This paper is a comparative study on the preparation techniques used to make the support layer of polyamide‐thin‐film composite forward osmosis (TFC‐FO) membranes. The role played by the support ...layer preparation technique in membrane performance is thoroughly investigated in this study. Electrospinning is shown to produce membranes of lower structural parameter compared to those obtained by conventional phase inversion techniques. The electrospun polyamide selective layer can also be tailored with the required properties. This makes electrospinning a promising process to design efficient FO membrane substrates. It is shown in this work that the FO water flux is more dependent on the internal structure of the support layer than the preparation materials. The main challenge remaining for substrates to operate in FO is to achieve simultaneously a low structural parameter, a high surface porosity, and the required mechanical properties. As most of today's approaches are not suitable, further materials development is essential in future investigations on TFC‐FO membranes.
The main objective of our work is to optimize the 1st step of the dilute sulfuric acid hydrolysis of Moroccan sugar beet pulp. The optimal conditions were not only determined using the response ...surfaces methodology (RSM). They were defined by applying a multi-objective optimization using a desirability function. The effects of temperature (80–130 °C), sulfuric acid concentration (0.75–1.5 % v/v), and time (40–120 min) on the production of pentoses, hexoses, furfural, and 5-hydroxymethylfurfural (HMF) were determined by experiment according to a central composite design (CCD). These experimental data were exploited to develop four statistical models by RSM, relating the production of each product of pretreated pulp to the operating conditions. All these models produced very satisfactory results, in term of correlation coefficients and student test. These models have been used for a multi-objective optimization to maximize pentoses and hexoses production, and minimize concentrations of furfural and HMF, simultaneously. The optimal conditions were 130 °C for temperature, 0.75 (%, v/v) for sulfuric acid concentration, and 120 min for time. These conditions allowed 85.68 % of pentoses, 18.6% of hexoses, 8.53 % of furfural, and 6.58 % of HMF.
Green hydrogen production via alkaline water electrolysis has the capability to greatly reduce emissions of greenhouse gases and support the transition to a cleaner, more sustainable energy system. ...The use of modeling in the development and optimization of alkaline water electrolysis (AWE) systems can help in enhancing the performance of the electrolysis process, ultimately enabling the green hydrogen production at a lower cost and with a smaller carbon footprint. This article provides a comprehensive overview of numerous research studies on AWE systems that have been carried out in recent years. The goal is to provide readers a thorough understanding of the phenomena involved in modeling AWE electrolyzers, serving as a starting point for further exploration and highlighting significant considerations for developing more effective physical models of AWE. The review also summarizes models that focuses on electrochemical effects, mass transfer, heat transfer, and the two-phase flow effect, as well as the software used to implement the models and current research trends in this field.
•Alkaline water electrolysis systems: Recent research overview.•A thorough understanding of the phenomena involved in AWE electrolyzer modeling.•Model summary: Electrochemical effects, heat, mass transfer, two-phase flow effect.•Highlighting crucial considerations for creating more effective AWE physical models.•Current research focus and direction of alkaline water electrolysis modeling.
As an eco-friendlier way to manage mining waste, the use of solar energy to dry phosphate sludge in a rotary dryer is envisioned. As a first step toward this end, a design study for a bench-scale ...rotary dryer for phosphate sludge is detailed, using a one-dimensional mathematical model developed for this task. Using the Engineering Equation Solver (EES) software, a steady-state transport phenomena model was developed that enables an estimation of the moisture and temperature profiles for both gas and product in the dryer. A sensitivity analysis evaluated the effects and influence of different geometric parameters and operating conditions on the product moisture profile. Parameters involved include the diameter of the dryer, the residence time of the product to dry, inlet air temperature, and inlet product humidity. This allowed for the selection of suitable design parameters for the operation of a phosphate sludge dryer with a 1.5 m length and an internal diameter of 11.5 cm. The inlet air temperature of the rotary dryer was set at 200°C to achieve a reduction of moisture content in the product from 30% to 7%. The model was validated through literature and experimental datasets, with an error averaging 0.22% and 1.52%, respectively.
A comparative study is made between various optimized configurations of finned tube heat exchanger used to transfer thermal energy from a solar parabolic trough collector to a bench-scale dryer. The ...exchanger design relies on the logarithmic mean temperature difference (LMTD) and conjugate directions optimization method already integrated into the Engineering Equation Solver software (EES). Total cost minimization was set as the objective function. The model is first tested with previous literature results before being used to compare optimum configurations of four distinct heat exchanger configurations. The effect of five geometric and operating parameters is investigated. Results show that the third heat exchanger configuration (HX3) yields the lowest costs. Therminol -LT and -VP1, as well as Dowtherm -Q and -A, were found as the best working fluids for this application. Using copper as both tubes and fins material results in the smallest heat transfer surface area because of its high thermal conductivity. When economics are considered, aluminum and stainless steel alloys become suitable alternatives for fins and tubes, respectively. This yields savings of more than 40% on total costs from an all-copper construction.
In the process of desalination by indirect freezing, ice formed on the cooled surface contains impurities due to kinetic effects. Sweating is an efficient method by which ice layer is purified under ...the effect of temperature gradient. The main kinetic parameters influencing sweating of ice are initial concentration of ice, sweating temperature and sweating time. In the present work, the effects of these parameters were studied using an experimental design. A statistical model for ice weight and ice purity was developed. The graphical representation of this model in the space of the variables enabled optimization of the whole desalination process time, which led to ice salinity less than the drinking water standards (0.5g/kg).
►Layer melt crystallization was applied to seawater desalination. ►The process involves two consecutives steps: freezing and sweating. ►Sweating has enabled the obtention of ice with low salt concentration, satisfying standards of potability. ►Optimal operating conditions are proposed by means of an experimental design.
This work aims at developing a dynamic layer crystallizer operated batchwise, for freezing desalination of sea water. The experiments were performed with water/NaCl solutions and with samples of sea ...water from Nice, Rabat and Marseille. The pilot crystallizer consists of a cooled tube immersed in a cylindrical double jacketed tank. The solution is poured into the tank and the crystallization takes place on the external surface of the tube, by applying a cooling ramp in the tube. The solution is agitated by air bubbling. The whole process involves the freezing step, leading to the crystallization of the ice layer and the sweating step, which consists of purifying in depth the ice layer by melting the impure zones. A parametric study on the effect of the operating parameters has allowed quantifying the role of the different key parameters of the freezing and sweating steps. Three experiments allowed reaching salinities lower than 0.5g/kg, satisfying the standards of drinking water. The duration of the whole process dropped to only 8h (5h for freezing and 3h for sweating), with a yield of sweating equal to about 50%, provided severe conditions were applied for sweating. Higher yields required longer times. Overall, the results show the feasibility of the technique.
► Initial temperature, ice growth rate and solution salinity are the parameters affecting ice purity. ► The sweating step is able to efficiently complete the purification. ► The duration of the whole process dropped to only 8h (5h for freezing and 3h for sweating).
The catalytic hydrogenation of carbon dioxide (CO2) to methanol presents a significant opportunity for both mitigating climate change and producing a valuable chemical feedstock. While existing ...reviews delve into diverse modeling strategies, the role and potential of machine learning (ML) approaches remain largely unexplored. This review addresses the gap by comprehensively exploring the mechanism, workflow, and application of ML models in the methanol production process. The review highlights the significance of ML application in catalytic CO2 hydrogenation for methanol synthesis, emphasizing process optimization, predicting methanol performance indicators, thermodynamic modeling, reaction kinetics, and assessing catalyst activity. Furthermore, the review delves into cutting-edge approaches like hybrid models, gray-box models, and digital twins, showcasing their potential to revolutionize the methanol production process. This comprehensive review serves as a valuable resource for forthcoming research aimed at optimizing the CO2 conversion process to efficiently and sustainably produce methanol.
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•Machine learning models are extensively employed in catalytic hydrogenation to produce methanol.•This review is dedicated to the analysis and synthesis of these models as well as to their applications.•ML exhibits high accuracy in modeling CO2 hydrogenation into methanol.•ML models predict key performance indicators of methanol and optimize reaction conditions.•Innovative ML, gray box, digital twin, and Hybrid algorithms leverage vast databases in this domain.
•Dynamic modeling of a PVT collector with an extruded absorber was introduced.•A detailed model was developed for each layer of the PVT collector.•Collocation on finite elements was applied to ...discretize model equations.•A simulation of PVT using the python optimization modeling object was conducted.•The results revealed improved exergy compared to the conventional PVT collector.
Solar photovoltaic thermal (PVT) integrates photovoltaic panels and solar thermal collectors in one system for simultaneous electricity and heat production in a reduced area. The absorber type used for heat extraction significantly affects PVT performance. This work examines the performance of an extruded absorber PVT under varying solar irradiance, ambient temperature, and wind speed. A detailed dynamic mathematical model is developed from energy balance equations and heat transfer correlations for each layer of the PVT collector. Using orthogonal collocation on the finite difference method, the system of differential equations is discretized and solved numerically with Pyomo, a Python optimization modeling tool. Following validation against literature data, the model is used to predict the temperature of each layer and the thermal and electrical output of the PVT collector. The effect of cooling fluid mass flow rate, solar irradiance intensity, ambient temperature, and wind speed on PVT performance is analyzed. This design provides a maximum electrical efficiency of 15.47 % at a wind velocity of 3 m/s, regardless of the cooling fluid flow rate. Peak electrical power of 212.26 W is achieved at the highest flow rate (14.14 kg/hr) and with the highest wind velocity (3 m/s), while the peak thermal power of 348.03 W occurs at a wind velocity of 1 m/s and a flow rate of 11.31 kg/hr. Compared to the conventional sheet-and-tube design at 1 m/s wind speed and 5.65 kg/hr cooling fluid flow rate, the extruded absorber PVT delivers 203.18 W electrical and 189.27 W thermal power, outperforming the 207.46 W electrical and 128.9 W thermal power of the conventional design, demonstrating the potential of the extruded absorber design for enhancing heat generation.
Separation methods for ethanol production are among the most energy consumption in chemical industry. The design of efficient process is part of challenges faced by process engineering. The aim of ...this work is to reduce the operating energy and cost of a Moroccan distillery process. The separation process of this distillery consists of a distillation, purification and rectifying column under vacuum. In this study, a hybrid distillation-pervaporation process was proposed by replacing the rectifying column, which requires more than half of the total energy of the process, with the pervaporation unit. The pervaporation unit was modeled and simulated using appropriate model. Afterwards, the design of the hybrid process has been performed coupling the obtained pervaporation model with a simulator of the separation columns. The performance of the hybrid distillation-pervaporation process has been evaluated by simulation. A reduction of about 64.5% can be obtained for the operating energy and cost compared to the industrial distillation process.
•A benchmark of separation process for bioethanol production was examined.•A hybrid vacuum distillation-pervaporation process was developed based on Moroccan distillery.•A reduction of about 64.5% of the operating energy and costs was achieved using the hybrid process.
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