Highly efficient supported AlCl3-based cationic catalysts to produce polyα-olefin oil base stocks

The main aim of this research is to decrease the amount of AlCl₃ content that is very corrosive and hazardous in the catalytic system, required for the α-olefin oligomerization without substantial change of final oil features. This was successfully achieved by supporting AlCl₃ on different carriers. More precisely, a series of supported bimetallic catalysts was synthesized by immobilization of AlCl₃ and TiCl₄ onto Al₂O₃, SiO₂, and mixed supports, that is, Al₂O₃/FeCl₃ and SiO₂/FeCl₃. It was found that silica and alumina-based catalysts had higher catalytic activities compared to support free AlCl₃; however, this enhancement for silica-based supports was more significant. According to gel permeation chromatography (GPC) results, the use of single supports, that is, Al₂O₃ and SiO₂, increased oligomer's molecular weight, while the application of mixed supports resulted in the decrease of molecular weight of the oligomers. Viscosity characteristics of the synthesized oligomers have also been studied at two different temperatures of 40 and 100°C (KV⁴⁰ and KV¹⁰⁰). The viscosity index (VI) values, derived from KV⁴⁰ and KV¹⁰⁰, of the prepared oligomers were in the range of 126–145. The molecular weight and termination mechanisms of the oligomers were studied by ¹H-NMR spectroscopy. The obtained results disclosed that the employed reaction conditions led to the production of oligomer chains with various structures including vinylidene (Vd), and di and three-substituted vinylene (2Vn, 3Vn) structures.     

Output feedback controller for polytopic systems exploiting the direct searching of the design space

This paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.     

AMBO: All Members-Based Optimizer for Solving Optimization Problems

There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in AMBO, any member of the population can play a role in updating the population matrix. The theory of AMBO is described and then mathematically modeled for implementation on optimization problems. The performance of the proposed algorithm is evaluated on a set of twenty-three standard objective functions, which belong to three different categories: unimodal, high-dimensional multimodal, and fixed-dimensional multimodal functions. In order to analyze and compare the optimization results for the mentioned objective functions obtained by AMBO, eight other well-known algorithms have been also implemented. The optimization results demonstrate the ability of AMBO to solve various optimization problems. Also, comparison and analysis of the results show that AMBO is superior and more competitive than the other mentioned algorithms in providing suitable solution.     

Clearance angle and evolution of depth of cut in actuated disc cutting

This paper investigates the effect of cutter clearance angle on variation of depth of cut and cutting process with an actuated disc cutting(ADC). ADC is a cyclic cutting method with two main characteristics:(i) a disk-shape cutter is used to attack the rock in an undercutting mechanism; and(ii) the cutter is dynamically actuated as it is moved across the rock. Hence, the cutting process of such system is periodic, each recurrence known as actuation cycle. The first ADC model, developed in 2016, represented an idealization of the technology with a flat disc cutter, where no clearance angle was considered. The evolution of the contact between the disc and the rock was, therefore, computed only on horizontal x-y plane, ignoring the effect of normal component of the force acting on cartridge. This article reports on a study that incorporates the cutter inclination angle in derivation of cutter/rock interface laws. It extends the proposed kinematic and geometry based model to take into account the variable depth of cut in estimating the forces associated with cutting in one actuation cycle. Experiments were conducted using Wobble to test the predictions of the improved model at various operating conditions. The model predictions are matched with the experimental results and effects of various factors are analysed.     

Structural/texture evolution of CaO/MCM‐41 nanocatalyst by doping various amounts of cerium for active and stable catalyst: Biodiesel production from waste vegetable cooking oil

In present work, the aim of producing biodiesel from waste cooking oil was pursued by doping the cerium element into the MCM‐41 framework as catalyst with various Si/Ce molar ratio (5, 10, 25, 50, and Ce = 0). The catalytic performance and stability improved by employing the ultrasound irradiation in active phase loading step of catalyst preparation. The physicochemical characteristics of synthesized samples were investigated using various techniques as follows: Brunauer‐Emmett‐Teller (BET), X‐ray powder diffraction (XRD), Fourier transfer infrared (FTIR), energy‐dispersive X‐ray spectroscopy (EDX), transmission electron microscopy (TEM), and field emission scanning electron microscope (FESEM). The XRD patterns along with the results of FTIR and BET analysis revealed the MCM‐41 framework destruction while increasing the Ce content. The FESEM images of the nanocatalysts illustrated a well distribution and uniform morphology for the Ca/CeM (Si/Ce = 25). The particle size and size distribution of the Ca/CeM (Si/Ce = 25) were subsequently determined by TEM and FESEM images. The activity of fabricated nanocatalysts was evaluated by measuring the free acid methyl ester (FAME) content of produced biodiesel. The tests were carried out at constant operational conditions: T = 60°C, catalyst loading = 5 wt%, methanol/oil molar ratio = 9, and 6‐hour reaction time. A superior activity was observed for Ca/CeM (Si/Ce = 25) among other nanocatalysts with 96.8% conversion of triglycerides to biodiesel. The mentioned sample was utilized in five reaction cycles, and at the end of the fifth cycle, the conversion reached to 91.5% which demonstrated its significant stability.     

Investigation the impact of additives on the displacement of the onset point of asphaltene precipitation using interfacial tension measurement

The purpose of this study is to explore the impact of additives on the displacement of the onset point of asphaltene precipitation in crude oil using the interfacial tension measurement method, based on the examined oil has been taken from Iran reservoirs. The experimental results suggest that the addition of surfactants of dodecyl benzene sulfonic acid (DBSA) and coconut diethanolamide (CDEA) to the oil has triggered the onset of asphaltene precipitation. These findings imply that CDEA has a more effective role in preventing asphaltene precipitation. Also, it was observed that increasing the concentration of the surfactants has led to obtaining greater results. Finally, critical micelle concentration was calculated to be 5000 and 4700 ppm in the cases of CDEA and DBSA, respectively.     

Exploring the motivational factors on continuous usage intention of smartwatches among actual users

Nowadays, smart wearable technology comes up to different sectors and is gaining momentum to be implemented in everyday objects. Smartwatches are the most popular type of wearable devices. The current study attempts to understand the motivational factors of consumers’ continuous intention to use smartwatches. In particular, a netnography research has been conducted and consumers’ opinions on smartwatches on Amazon have been analysed. Eight key determinants of continuous usage intention of smartwatches have been identified. Some of them (healthology, complementary goods and enabling technologies) were not included in previous technology adoption models, highlighting that existing models need to be updated when it comes in the domain of continuous usage intention of wearable technologies.     

Interactive effects of aging parameters of AA6056

The effect of thermomechanical treatment on the aging behavior of AA6056 aluminum alloy was modeled using response surface methodology (RSM). Two models were developed to predict the final yield stress (FYS) and elongation amounts as well as the optimum conditions of aging process. These were done based on the interactive effects of applied thermomechanical parameters. The optimum condition predicted by the model to attain the maximum strength was pre-aging at 80 °C for 15 h, followed by 70% cold work and subsequent final aging at 165 °C for 4 h, which resulted in the FYS of about 480 MPa. As for the elongation, the optimum condition was pre-aging at 80 °C for 15 h, followed by 30% cold work and final-aging at 165 °C for 4 h, which led to 21% elongation. To verify the suggested optimum conditions, the tests were carried out confirming the high accuracy (above 94%) of the RSM technique as well as the developed models. It is shown that the RSM can be used successfully to optimize the aging process, to determine the significance of aging parameters and to model the combination effect of process variables on the aging behavior of AA6056.