Catastrophic Failure Research Articles

From Electrochemical Analysis to Machine Learning Prediction: A Comprehensive Approach to LIB Safety

The advancement of lithium-ion battery (LIB) technology has been pivotal in powering a wide range of applications, from portable electronics to electric vehicles (EVs). However, the safety of LIBs remains a significant concern, primarily due to the risk of thermal runaway (TR), a process where an increase in temperature leads to a self-sustaining chain reaction resulting in catastrophic failure. Our study introduces a groundbreaking framework that integrates multiphysics modeling with machine learning (ML) to predict the onset of TR in LIB modules, thereby advancing battery safety and reliability.The multiphysics model developed in this research incorporates the comprehensive electrochemical and thermal behavior of LIBs, with a particular focus on the degradation mechanisms that lead to TR. This includes a detailed analysis of the breakdown of solid electrolyte interface (SEI) and its impact on battery stability. The model simulates various operational scenarios, such as constant charge/discharge and dynamic driving cycles, to replicate real-world battery usage. The thermal, electrochemical, and mechanical stresses are computed, enabling the identification of conditions that cause TR. In parallel, we have implemented an ML framework utilizing a hybrid Graph Neural Network-Long Short-Term Memory (GNN-LSTM) algorithm. This innovative approach leverages the spatio-temporal data generated from the multiphysics simulations, effectively predicting temperature evolution across the battery module. The GNN component captures spatial dependencies related to the battery's internal structure and thermal pathways, while the LSTM network models the temporal dynamics of the battery's thermal response. This dual mechanism ensures a comprehensive analysis of the potential hotspots and thermal anomalies that precede TR events.The model's accuracy in representing the physical phenomena was validated against experimental discharge data at various C-rates, showing a high correlation with real-world battery behavior. One key finding was the identification of temperature thresholds where SEI decomposition accelerates, leading to rapid temperature increases. The model also highlighted the impact of operational stress, such as high C-rates, on accelerating degradation and advancing the onset of TR. Our findings reveal that the integrated multiphysics-ML model can accurately forecast critical thermal events in LIBs, offering a substantial lead time before the onset of TR. This predictive capability enables proactive measures to be taken, such as system shutdown or cooling interventions, thus averting potential damage and enhancing battery safety. Moreover, the model's adaptability to various battery configurations and operational conditions signifies a significant leap toward battery safety solutions.VY and TAK gratefully acknowledge financial support from the Department of Defense (DoD) Office of Naval Research (ONR) through the Defense Established Program to Stimulate Competitive Research (DEPSCoR).

Accuracy and Limitations of Measuring Corrosion Rates and Depth of Penetration on Corroded Steel Plates Using Dual-Element Ultrasonic Sensors

Monitoring corrosion is a vital step to prevent catastrophic structural failure. With accurate corrosion rate data, the risk of failure can be mitigated by performing routine maintenance on components that have become compromised. When corrosion occurs in an inaccessible area such as the inside of a pipe or back side of an underground storage tank, however, conventional monitoring techniques such as visual inspection are inadequate or impossible. Non-destructive evaluation (NDE) techniques must be used to determine the condition of the structure to maintain its integrity. Ultrasonic (UT) Thickness Sensors were investigated for corrosion monitoring use. The chosen sensors had a resolution of a limit of 25.4μm. A system was designed to utilize Electrochemical Machining (ECM) to simulate a corrosion at various rates in a localized region (approximately 1 cm in diameter) while its thickness was monitored by a permanently attached UT sensor. Multiple techniques such as a 3D profilometer, and depth-gauge were used to validate the measurement of the permanently attached UT sensor. Multiple ECM experiments were conducted using NaCl electrolyte solution at 1, 10, and 100 g/L concentrations. Occasionally, variations in pit formation were observed and likely caused by the orientation of the counter electrode to the steel surface. The smallest and most consistent surface roughness was obtained using the 10 g/L concentration. Larger variations in surface roughness were observed at 1 and 100 g/L NaCl concentrations leading to the selection of 10 g/L solution for experiments. The ECM system rendered reproducible machining rates showing that the UT sensors were capable of monitoring very low corrosion rates averaged to 3μm per day. Discrepancies up to a few mm were sometimes measured between the UT sensor, 3D profilometer and depth-gage values. The discrepancies were attributed to non-uniform corrosion in the vicinity of the permanently attached UT sensor. The sensor therefore provided readings of a specific localized spot of the corroded region, or the profile of the corroded region interfered with the UT signals. The accuracy of UT sensor readings was also studied for various geometrical pit profiles. Certain defect geometries made it impossible for the UT sensor to record accurate measurements. This was also observed on naturally corroded steel plates. Therefore, UT sensors may sometimes provide inaccurate or no reading over certain corrosion profiles and should therefore be used with prudence.

(Invited) Magnetic Field Imaging for Fault Diagnosis of Lithium-Ion Batteries

The popularity of Li-ion batteries for electric vehicles has spotlighted their importance in safety. Nonetheless, they can accidentally fail sometimes due to small, undetectable errors during manufacturing or use. Identifying these flaws and distinguishing between different types of cell failure without physically opening the cell presents a significant challenge. Although minor errors inside the cells can trigger catastrophic failures, tracing them and distinguishing cell failure modes without dissecting the cell remains difficult. Since various defects within the cell could cause abnormal current flow compared to normal cells, visualizing the current inside the battery allows us to pinpoint and track these invisible defects over large-area cells. Focusing on how the current moves inside the battery helps us uncover and address hidden defects, enhancing battery safety and ensuring the reliability of Li-ion batteries.This talk introduces a real-time, non-invasive magnetic field imaging (MFI) tool capable of detecting the magnetic field signal induced by abnormal current flow inside fault-simulated Li-ion pouch cells. MFI offers high-speed scanning (~100 mm/min) and high spatial resolution (0.161 mm) with the benefits of simple instrumentation and the acquisition of directional information. By validating the Biot-Savart law, normal current flow patterns can be identified through cross-validating simulation studies and experimental results using MFI. To demonstrate the efficacy of current flow pattern analysis in battery fault diagnosis, the MFI study was extended to identify detectable defects among various flaws and to determine if the severity of these defects can be quantified by building experimental and simulational fault-simulated cells. Direct visualization of current distribution patterns and understanding pattern changes during operation is believed to expedite the non-destructive, immediate diagnosis of commercial cells and address safety-related challenges.

How Much Safer Are Solid State Cells? - Quantified Failure Analysis of Next-Generation Solid State Cells during Abuse Testing

Solid-state lithium-ion batteries offer a promising solution for electric vehicle energy storage by replacing flammable liquid organic electrolytes with non-flammable solid alternatives, thus significantly enhancing safety levels.1 However, despite this potential, the safety of these batteries remains a subject of debate due to a lack of quantified understanding, and existing standards may not adequately address anticipated failure modes. Consequently, there is a pressing need to characterize and quantify the safety of solid-state cells, considering the unique chemistry of each component. Although solid electrolytes aim to reduce the instances of soft shorts between electrode, one of the major safety concerns in solid-state batteries is the occurrence of internal short circuits (ISCs) under faliure circumstance, which pose significant challenges in terms of durability and safety, particularly in automotive applications. ISCs can lead to rapid and catastrophic discharge of up to 70% of the total cell energy in under 60 seconds, resulting in substantial self-heating and potentially initiating thermal runaway.2 To evaluate the safety of solid-state cells, abuse testing has become a standard practice, involving techniques such as nail penetration, crush testing, accelerating rate calorimetry, and overcharging. These tests expedite ISC occurrences, enabling researchers to gain insights into cell behaviour under extreme conditions and facilitating safety assessments. In this study, we conducted a comprehensive examination by subjecting commercial solid-state cells and Li-ion cells of similar energy to catastrophic failure conditions. In conducting this work, we aim to provide a comparative analysis of the challenges encountered by solid-state cells and to quantify the impact of scale-up on safety and failure events, ranging from cell capacities of 2 Ah to 10’s of Ah, and examining the propagation of failure through battery packs. To achieve this, we utilized a diverse array of abuse testing and characterization techniques, including X-ray CT, SEM, and GCMS. Through this endeavour, we aim to establish a benchmark for solid-state failure analysis and quantification, contributing to the advancement of safer battery technologies.[1] Mauro Pasta et al 2020 J. Phys. Energy 2 032008[2] Hossein Maleki and Jason N. Howard 2009 J. Power Sources. 2 568-574

Numerical Simulation Study on Predicting the Critical Icing Conditions of Aircraft Pitot Tubes.

Aircraft pitot tubes are sophisticated instruments designed to detect airflow pressure and relay this information to onboard computers and flight instruments, enabling the calculation of airspeed through the measurement of total-static pressure differences. The formation of ice on aircraft pitot tubes can compromise the acquisition of airspeed data, misguide pilots, and potentially cause catastrophic flight control failures. This article introduces a predictive methodology for identifying critical conditions that lead to icing on aircraft pitot tubes. Utilizing numerical simulation techniques, the methodology calculates the critical conditions for pitot tube icing across cruise flight regimes and atmospheric conditions, resulting in the generation of a critical condition envelope surface. By comparing these critical conditions against actual sensor data, a predictive danger zone can be established, offering an advanced warning system to ensure flight safety.

Navigating the unknown: Leveraging self-information and diversity in partially observable environments

Reinforcement learning algorithms often struggle to learn in partially observable environments, where different states of the environment may appear identical. However, not all partially observable environments pose the same level of difficulty for learning. This work introduces the concept of dissonance distance, a metric that can estimate the difficulty of learning in such environments. We demonstrate that self-information, such as internal oscillations or memory of previous actions, can increase the dissonance distance and make learning easier in partially observable environments. Additionally, sensory occlusion may occur after learning was completed, leading to a lack of sufficient information and catastrophic failure. To address this, we propose a spatially layered architecture (SLA) inspired by the brain, which trains multiple policies in parallel for the same task. SLA can change the amount of external information processed at each timestep, providing an adaptive approach to handle the changing information in the environment state-space. We evaluate the effectiveness of our SLA method showing learnability and robustness against realistic noise and occlusion in sensory inputs for the partially observable Continuous Mountain Car environment. We hypothesize that multi-policy approaches like SLA might explain the complex dopamine dynamics in the brain that cannot be explained with the state of the art scalar Temporal Difference error.

Upgrading Mixed Plastic Waste through Industrial Symbiosis: Pseudoductile Regenerated Cellulose Fiber-Reinforced Shredder Residue Composites.

The mechanical performance of mixed plastic waste from shredder residue is hindered by brittleness and catastrophic failure, limiting its potential applications. In this study, the mechanical properties of mixed plastic is enhanced by reinforcement with rayon fibers through a wet powder impregnation process to leverage the fiber's ductility and entanglement. However, mixed plastic remains poorly dispersed in water during the composite manufacturing, resulting in poorly consolidated composite, which further deteriorates the mechanical properties of mixed plastic from 1.5% strain-at-break to 0.7%. To address this issue, the addition of sodium dodecyl sulfate (SDS) surfactant is explored, where the optimal concentration is found beyond the critical micelle concentration at 10 mM. Lowering the surface tension of water and the adsorption of the SDS on the mixed plastic powder surface facilitated homogeneous dispersion of mixed plastic particles, resulting in well-consolidated rayon fiber-reinforced composites. The 30 wt % rayon fiber-reinforced mixed plastic composite prepared with SDS demonstrated a progressive failure behavior, exhibiting a strain-at-break of 8% and a remarkable 350% increase in impact strength compared to unreinforced mixed plastic. This approach provides a platform to overcome the inherent limitations of mixed plastic waste, offering waste-derived plastic alternatives and reducing the need for fossil-derived virgin materials for a wide range of noncritical applications.

Failure and reinforcement of reservoir landslides: Insights from centrifuge modeling and numerical modeling

The construction of the Three Gorges Reservoir dam in China has led to an increase in reservoir landslide events. To mitigate these geohazards, multiple rows of stabilizing piles (MRSP) have been employed to stabilize massive reservoir landslides. This study utilizes centrifuge and numerical modeling to investigate the behavior of unreinforced landslides and MRSP-reinforced landslides in reservoir areas. The failure mechanisms of unreinforced landslides, as well as the mechanical behavior and stabilizing mechanisms of MRSP under reservoir water level (RWL) fluctuations, are examined. The results indicate that elevated downward seepage forces contribute to pre-failure sliding, but are not the sole cause of catastrophic failure. Instead, rapid pre-failure sliding leads to soil particle compression and crushing in the saturated sliding zone, resulting in excess pore water pressure and accelerated overall failure. This excess pore water pressure-dependent mechanism explains the observed “step-like” deformation pattern and rapid failure pattern in reservoir landslides. Furthermore, the study reveals the formation of soil arches between adjacent MRSP groups, causing stress concentration on boundary columns and necessitating reinforcement. The finding challenges traditional one-dimensional load transfer ratios, advocating for a two-dimensional approach that accounts for variations across rows and columns. Notably, the study also highlights significant variations in load transfer laws within MRSP under different RWL operations, emphasizing the need for a more nuanced understanding of MRSP behavior.

The Catastrophic Failure Mechanisms and the Prevention of Dynamic Pressure-Related Hazards During Mining Under an Interval Goaf Through an Isolated Coal Pillar in Shallow and Closely Spaced Coal Seams

Given the potential for dynamic load-induced support crushing that may occur during mining under an interval goaf through an isolated coal pillar (ICP) in shallow closely spaced coal seams, this paper systematically explored this issue through a case study of the 30,103 working face at the Nanliang Coal Mine. We employed a combined approach of similarity simulations, theoretical analyses, numerical simulations, and field measurements to investigate the catastrophic failure mechanisms and prevention strategies for dynamic pressure-related hazards encountered when mining a lower coal seam that passes through an ICP. The findings indicated that the synchronous cutting instability of the interlayer effective bearing stratum (IEBS) and double-arch bridge structure of the ICP roof were the primary causes of dynamic load-induced support crushing at the working face. A mechanical model was developed to characterize the IEBS instability during mining under an interval goaf. The sources and transmission pathways of dynamic mining pressure during mining passing through the ICP were clarified. The linked instability of the double-arch bridge structure of the ICP roof was induced by IEBS failure. The UDEC numerical model was utilized to elucidate the instability of the IEBS during mining in the lower coal seam and to analyze the vertical stress distribution patterns in the floor rock strata of the interval goaf. A comprehensive prevention and control strategy for roof dynamic pressure, which includes pre-releasing concentrated stress in the ICP, strengthening the support strength of the working face, and accelerating the advancement speed was proposed. The effectiveness of this prevention and control strategy was validated through actually monitoring the characteristics of mining pressure data from the 30,103 working face following pressure relief. The findings provide valuable insights for rock stratum control of shallow and closely spaced coal seam mining under similar conditions.

Origins of British reservoir safety legislation 1850–1930

One hundred years ago in 1925, there were two dam failures with significant loss of life, and following these disasters, the 1930 Reservoirs (Safety Provisions) Act was enacted. Catastrophic failures in the nineteenth century had produced demands for government action but legislation had been much delayed by changes of government at critical times and by concerns about inadvertently reducing the legal liability of reservoir owners. Also, there was a marked lack of enthusiasm within the civil engineering profession for a government inspectorate. The key feature of the 1930 Act was that reservoir owners were required to appoint qualified civil engineers to inspect their reservoirs and, following such inspections, to implement measures required in the interests of safety. Post-1930 legislation, which it is intended will be the subject of a further paper, has done much to enhance public safety but the fundamental importance of independent qualified civil engineers has not diminished.

Data-driven AI for the automated classification of the isothermal heat-treated thermal barrier coatings using pulsed infrared thermography

Abstract Development of reliable age prediction models are crucial in monitoring the formation of oxide layer and degradation of TBC at regular intervals. This study proposes an automated classification of isothermal heat-treated TBC samples using temperature data, which helps in predicting the TBC life and monitoring the TBC degradation. TBC-coated samples are isothermal heat-treated at 1000 °C, and the initial growth of thermally grown oxide is monitored using a non-destructive thermal imaging technique. The proposed study integrates data-driven AI (DAI) models and feature extraction techniques to interpret complex thermal patterns measured from the TBC coating surface. The performance of the proposed classification framework is tested using deep learning and classical machine learning models with different types and window sizes of input data. Input data used for validation are raw experiment data, logarithmic of experiment data, polynomial fit data, and thermal signal reconstruction fit coefficients. The maximum classification performance is obtained with gated recurrent unit with accuracy and F1-score of 89.2% and 89.0%, respectively with raw temperature data as input of window 300. The study demonstrates that the proposed DAI approach effectively predicts the age of thermal barrier coatings under isothermal heat-treatment conditions by correlating the thermal response with coating degradation.

Brief communication: Monitoring impending slope failure with very high-resolution spaceborne synthetic aperture radar

Abstract. We demonstrate how high spatial and temporal resolution spaceborne synthetic aperture radar (SAR) imagery can improve slope deformation monitoring. We process ICEYE data over the Brienz/Brinzauls slope instability in the Swiss Alps, where a catastrophic failure occurred on 15 June 2023. Image correlation applied to retrieve surface velocities shows results comparable to in situ measurements. Pre- and post-failure acquisitions used to map areas invaded by debris and to compute associated volumetric changes are in good agreement with photogrammetric data. This study sets the baseline for new-generation satellite SAR data aimed at providing timely information in landslide early warning scenarios.

Corrosion resistance properties and hydrogen embrittlement protection efficiency of single-layer and multi-layer metal and ceramic films deposited on SS316L substrates

Hydrogen is a promising source of clean energy. However, the tanks used to store hydrogen fuel are prone to hydrogen embrittlement and are thus at risk of stress cracking and catastrophic failure. Accordingly, this study deposited single-layer and double-layer Zr, Al, SiO2, Al2O3, Al@Al2O3, and Al@SiO2 films on 316L stainless steel substrates and examined their feasibility as protective coatings by measuring their anti-corrosion properties and hydrogen permeation currents. The results showed that the single-layer Al2O3 film had a higher corrosion resistance than the single-layer SiO2 film and bare 316L substrate. Among all the coatings, the Al@Al2O3 double-layer coating exhibited the highest protection efficiency of 95 %. Moreover, it showed the lowest hydrogen penetration current density (1.08 x 10−3 A/cm2), the longest hydrogen embrittlement time (16000 s), and the lowest hydrogen content (0.008 mol/cm3). In other words, the Al@Al2O3 double-layer coating combined superior corrosion resistance with excellent hydrogen permeation suppression. Consequently, it is a promising material for enhancing the safety and longevity of hydrogen storage tanks in practical applications.

Optimal (T,N,n) preventive replacement first policy for a parallel system

A ( T , N , n ) preventive replacement first (PRF) policy is proposed in this article to investigate a parallel system with two independent parts where the secondary part is in a cold-standby state initially. Before the system fails completely, a preventive replacement is carried out at the planned time T, the time when the system successively completes N jobs or the time when the system suffers the n-th type-I failure, whichever occurs first. The system deteriorates stochastically, and it may experience two types of failures: type-I (repairable or minor) failure and type-II (non repairable or catastrophic) failure. When the system suffers a type-II failure, it’s correctively replaced. This model is widely applied in real-life scenarios, especially in the aviation industry. Under the single-parameter optimization scenario, both cost-minimal N and n exhibit favorable convexity characteristics. This indicates that we can uniquely determine the optimal N and n under the principle of minimizing the mean cost rate. Furthermore, we find that the mean cost rate cannot be minimized as T is less than a certain threshold, which implies that the planned time of the preventive replacement should not be implemented too early. In addition, the optimal multi-dimensional replacement policy that minimizes the mean cost rate can be uniquely obtained by theoretical or numerical analysis. Our proposed model provides a versatile formulation for analyzing a large variety of replacement policies. Compared with previous literature, the PRF policy adopted in this article integrates T-, N- and n- control policies, making it more comprehensive. It’s of practical significance for relevant enterprises to make decisions, assisting them in minimizing the mean cost rate while enhancing system reliability.

Effects of openings on postbuckling behavior of large‐size composite C‐beam under bending‐shear coupling load

AbstractProper design and accurate mechanical assessment of composite C‐beam after opening are of great importance in structure engineering. This paper aims to experimentally and analytically investigate the postbuckling response of large‐size C‐beam with web opening under bending‐shear coupling load. New specimen with four different open shapes were designed and tested. Strain gauges and displacement measurements were applied to monitor its buckling behavior, strain field distribution and critical failure load. Four specimens with various openings were loaded until catastrophic failure occurred. Additionally, an analytical model was introduced to predict the residual strength of circular opening. The results indicate that while the presence of an opening significantly decreases the load carrying capacity, it has minimal effect on the bending stiffness. Compared with intact specimen, the initial delamination, buckling and ultimate strength of the circular opening decreases less than those of the rectangular opening. By altering the position of the rectangular opening, improvements can be made in terms of initial delamination resistance and buckling load; however, ultimate strength remains largely unaffected. Reinforcing the edge of an opening further reduces resistance to initial delamination but other two indicators are improved. Overall, from buckling to failure stages, post‐buckling bearing capacity after opening decreases by 40%. Moreover, the shear failure mode is observed during catastrophic failures. And the analysis method employed is relatively conservative.Highlights Ten large size composite C beams are conducted under coupling loads. Deformation, strain distribution and failure mode are presented. Influence of openings on postbuckling behavior of beam is analyzed. An analysis method is employed to predict the residual strength of beam. It could provide valuable insights for assisting in designing beam openings.

Method for Calculating the Unbalanced Current in Ungrounded Double Wye C-Type Harmonic Filters

This paper presents a methodology to calculate the neutral unbalanced current in C-type filters with an ungrounded double Wye topology; this equipment is widely used in the steel sector to mitigate the harmonic content in electrical installations caused by electric furnaces used in metal smelting processes. A common failure in these filters is the current unbalance caused by the degradation of the capacitor and inductor modules, leading to dangerous surges that affect these components, possible harmonic resonances, and deficient filtering by the equipment. Currently, there are no documented strategies for calculating the neutral current that allow for the proper adjustment of neutral protection in this type of equipment, resulting in catastrophic failures, costly unscheduled shutdowns, and potential harm to plant personnel. In this paper, we propose a methodology for calculating the unbalanced current in double Wye C-type harmonic filters, considering the natural degradation of capacitor and inductor modules and based on on-site measurements of the impedances for each element of the equipment. This allows for the predictive maintenance of these devices and the precise adjustment of neutral overcurrent protection. First, we review the operating principle of C-type harmonic filters and the neutral protection scheme. Then, the calculation methodology is proposed and validated in two practical case studies. In the first case, a 45 Mvar C-type second harmonic filter connected to a 34.5 kV bus is analyzed. In the second case, an 18.5 Mvar C-type second harmonic filter, part of a ±80 Mvar STATCOM system, connected to a 34.5 kV bus is examined. In both cases, these filters reduce the harmonic content in two steel plants: the first connected to a 400 kV bus and the second to a 230 kV bus. The results obtained with the proposed methodology were implemented in the protection device for a neutral current imbalance, considering different degradation values of the capacitors, and compared with the manufacturer’s suggested settings. The discussion highlights the good performance of the proposed methodology, particularly in terms of the protection device’s response speed to a risky unbalanced current.

Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis.

The frame beam structure of the mine screen, subjected to various excitations, is a critical component of mining machinery. Its stress is intricate, the operational environment is severe, and damage can lead to catastrophic failures resulting in machinery destruction and fatalities. Based on the characterization of the vibration response of mine screen frame beams with varying degrees of damage at the same location and with the same degree of damage but at different locations, this paper develops a method of strain modal difference vibration pattern analysis and damage feature extraction for the detection of structural damage in beams. This method is based on the sensitivity of the sudden change in vibration strain modal difference to small deformations. This method solves the problem of using the conventional structural finite element analysis or experimental modal analysis methods to obtain the displacement mode, intrinsic frequency, and other characteristics, which make it difficult to effectively identify the actual engineering, with the damage conditions of the damage state and damage location of the mine screen frame beam problems. The feasibility and validity of the engineering application of the concept are demonstrated through instances.

Numerical model of curved composite tiles under low-velocity impact loading

In recent years, composite structures have seen widespread application across diverse industries, including automotive and aerospace, owing to their favourable strength-to-weight ratio. However, these structures, particularly high-pressure vessels, are susceptible to extreme loadings such as impact forces, resulting in visible and latent damage, ultimately leading to catastrophic failures. Hence, it is imperative to assess such damages diligently. Given the cost implications associated with experimental investigations, numerical methodologies emerge as a potent means for conducting relevant analyses. This paper will introduce a numerical model approach to conducting virtual tests to assess curved carbon fibre composite tiles subjected to low-velocity impact. The primary focus of this study is to consider the impact-induced delamination on composite tiles through a numerical model. The composite tiles are conducted to 90J impact loading. Specifically, the study evaluates filament winding structures’ interface properties (shear resistance) variability during manufacturing. Notably, the parameter of shear resistance significantly impacts the anticipation of intralaminar damage (delamination) after impact loading. Three-point bending tests were performed to calibrate the composite material’s shear interface properties, followed by low-velocity impact tests on the curved composite tiles. The findings indicate that the shear resistance values, which ranged from 14.25 MPa to 60 MPa, play a critical role in predicting delamination, with lower shear resistance leading to increased damage areas. The results underscore the importance of accurately calibrating interface properties to enhance the predictive accuracy of numerical models for curved composite structures under impact loading.

Bench-scale thermomechanical assessment of carbon fibre reinforced polymer C-channels

This study investigates the thermomechanical response of carbon fibre reinforced polymer (CFRP) C-channels using a bench-scale apparatus that combines mechanical loading and radiant thermal exposure. The study aims to assess the behaviour of pre-loaded CFRP C-channels, representative of aircraft sub-structures when subjected to fire conditions. Woven prepreg CFRP C-channels were tested under cantilever point load deflection while exposed to varying heat fluxes. Key aspects examined during the study include failure times, displacement, temperature distribution, and failure modes. The findings reveal that heated, pre-loaded C-channels experience distinct phases of physico-chemical decomposition and mechanical degradation. The mechanical degradation includes upward shear buckling of the horizontal flanges and vertical web, along with outward buckling of the vertical web towards the heat source. The study shows that thermal decomposition and mechanical degradation occur simultaneously, influenced by heat flux intensity. Higher heat fluxes accelerate decomposition and reduce load-bearing capacity, while lower fluxes slow degradation. Displacement data indicates that heat flux intensity significantly affects structural response. Temperature measurements show higher fluxes lead to elevated temperatures and steeper gradients, impacting failure times and modes. Increased temperatures correlate with shorter failure times, and variability in failure times decreases as heat flux rises. These insights are significant for understanding the thermomechanical response of C-channels in aircraft sub-structures. The knowledge obtained can contribute to developing more robust and safer aircraft designs, particularly for components exposed to fire conditions, enabling engineers to establish more precise safety margins for CFRP structures, potentially preventing catastrophic failures and thereby enhancing overall aircraft safety.

Temperature dependent small-scale deformation of a refractory high entropy alloy

Temperature-dependent deformation behavior of [110] oriented micropillars of HfTaTiVZr refractory high entropy alloy (RHEA) was studied. Engineering stress–strain curves, strain rate sensitivity measurements, and in-situ observations revealed distinct deformation mechanisms at different temperatures: homogeneous at room temperature (RT), intermittent plasticity at 200 °C, chaotic stress drops at 400 °C, brittle failure at 600 °C, and creep-like behavior at 800 °C. Deformation morphology of the micropillars showed activation of few slip systems at RT and 200 °C, multiple slip systems at 400 °C, catastrophic failure at 600 °C, and minimal slip activity at 800 °C. These findings offer unique insights into the deformation of RHEAs.