Explore the vast range of titles available.

Digital twin models utilising point cloud data have received significant attention for efficient bridge maintenance and performance assessment. There are some studies that show finite element (FE) models from point cloud data. While most of those approaches focus on modelling by solid elements, modelling of some civil structures, such as bridges, requires various uses of beam and shell elements. This study proposes a systematic approach for constructing shell element FE models from point cloud data of thin-walled structural members. The proposed methodology involves k-means clustering for point cloud segmentation into individual plates, principal component analysis for neutral plane estimation, and edge detection based on normal vector variations for geometric structure determination. Validation experiments using point cloud data of a steel corner specimen revealed dimensional errors up to 5 mm and angular errors up to 6°, but static load analysis demonstrated good accuracy with maximum displacement errors within 3.8% and maximum stress errors within 7.7% compared to nominal models. Additionally, the influence of point cloud data quality on FE model geometry and analysis results was evaluated based on geometric accuracy and point cloud density metrics, revealing that significant variations in density within the same surface lead to reduced neutral plane estimation accuracy. Furthermore, toward practical application to actual bridge structures, on-site measurements and quality evaluation of point cloud data from a steel plate girder bridge were conducted. The results showed that thickness errors in the bridge data reached up to 2 mm, while surface deviation RMSE ranged from 3 to 5 mm. This research contributes to establishing practical FE modelling procedures from point cloud data and providing a model validation framework that ensures appropriate abstraction in structural analysis.

Dynamic analysis of structures is a key challenge in structural engineering, especially in choosing effective and accurate numerical methods. Steel–concrete composite structures, commonly used in bridges and floors, require calculations of dynamic parameters to ensure safety and comfort. Few studies compare the effectiveness of the finite element method (FEM) and the rigid finite element method (RFEM) in the dynamic analysis of such structures. This study fills this gap by comparing the methods using experimental results. FEM and RFEM models were developed using Abaqus, Python, and Matlab. The main parameters were identified, i.e., the Young’s modulus of the concrete slab (EC) and the stiffness of the connection (Kx, KRX, Kv, Kh). Both methods closely matched the experimental results. The RFEM matched natural frequencies with 2–3% deviations, while the FEM showed 3–4% deviations for the torsional, axial, and first three flexural frequencies. The RFEM reduced the computation time by about 65%, making it suitable for large-scale applications. The FEM provided a finer resolution of local effects due to its higher element density. The results can be applied to the design of bridges, floors, and other structures under dynamic loads. It will also provide the authors with a basis for developing structural health monitoring (SHM).

Grayscale digital light processing (DLP) printing is a simple yet effective way to realize the variation of material properties by tuning the grayscale value. However, there is a lack of available design methods for grayscale DLP 3D‐printed structures due to the complexities arising from the voxel‐level grayscale distribution, nonlinear material properties, and intricate structures. Inspired by the dexterous motions of natural organisms, a design and fabrication framework for grayscale DLP‐printed soft robots is developed by combining a grayscale‐dependent hyperelastic constitutive model and a voxel‐based finite‐element model. The constitutive model establishes the relationship between the projected grayscale value and the nonlinear mechanical properties, while the voxel‐based finite‐element model enables fast and efficient calculation of the mechanical performances with arbitrarily distributed material properties. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion (DoC) variation in a single voxel. The design framework is used to design structures with reduced stress concentration and programmable multimodal motions. This work paves the way for integrated design and fabrication of functional structures using grayscale DLP 3D printing. A design and fabrication framework for grayscale DLP printing is developed by combining a grayscale‐dependent hyperelastic constitutive model and a voxel‐based finite‐element model. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion variation of a single voxel. The framework is used in reducing stress concentration and multimodal soft robots.

To develop a high-fidelity three-dimensional finite element model of the whole spine-thorax complex based on high-resolution computed tomography (CT) images of a healthy adult male, and to perform initial validation under representative loading conditions for quantitative analysis of load transmission, coupled motion, and stress distribution. We hypothesized that the model would reproduce published quasi-static segmental moment-rotation behavior and cadaveric thoracic impact responses within acceptable error ranges. High-resolution CT data of one healthy adult Chinese male volunteer (25 years; 175 cm; 70 kg) were used to reconstruct detailed anatomical structures, including vertebrae, intervertebral discs, ribs, costal cartilage, sternum, ligaments, respiratory muscles, lungs, and heart. Material properties were assigned based on literature data, and nonlinear contacts were defined among articular and cartilaginous structures. Model validation was carried out using two scenarios: pure-moment loading of the T12-L1 functional spinal unit and a frontal chest impact simulation, with the numerical responses compared against available experimental and cadaveric data. The T12-L1 moment-rotation curves agreed well with published biomechanical ranges, and the frontal impact simulation produced a peak force (3,270 N) and chest compression (79 mm) closely matching experimental results (3,453 N and 80 mm), with errors of 5.3% and 1.25%, respectively. The finite element model reproduced static and dynamic responses of the spine-thorax complex within available experimental ranges for the loading conditions examined, providing an initial, non-invasive platform for investigating load transmission, coupled motion, and stress distribution under physiological, pathological, and interventional conditions.

Metastatic disease in bone is characterized by highly amorphous and variable lesion geometry, with increased fracture risk. Assumptions of idealized lesion geometry made in previous finite element (FE) studies of metastatic disease in the proximal femur may not sufficiently capture effects of local stress/strain concentrations on predicted failure strength. The goal of this study was to develop and validate a FE failure model of the proximal femur incorporating artificial defects representative of physiologic metastatic disease. Data from 11 cadaveric femur specimens were randomly divided into either a training set (n = 5) or a test set (n = 6). Clinically representative artificial defects were created, and the femurs were loaded to failure under offset torsion. Voxel-based FE models replicating the experimental setup were created from the training set pre-fracture computed tomography data. Failure loads from the linear model with maximum principal strain failure criterion correlated best with the experimental data (R2 = 0.86, p = 0.024). The developed model was found to be reliable when applied to the test dataset with a relatively low RMSE of 46.9 N, mean absolute percent error of 12.7 ± 17.1%, and cross-validation R2 = 0.88 (p < 0.001). Models simulating realistic lesion geometry explained an additional 26% of the variance in experimental failure load compared to idealized lesion models (R2 = 0.62, p = 0.062). Our validated automated FE model representative of physiologic metastatic disease may improve clinical fracture risk prediction and facilitate research studies of fracture risk during functional activities and with treatment interventions.

In order to efficiently investigate the effect of the mesoscale heterogeneity of a concrete core and the randomness of circular coarse aggregate distribution on the stress wave propagation procedure and the response of PZT sensors in traditional coupling mesoscale finite element models (CMFEMs), firstly, a mesoscale homogenization approach is introduced to establish coupling homogenization finite element models (CHFEMs) with circular coarse aggregates. CHFEMs of rectangular concrete-filled steel tube (RCFST) members include a surface-mounted piezoelectric lead zirconate titanate (PZT) actuator, PZT sensors at different measurement distances, a concrete core with mesoscale homogeneity. Secondly, the computation efficiency and accuracy of the proposed CHFEMs and the size effect of representative area elements (RAEs) on the stress wave field simulation results are investigated. The stress wave field simulation results indicate that the size of an RAE limitedly affects the stress wave fields. Thirdly, the responses of PZT sensors at different measurement distances of the CHFEMs under both sinusoidal and modulated signals are studied and compared with those of the corresponding CMFEMs. Finally, the effect of the mesoscale heterogeneity of a concrete core and the randomness of circular coarse aggregate distribution on the responses of PZT sensors in the time domain of the CHFEMs with and without debond defects is further investigated. The results show that the mesoscale heterogeneity of a concrete core and randomness of circular coarse aggregate distribution only have a certain influence on the response of PZT sensors that are close to the PZT actuator. Instead, the interface debond defects dominantly affect the response of each PZT sensor regardless of the measurement distance. This finding supports the feasibility of stress wave-based debond detection for RCFSTs where the concrete core is a heterogeneous material.

We present a new regularized inverse formulation, built upon the paradigm of force‐based Finite Element Model Updating (FEMU‐F), for identifying constitutive parameters from full‐field displacements and integrated external forces. In force‐based methods such as FEMU‐F and Equilibrium Gap Method (EGM), the minimized loss function is defined in terms of FE force residuals after imposing measured displacements as Dirichlet constraints. Such force‐based loss functions are known to be sensitive to noisy displacements. To overcome this limitation, we propose a new robust force‐based loss function that operates directly on elemental internal forces without assembling them into nodal values. The key innovation is the introduction of admissible elemental internal forces (AEIFs) as additional unknown variables into the proposed inverse formulation with inherent regularization effects. By definition, AEIFs satisfy static equilibrium with external forces, independent of kinematics and constitutive relations. The proposed loss function measures the discrepancy between AEIFs and the elemental internal forces computed from the FE model. The static equilibrium of AEIFs imposes purely force‐based admissibility conditions, which build a systematic reduction procedure delivering a compact, independent representation of the AEIFs space. This enables an analytical solution for unknown AEIFs when minimizing the proposed loss function, while the constitutive parameters are identified numerically. Numerical examples show that the regularized formulation reduces sensitivity to noisy full‐field displacements and inaccurate Dirichlet boundary conditions and mitigates FEMU‐F's bias toward local information near measured forces. Owing to its force‐only formulation, the method is simpler to implement than stress‐based approaches such as Constitutive Equation Gap (CEG). It identifies heterogeneous elasticity more accurately than FEMU‐F using a single measured integrated force. The method is also shown to remain robust in identifying parameters of a nonlinear, path‐dependent constitutive law with strain localization, highlighting its suitability for such challenging materials where measured full‐field displacements are directly imposed as Dirichlet constraints. The “E‐FEMU‐F loss” as a function of full‐field displacements, constitutive parameters, and “Admissible Elemental Internal Forces” (AEIFs). AEIFs are constructed from measured (integrated) external forces and optimized analytically, while constitutive parameters are inferred numerically to minimize the E‐FEMU‐F loss.

BackgroundEnvironmental-assisted fatigue (EAF) is a major issue for the long-term survival of nuclear power plant fleets in the U.S. and worldwide. Multi-material welded regions (e.g., nozzles) and other high-stress regions of reactor coolant system (RCS) components are prone to EAF-related damage.ObjectiveThe discussed work describes a system-level finite element (FE) model of RCS components of a pressurized water reactor (PWR). This is with the goal of predicting the stress hotspots, strain residuals, strain amplitudes and the resulting fatigue lives.MethodsThe FE model was developed considering system-level loading conditions (under connected system thermal–mechanical boundary conditions). Thermal–mechanical stress analysis was performed considering thermal stratification and a design-basis reactor loading cycle. Based on the FE model results, the strain residuals, strain amplitudes and resulting fatigue lives of RCS components were predicted.ResultsThe results show that some of the RCS components can have significantly different strain amplitudes, residual strain, and fatigue lives, despite having similar geometry and material. Higher residual strain can lead to accelerated cyclic hardening of material and the associated effect of EAF. The simulated component-level strain profile (under realistic multi-axial-multi-physics loading cycle) can guide the selection of appropriate test inputs for conducting laboratory-scale EAF tests, which is a focus of future works.ConclusionsDespite similar geometry and material the RCS component can have significantly different strain profiles and resulting fatigue lives. The discussed approach can help to identify and prioritize the RCS components for conducting expensive nondestructive evaluation (NDE) inspections.

This paper describes the development of a random finite element model (RFEM) that allows holistic simulation of frozen soil behaviors, including the effects of phase transition and the consequent internal stress and volume changes. The performance of the model is firstly validated with laboratory experiments. The model is implemented to simulate the effects of frost action on pavement. The coupled thermal-mechanical actions including the mechanical responses of subgrade soils subjected to freezing temperature and its effects on the pavement structure are analyzed. The results show that the frost action and expansion of ice lenses change the interaction modes between pavement layers. This leads to increase of stress and deformation in the pavement layer. Methods to mitigate the effects of frost heave are analyzed with this model. The simulation results indicate that the detrimental effects of frost heave on the pavement structure can be mitigated by increasing the thickness of base layer, use of thermal insulation layer or improve drainage in the subgrade layer. The RFEM combines the advantages of discrete element model (DEM) in holistically describing the microstructure effects and in the finite element model (FEM) in terms of computational efficiency. This allows to focus research on understanding the behaviors of individual soils phase and their interfacial interactions.