The demand for new novel flavour and fragrance (F&F) molecules has boosted the need for a systematic approach to designing fragrance molecules. However, the F&F-related industry still relies heavily on experimental approaches or on existing databases without considering the consequences resulting from changes in concentration, which could omit potential fragrances. Computer-aided molecular design (CAMD) has great potential to identify novel molecular structures to be used as fragrances. Using CAMD for this purpose requires models to predict the olfaction properties of molecules. A rough set-based machine learning (RSML) approach is used to develop an interpretable predictive model for odour characteristics in this work. New rule-based models are generated from RSML based on the dilution and a number of different topological indices which identify the structure-odour relationship of fragrance molecules. The most prominent rules are selected and formulated as constraints in a CAMD optimi... [more]

An experimentally validated CFD model was developed for lab-scale arsenic (As) fixed-bed columns using COMSOL Multiphysics. The effects of key factors such as the adsorbent bed depth, the feed flow rate, and the initial As concentration (conc.) on the overall As removal performance were investigated. Subsequently, the CFD was combined with response surface methodology (RSM) to optimize process conditions and examine main and interaction effects of these factors on model responses, i.e., the As removal efficiency and the bed saturation time. The ANOVA results suggested that quadratic regression models were highly significant for both responses. The established regression model equations predicted the response values closer to CFD measurements. It was found that, compared with the initial As conc. and the feed flow rate, the effect of the bed depth was more significant. Moreover, both the As removal efficiency and the bed saturation time were increased reasonably with the increasing bed... [more]

To improve the battery state of charge (SOC) of the electric vehicle (EV), this paper proposes a master−slave electro-hydraulic hybrid electric vehicle (MSEH-HEV). The MSEH-HEV uses a planetary row as the core transmission component to realize the interconversion between mechanical energy, hydraulic energy and electrical energy. Meanwhile, this paper introduces the six working modes in vehicle operation, matches the parameters of key components to the requirements of the vehicle’s performance and designs a rule-based control strategy to dominate the energy distribution and the operating mode switching. The research uses AMESim and Simulink to perform a co-simulation of the MSEH-HEV, and the superiority of MSEH-HEV is testified by comparing it with an AMESim licensed EV. The simulation results show that in the Economic Commission for Europe (ECE) and the Extra Urban Driving Cycle (EUDC), the MSEH-HEV has a 15% reduction in battery consumption, and the motor peak torque is greatly reduce... [more]

Desalination is set to become a major source of drinking water in several Middle Eastern countries over the coming decades. Solar distillation is a simple power-independent method of water desalination, which can be carried out in active or passive modes. This study is among the first attempts to investigate the possibility of desalinating brackish groundwater resources under the threat of saltwater intrusion in the southern areas of Razavi Khorasan province in Iran. For this purpose, a pilot solar distillation unit was constructed to analyze the effects of the unit orientation, depth of the water pool, atmospheric conditions, input salinity, and flow continuity on the solar distillation performance. The results showed that the unit exhibited the highest efficiency when it had a 3 cm deep water pool. It was oriented facing southward while operating a continuous flow for at least 3 days under sunny weather conditions. It was found that among the studied parameters, the unit orientation... [more]

This study undertakes the line balancing problem while allocating reconfigurable machines to different workstations. A multi-objective model is used to analyze the position of workstations, assignment of configurations to workstations, and operation scheduling in a reconfigurable manufacturing environment. A model is presented that comprises the objectives of the Total Time (TT), the Line Efficiency Index (LEI), and the Customer Satisfaction Index (CSI). The objective is to minimize the completion time and maximize the efficiency of a production line. The proposed model combines the Simple Line Balancing Problems Type 2 and Type E in the form of SLBP-2E. The presented problems are addressed by using a heuristic solution approach due to non-polynomial hard formulation. The heuristic approach is designed to assess different solutions based on no repositioning, separate repositioning of workstations and configuration, and simultaneous repositioning of workstations and configurations. A de... [more]

Currently, reducing energy consumption and fossil fuel emissions are key factors placed in the first position on the European agenda. District heating technology is an attractive solution, able to satisfy the energy and environmental goals of policymakers and designers. In line with this, a different approach to planning a district heating grid based on the optimization of building clusters is presented. The case study is Wilhelmsburg, a district of Hamburg city. This approach also investigates the usage of industrial waste heat as the grid’s heat source, which is CO2-neutral. First, the data acquisition regarding the buildings’ location and heat demand are described in detail. Based on the derived data and the source of the industrial waste heat, the district heating grid is created by clustering the buildings and connecting the obtained nodes. Furthermore, the grid’s efficiency is improved by eliminating nodes, which are too distant from the heat source, or have lower heat demand. Fi... [more]

Based on a combination of physical and simulation experiments, a set of basic physical characteristic parameters and contact parameters suitable for granular fungal fertilizers were calibrated, which up to now have received little attention. The physical morphological characteristic parameters (overall dimension, 1000 grain weight, density, and moisture content), mechanical characteristic parameters (Poisson’s ratio, elastic modulus, and shear modulus), and contact parameters (static friction coefficient, rolling friction coefficient and recovery coefficient) of particles were measured through physical experiments. The parameters were screened for significance using the Plackett−Burman test. The results showed that the impact recovery coefficient, static friction coefficient, and rolling friction coefficient for the granular fungal fertilizer particles had a significant effect on the repose angle. The best range for the three parameters was determined using the steepest climbing test.... [more]

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]