The Development of the Analysis Tool for Wind Resource using the LabVIEW

Fang-Hao Piao(박방호),Chae-Joo Moon(문채주),Tae-Gon Kim(김태곤),Byeong-Ju Park(박병주),Yeong-Hak Jang(장영학) 한국태양에너지학회 2014 한국태양에너지학회 학술대회논문집 Vol.2014 No.3

Attenuation effects of perforated plates with heterogeneously distributed holes on combustion instability in a spray flame combustor

Hao Zhou,Zihua Liu,Hao Fang,Chengfei Tao,Mingxi Zhou,Liubin Hu 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.11

Perforated plates have been widely used in combustors to attenuate harmful sounds. In this study, the acoustic absorption capability of plates with heterogeneously distributed holes under bias flow was evaluated in an impedance tube, and the sound attenuation effect of each plate located in the liquid fuel combustor inlet section was experimentally studied. The perforated plate with heterogeneously distributed large holes showed the best control effect under the designed experimental conditions. After control, the peak dynamic pressure in the chamber and plenum decreased by 90 % and 75 %, respectively, and the reduction in the heat release fluctuation was 60 %. When the primary air flow rate deviated from the optimal value, the plate with large holes still reduced the pressure amplitude in the chamber by approximately 70 %. It was also found that installing the perforated plate with a back cavity had the dual effect of gaining and damping combustion instability.

Classifying Endemic Fagaceae Species in Taiwan using Leaf Images

( Hao-chun Hsu ),( Cheng-hao Lee ),( Chih-kai Yang ),( Fang-hua Chu ),( Ming-jer Tsai ),( Yan-fu Kuo ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1

Fagaceae is one of the plant family which dominate the broad-leaved forests in Taiwan and have considerable value in economy and ecology. Traditionally, plant species identification based on leaf morphologies and is conducted using naked-eye observation. This study is proposed to distinguish the Fagaceae species using image processing and machine learning. In this study, leaf images of 10 Fagaceae species were collected. A serial of traits relevant to leaf morphologies, such as morphological, color, shape, and venation traits, were quantified from the leaf images. A support vector machine classifier was then developed to identify the species using the quantified traits. The proposed approach reached an identification accuracy of 95.8%.

Dynamic self-collision detection and prevention for 2-DOF robot arms using interval-based analysis

Hao Fang,Jie Chen,Lihua Dou 대한기계학회 2011 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.25 No.8

The problems related to self-collision detection and optimal collision-free trajectory planning for a robot arm subjected to dynamic constraints is investigated. First, a computed-torque method is used to obtain a linearized closed-loop system. For this linearized system,the reference state that the robot arm is capable of reaching is verified through phase plane analysis. This will ensure that the robot arm can be stopped before self-collision occurs. Dynamic constraints are taken into account for a continuous motion of deceleration by calculating the bounds of the commanded force/torques with interval evaluations. When the reference state at t+δt is not valid for selfcollision avoidance, a new feasible state is determined by adhering to an interval-based method which allows decomposition of a complex constrained optimization problem into a simple two-stage optimization problem with relaxed constraints. The optimized feasible state not only secures the robot arm against self-collision but also allows the robot arm to track the original reference trajectory closely. Simulation and experimental results of a 2-dof robot arm show the effectiveness of the proposed interval-based approach.

Enhanced Cellulolytic Enzyme Production by the Synergism between Trichoderma reesei RUT-C30 and Aspergillus niger NL02 and by the Addition of Surfactants

Hao Fang,Chen Zhao,Xiang-Yang Song,Mu Chen,Zheng Chang,Jie Chu 한국생물공학회 2013 Biotechnology and Bioprocess Engineering Vol.18 No.2

Two improvement approaches comprising of a mixed culture of Trichoderma reesei and Aspergillus niger and the addition of surfactants were employed in this study in order to enhance cellulolytic enzyme production as well as to improve the composition. Different delay times of A. niger inoculation (0, 24, and 48 h) and inoculum ratios of T. reesei versus A. niger (1:1 and 5:1) derived six mixed culture forms, which were 0 h/1:1, 0 h/5:1, 24 h/1:1, 24 h/5:1,48 h/1:1, and 48 h/5:1. It was found that the form 48 h/5:1allowed the highest FPA, 3.30 ± 0.34 IU/mL, and a relatively high BGA, 1.01 ± 0.25 IU/mL, thereafter being selected for the subsequent improvement step addition of surfactants. Among the three surfactants, including Triton X-100, CHAPS and sodium taurocholate, the third one was found to be the best one giving rise to the highest FPA and BGA, 5.02 ± 0.40 and 1.48 ± 0.28 IU/mL, respectively. Differently sourced cellulases were compared in the enzymatic hydrolysis of steam-exploded corn stover (SECS). Moreover, the cellulase produced by the mixed culture form 48 h/5:1 using SECS as a substrate showed the highest yield at 80.93 ± 2.04%, indicating that the composition of this cellulase was improved by the mixed culture of T. reesei and A. niger. The results validate that these two improvement approaches are efficient and applicable in cellulase production.

Biotechnological Advances and Trends in Engineering Trichoderma reesei towards Cellulase Hyperproducer

Hao Fang,Chaofeng Li,Jiajia Zhao,Chen Zhao 한국생물공학회 2021 Biotechnology and Bioprocess Engineering Vol.26 No.4

Cellulase has the biggest contribution to the high production costs of lignocellulose bioconversion and the substantial decrease of its production cost is the key to the commercialization of lignocellulosic biorefineries. Trichoderma reesei has the most robust cellulase among the candidates, which therefore is widely used for cellulase production in industry. This is not because of the size of its cellulase gene pool but its prodigious cargo of cellulase productivity. Still, T. reesei cellulase falls far short of perfection in real-world applications, especially for the composition. This review summarized the biotechnological advances in engineering T. reesei for enhanced cellulase production. Meanwhile, we proposed innovative ideas of systematically optimizing cellulase composition at the transcriptional level and improving cellulase production at the regulation level. Efficient genome editing is essential to achieving that target. Thus, the developments of the tools of multiple gene manipulations were discussed in detail here. This review provides ideas and/or inspirations to the future researches on T. reesei cellulase.

Control of thermoacoustic instability of liquid-spray flame with porous sound absorber

Hao Zhou,Hao Fang,Dongliang Wei,Zihua Liu,Zhaowen Wang,Hanxiao Meng 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.8

A kind of porous sound absorber was studied to control the thermoacoustic oscillation of liquid mist flame, which combined natural fibrous materials and perforated plate. It could optimize the sound absorption characteristics of fibrous materials by adding perforated plate and air cavity. The influences of the interlayer and back cavity depth of two kinds of fibrous materials with the mass of 20, 30, 40 g were investigated experimentally in an impedance tube and applied to control the oscillating ethanol flame. The results showed that the best depth of interlayer and back cavity were 20 cm and 30 cm, respectively. The addition of two kinds of fiber sandwich structures could reduce the amplitude of the sound pressure oscillation in the combustion chamber by 89.2 % and 92.6 %, as well as 88.0 % and 91.2 % in the plenum chamber, meanwhile, restrained the flame heat release fluctuation by 73 %. It was proved that the porous sound absorber could act as a damp in the acoustic transmission path and suppress the sound source.

Nitrogen-doped graphene loaded non-noble Co catalysts for liquid-phase cyclohexane oxidation with molecular oxygen

Fang Hao,Yuan Sun,Yidi Wang,Yang Lv,Pingle Liu,Xiong Wei,Hean Luo 한국화학공학회 2021 Korean Journal of Chemical Engineering Vol.38 No.8

Selective aerobic oxidation of cyclohexane to cyclohexanone and cyclohexanol (KA oil) with high yield under mild and green conditions is still a significant challenge in the current chemical industry. Herein, nitrogen doped graphene loaded non-noble Co (Co-N-rGO) catalysts, prepared by a facile post-impregnation method, exhibited a high catalytic performance and stability in liquid phase cyclohexane oxidation with molecular oxygen. The experiment and characterization results show that N doping in the catalysts promotes Co metal particle dispersion and induces carbon film coating on Co to prevent leaching and agglomeration. Besides, density functional theory (DFT) calculations show that N doping is beneficial to the O-O bonds breaking in cyclohexyl-hydroperoxides (CHHP), thereby promoting the dissociation of CHHP and enhancing the yield to KA oil. In addition, the catalyst can be easily separated without appreciable loss of catalytic activity after recycling for five times, and show potential industrial application value for the catalytic oxidation of cyclohexane to KA oil in the chemical industry.

Selective hydrogenation of benzene over Ru supported on surface modified TiO2

Fang Hao,Jingsong Zheng,Donghong Ouyang,Wei Xiong,Pingle Liu,Hean Luo 한국화학공학회 2021 Korean Journal of Chemical Engineering Vol.38 No.4

A series of catalysts with ruthenium nanoparticles (NPs) loaded on the binary oxide TS (TiO2-SiO2) support were prepared by facile sol-gel method for benzene selective hydrogenation. Different mole ratios of Ti/Si were investigated. The catalytic structure, composition, hydrophilicity, electronic state and acidity were characterized. The results indicate that the acidity of the samples increases gradually with the increase of the SiO2 amount. The dispersion of ruthenium nanoparticles was improved on binary oxide support compared with TiO2 and an obvious Ru size effect appeared with the increase of Ti/Si molar ratio. It was also found that the hydrophilicity of the supports could be efficiently improved by introducing a small amount of SiO2 to TiO2, which may be due to the large amount of surface hydroxyl groups on the binary oxide samples after SiO2 introduction. This result was consistent with the increasing trend of cyclohexene yield, indicating that the surface hydroxyl groups play a significant role in the motivation of cyclohexene desorption. Ru/TS (7 : 1) showed the best catalytic performance of 38.2% yield to cyclohexene with the highest initial selectivity to cyclohexene (S0) of 87.3%. The catalytic stability experiments showed that the yield of cyclohexene could maintain at 30% after five cycles.

Deep learning-based recovery method for missing structural temperature data using LSTM network

Liu, Hao,Ding, You-Liang,Zhao, Han-Wei,Wang, Man-Ya,Geng, Fang-Fang Techno-Press 2020 Structural monitoring and maintenance Vol.7 No.2

Benefiting from the massive monitoring data collected by the Structural health monitoring (SHM) system, scholars can grasp the complex environmental effects and structural state during structure operation. However, the monitoring data is often missing due to sensor faults and other reasons. It is necessary to study the recovery method of missing monitoring data. Taking the structural temperature monitoring data of Nanjing Dashengguan Yangtze River Bridge as an example, the long short-term memory (LSTM) network-based recovery method for missing structural temperature data is proposed in this paper. Firstly, the prediction results of temperature data using LSTM network, support vector machine (SVM), and wavelet neural network (WNN) are compared to verify the accuracy advantage of LSTM network in predicting time series data (such as structural temperature). Secondly, the application of LSTM network in the recovery of missing structural temperature data is discussed in detail. The results show that: the LSTM network can effectively recover the missing structural temperature data; incorporating more intact sensor data as input will further improve the recovery effect of missing data; selecting the sensor data which has a higher correlation coefficient with the data we want to recover as the input can achieve higher accuracy.