• 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$_{o}$).

• The Korean Journal of Physiology
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• v.1 no.1
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• pp.103-120
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• 1967

As pointed out by many previous investigators, the cardio-pulmonary system of well trained athletes is so adapted that they can perform a given physical exercise more efficiently as compared to non-trained persons. However, the time course of the development of these cardio-pulmonary adaptations has not been extensively studied in the past. Although the development of these training effects is undoubtedly related to the magnitude of an exercise load which is repeatedly given, it would be practical if one could maintain a good physical fitness with a minimal daily exercise. Hence, the present investigation was undertaken to study the time course of the development of cardio-pulmonary adaptations while a group of non-athletes was subjected to a daily 6 to 10 minutes running exercise for a period of 4 weeks. Six healthy male medical students (22 to 24 years old) were randomly selected as experimental subjects, and were equally divided into two groups (A and B). Both groups were subjected to the same daily running exercise (approximately 1,000 kg-m). 6 days a week for 4 weeks, but the rate of exercise was such that the group A ran on treadmill with 8.6% grade for 10 min daily at a speed of 127 m/min while the group B ran for 6 min at a speed of 200 m/min. In order to assess the effects of these physical trainings on the cardio-pulmonary system, the minute volume, the $O_2$ consumption, the $CO_2$ output and the heart rate were determined weekly while the subject was engaged in a given running exercise on treadmill (8.6% grade and 127 m/min) for a period of 5 min. In addition, the arterial blood pressure, the cardiac output, the acid-base state of arterial blood and the gas composition of arterial blood were also determined every other week in 4 subjects (2 from each group) while they were engaged in exercise on a bicycle ergometer at a rate of approximately 900 kg m/min until exhaustion. The maximal work capacity was also determined by asking the subject to engage in exercise on treadmill and ergometer until exhaustion. For the measurement of minute volume, the expired gas was collected in a Douglas bag. The $O_2$ consumption and the $CO_2$ output were subsequently computed by analysing the expired gas with a Scholander micro gas analyzer. The heart rate was calculated from the R-R interval of ECG tracings recorded by an Offner RS Dynograph. A 19 gauge Cournand needle was inserted into a brachial artery, through which arterial blood samples were taken. A Statham $P_{23}AA$ pressure transducer and a PR-7 Research Recorder were used for recording instantaneous arterial pressure. The cardiac output was measured by indicator (Cardiogreen) dilution method. The results may be summarized as follows: (1) The maximal running time on treadmill increased linearly during the 4 week training period at the end of which it increased by 2.8 to 4.6 times. In general, an increase in the maximal running time was greater when the speed was fixed at a level at which the subject was trained. The mammal exercise time on bicycle ergometer also increased linearly during the training period. (2) In carrying out a given running exercise on treadmill (8.6%grade, 127 m/min), the following changes in cardio·pulmonary functions were observed during the training period: (a) The minute volume as well as the $O_2$ consumption during steady state exercise tended to decrease progressively and showed significant reductions after 3 weeks of training. (b) The $CO_2$ production during steady state exercise showed a significant reduction within 1 week of training. (c) The heart rate during steady state exercise tended to decrease progressively and showed a significant reduction after 2 weeks of training. The reduction of heart rate following a given exercise tended to become faster by training and showed a significant change after 3 weeks. Although the resting heart rate also tended to decrease by training, no significant change was observed. (3) In rallying out a given exercise (900 kg-m/min) on a bicycle ergometer, the following change in cardio-vascular functions were observed during the training period: (3) The systolic blood pressure during steady state exercise was not affected while the diastolic blood Pressure was significantly lowered after 4 weeks of training. The resting diastolic pressure was also significantly lowered by the end of 4 weeks. (b) The cardiac output and the stroke volume during steady state exercise increased maximally within 2 weeks of training. However, the resting cardiac output was not altered while the resting stroke volume tended to increase somewhat by training. (c) The total peripheral resistance during steady state exercise was greatly lowered within 2 weeks of training. The mean circulation time during exorcise was also considerably shortened while the left heart work output during exercise increased significantly within 2 weeks. However, these functions_at rest were not altered by training. (d) Although both pH, $P_{co2}\;and\;(HCO_3-)$ of arterial plasma decreased during exercise, the magnitude of reductions became less by training. On the other hand, the $O_2$ content of arterial blood decreased during exercise before training while it tended to increase slightly after training. There was no significant alteration in these values at rest. These results indicate that cardio-pulmonary adaptations to physical training can be acquired by subjecting non-athletes to brief daily exercise routine for certain period of time. Although the time of appearance of various adaptive phenomena is not identical, it may be stated that one has to engage in daily exercise routine for at least 2 weeks for the development of significant adaptive changes.