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**O.Yoshida, M.Andou Tokyo Gas Co., Ltd.**

Development of EUC (End User Computing) System for the Design of HVAC (Heating, Ventilation and Air Conditioning) O.Yoshida, M.Andou Tokyo Gas Co., Ltd. Thank you, chair man. I am Osamu Yoshida from Tokyo Gas. I’d like to talk to you about End User Computing system using PHOENICS for the design of Heating, ventilation and Air Conditioning.

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**Contents Introduction Feature of the EUC system**

Wide variety of DB (data-base) Original user-subroutines Verification of DB Conclusions Here are contents of my presentation. I’d like to start with the introduction, then talk about the feature of the EUC system, Wide variety of DB (data-base), original user-subroutines, verification of DB, and finally I’ll conclude my presentation.

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Introduction CFD methods have become a promising tool to optimise design parameters of HVAC by predicting thermal environment in buildings. While many advantage are expected, CFD codes still require lots of expertise and time for designers to model and predict indoor environment. Wider application of CFD has been expected, in particular, to the field of EUC that designers and even sales engineers can easily take advantage of. CFD methods have become a promising tool. But CFD codes still require lots of expertise and time for designers. Wider application of CFD has been expected, in particular, to the field of EUC that designers and even sales engineers can easily take advantage of. These are the reason why I have developed an EUC system for HVAC. An EUC system for the optimal design of HVAC has been developed.

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**Feature of the EUC System**

Utilisation of PHOENICS Flexible pre-processor Powerful solver Easy VR post-processor Uniquely customised to predict indoor environment in faster, more accurate and user-friendly manners Wide variety of DB (data-base) for the analysis of HVAC Original user-subroutines Verification of DB This shows Feature of the EUC System. Utilizing the flexible pre-processor, powerful solver, easy VR post-processor of PHOENICS, this system is Uniquely customized to predict indoor environment in faster, more accurate and user-friendly manners. This system provides wide variety of data-base for the analysis of HVAC. Along with the DB, series of practical user-subroutines have been developed using GROUND. Prediction accuracy of DB was verified a-priori, by comparing with measurements. This is an interface window of the system.

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**Wide Variety of DB (Data-base)**

The system incorporated DB compiled during various cases of predictions and experiments. A/C DB A/C type Building DB Q1 The DB provides typical specifications of a variety of air-conditioners and buildings as a set of Q1 files. I’d like to talk about the DB (Data-base). The system incorporated DB compiled during various cases of predictions and experiments. The DB provides typical specifications of a variety of air-conditioners and buildings as a set of Q1 files. It is also maintains previous Q1 and PHI files as reference, which can be readily upgraded to predict similar problems . It also maintains previous Q1 and PHI files as reference, which can be readily upgraded to predict similar problems .

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**Original User-subroutines**

Along with the DB, series of practical user-subroutines have been developed using GROUND. These user-subroutines are applicable to predict ideal performance and operating conditions of air-conditioning units under desired optimal thermal environment. Optimisation of input conditions such as efflux temperature is conducted to obtain desired thermal environment in a room. This shows Original User-subroutines Along with the DB, series of practical user-subroutines have been developed using GROUND. These user-subroutines are applicable, for example, to predict ideal performance and operating conditions of air-conditioning units under desired optimal thermal environment. Optimisation of input conditions such as efflux temperature is conducted to obtain desired thermal environment in a room.

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**Original User-subroutines - Example Prediction of Optimal Efflux Temp.**

Mean temperature at the height of 0.6m for each of perimeter and interior areas needs to be 22℃ to achieve desired thermal environment. Office Room Type (Outside of Temp. = 0 C) Window Unit_P(Q=9m3/min) Unit_I1(Q=6) Unit_I2(Q=6) Perimeter (Area_P) Interior (Area_I) This demonstrates an example of user-subroutine to predict of optimal efflux Temperature from air-conditioning unit. An office room shown in this figure is modeled. Outside walls are exposed to cold air of 0 degrees centigrade. Area near the window is called ‘perimeter’. Inner area is called ‘interior’ There are three units of air conditioners. Flow rate of the perimeter unit is set at 9 cubic meters per minute. Those for interior units are 6 cubic meters per minute. Mean temperature at the height of 0.6m for each of perimeter and interior areas needs to be 22℃ to achieve desired thermal environment. In this subroutine, these efflux temperatures of units are separately controlled with reference to each area temperature. Z=0.6m Efflux temperatures are separately controlled with reference to respective area temperature.

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**Original User-subroutines - Example Algorithm**

Start Calculate Tm Calculate Rlx (Relax. factor) by Residual of NETSOURCE Te=Te+(Tm_end-Tm)*Rlx LSWEEP ? End Yes EARTH Solution No Tm_start=22 C, Tm_end=22 C, Te_start=40 C Temperatures. vs. Sweep No. Tm Te This shows the Algorithm of the sub-routine. Tm is the mean temperature of the monitoring areas, Te is efflux temperature from air conditioners. This algorism specifies relaxation factor Rlx by referencing the residual of enthalpy calculated in NETSOURCE. This figure presents the convergence of temperatures.

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**Original User-subroutines - Example Temperature Distributions**

Center plane of A/C units Efflux temp ≒ 30.6C Efflux temp ≒ 29.8C Plane at Z=0.6m Mean temp ≒ 22.0C Mean temp ≒ 22.0C This shows the result of the predictions. Efflux temperature has been calculated to be 30.6 degrees centigrade and 29.8 degrees centigrade for the perimeter and interior units respectively. Mean temperature at the height of 0.6m for each of the perimeter and interior areas has been successfully maintained 22 degrees centigrade. The algorism successfully predict optimal efflux temperature.

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**Verification of DB Computation Measurement**

Prediction accuracy of DB of the system was verified a-priori, by comparing with detailed measurements. Computation Measurement Verification Know-hows to generate a numerical grids have been compiled to secure practical accuracy with minimum calculation time . This shows Verification of DB. Prediction accuracy of DB of the system was verified a-priori, by comparing with detailed measurements. Then, Know-hows to generate grids have been compiled to secure practical accuracy with minimum calculation time .

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**Verification of DB - Example Artificial Climatic Room**

3D traverse apparatus Air-Conditioning unit Model Room Schematic Diagram This shows Artificial Climatic Room to measure indoor thermal environment. The model room was built in the Artificial Climatic Room. In the model room, distribution of air temperature and velocity were measured.

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**Verification of DB - Example Heating Conditions**

Outside of Temp. = 0 C Neighboring Temp. = 10 C Efflux Temp. = 46C Sink Air-Conditioning unit Living Room Type This demonstrates an example of the verification. A living room shown in this figure was modeled. The outside walls are exposed to cold air of 0 degrees centigrade and the others are to warmer air of 10 degrees centigrade. Warm air of 46 degrees centigrade flows out from the air conditioner downward at the angle about 27 degrees of the vertical line.

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**Verification of DB - Example Numerical Analysis**

PHOENICS 3.2 Steady states Rectangular grids 38×32×33 = 40128cells Elliptic-staggered equation k-epsilon turbulence model Hybrid differencing schemes Boussinesq buoyancy model Numerical Grid This shows is computing conditions for the verification. Using PHOENICS 3.2, steady state was performed. Rectangular grids about 40 thousand cells were used. The simulation was performed using Elliptic-staggered equation, k-epsilon turbulence model, Hybrid differencing schemes and Boussinesq buoyancy model.

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**Verification of DB - Example Center Plane of Air Conditioner**

Measured Computed This shows a comparison between measured and computed results of Center Plane of Air Conditioner . Both results are fairy similar in terms of air velocity and temperature distributions. Good agreement between the measured and computed results.

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**Verification of DB - Example Center Plane of Model Room**

This shows results of Center Plane of Room. The cold draft occurring near the window and extending to the floor is well simulated reasonably well. Measured Computed

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**Verification of DB - Example Temperature Profiles**

● This shows temperature profiles of vertical center line. Thermal stratums are also in good agreement.

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Conclusions An useful EUC system for the optimal design of HVAC has been developed using PHOENICS. The system incorporated DB for the analysis of HVAC as a set of Q1 files . Along with the DB, practical user-subroutines have been developed. Prediction accuracy of the system was verified a-priori, by comparing with detailed measurements. Computed result with incorporate DB was in good agreement with measured result. I’d like to conclude as follows. An useful EUC system for the optimal design of HVAC has been developed using PHOENICS. The system incorporated DB for the analysis of HVAC as a set of Q1 files . Along with the DB, practical user-subroutines have been developed. Prediction accuracy of the system was verified a-priori, by comparing with detailed measurements. Computed result with incorporate DB was in good agreement with measured result.

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