Convective Heat Transfer Coeicient Model Under Nanoluid Minimum Quantity Lubrication Coupled with Cryogenic Air Grinding Ti–6Al–4V

Jianchao Zhang,Wentao Wu,Changhe Li,Min Yang,Yanbin Zhang,Dongzhou Jia,Yali Hou,Runze Li,Huajun Cao,Hafiz Muhammad Ali 한국정밀공학회 2021 International Journal of Precision Engineering and Vol.8 No.4

Under the threat of serious environmental pollution and resource waste, sustainable development and green manufacturing have gradually become a new development trend. A new environmentally sustainable approach, namely, cryogenic air nanofluid minimum quantity lubrication (CNMQL), is proposed considering the unfavorable lubricating characteristic of cryogenic air (CA) and the deficient cooling performance of minimum quantity lubrication (MQL). However, the heat transfer mechanism of vortex tube cold air fraction by CNMQL remains unclear. The cold air fraction of vortex tubes influences the boiling heat transfer state and cooling heat transfer performance of nanofluids during the grinding process. Thus, a convective heat transfer coefficient model was established based on the theory of boiling heat transfer and conduction, and the numerical simulation of finite difference and temperature field in the grinding zone under different vortex tube cold air fractions was conducted. Simulation results demonstrated that the highest temperature initially declines and then rises with increasing cold air fraction. Afterward, this temperature reaches the lowest peak (192.7 °C) when the cold air fraction is 0.35. Experimental verification was conducted with Ti–6Al–4V to verify the convective heat transfer coefficient model. The results concluded that the low specific grinding energy (66.03 J/mm 3 ), high viscosity (267.8 cP), and large contact angle (54.01°) of nanofluids were obtained when the cold air fraction was 0.35. Meanwhile, the lowest temperature of the grinding zone was obtained (183.9 °C). Furthermore, the experimental results were consistent with the theoretical analysis, thereby verifying the reliability of the simulation model.

Two-Dimensional Unilamellar Cation-Deficient Metal Oxide Nanosheet Superlattices for High-Rate Sodium Ion Energy Storage

Xiong, Pan,Zhang, Xiuyun,Zhang, Fan,Yi, Ding,Zhang, Jinqiang,Sun, Bing,Tian, Huajun,Shanmukaraj, Devaraj,Rojo, Teofilo,Armand, Michel,Ma, Renzhi,Sasaki, Takayoshi,Wang, Guoxiu American Chemical Society 2018 ACS NANO Vol.12 No.12

<P>Cation-deficient two-dimensional (2D) materials, especially atomically thin nanosheets, are highly promising electrode materials for electrochemical energy storage that undergo metal ion insertion reactions, yet they have rarely been achieved thus far. Here, we report a Ti-deficient 2D unilamellar lepidocrocite-type titanium oxide (Ti<SUB>0.87</SUB>O<SUB>2</SUB>) nanosheet superlattice for sodium storage. The superlattice composed of alternately restacked defective Ti<SUB>0.87</SUB>O<SUB>2</SUB> and nitrogen-doped graphene monolayers exhibits an outstanding capacity of ∼490 mA h g<SUP>-1</SUP> at 0.1 A g<SUP>-1</SUP>, an ultralong cycle life of more than 10000 cycles with ∼0.00058% capacity decay per cycle, and especially superior low-temperature performance (100 mA h g<SUP>-1</SUP> at 12.8 A g<SUP>-1</SUP> and −5 °C), presenting the best reported performance to date. A reversible Na<SUP>+</SUP> ion intercalation mechanism without phase and structural change is verified by first-principles calculations and kinetics analysis. These results herald a promising strategy to utilize defective 2D materials for advanced energy storage applications.</P> [FIG OMISSION]</BR>

Secure and Fine-grained Electricity Consumption Aggregation Scheme for Smart Grid

( Gang Shen ),( Yixin Su ),( Danhong Zhang ),( Huajun Zhang ),( Binyu Xiong ),( Mingwu Zhang ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.4

Currently, many of schemes for smart grid data aggregation are based on a one-level gateway (GW) topology. Since the data aggregation granularity in this topology is too single, the control center (CC) is unable to obtain more fine-grained data aggregation results for better monitoring smart grid. To improve this issue, Shen et al. propose an efficient privacy-preserving cube-data aggregation scheme in which the system model consists of two-level GW. However, a risk exists in their scheme that attacker could forge the signature by using leaked signing keys. In this paper, we propose a secure and fine-grained electricity consumption aggregation scheme for smart grid, which employs the homomorphic encryption to implement privacy-preserving aggregation of users’ electricity consumption in the two-level GW smart grid. In our scheme, CC can achieve a flexible electricity regulation by obtaining data aggregation results of various granularities. In addition, our scheme uses the forward-secure signature with backward-secure detection (FSBD) technique to ensure the forward-backward secrecy of the signing keys. Security analysis and experimental results demonstrate that the proposed scheme can achieve forward-backward security of user’s electricity consumption signature. Compared with related schemes, our scheme is more secure and efficient.

Quasi-static test of the precast-concrete pile foundation for railway bridge construction

Zhang, Xiyin,Chen, Xingchong,Wang, Yi,Ding, Mingbo,Lu, Jinhua,Ma, Huajun Techno-Press 2020 Advances in concrete construction Vol.10 No.1

Precast concrete elements in accelerated bridge construction (ABC) extends from superstructure to substructure, precast pile foundation has proven a benefit for regions with fragile ecological environment and adverse geological condition. There is still a lack of knowledge of the seismic behavior and performance of the precast pile foundation. In this study, a 1/8 scaled model of precast pile foundation with elevated cap is fabricated for quasi-static test. The failure mechanism and responses of the precast pile-soil interaction system are analyzed. It is shown that damage occurs primarily in precast pile-soil interaction system and the bridge pier keeps elastic state because of its relatively large cross-section designed for railways. The vulnerable part of the precast pile with elevated cap is located at the embedded section, but no plastic hinge forms along the pile depth under cyclic loading. Hysteretic curves show no significant strength degradation but obvious stiffness degradation throughout the loading process. The energy dissipation capacity of the precast pile-soil interaction system is discussed by using index of the equivalent viscous damping ratio. It can be found that the energy dissipation capacity decreases with the increase of loading displacement due to the unyielding pile reinforcements and potential pile uplift. It is expected to promote the use of precast pile foundation in accelerated bridge construction (ABC) of railways designed in seismic regions.

An adaptive parameter optimization model and system for sustainable gear dry hobbing in batch production

Ying Zhang,Huajun Cao,Peng Chen,Li-Bin Zhu,Xiao Yang 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.6

Gear hobbing technology is one of the most widely used forming processes of gear teeth. And the development of dry hobbing technologyprovides a solution for realizing productive, economical, and ecological gear production. Since there is no cutting oil for coolingand lubrication in dry hobbing process, the hob tool life, thermal deformation errors of machine tool, and quality of workpiece are sensitiveto the cutting parameters, especially the cutting speed and tip chip thickness. Considering this situation, a dry hobbing parametersoptimization model with the hobbing efficiency as our objective, and the hobbing cost per piece, gear quality, tact time as constraints wasestablished, in which the cutting speed and tip chip thickness were considered as optimal variables and the material of workpiece, coatingof hob, and feed rate were considered comprehensively. An iterative test method is proposed to solve this model. And for the applicationin automated production line, an online adaptive application system was also developed based on SINUMERIK 840D NC system. Theparameters of five different kinds of material gear were optimized by applying this model and system, and the result showed the modeland the system were practical.

Research on bolt contour extraction and counting of locomotive running gear based on deep learning

Yong Zhang,Bo Long,Huajun Wang,Chunliang Gao 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5

The detection of abnormal running gear is essential to a locomotive’s daily maintenance, with the posture and quantity of various small bolts being important indicators to judge whether the locomotive is running safely. Traditional detection algorithms are easily affected by light changes, stain coverage, and image distortion, which is difficult to meet the detection requirements. Thus this paper proposes a deep learning based on bolt detection method that is appropriate for locomotive running gears. First, a bolt segmentation network was developed based on an improved U-netthat compensates the image information loss after multiple cross fusions involving the fusion of front and back convolution layer feature images. Furthermore, the proposed network utilizes the PReLU activation function and employs the concept structure to optimize the convolution method. This strategy aims to improve further the model’s segmentation accuracy and convergence speed. On this basis, we exploited several morphological transformations to improve the contour detection accuracy and ensure the bolt counting accuracy. The experimental results on the mainline running train data highlight that, compared with U-net, the proposed network’s recall rate and the mean intersection over union value are increased by 5.38 and 14.3, respectively. Furthermore, the bolt counting method’s loss function and mean absolute errors are significantly reduced compared with the contour extraction algorithm.

Ultra-sensitive graphene based mid-infrared plasmonic bio-chemical sensing using dielectric beads as a medium

Liu, Xiao,Zhang, Duan,Wu, Ye-Cun,Yang, Mei,Wang, Qian,Coileá,in, Cormac Ó,.,Xu, Hongjun,Yang, Chen,Abid, Mohamed,Abid, Mourad,Liu, Huajun,Chun, Byong Sun,Shi, Qingfan,Wu, Han-Chun Elsevier 2017 Carbon Vol.122 No.-

<P>Graphene is moving beyond the realm of simple electronic devices toward areas such as advanced biochemical sensing. The infrared (IR) response of graphene, characterized by collective long-lived charge-carrier oscillations, could be applied in IR-absorption spectroscopy, typically used for bio-chemical analysis. However, direct light absorption by propagating plasmons in graphene is forbidden due to the large momentum mismatch. Proposed methods to overcome this bottleneck come at a cost, the use of noble metal particles on graphene reduces the spectral bandwidth and nano-structuring graphene is expensive. Here, we propose a simple and cheap method to fabricate large scale ultra-sensitive graphene based mid-IR biosensors, by introducing dielectric beads to excite mid-IR range plasmons. Interference from waves scattered by the beads excite surface plasmon polaritons, which propagate several micrometers in graphene and enhance the interaction between the molecules and mid-IR light. This method opens an interesting window for the application of graphene in bio-chemical sensing. (C) 2017 Elsevier Ltd. All rights reserved.</P>

Obstacles modeling method in cluttered environments using satellite images and its application to path planning for USV

Binghua Shi,Huajun Zhang,Jiawen Liu,Lili Wan 대한조선학회 2019 International Journal of Naval Architecture and Oc Vol.11 No.1

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

Effects of tryptophan and phenylalanine on tryptophol production in Saccharomyces cerevisiae revealed by transcriptomic and metabolomic analyses

Gong Xiaowei,Luo Huajun,Hong Liu,Wu Jun,Wu Heng,Song Chunxia,Zhao Wei,Han Yi,Dao Ya,Zhang Xia,Zhu Donglai,Luo Yiyong 한국미생물학회 2022 The journal of microbiology Vol.60 No.8

Tryptophol (TOL) is a metabolic derivative of tryptophan (Trp) and shows pleiotropic effects in humans, plants and microbes. In this study, the effect of Trp and phenylalanine (Phe) on TOL production in Saccharomyces cerevisiae was determined, and a systematic interpretation of TOL accumulation was offered by transcriptomic and metabolomic analyses. Trp significantly promoted TOL production, but the output plateaued (231.02−266.31 mg/L) at Trp concentrations ≥ 0.6 g/L. In contrast, Phe reduced the stimulatory effect of Trp, which was strongly dependent on the Phe concentration. An integrated genomic, transcriptomic, and metabolomic analysis revealed that the effect of Trp and Phe on TOL production was mainly related to the transamination and decarboxylation of the Ehrlich pathway. Additionally, other genes, including thiamine regulon genes (this), the allantoin catabolic genes dal1, dal2, dal4, and the transcriptional activator gene aro80, may play important roles. These findings were partly supported by the fact that the thi4 gene was involved in TOL production, as shown by heterologous expression analysis. To the best of our knowledge, this novel biological function of thi4 in S. cerevisiae is reported here for the first time. Overall, our findings provide insights into the mechanism of TOL production, which will contribute to TOL production using metabolic engineering strategies.

Obstacles modeling method in cluttered environments using satellite images and its application to path planning for USV

Shi, Binghua,Su, Yixin,Zhang, Huajun,Liu, Jiawen,Wan, Lili The Society of Naval Architects of Korea 2019 International Journal of Naval Architecture and Oc Vol.11 No.1

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.