Band 20, Heft 3

The performance of proportional plus integral (PI) and proportional plus integral plus derivative (PID) controllers are investigated, using a horizontal tank liquid level as the control object. Additionally, sliding mode controller (SMC) is designed and suggested for the level control of horizontal tank process. Also, the closed loop responses of PI, PID and SMC are analyzed in MATLAB and the response of the horizontal tank model are obtained in different set-point levels. This work presents a SMC approach that improves control accuracy, set-point tracking and robustness in level control of horizontal tank process, where traditional and existing PID controllers are less effective. These results demonstrate that the designed SMC controller markedly reduces settling time and also completely eliminate the peak overshoot compared with responses of PI and PID controllers, and similarly minimizes the values of integral of absolute error (IAE) and integral of squared error (ISE). These findings underscore that SMC provides superior performance compared to PI and PID controllers. Furthermore, SMC offers an improved closed loop performance of level control of non-linear horizontal tank process. It also provides more efficient and stable system responses.

Non-equilibrium condensation (NEC) is a prevalent phenomenon in various industrial equipment, and it can substantially affect their operational efficiency and overall performance. Droplet nucleation and growth is one of the important aspects of NEC and needs to be investigated and studied, whatever affects these parameters. On the other hand, NEC has a considerable impact on the flow pattern and condensation shock causes a sudden change in flow parameters. This study has been conducted with the aim of investigating the impact of inlet pressure (IP) on the flow pattern and two-phase flow parameters. The values of 90 kPa, 95 kPa, 99.98 kPa, 105 kPa, and 110 kPa are considered as the nozzle IP for this investigation, and its impact on the parameters of pressure, temperature, speed, density, droplet radius, liquid mass fraction (LMF), nucleation rate, Number of drops and condensed mass rate. According to the results, as the IP increases, the condensation shock occurs earlier and the LMF in the nozzle increases. As the pressure increases from 90 kPa to 110 kPa, the amount of LMF increases by about 5.7 %, and more LMF is produced in the nozzle. This study provides a good understanding of the impact of IP on NEC.

In this computational investigation, the effects of helical tapering barriers on turbulent air flow through a horizontal circular tube with a constant surface heat flux were examined. The goal was to improve thermal performance and heat transfer. Multiple configurations were examined using the SST k - ϋ turbulence model in ANSYS Fluent 2023. These configurations included two helical tapering heights (2.5–5 mm, 2.5–7.5 mm) and helix ratios ( y  = 2, 3, 4), with Reynolds numbers ranging from (10,000 to 60,000). At Re = 10,000, the configuration with a tapering height of 2.5–5 mm and y  = 2 produced the greatest Nusselt number of 333, which is 151 % higher than the plain tube (Nu = 36). This was achieved due to the installation of helical barriers, which considerably boosted heat transport, nevertheless, in comparison to the plain tube, the friction factor increased by 82 % with this modification. Reducing the helix ratio or tapering height further enhanced both metrics, and increasing the Reynolds number increased the Nusselt number while decreasing the friction factor. All thermal performance factor (TPF) were greater than one, even with the higher flow resistance; the configuration that produced the most thermal enhancement had the highest TPF of 1.62. In particular, for low helix ratios and tapering heights, our results demonstrate that helical tapered obstacles are helpful in enhancing thermal performance.

The present work introduces a new method for forecasting the formation of CH 4 and C 2 H n gases in the gasification of biomass. The K-nearest neighbors (KNN) algorithm is utilized as the base model, while two innovative optimization techniques, Artificial Rabbits Optimization (ARO) and Smell Agent Optimization (SAO), are employed to enhance the overall performance and achieve optimal results. The goal of this investigation is to create a prediction model that can reliably and accurately anticipate the amount of CH 4 and C 2 H n gases produced during the gasification of biomass. By combining the strengths of the KNN algorithm with the optimization capabilities of ARO and SAO, the proposed approach aims to overcome existing limitations in gasification process predictions. The experimental results demonstrate the effectiveness of the combined approach in accurately predicting the gasification process and estimating the quantities of CH 4 and C 2 H n gases produced. The integration of ARO and SAO with the KNN algorithm enables better optimization of the model, leading to improved accuracy and reliability in predicting gasification outcomes. Additionally, the effectiveness of the suggested models was thoroughly evaluated and assessed utilizing performance evaluators. Remarkably, the KNSA (combination of KNN and SAO) model achieved the highest R 2 values of 0.994 and 0.995 for CH 4 and C 2 H n , correspondingly, which demonstrates the effectiveness of the suggested methods. The conclusion of this study contributes to the field of biomass gasification, as it proposed a new methodology that used the KNN algorithm as a base model, further improving its performance through the implementation of new optimization techniques. Further optimizations of the gasification process may now be opened, and a set of insights may be derived from the research for curiosity-driven scholars and practitioners in renewable energy production.

Techniques like extractive distillation and pressure swing distillation (PSD) have been commercially developed to separate azeotropic mixtures. Extractive distillation using conventional solvents offers advantages in achieving high purity levels, but challenges include difficulty in solvent recovery, increased energy consumption, higher costs, and potential negative environmental impact. Selecting appropriate solvents is a challenging task with potential compromises. PSD manipulates pressure to overcome azeotropic points without an entrainer, offering solvent-free operation. Ionic liquids may provide an alternative to conventional solvents in extractive distillation. Five imidazolium, ammonium and pyridinium based ILs have been chosen to investigate their impact on the separation of the selected azeotropic mixtures. The three techniques are employed for seven different (model) azeotropic mixtures to evaluate the commercial feasibility of each process by comparing energy requirements and Total Annual Cost (TAC). Aspen Plus software has been employed to perform a comparison simulation among the processes. This benchmark analysis and process simulation can aid in evaluating the efficacy and feasibility of the possible optimum commercial process in separation. There is no one-size-fits-all technique that provides the best cost-effective and energy-efficient process for every azeotropic separation.

Rising fossil fuel consumption intensifies CO 2 emissions, worsening climate change. Carbon Capture and Storage (CCS) technologies offer a promising solution by securely storing CO 2 in geological formations, mitigating environmental impacts. This paper presents a long-term synergistic study of multiple CO 2 trapping mechanisms in saline aquifers over 200 years and represents a key knowledge gap in the existing literature on CCS. The research was done with advanced numerical modeling using the CMG-GEM software and integrated all the structural, residual, solubility, and mineral trapping mechanisms to find their integrated effect on the efficiency of CO 2 storage. These results show that combined dissolution and mineral trapping increase the storage capacity by about 27 %, equivalent to a 400 % increase over the no-dissolution, no-trapping base case. By integrating these methods, a clearer understanding of the interrelations between various trapping mechanisms was obtained, and an effective tool for optimizing strategies in the sequestration of CO 2 . The complete uncertainty analysis using Monte Carlo simulations for the variability in main input parameters like porosity, permeability, and mineralogical composition is of special note. The approach quantifies the uncertainty over the range of possible results by providing confidence intervals of capacity estimates, enhancing the reliability and broader applicability of the outcomes. This research underlines the long-term stability, environmental safety, and uncertainty quantification of geological CO 2 storage; therefore, it provides practical implications for the design and implementation of CCS projects. This research contributes significantly to climate change mitigation by providing necessary guidance for policymakers and engineers to develop appropriate technology for secure and sustainable CO 2 storage by illustrating the advantages of a multi-mechanistic approach and discussing issues about uncertainties.

The drying of agro-seeds is essential for enhancing product quality and extending shelf-life. This paper explores the diffusion modeling and drying dynamics of ogbono seeds ( Irvingia gabonensis ), providing insights to improve drying processes and energy efficiency. The experiment employed Central Composite Design to assess the impacts of temperatures (40, 50, 60 °C) and seed sizes (small, medium, and large) at a constant air velocity of 1.5 m/s on specific energy utilization, energy efficiency, seed shrinkage, and drying duration. The kinetics of water desorption were examined using the superimposition technique under different conditions. The drying behaviour was best represented by the Avhad and Marchetti model ( R 2 = 0.9933, ε r m s   ${\varepsilon }_{\mathscr{r}\mathscr{m}\mathscr{s}\hspace{0.17em}}$ = 0.0120, χ 2 = 0.0004), revealing that drying time dropped from 240 to 180 min as the temperature increased. Shrinkage tests indicated considerable morphological defects in larger seeds due to greater porosity, whilst smaller seeds demonstrated higher structural resilience. Effective moisture diffusivity dropped by 42.5 %, from 1.21 to 3.52 × 10 −10  m 2 /s. The activation energy ranged from 55.91 to 80.68 kJ/mol. Specific energy consumption (1.05–1.60 kWh) and energy efficiency (60–85 %) exhibited a perfect balance between product quality and energy input. Under the optimal conditions of 60 °C and small seed size, the specific energy of 1.075 kWh, 82.52 % energy efficiency, 8.65 % seed shrinkage, and 46.25 % drying time reduced to 129 mins was achieved. These outcomes established a yardstick for sustainable and energy-efficient ogbono seed drying. The study provides potential pathways to work in sensor-based hybrid power crop dryers and their applications to other commercially valuable seeds.

Olive pomace, the solid by-product derived from the olive oil extraction process, is a rich but still underutilized source of bioactive polyphenols. Among the proposed recovery technologies, solvent extraction seems to be the simplest and economically viable method to achieve this purpose. In this study we investigate the recovery of polyphenols from olive pomace by a one-step extraction procedure using aqueous ethanol as solvent, with the aim to model and optimize the proposed process. A central composite rotatable design (CCRD) comprising 2 4 factorial points, eight axial points and six replicates was used to evaluate the effects of temperature (T), extraction time ( E ), liquid-to-solid ratio ( R ) and ethanol concentration in the solvent ( C ) on the extraction yield. The experimental results were correlated by a reduced second-order polynomial model. The statistical analysis of the results showed that all the main factors ( T , E , R , C ) and two binary interactions ( T – E , R – C ) had significant effects on the extraction yield. Under the best conditions ( T  = 70 °C, E  = 240 min, R  = 48 mL/g, C  = 50 %) more than 95 % of the extractable polyphenols were recovered. A mechanically stirred batch extractor operating under these conditions was used to produce dry extracts with a polyphenol content of 69.46 mg GAE (gallic acid equivalents) per gram and an antioxidant activity of 32.72 mg TE (Trolox equivalents) per gram. Overall, the results obtained indicate that polyphenol-rich extracts suitable for a variety of food and non-food applications can be easily obtained from olive pomace by subjecting it to the optimized extraction treatment.