The performance of gas-liquid mixing processes in mechanically agitated vessels is commonly expressed in terms of the degree of gas dispersion. In fact, the local measurement of mixing parameters provides a more accurate description of the mixing effectiveness, especially for systems containing non-Newtonian fluids. For instance, the fluid flow of complex yield-pseudoplastic solutions is highly affected by the local shear stress, leading to non-homogeneous air distribution throughout the mixing vessel. Coaxial mixers, in turn, have demonstrated energy-efficient characteristics for the non-Newtonian fluids that improve the mixing homogeneity due to the independent rotation of a central impeller and a close-clearance impeller. Therefore, the objective of the present work is to investigate the axial profile of the local gas holdup in a PBT-anchor coaxial mixer containing xanthan gum solutions, which is a biopolymer widely utilized as an emulsion stabilizer, dispersing agent, and thickener. The rheological behavior of the solutions was described by the Herschel-Bulkley model, and the effect of the xanthan gum concentration on the gas holdup distribution was analyzed. Electrical resistance tomography (ERT) was employed to obtain the gas holdup from the conductivity measurements of the mixture in each of the four horizontal planes. It was observed from the results that the volume fraction of the gas phase increased downwards for all biopolymer solutions. Furthermore, a decrease in xanthan gum concentration reduced both the non-homogeneity in the gas distribution and the overall gas volume fraction. In contrast, the larger viscosity gradient resulting from higher xanthan gum concentration enhanced the gas holdup in high shear stress regions, whereas the air dispersion distant from these regions was weakened due to the higher viscous forces.

The economic viability of guayule as an industrial crop for natural rubber production depends largely on the potential valorization of these co-products. According to the studies carried out on the subject, there is a broad consensus on the added value of the resin and bagasse in different fields of application. The process of extracting natural rubber from guayule produces mainly bagasse (±80% of the total dry mass) and resin (±10% of the total dry mass). Among guayule research, the high-value co-products would significantly improve the economic viability of guayule as an industrial crop and offset a substantial portion of the cultivation and processing costs.

According to studies, the resin remains the most fluctuating value, reducing this uncertainty, through future research on resin applications, is essential to the success of guayule as a natural rubber raw material, it finds applications in different industrial fields , such as coatings, varnishes, paints, treated wood, biocontrol agents and controlled release formulations. Bagasse is composed primarily of cellulose, hemicellulose, lignin, and resin, and has a high calorific value, making bagasse a suitable fuel for on-site combustion to produce electricity and thermal energy. Bagasse combustion in this scenario is less complex than the logistics of biofuel production. Resin-containing guayule bagasse has been combined with a plastic binder to make high-density composite panels resistant to termite degradation. In addition, the resinous material can be solvent extracted and used to impregnate the wood with the raw resin extract so that the wood is protected from destructive organisms
guayule bagasse containing resin can modify the soil nature and improve the growth of vegetables compared to de-resinated bagasse.

An in-depth analysis of the flow patterns and mixing dynamics in a twin paddle blender for bi-disperse non-spherical particles were implemented through the use of the discrete element method (DEM) and experiments. This study aimed to explore the mixing efficiency of a double paddle blender containing two different shapes of non-spherical particles. The study focussed on the demonstration of the applicability of the GPU-based DEM model. To achieve this, calibration tests were performed using a classical rotary drum to validate the accuracy of the model. The next step was to examine the impact of various parameters on the mixing performance, including the paddle rotational speed, particle number ratio and vessel fill level. The relative standard deviation (RSD) was employed as a measure of mixing performance. Results revealed that both the rotational speed of the impellers and the particle number ratio had a significant impact on the mixing performance. In addition, it was found that an increase in fill level and a decrease in impeller speed can lead to an increase in total particle contacts, indicating greater mixture compactness. The Peclet number and diffusivity coefficient were calculated in order to gain insight into the underlying mixing mechanism. The results indicated that diffusion was the dominant mixing mechanism, and the best mixing results were seen when the diffusion rates of both cube-shaped and cylinder-shaped particles were nearly equal.

Phenolic compounds are known to be toxic and inflict both severe and long‐lasting effects on both humans and animals. They act as carcinogens and cause damage to the red blood cells and the liver, even at low concentrations. These compounds are important biomedical wastes, and are classified as hazardous substances contaminating groundwater resources. Therefore, the removal of these organics compounds in order to reach the permitted levels before discharging becomes a challenging. Several processes have been developed to remove phenolic compounds from waters, including electrochemical oxidation, redox reactions, membrane separation and photocatalytic degradation. Recently, tendency of phenolic compounds removal involves adsorption and photocatalytic process, using synthetic or natural particles, such as carbon materials and clays. Actually, materials in nanometric scale play an important role in the processes previously mention due to their unique chemical and physical properties. Extensive research has been performed on these compounds resulting in the elucidation of their structure or classification, their sources of entry into the aquatic environment and their reactivity or interaction with other components of the aquatic environment. Significant efforts have been made for the total elimination of phenolic compounds from water before use. This resulted in the development of water treatment technologies including the conventional methods such as activated carbon adsorption, solvent extraction and advanced technologies such as electro Fenton method, membrane‐based separation method, photocatalysis and so on, which have all been successfully used for removal of phenolic compounds from water. Activated carbon is the most promising adsorbent material, presenting high adsorption capacity for many pollutants (dyes, metals etc.). However, the need to turn on more environmental-friendly materials leads to the use of low-cost ones derived from agricultural sources.
The aim of this work is to use environmental-friendly materials (low-cost) as adsorbents for the treatment of biomedical effluents. Potato peels (supplied as wastes from restaurants) were used to produce samples of carbon after pyrolysis. The absorption evaluation was done with a series of absorption-desorption experiments studying major parameters as the effect of pH, temperature, initial drug concentration, contact time and regeneration ability.

Modeling and simulation framework on CO₂ capture process from post-combustion CO₂ capture was developed by a hollow fiber membrane technology. The membrane cell was modeled using Aspen Custom modeler and exported to Aspen Plus software as a membrane unit. Aspen Plus methodology was effectively implemented to estimate the physical and chemical CO₂ absorption parameters by kinetic and thermodynamic models. The membrane cell for the permeation of gas mixtures was custom-built and successfully imported into the simulation tool, as no model block for the hollow fiber membrane was included yet in the commercial package for a process flowsheet simulation. The transport mechanism in hollow fiber membranes is discussed and both empirical and theoretical models are presented for the solution-diffusion theory of gases in membranes. The goal of the modeling of membrane cells is to design and optimize membranes for carbon capture processes. The concept of modeling of membrane process is identified and some of the most important aspects of the simulation of membrane systems are discussed. As the reference, CO₂ flux of more than 700 NL m⁻²h⁻¹ through membrane cell was obtained. Challenges adversely affecting the separation performance of hollow fiber-based gas separation membranes are explained in detail and the significance of incorporating the effect of such challenges into membrane models is clarified.

Temperature excursions and vaccine freezing are results of poor temperature control systems used in vaccine cold chain. The use of medium temperature fridges due to inadequate vaccine refrigerators has had great negative impacts on the coverage of national immunization programs in developing countries, as many vaccines are often wasted due to loss of vaccine potency, thereby leading to wastage of investment. To surmount these challenges, an adapted fridge displays case model using Aquila-based model predictive control strategy for preserving vaccines at the correct temperature range of 2^oC and 8^oC is proposed. Temperature responses using Aquila-based model predictive controller was compared with traditional model predictive controller (MPC) and proportional-integral-derivative (PID) controller. Simulation results show that Aquila-based MPC has better capability in mitigating against the problem of accidental freezing and temperature excursion by keeping the vaccine temperature at 5.8^oC even in the presence of additive disturbances, while the traditional MPC controller could not keep the temperature between the recommended range due to tuning by trial and error, and the PID controller has oscillations for about 4.5hours before settling at 8^oC in the absence of disturbances. All simulations are performed using MATLAB 2020a.

This research studied about the synthesis of green and novel catalyst from waste materials for biodiesel production. An activated carbon (AC) material from palm seed cake (PSK) was soaked with zine chloride (ZnCl₂) and treated with sulfonic acid (SO₃H). The use of a sulfonated palm seed cake (SO₃H-PSK) derived catalyst for the transesterification/esterification of triglyceride (TG) in waste cooking palm oil (WCPO) has been demonstrated. The synthesized SO₃H-PSK catalyst was characterized using powder X-ray diffraction (XRD), Fourier transform infrared spectrometer (FTIR), scanning electron microscopy (SEM), energy dispersive spectrometer (EDS) and Brunauer-Emmet-Teller (BET) method. To study the effects of methanol/oil mole ratio, amount of catalyst, and reaction time, the process of biodiesel production was optimized using a Box-Behnken design (BBD) approach with response surface methodology (RSM). As a result, the optimum reaction parameters found were 12:1 methanol/oil mole ratio, 1 wt.% of the SO₃H-PSK catalyst, and 4 min of reaction time. The synthesized biodiesel from WCPO meets the criteria for standard biodiesel (ASTM D-6751 and EN 14214). The heterogeneous catalyst demonstrates a promising and effective application for biodiesel process especially for feedstocks containing high free fatty acid (FFA) content.

Steam generator liquid level control system (SGLCS) is an important energy exchange equipment in nuclear power plant, and its control performance has an important impact on the safety, economy and efficient operation of nuclear power plant. The performance optimization process of this system has prominent problems such as time consuming, experience dependence and difficulty to achieve the best. In order to improve the performance optimization efficiency of the control system, a SPSA method (CG-SPSA) based on data-driven optimization idea and SPSA method. This method focuses on system performance measurement. Firstly, the dynamic reconstruction mechanism of iterative performance data is designed; Then, the gradient approximation is realized; then, the organic fusion of model gradient approximation and data gradient approximation at the dynamic confidence level is realized, and the optimal estimation of SPSA gradient approximation value is realized. Under the data-driven framework, this method provides a unique idea and implementation mechanism of data-driven and model-driven fusion, which maximizes the use of iterative measurements and effectively improves the efficiency of SPSA method. Simulation experiments show that the traditional SPSA and model-free optimization framework, and can significantly improve the efficiency of the level control performance of steam generator.

The rate of plastic deterioration is currently significantly outpacing the rate, at which plastic waste being produced, leading to a biome-wide imbalance. Biopolymers derived from sustainable raw materials are widely explored as potential alternative packaging materials to increasing the shelf life of fresh produce and processed food. Present work aims to develop polysaccharide based composite films. Sodium alginate and castor oil blended pectin films were developed as per 2⁴ (two-level four-factor) factorial design of experiments. Sodium alginate was used as a stabilizer and film forming agent to enhance the mechanical properties of the films. Castor oil was used as an additive to improve moisture barrier and antimicrobial properties. D-Sorbitol was used as a plasticizer to improve the flexibility of the films. The amount of sodium alginate (25% & 50% w/w), castor oil (10% & 15% w/w) and D-sorbitol (15% & 30% w/w) with respect to pectin and sonication time were chosen as the four factors. Based on our prior optimization studies, all other process variables, such as pH (< 4), drying temperature (60 ℃) and humidity (40%) were maintained constant. The moisture barrier, mechanical, surface hydrophobicity, morphological, thermal stability properties and biodegradability characteristics of each film were studied. All films were thin (~ 0.120 ± 0.004) and transparent (ΔΕ = 8 to 20). The moisture barrier properties improved threefold compared to pure pectin films. The elongation at break increased at least three times. The films were thermally stable at 400 ℃. The melting point of the films increased to 150 ℃ compared to 95 ℃ of pure pectin film. Based on the statistical analysis and analysis of variance (ANOVA), the effect of castor oil (p < 0.05) is more on the moisture barrier property and a combined effect of sodium alginate (p < 0.05) and sorbitol is significant on the mechanical properties.

Fault detection in multi-rate process systems is a challenging task. To make such process plant available till the next shutdown it is essential to detect faults and take corrective measures before they lead to failure. Common techniques used for fault detection of multi-rate systems include threshold-based detectors, statistical detectors, and machine learning-based detectors, one such statistical detector technique is Multiple Probabilistic Principal Component Analysis (MPPCA). MPPCA uses probabilistic PCA to detect fault signals from multiple sensors without down-sampling or up-sampling It considers the inter-dependencies among the sensors and helps in detecting and diagnosing faults in a timely and accurate manner, in this work MPPCA is applied for fault detection of Two-Phase Reactor-Condenser system with Recycle (TPRCR) in which three different classes of measurement are considered. Temperature and pressure measurement are considered as fast rate measurements, Liquid holdups are considered as medium rate and mole fractions are available at slower rates. This measurement data is used for development of MPPCA model using Expectation-Maximization (EM) algorithm. Based on this T² and SPE statistics are developed which are used for Fault-detection in TPRCR system and efficacy of MPPCA method is found to be satisfactory.