The review, led by Ziyang Liu and Minghe Li of Jilin Agricultural Science and Technology College together with colleagues, systematically examines how process-induced defects form, how they can be quantitatively characterized, and how they trigger damage initiation and propagation that degrades performance in nonlinear and often surprising ways. Its central conceptual move is to reinterpret defects not as isolated flaws with nominal dimensions and acceptance thresholds, but as local structural perturbation fields collectively shaped by the manufacturing process. What matters most, the authors conclude, is not simply how much void content a laminate contains or how large a wrinkle is, but how the defect changes the local fibre architecture, the interlaminar constraint between plies, and the pathways through which stress is transferred through the structure.

Voids are the most pervasive of these perturbation fields. They form during resin impregnation, cure and consolidation when air, volatiles or moisture become trapped in the polymer matrix. X-ray computed tomography has transformed the field by allowing researchers to map voids in three dimensions without destroying the specimen, revealing their spatial morphology, size distributions and clustering behaviour. Studies cited in the review show that voids can independently trigger matrix cracking, interfacial debonding and interlaminar delamination, and that their effects depend critically on where they sit relative to ply interfaces and stress concentrations. Under cyclic loading, voids shift the sites where cracks first appear and redirect the dominant propagation paths, producing fatigue life reductions that conventional mean-property knockdown factors fail to capture.

Fibre waviness presents a different kind of challenge. When fibres deviate from their intended alignment, whether through layup errors, tooling interactions or cure-induced deformation, the compressive strength of the composite can fall dramatically because misaligned fibres are prone to kinking, a cooperative buckling instability in which fibres rotate and fracture within a narrow band. The review highlights experimental and computational work showing that embedded wrinkles act as preferential sites for kink-band formation under longitudinal compression, and that waviness also degrades fatigue life by concentrating damage at the wavy region. Crucially, the authors note that waviness and voids do not act independently; recent failure analyses of unidirectional CFRP under longitudinal compression reveal coupled effects in which initial fibre waviness and voids interact synergistically to accelerate failure.

Automated fibre placement, the robotic process that has become the backbone of modern aerospace composite manufacturing, introduces its own defect signature. Tow-to-tow gaps, overlaps, steering-induced wrinkles and tow-drop effects arise from the interplay of machine kinematics, process conditions and material behaviour. The review draws on experimental studies demonstrating that these AFP defects can measurably reduce shear and compression properties, alter microstructure, and change progressive damage development under both static and fatigue loading. Because AFP defects are distributed across large areas rather than concentrated at single points, their cumulative effect on complex structures is difficult to assess with the single-defect acceptance thresholds that certification practice has traditionally relied upon.

Perhaps the most consequential finding of the review is that the effects of multiple defects are generally non-additive. Two defects that individually cause modest property reductions can together produce a disproportionate loss of strength, or conversely can partially compensate for one another depending on their spatial arrangement and the loading condition. This non-additivity means that conventional quality control, which screens parts against nominal defect content limits and applies mean-property knockdown factors, is structurally inadequate for the reliability assessment of complex composite structures. The authors argue that what is needed instead is a probabilistic multidefect and multiscale framework that accounts for the stochastic spatial distribution of defects and their interactions, validated by in situ observations of damage evolution under realistic loading.

Computational micromechanics and stochastic multiscale analysis are emerging as the tools that could make such a framework possible. Explicit defect modelling allows researchers to insert realistic three-dimensional defect geometries, obtained from tomography, into finite element models and track how damage initiates and propagates through the perturbed microstructure. Bottom-up stochastic multiscale models, highlighted in the review, propagate microvoid randomness through to laminate-level mechanical behaviour, enabling fast uncertainty quantification for large composite structures. Data-driven prediction, including deep-learning segmentation of tomography images and machine-learning identification of damage mechanisms from acoustic emission signals, is accelerating the extraction of quantitative insight from experimental data that was previously too complex to analyse systematically.

The review also points toward a future in which defect control shifts from post-manufacturing screening to proactive intervention during defect formation. Process monitoring of automated fibre placement, digital twins that simulate cure and consolidation in real time, and online repair frameworks that detect and correct defects as they arise are all identified as components of a closed-loop manufacturing paradigm. Standardized three-dimensional defect characterization and data-reporting frameworks, aligned with FAIR data principles, would allow results from different laboratories and processes to be compared on a common basis, something the field currently lacks and which the authors identify as a prerequisite for building the large, harmonized datasets needed to train reliable predictive models.

The implications reach far beyond the laboratory. As composites spread from aerospace into automotive structures, hydrogen storage, wind energy and consumer products, the cost of undetected defect interactions grows accordingly. A certification regime built on single-defect thresholds may pass a component that contains a synergistic combination of voids, waviness and AFP gaps capable of triggering nonlinear performance degradation in service. Conversely, a more sophisticated probabilistic framework could unlock lighter, more efficient designs by allowing engineers to quantify reliability with greater precision rather than applying conservative blanket knockdowns. The review’s message is ultimately one of opportunity: by understanding defects as perturbation fields whose effects depend on local architecture and stress transfer, and by integrating process monitoring, multiscale modelling and data-driven prediction into a closed loop, the composites community can move from reacting to defects after they form to controlling them as they form, transforming both the safety and the performance ceiling of the materials that carry us into the sky and across the road.

Subject of Research: Materials Science

Article Title: Review: process-induced defects and damage evolution in carbon-fibre-reinforced polymer composites

Article References: Liu, Z., Li, M., Cui, B., Wei, G., Chen, Q., Guo, X., He, K., & Chen, R. (2026). Review: process-induced defects and damage evolution in carbon-fibre-reinforced polymer composites. Journal of Materials Science, 61(41), 31600-31639. https://doi.org/10.1007/s10853-026-13657-0

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13657-0

Keywords: carbon-fibre composites, CFRP, manufacturing defects, voids, fibre waviness, automated fibre placement, damage evolution, computational micromechanics, multiscale modelling, digital twins, X-ray computed tomography, reliability

The research, led by Phani Prasanthi together with B. Raghu Kumar, U. Koteswara Rao, and T. Srinag, presents an integrated framework that weaves together three complementary strands of investigation: physical tensile testing, finite element simulation, and Arrhenius-based kinetic modeling. The goal was not simply to measure how carbon fiber-reinforced polymer composites weaken under heat, but to build a predictive pipeline that can forecast both strength loss and service life across a wide range of operating temperatures, including conditions that were never directly tested in the laboratory.

The experimental backbone of the study consisted of tensile tests conducted at four temperatures: room temperature, 50 degrees Celsius, 80 degrees Celsius, and 100 degrees Celsius. These are not exotic conditions. Components under an aircraft hood, near engine bays, or in sun-exposed automotive structures routinely experience thermal environments in this range, which makes the findings directly relevant to real-world design decisions. The tests were designed to capture the thermo-mechanical behavior of the composites as the polymer matrix that binds the carbon fibers together begins to soften and degrade.

The results were striking. Compared with room-temperature performance, tensile strength fell by 33.33 percent at 50 degrees Celsius, by 61.92 percent at 80 degrees Celsius, and by 57.94 percent at 100 degrees Celsius. The non-monotonic pattern, in which the drop at 100 degrees Celsius was slightly smaller than at 80 degrees Celsius, underscores how complex the underlying degradation mechanisms can be. The polymer matrix is the weak link in this story: carbon fibers themselves retain their strength at these temperatures, but the epoxy or similar resin surrounding them loses stiffness and load-transfer capability as thermal energy disrupts its molecular network. Once the matrix can no longer grip the fibers effectively or transfer stress between them, the composite as a whole fails far below its nominal capacity.

What makes the new work more than another set of measurements is the second pillar of the framework: finite element simulation. The team built numerical models of the tensile tests and calibrated them against the experimental data. The simulations tracked the experiments closely, with prediction errors below 5 percent at room temperature and at 50 degrees Celsius. That level of agreement matters because it establishes the model as trustworthy enough to extrapolate. Having validated the simulation against real data at the lower temperatures, the researchers then used it to predict tensile behavior all the way up to 200 degrees Celsius, a regime where direct testing becomes more difficult and more expensive.

This experimental-to-numerical handoff is a pattern increasingly common in materials engineering, and it addresses a genuine bottleneck. Physical testing at every temperature of interest would demand dozens of specimens, environmental chambers, and weeks of laboratory time. A validated simulation, by contrast, can sweep through a temperature range in hours and flag the conditions that deserve closer experimental scrutiny. In safety-critical fields such as aerospace, where certification authorities demand evidence rather than intuition, a simulation that has been anchored to experimental reality provides exactly the kind of defensible evidence that design reviews require.

The third pillar pushes the work from static prediction into the realm of lifetime forecasting. The researchers employed an Arrhenius kinetic model, a mathematical approach with roots in chemical kinetics that describes how reaction rates accelerate exponentially with temperature. Originally developed to characterize the temperature dependence of chemical reactions, Arrhenius modeling has become a standard tool for predicting the thermal aging and degradation of polymers. In this study, the team used it to establish a quantitative relationship between thermal degradation kinetics and the degradation of tensile strength, effectively linking the speed of molecular-level damage to the macroscopic property that engineers care about most.

The practical payoff of that link is service life prediction. By fitting the kinetic model to the strength data, the framework can estimate how long a composite component will retain adequate strength when held at a given elevated temperature, rather than merely reporting a single strength value measured after an arbitrary exposure. This is the kind of information that maintenance planners and structural designers actually need: not just how strong the material is today, but how strong it will be after years of service in a hot environment. The authors position the integrated framework as a reliable and efficient methodology for predicting tensile strength degradation and service life across a wide range of operating temperatures, supporting both design and long-term reliability assessment in high-temperature applications.

The broader context makes the contribution timely. Carbon fiber composites are expanding into new territory, from wind turbine blades that bake in the sun for decades to electric vehicle battery enclosures that must survive thermal excursions, and the literature has documented repeated concerns about elevated-temperature performance. Previous studies have examined temperature effects on composite mechanics, aging and durability, and failure mechanisms under combined thermal and mechanical loads, but comprehensive frameworks that unite experiment, simulation, and kinetic lifetime modeling in a single validated pipeline remain comparatively rare. The new study also connects to a wider engineering tradition: damage mechanisms and life assessment of high-temperature components have been studied in metals for decades, and this work extends similar predictive logic to polymer-matrix composites.

There are, of course, boundaries to what the study claims. The data availability statement notes that no datasets were generated or analyzed beyond the study itself, and the reported predictions above 100 degrees Celsius rest on simulation and kinetic extrapolation rather than direct measurement, which is precisely why the validation at lower temperatures was so important. The non-monotonic strength behavior between 80 and 100 degrees Celsius also hints that matrix-dominated failure mechanisms may shift with temperature, a nuance that future experimental work could probe further. Still, the framework’s architecture is deliberately modular: as new experimental data arrives, the finite element model and the Arrhenius parameters can be refined, tightening the predictions over time. For an industry that increasingly stakes safety and performance on materials whose weakest ingredient is the polymer holding them together, a tool that turns scattered test data into a continuous, temperature-resolved map of strength and lifespan is a meaningful step forward. It transforms a question that once required a laboratory and a calendar into a calculation that can be run before the first part is ever manufactured.

Subject of Research: Temperature-dependent tensile behavior and service life prediction of carbon fiber-reinforced polymer composites

Article Title: An integrated experimental–numerical–kinetic framework for predicting the tensile behavior of carbon fiber reinforced composites at different temperatures

Article References: Prasanthi, P., Kumar, B. R., Rao, U. K., & Srinag, T. (2026). An integrated experimental–numerical–kinetic framework for predicting the tensile behavior of carbon fiber reinforced composites at different temperatures. Polymer Bulletin, 83(12), Article 673. https://doi.org/10.1007/s00289-026-06709-7

Image Credits: AI Generated

DOI: 10.1007/s00289-026-06709-7

Keywords: carbon fiber composites, tensile strength, finite element analysis, Arrhenius model, thermal degradation, service life prediction, polymer matrix, elevated temperature, CFRP, aerospace materials, structural reliability, integrated

The research, conducted by Resat Oyguc and Evrim Oyguc of the Institute of Disaster Management, Earthquake Engineering Department at Istanbul Technical University, focuses on a class of buildings that keeps structural engineers awake at night: non-ductile reinforced concrete frames. These are structures designed before modern seismic codes demanded the careful reinforcement detailing that allows a building to bend and deform without collapsing. Many such buildings across seismically active regions, from Türkiye to California, remain in service today, and retrofitting them has become a global engineering priority.

Two of the most common retrofit strategies anchor the study. The first involves wrapping columns with bonded carbon fiber-reinforced polymer, or CFRP, jackets—thin, immensely strong composite sheets that confine the concrete and delay brittle failure. The second deploys steel buckling-restrained braces, ingenious devices in which a steel core designed to yield in both tension and compression is housed within a tube that prevents it from buckling, allowing the brace to dissipate seismic energy stably through hundreds of loading cycles. Both approaches can dramatically improve a frame’s performance, but they do so in fundamentally different ways, and this difference has long frustrated attempts at unified assessment.

The problem, as the authors explain, lies in the very design of existing damage indices. Scalar indices calibrated against one intervention family record how much damage has occurred rather than which mechanism produced it. An index tuned to the behavior of CFRP-retrofitted frames transfers poorly to braced frames, and neither can sound an alarm when a brittle mode—such as joint panel shear failure or sliding—is about to take control of the response. In a severe earthquake, that distinction can mean the difference between a repairable structure and a catastrophic collapse.

The researchers’ answer is the Mechanism Evolution Index, or MEI, a framework that condenses six independently measurable response quantities into a bounded scalar on the unit interval, while simultaneously decomposing the structural state into a ternary coordinate that separates demand into three interpretable channels: ductility, shear, and connection. The six constituents include quantities familiar to any experimentalist: the normalized hysteretic energy dissipated during a run, the ratio of peak base shear to design-level capacity, the peak interstorey drift ratio, the residual drift left after shaking stops, the dynamic amplification between the shaking table and the structure above it, and the period softening ratio that captures how much the structure’s fundamental frequency has degraded from one excitation to the next.

What makes the framework remarkable is its economy of calibration. The six constituents are combined through a single frozen weight set, anchored once at the joint-panel cracking and sliding thresholds of a three-specimen calibration series. Each constituent passes through a sigmoid normalization function whose half-saturation value is fixed to the measured response of the bare specimen at design intensity. Once these anchors are set, the weights are frozen and applied without any re-tuning across retrofit type and shaking intensity. This is a deliberate departure from the prevailing practice, in which every new structural configuration demands its own bespoke index calibration, rendering comparisons across interventions nearly impossible.

The ternary coordinate is where the index earns its diagnostic power. The three components—ductility, shear, and connection—sum to one, placing every response state as a point within a triangular coordinate space whose corners represent pure ductile, pure shear, and pure connection demand. As a frame is shaken progressively harder, its point traces a trajectory through this space, and the leading axis at any moment names the mechanism that governs. The framework also defines a dominance margin, the difference between the two largest coordinates, which quantifies how decisively one mechanism leads over the others—a measure of confidence in the diagnosis itself.

To build and test the framework, the researchers drew on a one-third-scale specimen series: a bare non-ductile frame, the same frame retrofitted with a three-ply CFRP jacket, and a version strengthened with an innovative tube-in-tube buckling-restrained brace. All three configurations were reproduced by a single calibrated OpenSees finite element model, whose joint hysteresis was tuned to match measured displacement traces, base shear histories, hysteretic energy, and the fundamental periods identified from white-noise excitation before and after each strong-motion run. The calibration objective weighted all four error measures simultaneously, ensuring the simulation platform captured not just peak responses but the degradation pathways that unfold between them.

The findings tell a story that should concern anyone responsible for retrofit decisions. Under design-level intensity, the bare frame became connection-dominated, its ternary point migrating toward the joint sliding threshold exactly as its unreinforced beam-column panels began to fail. The CFRP jacket, perhaps counterintuitively, suppressed joint engagement through the design band but then collapsed through the very same connection channel when pushed to the ultimate level—the strengthening shifted the brittle mode upward in intensity rather than eliminating it. Only the braced frame remained on the ductility axis throughout, converting the failure mode into a stable, energy-dissipating one. The connection component of the index thus serves as an indicative retrofit-screening signal, flagging interventions that leave a residual brittle pathway even when headline performance metrics look satisfactory.

Transferability—the acid test for any index claiming generality—was examined on six external cases lying outside the calibration set, four bare and two retrofitted. In every labelled case, the mechanism reported by the experimental or analytical source landed on the leading ternary axis of the index. The classical scalars, by contrast, tracked damage severity faithfully but could not name the mechanism in any of them. This separation between knowing how much and knowing what kind is, in the authors’ framing, the essential contribution of the work.

The practical implications extend well beyond the laboratory. Post-earthquake reconnaissance following recent sequences in Türkiye has repeatedly documented the lethal consequences of brittle joint failures in non-ductile frames, and retrofit campaigns guided only by severity-based indices may inadvertently favor interventions that mask rather than remove the underlying vulnerability. A screening tool that can be applied identically across bare, jacketed, and braced configurations, using response quantities measurable from instrumentation or extracted from a calibrated simulation, offers engineers a common currency for comparing retrofit options on the dimension that matters most in a collapsing building: which mechanism will win.

The authors are careful to delineate the scope of their framework. It applies to regular planar systems under single-direction motion, and the frozen weight set is anchored to joint-panel thresholds specific to the calibration series used. Extending the approach to three-dimensional response, torsionally irregular buildings, and bidirectional ground motion remains open. The data supporting the study are available from the corresponding author upon reasonable request, and the authors report no external funding or competing interests. Even within these bounds, however, the Mechanism Evolution Index represents a meaningful conceptual advance: a damage measure that evolves alongside the structure, tracing not just the accumulation of harm but the shifting identity of the mechanism inflicting it.

As cities with vast stocks of pre-modern-code concrete buildings confront escalating seismic risk, the difference between a retrofit that redirects failure into a ductile pathway and one that merely postpones a brittle one is not an academic distinction—it is a matter of life and death. By giving engineers a single bounded number paired with an interpretable mechanism diagnosis, the Istanbul Technical University team has provided a tool that could make that distinction visible before the next earthquake makes it tragically apparent.

Subject of Research: A mechanism evolution index for the seismic assessment of retrofitted non-ductile reinforced concrete frames

Article Title: A mechanism evolution index for the seismic assessment of retrofitted non-ductile RC frames

Article References: Oyguc, R., & Oyguc, E. (2026). A mechanism evolution index for the seismic assessment of retrofitted non-ductile RC frames. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02679-3

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02679-3

Keywords: seismic retrofitting, reinforced concrete, damage index, ductility, CFRP, buckling-restrained brace, OpenSees, non-ductile frames, beam-column joints, shake table testing, earthquake engineering, structural assessment