• 제목/요약/키워드: Distillation boundary

검색결과 6건 처리시간 0.021초

Numerical study of desalination by Sweeping Gas Membrane Distillation

  • Loussif, Nizar;Orfi, Jamel
    • Membrane and Water Treatment
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    • 제11권5호
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    • pp.353-361
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    • 2020
  • The present study deals with a numerical investigation of heat and mass transfer in a Sweeping Gas Membrane Distillation (SGMD) used for desalination. The governing equations expressing the conservation of mass, momentum, energy and species with coupled boundary conditions were solved numerically. The slip boundary condition applied on the feed saline solution-hydrophobic membrane interface is taken into consideration showing its effects on profiles and process parameters.The numerical model was validated with available experimental data and was found to be in good agreement particularly when the slip condition is considered. The results of the simulations highlighted the effect of slip boundary condition on the velocity and temperature distributions as well as the process effectiveness. They showed in particular that as the slip length increases, the permeate flux of fresh water and process thermal efficiency rise.

에너지 절약형 증류시스템의 에탄올 제조공정에의 응용 (Application of Energy-Efficient Distillation System in Ethanol Process)

  • 이문용;김영한
    • Korean Chemical Engineering Research
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    • 제46권5호
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    • pp.892-897
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    • 2008
  • 열복합 증류탑을 활용하여 기존의 에탄올 농축공정보다 에너지 사용량을 절감한 새로운 에탄올 농축공정을 제안하였다. 벤젠을 분리제로 사용한 제안된 증류 시스템은 증류곡선이 평형농도 곡선과 유사하게 분포되도록 설계되었으며, 증류영역의 경계에 가까운 원료 조성을 가지도록 설계하여 최대의 증류효율을 얻도록 구성하였다. 본 연구의 증류시 스템은 기존의 농축시스템에 비해 약 18%의 에너지 절감효과를 얻을 수 있었다. 또, 여타의 유사한 공비증류 공정에 활용할 수 있는 설계방안을 제시하였다.

지식의 증류기법을 이용한 샷 경계 검출 모델 (Shot Boundary Detection Model using Knowledge Distillation)

  • 박성민;윤의녕;조근식
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송∙미디어공학회 2019년도 하계학술대회
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    • pp.29-31
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    • 2019
  • 샷 경계 검출(Shot Boundary Detection)은 영상 콘텐츠 분석을 위한 필수적인 기술이며, 다양한 방식으로 편집된 영상의 샷 경계를 정확하게 검출하기 위한 연구가 지속되어 왔다. 그러나 기존에 연구들은 고정된 샷 경계 검출 알고리즘이나 매뉴얼한 작업과 같이 학습이 불가능한 과정이 포함되어 있어 성능 개선에 한계가 있었다. 본 논문에서는 이러한 과정을 제거한 End-to-End 모델을 제안한다. 제안하는 모델은 시공간 정보 추출성능을 높이기 위해 행동 인식 데이터셋을 이용한 전이학습을 사용하고, 샷 경계 검출 성능을 높이기 위해 개선된 지식의 증류기법(Knowledge Distillation)을 결합한다. 제안하는 모델은 ClipShots 데이터셋에서 DeepSBD 에 비해 cut transition 과 gradual transition 이 각각 5.4%, 41.29% 높은 성능을 보였고, DSM 과의 비교에서 cut transition 의 정확도가 1.3% 더 높은 결과를 보였다.

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Steady State Design for the Separation of Acetone-Chloroform Maximum Boiling Azeotrope Using Three Different Solvents

  • Pokhrel, Manish;Owusu, Asante Daniel;Cho, Jungho
    • Korean Chemical Engineering Research
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    • 제55권4호
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    • pp.490-496
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    • 2017
  • We have designed an extractive distillation for separating maximum boiling azeotrope of acetone-chloroform system. PRO/II 9.4 was used to simulate the overall process. The VLE data adopted from Dortmund data bank was regressed to obtain a new set of binary interaction parameters. Three different entrainers were used for the separation process--dimethyl sulfoxide (DMSO), ethylene glycol (EG) and benzene--to test their viability for the acetone-chloroform system. Thermodynamic feasibility analysis was done through ternary map diagrams. Two different thermodynamic models, NRTL and UNIQUAC, were explored for the study of overall process.

임베디드 시스템에서의 객체 분류를 위한 인공 신경망 경량화 연구 (Neural Network Model Compression Algorithms for Image Classification in Embedded Systems)

  • 신희중;오현동
    • 로봇학회논문지
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    • 제17권2호
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    • pp.133-141
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    • 2022
  • This paper introduces model compression algorithms which make a deep neural network smaller and faster for embedded systems. The model compression algorithms can be largely categorized into pruning, quantization and knowledge distillation. In this study, gradual pruning, quantization aware training, and knowledge distillation which learns the activation boundary in the hidden layer of the teacher neural network are integrated. As a large deep neural network is compressed and accelerated by these algorithms, embedded computing boards can run the deep neural network much faster with less memory usage while preserving the reasonable accuracy. To evaluate the performance of the compressed neural networks, we evaluate the size, latency and accuracy of the deep neural network, DenseNet201, for image classification with CIFAR-10 dataset on the NVIDIA Jetson Xavier.

Heat and mass transfer analysis in air gap membrane distillation process for desalination

  • Pangarkar, Bhausaheb L.;Sane, Mukund G.
    • Membrane and Water Treatment
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    • 제2권3호
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    • pp.159-173
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    • 2011
  • The air gap membrane distillation (AGMD) process was applied for water desalination. The main objective of the present work was to study the heat and mass transfer mechanism of the process. The experiments were performed on a flat sheet module using aqueous NaCl solutions as a feed. The membrane employed was hydrophobic PTFE of pore size 0.22 ${\mu}m$. A mathematical model is proposed to evaluate the membrane mass transfer coefficient, thermal boundary layers' heat transfer coefficients, membrane / liquid interface temperatures and the temperature polarization coefficients. The mass transfer model was validated by the experimentally and fitted well with the combined Knudsen and molecular diffusion mechanism. The mass transfer coefficient increased with an increase in feed bulk temperature. The experimental parameters such as, feed temperature, 313 to 333 K, feed velocity, 0.8 to 1.8 m/s (turbulent flow region) were analyzed. The permeation fluxes increased with feed temperature and velocity. The effect of feed bulk temperature on the boundary layers' heat transfer coefficients was shown and fairly discussed. The temperature polarization coefficient increased with feed velocity and decreased with temperature. The values obtained were 0.56 to 0.82, indicating the effective heat transfer of the system. The fouling was observed during the 90 h experimental run in the application of natural ground water and seawater. The time dependent fouling resistance can be added in the total transport resistance.