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20 pages, 1924 KiB

Open AccessArticle

Comprehensive Empirical Modeling of Shear Strength Prediction in Reinforced Concrete Deep Beams

by Eyad K. Sayhood, Nisreen S. Mohammed, Salam J. Hilo and Salih S. Salih

Infrastructures 2024, 9(4), 67; https://doi.org/10.3390/infrastructures9040067 - 28 Mar 2024

Viewed by 767

This paper presents comprehensive empirical equations to predict the shear strength capacity of reinforced concrete deep beams, with a focus on improving the accuracy of existing codes. Analyzing 198 deep beams imported from 15 existing investigations, this study considers various parameters such as [...] Read more.

This paper presents comprehensive empirical equations to predict the shear strength capacity of reinforced concrete deep beams, with a focus on improving the accuracy of existing codes. Analyzing 198 deep beams imported from 15 existing investigations, this study considers various parameters such as concrete compressive strength (f′_c), the shear span-to-effective depth ratio (a_v/d), and reinforcement ratios (p_s, p_v, and p_h). Introducing a novel predictive empirical equation, this study conducts a rigorous evaluation using statistical metrics and a linear regression analysis (MAE, RMSE, and R²). The proposed model demonstrates a significant reduction in the coefficient of variation (CV) to 27.08%, compared to the existing codes’ limitations. Comparative analyses highlight the accuracy of the empirical equation, revealing an improved convergence of data points and minimal sensitivity to variations in key parameters. The results proved that the proposed empirical equation enhanced the accuracy to predict the shear strength capacity of the reinforced concrete deep beams in various scenarios, making it a valuable tool for structural engineers. This research contributes to advancing the understanding of shear strength capacity in reinforced concrete deep beams, offering a reliable empirical equation with implications for refining design methodologies and enhancing safety with the efficiency of structural systems. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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20 pages, 3172 KiB

Open AccessArticle

Machine Learning and Signal Processing for Bridge Traffic Classification with Radar Displacement Time-Series Data

by Matthias Arnold and Sina Keller

Infrastructures 2024, 9(3), 37; https://doi.org/10.3390/infrastructures9030037 - 22 Feb 2024

Viewed by 1235

Abstract

This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. [...] Read more.

This paper introduces a novel nothing-on-road (NOR) bridge weigh-in-motion (BWIM) approach with deep learning (DL) and non-invasive ground-based radar (GBR) time-series data. BWIMs allow site-specific structural health monitoring (SHM) but are usually difficult to attach and maintain. GBR measures the bridge deflection contactless. In this study, GBR and an unmanned aerial vehicle (UAV) monitor a two-span bridge in Germany to gather ground-truth data. Based on the UAV data, we determine vehicle type, lane, locus, speed, axle count, and axle spacing for single-presence vehicle crossings. Since displacement is a global response, using peak detection like conventional strain-based BWIMs is challenging. Therefore, we investigate data-driven machine learning approaches to extract the vehicle configurations directly from the displacement data. Despite a small and imbalanced real-world dataset, the proposed approaches classify, e.g., the axle count for trucks with a balanced accuracy of 76.7% satisfyingly. Additionally, we demonstrate that, for the selected bridge, high-frequency vibrations can coincide with axles crossing the junction between the street and the bridge. We evaluate whether filtering approaches via bandpass filtering or wavelet transform can be exploited for axle count and axle spacing identification. Overall, we can show that GBR is a serious contender for BWIM systems. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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24 pages, 8021 KiB

Open AccessArticle

The “M and P” Technique for Damage Identification in Reinforced Concrete Bridges

by Athanasios Bakalis, Triantafyllos Makarios and Vassilis Lekidis

Infrastructures 2024, 9(2), 18; https://doi.org/10.3390/infrastructures9020018 - 25 Jan 2024

Viewed by 1487

Abstract

The seismic damage in reinforced concrete bridges is identified in this study using the “M and P” hybrid technique initially developed for planar frames, where M signifies “Monitoring” and P denotes “Pushover analysis”. The proposed methodology involves a series of pushover [...] Read more.

The seismic damage in reinforced concrete bridges is identified in this study using the “M and P” hybrid technique initially developed for planar frames, where M signifies “Monitoring” and P denotes “Pushover analysis”. The proposed methodology involves a series of pushover and instantaneous modal analyses with a progressively increasing target deck displacement along the longitudinal direction of the bridge. From the results of these analyses, the diagram of the instantaneous eigenfrequency of the bridge, ranging from the health state to near collapse, is plotted against the inelastic seismic deck displacement. By pre-determining the eigenfrequency of an existing bridge along its longitudinal direction through “monitoring and frequency identification”, the target deck displacement corresponding to the damage state can directly be found from this diagram. Subsequently, the damage can be identified by examining the results of the pushover analysis at the step where the target deck displacement is indicated. The effectiveness of this proposed technique is evaluated in the context of straight multiple span bridges with unequal pier heights, illustrated through an example of a four-span bridge. The findings demonstrate that the damage potential in bridge piers can be successfully identified by combining the results of a monitoring process and pushover analysis. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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16 pages, 9253 KiB

Open AccessArticle

Deep Learning-Based Steel Bridge Corrosion Segmentation and Condition Rating Using Mask RCNN and YOLOv8

by Zahra Ameli, Shabnam Jafarpoor Nesheli and Eric N. Landis

Infrastructures 2024, 9(1), 3; https://doi.org/10.3390/infrastructures9010003 - 20 Dec 2023

Cited by 1 | Viewed by 2499

Abstract

The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application of convolutional neural networks (CNNs) for [...] Read more.

The application of deep learning (DL) algorithms has become of great interest in recent years due to their superior performance in structural damage identification, including the detection of corrosion. There has been growing interest in the application of convolutional neural networks (CNNs) for corrosion detection and classification. However, current approaches primarily involve detecting corrosion within bounding boxes, lacking the segmentation of corrosion with irregular boundary shapes. As a result, it becomes challenging to quantify corrosion areas and severity, which is crucial for engineers to rate the condition of structural elements and assess the performance of infrastructures. Furthermore, training an efficient deep learning model requires a large number of corrosion images and the manual labeling of every single image. This process can be tedious and labor-intensive. In this project, an open-source steel bridge corrosion dataset along with corresponding annotations was generated. This database contains 514 images with various corrosion severity levels, gathered from a variety of steel bridges. A pixel-level annotation was performed according to the Bridge Inspectors Reference Manual (BIRM) and the American Association of State Highway and Transportation Officials (AASHTO) regulations for corrosion condition rating (defect #1000). Two state-of-the-art semantic segmentation algorithms, Mask RCNN and YOLOv8, were trained and validated on the dataset. These trained models were then tested on a set of test images and the results were compared. The trained Mask RCNN and YOLOv8 models demonstrated satisfactory performance in segmenting and rating corrosion, making them suitable for practical applications. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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16 pages, 8284 KiB

Open AccessArticle

Evaluation of the Szapáry Long-Span Box Girder Bridge Using Static and Dynamic Load Tests

by Marame Brinissat, Richard Paul Ray and Rajmund Kuti

Infrastructures 2023, 8(5), 91; https://doi.org/10.3390/infrastructures8050091 - 09 May 2023

Cited by 4 | Viewed by 1343

Abstract

This paper presents the results of a recent field test carried out before the opening phases of the Szapáry motorway bridge across the Tisza River in central Hungary. The evaluation test was based on static and dynamic load tests that provided information on [...] Read more.

This paper presents the results of a recent field test carried out before the opening phases of the Szapáry motorway bridge across the Tisza River in central Hungary. The evaluation test was based on static and dynamic load tests that provided information on deflection, stresses, and dynamic mode shapes along the bridge. The structure has two large continuous independent steel box girders that cover spans across the floodplain and river. Various configurations of truck loading applied up to 6400 kN of loading on the deck. During the static tests, string potentiometers recorded deflections at mid-span. Additionally, strain gauges enabled strain/stress measurements at the mid-point of the longest span and directly above one support. Dynamic loadings showed variation in deflection response due to vehicle speed, and ambient vibration testing led to determining vibration modes and frequencies. A three-dimensional finite-element model produced similar deflections, stresses, and modal behavior. Measured and modeled deflections and stresses indicated that the bridge performed within design margins. The testing and analysis results will be part of a future program assessing conditioned-based maintenance. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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17 pages, 7050 KiB

Open AccessArticle

Study on Deflection-Span Ratio of Cable-Stayed Suspension Cooperative System with Single-Tower Space Cable

by Lin Xiao, Yaxi Huang and Xing Wei

Infrastructures 2023, 8(3), 62; https://doi.org/10.3390/infrastructures8030062 - 22 Mar 2023

Cited by 2 | Viewed by 1870

Abstract

This study uses the wind–vehicle–bridge coupling vibration analysis method to investigate the bridge stiffness problem of a large-span cable-stayed-suspension cooperative system. On the basis of the particle-damping-spring vehicle model, the TMeasy surface contact tire model is introduced, and a set of universal wind–vehicle–bridge [...] Read more.

This study uses the wind–vehicle–bridge coupling vibration analysis method to investigate the bridge stiffness problem of a large-span cable-stayed-suspension cooperative system. On the basis of the particle-damping-spring vehicle model, the TMeasy surface contact tire model is introduced, and a set of universal wind–vehicle–bridge coupling analysis algorithm is built in the framework of the whole process iterative method. Based on the Latin supercube sampling principle, random traffic flow is generated and loaded onto bridge structures with different stiffness conditions to analyze the driving comfort and safety under each stiffness condition. Combining the specification requirements, engineering experience, and research results, the vertical stiffness limit applicable to the bridge of the highway cable-stayed-suspension collaborative system is proposed. Existing engineering experience shows that the vertical deflection-to-span ratio of a cable-stayed bridge under live load is distributed between 1/400 and 1/1600, and the vertical deflection span ratio under the action of lane load is recommended based on numerical analysis. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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23 pages, 9026 KiB

Open AccessArticle

Micro-Scale Experimental Approach for the Seismic Performance Evaluation of RC Frames with Improper Lap Splices

by Ali Javed, Chaitanya Krishna, Khawaja Ali, Muhammad Faheem Ud Din Afzal, Armin Mehrabi and Kimiro Meguro

Infrastructures 2023, 8(3), 56; https://doi.org/10.3390/infrastructures8030056 - 15 Mar 2023

Cited by 10 | Viewed by 1690

Abstract

Reinforced concrete (RC) frames are an integral part of modern construction as they resist both gravity and lateral loads in beams and columns. However, the construction methodologies of RC frames are vulnerable to non-engineering defects, particularly in developing countries. The most common non-engineering [...] Read more.

Reinforced concrete (RC) frames are an integral part of modern construction as they resist both gravity and lateral loads in beams and columns. However, the construction methodologies of RC frames are vulnerable to non-engineering defects, particularly in developing countries. The most common non-engineering defect occurs due to improper lap splice, which can compromise the structural integrity. This research demonstrates an easy, low-cost, and verifiable experimental technique incorporating micro-concrete to evaluate the seismic performance of a completely engineered RC frame with the defect of improper lap splice. The micro-concrete was prepared by using the locally available material for a target compressive strength and then two scaled-down RC frames (1/16 scale) were prepared, including one proper frame and another with improper lap splice. Finally, these frames were tested on a shake table to study their behavior under various seismic loading conditions. This study quantifies the severity of high-risk structural systems due to non-engineering defects. The experimental results demonstrate that improper lap splice can alter the frame’s damage points, triggering the failure of the whole structure. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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Review

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36 pages, 1992 KiB

Open AccessReview

Operational Modal Analysis on Bridges: A Comprehensive Review

by Hamed Hasani and Francesco Freddi

Infrastructures 2023, 8(12), 172; https://doi.org/10.3390/infrastructures8120172 - 04 Dec 2023

Cited by 2 | Viewed by 2269

Abstract

Structural health monitoring systems have been employed throughout history to assess the structural responses of bridges to both natural and man-made hazards. Continuous monitoring of the integrity and analysis of the dynamic characteristics of bridges offers a solution to the limitations of visual [...] Read more.

Structural health monitoring systems have been employed throughout history to assess the structural responses of bridges to both natural and man-made hazards. Continuous monitoring of the integrity and analysis of the dynamic characteristics of bridges offers a solution to the limitations of visual inspection approaches and is of paramount importance for ensuring long-term safety. This review article provides a thorough, straightforward examination of the complete process for performing operational modal analysis on bridges, covering everything from data collection and preprocessing to the application of numerous modal identification techniques in both the time and frequency domains. It also incorporates advanced methods to address and overcome challenges encountered in previous approaches. The paper is distinguished by its thorough examination of various methodologies, highlighting their specific advantages and disadvantages, and providing concrete illustrations of their implementation in practical settings. Full article

(This article belongs to the Special Issue Structural Health Monitoring and Performance Evaluation of Bridges and Structural Elements)

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