Optimization Of Operating Conditions Research Articles

Optimization of catalyst pellet structures and operation conditions for CO methanation

A fundamental understanding of the effects of catalyst pellet structures and operation conditions on catalytic performance is crucial for the reactions limited by diffusion mass transfer. In this work, a numerical investigation has been carried out to understand the effect of catalyst pellet shapes (sphere, cylinder, trilobe and tetralobe) on the reaction-diffusion behaviors of CO methanation. The results reveal that the poly-lobe pellets with larger external specific surface area have shorter diffusion path, and thus result in higher effectiveness factors and CO conversion rates in comparison with the spherical and cylindrical pellets. The effects of operating conditions and pore structures on the trilobular catalyst pellet with high performance are further probed. Though lower temperature can contribute to larger effectiveness factors of pellets, it also brings about lower reaction rates, and pressure has little impact on the effectiveness factors of the pellets. The increase in porosity can reduce the pellet internal diffusion limitations effectively and there exists an optimal porosity for the methanation reaction. Finally, the height of the trilobular pellet is optimized under the given geometric volume, and the results demonstrate that the higher the trilobular catalyst, the better the reaction performance within the allowable mechanical strength range.

Optimization of Operating Conditions for Electrochemical Decolorization of Methylene Blue with Ti/α-PbO2/β-PbO2 Composite Electrode

α-PbO2 was introduced into the intermediate layer of an electrode to prevent the separation of the electrodeposited layer and maintain oxidizing power. The resulting Ti/α-PbO2/β-PbO2 composite electrode was applied to the electrochemical decolorization of methylene blue (MB) and the operating conditions for MB decolorization with the Ti/α-PbO2/β-PbO2 electrode were optimized. The morphology, structure, composition, and electrochemical performance of Ti/α-PbO2 and Ti/α-PbO2/β-PbO2 anode were evaluated using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). The optimum operating parameters for the electrochemical decolorization of MB at Ti/α-PbO2/β-PbO2 composites were as follows: Na2SO4 electrolyte 0.05 g L−1, initial concentration of MB 9 mg L−1, cell voltage 20 V, current density 0.05–0.10 A cm−2, and pH 6.0. MB dye could be completely decolorized with Ti/α-PbO2/β-PbO2 for the treatment time of less than one hour, and the dye decolorization efficiency with Ti/α-PbO2/β-PbO2 was about 5 times better, compared with those obtained with Ti/α-PbO2.

Determination of Key Parameters Required to Optimize Calcination Process in Ferrous Metallurgy Heating Plants

Lime is the product of calcination. Its formation is always related to removal of carbon dioxide generated in the course of carbonate decomposition. Ferrous metallurgy, construction material, chemical and food industry companies account for about 90 % of lime produced in the country. Ferrous metallurgy is the major consumer of commercial lime using up to 40 % of all produced lime. Currently, despite occurrence of new binding and artificially produced chemical compounds, lime remains the major chemical compound produced by the industry in terms of output. Various units (shaft, rotary tubular kilns and fluidized bed kilns) are used for calcination. Shaft kilns are used the most widely. Considering continuously growing demand for lime, the need occurs for intensification of the burning process and optimization of the shaft kiln operating conditions. This requires knowledge of calcination physicochemical and heat transfer process mechanisms. Thus, the work deals with the issues related to determination of the optimal specific fuel consumption for burning of limestone from a particular deposit. It may be done only basing on thermal calculations for an operating shaft kiln, what, in its turn, causes the need for determination of the whole set of limestone and lime heat transfer properties. The obtained work results may be used to optimize the operating conditions of not only shaft but also rotary kilns intended for limestone heat treatment.

Investigation and Optimisation of Operating Conditions for Low-Temperature CO2 Reduction to CO in a Forward-Bias Bipolar-Membrane Electrolyser

The most recent investigations of operating conditions in a forward-bias bipolar-membrane zero-gap electrolyser using a silver cathode catalyst for the reduction of CO2 to CO at low temperatures and near-ambient pressures are reported. First, the CO2 electrolyser performance was investigated as a function of cathode feed humidification and composition. The highest CO partial current density was 127 mA cm−2, which was obtained at an iR-corrected cell voltage of 2.9 V, a cathode feed humidification of 50%RH, CO2 feed concentration of 90% and a CO Faradaic efficiency of 93%. The cells were tested continuously for 12 h at 3 V and 8 h at 3.4 V cell voltage to investigate system stability. While Faradaic efficiencies were maintained during the measurements at 3.0 V, a shift in selectivity was observed at 3.4 V, while a deterioration in current densities occurred in both cases. Using a specially designed electrochemical cell with an integrated reversible hydrogen reference electrode, it was found that the cathode catalyst is the main responsible for the observed loss in performance. It was furthermore determined via post-mortem SEM and EDX investigations that cathode deterioration is caused by catalyst agglomeration and surface poisoning.

Energy Efficient Seawater Desalination: Strategies and Opportunities

With the change in climate patterns, rapid industrialization, and population growth, the increasing water and energy demand became a major concern in the past decades. Desalination has been touted as the answer to the global water crisis, due to its capability in producing high‐quality fresh water from saline water. The continual research and innovations in the desalination field have resulted in the commercialization of large‐scale desalination in many water scarce regions. In the energetic context, all desalination processes are energy intensive. With the necessity to make desalination a more affordable and sustainable process, the energy efficiency of desalination is becoming an important topic. Herein, it is aimed to provide insights into the recent efforts and strategies established to tackle the energy‐related issues of both, thermal‐based and membrane‐based desalination processes. Depending on the principle of various commercial and emerging desalination processes, the directions of energy efficiency improvements, which include operating condition optimization, high‐performance material development, and renewable energy exploitation are discussed. The ideas and strategies reviewed herein, whether in their implementation or theoretical stage, are expected to provide insights into the possible improvement for application in commercial desalination plants.

Development and optimization of an innovative three-stage bioprocess for converting food wastes to hydrogen and methane

This paper sheds new light on biological hydrogen and methane technologies. An integrated process of dark fermentation, microbial electrolysis cell, and biomethanation producing both hydrogen and methane was investigated for the first time. For this purpose, operating condition optimization in terms of hydrogen and methane generated in this process from food waste was conducted. The optimization procedure correlates the substrate to inoculum ratio, applied voltage, and electrode distance to hydrogen and methane potentials using the full factorial statistical experimental design and the response surface methodology approach. Results show that the process was strongly affected by the three studied parameters. The most suitable substrate to inoculum ratio, applied voltage, and electrode distance resulting in the highest hydrogen gas yield (85.13 mL H2/gVSin) and methane gas yield (364.9 mL CH4/gVSin) were defined as 1.5, 0.5 cm. The overall integrated process reached a global energy yield of 13.91 kJ/gVSin. Yields achieved in this study attest that food waste constitute a good substrate for hydrogen and methane production, and the multiple stage combination shows advantageous process performance. Further research is necessary to evaluate its economic feasibility, and energetic and environmental benefit.

Performance of Iron-Functionalized Activated Carbon Catalysts (Fe/AC-f) on CWPO Wastewater Treatment

Two commercial activated carbon were functionalized with nitric acid, sulfuric acid, and ethylenediamine to induce the modification of their surface functional groups and facilitate the stability of corresponding AC-supported iron catalysts (Fe/AC-f). Synthetized Fe/AC-f catalysts were characterized to determine bulk and surface composition (elemental analysis, emission spectroscopy, XPS), textural (N2 isotherms), and structural characteristics (XRD). All the Fe/AC-f catalysts were evaluated in the degradation of phenol in ultrapure water matrix by catalytic wet peroxide oxidation (CWPO). Complete pollutant removal at short reaction times (30–60 min) and high TOC reduction (XTOC = 80 % at ≤ 120 min) were always achieved at the conditions tested (500 mg·L−1 catalyst loading, 100 mg·L−1 phenol concentration, stoichiometric H2O2 dose, pH 3, 50 °C and 200 rpm), improving the results found with bare activated carbon supports. The lability of the interactions of iron with functionalized carbon support jeopardizes the stability of some catalysts. This fact could be associated to modifications of the induced surface chemistry after functionalization as a consequence of the iron immobilization procedure. The reusability was demonstrated by four consecutive CWPO cycles where the activity decreased from 1st to 3rd, to become recovered in the 4th run. Fe/AC-f catalysts were applied to treat two real water matrices: the effluent of a wastewater treatment plant with a membrane biological reactor (WWTP-MBR) and a landfill leachate, opening the opportunity to extend the use of these Fe/AC-f catalysts for complex wastewater matrices remediation. The degradation of phenol spiked WWTP-MBR effluent by CWPO using Fe/AC-f catalysts revealed pH of the reaction medium as a critical parameter to obtain complete elimination of the pollutant, only reached at pH 3. On the contrary, significant TOC removal, naturally found in complex landfill leachate, was obtained at natural pH 9 and half stoichiometric H2O2 dose. This highlights the importance of the water matrix in the optimization of the CWPO operating conditions.

Dry Phosphorus silicate glass etching and surface conditioning and cleaning for multi-crystalline silicon solar cell processing

As an alternative to the wet chemical etching method, dry chemical etching processes for Phosphorus silicate glass [PSG} layer rel11ova] using Tri?uormethane/Sulfur Hexafluoride (CHF3/ SF6) gas mixture in commercial silicon-nitride plasma enhanced chemical vapour deposition (SiN-PECVD) system is applied. The dependence of the solar cell performance on the etching temperature is investigated and optimized. It is found that the SiN-PECVD system temperature variation has a signi?cant impact on the whole solar cell characteristics. A dry plasma cleaning treatment of the Si wafer surface after the PSG removal step is also investigated and developed. The cleaning step is used to remove the polymer ?lm which is formed during the PSG etching using both oxygen and hydrogen gases. By applying an additional cleaning step, the polymer ?lm deposited on the silicon wafer surface after PSG etching is eliminated. The effect of different plasma cleaning conditions on solar cell performance is investigated. After optimization of the plasma operating conditions, the performance of the solar cell is improved and the overall gain in ef?ciency of 0.6 % absolute is yielded compared to a cell without any further cleaning step. On the other hand, the best solar cell characteristics can reach values close to that achieved by the conventional wet chemical etching processes demonstrating the effectiveness of the additional O2/H2 post cleaning treatment.

An efficient and stable solar flow battery enabled by a single-junction GaAs photoelectrode

Converting and storing solar energy and releasing it on demand by using solar flow batteries (SFBs) is a promising way to address the challenge of solar intermittency. Although high solar-to-output electricity efficiencies (SOEE) have been recently demonstrated in SFBs, the complex multi-junction photoelectrodes used are not desirable for practical applications. Here, we report an efficient and stable integrated SFB built with back-illuminated single-junction GaAs photoelectrode with an n-p-n sandwiched design. Rational potential matching simulation and operating condition optimization of this GaAs SFB lead to a record SOEE of 15.4% among single-junction SFB devices. Furthermore, the TiO2 protection layer and robust redox couples in neutral pH electrolyte enable the SFB to achieve stable cycling over 408 h (150 cycles). These results advance the utilization of more practical solar cells with higher photocurrent densities but lower photovoltages for high performance SFBs and pave the way for developing practical and efficient SFBs.

Electrocatalytic activity survey of some cathode materials for the reduction of nitrites and nitrates in aqueous solution

The electrochemical techniques are the subject of increasing interest on the environmental remediation methods thanks to their efficiency and their selectivity. It was classified among the cleanest methods because it does not produce sludge and undesirable intermediate byproducts. For these reasons, we have chosen this technology for the reduction of nitrites and nitrates ions from aqueous solutions. The objective of our study is the comparison of several cathodes materials performances, in order to promote an optimal electro-reduction of these ions. Indeed, we have used the copper, graphite, stainless steel and zinc as cathodes; among them, we have selected the most efficient on which we have optimized the operational conditions. The results suggested that the copper cathode was the most efficient for the reduction of both tested ions compared to the other tested materials. Therefore, the optimization of operational conditions allows us to fixed them at: scan rate=50mV/s, initial effluent concentration=100 mg/L, pH=7 and potential range of the cyclic voltammetry scanning of [-1,+1]V/SCE for both ions. Under these optimal parameters, the reduction yield after 45min was important that can achieve 96.5% and 99% for nitrites and nitrates respectively.

Increasing the Efficiency and Selectivity of Separation of Components in Chromatographic Analysis of Natural Gas

The composition of natural gas plays an important role in gas processing and transportation, and the main method for determination of the composition of natural gas is gas chromatography. In gas chromatography the efficiency of separation and the selectivity are the main characteristics of the analytical process. In this work the influence of the type of packed column on separation efficiency and selectivity during chromatographic analysis of natural gas under various conditions was investigated. The highest theoretical plate number was obtained with a Porapak R 4233 column (3 m), the best symmetry of the peaks was obtained with an OPN/Porous-Sil C Column 4355 (3 m), and the highest resolution was obtained with the Hayesep Q# 1754 (3 m), Hayesep D 4741 (2 m), and Porapak Q 1723 (2 m) columns. It was shown that optimization of operation conditions can significantly improve the efficiency and selectivity of chromatographic determination of the composition of natural gas.

Kratkoročno predviđanje gustine snage vetra korišćenjem konvolucione LSTM mreže

Efficient extraction of renewable energy from wind depends on the reliable estimation of wind characteristics and optimization of wind farm installation and operation conditions. There exists uncertainty in the prediction of wind energy tapping potential based on the variability in wind behavior. Thus the estimation of wind power density based on empirical models demand subsequent data processing to ensure accuracy and reliability in energy computations. Present study analyses the reliability of the ANN-based machine learning approach in predicting wind power density for five stations (Chennai, Coimbatore, Madurai, Salem, and Tirunelveli) in the state of Tamil Nadu, India using five different non-linear models. The selected models such as Convolutional Neural Network (CNN), Dense Neural Network (DNN), Recurrent Neural Network (RNN), Bidirectional Long Short Term Memory (LSTM) Network, and linear regression are employed for comparing the data for a period from Jan 1980 to May 2018. Based on the results, it was found that the performance of (1->Conv1D|2->LSTM|1-dense) is better than the other models in estimating wind power density with minimum error values (based on mean absolute error and root mean squared error).

Optimization of reverse osmosis operational conditions to maximize ammonia removal from the effluent of an anaerobic membrane bioreactor

RO enables the recovery of clean water and ammonium in anaerobic membrane bioreactor effluent. pH governs the ammonia speciation and membrane surface charge and is the key operational factor that affects the total ammonia rejection efficiency of RO.

Optimization of Operating Conditions of Vapor-compression Type Air-conditioning Systems Using Zeotropic Refrigerant Mixture

Optimization of Operating Conditions of Vapor-compression Type Air-conditioning Systems Using Zeotropic Refrigerant Mixture

Sensitivity Analysis of Genetic Algorithms for Optimization of Operating Conditions for Protein Production Plants

This work introduces genetic algorithms, which will be investigated and used to perform sensitivity analysis. Genetic algorithms are part of a collection of stochastic optimization algorithms based on the concepts of biological evolutionary theory. This research deals with the problem of the search for optimal investment cost of multiproduct batch chemical plants found in a chemical engineering process with uncertain demand. The aim of this work is to minimize the investment cost and find out the number and size of parallel equipment units in each stage. For this purpose, it is proposed to solve the problem by using Genetics Algorithms (GAs). This GAs consider an effective mixed continuous discrete coding method with a four point crossover operator, which take into account, the uncertainty on the demand using Gaussian process modeling. Experiments indicated that relatively good results could be obtained using 4-point crossover with an applied rate of 0.7 and mutation rate ranged between 0.01 and 0.09 promised to give best performance. The results (number and size of equipment, investment cost, production time (Hi), CPU time and Idle times in plant) obtained by GAs are much more rapidly than mixed integer linear programming. This methodology can help the decision makers and constitutes a very promising framework for finding a set of “good solutions”.

Optimization of operational conditions using the experimental design method to remove Escherichia coli from contaminated groundwater by an adsorbent material prepared from Moroccan oil shales

The aim of the present study is to investigate the removal of Escherichia coli (E. coli) strain from contaminated groundwater using an adsorbent material prepared from Moroccan oil shales extracted in the Timahdit region (layer X). Several factors were studied and optimized using the experimental design method based on the Plackett-Burman Experimental plan (PBE); namely, the bacterial suspension concentration (105–108 CFU/mL), the adsorbent mass (1–30 mg), the pH (3–9), the temperature (20–37 °C), the contact time (5–360 min) and the stirring speed (45–150 rpm). Data analysis, by the PBE model, showed that the bacterial suspension concentration, the adsorbent mass and the stirring speed are the most significant factors that influence the removal of E. coli. The optimum process conditions were found with a suspension concentration below 5 × 107 CFU/mL, about 15.5 mg of the adsorbent material and a stirring speed over 97.5 rpm at 28.5 °C and pH 6 during 182 min. Under these conditions, the adsorption efficiency of E. coli reached 70.57%.

Evolutionary Design Optimization of an Alkaline Water Electrolysis Cell for Hydrogen Production

Hydrogen is an excellent energy source for long-term storage and free of greenhouse gases. However, its high production cost remains an obstacle to its advancement. The two main parameters contributing to the high cost include the cost of electricity and the cost of initial financial investment. It is possible to reduce the latter by the optimization of system design and operation conditions, allowing the reduction of the cell voltage. Because the CAPEX (initial cost divided by total hydrogen production of the electrolyzer) decreases according to current density but the OPEX (operating cost depending on the cell voltage) increases depending on the current density, there exists an optimal current density. In this paper, a genetic algorithm has been developed to find the optimal evolution parameters and to determine an optimum electrolyzer design. The optimal current density has been increased by 10% and the hydrogen cost has been decreased by 1%.

Treatability of household waste plastic garbage bag recycling industry wastewater with membrane

In this study, household waste plastic garbage bag recycling industry wastewater was treated by a membrane process to recycle water for using in the bags washing process. Two different ultrafiltration (UP150 and UP005) and nanofiltration (NF270 and NF90) membranes were tested. The steady-state permeate flux was obtained 14.9 and 19.2 L/m2.h at 5 bar for UP150 and UP005 membranes, respectively. However, the steady-state permeate flux was 12.9 and 8.9 L/m2.h at 20 bar for NF270 and NF90 membranes, respectively. The chemical oxygen demand (COD) was also tested for all membrane permeates and the highest COD removal efficiency was obtained for NF90 membrane. Thus, optimization was carried out using NF90 membrane and the effect of transmembrane pressure (10, 20, 30 bar) and solution pH (5, 7, 9) on COD removal efficiency was tested. The results showed that the highest steady-state permeate flux (23.5 L/m2.h) and COD removal efficiency (95.1%) were obtained at 30 bar and pH 9. After the optimization of the membrane type and operating conditions, 75% recovery was obtained to re-use in the bags washing process. The concentrate stream was treated by an activated sludge process to manage membrane concentrate and to provide discharge standards. The maximum COD removal efficiency in biological treatment for membrane concentrate stream was 96.2% under steady-state condition using a sequencing batch reactor (SBR) operated at 10 days of sludge retention time and 12 h of hydraulic retention time. The proposed combined process including membrane and activated sludge processes was successfully used to recover wastewater.

Prognostic-oriented Fuel Cell Catalyst Aging Modeling and Its Application to Health-Monitoring and Prognostics of a PEM Fuel Cell

Today, poor long-term performance and durability combined with high production and maintenance costs remain the main obstacles for the commercialization of the polymer electrolyte membrane (PEM) fuel cells (PEMFCs). While on-line diagnosis and operating condition optimization play an important role in addressing the durability issue of the fuel cell, health-monitoring and prognosis (or PHM) techniques are of equally great significance in terms of scheduling condition-based maintenance (CBM) to minimize repair and maintenance costs, the associated operational disruptions, and also the risk of unscheduled downtime for the fuel cell systems.The two essential components of a PHM scheme for a general engineering system are 1) an accurate aging model that is capable of capturing the system’s gradual health deterioration, and 2) an algorithm for damage estimation and prognostics. In this paper, a physics-based, prognostic-oriented fuel cell catalyst degradation model is developed to characterize the relationship between the operating conditions and the degradation rate of the electro-chemical surface area (ECSA). The model complexity is kept minimal for on-line prognostic purpose. An unscented Kalman filter (UKF) approach is then proposed for the purpose of damage tracking and remaining useful life prediction of a PEMFC.

Optimization of Bench-scale Shipboard STP Operating Conditions for Artificial Wastewater Treatment

This study intended to optimize the favorable operating conditions for Bench-scale shipboard STP by using artificial wastewater. For this purpose, the previously developed advanced sequence batch reactor and membrane bioreactor (MBR) combined system by our group was adopted at Bench-scale to study the applicability of this system for wastewater treatment and for the removal of nutrient and organic matter. The COD:T-N:T-P ratios of the influent were adjusted at 10:3:1 and the aeration during MBR process was provided at 7 min aeration and 3 min stop. The operating conditions were optimized by measuring the removal efficiencies of CODcr, T-P, and T-N at different time intervals of mixing and aeration. The operating conditions included mixing and aeration for 90:30, 80:40, 70:50, and 60:60 min, respectively. The optimal removal efficiencies were achieved under mixing and aeration for 70 min and 50 min, respectively, using Bench-scale shipboard STP. The results of the present study were in accordance with the MEPC.227(64) regulations for the removal of CODcr, phosphorus, and nitrogen for advanced shipboard wastewater treatment. A further study is required to evaluate a detailed mechanism of shipboard STP to justify the MEPC.227(64) regulations.