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1. and go 0 0095 kg kgaa respectively and those of the air leaving the dryer spent air are t 60 C and gs 0 041 kg kgua where the subscripts wv and da denote water vapour and dry air respectively The drying of the moist material can be ac complished by any of the following three arrangements RH 100 a The temperature of the outdoor air is raised in the heater be fore it enters the dryer the humid air leaving the dryer spent air is exhausted into the atmosphere b The temperature of the outdoor air is raised to 100 C in the heater it enters the dryer and partially dries the moist material it then enters the reheater where its temperature is again raised to 100 C before it is reintroduced into the tabo tasa tats tabe tab taba dryer to complete the drying process the spent air is then S Z exhausted into the atmosphere c The outdoor air is mixed with 80 recirculated it is then heated in the heater and introduced into the dryer to process the moist material the spent air is exhausted into the atmosphere Data read psychrometric data obtained using the add in Figure 4 The convective drying plant and processes Determine the outdoor air flow rate through the dryer and S No the power consumption heat transfer rate for each of the dry d Bi A f Al h ials ofth q Outside air specific ho KJ kZaa tabo Bo 46 25 ing arrangements Also compare the2. Mi M 0 614 2 mass flow rate of air entering the dehumidifier Ma kg s mMM Mi2 0 363 3 recirculation fresh air mass mixing ratio Vito Yio Mi1 Mo 0 644 4 temperature of air entering the dehumidifier tabi C tav tabot Gii otabi 1 6i1 0 32 165 5 specific volume of air entering the dehumidifier v m kgaa tag 0 878 6 volume flow rate of air through the dehumidifier Va m s Va myv 0 318 7 specific humidity of air at the exit of the dehumidifier g kgu kgaa go 0 1273g 0 00382 0 003 8 mass flow rate of recirculated air before the dehumidifier mii kg s m M 21 20 gi g1 0 142 9 specific humidity drop in the dehumidifier Aca kgu kgaa Aga 22 81 0 007 20 heat transfer rate due to condensation in dehumidifier Qeond kW Qeone 2500mlAgal 6 345 21 heat transfer rate due to adsorption of moisture in the dehumidifier Qads kW Qaa Qamal gal 0 990 22 total heat transfer rate in the dehumidifier Qa kW Qu Qcona Quas 7 335 23 temperature rise in the dehumidifier Ataa C Ataba Qa MaCp 19 756 24 temperature of air exiting the dehumidifier taz C tapo tap Atapa 51 920 25 dehumidifier recirculation air mass mixing ratio Yi22 Yi22 5Mi Ma 1 693 26 temperature of air entering the cooler tav3 C tars tav2 Vi2 2tavi H7 i2 2 31 851 27 specific enthalpy of air entering the cooler h KJ kZaa 2 tav3 8s 41 260 28 specific enthalpy of the supply air hs KJ kZaa 2 tasg 22 120 29 heat transfer rate in the cooler Qe kW Q m Ih h I 18 691 g
3. basic psychrometric properties are related as follows C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 Specific humidity g g 0 622 2 1 F Pw where P and P are the barometric pressure and partial pressure of the water vapour respectively If the temperature of humid air f is higher than the tem perature of saturation of water vapour wv at the dry air da pressure P4a that is t gt t then Pwy Pa and RH g 0 622 __ a 1 RH where RH is the relative humidity of the air given as P RH 100 2 F where P is the saturation pressure of the water vapour Enthalpy of Moist Air h 3 h c t g 250l c t 3 where f Cp and Cp are the dry bulb temperature specific heat capacity of the dry air and specific heat capacity of the water va pour respectively The average specific heat capacities are given respectively for air conditioning and drying processes as Cp 1 005 AJ kgK and Cp 1 88 KJ kgK and Cp 1 01 kJ kgK and Cp 1 97 kJ kgK Wet Bulb Temperature twb and Thermodynamic Wet Bulb Temperature k h fe jwb tip t ar AA Zm E 4 and t t g g 5 P where Cp Cpa T a ve 6 Le 0 945 is the Lewis number for humid air in which case two Aq W mK ku kgyy ms and Cp kJ kga4K are the heat transfer coefficient of the air film around the wetted surface the mass tra
4. drying potentials of these enthalpy arrangements 12 Quantity Symbol Units Value Value 2 Spent air specific h kI kgia 2 tavs Zs 168 13 enthalpy Solution The following solution steps are carried out on the MS 3 aT relative RH K tabooZo 43 33 Excel worksheet spent air relative o A RH Plt g 31 09 Input data the given data in the problem bulb 5 spent air wet bu S No Quantity Symbol Units Value temperature fete C ltag B 1 initial mass of moist material Mmm kg s 0 278 6 ds aan taba G goh 139 1 2 initial moisture content of material Uin 0 5 pee humidity of 3 final moisture content of material Usn 5 0 06 7 T pro amp Kgw kgda A tapsshs 0 02528 4 temperature of air in case b heater tabb C 100 r Go mis eee in iG pies we 5 fraction of recirculated air K 0 8 ture 6 outside air dry bulb temperature tabo C 25 7 outside air specific humidity Zo kg kga 0 0095 8 spent air dry bulb temperature tabs C 60 9 spent air specific humidity gs kg kgaa 0 041 11 C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 Computation Answers the question asked S No a 1 2 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 Quantity rate of moisture removal in the dryer rise in the specific humidity of the working fluid air in the dryer mass of dry air per kilogram of moisture evaporated mass flow rate of dry
5. output for process simulation and analysis if desired plot psychrometric charts if desired stop The software was developed in MS Excel Visual Basic for Application Integrated Development Environment Excel VBA IDE as an Excel add in called Psychrometric_data using all the relevant correlations for the thermodynamic analysis of humid air given in the governing equations and following the computation al algorithm Some of the procedures are iterative with an error bound of 0 01 The interface retrieves and supplies information on any of the humid air properties A command button control on the Excel form is used to run the macro that implements a particu lar function After a successful installation of the Excel add in the Psy chrometric_data menu is seen on the standard menu bar By click ing on the Start button of the Psychrometric_data menu the win dow shown in Figure appears Select the process type Drying or Air Conditioning by clicking on the relevant OptionButton If the barometric pressure is different from the standard P 101 325 kPa check the No box and enter the prevailing barometric pres sure in the TextBox provided Select the unknown property from the ComboBox captioned Unknown Property In the ComboBox captioned Function select the known properties Key in C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 the numerical values of the
6. tion J of Enging Educ 89 3 pp 331 336 Arora C P 2000 Refrigeration and Air Conditioning Tata McGraw Hill New Delhi Akpan I E 2000 Analysis of Psychrometric Data for the Niger Delta Region of Nigeria A thesis in Mechanical Engineering for the award of M Eng University of Port Harcourt Port Harcourt Pavlov K F et al 1979 Examples and problems to the course of unit operations of Chemical Engineering Mir Moscow Eastop T D and McConkey A 1993 Applied Thermodynamics For Engineering Technology Fifth edition Pearson Education New Delhi 10 1 12 13
7. tools online References 1 Beckmanand W and Klein S 1996 Engineering Equation Solver EES User manual McGraw Hill N Y Lemmon E W Huber M L and McLinden M O 2002 Refprop Ver sion 7 0 User Guide U S NIST Department of Commerce Deane A 2005 Developing Mathematics Creativity with Spreadsheets J of Korea Society of Math Educ Series D R in Math Educ 9 3 187 201 Deane A Erich N and Robert S S 2005 Mathematical Modelling and Visualization with Microsoft Excel KAIST Retrieved April 26th 2006 http www mathnet or kr kaist2005 article arganbright pdf Liengme V B 2000 A Guide to Microsoft Excel For Scientist and Engi neers Woburn Butterworth Heinemann 6 Schumack M R 1997 Teaching heat transfer using automation related case studies with a spreadsheet analysis package Int J Engineering Edu cation 25 177 196 7 Lira C T 2000 Advanced Spreadsheet Features for Chemical Engineer ing Calculations Submitted to Chem Eng Educ Retrieved March 22nd 2009 http www egr edu lira spreadsheats pdf 13 8 Viali L 2005 Using spreadsheets and Simulation to Enhance the Teach ing of Probability and Statistics to Engineering Students Int Conf on Eng Educ Poland July 25 29th Silesian University of Technology Gliwice 9 Whiteman W and Nygren K P 2000 Achieving the Right Balance Prop erly Integrated Mathematical Software Packages into Engineering Educa
8. CIF Research Article Journal of Engineering Science and Technology Review 3 1 2010 7 13 JOURNAL OF Engineering Science and Technology Review www jestr org Analysis of air conditioning and drying processes using spreadsheet add in for psychrometric data C O C Oko and E O Diemuodeke Department of Mechanical Engineering University of Port Harcourt P M B 5323 Port Harcourt Nigeria Received 6 October 2009 Accepted 23 December 2009 Abstract A spreadsheet add in for the psychrometric data at any barometric pressure and in the air conditioning and drying tempera ture ranges was developed using appropriate correlations It was then used to simulate and analyse air conditioning and dry ing processes in the Microsoft Excel environment by exploiting its spreadsheet and graphic potentials The package allows one to determine the properties of humid air at any desired state and to simulate and analyse air conditioning as well as drying processes This as a teaching tool evokes the intellectual curiosity of students and enhances their interest and ability in the thermodynamics of humid air processes Keywords Psychrometry air conditioning drying spreadsheet add in Microsoft Excel 1 Introduction The properties of humid air are very important in air conditioning and drying process analysis and system design The property data are usually provided as tables and charts of properties But reading the psychromet
9. _8i 0 E ae m m8 8 g lt o 8 0 12732g 0 00382 f g oe m g m 8 g 1 m m g m g m i By curve fitting the experimental data for the dehumidifier performance using MS Excel curve fitting tool we obtain g 20 928 g 0 08g 7 x 10 9 g Figure 3 Equating the last two equations fig 9 g we get the iteration scheme g 100 989 g 0 01877 Setting 3 0 00286 and iterating in Excel environment within an absolute error bound of 10 we obtain the values of g and g as g 0 0097 and g2 0 1273g 0 00382 0 0027 kgw kgaa 10 C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 0 006 7 Sketches Diagrams gi 92 20 928g 2 0 0891 7E 05 Figure 3 shows the plant flow sheet and process diagram 0 005 4 R 0 9975 ee f g1 0 1273g1 0 00382 recirculated air amp 0 003 4 0 002 4 0 001 4 MS SSO Se 0 002 0 004 0 006 0 008 0 01 0 012 0 014 gt g a O 1a S Figure 3 Curve fitting of the dehumidifier data and solution of th OTS igure 3 Curve fitting of the dehumidifier data and solution of the equa c O 4 1c S reheatar tion f g ole 2 One tonne of some moist material is to be dried per hour from an initial moisture content of Ui 50 to a final mois ture content of ug 6 wet basis The temperature and humidity of the outdoor air are te 25
10. add in 0 Data read from literature S No Quantity Symbol Units Function Value 1 eoo g Cp kJ kg 1 024 Rm w CURE T210 p Speelieheto hy kg 250 2 PE E ho KJ kgaa K2 t ostweo 75 760 3 reference temperature tref C 25 3 specifie enthalpy hi KJ kgaa t i RH 29 010 4 Reference density Pret kg m 12 4 PSF Pe aoo 8o k8wn K8aa 2 tavostwvo 0 014 5 heat of adsorption Qa kW 390 3 B Si Kk8wn Kgaa 62 t i RH 0 003 6 Iteration error 0 000005 o Specific volumeof yg m kgaa taoto 0 907 g Fe ee RH Al tavostso 29 570 g Specific volumeof y M kgya fo taixRH 0 835 Computation provides answers the questions asked S No Quantity Symbol Units Function Value 1 mass flow rate of fresh air mo kg s m Vo Vo 0 221 2 temperature rise of supply air in the room Atabs C At tapi tars 6 000 3 sensible volumetric heat constant Ks kJ m Ks PreCp 273 trer 366 4 volume flow rate of supply air V m s V Qears tabs 273 KsAtats 0 784 5 Latent volumetric heat constant Ki kJ m K Predizre 273 trer 894000 6 specific humidity of supply air gs kgu kgaa 25 2i Qri tast273 V KLVs 0 003 7 heat taken by the supply air per unit mass qs kJ kg qs CpAtavs 6 144 8 mass flow rate of fresh air Mms kg s m Qrs qs 0 977 9 mass flow rate of the recirculated air mi kg s m m mM 0 756 0 specific humidity of air at the inlet of the dehumidifier g kg kgaa g g1 0 010 11 mass flow rate of recirculated air mixing before the cooler Miz kg s Mp
11. b drying potential relative to that of a dry bulb temperature of air after the heater for c big wet bulb depression for b first pass through the dryer small wet bulb depression for b first pass through the dryer drying potential LMTD for c drying potential relative to that of c 12 Symbol Mw Aga Xa Moca Aha qda Qe Agiv2 X b Mob Aho qda Qo 84 Ago Xo Moc hy Aho qdo Qo AteBa Atsa Atya Eala AtB b 1 Atso Ato Atsgo 2 Atsi 2 Atp Atho Ea b tabe Atso Ats e Ato Ea c Units kg s k8wy KZaa kgaa kgwy kg s kJ kg KJ kgwv kW k8wvy KZaa kgaa kgwy kg s kI kgaa kJ kgw kW kgwv kZaa kgwv kZaa kga kgwy kg s kg s kKI kgaa kI kgaa kI kgwy kW K Formula Myy Mmm Uin Usin 1 Usn AS a Bs Bo Xa 1 Ago Moa Mwy X a Aha hh daxa Aho Qa Mw Gey A858280 X l Ag Mo b 0 5 Myy X Ahw h h doo Aho Qiy 0 5 Mw qo ga 1 K go K g AS Bs Ba X l Agee M4 Mw Xo Moo 1 K m4 hy 1 k ho k h Aho h h4 Qo X Aho Qo Mw qe Atega taba twbs Atsa tabs twbs Atro Atsa Atsa In At Atsc Eq ay Atyyay Atyca 100 Atega 1 tabb twbb Atsa 1 tabs twbb Atp Ats0 1 Ats 1 In Atgo 1 Atso 1 Atega 25 tabb twbs Ats a 25tabs twbs Atpo2 Atgo 2 Atso 2 In Atso Atso2 Atyy 0 5 Atpo 1 tAtpo 2 Eao At o Atpa 100 2 a hs Atgo tave twos Ats c tans t
12. gy All rights reserved Therefore it is possible to develop computer procedures in Visual Basic for Applications VBA for generating the psy chrometric data as spreadsheet add ins Such a procedure would then be used in the MS Excel environment for the simulation and analysis of air conditioning and drying processes in an interac tive fashion and in a manner that fully exploits the spreadsheet and graphic potentials of MS Excel Such tool would assist the design engineer in his work especially when incorporated into a larger plant design software It would also be tool an easily afford able tool for the effective teaching of air conditioning and drying engineering principles to students of mechanical and chemical engineering The use of the MS Excel environment for enhanc ing the learning process in engineering is not new 6 7 8 9 Our experience has also shown that students exhibit greater inter est commitment and ability in using the spreadsheet for problem solving especially when graphical output is involved than in the traditional approach This paper therefore presents a spreadsheet add in for the psychrometric data for any barometric pressure and in the dry bulb temperature range of 0 to 550 C and uses it to illustrate the interactive determination of the state properties of humid air and simulation and analysis of air conditioning and drying processes 2 Governing Equations Following the works of 10 11 12 the
13. he dryer m and drying potential At as function of fraction of dryer spent air recirculated Problem 2 c and participation in students and its graphic equation solving and curve fitting capabilities permit the student to visualise the humid air processes and appreciate the scope and applications of thermo dynamics of humid air Comparism of process characteristics is relatively simple and process simulation under a range of varying input parameters is always possible as in Figure 5 which shows the dependence of the outdoor dry air mass flow rate 7i mass flow rate of air through the dryer m and drying potential A on the fraction of dryer spent air recirculated 1 4 Conclusion The spreadsheet add in is provided in an easily accessible MS Ex cel environment to facilitate process analysis and simulation ef forts of students as well as practising air conditioning and drying engineers Our experience has shown that students exhibit greater interest commitment and ability in using the spreadsheet for prob lem solving especially when graphical output is involved than in the traditional approach The tool proposed in this paper is easy to install use and modify by engineering students in any computer driven by the MS Office It is therefore strongly recommended as a teaching tool for engineering students especially in localities with limited access to internet facilities which may offer alterna tive
14. ir is mixed with a part of the recirculated air and another passed over the adsorption dehumidifier It is then mixed with another part of the recirculated air and sensibly cooled in the cooler before being supplied to the room at 14 C The room sensi inlet humidity ratio g x 103 g kgaa g kgaa 2 86 0 43 exit humidity ratio g x10 ble and latent heat gains are 6 and 0 8 kW respectively The performance of the dehumidifier adsorbent material is characterized by the inlet and exit humidity ratios of the air flowing through it which are tabulated below Assume the heat of adsorption of moisture to be 390 kJ kgw Determine the volume flow rate of the air through the dehumidifier and the heat transfer rate in the cooler 10 Solution The following solution steps are carried out on the MS Excel worksheet Input data the given data in the problem S No Quantity Symbol Units Value dry bulb temperature of tai oC 20 2 relative humidity of RH 25 3 dry bulb ternperature of tao oC 40 4 wet bulb temperature of tuvo oC 25 gt Sea ae Me ofr te 7 room sensible heat Qrs kW 6 0 8 room latent heat Qari kW 0 8 Sketches Diagrams Figure 2 shows the plant flow sheet and process diagram RH 100 Figure 2 The air conditioning plant and processes C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 psychrometric data obtained using the
15. known properties into the TextBoxes in the Frame captioned Input the known data By clicking on the CommandButton captioned Read the Psychrometric_data uses the relevant correlations to obtain the numerical value of the desired property which is displayed in the Output Data Frame and is also automatically transferred to a pre selected cell in the worksheet for further use The process continues for another state by clicking on the Continue drop menu of the Psychrometric_data menu 18 Bie Got yes port Format pos o prd gtdetToos Peyctromrk ao LIF sid AIF DLA uA SA E 2 Rb owt Geromeric Presere in opera WPa Standard Barometric Pressure Fes wins m No Uranewn Property wet bub temperature Peter PL ned rel humid and dry bu temp Pot te horn HIN Ta ba Figure 1 The add in Psychrometric_data window 3 Results and Discussion As an Excel add in Psychrometric_data is designed to aid students as well as practicing air conditioning or drying plant engineers in their design performance analysis by automatically providing the desired property data in the environment for the relevant spread sheet analysis To illustrate how this is achieved we consider the following problems 1 A room for process work is maintained at 20 C dry bulb db temperature and 25 relative humidity RH The out side air is at 40 C db and 25 C wet buld wb temperature Twelve cubic metre per minute cmm of fresh a
16. nsfer coefficient based on the specific humidity g and the humid specific heat respectively Ag and gware the specific latent enthalpy and specific humidity at the wet bulb temperature respectively and R 0 2873 kJ kgK is the dry air gas constant the superscript denotes adiabatic saturation properties and the indices fg and wb denote latent conditions and wet bulb tem perature respectively The Carrier s equation for the partial pressure of the water vapour P is given as 1 8 Pw Prsywo t twb Pa R wi 7 w 2800 1 3 1 8 32 e where Pew kPa is the saturation pressure at the wet bulb tem perature Specific volume v R T y ie 8 F a E where T K is the absolute temperature of humid air T 273 t tis temperature in degree celsius The humid air analysis is carried out using the following algorithm start input data i obtain the prevailing barometric pressure ii obtain the desired unknown property specific en thalpy dry bulb temperature wet bulb temperature specific volume specific humidity relative humidity or dew point temperature iii obtain two known properties and their values compute using the relevant relationships for the psychro metric properties the specific humid volume specific enthalpy specific humidity dry bulb wet bulb or dew point temperature output the desired data property name and numerical value use the
17. outdoor air through the dryer change in the specific enthalpy of air heat consumption per kilogram moisture evaporated power consumption rise in the specific humidity of the air during the first pass through the dryer process O 1b 2 mass of dry air per kilogram of moisture evaporated in the first process mass flow rate of dry outdoor air through the dryer change in the specific enthalpy of air heat consumption per kilogram moisture evaporated power consumption specific humidity of air after mixing of the outdoor and recirculated air rise in the specific humidity of air in the dryer mass of dry air per kilogram of moisture evaporated mass flow rate of dry air through the dryer mass flow rate of dry outdoor air through the dryer specific enthalpy of air after mixing change in the specific enthalpy of air heat consumption per kilogram moisture evaporated power consumption big wet bulb depression for a small wet bulb depression for a drying potential logarithmic mean temperature difference LMTD for a drying potential relative to that of a big wet bulb depression for b first pass through the dryer small wet bulb depression for b first pass through the dryer drying potential LMTD for b first pass big wet bulb depression for b second pass through the dryer small wet bulb depression for b second pass through the dryer drying potential LMTD for b first pass drying potential for
18. ric charts is strenuous time consuming and always prone to errors and the use of property tables frequently requires interpolation between the tabulated data which is also manual and time consuming activity However the proliferation of computer technology in contemporary engineering practice ensures greater speed and accuracy and thus should limit or even eliminate the use of property charts and tables in engineering analysis The present trend in engineering practice is therefore towards the de velopment of computer packages that are capable of automatic generation of the values of the desired thermodynamic properties and thus facilitating their use in engineering analysis 1 Many computer software packages are now available for en gineering analysis which have the facility for providing the ther modynamic properties of working fluids 1 2 But these packages are not available in most computers they must be bought and in stalled they cannot be modified by their users say to account for varying barometric pressure special training is usually required for their users and internet connectivity may be necessary But these shortcomings can be overcome if computer packages that are easy to develop modify and exploit by users are available The Microsoft MS Excel offers a suitable environment for the development of such packages 3 4 5 E mail address chimaoko yahoo com ISSN 1791 2377 2010 Kavala Institute of Technolo
19. wos Ato Atso Atso n AtsoyAtso Eao Atco Atya 100 Value 0 130128 0 0315 31 74603 4 131037 121 88 3869 206 503 4908 0 01578 63 37136 4 123183 121 88 7123 701 502 5336 0 0347 0 0063 158 7302 20 65518 4 131037 143 754 24 376 3869 206 503 4908 99 3 20 2 49 7 100 65 3 25 3 42 2 60 2 20 2 36 7 39 5 79 5 73 25 33 5 20 2 26 3 52 92 C 0 C Oko and E O Diemuodeke Journal of Engineering Science and Technology Review 3 1 2010 7 13 The results of the solutions of the illustrative problems 1 and 2 using the add in are in good agreement with those obtained by 10 and 12 respectively The psychrometric data provided by the add in are in agreement with those from the psychrometric charts for air conditioning processes and drying processes 12 and 13 respectively It was however observed that the maximum relative deviation of 4 5 occurs in the values of the specific enthalpy but this is within an acceptable limit for most applications The interactive nature of the MS Excel environment evokes curiosity 45 4 7 60 Atp c 40 011 48 8331 12 547 49 294 drying potential Atp c K mg 470 53x 666 31x 303 48 35 63 R 0 9965 m mass flow rates m4 Mo c kg s 02 0 4 0 6 0 8 fration of dryer spent air recirculated k Figure 5 Variation of outdoor air flow rate mao mass flow rate of air through t
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