Structural Failure Modes Research Articles

Study on the dynamic characteristics of pile wharves subjected to underwater explosion

A test was conducted to investigate the dynamic response characteristics and damage modes of pile wharves subjected to underwater explosions. To simulate the explosion process, a fluid-solid coupling finite element model of the pile wharf was constructed. The structural damage process, response characteristics, and failure modes of the pile wharf were analyzed based on the experimental and numerical simulation results. The results showed that the main damaged components of the pile wharf were the piles, with damage modes of cracks, spalling, and brittle shear. The probability of moderate or more significant damage to the inclined piles was 25% higher than that of the vertical piles. The inclined piles with low deformation ability were more prone to local concrete brittle failure, significantly increasing the possibility of instability and failure of the pile wharf structure. The acceleration response spectrum indicated that although the structure of the pile wharf was severely damaged, the personnel on its surface slab still had a high probability of survival. The study indicates that replacing inclined piles with alternative optimized structures benefits the blast resistance of pile wharves.

Study on the Seismic Response of Shield Tunnel Structures with the Preload Loss of Bolts

Shield tunnels can experience preload loss in their connecting bolts during the operational phase, leading to changes in tunnel structure stiffness, which, in turn, affect the seismic performance of shield tunnels. A refined three-dimensional model of shield tunnel was established using the finite element method to study the impact of preload loss in connecting bolts on the seismic dynamic response of shield tunnels. An artificial viscoelastic boundary was used to simulate the propagation of seismic waves from an infinitely distant field. This study investigated the effects of different levels of preload loss on the seismic response of shield tunnels. In addition, the Arias intensity, which can reflect the degree of seismic impact on structures, was used to analyse the extent of damage to the tunnel. The conclusions drawn from the study are as follows: As the level of preload loss increases, the tightness of the segments during the static phase gradually deteriorates, and the maximum joint opening during the seismic loading phase continues to increase. Post-earthquake non-recoverable ellipticity and radial deformation progressively increase with an increase to preload loss level. Overall tunnel damage becomes more significant with the degree of preload loss increases depending on the Arias intensity. Preload loss leads to a decrease in the overall structural stiffness and an increase in longitudinal relative displacement. In conclusion, preload loss also affects structural failure mode and seismic performance. These research findings are of reference value for enhancing the seismic performance of shield tunnel structures and ensuring engineering safety.

Comparative study on damage effects of penetration and explosion modes on airport runway

As an important part of civil and military buildings, airport runway is an important research object in the field of protection. In this study, damage assessment of scaled-down target of airport runway was carried out through experiment and numerical simulation. Two experimental methods, static explosion of charge after penetration and explosion of prefabricated hole, were used to damage the target and crater size and surface acceleration of the target were measured and analyzed. The experiment proves that the damage effects of the two methods were obviously different. The crater size produced by static explosion of charge after penetration was obviously larger than that produced by explosion of prefabricated hole under the same explosion depth and explosive charge, of which the shapes were also different. The numerical calculation model was established, and static explosion of charge after penetration was realized and detonation products leakage in inward explosion were solved through restart and S-ALE numerical calculation methods. Calculation results were compared with the experimental results; state equation and parameters were verified; damage effect diagram was obtained by numerical calculation, and mechanism of damage difference was analyzed. The study noted that obvious difference in explosion pressure transmitting and structural failure modes in multi-layer medium and that in a single medium. It proved that the damage caused by penetration will affect cratering effect and the movement of detonation products. Based on the experimental and numerical results, two formulas were given for calculating the crater sizes of airport runway under static explosion of charge after penetration and under explosion of prefabricated hole. The effect of dimensionless penetration coefficient and dimensionless explosion coefficient on crater size was determined by analyzing the crater relation curve of airport runway. The study indicates that the size difference between static explosion of charge after penetration and explosion of prefabricated hole charge can reach 30%. To carry out more accurate study on the damage of the projectile to target, the experiment should adopt static explosion of charge after penetration.

Optimal risk-based design of reinforced concrete beams against progressive collapse

Risk analyses addressing consequences of progressive collapse have shown that, due to the small probabilities of element loss due to abnormal loads, structural strengthening for alternate load paths has negative cost-benefit for most buildings subjected to typical threats. This study addresses optimal risk-based design of reinforced concrete beams subjected to supporting column removal, with specific focus on reinforced concrete behavior. Nonlinear finite element analysis (NLFEA) is carried out, allowing both compressive arch and catenary actions to be predicted under large deflections. NLFEA results are compared to experimental data, showing good agreement and allowing quantification of model errors. Risk optimization results show that optimal beam designs change significantly with local damage probability, which is considered an independent parameter. More importantly, the study shows how different failure modes compete for limited construction and strengthening budgets. In case of intact structure, optimal design is governed by serviceability displacements, bending failure at midspan, and bending-shear failure at beam ends. Optimal design of the damaged structure is controlled by shear failure at beam ends and tensile rupture of steel rebar due to either catenary action or snap-through instability. Results highlight that, under significant column-loss probabilities, progressive collapse resistance is reached by larger beam depth, greater reinforcement area and reduced stirrup spacing. Such design measures against progressive collapse also provide greater safety margins against all failure modes of the intact structure.

An adaptive structural dominant failure modes searching method based on graph neural network

Dominant failure modes (DFMs) of structural systems are integral to life prediction and reliability assessment. However, the computational efficiency of existing DFMs searching methods is constrained by neglecting the structural non-Euclidean properties. To break free from this shackle, this paper proposes a DFMs searching algorithm based on the graph neural network (GNN). The proposed algorithm can adaptively identify graph samples representing DFMs via completing graph classification. First, the target structural system is converted into an undirected graph to preserve its topological features. Second, a hierarchical graph attention mechanism is developed to establish the mapping relationship between structure intrinsic properties and DFMs. Finally, two adaptive sample selection strategies are devised to iteratively search DFMs and supplement graph datasets. In order to reduce the number of reliability analyses, the algorithm will terminate prematurely when unable to identify new DFMs. A 2D truss and a 3D frame are selected to test the computational efficiency and stability of the algorithm. The search results indicate that, despite providing different initial training sets, this GNN-based algorithm still converges to DFMs consistent with the result of Monte Carlo Simulation (MCS). Compared to the genetic algorithm (GA) and the β-unzipping method, the proposed algorithm exhibits higher computational efficiency.

Fragility Analysis of the Main Building–Coal Conveyor Trestle Interaction System of a Thermal Power Plant

Thermal power plants play a crucial role in the power system as critical lifeline infrastructure. In order to meet the production process requirements, the main building of a thermal power plant is often connected to a coal conveyor trestle. This study focuses on investigating the seismic interaction between the common three-row reinforced concrete frame-bent main building and the steel trestle in a circulating fluidized bed (CFB) unit. The objective is to assess the influence of the trestle on the main building and understand the failure mode of the trestle structure. The seismic interaction is analyzed through fragility analysis based on Incremental Dynamic Analysis (IDA). The results indicate that the trestle has minimal influence on the main building, except during the large deformation stage. The study identifies the failure mode of the coal conveyor trestle as excessive relative displacement along the longitudinal direction at the connection points, leading to collisions or falls. A seismic demand model based on longitudinal relative displacement is developed to obtain the fragility curve for the trestle structure. These findings offer valuable insights for assessing the seismic performance of thermal power plants.

Improved seismic risk evaluation for high‐voltage switchgear equipment: A copula‐based framework considering joint failure modes

AbstractTraditional seismic evaluations for high‐voltage switchgear equipment, the critical power facilities, consider only structural failure mode and may underestimate the actual seismic risk. By additionally introducing a probable functional failure mode caused by the excessive deformation of the switchable blade of equipment, a novel copula‐based framework is proposed to utilize limited samples to generate simulation data and evaluate the joint failure probability (JFP). The correlation index and Akaike Information Criterion are employed to optimize the Copula function. For illustration, a disconnector, representative switchgear equipment, was selected as an example and modeled with the experiment validation. Model analysis results demonstrate the Clayton type is the most competent for evaluation. Neglecting functional failure can significantly underestimate the actual failure probability at various seismic intensities, up to 50%. Furthermore, it was found that the current equipment material strength level already meets the requirements, and enhancing strength alone does not effectively improve reliability under strong earthquakes. For PGA intensities ≥0.7 g, the blade deformation capacity plays the primary reliability constraint, independent of material stress. A cost‐effective seismic design should optimize the combination of allowable material stress and blade deformation based on the JFP considering seismic intensity and targeted reliability.

A random forest regression with Bayesian optimization-based method for fatigue strength prediction of ferrous alloys

Fatigue is a prevalent failure mode in mechanical structures, and the significance of fatigue strength as a process parameter for predicting the life of a material or structure cannot be emphasized enough. Given the high cost and time consumption associated with traditional experimental approaches for determining fatigue strength, which leads to prolonged analysis and design cycles, it is crucial to investigate efficient and precise methods for predicting fatigue strength. In this paper, we present a fatigue strength prediction method that utilizes Bayesian optimization for the random forest regression (RFR) model. During the training of the RFR model, a Bayesian optimization algorithm is employed to optimize the five main parameters of the model, mitigating the issue of overfitting or underfitting. The optimized RFR model demonstrates superior performance and accuracy in comparison to linear regression (LR), artificial neural network (ANN), decision tree regression (DTR), and support vector regression (SVR). This is determined by evaluating the mean absolute error (MAE), root mean square error (RMSE), R-squared (R2), and mean absolute percentage error (MAPE) scores of the feature parameter-fatigue strength dataset. The fatigue strength of unknown ferrous alloys can be predicted with the proposed model, which largely reduces the need to obtain fatigue strength data through traditional fatigue tests and saves fatigue analysis time and test costs.

Torsional Effects on Wind Turbine Blades and Impact on Field Damages

The purpose of this paper is to present the importance of torsional loads when understanding the significant increase in structural damages on large wind turbine blades. By comparing the stress state of two blades of different length, it is shown that torsional loads grow with an exponent of four (4). Thereby, a function of the length of the blades leading to a new range of challenges that are not met by the current process for design, testing and certification.The paper presents the study of these new challenges in detail, based upon:- An experimental perspective, with results from large-scale cyclic loading tests on two blade cut-outs conducted under controlled laboratory conditions in. Both blades were tested to failure.- A numerical perspective, non-linear geometrical 3D FEM simulations has been performed to study the impact of torsional loads on relevant current structural failure modes on large wind turbine blades.The conclusion is that the larger torsional loads may explain shear-web disbond, as well as sandwich skin debonding in both the transition zone and in the max chord area of wind turbine blades. In view of the findings, the paper includes proposals for remedies that are expected to mitigate some of the significant failures currently seen in the field.

Failure mechanism of steel frames with angle steel-bolted connections exposed to fire under progressive collapse condition

Partially restrained connections comprise intricate systems of multiple components, each exhibiting varying degrees of performance degradation under fire conditions. Consequently, the damage patterns within these connections are reconfigured. Moreover, owing to the insulating effect of floor slabs, the thermal and mechanical states of remaining structures differ in hogging and sagging bending moment regions after removing critical members, thereby influencing the potential damage modes and collapse-resistant mechanisms. To elucidate this impact mechanism, a comprehensive analysis of the influence parameters on the failure mechanism and collapse-resistant action of a typical partially restrained connection (angle steel-bolted connection) steel frames exposed to fire was conducted based on multi-scale models. The results revealed that steel frame structures with different connection configurations all enter the compressive arching action (CAA) stage after the heating phase due to the thermal expansion behavior of beams. After the completion of load application, the deformations of all three connection models remain below 0.2 rad. The variation of beam load magnification factor α does not affect the structural failure mode, while a higher column load ratio causes the damage location to shift from the connection to the column under fire conditions and triggers a chain failure reaction. Compared to axial constraint kas, the rotational constraint krs is a critical factor influencing the damage mode. The negative axial force generated by the thermal expansion behavior of the fire-affected region can enhance the flexural action resistance in the unheated region by employing the CAA. Finally, a theoretical method is proposed to predict the failure mechanism of steel frames with angle steel-bolted connections exposed to fire under progressive collapse condition, providing a novel approach for identifying weak components of similar structures and improving anti-collapse capabilities.

Modeling and analysis of multi-functional self-healing material using Runge-Kutta Method for investigation of aircraft wing structure

ABSTRACT This paper presents the deployment of Runge-Kutta method to overcome the main challenge in analysis of failure of aircraft wing structure subjected to wind pressure and point loading. Failure phenomenon of any structure is time dependents and is typically referred as dynamic in engineering mechanics and is fairly a complex to investigate. In this context, the dynamic analysis concept has successfully implemented by using computer program in SCILAB software. The numerical technique is adopted as Runge-Kutta fourth order (RK4) method for performing dynamic behaviour of wind structure. The demonstration of failure mode of wing structure is based on function of time. The numerical approach is deemed to provide a detailed description of these phenomena affecting the overall dynamic of failure envelope of wing structure. The parametric study is presented; likewise the effect on failure of wing structure by changing different wind pressure, length and moment, respectively. The wing structure is analytically validated against available literature. Finally, others important failure results obtained from this analysis has discussed in detail.

A design methodology of composite scarf repairs using artificial intelligence

Composite Scarf Bonded (CSB) based techniques are highly effective in structural connections and structural repairs. In this article, a preliminary design methodology based on Machine Learning (ML) algorithms trained on databases obtained via a semi-analytical approach is proposed and used to generate the design space for CSB structures under tensile loads. This ML framework introduces the one-hot encoding technology to deal with discrete inputs, such as multiple stacking sequences. Four ML algorithms, Adaptive Boosting, Gradient Boosting Regression, Extreme Gradient Boosting, and Artificial Neural Networks are studied. The best-performing model is then used to generate the damage tolerance-based design space for CSB structures made from fabric and unidirectional prepregs, accounting for material and geometrical uncertainties. Very good representations of the design space and accuracy in structural strength and failure mode are obtained. An optimal scarf angle zone, where laminate and adhesive fail simultaneously, was identified using the proposed framework. This design framework opens new avenues for the selection of material and layup configuration in structural design and enables the fast estimation of the optimal scarf angle range for the preliminary design of CSB structures.

Numerical Analysis of Openings in Stiffeners under Impact Loading: Investigating Structural Response and Failure Behavior

<span lang="EN-US">As the demand for lightweight ships continues to rise, there is a growing necessity to explore innovative methods that can reduce the weight of ship structures without altering the materials used. This research addresses this challenge by investigating the effect of opening in stiffener under impact loading. The research aims to provide valuable insights into optimizing weight reduction strategies while ensuring the ship's overall strength and performance remain uncompromised. To achieve this goal, the study employed the finite element method as a solver. By simulating impact scenarios and analyzing stiffener responses, the numerical analysis quantified the structural behavior and failure modes. The focus was on understanding the impact of openings on the structural integrity and how it relates to their positioning relative to the impact point. The results of the study indicate that opening slightly distant from the impact point exhibit greater strength, showcasing a counterintuitive relationship between opening placement and structural response.</span>

Compressive properties and failure mechanisms of 3D-printed continuous carbon fiber-reinforced auxetic structures

3D printing of continuous carbon fiber-reinforced (CCFR) composites is an innovative and promising fabrication technique that meets the booming demands of lightweight and structural diversity in advanced transportation industries. In the present work, 3D printing of CCFR composites is introduced to design and fabricate auxetic structures with four Poisson's ratios. The compression characteristics of the 3D-printed CCFR auxetic structures are experimentally investigated under quasi-static loading. The characterization of fracture microstructures and the finite element simulation are carried out to go deeper into the compressive behaviors and failure mechanisms. Moreover, the compressive characteristics of the auxetic structures under diverse Poisson's ratios are analyzed based on the stress-strain curve, energy absorption and failure modes. The results reveal that the transformed configuration significantly affects the compressive properties and deformation behaviors under different Poisson's ratios. The 3D-printed CCFR auxetic structure with Poisson's ratio of -0.531 possesses the preferrable transformed configuration, leading to the highest specific energy absorption (SEA, 2.302 J·g-1). The bend-induced damage evolves from the whitish resin to the complete breakage of fibers, which is the dominant failure mode of 3D-printed CCFR auxetic structures. The research plays a vital guiding role in the structural design and engineering applications of 3D-printed CCFR auxetic structures with desired mechanical properties.

Mechanical Properties of Textile-Reinforced Composites with a 3D Printed Core

Abstract The article discusses the mechanical properties of glass fiber epoxy composites with three types of textile structures. Braided, knitted and woven sleeves were placed on a 3D printed flat core and impregnated with resin using the vacuum bag method. The 3-point flexural and tensile tests were performed. The results were compared with those of 3D-printed flat bars and proved that woven textile structures increase the strength and modulus of elasticity, whereas braided and knitted structures only increase the moduli. The advantages, drawbacks and failure modes of each reinforcement structure are also discussed including the drapeability on the spatial core.

The Mechanism of Rockbolts in Jointed Rock under Uniaxial Tension

In this research, the rockbolt mechanism of a jointed rock mass under uniaxial tension was systematically revealed with a laboratory test and a numerical simulation. It was found that the rockbolt rock mass experienced five stages under uniaxial tension, the densification stage, elastic stage, plastic deformation stage, progressive debonding stage, and complete debonding stage. The stress-strain curve and ultimate tensile strength of a rockbolt rock mass were analyzed by taking the rockbolt spacing and rockbolt angle as variables. It was found that the improvement effect of the reduction of the rockbolt spacing on the ultimate tensile strength was limited. When the rockbolt spacing was reduced to a certain limit, the stress concentration area between adjacent rockbolts was connected and destroyed, resulting in the increase of the rockbolt rock strength becoming smaller, and even having a downward trend. The increase of the rockbolt angle led to the change of the stress mode and failure mode of the whole structure, and the ultimate tensile strength first increased and then decreased. The optimal rockbolt angle was between 60° and 70°. It is worth noting that there was an obvious mechanical occlusion between the thread on the rockbolt surface and the rock mass, resulting in the multi-stage step-down characteristic of the stress-strain curve in the complete debonding stage. The results of this study can provide a reference for the design and construction of similar projects.

Research of reflective crack in asphalt pavement using SCB specimen and XFEM: From laboratory test to numerical simulation

Reflective cracking is one of the main failure mode of pavement structures, resulting in structure deterioration and reduced traffic safety. This study investigated the cracking behavior of reflective cracks using semi-circular bending (SCB) specimens and fracture tests were conducted to obtain fracture energy, which is the critical parameter of facture calculation, and the reasonability of fracture energy was validated using a numerical model of SCB specimen. Then, a numerical model of typical pavement structure was established and cracking behavior of reflective cracks and related parameters influencing cracking were investigated in detail. The simulation results indicate the main form of reflective crack is mode I and mode II mixed crack, among which mode I takes the dominant position. Among the four investigated influence factors, overloading and long-time loading have a significant influence on the expansion of reflective cracks, while the temperature mainly influences the expansion of mode I crack. The traffic speed mainly affects the direction of crack expansion, while other factors do not have a significant effect on it.

Experimental study on crashworthiness and failure mechanisms of aeronautical multi-fibers hybrid composite corrugated structures with Carbon, Glass, Kevlar

Crashworthiness of aeronautical composite structures can be effectively regulated and controlled by fiber hybridization design, because the structural failure modes are highly sensitive to hybrid parameters. However, the complex failure mechanism is still unclear, resulting in the inability to optimize the fiber hybridization. Hence, this study focuses on crashworthiness and failure mechanisms of aeronautical multi-fiber hybrid composite corrugated structures consisting of carbon, glass, and Kevlar fiber. The composite corrugated structures with single-fiber, double-fiber hybridization and triple-fibers hybridization are prepared by hand lay-up process. The quasi-static axial crushing tests are conducted to evaluate the crashworthiness and failure modes. The experimental results show both the crashworthiness and failure modes are very sensitive to fiber hybridizations with different fiber type and stacking sequence. Both double-fiber hybridization and triple-fibers hybridization can obtain high comprehensive properties including specific properties and cost effectiveness. However, Kevlar fibers placed in inner layers or alternately stacked with other fibers are vulnerable to the buckling-dominated failure mode that is detrimental to energy-absorption. The typical failure mechanisms of proposed hybrid composite corrugated structure are extensively revealed through the corresponding mechanism models. Overall, this study on disclosing complex failure mechanism can guide the optimization of fiber hybridization to improve crashworthiness of hybrid fiber composite corrugated structures.

CAISSON DESIGN AND VERIFICATION OF FRICTION COEFFICIENT OF CAISSON FOUNDATION FOR TUAS PORT PHASE 1

Reinforced precast concrete caisson has been selected as wharf front structure for the project of Tuas Port Phase 1 in Singapore. The caisson structure and foundation were designed to withstand various loading cases comprising loads during both construction and operation stages. It was identified that sliding failure mode of the caisson structures could be one of the critical design checks. The friction tests were conducted under various conditions to assess the Coefficient of Friction (m) between rock mound surface and concrete slab of caissons. The results show that the design value mu of 0.6 for rock mound and concrete interface could be achieved for normal flat concrete surface.

Reliability assessment of steel‐framed industrial buildings

AbstractThe classical reliability problem seeking an estimation of the probability of failure is usually undefined due to: i) its scale (size of the design problems), and ii) deficient characterization of the randomness (lack of statistical characterization of the basic random variables). A common challenge in current approaches for the assessment of structural reliability adopted in EN 1990 is the lack of data examples that could support additional research, simulation, and experiments. As the failure probability in Eurocode is about 10‐4, millions of simulations are required, which limits the accuracy of commonly used Monte Carlo simulations (MCS). Nowadays, there are different intelligent data management approaches to augment existing data points by creating synthetic examples that can then be further used in specific behavior prediction. One such intelligent approach is the recently developed Generative Adversarial Networks (GAN), which has found its use mainly in image augmentation, but also in other applications where finding new data examples is challenging, e.g., credit card fraud detection, defect detection, etc. In this paper, a reliability assessment of steel‐framed industrial buildings is presented. For that purpose, a set of portal frames is first selected as a case study and designed using the actual design codes, whereby the critical structural members and failure modes are identified. Subsequently, based on these representative case studies, the database is expanded using GAN, and the current state of reliability for the selected type of buildings is assessed, aiming to provide a statement of the current safety of industrial sheds using the Eurocodes.