Model-based control of a molten carbonate fuel cell (MCFC) process

To improve availability and performance of fuel cells, the operating temperature of molten carbonate fuel cells (MCFC) stack should be strictly maintained within a specified operation range, and an efficient control technique should be employed to meet this objective. While most modern control strategies are based on process models, many existing models of MCFC are not ready to be applied in synthesis and operation of control systems. In this study, we developed an auto-regressive moving average (ARMA) model and machine learning methods of least squares support vector machine (LS-SVM), artificial neural network (ANN) and partial least squares (PLS) for the MCFC system based on input-output operating data. The ARMA model showed the best tracking performance. A model predictive control method for the operation of MCFC system was developed based on the proposed ARMA model. The control performance of the proposed MPC methods was compared with that of conventional controllers using numerical simulations performed on various process models including an MCFC process. Numerical results show that ARMA model based control provides improved control performance compared to other control methods.     

A carbon in molten carbonate anode model for a direct carbon fuel cell

The electrochemical oxidation of carbon at the anode of a direct carbon fuel cell (DCFC) includes charge transfer steps and chemical steps. A microstructural model of carbon particle is built, in which perfect graphene stacks are taken as the basic building blocks of carbon. A modified mechanism taking account of the irreversibility of the process and supposing that the electrochemical oxidation of carbon takes place only at the edges of the graphene sheets is proposed. A Tafel type overall rate equation is deduced along with expressions of exchange current density (j₀) and activation polarization (η_act). The performance of carbon black and graphite as the fuel of DCFC is examined. It has been found that j₀ is in the range of 0.10-6.12 mA cm⁻² at 923-1123 K and η_act is in the range of 0.024-0.28 V at 923-1123 K with current density in 10-120 mA cm⁻². Analysis of the j₀, η_act values and the product composition reveals that the charge transfer steps as well as the oxygen ion absorption steps are both important for the reaction rate. The activity of the carbon material with respect to atom location is introduced to the open circuit potential difference (OCP) calculation with Nernst equation.     

A comparative study of models for molten carbonate fuel cell (MCFC) processes

The necessity of this work arose from the need for identification of a comprehensive plant model that can be used in the model-based control of the MCFC plant. Various models for molten carbonate fuel cell (MCFC) processes are presented and evaluated in this paper. Both a rigorous model based on mass and energy balances and implicit models based on operation data were investigated and analyzed. In particular, auto-regressive moving average (ARMA) model, least-squares support vector machine (LSSVM) model, artificial neural network (ANN) model and partial least squares (PLS) model for a MCFC system were developed based on input-output operating data. Among these models, the ARMA model showed the best agreement with plant operation data.     

A study on the start-up and performance of a kW-class molten carbonate fuel cell (MCFC) stack

A kW-class internal-manifolded molten carbonate fuel cell (MCFC) stack (52 cells) was assembled with inorganic adhesive under a suitable stacking pressure. The organic compounds in the matrices were burnt out under the conditions of slow and uniform elevation of temperature and big flow of oxygen gas in the stack. The stacking pressure dropped with elevating temperature. The output power of the stack at 150 mA cm⁻² was 1025.5 W when the reactant gas pressure and utilization were 0.5 MPa and 20%, respectively. The thermal-electrical efficiency of the stack was enhanced by increasing the pressure of the reactant. However, it was contrarily decreased when current density was increased.     

Studies on the modeling of a molten carbonate fuel cell (MCFC) 5 kW class stack

A mathematical model was developed to simulate the performance of a molten carbonate fuel cell (MCFC) 5 kW class stack. In the modeling calculations, the average current densities of each cell were adjusted to be same for all cells in the stack. In this procedure the operating voltages of each cell were decided. Temperatures of matrixes with an electrolyte increased to a maximum value at the 7 ^th cell. Because the temperatures of the 1 ^st and 9 ^th cells were lower than those of the other cells, the operating voltage of these cells was lower than those of the other cells. Compared to the measured temperature distributions, the calculated results were quite low near the gas entrance. The measured data of the temperature of the matrixes with an electrolyte and the power were estimated well with the modeling calculations. The current density distributions in all cells from the model calculations were similar.     

Carbon activity measurement using a solid state potentiometric cell: Application to boron carbides

The interface between -alumina and carbonaceous materials has been studied from both thermodynamic and electrochemical viewpoints. Based on the results, a solid electrolyte potentiometric cell has been devised and the conditions enabling carbon activity to be measured have been determined. In spite of the chemical inertness of the materials involved, the measurements must be performed at low temperature (T<720 K). Carbon activity measurements in the boron-carbon system are presented.     

Assessment and comparison of distributed model predictive control schemes: Application to a natural gas refrigeration plant

A number of decentralized and distributed control schemes based on model predictive control (MPC) have been introduced in the last years. They have been proposed as viable solutions to the computational, transmission and robustness issues arising in the centralized context in case of large-scale and/or distributed plants. Such MPC-based control schemes are very heterogeneous, based on different model structures and realizations, with different features and infrastructural/memory/computational requirements.In this paper, we test and compare, with a realistic case study, a robust non-cooperative scheme and a cooperative iterative one. The main scope is to analyze and unravel, in a fair comparison scenario, these methods from different viewpoints, spanning from the model realization issues to the communication and computational requirements, to the control performances. The benchmark case study consists of an existing natural gas refrigeration plant. Realistic simulations and validation tests are obtained through in the DynSim industrial process simulation environment.     

Preparation of a functional poly(ether imide) membrane for potential alkaline fuel cell applications: Chloromethylation

We have developed a novel poly(ether imide)‐based alkaline anion‐exchange membrane. The effects of several important parameters on the chloromethylation of the membrane have been investigated. These parameters include the reaction temperature, reaction time, concentration of the chloromethylation agent, concentration of the polymer, and amount of the catalyst. The results show that all the studied parameters have significant impacts on chloromethylation. Among them, the concentration of the chloromethylation agent plays a key role in increasing the attachment of chloromethyl functional groups onto the polymer. It ha been found that gelation can be avoided if these reaction parameters are controlled. This study also provides useful information for the successful chloromethylation of other membrane‐related polymers. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Experimental predictive control of the infrared cure of a powder coating: A non-linear distributed parameter model based approach

This paper deals with the experimental model based predictive control of the infrared cure cycle of a powder coating. It is based on a dynamic infinite dimensional model of the cure in one spatial domain, which aims to represent the evolution of the temperature and the degree of cure during the cure under infrared flow. The sensitivity of this model with respect to the main radiative property is experimentally highlighted under open loop conditions. This partial differential equation model is then approximated in finite dimension in order to be used by the predictive controller. Since the sampling time is small (one second), a special model predictive control formulation is used here, which aims to decrease the on-line computational time required by the control algorithm. Experimental evaluation of this controller that is based on the MPC@CB software is then presented. For black and white paintings, the robustness of this control algorithm is shown during an experimental temperature constrained trajectory tracking, even under a strong modeling uncertainty. The conclusion of this study is that this controller may be used for advanced control of powder coating cure.     

Photo-Fenton-peroxide process using FE (II)-embedded composites based on activated carbon: Characterization of catalytic tests

Cost-efficient Fenton-like catalysts for the removal of organic molecules in aqueous solutions were elaborated by a simple process. Porous activated carbons (ACs) were directly impregnated with a precursor solution using the wet impregnation method. Their efficiency as Fenton-like catalysts was studied. Photo-Fenton tests were performed to establish the performance of the prepared Fe-impregnated activated carbons in relation to the degradation of an organic pollutant (Indigo Carmine) model in aqueous solution, under different conditions. Photo-catalytic tests were carried out by means of a laboratory photo-reactor (UV-Consulting Peschl). The influence of several parameters such as solution pH value, initial concentration of the model pollutant, and hydrogen peroxide dose on the process performance was investigated. The ACs and prepared catalysts were characterized by nitrogen adsorption-desorption isotherms at 77 K, SEM, and thermogravimetric analyses. The total Fe content of the synthesized composites was estimated by the phenanthroline method using UV-vis spectrophotometry. The results show an increase in the degradation rate when the heterogeneous photo-Fenton process is conducted with an ozone generating UV lamp.     

Optimizing the performance of aerosol photoacoustic cells using a finite element model. Part 2: Application to a two-resonator cell

Abstract

Photoacoustic spectroscopy (PAS) measures aerosol absorption in a noncontact manner, providing accurate absorption measurements that are needed to improve aerosol optical property representations in climate models. Central to PAS is resonant amplification of the acoustic pressure wave generated from laser-heated aerosol transferring heat to surrounding gas by a photoacoustic cell. Although this cell amplifies pressure sources from aerosol absorption (signal), it also amplifies noise and background sources. It is important to maximize the cell signal-to-background ratio (SBR) for sensitive absorption measurements. Many researchers have adopted the two-resonator cell design described by Lack et al. (2006 Lack, D. A., E. R. Lovejoy, T. Baynard, A. Pettersson, and A. R. Ravishankara. 2006. Aerosol absorption measurement using photoacoustic spectroscopy: Sensitivity, calibration, and uncertainty developments. Aerosol Sci. Technol. 40 (9):697–708. doi: 10.1080/02786820600803917.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). We show that the uncertainty in PAS measurements of aerosol absorption using this two-resonator cell is significantly degraded by its large sensitivity to background contributions from laser scattering and absorption at the cell windows. In Part 1, we described the use of a finite element method (FEM) to predict cell acoustic properties, validated this framework by comparing model predictions to measurements, and used FEM to test various strategies applied commonly to single-resonator cell optimization. In this second part, we apply FEM to understand the excitation of resonant modes of the two-resonator cell, with comparison measurements demonstrating accurate predictions of acoustic response. We perform geometry optimization studies to maximize the SBR and demonstrate that the laser–window interaction background is reduced to undetectable levels for an optimal cell. This optimized two-resonator cell will improve the sensitivity and accuracy of future aerosol absorption measurements.     

A simple model to assess the contribution of alloyed and non-alloyed platinum and tin to the ethanol oxidation reaction on Pt-Sn/C catalysts: Application to direct ethanol fuel cell performance

A simple model is proposed to evaluate the contribution of alloyed and non-alloyed platinum and tin to the ethanol oxidation reaction on Pt-Sn/C catalysts for direct ethanol fuel cells. On the basis of the model, the ethanol oxidation on partially alloyed catalysts occurs through a dual pathway mechanism, separately involving the Pt₃Sn phase and Pt-SnO_x. The model, validated by experimental data, can predict the performance of a single direct ethanol fuel cell by varying the Sn content and/or the degree of alloying of Pt-Sn/C catalysts used as the anode material.     

A Reynolds mass flux model for gas separation process simulation:II. Application to adsorption on activated carbon in a packed column☆

Simulations of adsorption process using the Reynolds mass flux model described in Part I of these serial articles are presented. The object of the simulation is the methylene chloride adsorption in a packed column (0.041 m id, packed with spherical activated carbon up to a length of 0.2 m). With the Reynolds mass flux model, breakthrough/regeneration curves, concentration and temperature as well as the velocity distributions can be obtained. The simulated results are compared with the experimental data reported in the literature and satisfactory agreement is found both in breakthrough/regeneration curves and temperature curves. Moreover, the anisotropic turbulent mass diffusion is characterized and discussed.     

A novel fault detection scheme for a nonlinear dynamic process based on generalized non-negative matrix projection-maximum mean discrepancy: Application on the DAMADICS benchmark process

In order to address the issue of minor fault detection in nonlinear dynamic processes, this paper proposes a fault detection method based on generalized non-negative matrix projection-maximum mean discrepancy (GNMP-MMD). Firstly, the GNMP is employed to acquire the residual scores of the samples. Subsequently, a sliding window approach is integrated with MMD for real-time monitoring of sample status within the residual subspace. In this study, GNMP is utilized to mitigate the impact of non-Gaussianity in data distribution, while MMD serves to alleviate autocorrelation among samples. A numerical case and experimental data collected from the DAMADICS process are utilized to simulate and validate the proposed method. Compared to traditional principal component analysis (PCA), dynamic principal component analysis (DPCA), dynamic kernel principal component analysis (DKPCA), non-negative matrix factorization (NMF), GNMP, and MMD, the experiment results clearly illustrate the feasibility of the proposed method.     

A novel solid state battery based on a polymer proton conductor: poly(propargyl alcohol) doped with perchloric acid

A battery was constructed by including a polymer proton conductor, poly(propargyl alcohol) doped with perchloric acid, between electrodes of magnesium and gold. The characteristics of the cell, showing an open circuit voltage of 2.0–2.2V, were studied as the function of the relative humidity. It was found that the system behaves as a fuel cell and that the discharge current of the battery is due to magnesium oxidation at the anode and proton reduction at the cathode.     

The transient nature of maximum maleic anhydride grafting of polypropylene: A mechanistic approach based on a consecutive reaction model Part 1: Batch solution process

This article reports the chemical modification of an atactic polypropylene performed in solution. To model the process, a Box‐Wilson experimental design was used, taking in to consideration the concentrations of maleic anhydride and dycumile peroxide, as well as reaction time, as independent variables. The dynamic character of the process is proposed on the basis of model forecasts supported by experimental results. The proposed kinetic pathway agrees with the fact that short reaction times are not only sufficient but necessary for the greatest graft yields to be attained, while preventing degradative processes in the system. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 1182–1190, 2006.     

Biodegradable nanocomposite blown films based on poly(lactic acid) containing silver-loaded kaolinite: A route to controlling moisture barrier property and silver ion release with a prediction of extended shelf life of dried longan

Novel biodegradable nanocomposite blown films based on compatibilized poly(lactic acid)-poly(butylene adipate-co-terephthalate) blend are fabricated for use as a model package for dried longan. Silver-loaded kaolinite (AgKT) dispersing in the polymer matrix in intercalated-exfoliated fashion functions as an excellent property improver of the blend. The emphasis of this paper is enhancement of film moisture barrier property by inducing polymer crystallization coupled with formation of AgKT tortuous path. Additionally, controlled silver release which provides long-term antibacterial activity is attributed to AgKT's layered structure. The amount of released silver ions herein also complies with migration levels specified by the standard for food-contact plastic packages. Dried longan shelf lives as eventually predicted by experimental moisture sorption isotherm and by Peleg model are almost identical (∼308 days) for the nanocomposite films being over two folds of that obtained from the compatibilized blend package at ambient condition.     

Synthesis of reactive dyes based on the bis-(N-carboxymethylamino)monoquaternary-triazine-bis-ethylsulphone reactive group. Part 1: Application to cotton cellulose

Reactive dyes containing the bis-( N -carboxymethylamino)monoquaternary-triazine-bis-ethylsulphone [bis-( N -CMA)-MQT-bis-ES] group and related derivatives have been synthesised. When boiled under mildly acidic conditions, such dyes are able to form two small vinylsulphone dye molecules through a process of 1,2-trans elimination. The bis-( N -CMA)-MQT-bis-ES dye was applied using different dyeing procedures (novel dyeing methods 1 and 2). The dyeing and soaping-off results of bis-( N -CMA)-MQT-bis-ES dye were compared with a model sulphatoethylsulphone dye applied using the conventional alkaline fixation method used for applying this type of reactive dye to cotton. The bis-( N -CMA)-MQT-bis-ES dye showed higher exhaustion and fixation values applied using novel dyeing method 2 compared with the sulphatoethylsulphone dye applied using the alkaline fixation method. The soaping-off efficiency for the large bis-( N -CMA)-MQT-bis-ES dye applied using novel dyeing method 2 was the same as that obtained for the sulphatoethylsulphone dye applied using the alkaline fixation method.     

Feasibility study and benefit analysis of biomass-derived energy production strategies with a MILP (mixed-integer linear programming) model: Application to Jeju Island,Korea

We developed a new approach to analyze the feasibility and benefits of biomass utilization strategies for energy production. To achieve this goal, we first generated a biomass-to-energy network which consists of different conversion technologies and corresponding compounds. We then developed new optimization models using a mixed integer linear programming technique to identify the optimal and alternative strategies and point out their major cost drivers. We applied these models to the biomass-derived energy supply problem on Jeju Island, Korea, to answer a wide range questions related to biomass utilization. What is the cheapest way to produce liquid fuels from available biomass on Jeju Island? How much demand can be satisfied by biomass-derived liquid fuels? What combination of technologies and biomass resources gives the best economic benefits or productivity? Based on the case study of Jeju Island, we could provide useful guidelines to policy-makers and stakeholders in the energy business.