Structural Engineering Practice Research Articles

Numerical simulation of the vortex-induced vibrations of a 4:1 rectangular cylinder subjected to yaw uniform currents

The practical engineering structures are not always perpendicular to the wind but often in skew positions. This yawed configuration may lead to more complex three-dimensional flow characteristics and different vortex-induced vibration (VIV) responses. However, the related study is very inadequate. Therefore, comprehensive numerical investigations of the VIV characteristics of a 4:1 rectangular cylinder have been conducted using the three-dimensional (3D) Large-Eddy Simulation (LES) at five different yaw angles (β = 0°, 5°, 10°, 20°, 30°). An innovative method for creating 3D meshes was introduced, demonstrating a good agreement with the experimental results while significantly reducing the mesh number, and consequently the computation time. The VIV response, pressure distribution, aerodynamic force, flow field, and energy input/output were analyzed for various yaw angles. The results demonstrate that the periodic boundary conditions on the spanwise domain side is more reliable than those of the wall boundary conditions. The velocity component parallel to the cylinder axis can be ignored in the analysis of elastically-mounted rectangular rigid cylinders for β up to 30°. If only considering the perpendicular axis velocity component, the amplitudes and lock-in regions for β = 5°, 10°, 20°, and 30° are highly consistent with those of β = 0°, which have effectively validated the accuracy of Independence Principle in evaluating the VIV of a 4:1 rectangular cylinder.

End-rotation-driven kinetic elastica structures: Concept and morphology design

Euler’s elastica, a family of planar curves describing the equilibrium shapes of a thin elastic beam subjected to end forces and moments, demonstrates both geometric versatility and mechanical functionality, leading to its diverse applications across multiple disciplines. Despite its roots in ancient structural engineering practices, the kinetic potential of Euler’s elastica remains largely unexplored in this domain. To address this gap, this paper proposes the concept of end-rotation-driven kinetic elastica (ERKE) structures. This novel kinetic form consists of a sequence of discrete elastica arches transformed from initially straight members by elastic bending. The kinetic behavior arises from manipulating the end rotations of each elastica arch, prompting a continuous flow of motions resulting from adaptations in the arch shape. This adaptive quality opens up limitless possibilities for creating visually captivating dynamic patterns in the overall structure by coordinating the motions of individual arches. As the inaugural exploration of ERKE structures, this paper centers around their conceptualization, with an emphasis on morphology design, which refers to the creation of desirable dynamic patterns. To this end, the paper provides an exposition of the general design procedure and criteria, along with demonstrative examples. The paper also envisions potential application scenarios and identifies research needs, paving the way for future investigations.

Solutions of crack constraint parameter in 3D models −− II: Through T-stress

To more accurately analyze the crack front fields, especially under the low constraint conditions which are more common in practical engineering structures, two-parameter approaches (e.g. J-A(A2), J-Q, etc.) are proposed. Currently, no theoretical solutions of the constraint parameters (e.g. A(A2), Q, etc.) in two-parameter approaches are available. Meanwhile, numerical methods for constraint parameter determination are not practical because of significant resource and time consumption, especially for 3D solid models or engineering structures. Therefore, theory and formulae for the estimation of constraint parameter A in 3D solid models are developed in the current work based on T-stress, so as to make it possible to apply two-parameter approaches in practical engineering structures under normal working condition. Two actual structures are used to validate the engineering application of the developed estimate method and formulae.

COMPARATIVE STUDY OF STEEL CONNECTION USING US AND IS CODE ON TEKLA STRUCTURE

This paper presents a comprehensive comparative study of steel connections implemented in Tekla Structures software, employing both the US and IS (Indian Standards) codes. The investigation focuses on analyzing the differences in design criteria, detailing requirements, and fabrication practices between the two codes. Specifically, the study explores variations in bolt sizing, beam and column dimensions, as well as detailing specifications for bolted connections. Through detailed examination and comparison, significant disparities are identified, highlighting the importance of adhering to specific standards to ensure structural integrity and compatibility in construction projects. Additionally, the study addresses the implications of these differences on material estimation, cost evaluation, and overall project outcomes. By providing insights into the utilization of US and IS codes within Tekla Structures, this research contributes to enhancing the understanding and implementation of international standards in structural engineering practices. Keyword- Tekla Structure, Steel Structure, Us and Is Codes

Efficient Sizing and Layout Optimization of Truss Benchmark Structures Using ISRES Algorithm

This paper presents a comprehensive investigation into the application of the Improved Stochastic Ranking Evolution Strategy (ISRES) algorithm for the sizing and layout optimization of truss benchmark structures. Truss structures play a crucial role in engineering and architecture, and optimizing their designs can lead to more efficient and cost-effective solutions. The ISRES algorithm, known for its effectiveness in multi-objective optimization, is adapted for the single-objective optimization of truss designs with multiple design constraints. This study encompasses a wide range of truss benchmark structures, including 10-bar, 15-bar, 18-bar, 25-bar, and 72-bar configurations, each subjected to distinct loading conditions and stress constraints. The objective is to minimize the truss weight while ensuring stress and displacement limits are met. Through extensive experimentation, the ISRES algorithm demonstrates its ability to efficiently explore the solution space and converge to optimal solutions for each truss benchmark structure. The algorithm effectively handles the complexity of the problems, which involve numerous design variables, stress constraints, and nodal displacement limits. A comparative analysis is conducted to assess the performance of the ISRES algorithm against other state-of-the-art optimization methods reported in the literature. The comparison evaluates the quality of the solutions and the computational efficiency of each method. Furthermore, the optimized truss designs are subjected to finite element analysis to validate their structural integrity and stability. The verification process confirms that the designs adhere to the imposed constraints, ensuring the safety and reliability of the final truss configurations. The results of this study demonstrate the efficacy of the ISRES algorithm in providing practical and reliable solutions for the sizing and layout optimization of truss benchmark structures. The algorithm’s competitive performance and robustness make it a valuable tool for structural engineers and designers, offering a versatile and powerful approach for complex engineering optimization tasks. Overall, the findings contribute to the advancement of optimization techniques in structural engineering, promoting the development of more efficient and cost-effective truss designs for a wide range of engineering and architectural applications. The study’s insights empower practitioners to make informed decisions in selecting appropriate optimization strategies for complex truss-design scenarios, fostering advancements in structural engineering and sustainable design practices.

Damage Identification of Full-Scale Steel Truss Structure Based on Model Condensation and Mean-Value Normalization Regularization Techniques

Structural health monitoring and damage identification aim to detect the internal damage and evaluate the health conditions of the practical engineering structure, which has been the most popular research field for several decades. The sensitivity-based method incorporated with the regularization techniques is the classical and useful approach, and it can obtain accurate damage detection results. However, with the development of civil engineering structures, this classical method faces two problems: one is it is only applied to simple structures rather than full-scale structures, and second is the iterative calculation efficiency is lower. Therefore, aiming at these drawbacks, the two improvement strategies have been introduced to the original method for its enhancement in the application potential and computational efficiency. The proposed method has been verified based on two examples, i.e., a numerical steel truss with 144 elements and a full-scale experimental steel truss with 160 elements. The results prove that the proposed method has better efficiency and good application potential in the practical full-scale engineering structure.

Prediction of Torque Capacity in Circular Concrete-Filled Double-Skin Tubular Members under Pure Torsion via Machine Learning and Shapley Additive Explanations Interpretation

The prediction of torque capacity in circular Concrete-Filled Double-Skin Tubular (CFDST) members under pure torsion is considered vital for structural design and analysis. In this study, torque capacity is predicted using machine learning (ML) algorithms, such as Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Random Forest (RF), and Decision Tree (DT), which are employed. The interpretation of the results is conducted using Shapley Additive Explanations (SHAPs). The performance of these ML models is evaluated against two traditional analytical formulas that have been proposed and are available in the literature. Through comprehensive analysis, it is shown that superior predictive capabilities are possessed by the CatBoost and XGBoost models, characterized by high R2 values and minimal mean errors. Additionally, insights into the influence of input features are provided by SHAP interpretation, with an emphasis on key parameters such as concrete compressive strength and steel tube dimensions. The gap between empirical models and ML techniques is bridged by this study, offering engineers a more accurate and efficient tool for CFDST structural design. Significant implications for optimizing CFDST column designs and advancing structural engineering practices are presented by these findings. Directions for future research include the further refinement of ML models and the integration of probabilistic analyses for enhanced structural resilience. Overall, the transformative potential of ML and SHAP interpretation in advancing the field of structural engineering is showcased by this study.

Development of methods of structural reliability

The growth of structural reliability theory and applications, along with a recognition of its role in guiding the structural engineering profession in addressing some of the most important issues in design of the built environment, represents one of the key engineering achievements during the past five decades. Structural reliability provides a unifying framework for managing uncertainties affecting performance of structures and a quantitative link between the practice of structural engineering and its social consequences. Such links perhaps are most obvious in probability-based codified design and performance evaluation but there are numerous other applications, which are summarized in this special issue. As the field has matured, researchers in reliability have worked with structural engineers to elevate both the practice of structural engineering and the quality of research to levels that otherwise would not have been possible. The Joint Committee on Structural Safety has played a central role in this historic development and it will inspire future opportunities for the reliability community to build upon past successes to improve structural engineering and construction practices. This paper surveys the key theoretical developments and milestones that enable these opportunities.

Experimental and numerical investigation of through-diaphragm in H-shaped steel beam to CFST column connections

This research proposes a cruciform through-diaphragm (CTD) for an H-shaped steel beam to concrete-filled steel tubular (CFST) column and investigates its seismic performance experimentally and numerically. The proposed connection consists of through-plates passing through the aligned slots in the panel zone and end plates directly welded to an H-shaped steel beam. This connection eliminates welding inside the steel tube for installation of the diaphragm, while providing a reliable load path from the steel beam to the CFST column. The experimental program examined the connection hysteretic behaviors, including the moment-rotation response, ductility, initial stiffness, and energy dissipation capacity. The proposed connection shows stable hysteric behavior and good energy dissipation up to a story drift up to 4 % and satisfies the AISC seismic provisions criteria for special moment connection. A finite element (FE) model was established and verified against the experimental results. The effects of concrete infill, steel tube column thickness, axial load ratio, and through-plate thickness on the hysteretic behavior of the proposed connection were investigated through parametric analysis of 24 FE models. This study provides the information on the optimized design parameters that ensures the stable seismic performance of the proposed connection that could be used in structural engineering practice.

Wavelet denoising based on comprehensive index optimization and improved L2 regularization for load identification

Load identification, as an inverse problem, is still one of the challenges in the field of vibration engineering. In this paper, a comprehensive load identification method combining entropy weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) noise reduction evaluation algorithm and improved L2 regularization method is proposed to improve the load identification accuracy from the following two perspectives. Firstly, the entropy weight TOPSIS method is used to evaluate the wavelet denoising scheme comprehensively, and the optimal denoising scheme is found to reduce the noise interference in the process of inverse problem solving. Secondly, we introduce a new regularization filter function, and search for the regularization parameters by Generalized Cross-Validation (GCV) criterion and one-dimensional optimization algorithm to improve the ill-posedness of the inverse problem. Finally, the simulation and experimental verification of single-source load identification are carried out with the scaled crankcase model, while the accuracy is compared with the Tikhonov regularization method. The results show that the integrated algorithm proposed in this paper can improve the accuracy of load identification while overcoming the inadequacy of inverse problem. Unlike previous studies, the comprehensive evaluation method of denoising effect introduced in this paper provides a way to judge the denoising effect in practical engineering, and the experimental model is closer to practical engineering structures, which shows potential engineering application value.

The Practice of Forensic Structural Engineering in IABSE's Member Countries

The IABSE Task Group 5.1 on Forensic Structural Engineering aims to examine and to mitigate structural failures by sharing knowledge of technical, human and organizational causes of failure, in addition to methods and techniques in forensic investigation processes. Forensic engineering expertise has yet to be recognized worldwide as a specific domain of civil engineering practice, and this paper amends previously published technical reports in 2012, 2014 and 2015 by former IABSE Working Group 8 following a new survey carried out in 2020–2022. This new survey has been developed with the lessons learnt from the previous survey in 2013–2014, including the validation of the results obtained by eliminating potential subjectivity in the former assessment. This survey also includes further understanding of the institutional and national regulatory framework. The survey was completed by 22 IABSE member countries whose responses were provided by national experts on forensic structural engineering. This paper will allow the reader to familiarize him/herself with the state of the art in forensic structural engineering practice across 22 countries, allowing a national-level diagnosis. The survey will also help to identify the main challenges within each country related to forensic engineering. Furthermore, recommended steps, as suggested by the national experts, for the awareness and/or development of good industry practice within forensic structural engineering are highlighted in this paper. Online supplemental data for this article can be accessed at https://doi.org/10.1080/10168664.2024.2307411.

Data-driven estimates of the strength and failure modes of CFRP-steel bonded joints by implementing the CTGAN method

The bond strength between the CFRP and steel usually dominates the final strengthened effectiveness. However, the CFRP-steel bond strength is affected by various geometric and material properties and exhibits different failure modes, making accurate predictions challenging. This study utilises data-driven machine learning (ML) methods to predict the strength and failure modes of CFRP-steel joints. An experimental dataset consisting of 178 single-lap shear test results was first built, after which the Conditional Tabular Generative Adversarial Networks (CTGAN) method was applied to augment the limited available data. Four broadly used ML algorithms: Support Vector Machines (SVM), K-Nearest Neighbours (KNN), Decision Trees (DT) and Artificial Neural Networks (ANN) were applied. The ANN regression model achieved the best performance in predicting joint strength (Rtest2=0.95), while the SVM classification model achieved the best performance in predicting failure modes (accuracy ≥ 92.3 %). The SHapley Additive exPlanations analysis further revealed that the Young's modulus of the adhesive was most significant to the joint strength, while the tensile strength of the adhesive was most significant to the failure modes. The ultimately constructed ML models and the corresponding analyses presented can benefit practical structural engineering applications and provide insights into the optimal CFRP-steel joint design.

Continuous adsorption of Metanil Yellow and Remazol Black B dyes onto fixed-bed of 3D graphene oxide/chitosan biopolymer

Treatment of dye polluted water using sustainable and efficient approaches is essential to mitigate the detrimental effects of dyes. The present work reports on the adsorption effectiveness of a graphene-based adsorbent configured into a practical engineering structure, namely three-dimensional graphene oxide integrated with chitosan biopolymer (3D-GCB). This unique graphene configuration enabled its application in continuous fixed-bed adsorption of Metanil Yellow (MY) and Remazol Black B (RBB) dyes from polluted water for the first time. The breakthrough attributes of the fixed-bed of 3D-GCB were established in terms of bed depth (3 – 5 cm), influent concentration (100 – 200 mg/L for MY and 100 – 300 mg/L for RBB) and feed flowrate (2 – 4 mL/min). The greatest bed adsorption capacities attained were 157.06 and 247.96 mg/g for MY and RBB, respectively. The column parameters for obtaining these results were 5 cm bed depth, 2 mL/min feed flowrate, and 150 and 200 mg/L influent concentrations respectively for MY and RBB. The fixed-bed performance of the 3D-GCB was well correlated to the Thomas and Yoon-Nelson models, and the corresponding kinetic properties were determined. Furthermore, the higher affinity of the 3D-GCB for RBB as compared to MY was elucidated based on the ionic strengths of the dye molecule. The utilisation of sustainable and renewable raw materials, such as graphite and chitosan, have resulted in a 3D-GCB production cost of approximately RM 10.72 per gram. This work revealed the suitability of 3D-GCB as the state-of-the-art graphene composite for continuous adsorption of anionic dyes, specifically MY and RBB.

Integrated behavioural analysis of FRP-confined circular columns using FEM and machine learning

This study investigates the structural behaviour of double-skin columns, introducing novel double-skin double filled tubular (DSDFT) columns, which utilise double steel tubes and concrete to enhance the load-carrying capacity and ductility beyond conventional double-skin hollow tubular (DSHT) columns, employing a combination of finite element model (FEM) and machine learning (ML) techniques. A total of 48 columns (DSHT+DSDFT) were created to examine the impact of various parameters, such as double steel tube configurations, thickness of fibre-reinforced polymer (FRP) layer, type of FRP material, and steel tube diameter, on the load-carrying capacity and ductility of the columns. The results were validated against the experimental findings to ensure their accuracy. Key findings highlight the advantages of the DSDFT configuration. Compared to the DSHT columns, the DSDFT columns exhibited remarkable 19.54 % to 101.21 % increases in the load-carrying capacity, demonstrating improved ductility and load-bearing capabilities. Thicker FRP layers enhanced the load-carrying capacity up to 15 %, however at the expense of the reduced axial strain. It was also observed that glass FRP wrapping displayed 25 % superior ultimate axial strain than aramid FRP wrapping. Four different ML models were assessed to predict the axial load-carrying capacity of the columns, with long short-term memory (LSTM) and bidirectional LSTM models emerging as superior choices indicating exceptional predictive capabilities. This interdisciplinary approach offers valuable insights into designing and optimising confined column systems. It sheds light on both double-tube and single-tube configurations, propelling advancements in structural engineering practices for new constructions and retrofitting. Further, it lays out a blueprint for maximising the performance of the confined columns under the axial compression.

Pertinent Emplacement of Shear Walls to Diminish the Torsional Effects in Asymmetric-RC Framed Buildings

In seismic conditions, asymmetric structures typically experience lateral deflection. The magnitude of this deflection is dependent on various factors, including the configuration of the structural system, the mass of the structure, and the mechanical properties of the materials used. One critical factor that can reduce a structure's seismic resistance is torsion irregularity. To combat this, shear walls can be installed in the pertinent location to provide stability and stiffness to the structure. This study explores the seismic analysis of a G+10 storey asymmetric RC frame-shear wall structure using the response spectrum method as per ASCE7-16. The study encompasses six models with varying shear wall placements, with the initial model lacking a shear wall. The results are compared, and recommendations are made to avoid torsional irregularity destruction under seismic loads. Based on the analysis, Model-2 (shear wall in the periphery) shows the worst condition from the 1st storey through the 11th storey, possibly due to maximum eccentricity in upper storeys. In contrast, Model-5 (shear wall in core and corners) shows the best performance among all models, likely due to increased stiffness in the corners and core of the structure. Overall, this study contributes to the advancement of structural engineering practices by enhancing the understanding of complex interplay between torsional irregularity, shear wall placement, and structural asymmetry.

Multiscale analysis and application of modified PVA fiber reinforced rubber concrete in frame structures

The paper presents a multiscale analysis of PVA fiber-reinforced rubber concrete modified with KH-560. Through a combined approach of experiments and numerical simulations, the feasibility of applying PVA fiber-reinforced rubber concrete in frame structures is validated. Firstly, utilizing molecular dynamics simulations with MS software, the modification effect of KH-560 on PVA fiber material is explored at the molecular level, confirming its ability to effectively enhance the bonding strength between PVA fibers and rubber concrete. Subsequently, a portal frame structure experiment is conducted, validating the actual strength and stiffness of the material through mechanical performance measurements. Lastly, employing Abaqus finite element software, a numerical simulation of the material's application in concrete frame structures is conducted, analyzing its mechanical response and performance in real engineering environments. The research findings indicate that by fully exploiting the deformation characteristics of PVA fiber-reinforced rubber concrete after modification, the use of this material in structural frameworks can maintain or even slightly increase the load-bearing capacity. This study pioneers new prospects for the application of PVA fiber-reinforced rubber concrete in concrete frame structures, providing a more reliable and secure option for structural engineering practice. It offers concrete and innovative solutions for the sustainable development of actual engineering projects.

Unsupervised structural damage assessment method based on response correlations

Structural damage assessment for civil engineering structures has become an important research topic and has gained much attention for decades in the field of structural health monitoring (SHM). Current unsupervised structural damage assessment methods can achieve damage detection for practical civil engineering structures. However, these methods cannot fully mine the response correlations among sensors, thus are difficult to localize damage in practical engineering applications. Therefore, this study proposes an unsupervised structural damage assessment method with bidirectional long short-term memory (BiLSTM) networks to establish the response correlations among sensors. Numerical studies of a beam-like bridge model, an experimental study of Yellow Frame, and an in-field study of Yonghe Bridge were conducted to validate the accuracy and reliability of the proposed approach. The results show that unsupervised structural damage identification and localization can be achieved even in the case of sparse sensor deployment due to the fact that the response correlations among sensors can be well extracted. The proposed approach can be applied to damage identification of practical engineering structures under operational and ambient excitations and can automatically provide damage location warnings to ensure structural health and prevent catastrophic events.

Stress-strain characteristics of autoclaved aerated concrete masonry under varying displacement rates

Comprehending the impact of displacement rate on the mechanical properties of autoclaved aerated concrete (AAC) masonry is critical for predicting the response of structures to seismic and other natural dynamic loads. This study investigates the effect of varying displacement rates (0.1 mm/min, 1 mm/min, and 10 mm/min) on the mechanical properties of AAC masonry under uniaxial compression through systematic laboratory tests. Results indicate a substantial increase in elastic modulus (100 %) and compressive strength (200 %) as displacement rates rise from 0.1 mm/min to 10 mm/min. Finite element analysis using a micro-modelling strategy in Abaqus corroborates experimental findings, simulating crack propagation and identifying stress and strain distribution. The outcomes of this study would facilitate the accurate design and analysis of framed buildings infilled with AAC block masonry, especially under dynamic loading. These findings are expected to significantly contribute to the enhancement of structural engineering practices, enhancing the reliability and effectiveness of AAC block masonry for constructing resilient buildings.

Developing Structural and Civil Engineering (SCE) Curriculum in sub-Sahara African Nations on the Foundation of the Developed Nations, in Training, Practices and Technology – Nigeria as Case Study

The training and practice of structural and civil engineering (SCE) education in developing nations, especially the sub-Sahara African nations, are not as robust and dynamic when compared to what are operating in the developed Nations of the World. Available resources in the public domain show strong evidence of a sustained fundamental link of SCE training and practice of the developed nations to the classical training of the ancient Caesar’s Rome. This paper looks into the training and practice of structural and civil engineering about 2000 years ago in the imperial Caesar’s Rome. The data used were collected from the information available from the public domain. The results showed that: (i) the curriculum for SCE education was very wide and deep and it is in partnership with the State (ii) the training together with the attendant skill development program/schemes began early at Roman home, (iii) SCE is deeply connected to Latin and Greek languages, and (iv) a heavy dependence on classical philosophical studies existed. It is thus concluded that the curriculum for SCE engineering in developing nations be tied to these foundations.

Numerical Modeling of the Geotechnical and Structural Strengthening of Quay Structures with a Case Study

With developments in maritime trade, the need to increase port capacities has emerged. It is important that the reconstruction of such port structures be carried out without disrupting the activities of the existing port and without damaging the old structures. However, the reconstruction and strengthening of these structures require significant engineering work. Especially in the design of such structures, geotechnical and structural engineering theories and practices need to be considered together. The most important challenge in this type of engineering design is to ensure harmony in geotechnical and structural analyses. In this study, the strengthening of a port structure in Guinea is taken as a case study. First, the existing quay wall was evaluated, and then the geotechnical and structural design of the new structure to be built for capacity increase was discussed. A geotechnical design was made with the Plaxis 2D program, and the structural design was made with the Sap2000 program. The soil behavior was analyzed nonlinearly with the Plaxis program and was modeled with the same accuracy as the Sap2000 program. In addition, pile capacities were confirmed by loading tests performed on the piles. The results show that complex hybrid solutions consisting of reinforced and unreinforced piles can be modeled with the finite element method. As seen from this case study, the capacities of existing port structures can be safely increased, provided that necessary geotechnical precautions are taken.