The dynamic thermomechanical properties of wood–plastic composites (WPCs) are influenced by various factors, such as the selection of raw materials and processing parameters. To investigate the effects of different wood fiber content ratios and...
This article addresses the complex behavior of composite laminates under varied layer orientations during tensile tests, focusing on carbon fiber and epoxy matrix composites. Data characterizing the mechanical load behavior are obtained using twelve...
Delamination in laminated structures is a concern in high-performance structural applications, which challenges the latest non-destructive testing techniques. This study assesses the delamination damage in the glass fiber-reinforced laminated composi...
Polymer composites show complex, nonlinear mechanical behavior. This makes their rational design hard. Running tests or high-fidelity simulations for every candidate design is slow and costly. Purely data-driven models are fast, but they can break ba...
Thermoforming is a process where the laminated sheet is pre-heated to the desired forming temperature before being pressed and cooled between the molds to give the final formed part. Defects such as wrinkles, matrix-smear or ply-splitting could occur...
This research focuses on investigating the buckling strength of thin-walled composite structures featuring various shapes of holes, laminates, and composite materials. A parametric study is conducted to optimize and identify the most suitable combina...
Early and reliable detection of plant diseases is critical for sustaining agricultural productivity and reducing economic losses. In olive cultivation, peacock eye disease poses a significant threat by adversely affecting leaf health and crop yield....
CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high s...
This paper surveys the application of machine learning in fiber composite manufacturing, highlighting its role in adaptive process control, defect detection, and real-time quality assurance. First, the need for ML in composite processing is highlight...
Material considerations are often neglected when developing digital twins, particularly at the relevant length scales that drive material and structural performance. For reinforced composite materials, the microscale has the largest impact on nonline...
The body of a high-speed train is a composite structure composed of different materials and structures. This makes the design of a noise-reduction scheme for a car body very complex. Therefore, it is important to clarify the key factors influencing s...
In the present work, the potential application of machine learning techniques in the flutter prediction of composite materials missile fins is investigated. The flutter velocity data set required for different fin aerodynamic geometries and materials...
Accurate prediction of erosion rates in polymeric and composite materials is essential for their effective design and maintenance in diverse industrial environments. This study presents a predictive modelling framework developed using the JMP Pro mac...
Biodegradable polymers have recently found significant applications in pharmaceutics processing and drug release/delivery. Composites based on poly (L-lactic acid) (PLLA) have been suggested to enhance the crystallization rate and relative crystallin...
Flax fiber/shape memory epoxy hygromorph composites are a promising area of research in the field of biocomposites. This paper focuses on the tensile modulus of these composites and investigates how it is affected by factors such as fiber orientation...
The dynamic characteristics of bridges are not only influenced by structural damage but also by ambient environmental variations. If environmental factors are not incorporated into the detection algorithm, they may lead to false positives or false ne...
Delamination is one of the detrimental defects in laminated composite materials that often arose due to manufacturing defects or in-service loadings (e.g., low/high velocity impacts). Most of the contemporary research efforts are dedicated to high-fr...
Due to the uncertainty of material properties of plate-like structures, many traditional methods are unable to locate the impact source on their surface in real time. It is important to study the impact source-localization problem for plate structure...
This paper investigates a novel robust adaptive dynamic surface control scheme based on the barrier Lyapunov function (BLF), online composite learning, disturbance observer, and improved saturation function. It is mainly designed for a class of skid-...
This study proposes an incremental neural network adaptive control algorithm based on composite learning for a two-degree-of-freedom (2-DOF) helicopter system characterised by dynamic event triggering and input saturation. Firstly, by integrating a c...
The evolution of the damage process in PAEK-type thermoplastic carbon fiber-reinforced polymer (CFRP) quasi-isotropic composite tensile specimens was investigated using acoustic emission (AE) monitoring under quasi-static loading to failure. Key obje...
Accurate national-scale mangrove mapping remains challenging because mangroves occur in narrow intertidal belts affected by tidal variation, residual clouds, water background effects, and spectral confusion with adjacent vegetation. This study evalua...
Weather radars are commonly used to track the development of convective storms due to their high resolution and accuracy. However, the coverage of existing weather radar is very limited, especially in mountainous and ocean areas. Geostationary meteor...
Composite-score estimation (or assessment auditing) and student profiling are two fundamental tasks in Educational Data Mining (EDM). However, existing studies often treat them as separate problems, typically adopting a sequential pipeline in which c...
In this study, a finite element (FE)-based machine learning model was developed to predict the mechanical properties of bioglass (BG)-collagen (COL) composite hydrogels. Based on the experimental observation of BG-COL composite hydrogels with scannin...
The thermodynamic competition among multiple precipitate phases and its coupling with solidification behavior in P91-type steel remain insufficiently explored across multicomponent composition spaces, limiting the systematic identification of favorab...
Diabetes mellitus represents a major public health issue, and the early identification of individuals at risk is essential for prevention. The aim of this study was to develop a predictive model for identifying diabetes mellitus based on body composi...
To identify hygrothermal transfer patterns of exterior walls is a crucial issue in the design, assessment, and construction of buildings. Temperature and relative humidity, as sensor monitoring data, were collected from the outside of the wall to int...
Natural fiber-reinforced unidirectional composites are increasingly adopted in modern industries due to their superior mechanical performance and desirable properties from both material and engineering perspectives. Among various approaches, represen...
Woven fabric composite structures are applied in a wide range of industrial applications. Composite structures are vulnerable to damage from working in complex conditions and environments, which threatens the safety of the in-service structure. Damag...
This study aims to develop a high-generalizability machine learning framework for predicting the homogenized mechanical properties of short fiber-reinforced polymer composites. The ensemble machine learning model (EML) employs a stacking algorithm us...
Current development of high-performance fiber-reinforced cementitious composites (HPFRCC) mainly relies on intensive experiments. The main purpose of this study is to develop a machine learning method for effective and efficient discovery and develop...
Handheld X-ray fluorescence (HHXRF) scanners generate rapid, low-cost geochemical datasets from core and cuttings, yet their potential for quantitative reservoir characterisation remains largely unrealised, partly because standard multivariate method...
Conventional mechanical machining of composite is a challenging task, and thus, electric discharge machining (EDM) was used for the processing of the developed material. The processing of developed composite using different electrodes on EDM generate...
Composite materials are one of the primary structural components in most current transportation applications, such as the aerospace industry. Composite material diagnostics is a promising area in the fight against structural damage in aircraft and sp...
Background: Computed tomography-based body composition assessment enables the quantification of clinically relevant prognostic conditions such as sarcopenia, myosteatosis, and visceral adiposity; the manual segmentation process limits its routine imp...
The optimization of multilayer composite structures requires balancing mechanical performance, economic efficiency, and computational feasibility. This study introduces an innovative approach that integrates Curriculum Learning (CL) with a multi-fide...
Sandwich structures made with fibre-reinforced plastics are commonly used in maritime vessels thanks to their high strength-to-weight ratios, corrosion resistance, and buoyancy. Understanding their mechanical performance after moisture uptake and the...
Over the last two decades, several experimental and numerical studies have been performed in order to investigate the acoustic behavior of different muffler materials. However, there is a problem in which it is necessary to perform large, important,...
Prediction of mechanical properties is an essential part of material design. State-of-the-art simulation-based prediction requires data on microstructure and inter-component interactions of material. However, due to high costs and time limitations, s...
Recent advancements in composite materials design have made glass fiber-reinforced polymer composites (GFRPC) a viable choice for a wide range of engineering and industrial applications. Although GFRPCs boast attractive characteristics such as low sp...
Manufacturing polypropylene (PP) composites to meet customers’ needs is difficult, time-consuming, and costly, owing to the ever-increasing diversity and complexity of the corresponding specifications and the trial-and-error method currently us...
Cloud computing has experienced rapid growth in recent years and has become a critical computing paradigm. Combining multiple cloud services to satisfy complex user requirements has become a research hotspot in cloud computing. Service composition in...
In this work, a supervised machine learning (ML) model was developed to detect flow disturbances caused by the presence of a dissimilar material region in liquid moulding manufacturing of composites. The machine learning model was designed to predict...
In this research, the effect of change in stacking sequences on the impact performance of bio-hybrid fiber-reinforced polymer (bio-HFRP) composite materials was analyzed and evaluated. The methodology was developed, based on the mechanical testing an...
The development of filled photopolymer composites for Digital Light Processing (DLP) additive manufacturing requires optimizing processing parameters to achieve the desired mechanical properties. Traditional experimental approaches are time-intensive...
Coal combustion residues are increasingly viewed as alternative sources of rare earth elements (REEs), but their heterogeneous composition and post-depositional alteration complicate resource evaluation. This study analyzes 50 coal ash (CA) samples c...
The exposure of carbon-fiber-reinforced polymers (CFRPs) to open-field conditions was investigated. Establishment of structure–property relations with nanoindentation enabled the observation of modification effects on carbon-fiber interfaces, and imp...
Wear is induced when two surfaces are in relative motion. The wear phenomenon is mostly data-driven and affected by various parameters such as load, sliding velocity, sliding distance, interface temperature, surface roughness, etc. Hence, it is diffi...
Structural health monitoring (SHM) of composite structures using surface strain fields measured by digital image correlation (DIC) has been widely demonstrated; however, accurate damage quantification remains challenging. This study proposes a hybrid...
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