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Abstract Economically harvesting energy from a microbial fuel cell (MFC), increasing its electrical power production, and developing its role as a practical energy supply, needs a low-cost and high-performance design of the MFC compartments. According to this strategy, a novel monolithic membrane electrode assembly (MEA) was fabricated and evaluated as an air–cathode in a single-chamber MFC (SCMFC). The MEA was made of bacterial cellulose (BC), conductive multi-walled carbon nanotubes (CNT), and nano-zycosil (NZ). BC, as a nano-celluloses with oxygen barrier property, can maintain anaerobic conditions for the anode compartment. Binder-less CNT coating on BC avoids costly binders such as poly-tetra fluoro ethylene (PTFE) and Nafion and decreases the MEA charge transfer resistance. NZ, as a very cheap modifier, not only prevents the anolyte leakage but also provides more MEA’s active sites for the oxygen reduction reaction (ORR). The electrochemical performance of the MEA was compared to a PTFE- based gas diffusion electrode (GDE) in the SCMFC. The MEA cell provided a pulse power density of 1790 mW/m2, roughly twice as high as the pulse power density of GDE (920 mW/m2). SCMFC’s internal resistance decreased from 1.84 KΩ (with GDE) to 0.8 KΩ (with MEA). Also, the cell’s columbic efficiency increased from 4.2% (with GDE) to11.7% (with MEA). Additionally, the capacitance of the MEA (65 mF) was much higher than the value for GDE (0.73 mF). Thus, the MEA compared to the GDE showed higher performance in the SCMFC for electricity generation and wastewater treatment at a lower cost.

Abstract This paper investigates the anode electrokinetics during the start-up or warm-up period of a high-temperature proton exchange membrane fuel cell (HT-PEMFC) from a temperature above 100 °C, to the desired temperature of 180 °C, where carbon monoxide (CO) contaminated hydrogen (H2) is used as the fuel. The heating strategy considered in this study involves an initial heating of the HT-PEMFC by an external source to a temperature above 100 °C, after which current is drawn, where electrochemical reaction heating is expected to contribute to the heating process. Thus, a numerical transient three-dimensional model is derived addressing the anode electrokinetics under a specific temperature increase rate during the warm-up process. Operational parameters such as temperature increase rate, initial start-up temperature, CO volume fraction and extracted current density are varied and their effects on the CO and hydrogen coverage fractions on the electrode, the anode overpotential and the cell potential with respect to time, are studied. The results indicate that parameters such as temperature increase rate, initial start-up temperature, CO volume fraction and extracted current density would significantly affect the anode overpotential and the cell potential. Specifically, it is critical to reduce the extracted current density and CO volume fraction, and increase the temperature increase rate, to avoid a sudden shoot up of the anode overpotential that can result in the premature shutdown of the fuel cell. Having a low initial start-up temperature does result in a higher base value of the anode overpotential. The results also indicate that if the fuel cell reaches 130 ± 5 °C before the anode overpotential is overly high, then the fuel cell would not shut down prematurely due to the high anode overpotential.

Abstract The present work focuses on the numerical simulation of Moderate or Intense Low oxygen Dilution combustion condition, using the Partially-Stirred Reactor model for turbulence-chemistry interactions. The Partially-Stirred Reactor model assumes that reactions are confined in a specific region of the computational cell, whose mass fraction depends both on the mixing and the chemical time scales. Therefore, the appropriate choice of mixing and chemical time scales becomes crucial to ensure the accuracy of the numerical simulation prediction. Results show that the most appropriate choice for mixing time scale in Moderate or Intense Low oxygen Dilution combustion regime is to use a dynamic evaluation, in which the ratio between the variance of mixture fraction and its dissipation rate is adopted, rather than global estimations based on Kolmogorov or integral mixing scales. This is supported by the validation of the numerical results against experimental profiles of temperature and species mass fractions, available from measurements on the Adelaide Jet in Hot Co-flow burner. Different approaches for chemical time scale evaluation are also compared, using the species formation rates, the reaction rates and the eigenvalues of the formation rate Jacobian matrix. Different co-flow oxygen dilution levels and Reynolds numbers are considered in the validation work, to evaluate the applicability of Partially-Stirred Reactor approach over a wide range of operating conditions. Moreover, the influence of specifying uniform and non-uniform boundary conditions for the chemical scalars is assessed. The present work sheds light on the key mechanisms of turbulence-chemistry interactions in advanced combustion regimes. At the same time, it provides essential information to advance the predictive nature of computational tools used by scientists and engineers, to support the development of new technologies.

Abstract In Concentrated Solar Power Plants, steam turbines controlled with standard Proportional Integrative Derivative (PID) methods may suffer from performance downgrading in power generation when the steam conditions deviate from nominal ones. An enhancement of standard steam turbine controller can be the key to achieve optimal performance also in non-nominal steam conditions. This paper presents the improvement of the PID control concept by exploiting Fuzzy Logic, an artificial intelligence technique that allows taking into account the human experience and knowledge on the system behavior. A real Concentrated Solar Power Plant has been modeled focusing on generated power control loop, its stability and performance analysis, knowledge useful to design a Fuzzy Inference System. A fuzzy logic controller is proposed to continuously adapt the PID parameters, to improve the steam turbine governor action. Its performance is compared to the classical PID tuned according to three different approaches. The fuzzy logic PID controller extends the simplicity of PID and adapts the control action to actual operating condition by providing the system with a sort of “decision-making skill”. The possibility to design implementable algorithms on a Programmable Logic Controller, which have stringent computational speed and memory requirements, has been explicitly taken into account in the developed work, through the minimization of the controller complexity with a reduced number of fuzzy sets and fuzzy rules within the fuzzy inference system.

This study proposed a hybrid model consisting of a characteristic time combustion (CTC) model and a closed reactor model for the combustion modelling with detailed chemistry in RCCI engines. In the light of the basic idea of the CTC model of achieving chemical equilibrium in high temperature, this hybrid model uses the CTC model to solve the species conversion and heat release in the diffusion flame. Except for the diffusion flame, the auto-ignition in RCCI combustion is computed by a closed reactor model with the CHEMKIN library by assuming that the computational cells are closed reactors. The border of the transition between the CTC model and closed reactor model is determined by two criteria, a critical temperature and a critical Damkohler number. On the formulation of this hybrid model, emphasis is placed on coupling detailed chemistry into this hybrid model. A CEQ solver for species equilibrium calculations at certain temperature, pressure was embedded with CTC for detailed chemistry calculation. Then this combustion model was integrated with the CFD framework KIVA4 and the chemical library CHEMKIN-II and validated in a RCCI engine. The predicted in-cylinder pressure and heat release rate (HRR) show a good consistency with the data from the experiment and better accuracy than that computed from the sole closed reactor model. More importantly, it is observed that this model could save computational time compared with closed reactor model due to less stiff ordinary differential equations (ODEs) computation. A sensitivity analysis of the critical temperature and critical Damkohler number was conducted to demonstrate the effect of these two parameters in the current model.

Abstract Carbon intensity is a valuable indicator for balancing economic growth and environmental pollution, and plays an important role in mitigating global climate change and promoting environmental sustainability. This study attempts to examine the impacts of export on carbon intensity by proposing a novel framework that targeting at the gap between export aggregate carbon intensity (EACI) and self aggregate carbon intensity (SACI) which constitute the total carbon intensity to reveal export effects. Multi-region input-output model was used to calculate EACI and SACI in 44 world regions in 2014. LMDI approach was further adopted to decompose the gap between EACI and SACI from sectoral perspective. Some main results are concluded. (1) On global scale, exports increased 7.2% in carbon intensity. On national scale, exports showed increased effects on most countries (42/44). The regional EACI/SACI ranged from 0.79 to 3.53. (2) Sectoral aggregate carbon intensity (ACI) of export decreased EACI by 51 g/$, while sectoral aggregate structure (AS) of export increased EACI by 186 g/$, resulting in 135 g/$ increase in EACI globally. (3) For most regions, although ACI of carbon-intensive sectors (Elec., Metal, Nonmetal, Trans., Chem. and Coke&petrol.) in exports was lower than that in self, the high AS of these sectors in exports resulted in EACI higher than SACI, causing pulling force of export on global carbon intensity. Thus reducing carbon-intensive industries’ weights in exports would have great effects on global and national carbon intensity mitigation.

Laboratory-created samples of methane hydrate (MH)-bearing media are a necessity because of the rarity and difficulty of obtaining naturally-occurring samples. The hypothesis that the inevitable heterogeneity in the phase saturations of the laboratory samples may lead to unreliable and non-repeatable results provided the impetus for this study, which aimed to determine the conditions under which maximum uniformity can be achieved. To that end, we designed four experiments involving different multi-stage cooling regimes (in terms of their duration and number of stages) to induce MH formation under excess-water conditions. In the absence of direct visualization capabilities, we analysed the experimental results by means of numerical simulation, which provided high-resolution predictions of the spatial distributions of the phase saturations in the cores and enabled the estimation of the parameters controlling the kinetic MH-formation behaviour through history-matching. Analysis of the numerical results indicated that, under the conditions of the experiments and with the design of the reactor, significant heterogeneities in phase saturation distributions were observed in all cases, leading to the conclusion that it is not possible to obtain cores with uniform phase saturation. Additionally, contrary to expectations, heterogeneities increased with the number of cooling stages and the duration of cooling, and this was attributed to imperfect insulation of the upper part of the reactor. A set of simulations involving perfect insulation of the reactor top confirmed the validity of this assumption: (a) predicting the formation of high-uniformity MH-bearing cores that became more homogeneous as the number of cooling stages and the length of the cooling period increased; and (b) providing important information for the improvement of the standard design of the experimental apparatus for the laboratory creation of MH-bearing cores using the excess water method.