Effect of Different Process Parameters on The Heat Transfer of Liquid Coolant in Electronic System
By
Wan Mohd Arif bin W. Ibrahim (1130410686)
A thesis submitted in fulfilment of the requirements for the degree of Master of Science in Materials Engineering
School of Materials Engineering UNIVERSITI MALAYSIA PERLIS
2017
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ACKNOWLEDGEMENT
In the name of Allah, the most Beneficent, the most Merciful Praise be to Allah who gave me the power, the undying strength and the patience bestowed upon me during the course of this study, blessing and peace be upon our prophet Muhammad.
First of all, I would like to express my sincere gratitude and utmost appreciation to my supervisor, Dr. Yeoh Cheow Keat and my co-supervisors, Assoc. Prof Dr.
Khairel Rafezi Ahmad and Prof. Dr. Hj. Zainal Arifin Ahmad from Universiti Sains Malaysia. Their guidance, valuable assistance and support during my research project have helped me accomplish this work successfully – Alhamdulillah.
Special thanks to the management of School of Materials Engineering, Center of Graduate Studies and Universiti Malaysia Perlis for providing me the opportunity to pursue my master study. There are many people who deserve my gratitude since they have been contributing to this thesis. Thanks to my office colleagues, to name few of them, especially Lokman Hakim, Azrem Azmi, Faizul Che Pa, Murizam Darus and Ruhiyuddin Zaki for their help, support and co-operation.
Finally, I would like to acknowledge with gratitude, the support, patient and love of my family – my parents, Wan Ibrahim and Fatimah Omar; and my wife Noorina Hidayu as well as for my princesses Rifaa, Zaara and Keisha. Five years is a lot of times, they all kept me going, and this thesis would not been possible without them.
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TABLE OF CONTENTS
PAGE
THESIS DECLARATION i
ACKNOWLEDGMENT ii
TABLE OF CONTENTS iii
LIST OF TABLES vi
LIST OF FIGURES vii
LIST OF ABBREVIATIONS ix
LIST OF SYMBOLS x
ABSTRAK xi
ABSTRACT xii
CHAPTER 1 : INTRODUCTION
1.1 Research Background 1
1.2 Problem Statement 2
1.3 Research Objectives 3
1.4 Scope of Study 3
CHAPTER 2 : LITERATURE REVIEW
2.1 Introduction 6
2.2 Overview on Electronic Cooling Methods 6
2.3 Air Cooling 12
2.4 Liquid Cooling 16
2.5 Modes of Heat Transfer 23
2.6 Properties of Cooling Materials 25
2.6.1 Water 25
2.6.2 Oil 27
2.6.3 Nanofluid 28
2.7 Effects of Different Parameters on Thermal Conductivity of Nanofluids 29
2.7.1 Particle Volume Fraction 29
2.7.2 pH Value 32
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2.8 Fluid Behaviour 33
2.9 Flow Rate of Fluids 34
2.10 Input Power 35
CHAPTER 3: METHODOLOGY
3.1 Introduction 38
3.2 Raw Materials 40
3.2.1 Preparation of Alumina Sol 40
3.3 Liquid Cooling System 41
3.4 Calibration and System Setup 42
3.4.1 Calibration of Thermocouple 42
3.4.2 Leakage Test 44
3.4.3 Calibration of Pump (Mass Flow Rate) 44
3.5 Experimental Design 45
3.6 Characterisation of Coolant Viscosity 47
CHAPTER 4 : RESULT AND DISCUSSIONS
4.1 Introduction 48
4.2 Stability of The Alumina Sols at Different pH Values 48
4.3 Viscosity of The Different Solutions Used 51
4.4 Mass Flow Rate at Different Speed and Input Power 55
4.5 The Heat Removal Capability of The Solutions 56
4.5.1 Relationships between temperatures of copper block (T1) and different of solutions used under different input powers(29 W, 38.5 W and 48 W)
56
4.5.2 Relationships between solutions’ temperatures and types of solutions used under different input powers (29 W, 38.5 W and 48 W)
59
4.5.2.1 Relationships between Thermocouple 2 (T2) temperatures and types of solutions used under different input powers
60
4.5.2.2 Relationships between Thermocouple 3 (T3) temperatures and types of solutions used under different input powers
63
4.6 Effective Heat Transfer of Solutions Used 66
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4.6.1 Relationships between temperatures of copper block (T1) and different solutions used under different pump speeds (speed 1, speed 2 and speed 3)
67
4.6.2 Relationships between solutions’ temperatures and types of solutions used under different pump speed (speed 1, speed 2 and speed 3)
69
4.6.2.1 Relationships between Thermocouple 2 (T2) temperatures and types of solutions used at different speed of pump
70
4.6.2.2 Relationships between Thermocouple 3 (T3)
temperatures and types of solutions used at different pump speeds
72
4.7 Time to Achieve 90 % of Final Temperature 74
4.7.1 Relationship between time to achieve 90% of final temperature T1 and solutions used
75
4.7.2 Relationship between time to achieve 90% of final temperature T2 and solutions used
77
4.7.3 Relationship between time to achieve 90% of final temperature T3 and solutions used
80
4.7.4 Relationship between time and solution used for different input power
82
4.7.5 Relationship between time and solution used for different pump speed
83
CHAPTER 5 : CONCLUSION AND RECOMMENDATIONS
5.1 Summary 85
5.2 Recommendation for Future Project 86
REFERENCES 87
APPENDICES
Appendix A [List of Publication] 94
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LIST OF TABLES
NO. PAGE
2.1 Thermal properties of commonly used electronic packaging material 26
3.1 Fluids use as cooling material in the experiment 40
3.2 Mass flow rate of solution used at 10 W pump power 45 3.3 Process parameters of each run of liquids in the liquid cooling system 46
4.1 Analysis of Variation (ANOVA) for selected factorial mode (Viscosity) by Design of Experiment (DOE)
53
4.2 Mass flow rate of different fluids at different pump speed and input Power
56
4.3 Analysis of Variation (ANOVA) for Response Surface Linear Model (Thermocouple 1) to input power and types of solutions by Design of Experiment (DOE)
58
4.4 ANOVA for Response Surface Linear Model (Thermocouple 2) to input power and types of solutions by DOE
61
4.5 ANOVA for Response Surface Linear Model (Thermocouple 3) to input power and types of solutions by DOE
65
4.6 ANOVA for Response Surface Linear Model (Thermocouple 1) to types of solutions and pump speed by DOE
68
4.7 ANOVA for Response Surface Linear Model (Thermocouple 2) to types of solutions and pump speeds by DOE
71
4.8 ANOVA for Response Surface Linear Model (Thermocouple 3) to types of solutions and pump speeds by DOE
73
4.9 ANOVA for Response Surface Linear Model (Time) to types of solutions for T1 by DOE
76
4.10 ANOVA for Response Surface Linear Model (Time) to types of solutions for T2 and T3 by DOE
79
4.11 ANOVA for Response Surface Linear Model (Time) to input power by DOE
83
4.12 ANOVA for Response Surface Linear Model (Time) to pump speeds and by DOE
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LIST OF FIGURES
NO. PAGE
2.1 The growth of CPU power density 7
2.2 Effect of temperature on failure rate 9
2.3 Temperature spectrum of operating junctions 10
2.4 Chip power dissipation chart 11
2.5 A typical air-cooled heat sink attached with fan 13
2.6 Front and side view of air-cooled heat sink 14
2.7 Thermal performance comparison between air cooling and liquid cooling
17
2.8 Illustrations of direct immersion cooling techniques: 18 (a) natural convection; (b) assisted with evaporation; (c) two-phase loop
thermosyphon; and (d) enhanced with pool boiling
2.9 Thermal Conduction Module used on IBM 3080X/3090 series 18 2.10 Evolution of module level heat flux in high-end computers 19 2.11 Comparison of nanoparticle and microparticle in heat transfer of fluid 21 2.12 Effect of concentration on thermal conductivity of Al2O3-based
nanofluids
30
3.1 Research flow chart 39
3.2 Schematic diagram of the liquid cooling system 42
3.3 Calibration curve type-K adjustable bayonet thermocouple (T1) 43 3.4 Calibration curve type-K T-shaped thermocouples (T2, T3 and T4) 44 4.1 Behavior of the Al2O3 sol as function of pH after centrifugation 49 4.2 Pourbaix diagram shows the stability of the aluminum surface as a
function of pH
50
4.3 Relationship between the viscosity of different solutions used and the speeds of the Brookfield Viscometer
52
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NO. PAGE
4.4 Relationship between temperatures of copper block (T1) and different solutions used at different power
57
4.5 Graph temperature of T2 versus different types of solutions at different input powers
60
4.6 Graph temperature of T3 versus different types of solutions at different input powers
63
4.7 Graph temperatures of T1 versus different types of solutions at different pump speeds
67
4.8 Graph of T2 versus different types of solution at different pump speeds 70 4.9 Graph of T3 versus different types of solution at different pump speeds 72 4.10 Graph of time to achieve 90% of final copper block temperature versus
different types of solutions for T1
75
4.11 Graph of time to achieve 90% final solution temperatures versus different types of solutions for T2
77
4.12 Graph of time to achieve 90% final solution temperatures versus different types of solutions for T3
80
4.13 Graph of time versus different types of solutions for different input power
82
4.14 Graph of time versus different types of solutions for different pump speed
83
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LIST OF ABBREVIATIONS
Al2O3 Alumina
Al (NO3)3 . 9H2O Aluminium nitrate nanohydrate
CuO Copper oxide
CPU Central Processing Unit DAQ Data Acquisition System
IO Input Output
LCHS Liquid Cooled Heat Sink MEMs Micro-electrochemical system
NaOH Sodium Hydroxide
SiC Silicon carbide
TDP Thermal Design Power
TiO2 Titanium dioxide
OHP Oscillating Heat Pipe
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LIST OF SYMBOLS
˚C Celcius
% Percent
∆T Temperature difference A Heat transfer area cm2 centimetre square h Heat transfer coefficient
J Joule
K Kelvin
mPa.s Viscosity
M Molarity
Re Reynold number
s Seconds
Q heat flow,
W Watt
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Kesan Perbezaan Parameter Proses Terhadap Pemindahan Haba Sistem Pendinginan Cecair dalam Sistem Elektronik
ABSTRAK
Sistem pemindahan haba yang berkesan adalah sangat penting untuk meningkatkan prestasi pemindahan haba dalam pengaplikasian teknologi terkini, terutamanya, tren pengecilan saiz sistem elektronik yang menyebabkan peningkatan jumlah haba yang dihasilkan. Dalam keadaan di mana sistem pendinginan udara tidak lagi mampu untuk memindahkan sejumlah haba yang banyak, sistem pendinginan cecair dilihat mampu memberikan kelebihan penyejukan berbanding sistem pendinginan udara disebabkan oleh sifat pemindahan haba yang lebih baik. Tetapi pemilihan bahan pendiginan cecair yang tidak sesuai akan menyebabkan prestasi yang rendah atau memberikan masalah terhadap sistem pendinginan. Kajian ini bertujuan untuk mengkaji kesan perbezaan parameter proses terhadap pemindahan haba bagi sistem pendinginan cecair. Kajian telah dijalankan bagi menentukan prestasi pendinginan oleh air suling, minyak sayuran dan larutan alumina dalam sistem pendiginan unit pemprosesan pusat (CPU) terhadap parameter kuasa masukan dan kadar aliran jisim yang berbeza. Pengoptimuman nilai pH adalah sangat penting kerana ia akan menentukan kestabilan larutan alumina, nilai pH yang optimum iaitu pH 4 diperolehi untuk larutan alumina. Penambahan kepekatan zarah alumina yang rendah ke dalam bendalir asas tidak memberikan kesan ketara terhadap kelikatan larutan alumina. Kuasa masukan merupakan pengaruh langsung kepada suhu akhir blok CPU dan bendalir. Pekali pemindahan haba bendalir bertambah baik serta penurunan yang jelas suhu persimpangan antara komponen yang dipanaskan dan blok pendingin air dapat diperolehi kerana kadar aliran jisim yang lebih tinggi.
Larutan alumina menunjukan keupayaan penyingkiran haba yang lebih baik serta menmpunyai nilai pekali pemindahan haba yang lebih tinggi berbanding air suling dan minyak sayuran disebabkan oleh penambahan zarah alumina dalam bendalir tersebut.
Keputusan ujikaji menekankan komalaran larutan alumina yang lebih tinggi akan menyumbangkan kepada nilai pekali pemindahan haba yang lebih tinggi. Keupayaan penyingkiran haba oleh 0.1 M, 0.5 M dan 1.0 M larutan alumina adalah lebih tinggi iaitu sebanyak 15.4 %, 32.3 % dan 40.8 % berbanding air suling. Kajian ini mengesyorkan 1.0 M larutan alumina yang stabil boleh digunakan sebagai bahan pendinginan cecair terhadap sistem pendinginan CPU dan juga pengendali ujian komponen dalam industri semikonduktor.
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Effect of Different Process Parameters on The Heat Transfer of Liquid Coolant in Electronic System
ABSTRACT
An effective heat transfer system is important for new technologies today to enhance the performance of heat transfer, especially, since the miniaturization of electronic system that resulted in dramatic increase in the amount of heat generated. In the case, where air cooling could not meet requirements, liquid cooling does offer significant cooling advantages over conventional air cooling because of its better thermal transfer property.
But unsuitable selection of liquid coolants may result to low performance or problems to the cooling systems. This study investigates the effect of different process parameters on the heat transfer of the liquid cooling. Experimental investigations have been carried out for determining the cooling performance of distilled water, vegetable oil and alumina sols in cooling system of central processing units (CPU) at different parameters of input power and mass flow rate. Optimising the pH values is very crucial because it will determine the stability of alumina sols, an optimal pH value of pH 4 is obtained for the alumina sols. There is no significant effect to the viscosity of the alumina sols because of low concentrations of alumina particles are dispersed in base fluids. Input power is direct influence to the final temperatures of CPU block and fluids. The heat transfer coefficient of the fluids is improved and a clear decrease of the junction temperature between the heated component and the water cooling block due to the higher mass flow rate. Alumina sols show better heat removal capability and higher heat transfer coefficient than distilled water and vegetable oil due to the presence of alumina particles in the fluids. Experimental results emphasize the higher molarity of alumina sols contributes higher heat transfer coefficient. The heat removal capability of 0.1 M, 0.5 M and 1.0 M alumina sols have been found as much as 15.4 %, 32.3 % and 40.8 % higher than distilled water. This study recommend that a stable 1.0M alumina sol may be use as liquid coolant for CPU cooling system as well as in component test handlers in semiconductor industry.
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1 CHAPTER 1
INTRODUCTION
1.1 Research Background
Recent development of microprocessor is getting complex with more sophisticated architecture design, stringent design rules and multi-core package to promise a tremendous performance. But all of these needs to be designed in smaller form factor (yet not to sacrifice the higher IO density) to meet current trend, hence lead to inefficient thermal management due to dramatically increase in power density and heat flux. This research will introduce the use of liquid cooling method to replace the conventional air cooling and heat pipe cooling methods that believed will no longer capable to meet the futuristic thermal needs of the next generation computers or supercomputers.
The development of earlier generation computer has started back in year 1940s, since then, the evolution of the Central Processing Unit (CPU) is heading towards better design in terms of higher clock speed, multi-core design and complex architecture mainly for speedy performance and multitasking operations. But all these criteria’s need to be designed in smaller form factor to meet current trend (Viswanath et al., 2000).
Over the past few years, with the increase of performance requirements for smaller, more capable and more efficient electronic system, management of generated heat is
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becoming an even-more important issue (Grujicic et al., 2005; Tong, 2011). Improper heat management on the microprocessor due to ineffective of the thermal energy will lead to poor performance as well as shorten the life cycle and reliability of the electronic devices. A distinct fact can be observed from the evolution of module level heat flux in computers, which shows that the heat flux is dramatically increasing since 1990’s. The average module heat flux for IBM RY6 that released in year 1998 is 3 W/cm2, and in year 2002, Intel released Itanium 2 processor, its average module heat flux is 9 W/cm2. Comparing to Pentium 4 processor which released in year 2004, its average heat flux is 11 W/cm2 (Ellsworth & Simons, 2005). This trend leads to higher heat flux that produce from CPU, improper management of the heat generated will lead to the life shortening and weaken the product’s reliability.
The current air cooling and heat pipe cooling technology present diminishing returns (Sauciuc et al., 2005), and this is important for the industry to establish the research and development to focus on the future non-air cooling technology which is hoped can be the solution to the futuristic thermal needs of the next generation computers. One of the potential solutions to manage the becoming higher heat flux and heat dissipation is by using liquid cooling method. This liquid cooling method can be applied indirectly (indirect liquid cooling) and directly (direct liquid cooling) to the microelectronic chips.
1.2 Problem Statement
Cooling of electronic devices is one of the main challenges of latest generation technology (Colangelo et al., 2017) such as to maintain the heats in component test
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handler for semiconductor industry as well as higher thermal design point of latest chipset technology. Hence, liquid cooling system could be a better method for thermal management in electronic system due to its better heat transfer capability (Mochizuki et al., 2011). Liquid cooling systems are not widely used even though it may promise better performance compared to conventional cooling systems. The liquid used for cooling materials in this study are water, vegetable oil and alumina sols. Water is commonly used as liquid cooling because of its good thermal properties (Lin et al., 2014), vegetable oil is selected to understand the effect of high viscosity towards the efficiency of heat transfer and selection of alumina sols because of its thermal performance, better stability and cheaper compare to other additive powders (Colangelo et al., 2017; Lee et al., 2008; Yoo et al., 2007).
Unsuitable selection of liquid coolants may result to low performance or problems to the cooling systems. Unsuitable selection of liquid coolants may result to low performance or problems to the cooling system. A proper selection of the solution will result to better performance and longer the life span of the processor. The instability of the solution may lead to poor heat transfer performance, failure in determine the correct pH and concentration of coolant may resulted to instable solution that lead to low efficiency of thermal management and clog the system. Different solutions may have different optimised parameter, hence process parameters optimising is important to ensure the solution can perform best cooling performance.
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4 1.3 Research Objectives
Experiments are conducted to determine the effect of mass flow rate and different input power to the cooling performance of different liquid cooling inclusive of alumina sol, vegetable oil and water on indirect liquid cooling system of a computer.
1- To study the effect of different liquid cooling materials on the performance of a liquid cooling system.
2- To determine the effects of different pH and concentration on the stability of alumina sol.
3- To optimise the process parameters of a liquid cooling materials.
1.4 Scope of Study
Increasing microprocessor performance has always been accompanied by increasing power and increasing on-chip power density. In addition, local power densities are more difficult to be managed, thus making thermal management become more challenging. Liquid cooling is being research due to the limitation in conventional air cooling in thermal heat transfer and increasing needs of high efficiency cooling system for microprocessor. However, the selection of cooling fluids is very critical to ensure good heat transfer can be achieved in microprocessor. This project will focus on the performance of the heat removal capability of different cooling fluids which are distilled water, vegetable oil and alumina sol. The right selection of cooling fluid will enhance thermal transfer performance.
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The project also study on the influence of process parameter such as mass flow rate and input power on liquid cooling for computer. The process parameter needs to be optimized to ensure the best performance in the cooling design. This project focused on the effect of mass flow rate and input power on the heat removal capability of water, vegetable oil and alumina sol. Mass flow rate of each liquid cooling will be measured at different pump speed ranging from 1800 rpm to 3300 rpm. The study will focus on two different input powers which are 29.12 watt and 47.66 watt. The viscosity characteristic of the fluid is also being study to understand the flow behaviour of the transfer fluid.
In the experiment, a model of closed loop liquid cooling system was constructed using commercial liquid cooling parts to run the simulation test. The system consists of liquid tank, tygon tube, radiator, pump, heat sink, copper block and thermocouples.
Distilled water, vegetable oil and alumina sol are the types of liquid cooling that being study throughout the simulation test. The different properties of the cooling fluids, flow rate and input power are the process parameters that be observed during the test to understand the cooling performance based on the maximum CPU temperature, heat transfer coefficient of liquid and thermal resistance of the water block.
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6 CHAPTER 2
LITERATURE REVIEW
2.1 Introduction
This section details the available information and theories related to the current trend of heat flux for microprocessor, the current available cooling methods, the future development of cooling methods and relevant fluid behaviour.
2.2 Overview on Electronic Cooling Methods
The reliability of the electronics of a system is a major factor in the overall reliability of the system. Recently, high efficiency cooling systems have been received great attention due to importance of thermal management that able to safely dissipate enormous amounts of heat from a very small area in high performance electronic devices. Meanwhile, miniaturization of electronic system has resulted in dramatic increase in the amount of heat generated per unit volume. The thermal management become a great challenge due to continuously rising of the heat flux from microprocessor according to International Technology Roadmap (Ebadian & Lin, 2011). Electronic packaging devices are continuously demands of high performance with miniaturized packaged designed and low cost (Tong, 2011), this evolution of the microprocessor is one of the most visible and representative facets of the computing
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revolution (Mahajan et al., 2006). Currently, the development of microprocessor is rapidly developed with smaller form factor and higher input density will lead to higher heat density and enormous power density. Improper managed in heat dissipation of the electronic package can result in microprocessor failure. Figure 2.1 is indicative of the CPU heat flux level predicted into the future. Based on the present trend, heat released by the CPU of a desktop and server computer is 80 – 130 W and of notebook is 25 to 50 W (Duangthongsuk & Wongwises, 2010).
Figure 2.1 : The growth of CPU power density (Davis et al., 2006).
An effective heat transfer system is important for new technologies today to enhance to performance of heat transfer. Technological developments such as microelectronic devices with smaller (sub-100 nm) features and faster (multi-GHz) operating speeds requiring advances in cooling. Especially, for personal computers today have shown a competitive released in more speedy and powerful product and shift
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to be more compact and smaller in size. Therefore, thermal management becomes a main challenge as the heat flow demands have increased over time.
The flow of heat in a process is shown in Equation 2.1
Q = hA ∆T (2.1)
Where, Q is the heat flow, h is the heat transfer coefficient, A is the heat transfer area, and ∆T is the temperature difference that results in heat flow.
The effective heat transfer is direct proportional to the heat transfer coefficient (h), heat transfer area (A) and temperature difference (∆T). Other than the factor of temperature difference ∆T that can lead to increase heat flow, maximizing the heat transfer area A is a common method to enhance heat transfer performance. In order to optimize the heat transfer, advanced exchangers such as radiators are designed to maximize the heat transfer area, but this method cannot be applied in microprocessor and micro-electromechanical system (MEMs) due to the shrinkage of electronic packaging. Heat transfer improvement can also be achieved by increasing the heat transfer coefficient h with enhancing the properties of the coolant (Ijam & Saidur, 2012). Additives are often added to liquid coolant to improve the heat transfer coefficient.
The primary purpose of electronics thermal control is to prevent the catastrophic failure, which is closely associated with a large temperature rise that may cause a drastic deterioration in semiconductor behaviour, delaminating, fracture and melting of packaging materials (Feroz & Uddin, 2009). This will lead to an immediate and total
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loss of electronic function and package integrity. The prime failure of electric equipment is always temperature related. Figure 2.2 is shown to reflect a near exponential dependence of the thermal acceleration factor on component temperature.
Thus, a rise in temperature from 75 ˚C to 125 ˚C can be expected to result in a five-fold increase in failure rate. Under some conditions, a 10 ˚C to 20 ˚C increase in chip temperature can double the component failure rate (Bar-Cohen et al., 2001).
Figure 2.2 : Effect of temperature on failure rate (Bar-Cohen et al., 2001).
The reliability of an electronic system comprising a group of components is most simply stated as the probability, expressed in percent, of operating continuously over a specified period of time with no failures. The failure rate model of CPU may be competitively described by the Arrhenius-type model:
(2.2)
where the coefficients Ai, Bi, and Ei are independent of temperature.
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Figure 2.3 shows typical junction temperatures for equipment presently operating in a large number of field applications. The 40 °C to 60 °C is the acceptable operating temperatures of range for semiconductor junctions. The reliability below 0°C is uncertain and some semiconductors stop operating, only to return to operation at higher temperatures with no apparent permanent damage. 85 °C is set as the upper limit operating temperature for commercial applications and for military equipment the acceptable upper limit operating temperature is 100 °C to 110 °C semiconductors in power supplies and processors.
Figure 2.3 : Temperature spectrum of operating junctions (Kaseb, 2011).
The most common cooling method for CPU today is air cooling method because air cooling system is low cost, ready available and transparency to the end user. All IBM computers were cooled solely by forced air due to the introduction of the System/360 Model 91 Processor in 1964 (Ebadian & Lin, 2011). The cooling system which is equipped with heat generating component with heat sinks and fans is named as Air-Cooled Heat Sink. In heat generation module, the heat sink is constructed of a base region that is in contact with the module. The fins push forward from the base serve to
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