Low thermal-potential energy can be utilized for a vapor absorption refrigerator in an air conditioning system. Operation with low grade energy, such as 60℃ to 95℃ hot water from solar collectors is possible. However, it's coefficient of performance is smaller than a vapor compression refrigerator. This paper discusses the availability of both refrigerators with the excergy loss in their heat source. The absorbent-refrigerant combinations investigated in this paper are water-ammonia and lithiumbromide-water. The refrigerant for the vapor compression system is ammonia. The operating conditions of the vapor absorption refrigeration system have been computed from various operating parameters. The excergy loss of the vapor absorption refrigerator has been calculated from the excergy difference between the inlet and outlet of the hot water supplied to the generator. The excergy loss of a vapor compression refrigerator under the same conditions has been obtained by the excergy difference between the inlet and outlet of the vapor in the steam turbine at the present power station. At the operating conditions, the excergy loss of the vapor absorption refrigeration system is smaller than that of the vapor compression refrigeration system in this paper. The advantage of a vapor absorption system may be it's lower operating cost compared with a vapor compression system.

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Fluid branch systems with the rectangular-sectioned ducts are used in diverse applications, such as an air-conditioning apparatus, ventilating systems, and other industrial purposes. In fluid branch systems, clarification of the separating flow characteristics, as well as the determination of mechanical potential drop, is very important in engineering in the design and study of such systems. This paper studies the separating flows at 90deg equal area branches consisting of rectangular-sectioned ducts with aspect ratios of 1/4 to 4. The stream-wise flow velocities of the air are measured in the ducts for Reynolds numbers of 44000 and 47000. The purpose of these measurements is twofold. First is to provide detailed observations, particularly of the spatial redistribution of the velocities behind a separating point at several stream-wise stations. By using two others parameters, such as "tertiary moment and fourth moment distribution", in addition to the ordinary ones, the shapes of the velocity profiles and the flow developments in the main duct and lateral duct are fully evaluated and considered. The second purpose is to clarify the dependence of the aspect ratios of duct cross-sections on the flow developments. As a result of a series of tests, experimental equations on the relations between the aspect ratios and the distances required for the flow developments in the both stream-wise directions are obtained.

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Since the Hardy Cross Method was published in 1936, various calculation methods have been developed for the analysis of the flow in piping networks. With these methods, the energy losses at branches are usually ignored as being minor compared to the friction losses in pipes. But the losses at branches are not minor in many industrial piping systems. This paper analyzes a basic T-type dividing flow by considering the dividing energy losses at branches. The results obtained are, 1) Flow distributions are, strictly speaking, the function of Re_1 which is the representative Reynolds number of a piping system, though the rate of change is not large. 2) The errors in the flow distributions and over-all loss coefficients caused by neglecting the dividing losses are calculated and their characteristics are illustrated in several graphs. 3) The idea, "Among the flow distributions in a piping network which satisfy the theorem of conservation of mass, the true and compatible flow distribution has the least hydraulic energy loss in the network" is not verified in the case of T-type dividing flow.

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Some of the elements of practical pipeline systems, e.g. bend, elbow, valve and so on, are often placed near one another. The flow through these elements exhibits a complex flow pattern different from that through a single element. In such cases, the total loss of the flow is not equal to the sum of each loss through a single element. This phenomenon is caused by the mutual interference of flow and has seldom been examined and will be an important subject hereafter. This study investigates the mutual interference of flow through multiple sharp-edge orifices in series, which is typical of successive area contraction and expansion in a pipeline, experimentally. First, the characteristics of resistance of each orifice are examined. Next, the energy loss of 2 to 5 orifices having same area contraction ratio and set in series in a pipeline is investigated. Then, a physical picture of the mutual interference of flow through the multiple orifices was obtained by measuring the velocity and pressure profile. In conclusion, the results obtained were as follows. 1) In spite of variations in the Reynolds number, the resistance coefficient of the multiple orifices is nearly constant, the same as with a single orifice. 2) For multiple orifices of the same area contraction and number, the smaller the spacing between the orifices, the more the resistance coefficient is affected due to interference. However, when the spacing is larger than 4.5. pipe diameters, the interference almost decreases. 3) For multiple orifices of the same area contraction, the greater the number of orifices (for very small orifice spacing) and the smaller the numbers of orifices (for large orifice spacing), the greater the resistance coefficient is affected due to interference. 4) For multiple orifices of the same spacing and same number, the larger the area contraction, the more intense the interference. 5) The resistance interference coefficient of each orifice composing multiple orifices is divided into three classes; comparatively less interference in the first orifice, extreme interference in the second orifice, and medium interference. 6) The mutual interference of flow through multiple orifices is explained qualitatively with the results of measurements of the static pressures and velocity distributions in up- and downstream side of orifices.

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A multiobjective optimization approach to the planning of an air-cooling system composed of a refrigerating machine, single-cell type heat storage unit, air conditioning apparatus, etc. has been proposed. In this paper, the heat storage unit mentioned above is assumed to be installed in the system to reduce the capacity of refrigerating machine. First the physical relationships of the system are expressed by time-difference simultaneous equations. Then, a typical day's heat demand pattern for air-cooling is assumed and a multiobjective nonlinear optimization problem is formulated by considering the following three mutually incommensurable objective functions; i.e., (a) to minimize the size of the refrigerating machine, (b) to minimize the size of the heat storage unit, and (c) to minimize the total thermal energy supplied from the refrigerating machine. Adopting both the ε-constraint method and the generalized reduced gradient algorithm, a set of Pareto optimal solutions is derived. A numerical study using the planning method proposed here clarified the trade-off relationships of the three objective functions mentioned above; that is, the objective of minimizing the size of the refrigerating machine conflicts with both objectives of minimizing the size of heat storage unit and minimizing the total thermal energy supplied from the refrigerating machine, but the last two objectives do not conflict with each other. As a result, it is ascertained that the planner can determine the scale of both the refrigerating machine and the heat storage unit by analyzing the trade-off relationships among the objective functions in a rational manner. In addition, the optimal operational policy of the objective system is determined explicitly for each Pareto optimal solution.

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The buoyancy acting on warm water discharged near the water surface causes it to spread rapidly in the direction of the width of open channel. This phenomenon, however, can not be simulated adequately by Patankar's SIMPLE or iterative SIMPLE proposed in Part 7 of the study. In this paper, the authors propose a model for promoting warm water movement in the thin surface layer, which was designed by observing the behaviours of visualized warm water by making detailed measurements of the temperature distribution in the surface layer. The spread of warm water in the direction of the width of an open channel is well simulated by applying the model to iterative SIMPLE. Several calculations are performed to invesgate the effect of the model when warm water is discharged into a open channel in parallel to the main flow direction.

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The effect of the model for promoting surface layer flow, which was proposed in Part 8 of the study, when warm water is discharged into the main flow from a rectangular conduit in a side wall of channel is discussed. Calculations are made with the model to simulate the behaviour of warm water flowing into an open channel in the authors' laboratory and into a natural river. The Tennessee River in the United States is chosen as an example of a natural river because temperature distribution data measured downstream of the Widows Creek power plant by the Tennessee Valley Authority in 1967 is avairable. The computed results show that the model is effective for open channels or natural rivers where warm water is discharged transversely from the main flow. Information on the water surface temperature is necessary when the model is applied. Water surface temperature prediction methods are based on a bimodal model are also shown.

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We researched and analyzed the yearly, monthly, and hourly hot-water consumption at many apartment houses with district heating system to obtain engineering data. First, we analyzed the yearly hot-water consumption in comparison with the number of persons in a family (Fig. 4) and yearly income (Fig. 5). Next, we analyzed the correlation between the average montly hot-water consumption of 84 houses and the city water temperature (Fig. 6). Finally, we analyzed the hourly consumption patterns of 1〜40 houses in comparison with the city water temperature to obtain basic data for plant design. 1) Fig. 8 shows the hourly consumption patterns of 40 houses. 2) Fig. 16 shows how the peak load changes with the city water temperature and number of houses. 3) Fig. 22 shows the necessary capacity of the heat source equipment and storage tank for 1, 10, and 40 houses for city water temperatures of 5〜10℃.

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