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Abstract: Abstract The shear behaviour of natural joints generally exhibits anisotropy due to variations in morphological characteristics. The anisotropic shear behaviour of natural joints mainly determines the rock mass stability. It is improbable to sample a large number of natural joints with same surface morphologies in the field. In this study, 3D laser scanning and 3D engraving techniques were adopted to reconstruct natural joints in the laboratory. In the reconstruction process, a series of trial and error engraving tests were conducted due to the lack of engraving resolution evaluation and engraving parameter selection methods. Both 2D and 3D characterization methods were used to quantitatively assess the engraving resolution. A method was proposed to determine the interval path based on the cone angle of the cutter. A series of engraving tests were conducted to study the effect of the path interval on the engraving resolution and to verify the proposed method. The results indicated that the engraving path interval should not be too large (> 0.20 mm) or too small (< 0.10 mm), which could result in a strip between adjacent engraving paths or overengraving, respectively. The natural joints in the sandstone specimen could be successfully reconstructed when the optimal cutter radius and path interval were 0.40 and 0.10 mm, respectively. The root mean square error (RMSE) of the profile height between the original and reconstructed joints was less than 0.10 mm. The difference in the 3D roughness \(\left( {\theta_{{{\text{max}}}}^{*} /\left( {C + {1}} \right)} \right)\) between the original and engraved joints was less than 0.5. The methods proposed in this study can be employed to accurately assess the engraving resolution and to quickly determine reasonable engraving parameters. In this way, natural joints can be reconstructed with high engraving resolution. The anisotropic shear behaviour of natural joints can be suitably investigated in the laboratory. PubDate: 2023-12-04
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Abstract: Abstract According to the National Association of Corrosion Engineers, erosion–corrosion costed the world economy approximately 2.5 trillion in 2020. In general, erosion precedes corrosion and both processes accelerate each other leading to major shutdown and maintenance costs. This research numerically investigates the erosion behavior of an electro-hydraulic servo-valve, which serves as a critical component in automation in industrial production systems. Furthermore, this study thoroughly investigates the cavitation phenomenon at various inlet pressures, first monitoring erosion without cavitation effects and then performing a comparative analysis of erosion rates in the presence and absence of cavitation. The effect of particle size, flow rate, and material hardness on erosion rate is also studied. The results show that erosion is highly concentrated at the shunt wedge region and is heavily influenced by particle size and flow rate; additionally, decreasing the hardness of the material results in lower erosion rates. The outcomes of this study are valuable for manufacturers looking to improve the performance of deflector jet servo-valves (DJSV) by addressing erosion concerns. This work provides a significant contribution by examining erosion mechanisms in electro-hydraulic servo-valves and quantifying the impact of various parameters on erosion rates, thereby providing valuable recommendations for manufacturers. PubDate: 2023-12-04
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Abstract: Abstract The laser ablation technique was utilized to fill the carboxy methyl cellulose (CMC) solution with zirconium dioxide (ZrO2) and copper oxide (CuO) nanoparticles with different concentrations. Different techniques have been used to study the physical behavior of fabricated compositions. CuO has shown different peaks at related to the monoclinic phase of the prepared CuO NPs lattice constants (JCPDS No. 02-1225). According FTIR results, ZrO2 has exhibited vibrating bands at 460 cm−1, 477 cm−1, 670 cm−1, and 690 cm−1 which are corresponding to Zr–O vibration. In addition, CuO has shown vibrating bands at 439, 494, and 594 cm−1. The dielectric properties have been investigated. The TGA results showed that the sample CMC-ZrO2-CuO/20 min has excellent thermal stability as the weight loss is 36% of its initial weight at 796 °C. The optical and electrical characterization showed that the addition of ZrO2 and CuO has changed and enhanced the electrical characterization of CMC. The enhancement in electrical conductivity of the system encourages it for electrical applications. PubDate: 2023-12-03
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Abstract: Abstract Drag reduction plays an essential role in the nuclear industry and has been an area of interest for many researchers. Accordingly, in the present study, an experimental investigation has been carried out on the effect of a drag reducing polymer (DRP) on the flow characteristics through a serial arrangement of flow restricting orifices with different diameter ratios and spacing. Experiments were performed on both single and double orifice arrangements in a 0.0254 m diameter, horizontal acrylic pipe. These experiments were done both with and without a DRP and used a particle image velocimetry (PIV) technique. A water-soluble DRP was used as an example of a synthetic high molecular weight polyacrylamide. The flow using the DRP was characterized by a comparatively smaller circulation zone downstream of the orifice, as well as lower local velocity values. It was found that the pressure drop through the orifice was reduced by approximately 8–22% when a DRP was used. In addition, the percentage reduction in the pressure drop was found to be considerable in lower Reynolds number flows than for higher Reynolds number flows. As well, the reduction in the pressure drop was found to be independent of the tested polymer concentration between 51 and 125 ppm. Moreover, the two-phase pressure drop was greater than the single-phase pressure drop at the corresponding liquid superficial Reynolds number. However, the percentage of drag reduction while using a DRP in two-phase flows was found to be much smaller than for cases with a single-phase flow. PubDate: 2023-12-01
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Abstract: Abstract Drilling fluids are crucial for the safe and effective extraction of hydrocarbons from deep petroleum reserves. Lubricating, suspending, and conveying drilled cuttings to the surface are some of the functions of drilling fluids. Their performance depends on lubricity, fluid loss (FL) control, and rheology. Nanoparticles (NPs) have emerged in the oil and gas industry as an efficient fluid additive to modify and stabilize the properties of drilling fluids. NPs are thermally, chemically, and physically stable in drilling fluids; however, field data show they are inefficient at reducing drill string wear. Graphene nanoplatelets (GNPs) are now a useful drilling fluid agent because of their small particles with high specific surface area, good dispersion, high thermal and electrical stability, and their ability to lower stress and wear on the drill string. Thus, this study examined GNPs in drilling fluids, including surface modification methods and their effects on rheology, FL management, and lubricity. The unique properties of GNPs that make them a potential game-changer in drilling fluid are highlighted. The techniques used to modify GNP surfaces to improve drilling fluid compatibility, stability, and dispersion were also addressed. The broad study of laboratory GNP-modified drilling fluids is the central focus of this review. A scrutiny of the mechanisms by which GNPs influence the rheological behavior of drilling fluids and their impact on drilling efficiency and wellbore stability was also highlighted. Beyond laboratory tests, GNP’s real-world applications and commercialization possibilities were examined, taking economic and environmental considerations into account. Comparative examination of methods and results helps optimize GNP-enhanced drilling fluids. Small concentrations of GNPs (0.1–2.5 g) increased the base fluid lubricity and rheology. They also reduced the FL by 40–89%. Due to hydroxyl groups on clay surfaces, GNP has a strong affinity for organophilic clays. The challenges and limitations of GNP-modified drilling fluids were highlighted, along with future research directions. Finally, using GNPs as a fluid modification agent may improve drilling fluid lubricity, FL control, and rheology. These attributes will improve oil and gas drilling safety and efficiency. This review consolidates information and lays the groundwork for this growing field's study and innovation. PubDate: 2023-12-01
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Abstract: Abstract The clean and abundant nature of photovoltaic technology makes it eminent among other renewable energy sources and to obtain the best benefit from these sources, an efficient maximum power point tracking technique is needed that can produce the required output even under varying environmental conditions. This work deals with the development of a global maximum power point tracking technique combining bio-inspired algorithms and one-cycle control which helps in effective tracking even under partial shading conditions. This technique generates signals for the KY converter from the duty cycle obtained from bio-inspired algorithms. The voltage at the output of the photovoltaic panel is fed to the load through KY converter. The analysis of the system is carried out using resistive load under different patterns of the photovoltaic array using particle swarm optimization, flower pollination and flying squirrel search optimization algorithms through simulation and experimentation. The performance indices like tracking speed, tracking efficiency and steady-state oscillations are taken for comparison with the existing systems without one-cycle control, and the results indicate its capability in GMPP tracking with an average efficiency and tracking time of 99.1% and 0.13 s, respectively. PubDate: 2023-11-30
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Abstract: Abstract We present the successful synthesis of a biogenic ZnO/CuO/Fe2O3 nanocomposite using an aqueous leaf extract of Ocimum Basilicum L. The confirmation of biosynthesis was achieved through UV–Visible spectrophotometry (UV–Vis), which provided evidence of ZnO/CuO/Fe2O3 NC formation. Scanning Electron Microscopy further confirmed the nanoscale size of the NC, measuring at 65 nm. X-Ray Diffraction analysis revealed a hexagonal structure for ZnO and a monoclinic structure for CuO. The successful synthesis of the environmentally friendly ZnO/CuO/Fe2O3 NC was further verified using Fourier transformed infrared (FT-IR) spectroscopy, which identified the functional groups present in the composite. Notably, the ZnO/CuO/Fe2O3 NC demonstrated exceptional degradation capabilities for toluidine blue (TB), p-toluidine (PT), and m-Toluidine (MT), with degradation rates of 99%, 99.1%, and 99.7%, respectively, within a reaction time of 120 min. The reaction kinetics followed a pseudo-first order model, with rate constant (k) values of 0.0314 min−1 and 0.0189 min−1 for TB and PT, respectively. This high rate of dye degradation can be attributed to the low band gap of the NC, which was determined to be 1.44 eV for the indirect bandgap. Furthermore, the nanocomposite exhibited excellent degradation reusability, maintaining a high degradation rate in each cycle. PubDate: 2023-11-30
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Abstract: Abstract This paper proposes a novel, robust flight control system using adaptive nonlinear sliding mode control for a quadrotor UAV in the presence of parametric uncertainties and aerodynamical disturbances. The proposed control system is based on a proportional derivative sliding surface combined with a non-singular fast terminal sliding mode control to enhance the tracking accuracy and reduce the chattering influence. Moreover, an adaptive mechanism is proposed to approximate the unknown upper limit of external disturbances/uncertainties. The Lyapunov criteria is used to prove the closed-loop stability and calculate the adaptive mechanism. The proposed adaptive PD-NFTSMC (APD-NFTSMC) can cope with the negative influence of modeling uncertainties, external disturbances, and measurement noise, allows null error in the steady state, and solves the chattering problem. Moreover, intensive simulation experiments under various external conditions are carried out to highlight the sovereignty of the developed control approach. Finally, comparisons with some well-known control techniques are performed to show the usefulness, smoothness, and robustness of the proposed APD-NFTSMC strategy. PubDate: 2023-11-29
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Abstract: Abstract The demand for a quick response from cloud services is rapidly increasing day-by-day. Fog computing is a trending solution to fulfil the demands. When integrated with the cloud, this technology can tremendously improve the performance. Like any other technology, Fog also has the shortcoming of limited resources. The difficulty of efficient scheduling of tasks among limited resources to minimize makespan and energy consumption, while still guaranteeing appropriate execution cost, continues to be a significant issue for research. Hence, this study introduces a Differential Evolution-Grey Wolf Optimization (DE-GWO) technique to enhance the scheduling of scientific workflows under cloud-fog settings. The objective of the proposed DE-GWO algorithm is to mitigate the issue of slow convergence and low accuracy that is often seen in the classical GWO algorithm. The DE method is chosen as the evolutionary pattern of wolves to speed up convergence and enhance GWO’s accuracy. This study further formulates a weighted sum based objective function which incorporates three criteria, namely makespan, cost and energy consumption. In this study, the DE-GWO technique is evaluated and compared with many conventional and hybrid optimization algorithms. The simulations use five scientific workflows datasets which includes Montage, Cybershake, Epigenomics, LIGO and SIPHT. The DE-GWO algorithm demonstrates superior performance compared to all conventional algorithms across several scientific workflows and performance criteria. The methodology has a commendable level of competitiveness when compared to other methods, since DE incorporates evolution and elimination mechanisms in GWO and GWO retains a good balance between exploration and exploitation. PubDate: 2023-11-29
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Abstract: Abstract A numerical simulation of the film blowing process is performed. The Phan–Thien and Tanner (PTT) constitutive equations with quiescent and flow-induced crystallization effects are considered with proper boundary and initial conditions. The PTT model is employed both for molten and crystallized polymer. Modeling of crystallization is done with nested Schneider rate equations and the Kolmogorov–Avrami model. The current model can predict the shape and size of the bubbles, as well as their temperature, stress, space filling and morphological changes for given process conditions. The study focuses on investigating the impact of process conditions on the mechanical response of the blown film, as well as on the morphological structure of the crystallizing molten polymer. It is observed that the axial stress increases at a faster rate compared to the circumferential stress with increase in draw ratio. The trend is reversed for increasing blow-up ratios. Increasing the draw ratio does not result in significant improvement in the quiescent contribution to the crystalline structure, but it leads to a decrease in the flow-induced contribution. Increasing blow-up ratio leads to increase in total space filling and the flow-induced component of the crystalline structure. Finally, three heat transfer coefficients chosen from the literature are compared. It is observed that the model choice is not critical for higher draw ratio values, but for low and moderate values, detailed investigations are required. The presented model enables accurate prediction of both the morphological structure and mechanical properties of semicrystalline polymers in a film blowing process. PubDate: 2023-11-29
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Abstract: Abstract Cognitive load detection using electroencephalogram (EEG) signals is a technique employed to understand and measure the mental workload or cognitive demands placed on an individual while performing a task. EEG is a noninvasive method that records fluctuations in brain activity at different cognitive load levels. The publicly available multi-arithmetic task EEG dataset was used. This study introduces a novel approach to detecting cognitive load by utilizing both the 1D-EEG signal and its various time–frequency (T–F) representations as 2D images. The signal underwent preprocessing, including artifact-free segmentation using filters and subsequent normalization, before being fed into a bidirectional long short-term memory (Bi-LSTM) model with different optimizers for classification. It was trained and fine-tuned to achieve high accuracy. Remarkably, our proposed method demonstrates promising performance even with short EEG segments as 4 s. Through 10-fold cross-validation, we achieved an accuracy (Ac%) of 99.55 and 99.88 using 5:5 and 8:2 data splits, respectively. Furthermore, this manuscript includes subject-wise cognitive load detection, providing valuable insights into individual cognitive processes. This approach enables targeted interventions, performance optimization, and mental health monitoring across various domains. For 36 subjects, an average Ac% of 85.22 was attained. Notably, the spectrogram T–F conversion-based 2D image, coupled with a Bi-LSTM classifier and Adam optimizer, outperformed previous state-of-the-art techniques in terms of evaluation metrics. PubDate: 2023-11-29
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Abstract: Abstract An axial flow circulating pump (AFCP), as a key facility of the large vessel power system, is designed for conveying cooling water of the power system. The pump will be rotated actively under the drive of motor when the vessel is navigated at a low speed, which is called the pump operating condition (POC). Besides, it will be rotated passively under the drive of Inlet flow fluid energy in the case of the vessel at a high speed, which is called the unpowered driven condition (UDC). It is worth noting that the characteristics of internal flow, energy generation and dissipation laws of the AFCP are varied under UDC and POC. This paper analyzes the energy transfer laws of the AFCP under UDC and POC using the modified PANS model and energy conveying theory. Pressure propulsion power (accounting for 82.6%) is a primary factor affecting energy conveying, while Lamb vector divergence and enstrophy (accounting for 17.4%) have limited effects on energy conveying, according to the research findings. Moreover, more intense energy generation and dissipation can be found under UDC with a rising proportion between Lamb vector divergence and enstrophy. PubDate: 2023-11-29
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Abstract: Abstract Steady-shear rheometry equipped with the perfect circular geometry has been used for decades to characterize the viscous characteristics of EOR polymer systems. Recently (Azad in SPE J, 2023), they have been successfully used to characterize the shear thickening characteristics of higher Mw (molecular weight)-higher elastic polymer systems. However, circular geometry fails to thicken the low Mw-lesser elastic polymer systems that exhibited thickening in consolidated porous media. Despite the fact that the different geometries could impose a different deformation, no effort was made to study the effect of non-circular geometry on their rheological behavior. This paper addresses this gap. The results indicate that non-circular geometry not only thickens the higher Mw-elastic systems strongly, but also the lower Mw-lesser elastic systems. Compared with concentric cylinder (CC) geometry, non-circular geometry better predicts the nonlinear viscoelastic properties of polymer systems especially those characterized by low Mw-low salinity-high concentration in porous media. However, CC appears to characterize the Newtonian behavior well and thereby suggests that the combination of both geometries could improve the selection criteria for viscoelastic polymer EOR applications. PubDate: 2023-11-28
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Abstract: Abstract Reusing waste materials presents a significant challenge for researchers across the globe. One of the most prevalent waste materials found in all communities is waste glass, as it plays a substantial role in various aspects of human life. Numerous experiments have been conducted to incorporate waste glass as a raw material in concrete and mortar, serving as a replacement for components like coarse aggregate, sand, or even cement. The most efficient utilization of waste glass appears to be when it is used as a partial substitute for cement, primarily due to its contribution to the pozzolanic reaction and its ability to enhance the compressive strength of mortar and concrete. This article is dedicated to reviewing prior experimental work on the use of waste glass powder as a partial replacement for cement in mortar. These studies have demonstrated that the size and chemical composition of waste glass powder are crucial factors in determining its impact on various properties of mortar. Additionally, experimental data have been collected and employed to propose a statistical model for predicting the compressive strength of mortar, taking into account all independent variables that influence strength. Two modeling techniques, multi logistic linear regression (MLR) and artificial neural network (ANN), were compared, with ANN emerging as the more effective model. This conclusion is supported by the fact that ANN achieved an R-squared value 30% higher than that of MLR, and the performance indices (SI values) for both training and testing data were equal and below 0.1, indicating its superior predictive capability. PubDate: 2023-11-28
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Abstract: Abstract We have successfully synthesized ZnFe2O4/SiO2—Morus alba L. nanoparticles as a drug delivery agent. The nanostructural and optical properties of ZnFe2O4/SiO2—Morus alba L. were evaluated using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy–energy dispersive X-ray (SEM–EDX) spectroscopy, transmission electron microscopy (TEM), and ultraviolet–visible spectroscopy. Antibacterial and drug delivery tests were conducted to examine the antibacterial activity and drug delivery performance of the nanoparticles, respectively. The peaks in the XRD patterns indicated the existence of ZnFe2O4 and SiO2 phases at 2θ = 35.4° and 22°–28°, respectively, in the sample. Meanwhile, the FTIR spectrum showed the functional group of ZnFe2O4—Morus alba L. at wavenumbers of 400–600 cm−1 and Si–O–Si at 1086 and 950 cm−1. The Si–O–Fe peak was also detected at 541–575 cm−1. The calculated bandgap energy was in the range of 3.003–3.218 eV. The TEM and SEM images revealed that the particle size varied in the range of 28.7–47.3 nm and confirmed the formation of a composite. The samples exhibited excellent antibacterial activity and inhibited the growth of S. aureus and E. coli by up to 72% and 78%, respectively. The samples also possessed a desirable doxorubicin (DOX) loading, indicated by the appearance of DOX absorption peaks at wavelengths of 200–250 nm and 450–550 nm. Herein, the increase in SiO2 composition can speed up the DOX release process. Thus, the synthesized samples in this work meet the riteria for drug delivery application. PubDate: 2023-11-28
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Abstract: Abstract Herein, a convenient and environment-friendly reduction strategy was employed to attach silver nanoparticles onto ceria nanorods (AgCe). Nanorods were synthesised through a green chemistry approach with varied silver contents and Citrus maxima peel extract as a reducing agent. The resulting AgCe nanocomposites were evaluated for their efficacy in reducing methyl orange (MO) at ambient temperature by employing NaBH4 as a protonating agent. The as-prepared samples were characterised by X-ray diffraction, Fourier transform infrared spectroscopy, X-ray energy-dispersive spectroscopy, Raman spectroscopy, Brunauer–Emmett–Teller method, and high-resolution transmission electron microscopy. The as-prepared sample exhibited outstanding activity on the catalytic reduction of MO, and the synergistic effect between Ag nanoparticles and CeO2 nanorods was proved. Silver nanoparticles were formed and dispersed well on the surface of ceria nanorods. Based on the UV–Vis results, the activity of the samples with silver was superior to that of pure ceria. The 0.2AgCe sample was the most effective when the catalyst concentration was 0.08 g/L, and the molar ratio between MO and NaBH4 was 1/200. The entire catalytic reduction was thought to follow pseudo-first-order kinetics. Hence, Ag nanoparticles decorated on CeO2 efficiently offered excellent catalytic efficiency and stability in MO reduction and that the catalyst was suitable for practical applications, such as wastewater treatment. PubDate: 2023-11-28
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Abstract: Abstract Engineered geopolymer composites (EGC) have emerged as a more environmentally friendly alternative to conventional engineered cementitious composites (ECC). These composites offer high mechanical and durability features. However, there is a lack of research on EGC, particularly with basic oxygen furnace (BOF) slag as a precursor and iron ore tailings (IOT) as a partial replacement to fine aggregate. Despite their effectiveness as industrial waste products in conventional concrete, this study aimed to determine the optimal compositions of fly ash (FA), steel fibres (SF), and IOT by varying their percentages. Overall, 150 mix combinations were tested, including six binder combinations, five combinations of fine aggregates, and five percentage variations in SF. Finally, one optimum mix was selected for each binder combination, based on the ultimate compressive strength values corresponding to the six optimal mixes. The compressive strengths of all the mixes were evaluated at both 7 and 28 days of curing, involving three replicate samples after oven curing (initial 24 h) followed by subsequent ambient curing until their respective ages. The highest observed compressive strength after 28 days was 41.77 MPa for 50 mm cubes. This strength was achieved with a composition of 60% FA, 1.5% SF, and 45% IOT. An increase in IOT percentage led to a nearly linear increase in strength, while the strength peaked at 1.5% for steel fibres. The addition of BOF slag significantly enhanced the compressive strength compared to mixes with full FA. A 40% fly ash replacement with BOF slag resulted in an average strength that was 39% higher than the combination with 100% fly ash. However, the strength growth decreased after a 10% replacement. Analysis of variance was conducted using the design of experiments methodology to determine the significance of the parameters and their interactions. All three independent parameters were found to be statistically significant, while their interactions were not. Utilizing Taguchi’s analysis method with the L25 orthogonal array, it was concluded that IOT percentage was the most influential parameter. PubDate: 2023-11-28
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Abstract: Abstract Tight sandstone reservoirs are prominent in the lower Kepingtage formation in the Shuntuoguole area of the Tarim basin. While previous research points to a discontinuous accumulation mode via faults leading to oil and gas concentration in structural highs, our findings unveil increased complexity in the oil system due to the presence of “quasi-continuous” sand bodies. This complexity underscores the emergence of a high porosity and permeability accumulation model in the tight sandstone, marking the first identification of two distinct oil and gas accumulation modes in the northern Shuntuoguole area. The intricate migration pathways and accumulation patterns echo the inherent reservoir heterogeneity, a hallmark of marine tight oil accumulations. Consequently, future explorations and developments should incorporate both the conventional fault-controlled and the quasi-continuous tight sandstone distribution models for a comprehensive assessment. PubDate: 2023-11-28
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Abstract: Abstract Flexible links possess numerous advantages over rigid links which impose the research attention towards employing flexible links in robotics. However, flexible links have a tip vibration that has the difficulty of being presented in dynamic models. Furthermore, the tip vibration leads to the control difficulty as a controller must control a system for the position and the tip elastic vibration. This research proposes a dynamic model and an intelligent hybrid optimal controller of a hybrid manipulator, the hybrid manipulator has a rigid link, a flexible link, and a variable payload. The proposed dynamic model is obtained using a combined technique of the finite element method and the Lagrangian method. The proposed dynamic model is compared with a SimMechanics model in terms of their open-loop responses, and both models have close match responses which indicates that the novel dynamic model is accurate. The intelligent hybrid optimal controller is also proposed based on the integration of an optimal linear quadratic regulator and a fuzzy logic controller. The integration of the fuzzy control and the linear quadratic regulator controller achieves 39.5% reduction of the fuzzy rules which assists to solve the explosion of the fuzzy rules problem since the hybrid manipulator is a multi-input system. The proposed intelligent optimal controller demonstrates improved position control, effective tip vibration suppression, better tip trajectory tracking, and better robustness to overcome the impact of the payload uncertainty compared to the linear quadratic regulator controller based on the simulation validation of the Simulink in MATLAB. PubDate: 2023-11-28
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