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Nondestructive Evaluation and Intelligent Monitoring for Composite Materials

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 30 May 2026 | Viewed by 8804

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Special Issue Editors

Dr. Xiaodong Shi

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Guest Editor

Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA
Interests: NDE; sensor; image processing; sginal

Prof. Dr. Michel Darmon

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Guest Editor

Laboratory of Research on Software-Intensive Technologies (LIST), Atomic Energy and Alternative Energies Commission (CEA), Paris-Saclay University, F-91120 Palaiseau, France
Interests: ultrasonics; nondestructive testing; wave propagation in solids and complex media; acoustic/elastic wave scattering and diffraction; surface acoustic waves; ray tracing; high frequency modelling; transducers; acoustic signal processing; noise analysis; artificial intelligence
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Special Issue Information

Dear Colleagues,

Concrete and masonry, composite wood, reinforced plastics, ceramics, metal matrix composites, advanced composite materials, laminates, and so on.

Advancements in composite materials have revolutionized industries such as aerospace, automotive, and civil engineering, where high performance and reliability are crucial. Ensuring the integrity of these materials is essential, especially in critical applications that directly impact safety and success. Nondestructive evaluation (NDE) technologies have rapidly evolved, offering effective solutions for the inspection and monitoring of these advanced materials without causing damage. Coupled with intelligent monitoring systems, such as those utilizing data analytics and artificial intelligence, these technologies are key to improving the quality and reliability of composite components.

This Special Issue invites researchers, engineers, and practitioners to submit original research, reviews, and practical case studies focused on the application of NDE and intelligent monitoring for composite materials. Both theoretical and practical contributions are encouraged, with the aim of advancing the field and offering valuable insights to the wider engineering community.

Dr. Xiaodong Shi
Prof. Dr. Michel Darmon
Guest Editors

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Keywords

nondestructive evaluation (NDE)
composite materials
intelligent monitoring systems

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Published Papers (10 papers)

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Research

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19 pages, 6054 KB

Open AccessArticle

Chitosan Enhanced Polymers for Active Packaging: Intelligent Moisture Regulation and Non-Invasive Assessment

by Jesús R. Villegas Méndez, María Maura Téllez Rosas, Rafael Aguirre Flores, Felipe Avalos Belmontes, Francisco J. González and Mario Hoyos

Appl. Sci. 2025, 15(21), 11744; https://doi.org/10.3390/app152111744 - 4 Nov 2025

Viewed by 360

Abstract

This work presents the non-destructive assessment of polymeric composites based on synthetic matrices low-density polyethylene (LDPE) and polystyrene (PS) enhanced with chitosan (CS) biopolymer for use in active packaging systems for moisture control. Composites were prepared by incorporating CS at different contents (1, 3 and 5 phr) into LDPE and PS matrices. To evaluate the structural and thermal alterations induced by biopolymer loading, the materials were characterized using scanning electron microscopy (SEM), X-ray diffraction (XRD), and differential scanning calorimetry (DSC). The composites’ water-regulating properties—specifically, moisture absorption, retention, diffusion, and water vapor transmission rate—were quantitively tracked. Furthermore, the mechanical integrity of both dried and water-exposed systems was assessed via Shore D hardness testing. The results reveal a direct correlation between CS concentrations and enhanced hydrophilic behavior and water absorption, primarily attributed to the polar hydroxyl and amine groups within its molecular structure. The composites maintained adequate mechanical strength even after water exposure, confirming their structural stability for practical applications. This study demonstrates that the incorporation of CS into non-polar synthetic matrices significantly improves water affinity without requiring chemical compatibilizers, representing a cost-effective route to develop responsive packaging. The promise of these composites as responsive materials for real-time environmental interaction is highlighted by the successful non-destructive monitoring of their performance. This research establishes the feasibility and efficacy of non-destructive monitoring techniques in developing active packaging technologies, accelerating the progress of polymer-based systems with integrated and tunable moisture regulation capabilities. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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29 pages, 5388 KB

Open AccessArticle

Bio-Inspired Structural Design for Enhanced Crashworthiness of Electric Vehicles’ Battery Frame

by Arefeh Salimi Beni and Hossein Taheri

Appl. Sci. 2025, 15(20), 11052; https://doi.org/10.3390/app152011052 - 15 Oct 2025

Viewed by 408

Abstract

The increasing reliance on lithium-ion batteries (LIBs) in electric vehicles (EVs) has intensified the need for structurally resilient and lightweight protective enclosures that can withstand mechanical abuse during crashes. This study addresses the challenge by drawing inspiration from the hierarchical geometry of bighorn sheep horns to design a bio-inspired battery frame with improved crashworthiness. A multilayered structure, replicating both the internal and external features of the horn, was fabricated using Fused Deposition Modeling (FDM) with Acrylonitrile Butadiene Styrene (ABS) and carbon fiber composite (CFC) materials. The experimental evaluation involved tensile and compression testing, Izod impact tests, digital image correlation (DIC), and acoustic emission (AE) monitoring for full-field strain mapping, aiming to assess structural performance under various loading scenarios. Results demonstrate that the bioinspired designs exhibit enhanced energy absorption, mechanical strength, and strain distribution compared to conventional configurations. The improved vibration response and damage tolerance observed in structured samples suggest their potential for application in battery protection systems. This work underscores the feasibility of leveraging natural design principles to engineer robust, lightweight enclosures for advanced energy storage systems, contributing to safer and more reliable EV technologies. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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19 pages, 5826 KB

Open AccessArticle

The Development of Data-Driven Algorithms and Models for Monitoring Void Transport in Liquid Composite Molding Using a 3D-Printed Porous Media

by João Machado, Masoud Bodaghi, Suresh Advani and Nuno Correia

Appl. Sci. 2025, 15(19), 10690; https://doi.org/10.3390/app151910690 - 3 Oct 2025

Viewed by 470

Abstract

In Liquid Composite Molding (LCM), the high variability present in reinforcement properties such as permeability creates additional challenges during the injection process, such as void formation. Although improved injection strategy designs can mitigate the formation of defects, these processes can benefit from real-time process monitoring and control to adapt the injection conditions when needed. In this study, a machine vision algorithm is proposed, with the objective of detecting and tracking both fluid flow and bubbles in an LCM setup. In this preliminary design, 3D-printed porous geometries are used to mimic the architecture of textile reinforcements. The results confirm the applicability of the proposed approach, as the detection and tracking of the objects of interest is possible, without the need to incur in elaborate experimental preparations, such as coloring the fluid to increase contrast, or complex lighting conditions. Additionally, the proposed approach allowed for the formulation of a new dimensionless number to characterize bubble transport efficiency, offering a quantitative metric for evaluating void transport dynamics. This research underscores the potential of data-driven approaches in addressing manufacturing challenges in LCM by reducing the overall process monitoring complexity, as well as using the acquired reliable data to develop robust, data-driven models that offer new understanding of process dynamics and contribute to improving manufacturing efficiency. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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16 pages, 7726 KB

Open AccessArticle

Digital Shearography for NDE of Crack Classification in Composite Materials

by Zhongfang Gao, Siyuan Fang, Riad Dandan and Lianxiang Yang

Appl. Sci. 2025, 15(19), 10317; https://doi.org/10.3390/app151910317 - 23 Sep 2025

Viewed by 558

Abstract

This paper presents a relevant and timely study on the application of thermal loaded digital shearography for crack classification in glass fiber reinforced plastic (GFRP) structures, particularly air-cooled condenser (ACC) fan blades. A thermal loaded digital shearography system was applied to measure strain concentration caused by the cracks at different fatigue cycles. A thermomechanical model was introduced to estimate the heating temperature and the time to ensure heat can reach to the desired depth and that both shallow and deep cracks can be detected. In order to correlate the information of strain concentration in the shearograms to the different stages of cracks, fatigue testing with dynamic three-point bending was conducted. The fatigue tests demonstrated how the strain concentration evolved in the shearograms, while the crack developed from the early (no noticeable strain concentration), to the middle (strain concentration is forming), to the late stage (significant strain concentration is found). The relationships between the degrees of strain concentration in the shearograms and the different stages of cracks can be obtained from testing of the artificial cracks. Using the rules and experimental results obtained from artificial samples, digital shearography was applied to classify the crack stages in parts of ACC fan blades from industry. The combination of artificial crack testing, fatigue loading experiments, and validation with CT scans demonstrates a comprehensive approach and provides potential guidance for industry to determine criticality and maintenance criteria. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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15 pages, 652 KB

Open AccessArticle

Computational Solution of an Inverse Boundary-Value Problem for Heat Transfer in a Composite Material

by Miglena N. Koleva and Lubin G. Vulkov

Appl. Sci. 2025, 15(18), 10230; https://doi.org/10.3390/app151810230 - 19 Sep 2025

Viewed by 426

Abstract

In the numerical simulation of composite material models, it is often necessary to recover boundary values of the solution to parabolic problems from integral constraints. In this work, we consider an inverse problem of determining a Dirichlet boundary condition for a heat equation with multiple interfaces and integral overspecification on a part of the spatial domain. After establishing the well-posedness of the direct problem, we propose an efficient numerical method for identifying an unknown Dirichlet boundary condition. The method decomposes the global inverse problem into a sequence of local subproblems, solved independently within each layer, including the accurate reconstruction of the solution at the interfaces. The approach relies solely on explicit schemes, employing an unconditionally stable Saulyev-type discretization and a novel interface treatment that avoids matrix inversion. Results from numerical experiments are presented and discussed. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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20 pages, 8458 KB

Open AccessArticle

Characterization of Defects by Non-Destructive Impulse Excitation Technique for 3D Printing FDM Polyamide Materials in Bending Mode

by Fatima-Ezzahrae Jabri, Imi Ochana, François Ducobu, Rachid El Alaiji and Anthonin Demarbaix

Appl. Sci. 2025, 15(15), 8266; https://doi.org/10.3390/app15158266 - 25 Jul 2025

Viewed by 715

Abstract

The presented article analyzes the impact of internal defects on the modal responses of polyamide parts subjected to bending. Samples with defects of various sizes (0, 3, 5, 7, and 10 mm) located at the neutral bending line were tested. Modal properties were measured via an acoustic and a vibration sensor, using impulse excitation and fast Fourier transform (FFT) analysis. Modal properties include peak frequency, damping and amplitude. Non-defective samples show lower peak frequency and stronger amplitude for both detectors. Moreover, defects larger than 3 mm have minimal impact on peak frequency. The vibration detector is more sensitive to delamination presented at 7 and 10 mm defects. In addition, elevated peak frequency at 3 mm is the result of local hardening at the defect edge. Moreover, a neutral line position reduces damping when the defect size approaches 5 mm. Conversely, acoustic detectors ignore delamination and reveal lower damping and amplitude at 7 and 10 mm defects. Furthermore, internal sound diffusion from 3 and 5 mm defects enhances air losses and damping. Acoustic detectors only evaluate fault size and position, whereas vibrational detectors may detect local reinforcement and delamination more easily. These results highlight the importance of choosing the right detector according to the location, size, and specific modal characteristics of defects. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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24 pages, 4358 KB

Open AccessArticle

Damage Indicators for Structural Monitoring of Fiber-Reinforced Polymer-Strengthened Concrete Structures Based on Manifold Invariance Defined on Latent Space of Deep Autoencoders

by Javier Montes, Juan Pérez and Ricardo Perera

Appl. Sci. 2025, 15(11), 5897; https://doi.org/10.3390/app15115897 - 23 May 2025

Cited by 1 | Viewed by 647

Abstract

Deep learning approaches based on autoencoders have been widely used for structural monitoring. Traditional approaches of autoencoders based on reconstruction errors involve limitations, since they do not exploit their hierarchical nature, and only healthy data are used for training. In this work, some health indicators, based on manifold invariance through the encoding procedure, were built for the monitoring of concrete structures strengthened with carbon fiber-reinforced polymers by directly exploring the latent space representation of the input data to a deep autoencoder. Latent representations of experimental observations of different classes were used for the learning of the network, delimiting areas in a low-dimensional space. New synthetic data with their variations, generated with a variational autoencoder, were encompassed to the trained autoencoder. The proposed method was verified on raw electromechanical impedance spectra obtained from lead zirconate titanate sensors bonded on a specimen subjected to different loading stages. The results of this research demonstrate the efficiency of the proposed approach. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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16 pages, 16221 KB

Open AccessArticle

Advancing Concrete Pavement Rehabilitation and Strategic Management Through Nondestructive Testing at Toll Stations

by Konstantinos Gkyrtis, Christina Plati and Andreas Loizos

Appl. Sci. 2025, 15(10), 5304; https://doi.org/10.3390/app15105304 - 9 May 2025

Viewed by 684

Abstract

In contrast to maintaining asphalt pavements, maintaining healthy and functional concrete pavements is a much greater challenge due to the especially brittle nature of concrete, which may require a more complex rehabilitation plan. Thanks to nondestructive testing, noninvasive on-site inspections can be carried out to assess a pavement’s condition, with the falling weight deflectometer (FWD) being the most representative example. In this study, five toll stations with concrete pavements in operation, for which no long-term monitoring protocols existed yet, were evaluated mainly with deflectometric tests using the FWD. The objective of the study was to propose a methodological framework to support responsible decision-makers in the strategic management of concrete pavements at toll stations. To meet this aim, a test campaign was organized to evaluate the pavement condition of individual slabs or lanes, assess the durability of the slabs, and determine the efficiency of load transfer across joints and cracks. As a key finding, pavement slab deflections were found to exhibit a considerable range; in particular, a range of 50–1450 μm for the maximum deflection of the FWD was observed. This finding stimulated a distribution fitting analysis to estimate characteristic values and thresholds for common deflection indicators that were validated on the basis of pavement design input data. Finally, the study proceeded with the development of a conceptual approach proposing evaluation criteria for individual slab assessment and the condition mapping of in-service concrete pavements. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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25 pages, 12513 KB

Open AccessArticle

Script-Based Material and Geometrical Modeling of Steel–Concrete Composite Connections for Comprehensive Analysis Under Varied Configurations

by Dániel Gosztola, Péter Grubits, János Szép and Majid Movahedi Rad

Appl. Sci. 2025, 15(6), 3095; https://doi.org/10.3390/app15063095 - 12 Mar 2025

Cited by 1 | Viewed by 899

Abstract

The behavior of steel–concrete composite structures is significantly influenced by the efficiency of the shear connections that link the two materials. This research examines the performance of stud shear connectors, with an emphasis on analyzing the effect of different geometric design parameters. A computational model was created utilizing Python 3.13 to enable thorough digital monitoring of the influence of these parameters on the structural performance of composite connections. Developed within the ABAQUS framework, the model integrates geometric nonlinearity and the Concrete Damage Plasticity (CDP) approach to achieve detailed simulation of structural behavior. Essential design aspects, including stud diameter, stud height, head dimensions, and spacing in both longitudinal and transverse directions, were analyzed. The Python-based parametric model allows for easy modification of design parameters, ensuring efficiency and minimizing modeling errors. The significance of stud diameter changes was analyzed in accordance with Eurocode standards and previous studies. It was found that stud length has a reduced effect on structural performance, particularly when considering the concrete properties used in bridge construction, where compressive failure of the concrete zone is more critical at lower concrete strengths. Additional factors, such as stud head dimensions, were investigated but were found to have minimal effect on the behavior of steel–concrete composite connections. Longitudinal stud spacing emerged as a critical factor influencing structural performance, with optimal results achieved at a spacing of 13d. Spacings of 2d, 3d, and 4d demonstrated overlapping effects, leading to significant performance reductions, as indicated by comparisons of ultimate load and force–displacement responses. For transverse spacing, closer stud arrangements proved effective in reducing the likelihood of slip at the steel–concrete interface, enhancing composite action, and lowering stress concentrations. Additionally, reducing the transverse distance between studs allowed for the use of more shear connectors, increasing redundancy and enhancing performance, especially with grouped-stud connectors (GSCs). Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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Review

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27 pages, 6827 KB

Open AccessReview

A Review on Design Considerations and Connection Techniques in Modular Composite Construction

by Manivannan Thulasirangan Lakshmidevi, K. S. K. Karthik Reddy, Riyadh Al-Ameri and Bidur Kafle

Appl. Sci. 2025, 15(10), 5256; https://doi.org/10.3390/app15105256 - 8 May 2025

Cited by 2 | Viewed by 2791

Abstract

Precast concrete structures have become increasingly popular in the construction industry due to their ability to enhance efficiency, structural soundness, quality, and sustainability. Among these, modular construction has emerged as a transformative approach that fully leverages precast technology by manufacturing 3D modules off-site and assembling them on-site using inter-module connections. This study reviewed current literature trends on precast concrete structures and modular construction, analysing how modular construction distinguishes itself from other precast systems. This review further emphasises the role of composite connections—grouted, bolted, and hybrid systems—critical in ensuring structural integrity, efficiency in load transfer, and seismic resilience in modular construction. Advancements in composite connections have demonstrated significant promise, particularly in seismic performance, with reported energy dissipation improvements of up to 30% in hybrid connection systems. Yet limitations still exist, necessitating improvements in load transfer efficiency, ductility, and reliability under dynamic loads. Additionally, design considerations for modular construction, such as modular configurations, handling stresses, and transportation challenges, are explored to highlight their influence on system performance. This review underscores the feasibility and potential of modular construction in fostering sustainable and resilient infrastructure, as studies indicate that modular construction can reduce project timelines by up to 50% while minimising material waste by approximately 30%. The role of Non-Destructive Evaluation (NDE) techniques and intelligent monitoring systems in assessing and enhancing the lifecycle performance of composite connections is also emphasised. This review further advocates for continued research to refine composite connections and support the broader adoption of modular construction in modern building practices. Full article

(This article belongs to the Special Issue Nondestructive Evaluation and Intelligent Monitoring for Composite Materials)

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