Advanced Finite Element Research Articles

Hybrid CFRP-BFRP Rebars for Prestress Concrete Slabs: Abaqus Analysis and Experimental Validation

This study utilizes Abaqus finite element software to analyze concrete slabs reinforced with a novel hybrid of Carbon Fiber Reinforced Polymers (CFRP) and Basalt Fiber Reinforced Polymers (BFRP) rebars known as CBRP rebars. The investigation focuses on assessing the structural performance of these slabs under varying prestressing levels (PL) and FRP reduction factors (FR), along with the prestress index level (PI). The study defines the FR factor as the reduction in the transverse reinforcement area of FRP compared to the control slab. The PI is the ratio of prestressed CBRP rebars to the total FRP reinforcement in the transverse direction, aiming to determine a lower FRP reduction factor without compromising the FRP slabs' design requirements. Three FR values (0.45, 0.37, and 0.29) are considered, with the CBRP tendon tensioned at 35% and 50% of the ultimate strength, including 0.5 and 0.6 of the PI, for validation against experimental test data. The numerical analysis incorporates advanced finite element modeling techniques, integrating material properties, load conditions, and structural parameters to detail the behavior of CBR-reinforced concrete slabs. Various loading scenarios are simulated to evaluate the performance of CBRP rebars under diverse conditions. Comparison with experimental data validates the hybrid reinforcement approach's reliability. The study's findings contribute significantly to understanding the structural performance of concrete slabs reinforced with CBRP rebars. The hybridization of CFRP and BFRP rebars offers a promising alternative for enhancing concrete structure strength while reducing the carbon footprint associated with traditional reinforcement materials. The versatility of CBRP rebars allows customization based on specific structural requirements. Based on the Abaqus numerical analysis and its alignment with experimental data, the study recommends optimizing the CFRP-BFRP ratio to meet structural demands, evaluating long-term performance, and exploring environmental benefits associated with sustainable reinforcement materials. This research advances knowledge in the hybrid fiber-reinforced polymers field, offering insights for engineers and researchers seeking innovative solutions for concrete structure enhancement using Abaqus as a powerful analytical tool.

Three‑dimensional finite element analysis: Anatomical splint fixation for Colles fractures.

With the rapid development of digital research in clinical orthopedics, the efficacy and safety of splint fixation can be better evaluated through biomechanical analysis based on a three-dimensional (3D) finite element model. It is essential to address the current gap in understanding the biomechanical implications of anatomical splint fixation for Colles fractures. By employing advanced 3D finite element analysis, the present study aimed to provide a comprehensive evaluation, offering valuable insights that can contribute to enhancing the effectiveness of anatomical splint fixation in the clinical management of Colles fractures. The 3D finite element models of the forearm and hand were constructed using Mimics 15.0 according to data from computed tomography of a patient with a Colles fracture. After the validity of the model was verified, the corresponding material properties of the models were adjusted to simulate a Colles fracture. Subsequently, the reduction functions, such as radial inclination and ulnar deviation, of the simulated fracture were completed and the mechanical changes of the tissues surrounding the fracture were calculated. Anatomical splints were then placed on the surfaces of the 3D finite element models of Colles fractures at various positions to analyze the changes in the stress cloud diagram, such as for the soft tissue and anatomical splints. In the present study, the constructed 3D finite element models were accurate and valid. The maximum stress of the anatomical splints and soft tissues was 2.346 and 0.106 MPa in pronation, 1.780 and 0.069 MPa in median rotation and 3.045 and 0.057 MPa in supination, respectively. Splint stress reached the highest level in supination and soft tissue stress achieved the highest level in pronation. The peak of splint stress occurred during supination, which contrasts to the peak of soft tissue stress observed in pronation, suggesting splint fixation median rotation can effectively avoid compression of the local soft tissue.

Finite element analysis of JCO-E fabrication process and its influence on the collapse capacity of offshore pipelines

In the present work, the JCO-E fabrication process is numerically simulated using advanced finite element tools for the case of a thick-walled 30-inch-diameter pipe, which is candidate for deep water installation. Subsequently, the structural performance of the line pipe under external pressure is investigated in a unified approach. Uniaxial tests are performed to obtain the material properties used in the finite element model, which are representative of the loading history that the plate is subjected during the process. The finite element model is validated with geometric measurements from the actual pipe fabricated in the pipe mill. The effect of the expansion level on the properties of the final product is investigated through extensive numerical studies. The results have shown that there exists an optimum expansion range for achieving the minimization of the geometric imperfections of the final product and the maximization of the collapse capacity of the pipe.

Prediction of the Response of Masonry Walls under Blast Loading Using Artificial Neural Networks

A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex due to the potential opening and sliding of the mortar joint interfaces between the masonry stones. To capture this response, advanced computational models can be developed requiring a significant amount of resources and computational effort. The article uses an advanced non-linear finite element model to capture the failure response of masonry walls under blast loads, introducing unilateral contact-friction laws between stones and damage mechanics laws for the stones. Parametric finite simulations are automatically conducted using commercial finite element software linked with MATLAB R2019a and Python. A dataset is then created and used to train an artificial neural network. The trained neural network is able to predict the out-of-plane response of the masonry wall for random properties of the blast load (standoff distance and weight). The results indicate that the accuracy of the proposed framework is satisfactory. A comparison of the computational time needed for a single finite element simulation and for a prediction of the out-of-plane response of the wall by the trained neural network highlights the benefits of the proposed machine learning approach in terms of computational time and resources. Therefore, the proposed approach can be used to substitute time consuming explicit dynamic finite element simulations and used as a reliable tool in the fast prediction of the masonry response under blast actions.

(Invited) New Experimental and Modelling Approaches to Predict Better Corrosion and Protection Properties of Coated Metals

The development of new materials is very time and material intensive. To assess the corrosion properties of coated metallic systems, typically accelerated laboratory corrosion tests are performed. Unfortunately, in the current state of the art there is no proven relationship between laboratory testing data and field performance data. This is particularly due to a lack of data from the field in which the key performance affecting properties are measured, and a lack of understanding of the mechanisms of failure and the absence of a detailed model that allows to predict the coating performance based on laboratory test data. The innovative goal of the project is to develop an integrated corrosion modelling tool that is reliable and predictive. Integrated means that all subsystems (metal, coating, electrolyte) and all phenomena leading to corrosion of the system (transport through the coating, interfacial (electro)chemistry, delamination) are brought together in one model. To achieve our goals, we need to use a combined experimental/finite element modelling (FEM) approach. The modelling is necessary for the quantitative description of all relevant phenomena. The experimental approach is necessary at two levels: on the one hand we need to perform experiments to gain mechanistic insight in the occurring phenomena and to determine input parameters for the modelling, on the other hand we need to do the experimental validation of the proposed model(s). We try to focus on both aspects bringing in new advanced combined electrochemical & in situ surface analysis, advanced finite element electrochemical modelling and more recently quantum chemical modelling. At the end of the presentation the recently started Horizon 2020 project VIPCOAT will be introduced. The goal of the EU-funded VIPCOAT project is to create an open innovation platform that should assist engineers in developing coating materials and constructing accelerated life test scenarios to assess their durability.Acknowledgements: FWOSBO project S000718N,Predictcorr and H2020-NMBP-TO-IND-2020,Vipcoat

Analysis of the pattern of microstructural changes in the brain after mTBI with diffusion tensor imaging and subject-specific FE models

Traumatic brain injury (TBI) is a major public health challenge. Up to 90 % of TBIs are on the mild spectrum of TBI (mTBI), where diagnosis is a major challenge. Majority of studies in this field have been conducted on human subjects, which inherently suffer from the lack of appropriate control group, selection bias, and individual differences in patients. To overcome these limitations, animal studies have been used as an alternative approach to provide deeper insights into the underlying mechanism related to the injury. Therefore our aim is to investigate various quantitative imaging biomarkers acquired from T1-W and diffusion tensor imaging (DTI) sequences to provide more information about the microstructural changes in the brain after mTBI. We then use this to generate subject-specific finite element models of the brain and examine how the changes in the brain material properties reflected in MR images affects strain distribution patterns on a subsequent head hit. Our study revealed a decrease in FA and an increase in diffusivity indices (MD, AD, RD) in the white matter tracts of the brain. This finding may represent the axonal damage, demyelination and gliosis after mild TBI, which have been shown in other animal and human studies. Moreover, our FE analysis showed that microstructural changes in the brain after mTBI might have weakened the structural integrity of the brain as the subsequent head hit led to wider and more severe brain deformations. SignificanceAnimal models have been used to investigate biomechanical and pathophysiological aspects of mild traumatic brain injuries in the past. Still, most of them used small animals such as rats and mice. These models provided valuable insight into the pathophysiology of mTBI, but their findings have limitations due to their inherent differences to human brains. We have developed a large animal model of mTBI with sheep brains by combining advanced MRI and finite element analysis as they mimic the human brain better. To the best of our knowledge, this study is the first mTBI neuroimaging study conducted on large animal brains to investigate the diffusional changes in the white matter tracts after mTBI. Our FE analysis revealed that such microstructural changes resulted in tissue softening as the extent of brain deformation increased on a subsequent head hit, indicating increased brain vulnerability after head impacts.

Stochastic Excitation-Incorporated Seismic Fragility Assessment Using Monte Carlo Simulations

Structures are susceptible to damage from natural disasters like tornadoes, floods, and seismic events. A resilient structure can withstand such damage and ensure cost-effectiveness. Therefore, accurately assessing the probability of structural failure is imperative for structural designers. This study employs an innovative fragility methodology to assess seismic damage in structures. In comparison to conventional fragility approaches, this method is cost-effective, universally applicable across various seismic sources, and highly precise. Specifically, this method involves the generation of artificial seismic records using the point-source stochastic seismological model and Monte Carlo simulation method. These synthetic seismic records offer distinct advantages when compared to the seismic data collected from real earthquakes at recording stations, such as the ability to adjust the epicentral distance of the synthetic waves as needed. Therefore, this approach enables a comprehensive analysis of structural responses under seismic waves characterized by different attributes. For example, the influence of different seismological parameters such as wave magnitude and epicentral distance are well studied and compared. The advanced finite element software, OpenSees, serves as the computational platform for examining how structures react to diverse seismic waves. The research findings suggest that, compared to traditional methods, utilizing OpenSees can significantly enhance computational efficiency. Furthermore, the methods employed introduce a novel technique for factoring in wave magnitudes and distances during the calculation of structural seismological responses/fragility. This innovation holds significance for the development of next-generation structural resilience designs.

Novel corrugated tube–rubber–concrete flexible joint for lining water conveyance tunnels crossing reverse Faults: Numerical analysis of dislocation resistance performance

When water conveyance tunnels cross seismic fault fracture zones, significant deformation may occur, threatening the structural integrity of the tunnel. To resolve this problem, a novel corrugated tube–rubber–concrete flexible joint (CTRCFJ) for improving fault resistance is proposed for the first time. The effectiveness of the CTRCFJ was evaluated using advanced three-dimensional non-linear finite element analysis. The design parameters of the CTRCFJ, including rubber width, corrugated tube interval, and corrugated tube width, were selected based on the distribution of the axial bending moment of the lining structure. An orthogonal test was performed to determine the optimal combination of parameters. The effects of the number of crests, different steel grades, and wall thickness of the corrugated tube on the fracture resistance of the CTRCFJ are investigated. Results show that the CTRCFJ can effectively improve the dislocation resistance performance of composite lining water conveyance tunnels crossing reverse faults by reducing axial compression and bending strain. This study provides a reference for the structural design of composite lining structures that can cross reverse faults.

On the use of mechanics-informed models to structural engineering systems: Application of graph neural networks for structural analysis

This paper investigates the application of mechanics-informed artificial intelligence to civil structural systems. Structural analysis is a traditional practice that involves engineers to solve different real-life problems. Several approaches can be used for this task, going from “by hand” computation to the recent advanced finite element method. However, when structures become complex, the success of the analysis can be complicated, often requiring high computational efforts and time. To tackle this challenge, traditional high-demanding methods can be supported by new technologies, such as machine-learning tools. This new paradigm aims to solve structural problems by defining the desired output after directly elaborating input data. One of the current limitations is that often the physics behind the problem is ignored. To solve this issue, resolution models can combine empirical data and available mechanics prior knowledge to improve the predictive performance involving physical mechanisms. In this paper, a method to develop a Mechanics-Informed Surrogate Model (MISM) on structural systems is proposed, for which input structured data are used to enrich the informative content of mechanics systems. Then, Graph Neural Networks (GNNs) are explored, as a method capable of properly representing and embedding knowledge about a structural system, such as truss structures. The main advantage of the proposed approach is to provide an alternative way to the usual black-box machine-learning-based models. In fact, in the proposed MISM, the mechanics of the structural system plays the key role in the surrogate model definition, in order to obtain physically based outputs for the investigated problem. For the case at hand, MISMs are developed and employed to learn the deformations map of the system, starting from the knowledge of the structural features. The proposed approach is applied to bi-dimensional and tri-dimensional truss structures and the results indicate that the proposed solution performs better than standard surrogate models.

Advanced Finite Element Limit Analysis and Machine Learning for Assessing the Stability of Square Tunnels in Rock Slope

Advanced Finite Element Limit Analysis and Machine Learning for Assessing the Stability of Square Tunnels in Rock Slope

Artificial neural network surrogate modeling for uncertainty quantification and structural optimization of reinforced concrete structures

AbstractOptimization approaches are important to design sustainable structures. In structural mechanics, different design objectives can be defined, for example, to minimize the required construction material or to maximize the structural durability. In this paper, the durability of a reinforced concrete (RC) structure is assessed by advanced finite element (FE) models to simulate the cracking behavior and the chloride transport process. The corrosion initiation time is used as durability measure to be maximized within an optimization approach, where the concrete cover is defined as design variable. The variability of structural loads and material parameters and unavoidable construction imprecision leads to a probabilistic reliability and durability assessment, where aleatory as well as epistemic uncertainties are quantified by random variables, intervals and probability‐boxes. The FE simulation models cannot directly be applied to structural analyses and optimizations with polymorphic uncertain parameters and design variables because of the high computational demand of the multi‐loop algorithm (Monte Carlo simulation, interval analysis, global optimization). In this paper, a new surrogate modeling strategy is presented, where artificial neural networks are trained sequentially to speed‐up the coupled mechanical and transport simulation FE models. The new approach is applied to the uncertainty quantification and the structural durability optimization of a RC structure.

Advanced finite element analyses to compute the J-integral for delaminated composite plates

This study concerns several possible ways of computing the J-integral in the cases of laminated composite plate structures containing delamination. On the one hand, two special types of plate finite element families are provided for advanced fracture mechanical analyses. On the other hand, a numerical algorithm is introduced also that utilizes results derived from solid element models built in commercial finite element software. In order to create plate elements, the first-order (FSDT) and the third-order shear deformation theories (TSDT) are applied with two equivalent single layers. A subparametric element family is created by using the Hermite interpolation with the FSDT that grants the continuity of the derivatives at the element borders. Besides, an isoparametric family is created also with the TSDT employing the Lagrange interpolation scheme. This paper aims to present the compact formulations of calculating the J-integral around the delamination fronts for both plate element families. The calculation of the J-integral is implemented as a matrix multiplication by taking advantage of the properties of plate transition elements. The models yield improved fracture mechanical analyses for delaminated composite plates with linear elastic material behaviour. In addition, computing the J-integral is not available in most commercial finite element software for laminated orthotropic materials, therefore, an appropriate algorithm is presented here for this purpose. To conclude, the models and algorithms are applied to two case studies and subjected to a comprehensive comparison with analytical and formerly used finite element solutions.

Design of a large-scale model for wind tunnel test of a multiadaptive flap concept

The design and application of morphing systems are ongoing issues compelling the aviation industry. The Clean Sky - program represents the most significant aeronautical research ever launched in Europe on advanced technologies for greening next-generation aircraft. The primary purpose of the program is to develop new concepts aimed at decreasing the effects of aviation on the environment, increasing reliability, and promoting eco-friendly mobility. These ambitions are pursued through research on enabling technologies fostering noise and gas emissions reduction, mainly by improving aircraft aerodynamic performances. Within the Clean Sky framework, a multimodal morphing flap device was designed based on tight industrial requirements and tailored for large civil aircraft applications. The flap is deployed in one unique setting, and its cross section is morphed differently in take-off and landing to get the necessary extra lift for the specific flight phase. Moreover, during the cruise, the tip of the flap is deflected for load control and induced drag reduction. Before manufacturing the first flap prototype, a high-speed (Ma = 0.3), large-scale test campaign (geometric scale factor 1:3) was deemed necessary to validate the performance improvements brought by this novel system at the aircraft level. On the other hand, the geometrical scaling of the flap prototype was considered impracticable due to the unscalability of the embedded mechanisms and actuators for shape transition. Therefore, a new architecture was conceived for the flap model to comply with the scaled dimensions requirements, withstand the relevant loads expected during the wind tunnel tests and emulate the shape transition capabilities of the true-scale flap. Simplified strategies were developed to effectively morph the model during wind tunnel tests while ensuring the robustness of each morphed configuration and maintaining adequate stiffness levels to prevent undesirable deviations from the intended aerodynamic shapes. Additionally, a simplified design was conceived for the flap-wing interface, allowing for quick adjustments of the flap setting and enabling load transmission paths like those arising between the full-scale flap and the wing. The design process followed for the definition of this challenging wind tunnel model has been addressed in this work, covering the definition of the conceptual layout, the numerical evaluation of the most severe loads expected during the test, and the verification of the structural layout by means of advanced finite element analyses.

Ground stability of ellipsoidal cavity due to pipeline defects

The problem of road-related sinkhole stability has long been one of the main safety concerns to pavement engineers. Collapse and blowout failures are two typical types of pipeline-related sinkhole failures. Although much research on sinkhole stability analyses can be found in the literature, most of them assume a simple circular or rectangular shape of a cavity. In this study, the problem of sinkhole stability in an ellipsoidal cavity is investigated under both blowout and collapse conditions using advanced finite element limit analysis with adaptive meshing in an axisymmetric condition. A dimensionless pressure ratio is defined to represent sinkhole stability that is a function of many design parameters such as depth ratio, elliptical shape ratio, and soil strength ratio. Selected results are compared with published solutions, and comprehensive solutions of the parametric study are presented in the form of charts for use by design engineers. The present study contributes to the understanding of sinkhole stability under an ellipsoidal cavity, and it should be of interest to the road engineering community.

Advanced finite element modelling of stainless steel bolted T-stubs under large deformations

Following upon the recently published experimental and numerical studies on stainless steel bolted T-stubs in tension, this study reports the development and validation of an advanced FE model that reveals the effect of initial contact between the bolts and bolt holes and constructional imperfections on the response of stainless steel bolted T-stubs subjected to large deformations. Key simulation strategies regarding the modelling of bolts, initial position of the bolts, flange bowing effect due to the initial constructional imperfections and overcoming numerical instabilities are discussed. The developed FE model first validated against the available test data in the literature. The effect of pre-established contact between the bolts and bolt holes and constructional imperfections on the overall response of the bolted T-stubs are reported comprehensively by comparing the plastic and ultimate resistances with the experimental ones. Moreover, the membrane action developing in the flange influences the ductility reserve of the T-stub which has a vital role in case of progressive collapse and robustness scenarios. Therefore, by inspecting the stress distribution through the flange thickness at various locations along the T-stubs, effects of different modelling configurations on the flexural and the membrane component of the load transfer mechanism are revealed. A parametric study is performed to investigate the influence of all these aspects on resistance of T-stub connections. On the basis of the obtained results and the discussions, modelling recommendations for the simulation of stainless steel T-stubs are made.

Enhancing medium voltage underground circuit design: Assessing limitations, thermal influence, and accurate modelling

The research article conducted a study aimed at elucidating the limitations present in existing international standards related to the permissible quantity of medium voltage circuits that can be placed within a single trench. The study also explored important considerations for underground circuits in the context of renewable energy projects, particularly focusing on the crucial roles of capacity and load requirements in cable design. The research employed advanced finite element methods with Composition, Environmental, Structure, and Mechanism (CESM) and mathematical modeling to enhance existing procedures defined by international standards like IEC 60287, 60502, and 60228. The primary parameter of interest was the thermal influence of subterranean XLPE (cross-linked polyethylene) current capacity, considering various factors such as circuit quantities, distances, and depths. Notably, the study made several key findings, including a notable reduction in the current capacity of the underground circuits. This reduction in current capacity was found to vary, ranging from 100 % to 25.75 %. The reduction was attributed to factors such as native soil conditions, circuit separation. The findings furnish valuable insights into the challenges pertinent to medium voltage underground circuit design. Moreover, the paper establishes the accuracy of the proposed process, achieving a precision of 99.4850 ± 0.5150 % for 240 mm2 and 99.3698 ± 0.6301 % for 630 mm2.

Embedding strain-rate sensitivities of multiple deformation mechanisms to predict the behavior of a precipitate-hardened WE43 alloy under a wide range of strain rates

A rare earth Mg alloy, WE43, exhibits high strength, good ductility, low anisotropy, and moderately high strain rate sensitivity. As such, the alloy is a viable candidate for high strain rate applications. In this work, a comprehensive set of mechanical and microstructure data recorded during quasi-static, high strain rate split Hopkinson bar (SHB), and impact tests on specimens of WE43 Mg alloy reported in (Savage et al., 2020b) is simulated and interpreted using an advanced Taylor-type crystal plasticity finite element (T-CPFE) model. The T-CPFE model is formulated physically to embed two sources of strain-rate sensitivities inherent to each slip and twinning mode in WE43, one that occurs under constant structure and another that affects structure evolution. The model parameters are established for the alloy by achieving agreement in the stress-strain response and microstructure evolution under quasi-static and SHB tests. Density functional theory calculations of anti-phase boundary (APB) energy are carried out to explain origins of the unusually large initial slip resistance for basal dislocations, which shear precipitates in the alloy. The initial slip resistances of the prismatic and pyramidal dislocations are, instead, rationalized by Orowan looping around precipitates. After calibration and validation, the model is shown to successfully predict WE43 response at much larger strain rates than those used for model calibration. Specifically, mechanical response, specimen geometry changes, twin volume fractions, and texture evolution are predicted for different orientations of the Taylor cylinders. Details of the modeling framework, comparison between simulation and experimental results, and insights from the results are presented and discussed.

Reconsideration of shear strength expressions for CFSTs: Rectangular tubes

Concrete filled steel tubes (CFSTs) are typically circular or rectangular. Circular CFSTs are mostly used as vertical components of deep foundation systems; rectangular sections are more commonly used in building construction such as square CFSTs for columns. Prior work has focused on circular CFSTs with far fewer studies on square or rectangular sections. In addition to being more limited, prior research on square CFST sections has focused on flexural and axial response; there have been far fewerstudies on the shear response. As such, the accuracy of shear-strength equations is uncertain. A research study was undertaken to understand and improve design expressions for the shear design of rectangular CFSTs. First, the research team collectedexperimental data on shear resistance of rectangularCFSTs. Selected experimental data was used to develop and validate an advanced nonlinear finite element model (FEM) to predict the measured response and observed damage of rectangular CFSTs controlled by shear behavior. The validated model was then used to conduct parameter studies to investigate important design parameters of rectangular CFSTs responding primarily in shear including: 1) concrete and steel material properties, 2) cross-sectional aspect ratio, and 3) impact of enhanced bond capacity/composite action through the introduction of a single shear key at each end of the member. The results were used to better understand the importance of each parameter on the shear response and strength. A database was assembled, combining the experimental data with the strength predicted by each FEM, to evaluate existing design equations. The shortcomings of the existing equations included (1) only accounting for the steel or the concrete fill contribution, and (2) overestimating the total shear strength because the behavior of the CFST in shear is not well understood. This paper provides a new approach to assessing the shear strength as the individual contributions of the steel tube and the concrete fill are computed for each model to better understand their interaction. This also permits the development of a new design equation to remedy the shortcomings of existing codified models. In particular, the proposed model accurately estimates the individual contributions of steel tube and concrete fill to the shear resistance for salient design parameters.

Deep predictions and transfer learning for simulation-driven structural health monitoring based on guided waves

Simulation-driven structural health monitoring (SHM) is crucial for enhancing the safety and reliability of structures. Its primary aim is to utilize numerical simulations to design efficient SHM systems, reducing costs while maintaining effectiveness. However, challenges arise due to disparities between simulations and physical measurements, stemming from uncertainties, noise, and simplifications. These challenges also extend to SHM methods using machine learning, particularly deep neural networks (DNNs).This paper bridges the gap between DNNs trained on simulated data and real-world experiments by investigating three transfer learning (TL) techniques: feature augmentation, direct fine-tuning, and boosting-based fine-tuning. The focus is on guided wave damage interaction coefficients (WDICs) as damage-sensitive features, modeled by DNNs for damage identification in thin plates, commonly found in aerospace structures like aircraft fuselages. This classification task compares measured and predicted WDICs in a common guided wave SHM configuration with one actuator and three sensors. Training and extensive testing datasets are generated using advanced finite element simulations and laser Doppler vibrometer experiments.The study demonstrates that TL techniques significantly enhance DNN prediction accuracy and improve damage identification performance for untrained scenarios compared to purely simulation-based DNNs. Among the TL approaches explored, feature augmentation with appropriate activation functions and boosting-based fine-tuning yield the most promising results. Using four out of twelve TL datasets, feature augmentation reduces the simulation-based mean absolute percentage error from 46.80% to 35.98% and increases coefficient of determination R2 values from 0.02 to 0.72. With six TL datasets and a boosting-based fine tuning, the mean absolute percentage error decreases from 47.42% to 35.20%, maintaining similar R2 values. While TL substantially enhances prediction accuracy, its impact on damage identification is slightly less pronounced, with improvements in relative classification accuracy by approximately 5% compared to simulation-based DNNs.These findings highlight the efficacy of TL techniques for damage identification in thin plates using WDICs and DNNs, emphasizing the influence of TL training and DNN model variations. Furthermore, they showcase the potential of TL methods to enhance DNN performance in future SHM applications, particularly emphasizing the promise of feature augmentation and boosting.

Numerical analysis of curved steel plate girders subjected to patch loading

Curved steel plate girders are often utilized in bridges built in congested urban areas, where intricate plan alignments are required. Their performance and design is, however, more complex than that of equivalent straight girders, especially regarding concentrated forces: while AASHTO adopts a simplified and empirical approach for the design of curved steel girders, the Eurocode for plated structures EN 1993-1-5 does not address the patch loading design of steel plate girders curved in plan, being only applicable to straight girders. Therefore, it is necessary to carry out further research in order to achieve a better understanding of the behavior of curved steel plate girders so that suitable design approaches accounting for the specific response of these structures can be developed. This paper presents a comprehensive numerical study on curved steel plate I-girders subjected to patch loading, considering material and geometric nonlinearities as well as initial imperfections. The numerical models are developed by means of the advanced finite element software ABAQUS and validated against experimental tests available in the literature. The numerical results demonstrate that the elastic critical buckling loads increase with increasing span-to-plan radii, which can be conservatively estimated using the EN 1993-1-5 provisions for straight steel girders, and that the ultimate patch loading resistance decreases with the radius of curvature. Based on this, practical recommendations are proposed to extend the applicability of the design provisions prescribed in the next version of EN 1993-1-5 for straight steel I-girders to the case of curved steel I-girders.