Steel Arch Research Articles

Evaluation of Load-Bearing Capacity in Japanese Arch Steel Aqueduct Bridge through Structural Redundancy Assessment

Structural redundancy assessment of steel aqueduct bridges is made by the analysis of a case study using the Musota Aqueduct bridge structure: a simply supported steel arch bridge erected in 1973 and a seven- span continuous steel aqueduct bridge. In this paper, as a case study, after the validation of the model, the structural redundancy of the Musota aqueduct bridge in Wakayama City with respect to its load-carrying capacity after the failure of hanging components due to corrosion was investigated. The conventional procedure for the assessment of redundancy makes use of static nonlinear structural analysis. A three-dimensional finite-element model of this bridge was developed to simulate its behavior. The results from the linear analysis are compared with those from the nonlinear analysis to investigate the appropriateness of the former in the evaluation of redundancy. A detailed nonlinear static finite element study is carried out into the hangers' components of the arch bridge in order to clarify the implications involved in the failure of redundancy. Finally, recommendations for prudent bridge maintenance methods are presented based on findings from the investigation.

Research on the Construction Mechanics and Stability Control Technology of Expressway Tunnel Based on Numerical Analysis

As an effective structural form, connecting arch tunnel has been widely used in practical engineering because of its smooth linear shape, small footprint and good bridge and tunnel connection. With the increase of domestic traffic volume year by year, the width of the even arch tunnel is gradually changed from two-way four lanes to two-way six lanes. I20 I-steel, spacing 0.75∼1 m, anchor length 3∼4 m, ring spacing 0.5∼1 m, the side ring spacing of the middle wall is 0.75 m, the side ring spacing of the side wall is 1 m, and the shotcrete thickness is 0.25∼0.3 m. The excavation span of a two-way six-lane continuous-arch tunnel is considerable, leading to complex stress characteristics, thereby posing risks to construction safety and structural stability. Following the construction of the initial tunnel, disturbance to the surrounding rock occurs, affecting subsequent excavation phases. The initial support requirements for subsequent excavations are more intricate, with increased internal forces compared to the initial tunnel segment. As the rear tunnel progresses, the surrounding rock near the middle wall shifts towards the rear tunnel, reducing internal forces in the concrete and steel arch frame. However, as the rear tunnel distance increases, concrete stress and axial forces on the middle wall side of the initial tunnel begin to rise. Throughout the construction, the steel arch frame’s internal forces and spray concrete stress on the middle wall side’s arch waist and foot are the highest, making them susceptible to disruption from construction on the opposite side, thus constituting critical tunnel components. Numerical simulations effectively capture surrounding rock and structural stress dynamics during large-span arch tunnel construction. Simulation outcomes align closely with field measurements, particularly in three-dimensional simulations, enhancing construction understanding and management.

Study on the Susceptibility of Steel Arches with Letting Pressure Nodes Based on Incremental Dynamic Analysis

When soft rock tunnels pass through fractured fault zones, they are particularly susceptible to extrusion and large-scale deformations, especially during seismic events. To address these challenges, this study introduces an innovative yield-support steel arch design featuring a circumferential letting pressure node at its core. This design delivers incremental support resistance within the deformation zone and a susceptibility curve is applied to evaluate the damage probability of the steel arch with a letting pressure node under seismic loading conditions. Measurements of the surrounding rock pressure and structural forces on the steel arch with the letting pressure node were conducted at the Baoshan Jewel Mountain Tunnel in China. The field experiment results revealed a 23% reduction in the surrounding rock pressure and an 11% decrease in the internal forces of the support structure. These findings demonstrate the successful application of the letting pressure node-supported steel arch in mitigating large deformations in soft rock environments. Additionally, using finite element software ANSYS 2022, a seismic time-history analysis was conducted, employing the relative deformation rate of the letting pressure node steel arch as the damage index and the peak ground acceleration (PGA) as the strength parameter to generate the incremental dynamic analysis (IDA) curve. According to the susceptibility curve derived from the incremental dynamic analysis, at the design ground motion level of 8 degrees, the letting pressure node steel arch has a 94% probability of exceeding its normal service life limit and experiencing damage. The findings of this study offer a novel approach to addressing large deformations in soft rock tunnels. The proposed susceptibility curves for steel arches with letting pressure nodes provide a robust foundation for predicting the damage probability of yielding support structures under seismic conditions.

Application of FBG Sensing Technology for Real-Time Monitoring in High-Stress Tunnel Environments

In the process of tunnel construction, problems such as high-stress rockburst, large deformation of soft rock, water inrush and mud gushing, secondary cracking of linings, blasting interference, man-made damage, and mechanical damage are often encountered. These pose a great challenge to the installation of monitoring equipment and line protection. In order to solve these problems, the 2# inclined shaft of Muzhailing Tunnel in the Gansu Province of China, which exists under high stress, water bearing, and bias conditions, was taken as the research object in this paper. By assembling a string, drilling grouting and sealing, and introducing multiple modes of protection, new fiber grating sensor group installation and line protection methods were proposed. The automatic continuous monitoring of the deep deformation of surrounding rock and the automatic continuous monitoring of steel arch stress were realized. The field monitoring results showed that: (1) the fiber grating displacement sensor group could be used to verify the authenticity of the surface displacement results monitored by the total station; (2) the NPR anchor cable coupling support effectively limited the large deformation of soft rock and the expansion of surrounding rock in a loose circle, and the range of the loose circle was stable at about 1 m; and (3) the main influence range of blasting was at a depth of 0~5 m in surrounding rock, and about 25 m away from the working face. In addition, to secure weak links in the steel arch due to the hardening phenomenon, a locking tube was set at the arch foot. In the support design, the fatigue life of the steel was found to be useful as the selection index for the steel arch frame to ensure the stability of the surrounding rock and the long-term safety of the tunnel. The present research adopted a robust method and integrates a variety of sensor technologies to provide a multifaceted view of the stresses and deformations encountered during the tunneling process, and the effective application of the above results could have certain research and reference value for the design and monitoring of high stress, water-bearing, and surrounding rock supports in tunnels.

Steel Arch Structures with Prestressed Concrete Deck

AbstractFootbridges with prestressed concrete deck, which are suspended on steel arch ribs, are described in terms of the structural arrangement, static function and erection. These bridges create stiff structural systems which guarantee the bridges' favourable dynamic response. While steel arch ribs allow easy erections, the concrete deck guarantees structural integrity. The footbridges are structurally efficient, they are light and transparent, corresponds to the scale of the landscape and all structural members have human dimensions. They were erected with a minimum impact on the environment. Their structural arrangement is illustrated on examples of four bridges.

Prediction of fatigue life of a bolted joint in railway steel arch bridge using multiaxial fatigue criteria

Fatigue represents a critical condition for infrastructure subjected to repeated cyclic loads, such as steel railway bridges. The literature offers several methods to estimate fatigue life, consisting of three main phases: cycle counting, fatigue damage criterion, and damage accumulation criterion. Applying S-N curves might not be conservative in the case of railway bridges subjected to traffic because the stress-time history is complex and cannot be reduced to a sinusoidal history. Additionally, the presence of a multiaxial stress state must be considered. Therefore, this work compares eight multiaxial fatigue damage criteria for evaluating fatigue life in a scenario between high and low-cycle fatigue. Specifically, the authors considered four low-cycle fatigue criteria, namely Smith–Watson–Topper (SWT), Kandil, Brown and Miller (KBM), Glinka, Fatemi and Socie (FS), and four high-cycle fatigue criteria, Crossland, Basquin and the methods recommended by Eurocode 3 and British Standard. The rainflow counting method in ASTM E1049-85 (2011) and Miner’s rule for damage accumulation were used. The Polcevera railway steel bridge was selected as a case study. A 3D numerical model was developed for this purpose using Midas Civil software, taking into account the material non-linearity of the bridge’s elements. Once the area with the highest stress concentration was identified, a detailed analysis was conducted to estimate the stress and strain time histories induced by train traffic. A sensitivity analysis was conducted after critically comparing the eight methods for predicting fatigue life to assess the impact of traffic parameters, train velocity, axle load, and convoy length on fatigue life. It has been found that the criteria considering axial stress tend to overestimate the number of fatigue cycles to failure compared to the criteria, including the effect of shear stress components.

The corrosion expansion force and cracking separation between corroded section steel arch frame and shotcrete in tunnel primary support

High chloride content in the subsea tunnel environment leads to inevitable corrosion of I-shaped steel in primary support. Corrosion generates expansive force between I-shaped steel and concrete, eventually cracking the concrete protective layer, and weakening the bond strength, severely impacting the tunnel support system’s durability. The main purpose of this article is to obtain the corrosion expansion force generated at the interface between corroded I-shaped steel and concrete, as well as the mechanical response characteristics of concrete under the action of corrosion expansion force. Firstly, nine I-shaped steel concrete components were fabricated for electro-accelerated corrosion test, obtaining the variation curve of corrosion expansion force with corrosion rate and protective layer thickness. The experimental results indicated that the development of corrosion expansion force can be divided into three stages: initial free corrosion stage (corrosion rate ρ = 0.5 % – 0.7 %), stage with a noticeable increase in corrosion expansion force (corrosion rate ρ = 0.7 % – 12 %), and expansion-induced cracking (corrosion rate ρ > 12 %). Meanwhile, a three-stage corrosion expansion force model for concrete and corroded I-shaped steel was proposed, which was correlated to the experimental curve well. Finally, the mechanical characteristics of the surrounding concrete during the development process of different corrosion expansion forces were explored through ANSYS software. The numerical results indicated that these cracks due to corrosion expansion force primarily occurring in the contact region between the concrete and the I-shaped steel flange, specifically in three areas: the central part of the flange and its two corners; The tensile stress in the concrete surrounding the web plate is less than that at the flange, leading to the initial longitudinal cracking observed on the outer surface of the flange.

Experimental Study of the Mechanical Behavior of a Steel Arch Structure Used in the Main Lining of a Highway Tunnel

Experimental Study of the Mechanical Behavior of a Steel Arch Structure Used in the Main Lining of a Highway Tunnel

Research on the Mechanism of Loose Deformation in Weak Fracture Zone Tunnel Surrounding Rock and Support Control

In the fractured weak fault zone, rock mass exhibits low strength and poor self-stability. The geological conditions are complex, and when tunnels cross through fractured zones, significant deformations and collapses are prone to occur, leading to geological hazards. This paper investigates the in situ stress and deformation patterns of the Dongmachang Tunnel No. 1, proposing support solutions for addressing tunnel deformations through field experiments and numerical simulations. The on-site monitoring results indicate that despite implementing measures such as grouting reinforcement and temporary steel supports to control surrounding rock deformation, significant structural damage still occurred in the tunnel support system. The manifestations included severe sinking and cracking of the arch crown, strong inward deformation of the sidewalls, widespread cracking, crushing, and spalling of shotcrete, slight arching uplift, and severe distortion and twisting of steel arches forming a “Z” or “S” shape. To ensure tunnel safety and control the stability of excavations in weak fault zones, a comparison of tunnel deformation support schemes is conducted through field experiments and numerical simulations, indicating that replacing the upper tunnel structure and invert can effectively prevent tunnel deformations. These measures are vital for the sustainable development of tunnel.

Failure mechanisms and reinforcement support of soft rock roadway in deep extra-thick coal seam: A case study

The soft rock roadway in deep extra-thick coal seam is prone to large deformation disaster. In order to solve this problem effectively, taking the W3101 coalface of Xiao’kang coal mine as the engineering background, the failure mechanisms and the corresponding control technology were investigated by the methods of laboratory test, numerical simulation and field measurement. First, a series of tests were carried out on the basic mechanical properties of rock mass, in-situ stress and loose zone, and it was found that the failure mechanisms of soft rock roadway in deep extra-thick coal seam are poor lithology of surrounding rock, high in-situ stress, large loose circle and unreasonable original support. Then, based on the supporting mechanisms of grouting cable and concrete-filled steel tube (CFST) of bottom angle, a new collaborative reinforcement support (CRS) technology combining the two was proposed. Next, the numerical simulation shows that the CRS technology has good applicability in controlling large deformation of soft rock roadway in deep extra-thick coal seam. Finally, to exhibit the engineering application effect of the proposed CRS scheme, it was also applied in Xiao’kang coal mine. Comparing to the controlling effect of original support scheme, it can be seen that the average deformation of soft rock roadway reduces by 73.2 % under the proposed CRS scheme, and the steel arch frame of bottom angle is slightly deformed. Meanwhile, it is found that the grouts diffusion radius is nearly 1.21 m, and the deepest diffusion depth is 4.25 m, which also indicates again that the feasibility of the proposed CRS scheme in controlling large deformation of soft rock roadway in deep extra-thick coal seam.

Design of a Composite Structure Composed of Large Rise-Span Ratio Cross Steel Arch and Hectometre Corridor

Design of a Composite Structure Composed of Large Rise-Span Ratio Cross Steel Arch and Hectometre Corridor

Construction Technology and Application of TBM in Shengli Tunnel of Tianshan Mountain under poor geological conditions

When a tunnel boring machine (TBM) excavates in poor geological conditions like fracture zones, soft rock with high ground stress, hard rock with high ground stress, and water inrush ground, severe problems such as surrounding rock collapse, convergence, rock burst and water and mud outburst are usually encountered. These problems existed in the Tianshan Shengli Tunnel project in Xinjiang, China. Several methods and techniques were adopted to reduce construction risks and improve construction efficiency. The seismic wave reflection long-distance geological forecasting method was employed to forecast and predict these adverse geological conditions. The pre-reinforcement construction method was employed on the surrounding broken rocks in front of the tunnel face to lower the risks of tunnel collapse and machine jamming. A combined steel arch was applied to prevent tunnel arch collapse. An artificial cap method was applied to prevent the jamming caused by high-ground stress soft rock. Measures such as spraying water on the tunnel face and drilling stress holes were employed to prevent rock bursts caused by high-ground stress in hard rock. Implementing the advanced pipe shed method during water influx, sudden mud, and other working conditions reduced the risk of groundwater damage to equipment and lowered risks to personnel safety. The successful application of these techniques can provide a reference for TBM tunnel construction in similar ground conditions.

Stress-strain state zoning model and novel large deformation classification method for squeezing tunnels

Accurately assessing the level of large deformation in squeezing tunnels is of great importance for the design of support structures. The current large deformations classification methods fail to account for the effect of support pressure on the relative deformation of surrounding rock. In this study, a theoretical model for the stress–strain state zoning of the surrounding rock in squeezing tunnels is established. A sensitivity analysis of the model parameters is conducted. The distribution law of the strength-stress ratio, relative deformation, and relative support pressure indices in 43 field monitoring squeezing tunnels are statistically analyzed. A novel large-deformation classification method based on the relative support pressure index is proposed and applied in case studies. The parameter sensitivity analysis shows that mechanical parameters of the surrounding rock significantly affect the deformation and the stress–strain state zoning of the surrounding rock. The stress–strain state zoning and deformation of the surrounding rock are also primarily dependent on the matching relationship between strength-stress ratio and support pressure. Statistical analyses indicate that there is a nonlinear negative correlation between the relative deformation of the surrounding rock and the strength-stress ratio, as well as the relative support pressure, which includes the steel arch relative support pressure index (SSPI) and the anchor bolt relative support pressure Index (ASPI). The key to controlling surrounding rock deformation lies in the rational matching of support pressure to the strength-stress ratio. In the novel large deformation classification method, three key indexes of strong stress ratio, relative deformation and relative support pressure are quantitatively included, and squeezing large deformation is divided into three levels. Moreover, the case study demonstrated that the novel large deformation classification method has significant guiding importance in verifying feasibility and optimizing support design schemes during both the design and construction phases.

A DL method to detect multi-type hidden objects in tunnel linings using a comprehensive GPR dataset

This study proposes an enhanced detection method for tunnel lining hidden objects based on the comprehensive Ground Penetrating Radar (GPR) dataset and an improved deep learning (DL) algorithm. To mitigate the issue of data scarcity, a tailored dataset consisting of six types of hidden objects was compiled, which contained 7426 on-site collected GPR images and 71,014 well-labeled objects. This bespoke dataset offered substantial support for algorithm training and validation, making it one of the most extensive datasets in the domain for tunnel lining GPR detection. An enhanced Faster R-CNN algorithm was then developed to effectively detect different types of hidden objects. Modifications were made in four key areas: Feature extraction module, Feature Pyramid Network (FPN), customized anchor scheme and modified loss function. This algorithm was subsequently trained and validated using the comprehensive dataset. Evaluation metrics demonstrated the performance of this approach, with a mean average Precision (mAP) of 81.2%. Results also proved particularly effective in detecting rebars, pipelines, and steel arches while demonstrating a shortfall in detecting voids and cavities due to the data limitation. The results underscore the potential of this enhanced algorithm for the automatic detection of diverse hidden objects in tunnel linings, thus stimulating further research in this vital field.

Failure Mechanism and Structural Optimization of the Primary Support Structure for Expressway Tunnel in Soft Rock: A Case Study

When the highway tunnel crosses the soft rock, the primary support structure often fails and damages because it cannot withstand the excessive surrounding rock pressure. For the Magu tunnel in Yunnan Province, which is in the upper hard and lower soft stratum, the surrounding rock deformation is large, and the primary support structure occurs spray concrete cracking, steel arch frame twisting deformation. According to the convergence constraint curve, this paper proposes to adopt the primary support optimization design scheme of "shortening the bench length + optimizing the length and arrangement of anchor rods". According to the numerical simulation results of FLAC3D, the important indexes such as deformation convergence, surrounding rock stress, anchor axial force and thickness of plastic zone in different excavation support conditions are analyzed. The conclusions are as follows: 1. The soft rock at the foot of the benches does not provide sufficient support resistance, resulting in large settlement and convergence deformation that can cause the primary support structure to fail and become damaged. 2. The length of the middle bench and the primary support strength and stiffness contribute most to the deformation. 3. The deformation control effect of the short anchor rods on the surrounding rock is relatively weak. Increasing the length of anchor can better play the role of anchor suspension enhancement and give full play to the surrounding rock's own bearing capacity. Finally, the deformation of the tunnel is under control after adopting the optimized primary support structure, which ensures the smooth construction.

Mitigation of unmeasured environmental and operational variability in long-term bridge health monitoring by unsupervised statistical learning

Environmental and operational variations present a significant challenge in the long-term health monitoring of bridge structures due to their potential to cause serious confounding influences and wrong decisions. These influences may lead to false alarms of damage during normal operation of a civil structure or, conversely, mask actual damage, resulting in a failure to correctly signal a warning. Consequently, a critical task in structural health monitoring, particularly for bridges, is to mitigate the negative impact of environmental variability. An initial approach is to measure the most influential environmental and operational factors and then apply statistical tools to eliminate their effects. However, this approach may not be effective under all conditions. Therefore, the primary objective of this paper is to propose an innovative unsupervised statistical learning method that addresses the challenges posed by environmental and operational variability by considering unmeasured factors. The proposed method involves three steps: data clustering, unsupervised feature selection, and novelty detection. The initial step utilizes k-means clustering to categorize features (modal frequencies) into five types of clusters, reflecting the influence of five environmental and operational factors on bridge structures; that is, temperature, humidity/rain/snow, wind speed/direction, traffic, and damage. These clustered features are then processed through an unsupervised feature selection algorithm based on reconstruction independent component analysis to extract new features. These reduced features are subsequently employed in a novelty detection model, developed using the Mahalanobis-squared distance, to analyze the environmental and operational effects. Real dynamic data of a steel arch bridge is utilized to verify the proposed method. Results demonstrate that this method can effectively handle the demanding issue stemming from unmeasured environmental and operational variability conditions.

The Effects of Air Abrasive Polishing on the Release of Iron Ions from Various Orthodontic Arch Wires (Stainless Steel and Nickel Titanium)

Orthodontic treatment with has been increasingly demanded. However, when using fixed appliances for orthodontic treatment, oral hygiene is compromised, and there is a higher chance of developing dental stains, plaque-related diseases, and corrosion-related problems. Air abrasive polishing had a superior effect over the conventional method in removing dental deposits, however, its effect on corrosion process was not investigated thoroughly in details. This study designed to assess the effects of air polishing onion release and surface micromorphology of stainless steel and Nickel titanium arch wires. A total of 288 ( stainless-steel , coated stainless steel , Nickel titanium and coated Nickel titanium rectangular arch wires ) of one brand ( The Ultimate Wire) ™ From IOS (International Orthodontic Services, Stafford, USA), (0.016 * 0.022 ) were subjected to varying air abrasion polishing periods (5, 10, and 20 seconds), after which they were immersed in artificial saliva with a pH of 6.75 and incubated at 37°C for 28 days. Ion release was measured using an atomic absorption spectrophotometer at 7 days, 14 days, and 28 days. The cumulative effect was then calculated. After polishing the chosen sample, corrosion and surface changes were evaluated using a scanning electron microscope (SEM). The significant difference between the analysed groups was found using an analysis of variance (ANOVA) and the LSD test, with a significance level of p 0.05. The results revealed that all types of arch wire showed a significant amount of release in the tested ions and the amounts of nickel and iron ions released was higher than chromium ion. Additionally, the longer the polishing time the higher the number of ions release that’s yields the level of significance, air abrasion polishing increased surface roughness and surface pits and crevices.It may be concluded that the air polishing method enhanced the amount of ion release to a subtoxic level and could be employed in adult patients with a lengthy time between visits.This study was performed to:1. Evaluate the effect of calcium carbonate airborne particles abrasion with different polishing times 5, 10 and 20 seconds on (Fe) ions release from orthodontic arch wires. 2. Assess the surface micromorphology of orthodontic arch wires after air polishing procedure.

Structural Health Monitoring for Dębica Railway Steel Arch Bridge in Poland

The study presents the vibration-based SHM system for the Dębica railway bridge located in Poland. The railway bridge owner was concerned about the excessive and self-excited vibrations of the hangers, the vibration measurement of 8 hangers per span in a total of two spans being monitored. The dynamic responses in both the transverse and longitudinal directions for each hanger under different load events over a nine-month period were recorded and introduced in this paper. The tension force and stress on each hanger are estimated through the natural frequency of the experimental vibration analysis. The proposed approaches could be used to develop a smart alarm system integrated into a vibration-based data-driven SHM system for heavy railway bridges.

Determination of the Ground Reaction Curve for an Elasto-Plasto-Fractured Rock Mass

Polish National Standards for underground excavation support design outline the deformational pressure model for assessing loads acting on the support systems of deep underground excavations. They distinguish two different rock mass models, highlighting the pivotal role of the critical longitudinal strain of the rock mass in appropriate model selection. A comparison between the design method given by Polish Standards and the widely recognized convergence–confinement method, consisting of a ground reaction curve (GRC), longitudinal displacement profile (LDP), and support characteristics curve (SCC), reveals the advantages of the latter in capturing the three-dimensional nature of underground excavations. The following study presents a method for establishing a GRC curve for the elasto-plasto-fractured rock mass model, featured in Polish Standards, demonstrating its applicability through analyses of a typical circular roadway under varying rock mass conditions. Practical implications are discussed, including the design of yielding steel arches as the primary support system and the calculation of safety factors for both the support system and the surrounding rock mass, considered as a natural support component. Overall, the study contributes to a deeper understanding of the actions of rock masses in the vicinity of excavations located at great depths. Furthermore, it provides practical insights for engineering applications.

Vibration-based SHM of railway steel arch bridge with orbit-shaped image and wavelet-integrated CNN classification

The study presents the data-driven applications of continuous wavelet transforms (CWT), orbit-shaped analysis and convolutional neural networks (CNN) using GoogLeNet for Dębica railway bridge health monitoring in Poland. Training and validation data sets are the dynamic behavior of the bridge deck recorded through an IEPE vibration sensor with a sampling frequency of 128 Hz from vibration-based structural health monitoring (SHM) system over a nine-month period from December 2019 to September 2020. Utilizing Morse, Morlet, and Bump wavelet, the vibration signal scalogram images are produced in the frequency–time domain as the input for CNN classification models, while the output is to predict health states based on the experimental tension force of eight hangers using label thresholds developed by calibrated finite element model. Moreover, the vibration-based orbit-shaped image patterns, acquired through a bidirectional sensor on each hanger are processed with CNN classification models for automated hanger health diagnostic. The accuracies and weighted F1-scores of the wavelet-assisted and orbit-shaped CNN models are more than 83% on imbalanced validation images. The results show that the proposed CNN approaches can classify the potential structural problems.