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Thermal Design and Analysis of Electronics – Part III

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In part I, package level analysis and thermal design along with the important topic of Thermal Interface Materials were discussed. Then, in part II, the thermal route continued to board level as design and analysis guidelines were given and some frequently used board level cooling solutions were introduced. To complete the voyage to its final destination, ambient, the ultimate heat sink, System level design and analysis consideration are going to be discussed, with special emphasis on my favored subject, CFD and turbulence modeling, finishing with my personal experience and recommended choices for thermal management dedicated and general purpose commercial software packages.


system-level thermal management considerations

Environmental conditions

When thermal designing for system level some crucial decisions have to be made concerning the dominating mode of heat transfer (conduction, natural convection, forced convection, radiation). These crucial choices are ever so affected by the environmental conditions which are often standardized (MIL-STD-810x, RTCA-DO-160, MIL-STD-167, ISO/DIS-19453, IEEE-STD-1478, J1455, etc’…) in order to help tailoring qualification conditions that the mechanical design should meet. It is highly recommended to be aware of the different subtleties that might have an enormous impact on the thermal design.

system-level-analysis1.pngMIL-HDBK-5400 – guidelines for temperature and altitude
qualification test conditions

Let us take some examples to understand how and why those decisions crucially affect the design. Suppose we would like to improve heat transfer of a ruggedized PCB cover by replacing the material it’s manufactured by from Aluminum (thermal conductivity of 169W/mK) to Copper (thermal conductivity of 395W/mK) to achieve better overall conduction and heat spreading.

ruggedized.png
Ruggedized cover different designs

Not taking into consideration the environmental standard might result catastrophic corrosion evolving if the ruggedized cover is to be attached to an aluminum ATR chassis and endure salt-fog qualification testing.
As another example, lets say we are to design an electronic unit dissipating 500W. We follow a thermal design guideline of keeping the cooling methodology such as to tighten the margin of safety as much as possible. We perform a CFD calculation knowing that the highest ambient temperature that the unit shall meet is 71°C. now suppose that the unit is to be installed on an F-16, inside a non-pressurized (the density varies with bay temperature and flight altitude) conditioned avionic bay (the bay itself enjoys the aircraft’s ECS).

system-level-analysis-conditioned.png
Conditioned and unconditionedavionic bay

Not prescribing a direct ECS flow to the unit shall have a catastrophic consequence if are to meet the F-16 standard for temperature and altitude qualification test conditions (71°C@60kft) as the fan’s ability to cool is hampered severely by the air density at these conditions (by an order of magnitude).


Pre-simulation analysis and the benefit of the “first law of thermodynamics”

Advances in high-tech industries are strongly linked to Moore’s law predicting an exponential growth in computing resources such that the availability of advanced CAE tools to predict three dimensional complex flows and thermal fluxes not available to almost anyone 20 years ago are now a general commodity.

moore_lawMoore’s Law

The availability of CFD created a tendency of thermal engineers to what I call “simulation first”. Many “new-age” thermal engineers confront a thermal management problem with a success oriented methodology, by which simulations are conducted without any appeal to hand calculations (why speculate when you can simulate?…).  In many cases where a simpler theory or even a simple desktop experiment would provide an answer with less effort, or even a better answer, there is a temptation to use CFD anyway.
Hand calculations are mandatory! A lot of simulation time may be saved and possibly even overruled by performing a set of simple calculations before resorting to simulations.
A simple first law of thermodynamics based integral calculation such as:

1st law thermodynamics(Where q-heat dissiption, m_dot-mass flow rate, Cp-specific heat, ro-density, Tin-inlet flow temperature to the control volume, Tout-outlet flow temperature from the control volume)

may lead to a decision about which and how many fans to use, what might be a module attachment temperature boundary condition (for the case of a conduction-based ruggedized cover to be attached to a cold-plate cooled by forced convection) and even to a decision to rule out a forced air convection cooling mechanism due to insufficient cooling ability.


Modes of heat transfer and the effect on system level

In system level thermal design the choice of heat transfer mode is a crucial one, affecting both continuous operation in full performance and reliability.
Accommodating heat flux for a desired temperature gradient is a function of the effective heat transfer coefficient derived from the cooling technique chosen.

cooling mode

There are many constrains to such as choice among some are mechanical outline limitations, installation options, cost, environmental considerations and many other, but once a choice has been made the thermal design must support that choice. A chassis designed by cold-plates to be cooled by forced convection shall have lousy performance under natural convection cooling as there is not enough wetted area for buoyancy effects to support such a heat transfer mode.
Furthermore, if installation allows the attachment of the system to a base-plate, then the design must support conduction mode of heat transfer by the system to the platform  by creating a heat flux route as short as possible and allow optimal heat spreading. Care must be taken to avoid bottlenecks that may cause high local temperature gradients such as an insufficient area of which normal is aligned with the heat flux, without resorting to over-design.

If the installation does not allow a dominating conduction mode and heat dissipation is such that allows for passive convection cooling in the form of natural convection, then an optimal heat-sink calculation procedure should be conducted (there is an abundance of online guidelines for that). Moreover, care must be taken to designing the conduction route from the hotspot to the base plate as short as possible to avoid bottlenecking the design while pursuing a goal of creating an isothermal attachment surface to the heat-sink as much as possible (e.g. heat spreading).

ruggedized1-e1494446844764.png
Indirect cooling of a high density dissipative board, cooled by Air-Flow Through Cover
(AFTC) methodology (VITA 48.5), including a vapor chamber to diminish a hotspot above a 5mmx5mm, 30W component

When heat dissipation density and/or ambient temperature are too high to support natural convection, active cooling by fans should be considered such as to support a point of operation supplying enough volumetric flow to cool the system.
For direct cooling of the board (airborne electronic equipment guidelines do not allow that for example) a tubeaxial fan is the better choice, supplying relatively large amounts of volumetric flow at a low pressure difference, otherwise, if the design dictates indirect cooling (due to harsh environmental conditions for example) such as pushing/drawing the air through a cold-plate (especially for brazed or folded fins methodology, where an increased static pressure difference is expected), the better choice is of a vaneaxial fan designed to deliver a little bit less volumetric flow but at a higher static pressure difference and has the drawback of being much more noisy.

vaneaxial1.png  
Vaneaxial fan static pressure difference to
volumetric flow fan curve (Q-P curve)

Tubeaxial
Tubeaxial fan static pressure difference to
volumetric flow fan curve (Q-P curve)

While performing a simulation of a fan in dedicated commercial thermal management software it is customary to define the fan as an object described by its P-Q curve, outer diameter, hub diameter and swirl, it is most important not to forget to correct the input fan curve according to fan laws (e.g. density correction).

fan laws
Basic fan laws

When forced convection by air as a cooling fluid does not suffice, active liquid cooling should be considered. Accommodating a heat flux of 50 W/cm^2 to a 50⁰C temperature difference from its final heat-sink requires an effective heat transfer coefficient of ≈20,000 achieved only by liquid cooling (and possible area enlarging factor by heat spreading).
Designing an active cooling system is a complicated task and care must be taken to reliability issues (e.g. leaks) as much as for performance. The most important aspect to remember is that adding active liquid cooling, whether its of the shelf or personal design, means adding another system which might complicate qualification by doubling the qualification process, so its  highly recommended to avoid resorting to active liquid cooling if ambient conditions and component sensitivity allow it.

cooling-mode3.png

Active liquid cooling

CFD and turbulence modeling for electronic equipment

Since the late 1980s, the capabilities of computers and CFD, and our knowledge of how to use them, have grown tremendously. Over that time, CFD-based analysis methods have revolutionized the practice of thermal analysis conjugate heat transfer for electronics. Knowledgeable of how to use CFD can now routinely produce robust designs that don’t need further design changes due to thermal aspects after the initial phase of analysis, only verification. Moreover, by applying CFD, we can explore a much larger number of design geometry variations that are not practical to manufacture for development phase only.
Saying all that, there are important aspects to remember while applauding CFD. Defining the surface geometry and generating the mesh for a calculation can represent a significant investment in engineering time. Three dimensional simulations require high spatial resolution, computer time is still a significant cost even when considering RANS oriented applications, although it is diminishing rapidly as computational resources still increase exponentially and new infrastructures for parallel computing are under development (see CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences ).
Then there is another aspect that should be regarded. Effective use of CFD is a specialized skill that requires time and practice to develop. Effective users must often spend much of their careers learning methodologies of simplifying geometry, generating valid meshes and running codes as well as developing the judgment needed for effectively interpret CFD results.

As there is a vast number of topics comparably important in CFD, turbulence modeling stands above all in most fluid dynamics applications of practical engineering importance. This is especially true considering forced convection cooling of electronics. Confined and complex geometries involved with many obstructions to the flow and swirling flows originating from fans do not lend themselves easily to turbulence modeling.

In general, it is recommended to separate component/board level analysis from system level analysis. this is kind of methodology applies when the heat flux from heat dissipative components is based on conduction to a cold-plate (indirect flow cooling) and no direct cooling of the board exists. In these kind of configurations it is customary to evenly distribute the heat dissipation of a board and solve for the attachment temperature to serve as boundary condition for a subsequent board level simulation  where component and board level modeling shall apply.

In what follows, a brief summary of turbulence models frequently used in turbulence modeling are going to be discussed, but before doing that I think that it is important to take into mind that although it is not mandatory for a thermal analysis engineer to master his CFD skills till becoming an expert CFD practitioner, and as thermal management dedicated CFD codes are working on automating the process of actually dealing with many of the vast number of topics crucial for a meaningful CFD analysis (proper mesh resolution, choice of turbulence model, stability, etc…) it is still mandatory to understand at the very least what it is exactly that is being simulated and by which turbulence model approach, for as much as nowadays advanced digital graphics and robust (dissipative) numerical schemes allow to see a complicated flowfield, predicted with all the right general features, and displayed in glorious detail that looks ever so impressing and real, we must always remember the limitations of CFD and especially turbulence modeling when applied to the field of electronics.


Turbulence models and commercial codes

When performing CFD to electronic equipment there are two key observations to make before choosing how to regard turbulence modeling:

  • The resolution we are intending to simulate.
    Judgment is needed because the simulation of reality that CFD can provide is usually far from perfect. A fundamental physical limitation on accuracy comes from turbulence modeling and a user may inadvertently use a mesh that is too coarse, or, in many cases the densest grid one can afford to use isn’t dense enough to provide the resolution needed for an accurate simulation.
  • The code that we are intending to use.
    In contrast to some other fields of CFD, the flowfields encountered in thermal management of electronic systems is very diverse as it includes bluff bodies, massive and light separations, transition and relaminariztion, etc’… while general purpose high-end codes seem like the best choice to model such flowfields their “time to market” results is very long. On the other hand, thermal management dedicated codes are very easy for obtaining quick results but suffer from the lack of physical fidelity of their turbulence models with respect to such complicated flows.

I found it better to hold both a general purpose high-end CFD code and a thermal management dedicated code.
For simulations of direct fan originating flow over a highly populated PCB general purpose codes are essential if the practitioner wants the turbulence model perform inside its range of validity (the exception being ANSYS ICEPAK which actually uses the Fluent solver and has a variety of turbulence models to choose from). Saying that, my first choice for a general purpose code would be ANSYS Fluent. The code offers a complete set of tools to deal various levels of turbulence modeling, emenating from various k-ε turbulence Models (standard, renormalization group and realizable), then k-ω SST model which is an exceptional model for confined flows, the Local-Based Transition Model (LCTM) for flows that might exhibit transition and relaminarization, Scale-Adaptive Simulation (SAS) for flows of which massive separation is encountered (such as large component turbulent in flowfield exploration) and Detached-Eddy Simulation (DES) variants for instances where the focus is on a specific high resolution exploration task, where massive separations occur and turbulent shear flow are to be simulated, in order to get better insight of the flowfield otherwise not possible.

Steady State Thermal CFD Analysis of PCB in Enclosure – Ansys CFX

 For indirect fan cooling (flow through a cold-plate) where the accepted resolution need not be so high and physical fidelity is limited to extracting board attachment temperature (for subsequent conduction-based board level thermal analysis) but the geometry contains objects such as fans, contact resistances, porous media, etc’… the choice should be a thermal management dedicated code. The first advantage of such codes is the ease of use and the time spent until results are obtained. The main disadvantage is that considering the complex geometry frequently encountered, the two transport equation based turbulence model generally applied for turbulence modeling by such codes, is operating way out of its limits of validity.
Nonetheless, It is common also beyond the thermal analysis of electronics field to solve for complex turbulent flowfields with two transport equation turbulence models. Usually for applications such as electronic equipment thermal management, as the aim is extracting surface attachment temperature for the boards (attached by wedge-locks) at a cold-plate station the results are surprisingly accurate enough and could be even more pleasing when subsequently calibrated by conducting a set of simple engineering experiments.
In choosing a thermal management dedicated software my experience left me quite satisfied with a few. As shortly explained in the above paragraph, ANSYS ICEPAK has by far the best turbulence modeling diversity of turbulence modeling levels. But as the geometry for indirect cooling is very complex (porous media, brazed cold-plates with 0.2mm of fin spacing, obstruction to the flow in the form of semi-rigids finding their way to the flow field due to lack of space, etc’…) and the results are extracted to a reasonable accuracy, other codes which might be very user friendly and robust may be a choice to consider. A code I found to be very appealing to serve such a purpose is Mentor Graphics FloEFD. The GUI of FloEFD is native CAD (SolidWorks, UG, Catia, Creo) making it very easy to use, especially for those who acquired previous experience with CAD. FloEFD uses the octal tree mesh methodology, which is not very efficient but very easy to control. The software has an electronics thermal management bundle to be added upon purchasing which is not as supportive as its parent thermal management dedicated software, FloTHERM, but satisfactory for indirect system analysis purposes. FloEFD is essentially a general purpose CFD package, allowing the user to exploit it for applications other than thermal management of electronics.
As far as turbulence modeling goes, FloEFD uses the k-ε model for turbulence. If the first grid point lies innermost layer of the turbulent boundary layer (in the “viscous /laminar sublayer”), a low Reynolds model is chosen. Otherwise, if the first grid point is located outside the innermost layer (in the “inertial range”) wall functions formulation is applied. FloEFD does that without user intervention but solely by applying an inherent switching function to decide upon the location of the first grid point and the subsequent adoption of low Reynolds or wall functions formulation.

FloEFD system level CFD simulation –
indirect cooling flow through folded fins cold-plate

 

The end

There are many topics left out from the specific Part III due to the vast number of considerations to be taken into account. I am considering adding a part IV to account for topics I find interesting (transient heating, system level cooling solutions, radiation, and some more 😉 ).

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