The rising amount of carbon fiber reinforced polymer (CFRP) composite waste requires new processes for reintroducing waste into the production cycle. In the present research, the objective is the design and study of a reuse process for carbon fibers and CFRP by mechanical recycling consisting of length and width reduction, obtaining rods and reintegrating them as fillers into a polymeric matrix. Preliminary studies are carried out with continuous and discontinuous unidirectional fibers of various lengths. The processing conditions are then optimized, including the length of the reinforcement, the need for a plasma surface treatment and/or for resin post-curing. The resin is thermally characterized by differential scanning calorimetry (DSC), while the composites are mechanically characterized by tensile strength tests, completed by a factorial design. In addition, the composites tested are observed by scanning electron microscopy (SEM) to study the fracture mechanics. Optimal processing... [more]

For machine learning algorithms, fine-tuning hyperparameters is a computational challenge due to the large size of the problem space. An efficient strategy for adjusting hyperparameters can be established with the use of the greedy search and Swarm intelligence algorithms. The Random Search and Grid Search optimization techniques show promise and efficiency for this task. The small population of solutions used at the outset, and the costly goal functions used by these searches, can lead to slow convergence or execution time in some cases. In this research, we propose using the machine learning model known as Support Vector Machine and optimizing it using four distinct algorithms—the Ant Bee Colony Algorithm, the Genetic Algorithm, the Whale Optimization, and the Particle Swarm Optimization—to evaluate the computational cost of SVM after hyper-tuning. Computational complexity comparisons of these optimization algorithms were performed to determine the most effective strategies for hyper... [more]

The optimal power flow (OPF) is an important tool for the secure and economic operation of the power system. It attracts many researchers to pay close attention. Many algorithms are used to solve the OPF problem. The decomposition-based multi-objective algorithm (MOEA/D) is one of them. However, the effectiveness of the algorithm decreases as the size of the power system increases. Therefore, an improved MOEA/D (IMOEA/D) is proposed in this paper to solve the OPF problem. The main goal of IMOEA/D is to speed up the convergence of the algorithm and increase species diversity. To achieve this goal, three improvement strategies are introduced. Firstly, the competition strategy between the barnacle optimization algorithm and differential evolution algorithm is adopted to overcome the reduced species diversity. Secondly, an adaptive mutation strategy is employed to enhance species diversity at the latter stage of iteration. Finally, the selective candidate with similarity selection is used... [more]

Among the pillars of decarbonization of the global energy system, energy efficiency plays a key role in reducing energy consumption across end-use (industry, transport and buildings) sectors. In industrial processes, energy efficiency can be improved by exploiting heat recovery via heat exchange between process streams. This paper develops a stage-wise superstructure-based mathematical programming model for the optimization of heat exchanger networks. The model incorporates rigorous formulation to handle process streams with phase change (condensation or evaporation), and is applied to a case study of an ethylene glycol production plant in Taiwan for minimizing utility consumption. The results show a compromise between steam savings and process feasibility, as well as how the model is modified to reflect practical considerations. In the preliminary analysis, with a substantial potential steam saving of 15,476 kW (28%), the solution involves forbidden matches that pose a hazard to the p... [more]

To improve the hydraulic performance of a new type of dishwasher pump and solve the multi-parameter optimization problem, a genetic algorithm was introduced to optimize the special design of the twin-volute structure. Six curvature radii of the twin-volute structure were defined as the optimization parameters, and 100 groups of design samples were generated based on the Latin hypercube sampling (LHS) method. The pump head and the efficiency were taken as the optimization objectives, i.e., to improve the efficiency as much as possible while ensuring that the head would not be lower than 2 m. The important parameters were identified via sensitivity analysis, and the optimization problem was solved in detail by using the multi-objective genetic algorithm (MOGA). The results showed that the external profile of the first to the fourth section of the twin-volute structure had the most significant effect on the pump head and efficiency. The response surface method (RSM) was used to select the... [more]

Electric vehicles (EVs) will be dominating the modes of transport in the future. Current limitations discouraging the use of EVs are mainly due to the characteristics of the EV battery and lack of easy access to charging stations. Charging schedules of EVs are usually uncoordinated, whereas coordinated charging offers several advantages, including grid stability. For a solar photovoltaic (PV)-based charging station (CS), optimal utilization of solar power results in an increased revenue and efficient utilization of related equipment. The solar PV and the arrival of EVs for charging are both highly stochastic. This work considers the solar PV forecast and the probability of EV arrival to optimize the operation of an off-grid, solar PV-based commercial CS with a battery energy storage system (BESS) to realize maximum profit. BESS supports the sale of power when the solar PV generation is low and subsequently captures energy from the solar PV when the generation is high. Due to contrastin... [more]

The helium-cooled pebble bed (HCPB) breeding blanket (BB) is one of the two driver-blanket candidates for the European DEMO fusion reactor. Recent design activities were focused, among other objectives, on the achievement of an efficient shielding system to adequately protect the vacuum vessel (VV) and toroidal field coils (TFCs). Several shielding options have been studied in terms of architecture (e.g., in-BB shield and ex-BB shield) and materials (e.g., B4C, WC, WB, YHx, and ZrHx). In this study, the B4C material was selected as the most attractive option considering not only shielding performance but also availability, industrialization, experience, and cost factors. Subsequently, we performed a parametric study by implementing different thicknesses of a B4C external shield and reporting information of its effect on shielding performance, structural behavior, swelling and tritium breeding. Furthermore, a detailed structure for the VV was developed considering an internal layered co... [more]

In long-distance gas transmission pipelines, there are many booster compressor stations consisting of parallel compressors that provide pressure for the delivery of natural gas. So, it is economically important to optimize the operation of the booster compressor station. The booster compressor station optimization problem is a typical mixed integer nonlinear programming (MINLP) problem, and solving it accurately and stably is a challenge. In this paper, we propose an improved salp swarm algorithm based on good point set, adaptive population division and adaptive inertia weight (GASSA) to solve this problem. In GASSA, three improvement strategies are utilized to enhance the global search capability of the algorithm and help the algorithm jump out of the local optimum. We also propose a constraint handling approach. By using semi-continuous variables, we directly describe the on or off state of the compressor instead of using auxiliary binary variables to reduce the number of variables a... [more]

This paper proposes a modified quasi-opposition-based grey wolf optimization (mQOGWO) method to solve complex constrained optimization problems. The effectiveness of mQOGWO is examined on (i) 23 mathematical benchmark functions with different dimensions and (ii) four practical complex constrained electrical problems that include economic dispatch of 15, 40, and 140 power generating units and a microgrid problem with different energy sources. The obtained results are compared with the reported results using other methods available in the literature. Considering the solution quality of all test cases, the proposed technique seems to be a promising alternative for solving complex constrained optimization problems.

Latent heat storage technology is widely used in solar power generation. Aiming to enhance the energy utilization rate to a greater extent, an innovative fan-shaped structure has been proposed to construct the metal fins of the shell-and-tube thermal storage device. The enthalpy method is used to simulate the heat storage process and focuses on the influence of inlet conditions on heat transfer. The influence of the fin structure on the melting properties of phase change material has been studied. The results show that increasing inlet temperature and inlet flow rate is a convenient and effective way to improve energy efficiency. As the inlet temperature is increased from 343 K to 358 K, the total heat storage and energy efficiency are improved by 13.4% and 10.2%, respectively, and the melting time is reduced by 36.2%. As the flow rate is increased from 3 L/min to 9 L/min, the complete melting time is reduced by 33.4%. Energy efficiency peaks at a flow rate of 5 L/min. Reasonable optim... [more]

Catalytic upgrading of vapors from pyrolysis of triglycerides materials is a promising approach to achieve better conversions of hydrocarbons and production of liquid biofuels. Catalytic cracking often shows incomplete conversion due to distillation of initial reaction products and the addition of a second catalytic reactor, whereas pyrolytic vapors are made in contact to a solid catalyst was applied to improve the physical-chemical properties and quality of bio-oil. This work investigated the effect of catalyst content and reaction time by catalytic upgrading from pyrolysis vapors of residual fat at 450 °C and 1.0 atmosphere, on the yields of reaction products, physicochemical properties (density, kinematic viscosity, refractive index, and acid value), and chemical composition of organic liquid products (OLP), over a catalyst fixed bed reactor, in semi pilot scale. Pellets of red mud chemically activated with 1.0 M HCl were used as catalysts. The thermal catalytic cracking of residual... [more]

Refrigeration systems based on cooling towers and chillers are widely used equipment in industrial buildings, such as shopping centers, gas and oil refineries and power plants, among many others. Cooling towers are used to recover the heat rejected by the refrigeration system. In this work, the refrigeration is composed of cooling towers dotted with ventilators and compression chillers. The growing environmental concerns and the current scenario of scarce water and energy resources have lead to the adoption of actions to obtain the maximum energy efficiency in such refrigeration equipment. This backs up the application of computational intelligence to optimize the operating conditions of the involved equipment and cooling processes. In this context, we utilize multi-objective optimization algorithms to determine the optimal operational setpoints of the cooling system regarding the cooling towers, its fans and the included chillers. We use evolutionary multi-objective optimization to pr... [more]

Photovoltaic (PV) systems have been used extensively worldwide over the past few years due to the mitigation of fossils fuels; it is the best source because of its eco-friendly nature. In PV systems, the main research area concerns its performance under partial shading (PS) and complex partial shading (CPS) conditions. PV sources perform perfectly under ideal conditions, but under practical conditions, their performance depends upon many factors, including shading conditions, temperature, irradiance, and the angle of inclination, which can bring a photovoltaic or solar system into a PS or CPS condition. In these conditions, many power peaks appear, and it is hard to find the global peak among many local peaks. The ability to track the maximum power peak and maintain it to avoid fluctuations depends on the maximum power point tracking (MPPT) technique used in a photovoltaic system. This article is based on the implementation of a hybrid algorithm, combining Harris hawk’s optimization (H... [more]

The aim of this work is to optimize biogas production from thermophilic dry anaerobic digestion (AD) of the organic fraction of municipal solid waste (OFMSW) by comparing various operational strategies to reduce ammonia inhibition. A pilot-scale plug flow reactor (PFR) operated semi-continuously for 170 days. Three scenarios with different feedstock, namely solely OFMSW, OFMSW supplemented with structural material, and OFMSW altered to have an optimal carbon-to-nitrogen (C/N) ratio, were tested. Specific biogas production (SGP), specific methane production (SMP), the biogas production rate (GPR), and bioenergy recovery were evaluated to assess the process performance. In addition, process stability was monitored to highlight process problems, and digestate was characterized for utilization as fertilizer. The OFMSW and the structural material revealed an unbalanced content of C and N. The ammonia concentration decreased when the optimal C/N ratio was tested and was reduced by 72% if com... [more]

The cogeneration of power and heat was investigated for Biomass Boiler−Organic Rankine Cycle (BB−ORC) plants with the characteristics of typical units, such as the 1 MWel Turboden ORC 10 CHP. The thermodynamic analysis of the ORC unit was undertaken considering forty-two (42) dry and isentropic candidate pure working fluids. Only subcritical Rankine cycles were considered, and the pinch point temperature differences for the evaporation and condensation heat exchangers were kept constant at 10 °C in all cases. The study provides an original and unique screening of almost all pure working fluids that are considered appropriate in the literature under the same operation and optimization conditions and compiles them into a single reference. In its conclusions, the study provides useful fluid selection and design guidelines, which may be easily followed depending on the optimization objective of the ORC designer or operator. In general, hydrocarbons are found to lie in the optimum middle ra... [more]

Against a background of the energy internet and low-carbon electricity, regional integrated energy system (RIES) has become a key way to achieve sustainable energy development, leading to reduced operating costs and system carbon emissions, and improved system operating efficiency. This paper puts forward a low-carbon economic dispatching optimization method for RIES with a heating network and power-to-gas (P2G). First, the heating network model and the mathematical model of P2G were constructed. Second, the carbon trading mechanism was introduced, the objective function being: to minimize the sum of the system operating cost and carbon trading cost; and ensure that the balance of cooling, heating, electric power, and the operating constraints—of RIES and the heating network—were comprehensively considered. Finally, the CPLEX optimization software simulation was used. The results show that the proposed method can take into account both low-carbon and economic factors, and can provide a... [more]

The main problem of fluid sampling during well testing of reservoirs with near-critical fluids (gas condensate and volatile oil) is due to the fact that even a small pressure drawdown usually leads to the formation of a two-phase mixture in the bottom hole area, and it is almost impossible to take representative samples with downhole samplers or a formation tester. Sampling via test-separator and the current non-separation methods are also imperfect. An alternative method—MIKS (Multiphase IsoKinetic Sampling)—of gas condensate well testing was proposed, which is based on emulsifying a multiphase flow to particles of about 1−10 μm. Thereby MIKS would eliminate the problem of particle slippage in a homogeneous flow and enables high-quality sampling directly from the flowmeter line. The initial formation fluid is characterized by the maximum value of the condensate-gas ratio (CGR). Therefore, first, the well effluent would be adjusted to the mode with the maximum CGR using a choke manifol... [more]

Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model... [more]

This paper presents an energy-saving strategy that was applied to a parallel variable frequency pump system of a water circulation pumping station. Firstly, the mathematical model of shaft power consumption for the parallel pump system was established using quadratic polynomial fitting, with some constraints configured according to the system’s water supply demands. Then, the algorithm program was designed with the goal of minimizing the energy consumption through the application of an improved differential evolution algorithm. Additionally, the energy consumption model and constraints were integrated and simplified in order to adapt to the algorithm calculation. In the end, the algorithm was implemented according to the pump design parameters and supply targets of the pumping station. Meanwhile, a comparison was done between the differential evolution (DE) algorithm and the genetic algorithm (GA). Furthermore, an experimental test was conducted in an aluminum company in order to verif... [more]

The scramjet of hypersonic vehicles faces severe high-temperature challenges, but the heat sink available for scramjet cooling is extremely finite. It is necessary to optimize its power and thermal management system (PTMS) with a finite heat sink of hydrocarbon fuel. This paper proposes a two-level optimization method for the PTMS of hypersonic vehicles at Mach 6. The PTMS is based on a supercritical carbon dioxide (SCO2) closed Brayton cycle, and its heat sink is airborne hydrocarbon fuel. System-level optimization aims to obtain the optimal system parameters for the PTMS. The minimum fuel weight penalty and the minimum heat sink consumption of fuel are the optimization objectives. The segmental (SEG) method is used to analyze the internal temperature distribution of fuel−SCO2 heat exchangers in the system-level optimal solution set. This ensures the selected optimal solutions meet the requirement of a pinch temperature difference greater than or equal to 10 °C. Further, the component... [more]

With the increasing interdependence among energies (e.g., electricity, natural gas and heat) and the development of a decentralised energy system, a novel retail pricing scheme in the multi-energy market is demanded. Therefore, the problem of designing a customised multi-energy pricing scheme for energy retailers is investigated in this paper. In particular, the proposed pricing scheme is formulated as a bilevel optimisation problem. At the upper level, the energy retailer (leader) aims to maximise its profit. Microgrids (followers) equipped with energy converters, storage, renewable energy sources (RES) and demand response (DR) programs are located at the lower level and minimise their operational costs. Three hybrid algorithms combining metaheuristic algorithms (i.e., particle swarm optimisation (PSO), genetic algorithm (GA) and simulated annealing (SA)) with the mixed-integer linear program (MILP) are developed to solve the proposed bilevel problem. Numerical results verify the feas... [more]

A multilayer soil structure model is fundamental to design grounding systems. A new method is presented to invert the structure parameters of horizontal multilayer soil. The structure parameters of soil are determined by analyzing the kernel function of the integral equation of the apparent resistivity. The essence of the proposed method avoids the difficulties encountered in general optimization methods; namely, the calculation of the apparent resistivity and its derivative.

Gas Brayton cycles have been considered the next promising power cycles for microreactors. Especially the open-air and closed supercritical CO2 (S-CO2) Brayton cycles have received attention due to their high thermal efficiency and compact component sizes when compared to the steam Rankine cycle. In this research, the performances of the open-air and closed S-CO2 Brayton cycle at microreactor power range are compared with polytropic turbomachinery efficiency. When optimizing the cycle, three different optimization parameters are considered in this paper: maximum efficiency, maximum cycle specific work, and maximum of the product of both indicators. For the air Brayton cycle, the maximum of the product of both indicators allows to consider both efficiency and specific work while optimizing the cycle. However, for the S-CO2 Brayton cycle, the best performing conditions follow either maximum efficiency or the maximum cycle specific work conditions. In general, the S-CO2 power cycle should... [more]

The design of moisture-durable building enclosures is complicated by the number of materials, exposure conditions, and performance requirements. Hygrothermal simulations are used to assess moisture durability, but these require in-depth knowledge to be properly implemented. Machine learning (ML) offers the opportunity to simplify the design process by eliminating the need to carry out hygrothermal simulations. ML was used to assess the moisture durability of a building enclosure design and simplify the design process. This work used ML to predict the mold index and maximum moisture content of layers in typical residential wall constructions. Results show that ML, within the constraints of the construction, including exposure conditions, does an excellent job in predicting performance compared to hygrothermal simulations with a coefficient of determination, R2, over 0.90. Furthermore, the results indicate that the material properties of the vapor barrier and continuous insulation layer... [more]

Many repeated manual feature adjustments and much heuristic parameter tuning are required during the debugging of machine learning (ML)-based transient stability assessment (TSA) of power systems. Furthermore, the results produced by ML-based TSA are often not explainable. This paper handles both the automation and interpretability issues of ML-based TSA. An automated machine learning (AutoML) scheme is proposed which consists of auto-feature selection, CatBoost, Bayesian optimization, and performance evaluation. CatBoost, as a new ensemble ML method, is implemented to achieve fast, scalable, and high performance for online TSA. To enable faster deployment and reduce the heavy dependence on human expertise, auto-feature selection and Bayesian optimization, respectively, are introduced to automatically determine the best input features and optimal hyperparameters. Furthermore, to help operators understand the prediction of stable/unstable TSA, an interpretability analysis based on the S... [more]