In addressing the issue of a low drawing rate in a steeply inclined and extremely thick coal seam, this study focused on the engineering background of the +575 horizontal working faces in the Wudong Coal Mine. By utilizing physical similarity simulation experiments, research was carried out on the top-coal-drawing rate and the gangue ratio at different coal-drawing intervals in horizontal segment mining for steeply inclined and thick coal seams, in which the relationships between the top-coal-drawing law and the drawing interval and technologies were revealed. The discrete element method was used to establish a numerical simulation model for the horizontal segment mining of steeply inclined and thick coal seams, and the roof-drawing law in the cases of the three-interval-group-of-support and drawing-once-every-two-support methods were analyzed before finally obtaining the optimal drawing technology. Through field practice, the coal-drawing effect of the technology was verified. The res... [more]

In order to improve the erosion resistance of steel PDC (Polycrystalline Diamond Compact) bit under high-speed fluid flow conditions underground, it is necessary to develop a high-performance erosion-resistant coating. In this paper, laser cladding was used to prepare the new coating by modifying tungsten carbide with graphene. And the effects of tungsten carbide content and graphene content on the coating performance have been thoroughly studied and analyzed to obtain the optimal covering layer. The research results indicate that, for new coatings, 60% tungsten carbide and 0.3% graphene are the optimal ratios. After adding tungsten carbide, the hardness has significantly improved. However, when the tungsten carbide content further increases more than 30%, the increase in hardness is limited. In addition, when the content of graphene is more than 0.3%, the branched structure becomes thicker. In detail, this is a phenomenon where the segregation of Cr, Si, and W becomes very obvious aga... [more]

The selection of growth substrate geometries for the mechanical dry transfer of carbon nanotubes to device substrates depends on the precision of the assembly equipment. Since these geometries play a decisive role in the overall efficiency of the process, an investigation of the most important geometry parameters is carried out. The substrate geometry affects the number of carbon nanotubes suspended during the growth process and the speed of mechanical assembly at the same time. Since those two criteria are interlinked and affect productivity, a meta-model for the growth and selection of the nanotubes is simulated and a time study of the resulting assembly motions is subsequently performed. The geometry parameters are then evaluated based on the total number of suspended carbon nanotubes and the throughput rate, measured in transfers per hour. The accuracy specifications are then taken into account. Depending on the overall accuracy that can be achieved, different offset angles and ove... [more]

The separation section of the methanol-to-olefin (MTO) process is energy-intensive, and the optimization and heat integration can enhance energy efficiency and reduce costs. A bi-level optimization model framework is proposed to optimize the separation process and simultaneously integrate the heat exchanger network (HEN). The upper level employs a data-driven BP neural network proxy model instead of the mechanism model for the separation process, while the lower level adopts a stage-wise superstructure for the HEN without stream splits. The interaction between the two systems is realized effectively through information exchange. A bi-level particle swarm algorithm is employed to optimize complex problems and determine the optimal operational parameters for the distillation system and HEN. Compared with the typical sequential synthesis method, the optimization by the proposed approach reduces the total annual cost by 1.4293×106 USD/y, accounting for 4.76%.

Micro-pits are widely used in the aerospace and tribology sectors on cylindrical surfaces and electrochemical micromachining which are of great significance for the high material removal rate, absence of tool wear, and mechanical stress, while facing significant challenges such as stray corrosion and low machining efficiency. Aiming at the above problems, this paper proposes a comprehensive method called radial ultrasonic rolling electrochemical micromachining (RUREMM) in which an ultrasonic field has been added onto the cylindrical surface. First, a theoretical model was created to gain the rules of the formation and collapse of bubbles in the liquid medium. Second, to analyze the optimal size of the cathode electrode, the COMSOL5.2 simulation software was proposed to research the influence of the electric field on the different dimensions, and the influences of different parameters in RUREMM on material depth/diameter ratio and roughness are explored through processing experiments. R... [more]

To eliminate or reduce stick−slip vibration in torsional vibration of the drilling string and improve the rate of penetration (ROP), a stick−slip vibration model of the drilling string considering the ROP was established based on the multidimensional torsional vibration model of the drilling string. The model was verified by simulation analysis. The characteristics of the drilling string stick−slip vibration in the three stages of stationary, slip, and stick were analyzed. This paper investigated the influence of rotary torque, rotary speed, and weight on bit (WOB) on stick−slip vibrations in the drill string. Based on this, the relationship between the drilling parameters and ROP was established. Drilling parameter optimization was completed for soft, medium-hard, and hard formations. Results showed that appropriately increasing torque and decreasing WOB can reduce or even eliminate stick−slip vibrations in the drill string and increase the ROP. The parameter optimization increased th... [more]

Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov−Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carri... [more]

Separating heavy components from natural gas not only enhances safety, improves pipeline transportation, ensures product quality, and addresses environmental considerations, but it also exerts an influence on global energy trends. Therefore, separating heavy components is necessary and can result in beneficial goods. This article presents a comprehensive study on the process simulation and optimization of the recovery of natural gas condensate via the combined refrigeration of a mixture of ethane and propane as a refrigerant. The optimization objectives include maximizing the recovery of ethane and propane, minimizing energy consumption, and achieving desired product quality targets. A sensitivity analysis was performed to assess the impact of key parameters on process performance. Using Aspen HYSYS software, the influence of the cooler outlet stream temperature and expander outlet stream pressure on the shaft power and profit of a dry gas compressor was analyzed based on the operating... [more]

This paper aims to optimize the quality characteristics of the drilling process in glass fiber-reinforced polymer (GFRP) composites. It focuses on optimizing the drilling parameters with drill point angles concerning delamination damage and energy consumption, simultaneously. The effects of drilling process parameters on machinability were analyzed by evaluating the machinability characteristics. The cutting power was modeled through drilling parameters (speed and feed), drill point angle, and laminate thickness. The response surface analysis and artificial neural networks enhanced by the particle swarm optimization algorithm were applied for modeling and evaluating the effect of process parameters on the machinability of the drilling process. The most influential parameters on machinability properties and delamination were determined by analysis of variance (ANOVA). A multi-response optimization was performed to optimize drilling process parameters for sustainable drilling quality cha... [more]

The present study aimed to optimize the process parameters (milling depth and advanced speed) for an asphalt milling operation using a multi-response approach based on Taguchi design of experiments (DOE) and Grey Relational Analysis (GRA). Nine simulations tests were conducted using Discrete Element Method (DEM) in order to determine the forces acting on the cutting tooth support and tip. The considered performance characteristics were cutting forces (smaller is better category) and chip section area (larger is better category). A Grey Relational Grade (GRG) was determined from GRA, allowing to identify the optimal parameter levels for the asphalt milling process with multiple performance characteristics. It was found that that the optimal milling parameters for multi-response analysis are a milling depth of 200 mm and an advanced speed of 30 mm/min. Furthermore, analysis of variance (ANOVA) was used to determine the most significant factor influencing the performance characteristics.... [more]

Phosphatidylserine (PS) has significant biological and nutritional effects and finds wide applications in the food, pharmaceutical, and chemical industries. To produce high-value PS efficiently, phospholipase D (PLD)-induced transphosphatidylation of low-value phosphatidylcholine (PC) with L-serine has been explored. In this research, we purified recombinant PLD from Streptomyces antibioticus SK-3 using ion exchange chromatography and gel filtration chromatography. Subsequently, we thoroughly characterized the purified enzyme and optimized the transphosphatidylation conditions to identify the most favorable settings for synthesizing PS in a biphasic system. The purified recombinant PLD displayed a robust transphosphatidylation function, facilitating efficient catalysis in the synthesis of PS. Under the optimal conditions (butyl acetate/enzyme solution 1:1, L-serine 160 mg/mL, soybean lecithin 2 mg/mL, and MgCl2 15 mM, at 50 °C for 2.5 h with shaking), we achieved a conversion rate of 9... [more]

Nanofiltration is well suited to separate monovalent ions from multivalent ions, such as the separation of Li+ and Mg2+ from seawater, a potential lithium source for the production of lithium-ion batteries. To the best of our knowledge, there is no existing work on the optimization of a multi-stage membrane plant that differentiates between different ions and that is based on a validated transport model. This study presents a method for modeling predefined membrane interconnections using discretization along the membrane length and across the membrane thickness. The solution-diffusion−electromigration model was used as the transport model in a fundamental membrane flowsheet, and the model was employed to optimize a given flowsheet with a flexible objective function. The methodology was evaluated for three distinct separation tasks, and optimized operating points were found. These show that permeances and feed concentrations might cause negative rejections and positive rejections (espec... [more]

Parallel flow double and triple-effect vapor absorption cooling systems (VACS) are trying to meet the challenges of vapor compression cooling systems due to their better performance. Therefore, the present study deals with the review, thermodynamic analysis, and optimization of operating parameters for both double and triple-effect VACS. Lithium bromide water was selected as the working fluid, while liquified petroleum gas (LPG) and compressed natural gas (CNG) were taken as the source of energy to drive both the VACS. Detailed First Law analysis, i.e., coefficient of performance (COP), was examined along with the optimization of operating parameters (such as salt concentration and operating generators temperature at different pressure levels) and the volume flow rate of the gases. Optimization was carried out for maximum COP of the VACS using an iterative technique. Our results show that the COP of the triple-effect system was approximately 32% higher than the double effect, while 15−... [more]

The research presented aimed to address the treatment of fluid waste with significant environmental impact by utilizing plasma technology, specifically plasma arc flow (PAF). The goal was to develop a novel purification material based on graphene for industrial applications and to optimize the treatment process. Analysis and monitoring of a submerged arc plasma reactor were the main goals of this research. This entailed a careful examination of the incoming wastewater that needed to be treated with the goal of identifying its precise composition characteristics with the relative tolerances needed for the reactions that were to follow in the reactor. The focus of the analysis was on input-parameter optimization, production of characteristic curves, and analysis of the factors affecting hydrogen evolution in syngas. Additionally, the study investigated how to determine the best viscosity for a particular input matrix by carrying out an evaluation study. The effects of this parameter were... [more]

Research on cannabis oil has evolved to encompass the pharmaceutical industry for the therapeutic potential of the active compounds for pathologies such as Alzheimer, auto-immune disorders, and cancer. These debilitating diseases are best treated with cannabinoids such as tetrahydrocannabinol (∆9-THC), cannabigerol (CBG), and cannabinol (CBN), which relieve neuropathic pain and stimulate the immune system. We extracted cannabinoids from plants with supercritical CO2 and produced an extract with a total yield close to 26%. The three-level Box−Behnken experimental design considered four factors: Temperature, pressure, CO2 flow rate, and processing time, with predetermined parameters at low, medium, and high levels. The mathematical model was evaluated by regression analysis. The yield of ∆9-THC and CBG reached a maximum after 2 h and 15 g/min of CO2, 235 bar, 55 °C (64.3 g THC/100 g of raw material and 4.6 g CBG/100 g of raw material). After another 2 h of extraction time, the yield of C... [more]

This work addresses the lot-sizing and production scheduling problem of multi-stage multi-product food industrial facilities. More specifically, the production scheduling problem of the semi-continuous yogurt production process, for two large-scale Greek dairy industries, is considered. Production scheduling decisions are made using two approaches: (i) an optimization approach and (ii) a rule-based approach, which are followed by a comparative study. An MILP model is applied for the optimization of short-term production scheduling of the two industries. Then, the same problems are solved using the commercial scheduling tool ScheduleProTM, which derives scheduling decisions using simulation-based techniques and empirical rules. It is concluded that both methods, despite having their advantages and disadvantages, are suitable for addressing complex food industrial scheduling problems. The optimization-based approach leads to better results in terms of operating cost reduction. On the oth... [more]

Research on fault diagnosis and positioning of the distribution network (DN) has always been an important research direction related to power supply safety performance. The back propagation neural network (BPNN) is a commonly used intelligent algorithm for fault location research in the DN. To improve the accuracy of dual fault diagnosis in the DN, this study optimizes BPNN by combining the genetic algorithm (GA) and cloud theory. The two types of BPNN before and after optimization are used for single fault and dual fault diagnosis of the DN, respectively. The experimental results show that the optimized BPNN has certain effectiveness and stability. The optimized BPNN requires 25.65 ms of runtime and 365 simulation steps. And in diagnosis and positioning of dual faults, the optimized BPNN exhibits a higher fault diagnosis rate, with an accuracy of 89%. In comparison to ROC curves, the optimized BPNN has a larger area under the curve and its curve is smoother. The results confirm that t... [more]

Gas-To-Liquid (GTL) processing involves the conversion of natural gas to liquid hydrocarbons that are widely used in the chemical industry. In this process, the Fischer−Tropsch (F-T) approach is utilized and, as a result, wastewater is produced as a by-product. This wastewater commonly contains alcohols and acids as contaminants. Prior to discharge, the treatment of this wastewater is essential, and biological treatment is the common approach. However, this approach is not cost effective and poses various waste-related issues. Due to this, there is a need for a cost-effective treatment method. This study evaluated the adsorption performance of activated carbon fibers (ACFs) for the treatment of GTL wastewater. The ACF in this study exhibited a surface area of 1232.2 m2/g, which provided a significant area for the adsorption to take place. Response surface methodology (RSM) under central composite design was used to assess the effect of GTL wastewater’s pH, initial concentration and dos... [more]

The intermediate fluid thermoelectric generator (IFTEG) represents a novel approach to power generation, predicated upon the principles of gravity heat pipe technology. Its key advantages include high-power output and a compact module area. The generator’s performance, however, is influenced by the variable exhaust parameters typical of automobile operation, which presents a significant challenge in the design process. The present study establishes a mathematical model to optimize the design of the IFTEG. Our findings suggest that the optimal module area sees substantial growth with an increase in both the exhaust heat exchanger area and the exhaust flow rate. Interestingly, the optimal module area appears to demonstrate a low sensitivity to changes in exhaust temperature. To address the challenge of determining the optimal module area, this study introduces the concept of peak power deviation. This method posits that any deviation from the optimal module area results in an equivalent... [more]

Heat integration by a heat exchanger network (HEN) is an important topic in chemical process system synthesis. From the perspective of optimization, the simultaneous synthesis of HEN belongs to a mixed-integer and nonlinear programming problem. Both the stage-wise superstructure (SWS) model and the chessboard model are the most widely adopted and belong to structural models, in which a framework is assumed for stream matching, and the global optimal solution outside its feasible domain may be defined by the framework. A node-wise non-structural model (NW-NSM) is proposed to find more universal stream matching options, but it requires a mass of structural variables and extra multiple correction strategies. The aim of this paper is to develop a novel matrix non-structural model (M-NSM) for HEN without stream splits from the perspectives of global optimization methods and superstructure models. In the proposed M-NSM, the heat exchanger position order is quantized by matrix elements at eac... [more]

Class and shape transformation functions are proposed to carry out the parametric design of the blade profiles because fan efficiency is closely related to the shape of blade profiles. An optimization with the objectives of fan efficiency and static pressure based on the Kriging models was established, and numerical simulation data were applied to construct the Kriging models. The dissipation function was used to analyze the fan energy loss. The prediction results show that the maximum accuracy error between the Kriging model and the experimental data is approximately 0.81%. Compared with the prototype fan, the optimized fan was able to ameliorate the distribution of the flow field pressure and velocity; the outlet static pressure increased by 9.03%, and the efficiency increased by 2.35%. The dissipation function is advantageous because it can intuitively indicate the location and amount of energy loss in the fan, while effectively obtaining the total energy loss as well. The situation... [more]

Jacq., from the Yucatan peninsula, is recognized worldwide for its pungency, flavor, and secondary metabolites content. This has resulted in an increase in its production, which has led to an increase in the number of byproducts considered waste, mainly its leaves. Capsicum chinense leaves have been demonstrated to contain polyphenols with bioactive properties (antioxidant, anti-inflammatory, antiobesogenic capacity, etc.); hence, the extraction of polyphenols through the use of natural deep eutectic solvents (NADES) with a green technology, such as an ultrasonic probe, could help to revalue these leaves by maximizing the extraction efficiency and preserving their bioactive properties. The objective of this study was to optimize the composition of a eutectic solvent for obtaining an extract rich in polyphenols from the Capsicum chinense leaf using a sonic probe. The optimum conditions of the composition of NADES for obtaining the highest Antioxidant capacity (Ax, 79.71% inhibition) wer... [more]

Due to increased demands of production capacity and higher quality requirements, industries are automating at a fast pace. Industrial robots are an important component of the industrial automation ecosystem. However, the selection of appropriate robots is a challenging task due to the sheer number of alternatives present and their varied specifications. The various characteristics or attributes of industrial robots that need due consideration before selection of an optimal robot for a given application are found to be conflicting in nature. Thus, in this paper, several multi-criteria decision-making (MCDM) methods are deployed to select an optimal robot depending on the application. Three different industrial robot selection problems are solved in this paper by using Simple Additive Weighing (SAW), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Linear Programming Technique (LINMAP), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Elimi... [more]

In modern high-volume industries, the serial production line (SPL) is of growing importance due to the inexorable increase in the complexity of manufacturing systems and the associated production costs. Optimal decisions regarding buffer size and the selection of components when designing and implementing an SPL can be difficult, often requiring complex analytical models, which can be difficult to conceive and construct. Here, we propose a model to evaluate and optimize the design of an SPL, integrating numerical simulation with artificial intelligence (AI). Numerous studies relating to the design of SPL systems have been published, but few have considered the simultaneous consideration of a number of decision variables. Indeed, the authors have been unable to locate in the published literature even one work that integrated the selection of components with the optimization of buffer sizes into a single framework. In this research, a System of Integrated Agents Numerical Optimization (S... [more]

The yields of chemical reactions are highly dependent on the mixing pattern between reactants. Herein, we report the modification of a meso-micromixing interaction reaction model which is applied in batch reactors by leveraging the flow characteristics in the continuous reactors. Both experimental and model-predicted yields were compared using the classical Villermaux−Dushman method in a self-designed split and recombination reactor. This modified model significantly reduced the error in predicted product yields from approximately 15% to within 3%, compared to a model containing the micromixing term only. The effects of flow rates and reactor structure parameters on mixing performance were analyzed. We found that increasing flow rates and the degree of twist in the mixing element’s grooves, as well as decreasing the cross-sectional area of grooves, improved mixing performance. The optimization of reactor flow rates and structural parameters was achieved by combining Gaussian process re... [more]