Using honeysuckle as raw material, chlorogenic acid (CGA) was extracted with different alcohols. Based on the single-factor experiment design, the relationship between each parameter and the response value was explored by Box−Behnken method to optimize the process conditions. Best extraction results were obtained under the conditions of solid-to-liquid ratio of 1:20, the ultrasonic time of 40 min, the ultrasonic vibrator power of 240 w, and the CGA extraction rate of 2.98%. The experimental data show that the extraction rate of CGA is related to the length of the alcohol carbon chain and the number of hydroxyl groups in the extractant. The results from this work can provide technical basis for the safe and efficient production of CGA from honeysuckle.

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 complex operating environment of gearboxes and the easy interference of early fault feature information make fault identification difficult. This paper proposes a fault diagnosis method based on a combination of whale optimization algorithm (WOA), variational mode decomposition (VMD), and deep transfer learning. First, the VMD is optimized by using the WOA, and the minimum sample entropy is used as the fitness function to solve for the K value and penalty parameter α corresponding to the optimal decomposition of the VMD, and the correlation coefficient is used to reconstruct the signal. Second, the reconstructed signal after reducing noise is used to generate a two-dimensional image using the continuous wavelet transform method as the transfer learning target domain data. Finally, the AlexNet model is used as the transfer object, which is pretrained and fine-tuned with model parameters to make it suitable for early crack fault diagnosis in gearboxes. The experimental results show t... [more]

Aimed at solving the large power consumption and high operating cost problems associated with the process of harvesting tiger nuts, the use of a conveying and soil-removing device which removes sandy soil while conveying tiger nuts was proposed. The device was numerically simulated with and without vibration using EDEM software. The results showed that the vibrating force was more conducive to the complete removal of sandy soil and the effective conveyance of tiger nuts. The simulation testing was carried out using spiral speed, vibration amplitude, and vibration frequency as the independent variables and conveyance efficiency, sandy soil removal rate, etc., as the dependent variables. The test results showed that the optimal parameter combination was a spiral speed of 107 r/min, a vibration amplitude of 8.5 mm, and a vibration frequency of 10.7 Hz, under which the theoretical value of conveyance efficiency was 80.39%, the sandy soil removal rate was 84.61%, and the variation coefficie... [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]

In this work, the possibility of limiting energy consumption in the manufacturing process of bioethanol to obtain biofuel was analysed. For this purpose, a control algorithm has been optimised while retaining the good quality of the control signals. New in this study is the correlation of the control algorithm not only with the signal’s quality, but also with the energy consumption in such an energy-intensive process as rectification. The rectification process in a periodic production system has been researched. The process was modelled on a test station with the distillation mixture capacity of 25 dm3. For the optimization, the following control algorithms have been applied: relay, PID and PID after modification to I-PD. The simulation was carried out on a transfer function model of the plant that has been verified on a real object, a rectification column. The simulations of energy consumption and control signal’s quality have been carried out in the Matlab®-Simulink environment after... [more]

Environmental concerns and soaring energy prices have brought huge pressure of energy saving and emission reduction to tissue paper mills. Electricity is one of the main energy sources of tissue paper mills. The production characteristics of tissue paper mills make it easy to decrease energy cost by using time-of-use (TOU) electricity tariffs. This study investigates the bi-objective energy-efficiency scheduling of tissue paper mills under time-of-use electricity tariffs, the objectives of which are makespan and energy cost. First, considering the processing energy cost, setup energy cost, and transportation energy cost, an energy cost model of a tissue paper mill under TOU electricity tariffs is established. Second, the energy-efficiency scheduling model under TOU electricity tariffs is built based on the energy cost model. Finally, on the basis of decomposition and teaching−learning optimization, this study proposes a novel multi-objective evolutionary algorithm and further combined... [more]

When considering the interaction between the impeller and diffuser, it is necessary to provide logical and systematic guidance for their matching optimization. In this study, the goal was to develop a comprehensive matching optimization strategy to optimize the impeller and diffuser of a mixed flow pump. Some useful tools and methods, such as the inverse design method, computational fluid dynamics (CFD), design of experiment, surrogate model, and optimization algorithm, were used. The matching optimization process was divided into two steps. In the first step, only the impeller was optimized. Thereafter, CFD analysis was performed on the optimized impeller to get the circulation and flow field distribution at the outlet of the impeller. In the second step of optimization, the flow field and circulation distribution at the inlet of the diffuser were set to be the same as the optimized impeller outlet. The results show that the matching optimization strategy proposed in this study is eff... [more]

Hydrogen is increasingly considered as an environmentally friendly energy source as it stores a large amount of chemical energy per unit mass (142 MJ·kg−1) that can be released without the emission of combustion by-products. The presented research is based on simulation modeling of biohydrogen production projects from agricultural waste. Based on the probability theory and mathematical statistics, the models of the variable market value of biohydrogen and natural gas are substantiated. The results of the research indicate that in 2019, projects regarding the production of biohydrogen from agricultural raw materials were mostly unprofitable for the investors. However, starting in 2030, the forecasted return on investment in biohydrogen production projects from agricultural raw materials indicates that such projects will be profitable for investors, and the number and scale of such projects will significantly increase worldwide.

In this article, chaotic search based constrained equilibrium optimizer algorithm (CS-CEOA) is suggested by integrating a novel heuristic approach called equilibrium optimizer with a chaos theory-based local search algorithm for solving general non-linear programming. CS-CEOA is consists of two phases, the first one (phase I) aims to detect an approximate solution, avoiding being stuck in local minima. In phase II, the chaos-based search algorithm improves local search performance to obtain the best optimal solution. For every infeasible solution, repair function is implemented in a way such that, a new feasible solution is created on the line segment defined by a feasible reference point and the infeasible solution itself. Due to the fast globally converging of evolutionary algorithms and the chaotic search’s exhaustive search, CS-CEOA could locate the true optimal solution by applying an exhaustive local search for a limited area defined from Phase I. The efficiency of CS-CEOA is stu... [more]

Simulated moving bed technology is applied in the field of pharmaceutical, petrochemical and fine chemistry. It shows capability in separating multicomponent mixtures up to high purities. In this work, an attempt was made to optimize the production of 1,1-diethoxybutane (DEB), using the simulated moving bed technology. A fixed bed model is made with good agreement with experimental results. This fixed bed model was expanded to a simulated moving bed model. This model was used to determine the optimum conditions regarding the switching time and flowrates in each section. From this model, the optimum switching time was found to be 2.4 min, and the ratio of liquid flowrate over the solid flowrate in Section 1Section 2Section 3 and Section 4 of the SMBR was found to be 4.24, 1.77, 3.03 and 1.35, respectively. Under those conditions, the productivity was 19.8 kg DEB per liter of adsorbent per day, and the desorbent consumption was 6.1 L of ethanol per kg of DEB. The results were obtained wi... [more]

While pipeline transport traditionally has been regarded as the best option for CO2 transport due to its low cost over short distances and important economies of scale, interest in vessel-based transport of CO2 is growing. While virtually all recent literature has focused on low pressure transport (at 7 barg and -46°C), the issue of optimal transport conditions, in terms of pressure, temperature and gas composition, is becoming more relevant as carbon capture and storage chains based on ship transport move closer towards implementation.
This study focuses on an in-depth comparison of the two primary and relevant transport pressures, 7 and 15 barg, for annual volumes up to 20 MtCO2/y and transport distances up to 2000 km. We also address the impact of a number of key factors on optimal transport conditions, including (a) transport between harbours versus transport to an offshore site, (b) CO2 pressure prior to conditioning, (c) the presence of impurities and of purity constraints, and... [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]

The demand for hydrogen in refineries is growing due to its importance as a sulfur capture element. Therefore, hydrogen management is critical for fulfilling demands as efficiently as possible. Through mathematical modeling, hydrogen network management can be better performed. Cost-efficient Mixed-Integer Linear Programming (MILP) and Mixed-Integer Nonlinear Programming (MINLP) optimization models for (re)designing were proposed and implemented in GAMS with two case studies. Linear programming has the limitation of no stream mixing allowed; therefore, to overcome this limitation, an algorithm-based procedure called the Virtual Compressor Approach was proposed. Based on the MILP optimal solution obtained, the streams and compressors were merged. As a result, the number of compressors was reduced, along with the inherent investment costs. An operational cost reduction of more than 28% (example 1) and 26% (example 2) was obtained with a linear model. The optimal MILP solution after rearra... [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]

The ability to use complex computer simulations in quantitative analysis and decision-making is highly desired in science and engineering at the same rate as computation capabilities and first-principle knowledge advance. Due to the complexity of simulation models, direct embedding of equation-based optimization solvers may be impractical and data-driven optimization techniques are often needed. In this work, we present a novel data-driven spatial branch-and-bound algorithm for simulation-based optimization problems with box constraints, aiming for consistent globally convergent solutions. The main contribution of this paper is the introduction of the concept data-driven convex underestimators of data and surrogate functions, which are employed within a spatial branch-and-bound algorithm. The algorithm is showcased by an illustrative example and is then extensively studied via computational experiments on a large set of benchmark problems.

The fourth industrial revolution based on information and communication technology (ICT and IoT) is converging into the overall realm of technology, economy and society, creating innovative changes. In line with these changes, research is being actively carried out to integrate information and communication with automation at construction sites. This study was started to analyze problems arising from inefficient operation of construction equipment through analysis of risks arising at construction sites and to provide solutions related to these problems. In order to provide the optimal route of movement of construction equipment, an expert survey was conducted and an algorithm was developed to establish the optimal route of movement by analyzing the weights for each item of the survey. The adequacy of the algorithm was determined by comparing the developed algorithm with the actual data of the construction site in operation, and a safe and productive route as well as problems related to... [more]

Industry, construction and transport are the three sectors that traditionally lead to the highest energy requirements [...]

Real-world problems such as scientific, engineering, mechanical, etc., are multi-objective optimization problems. In order to achieve an optimum solution to such problems, multi-objective optimization algorithms are used. A solution to a multi-objective problem is to explore a set of candidate solutions, each of which satisfies the required objective without any other solution dominating it. In this paper, a population-based metaheuristic algorithm called an artificial electric field algorithm (AEFA) is proposed to deal with multi-objective optimization problems. The proposed algorithm utilizes the concepts of strength Pareto for fitness assignment and the fine-grained elitism selection mechanism to maintain population diversity. Furthermore, the proposed algorithm utilizes the shift-based density estimation approach integrated with strength Pareto for density estimation, and it implements bounded exponential crossover (BEX) and polynomial mutation operator (PMO) to avoid solutions tra... [more]

With the development of integrated modular avionics (IMA), the dynamic reconfiguration of IMA not only provides great advantages in resource utilization and aircraft configuration, but also acts as a valid means for resource failure management. It is vital to ensure the correction of the IMA dynamic reconfiguration process. The analysis of the dynamic reconfiguration process is a significant task. The Architecture Analysis & Design Language (AADL) is widely used in complicated real-time embedded systems. The language can describe the system configuration and the execution behaviors, such as configuration changes. Petri net is a widely used tool to conduct simulation analysis in many aspects. In this study, a model-based analyzing method with multiple constraints for the IMA dynamic reconfiguration process was proposed. First, several design constraints on the process were investigated. Second, the dynamic reconfiguration process was modeled based on the AADL. Then, a set of rules for t... [more]

This tutorial and review of multi-objective optimization (MOO) gives a detailed explanation of the 5 steps to create, solve, and then select the optimum result. Unlike single-objective optimization, the fifth step of selection or ranking of solutions is often overlooked by the authors of papers dealing with MOO applications. It is necessary to undertake a multi-criteria analysis to choose the best solution. A review of the recent publications using MOO for chemical process engineering problems shows a doubling of publications between 2016 and 2019. MOO applications in the energy area have seen a steady increase of over 20% annually over the last 10 years. The three key methods for solving MOO problems are presented in detail, and an emerging area of surrogate-assisted MOO is also described. The objectives used in MOO trade off conflicting requirements of a chemical engineering problem; these include fundamental criteria such as reaction yield or selectivity; economics; energy requireme... [more]

Dynamic optimization problems (DOPs) are widely encountered in complex chemical engineering processes. However, due to the existence of highly constrained, nonlinear, and nonsmooth environment in chemical processes, which usually causes nonconvexity, multimodality and discontinuity, handling DOPs is not a straightforward task. Heat transfer search (HTS) algorithm is a relative novel metaheuristic approach inspired by the natural law of thermodynamics and heat transfer. In order to solve DOPs efficiently, a new variant of HTS algorithm named quadratic interpolation based simultaneous heat transfer search (QISHTS) algorithm is proposed in this paper. The QISHTS algorithm introduces three modifications into the original HTS algorithm, namely the effect of simultaneous heat transfer search, quadratic interpolation method, and population regeneration mechanism. These three modifications are employed to provide lower computational complexity, as well as to enhance the exploration and exploit... [more]

The conventional maximum power point tracking (MPPT) method fails in partially shaded conditions, because multiple peaks may appear on the power−voltage characteristic curve. The Pigeon-Inspired Optimization (PIO) algorithm is a new type of meta-heuristic algorithm. Aiming at this situation, this paper proposes a new type of algorithm that combines a new pigeon population algorithm named Parallel and Compact Pigeon-Inspired Optimization (PCPIO) with MPPT, which can solve the problem that MPPT cannot reach the near global maximum power point. This hybrid algorithm is fast, stable, and capable of globally optimizing the maximum power point tracking algorithm. Therefore, the purpose of this article is to study the performance of two optimization techniques. The two algorithms are Particle Swarm Algorithm (PSO) and improved pigeon algorithm. This paper first studies the mechanism of multi-peak output characteristics of photovoltaic arrays in complex environments, and then proposes a multi-... [more]

Most seed oils are edible while some are used generally as raw material for soap production, chocolate, margarine, and recently in biodiesel formulations as potential candidates capable of replacing fossil fuels which are costly and destructive to the environment. Oilseeds are a green and major reservoir which when properly exploited can be used sustainably for the production of chemicals at both the laboratory and industrial scales. Oil extraction is one of the most critical steps in seed oil processing because it determines the quality and quantity of oil extracted. Optimization of the extraction conditions for each extraction method enhances yield and quality meanwhile a carefully chosen optimization process equally has the potential of saving time and heat requirements with an associated consequence on cost reduction of the entire process. In this review, the techniques used to optimize oil extraction from plant materials which can be consulted by stakeholders in the field are brou... [more]

Mathematical optimization is the selection of the best element in a set with respect to a given criterion [...]