École Mohammadia d'Ingénieurs

This study evaluates the effectiveness of pyrolysis oils, derived from key waste byproducts of the sugar industry, as collectors in the flotation of calcite, using phosphoric acid (PA) as depressant.The chem. structure of pyrolysis oil collectors (POCs) was analyzed using FTIR, GC-MS, and surface tension measurements, revealing a complex mixture of various mol. groups, including hydroxyl, carboxylic, aromatic, and alkane.The collecting effect of POC in calcite flotation was assessed through microflotation using an exptl. setup based on Box-Behnken design (BBD).The findings revealed that, with an air flow rate of 0.9 L/min, a specific consumption of 95-99 mg/g, and a pH 6-7, the recovery rate of calcite achieved 88%.To validate the collector′s performances further, bench-scale flotation experiments revealed an enrichment of phosphate ore to 68.74 and 69.44% Bone Phosphate of Lime (BPL).The comprehensive multimodal characterization revealed distinct topog. changes in the calcite surface morphol., observed via AFM.This was followed by characteristic peak shifts in the Raman spectra, indicative of mol.-level interactions.Concurrently, the zeta potential measurements showed significant decreases to -22.32 and -20.95 mV for both POCs, corresponding to a notable enhancement in surface wettability.As a result, carboxylic acids, hydroxyls, and ester mols. were initially found to bind to Ca²⁺ sites on the lattice layer of the calcite surface, followed by the coadsorption of aromatics and hydrocarbon chains via hydrophobic interactions.

Enhanced penstock structural models significantly advance hydropower engineering, yet their increasing complexity introduces challenges. As model interactions intensify, predictability and comprehensibility decrease, complicating the evaluation of model accuracy and alignment with operational performance metrics and safety standards. This issue is particularly pronounced in dynamic modeling, where knowledge gaps hinder straightforward validation via observational data. Traditional techniques for model calibration and validation are becoming impractical, necessitating a strategic approach to prioritize sources of uncertainty related to critical response variability. This study aims to advance our understanding and management of structural variabilities in penstock models by developing a comprehensive, step-by-step Global Sensitivity Analysis (GSA), designed to meet the specific needs of penstock modeling. Illustrated through a free vibration analysis model of a penstock span, this structured methodology begins with Uncertainty Analysis (UA) to identify variabilities, followed by a screening phase using the Morris method to enhance computational efficiency. Subsequent application of multi-method GSA ranks parameter sensitivities, assesses robustness, and provides a comparative evaluation, providing insights into the effective tools for conducting GSA on penstock models. The process culminates with Regional Sensitivity Analysis (RSA), targeting local sensitivities and enhancing understanding of local parameter influences, thereby supporting model adjustments and design optimization. Results from this application characterize model sensitivities for the most prominent mode shapes to specific structural parameters and indicate that these sensitivity outcomes are influenced by variability in parameter spaces and output sub-range definitions. This study provides a practical framework for addressing uncertainties in penstock design, enhancing model accuracy, prioritizing parameters, managing risks, and improving the reliability and efficiency of hydropower infrastructure.

Although the FO process steady state performance has been extensively investigated, there is a huge gap in forward osmosis dynamic studies especially for water desalination applications.In this paper, an appropriate dynamic model was developed based on the phenomena involved in the FO process.For its validation, an exptl. study was carried out using a FO test bench and flat-sheet membrane for two draw solutes (MgCl₂ and NaCl), to measure the water flux, Jw, and the reverse solute flux (RSF), Js.The time evolution of these two exptl. obtained fluxes were compared to those calculated using a dynamic model developed using Python language for both draw solute.This comparison shows that the mean absolute error did not exceed 5.25% for water flux and 5.63% for RSF.The dynamic model can thus be considered reliable when considering exptl. errors.The resulting model can thus analyze the influence of the initial draw solute (DS) concentration on both water flux and reverse solute flux dynamics, and subsequently compare the osmotic performances of MgCl₂ and NaCl based on the specific RSF ratio.The water flux obtained with MgCl₂ is on average 8.23% lower than for NaCl.MgCl₂ nevertheless performed better in terms of reverse solute flux and has been demonstrated to be 28.87% lower than NaCl.The calculated specific RSF ratio is shown to be independent of both time and DS concentration