Water is the most important resource of the Earth and is significantly utilized for agriculture, urbanization, industry, and population. This increases the demand for water; meanwhile, the climatic condition decreases the supply of it. A rise in temperature of 1 degree Celsius might dry up 20% of renewable water resources, and to circumvent the water scarcity, it is necessary to reuse, create, and consume less water without wasting it. Water desalination is the process used to reuse the used or saline water by promptly extracting the salt or unwanted minerals and producing fresh consumable water. Based on the International Desalination Association, around 300 million people rely on desalination and the people of the Middle East region rely the most upon it. Around 7% of desalination plants are located in countries such as Saudi Arabia, Bahrain, Kuwait, and the United Arab Emirates. Reverse osmosis (RO) is the relevant desalination process in this type of area however, the conventional... [more]

Conventional power systems have been heavily dependent on fossil fuel to meet the increasing energy demand due to exponential population growth and diverse technological advancements. This paper presents an optimal energy model and power management of an off-grid distributed energy system (DES) capable of providing sustainable and economic power supply to electrical loads. The paper models and co-optimizes multi-energy generations as a central objective for reliable and economic power supply to electrical loads while simultaneously satisfying a set of system and operational parameters. In addition, mixed integer nonlinear programing (MINLP) optimization technique is exploited to maximize power system generation between interconnected energy sources and dynamic electrical load with highest reliability and minimum operational and emission costs. Due to frequent battery cycling operation in the DES, rainflow algorithm is applied to the optimization result to estimate the depth of discharg... [more]

The concept of transportation electrification is proliferating due to its high impact on emission reduction. However, the increased usage of electric vehicles strains the power grid’s charging infrastructure. As a result, to reduce demand on the power grid, lower the emissions, and solve the intermittency problem of Renewable Energy Sources (RESs), a Nuclear−renewable Hybrid Energy System (N-R HES) is proposed in this research to support the load demand of a Fast Charging Station (FCS). Fulfilling the power demand of the FCS while reducing the generation cost and waste of energy is a vital issue, and hence, energy management with optimization is a must for the hybrid energy system. To address this issue, a model reference adaptive control with a mixed-integer linear programming-based energy management method was modelled to accomplish the charging station’s extensive performance. MATLAB/Simulink software has been used to model and simulate the proposed system, and the results are analy... [more]

The electric power quality has become a serious concern for electric utilities and end users owing to its undesirable effects on system capabilities and performance. Harmonic levels on power systems have been pronounced to a greater extent with the continuous growth in the application of solid-state and reactive power compensatory devices. Harmonics are the key constituents that are mainly responsible for power quality deterioration. Power system harmonics need to be correctly estimated and filtered to increase power quality. This research work focuses on accurate estimation of power system harmonics with the proposed hybrid weighted least-square multi-verse optimizer (WLS−MVO) based framework. Multi-verse optimizer replicates the phenomenon of the formation of new universes as described by multi-verse theory to solve complex real-world optimization problems. The proposed WLS−MVO framework is tested and validated by estimating the harmonics present in multiple test signals with differe... [more]

To simultaneously reduce automobile exhaust pollution to the environment and satisfy the demand for high-quality gasoline, the treatment of fluid catalytic cracking (FCC) gasoline is urgently needed to minimize octane number (RON) loss. We presented a new systematic method for determining an optimal operation scheme for minimising RON loss and operational risks. Firstly, many data were collected and preprocessed. Then, grey correlative degree analysis and Pearson correlation analysis were used to reduce the dimensionality, and the major variables with representativeness and independence were selected from the 367 variables. Then, the RON and sulfur (S) content were predicted by multiple nonlinear regression. A multi-objective nonlinear optimization model was established with the maximum reduction in RON loss and minimum operational risk as the objective function. Finally, the optimal operation scheme of the operating variable corresponding to the sample with a RON loss reduction greate... [more]

With the increasing reliance on global sourcing and the growth in the likelihood of disruptive incidents, today’s supply networks are more prone to unexpected natural and man-made disruptive events. In order to alleviate the losses caused by these disruptive events, when a large-scale event disrupts multiple suppliers simultaneously, a single or several critical suppliers should be selected from the disrupted ones to assist them to recover their production as soon as possible. The selection of these recovery suppliers is of great importance in the recovery process of the entire supply network. Thus, this paper proposes a recovery supplier selection method from the view of the supply network structure. Firstly, a tripartite graph-based supply model is proposed to depict a two-stage supply network, which consists of multiple manufacturers and suppliers as well as the diverse product supply-demand interdependence connecting them. To measure the impacts caused by supplier disruptions and t... [more]

In this paper, the vibration frequency of the stator of 3.6 MW fully immersed evaporative cooling permanent magnet semi-direct drive generators (ECPMSDDGs) was analyzed based on the fluid-structure coupling theory and solved by finite element analysis (FEA) simulation. The resonance noise reduction research under the typical working condition induced by two-phase flow and electromagnetic force was studied based on the method of structural optimization. In this paper, a structural optimal design method for the stator of the 3.6 MW ECPMSDDGs was presented. First of all, the frequency and characteristics of electromagnetic force of 3.6 MW ECPMSDDGs under the rated power were analyzed. Secondly, the frequency and characteristics of two-phase flow boiling vibration were analyzed based on the bubble oscillation theory of the two-phase flow and the experiment. Thirdly, the wet modal natural frequency of the stator core cooling structure was analyzed based on the fluid-structure coupling theor... [more]

This study was performed to optimize and validate Rancimat (Metrohm Ltd., Herisau, Switzerland) operational parameters including temperature, air-flow, and sample weight to minimize Induction-Time (IT) and IT-Coefficient-of-Variation (CV), using Response Surface Methodology (RSM). According to a Box−Behnken experimental design, walnut oil equivalent to 3-, 6-, or 9-g was added to each reaction vessel and heated to 100, 110, or 120 °C, while an air-flow equal to 10-, 15-, or 20-L·h−1 was forced through the reaction vessels. A stationary point was found per response variable (IT and CV), and optimal parameters were defined considering the determined stationary points for both response variables at 100 °C, 25 L·h−1, and 3.9 g. Optimal parameters provided an IT of 5.42 ± 0.02 h with a CV of 1.25 ± 0.83%. RSM proved to be a useful methodology to find Rancimat operational parameters that translate to accurate and efficient values of walnut oil IT.

Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization... [more]

Liquefied natural gas (LNG) is a clear and promising fossil fuel which emits less greenhouse gas (GHG) and has almost no environmentally damaging sulfur dioxide compared with other fossil fuels. An LNG import terminal is a facility that regasifies LNG into natural gas, which is supplied to industrial and residential users. Modeling and optimization of the LNG terminals may reduce energy consumption and GHG emission. A mixed-integer nonlinear programming model of the LNG terminal is developed to minimize the energy consumption, where the numbers of boil-off gas (BOG) compressors and low-pressure (LP) pumps are considered as integer variables. A case study from an actual LNG terminal is carried out to verify the practicality of the proposed method. Results show that the proposed approach can decrease the operating energy consumption from 9.15% to 26.1% for different seasons.

This study investigates the optimization of the hull form of a tanker, considering the operational efficiency in waves, in accordance with the recent Energy Efficiency Design Index regulation. For this purpose, the total resistance and speed loss of the ship under representative sea conditions were minimized simultaneously. The total resistance was divided into three components: calm water resistance, added resistance due to wind, and to waves. The first two components were calculated using regression formulas, and the last component was estimated using the strip theory, far-field method, and the short-wave correction formula. Next, prismatic coefficient, waterline length, waterplane area, and flare angle were selected as design variables from the perspective of operational efficiency. The hull form was described as a combination of cross-sectional curves. A combination of the method shifting these sections in the longitudinal direction and the Free-Form Deformation method was used to... [more]

The production of heterologous proteins for medical use is an important area of interest. The optimization of the bioprocesses includes the improvement of time, costs, and unit operations. Our study shows that a lectin fraction from Tepary bean (Phaseolus acutifolius) (TBLF) has cytotoxic effects on colon cancer cells and in vivo antitumorigenic activity. However, the low-yield, time-consuming, and expensive process made us focus on the development of a strategy to obtain a recombinant lectin using engineered Pichia pastoris yeast. Pure glycerol is one of the most expensive supplies; therefore, we worked on process optimization using crude glycerol from biodiesel production. Recombinant lectin (rTBL-1) production and purification were evaluated for the first time by an experimental design where crude glycerol (G65) was used and compared against pure glycerol (G99) in a controlled stirred-tank bioreactor with a fed-batch system. The recombinant lectin was detected and identified by SDS-... [more]

Traditionally, methanol is produced in large amounts from synthesis gas with heterogeneous Cu/ZnO/Al2O3 catalysts under steady state conditions. In this paper, the potential of alternative forced periodic operation modes is studied using numerical optimization. The focus is a well-mixed isothermal reactor with two periodic inputs, namely, CO concentration in the feed and total feed flow rate. Exploiting a detailed kinetic model which also describes the dynamics of the catalyst, a sequential NLP optimization approach is applied to compare optimal steady state solutions with optimal periodic regimes. Periodic solutions are calculated using dynamic optimization with a periodicity constraint. The NLP optimization is embedded in a multi-objective optimization framework to optimize the process with respect to two objective functions and generate the corresponding Pareto fronts. The first objective is the methanol outlet flow rate. The second objective is the methanol yield based on the total... [more]

The demand for safety and to provide safety are increasing, parallel with the growth of the need for mobility, transport and logistics. A big part of the demands and recommendations to provide safety in air traffic is related to the safety at and in the surroundings of the runways. The research focused on exploring the airport infrastructure; mainly with the aim of detecting and monitoring the deformations (cracks, displacements, etc.) of the runways which are causally connected with unusual landings or taking offs, with trips from the runways and with loss of control over the aircraft during the landings, taking offs and while moving the runways or taxiways, etc., and researching their effect on providing safety and the efficiency of the airports’ function. The research was executed at the Maribor Edvard Rusjan Airport in three phases; the first two were meant for geodetic measurements to determine vertical deformations and the third for supplementary measurements to determine static... [more]

The renewable energy microgrid is an effective solution for island energy supply with the advantages of low energy cost, environmental protection, and reliability. In this paper, an island renewable energy microgrid integrated with desalination units and electric vehicles is established to meet the self-satisfaction of the island’s sustainable electricity, fresh water, and transportation. The source side components of the system include photovoltaic cells, wind turbines, diesel generators, battery energy storage systems. A multi-objective dispatching optimization method based on the flexibility of electric vehicles and desalination units is proposed comprehensively considering the economy and renewable energy penetration indexes. The optimization objectives are minimizing the comprehensive operating cost, and the net load fluctuation. An improved multi-objective grey wolf optimizer is adopted to solve the dispatching problem. The system is modeled and simulated by MATLAB software. The... [more]

This study aimed to optimize the texture modification process of yellowfin sole (Pleuronectes aspera) to improve its quality characteristics for easier consumption by the elderly. Yellowfin sole was immersed in enzyme solution (Protamex:Neutrase = 1:2), marinated in herbal extract solution, and roasted by superheated steam. The product was evaluated for microbial, physicochemical, and sensory properties, as well as shelf life. Specifically, the optimal enzymatic treatment comprised a protease concentration of 1.00% (w/v) with an immersion time of 3.16 h. The optimal marination herb was determined to be bay leaves, as indicated by highest overall acceptance. The texture modification process led to lower hardness and higher overall acceptance values (76.23 kN/m2 and 8.38, respectively) compared with nonenzyme processed product (120.43 kN/m2, 7.43), also retaining high nutritional value and low trimethylamine levels. Shelf-life analysis indicated microbial activity was inhibited (not dete... [more]

The quality of product and process is one of the most important factors in achieving constructively and then functionally safe products in any industry. Over the years, the concept of Industry 4.0 has emerged in all the quality processes, such as nondestructive testing (NDT). The most widely used quality control methods in the industries of mechanical engineering, aerospace, and civil engineering are nondestructive methods, which are based on inspection by detecting indications, without affecting the surface quality of the examined parts. Over time, the focus has been on research with the fourth generation in nondestructive testing, i.e., NDT 4.0 or Smart NDT, as a main topic to ensure the efficiency and effectiveness of the methods for a safe detection of all types of discontinuities. This area of research aims at the efficiency of methods, the elimination of human errors, digitalization, and optimization from a constructive point of view. In this paper, we presented a magnetic partic... [more]

The numerical solution of the dynamic optimization problem is often sought for chemical processes, but the discretization of control variables is a difficult problem. Firstly, based on the analysis of the seagull optimization algorithm, this paper introduces the cognitive part in the process of a seagull’s attack behavior to make the group approach the best position. Secondly, the algorithm adds the mechanism of natural selection, where the fitness value is used to sort the population, and the best half is used to replace the worst half, so as to find out the optimal solution. Finally, the improved seagull optimization algorithm (ISOA) is combined with the unequal division method to solve dynamic optimization problems. The feasibility of the method is verified by three practical examples of dynamic optimization in chemical industry.

Nowadays, ever-increasing energy demands and the depletion of fossil fuels require efficient and environmentally friendly technologies for energy generation. In this context, energy systems integration makes for a very strong proposition since it results in energy saving, fuel diversification, and the supply of cleaner energy. To this end, it is of the utmost importance to realize the current developments in this field and portray the state of the art of renewable generation in integrated energy systems. This review evaluates the utilization of bioenergy in cogeneration and trigeneration systems. The statistical reports of bioenergy and combined heat and power deployments in 28 countries of the European Union are discussed. Then, the most common research objectives of biomass-fueled combined heat and power systems are classified into three primary performance analyses, namely, energy and exergy analysis, thermo-economic optimization, and environment assessment. The influencing paramete... [more]

In the present work, various objective functions were formulated and optimized using the mixed integer nonlinear programming and the generalized reduced gradient nonlinear method from the solver tool of Microsoft® Excel 2016, respectively. The CH3FO2, C2H4F2O, CH2F2O2, CH2F2O, C3H4F2, and the C2H2F2O molecules were found to meet structural feasibility constraints and physical properties from refrigerant molecules and have not previously been reported in the literature. These new refrigerants present global warming potential values similar to that from the R-134a and Freon 12 refrigerants and null ozone depletion potential. Moreover, these molecules are normally flammable, as similar as to R-134a refrigerant. The CH3FO2, C2H4F2O, CH2F2O2, C2H2F2O, and CH2F2O show toxicity values similar to R-134a and Freon 12 refrigerants.

The research on malware detection enabled by deep learning has become a hot issue in the field of network security. The existing malware detection methods based on deep learning suffer from some issues, such as weak ability of deep feature extraction, relatively complex model, and insufficient ability of model generalization. Traditional deep learning architectures, such as convolutional neural networks (CNNs) variants, do not consider the spatial hierarchies between features, and lose some information on the precise position of a feature within the feature region, which is crucial for a malware file which has specific sections. In this paper, we draw on the idea of image classification in the field of computer vision and propose a novel malware detection method based on capsule network architecture with hyper-parameter optimized convolutional layers (MalCaps), which overcomes CNNs limitations by removing the need for a pooling layer and introduces capsule layers. Firstly, the malware... [more]

Bio-based levulinic acid (LA), furfural (FF), and hydroxymethylfurfural (HMF) represent key chemical intermediates when biorefining biomass resources, i.e., either cellulose, glucose, hexoses, etc. (HMF/LA), or hemicellulose, xylose, and pentose (FF). Despite their importance, their online in situ detection by process analytical technologies (PATs), solubility, and its temperature dependence are seldom available. Herein, we report their solubility and temperature dependence by examining n-hexane, cyclohexane, benzene, toluene, 1,4-dioxane, diethyl ether, dichloromethane, tetrahydrofuran, ethyl acetate, acetone, dimethylformamide, acetonitrile, dimethyl sulfoxide, formic acid, n-butanol, n-propanol, ethanol, methanol, and water. These solvents were selected as they are the most common nonpolar, polar aprotic, and polar protic solvents. Fourier-transform infrared (FTIR) spectroscopy was applied as a fast, accurate, and sensitive method to the examined solutions or mixtures. The latter al... [more]

Most real-world problems that have two or three objectives are dynamic, and the environment of the problems may change as time goes on. For the purpose of solving dynamic multi-objective problems better, two proposed strategies (second-order difference strategy and random strategy) were incorporated with NSGA-III, namely SDNSGA-III. When the environment changes in SDNSGA-III, the second-order difference strategy and random strategy are first used to improve the individuals in the next generation population, then NSGA-III is employed to optimize the individuals to obtain optimal solutions. Our experiments were conducted with two primary objectives. The first was to test the values of the metrics mean inverted generational distance (MIGD), mean generational distance (MGD), and mean hyper volume (MHV) on the test functions (Fun1 to Fun6) via the proposed algorithm and the four state-of-the-art algorithms. The second aim was to compare the metrics’ value of NSGA-III with single strategy an... [more]

To improve the comprehensive benefits of the CCHP system, this paper proposes a bi-level optimal configuration model of the CCHP system based on the improved FCM clustering algorithm. Firstly, based on the traditional FCM clustering algorithm, the entropy method is used to introduce the PFS index and the Vp index in a weighted form to achieve a comprehensive evaluation of the clustering effect. The effectiveness of the improved FCM algorithm is verified by analyzing the clustering process of the load and meteorological data using the improved FCM algorithm. Then the best cluster number and fuzzy coefficient is found using the traversal method. Secondly, a bi-level configuration optimization model is constructed. The outer layer is the configuration optimization layer, and the inner layer is the operation optimization layer. The model is solved by combining the NSGA-II and PSO algorithms. Finally, a bi-level optimal configuration model is constructed for actual cases, and the clustering... [more]

This paper reviews actual sustainability assessments in the construction sector to define whether and how a Life Cycle Sustainability Assessment (LCSA) is applied and interpreted in this sector today. This industry has large shares in global energy (33%), raw material consumption (40%) and solid waste generation (40%). Simultaneously, it drives the economy and provides jobs. The LCSA is a method to identify environmental, social and economic impacts of products/services along their life cycles. The results of this study showed a mismatch between sectoral emissions and the number of LCSA-based impact evaluations. It was found that only 11% of papers reviewed assessed all three sustainability pillars. The economic and especially the social pillars were partly neglected. In Life Cycle Assessments (LCAs), 100% made use of Global Warming Potential (GWP) but only 30% assessed more than five indicators in total. In Life Cycle Costing (LCC), there were a variety of costs assessed. Depreciation... [more]