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]

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.

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

This study focuses on the techno-economic assessment integrated with detailed optimisation of a four step vacuum swing adsorption (VSA) process for post-combustion CO2 capture and storage (CCS) from steam-methane reformer dried flue gas containing 20 mol% CO2. The comprehensive techno-economic optimisation model developed herein takes into account VSA process model, peripheral component models, vacuum pump performance, scale-up, process scheduling and a thorough cost model. Three adsorbents, namely, Zeolite 13X and two metal-organic frameworks, UTSA-16 and IISERP MOF2 are optimised to minimise the CO2 capture cost. Monoethanolamine (MEA)-based absorption technology serves as a baseline case to assess and compare optimal techno-economic performances of VSA technology for three adsorbents. The results show that the four step VSA process with IISERP MOF2 outperforms other two adsorbents with a lowest CO2 capture cost (including flue gas pre-treatment) of 33.6 € per tonne of CO2 avoided an... [more]

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.

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]

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.

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]

Hydrogen purification and CO2 capture are of great significance in refineries and pre-combustion power plants. A dual membrane separator offers an alternative approach for improving H2/CO2 separation efficiency. In this work, H2/CO2/CH4 ternary gas mixtures separation can be achieved by a dual membrane separator with an integrated polyimide (PI) membrane and polydimethylsiloxane/polyetherimide (PDMS/PEI) composite membrane. A hollow fiber dual membrane separation equipment is designed and manufactured. Through the self-designed device, the effects of stage cut, operating temperature, operating pressure, and membrane area ratio on separation performance of dual membrane separator have been studied. The results indicate that, at a high stage cut, a dual membrane separator has obvious advantages over a single membrane separator. Operating temperature has a significant impact on gas permeation rates. At 25 °C, a dual membrane separator can obtain the highest purity of H2 and CO2. By increa... [more]

Due to the expanding concern on cleaner production and sustainable development aspects, a technology shift is needed for the hydrogen production, which is commonly derived from natural gas. This work aims to synthesise a large-scale bio-hydrogen network in which its feedstock, i.e., bio-methane, is originated from landfill gas and palm oil mill effluent (POME). Landfill gas goes through a biogas upgrader where high-purity bio-methane is produced, while POME is converted to bio-methane using anaerobic digestor (AD). The generated bio-methane is then distributed to the corresponding hydrogen sink (e.g., oil refinery) through pipelines, and subsequently converted into hydrogen via steam methane reforming (SMR) process. In this work, P-graph framework is used to determine a supply network with minimum cost, while ensuring the hydrogen demands are satisfied. Two case studies in the West and East Coasts of Peninsular Malaysia are used to illustrate the feasibility of the proposed model. In C... [more]

The hydrophobicity of composite insulators is a great significance to the safe and stable operation of transmission lines. In this paper, a recognition method of the hydrophobicity class (HC) of composite insulators based on features optimization was proposed. Through the spray method, many hydrophobic images of water droplets on the insulator surface at various hydrophobicity classes (HCs) were taken. After processing of the hydrophobic images, seven features were extracted: the number n, mean eccentricity Eav and coverage rate k₁ of the water droplets, and the coverage rate k₂, perimeter Lmax, shape factor fc, and eccentricity Emax of the maximum water droplet. Then, the maximum value Δxmax, the minimum value Δxmin, and the average value Δxav of the change rate of each feature value between adjacent HCs, and the volatility Δs of each feature value, were used as the evaluation indexes for features optimization. After this features optimization, the five features that are most closely... [more]

The Middle East is one among the areas of the world that receive high amounts of direct solar radiation. As such, the region holds a promising potential to leverage clean energy. Owing to rapid urbanization, energy demands in the region are on the rise. Along with the global push to curb undesirable outcomes such as air pollution, emissions of greenhouse gases, and climate change, an urgent need has arisen to explore and exploit the abundant renewable energy sources. This paper presents the design, performance analysis and optimization of a 100 MWe parabolic trough collector Solar Power Plant with thermal energy storage intended for use in the Middle Eastern regions. Two representative sites in the Middle East which offer an annual average direct normal irradiance (DNI) of more than 5.5 kWh/m²/day has been chosen for the analysis. The thermodynamic aspect and annual performance of the proposed plant design is also analyzed using the System Advisor Model (SAM) version 2017.9.5. Based on... [more]

This paper proposes a multi-objective optimal energy management framework for the integrated electrical and natural gas network (IEGN) with combined cooling, heat, and power (CCHP) plants. Various energy conversion devices that are installed in the CCHP plant provide redundant generation options and energy pathways, which could be optimally chosen and shifted with given objectives, while meeting the multi-energy (ME) demands. However, this flexible energy dispatch manners may frequently change the energy distribution in the IEGN and challenge their mutual accommodation. In particular, the linepack reserve in the natural gas network, which supports the ramping capabilities of both the gas turbines and the flexible energy dispatch of the gas-dependent ME devices, is highly influenced. Without enough linepack reserve, not only will the flexible operation of the CCHP plants be hindered, but also the gas turbines will be prevented from balancing the supply and the demand in the electrical n... [more]

Astaxanthin is a valuable carotenoid, which has been approved as a food coloring by the US Food and Drug Administration and is considered as a food dye by the European Union (European Commission). This work aimed to attain Rhodosporidium toruloides mutants for enhanced astaxanthin accumulation using ultraviolet (UV) and gamma irradiation mutagenesis. Gamma irradiation was shown to be more efficient than UV for producing astaxanthin-overproducer. Among the screened mutants, G17, a gamma-induced mutant, exhibited the highest astaxanthin production, which was significantly higher than that of the wild strain. Response surface methodology was then applied to optimize the medium compositions for maximizing astaxanthin production by the mutant G17. The optimal medium compositions for the cultivation of G17 were determined as a peptone concentration of 19.75 g/L, malt extract concentration of 13.56 g/L, and glucose concentration of 19.92 g/L, with the maximum astaxanthin yield of 3021.34 µg/L... [more]

The goal of this work is to design a supply chain network that distributes algae biomass from supply locations to meet biodiesel demand at specified demand locations, given a specified algae species, cultivation (i.e., supply) locations, demand locations, and demand requirements. The final supply chain topology includes the optimum sites to grow biomass, to extract algal oil from the biomass, and to convert the algae oil into biodiesel. The objective is to minimize the overall cost of the supply chain, which includes production, operation, and transportation costs over a planning horizon of ten years. Algae production was modeled both within the U.S. State of Oklahoma, as well as the entire contiguous United States. The biodiesel production cost was estimated at $7.07 per U.S. gallon ($1.87 per liter) for the State of Oklahoma case. For the contiguous United States case, a lower bound on costs of $13.68 per U.S. gallon ($3.62 per liter) and an upper bound of $61.69 ($16.32 per liter) w... [more]