• Journal of Korean Society of Environmental Engineers
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• v.39 no.6
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• pp.356-370
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• 2017

The energy savings and $CO_2$ emission reductions obtainable from the situation that the Smart Grid system (SGs) is assumed to be applied in Korea up to 2030 is quantitatively analyzed with many reported data. For calculation, SGs is divided into five sectors such as Smart Transmission and Distribution (ST&D), Smart Consumer (SC), Smart Electricity Service (SES), Smart Renewable Energy (SRE) and Smart Transportation (ST). Total annual energy savings in 2030 is estimated to be approximately 103,121 GWh and this is 13.1% of total electricity consumption outlook. Based on this value, total amount of reducible $CO_2$ emissions is calculated to 55.38 million $tCO_2$, which is 17.6% of total nation's GHG reduction target. Although the contribution of energy saving due to SGs to total electricity consumption increases as years go by, that of $CO_2$ emission reduction gradually decreases. This might be because that coal fired based power generation is planned to be sharply increased and the rate of $CO_2$ emission reduction scheduled by nation is very fast. The contributable portion of five each sector to total $CO_2$ emission reductions in 2030 is estimated to be 44.37% for SC, 29.16% for SRE, 20.12% for SES, 5.11% for ST&D, and 1.24% for ST.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).

• Journal of Bio-Environment Control
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• v.24 no.2
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• pp.100-105
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• 2015

The calculation method of infiltration loss in greenhouse has different ideas in each design standard, so there is a big difference in each method according to the size of greenhouses, it is necessary to establish a more accurate method that can be applied to the domestic. In order to provide basic data for the formulation of the calculation method of greenhouse heating load, we measured the infiltration rates using the tracer gas method in plastic greenhouses equipped with various thermal curtains. And then the calculation methods of infiltration loss in greenhouses were reviewed. Infiltration rates of the multi-span and single-span greenhouses were measured in the range of $0.042{\sim}0.245h^{-1}$ and $0.056{\sim}0.336h^{-1}$ respectively, single-span greenhouses appeared to be slightly larger. Infiltration rate of the greenhouse has been shown to significantly decrease depending on the number of thermal curtain layers without separation of single-span and multi-span. As the temperature differences between indoor and outdoor increase, the infiltration rates tended to increase. In the range of low wind speed during the experiments, changes of infiltration rate according to the outdoor wind speed could not find a consistent trend. Infiltration rates for the greenhouse heating design need to present the values at the appropriate temperature difference between indoor and outdoor. The change in the infiltration rate according to the wind speed does not need to be considered because the maximum heating load is calculated at a low wind speed range. However the correction factors to increase slightly the maximum heating load including the overall heat transfer coefficient should be applied at the strong wind regions. After reviewing the calculation method of infiltration loss, a method of using the infiltration heat transfer coefficient and the greenhouse covering area was found to have a problem, a method of using the infiltration rate and the greenhouse volume was determined to be reasonable.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.409-417
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• 2013

Mu-communication board supported by multi-communication is designed with Atxmega 128A1 which is a low power energy consuming of 8-bit microcontroller. ATxmega128A1 microcontroller consists of 8 UART(Universal asynchronous receiver/transmitter) ports which can be setting appropriate user interface having command line interpreter(CLI) program with each port, 2 kbytes EEPROM, 128 kbytes flash memory, 8 kbytes SRAM. 8 URAT ports are used for the multi communication modem, GPS module, etc. and EEPROM is used for saving a configuration for program running, and flash memory of 128 kbytes is used for storing a Firm Ware, and 8 kbytes SRAM is used for stack, storing memory of global variables while program running. If we uses the hybrid communication of path optimization of VHF, TRS and CDMA to remote control AtoN(aid to navigation), it is able to remove the communication shadow area. Even though there is a shadow area for individual communication method, we can select an optimum communication method. The compatibility of data has been enhanced as using of same data frame per communication devices. For the test, 8640 of data has been collected from the each buoy during 30 days in every 5 minutes and the receiving rate of the data has shown more than 99.4 %.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.1
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• pp.40-49
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• 1986

Crack, craze and void are common defects which may be found in the bulk of polymeric materials such as either themoplastics or thermosets. The healing phenomena, autohesion, of these defects are known to be a intrinsic material property of various polymeric materials. However, only a few experimental and theoretical investigations on crack, void and craze healing phenomena for various polymeric materials have been reported up to date [1, 2, 3]. This may be partly due to the complications of healing processes and lacking of appropriate theoretical developments. Recently, some investigators have been urged to study the healing phenomena of various polymenic materials since the significance of the use of polymer based alloys or composites has been raised in terms of specific strength and energy saving. In the earlier published reports [1, 2, 3, 4], the crack and void healing velocity, healing toughness and some other healing mechanical and physical properties were measured experimentally and compared with predicted values by utilizing a simple model such as the reptation model under some resonable assumptions. It seems, however, that the general acceptance of the proposed modeling analyses is yet open question. The crack healing processes seem to be complicate and highly dependent on the state of virgin material in terms of mechanical and physical properties. Furthermore, it is also strongly dependent on the histories of crack, craze and void development including fracture suface morphology, the shape of void and the degree of disentanglement of fibril in the craze. The rate of crack healing may be a function of environmental factors such as healing temperature, time and pressure which gives different contact configurations between two separated surfaces. It seems to be reasonable to assume that the crack healing processes may be divided in several distinguished steps like stress relaxation with molecular chain arrangement, surface contact (wetting), inter- diffusion process and com;oete healing (to obtain the original strength). In this context, it is likely that we no longer have to accept the limitation of cumulative damage theories and fatigue life if it is probable to remove the defects such as crack, craze and void and to restore the original strength of polymers or polymer based compowites by suitable choice of healing histories and methods. In this paper, we wish to present a very simple and intuitive theoretical model for the prediction of healed fracture toughness of cracked or defective polymeric components. The central idea of this investigation, thus, may be the modeling of behavior of chain molecules under healing conditions including the effects of chain scission on the healing processes. The validity of this proposed model will be studied by making comparisons between theoretically predicted values and experimentally determined results in near future and will be reported elsewhere.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.