Man has brought many agricultural operations into confinement which modifies the environmental conditions from those occuring naturally. He is now faced with the problem of optimizing production or profit through structural design and management decisions. In order to accomplish this it is desireable to develop methods of accurately predicting the conditions which occur from hour to hour as well as methods to simulate conditions for aid in design.
In order to analyse the thermal environment of animal shelters, a transient method (matrix technique) has been applied (Jordan, et al.. 1968). This method evaluates the periodic responses of animal shelters as influenced by external temperature patterns. However, each harmonic term in a Fourier series representation of the outside weather conditions has to be determined separately.
In the present study, another technique of dynamic simulation (impulse method) has been used. This technique has been found useful for the analysis of greenhouse prior to this study (Takakura, 1967 and 1968). A mathematical model of the system shown in Fig. 1 is developed and the temperature regime of the system is simulated. Considering that temperature is composed of a steady state term and a transient term, the inside temperature of the animal shelter can be expressed as θ_in=θ_n+θ′_in. Where: θ_in is the inside temperature of the animal shelter; θ_in is the steady state term of the inside air termperature; and θ′_in is the transient term of the inside air temperature.
The steady state term is calculated from a fundamental heat balance (that is Eq. (1)) where each component is developed in Eq.(3) through Eq. (6). The component considered are: q_h, the heat transferred from the wall; q_v, the heat transported by ventilation; q_s, the heat transferred from the ground; and q_c, the heat produced by the animals.
The transient term is calculated by impulse technique. The basic equations are presented in Eq. (8) through Eq. (16). Using the Laplace transforms of these equations ((A-1)through (A-7) as shown in Appendix) the weighting function is given in Eq. (A-14). If a forcing function impressed upon the system is expressed as F(t) (in Eq. 17)), the response to the input would be given as R(t) (in Eq. (18)).
The Fourier coefficients of the inside and the outside air temperature calculated from the observed data are presented in Table 1. The calculated temperatures and the observed temperatures are shown in Figs. 2 and 3. The results are in good aggreement. From the present analysis, it is concluded that impulse techniques as well as matrix techniques are useful in simulation of the thermal environment of animal shelters. Previous work indicates the application to greenhouse simulation. Therefore it is concluded that these techniques have considerable generality.
The present study was conducted at University of Minnesota, where the senior author had the previlege of working with the other authors on post-doctsral studies. The computer time was supported through a grant from the University of Minnesota Computer Center and is greatfully acknowledged. The experimental data taken in a 5000 bird laying house in North Carolina, USA, was graciously supplied by Dr. Jordan.

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From 28th of June to 8th July, 1969, very active Baiu front passing through the southern past of Kyushu, especially kagoshima prefecture, brought about extraordinarily heavy railfall, and disastrous floods, landslides, and agricultural calamities resulted. The author investigated from a point of calamity the relation of the distribution of landslidse to rainfall, landform and geology.
The results are summarized as follows:
(1) The Shirasu areas of the most frequent landslides nearly coincides with the area where the maximum 10min. rainfall exceeded 10-45mm, or hourly rainfall exceeded 30-50mm.
(2) The Shirasu areas where few landslides occurred in spite of hourly rainfall exceed 50mm has a landform composed mainly of gently slope.
(3) After intermittent rain which has continued from the morning of 28th of June, downpour started by midnight. At the time of maximum intensity more than 50mm or rainfall where recorded during one hour and a half. It was after this time that most of landslides occured.
(4) All the landslides are of a small-scale and only the weathered material 0.5-2.0 meters thick lying on the top has slided.
(5) Results of rainfall network analysis for June 30, 1969 storms seems to indicate direct correlations between the movements of severe storms and the surface topographical parameter distribution. These correlation were particular remarkable in the rain intensity and wind fields. There was also some evidence of correlation between the 10min. intensity of rainfall and number of landslides per Km².

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In order to calculate the heat requirement per unit floor area for greenhouse heating design, a simple equation has been derived (eq. 1), and its constant has been defined as heating load coefficient(K). Suppose that r% of the total heat loss from the greenhouse is transferred into the soil, the heating load coefficient results in 100kt/(100-r) and the total heat requirement is given by eq. 6, where Kt is the sum of thee overall heat transfer coefficient of the greenhouse wall (k) and the heat transfer coefficient due to ventilation (h_ven). These coefficients, the over-all heat transfer coefficient of the greenhouse wall and the heat transfer coefficient due to ventilation are expressed by eqs. 3 and 4, respectively.
In the present field experiment, two identical greenhouses, one is east-west oriented and the other is north-south have been used. Both of them were heated by circulating hot water.
The heat balance analysis of the greenhouses shows that 50% of the total heat loss from the greenhouse is due to radiation, 20% due to convection from the outside surface to the outside air, 20% due to ven tilation, and 10% due to conduction into the soil in approximate values. It is also shown that the over-all heat transfer coefficient of the greenhouse wall is constant (k=4.8) and would not be affected by the fluctuation of the outside weatherconditions, and the heat transfer coefficient due to ventilation is a linear function of the outside wind speed(eq. 7).
The ratio of the heat loss into the soil to the total heat loss of the greenhouse given as percentage is presented in Fig. 5. In order to evaluate the heating load coefficient, the value of r must be determined. In the present study, the value of 10 is adopted for fail safe. Consequently, the heating load coefficient of the greenhouse is determined as a linear function of outside wind speed, i. e., eq. 10. Using eqs.1 and 10, the stochastic evaluation of the heat requirement of the greenhouse is demonstrated in relation to outside wind speed and daily minimum temperature in Figs. 6a and b. In the same figure, the heat requirement lines are indicated by the group of hyperbolic curves.

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Thermal radiation cooling during the night is one of the most significant phenomena for the greenhouse and the long wave net radiation exchange between the cold sky and the greenhouse surface has been analysed under the assumption that there is no significant temperature difference betwen the greenhouse surface and the surrounding ground surface.
In order tlo calculate the air-conditioning load, especially the heating load of the greenhouse, it is indispensable to analyse the radiative heat transfer mechanism of the whole system which includes the green house and to calculate the amount of the heat flow of each section involved. The diagrammatic representation each radiation exhange path is given in Fig. 3.
In the present study, the theoretical analysis is expanded to the thermal radiation cooling of the heated greenhouse as well as experimental verification. The view factor to the sky of the finite glass plane whose inclination angle is α is expressed as (1+cosα)/2 under the assumption that the long wave radiation from the sky is uniform and this factor is introduced as one of the important factor of the heat loss from the unheated greenhouse (Takakura 1967 a). Using this relationship, the ratio of the net radiation between the greenhouse surface and the sky to that between the sky and the horizontal surface whose area is the same as the greenhouse floor is expressed as (1+β)/2, where β is the ratio of the greenhouse floor area to the greenhouse surface area (Tachibana 1971).
The net radiation between the greenhouse surface and the sky is a function of the water vapor pressure in the air and the angular height of the net radiation intensity. Therfore, the numerical integration of Kondrat'yev's equation has been conducted and one of the results, which is the curve for 6mmHg is given in Fig. 2. The deviation from this curve due to the variation of the water vapor pressure is given as vertical deviation bands at three inclination angles in the same figure instead of giving the family of curves. This curve is expressed by the function (1+cosα-0.23 sin²α)/2 under 2% error.
Using this function, the ratio of the net radiation loss from the greenhouse surface to the net radiation of the horizontal surface is expressed as (0.77+β+0.23β²)+γ(1-β)/2, where γ is the ratio of the net radiation between the greenhouse wall and the surrounding ground surface to the net radiation between the greenhouse wall and the cold sky. Suppose that there is no temperature difference between the greenhouse wall and the surrounding ground surface, γ is equal to zero. On the other hand, if there is a significant temperature difference between them, e. g., 10 deg C, γ is approximately 0.5 and the value is increased 60% more than the value at γ is zero in the smaller range of β. The results are given in Fig. 4. Therefore, it is concluded that the thermal radiation cooling of the heated greenhouse should be calculated by Eqs. 13 and 14.
The calculation results are verified experimentally.

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温室の設計, 改良およびその効果的な環境調節を行なうに際しての, 温室内日射量に関する基礎資料を得るために, 温室内日射の透過機構を理論的に解析し, 3次元の上に凸な温室の床面における直達および天空日射量の各時刻および日の積算1日射量の平均値およびその分布を, 任意の季節, 建設方位および日射条件に対して, 与える計算モデルを示した。このモデルでは, 各ガラス面への直達および天空日射の入射角がそのガラス面の日射透過率に及ぼす影響およびフレーム等の不透明構造物による入射日射の減少等が考慮されている。但し, モデルの作成に際しては, 次のつ3の基本的な仮定がなされた。1. 直達日射は完全な平行光線とする。2. フレームの厚さは非常に薄い (ゼロ) とする。3. 温室内における日射の2次以上のガラス面での反射は無親する。
このようにして得られた計算モデルに基づいて, 今回は, 温室の建設方位, 季節等による温室内の日射特性の差異を比較検討するための幾つかの数値実験を電子計算機を利用して行なつた。その結果, 大略各, 次のような事が分つた。
1. 各時刻の温室の平均日射透過率はその建設方位の違によつてかなり異なり, その差はおよそ15%にもなることがある。
2. 温室内の日積算日射透過率は場所によつてかなり違いがあり, その最大と最小の差は約30%にも及ぶことがある。
3. 日積算日射透過率の場所による違いは, 温室の形態よりもむしろフレーム等の不明構造物の配置による影響が強い。
4. 現存する温室の一般的な形態は, 日射に関しては必ずしも好ましいとは云えず, 改良の余地が残されている。
5. 温室床面における天空日射透過率は中央で高く, 周辺で低いという分布になり, その差の最大は普通約10%内外である。
なお, 上に述べた仮定3を取り除いた計算モデルおよび実測値と計算値との比較は続報として引き続き取り扱う予定である。

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