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Achieving the desired accuracy in time series forecasting has become a binding domain, and developing a forecasting framework with a high degree of accuracy is one of the most challenging tasks in this area. Combining different forecasting methods to construct efficient hybrid models has been widely reported in the literature regarding this challenge. Various types of hybrid models have been developed and successfully employed to improve forecasting accuracy. The well-known hybrid models can be generally categorized into four classes: (1) preprocessing-based, (2) parameter optimization-based, (3) components combination-based, and (4) postprocessing-based hybrid models. Despite the significant successes of hybrid models, efforts to access more accurate results face continued growth. Hybridization of hybrid models is a novel idea proposed to obtain extreme accuracy in recent literature, in which two or more hybrid classes are combined instead of conjoining the conventional individual forecasting methods. Although, in many publications, the aforementioned classes of hybrid models have been reviewed and analyzed in a wide variety of forecasting fields; no study is conducted to review the hybridization of hybrid models. This paper’s main contribution is to fill this gap and provide classification and comprehensive review of the current endeavors done in the hybridization of hybrid models in time series forecasting areas. Our searches indicate that more than 250 papers have been published in recent years utilizing hybridization of hybrid models. In this paper, these published papers have been classified regarding their different used combination strategies into four main categories, including (1) Hybridization with preprocessing-based hybrid models (HPH), (2) Hybridization with parameter optimization-based hybrid models (HOH), (3) Hybridization with components combination-based hybrid models (HCH) and, (4) Hybridization with postprocessing-based hybrid models (HSH). Each hybridization of the hybrid class is evaluated regarding the usage frequency, specific merits, and limitations. It can be inferred from reviewing articles that the hybridization of the hybrid concept, as a recent advancement in time series forecasting, can significantly improve traditional hybrid models’ accuracy. Furthermore, each category’s research gaps and some future research directions are identified in this paper.

Metal–polymer hybrid structures are becoming desirable due to their wide range of applications in the automotive, aerospace, biomedical and construction industries. Properties such as a light weight, high specific strength, and design flexibility along with the low manufacturing costs of metal–polymer hybrid structures make them widely attractive in several applications. One of the main challenges that hinders the widespread utilization of metal–polymer hybrid structures is the challenging dissimilar joining of metals to polymers. Friction stir welding (FSW) shows a promising potential in overcoming most of the issues and limitations faced in the conventional joining methods of such structures. Several works in the literature have explored the FSW of different metal-to-polymer combinations. In some of the works, the joints are examined based on processing parameter optimization, microstructural characteristics, and mechanical performances. It is, therefore, important to summarize the findings of these works as a means of providing a reference to researchers to facilitate further research on the utilization of FSW in joining metals to polymers. Thus, this work aims to present a comprehensive technical review on the FSW technique for joining metals to polymers by reviewing the reported literature findings on the impact of materials, tools, process parameters, and defects on the strength and microstructure of the produced joints. In addition, this work reviews and presents the latest practices aiming to enhance the metal–polymer joint quality that have been reported in the literature.

This work aims to explore crashworthiness of square aluminum/CFRP tubes with different hybrid schemes under quasi-static axial loading condition, and maximize their crashworthiness by performing multi-objective discrete robust optimization design. In the present study, metal/CFRP hybrid tubes with two hybrid schemes and their corresponding individual tubes are manufactured. The crushing process and crashworthiness indictors of all specimens are experimentally investigated under quasi-static axial crushing load. According to the experimental results, the AC hybrid tubes, made of outer aluminum square tube and internally adhered CFRP layers, show excellent energy-absorbing characteristics. Subsequently, numerical simulations are performed for the AC hybrid tubes to further investigate the effects of aluminum wall thickness, CFRP layer number and ply orientation on the energy-absorbing characteristics. It is found that the total energy absorption increases with the increasing tubal wall thickness of aluminum and CFRP layer, and ply orientation makes great contribution to the overall deformation modes and energy-absorbing characteristics of AC hybrid structures. Finally, a multi-objective discrete robust optimization has been conducted to optimize AC hybrid structures for the optimal crashworthy performance.

Currently, the need for resource efficiency and CO2 reduction is growing in industrial production, particularly in the automotive sector. To address this, the industry is focusing on lightweight components that reduce weight without compromising mechanical properties, which are essential for passenger safety. Hybrid designs offer an effective solution by combining weight reduction with improved mechanical performance and functional integration. This study focuses on a one-step manufacturing process that integrates forming and bonding of hybrid systems using compression molding. This approach reduces production time and costs compared to traditional methods. Conventional Post-Mold Assembly (PMA) processes require two separate steps to combine fiber-reinforced plastic (FRP) structures with metal components. In contrast, the novel In-Mold Assembly (IMA) process developed in this study combines forming and bonding in a single step. In the IMA process, glass-mat-reinforced thermoplastic (GMT) is simultaneously formed and bonded between two metal belts during compression molding. The GMT core provides stiffening and load transmission between the metal belts, which handle tensile and compressive stresses. This method allows to produce hybrid structures with optimized material distribution for load-bearing and functional performance. The process was validated by producing a lightweight hybrid brake pedal. Demonstrating its potential for efficient and sustainable automotive production, the developed hybrid brake pedal achieved a 35% weight reduction compared to the steel reference while maintaining mechanical performance under quasi-static loading

Application of multilevel inverters for higher voltage goals in industries has become more popular. In this study, new structures for symmetric, asymmetric and hybrid multilevel inverter are recommended. The proposed hybrid structure is used in high-voltage levels. The proposed structures can generate a great number of output voltage levels with minimum number of power electronic components such as insulated gate bipolar transistors (IGBTs) and gate drivers. For proposed asymmetric and hybrid inverter, new methods for determination of dc voltage sources values are presented. Comparison of the results of various multilevel inverters is presented to reflect the merits of the recommended structures. The operations of the proposed multilevel inverter structures are verified with the experimental and simulation results of an asymmetric 15-level prototype and a 19-level hybrid inverter. Fundamental frequency-switching method is applied to the new topologies to trigger the power switches for controlling the voltage levels generated on the output. Verification of the analytical results is performed using MATLAB/SIMULINK software.

Steel-carbon-fibre–reinforced thermoplastic hybrid structures are widely used in engineering. Their performances are highly constrained by interface strength. This paper applies the laser-assisted in situ consolidation process to achieve the direct additive manufacturing of steel-carbon fibre reinforced polyetheretherketone (CF/PEEK) hybrid structure, with upgraded interface bonding strength. PEEK film is introduced, as an interlayer, to improve the bonding strength between the steel and CF/PEEK prepreg tape. The influence of surface texture, PEEK film thickness, cooling condition, laser power, and placement rate on the interface bonding strength between the steel and CF/PEEK is investigated and discussed. Based on optimal parameters, the maximum lap shear strength of 14.9 MPa is achieved. In addition, the crystallinities of PEEK films are measured to interpret the failure mode. The pyrolysis kinetics model of CF/PEEK prepreg tape is established to investigate the influence of the process parameters during the laser-assisted in situ consolidation process. Finally, a steel-CF/PEEK hybrid shaft with high interface bonding performance is fabricated through the proposed method, which shows overwhelming potential for the steel-carbon-fibre–reinforced thermoplastic composite (CFRTP) hybrid structure manufacture. 

Adhesive bonding between steel and carbon-fiber-reinforced polymer (CFRP) composite leads to hybrid structures that combine the high strength and ductility of steel with the excellent specific strength and stiffness of CFRP composite. There is, however, a concern regarding possible galvanic corrosion when steel and carbon fibers are bonded together. One way to overcome this problem is placing glass fiber-reinforced polymer (GFRP) composite between the steel and CFRP composite, creating a more complex steel/GFRP/CFRP hybrid structure. Therefore, experimental and numerical studies on the mechanical behavior of the adhesive bonds between the steel sheet and the GFRP/CFRP hybrid composite were carried out. Among the different failure patterns, mode II was chosen for analysis because metal–polymer composite structures are usually subjected to bending, and debonding may occur due to in-plane shear stress. The tested steel/GFRP/CFRP hybrid structure was made of a hot-formed 22MnB5 boron steel sheet, intermediate single-ply bidirectional GFRP composite, and three-ply unidirectional CFRP composite. Additional mechanical tests were also carried out to determine various engineering constants of the components to simulate the debonding process. A finite element model of the steel/GFRP/CFRP hybrid structure with a typical cohesive interface was established and verified against the experimental data. The results showed that due to the use of various materials, the dominant failure modes in the hybrid structure under bending loading were a brittle fracture of the CFRP composite and debonding between the steel and the GFRP composite. However, the load-bearing capacity of the hybrid structure was five times greater than that of a non-reinforced steel sheet. In addition, its mass was only 28% greater than the non-reinforced steel sheet. The obtained results provided valuable conclusions and useful data to continue further research on the mechanical behavior of steel/GFRP/CFRP hybrid structures.

This work presents a data-driven design approach to hierarchical hybrid structures with multiple lattice configurations. Two design variables are considered for each lattice substructure, one discrete variable indicating the configuration type and the other continuous density variable determining the geometrical feature size. For each lattice configuration, a series of similar lattice substructures are sampled by varying the density variable and a corresponding data-driven interpolation model is built for an explicit representation of the constitutive behavior. To reduce the model complexity, substructuring by means of static condensation is performed on the sampled lattice substructures. To achieve hybrid structure with multiple lattice configurations, a multi-material interpolation model is adopted by synthesizing the data-driven interpolation models and the discrete lattice configuration variables. The proposed approach has proved capable of generating hierarchically strongly coupled designs, which therefore allows for direct manufacturing with no post-processing requirement as required for homogenization-based designs due to the assumption on scales separation.

A hydrothermal process was used to grow titanium dioxide (TiO2) nanorods on p-type silicon substrates, and a dip-coating process was then used to fabricate TiO2 thin film–nanorod hybrid structures. The nanorod-like structures were obtained for processing temperatures of 160°C and 180°C. The thin films were dip-coated on the nanorods with a withdrawal speed of 1 cm/min. Afterwards, thin film–nanorod hybrid structures were annealed at 500°C for 1 h. Morphological characterization carried out by scanning electron microscopy (SEM) studies confirmed the formation of nanorods. XRD and Raman studies confirmed the presence of anatase and rutile phases of TiO2-based hybrid structures. The oxide charge density (Qox) and the interface charge density (Dit) of the hybrid structures were measured from the capacitance–voltage (C–V) plot. Qox and Dit were calculated as 2.29 × 1012 cm−2 and 0.89 × 1012 eV−1 cm−2, respectively, for a temperature of 180°C and growth time of 60 min. The resistive switching properties of TiO2-based hybrid structures showed a good on/off ratio, and hence the hybrid structure-based device can be considered a suitable element for memory devices.

Efficient photoelectrochemical photodetectors based on WSe2/rGO have been fabricated using an annealing process. The initial performance enhancement of these devices was primarily attributed to the improved bandgap structure of WSe2 and the high carrier mobility of rGO, which facilitated an efficient transition of valence band electrons to the conduction band. Upon this understanding, a comparison between bulk WSe2 and WSe2 nanosheets (WSe2 NSs) was conducted. It was found that, at a bias voltage of 0.6 V, the photocurrent density of WSe2 NSs devices was 76% higher than that of similar bulk WSe2 devices, reaching 0.044 μA/cm2. Owing to the significant advantages of rGO, extensive testing of various WSe2 to rGO ratios was performed, identifying the precise composition that optimized photoelectric performance. Notably, under conditions of 0.5 M Na2SO4 electrolyte, 120 mW/cm2 irradiance, and 0.6 V bias potential, the devices achieved a photocurrent density of 0.64 μA/cm2, which is approximately 25.72 times higher than that of bulk WSe2 and 14.61 times more than WSe2 NSs. Moreover, the photoresponse trended upward with increasing irradiation intensity. Specifically, when the irradiation intensity was increased to 160 mW/cm2 and the bias voltage was raised from 0 V to 0.6 V, the photoresponsivity increased by 5.8 times, from 1 μA/W to 5.8 μA/W. The photodetectors constructed using the optimal WSe2/rGO ratio exhibited no significant performance degradation during a 4000-s cyclic on/off test, demonstrating their robustness under operational conditions. This study highlights the substantial potential of WSe2/rGO hybrids in enhancing the performance of photoelectrochemical photodetectors.