Abstract
This study aimed to analyse the performance parameters such as surface roughness Ra, flank wear VB and material removal rate MRR, in conjunction with the cutting conditions and the cutting tool material, during the hard turning of AISI 4140 steel. The experiments were carried out following the Taguchi L9 design, which includes four factors: cutting speed Vc, feed rate f, depth of cut DOC and cutting tool material Mi (M1: uncoated mixed ceramic, M2: coated mixed ceramic and M3: composite ceramic). The results were examined using analysis of variance (ANOVA) to explore the influence of the input parameters on the dependent output variables (Ra, VB and MRR). Mathematical models were developed using regression analysis to represent the different outputs as a function of the input parameters. Subsequently, a multi-criteria decision-making process based on the MARCOS method was performed in conjunction with four weighting methods, namely Equal, Entropy, CRITIC and AHP, in order to obtain the optimal cutting regime that minimises Ra and VB and maximises MRR. ANOVA revealed a predominance of f over Ra, followed by Vc. In addition, Vc had the greatest influence on VB followed by f. The M2 insert was found to offer low VB and Ra compared to other inserts. The optimum regime for achieving a good balance between the three output parameters under consideration is achieved with: Vc=100 m/min, f=0.08 mm/rev, DOC=0.3 mm using the M2 insert, and this result is consistent with the Equal, Entropy and CRITIC methods. However, a difference was observed in the regime obtained with the AHP method, which showed a lower DOC (0.1 mm).
Key Words
ceramics; hard turning; MCDM optimisation; surface roughness; tool wear
Address
Mohand Ouidir Sahbi: Laboratoire de Mécanique, Matériaux et Energétique, Faculté de Technologie, Univesité de Bejaia,
06000 Bejaia, Algérie
Abdelhamid Sadeddine: Laboratoire de Mécanique, Matériaux et Energétique, Faculté de Technologie, Univesité de Bejaia,
06000 Bejaia, Algérie
Mohamed Athmane Yallese: Department of Mechanical Engineering, Mechanics and Structure Laboratory (LMS), University 8 Mai 1945, BP 401, 24000 Guelma, Algeria
Septi Boucherit: Department of Mechanical Engineering, Mechanics and Structure Laboratory (LMS), University 8 Mai 1945, BP 401, 24000 Guelma, Algeria
Vincent Wagner: Laboratoire Génie de Production, LGP, Université de Technologie Tarbes Occitanie Pyrénées (UTTOP),
47 Avenue d'Azereix, 65000, Tarbes, France
Berk Tekkaya: Institute of Metal Forming, Intzestra
Abstract
This study introduces a numerical framework for analyzing the natural frequencies of axially moving Timoshenko beams with intermediate elastic support. The proposed method evaluates the effects of moving speed, axial load, and intermediate elastic support on the natural frequencies of moving beams under three boundary conditions. The elastic support is modeled as a translational spring, and the frequency determinant is derived using the transfer matrix method. The proposed method is validated by comparing its accuracy with those of previously reported approaches. The critical speed corresponding to the fundamental frequency mode is identified as the moving speed at which the natural frequency becomes zero, leading to divergence instability. The effect of elastic support on critical speed is examined by adjusting the spring constant, defined as a dimensionless stiffness parameter. The variation in critical speed with respect to the spring constant is examined in detail, and relevant results are presented.
Address
Jin Kim, Jung Woo Lee: Department of Mechanical System Engineering, Kyonggi University, Yeongtong-gu, Suwon-si, Gyeonggi-do, 16227, Republic of Korea
Abstract
Effective damage identification in large-scale spatial grid structures is often hindered by the practical limitations of sparse sensor instrumentation and measurement noise. This study develops an integrated framework that synergistically combines an enhanced sensor placement algorithm with a robust two-stage identification strategy to overcome these challenges. For damage localization, a weighted Modal Residual Force (wMRF) method is proposed, which uses the Modal Assurance Criterion (MAC) as a confidence weight to amplify damage-sensitive modes and suppress noise, enhancing accuracy with incomplete modal data. For optimal sensor placement, an enhanced Genetic Algorithm (eGA) is developed, featuring a Modal Strain Energy (MSE)-based pre-screening stage that significantly accelerates convergence by focusing the search on dynamically significant locations. The framework operates in two stages: the wMRF method first localizes a candidate set of damaged elements, after which the Cross-Model Cross-Mode (CMCM) method accurately quantifies their severity. The integrated framework is validated on a large-scale grid structure. Numerically, even with a sparse sensor layout (18 sensors, 2.5% of DOFs) and under 10% measurement noise, the proposed system successfully identifies multiple damaged members with a maximum quantification error below 10%. The results demonstrate the framework's capability to achieve high-accuracy damage identification under realistic sparse-data conditions, presenting a viable approach for the practical health monitoring of complex structures.
Key Words
damage identification; damage localization; sensor placement optimization; space grid structures; two-stage method
Address
Zhi-Wei Shan: China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast University, Nanjing, China
Ling Liu: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, China
Shu-Hui Huang: China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast University, Nanjing, China
Kun Liang: Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China
Abstract
Reinforced concrete (RC) corbels are critical load-bearing elements used to support beams and roof systems in industrial and precast concrete structures. Their structural performance and durability are often compromised by cyclic loading, fatigue-induced cracking, and environmental degradation. Strengthening with carbon fiber-reinforced polymer (CFRP) composites offers a promising solution to enhance their load-carrying capacity and stiffness. Although the monotonic behavior of CFRP-strengthened RC elements has been widely investigated, limited studies have addressed their cyclic response. The present study examines the cyclic behavior of CFRP-strengthened reinforced concrete (RC) corbels utilizing numerical simulation. Nonlinear finite element model accuracy was confirmed using experimental data. A comprehensive parametric study was conducted to evaluate the influence of different CFRP configurations on stiffness degradation, strength reduction, energy dissipation, and pinching behavior under reversed cyclic loading. The results demonstrate that CFRP strengthening significantly enhances the cyclic performance of RC corbels. Compared to unstrengthened specimens, compared to unstrengthened specimens, the wrapped CFRP configuration exhibited increases in ultimate strength (up to 96%), initial stiffness (by approximately 17%), and energy dissipation capacity (by around 125%). Additionally, CFRP strengthening effectively mitigated cyclic degradation phenomena by improving stiffness retention and reducing pinching effects, with strengthened specimens exhibiting stiffness enhancements ranging from 7% to 17% and improved pinching width ratio values of up to approximately 14%, thereby improving overall structural resilience and serviceability under repeated loading.
Key Words
CFRP strengthening; cyclic loading; energy dissipation; finite element analysis; load-bearing capacity; pinching behavior; reinforced concrete corbels; stiffness degradation; strength degradation
Address
Hiba Zaioune, Samy Mezhoud: Department of Civil Engineering, University of Constantine 1, Laboratoire (LMDC), Constantine, 25016, Algeria
Ivelina Ivanova, Jules Assih, Cheikhna Diagana: Université de Reims Champagne-Ardenne, ITHEMM EA 7548, Reims, France
Abstract
The scissor-jack-damper (SJD) assembly is highly efficient in amplifying the working stroke of its embedded damper, thus providing notably elevated energy-dissipation capacities for structures under earthquake excitations. In compliance with the amplified damper's deformation, the member force in a SJD rises and in many cases the assembly suffers from a global instability problem. This issue is quite pronounced for the conventional planar SJD configurations and it is preventing the SJD assembly from being adopted in practice. Replacing the rigid rods in the conventional SJD configuration with pre-tensioned cables, the compression-induced instability can be fully eliminated. Given in this work is an in-depth study on the mechanical property of the tensegrity SJD assembly. Force equilibrium and geometric compatibility were combined, with cable elasticity explicitly considered, to formulate a set of coupled nonlinear equations describing the force-displacement-velocity relationship of the SJD-frame integrity. Due to the inherent complexity and nonlinearity of these equations, it is very difficult to get an explicit analytical solution. Therefore, numerical methods were employed to obtain the solutions. Parametric analyses were firstly conducted to check the influences of some key parameters on the tensegrity SJD. Then, based on 400 numerical simulation cases, six machine-learning (ML) models were trained to predict the two most important amplification factors of the tensegrity SJD assembly. Results show that the particle-swarm-optimized Gaussian process regression (PSO-GPR) model achieved the highest predictive accuracy. A SHAP-based interpretability further quantified the contribution of each feature. The proposed approach enabled rapid and accurate prediction of the amplification performance, supporting efficient design of tensegrity SJD-based energy-dissipation systems.
Address
Yi-Qiong Cui: Department of Structural Engineering, Tongji University, Shanghai, China
Yang Xiang: Department of Structural Engineering, Tongji University, Shanghai, China; State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China
Xi-Ling Yang: Department of Structural Engineering, Tongji University, Shanghai, China
Jinkoo Kim: Department of Civil and Architectural Engineering, Sungkyunkwan University, Suwon, South Korea
Guo-Qiang Li: Department of Structural Engineering, Tongji University, Shanghai, China; State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China
Abstract
Steel spring floating slab tracks (FSTs) effectively mitigate high-frequency vibrations, but they exhibit low-frequency resonance at approximately 10 Hz. This study develops a unified vehicle-track-inerter model to examine the dynamic behavior of FSTs equipped with Tuned Viscous Mass Damper (TVMD) and Tuned Inerter Damper (TID). A multi-objective optimization strategy is further implemented to optimize the inerter-enhanced FSTs performance, followed by a comparative assessment of the vibration reduction effectiveness of TVMD and TID. The results show that both optimized TVMD and TID effectively suppress low-frequency vibrations, with TID outperforming TVMD in the 10-30 Hz range. Specifically, around 10 Hz, foundation vibrational acceleration levels (VALs) are reduced by approximately 14 dB and 11 dB for the TID and TVMD, respectively. Comparative and statistical analysis further reveals that the low-frequency mitigation performance of the TVMD is predominantly governed by stiffness, whereas that of the TID is primarily controlled by inertance and damping. These findings provide systematic guidance for selecting and optimizing inerter configurations, offering an effective solution for low-frequency vibration mitigation in urban rail systems.
Address
Yun Li, Yu Zhou, Can Shi: College of Civil and Transportation Engineering, Shenzhen University, Shenzhen, 518060, China
Xi Sheng, Zhixiang Zhou: School of Civil Engineering, Chongqing Jiaotong University, Chongqing, 400074, China
