Advances on Structural Engineering, 3rd Edition

Topic Information

Dear Colleagues,

Structural engineering is centered on the analysis, design, and evaluation of engineering structures. This topic reports key findings from unpublished studies on advances and applications in all structural engineering fields. As we are aware of the comprehensiveness of the suggested topic, we encourage you to send manuscripts containing scientific findings within the broad field of structural engineering, which includes but is not limited to the following:

• structural analysis and design;
• bridge engineering;
• building assessment;
• earthquake engineering;
• wind engineering;
• impact engineering;
• reliability evaluation;
• structural monitoring;
• image analysis;
• noncontact sensors;
• control structures;
• multi-hazard simulation;
• computational analysis;
• lab and field testing;
• multiscale analysis;
• smart structures;
• disaster mitigation;
• big data evaluation.

Both theoretical and practice-oriented papers, including case studies and reviews, are encouraged.

Prof. Dr. Jong Wan Hu
Dr. Junwon Seo
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Mechanics applmech	-	2.3	2020	23.1 Days	CHF 1200	Submit
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400	Submit
Buildings buildings	3.1	3.4	2011	15.3 Days	CHF 2600	Submit
CivilEng civileng	-	2.8	2020	24.4 Days	CHF 1200	Submit
Infrastructures infrastructures	2.7	5.2	2016	17.8 Days	CHF 1800	Submit

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Published Papers (3 papers)

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All Applied Mechanics Applied Sciences Buildings CivilEng Infrastructures

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23 pages, 3932 KiB  

Open AccessArticle

A Predictive Model for the Shear Capacity of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers Using a Hybrid ANN-ANFIS Algorithm

by Hossein Mirzaaghabeik, Nuha S. Mashaan and Sanjay Kumar Shukla

Appl. Mech. 2025, 6(2), 27; https://doi.org/10.3390/applmech6020027 - 4 Apr 2025

Viewed by 93

Abstract

Ultra-high-performance concrete (UHPC) has attracted considerable attention from both the construction industry and researchers due to its outstanding durability and exceptional mechanical properties, particularly its high compressive strength. Several factors influence the shear capacity of UHPC deep beams, including compressive strength, the shear [...] Read more.

Ultra-high-performance concrete (UHPC) has attracted considerable attention from both the construction industry and researchers due to its outstanding durability and exceptional mechanical properties, particularly its high compressive strength. Several factors influence the shear capacity of UHPC deep beams, including compressive strength, the shear span-to-depth ratio (λ), fiber content (FC), vertical web reinforcement (ρ_sv), horizontal web reinforcement (ρ_sh), and longitudinal web reinforcement (ρ_s). Considering these factors, this research proposes a novel hybrid algorithm that combines an adaptive neuro-fuzzy inference system (ANFIS) with an artificial neural network (ANN) to predict the shear capacity of UHPC deep beams. To achieve this, ANN and ANFIS algorithms were initially employed individually to predict the shear capacity of UHPC deep beams using available experimental data for training. Subsequently, a novel hybrid algorithm, integrating an ANN and ANFIS, was developed to enhance prediction accuracy by utilizing numerical data as input for training. To evaluate the accuracy of the algorithms, the performance metrics R² and RMSE were selected. The research findings indicate that the accuracy of the ANN, ANFIS, and the hybrid ANN-ANFIS algorithm was observed as R² = 0.95, R² = 0.99, and R² = 0.90, respectively. This suggests that despite not using experimental data as input for training, the ANN-ANFIS algorithm accurately predicted the shear capacity of UHPC deep beams, achieving an accuracy of up to 90.90% and 94.74% relative to the ANFIS and ANN algorithms trained on experimental results. Finally, the shear capacity of UHPC deep beams predicted using the ANN, ANFIS, and the hybrid ANN-ANFIS algorithm was compared with the values calculated based on ACI 318-19. Subsequently, a novel reliability factor was proposed, enabling the prediction of the shear capacity of UHPC deep beams reinforced with fibers with a 0.66 safety margin compared to the experimental results. This indicates that the proposed model can be effectively employed in real-world design applications. Full article

(This article belongs to the Topic Advances on Structural Engineering, 3rd Edition)

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26 pages, 3014 KiB  

Open AccessReview

Shear Behavior of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers: A State-of-the-Art Review

by Hossein Mirzaaghabeik, Nuha S. Mashaan and Sanjay Kumar Shukla

Infrastructures 2025, 10(3), 67; https://doi.org/10.3390/infrastructures10030067 - 20 Mar 2025

Viewed by 210

Abstract

Ultra-high-performance concrete (UHPC) is considered a highly applicable composite material due to its exceptional mechanical properties, such as high compressive strength and ductility. UHPC deep beams are structural elements suitable for short spans, transfer girders, pile caps, offshore platforms, and bridge applications where [...] Read more.

Ultra-high-performance concrete (UHPC) is considered a highly applicable composite material due to its exceptional mechanical properties, such as high compressive strength and ductility. UHPC deep beams are structural elements suitable for short spans, transfer girders, pile caps, offshore platforms, and bridge applications where they are designed to carry heavy loads. Several key factors significantly influence the shear behavior of UHPC deep beams, including the compressive strength of UHPC, the vertical web reinforcement (ρ_sv), horizontal web reinforcement (ρ_sh), and longitudinal reinforcement (ρ_s), as well as the shear span-to-depth ratio (λ), fiber type, fiber content (FC), and geometrical dimensions. In this paper, a comprehensive literature review was conducted to evaluate factors influencing the shear behavior of UHPC deep beams, with the aim of identifying research gaps and enhancing understanding of these influences. The findings from the literature were systematically classified and analyzed to clarify the impact and trends associated with each factor. The analyzed data highlight the effect of each factor on the shear behavior of UHPC deep beams, along with the overall trends. The findings indicate that an increase in compressive strength, FC, ρ_sv, ρ_s, and ρ_sh can enhance the shear capacity of UHPC-DBs by up to 63.36%, 63.24%, 38.14%, 19.02%, and 38.14%, respectively. Additionally, a reduction of 61.29% in λ resulted in a maximum increase of 49.29% in the shear capacity of UHPC-DBs. Full article

(This article belongs to the Topic Advances on Structural Engineering, 3rd Edition)

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21 pages, 13440 KiB  

Open AccessArticle

Dynamic Adaptability of Spherical Bearings in Small-Span Bridges for Heavy-Haul Railways

by Shuli Chen, Ye Zhou, Kaize Xie, Panhui Zhang and Chen Li

Buildings 2025, 15(4), 619; https://doi.org/10.3390/buildings15040619 - 17 Feb 2025

Viewed by 348

Abstract

Plate bearings in existing small-span bridges for heavy-haul railways have exhibited corrosion, detachment, and surface cracks under large axle loads, making them inadequate for the “capacity expansion and renovation” of heavy-haul railways. Therefore, identifying new bearings suitable for small-span bridges and developing a [...] Read more.

Plate bearings in existing small-span bridges for heavy-haul railways have exhibited corrosion, detachment, and surface cracks under large axle loads, making them inadequate for the “capacity expansion and renovation” of heavy-haul railways. Therefore, identifying new bearings suitable for small-span bridges and developing a rapid bearing replacement method tailored to the operational needs of heavy-haul railways are urgent priorities. This paper takes spherical bearings as an example and proposes a method for rapidly replacing plate bearings with spherical bearings. The bearing replacement tests of six simply supported beams were carried out to verify the effectiveness of the proposed method. Dynamic performance tests of bridges and bearings were performed before and after the replacement. A finite element model was established to analyze the effects of bridge span and pier height. The results show that the entire bearing replacement process for a span bridge could be completed within 4 h using the proposed method. Compared to plate bearings, spherical bearings could improve the lateral dynamic performance of both the bridge and bearings. However, the improvement decreases as bridge span and pier height increase. For 2.2 m diameter cylindrical piers commonly used in heavy-haul railways, the pier height with spherical bearings should be limited to 10 m. Full article

(This article belongs to the Topic Advances on Structural Engineering, 3rd Edition)

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