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Records with Keyword: Optimization
Showing records 1 to 25 of 121. [First] Page: 1 2 3 4 5 Last
Extreme Learning Machine Based on Firefly Adaptive Flower Pollination Algorithm Optimization
Ting Liu, Qinwei Fan, Qian Kang, Lei Niu
June 29, 2021 (v1)
Keywords: extreme learning machine, firefly algorithm, flower pollination algorithm, Optimization
Extreme learning machine (ELM) has aroused a lot of concern and discussion for its fast training speed and good generalization performance, and it has been used diffusely in both regression and classification problems. However, on account of the randomness of input parameters, it requires more hidden nodes to obtain the desired accuracy. In this paper, we come up with a firefly-based adaptive flower pollination algorithm (FA-FPA) to optimize the input weights and thresholds of the ELM algorithm. Nonlinear function fitting, iris classification and personal credit rating experiments show that the ELM with FA-FPA (FA-FPA-ELM) can obtain significantly better generalization performance (such as root mean square error, classification accuracy) than traditional ELM, ELM with firefly algorithm (FA-ELM), ELM with flower pollination algorithm (FPA-ELM), ELM with genetic algorithm (GA-ELM) and ELM with particle swarm optimization (PSO-ELM) algorithms.
Optimization of Oxidative Leaching for Vanadium Extraction from Low-Grade Stone Coal Using Response Surface Methodology
Zulv Huang, Tao Chen, Yang Zhou, Wenbin Xu, Hanzhi Lin, Bo Yan
June 21, 2021 (v1)
Subject: Other
Keywords: kinetics, Optimization, oxidation leaching, stone coal, vanadium
The feasibility and kinetics of vanadium (V) recovery from oxidative leaching of low-grade stone coal using MnO2 were investigated. Oxidative leaching processes (OLPs) were designed using response surface methodology (RSM) based on the central composite design (CCD) model. The results show that the order of factors that influence OLPs is leaching temperature > H2SO4 concentration > leaching time > MnO2 dosage. The interaction between leaching temperature and H2SO4 concentration on the OLP is the most significant. Vanadium leaching efficiency was 89.3% using 31% H2SO4 and 3% MnO2 at 90 °C for 7.9 h. The kinetics of V leaching from stone coal show that the leaching rate is controlled by chemical reaction through a layer according to the shrinking core model and the activation energy is 55.62 kJ/mol. A comparison of the SEM-EDS results of minerals before and after leaching confirms that the muscovite structure was significantly destroyed and V and aluminum (Al) were effectively dissolved... [more]
Ultrasound-Assisted Extraction of Antioxidants from Baccharis dracunculifolia and Green Propolis
Renata Iara Cavalaro, Luis Felipe de Freitas Fabricio, Thais Maria Ferreira de Souza Vieira
June 21, 2021 (v1)
Keywords: antioxidant, Baccharis dracunculifolia, green propolis, Optimization, response surface methodology (RSM), ultrasound
Baccharis dracunculifolia or rosemary-of-field is the principal botanical source used by Africanized bees Apis mellifera L. to produce green propolis in Southeastern Brazil. The phenolic compounds present in the plant and green propolis have been reported to be responsible for biological activities such as antioxidant capacity. This study aimed to optimize the ultrasound-assisted extraction of antioxidants compounds from rosemary-of-field using a central composite rotatable design (CCRD), and compare results to green propolis extract. An experimental design was performed to obtain responses of total phenolic content and antioxidant capacity. The results allowed observing that the optimum condition for both Baccharis dracunculifolia floral bud and raw green propolis antioxidant extraction was obtained with 99% ethanol solution. In this condition, Total Phenolic Content (TPC), Ferric Reducing Antioxidant Power (FRAP), and 2,2-diphenyl-1-picryl-hydrazyl (DPPH) values were 612.14 mg GAE. g... [more]
Modeling and Optimization for Konjac Vacuum Drying Based on Response Surface Methodology (RSM) and Artificial Neural Network (ANN)
Zhiheng Zeng, Ming Chen, Xiaoming Wang, Weibin Wu, Zefeng Zheng, Zhibiao Hu, Baoqi Ma
May 25, 2021 (v1)
Keywords: drying, glucomannan, konjac, Optimization, vacuum
To reveal quality change rules and establish the predicting model of konjac vacuum drying, a response surface methodology was adopted to optimize and analyze the vacuum drying process, while an artificial neural network (ANN) was applied to model the drying process and compare with the response surface methodology (RSM) model. The different material thickness (MT) of konjac samples (2, 4 and 6mm) were dehydrated at temperatures (DT) of 50, 60 and 70 °C with vacuum degrees (DV) of 0.04, 0.05 and 0.06 MPa, followed by Box−Behnken design. Dehydrated samples were analyzed for drying time (t), konjac glucomannan content (KGM) and whiteness index (WI). The results showed that the DT and MT should be, respectively, under 60 °C and 4 mm for quality and efficiency purposes. Optimal conditions were found to be: DT of 60.34 °C; DV of 0.06 MPa and MT of 2 mm, and the corresponding responses t, KGM and WI were 5 h, 61.96% and 82, respectively. Moreover, a 3-10-3 ANN model was established to compare... [more]
Economic Analysis of a Freeze-Drying Cycle
Lorenzo Stratta, Luigi C. Capozzi, Simone Franzino, Roberto Pisano
May 25, 2021 (v1)
Keywords: costs analysis, freeze-drying, lyophilization, Optimization
Freeze-drying has always been considered an extremely expensive procedure to dehydrate food or pharmaceutical products, and for this reason, it has been employed only if strictly necessary or when the high added value of the final product could justify the costs. However, little effort has been made to analyze the factors that make this technology so unaffordable. In this work, a model was proposed to calculate in detail the operational (OC) and capital costs (CC) of a freeze-drying cycle and an evaluation of the process bottlenecks was made. The main result is that the process itself, contrary to the classic belief, is not the most expensive part of freeze-drying, while the initial investment is the real limiting factor. Under this consideration, the optimization of a freeze-drying cycle should be formulated in order to fit more cycles in the lifespan of the apparatus, instead of merely reducing the power consumption of the machine.
Determination of Dissolved CO2 Concentration in Culture Media: Evaluation of pH Value and Mathematical Data
Amir Izzuddin Adnan, Mei Yin Ong, Saifuddin Nomanbhay, Pau Loke Show
May 17, 2021 (v1)
Subject: Biosystems
Keywords: Carbon Dioxide, culture media, microorganism, Optimization
Carbon dioxide is the most influential gas in greenhouse gasses and its amount in the atmosphere reached 412 µmol/mol in August 2020, which increased rapidly, by 48%, from preindustrial levels. A brand-new chemical industry, namely organic chemistry and catalysis science, must be developed with carbon dioxide (CO2) as the source of carbon. Nowadays, many techniques are available for controlling and removing carbon dioxide in different chemical processes. Since the utilization of CO2 as feedstock for a chemical commodity is of relevance today, this study will focus on how to increase CO2 solubility in culture media used for growing microbes. In this work, the CO2 solubility in a different medium was investigated. Sodium hydroxide (NaOH) and monoethanolamine (MEA) were added to the culture media (3.0 g/L dipotassium phosphate (K2HPO4), 0.2 g/L magnesium chloride (MgCl2), 0.2 g/L calcium chloride (CaCl2), and 1.0 g/L sodium chloride (NaCl)) for growing microbes in order to observe the dif... [more]
Carbon Emission Reduction Potential in the Finnish Energy System Due to Power and Heat Sector Coupling with Different Renovation Scenarios of Housing Stock
Ilkka Jokinen, Arslan Ahmad Bashir, Janne Hirvonen, Juha Jokisalo, Risto Kosonen, Matti Lehtonen
May 17, 2021 (v1)
Subject: Energy Policy
Keywords: borehole heat exchanger, emission reduction, Optimization, power-to-heat, residential building renovation, sector coupling, wind power
In the pursuit of mitigating the effects of climate change the European Union and the government of Finland have set targets for emission reductions for the near future. This study examined the carbon emission reduction potential in the Finnish energy system with power-to-heat (P2H) coupling of the electricity and heat sectors with different housing renovation levels. The measures conducted in the energy system were conducted as follows. Wind power generation was increased in the Finnish power system with 10 increments. For each of these, the operation of hydropower was optimized to maximize the utilization of new wind generation. The excess wind generation was used to replace electricity and heat from combined heat and power production for district heating. The P2H conversion was performed by either 2000 m deep borehole heat exchangers coupled to heat pumps, with possible priming of heat, or with electrode boilers. The housing stock renovated to different levels affected both the elec... [more]
Fitness Landscape Analysis and Edge Weighting-Based Optimization of Vehicle Routing Problems
László Kovács, Anita Agárdi, Tamás Bányai
May 17, 2021 (v1)
Subject: Optimization
Keywords: fitness landscape, Optimization, traveling salesman problem, vehicle routing problem
Vehicle routing problem (VRP) is a highly investigated discrete optimization problem. The first paper was published in 1959, and later, many vehicle routing problem variants appeared to simulate real logistical systems. Since vehicle routing problem is an NP-difficult task, the problem can be solved by approximation algorithms. Metaheuristics give a “good” result within an “acceptable” time. When developing a new metaheuristic algorithm, researchers usually use only their intuition and test results to verify the efficiency of the algorithm, comparing it to the efficiency of other algorithms. However, it may also be necessary to analyze the search operators of the algorithms for deeper investigation. The fitness landscape is a tool for that purpose, describing the possible states of the search space, the neighborhood operator, and the fitness function. The goal of fitness landscape analysis is to measure the complexity and efficiency of the applicable operators. The paper aims to invest... [more]
Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages
Mehdi A. Ehyaei, Abolfazl Ahmadi, Marc A. Rosen, Afshin Davarpanah
April 29, 2021 (v1)
Keywords: Genetic Algorithm, geothermal cycle, Optimization, organic Rankine cycle
Due to the harmful effects and depletion of non-renewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 M... [more]
Optimization Design of a Two-Vane Pump for Wastewater Treatment Using Machine-Learning-Based Surrogate Modeling
Sang-Bum Ma, Sung Kim, Jin-Hyuk Kim
April 16, 2021 (v1)
Keywords: Computational Fluid Dynamics (CFD), Machine Learning, Optimization, Reynolds-averaged Navier-Stokes (RANS), two-vane pump
This paper deals with three-objective optimization, using machine-learning-based surrogate modeling to improve the hydraulic performances of a two-vane pump for wastewater treatment. For analyzing the internal flow field in the pump, steady Reynolds-averaged Navier-Stokes equations were solved with the shear stress transport turbulence model as a turbulence closure model. The radial basis neural network model, which is an artificial neural network, was used as the surrogate model and trained to improve prediction accuracy. Three design variables related to the geometry of blade and volute were selected to optimize concurrently the objective functions with the total head and efficiency of the pump and size of the waste solids. The optimization results obtained by using the model showed highly accurate prediction values, and compared with the reference design, the optimum design provided improved hydraulic performances.
Applications of an Improved Aerodynamic Optimization Method on a Low Reynolds Number Cascade
Shuyi Zhang, Bo Yang, Hong Xie, Moru Song
March 24, 2021 (v1)
Subject: Other
Keywords: aerodynamic, cascade, incidence angle, Optimization, parameterization, plane cascade design, PSO-MVFSA
The effect of cascade aerodynamic optimization on turbomachinery design is very significant. However, for most traditional cascade optimization methods, aerodynamic parameters are considered as boundary conditions and rarely directly used as the optimization variables to realize optimization. Given this problem, this paper proposes an improved cascade aerodynamic optimization method in which an incidence angle and nine geometric parameters are used to parameterize the cascade and one modified optimization algorithm is adopted to find the cascade with the optimal aerodynamic performance. The improved parameterization approach is based on the Non-Uniform Rational B-Splines (NURBS) method, the camber line superposing thickness distribution molding (CLSTDM) method, and the plane cascade design method. To rapidly and effectively find the cascade with the largest average lift-drag ratio within a certain range of incidence angles, modified particle swarm optimization combined with the modifie... [more]
Modeling and Optimization of COD Removal from Cold Meat Industry Wastewater by Electrocoagulation Using Computational Techniques
Juan Morales-Rivera, Belkis Sulbarán-Rangel, Kelly Joel Gurubel-Tun, Jorge del Real-Olvera, Virgilio Zúñiga-Grajeda
March 24, 2021 (v1)
Keywords: artificial neural network, cold meat industry wastewater, computer modeling, electrocoagulation, Optimization, response surface methodology
In this paper, electrocoagulation (EC) treatment for the removal of chemical oxygen demand (COD) from cold meat industry wastewater is modeled and optimized using computational techniques. Methods such as artificial neural networks (ANNs) and response surface methodology (RSM), based on the Box−Behnken design using three levels, were employed to calculate the best control parameters for pH (5−9), current density (2−6 mA/cm2) and EC time (20−60 min). Analysis of variance (ANOVA) and 3D graphs revealed that pH and current density are the main parameters used for depicting the EC process. The developed models successfully describe the process with a correlation coefficient of R2 = 0.96 for RSM and R2 = 0.99 for ANN. The models obtained were optimized applying the moth-flame optimization (MFO) algorithm to find the best operating conditions for COD removal. ANN-MFO was used and showed superior COD removal (92.91%) under conditions of pH = 8.9, current density = 6.6 mA/cm2 and an EC time of... [more]
Improving the Energy Efficiency of Industrial Refrigeration Systems by Means of Data-Driven Load Management
Josep Cirera, Jesus A. Carino, Daniel Zurita, Juan A. Ortega
March 1, 2021 (v1)
Keywords: Compressors, data-driven, energy disaggregation, Energy Efficiency, load management, multi-layer perceptron, NILM, Optimization, partial load ratio, refrigeration systems
A common denominator in the vast majority of processes in the food industry is refrigeration. Such systems guarantee the quality and the requisites of the final product at the expense of high amounts of energy. In this regard, the new Industry 4.0 framework provides the required data to develop new data-based methodologies to reduce such energy expenditure concern. Focusing in this issue, this paper proposes a data-driven methodology which improves the efficiency of the refrigeration systems acting on the load side. The solution approaches the problem with a novel load management methodology that considers the estimation of the individual load consumption and the necessary robustness to be applicable in highly variable industrial environments. Thus, the refrigeration system efficiency can be enhanced while maintaining the product in the desired conditions. The experimental results of the methodology demonstrate the ability to reduce the electrical consumption of the compressors by 17%... [more]
Optimal Energy Management for Microgrids Considering Uncertainties in Renewable Energy Generation and Load Demand
Haotian Wu, Hang Li, Xueping Gu
February 22, 2021 (v1)
Keywords: ant colony optimization, energy management, microgrids, Optimization, pattern search optimization, Renewable and Sustainable Energy, uncertainty, wind power
This paper proposes an efficient power management approach for the 24 h-ahead optimal maneuver of Mega−scale grid−connected microgrids containing a huge penetration of wind power, dispatchable distributed generation (diesel generator), energy storage system and local loads. The proposed energy management optimization objective aims to minimize the microgrid expenditure for fuel, operation and maintenance and main grid power import. It also aims to maximize the microgrid revenue by exporting energy to the upstream utility grid. The optimization model considers the uncertainties of the wind energy and power consumptions in the microgrids, and appropriate forecasting techniques are implemented to handle the uncertainties. The optimization model is formulated for a day-ahead optimization timeline with one-hour time steps, and it is solved using the ant colony optimization (ACO)-based metaheuristic approach. Actual data and parameters obtained from a practical microgrid platform in Atlanta,... [more]
Surface-Response Analysis for the Optimization of a Carbon Dioxide Absorption Process Using [hmim][Tf2N]
Grazia Leonzio, Edwin Zondervan
February 22, 2021 (v1)
Keywords: Carbon Dioxide Capture, ionic liquid, Optimization, process simulation, statistical analysis
The [hmim][Tf2N] ionic liquid is considered in this work to develop a model in Aspen Plus® capturing carbon dioxide from shifted flue gas through physical absorption. Ionic liquids are innovative and promising green solvents for the capture of carbon dioxide. As an important aspect of this research, optimization is carried out for the carbon capture system through a central composite design: simulation and statistical analysis are combined together. This leads to important results such as the identification of significant factors and their combinations. Surface plots and mathematical models are developed for capital costs, operating costs and removal of carbon dioxide. These models can be used to find optimal operating conditions maximizing the amount of captured carbon dioxide and minimizing total costs: the percentage of carbon dioxide removal is 93.7%, operating costs are 0.66 million €/tonCO2 captured (due to the high costs of ionic liquid), and capital costs are 52.2 €/tonCO2 capt... [more]
Scheduling Two Identical Parallel Machines Subjected to Release Times, Delivery Times and Unavailability Constraints
Adel M. Al-Shayea, Mustafa Saleh, Moath Alatefi, Mageed Ghaleb
February 3, 2021 (v1)
Keywords: Cmax, delivery times, genetic algorithm (GA), Optimization, parallel machine scheduling, preventive maintenance, release times
This paper proposes a genetic algorithm (GA) for scheduling two identical parallel machines subjected to release times and delivery times, where the machines are periodically unavailable. To make the problem more practical, we assumed that the machines are undergoing periodic maintenance rather than making them always available. The objective is to minimize the makespan (Cmax). A lower bound (LB) of the makespan for the considered problem was proposed. The GA performance was evaluated in terms of the relative percentage deviation (RPD) (the relative distance to the LB) and central processing unit (CPU) time. Response surface methodology (RSM) was used to optimize the GA parameters, namely, population size, crossover probability, mutation probability, mutation ratio, and pressure selection, which simultaneously minimize the RPD and CPU time. The optimized settings of the GA parameters were used to further analyze the scheduling problem. Factorial design of the scheduling problem input v... [more]
Grand Tour Algorithm: Novel Swarm-Based Optimization for High-Dimensional Problems
Gustavo Meirelles, Bruno Brentan, Joaquín Izquierdo, Edevar Luvizotto Jr
December 22, 2020 (v1)
Subject: Optimization
Keywords: benchmarking problems, Optimization, swarm optimization
Agent-based algorithms, based on the collective behavior of natural social groups, exploit innate swarm intelligence to produce metaheuristic methodologies to explore optimal solutions for diverse processes in systems engineering and other sciences. Especially for complex problems, the processing time, and the chance to achieve a local optimal solution, are drawbacks of these algorithms, and to date, none has proved its superiority. In this paper, an improved swarm optimization technique, named Grand Tour Algorithm (GTA), based on the behavior of a peloton of cyclists, which embodies relevant physical concepts, is introduced and applied to fourteen benchmarking optimization problems to evaluate its performance in comparison to four other popular classical optimization metaheuristic algorithms. These problems are tackled initially, for comparison purposes, with 1000 variables. Then, they are confronted with up to 20,000 variables, a really large number, inspired in the human genome. The... [more]
Optimization of CCUS Supply Chains for Some European Countries under the Uncertainty
Grazia Leonzio, Pier Ugo Foscolo, Edwin Zondervan
December 17, 2020 (v1)
Keywords: CCUS supply chain, mathematical model, Optimization, stochastic model
This paper develops a two-stage stochastic mixed integer linear programming model to optimize Carbon Capture, Utilization and Storage (CCUS) supply chains in Italy, Germany and the UK. Few works are present in the literature about this topic, thus this paper overcomes this limitation considering carbon supply chains producing different products. The objective of the numerical models is to minimize expected total costs, under the uncertainties of the production costs of carbon-dioxide-based compounds. Once carbon dioxide emissions that should be avoided are fixed, according to environmental protection requirements for each country, the optimal design of these supply chains is obtained finding the distribution of carbon dioxide captured between utilization and storage sections, the amount of different carbon-based products and the best connection between each element inside the system. The expected total costs for the CCUS supply chain of Italy, Germany and the UK are, respectively, 77.3... [more]
Liquid Polymer Eutectic Mixture for Integrated Extractive-Oxidative Desulfurization of Fuel Oil: An Optimization Study via Response Surface Methodology
Mohd. Faridzuan Majid, Hayyiratul Fatimah Mohd Zaid, Chong Fai Kait, Khairulazhar Jumbri, Jun Wei Lim, Asiah Nusaibah Masri, Siti Musliha Mat Ghani, Hiroshi Yamagishi, Yohei Yamamoto, Brian Yuliarto
November 9, 2020 (v1)
Keywords: deep eutectic solvent, extraction efficiency, extractive desulfurization, Optimization, response surface methodology
Hydrodesulfurization (HDS) has been commercially employed for the production of ultra-low sulfur fuel oil. However, HDS is unable to remove sterically hindered sulfur-containing compounds such as dibenzothiophene (DBT) and benzothiophene (BT). An alternative way to remove sulfur is via extractive desulfurization system (EDS) using deep eutectic solvents (DES) as sustainable extractant. In this work, liquid polymer DES was synthesized using tetrabutylammonium chloride (TBAC) and poly(ethylene glycol) 400 (PEG) with different molar ratios. Response surface methodology (RSM) was applied to study the effect of independent variables toward extraction efficiency (EE). Three significant operating parameters, temperature (25−70 °C), DES molar ratio (1−3), and DES volume ratio (0.2−2.0), were varied to study the EE of sulfur from model oil. A quadratic model was selected based on the fit summary test, revealing that the extraction efficiency was greatly influenced by the amount of DES used, fol... [more]
Optimizing the Processing Factor and Formulation of Oat-Based Cookie Dough for Enhancement in Stickiness and Moisture Content Using Response Surface Methodology and Superimposition
Mohd Salahuddin Mohd Basri, Nurain Mohd Jais, Alifdalino Sulaiman, Mohd Zuhair Mohd Nor, Nor Nadiah Abdul Karim Shah, Siti Hajar Ariffin
October 26, 2020 (v1)
Keywords: dough stickiness, moisture content, Optimization, response surface methodology, superimposition
Despite the utilization of dusting flour and oil to reduce dough stickiness during the production process in food industry, they do not effectively help in eliminating the problem. Stickiness remains the bane of the production of bakery and confectionery products, including cookies. In addition, the high moisture content of cookie dough is unduly important to obtain a high breaking and compression strengths (cookies with high breaking tolerance). This study was conducted in light of insufficient research hitherto undertaken on the utilization of response surface methodology and superimposition to enhance the stickiness and moisture content of quick oat-based cookie dough. The study aims at optimizating, validating and superimposing the best combination of factors, to produce the lowest stickiness and highest moisture content in cookie dough. In addition, the effect of flour content and resting time on the stickiness and moisture content of cookie dough was also investigated, and micros... [more]
Optimization and Selection of Maintenance Policies in an Electrical Gas Turbine Generator Based on the Hybrid Reliability-Centered Maintenance (RCM) Model
Moath Alrifaey, Tang Sai Hong, Azizan As’arry, Eris Elianddy Supeni, Chun Kit Ang
August 29, 2020 (v1)
Keywords: analytic network process (ANP), co-evolutionary multi-objective particle swarm optimization (CMPSO), developed maintenance decision tree (DMDT), failure modes (FMs), hybrid linguistic failure mode and effect analysis (HL-FMEA), oil and gas plant, Optimization, policy selection, reliability-centered maintenance (RCM)
The electrical generation industry is looking for techniques to precisely determine the proper maintenance policy and schedule of their assets. Reliability-centered maintenance (RCM) is a methodology for choosing what maintenance activities have to be performed to keep the asset working within its designed function. Current developments in RCM models are struggling to solve the drawbacks of traditional RCM with regards to optimization and strategy selection; for instance, traditional RCM handles each failure mode individually with a simple yes or no safety question in which question has the possibility of major error and missing the effect of a combinational failure mode. Hence, in the present study, a hybrid RCM model was proposed to fill these gaps and find the optimal maintenance policies and scheduling by a combination of hybrid linguistic-failure mode and effect analysis (HL-FMEA), the co-evolutionary multi-objective particle swarm optimization (CMPSO) algorithm, an analytic netwo... [more]
On the application of shooting method for determining semicontinuous distillation limit cycles
Thomas Adams II, Pranav Bhaswanth Madabhushi
August 17, 2020 (v1)
Keywords: Hybrid Dynamical System, Limit Cycle, Optimization, Process Design, Semicontinuous Distillation
Semicontinuous distillation is a new separation technology for distilling multicomponent mixtures.
This process was designed using design methodologies with heuristic components that evolved
over twenty years. However, the fundamental philosophy of these design methodologies, which
involves guessing, checking and then using a black-box optimization procedure to find the values
of the design variables to meet some performance criteria, has not changed. Mainly, to address the
problem of having a heuristic simulation termination criterion in the black-box optimization phase,
the single shooting method for semicontinuous distillation design was proposed in this study. We
envision that this is a first step in the transformation of the semicontinuous distillation design
process for obtaining optimal designs. We demonstrate the application of this method using two
case studies, which involve the separation of hexane, heptane and octane.
Electro-Discharge Machining of Zr67Cu11Ni10Ti9Be3: An Investigation on Hydroxyapatite Deposition and Surface Roughness
Abdul’Azeez Abdu Aliyu, Ahmad Majdi Abdul-Rani, Saeed Rubaiee, Mohd Danish, Michael Bryant, Sri Hastuty, Muhammad Al’Hapis Razak, Sadaqat Ali
August 5, 2020 (v1)
Keywords: coating, deposition rate, elecro-discharge, hydroxyapatite, machining, metallic glass, Optimization, RSM, surface roughness
This study attempts to simultaneously machine and synthesize a biomimetic nanoporous hydroxyapatite coating on the Zr67Cu11Ni10Ti9Be3 bulk metallic glass (BMG) surface. The aim is to investigate and optimize the hydroxyapatite deposition rate and the surface roughness during the electro-discharge coating of Zr67Cu11Ni10Ti9Be3 BMG. Scanning Electron Microscopy (SEM), X-ray powder Diffraction (XRD) and Energy-dispersive X-ray Spectroscopy (EDS) were employed to characterize and analyze the results. Response Surface Methodology using D-optimum custom design approach was utilized to generate the models and optimize the input parameters. A globule nanostructured and nanoporous coating of about 25.2 µm thick, containing mainly Ca, O, and K were ascertained. Further XRD analysis confirmed the deposition of biocompatible oxides (HA, CaZrO3, and ZrO2) and hard ZrC coating on the Zr67Cu11Ni10Ti9Be3 BMG surface. A significant improvement in cell viability was observed in the HA electro-discharge... [more]
Scope and Limitations of Modelling, Simulation, and Optimisation of a Spiral Wound Reverse Osmosis Process-Based Water Desalination
Alanood A. Alsarayreh, Mudhar A. Al-Obaidi, Raj Patel, Iqbal M. Mujtaba
July 17, 2020 (v1)
Keywords: Modelling, Optimization, reverse osmosis process, Simulation, spiral wound (SW) module, water desalination
The reverse osmosis (RO) process is one of the best desalination methods, using membranes to reject several impurities from seawater and brackish water. To systematically perceive the transport phenomena of solvent and solutes via the membrane texture, several mathematical models have been developed. To date, a large number of simulation and optimisation studies have been achieved to gauge the influence of control variables on the performance indexes, to adjust the key variables at optimum values, and to realise the optimum production indexes. This paper delivers an intensive review of the successful models of the RO process and both simulation and optimisation studies carried out on the basis of the models developed. In general, this paper investigates the scope and limitations of the RO process, as well as proving the maturity of the associated perspective methodologies.
Optimization of the Technological Parameters for Obtaining Zn-Ti Based Composites to Increase the Performance of H2S Removal from Syngas
Annette Madelene Dăncilă, Simona Căprărescu, Constantin Bobiricǎ, Violeta Purcar, Gabriel Gârleanu, Eugeniu Vasile, Cristina Modrogan, Claudia Borda, Dan Dobrotǎ
July 17, 2020 (v1)
Subject: Materials
Keywords: composites, hydrogen sulfide, Optimization, Syngas, technological parameters
The realization of some composite materials that allow the best removal of H2S from syngas was the main objective of this work. Thus, the optimization of the technological parameters for obtaining composites based on Zn-Ti was achieved. The paper studies the influence of calcination temperature on the characteristics of the binary ZnO-TiO2 system used to synthesize a composite material with suitable properties to be used subsequently for syngas treatment. The mineralogical and structural analyzes showed that starting with the calcination temperature of 700 °C the material synthetized is composed mainly of zinc orthotitanate which possess the corresponding characteristics to be finally used in the treatment of the syngas for its desulfurization. At this calcination temperature the material has a compact structure most likely due to sintering of the formed titanates. These composites have a texture that places them rather in the category of non-porous materials, the pore volume and their... [more]
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