer in material). steel tube (Since According reforming to this figure, reaction is maximal endormic, stress in ChemEngineering 2018, 2, x FOR PEER REVIEW 17 of 24 steel it absorbs tube reached more heat toand maximal cools of value reformer of 1.3 GPa. material). According to this figure, maximal stress in steel tube reached to maximal value of 1.3 GPa. are much lower than temperature in steel tube (Since reforming reaction is endormic, it Multiphysics absorbs more heat Results and for cools High of Heat reformer Flux material). Input According to this figure, maximal stress Multiphysics Results for High Heat Flux Input The in numerical steel tube reached results to for maximal heat flux value of of 200, GPa. (W/m 2 ) are presented in this section. Figure 14 The numerical results for heat flux of 200,000 (W/m shows 3D temperature field inside reformer. 2 ) are presented in this section. Figure shows Multiphysics 3D temperature Results field for High inside Heat Flux reformer. Input The numerical results for heat flux of 200,000 (W/m 2 ) are presented in this section. Figure 14 shows 3D temperature field inside reformer. Figure 14. 3D plot of reformer temperature field. Figure 14. 3D plot of reformer temperature field. The maximal temperature obtained in steel jacket for case of 200,000 (W/m 2 ) is about 652 Figure 14. 3D plot of reformer temperature field. The C. Figure maximal 15 shows temperature mass fractions obtainedof in species steel(, jacket for CO2 and case H2O) ofalong 200,000 reformer (W/m 2 ) axis. about 652 C. Figure The maximal 15 shows temperature mass obtained fractions in steel of jacket species for (, case of 200,000 CO 2 (W/m and 2 ) His 2 about O) along 652 reformer C. Figure axis. 15 shows mass fractions of species (, CO2 and H2O) along reformer axis. Figure 15. Mass fractions of species (, CO2 and H2O) along reformer axis. It can be seen from Figures 10 and 15 that mass fractions of and steam decay with Figure 15. Mass fractions of species (, CO2 and H2O) along reformer axis. increasing Figure heat 15. flux. MassThe fractions ofconversion species is (, about 85.4%. CO 2 and Figure H 2 O) 16 along shows reformer mass fractions axis. of hydrogen along reformer axis. It can be seen from Figures 10 and 15 that mass fractions of and steam decay with It increasing can be seen heat from flux. The Figures 10 conversion and 15 that is about mass 85.4%. fractions Figure of 16 shows and mass steam fractions decay of with increasing hydrogen heat along flux. The reformer axis. conversion is about 85.4%. Figure 16 shows mass fractions of hydrogen along reformer axis.

18 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 18 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 18 of 24 Figure 16. Mass fractions of H2 along reformer axis. Figure 16. Mass fractions of H 2 along reformer axis. Figure 16. Mass fractions of H2 along reformer axis. Figure 16 indicates that increase in hydrogen mass fraction is 89.9%. The hydrogen mass Figure fraction Figure 16 indicates is increased. 16 indicates that Figure that increase in hydrogen mass fraction is 89.9%. The hydrogen mass 17 shows increase in temperature hydrogen distribution mass fraction along is 89.9%. The axis hydrogen of reformer mass fraction fraction is increased. Figure 17 shows axis of reformer for for two is increased. cases. Figure 17 shows temperature distribution along z axis of reformer two for cases. two cases. Figure 17. Temperature distribution along z axis of reformer. Figure 17. Temperature distribution along z axis of reformer. Figure 17. Temperature distribution along z axis of reformer. It can be seen from Figure 17 that temperature increases with increasing heat flux. As a result It of can that be seen hydrogen from Figure mass 17 fraction that increases temperature ( reforming increases with rate increases). increasing The heat 3D Von-Mises flux. As a It can be seen from Figure 17 that temperature increases with increasing heat flux. As a result stress distribution of that hydrogen of reformer mass is shown fraction in increases Figure 18. ( reforming rate increases). The 3D Von-Mises result of that hydrogen mass fraction increases ( reforming rate increases). The 3D Von-Mises stress distribution of reformer is shown in Figure 18. stress distribution of reformer is shown in Figure 18.

19 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 19 of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 19 of 24 Figure 18. 3D plot of reformer Von-Mises stress field. Figure Figure D 3D plot plot of of reformer Von-Mises Von-Mises stress stress field. field. Figure 19 shows Von-Mises distribution along z axis of steel tube for two cases. Figure Figure 19 shows 19 shows Von-Mises Von-Mises distribution along z axis axisof of steel steel tube tube for for two two cases. cases. Figure 19. Von-Mises distribution along z axis of steel tube. Figure 19. Von-Mises distribution along z axis of steel tube. Figure 19. Von-Mises distribution along z axis of steel tube. Figure 19 indicates that Von-Mises stresses increases with heat flux. The effect of increasing heat Figure fluxes 19 indicates increases that temperature Von-Mises stresses inside increases steel tube with and enhances heat flux. The rmal effect of stresses. increasing Figure 19 indicates that Von-Mises stresses increases with heat flux. The effect of increasing The rmal heat fluxes stresses increases which are developed temperature inside inside steel steel tube tube are and much enhances higher than rmal those stresses. which were The heat fluxes increases temperature inside steel tube and enhances rmal stresses. rmal obtained stresses in which previous are developed section. The inside increase steel of tube heat are much flux enhances higher than a those little which were The rmal stresses which are developed inside steel tube are much higher than those which obtained conversion, in but also previous increases section. rmal The increase stresses of developed heat inside flux enhances steel tube. a little This effect can wereconversion, obtained inbut also previous increases section. rmal Thestresses increase developed of heat inside flux enhances steel tube. athis little effect can conversion, but also increases rmal stresses developed inside steel tube. This effect can cause to mechanical failure in steel tube. In order to maintain structural integrity of tube, HK-40 alloy has been applied in this work. HK alloy, known as HK 40, is an austenitic Fe-Cr-Ni alloy that

20 ChemEngineering 2018, 2, x FOR PEER REVIEW 20 of 24 ChemEngineering 2018, 2, of 24 cause to mechanical failure in steel tube. In order to maintain structural integrity of tube, HK-40 alloy has been applied in this work. HK alloy, known as HK 40, is an austenitic Fe-Cr-Ni alloy has that been has abeen standard a standard heat resistant heat resistant material material with moderately with moderately high temperature high temperature strength, and strength, oxidation and resistance. oxidation resistance. Figure 20 shows Figure 20 effect shows of temperature effect of increasing temperature on increasing tensile ultimate on tensile strength ultimate of HK 40 strength alloy and of HK stainless alloy and steels 310 [30]. stainless steels [30]. According to to Figure 20, 20, maximal stress stress in in steel steel tube tube reached reached to maximal to maximal value value of 482of MPa 482 (70 MPa ksi). (70 From ksi). Figures From Figures 19 and19 20and it can 20 be it can seenbe that seen that rmal rmal stresses stresses developed developed for low heat for low fluxheat are much flux are lower much than lower than ultimate ultimate tensile strength tensile strength of HK-40 of (According HK-40 (According to Figure to Figure 20, 20, Von Mises Von stresses Mises stresses developed developed in middle in middle section section of tube of aretube lessare than less 450 than MPa). 450 MPa). From Figure 20, it it can be also seen that decrease in ultimate tensile strength is less than 10% (The temperature of of steel is is about C C or or F). F). Since Since steam steam reforming occurs occurs at relatively relatively lower lower temperatures temperatures compared compared with or with hydrocarbon or hydrocarbon fuels, fuels, decrease indecrease strength in of strength Steel tube of is low. Steel Therefore, tube is low. Therefore, structural integrity structural of integrity HK-40 steel of tubehk-40 is kept. steel Figure tube 21is shows kept. Figure effect 21 of shows temperature effect stress of temperature rupture of HK stress 40-2 rupture steel alloy of HK [30] steel alloy [30]. Figure clearly clearly indicates indicates that under that under normal normal conditions conditions of of reforming ( reforming temperature ( of temperature steel tube of is about steel tube 600 is C about or F), C or rupture 1112 F), time rupture increases time considerably. increases considerably. For this case For rupture this case time rupture is greater time thanis 100,000 greater h than (more 100,000 than h 11.4 (more years). than 11.4 years). Figure 20. The effects of temperature on ultimate tensile strength of HK 40 and 310 steels [28]. Figure 20. The effects of temperature on ultimate tensile strength of HK 40 and 310 steels [28].

21 ChemEngineering 2018, 2, of 24 ChemEngineering 2018, 2, x FOR PEER REVIEW 21 of 24 Figure 21. The effects of on rupture time of HK 40-2 alloy [30]. Figure 21. The effects of temperature on rupture time of HK 40-2 alloy [30]. 4. Discussion 4. Discussion Hydrogen could be a promising fuel, and if often considered as a clean energy carrier as it only Hydrogen could be a promising fuel, and if often considered as a clean energy carrier as it only emits water during combustion. It can be produced from different kinds of renewable feedstocks, emits such water as. during combustion. The use of It can as be raw produced material from presents different several kinds advantages of renewable because feedstocks, it is a suchrenewable as. feedstock, The use easy of to transport, as raw biodegradable, material presents has low toxicity, several contains advantages high because hydrogen it is a renewable content, feedstock, and easy easy to store transport, and handle. biodegradable, Ethanol steam has low reformation toxicity, contains occurs at high relatively hydrogen lower content, and easy temperatures to storecompared and handle. with Ethanol or hydrocarbon steam reformation fuels and has occurs been widely at relatively studied lower due to temperatures high compared yield provided with or for hydrocarbon formation fuels of hydrogen. and hasin been this reformation widely studied reaction, duewater to and high yield react provided for over formation a catalyst of bed hydrogen. to produce Ina this mixture reformation of hydrogen reaction, rich gas. water A new andtool has been react developed over a catalyst in bed to this produce work in a order mixture to of analyze hydrogen reformer rich gas. operation. A new tool The has proposed been developed computational in this work work is in composed of two phases simulation of burner by using FDS software and multiphysics order to analyze reformer operation. The proposed computational work is composed of two simulation of steam reforming process occurring inside reformer. This software calculates phases simulation of burner by using FDS software and multiphysics simulation of steam temperature, density, pressure, velocity, and chemical composition within each numerical grid cell reforming at each process discrete occurring time step. It inside computes reformer. temperature, This heat software flux, and calculates mass loss rate. temperature, There are three density, pressure, major velocity, components andof chemical model: composition Hydrodynamic, within combustion, each numerical and radiation grid cell models. at each FDS discrete code time step. formulated It computes based on temperature, CFD of fire-driven heat flux, fluid and flow. mass The loss FDS rate. numerical Theresolution are three can major be carried components out of using model: eir Hydrodynamic, a DNS method combustion, LES. FDS uses anda radiation mixture fraction models. combustion FDS codemodel. is formulated The mixture based on CFDfraction of fire-driven is a conserved fluid flow. scalar The quantity FDS that numerical is defined solution as fraction can be of carried gas at out a given using point eir in a DNS method flow LES. field FDS that originated uses a mixture as fuel. fraction The model combustion assumes that model. combustion The mixture is mixing fraction controlled, is and a conserved that scalar quantity reaction that of fuel is defined and oxygen as is infinitely fraction fast. of gas Radiative at a given heat transfer point in is included flow field in that model originated via solution of radiation transport equation for a non-scattering gray gas. The radiation equation as fuel. The model assumes that combustion is mixing controlled, and that reaction of fuel and is solved using a technique similar to a finite volume method for convective transport, thus name oxygen is infinitely fast. Radiative heat transfer is included in model via solution of given to it is FVM. One advantage of FDS simulation is that it can provide much detailed radiation information transport on equation fire, including for a non-scattering local and gray transient gas. gas The velocity, radiation gas equation temperature, is solved species using a technique concentration, similar solid to awall finite temperature, volume method composite for convective burning rate, transport, radiation heat thustransfer, name convection given to it is FVM. heat transfer One advantage and HRR. of It has FDSbeen simulation found out is that it can maximal provide temperature much detailed at t = 77.5 information s approaches on fire, including to 815 C. The magnitude local and transient of radiation gas velocity, heat flux gas is 95,300 temperature, (w/m 2 ). species concentration, solid wall temperature, The composite second part burning deals with rate, numerical radiationanalysis heat transfer, of convection reformer. The heatreformation transfer andchemical HRR. It has beenreactions found out occur thatin a porous maximal catalytic temperature bed where at t = 77.5 heat s is approaches supplied through to 815 C. Ethanol The magnitude burner to of radiation drive heat endormal flux is 95,300 reaction (w/m 2 ). system. The reactor is enclosed with a HK-40 alloy steel tube. Ethanol and steam are mixed in stoichiometric amounts and enter through inlet of catalytic The second part deals with numerical analysis of reformer. The reformation chemical reactions reactor. The COMSOL multi-physics software has been applied in this work. It solved occur in a porous catalytic bed where heat is supplied through Ethanol burner to drive simultaneously fluid flow, Heat transfer, diffusion with chemical reaction kinetics equations and endormal reaction system. The reactor is enclosed with a HK-40 alloy steel tube. Ethanol and steam are mixed in stoichiometric amounts and enter through inlet of catalytic reactor. The COMSOL multi-physics software has been applied in this work. It solved simultaneously

22 ChemEngineering 2018, 2, of 24 fluid flow, Heat transfer, diffusion with chemical reaction kinetics equations and structural mechanics. The diffusion equations values are obtained from Chapman-Enskog ory. As far as I know, this work is first CFD structural simulation study of ESR system. It is probably first time that FDS software has been applied to simulate burner. A parametric study has been performed in order to analyze influence of heat flux on reformer performance and its structural integrity. The numerical results were obtained for heat fluxes of 95,300 (W/m 2 ) and 200,000 (W/m 2 ). It is shown that HRR produced by burner, can provide necessary heat flux required for maintaining reforming process. It has been found out that mass fractions of and steam decays along reformer axis. The hydrogen and carbon dioxide mass fraction are increased along reformer axis. The hydrogen mass fraction increases with enhancing radiation heat flux. For first case (heat flux magnitude of 95,300 (W/m 2 )) it was found out that conversion is 80.3%. The and steam are decaying at same rate. Similar values have been reported in literature. A sensitivity test has been carried out in order to analyze influence of inlet temperature on conversion. The results show that for inlet temperature of 500 C, conversion is 70.0%. For inlet temperature of 400 C, conversion is 43.8%. Therefore, conversion increases with inlet temperature. There is a considerable increasing of Hydrogen mass fraction along reformer axis. The increase in hydrogen mass fraction is 89.4%. The sum of hydrogen,, carbon dioxide and steam mass fraction at reformer output is 1, as expected according mass conservation law. Similar physical behavior has been observed in second case. The conversion is about 85.4%. The increase in hydrogen mass fraction along reformer is 89.4%. The rmal stresses which are developed inside steel tube are higher for case of heat flux of 200,000 (W/m 2 ). The increase of heat flux enhances a little conversion, but also increases rmal stresses of steel tube. This effect can cause to mechanical failure in steel tube. In order to maintain structural integrity of tube, HK-40 alloy has been applied in this work. HK alloy, known as HK 40, is an austenitic Fe-Cr-Ni alloy that has been a standard heat resistant material with moderately high temperature strength, and oxidation resistance. This alloy is used in a wide variety of industrial applications such as: Ammonia, m, and hydrogen reformers; ethylene pyrolysis coils and fittings; and steam super heater tubes and fittings. It has been found out that by increasing heat flux of reformer, decrease in tensile yield strength of HK-40 alloy is less than 10% ( temperature of steel is about 600 C or 1112 F). The effect of increasing heat fluxes increases temperature inside steel tube and enhances rmal stresses (produced by rmal expansion). Since steam reforming occurs at relatively lower temperatures compared with or hydrocarbon fuels, decrease in strength of steel tube is low. Thus, structural integrity of HK-40 steel tube is kept. The numerical results for clearly indicates that under normal conditions of reforming ( temperature of steel tube is about 600 C or 1112 F), rupture time increases considerably. For this case rupture time is greater than 100,000 h (more than 11.4 years). The described algorithm described in this work may be applied or reformer system (diesel, m, or methane). 5. Conclusions A new tool has been developed in this work in order to analyze burner and steam reformer operation. This model may be implemented for simulating or reforming systems (such as m, and diesel). Future work will focus on performing coupled heat transfer, chemical reactions, and creep analyses on reformer. Funding: This research received no external funding. Conflicts of Interest: The author declares no conflict of interest. No funding sponsors had any role in numerical analyses, or interpretation of data; in writing of manuscript, and in decision to publish results.

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