• Title/Summary/Keyword: Input Generator

Search Result 523, Processing Time 0.02 seconds

Study on Hydrogen Production and CO Oxidation Reaction using Plasma Reforming System with PEMFC (고분자 전해질 연료전지용 플라즈마 개질 시스템에서 수소 생산 및 CO 산화반응에 관한 연구)

  • Hong, Suck Joo;Lim, Mun Sup;Chun, Young Nam
    • Korean Chemical Engineering Research
    • /
    • v.45 no.6
    • /
    • pp.656-662
    • /
    • 2007
  • Fuel reformer using plasma and shift reactor for CO oxidation were designed and manufactured as $H_2$ supply device to operate a polymer electrolyte membrane fuel cell (PEMFC). $H_2$ selectivity was increased by non-thermal plasma reformer using GlidArc discharge with Ni catalyst simultaneously. Shift reactor was consisted of steam generator, low temperature shifter, high temperature shifter and preferential oxidation reactor. Parametric screening studies of fuel reformer were conducted, in which there were the variations of the catalyst temperature, gas component ratio, total gas ratio and input power. and parametric screening studies of shift reactor were conducted, in which there were the variations of the air flow rate, stema flow rate and temperature. When the $O_2/C$ ratio was 0.64, total gas flow rate was 14.2 l/min, catalytic reactor temperature was $672^{\circ}C$ and input power 1.1 kJ/L, the production of $H_2$ was maximized 41.1%. And $CH_4$ conversion rate, $H_2$ yield and reformer energy density were 88.7%, 54% and 35.2% respectively. When the $O_2/C$ ratio was 0.3 in the PrOx reactor, steam flow ratio was 2.8 in the HTS, and temperature were 475, 314, 260, $235^{\circ}C$ in the HTS, LTS, PrOx, the conversion of CO was optimized conditions of shift reactor using simulated reformate gas. Preheat time of the reactor using plasma was 30 min, component of reformed gas from shift reactor were $H_2$ 38%, CO<10 ppm, $N_2$ 36%, $CO_2$ 21% and $CH_4$ 4%.

60 GHz CMOS SoC for Millimeter Wave WPAN Applications (차세대 밀리미터파 대역 WPAN용 60 GHz CMOS SoC)

  • Lee, Jae-Jin;Jung, Dong-Yun;Oh, Inn-Yeal;Park, Chul-Soon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.21 no.6
    • /
    • pp.670-680
    • /
    • 2010
  • A low power single-chip CMOS receiver for 60 GHz mobile application are proposed in this paper. The single-chip receiver consists of a 4-stage current re-use LNA with under 4 dB NF, Cgs compensating resistive mixer with -9.4 dB conversion gain, Ka-band low phase noise VCO with -113 dBc/Hz phase noise at 1 MHz offset from 26.89 GHz, high-suppression frequency doubler with -0.45 dB conversion gain, and 2-stage current re-use drive amplifier. The size of the fabricated receiver using a standard 0.13 ${\mu}m$ CMOS technology is 2.67 mm$\times$0.75 mm including probing pads. An RF bandwidth is 6.2 GHz, from 55 to 61.2 GHz and an LO tuning range is 7.14 GHz, from 48.45 GHz to 55.59 GHz. The If bandwidth is 5.25 GHz(4.75~10 GHz) The conversion gain and input P1 dB are -9.5 dB and -12.5 dBm, respectively, at RF frequency of 59 GHz. The proposed single-chip receiver describes very good noise performances and linearity with very low DC power consumption of only 21.9 mW.

True Orthoimage Generation from LiDAR Intensity Using Deep Learning (딥러닝에 의한 라이다 반사강도로부터 엄밀정사영상 생성)

  • Shin, Young Ha;Hyung, Sung Woong;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.38 no.4
    • /
    • pp.363-373
    • /
    • 2020
  • During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.