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This study focuses on the structural performance assessment of hybrid polymer composites for pick-and-place robot grippers used in critical infrastructure. This research involved the creation of composite materials with different nanoparticle concentrations, followed by extensive testing to assess the mechanical properties of the materials, such as strength, stiffness and durability.

The composites comprised bidirectional interply inclined carbon fibers (C), S-glass fibers (SG), E-glass (EG), an epoxy matrix and silica nanoparticles (SNiPs). During construction, the composite materials must be carefully layered using quasi-static sequence techniques (45°C1/45°SG2/45°EG2/45°C1/45°EG2/45°SG2/45°C1) to obtain the epoxy matrix reinforcement and bonding using 0, 2, 4 and 6 wt. % of silica nanoparticles.

According to various test findings, the 4 wt. % of SNiPs added to polymer plates exhibits the maximum strength outcomes. The average results of the tensile and flexural tests for the polymer composite plates with 4 wt. % addition SNiPs were 127.103 MPa and 223.145 MPa, respectively. The average results of the tensile and flexural tests for the plates with 0 wt.% SNiPs were 115.457 MPa and 207.316 MPa, respectively.

The authors hereby attest that the research paper they have submitted is the result of their own independent and unique labor. All of the sources from which the thoughts and passages were derived have been properly credited. The work has not been submitted for publication anywhere and is devoid of any instances of plagiarism.

1. The study enhances the engineering materials for innovative applications.

2. The study explores the mechanical behavior of carbon/S-glass/E-glass fiber composites.

3. Silica nanoparticles were enhancing mechanical characteristics of the composite structure.

The study enhances the engineering materials for innovative applications.

The study explores the mechanical behavior of carbon/S-glass/E-glass fiber composites.

Silica nanoparticles were enhancing mechanical characteristics of the composite structure.

Business process modeling faces a difficult balance: on the one hand, organizations seek to enact, control and automate business processes through formal structures (procedures and rules). On the other hand, organizations also seek to embrace flexibility, change, innovation, value orientation, and dynamic capabilities, which require informal structures (unique user experiences). Addressing this difficulty, the authors propose the composite approach, which integrates formal and informal process structures. The composite approach adopts a socio-material conceptual lens, where both material and human agencies are supported.

The study follows a design science research methodology. An innovative artifact – the composite approach – is introduced. The composite approach is evaluated in an empirical experiment.

The experimental results show that the composite approach improves model understandability and situation understandability.

This research explores the challenges and opportunities brought by adopting a socio-material conceptual lens to represent business processes.

The study contributes an innovative hybrid approach for modeling business processes, articulating coordination and contextual knowledge. The proposed approach can be used to improve model understandability and situation understandability. The study also extends the socio-material conceptual lens over process modeling with a theoretical framework integrating coordination and contextual knowledge.

Ensuring the early detection of structural issues in aircraft is crucial for preserving human lives. One effective approach involves identifying cracks in composite structures. This paper employs experimental modal analysis and a multi-variable Gaussian process regression method to detect and locate cracks in glass fiber composite beams.

The present study proposes Gaussian process regression model trained by the first three natural frequencies determined experimentally using a roving impact hammer method with crystal four-channel analyzer, uniaxial accelerometer and experimental modal analysis software. The first three natural frequencies of the cracked composite beams obtained from experimental modal analysis are used to train a multi-variable Gaussian process regression model for crack localization. Radial basis function is used as a kernel function, and hyperparameters are optimized using the negative log marginal likelihood function. Bayesian conditional probability likelihood function is used to estimate the mean and variance for crack localization in composite structures.

The efficiency of Gaussian process regression is improved in the present work with the normalization of input data. The fitted Gaussian process regression model validates with experimental modal analysis for crack localization in composite structures. The discrepancy between predicted and measured values is 1.8%, indicating strong agreement between the experimental modal analysis and Gaussian process regression methods. Compared to other recent methods in the literature, this approach significantly improves efficiency and reduces error from 18.4% to 1.8%. Gaussian process regression is an efficient machine learning algorithm for crack localization in composite structures.

The experimental modal analysis results are first utilized for crack localization in cracked composite structures. Additionally, the input data are normalized and employed in a machine learning algorithm, such as the multi-variable Gaussian process regression method, to efficiently determine the crack location in these structures.

The objective of the present work is to present the design optimization of composite cylindrical shell subjected to an axial compressive load and lateral pressure.

A novel optimization method is developed to predict the optimal fiber orientation in composite cylindrical shell. The optimization is carried out by coupling analytical and finite element (FE) results with a genetic algorithm (GA)-based optimization scheme developed in MATLAB. Linear eigenvalue were performed to evaluate the buckling behaviour of composite cylinders. In analytical part, besides the buckling analysis, Tsai-Wu failure criteria are employed to analyse the failure of the composite structure.

The optimal result obtained through this study is compared with traditionally used laminates with 0, 90, ±45 orientation. The results suggest that the application of this novel optimization algorithm leads to an increase of 94% in buckling strength.

The proposed optimal fiber orientation can provide a practical and efficient way for the designers to evaluate the buckling pressure of the composite shells in the design stage.

Three-dimensional (3D) printing is popular for many applications including the production of photocatalysts. This paper aims to focus on developing of 3D-printed photocatalyst-nano composite lattice structure. Digital light processing (DLP) 3D printing of photocatalyst composites was performed using photosensitive resin mixed with 0.5% Wt. of TiO₂ powder and varying amounts (0.025% Wt. to 0.2% Wt.) of graphene nanoplatelet powder. The photocatalytic efficiency of DLP 3D-printed photocatalyst TiO₂ composite was investigated, and the effects of nano graphite powder incorporation on the photocatalytic activity, thermal and mechanical properties were investigated.

Methods involve 3D computer-aided design modeling, printing parameters and comprehensive characterization techniques such as structural equation modeling, X-ray diffraction, thermogravimetric analysis, Fourier-transform infrared (FTIR) and mechanical testing.

Results highlight successful dispersion and characteristics of TiO₂ and graphene nanoplatelet (GNP) powders, intricate designs of 3D-printed lattice structures, and the influence of GNPs on thermal behavior and mechanical properties.

The study suggests applicability in wastewater treatment and environmental remediation, showcasing the adaptability of 3 D printing in designing effective photocatalysts. Future research should focus on practical applications and the long-term durability of these 3D-printed composites.

Stab-resistant body armor (SRBA) is used to protect the body from sharp knives. However, most SRBA materials currently have the disadvantages of large weight and thickness. This paper aims to prepare lightweight and high-performance SRBA by 3D printing truss structure and resin-filling method.

The stab resistance truss structure was prepared by the fused deposition modeling method, and the composite structure was formed after filling with resin for dynamic and quasi-static stab tests. The optimized structural plate can meet the standard GA68-2019. Digital image correlation technology was used to analyze the local strain changes during puncture. The puncture failure mode was summarized by the final failure morphologies. The explicit dynamics module in ANSYS Workbench was used to analyze the design of the overlapped structure stab resistance process in this paper.

The stab resistance performance of the 3D-printed structural plate is affected by the internal filling pattern. The stab resistance performance of 3D-printed structural parts was significantly improved after resin filling. The 50%-diamond-PLA-epoxy, with a thickness of only 5 mm was able to meet the stab resistance standard. Resins are used to increase the strength and hardness of the material but also to increase crack propagation and reduce the toughness of the material. The overlapping semicircular structure was inspired by the exoskeleton structure of the demon iron beetle, which improved the stab resistance between gaps. The truss structure can effectively disperse stress for toughening. The filled resin was reinforced by absorbing impact energy.

The 3D-printed resin-filled truss structure can be used to prepare high-performance stab resistance structural plates, which balance the toughness and strength of the overall structure and ultimately reduce the thickness and weight of the SRBA.

As a high-performance engineering plastic, polyimide (PI) is widely used in the aerospace, electronics and automotive industries. This paper aims to review the latest progress in the tribological properties of PI-based composites, especially the effects of nanofiller selection, composite structure design and material modification on the tribological and mechanical properties of PI-matrix composites.

The preparation technology of PI and its composites is introduced and the effects of carbon nanotubes (CNTs), carbon fibers (CFs), graphene and its derivatives on the mechanical and tribological properties of PI-based composites are discussed. The effects of different nanofillers on tensile strength, tensile modulus, coefficient of friction and wear rate of PI-based composites are compared.

CNTs can serve as the strengthening and lubricating phase of PI, whereas CFs can significantly enhance the mechanical properties of the matrix. Two-dimensional graphene and its derivatives have a high modulus of elasticity and self-lubricating properties, making them ideal nanofillers to improve the lubrication performance of PI. In addition, copolymerization can improve the fracture toughness and impact resistance of PI, thereby enhancing its mechanical properties.

The mechanical and tribological properties of PI matrix composites vary depending on the nanofiller. Compared with nanofibers and nanoparticles, layered reinforcements can better improve the friction properties of PI composites. The synergistic effect of different composite fillers will become an important research system in the field of tribology in the future.

Conventional sportswear design does not take into account body size changes that many individuals experience (e.g. through pregnancy, puberty, menstruation, etc.). This paper aims to detail both the construction of a novel wearable shape-adaptive composite and a new meso-scale material design method, which enables the optimal creation of these structures.

This work reports the development of a predictive computational model and a corresponding design tool, including results of a tensile testing protocol to validate their outputs. A mathematical model was developed to explore the geometric parameter space of a bi-stable composite system, which then feeds into an optimization design tool.

The authors found that it is possible to fabricate shape-adaptive composites via 3D printing bi-stable structures, and adhering them to a base textile. Experimental mechanical tensile testing showed good agreement with the predictive model in mid-range unit cell amplitude designs. To illustrate how the optimization design tool works this paper details two design examples, one for expected shape change during pregnancy and one for targeted compression for high performance swimwear. The optimized design parameters are shown to replicate the target parameters, however there is potential for further improvement with a lower stiffness base textile.

Although there is a wealth of research on multi-stable mechanisms, there is a dearth of studies that apply these structures in the wearable composite space. Additionally, there is a need for design methods which leverage the structurally-programmable capabilities of multi-stable structures to create optimized, high-performance functional composites.

The aim of this study is to determine the fracture behavior of wool felt and fabric based epoxy composites and their responses to electromagnetic waves.

Notched and unnotched tensile tests of composites made of wool only and hybridized with a glass fiber layer were carried out, and fracture behavior and toughness at macro scale were determined. They were exposed to electromagnetic waves between 8 and 18 GHz frequencies using two horn antennas.

The keratin and lignin layer on the surface of the wool felt caused lower values to be obtained compared to the mechanical values given by pure epoxy. However, the use of wool felt in the symmetry layer of the laminated composite material provided higher mechanical values than the composite with glass fiber in the symmetry layer due to the mechanical interlocking it created. The use of wool in fabric form resulted in an increase in the modulus of elasticity, but no change in fracture toughness was observed. As a result of the electromagnetic analysis, it was also seen in the electromagnetic analysis that the transmittance of the materials was high, and the reflectance was low throughout the applied frequency range. Hence, it was concluded that all of the manufactured materials could be used as radome material over a wide band.

Sheep wool is an easy-to-supply and low-cost material. In this paper, it is presented that sheep wool can be evaluated as a biocomposite material and used for radome applications.

The combined evaluation of felt and fabric forms of a natural and inexpensive reinforcing element such as sheep wool and the combined evaluation of fracture mechanics and electromagnetic absorption properties will contribute to the evaluation of biocomposites in aviation.

This study aims to deal with both the development and mechanical investigations of unsaturated polyester matrix (UPR) composites containing recycled polyethylene terephthalate (PET) fibers as new fillers.

UPR/PET fibers composites have been developed as mats by incorporating 5, 8, 13 and 18 parts per hundred of rubber (phr) of 6-, 10- and 15-mm length PET fibers from the recycling of postconsumer bottles. The mechanical and physical properties of the composites were investigated as a function of fiber content and length. A significant increase in stress at break and in ultimate stress (sr) were observed for composites reinforced with 5 and 8 phr of 15-mm length PET fibers. The Izod impact strength of UPR/mat PET fiber composites as a function of fiber rate and length showed that the 5 and 8 phr composites for the 15-mm length PET fiber have the optimal mechanical properties 13.55 and 10.50 Kj/m², respectively. The morphological study showed that the strong adhesion resulting from the affinity of the PET fiber for the UPR matrix. The ductile fracture of materials reinforced with 5 and 8 phr is confirmed by the fiber deformation and fracture surface roughness.

This study concluded that the PET fiber enhances the properties of composites, a good correlation was observed between the results of the mechanical tests and the structural analysis revealing that for the lower concentrations, the PET fibers are well dispersed into the resin, but entanglements are evidenced when the fiber content increases.

It can be shown from scanning electron microscopy micrographs that the fabrication technique produced composites with good interfacial adhesion between PET fibers and UPR matrix.