In order to improve the operation performance of the multi-stage double-suction centrifugal pump and reduce the internal energy loss of the pump, this paper proposes a single-objective optimization design method based on the non-hierarchical response surface methodology (RSM) and the multi-island genetic algorithm (MIGA). Nine parameters, such as the blade outlet width and blade wrap angle, were used as design variables, and the optimization objective was efficiency under design conditions. In total, 149 sets of valid data were obtained under the Latin hypercube sampling method (LHS), the corresponding thresholds were set for efficiency and head, and 99 sets of valid data were obtained. A cross-validation analysis of the sieved data was carried out based on non-hierarchical RSM, global optimization of the efficiency was carried out using MIGA, and numerical verification was carried out via CFD. The research results show that compared with hierarchical RSM, non-hierarchical RSM can appr... [more]

Distillation-based separation processes, such as extractive or heteroazeotropic distillation, present important processes for separating azeotropic mixtures in the chemical and biochemical industry. However, heteroazeotropic distillation has received much less attention than extractive distillation, which can be attributed to multiple reasons. The phase equilibrium calculations require a correct evaluation of phase stability, while the topology of the heterogeneous mixtures is generally more complex, comprising multiple azeotropes and distillation regions, resulting in an increased modeling complexity. Due to the integration of distillation columns and a decanter, even the simulation of these processes is considered more challenging, while an optimal process design should include the selection of a suitable solvent, considering the performance of the integrated hybrid process. Yet, the intricate mixture topologies largely impede the use of simplified criteria for solvent selection. To... [more]

In this study, dry fractionation process was proposed in order to obtain protein-enriched sunflower meal fractions. The process includes two-stage grinding using a hammer mill and a roll mill, and fractionation of sunflower meal by sieving. Central composite design (CCD) with four variables on three levels within response surface methodology was applied in order to estimate the influence of grinding parameters (sieve openings diameter of the hammer mill: 2, 4, and 6 mm, roll gap: 0.15, 0.2, and 0.25 mm, feed rate: 0.1, 0.175, and 0.25 kg/cm min, and roll speed: 400, 500, and 600 rpm) on responses (protein content, fraction yield and grinding energy consumption). Sieve openings diameter expressed the highest impact on fraction yield while roll gap expressed the most dominant influence on protein content in the fraction and grinding energy consumption. The highest protein content obtained was 48.06%(dm) with fraction yield of 77.22%. A multi-response optimization procedure was performed... [more]

Scholars seek to recycle wasted energy to produce electricity by integrating thermoelectric generators (TEGs) with internal combustion engines (ICE), which rely on the electrical conductivity, β, of the thermal conductor strips. The TEG legs are alloyed from iron, aluminum and copper in a strip shape with specific characteristics that guarantee maximum thermo-electric transformation, which has fluctuated between a uniform, Gaussian, and exponential distribution according to the structure of the alloy. The ICE exhaust and intake gates were chosen as the TEG sides. The digital simulator twin model checks the integration efficiency through two sequential stages, beginning with recording the causes of thermal conductivity failure via filming and extracting their data by neural network procedures in the feed of the second stage, which reveal that the cracks are a major obstacle in reducing the TEG-generated power. Therefore, the interest of the second stage is predicting the cracks’ positio... [more]

(anise) is a dense vegetal matrix with considerable amounts of bioactive components known for its pharmacological properties. The optimization of extraction constitutes an important key to improving efficacy and avoiding wasting time. Within this framework, the present study was designed to select the most appropriate extractor solvent mixture to extract phenolic and flavonoids using Mixture Design Methodology. The concerned responses were the total phenolic content (TPC), total flavonoid content (TFC) and antioxidant ability examined by 2,2-diphenyl-l-picrylhydrazyl (DPPH) assay. Before mixture design optimization, a screening of solvents was conducted on ten polar and nonpolar solvents to choose the best solvents that give a maximum of total phenolic compounds. This first step has shown that water, ethanol and methanol were the best-used solvents. Later, an augmented centroid design investigated the solvent system’s optimization. The results of simultaneous optimization have shown th... [more]

Soil and groundwater systems have natural attenuation potential to degrade or detoxify contaminants due to biogeochemical processes. However, such potential is rarely incorporated into active remediation strategies, leading to over-remediation at many remediation sites. Here, we propose a framework for designing and searching optimal remediation strategies that fully consider the combined effects of active remediation strategies and natural attenuation potentials. The framework integrates machine-learning and process-based models for expediting the optimization process with its applicability demonstrated at a field site contaminated with arsenic (As). The process-based model was employed in the framework to simulate the evolution of As concentrations by integrating geochemical and biogeochemical processes in soil and groundwater systems under various scenarios of remedial activities. The simulation results of As concentration evolution, remedial activities, and associated remediation c... [more]

In recent years, we have seen an increasing dependency between different urban critical infrastructures, which raises the demands on their analysis and cybersecurity. Current open-source solutions do not provide simulations of interconnected data networks and power grids, which are essential for analysing of both infrastructures weak parts and reducing the risk of emerging threats. The main purpose of this paper is to describe the design of a simulation platform that provides this type of simulation to customers using the virtual user interface. The paper describes the development of a complex model of interconnected power and data infrastructures. Created virtualization platform that consists of several open-source tools is described in detail. Outputs of this paper can be used for analysis of critical infrastructures at the level of urban networks.

The energy consumption of production processes is increasingly becoming a concern for the industry, driven by the high cost of electricity, the growing concern for the environment and the greenhouse emissions. It is necessary to develop and improve energy efficiency systems, to reduce the ecological footprint and production costs. Thus, in this work, a system is developed capable of extracting and evaluating useful data regarding production metrics and outputs. With the extracted data, machine learning-based models were created to predict the expected energy consumption of an automotive spot welding, proving a clear insight into how the input values can contribute to the energy consumption of each product or machine, but also correlate the real values to the ideal ones and use this information to determine if some process is not working as intended. The method is demonstrated in real-world scenarios with robotic cells that meet Volkswagen and Ford standards. The results are promising,... [more]

Homogeneous catalysis is relevant for biodiesel fuel synthesis; however, it has the disadvantage of difficult separation of the catalyst. In the present work, heterogeneous catalysis was applied for rapeseed oil transesterification with methanol, while snail shells were used as a catalyst. CaO content in the catalyst was investigated. Transesterification reactions were carried out in a laboratory reactor, ester yield was analyzed using gas chromatography. Response surface methodology was used for process optimization. It was found that the optimum transesterification conditions when the reaction temperature is 64 °C are the following: a catalyst amount of 6.06 wt%, a methanol-to-oil molar ratio of 7.51:1, and a reaction lasting 8 h. An ester yield of 98.15 wt% was obtained under these conditions.

Improving surface quality attributes is a critical task in the production of micro-sized near-net-shaped components for end-use applications using additive manufacturing techniques. In the present study, we investigated the effect of fused deposition modeling (FDM) process parameters such as layer thickness, part orientation, raster width and raster angle on the surface quality characteristics of as-fabricated test specimens in order to develop the assembly of a flapping wing micro mechanism. Through a Box−Behnken design, a suitable experimental strategy was developed, and test specimens were manufactured. The performance of the experiments was statistically assessed using multi-response analysis of variance (ANOVA). The microstructures of the test specimens produced with various processing parameters were examined using a scanning electron microscope to identify micro surface flaws under various processing conditions. Furthermore, the optimal FDM parameters for improved surface qualit... [more]

A model that captures realistic viral growth dynamics has been developed based on a continuous and semi-continuous production model of an influenza A virus. This model considers viral growth parameters such as viral latency. It also captures the lag observed during the early production of viruses in a culture and explains later-phase growth dynamics. Furthermore, a sensitivity analysis was performed to investigate the effects of each input on each output. This revealed that production of defective interfering particles (DIPs) highly depends on the number of cells introduced to the viral reactor. The rationale for this is, as per the model, that a reduction in number of cells to be infected causes a reduction in DIPs formed as rate of viral infection decreases. Finally, a flowsheet model was created to optimize the continuous platform, including number of cells supplied to the viral reactor. From this, it was observed that the peak number of DIPs formed could be reduced by one-third. Fi... [more]

The research aims to produce, model, and optimise the mechanical properties of novel composite material through a structured multidisciplinary approach. The primary objective is to combine materials science, mechanical engineering, and statistical concepts to ensure Design for Manufacturability (DFM) from the industrial perspective. More specifically, the article is intended to determine the optimal mixture components and predictive model of Al-Si alloy with Al2O3 by accommodating multi-responses that enable DFM. The study adopted ASTM standards to prepare and test the novel composite material. Additionally, the Mixture Design of Experiment (DOE) approach was used to design the experimentation and subsequent analysis. In addition, microstructural images, Cox Response Trace plot, and Response Optimiser plot are effectively utilised to draw robust inferences. For multi-response modelling and optimisation, the composite material’s mechanical properties, like impact strength, hardness, den... [more]

The activated sludge process (ASP) is the most widely used biological wastewater treatment system. Advances in research have led to the adoption of Artificial Intelligence (AI), in particular, Nature-Inspired Algorithm (NIA) techniques such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) to optimize treatment systems. This has aided in reducing the complexity and computational time of ASP modelling. This paper covers the latest NIAs used in ASP and discusses the advantages and limitations of each algorithm compared to more traditional algorithms that have been utilized over the last few decades. Algorithms were assessed based on whether they looked at real/ideal treatment plant (WWTP) data (and efficiency) and whether they outperformed the traditional algorithms in optimizing the ASP. While conventional algorithms such as Genetic Algorithms (GAs), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) were found to be successfully employed in optimizatio... [more]

The reaction and separation sections are the keys to the methanol-to-olefins (MTO) chemical processes, and they should be optimized to reduce the cost of production. This work develops a framework for the simultaneous design and optimization of the reaction and distillation sections. An optimization model with shortcut and rigorous methods combined is established for distillation columns to improve accuracy and efficiency. With the auxiliary devices and the selection of utilities considered, the reaction and distillation sections are integrated to maximize profits. The genetic algorithm targets the optimal parameters, including the catalyst’s coke content and reaction temperature, each column’s operating pressure, and the allocation of utilities and auxiliary devices. For the studied MTO process, the optimal reaction temperature and catalyst’s coke content were identified to be 496 °C and 7.8%, respectively. The maximum profit is 15.3% greater than that identified with only the separat... [more]

Endosulfan lactone is a metabolite obtained from the biological oxidation of the insecticide endosulfan by action of the microorganisms present in the soil. This metabolite is more toxic and persistent than the parent compound. Therefore, it is extremely important to be able to determine the presence of this metabolite in the soil. However, accessible methods for extraction of endosulfan lactone in soil were not found in published literature. For this reason, the aim of this study was to evaluate two conventional methods of liquid−solid extraction for the determination of endosulfan lactone in solid substrate using two solvents (ethyl acetate and acetonitrile) and HPLC UV-VIS. The acetonitrile and rotary agitation extraction method was the one with the highest efficiency (97%), optimized using a factorial 32 response surface design, and validated in terms of linearity and precision. The linearity shown was r > 0.999 in a wide spike level (0.15−100 mg kg−1), with the detection limit (DL... [more]

Due to the substantial usage of fossil fuels, the utilization of lignocellulosic biomass as renewable sources for fuels and chemical production has been widely explored. The dissolution of lignocellulosic biomass in proper solvents is vital prior to the extraction of its important constituents, and ionic liquids (ILs) have been found to be efficient solvents for biomass dissolution. However, the high viscosity of ILs limits the dissolution process. Therefore, with the aim to enhance the dissolution of lignocellulosic biomass, a series of new ether-functionalized ILs with low viscosity values were synthesized and characterized. Their properties, such as density, viscosity and thermal stability, were analyzed and discussed in comparison with a common commercial IL, namely 1-butyl-3-methylimidazolium chloride (BMIMCl). The presence of the ether group in the new ILs reduces the viscosity of the ILs to some appreciable extent in comparison to BMIMCl. 1-2(methoxyethyl)-3-methylimidazolium ch... [more]

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.

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]

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]

This study investigated the use of brewing wastewater (BW) as the primary carbon source in the Postgate medium for the optimisation of sulphate reduction in acid mine drainage (AMD). The results showed that the sulphate-reducing bacteria (SRB) consortium was able to utilise BW for sulphate reduction. The response surface methodology (RSM)/Box−Behnken design optimum conditions found for sulphate reduction were a pH of 6.99, COD/SO42− of 2.87, and BW concentration of 200.24 mg/L with predicted sulphate reduction of 91.58%. Furthermore, by using an artificial neural network (ANN), a multilayer full feedforward (MFFF) connection with an incremental backpropagation network and hyperbolic tangent as the transfer function gave the best predictive model for sulphate reduction. The ANN optimum conditions were a pH of 6.99, COD/SO42− of 0.50, and BW concentration of 200.31 mg/L with predicted sulphate reduction of 89.56%. The coefficient of determination (R2) and absolute average deviation (AAD)... [more]

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]

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.

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]

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]

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]