New Model for Predicting Instantaneous Cutting Rate of Axial-type Roadheaders

Qianqian Zhang,Zhennan Han,Mengqi Zhang,Jianguang Zhang 대한토목학회 2017 KSCE JOURNAL OF CIVIL ENGINEERING Vol.21 No.1

Roadheaders are mechanical excavators which have been extensively used in tunneling, mining and civil engineering works. Performance prediction of the roadheader is major factor in determining the economy of an underground excavation project. In this study, a new model for predicting the Instantaneous Cutting Rate (ICR) has been developed. The performance of EBZ260W axialtype roadheader has been evaluated in the laboratory artificial rock cutting tests and in the tunneling field tests. Using the model, the processes of the artificial rock cutting in the laboratory tests have also been simulated. The predicted average ICRs in the laboratory tests, and in the simulations, together with the measured average ICRs in the laboratory tests and in the field tests are presented in this paper. The comparison of the predicted and measured ICRs shows that the relative error is within 5%. There are also reasonable agreements and strong correlations between the model and tests results. The new ICR prediction model is also supported by the empirical prediction formulas developed by other researchers. Hence, the model can be used to reliably predict the ICR for axial-type roadheaders.

CDs/ZnO composite material with solid state fluorescence performance for quantitative determination of methyl red content and antibacterial properties

Mengqi Wang,Kaiyue Zhang,Feixiang Ji,Yurong Guo,Chao Wang,Shiping Wang,Ya Chu,Guangjiu Zhao 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.104 No.-

A water-soluble probe composite material (CDs/ZnO) was synthesized by microwave pyrolysis methodsof citric acid, urea and zinc oxide (ZnO) with aggregation-induced emission activity. We creatively realizedthe composite of CDs and nano-ZnO in the form of foam, then used as bactericide for the first timeand showed excellent antibacterial properties. Also, the composite materials overcame the problem ofaggregation-induced quenching (ACQ) and realized solid-state emission. The materials had two differentemission centers, and the two emission peaks were varied with the change of excitation wavelength. Furthermore, Methyl red (MR) showed fluorescence quenching for CDs/ZnO with obvious linear correlation,which demonstrated potential in the measurement of MR in dyeing wastewater. The CDs/ZnO weobtained perfectly inherited the advantages of CDs and nano ZnO, it has not just no cytotoxicity to cells,but also has a good killing effect on bacteria. Hence, this work shows significant adaptable fluorescencebasedprotocol with enormous potential applications in biology.

Integrated analysis of transcriptomic and proteomic analyses reveals different metabolic patterns in the livers of Tibetan and Yorkshire pigs

Duan, Mengqi,Wang, Zhenmei,Guo, Xinying,Wang, Kejun,Liu, Siyuan,Zhang, Bo,Shang, Peng Asian Australasian Association of Animal Productio 2021 Animal Bioscience Vol.34 No.5

Objective: Tibetan pigs, predominantly originating from the Tibetan Plateau, have been subjected to long-term natural selection in an extreme environment. To characterize the metabolic adaptations to hypoxic conditions, transcriptomic and proteomic expression patterns in the livers of Tibetan and Yorkshire pigs were compared. Methods: RNA and protein were extracted from liver tissue of Tibetan and Yorkshire pigs (n = 3, each). Differentially expressed genes and proteins were subjected to gene ontology and Kyoto encyclopedia of genes and genomes functional enrichment analyses. Results: In the RNA-Seq and isobaric tags for relative and absolute quantitation analyses, a total of 18,791 genes and 3,390 proteins were detected and compared. Of these, 273 and 257 differentially expressed genes and proteins were identified. Evidence from functional enrichment analysis showed that many genes were involved in metabolic processes. The combined transcriptomic and proteomic analyses revealed that small molecular biosynthesis, metabolic processes, and organic hydroxyl compound metabolic processes were the major processes operating differently in the two breeds. The important genes include retinol dehydrogenase 16, adenine phosphoribosyltransferase, prenylcysteine oxidase 1, sorbin and SH3 domain containing 2, ENSSSCG00000036224, perilipin 2, ladinin 1, kynurenine aminotransferase 1, and dimethylarginine dimethylaminohydrolase 1. Conclusion: The findings of this study provide novel insight into the high-altitude metabolic adaptation of Tibetan pigs.

以法律职业为目标的法学本科研究型教学实践与思考

张朝霞 ( Zhang Zhaoxia ),李孟超 ( Li Mengchao ),韦梦琦 ( Wei Mengqi ) 경상대학교 교육연구원(구 경상대학교 중등교육연구소) 2021 중등교육연구 Vol.33 No.1

전문성을 갖춘 법학교육에 있어서 지식교육과 기술교육을 포함하는데, 기술교육으로는 스마트기술과 실무기술 등이 있다. 법조인 양성을 위한 법학교육은 법학지식과 더불어 스마트기술의 습득을 필요로 한다. 법학교육과 스마트기술의 습득은 미래사회가 인재에 대한 수요일 뿐만 아니라 업무의 효률성과도 연관되어 있다. 이러한 법학교육은 훌륭한 인재 양성을 위해 직업교육을 강화하고 전문적인 지식과 기술을 갖춘 법조인을 양성하는 데에 그 의미가 있다. 이를 위하여 법학교육의 실천과정에 지식전달 위주의 수업방식에서 실무능력 양성을 주요 특징으로 하는 연구형 수업방식으로 전환하여야 한다. 즉 전문적인 지식과 기술을 갖춘 법조인 양성을 위한 법학교육의 연구형 수업은 교수자의 주도하에 학습자들이 적극적으로 참여하는 연구형 수업방식이다. 이 과정에서 교수자와 학습자 간 협력하여 법률 지식과 스마트기술을 습득하는 질 높은 수업방식을 공동구축하도록 요구된다. 교육실천과정에서 나타나는 여러 문제점에 대비해 연구형 법학교육이 이상적인 학습효과를 달성하고 법률지식과 스마트기술을 갖춘 법조인을 양성하기 위해 아래 몇 가지 대안을 제시한다. 첫째, 연구형 수업의 실천과정에서 스마트기술의 습득이 우선시 되어야 한다. 둘째, 법학지식에 관한 검색능력을 강화해야 한다. 셋째, 교수자는 교육과정에서 특정 역할에 충실해야 한다. 넷째, 교수자와 학습자 간의 좋은 수업분위기를 조성하기 위하여 공동으로 노력해야 한다. In order to do a good job in professional legal education, we must distinguish skill and knowledge. Intelligent skills and practical skills. The teaching task of undergraduate law education aiming at legal profession should be to impart knowledge and cultivate intelligent skills, so that students can have solid legal knowledge, skill foundation and lifelong learning ability. The legal professional skills of students to effectively match and the future social demand for talents, education must take vocational education as the basic orientation of law, cultivate good professional skill of legal person, must stress that inquiry learning teaching of undergraduate course of law practice, to impart knowledge as the main characteristics of the type of teaching teaching to cultivate ability as the main characteristics of research-based teaching. The research-oriented teaching of law undergraduate with the goal of legal profession requires teachers to take the initiative to guide, students to take an active part in the research-oriented learning, and teachers and students to work together to construct a good teaching mode of legal knowledge impartation and legal intelligence skill training. In view of the problems in teaching practice, in order to achieve the ideal teaching effect and lay a solid foundation of legal knowledge and skills for the students to become outstanding legal talents, the following work must be done in the teaching: to make clear that the research exercise is the best way to cultivate intelligent skills; Strengthen the cultivation of students' legal information retrieval ability; Teachers take their role in teaching seriously; Build a good teaching atmosphere.

A Novel Fixed Twin-Rotor Unmanned Aerial Vehicle with Variable Angle Louver Rudder

Yixin Zhang,Jianfeng Zhou,Shaoping Wang,Mengqi Yang,Shaoshi Li 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10

A novel fixed twin-rotor unmanned aerial vehicle (UAV) based on the variable angle louver rudder (VALR) is developed in this work. In view of the mechanical characteristics under the action of the louver rudder, specific kinematics and dynamics models are derived. The aerodynamic characteristics of the UAV are studied through computational fluid dynamics simulation, and a ground measurement system is designed to analyze the aerodynamic characteristics of the prototype. An attitude control model is proposed, and maneuvers such as take-off, landing, hovering, and braking are realized through flight experiments, which verify the feasibility of the prototype design. This research shows that the new layout with the VALR system, combined with the advantages of rudder control and vector control, can reduce the structural complexity and deadweight of the UAV while ensuring flight stability and improving maneuverability. Moreover, the novel UAV has higher energy efficiency and economy.

Scattering Correction for Image Reconstruction in Flash Radiography

LIANGZHI CAO,Mengqi Wang,Hongchun Wu,Zhouyu Liu,Yuxiong Cheng,Hongbo Zhang 한국원자력학회 2013 Nuclear Engineering and Technology Vol.45 No.4

Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.

SCATTERING CORRECTION FOR IMAGE RECONSTRUCTION IN FLASH RADIOGRAPHY

Cao, Liangzhi,Wang, Mengqi,Wu, Hongchun,Liu, Zhouyu,Cheng, Yuxiong,Zhang, Hongbo Korean Nuclear Society 2013 Nuclear Engineering and Technology Vol.45 No.4

Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.

Comparative Study of Exposure Assessment of Dust in Building Materials Enterprises Using ART and Monte Carlo

Jiang Wei,Wu Zonghao,Zhang Mengqi,Zhang Haoguang 한국산업안전보건공단 산업안전보건연구원 2024 Safety and health at work Vol.15 No.1

Background Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m3. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m3. Conclusion ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m3; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m3. Background Dust generated during the processing of building materials enterprises can pose a serious health risk. The study aimed to compare and analyze the results of ART and the Monte Carlo model for the dust exposure assessment in building materials enterprises, to derive the application scope of the two models. Methods First, ART and the Monte Carlo model were used to assess the exposure to dust in each of the 15 building materials enterprises. Then, a comparative analysis of the exposure assessment results was conducted. Finally, the model factors were analyzed using correlation analysis and the scope of application of the models was determined. Results The results show that ART is mainly influenced by four factors, namely, localized controls, segregation, dispersion, surface contamination, and fugitive emissions, and applies to scenarios where the workplace information of the building materials enterprises is specific and the average dust concentration is greater than or equal to 1.5 mg/m3. The Monte Carlo model is mainly influenced by the dust concentration in the workplace of building materials enterprises and is suitable for scenarios where the dust concentration in the workplace of the building materials enterprises is relatively uniform and the average dust concentration is less than or equal to 6mg/m3. Conclusion ART is most accurate when workplace information is specific and average dust concentration is > 1.5 mg/m3; whereas, The Monte Carlo model is the best when dust concentration is homogeneous and average dust concentration is < 6 mg/m3.

Automatic assessment of post-earthquake buildings based on multi-task deep learning with auxiliary tasks

Huamei Zhu,Zhihang Li,Mengqi Huang,Pengxuan Ji,Hongyu Huang,Qianbing Zhang 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.4

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

One-step deep learning-based method for pixel-level detection of fine cracks in steel girder images

Huamei Zhu,Zhihang Li,Mengqi Huang,Pengxuan Ji,Qianbing Zhang 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.29 No.1

Identifying fine cracks in steel bridge facilities is a challenging task of structural health monitoring (SHM). This study proposed an end-to-end crack image segmentation framework based on a one-step Convolutional Neural Network (CNN) for pixel-level object recognition with high accuracy. To particularly address the challenges arising from small object detection in complex background, efforts were made in loss function selection aiming at sample imbalance and module modification in order to improve the generalization ability on complicated images. Specifically, loss functions were compared among alternatives including the Binary Cross Entropy (BCE), Focal, Tversky and Dice loss, with the last three specialized for biased sample distribution. Structural modifications with dilated convolution, Spatial Pyramid Pooling (SPP) and Feature Pyramid Network (FPN) were also performed to form a new backbone termed CrackDet. Models of various loss functions and feature extraction modules were trained on crack images and tested on full-scale images collected on steel box girders. The CNN model incorporated the classic U-Net as its backbone, and Dice loss as its loss function achieved the highest mean Intersection-over-Union (mIoU) of 0.7571 on full-scale pictures. In contrast, the best performance on cropped crack images was achieved by integrating CrackDet with Dice loss at a mIoU of 0.7670.