1
DESIGN PROJECT ON THERMAL ANALYSIS OF HEAT SINK
2
ABSTRACT In this paper, we compare thermal performances of two types of heat sinks commonly used in the electronic equipment industry: plate-fin and pin-fin heat sinks. In particular, heat sinks subject to an impinging flow are consid ide ered. For comparison son of the hea heat sinks nks, experimental investigations are performed for various flow rates and and chann channel el width widths. s. From From expe experi rime ment ntal al data data,, we su sugge ggest st a model based on the volume averaging approach for predicting the pressure drop and the thermal resistance. By using the model, thermal resistances of the the opti optimi mize zed d pl plat atee-fin fin and pin-f pin-fin in heat heat sink sinks s are are compa compare red. d. Finally, a contour map, whi hich ch depi depict cts s the ratio atio of the the therm hermal al resi resist stan ance ces s of the the opti optimi mize zed d pl plat atee-fi fin n and and pi pinn-fi fin n heat heat sink sinks s as a func functi tion on of dimen dimensi sionl onles ess s pumpi pumping ng powe powerr and and di dime mensi nsionl onless ess lengt length, h, is presented. The contour map indicates that hat opti optim mized ized pi pin n-fin -fin heat heat sink sinks s poss posses ess s lowe lowerr therm hermal al resistances than optimized plate-fin heat sinks when dimensionless pumping power is small and the dimensionless length of heat sinks is large. On the contrary, the optimized plate-fin heat sinks have smaller thermal resistances when dimensionless pumping power is large and the dimensionless length of heat sinks is small.
3
CHAPTER NO
TABLE OF CONTENTS
PAGE NO
ABSTRACT LIST OF ABBRIVATIONS LIST OF FIGURES 1
INTRODUCTION
6
2
OBJECTIVE
7
3
INNOVATION IN WORK
8
4
LITERATURE SURVEY
5
DATA COLLECTION
11
5.1 COMPUTATIONAL FLUID DYNAMICS
11
5.1.1 ADVANTAGES 5.1.2 APPLICATIONS
6
7
9
12 12
5.2 NTU
13
FIN
15
6.1 FIN INTRODUCTION
15
6.2 PLATE FIN HEAT SINK
16
6.3 PIN FIN HEAT SINK
16
PROBLEM DEFINITION
18
4
8
9
7.1 PROBLEM DEFINITION
18
7.2 PRE-PROCESSOR
19
7.3 SOLVER 7.3.1 FINITE DIFFERENT METHOD 7.3.2 FINITE VOLUME METHOD 7.3.3 FINITE ELEMENT METHOD 7.4 POST PROCESSOR INITIAL CAD DESIGN USING SOLID WORKS
20 21 21 21 22 24
THERMAL ANALYSIS OF CFD USING ANSYS
25
ANSYS SIMULATION
26
10.1 PLATE FIN APPARATUS
26
ANSYS SIMULATION
27
11.1 PIN FIN APPARATUS
27
12
FORMULA AND CALCULATION
29
13
ANSYS SIMULATION ON EACH FIN
31
10
11
14
RESULT AND FINAL DISCUSSION
15
CONCLUSION
46
16
REFERENCE
47
LIST OF ABBRIVATIONS CFD COMPITATIONAL FLUID DYNAMICS NTU NUMBER OF TRANSFER UNIT
45
5
LIST OF FIGURES
PAGE NO
1
PLATE FIN HEAT SINK
16
2
PIN FIN HEAT SINK
17
3
INITIAL CAD DESIGN USING SOLID WORKS 3.1 PLATE FIN 3.2 PIN FIN
24 24
ANSYS SIMULATION 4.1 PLATE FIN 4.2 PIN FIN
26 27
4
5
ANSYS SIMULATION ON EACH FIN
29-44
6
CHAPTER 1 INTRODUCTION A heat sink is a passive heat exchanger component that cools a device by dissipating heat into the surrounding air. Used in electronic systems wherever the heat dissipation ability of basic device package is insufficient to control its temperature. In this project we will be looking in detail about the temperature distribution in a heat fin which is produced by an electronic circuit to which the fin is attached.
7
CHAPTER 2 OBJECTIVE
The main objectives of this project are – To determine the nodal temperature in the component. To determine the maximum value of temperature in the component. To come up with better fin arrangement comparing the plate fin and pin fin. The project is to be done with the help of ANSYS software which is available in CAD lab.
8
CHAPTER 3 INNOVATION IN THE WORK
AIM- improves heat dissipating capacity of heat sink without changing its available area. After analysis, an appropriate and suitable material to be suggested for the manufacturing of heat sinks. Also the arrangement and shape of the fins in the heat sinks to be altered.
9
CHAPTER 4 LITERATURE SURVEY
Wuhan Yuan (2012) has analyse the factors of the computational fluid dynamic software FLUENT is used in assessing the electronics cooling potential of a plate pin fin heat sink (PPFHS), including the conjugate effect. The simulation results are validated with reported experimental data. The simulation shows that pin height and air velocity have significant influences on the thermal hydraulic performances of PPFHS while the influences of in-line/staggered Array and neighbour pin flow-directional center distance (NPFDCD) of the PPFHS are less notable. notable. In applying the present design to the cooling of a desktop desktop PC CPU at a heat flux of 2.20 W/cm2, the temperature can be kept at less than 358 K with an air velocity over 6.5 m/s.
Xiaoling Yu (2004) has conducted an experimental study based on plate fin heat sinks (PFHSs), a new type of plate-pin fin heat sink (PPFHS) is constructed, which is composed of a PFHS and some columnar pins staggered between plate fins. Numerical simulations and some experiments were performed to compare thermal performances of these two types of heat sinks. The simulation results showed that thermal resistance of a PPFHS was about 30% lower than that of a
10
PFHS used to construct the PPFHS under the condition of equal wind velocity. Another obvious advantage of PPFHSs is that users can change an existing unsuitable PFHS into a required PPFHS by themselves to achieve better aircooling results
Hung-Yi Li (2009) His investigation assesses the performance of plate-fin heat sinks in a cross flow. The effects of the Reynolds number of the cooling air the fin height and the fin width on the thermal resistance and the pressure drop of heat sinks are considered. Experimental results indicate that increasing the Reynolds number can reduce the thermal resistance of the heat sink. However, the reduction of the thermal resistance tends to become smaller as the Reynolds number increases. Additionally, enhancement of heat transfer by the heat sink is limited when the Reynolds number reaches a particular value. Therefore, a preferred Reynolds number can be chosen to reduce the pumping power. For a given fin width, the thermal performance of the heat sink with the highest fins exceeds that of the others, because the former has the largest heat transfer area. For a given fin height, the optimal fin width in terms of thermal performance increases with Reynolds number. As the fins become wider, the flow passages in the heat sink become constricted .As the fins become narrower, the heat transfer area of the heat sink declines. Both conditions reduce the heat transfer of the heat sink. Furthermore, different fin widths are required at different Reynolds numbers to minimize the thermal resistance.
Dong-Kwon Kim (2009) compares thermal performances of two types of heat sinks commonly used in the electronic equipment industry: plate-fin and pin-fin heat sinks. In particular, heat sinks subject to an impinging flow are considered. For comparison of the heat sinks, experimental investigations are performed for various flow rates and channel widths. From experimental data, we suggest a model based on the volume averaging approach for predicting the pressure drop and the thermal resistance. By using the model, model, thermal resistances of the optimized plate-fin and pin-fin heat sinks are compared. Finally, a contour map, which depicts the ratio of the thermal resistances of the optimized plate-fin and and pinpin-fin fin heat heat sink sinkss as a funct functio ion n of dime dimens nsio ionl nles esss pump pumpin ing g powe powerr and and dimensionless length, is presented. The contour map indicates that optimized pin-fin heat sinks possess lower thermal resistances than optimized plate-fin heat sinks when dimensionless pumping power is small and the dimensionless length
11
of heat sinks is large .On the contrary, the optimized plate-fin heat sinks have smaller thermal resistances when dimensionless pumping power is large and the dimensionless length of heat sinks is small.
CHAPTER 5
5.1 Computational Fluid Dynamics : Computational Fluid Dynamics Dynamics or CFD as it is popularly known is used to generate flow simulations with the help of computers. CFD involves the solution of the governing laws of fluid dynamics numerically. The complex sets of partial differential equations are solved on in geometrical domain divided into small volumes, commonly known as a mesh (or grid). CFD enables analysts to simulate and understand fluid flows without the help of instruments for measuring various flow variables at desired locations. The develo developme pment nt CFD analys analysis is leads leads to a consid considera erable ble reduct reduction ion of investment and operating costs by optimized design, by an increased availability of the system. This can be achieved by an appropriate design of the manifold. CFD analysis helps to evaluate and avoid velocity and temperature peaks in manifold sections which are of special relevance regarding material stress and deposit formation. CFD analysis helps to predict the temperature, velocity and pressure distribution in the system. Traditionally this has provided a cost effective alternative to full scale measurement. However, in the design of equipment that depends critically on the flow behavior, for example the aerodynamic design of an aircraft, full scale measurement as part of the design process is economically impractical. This
12
situation has led to an increasing interest in the development of a numerical wind tunnel. The development of more powerful computers has furthered the advances being made in the field of computational fluid dynamics. Consequently CFD is now the preferred means of testing alternative designs in many engineering companies before final, if any, experimental testing takes place. 5.1.1 ADVANTAGES : > CFD allows numerical simulation of fluid flows, results for which are
available for study even after the analysis is over. This is a big advantage over, say, wind tunnel testing where analysts have a shorter duration to perform flow measurements. > CFD allows observation of flow properties without disturbing the flow
itse itself lf,, whic which h is not not alwa always ys poss possib ible le with with conv conven enti tion onal al meas measur urin ing g instruments. > CFD allows observation of flow properties at locations which may not be
accessible to (or harmful for) measuring instruments. For example, inside a combustion chamber, or between turbine blades. > CFD can be used as a qualitative tool for discarding (or narrowing down the choices between), various designs. Designers and analysts can study prototypes numerically, and then test by experimentation only those which show promise. 5.1.2 Applications: Biomedical: Flow modeling with computational fluid dynamics (CFD) software lets you you visu visual aliz izee and and predi predict ct phys physic ical al phen phenom omen enaa rela relate ted d to the the flow flow of any any subs substa tanc nce. e. It is wide widely ly used used in medi medica cal, l, phar pharma mace ceut utic ical al,, and biom biomed edic ical al applications to analyze.
13
Electronics: Ansy Ansyss prov provid ides es a full full spec spectr trum um of prob proble lem m solv solvin ing g produ product ctss for for the the electronics industry. The Ansys flagship CFD software, FLUENT, as well as the electronics indust industry ry custom custom-des -design igned ed Icepak Icepak suite, suite, offer offer high-p high-perfo erforma rmance nce electr electroni onics cs cooling solutions covering a wide range of real life problems on any level. Industrial: To meet the vast fluid flow modeling needs of a broad spectrum of industries around the world, Fluent has been at the forefront of developing and driv drivin ing g comp comput utat atio ional nal flui fluid d dyna dynami mics cs (CFD (CFD)) for for more more than than two two deca decade des. s. Dive Diverse rse mode modeli ling ng capa capabi bili liti ties es allo allow w Flue Fluent nt's 's soft softwa ware re prod produc ucts ts to tack tackle le problems from most major industry sectors. Environmental : Protecting and improving the quality of our environment today requires innovative innovative design solutions solutions that establish compliance with ever-expandin ever-expanding g and more stringent regulations. Flow modeling with Fluent's computational fluid dynamics (CFD) software helps you tackle your environmental flow problems in the most efficient and cost-effective way. Civil : Within the built environment, it is critical to assess a number of important building characteristics char acteristics at the design stage, including the ability to improve the energy efficiency of a building, quantify solar radiation effects, analyze wind flow flow effec effects ts,, stud study y poss possib ible le fire fire and and smoke smoke hazar hazard d scen scenari arios os,, and and pred predic ictt occupant comfort. 5.2 NTU :
14
The NTU, or Number of Transfer Units, is a dimensionless parameter that relates the heat transfer convective resistances to the coolant flow heat capacity. While the details are beyond the scope of this short column, a typical heat sink (or cold plate) can be described with the following equations (assuming that the simplifying assumption of one surface temperature is reasonable). 1 Actual heat transfer = Ccool*(Tcool-out – Tcool-in); (Ccool is the mass flow times the heat capacity for the coolant) 2 Maximum possible heat transfer = Ccool*(Tsurf – Tcool-in) 3 Effectiveness = E = (Tcool-out – Tcool-in)/ (Tsurf – Tcool-in) 4 Effectiveness = 1 – exp (-NTU), where NTU = hA/C cool
One way to increase the NTU term is to decrease the coolant heat capacity but while our effectiveness increased, the resulting temperature for the surface may not be acceptable. The other way is to increase the hA term which means either larger area or a higher effective heat transfer coefficient. The engineering challenge is to minimize the decrease in effectiveness as coolant flow rates increase. Note that the limit is when the surface temperature and the coolant exit are at the same temperature,
15
CHAPTER 6 FIN 6.1 FIN INTRODUCTION A fin is a surface used to produce lift and thrust or to steer while traveling in water, air, or other fluid media. Fins improve heat transfer in two ways. One way is by creating turbulent flow through fin geometry, which reduces the thermal resistance through the nearly stagnant film that forms when a fluid flows parallel parallel to a solid surface. A second way is by increasing increasing the fin density, which increases the heat transfer area that comes in contact with the fluid. The plate fin heat exchanger is one of the most efficient designs used to transfer heat from one fluid to another. The best way to increase the efficiency of one of these devices is to alter the inner fin layout of the design. The fins are very important to the overall design because they add a large amount of surface area of contact between the fluid and the plate, which supplies heat. Altering the fin's geometry and other traits can drastically change the way a heat exchanger performs. Changing certain properties of a fin can have diminishing returns while others can have very beneficial effects. Effective ways to change a fin would be to change its height, length, the angle at which it is oriented with respect to the flow, and the amount of fins per unit length.
16
The fin angle is also an important factor to consider. Introducing different fin angles will create more vortices in the flow but will also create a lot more turbulence. Vortices are good to have because the mixing swirling fluid is more efficient at transferring transferring heat than a laminar boundary region attached to the surface. As the fluid hits the fin and passes over it, the wake region behind the fin sees almost no fluid velocity or mixing and has a large pressure drop.
6.2 PLATE FIN HEAT SINK : The problem under consideration is an impinging flow through a plate-fin heat sink as shown in Fig. 1(a) 1(a) and (b). The bottom surface is kept constant at a high high temperature. Air impinges on the heat sink along along the y-axis and then flows parallel to x-axis .Air, employed as a coolant, passes through the heat sink, thus removing the heat generated by the component attached at the bottom of the heat sink substrate. In analyzing this problem, the flow is assumed to be steady and laminar. In addition, all thermal properties are evaluated at the film temperature of fluid. In addition, it is assumed that the aspect ratio of the channel is higher than 1 and the solid conductivity is higher than the fluid conductivity
17
6.3 PIN FIN HEAT SINK :
The fluid flow in the pin-fin heat sink is axisymmetric in nature rather than two-dimensional. In the present study, the pin-fin heat sink is modeled as an equivalent porous cylinder which has the same porosity, wetted surface, and base area. The top view for the equivalent porous cylinder is shown in Fig. 2(b). 2(b).
18
CHAPTER 7 7.1 PROBLEM DESCRIPTION: In early days the rectangular ducts are made up with straight array of plates. This type of rectangular duct has low surface conduct with air flowing inside the rectangular duct. This results in the reduced total pressure drop across the rectangular duct and also reduced heat transfer rate. Due to straight array of plates air passing in the straight direction there is no mixing between the airs flowing across the rectangular duct and there is no secondary flow formation.
19
CFD codes are structured around the numerical algorithms that can tackle fluid flow problems. In order to provide easy access to their solving power all comm commer erci cial al CFD CFD pack packag ages es incl includ udee sophi sophist stic icat ated ed user user inte interfa rface cess to input input problem parameters and to examine the results. Hence all codes contain three main elements. > Pre-processor >
Solver
>
Post-processor
We briefly examine the function of each of these elements within the context of a CFD code. 7.2 PRE-PROCESSOR: 'Pre processing consists of the input of a flow problem by means of an operator friendly interface and the subsequent transformation tr ansformation of this input into a form suitable for use by the solver. The user activity at the pre-processing stage involves, Defini niti tion on of the the geom geomet etry ry of the the regi region on of the the inte intere rest st:: the the > Defi computational domain. > Grid generation: the sub-division of the domain into a number of
the smaller, non-overlapping sub-domains: a grid (or mesh) of cells (or control volumes or elements). > Selection of the physical and chemical phenomena that need to be
modeled. > Definition of fluid properties. > Specification of appropriate boundary conditions at cells, which
coincide with or touch the domain boundary.
20
The solution to a flow problem (velocity, pressure, temperature etc) is defined at nodes inside each cell. The accuracy of a CFD solution is governed by the number of cells the better the solution accuracy. Both the accuracy of a solution and its cost in terms of necessary computer hardware and calculation time are dependent on the fineness of the grid. Optimal meshes are often nonuniform: finer in areas where large variations occur from point and coarser in regions with relatively little change. Efforts are under way to develop CFD codes codes with with an adapti adaptive ve meshin meshing g capabi capabilit lity. y. Ultima Ultimatel tely y such such progra programs ms will will automatically refine the grid in area of rapid variations. A substantial amount of basic development work still needs to be done before these techniques are robust enough to be incorporated into commercial CFD codes. At present it is stil stilll up to the the skil skills ls of the the CFD CFD user user to desi design gn a grid grid that that is a suit suitab able le compromise between desired accuracy and solution cost. 7.3 SOLVER: There are three distinct streams of numerical solution techniques: finite diffe differe renc nce, e, fini finite te elem elemen entt and and spec spectr tral al meth method ods. s. In outl outlin inee the the nume numeri rica call methods that form the basis of the solver perform the following steps, > Approximation of the unknown flow variables by means of simple
functions. > Diseretizations by substitution of the approximations into the
governing flow equations and subsequent mathematical manipulations. > Solution of the algebraic equations.
The main differences between the three separate streams are associated with with the the way way in whic which h the the flow flow vari variab able less are are appro approxi xima mate ted d and and with with the the diseretizations processes.
21
7.3.1 Finite Difference Method: Finite difference methods describe the unknown's of the flow problem by means of point samples at the node points of a grid co-ordinate lines. Truncated Tayl Taylo or seri series es expa expans nsio ions ns are are oft often used used to gene genera rate te finit initee diff differ eren ence ce approximations of derivatives of F in terms of the point samples O at each grid point and its immediate immediate neighbors. Those derivatives appearing in the governing equations are replaced by finite differences yielding an algebraic equation for the values of at each grid point. 7.3.2 Finite Element Method: Finite element methods use simple piecewise functions (e.g. linear or quadratic) valid on elements to describe the local variations of unknown flow variables. The governing equation is precisely satisfied by the exact solution. If the piecewise approximating functions for are minimized in some sense by mult ultipl iplying ying them them by equa equattions ions for for the unkn unknow own n coef coeffi fici cien entts of the approximati approximating ng functions. functions. The theory theory of finite finite elements elements has developed developed initially initially for structural analys 7.3.3 Finite Volume Method : The finite volume method was originally developed as a special finite difference formulation. It is central to four of the five main commercially available CFD codes: PHOENICS, FLUENT, FLOW3D and STAR-CD. The numerical algorithm consists of the following steps, > Formal integration of the governing equations of fluid flow over all
the (finite) control volumes of the solution domain. Disere reti tiza zati tion onss invo involv lves es the the subs substi titu tuti tion on of a vari variet ety y of fini finite te > Dise diff differ eren ence ce type type appr approx oxim imat atio ions ns for for the the term termss in the the inte integr grat ated ed equation representing flow processes such as convection, diffusion
22
and sources. This converts the integral equations into a system of algebraic equations. > Solution of the algebraic equations by an iterative method.
The first step, the control volume integration, distinguishes the finite volume method from all other techniques. The resulting statements express the (exact) conversation of relevant properties for each finite size cell. This clear relati relations onship hip betwee between n the numeri numerical cal algori algorithm thm and the underl underlyin ying g physic physical al conservation principle forms one of the main attractions of the finite volume method and makes its concepts much simple to understand by engineers than finite volume method and spectral methods. The conservation of a general flow variable, variable, for example example a velocity velocity component or enthalpy, enthalpy, within a finite finite control control volume can be expressed as a balance between the various processes tending to increase or decrease it. CFD codes contain diseretizations techniques suitable for the treatment of the key transport phenomena, convection (transport due to fluid flow) and diffusion (transport due to variations of O from point to point) as well as for the source terms (associated with the creation of destruction of O) and the rate of change with respect to time. The underlying physical phenomena are complex and non-linear so an iterative solution approach is required. The most popular solu soluti tion on proc proced edur ures es are are the the TDMA TDMA line line-b -byy-li line ne solv solver er of the the alge algebr brai aicc equations equations and the simple algorithm to ensure correct linkage between pressure and velocity. 7.4 POST PROCESSOR: As in pre-processing a huge amount of development work has recently taken place in the post-processing field. Owing to the increased popularity of engi engine neer erin ing g
work workst stat atio ions ns,,
many many of whic which h
have have outs outsta tand ndin ing g
grap graphi hics cs
capabilities, the leading CFD packages are now equipped with versatile data visualization tools. These include,
23
> Domain geometry and grid display > Vector plots > Line and shaded contour plots > 2D and 3D surface plots > Particle tracking > View manipulation (translation, rotation, scaling etc) > Color postscript output
More recently these facilities may also include animation for dynamic result display and in addition to graphics all codes produce trusty alphanumeric output and have data export facilities for further manipulation external to the code. As in many other branches of CAE the graphics output capabilities of CFD codes have revolutionized the communication of ideas to non-specialist
CHAPTER 8 INITIAL CAD DESIGN USING SOLID WORKS
PLATE FIN :
PIN FIN :
CHAPTER 9 THERMAL ANLYSIS OF CFD USING ANSYS
CHAPTER 10 ANSYS SIMULATION PLATE FIN ARRANGEMENT : FRONT VIEW - TEMPERATURE DISTRIBUTION
ISOMETRIC VIEW – TEMPERATURE DISTRIBUTION ANSYS SIMULATION – MODIFIED
CHAPTER 11 ANSYS SIMULATION PIN FIN ARRANGEMENT FRONT VIEW - TEMPERATURE DISTRIBUTION
ANSYS SIMULATION – MODIFIED DESIGN ISOMETRIC VIEW – TEMPERATURE DISTRIBUTION
CHAPTER 12 FORMULAS AND CALCULATION :
θl=(Tl-T∞)/(Tb- T∞) θl=Temperature distribution at specified end temperature Tl= Specified end temperature Tb=temperature of the base T∞=ambient temperature
For plate fin
θl=(84-20)/(100-20)=0.8 For pin fin
θ l=(78-20)/(100-20)=0.725
FORMULAES FOR THEORETICAL CALCULATIONS Q=hA∆T Q à heat dissipation rate W h à heat convection coefficient W/m2K A à area of fins m 2 ∆T à temperature difference K For Plate Fin A = 0.0106 m 2 h = 50 W/m 2K
∆T = 100-84 = 16 K Q = 50*0.0111*16=8.9 W
For Pin Fin A = 0.0106 m 2 h = 50 W/m 2K ∆T = 100-78 = 22 K Q=50*0.0106*22=11.66 W
CHAPTER 13 ANSYS SIMULAION OF EACH FIN
CHAPTER 14 RESULT AND FINAL DISCUSSION : Ansys simulation have been made on each pin fin using computational fluid dynamics and dissipation of heat at various region of fin has been calculated. From the chart it has been identified that heat dissipation is high in pin fins due to large number number of air passages between fins. fins. whereas in a plate fin heat dissipation rate is low when compared to pin fin due to less number of air passage. So usage of pin fin will be more effective to provide cooling condition to system instead of plate fin
CHAPTER 15
CONCLUSION Thus the analysis have been done on the rate of heat dissipation of plate fin and pin fin using ansys simulation software . we found that the rate of heat dissipated is high in pin fin when compared compared to plate fin. so usage of pin fin in electronic electronic component componentss is more effective effective as it dissipates a lot of heat generated . Also usage of material is less in pin fin when compared to plate fin
CHAPTER 16
REFERENCES : 1. Opti Optima mall desig design n of plat plate-a e-and nd-fr -fram amee heat heat exch exchan ange gers rs for for effic efficie ient nt heat heat recov recover ery y in process industries. Olga P. Arsenyeva b, et al(2011),pp. 4588-4598. 4588-4598. 2. J. A. W. Gu Gut, J. M. Pin Pinto, Modelling of plate heat exchangers with generalized configurations, International journal of heat and mass transfer,, 2003, pp. 2571-2585. 3. R. K. Shah Shah,, W. W. W. W. Foc Focke ke,, Plate heat exchangers and their designtheory, designtheory, Heat transfer Equipment Design, Hemisphere, New York, 1988,pp. 227-254 . 4. T. Zal Zales eski ki,, K. Kle Klepa pack ck Approximate Approximate method of solving equations for plate heat exchangers, exchangers, International journal of heat and mass transfer, vol. 35, n°5 , pp. 11251130. 5. Numerical Numerical Analysis Analysis of Plate Plate Heat Heat Exchanger Exchanger Performan Performance ce in Co-Current Co-Current Fluid Flow Flow Configuration. H. Dardour, S. Mazouz, and A. Bellagi (2009). 6. Develo Developme pment nt of structu structural ral design design proced procedure ure of plate-f plate-fin in heat exchange exchangerr for HTGR. HTGR. Yorikata Yorikata Mizokamia, Mizokamia, Toshihide Igari b, Fumiko Fumiko Kawashimae, Kawashimae, et al.(2011),p al.(2011),pp. p. 248– 262..
RESULTS PLATE FIN The maximum temperature is observed to be 100.55 degree Celsius. The minimum temperature is observed to be 84.55 degree Celsius
PIN FIN The maximum temperature is observed to be 100.55 degree Celsius. The minimum temperature is observed to be 78.689 degree Celsius.
RESULTS PLATE FIN Q =8.9 W PIN FIN Q=11.7W The dissipation rate is higher for pin-fin arrangement and hence it is more efficient in cooling the circuit.
LEARNING OUTCOMES
Understood the basic working of Heat Sinks and understood the importance of their usage Understood how heat is dissipated through Heat Sinks. Learnt how different designs can alter the rate of heat dissipation.
REFERNCE http://en.wikipedia.org/wiki/Fin_(extended_surface) http://en.wikipedia.org/wiki/Heat_sink http://www.howstuffworks.com/heat-sink.htm
