Detailed One-dimensional Model Research Articles

Modeling the structure of the dayside Venusian ionosphere: Impacts of protonation and Coulomb interaction

The CO$_2$-dominated thick atmosphere of Venus coexists with an ionosphere that is mainly formed, on the dayside, via the ionization of atmospheric neutrals by solar extreme ultraviolet and soft X-ray photons. Despite extensive modeling efforts that have reproduced the electron distribution reasonably well, we note two main shortcomings with respect to prior studies. The effects of protonation and Coulomb interaction are crucial to unveiling the structure and composition of the Venusian ionosphere. We evaluate the role of protonated species on the structure of the dayside Venusian ionosphere for the first time. We also evaluate the role of ion-ion Coulomb collisions, which are neglected in many existing models. Focusing on the solar minimum condition for which the effect of protonation is expected to be more prominent, we constructed a detailed one-dimensional photochemical model for the dayside Venusian ionosphere, incorporating more than 50 ion and neutral species (of which 17 are protonated species), along with the most thorough chemical network to date. We included both ion-neutral and ion-ion Coulomb collisions. Photoelectron impact processes were implemented with a two-stream kinetic model. Our model reproduces the observed electron distribution reasonably well. The model indicates that protonation tends to diverge the ionization flow into more channels via a series of proton transfer reactions along the direction of low to high proton affinities for parent neutrals. In addition, the distribution of O$_2^+$ is enhanced by protonation by a factor of nearly 2 at high altitudes, where it is efficiently produced via the reaction between O and OH$^+$. We find that Coulomb collisions influence the topside Venusian ionosphere not only directly by suppressing ion diffusion, but also indirectly by modifying ion chemistry. Two ion groups can be distinguished in terms of the effects of Coulomb collisions: one group preferentially produced at high altitudes and accumulated in the topside ionosphere, which is to be compared with another group that is preferentially produced at low altitudes and, instead, depleted in the topside ionosphere. Both protonation and Coulomb collisions have appreciable impacts on the topside Venusian ionosphere, which account for many of the significant differences in the model ion distribution between this study and early calculations.

Multi-scale modelling of a fluidized bed biomass gasifier of industrial size (1 MW) using a detailed particle model coupled to CFD: Proof of feasibility and advantages over simplified approaches

Fluidized bed biomass gasification is a complex process whereby gas source terms are released by reactions at the particle level during the movement of fuel particles throughout the reactor. The current study presents for the first time the application of a multi-scale modelling approach for a fluidized bed biomass gasifier of industrial size, coupling a detailed one-dimensional particle model based on the progressive conversion model (PCM) with a commercial CFD software. Results of particle movement and gas source terms are compared with results of an additional simulation employing the simplified uniform conversion model (UCM) which is commonly used in literature. Validation at the particle level showed that the UCM leads to a massive underprediction of the time needed for pyrolysis whereas the PCM is in good agreement with experimental data. This heavily influences the gas sources released during pyrolysis of the biomass particles in the coupled reactor simulations. Volatiles are much more concentrated to the close proximity of the fuel feed when using the UCM whereas the PCM leads to a more homogeneous distribution over the reactor cross-section. The calculation time analysis of the coupled simulations showed that despite the increased complexity, the PCM shows only an increase of 20% in calculation time when compared to the UCM, whereas it is much better suited for these conditions. The coupled multi-scale simulations using the PCM showed the numerical feasibility of the modelling approach for 1,200,000 bed parcels and about 80,000 reacting fuel parcels and furthermore highlighted the importance of a comprehensive description of the particle level.

Practical Mathematical Model for the Evaluation of Main Parameters in Polymer Flooding: Rheology, Adsorption, Permeability Reduction, and Effective Salinity.

Polymer flooding is one of the most used chemical enhanced oil recovery (CEOR) technologies worldwide. Because of its commercial success at the field scale, there has been an increasing interest to expand its applicability to more unfavorable mobility ratio conditions, such as more viscous oil. Therefore, an important requirement of success is to find a set of design parameters that balance material requirements and petroleum recovery benefits in a cost-effective manner. Then, prediction of oil recovery turns out to handle more detailed information and time-consuming field reservoir simulation. Thus, for an effective enhanced oil recovery project management, a quick and feasible tool is needed to identify projects for polymer flooding applications, without giving up key physical and chemical phenomena related to the recovery process and avoiding activities or projects that have no hope of achieving adequate profitability. A detailed one-dimensional mathematical model for multiphase compositional polymer flooding is presented. The mathematical formulation is based on fractional flow theory, and as a function of fluid saturation and chemical compositions, it considers phenomena such as rheology behavior (shear thinning and shear thickening), salinity variations, permeability reduction, and polymer adsorption. Moreover, by setting proper boundary and initial conditions, the formulation can model different polymer injection strategies such as slug or continuous injection. A numerical model based on finite-difference formulation with a fully implicit scheme was derived to solve the system of nonlinear equations. The validation of the numerical algorithm is verified through analytical solutions, coreflood laboratory experiments, and a CMG-STARS numerical model for waterflooding and polymer flooding. In this work, key aspects to be considered for optimum strategies that would help increase polymer flooding effectiveness are also investigated. For that purpose, the simulation tool developed is used to analyze the effects of polymer and salinity concentrations, the dependence of apparent aqueous viscosity on the shear rate, permeability reduction, reversible–irreversible polymer adsorption, polymer injection strategies on petroleum recovery, and the flow dynamics along porous media. The practical tool and analysis help connect math with physics, facilitating the upscaling from laboratory observations to field application with a better-fitted numerical simulation model, that contributes to determine favorable scenarios, and thus, it could assist engineers to understand how key parameters affect oil recovery without performing time-consuming CEOR simulations.

Toward a digital twin of a mid-speed marine engine: From detailed 1D engine model to real-time implementation on a target platform

System complexity is challenging for development of marine mid-speed engines when striving to meet increasingly stringent emission targets. Control-oriented modeling offers a solution, cutting calibration time and enabling robust control strategies. Simultaneously, real-time, physics-based engine models (digital twins) are emerging as they offer better predictive capability and scalability than typical mean-value, data-driven approaches. This study explored development of a control-oriented digital twin of a Wärtsilä 4L20 marine engine. Starting from a detailed one-dimensional model (GT-Suite), it explored reduction strategies toward a fast-running engine model (FRM), balancing the calculation speed and accuracy trade-off. Finally, the FRM was tested for real-time implementation on a target machine. Comprehensive experimental data from the 4L20 platform in the VEBIC Engine Laboratory provided the baseline for model calibration. Model calibration and validation covered four representative operating points and involved correlation of crank-angle, resolved in-cylinder pressures, thermal state at several locations of the engine air-path and relevant performance indicators. The results shed new light on the feasibility of digital twins in the marine engine domain. The obtained FRM was three times faster than real-time, while the accuracy loss was comfortably within the 5% tolerance levels for the governing outputs, including crank angle resolved in-cylinder pressure. The grid-resolved simulation was obtained with four times fewer flow components and internal discretization length of 100% and 150% of the cylinder bore for intake and exhaust components respectively. The balance between predictivity, accuracy and real-time surplus, was ultimately more favorable than in state of the art automotive applications and enables exploring further coupling with semi-predictive emission sub-models. The real-time capable FRM is considered applicable in hardware-in-the-loop simulation, and this application is scheduled in a follow-up project.

Triple oxygen isotope constraints on atmospheric O2 and biological productivity during the mid-Proterozoic

Reconstructing the history of biological productivity and atmospheric oxygen partial pressure (pO2) is a fundamental goal of geobiology. Recently, the mass-independent fractionation of oxygen isotopes (O-MIF) has been used as a tool for estimating pO2 and productivity during the Proterozoic. O-MIF, reported as Δ'17O, is produced during the formation of ozone and destroyed by isotopic exchange with water by biological and chemical processes. Atmospheric O-MIF can be preserved in the geologic record when pyrite (FeS2) is oxidized during weathering, and the sulfur is redeposited as sulfate. Here, sedimentary sulfates from the ∼1.4-Ga Sibley Formation are reanalyzed using a detailed one-dimensional photochemical model that includes physical constraints on air-sea gas exchange. Previous analyses of these data concluded that pO2 at that time was <1% PAL (times the present atmospheric level). Our model shows that the upper limit on pO2 is essentially unconstrained by these data. Indeed, pO2 levels below 0.8% PAL are possible only if atmospheric methane was more abundant than today (so that pCO2 could have been lower) or if the Sibley O-MIF data were diluted by reprocessing before the sulfates were deposited. Our model also shows that, contrary to previous assertions, marine productivity cannot be reliably constrained by the O-MIF data because the exchange of molecular oxygen (O2) between the atmosphere and surface ocean is controlled more by air-sea gas transfer rates than by biological productivity. Improved estimates of pCO2 and/or improved proxies for Δ'17O of atmospheric O2 would allow tighter constraints to be placed on mid-Proterozoic pO2.

Modeling of Hierarchical Cathodes for Li-Air Batteries with Improved Discharge Capacity

The non-aqueous Li-air battery is considered to be a promising energy source for electric-vehicles owing to its ultrahigh theoretical energy density. However, its commercialization is limited by the attained lower energy density value, which is mainly due to pore blockage and passivation which requires a more strategic design of the cathode. In this work, we have developed and validated a detailed one-dimensional continuum model of Li-Air battery that helps in examining the potential of hierarchical cathodes in guiding and enhancing the efficiency of ions transport and discharge product formation inside microstructures. The obtained results reveal the importance of reducing the tortuosity (shorten the path of oxygen transport) and increasing porosity at the airside of the hierarchical cathode, which improved discharge capacity at approximately 20.9 and 56%, respectively. The improved capacity is due to enhanced effective oxygen transport, impregnation of electrolyte, alignment of pores, and formation of permeable and low crystalline aggregates of Li2O2. Hence, strategies considering these insights can help in the design and fabrication of non-aqueous Li-air batteries with enhanced energy density and capacity.

A Detailed One-Dimensional Hydrodynamic and Kinetic Model for Sorption Enhanced Gasification

Increased installation of renewable electricity generators requires different technologies to compensate for the associated fast and high load gradients. In this work, sorption enhanced gasification (SEG) in a dual fluidized bed gasification system is considered as a promising and flexible technology for the tailored syngas production for use in chemical manufacturing or electricity generation. To study different operational strategies, as defined by gasification temperature or fuel input, a simulation model is developed. This model considers the hydrodynamics in a bubbling fluidized bed gasifier and the kinetics of gasification reactions and CO2 capture. The CO2 capture rate is defined by the number of carbonation/calcination cycles and the make-up of fresh limestone. A parametric study of the make-up flow rate (0.2, 6.6, and 15 kg/h) reveals its strong influence on the syngas composition, especially at low gasification temperatures (600–650 °C). Our results show good agreement with the experimental data of a 200 kW pilot plant, as demonstrated by deviations of syngas composition (5–34%), lower heating value (LHV) (5–7%), and M module (23–32%). Studying the fuel feeding rate (22–40 kg/h), an operational range with a good mixing of solids in the fluidized bed is identified. The achieved results are summarized in a reactor performance diagram, which gives the syngas power depending on the gasification temperature and the fuel feeding rate.

Reduced-order model for redox kinetics of oxygen carrier in chemical looping combustion

A reduced-order model was developed to calculate the redox kinetics of oxygen carrier in chemical looping combustion. The reduced-order model can describe the major physical/chemical features of the redox steps of oxygen carrier, such as gas diffusion around and inside the particle, surface reaction, product growth, product layer diffusion, pore structure change etc. It is an analytical model simplified using the Thiele modulus method and thus is much easier for computational fluid dynamics modeling and reactor design. The accuracy of variations of redox conversion under different temperatures and gas concentrations predicted by the reduced-order model is verified by comparison with both the detailed one-dimensional model and the experimental data. The results indicate that the reduced-order model can reproduce the prediction accuracy of the detailed one-dimensional model and agrees well with the experimental data. The well observed two-stage behavior of a fast initial stage followed by a second slower stage was discussed in detail. Further, the reduced-order model was used to analyze the effect of particle structural parameters on the kinetics. The relative importance of each controlling step in the kinetics of oxygen carrier predicted by the reduced-order model was compared.

Reduced-order model for CaO carbonation kinetics measured using micro-fluidized bed thermogravimetric analysis

A reduced-order model was developed to describe the CaO carbonation kinetics by simplifying the detailed one-dimensional rate-equation-based grain model. The reduced-order model was derived using the Thiele modulus method and is an analytical model, which can be easily used in the reactor scale model or computational fluid dynamics (CFD) simulation. In the reduced-order model, physical/chemical steps occurring during the carbonation process were considered, including external diffusion of gas around the particle, intraparticle diffusion, surface reaction, product islands growth and product layer diffusion. This model can be used to investigate the complex kinetic behaviors such as reaction controlled steps, kinetics transition from chemical reaction to product layer diffusion, and the effect of particle structure change on intraparticle diffusion, such as pore plugging phenomenon. The prediction accuracy of reduced-order model was verified by the detailed one-dimensional model. In order to demonstrate the application of the reduced-order model for reactor scale analysis, the CaO carbonation kinetics under different temperatures (600–750 °C), CO2 concentrations (25–75 vol%) and particle sizes (0.2–3 mm) were measured using a novel micro-fluidized bed thermogravimetric analysis (MFB-TGA) method, which is based on real-time mass measurement of CaO sample in a fluidizing state. The reduced-order model was implemented into a K-L two-phase bubbling bed reactor model to analyze the experimental data of a micro-fluidized bed reactor. Results indicated that the two-stage behavior of carbonation kinetics can be described successfully using the model, and the effect of particle structure change on pore plugging and intraparticle diffusion can be well predicted and explained. The carbonation is first-order reaction when the CO2 partial pressure is within 75% (1 bar). The effect of particle size on carbonation kinetics shows three-zone characteristics of reaction/diffusion combined controlling mechanism, and was discussed in detail. The reduced-order model provides a promising application for describing multiscale mechanisms (surface, particle and reactor) of carbonation kinetics.

Numerical investigation of water injection quantity and water injection timing on the thermodynamics, combustion and emissions in a hydrogen enriched lean-burn natural gas SI engine

Water direct injection into the cylinder is one of effective ways to suppress the combustion rate and knocking combustion in turbocharged SI engine. In this study, a detailed one-dimensional model coupled with the water direct injection was built by using the GT-Power according to the real tested hydrogen-enriched lean-burn natural gas (NG) SI engine, and validated against the experimental data. Then, a series of cases with various water injection quantity and injection timing were comprehensively investigated on the thermodynamics, combustion and emissions characteristics of the NGSI engine. The impact of the thermo-physical of the water were discussed in detailed by sweeping various water injection quantity and water injection timing. The results indicated that peak combustion pressure and peak heat release rate decreased with the increasing the water injection quantity. In addition, the 50% combustion location and peak combustion pressure location were retarded with the increasing the water injection quantity. As for the water injection timing, the peak combustion pressure and peak combustion temperature were slightly decreased with retarding the water injection timing. Apart from that, the indicated thermal efficiency decreased 4.03% and the equivalent fuel consumption increased 3.56% with injecting 60 mg water into the cylinder compared the case without water injection. Furthermore, the indicated thermal efficiency decreased 4.68% and the equivalent fuel consumption increased 4.66% by sweeping the water injection timing from the 150 CA to 50 CA before top dead center. However, the volumetric efficiency slightly ascended with increasing the water injection quantity and retarding the water injection timing. Finally, the NOx emissions declined with increasing the water injection quantity and retarding the water injection timing. However, CO emission and unburned HC emissions increased with increasing the water injection quantity and retarding the water injection timing. The main aim of this paper is expected to provide a comprehensively assessment of the thermo-physical of water on the thermodynamics, combustion, and emissions of the hydrogen enriched NGSI engine.

Transient Modelling of Solid Oxide Cell Modules and 50 kW Experimental Validation

Solid oxide cells (SOC) can be a major contributor to shaping the future energy system. To achieve this, SOC plants containing large reactor modules have to reach the megawatt and multi-megawatt scale. Moving from individual stacks to these large modules is challenging. Therefore, this contribution addresses investigations of large SOC modules that consist of tens or even hundreds of stacks, manifolds, piping and insulation. Experimental results show that the individual stacks of a module work under different operating conditions due to their spatial location. In order to investigate and predict these different operating conditions, a module model is being developed. This paper explains the development of a reactor module model from a detailed one-dimensional cell model. Subsequently, an exemplary simulation result is presented and the next steps are described.

Detailed One-Dimensional Model for Steam-Biomass Gasification in a Bubbling Fluidized Bed

A one-dimensional unsteady state model is developed for simulation of biomass gasification in a bubbling fluidized bed. The proposed model accounts for the effect of hydrodynamic behavior of the fl...

Surrogate-based uncertainty and sensitivity analysis for bacterial invasion in multi-species biofilm modeling

In this work, we present a probabilistic analysis of a detailed one-dimensional biofilm model that explicitly accounts for planktonic bacterial invasion in a multi-species biofilm. The objective is (1) to quantify and understand how the uncertainty in the parameters of the invasion submodel impacts the biofilm model predictions (here the microbial species volume fractions); and (2) to spot which parameters are the most important factors enhancing the biofilm model response. An emulator (or “surrogate”) of the biofilm model is trained using a limited experimental design of size N=216 and corresponding to a Halton’s low-discrepancy sequence in order to optimally cover the uncertain space of dimension d=3 (corresponding to the three scalar parameters newly introduced in the invasion submodel). A comparison of different types of emulator (generalized Polynomial Chaos expansion – gPC, Gaussian process model – GP) is carried out; results show that the best performance (measured in terms of the Q2 predictive coefficient) is obtained using a Least-Angle Regression (LAR) gPC-type expansion, where a sparse polynomial basis is constructed to reduce the problem size and where the basis coordinates are computed using a regularized least-square minimization. The resulting LAR gPC-expansion is found to capture the growth in complexity of the biofilm structure due to niche formation. Sobol’ sensitivity indices show the relative prevalence of the maximum colonization rate of autotrophic bacteria on biofilm composition in the invasion submodel. They provide guidelines for orienting future sensitivity analysis including more sources of variability, as well as further biofilm model developments.

Dynamic measurements of drainage capillary pressure curves in carbonate rocks

The heterogeneity of rocks represents a challenge for interpreting and using outcomes from multiphase-flow experiments carried out on laboratory samples. While the capillary pressure–saturation function, pc(S), is known to vary spatially and cause local saturation development during immiscible displacements, its variation remains difficult to measure. This is particularly challenging for rocks with complex fabrics, such as carbonates. Here, we present a workflow for the dynamic measurement of core- and subcore-scale drainage pc(S) curves in heterogeneous porous media. Multi-rate, two-phase core-flooding tests are conducted on three carbonate rocks with direct observations of local saturation data. The interpretation of the experiments is done by fitting the parameters of the pc(S) curve, while describing both steady-state saturation and pressure profiles with a detailed one-dimensional model that accounts for the variation of subcore-scale properties in the direction of displacement. Workflow validation is achieved by means of synthetic data, thereby demonstrating the uniqueness of the solution of the resulting multi-objective optimisation problem. The model reproduces accurately experimental data on the three rocks and enables computing the effective core-scale pc(S) curve in the limit of zero velocity, as it would be expected during a porous-plate experiment. The output of the proposed technique is however much richer and includes the relativepc(S) curve that is universal and independent of the specific pattern of heterogeneity, in addition to a set of scaling factors. The latter describe the distribution of the pc(S) curves at the subcore-scale due to heterogeneity and form the statistical basis needed for upscaling studies.

A detailed one-dimensional model to predict the unsteady behavior of turbocharger turbines for internal combustion engine applications

This article describes an investigation of the unsteady behavior of turbocharger turbines by one-dimensional modeling and experimental analysis. A one-dimensional model has been developed to predict the performance of a vaneless radial-inflow turbine submitted to unsteady flow conditions. Different from other approaches proposed in the literature, the turbine has been simulated by separating the effects of casing and rotor on the unsteady flow and by modeling the multiple rotor entries from the volute. This is a simple and effective way to represent the turbine volute by a network of one-dimensional pipes, in order to capture the mass storage effect due to the system volume, as well as the circumferential variation of fluid dynamic conditions along the volute, responsible for variable admittance of mass into the rotor through blade passages. The method developed is described, and the accuracy of the one-dimensional model is shown by comparing predicted results with measured data, achieved on a test rig dedicated to the investigation of automotive turbochargers. The validation of the code is presented and an analysis of the flow unsteadiness, based on a variety of parameters, is proposed.

An extended calculation approach of exhaust thermocouple temperatures in one-dimensional gas exchange simulation for turbocharged gasoline direct-injection engines

A new model approach is presented to determine exhaust thermocouple temperatures in gas exchange calculations for turbocharged gasoline direct-injection engines. Since the measured thermocouple temperature at turbine inlet is typically used as a criterion to fix the required fuel enrichment for turbocharger protection, an accurate prediction of this value is decisive in the development of future engine concepts. Therefore, a detailed one-dimensional thermocouple model has been developed which captures the measurement principle by a physical approach. The major advantage of this approach is the integration of detailed data of convective heat transfer along the thermocouple protrusion length from three-dimensional computational fluid dynamic exhaust flow simulations. Detailed investigations by means of three-dimensional and one-dimensional simulations are presented for steady-state flow as well as in full and part load operations of four turbocharged gasoline direct-injection engines. For further verificati...

PP.LB02.05] THE CORONARY BACKWARD-PROPAGATING ‘SUCTION’ WAVE ARISES FROM A COMBINATION OF MICROCIRCULATORY DECOMPRESSION AND REFLECTION OF A FORWARD-PROPAGATING WAVE ORIGINATING IN THE AORTA

Objective: Coronary wave intensity (WI) analysis has revealed the existence of a large backward-propagating decompression (or ‘suction’) wave (BDW) occurring in early diastole that plays a major role in establishing diastolic coronary blood flow and may have clinical relevance. It has so far been considered that this wave arises entirely due to decompression of intramyocardial vessels during cardiac relaxation, then propagating back towards the aorta. In this study, we investigated whether reflection of the closely preceding forward-propagating decompression wave (FDW), which originates in the aorta, also contributes to the BDW. Design and method: Mechanisms underlying the BDW were elucidated using a previously validated muti-scale computational model of the coronary circulation (Mynard et al, Am J Physiol Heart Circ Physiol, 306 (4):H517-H528, 2014) and left anterior descending (LAD) WI analysis. The model was composed of a lumped parameter heart model, a simple closed loop circulation model, a detailed one-dimensional model of the main conduit coronary arteries and a regionally instantiated multi-layered lumped parameter model of the intramyocardial circulation. After establishing a reference simulation representing an older adult with high blood pressure (155/84 mmHg), all waves arising from the aorta were eliminated by prescribing a reflection coefficient of -1 at the coronary ostia, while maintaining identical intramyocardial conditions as the reference simulation, such that coronary waves could only originate from within the myocardial microvasculature.Results: The LAD WI profile in the reference simulation closely resembled published human data in all respects (Fig. 1). After eliminating waves arising from the aorta, the amplitude of the BDW fell by 69%, indicating that, in the reference case, reflection of the FDW was a major contributor to the BDW. In both simulations, reflection of the BDW at the coronary ostium also produced a forward compression wave (FCW) after the FDW. Conclusions: These virtual experiments suggest that the BDW arises from a combination of 1) active wave generation in the intramyocardial vessels and 2) passive wave reflection of a FDW originating in the aorta. These findings suggest that the conventional interpretation of coronary WI needs to be reconsidered.

Reduced-order model of char burning for CFD modeling

A reduced-order model of char burning is developed for CFD modeling suitable for typical pulverized coal boiler. Comparing with the detailed one-dimensional model, the reduced-order model is much simpler and “smaller” but can still describe many aspects of porous char burning accurately by using the Thiele modulus method. The accuracy of variations of char conversion, particle size, apparent density and specific surface area predicted by the reduced-order model is firstly verified by comparison with the detailed one-dimensional model. Then combustion test data of a kind of anthracite conducted in a drop tube furnace are used to validate it further. The results indicate the reduced-order model can predict the char burning rate quite accurately with considering the ash inhibition effect and the predicted evolution of particle mass average diameter with mass loss agreeing well with experiment data. If comparing in detail by investigating particle size distribution carefully, the diameter change originated from chemical reaction can be described reasonably while finer particles generated due to fragmentation still could not be predicted by the current model. Finally, the reduced-order model is successfully implemented into CFD software, Fluent, and applied to a parallel CFD simulation of a 600-MWe supercritical W-shaped flame boiler. The reduced-order model can reasonably describe different particle size variation modes for different initial particle sizes in different temperature ranges.

Design concepts of a scaled-down autothermal membrane reformer for on board hydrogen production

The design of an on-board autothermal membrane reactor producing pure hydrogen at atmospheric pressure, while recuperating heat, is analyzed mathematically. The suggested design incorporates two reactors exchanging heat; an endothermic methane steam-reforming (MSR) reactor embedding Pd membranes to separate pure H2, and an exothermic methane oxidation (MOx) reactor fed by the MSR effluent. The analysis is conducted at three levels of details: (i) Thermodynamics reveals that the minimum operating temperature for high thermal efficiency under adiabatic conditions with full recycle of MSR effluents is 550°C. Feeding the oxidation reactor with added fuel does not improve efficiency. (ii) A kinetic model that accounts for the permeance of the Pd membranes suggests even higher temperatures should be considered when operating with limited membrane area. The effect of catalytic kinetics is small. (iii) A transient detailed one-dimensional model considering heat exchange between the reactors, heat losses to surroundings and axial distribution of the MOx feed is used to study the performance of a 1.3L system in terms of thermal efficiency and permeate flow rate. Efficiency and H2 output are favored by higher flow rates, which result in higher temperatures. Combustion of recycled effluent produces hot spots, but distributing the feed axially mitigates the non-uniformity, and improves efficiency and permeate flow rate. Some distinct dynamical aspects are presented.We conclude that such a nonadiabatic autothermal system can operate at efficiencies of ∼66% and expected power density of 0.5kW/L at maximum MSR temperature of 700°C, when feeding the MSR reactor with liquid H2O instead of pre-vaporizing it. This represents significant improvement over previous designs, and is currently tested experimentally.

Devolatilization of a single fuel particle in a fluidized bed under oxy-combustion conditions. Part B: Modeling and comparison with measurements

A detailed one-dimensional transient model is developed to describe the conversion of a single fuel particle in O2/N2 and O2/CO2 atmospheres in a fluidized bed (FB). The model takes into account the main relevant phenomena occurring from the addition of a particle to the FB up to the instant when most of the volatiles have been released. The model accounts for the rates of drying, fuel devolatilization, homogeneous combustion of volatiles in a thin flame, heterogeneous combustion of char, and mass and heat transfer, the latter involving the heat transfer from the FB reactor and flame to the particle. The model is used to simulate and explain the experiments given in Part A of the present work, which includes tests with four ranks of coal (from anthracite to lignite) and one type of wood in O2/N2 and O2/CO2 atmospheres with the O2 volume concentration varying in the range of 0–40% at a fixed bed temperature of 1088K. The predicted history of the temperature of the fuel particle and of the volatiles flame agrees well with the measurements. The simulated results indicate that the heat transfer processes at the particle scale are similar in pure N2 and CO2. The model reveals that only a small amount of heat from the flame is transferred to the fuel particle, explaining why the rate of particle heating is hardly affected by the flame. The decrease in the devolatilization time measured at higher O2 concentration is explained by heterogeneous (char) combustion, which is seen to be significant during the last stages of devolatilization. The model shows that the char combustion is limited by the rate of diffusion of O2 to the particle and justifies the lower heating rate observed in O2/CO2 compared to in O2/N2. A sensitivity analysis shows that the thermal capacity and conductivity of the fuel, as well as the convective heat transfer coefficient, are the most influencing parameters affecting the time of devolatilization.