Engineering Structures Research Articles

Prediction of seismic performance of steel frame structures: A machine learning approach

The study of seismic performance in structural engineering is deemed crucial due to the intricate and unpredictable nature of earthquakes. This study explores advanced seismic performance prediction in structural engineering using machine learning techniques. Non-Linear Dynamic Analysis (NDA) was conducted on Steel Moment-Resisting Frames (SMRFs) situated on soil type D in seismic zone II with varying configurations using ETABS software. A substantial dataset comprising 29,200 data points from 292 models was generated to train machine learning models aimed at predicting the Maximum Inter-Story Drift Ratio (M-IDR), a critical parameter for assessing seismic limit-state capacity. The machine learning models, including Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost), and Artificial Neural Networks (ANN), demonstrated high accuracy with R2 of 0.9625, 0.95327, and 0.94247 respectively, indicating a robust correlation between predicted and actual values. These results imply that the trained models can effectively predict seismic performance with high precision. A user-friendly Graphical User Interface (GUI) was developed using the trained models to facilitate the practical application of these models, significantly reducing computational costs and analytical efforts for researchers and engineers. The findings underscore the potential of integrating machine learning with structural engineering to enhance seismic performance predictions, contributing to the development of safer and more resilient structures.

Dynamic characteristics of shape-memory alloy plates immersed in liquid subjected to blast loading

As a critical structure in ship and marine engineering, axially moving shape-memory alloy (SMA) plates may exhibit complex dynamic behaviors. However, there are few studies investigating the dynamic response of SMA plates under underwater blast, let alone consider the effect of initial geometric imperfection and axial motion. Therefore, further studies on such topic are warranted. Based on this, the current paper dedicates to conducting the dynamic research of the geometrically imperfect SMA plate subjected to underwater blast. Firstly, adopting Falk's polynomial constitutive model, the stress strain constitutive relationship of SMA plate can be determined. Secondly, the Hamilton's principle is employed to derive the vibration equation. Thirdly, the assumed mode method and Runge-Kutta technique are applied for solving the dynamic system. After that, several comparative analyses are performed. Finally, the influences of immersed depth, axially moving velocity, initial geometric imperfection, elastic foundation, pulse load type, aspect ratio, length-to-thickness ratio, as well as blast loading parameter on the transient response path are discussed. These findings can contribute to understanding the dynamic behavior of the geometrically imperfect SMA plates immersed in water when subjected to blast loading, and thus providing valuable thinking for the manufacturing and design of submarine equipment.

Electronic Structure Engineering of Transition-Metal-based Electrocatalysts for Water Splitting

Electronic Structure Engineering of Transition-Metal-based Electrocatalysts for Water Splitting

Improved krill swarm algorithm and its application in structural optimization

This paper improves and perfects the standard Krill herd algorithm (KH), which has the defects of slow convergence speed, insufficient calculation accuracy and easy to fall into local optimal solution for complex problems. An improved Krill herd algorithm (SDEKH) integrating improved differential evolution operator and S-type adaptive inertia weight is proposed. SDEKH, KH and other intelligent algorithms are compared and tested through a variety of standard test functions to verify the excellent performance of SDEKH; SDEKH is used to optimize the design of truss structure. By comparing the optimization results with other methods, it is verified that the optimization efficiency and accuracy of SDEKH are improved, which provides a more efficient and accurate method for the optimization design of engineering structures.

Critical lateral‐torsional buckling loads of porous orthotropic rectangular beams containing warping effects

AbstractDue to their elemental porosity, porous materials display individual mechanical properties, rendering them essential components in various engineering applications. So, this study investigates the lateral‐torsional buckling (LTB) sensitivity of porous orthotropic rectangular beams subjected to a concentrated load, including the warping effects. Porosity‐dependent material properties vary along the beam's height via four different porosity distribution patterns. The constitutive equations are obtained using the principle of virtual work based on the classical beam theory containing the warping effect, and the governing equations are solved by performing the Ritz method to obtain the critical LTB load. The porous orthotropic beams and the warping effects add complexity to the analysis. So, the influence of some parameters, such as porosity coefficients, porosity distribution patterns, orthotropy, height‐to‐width ratio, slenderness ratio, and warping coefficients, on the LTB characteristics of porous orthotropic rectangular beams are investigated in detail. The novelty of this study lies in its comprehensive LTB analysis of orthotropic rectangular beams under specific effects, such as porosity and warping factors. The findings offer valuable insights into the LTB characteristics of orthotropic porous beams, contributing to an improved comprehension of their structural behavior and facilitating the design of engineering structures. This study contributes to the composite materials and structural stability analysis, offering potential applications in many engineering domains.

Experimental and numerical investigation of the damage propagation in regularly arrayed short fiber reinforced composite laminates under low‐velocity impact

AbstractThe outstanding mechanical performance and flowability of unidirectionally arrayed chopped strands (UACSs) give them an advantage in the manufacture of engineering structures with complex geometry. For the application of practical structures, the impact responses and damage evolution of material under low‐velocity impact must be investigated in advance. In this study, UACS laminates and continuous carbon fiber laminates with a stacking sequence of [0/90]4s and a thickness of 2 mm were fabricated for low‐velocity impact tests at 7, 11, 15, and 20 J. The impact responses and postimpact intralaminar damage area were analyzed according to the experimental results, including impact load responses and ultrasound C‐scan inspections. Moreover, to predict the damage evolution of the internal structure, the 3D finite element models were constructed in ABAQUS using a progressive damage model (PDM) through a user‐material subroutine VUMAT. Compared with continuous carbon fiber laminates, the dissipated energy of UACS laminates increases by approximately 10.64% and 57.37% for the 15 and 20 J, respectively. However, the intralaminar damage area of UACS laminates decreased by 29.96% and 28.16% at 15 and 20 J, respectively, since the discontinuous slits in UACS laminates can guide damage paths and suppress damage propagation.Highlights The regularly arrayed short fiber reinforced composite was studied. Revealed the low‐velocity impact responses and predicted the damage evolution. UACS and CFRP laminates have comparable impact performance. Illustrated the slits design can suppress the damage to a relatively small area.

Grain Structure Engineering in Screen-Printed Silver Flake-Based Inks for High-Temperature Printed Electronics Applications.

We extensively studied serigraphic screen-printed commercial silver flake inks loaded with silicon inclusions in order to achieve pinning at the grain boundaries. Based on grain size measurements using electron backscattered diffraction (EBSD), commercial silver ink with silicon microparticle content of 5 wt.% shows significant grain growth retardation compared to pristine silver ink, which stabilizes electrical conductivity up to 700 °C via a Zener pinning mechanism. The modified silicon-loaded silver ink experiences a two-times increase in grain size when heated up to 700 °C, compared to a seven-times increase for pristine silver ink. In turn, this enables operation temperatures significantly higher than the conventional operational window of microparticle-based silver inks, which are usually limited to 400 °C. Using isothermal exposures of 10 min up to 4 h, this phenomenon is observed at temperatures ranging from 250 °C to 900 °C. The electrical conductivity stability, grain size evolution and oxide contents were studied up to 4 h. The activation energy of silver ink with silicon inclusions is 54% lower than for pristine silver ink due to the pining effect, which retards grain growth via the Zener mechanism. Most importantly, the electrical resistivity remains stable up to 700 °C, which is more than twice the operation limit for off-the-shelf screen-printable silver flake inks. Hence, we demonstrate that adding controlled amounts of silicon particles to silver inks for grain structure engineering can open new vistas of possibilities for screen-printed metallic inks.

Flexural behaviour and shear capacity of RC flat plate sections during fire exposure

PurposeFire safety is a pivotal requirement in building codes. Prescribed design criteria have been the norm to achieve it, which imposes limitations on engineers, including the inability to accommodate new solutions/materials. The shift towards performance-based design offers the potential to address shortcomings of the prescribed design. However, this shift also significantly increases the workload on structural engineers without a corresponding increase in their engineering fees. Simplified design tools are needed to assist engineers in this transition.Design/methodology/approachThe paper is divided into sections investigating equivalent standard fire duration, thermal deformations, flexural behaviour and shear capacity of flat slabs when exposed to fire. The first section conducts a parametric study correlating equivalent and realistic fire durations using the average internal temperature profile (AITP) method, resulting in statistical equations estimating equivalent fire duration. The second section evaluates thermal deformations and flexural behaviour through a parametric study considering various parameters. This section results in statistical equations estimating thermal deformations and flexural behaviour of flat slab sections during fire exposure. The final section focuses on shear capacity, developing simplified heat transfer formulas and statistical equations predicting compression zone depth reduction. The section presents methodologies predicting flat slab sections' one-way and two-way shear capacities during fire exposure.FindingsStructural engineers can use the proposed methods for daily design work without applying complex heat transfer calculations. When the equivalent standard fire duration is utilized, a flat slab’s thermal deformations, flexural behaviour and shear capacity under an actual fire condition can be calculated. As such, the methods would be highly beneficial in assessing the structural integrity of a building during an active fire incident.Originality/valueThe paper provides engineers with the tools required to evaluate the safety of flat slab sections during fire exposure. The methodologies presented in the paper enable engineers to use performance-based design for slab sections by (1) converting any real fire scenario to a standard fire with an equivalent duration, (2) assessing their thermal behaviour, (3) evaluating their flexural behaviour and (4) evaluating their flexural and shear capacities. The paper concludes with a case study example demonstrating the detailed application of the developed methods.

Bayesian updating of relationships between crack width and corrosion level in reinforced concrete based on a large set of experimental data

AbstractThe evaluation of rebar corrosion in reinforced concrete (RC) structures presents a significant challenge for structural engineers, with on‐site visual inspections and crack width measurements playing a key role in the preliminary assessment. A general approach is to use corrosion models to predict the corrosion level of existing structures, and subsequently update these predictions by means of on‐site data. In this process, empirical models are often applied that relate the observed damage, such as corrosion‐induced cracks, to the corrosion level. However, these models have large uncertainties and are often not applicable to conditions that deviate from the test setups used to derive the empirical relations. This research aims to expand the applicability of these practical, existing empirical models for on‐site corrosion assessment through Bayesian updating techniques. To this aim, a Bayesian framework is developed to update crack width–corrosion models. The Bayesian updating methodology is illustrated for a simple regression model, and for a more complex relation that accounts for additional variables. A novel online database (KUL‐edCCRC) is used that is published accompanying this paper. The obtained results illustrate that the updated models have better agreement with the experimental results, and it is found that the confidence intervals of the regression parameters decrease for an increasing number of observations, even for a small number of additional datapoints. The results hence prove the efficiency of the approach to integrate information from new observations with prior information to adjust the crack width–corrosion model for specific conditions or cases, resulting in a more relevant model as more information becomes available.

Testing and evaluation of PVCC nano layered reinforced concrete T-beam: Experimental study

This study examines the performance of reinforced concrete T-beams strengthened with PVCC nano layering and basalt fiber fabric wrapping. TP3, a PVCC nano-layered specimen with 1.2% PVA fiber, and TB2, a basalt fiber fabric-wrapped beam, outperform the other specimens. TP3 has a first fracture load of 112 kN and a maximum ultimate load of 165 kN, with 1.66 times the ductility and 1.51 times the stiffness of the control beam (T0). TP3 also has 1.61 times more energy absorption and the highest energy index, 1.46 times that of T0. TB2 can withstand a maximum ultimate load of 185 kN and has higher ductility, stiffness, energy absorption, and energy index than T0. The experimental results are validated by finite element analysis, which provides useful insights into strengthening procedures in structural engineering applications.

Artificial neural network-enhanced mathematical simulation based on Carrera unified formulation for dynamic analysis and structural integrity assessment of advanced nanocomposites reinforced tunnel structures

This article presents the application of the Carrera Unified Formulation (CUF) for dynamic analysis and structural integrity assessment of advanced nanocomposite-reinforced tunnel structures. CUF offers a generalized framework that simplifies the modeling of complex structures, providing an efficient approach to address the dynamic behavior of nanocomposites. Advanced nanocomposites, which enhance mechanical performance and durability, are increasingly used in critical infrastructure such as tunnel systems. Traditional methods often fall short in capturing the intricate interactions within these materials, particularly under dynamic loads. CUF overcomes these challenges by incorporating higher-order theories and multi-scale analysis, allowing for accurate prediction of displacements, stresses, and potential failure modes. To further validate the results, an Artificial Neural Network (ANN) model is trained using simulated data, ensuring robust predictions for various loading conditions. The ANN assists in approximating the dynamic response and integrity of the structure, enabling real-time assessments with minimal computational expense. The combined CUF-ANN approach demonstrates high accuracy and efficiency, making it a reliable tool for the structural integrity assessment of nanocomposite-reinforced tunnels. This study highlights the significant potential of integrating CUF and ANN for the analysis and design of advanced engineering structures subjected to dynamic environmental conditions.

Tailoring Physicochemical Properties of Photothermal Hydrogels Toward Intrinsically Regenerative Therapies

AbstractPhotothermal hydrogels (PTHs) are considered next‐generation biomaterials as they offer remotely defined biophysical information of the extracellular milieu. PTHs allow precise and non‐genetic control for the regeneration of native tissues, which is the ultimate goal of tissue engineering (TE). Molecular and physical properties of PTHs, such as components, structural configurations, and mechanical characteristics, collectively serve as determinants for understanding the dynamic tissue response and clinical translation. PTHs have entered a period of fruition due to the development of numerous manufacturing technologies and polymeric matrices. Herein, this review comprehensively and meticulously elucidates the mechanisms of regenerative therapeutics underlying the design and fabrication of PTHs. Recent advances in the photothermal principles and various categories of photothermal agents (PTAs) have been extensively discussed. Vital components and structures of PTHs are summarized to enable efficacious and precise therapeutic energy delivery. Emerging applications of PTHs in TE are also demonstrated, which expand the strategies for the intrinsic regeneration of injured tissues. Then deliberate the structural and chemical engineering of PTHs to enhance prognosis while highlighting the challenges associated with clinical translation. In this review, we aim to provide guidance and prospects for exploration and innovation of PTHs in the field of TE.

The influence of carbon content to the band gap of ABC stacked trilayer hybridized graphene and hexagonal boron nitride

The influence of carbon content on the band gap of ABC stacked trilayer hybridized graphene and hexagonal boron nitride (h-BNC) are calculated by first-principles calculations. The formation energy results indicate that the configurations with cluster of boron(B) and nitrogen(N) atoms are more stable than that with separate. By calculating the band structures of seven doping models, we found that the band gap reduces with the ascendance of carbon atom concentration. With the increase of the carbon atom content, the optical absorption peak shifts to longer wavelength range. Combined with the band structure results, the red-shift is due to the reduction of the bandgap with the increase of the carbon atom content. The density of states, charge densities and Mulliken populations suggest that the collapse of the band gap is attributed to the charge transfer between atoms in the seven doping models of the h-BNC system. This work is valuable for the band structure engineering of h-BNC.

Use of a multi-criteria approach to analyze the degradation of reinforced concrete beam bridges. Three case studies in the north west of Algeria

The main motivation for this research is to develop assessment and estimation tools for the degradation state of existing civil engineering structures. The longevity of a structure is influenced by a complex set of interconnected phenomena and parameters. Therefore, we adopt a multicriteria approach aimed at better identifying these elements, particularly the most influential ones. This study focuses on assessing the degradation of reinforced concrete beam bridges by developing a digital tool based on the Analytic Hierarchy Process (AHP). We have identified 30 factors impacting degradation, categorized as internal factors, such as the condition of structural elements, and external factors, such as age and environment. From these factors, we calculate a Global Bridge Degradation Index (GBDI) that reflects the overall condition of the bridge. This index allows us to establish a classification of the bridges, ranging from no danger to a critical state requiring immediate intervention. The innovation of our model lies in its ability to provide a quantified estimation of the degradation state while incorporating an unlimited number of factors and criteria. After applying this model to three bridges in Algeria, we observed satisfactory results. The ultimate goal is to provide managers with tools for reflection and comparison to assess the condition of bridges and consider the necessary actions for their maintenance, repair, or replacement, thereby contributing to the improvement of the management and safety of road infrastructures.

Lifetime engineering principles in highway asset management

Introduction. An important tendency of our time is sustainability, good value for money and long-term planning. These are also the goals of the recently developed discipline, lifetime engineering. Although the principles of the science were originally developed for buildings and engineering structures, they can also be adapted to public roads. The article — through a case study in Hungary — presents the applicability of life engineering science to public road asset management. Besides, examples of pavement structure design, durability, maintenance-operation and environmental protection are also presented. Problem Statement. The typical lifetime engineering science principles used in the presentation were: increasing (pavement) life cycle; complex, multi-disciplinary design methodology; modular design; effective, quality insurance methods; high level satisfaction of the customers’ needs; minimisation of lifetime costs; sustainable, end-of-life strategies. It is emphasized that lifetime engineering is based on specific basic principles that effectively promote an up-to-date approach to any discipline related to engineering infrastructure. The paper shows that the efficacy of a road asset management. can be considerably increased if some elements of lifetime engineering are utilized.

Intelligent vibration control of tensile cable based on deep reinforcement learning

Vibration of tensile cables commonly occurs in the engineering structures such as cable-stayed bridges, which may have negative effect on the driving comfort and safety, and further lead to the fatigue problems of the structure. This paper proposes a semi-active control strategy based on deep reinforcement learning and magneto-rheological (MR) damper, for the vibration control of tensile cables, and the corresponding algorithm have been developed. Through the interaction with the cable-damper system, the intelligent agent can evaluate every possible control parameter and achieve an effective control policy. Then, according to the real-time vibration state, the agent would determine an action current for the MR damper and thus change the damping coefficient of the damper, further make influences on the vibrating cable. Basically, the proposed strategy realizes the model-free semi-active control of cable vibrations. To validate the effectiveness of the proposed semi-active control strategy, a scale model test has been conducted, where the test cases of passive and semi-active control strategies are carried out and compared. Results show that, the semi-active control shows a prior performance in vibration reduction compared to the passive control strategy, with regard to the vibration profile, the vibration energy, as well as the energy dissipation of MR damper.

Stabilization and Surface Functionalization of Palladium Disulfide Nanoparticles with Acetylene Derivatives.

Metal chalcogenide nanoparticles have been attracting extensive attention in diverse fields. Traditionally these nanoparticles are stabilized by organic ligands such as thiols and amines involving nonconjugated core-ligand interfacial interactions. In the present study, a facile wet-chemistry method is described for the synthesis of palladium disulfide (PdS2) nanoparticles capped with acetylene derivatives. Spectroscopic and electrochemical measurements suggest that conjugated Pd-C≡ linkages are formed at the core-ligand interface and facilitate electronic coupling and hence manipulation of the nanoparticle optical and electronic properties. The unique interfacial linkages also allow further functionalization of the nanoparticles by metathesis reaction with olefin derivatives, as manifested in the reaction with vinylferrocene. This research opens new avenues for the structural engineering and functionalization of metal chalcogenide nanoparticles.

Explainable Boosting Machine Learning for Predicting Bond Strength of FRP Rebars in Ultra High-Performance Concrete

Aiming at evaluating the bond strength of fiber-reinforced polymer (FRP) rebars in ultra-high-performance concrete (UHPC), boosting machine learning (ML) models have been developed using datasets collected from previous experiments. The considered variables in this study are rebar type and diameter, elastic modulus and tensile strength of rebars, concrete compressive strength and cover, embedment length, and test method. The dataset contains two test methods: pullout tests and beam tests. Four types of rebar, including carbon fiber-reinforced polymer (CFRP), glass fiber-reinforced polymer (GFRP), basalt, and steel rebars, were considered. The boosting ML models applied in this study include AdaBoost, CatBoost, Gradient Boosting, XGBoost, and Hist Gradient Boosting. After hyperparameter tuning, these models demonstrated significant improvements in predictive accuracy, with XGBoost achieving the highest R2 score of 0.95 and the lowest Root Mean Square Error (RMSE) of 2.21. Shapley values analysis revealed that tensile strength, elastic modulus, and embedment length are the most critical factors influencing bond strength. The findings offer valuable insights for applying ML models in predicting bond strength in FRP-reinforced UHPC, providing a practical tool for structural engineering.

Prestressed concrete slabs subjected to low-velocity impact: Theoretical analysis model and design method

Bidirectional bonded prestressed concrete (PS) structures are widely used in energy engineering structures due to their excellent impermeability. Owing to the particularity of the structure and the severity of damage consequences, the impact dynamic performance of bidirectional bonded PS structures has been widely concerned. Nonetheless, the existing researches focus on the test and finite element, and lacks the theoretical analysis model that can consider the whole process of load action, let alone the corresponding anti-impact design method. Therefore, based on the existing test and finite element results, the resistance function model of bidirectional bonded PS slab is proposed in this paper, and the anti-impact design method is formed. Firstly, the performance of specimens under low-velocity impact loading and quasi-static loading conditions is compared, and the effects of inertia force and material strain rate on the dynamic performance of specimens under low-velocity impact are further explored. Then, a resistance function theoretical analysis model that can consider the whole process of load action is proposed with a quadrilinear form, and the analytical expressions of resistance and stiffness at characteristic points are derived. Subsequently, the accuracy of the resistance function model is verified based on the existing test results. Furthermore, based on the resistance function model, the influence laws of compressive strength of concrete, prestressing degree, reinforcement ratio of reinforcement and slab thickness on slab resistance are analyzed. Finally, an anti-impact design method considering perforation and scabbing failure is proposed, and the feasibility of the design method is verified by impact test results.

Preface: 3rd International Conference on Architecture, Geotechnical Engineering and Construction Technology (AGECT 2024)

The 2024 3rd International Conference on Architecture, Geotechnical Engineering and Construction Technology (AGECT 2024) was held in Barcelona, Spain from August 10-11, 2024. The conference brings together innovative scholars and industry experts in the fields of architecture design, urban planning, building materials, structural engineering, civil engineering, geotechnical engineering, and construction technology into a common forum. The main objective of AGECT 2024 was to promote research and development activities. Another goal is to promote the exchange of scientific information between researchers, engineers, PHDs, students, and practitioners working in the conference and workshop. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 8-15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-40 minutes to hold their speeches. We would like to acknowledge all of those who supported AGECT 2024. The help and contribution of each individual and institution was instrumental in the success of the conference. In particular, we would like to thank the organizing committee for its valuable inputs in shaping the conference program and reviewing the submitted papers. We are sure that the proceedings will serve as an important research source of references and knowledge, which will lead to not only scientific and engineering findings but also new products and technologies. With best regards, Conference Organizing Chair Barcelona, Spain