Numerical Simulation of the Creep Behavior of Beishan Deep Granite Tunnel under the Coupling Thermal -Stress Field

Jiawei Wang,Ju Wang,Zhichao Zhou,Peng Wu,Haoran Sun,Jiale Dou,Nan Li,Xianzhe Duan 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.4

This study conducts a three-dimensional numerical simulation of the creep behavior of deep granite tunnels at 560 meters underground during the coupled thermal-stress process, with an aim to elucidate the effect of the temperature and stress fields on the creep behavior of these deep hard rock tunnels. A 100-h creep period was set, and the mechanical structure of the experimental chamber was accurately replicated at a 1:1 scale, considering the actual mechanical structure of the granite tunnels in the Beishan underground laboratory. The simulation results can demonstrate that: 1) The maximum stress at 90°C and 50°C are 2.86 and 1.91 times than that at 23°C, respectively, demonstrating significant strain accumulation in the deep granite tunnels at the surface. This phenomenon can primarily be attributed to the thermal stress resulted from the coupling between temperature and stress. 2) The maximum creep at 90°C and 50°C is 16 and 3.5 times than that at 23°C. Under the influence of thermal coupling, the creep increases significantly with increasing temperature, indicating that temperature is an important factor influencing creep in granite. 3) Compared with variations in the stress field, the temperature field emerges as the most critical factor influencing granite creep.

Optimization Design of the Decentralized Multi-Vehicle Cooperative Controller for Freeway Ramp Entrance

Wang Jiawei,Ma Fangwu,Yu Yang,Zhu Sheng,Gelbal Sukru Yaren,Aksun-Guvenc Bilin,Guvenc Levent 한국자동차공학회 2021 International journal of automotive technology Vol.22 No.3

This research presents a multi-vehicle control strategy combining the merging control and platoon control to deal with the merging scenario in the freeway ramp entrance. In the merging controller, a selection algorithm is presented firstly to determine the merging sequence based on the initial states of the vehicles in the cooperative area. Subsequently, the optimized longitudinal trajectory of the facilitating vehicle and on-ramp vehicle is addressed by solving the Hamiltonian function. As for the platoon controller, string stability is analyzed to attenuate the impact of merging on the mainline traffic, considering the influence of communication time delay. Smooth mode switching is achieved by introducing the tracking policy of platoon controller to determine the terminal states of the facilitating vehicle. The proposed strategy is simulated at two typical merging scenarios, where two on-ramp vehicles attempt to cut into a six-vehicular platoon, to validate its feasibility and advantage.

Design and analysis of mechanical flux‑weakening device of axial flux permanent magnet machines

Shaopeng Wang,Jiawei Lu,Bin Li,Chengcheng Liu,Youhua Wang,Gang Lei,Youguang Guo,Jianguo Zhu 전력전자학회 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.4

Due to the low inductance of an axial flux permanent magnet machine (AFPMM), the constant power speed regulation range is small. A new mechanical flux-weakening method for single-rotor single-stator AFPMMs is proposed in this paper. By installing a mechanical flux-weakening device on one side of the stator and rotating it certain angle, the speed regulation of the flux-weakening can be realized. The device is simple in structure, easy to operate, and can be operated in the process of machine operation. The validity of the device is verified by applying it to a machine. Finite-element software is used to calculate and analyze the performances of two machines with the device.

An Anomaly Detection Framework for Detecting Anomalous Virtual Machines under Cloud Computing Environment

GuiPing Wang,JiaWei Wang 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.1

A variety of faults may cause performance degradation or even downtime of virtual machines (VMs) under Cloud environment, thus lowering the dependability of Cloud platform. Detecting anomalous VMs before real failures occur is an important means to improve the dependability of Cloud platform. Since the performance or state of VMs may be affected by the environmental factors, this article proposes an environment-aware anomaly detection framework (termed EaAD) for VMs under Cloud environment. EaAD partitions all the VMs in Cloud platform into several monitoring domains based on similarity in running environment, which makes the VMs in a same monitoring domain have similar running environment. In each domain, the equipped anomaly detection algorithm detects anomalous VMs based on their performance metrics. In addition, anomaly detection in a certain monitoring domain faces such challenges as multiple anomaly categories, imbalanced training sample sets, increasing number of training samples. To cope with these challenges, several support vector machine (SVM) based anomaly detection algorithms are implemented and equipped in EaAD, including C-SVM, OCSVM, multi-class SVM, imbalanced SVM, online learning SVM. This article conducts experiments on EaAD to test the performance of the adopted detection algorithms and looks into future work.

Fabrication of novel self-healable ultraslippery surface for preventing marine microbiologically influenced corrosion

Hao Jiang,Wenhuan Wang,Jiawei Li,Liyang Zhu,Dun Zhang,Peng Wang,Guoqing Wang 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.109 No.-

Slippery liquid-infused porous surfaces (SLIPS) have attracted wide attention in the field of marine anticorrosion. However, the stability problem severely restricts the broad applications of SLIPS. Herein, wefabricated a polyurethane-based ultraslippery surface with lubricant self-replenishing and matrix selfhealingproperties owing to the huge amount of dynamic hydrogen-bond. Besides, the bacteria culturetest and electrochemical analysis results indicate the prepared surface possesses superior properties inthe protection of microbiologically influenced corrosion (MIC). This paper offers an efficient strategy tosolve stability problem of SLIPS, and the as-obtained self-healable ultraslippery surface can be used asa promising material in mitigating MIC.

Long Noncoding RNA Expression Profiling During the Neuronal Differentiation of Glial Precursor Cells from Rat Dorsal Root Ganglia

Yunfei Dai,Wei Ma,Tong Zhang,Jinwei Yang,Chenghao Zang,Kuangpin Liu,Xianbin Wang,Jiawei Wang,Zhen Wu,Xingkui Zhang,Chunyan Li,Junjun Li,Xiangpeng Wang,Jianhui Guo,Liyan Li 한국생물공학회 2020 Biotechnology and Bioprocess Engineering Vol.25 No.3

Long noncoding RNAs (lncRNAs) play important roles in the process of cell fate determination. However, their function and expression profiles have not yet been systematically investigated during the transdifferentiation of glial precursor cells derived from dorsal root ganglia (DRG) in the peripheral nervous system. Our results demonstrated significant differences in gene architecture and expression among the three transcript types (lncRNA, mRNA, and TUCP). Distinct differences in transcript length, exon number, and ORF length were identified between lncRNAs and mRNAs after comparative analysis of their structure and sequence conservation. We found that the upregulated lncRNAs outnumbered the downregulated lncRNAs in glial precursor cells cultured with proBDNF antiserum compared with the levels in glial precursor cells cultured without proBDNF antiserum. By a series of GO and KEGG analyses, we found that the effects of some lncRNAs on their target genes in cis were related to nerve growth factor-induced cell cycle, cell phenotype change, and neuronal differentiation. The qRT-PCR verification results of lncRNAs ENSRNOT00000091991, ENSRNOT00000087717, and LNC_000429 were mostly consistent with the sequencing results. The candidate lncRNAs may be associated with the neuronal transdifferentiation of glial precursor cells. Our study provides the first evidence for a remarkably diverse pattern of lncRNA expression during neuronal differentiation of glial precursor cells from rat DRG, and also provides a resource for lncRNA studies in the field of cell differentiation.

Study on damage detection software of beam-like structures

Jiawei Xiang,Zhansi Jiang,Yanxue Wang,Xuefeng Chen 국제구조공학회 2011 Structural Engineering and Mechanics, An Int'l Jou Vol.39 No.1

A simply structural damage detection software is developed to identification damage in beams. According to linear fracture mechanics theory, the localized additional flexibility in damage vicinity can be represented by a lumped parameter element. The damaged beam is modeled by waveletbased elements to gain the first three frequencies precisely. The first three frequencies influencing functions of damage location and depth are approximated by means of surface-fitting techniques to gain damage detection database of forward problem. Then the first three measured natural frequencies are employed as inputs to solve inverse problem and the intersection of the three frequencies contour lines predict the damage location and depth. The DLL (Dynamic Linkable Library) file of damage detection method is coded by C++ and the corresponding interface of software is coded by virtual instrument software LabVIEW. Finally, the software is tested on beams and shafts in engineering. It is shown that the presented software can be used in actual engineering structures.

A simple method to detect cracks in beam-like structures

Jiawei Xiang,Toshiro Matsumoto,Jiangqi Long,Yanxue Wang,Zhansi Jiang 국제구조공학회 2012 Smart Structures and Systems, An International Jou Vol.9 No.4

This study suggests a simple two-step method for structural vibration-based health monitoring for beam-like structures which only utilizes mode shape curvature and few natural frequencies of the structures in order to detect and localize cracks. The method is firstly based on the application of wavelet transform to detect crack locations from mode shape curvature. Then particle swarm optimization is applied to evaluate crack depth. As the Rayleigh quotient is introduced to estimate natural frequencies of cracked beams, the relationship of natural frequencies and crack depths can be easily obtained with only a simple formula. The method is demonstrated and validated numerically, using the numerical examples (cantilever beam and simply supported shaft) in the literature, and experimentally for a cantilever beam. Our results show that mode shape curvature and few estimated natural frequencies can be used to detect crack locations and depths precisely even under a certain level of noise. The method can be extended for health monitoring of other more complicated structures.

A new method to detect cracks in plate-like structures with though-thickness cracks

Jiawei Xiang,Yongying Jiang,Udo Nackenhorst,Yanxue Wang,Haifeng Gao,Yumin He 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.14 No.3

In this paper, a simple two-step method for structural vibration-based health monitoring for beam-like structures have been extended to plate-like structures with though-thickness cracks. Crack locations and severities of plate-like structures are detected using a hybrid approach. The interval wavelet transform is employed to extract crack singularity locations from mode shape and support vector regression (SVR) is applied to predict crack serviettes form crack severity detection database (the relationship of natural frequencies and crack serviettes) using several natural frequencies as inputs. Of particular interest is the natural frequencies estimation for cracked plate-like structures using Rayleigh quotient. Only the natural frequencies and mode shapes of intact structures are needed to calculate the natural frequencies of cracked plate-like structures using a simple formula. The crack severity detection database can be easily obtained with this formula. The hybrid method is investigated using numerical simulation and its validity of the usage of interval wavelet transform and SVR are addressed.

A new method to detect cracks in plate-like structures with though-thickness cracks

Xiang, Jiawei,Nackenhorst, Udo,Wang, Yanxue,Jiang, Yongying,Gao, Haifeng,He, Yumin Techno-Press 2014 Smart Structures and Systems, An International Jou Vol.14 No.3

In this paper, a simple two-step method for structural vibration-based health monitoring for beam-like structures have been extended to plate-like structures with though-thickness cracks. Crack locations and severities of plate-like structures are detected using a hybrid approach. The interval wavelet transform is employed to extract crack singularity locations from mode shape and support vector regression (SVR) is applied to predict crack serviettes form crack severity detection database (the relationship of natural frequencies and crack serviettes) using several natural frequencies as inputs. Of particular interest is the natural frequencies estimation for cracked plate-like structures using Rayleigh quotient. Only the natural frequencies and mode shapes of intact structures are needed to calculate the natural frequencies of cracked plate-like structures using a simple formula. The crack severity detection database can be easily obtained with this formula. The hybrid method is investigated using numerical simulation and its validity of the usage of interval wavelet transform and SVR are addressed.