Papers by Keyword: Optimization

Abstract: The production of high-quality and long-lasting products requires the application of materials with specific properties in their production. Therefore, the share of application of materials with high hardness and strength has been increasing recently. This encourages many researchers to focus their development on materials with specific properties. These materials, which are characterized by specific properties, include sintered carbides. Therefore, research was conducted with the aim of obtaining relevant dependencies of the influence of the chemical composition of sintered carbides with a Co binder on their selected mechanical properties. As part of the research, significant dependencies of the influence of the percentage of the Co bonding element in the sintered carbide as well as the grain size on its hardness, flexural strength and fracture toughness were obtained. It was found that with an increasing proportion of the Co bonding element, hardness decreases and at the same time flexural strength and fracture toughness increase. At the same time, with increasing grain size, hardness and flexural strength decrease, while fracture toughness increases. The obtained data also provide suitable data for optimizing the mechanical properties of sintered carbides and drawing complex conclusions in several important contexts.

Abstract: The thermal swing adsorption process has been demonstrated as a promising technology for the biogas upgrading process, with ease of integration into renewable electricity sources. This study examined the influence of particle radius, regeneration temperature, and purge-to-feed flow rate ratio on the biogas upgrading process. A dynamic simulation model was developed to study the carbon dioxide capture process. Activated carbon pellets derived from coconut shells were used as the adsorbent material. The adsorption and desorption processes were based on single-component methane and carbon dioxide adsorption isotherms fitted to the Langmuir-Freundlich model. The developed simulation model was validated against experimental data. A particle radius, regeneration temperature, and purge-to-feed flow rate ratio range of 1 to 9 mm, 77 to 227 °C, and 0.1 to 0.7, respectively, were adopted for the parametric analysis. Multi-objective numerical optimization was performed using the response surface methodology. The results indicated that the purge-to-feed flow rate ratio had the highest contribution to the methane purity and recovery models of 92.37 % and 99.90 %, respectively. The optimal methane purity and recovery values obtained were 82.12 % and 37.21 %, respectively, achieved at a particle radius of 9 mm, a regenerating temperature of 227 °C and a purge-to-feed flow rate ratio of 0.4152.

Abstract: Ethiopia’s agriculture, which is mainly rainfed and managed by smallholder farmers, faces significant productivity challenges due to limited rainfall during a short rainy season. Solar-powered water pumping offers a sustainable and efficient alternative for dry-season irrigation by harnessing the country's abundant solar energy potential. This study presents a novel approach to optimizing solar-assisted water pumping systems by evaluating the hydraulic and electrical performance of both centrifugal and helical rotor pumps under varying flow rates and solar irradiance levels. The findings indicate that system efficiency peaks at specific heads depending on solar irradiance: at 450 W/m², a head of 16 meters achieves 33% efficiency; at 750 W/m², a head of 20 meters yields 34%; and at 950 W/m², a head of 28 meters achieves 32% efficiency with a centrifugal pump. Notably, the helical rotor pump demonstrates superior performance for applications requiring consistent pressure at low to moderate flow rates. This study provides valuable insights into the head-flow relationship, optimal operational conditions for various solar irradiance levels, and comparative performance metrics of different pump types, offering practical guidelines for enhancing the efficiency of solar-powered irrigation systems.

Abstract: Amongst various strategies to mitigate the environmental impact of non-degradable polymers, the integration of Cork with fossil fuel-derived Nylon is considered an attractive option to develop a lightweight, strong composite. To optimize the integration of these materials for processing as 3D printed structures requires the exploration of functional compatibilizers to enhance the homogeneity and 3D printability of the Nylon-Cork composite. In this paper, Nylon-12 (PA-12) was mixed with cork in varying melted compositions using one coupling agent/stabilizer/compatibilizer, namely: 3-aminopropyl triethoxysilane (APTS), to improve the interfacial bond between the components and amenability for 3D printed composite structures. This paper examines the characteristics of this composite using scanning electron microscope (SEM), rheology experiments and differential scanning calorimetry (DSC). These findings are used to understand and explain the ensuing 3D printed characteristics using the APTS compatibilizer and Nylon-Cork ratios. This work is expected to be critical for developing low-density engineering products using PA-12-Cork composites and for sustainable processing, using 3D printing technologies.

Abstract: Boring process, also referred to internal turning, is commonly used to machine critical features of landing gear components like struts, brackets, and main cylinders. Over the past years, extensive research efforts have addressed the stability of the process by developing instrumented boring bars and advanced monitoring techniques. However, although the surface integrity characteristics, particularly the residual stresses, are crucial for structural components, it hasn’t been considered and its evolution over the boring conditions still not well understood. Hence, the present paper proposes a comprehensive investigation on the effects of boring conditions on the surface integrity of the aluminum alloy 7175-T74 commonly used in landing gear components. A parametric analysis has shown that lower cutting forces and surface roughness can be achieved using a larger insert nose radius. It was also found that feed rate, cutting speed and depth of cut experienced strong interaction effects with the machining mode (dry/wet) regarding the resultant cutting force and surface roughness. Results have also shown that wet boring conditions generated compressive residual stresses. An optimal boring condition was obtained using Grey relational analysis (GRA) – Taguchi method. Further investigation is required to refine the obtained optimal machining condition by considering the GRA results and the parametric analysis outcomes.

Abstract: The integration of renewable energy sources, such as photovoltaic (PV) and wind turbines, has gained significant attention due to the growing demand for reliable and clean energy solutions. This paper presents a comprehensive modelling and optimization approach for hybrid PV and wind turbine systems to maximize system performance at the same time minimizing cost and surplus energy. The proposed model incorporates detailed mathematical formulations that capture the interactions between PV modules, wind turbines, and the storage system which is a battery energy storage system (BESS). The model also considers economic factors and methods to reduce the surplus energy of the system. The optimization scheme utilized the African vulture optimization algorithm (AVOA). The AVOA is a nature-inspired meta-heuristic algorithm created based on the hunting patterns of African vultures. In addition, the AVOA was constructed to handle a multi-objective optimization with size and costs as the objective functions. The optimized system provides the best system size to support the electricity supply of a coastline town (4.7231°N, 6.77881°E). The optimized system can deliver 41.80 GWh of energy annually, meeting 98.3% of the energy demands of the community; while the optimized system has a cost savings of 45.11%, with 92.9% penetration. The work provides valuable insights for system designers, energy planners, and policymakers in their efforts to promote renewable energy integration and address the challenges associated with the transition to a low-carbon future.

Abstract: The reliability of the distribution networks has been threatened by the disturbances which have occurred on the said networks and which have led to supply interruptions to customers. From the analysis of the faults that have occurred on these networks, it emerged that the most recurring disturbances are faults originating from external causes (atmospheric overvoltages, violent winds) and which represent 90% of the causes, transient faults (70%) and broken conductors (40%). The study of the reliability indices showed that the most disturbed departures are the MV departures from Ouidah, ITTA, Calavi and Togba whose SAIDIs are respectively 15.64; 13.9; 10.05; and 8.52. The optimization of the maintenance plan by genetic algorithms of the NSGA II type made it possible to identify the number of inspections which is 5 days and 11 days respectively during the rainy season and the dry season. The inter-inspection period related to these inspection periods is (21 days). This study led to the proposal of an optimal plan taking into account climatological criticalities and the aim of which is to reduce these disturbances which are more untimely in the rainy season. The resolution of the reliability problem by genetic algorithms of the NSGA-II type made it possible to deduce that the undistributed energies are reduced by 92.22% on the departure of Togba, 93.43% on the departure of ITTA and 95, 54% on departure from Ouidah. This energy could have brought Beninese Electricity Company (SBEE) a sum of nine hundred fifty-one million eighty-four thousand two hundred and fifty CFA francs (951,084,250 FCFA) on only three MV departures. This optimization denotes the technical and financial interest of SBEE by focusing more on strategies for reducing disruptions on its networks while giving priority to the rehabilitations, effectiveness and efficiency of its maintenance plans. The methodology used is efficient and effective and can allow SBEE to make substantial savings which will enable it to make a reinvestment in its distribution networks.

Abstract: The knee joint transmission mechanism of quadruped robots usually adopts a fixed transmission ratio. Because the output torque of the knee joint fluctuates greatly during the support phase, a higher requirement is set for the torque output capability of knee joint actuator. Experimental data of multiple walking gaits was collected and parameters of the four-link transmission mechanism with strut structure for the knee joint were optimized using the complex method. In order to reduce the fluctuation of the output torque of the knee joint actuator, the knee joint is expected to maintain a higher transmission ratio at angles with higher torque output requirements. The optimization result shows that due to the limitations of the four-link mechanism, the knee joint has a larger transmission ratio at smaller angles and the maximum output torque angle, and a smaller transmission ratio at larger angles. During the support phase, the output torque of the knee joint actuator is significantly smoother, which can meet the use requirements to a certain extent.

Abstract: This paper presents a comprehensive exploration of various methodologies and techniques aimed at enhancing tool path planning in CNC machining. It discusses differential vector optimization for generating smooth trajectories, kinematic constraint adjustment to optimize cycle time and minimize cornering errors, and equidistant tool path planning for curved freeform surfaces. Additionally, the paper delves into the integration of reinforcement learning (RL) algorithms, such as dynamic search strategies and deep RL models, to optimize tool path planning. Results showcase significant improvements in convergence rates, learning efficiency, and navigation performance with RL algorithms. Moreover, the synergy between RL and traditional optimization methods, like Artificial Potential Field theory, is highlighted, showing promise in addressing challenges in static workspaces. The paper also discusses the evolution of deep RL techniques over time, suggesting continual advancements in optimizing tool path planning. Overall, the findings underscore the critical role of advanced planning algorithms and RL techniques in enhancing CNC machining processes, paving the way for further advancements in manufacturing efficiency and accuracy.

Abstract: The thermal model of a permanent magnet motor (PMM) is investigated in this study using the lumped parameter thermal approach to calculate temperature variation at steady-state and transient conditions. The temperature variation of the motor components over time under various loads is investigated. The proposed thermal model was constructed with the MATLAB code. The thermal characteristics of the motor are examined using the simulation results. The optimization and sensitivity analysis are done using the response surface method (RSM) by design expert software. It can be seen that increasing the load and time increases the temperature of all parts in the machine. Also, point multiplication with 0.998 desirability is presented, which has the best efficiency with the lowest temperature.