Although emerging cementitious and fiber-reinforced composite materials offer enhanced strength and durability, their nonlinear, rate-dependent, and heterogeneous behavior is not consistently transferred into analysis-ready representations in conventional building information modeling–finite-element analysis (BIM-FEA) workflows. This study introduces a material-informed framework that integrates BIM geometry with a Python-assisted (version 3.11) automated building information modeling-finite-element analysis integration engine (ABFIE) coupled to nonlinear ANSYS (version 2025 R1) simulation, enabling direct incorporation of experimentally calibrated constitutive data into finite-element models. Within the validation cases considered here, ABFIE reproduces stiffness degradation, neutral-axis migration, and crack-initiation loads with prediction errors of 5%–9% relative to reported experimental benchmarks while reducing model-preparation time by more than 60% for the benchmark workflow and showing reduced operator-to-operator variation under the tested preprocessing settings. Supplementary ANSYS checks indicate stable mesh behavior across the 50–25-mm benchmark range, with peak-load variation below 3% once the critical-region element size reaches approximately 20–25 mm. These results suggest that a material-aware BIM-FEA workflow can improve predictive consistency and modeling efficiency for performance-based assessment of advanced construction materials within the tested validation scope.
This research examines the reliability of BIM-to-FEM transfer procedures using Autodesk Revit and CSI ETABS by systematically evaluating native API-mediated and IFC-based approaches to show that BIM-to-FEM interoperability is still a somewhat automated process that needs rigorous verification.
Banothu Sairam, Nayak, M. Devi et al.· 0 citations
This research examines the reliability of BIM-to-FEM transfer procedures using Autodesk Revit and CSI ETABS by systematically evaluating native API-mediated and IFC-based approaches and offers an integration process based on checkpoints that uses controlled modeling methods, validates models after transfer, and coordinates federated models.
Banothu Sairam Nayak, A. V. Anjani Devi, B. S. Chandra· International Journal of AI...· 0 citations
Homogeneous TC4 titanium alloy suffers from the strength–ductility trade-off and exhibits insufficient anti-penetration capacity under high-strain-rate impact. TiCp-reinforced functionally graded titanium matrix composites (FGTMCs) with a “hard outer, tough inner” gradient architecture are promising lightweight armor materials. The use of Abaqus/Explicit finite element simulation for FGTMCs under dynamic impact can capture transient deformation and damage evolution while enabling rapid evaluation of the impact resistance of different materials; however, research in this area remains scarce. This study conducts a systematic parametric analysis of key simulation parameters, including calibration of the Johnson–Cook constitutive and damage model parameters for TC4 titanium alloy, optimization of mesh partitioning strategies, hourglass control schemes, model dimensions, and boundary conditions to suppress “ghost mesh” numerical artifacts. Material property assignments for TC4 and three typical titanium matrix composites are designed, along with a methodology for constructing functionally graded material models. Two projectile–target matching configurations (small projectile/thin target vs. large projectile/thick target) are compared, and the optimal model of a 700 m/s small-caliber tungsten projectile impacting a 50 mm TC4 target is identified. Parametric analysis demonstrates that a damage parameter D4 = 0.1 significantly improves numerical stability, and a graded mesh strategy with further refinement along the penetration path balances computational accuracy and efficiency. Using the optimized material system, the simulation results reproduce the three-stage damage evolution of titanium alloys under impact—cratering, plastic penetration, and back-face spallation—providing reliable numerical support for the structural optimization of graded armor materials.
The calibration of structural models using field data is essential for improving the reliability of bridge assessment and the consistency of numerical simulations. This study presents an inspection-informed model updating approach for a real-world steel pedestrian bridge by integrating experimental modal data, BIM-based damage information, and finite element analysis results. The post-calibration consistency assessment is carried out using natural frequency comparison and the Modal Assurance Criterion (MAC). The proposed framework introduces a semi-automated workflow in which inspection-based damage grades stored in a BIM model are transferred to the finite element model via element identifiers. Damage is represented through inspection-based stiffness modifiers, while a global calibration parameter accounts for modelling uncertainties. This formulation enables a structured combination of inspection-based local stiffness modifiers and global model correction, improving the interpretability of the updated parameters. Field measurements were obtained using accelerometers under ambient excitation, and operational modal analysis was applied to identify natural frequencies and mode shapes. These results were compared with a finite element model, in which damage information from a Revit-based inspection dataset was semi-automatically mapped and incorporated into the numerical model. A constrained optimisation process was used to calibrate the damage coefficients and global stiffness factor by minimising the difference between numerical and experimental natural frequencies. The results show a reduction in frequency discrepancies and an improvement in modal correlation after calibration. The results show that the proposed approach enables a transparent and repeatable integration of inspection data into finite element model updating, particularly at the global level. Although the level of improvement remains moderate, the calibration process is constrained by inspection data and modelling assumptions, supporting a consistent interpretation of the calibrated parameters. The framework, therefore, prioritises consistency and transparency over purely numerical fitting, supporting more reliable structural assessment.
M. Oyarhossein, Fernanda Rodrigues, H. Rodrigues· Scientific Reports· 0 citations
The numerical modelling of existing reinforced concrete (RC) bridges represents one of the most time-consuming and operator-dependent phases of seismic vulnerability assessment. Although advanced nonlinear analysis procedures are widely available, the generation of finite element (FE) models is still commonly performed through manual operations, limiting modelling efficiency, repeatability, and interoperability between design and analysis environments. This paper presents a layer-based CAD-to-FEM workflow for the structured generation of simplified FE models of existing RC bridges. The proposed methodology uses a standardized layer-based CAD organization and direct DXF interoperability with MIDAS Civil to transfer a centroidal representation of the bridge into a simplified beam-based finite element model. The centroidal axes of the bridge components are extracted from the original engineering drawings and classified into dedicated structural layers, providing a structured basis for subsequent FE model generation. The proposed workflow is designed to reduce manual preprocessing operations and improve modelling consistency by organizing the structural geometry through standardized CAD layers, thereby facilitating the generation of analysis-ready models for seismic assessment. The workflow is integrated with a Multi-Modal Pushover Analysis (MPA) procedure to evaluate the seismic vulnerability of bridges characterized by multiple significant vibration modes. A case study involving an existing Italian RC bridge demonstrates the feasibility of using the proposed simplified modelling strategy within a multi-modal nonlinear seismic assessment, including the evaluation of both ductile and brittle collapse mechanisms through seismic risk indices. The proposed workflow provides a structured framework for integrating conventional engineering drawings with nonlinear seismic assessment procedures.
Additive manufacturing (AM) enables innovative product development through its material versatility and design freedom, further enhanced by advanced materials such as composites. A common example is the fabrication of polymer matrix composites (PMCs) via extrusion‐based AM. However, identifying optimal material–process combinations often requires costly and time‐consuming experiments. To address this challenge, this study proposes an analytical model for predicting the tensile mechanical properties of extrusion‐based additively manufactured PMCs. The model integrates classical laminate theory with volumetric considerations specific to material extrusion (ME) and accounts for key parameters, including fiber and matrix properties, layer thickness, nozzle diameter, and raster angle. The model is validated through tensile tests on ONYX specimens and comparison with literature data. Its predictive capability is also evaluated against previous approaches, including the rule of mixtures and the Halpin–Tsai model. Results show that the proposed model provides closer agreement with experimental findings across diverse cases, demonstrating its reliability and efficiency while reducing experimental effort. Finally, parametric studies are conducted using the validated model, and the effects of layer thickness, nozzle diameter, and fiber diameter on elastic modulus and stress are systematically analyzed.
Ozgur Poyraz, Abas Abasov· Polymer Composites· 0 citations
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