Search Results (123)

Accurate determination of elastic properties, especially Poisson’s ratio, is crucial for the design and modeling of composite materials. Traditional methods often struggle with low strain measurements and non-uniform strain distributions inherent in these anisotropic materials. This research work introduces a novel methodology that integrates Digital Image Correlation (DIC) with frequency analysis techniques to improve the precision of Poisson’s ratio determination during tensile tests, particularly at low strain ranges. The focus is on the evaluation of two distinct frequency-based approaches: Phase-Based Motion Magnification (PBMM) and Lock-in filtering. DIC + PBMM, while promising for motion amplification, encountered specific challenges in this application, particularly at very low strain amplitudes, leading to increased variability and computational demands. In contrast, the DIC + Lock-in filtering method proved highly effective. It provided stable, filtered strain distributions, significantly reducing measurement uncertainty compared to traditional DIC and other conventional methods like strain gauges and Video Extensometers. This study demonstrates the robust potential of Lock-in filtering for characterizing subtle periodic mechanical behaviors leading to a reduction of approximately 70% in the standard deviation of the measurement. This work lays a strong foundation for more precise and reliable material characterization, crucial for advancing composite design and engineering applications. Full article

This study systematically investigates the influence of laser pulse duration on cutting efficiency, heat-affected-zone (HAZ) formation, and mechanical integrity during carbon fiber-reinforced polymer (CFRP) laser cutting. Three distinct pulse-width lasers—picosecond, nanosecond, and quasi-continuous-wave (QCW)—are compared. Results show that pulse duration governs material removal mechanisms and HAZ extent: the nanosecond laser achieves the smallest HAZ and minimal porosity; the picosecond laser exhibits limited thermal accumulation due to low average power; and the QCW laser induces the largest HAZ (11.6 times that of the nanosecond laser) and significant porosity. Cutting efficiency scales inversely with pulse width, with single-hole processing times of 480.4 s for picosecond-laser cutting, 76.8 s for nanosecond-laser cutting, and 4.028 s for QCW-laser cutting, reflecting a transition from thermal ablation to mechanical spallation. Mechanical testing reveals that while tensile and flexural strengths vary by less than 5% across laser types, damage morphology and failure modes differ significantly. In situ digital image correlation (DIC) and 3D CT imaging show that longitudinal plies fail via fiber pull-out, whereas transverse plies fail via interfacial debonding. QCW-laser-cut specimens exhibit more uniform strain distribution and higher damage tolerance. An optimized process parameter is proposed: nanosecond-laser cutting at 200 W and 20 kHz achieves a HAZ of less than 50 µm and a cutting time of less than 80 s, offering the best balance between efficiency and quality. Full article

Densely integrated microarchitectures spanning three-dimensional integrated circuits (3D-ICs), chiplet-based designs, and system-in-package (SiP) assemblies make heat a first-order security concern rather than a mere reliability issue. This review consolidates the landscape of thermal side-channel attacks (TSCAs) on densely integrated microarchitectures: we systematize observation vectors and threat models, clarify core concepts and assumptions, compare the most credible evidence from the past decade, and distill the main classes of defenses across the hardware–software stack. We also explain why hardening against thermal leakage is integral to cyber–physical system (CPS) security and outline the most promising research directions for the field. The strategic relevance of this agenda is reflected in current policy and funding momentum, including initiatives by the United States Department of Homeland Security and the Cybersecurity and Infrastructure Security Agency (DHS/CISA) on operational technology (OT) security, programs by the National Science Foundation (NSF) on CPS, and Canada’s Regional Artificial Intelligence Initiative and Cyber-Physical Resilience Program (RAII, >CAD 35 million), to bridge advanced microelectronics with next-generation cybersecurity. This survey offers a clear, high-level map of the problem space and a focused baseline for future work. Full article

Short fibre-reinforced polymers (SFRPs) are increasingly used in structural applications where mechanical integrity under complex loading is critical. However, conventional modelling approaches often fail to accurately predict mechanical behaviour in weldline regions formed during injection moulding, where microstructural anomalies and pre-existing damage significantly degrade performance. This study addresses these limitations by extending a hybrid micro–macromechanical constitutive framework to incorporate localised initial damage at weldlines. Calibration and validation of the model were conducted using directional tensile tests on dumbbell-shaped polyamide 66 specimens reinforced with 25 wt% glass fibres, featuring controlled weldline geometry. Digital image correlation (DIC) was employed to capture strain fields, while injection moulding simulations provided fibre orientation distributions and weldline positioning. Results demonstrate that incorporating initial damage and its independent evolution for the cold weld region significantly improves prediction accuracy in weldline zones without compromising model efficiency. The proposed approach can be integrated seamlessly with existing finite element framework and offers a robust solution for simulating SFRP components with weldlines, enhancing reliability in safety-critical applications. Full article

This study investigates the mechanical behavior of Nylon 12 Carbon Fiber specimens manufactured through fused filament fabrication (FFF) for potential integration into light water well drilling rigs. Fifteen tensile test samples were 3D-printed on a MakerBot Method X printer in three orientations: horizontal, vertical, and lateral. Each specimen was printed with a soluble SR-30 support material, which was subsequently dissolved in an SCA 1200-HT wash station using heated alkaline solution. Following support removal, all samples underwent thermal annealing at 80 °C for 5 h in the printer’s controlled chamber to eliminate residual moisture and improve structural integrity. The annealed specimens were subjected to uniaxial tensile testing using an Instron 8875 electrohydraulic machine, with strain measured by digital image correlation (DIC) on a speckle-patterned gauge section. Key mechanical properties, including Young’s modulus, Poisson’s ratio, yield strength, and ultimate tensile strength, were determined. Finally, a finite element analysis (FEA) was performed using MSC Visual Nastran for Windows to simulate the tensile loading conditions and assess internal stress distributions for each print orientation. The combined experimental and numerical results confirm the feasibility of using additively manufactured parts in demanding engineering applications. Full article

To break through the bottleneck in the mapping of the mechanoluminescent (ML) intensity field to the strain field, a quantification method for full-field strain measurement based on pixel-level data fusion is proposed, integrating ML imaging with digital image correlation (DIC) to achieve precise reconstruction of the strain field. Experiments are conducted using aluminum alloy specimens coated with ML film sensor on their surfaces. During the tensile process, ML images of the films and speckle images of the specimen backsides are simultaneously acquired. Combined with DIC technology, high-precision full-field strain distributions are obtained. Through spatial registration and region matching algorithms, a quantitative calibration model between ML intensity and DIC strain is established. The research results indicate that the ML intensity and DIC strain exhibit a significant linear correlation (R² = 0.92). To verify the universality of the model, aluminum alloy notched specimen tests show that the reconstructed strain field is in good agreement with the DIC and finite element analysis results, with an average relative error of 0.23%. This method enables full-field, non-contact conversion of ML signals into strain distributions with high spatial resolution, providing a quantitative basis for studying ML response mechanisms under complex loading. Full article

This study elucidated the evolution and catastrophic failure mechanisms of concrete’s mechanical properties under high-temperature and moisture-coupled environments. Specimens underwent hygrothermal shock simulation via constant-temperature drying (100 °C/200 °C, 4 h) followed by water quenching (20 °C, 30 min). Uniaxial compression tests were performed using a uniaxial compression test machine with synchronized multi-scale damage monitoring that integrated digital image correlation (DIC), acoustic emission (AE), and infrared thermography. The results demonstrated that hygrothermal coupling reduced concrete ductility significantly, in which the peak strain decreased from 0.36% (ambient) to 0.25% for both the 100 °C and 200 °C groups, while compressive strength declined to 42.8 MPa (−2.9%) and 40.3 MPa (−8.6%), respectively, with elevated elastic modulus. DIC analysis revealed the temperature-dependent failure mode reconstruction: progressive end cracking (max strain 0.48%) at ambient temperature transitioned to coordinated dual-end cracking with jump-type damage (abrupt principal strain to 0.1%) at 100 °C and degenerated to brittle fracture oriented along a singular path (principal strain band 0.015%) at 200 °C. AE monitoring indicated drastically reduced micro-damage energy barriers at 200 °C, where cumulative energy (4000 mV·ms) plummeted to merely 2% of the ambient group (200,000 mV·ms). Infrared thermography showed that energy aggregation shifted from “centralized” (ambient) to “edge-to-center migration” (200 °C), with intensified thermal shock effects in fracture zones (ΔT ≈ −7.2 °C). The study established that hygrothermal coupling weakens the aggregate-paste interfacial transition zone (ITZ) by concentrating the strain energy along singular weak paths and inducing brittle failure mode degeneration, which thereby provides theoretical foundations for fire-resistant design and catastrophic failure warning systems in concrete structures exposed to coupled environmental stressors. Full article

The Internet of Medical Things (IoMT) is a rapidly expanding network of medical devices, sensors, and software that exchange patient health data. While IoMT supports personalized care and operational efficiency, it also introduces significant privacy risks, especially when handling sensitive health information. Data Identification and Classification (DIC) are therefore critical for distinguishing which data attributes require stronger safeguards. Effective DIC contributes to privacy preservation, regulatory compliance, and more efficient data management. This study introduces SDAIPA (SDAIA-HIPAA), a standardized hybrid IoMT data classification framework that integrates principles from HIPAA and SDAIA with a dual risk perspective—uniqueness and harm potential—to systematically classify IoMT health data. The framework’s contribution lies in aligning regulatory guidance with a structured classification process, validated by domain experts, to provide a practical reference for sensitivity-aware IoMT data management. In practice, SDAIPA can assist healthcare providers in allocating encryption resources more effectively, ensuring stronger protection for high-risk attributes such as genomic or location data while minimizing overhead for lower-risk information. Policymakers may use the standardized IoMT data list as a reference point for refining privacy regulations and compliance requirements. Likewise, AI developers can leverage the framework to guide privacy-preserving training, selecting encryption parameters that balance security with performance. Collectively, these applications demonstrate how SDAIPA can support proportionate and regulation-aligned protection of health data in smart healthcare systems. Full article

Wrinkling is a localized buckling phenomenon that significantly compromises the structural integrity of lightweight sandwich structures. The objective of this study was to validate the experimental design of a sandwich beam to observe the initiation of wrinkling under compression and, more specifically, under shear stresses. The specimen under consideration consists of glass fibre–epoxy skins with polymethacrylimide (PMI) ROHACELL^® foam cores. The experimental tests were monitored using Digital Image Correlation (DIC) techniques, in conjunction with displacement and force sensors. A linear buckling simulation was performed using Finite Element Analysis (FEA) in ABAQUS and was compared with both the experimental test results and analytical predictions. The simulations demonstrated a good correlation with both the experimental data and analytical models for compression wrinkling. In the case of shear wrinkling, the numerical analysis significantly overestimated the wrinkling load in comparison to the experimental results. Full article

Cold Spray Additive Manufacturing (CSAM) is a solid-state process that is being increasingly used for structural repairs in aerospace and energy sectors. It enables the deposition of dense material at low temperatures by accelerating metal particles to supersonic velocities, thereby reducing thermal distortion. However, the structural integrity of CSAM repairs—particularly at the interface between the deposited layer and the substrate—remains a critical concern. Various post-treatments and characterization methods have been explored to optimize performance. While X-ray Computed Tomography (XCT) is effective for sub-surface inspection, it cannot be applied in situ during mechanical testing. Digital Image Correlation (DIC), a surface-based method, also lacks sub-surface sensitivity. To address this, Infrared Thermography (IRT) was employed alongside DIC during the tensile and fatigue testing of aluminum CSAM-repaired specimens. A cooled IRT camera operating at 200 FPS captured thermal data, with lock-in processing subsequently applied in post-processing. IRT successfully detected early interfacial damage and enabled the tracking of crack propagation, which was later confirmed through fracture surface analysis. This extended abstract presents findings from fatigue tests using IRT. Full article

This study proposes a novel structural deflection measurement method using a single smartphone with an innovative scale factor (SF) calibration technique, eliminating reliance on laser rangefinders and industrial cameras. Conventional off-axis digital image correlation (DIC) techniques require laser rangefinders to measure discrete points for SF calculation, suffering from high hardware costs and sunlight-induced ranging failures. The proposed approach replaces physical ranging by deriving SF through geometric relationships of known structural dimensions (e.g., bridge length/width) within the measured plane. A key innovation lies in developing a versatile SF calibration framework adaptable to varying numbers of reference dimensions: a non-optimized calculation integrates smartphone gyroscope-measured 3D angles when only one dimension is available; a local optimization model with angular parameters enhances accuracy for 2–3 known dimensions; and a global optimization model employing spatial constraints achieves precise SF resolution with ≥4 reference dimensions. Indoor experiments demonstrated sub-0.05 m ranging accuracy and deflection errors below 0.30 mm. Field validations on Beijing Subway Line 13′s bridge successfully captured dynamic load-induced deformations, confirming outdoor applicability. This smartphone-based method reduces costs compared to traditional setups while overcoming sunlight interference, establishing a hardware-adaptive solution for vision-based structural health monitoring. Full article

The use of vertically stacked architectures in three-dimensional integrated circuits (3DICs) offers a transformative path for advancing Moore’s Law by significantly boosting computational density. A key obstacle arises from the integration of heterogeneous materials, which introduces critical thermo-mechanical challenges, particularly due to the mismatch in the coefficients of thermal expansion (CTE) of silicon (Si) and copper (Cu). Such mismatches can compromise mechanical reliability and complicate the definition of the keep-out zone (KOZ) in dense systems. This paper provides a detailed analysis of the thermo-mechanical behavior of stacked 3DICs, exploring a range of device geometries and process conditions. The findings reveal that CTE-induced stress is the dominant factor influencing mechanical integrity, surpassing other mechanical forces. It is concluded that the KOZ must be no less than 1.5 times the feature diameter to adequately mitigate stress-related risks. Additionally, thermal stress interactions in configurations with adjacent structures can increase the KOZ requirement by up to 33.3% relative to isolated instances. Yet, multi-layered designs show enhanced thermal performance, a benefit attributed to the high thermal conductivity of copper. The knowledge gained from this study provides a valuable framework for optimizing the reliability and thermal management of 3DIC systems and is especially relevant for high-performance sensor devices where both mechanical stability and efficient heat dissipation are vital. Full article

This scoping review paper provides an overview of the evolution, the current stage, and the future prospects of fracture studies on composite laminates. A fundamental understanding of composite materials is presented by highlighting the roles of the fiber and matrix, outlining the applications of various synthetic fibers used in current structural sectors. Challenges posed by interlaminar delamination, one of the critical failure modes, are highlighted. This paper systematically discusses the fracture behavior of these laminates under mixed-mode and complex loading conditions. Standardized fracture toughness testing methods, including Mode I Double Cantilever Beam (DCB), Mode II End-Notched Flexure (ENF) and Mixed-Mode Bending (MMB), are initially discussed, which is followed by a decade-wide chronological analysis of fracture mechanics approaches. Key advancements, including toughening mechanisms, Cohesive Zone Modeling (CZM), Virtual Crack Closure Technique (VCCT), Extended Finite Element Method (XFEM) and Digital Image Correlation (DIC), are analyzed. The review also addresses recent trends in fracture studies, such as bio-inspired architecture, self-healing systems, and artificial intelligence in fracture predictions. By mapping the trajectory of past innovations and identifying unresolved challenges, such as scale integration, dataset standardization for AI, and manufacturability of advanced architectures, this review proposes a strategic research roadmap. The major goal is to enable unified multi-scale modeling frameworks that merge physical insights with data learning, paving the way for next-generation composite laminates optimized for resilience, adaptability, and environmental responsibility. Full article

The structural health monitoring (SHM) of existing infrastructure and heritage buildings is essential for their preservation and safety. This is a review paper which focuses on modern three-dimensional (3D) measurement techniques, particularly those that enable the assessment of the structural response to environmental actions and operational conditions. The emphasis is on the detection of fractures and the identification of the crack geometry. While traditional monitoring systems—such as pendula, callipers, and strain gauges—have been widely used in massive, quasi-brittle structures like dams and masonry buildings, advancements in non-contact and computer-vision-based methods are increasingly offering flexible and efficient alternatives. The integration of drone-mounted systems facilitates access to challenging inspection zones, enabling the acquisition of quantitative data from full-field surface measurements. Among the reviewed techniques, digital image correlation (DIC) stands out for its superior displacement accuracy, while photogrammetry and time-of-flight (ToF) technologies offer greater operational flexibility but require additional processing to extract displacement data. The collected information contributes to the calibration of digital twins, supporting predictive simulations and real-time anomaly detection. Emerging tools based on machine learning and digital technologies further enhance damage detection capabilities and inform retrofitting strategies. Overall, vision-based methods show strong potential for outdoor SHM applications, though practical constraints such as drone payload and calibration requirements must be carefully managed. Full article

Groundwater at petroleum-contaminated sites typically exhibits elevated dissolved inorganic carbon (DIC) levels due to hydrocarbon biodegradation; however, our prior field investigations revealed an enigmatic DIC depletion anomaly that starkly contradicts this global pattern and points to an unrecognized carbon sink. In a breakthrough demonstration, this study provides the first experimental confirmation that sulfur-oxidizing bacteria (SOB) drive substantial carbon sequestration via a coupled sulfur oxidation autotrophic assimilation process. Through integrated hydrochemical monitoring and 16S rRNA sequencing in an enrichment culture system, we captured the complete DIC transformation trajectory: heterotrophic acetate degradation initially increased DIC to 370 mg/L, but subsequent autotrophic assimilation by SOB dramatically reduced DIC to 270 mg/L, yielding a net consumption of 85 mg/L. The distinctive pH dynamics (initial alkalization followed by acidification) further corroborated microbial regulation of carbon cycling. Critically, Pseudomonas stutzeri and P. alcaliphila were identified as the dominant carbon-fixing agents. These findings definitively establish that chemolithoautotrophic SOB convert DIC into organic carbon through a “sulfur oxidation-carbon fixation” coupling mechanism, overturning the conventional paradigm of petroleum-contaminated sites as perpetual carbon sources. The study fundamentally redefines natural attenuation frameworks by introducing microbial carbon sink potential as an essential assessment metric for environmental sustainability. Full article