Abstract
Based on Ahmadzadeh-Varvani hardening rule (A-V model), multiaxial ratcheting effect of Z2CND18.12N
austenitic stainless steel is simulated by ABAQUS with user subroutine UMAT. The results show that the predicted results of the
origin multiaxial A-V model are lower than the experimental data, and it is difficult to control ratcheting strain rate. In order to
improve the predicted capability of A-V model, the A-V model is modified. In this study. Moreover, under the assumption of the
von Mises yield criterion and normal plasticity flow rule, we develop a numerical algorithm of plastic strain with the improved
model to implement the finite element calculation of the model. Internal iteration in the numerical algorithm was implemented
with the Euler backward method, which calculated the trial strain for each equilibrium iteration using the consistent tangent
matrix. With a user subroutine, the proposed model is programmed into ABAQUS for a user - executable version. By simulating
the uniaxial ratcheting of a round bar made of Z2CND18.12N austenitic stainless steel, we observe that the predicted results
simulated by ABAQUS with UMAT are compared with the experimental data. The predicted results of the improved multiaxial
A-V model are consistent well with the experimental data.
Address
Xiaohui Chen, Yang Zhou, Wenwu Liu and Xu Zhao:School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China
Abstract
Steel–concrete composite slabs represent a very efficient floor solution combining the key performance of two
different materials: the steel and the concrete. Composite slab response is governed by the degree of the interaction between
these two materials, mainly depending by chemical and mechanical bond. The latter is characterized by a limited degree of
confinement if compared with the one of the rebars in reinforced concrete members while the former is remarkably influenced
by the type of concrete and the roughness of the profiled surface, frequently lubricated during the cold-forming manufacturing
processes. Indeed, owing to the impossibility to guarantee a full interaction between the two materials, a key parameter
governing slab design is represented by the horizontal shear-bond strength, which should be always experimentally estimated.
According to EC4, the design of the slab bending resistance, is based on the simplified assumption that the decking sheet is
totally yielded, i.e., always in plastic range, despite experimental and numerical researches demonstrate that a large part of the
steel deck resists in elastic range when longitudinal shear collapse is achieved. In the paper, the limit strain for composite slab,
which corresponds to the slip, i.e., the debonding between the two materials, has been appraised by means of a refined numerical
method used for the simulation of experimental results obtained on 8 different composite slab types. In total, 71 specimens have
been considered, differing for the properties of the materials, cross-section of the trapezoidal profiled metal sheets and specimen
lengths.
Address
Claudio Bernuzzi, Marco A. Pisani and Marco Simoncelli:Department of Architecture, Built environment and Construction engineering (ABC), Piazza Leonardo da Vinci 32, Politecnico di Milano, Italy
Abstract
The network theory studies interconnection between discrete objects to find about the behavior of a collection of objects. Also, nanomaterials are a collection of discrete atoms interconnected together to perform a specific task of mechanical or/and electrical type. Therefore, it is reasonable to use the network theory in the study of behavior of super-molecule in sport nano-scale. In the current study, we aim to examine vibrational behavior of spherical nanostructured composite with different geometrical and materials properties. In this regard, a specific shear deformation displacement theory, classical elasticity theory and analytical solution to find the natural frequency of the spherical nano-composite sport structure equipment. The analytical results are validated by comparison to finite element (FE). Further, a detail comprehensive results of frequency variations are presented in terms of different parameters. It is revealed that the current methodology provides accurate results in comparison to FE results. On the other hand, different geometrical and weight fraction have influential role in determining frequency of the structure.
Key Words
complex networks; mathematical simulation; mechanical behavior; nanotechnology
Address
Bo Jin Cheng:School of Physical Education, Guangzhou Sport University, Guangzhou 510000, Guangdong, China
Peng Cheng:Department of Public Physical, Changchun Humanities and Sciences College, Changchun 130117, Jilin, China
Abstract
Due to their efficient use of materials, hybrid reinforced concrete-steel (RCS) systems provide more practical and
economic advantages than traditional steel and concrete moment frames. This study evaluated the seismic design factors and
response modification factor 'R' of RCS composite moment frames composed of reinforced concrete (RC) columns and steel
(S) beams. The current International Building Code (IBC) and ASCE/SEI 7-05 classify RCS systems as special moment frames
and provide an R factor of 8 for these systems. In this study, seismic design parameters were initially quantified for this
structural system using an R factor of 8 based on the global methodology provided in FEMA P695. For analyses, multi-story (3,
5, 10, and 15) and multi-span (3 and 5) archetypes were used to conduct nonlinear static pushover analysis and incremental
dynamic analysis (IDA) under near-field and far-field ground motions. The analyses were performed using the OpenSees
software. The procedure was reiterated with a larger R factor of 9. Results of the performance evaluation of the investigated
archetypes demonstrated that an R factor of 9 achieved the safety margin against collapse outlined by FEMA P695 and can be
used for the design of RCS systems.
Address
Mohammad H. Habashizadeh:Department of Civil Engineering, Islamic Azad University- Marand Branch, Marand, East Azarbaijan, Iran
Nima Talebian, Dane Miller and Martin Skitmore:School of Sustainable Development, Faculty of Society and Design, Bond University, Robina, QLD 4226, Australia
Hassan Karampour:School of Engineering and Built Environment, Griffith University, Southport, QLD 4215, Australia
Abstract
This paper presents a development of empirical evaluations, which can be used to evaluate the damage of fiberreinforced concrete composites (FRC) wall subjected to close-in blast loads. For this development, a combined application of
numerical simulation and machine learning approaches are employed. First, finite element modeling of FRC wall under blast
loading is developed and verified using experimental data. Numerical analyses are then carried out to investigate the dynamic
behavior of the FRC wall under blast loading. In addition, a data set of 384 samples on the damage of FRC wall due to blast
loads is then produced in order to develop machine learning models. Second, three robust machine learning models of Random
Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) are employed to propose empirical
evaluations for predicting the damage of FRC wall. The proposed empirical evaluations are very useful for practical evaluation
and design of FRC wall subjected to blast loads.
Address
Duc-Kien Thai:Department of Civil and Environmental Engineering, Sejong University, 98 Gunja-Dong, Gwangjin-Gu, Seoul, 143-747, South Korea
Thai-Hoan Pham:Department of Concrete Structures, National University of Civil Engineering, 55 Giai Phong, Hanoi, Vietnam
Duy-Liem Nguyen:Department of Civil Engineering and Applied Mechanics, Ho Chi Minh City University of Technology and Education,
1 Vo Van Ngan St., Thu Duc District, Ho Chi Minh City, Vietnam
Tran Minh Tu:Faculty of Industrial and Civil Engineering, National University of Civil Engineering, 55 Giai Phong, Hanoi, Vietnam
Phan Van Tien:Department of Civil Engineering, Vinh University, Vinh 461010, Vietnam
Abstract
A simplified calculation method of natural vibration characteristics of high-speed railway multi-span bridgelongitudinal ballastless track system is proposed. The rail, track slab, base slab, main beam, bearing, pier, cap and pile
foundation are taken into account, and the multi-span longitudinal ballastless track-beam-bearing-pier-cap-pile foundation
integrated model (MBTIM) is established. The energy equation of each component of the MBTIM based on Timoshenko beam
theory is constructed. Using the improved Fourier series, and the Rayleigh-Ritz method and Hamilton principle are combined to
obtain the extremum of the total energy function. The simplified calculation formula of the natural vibration frequency of the
MBTIM under the influence of vertical and longitudinal vibration is derived and verified by numerical methods. The influence
law of the natural vibration frequency of the MBTIM is analyzed considering and not considering the participation of each
component of the MBTIM, the damage of the track interlayer component and the stiffness change of each layer component. The
results show that the error between the calculation results of the formula and the numerical method in this paper is less than 3%,
which verifies the correctness of the method in this paper. The high-order frequency of the MBTIM is significantly affected
considering the track, bridge pier, pile soil and pile cap, while considering the influence of pile cap on the low-order and highorder frequency of the MBTIM is large. The influence of component damage such as void beneath slab, mortar debonding and
fastener failure on each order frequency of the MBTIM is basically the same, and the influence of component damage less than
10m on the first fourteen order frequency of the MBTIM is small. The bending stiffness of track slab and rail has no obvious
influence on the natural frequency of the MBTIM, and the bending stiffness of main beam has influence on the natural
frequency of the MBTIM. The bending stiffness of pier and base slab only has obvious influence on the high-order frequency of
the MBTIM. The natural vibration characteristics of the MBTIM play an important guiding role in the safety analysis of highspeed train running, the damage detection of track-bridge structure and the seismic design of railway bridge
Key Words
frequency; high-speed railway; improved Fourier series; Rayleigh-Ritz method; track-bridge system
Address
Yulin Feng:1)School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China
2)State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure, Nanchang 330013, China
3)Central South University, National Engineering Research Center of High-speed Railway Construction Technology, Changsha 410075, China
Yaoyao Meng and Wenjie Guo:School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang 330013, China
Lizhong Jiang and Wangbao Zhou: Central South University, National Engineering Research Center of High-speed Railway Construction Technology, Changsha 410075, China
Abstract
An effective approach to promoting sustainability within the construction industry is the use of recycled aggregate
concrete (𝑅𝐴𝐶) as a substitute for natural aggregates. Ensuring the frost resilience of 𝑅𝐴𝐶 technologies is crucial to facilitate
their adoption in regions characterized by cold temperatures. The main aim of this study was to use the Random Forests (𝑅𝐹)
approach to forecast the frost durability of 𝑅𝐴𝐶 in cold locations, with a focus on the durability factor (𝐷𝐹) value. Herein,
three optimization algorithms named Sine-cosine optimization algorithm (𝑆𝐶𝐴), Black widow optimization algorithm (𝐵𝑊𝑂𝐴),
and Equilibrium optimizer (𝐸𝑂) were considered for determing optimal values of 𝑅𝐹 hyperparameters. The findings show that
all developed systems faithfully represented the 𝐷𝐹, with an 𝑅
2
for the train and test data phases of better than 0.9539 and
0.9777, respectively. In two assessment and learning stages, 𝐸𝑂 − 𝑅𝐹 is found to be superior than 𝐵𝑊𝑂𝐴 − 𝑅𝐹 and 𝑆𝐶𝐴 −
𝑅𝐹. The outperformed model's performance (𝐸𝑂 − 𝑅𝐹) was superior to that of 𝐴𝑁𝑁 (from literature) by raising the values of
𝑅
2
and reducing the 𝑅𝑀𝑆𝐸 values. Considering the justifications, as well as the comparisons from metrics and Taylor
diagram's findings, it could be found out that, although other 𝑅𝐹 models were equally reliable in predicting the the frost
durability of 𝑅𝐴𝐶 based on the durability factor (𝐷𝐹) value in cold climates, the developed 𝐸𝑂 − 𝑅𝐹 strategy excelled them
all.
Key Words
durability factor; frost durability; optimizers; random forests; recycled aggregate concrete
Address
Rui Liang:School of Architecture and Urban Planning, Guangdong University of Technology, Guangzhou, 510062, China
Behzad Bayrami:Department of Civil Engineering, Moghadas Ardabili Institute of Higher Education, Ardabil, Iran
Abstract
Headed studs welded to steel beams and embedded within the concrete of deck slabs are vital components of
modern composite floor systems, where safety and economy depend on the accurate predictions of the stud shear resistance. The
multitude of existing deck profiles and the complex behavior of studs in deck slab ribs makes developing accurate and reliable
mechanical or empirical design models challenging. The paper addresses this issue by presenting a machine learning (ML)
model developed from the natural gradient boosting (NGBoost) algorithm capable of producing probabilistic predictions and a
database of 464 push-out tests, which is considerably larger than the databases used for developing existing design models. The
proposed model outperforms models based on other ML algorithms and existing descriptive equations, including those in EC4
and AISC 360, while offering probabilistic predictions unavailable from other models and producing higher shear resistances for
many cases. The present study also showed that the stud shear resistance is insensitive to the concrete elastic modulus, stud
welding type, location of slab reinforcement, and other parameters considered important by existing models. The NGBoost
model was interpreted by evaluating the feature importance and dependence determined with the SHapley Additive exPlanations
(SHAP) method. The model was calibrated via reliability analyses in accordance with the Eurocodes to ensure that its
predictions meet the required reliability level and facilitate its use in design. An interactive open-source web application was
created and deployed to the cloud to allow for convenient and rapid stud shear resistance predictions with the developed model.
