Complex Bridge Research Articles

Mechanical Analysis and Optimization of Concrete Structures Based on Advanced Finite Element Method

This article explores the mechanical analysis and optimization problems of concrete structures based on the Advanced Finite Element Method. By integrating advanced numerical techniques with practical engineering cases, this study aims to improve the safety and economy of concrete structure design. Firstly, the paper outlines the limitations of traditional finite element methods in concrete structure analysis, such as insufficient computational accuracy and low computational efficiency. Subsequently, by introducing AFEM, we significantly improved the accuracy and efficiency of the analysis. For example, when simulating a complex bridge structure, AFEM not only reduces the calculation time by about 25%, but also improves the accuracy of stress distribution prediction by more than 10%. In the optimization stage, we utilized the analysis results of AFEM and optimized the material consumption, cross-sectional dimensions, and reinforcement parameters of concrete structures through multi-objective optimization algorithms. A comprehensive data analysis underscores that the optimized concrete structure triumphantly meets all safety performance criteria while achieving a remarkable 12% reduction in material usage. This substantial material savings translates into a substantial 8% decrease in overall construction costs, significantly bolstering the project’s economic feasibility. Moreover, these cost savings not only amplify the project’s profitability but also play a pivotal role in enhancing the structure’s longevity and durability, thereby contributing to its sustainable performance over its entire service life. Furthermore, we delved into the capability of AFEM in simulating intricate phenomena such as the nonlinear behavior of concrete materials, crack propagation patterns, and the intricate interactions between steel reinforcements and concrete. These complex mechanical behaviors are crucial for the safety and stability of structures, and AFEM provides more comprehensive and accurate references for structural design by accurately simulating these behaviors. This article conducts in-depth research on the mechanical analysis and optimization of concrete structures based on AFEM, and demonstrates the significant advantages of AFEM in improving structural safety and economy through specific data. These research results not only provide new theoretical support and practical tools for concrete structure design, but also provide valuable references for future research and application in related fields.

Dinuclear Dysprosium Compounds: The Importance of Rigid Bridges.

We report the synthesis, structures and magnetic behaviour of two isostructural dinuclear Dy3+ complexes where the metal ions of a previously reported monomeric building block are connected by a peroxide (O22-) or a pair of fluoride (2 x F-) bridges. The nature of the bridge determines the distance between the metal ion dipoles leading to a dipolar coupling in the peroxido bridged compound of only ca. 70% of that in the bis-fluorido bridged dimer. The sign of the overall coupling between the metals is antiferromagnetic for the peroxido bridged compound and ferromagnetic for the bis-fluorido bridged complex. This in turn influences the magnetisation dynamics. We compare the relaxation characteristics of the dimers with those of the previously reported monomeric building block. The relaxation dynamics for the bis-fluorido system are very fast. On the other hand, comparing the properties of the monomer, the peroxido bridged sample and the corresponding Y-doped sample show that the relaxation properties via a Raman process have very similar parameters. We show that a second dysprosium is important for either tuning or detuning the Single Molecule Magnet (SMM) properties of a system.

Reliability optimization of reliability-redundancy allocation problems based on K-mixed strategy

In a reliability-redundancy allocation problem (RRAP), system reliability is maximized by selecting component reliabilities and finding the most suitable redundancy of subsystems. The advantages of a K-mixed strategy were introduced by modeling, so as to better improve system reliability. Compared with other existing redundancy strategies, the performance of a K-mixed strategy was verified using redundancy allocation problems (RAP). In this study, for the first time, a reliability calculation model under the new structure ( [Formula: see text] = 2 and [Formula: see text] = 1) is proposed, and the K-mixed strategy under the new structure is used in the reliability-RAP (RRAP), which is more complex than the RAP and further saves the production cost. In practical optimization, there was a complex decision-making problem to ensure optimal system reliability while minimizing system volume, weight, and cost. Then, this K-mixed strategy was adopted for modeling three benchmark problems in RRAP to seek a better and more flexible system structure. A powerful evolutionary algorithm (NSGA-II) was used to solve the new RRAP model to obtain the best system structure and reliability. The advantages of this model were confirmed by comparison with results from previous reliability optimization studies. The results show that the cost-saving advantages of the new structure in ensuring maximum reliability are significant. All the optimized remaining costs are noticeably higher than those of other methods, with the cost savings of the series-parallel system being the greatest. The difference in remaining costs compared to previous optimizations remains in the tens. Moreover, in more complex systems (Complex bridge system), the advantage in remaining volume is very significant, with the improvement being three times that of the optimization results of other methods.

A conserved fertilization complex bridges sperm and egg in vertebrates.

Fertilization, the basis for sexual reproduction, culminates in the binding and fusion of sperm and egg. Although several proteins are known to be crucial for this process in vertebrates, the molecular mechanisms remain poorly understood. Using an AlphaFold-Multimer screen, we identified the protein Tmem81 as part of a conserved trimeric sperm complex with the essential fertilization factors Izumo1 and Spaca6. We demonstrate that Tmem81 is essential for male fertility in zebrafish and mice. In line with trimer formation, we show that Izumo1, Spaca6, and Tmem81 interact in zebrafish sperm and that the human orthologs interact invitro. Notably, complex formation creates the binding site for the egg fertilization factor Bouncer in zebrafish. Together, our work presents a comprehensive model for fertilization across vertebrates, where a conserved sperm complex binds to divergent egg proteins-Bouncer in fish and JUNO in mammals-to mediate sperm-egg interaction.

Network-level optimisation approach for bridge interventions scheduling

This paper introduces a novel extension of the multi-system optimisation method, known as the 3C concept, tailored for optimising budget allocation for bridge interventions at the network level. This extended methodology accounts for the interdependencies among bridges due to their spatial proximity within the network. It incorporates direct and user costs, bridge performance indicators, and a bridge deterioration model. A real-world case study involving a portfolio of 555 bridges demonstrates the practicality of the methodology, efficiently determining the optimal intervention sequence. Over an 18-year analysis period, the proposed methodology achieved a 23% reduction in total costs by combining repairs for bridges with high to severe damage and maintenance for the others. This represents a significant improvement compared to the traditional approach, used by bridge management agencies, which relies exclusively on maintenance. The optimised procedure outperforms human intuition in managing complex bridge networks, particularly over extended periods. This methodology can assist transportation agencies in implementing and exploring various scenarios by adjusting the time between consecutive interventions and budget constraints, supporting comprehensive analysis and informed decision-making.

Biomimetic structure-driven high strength and toughness in continuous SiC skeleton-reinforced graphite composites

Graphite-matrix structural composites with excellent mechanical properties and long-term reliability are ungently required in aerospace and nuclear industries. However, the enhancement of graphite-matrix composites by mainstream surface coating techniques or second-phase particle reinforcement is rather limited. Inspired by the structural-functional feature of plant cells, silicon carbide (SiC, cytoderm) coated mesocarbon microbeads (MCMB, cytoplasm) powders were prepared by combustion synthesis (CS), which were then densified via spark plasma sintering (SPS) to obtain the biomimetic cellular-structured SiC-reinforced MCMB (M@SiC) composites. The in-situ formed SiC ‘cytoderm’ ensures good interfacial bonding and contributed to the densification of the composites. Additionally, the continuous SiC skeleton and cellular-structured configuration improved the mechanical properties of M@SiC composites. Owing to the complex crack deflection, branching and bridging effects at the MCMB/SiC interfaces and graphite nanoflakes inside MCMB, the biomimetic M@SiC composite with SiC content of 47 vol% exhibited strengthening and toughening, with flexural strength and fracture toughness of 245 MPa and 3.82 MPa m1/2, respectively. The developed biomimetic graphite-matrix composites with excellent mechanical properties are expected to be applied in reusable spacecrafts and high-temperature gas-cooled reactors.

A finite element analysis method for random fiber-aggregate 3D mesoscale concrete based on the crack bridging law

Mesoscale modeling is an emerging analytical method that can be used to study fiber-reinforced concrete. However, fine fibers with micrometer diameters are distributed in millions in a standard specimen, so it is impossible to establish a mesoscale model and further analyze it, which severely limits the investigation of the reinforcement mechanism of fine fibers on concrete. This paper efficiently established a highly applicable mesoscale analytical model for random fiber-polyhedral aggregate concrete in Abaqus software based on a comprehensive examination of the crack bridging law and the supplementation of the fiber spacing theory, combined with the improvement of the algorithms of aggregate generation, fiber arrangement, and the judgment of the fiber-aggregate contact by the secondary development method of Python, as well as the matrix-dual arrangement method. Additionally, basalt fiber concrete and mortar specimens were prepared and tested, and the parameters of the model were calibrated to verify the model's authenticity. The result shows that the method proposed in this paper can accurately and efficiently perform mesoscale concrete analysis with fine fibers. In the peak load stage, the fiber has the strongest alleviation effect (Δ = 0.033) on the matrix damage, 10 times that of the crack initiation stage (Δ = 0.003). With the development of damage, fiber stress increases gradually from the crack initiation stage (0.68 σfu), and the growth rate (41.53 %) is the largest at the peak load stage (σfu), which reveals the complex dynamic bridging effect of fiber on the matrix. This investigation proposes a novel and broad applicability methodology for the finite element analysis of fiber-reinforced aggregate mesoscale concrete.

HuR/miR-124-3p/VDR complex bridges lipid metabolism and tumor development in colorectal cancer.

Maintaining a balanced lipid status to prevent lipotoxicity is of paramount importance in various tumors, including colorectal cancer (CRC). HuR, an RNA-binding protein family member, exhibits high expression in many cancers possibly because it regulates cell proliferation, migration, invasion, and lipid metabolism. However, the role of HuR in the regulation of abnormal lipid metabolism in CRC remains unknown. We found that HuR promotes vitamin D receptor (VDR) expression to ensure lipid homeostasis by increasing Triglyceride (TG) and Total Cholesterol (TC) levels in CRC, thus confirming the direct binding of an overexpressed HuR to the CDS and 3'-UTR of Vdr, enhancing its expression. Concurrently, HuR can indirectly affect VDR expression by inhibiting miR-124-3p. HuR can suppress the expression of miR-124-3p, which binds to the 3'-UTR of Vdr, thereby reducing VDR expression. Additionally, a xenograft model demonstrated that targeting HuR inhibits VDR expression, blocking TG and TC formation, and hence mitigating CRC growth. Our findings suggest a regulatory relationship among HuR, miR-124-3p, and VDR in CRC. We propose that the HuR/miR-124-3p/VDR complex governs lipid homeostasis by impacting TG and TC formation in CRC, offering a potential therapeutic target for CRC prevention and treatment.

Targeting p97-Npl4 interaction inhibits tumor Treg cell development to enhance tumor immunity.

Targeting tumor-infiltrating regulatory T (TI-Treg) cells is a potential strategy for cancer therapy. The ATPase p97 in complex with cofactors (such as Npl4) has been investigated as an antitumor drug target; however, it is unclear whether p97 has a function in immune cells or immunotherapy. Here we show that thonzonium bromide is an inhibitor of the interaction of p97 and Npl4 and that this p97-Npl4 complex has a critical function in TI-Treg cells. Thonzonium bromide boosts antitumor immunity without affecting peripheral Treg cell homeostasis. The p97-Npl4 complex bridges Stat3 with E3 ligases PDLIM2 and PDLIM5, thereby promoting Stat3 degradation and enabling TI-Treg cell development. Collectively, this work shows an important role for the p97-Npl4 complex in controlling Treg-TH17 cell balance in tumors and identifies possible targets for immunotherapy.

Discretized macro-element method to evaluate the crushing behavior and protective performance of crashworthy devices under ship collisions

For complex and bulky bridge crashworthy devices, accurate finite element (FE) simulation and impact testing both have significant limitations in verifying their protective performance. The simplified single macro-element method has demonstrated its efficiency in assessing ship-bridge collisions, and this study aims to extend the application of this method to the rapid assessment crashworthy devices performance. To accomplish this objective, the accurate determination of the crush curve for the crashworthy device is essential. Furthermore, the single macro-element approach encounters difficulties in accurately capturing the local deformation of a crashworthy device. This study introduced a discretized macro-element (DME) method aimed at rapidly evaluating the crushing behavior and protective performance of crashworthy devices during ship collisions by employing a comprehensive approach that combines experimental, numerical, and analytical techniques. The combination of theoretical analysis and FE simulations indicated that, based on the principles of similarity laws, the crush curve of large crashworthy devices can be deduced through experiments on scaled specimens. By utilizing the derived crush curve for both the ship and crashworthy device, the DME method accurately captured the local deformation of the crashworthy device. The accuracy of the DME method in assessing the performance of crashworthy devices was verified through an illustrative example. A parametric study has demonstrated the potential of the DME method for optimizing the structure of crashworthy device, owing to a significant increase in computational efficiency.

Effects of Structural Constraints on Excited-State Properties in Dimeric Cu(I) Diimine Complexes.

Copper(I) bis-diimine complexes have played important roles in light-activated processes that can lead to their potential applications in photocatalysis and chemical sensing. Their metal-to-ligand charge-transfer (MLCT) excited-state properties are tunable by various structural factors. Dimeric Cu(I) complexes with connecting diimine derivative ligands offer another structural tuning platform for the excited-state properties. Here, we investigate excited-state properties in two covalently connected dimeric Cu(I)'s with varying structural constraints exerted by the number of carbons in the polyethylene bridge (C0 and C4) connecting the two copper(I) diimine moieties. An interesting feature of Cu(I) diimine complexes is their ability to flatten following a photoinduced structural change. Herein, we observe larger structural constraints and more structural rearrangement required upon excitation of the longer bridged complex C4 to achieve a conformation toward a more flattened tetrahedral coordination geometry compared to the shorter bridged C0. Vibrational wavepacket analysis of these complexes further supports the effect of these structural constraints where we observe a more rapid dephasing of the C0 complex, as opposed to the C4 complex, despite similar normal mode vibrations. The experimental results were supplemented by TDDFT calculations. The studies provide insight into using metal-metal interactions through constraints to tune excited-state dynamics and pathways.

Efficiency and mechanism of modified carbon nitride for the co-adsorption of copper and tetracycline from water

The escalating contamination of heavy metal ions and antibiotics in the aqueous environment underscores the necessity of developing efficient treatment technologies for their concurrent removal. In this work, a phosphate-modified g-C3N4(PCN) by assembling phytic acid with graphitized carbon nitride was prepared through a hydrothermal reaction. The characterization results reveal that PCN exhibits increased porosity, an enhanced specific surface area, and larger pore volume in comparison to pristine CN. At pH 5.0 and 25 °C, PCN demonstrates remarkable adsorption capacities for Cu (II) (q = 172.3 mg g−1) and tetracycline (TC) (q = 63.1 mg g−1) in a single system, respectively, which correspondingly surpasses those of CN by 7 and 8 times. In systems where Cu (II) and TC coexist, Cu (II) enhances the TC removal rate by acting as a bridge. As Cu(II) concentration increases, TC adsorption efficiency significantly improves. Although common ions in solution influence PCN adsorption, it maintains high efficiency for TC and Cu(II) across various water matrices and in the presence of natural organic matter. Detailed characterization and computational chemical analysis reveal that the enhanced adsorption capacity of PCN is due to increased porosity and the presence of additional functional groups. Surface complexation and adsorption bridging are identified as the key mechanisms for effective Cu(II) and TC adsorption. Additionally, recycling experiments validate its reusability, thereby offering a novel avenue for the removal and recovery of TC and Cu(II) from wastewater.

Improving the Stability and Kinetic Inertness of Mn(II) Complexes by Increasing the Bridge Length in Bicyclic CDTA-Like Ligands.

Kinetic inertness of Mn(II)-based MRI contrast agents can be improved by increasing the rigidity of the polydentate ligand that tightly coordinate the metal ion. Taking inspiration from the remarkable increase in kinetic inertness of [Mn(CDTA)]2- compared to [Mn(EDTA)]2- due to the cyclohexyl backbone rigidity, we devised that bicyclic ligands would further improve the kinetic inertness of the Mn(II) complexes. The length of the alkyl bridge on the cyclohexane ring was varied from methylene (BCH-DTA), ethylene (BCO-DTA) to propylene (BCN-DTA) to evaluate the influence of the different trans-diaminotetraacetate ligands on relaxometric, thermodynamic and kinetic properties of the Mn(II) complexes. 1H and 17O NMR relaxometric studies showed a slight increase in relaxivity and a faster water exchange rate in these Mn(II)-complexes with respect to [Mn(CDTA)]2-. Solution studies revealed that the conditional stability (pMn) and dissociation half-life (t1/2) at pH 7.4 follow the order [Mn(BCH-DTA)]2-<[Mn(BCO-DTA)]2-<[Mn(BCN-DTA)]2- highlighting the effect of the bridge length on the overall stability of the Mn(II) complexes. Remarkably, [Mn(BCN-DTA)]2- shows an improved pMn value and a 7-times higher kinetic inertness than [Mn(CDTA)]2-. NMR studies on the Zn(II) analogues confirm the rigidity of the bicyclic complexes with an isomerization process at >313 K for the smaller bridged complex [Zn(BCH-DTA)]2-.

An EGO-based online model updating method for hybrid simulation

Hybrid simulation combines experimentally testing of physical substructures with computational simulation of numerical substructures to replicate structural responses under earthquakes. When numerical substructure involves parts that are similar to physical substructure, measured responses of physical substructure are often used to update similar parts within numerical substructure, aiming to improve accuracy of seismic assessment. This study proposes an efficient global optimization based approach for online model updating in hybrid simulation (HSMU-EGO) involving multiple key components yet with only one physically tested in laboratory. Kriging meta-model is constructed for the response error between the numerical model for updating and the experimental substructure, while efficient global optimization and optimal Latin hypercube design are integrated for parameter estimation to minimize the response error. Computational simulations are conducted for a simple steel braced frame and a complex concrete continuous bridge to comprehensively evaluate the performance of HSMU-EGO in the presence of constitutive parameter and model errors. The proposed method is demonstrated to effectively and efficiently improve the accuracy of hybrid simulation in almost all cases. Compared with Unscented Kalman Filter (UKF), this proposed HSMU-EGO provides more suitable alternative when prior information is limited for the physical substructure.

Analysis of Reliability and Cost of Complex Systems with Metaheuristic Algorithms

Introduction. The assessment of the reliability and cost of complex systems, such as Complex Bridge Systems (CBS) and Life Support Systems in Space Capsules (LSSSC), is fascinating. To achieve the ideal system design through diverse constraints and increase overall system reliability, researchers have extensively explored system reliability and cost optimization problems. Hence, the significant advancement in metaheuristic methods is the primary source of further system reliability and cost optimization process refinement.&#x0D; Aim and tasks. This research attempts to enhance the reliability and cost of complex systems named CBC and LSSSC has been presented. &#x0D; Results. The structure is based on few recent metaheuristic techniques, such as Moth Flame Optimization (MFO), Whale Optimization Algorithm (WOA), Gazelle Optimization Algorithm (GOA), Dragonfly Algorithm (DA), and Coati Optimization Algorithm (COA). Comparing the acquired findings to those found in other proposed techniques demonstrates the usefulness of a methodology based on COA. The proposed COA algorithm exhibits enhanced efficiency by offering superior solutions to reliability and cost-optimization problems. In addition, a non-parametric Friedman ranking was performed for validation. The results of this research are based on improving the reliability of the parameters and decreasing complex systems’ costs used by the five metaheuristic methods. Observing the convergence graph, Friedman ranking, statistical results test, and tables determined that COA is the most effective algorithm for a complex system’s cost and reliability parameters compared to other existing approaches, and also provided a faster solution.&#x0D; Conclusions. This study proposes unique ways to reduce costs while increasing parameter reliability in complex systems. After analysing the comparative solution, the authors found that when comparing these approaches (GOA, DA, MFO, WOA, and COA), the COA provided the best minimum solution for the cost and reliability of complex systems. Hence, the suggested COA procedure was more successful than that described in this study.

Exploring the Impact of Emerging Educational Technology in MBA Programs: Enhancing Brand Equity through Virtual Reality

Purpose: The increasing emphasis on continuous development in student learning worldwide, particularly in the Digital Age, necessitates leveraging technology to enhance educational experiences. This research focuses on exploring the potential of virtual reality (VR) to transform MBA education, aiming to inspire innovative teaching methods that extend beyond conventional knowledge exchange. Design/Methodology: Employing a mixed-methods approach, this study comprehensively examines the implementation and impact of VR-based learning experiences in MBA programs, Through surveys data is gathered from MBA students. This methodology enables a thorough evaluation of VR's effectiveness as a pedagogical tool in enhancing engagement, comprehension, and retention of MBA subjects Findings: The study uncovers a range of advantages and challenges linked to the integration of VR technology in MBA education. On the one hand, VR offers immersive, interactive learning experiences that bolster comprehension and critical thinking skills. However, significant challenges persist, including the initial cost of VR implementation, ensuring technological accessibility for all students, and providing sufficient faculty training to effectively leverage VR in teaching. Conclusion: This empirical study underscores the transformative potential of VR in enhancing MBA education. By providing immersive and interactive learning experiences, VR has the capacity to significantly enrich the learning journey of MBA students. VR shows promise in simulating complex business scenarios and bridging theory with real-world application. Originality/Value-This research aims to inspire greater adoption of educational technology, enhancing MBA learning experiences and preparing students for success in the digital age. Paper Type- Empirical Analysis

Improving sensitivity of XANES structural fit to the bridged metal-metal coordination.

Hard X-ray absorption spectroscopy is a valuable in situ probe for non-destructive diagnostics of metal sites. The low-energy interval of a spectrum (XANES) contains information about the metal oxidation state, ligand type, symmetry and distances in the first coordination shell but shows almost no dependency on the bridged metal-metal bond length. The higher-energy interval (EXAFS), on the contrary, is more sensitive to the coordination numbers and can decouple the contribution from distances in different coordination shells. Supervised machine-learning methods can combine information from different intervals of a spectrum; however, computational approaches for the near-edge region of the spectrum and higher energies are different. This work aims to keep all benefits of XANES and extend its sensitivity towards the interatomic distances in the first and second coordination shells. Using a binuclear bridged copper complex as a case study and cross-validation analysis as a quantitative tool it is shown that the first 170 eV above the edge are already sufficient to balance the contributions of Cu-O/N scattering and Cu-Cu scattering. As a more general outcome this work highlights the trivial but often overlooked importance of using `longer' energy intervals of XANES for structural refinement and machine-learning predictions. The first 200 eV above the absorption edge still do not require parametrization of Debye-Waller damping and can be calculated within full multiple scattering or finite difference approximations with only moderately increased computational costs.

Subspace Identification of Bridge Frequencies Based on the Dimensionless Response of a Two-Axle Vehicle.

As an essential reference to bridge dynamic characteristics, the identification of bridge frequencies has far-reaching consequences for the health monitoring and damage evaluation of bridges. This study proposes a uniform scheme to identify bridge frequencies with two different subspace-based methodologies, i.e., an improved Short-Time Stochastic Subspace Identification (ST-SSI) method and an improved Multivariable Output Error State Space (MOESP) method, by simply adjusting the signal inputs. One of the key features of the proposed scheme is the dimensionless description of the vehicle-bridge interaction system and the employment of the dimensionless response of a two-axle vehicle as the state input, which enhances the robustness of the vehicle properties and speed. Additionally, it establishes the equation of the vehicle biaxial response difference considering the time shift between the front and the rear wheels, theoretically eliminating the road roughness information in the state equation and output signal effectively. The numerical examples discuss the effects of vehicle speeds, road roughness conditions, and ongoing traffic on the bridge identification. According to the dimensionless speed parameter Sv1 of the vehicle, the ST-SSI (Sv1 < 0.1) or MOESP (Sv1 ≥ 0.1) algorithm is applied to extract the frequencies of a simply supported bridge from the dimensionless response of a two-axle vehicle on a single passage. In addition, the proposed methodology is applied to two types of long-span complex bridges. The results show that the proposed approaches exhibit good performance in identifying multi-order frequencies of the bridges, even considering high vehicle speeds, high levels of road surface roughness, and random traffic flows.

Theoretical Study Regarding the General Stability of Upper Chords of Truss Bridges as Beams on Continuous or Discrete Elastic Supports

New or in-service truss bridges, with or without upper bracing systems, may display instability phenomena such as general lateral torsional buckling of the upper chord. The buckling of structural elements, particularly in the case of steel bridges, can be associated with the risk of collapse or temporary/permanent withdrawal from service. Such incidents have occurred in the case of several bridges in different countries: the collapse of the Dee bridge with truss girders in 1847 in Cheshire, England; the collapse of the semi-parabolic truss girder bridge near Ljubičevo over the Morava River in Serbia in 1892; the collapse of the Dysart bridge in Cambria County, Pennsylvania in 2007; the collapse of the Chauras bridge in Uttarakhand, India in 2012; and the collapse of a bridge in Nova Scotia, Canada (2020), and such examples may continue. Buckling poses a significant danger as it often occurs at lower load values compared to those considered during the design phase. Additionally, this phenomenon can manifest suddenly, without prior warning, rendering intervention for its prevention impossible or futile. In contemporary times, most research and design calculation software offer the capability to establish preliminary values for buckling loads, even for highly intricate structures. This is typically achieved through linear eigenvalue buckling analyses, often followed by significantly more complex large displacement nonlinear analyses. However, interpreting the results for complex bridge structures can be challenging, and their accuracy is difficult to ascertain. Consequently, this paper aims to introduce an original method for a more straightforward estimation of the buckling load of the upper chord in steel truss bridges. This method utilizes the theory of beams on discrete elastic supports. The buckling load of the upper chord was determined using both the finite element method and the proposed methodology, yielding highly consistent results.

A Revit-Midas/Civil conversion approach for bridge superstructures analysis

In this study, a model conversion method that combined Revit with Midas Civil software was proposed to improve the modeling efficiency and accuracy of finite element calculations for a large bridge structure. The secondary development program was established using the Visual Studio 2022 platform, which was used to convert the model information. A model conversion interface was created by extracting, screening, and then sorting the geometric information of the business information model and generating a Midas Civil Text file. This interface served as a link between Revit and Midas Civil, specifically for the bridge superstructure. The feasibility and reliability of the proposed model conversion method was confirmed using a single-box three-cell Box-girder bridge. The results demonstrated that the model conversion method transfered the Revit model information successfully to a Midas Civil structural analysis model, thereby significantly enhancing the efficiency and accuracy of the finite element modeling of a complex bridge superstructure.