Robin Bornoff's blog

Views and insights into the concepts behind electronics cooling with a specific focus on the application of FloTHERM to the thermal simulation of electronic systems. Investigations into the application of FloVENT to HVAC simulation. Plus the odd foray into CFD, non-linear dynamic systems and cider making.

31 March, 2015

AngledSteppedThe shape of the small piece of geometry that is added so as to successively ‘relieve’ the design determines the overall ‘jaggedness’ of the final geometry. A square section rod can only lead to a stair stepped representation of angled portions of the shape, at worse resulting in a 41% increase (2/root2) in surface area in those regions. Increase in surface area, thus heat transfer, might be offset by the increase in surface friction thus reduction in through flow. But why risk relying on a cancelling of effects? It’s obvious that those jaggedy edges really want to be smooth. So why not (manually) smooth them?

The geometry was exported out of FloTHERM as STEP, via FloMCAD Bridge, and imported into FloTHERM XT. Think of FloTHERM XT as FloTHERM’s younger sister, an MCAD centric implementation with more arbitrary geometry support. I used the Chamfer command in FloTHERM XT  to smooth out those stair steps then went on to simulate the reduction in thermal resistance.

Stepped_ChamferedEven though we’re looking at 2D front projections, don’t forget this is full 3D:


The reduction in Rth was only 1.8% for the cancelling out of effects reasons mentioned above (though sure, in a fixed dP environment, not a fixed mass flow, the chamfered Rth reduction would have been greater).

I’m not sure that any other geometric section shape of the additive geometry would have removed this jaggedness effect. A hexagonal shape would be slightly better at resolving 45degree angled sections but not so good at axis aligned portions. As any player of Lego or user of FloTHERM knows, squares are good. Squares tessellate, are simple to handle and as has been shown here, together are capable of representing the most organic of geometries.

The Constructal Law, whose hand is very much at play in the above heatsink, is best described by its father, Professor Adrian Bejan. The concept goes beyond shapes and technology, into the very essence of the design by evolution and the preservation of living systems, including us humans:

“With science, we predict and construct our future”

1st April 2015, Ross-on-Wye

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25 March, 2015

LightningAdrian Bejan’s Constructal Law states: “For a finite-size system to persist in time (to live), it must evolve in such a way that it provides easier access to the imposed currents that flow through it.” This can be seen at play in both animate and inanimate systems, from trees to lighting, from river systems to lungs. Such persistent systems tend to carry something between a volume and point. Lightning-electricity, trees-water, lungs-air, rivers-water. A heatsink is no exception. Taking heat from a point to a volume, or inversely taking cold from a volume to quench a point of heat. ‘Evolving in such a way that it provides easier access…’ is at the heart of the additive design process.

The iterative procedure to grow the heatsink geometry:

  1. Start with a minimal section of heatsink base, a thin sliver.
  2. Simulate to see how hot it gets
  3. Where its surface is hottest ‘grow’ the geometry there by a very small amount
  4. GoTo 2
  5. Repeat until a design space has been filled

is actually slightly more refined. If the addition of a small piece of geometry leads to an increase in heatsink base temperature (or not a substantial enough decrease), then that piece of geometry is removed and that location marked so as not to add there subsequently. The next hottest location is then considered, and so on.

The end of the first year of growth occurred when no geometry could be added anywhere without extending beyond the design space, or causing an increase in base temperature. For the second year of growth, all those location that were marked as being detrimental were cleared and the iterative process repeated afresh.


A large surface area was achieved in the spindly growth of the first year. The second year saw a large ‘trunk’ develop that facilitated the flow of heat to the outer extremities. ‘Evolving in such a way that it provides easier access…’

The third year of growth further enhanced this flow of heat by thickening out ‘branches’ between the ‘trunk’ and the outer ‘leaves'(?)


It’s worth noting that the resulting complexity is a function of just a very basic set of growth criteria instructions. In much the same way that a seed is an instruction set for the consumption and conversion of local matter and energy into the resulting tree.

“Mighty oaks from little acorns grow”

No further reduction in growth could be achieved in subsequent years of trying. The additive process ended. That isn’t the end of the story though. The stepped nature of the geometry, due to the choice of the additive geometry shape, had opportunity to be further refined. More on chamfering in the next blog in this series.

25th March 2015, Ross-on-Wye.

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24 March, 2015

TypicalHeatsinkThis is what a typical extruded fin heatsink looks like. It’s made of metal and sits on top of IC packages that themselves are soldered to a PCB. It cools those packages by providing an increased air apparent surface area with which to pass on the heat that has been conducted up through it. It’s shape (topology) is in most ways set by the manufacturing process used to create it. In this case squeezing molten aluminum through a die with that shape as the profile. Similar constraints exist for other manufacturing processes, be it milling, casting, brazing etc. 3D printing removes many of these constraints and, as the technology matures, I believe all of them will be addressed. So, with a process that can print any 3D shape, how should design tools adapt to such an opportunity?

More specifically, how could you use simulation to identify an arbitrary heatsink topology that is thermally efficient?

The/an answer turned out to be very simple:

  1. Start with a minimal section of heatsink base, a thin sliver.
  2. Simulate to see how hot it gets
  3. Where its surface is hottest ‘grow’ the geometry there by a very small amount
  4. GoTo 2
  5. Repeat until a design space has been filled

We applied this novel process to a forced convection cooled environment and chose a full length ‘rod’ shape as the ‘very small amount of geometry’ with which to grow the heatsink. Here are the first 5 steps of the additive design method (simulated with FloTHERM of course!):

First_5_StepsEach time the heatsink geometry ‘grows’, its thermal efficiency improves, the temperatures drop. That’s the intention of increasing the surface area at the hottest point, the point at which heat is bursting to get out. By growing the geometry at that point the thermal bottleneck is relieved, bit by bit.

To visualise the rest of the growth we change to a 2D front view and animate the sequential additions. A graph also shows the gradual improvement in thermal performance, a decrease in the heatsink thermal resistance, calculated as ((Base center temperature – ambient temperature) / Power):


We’ve already introduced organic words such as ‘growth’ and it’s evident that the heatsink bears more than a passing resemblance to a type of tree. Shoots are going up, they branch so as to enter more of the design space volume. If this first year of growth sees the heatsink establishing its main FinalHeatsinkcanopy, then subsequent years will see the formation of a trunk and thickened branches. Over the next few blogs in this series I’ll show how we go from this initial shape right up to a final automatically identified topology. I’ll also touch on Bejan’s Constructal Law, fractal geometry, methods of 3D printing metal alloys and how this additive design methodology might be refined and applied to a wider range of design challenges.

If you can’t wait then check out the recently published Semitherm 31 paper “An Additive Design Heatsink Geometry Topology Identification and Optimisation Algorithm. Robin Bornoff, John Parry, Mentor Graphics, UK” which should be on IEEE Xplore in the near future. It also won 3rd best paper at Semitherm! Yay :)

Manufacturing is changing, so must design.

24th March 2015, Ross-on-Wye

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9 March, 2015

With Semi-Therm 31 just a week away I thought it would be a good time to expand on the (metaphorical) electronics cooling drinking game. Something extra to add to your enjoyment of a conference presentation, journal paper and especially a press release. Common electronics cooling industry drivers and concepts crop up again and again (well, they would do, they’re common), see if you can spot any of these next time you’re reading an article or listening to a presentation.

“What do points make? Prizes!” See how many you can score at Semi-Therm…

  • BottleneckThermal Bottleneck. Analogies are great for transposing a reason into a readily understandable form. Thermal management is essentially the management of the transport of heat energy through a series of geometric obstructions. It’s when a lot of heat finds it difficult to escape to a cold ambient do the (‘upstream’) temperatures start to rise sharply. These thermal bottlenecks are often mentioned, especially in the context of TIM1 and TIM2. Actually we quantified this bottleneck concept into something that can be simulated and displayed. Always an interesting concept, 3 points.


  • EPA_driving_profileDriving/Mission/Scenario Profiles. With ever decreasing thermal design margins the assumption that a system behaves in a steady state way, with powers dissipated for so long that the system attains a constant thermal state, is becoming untenable. It is far more common today to study the transient thermal response of a system as a function of how it will be deployed in the field. Driving (auto), mission (mil/aero) and scenario (consumer) profiles provide an indication of how the power consumption will vary in time, allowing for the resulting transient junction, case and touch temperatures to be simulated more accurately (and less conservatively than when based on steady state power assumptions). Transient simulations are the future, 4 points.


  • Rjc

Junction to case resistance is arguably the most common thermal metric. It relates quantifies the ease by which heat can pass from its source (die) to the peripheral, heatsunk, hopefully constant temperature case of the package. It’s deceptively simple. There will always be outstanding questions regarding what and where the case temperature is, how to measure the junction temperature etc. Actually these questions are addressed in JESD51 series standards. Important point to note, these metrics are always intended for comparative purposes, not for simulation. It’s when applied for the latter do these questions start to arise. EC 101, 1 point.


  • BudgetsHeat Flux Budgets. Despite heat transfer being an inherent 3D affair, we often fold the heat flows down into simple, easy to explain, 1D type paths and networks. A lot of (superfluous) extra information is lost but this method of presentation is a per-requisite for convincing others of (thermally) required design changes. It can becoming an even more compelling approach when coupled with the concept of thermal bottlenecks (see above). EC 102, 2 points.


  • Heatsink_with_heat_pipesHeat pipes and Vapour chambers. No longer considered an exotic thermal management solution, these heat moving devices are now commonplace, especially in computing applications. Very good at taking heat from confined spaces and moving that heat, with little dT penalty, to larger areas when the heat may be transferred onwards using more standard area extending heatsink solutions. Here’s a really good compare/contrast blog on the subject from George Meyer at Celsia. They’re everywhere, 1 point.


  • FanSystemCurveSystem operating point. When sizing fans or blowers it is critical to know what resistance to flow the system you are trying to ventilate, will offer. Only once this is known will you be able to determine how powerful a fan will be required, or what your derating strategy could be. Very much early stage design decision work achieved by matching the system’s flow resistance curve against that of a fan(s), the intersection being what flow rate would result. So common not often seen in conferences today, 1 point.


9th March 2015, Ross-on-Wye

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5 March, 2015

29th August, 2012. A Jaguar XJ parked in Fenchurch Street, London, suffered melted panels between 1200 and 1400, owner Martin Lindsay was shocked to find on his return. Not that the building at 20 Fenchurch Street had any malicious intentions but it was the concave reflecting surface of what is known as the ‘Walkie-Talkie’ that focused the sunlight on that particular day in such a way so as to increase the temperature of parts of the car beyond their melt temperature limits. Dubbed the ‘Walkie-Scorchy’, the reflectance issue has subsequently been resolved but it is a pointed reminder that, despite a rigorous engineering design process, unexpected things do occur!

20FenchurchStreetFloEFD is a general purpose CAD embedded CFD tool, developed by the Mechanical Analysis Division of Mentor Graphics. It has a number of key radiative optic features developed for LED, automotive and automotive lighting applications. We used FloEFD to study the physics behind this freak melting occurrence. The results were quite startling.

The incident solar flux that occurs at the height of summer can reach 1400 W/m2. That’s 1.4kW spread over every square meter (11 square feet). Over and above the local air temperature, it’s why you feel so warmed by the sun. As many young children learn, take a magnifying glass and you can focus those rays to a point, increasing the radiative heat flux to levels that can harm ants and start small fires.

In FloEFD we setup a transient thermal simulation, at the exact time period that the car melting occurred. The building geometry, glass surface properties, local street and neighbouring buildings, even the car in question (swapped out for a generic high spec car for legal  reasons) were all simulated. The main results are shown in the animations below. The colour equates to the total heat flux landing on solid surfaces. The location of the car is shown by the arrow.


(Click to Show Transient Animation)


(Click to Show Transient Animation)

It is the radiative flux landing on the solid surfaces that cause the increase in temperature. Assigning material properties to the solids in the model results in those temperatures being predicted.


3D_Heat_Flux>100degC is hot enough to cause plastic deformation in the wing mirror and certainly hot enough to cause plastic lemon deformation as seen in this BBC report!

How a design will behave after it is commissioned in its actual operating environment is often not intuitively obvious. Simulation plays a key role in providing design engineers with the insight necessary to ensure there won’t be any nasty surprises, warranty issues or car repair bills to be paid!

You can try out FloEFD right now by signing up for a VLab cloud based trial.

5th March 2015, Nottingham.

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2 March, 2015

Semi-Therm, the world’s largest dedicated electronics thermal conference, will take place between March 15-19 at the Doubletree Hotel in San Jose, California. Now in it’s 31st year, this IEEE sponsored conference maintains its high standards in peer reviewed papers covering a range of disciplines within the electronics cooling field.

As usual, the Mechanical Analysis Division of Mentor Graphics will be in attendance. Our division will be presenting 4 papers:

  •  “An Additive Design Heatsink Geometry Topology Identification and Optimization Algorithm” Robin Bornoff, John Parry. 3D printing is set to revolutionise rapid prototyping and manufacturing. Thermal design techniques will have to adapt to reflect the opportunities this presents. Myself and John have identified a novel approach to heatsink design, inspired by Bejan’s Constructal Law, that results in a heatsink topology being ‘grown’ based on a series of successive FloTHERM simulations. The details of ‘Dolly the Heatsink’ and how she was developed will be presented in Session 11 “Enhanced Heat Transfer” on Thursday March 19.

 DHS1    DHS2

  • “Lifetime Estimation of Power Electronics Modules Considering the Target Application”. Attila Szel, Zoltan Sarkany, Marton Bein, Robin Bornoff, Andras Vass-Varnai, Marta Rencz. Reliability prediction of power inverter modules involves a combination of both experimental methods to derive lifetime characteristics and simulation of the device under actual operating conditions. This flow will be presented in Session 12 “Quality and Reliability” on Thursday March 19.



  • “Application of the Transient Dual Interface Method in Test Based Modeling of Heat-sinks Aimed at Socket-able LED Modules” András Poppe, Gusztáv Hantos (BUTE), János Hegedűs (BUTE). Another application of the method that underpins JESD15-14, to be presented in Session 9 “Measurements and Characterization II” again on Thursday March 19.
  • “Range and Probabilities of LED Junction Temperature Predictions based upon Forward Voltage Population Statistics” James Petroski. To be presented in Session 12 “Quality and Reliability” on Thursday March 19.

So, Thursday March 19th, a date for your diaries! I will also be presenting at one of the two vendor presentation sessions on the 17th or 18th (tbd) where I will show the forthcoming, major and exciting features of FloTHERM V11 with a focus on workflow automation.

I’ll do my best to leave the English weather where it belongs, in England, and see you in sunny CA soon!

2nd March 2015, Ross-on-Wye

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24 February, 2015

It’s National Engineer’s Week in the US this week. A similar event takes place in the UK in March. I’ve been lucky enough to have been an engineer (mechanical) for my entire career and long may it continue! However I didn’t start out enthusiastic about engineering at all. When I was young I never really had an interest in renovating cars, fixing engines or taking things apart generally. I was best at mathematics and physics which was why I defaulted to studying mechanical engineering at university. It was there that my love of a specific type of picture drove my love of the subject.

Vicotrian_engineering_genius_isambard_kingdom_BrunelMand1Brunel was the most famous of Victorian engineers. Designer of bridges, railways and big big ships, the University that bears his name lies just to the west of London. 1988 was a good time to start at Brunel. At that point it was still fully government funded so we did have certain freedoms not enjoyed today. It was in my first year that I first saw a fractal, a real ‘wow’ moment. I was keen to find out more.

Mathematics is to Engineering as words are to poetry. Understanding the math(s) behind how a fractal is generated was a revelation. So much complexity, at an infinite number of scales, from the simplest of non-linear relationships. The universe’s artwork indeed. Spurred on to find out more I next came across the Lorenz attractor.

A_Trajectory_Through_Phase_Space_in_a_Lorenz_AttractorIn 1963 Ed Lorenz published his seminal paper “Deterministic nonperiodic flow. Journal of Atmospheric Sciences. Vol.20 : 130—141″. The butterfly effect was a term coined from it. Put simply, a (non-linear) mathematical model that intended to predict global weather patterns was found to be sensitive to initial conditions. Start two simulations with very very slightly different starting points and the two solutions will, after a while, deviate widely from each other. How fascinating and fundamental is that!

RaBeWhen I did specialise in fluid dynamics during my final couple of years at Brunel I was naturally motivated to understand the concepts behind Lorenz’ study. Unlike some of my fellow students I couldn’t wait to find out about boundary layer theory, turbulence, turbulence modelling and computational fluid dynamics (CFD). Once I had enough theory, I did study Lorenz’ paper in detail. His model was akin to a Rayleigh-Bernard convection configuration, hot floor, cold ceiling, the air circulates between the two, hot air rises, colder air sinks back down. The Lorenz attractor is simply a graphical representation of state of those convection cells, their rotational rate, the temperature difference across them. For some more extreme temp differences between hot floor and cold ceiling those convection cells spin one way, then spin another, in an a-periodic way. That point flying round the attractor NEVER crosses its own path, the system is random, chaotic and ultimately unpredictable. The displayed animated CFD simulation of such a convection can be considered as a single point on the attractor. It’s purely coincidental that the attractor and convection cells look somewhat similar!

After uni, infused with a love of CFD, I was extremely fortunate to go work for Flomerics, a UK CFD software vendor focusing on simulating HVAC and electronics thermal applications. I’ve been there ever since (now part of Mentor Graphics). Developing and demonstrating the value of CFD, surely engineering jobs don’t get much better than this!

Generic Laptop Section Top  Window_and_radiator   Air flow over heatsinks

There are no stereotypes in engineering. You don’t have to be into cars to excel in mechanical engineering, into stripping down radios to be a brilliant electrical engineer. All you need is a good grounding in math(s) and a love and enthusiasm for understanding the world around you.

24th Feb 2015, Ross-on-Wye

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10 February, 2015

A full 3D thermal simulation of an electronic system requires, not surprisingly, a 3D geometric representation of the proposed design. Much of the design data for a phone, laptop, blade server, IGBT cooling system etc. often already resides in an MCAD system and is readily importable into FloTHERM or loadable into FloTHERM XT. EDA design data, be it a PCB layout or BGA substrate, is often held in 2 or 2.5D descriptions. The need to convert that data into a 3D thermal representation has led us to evolve a couple of unique FloTHERM technologies.

PCB_Patch_ResolutionDirect interfaces (installed with FloTHERM) to Expedition, BoardStation and other EDA tools extract all the necessary information required for an efficient yet thermally accurate definition of the PCB/Substrate. The complexity of modern day PCB designs, as is evident from the winners of Mentor’s annual Technology Leadership Awards, is such that it is intractable to extract the EDA data as 3D at source. Instead we have pioneered a ‘light’ approach whereby all metallic routing/via information on conducting and dielectric layers is rendered to a high resolution raster image. When further compressed, the data is a fraction of the size it would otherwise be, without losing any of the fidelity required to reconstitute a detailed thermal representation. To do that, a real-time graphics processing technology is used in FloTHERM to convert the images to a thermal conductivity map. The resolution is slider-bar controlled, allowing an appropriate detail to be achieved. For forced convection applications, where most of the heat does not go into the PCB, a lower resolution can be used. For natural convection or conduction cooled environments a much higher resolution can be used that accurately resolves the patch-by-patch orthotropic conductivity thermal resistances on each PCB layer.

[As an aside, here’s an interesting whitepaper on 10 tips for streamlining PCB thermal design]

An alternative technology can also be used to convert any image (regardless of source) representing a metallic distribution into an extruded identical 3D representation. Here no orthotropic pixelated patches are created, a single object with an assigned material can be created that is the 3D (extruded) equivalent of the 2D image.

Just by obtaining some images of the Cu distribution in a BGA substrate a 3D model may be constructed and thermally simulated.


FloTHERM_MandlebrotI’m a big fan of fractals. So, to exercise this functionality further I converted a picture of a part of the Mandelbrot set into a 3D extruded solid, made it out of Copper, embedded in a lower conductivity substrate and imposed a 100degC temperature difference across it and simulated the resulting heat flow. I’ve yet to figure out a useful application for this but hey, it looks all kinds of stunning.



Not content to stop there (OK, I got carried away) I also simulated the hot spur of a well known footballing chicken (COYS!!)COYS

And finally, as Valentine’s day approaches, and as is representative of the love I have both for my wife and for this functionality, the thermal behaviour of a dissipating heart (6W, k=385W/mK embedded in a 2W/mK substrate, peripheral HTCs of 1000W/m2K (top) and 100W/m2K (other sides) @0degC), based simply on an image LoveHeart_small  was also simulated in FloTHERM.


Copper Heart Encased in Plastic


Temperature Distribution from the Dissipating Heart. That’s Some Hot Love.


Animated heat flux vectors (note the heart’s thermal stagnation point)

Happy Valentine’s day everyone. May your day be filled with love :)

10th February 2015, Ross-on-Wye

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21 January, 2015

Energy isn’t the only thing that is wasted when dealing with hot water supply. Time is as well. The house I live in is nearly 200 years old. It wasn’t a very well made house when it was new and, unlike a good wine, has not got better with time. The retrofitted, refitted, repaired, repaired and repaired again hot water supply system would have benefited from some up front design. As it is the flow rate of the hot water to the taps (faucets) is as tardy as it is tepid. #FirstWorldProblem, sure, 750 million don’t have access to a clean source of water, let alone a clean source of preheated water. Regardless of application, getting water from A to B has been a human endeavour for millennia. Fluids simulation helps you do it better.

Fat Finger SensorTurn the hot tap on in my kitchen and you have to wait ages for the dribbly stream of water to become hot. Despite knowing this and being reminded of it every day, I still deploy the FFS (fat finger sensor) every time I turn the hot tap on. That’s about 80 seconds of time wasted, just standing there, staring at my finger, waiting. A daily ritual that often involves my beloved hollering “You might as well put the bins out instead of just standing there!”.

The flow is so low because it’s a gravity fed (and ill-designed) system. A header tank above feeds water to the hot water tank below. There is a then a long run of 15mm diameter plastic pipe to the kitchen sink. The header tank is quite shallow and only a metre or so above the hot water tank. Not much head to force the water out through the ~23m run.

Mentor Graphics acquired Flowmaster 3 years ago, adding it’s ‘1D CFD’ systems simulation capability to the suite of simulation tools offered by the Mechanical Analysis Division. For large fluid dynamics systems, dominated by pipe delivery, 3D CFD is often too computationally inefficient to be deployed. 1D CFD offers a network based approach to solving for fluid flow and heat transfer in a fraction of the time, allowing pump/pipe sizing to be determined early in the design process.

HotWaterSystemSketchPersonally I’m just beginning to get familiar with the use of Flowmaster, so for this study I cajoled my colleague Doug Kolak into simulating my hot water system (thanks Doug!). In the absence of a CAD description I sketched out my configuration for him. And yes, after years of constant keyboard use my drawing skills have regressed to that of an 8 year old :(

A flow actuated pump would be a beneficial addition to the system. Forcing the water through faster than gravity alone manages. Flowmaster can easily be applied to simulate both configurations, giving an indication of what advantage the pump offers in terms of how long to wait until the water supply heats up and the subsequent sink bowl filling time. The animation shows both configurations, overlayed. Interesting to see how the ‘front’ of hot water becomes diffused leading to a gradual increase of temperature at the tap.


TankSinkThe Flowmaster network is constructed from a number of different components, pre-characterised for their fluid and thermal behaviours. Tanks, pumps, pipes, diffusers, jet pumps, bends, T-junctions, Y-junctions… with over 400 to select from a wide range of applications are covered. Despite the relative simplicity of this model, the control system at the sink end is quite interesting, set to start filling the sink bowl once the temperature of liquid coming out of the tap rises over 40degC (equating to me moving the tap over a plastic bowl in the sink when FFS starts to get too hot), then the tap is turned off when the bowl is filled to 99% of its volume.

Water Temperature at TapInclusion of the pump shortens the time it takes for the water at the tap to get warm by about a half, the bowl takes half the time to fill and there is a slight increase in the temperature coming out of the tap (due to there being less time for the water to lose heat as it flows through the pipes, from the tank to the sink).Sink Percent Full Any further improvement might be had by increasing the diameter of the pipe so that the pump would work at a higher flow rate. In fact the design challenge could be inverted so that the required time to fill the sink might be defined as an input to the model, the sizing of the components of the hot water system then be determined through simulation so as to achieve that design goal. With simulation time measured in seconds, the way in which Flowmaster can be deployed offers many advantages over classical 3D CFD.

Flowmaster is available for evaluation using our ‘Virtual Lab’ technology. No need to install locally, just log in and get going!

21st January 2015, Ross-on-Wye

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9 January, 2015

Horror vacui, Natura abhorret vacuum, Resintenza del vacuo; from Aristotle to Galileo, it has long been known that here on earth matter tends to flow from where it is to where it isn’t. Fast forward to Hobbes and Boyle, Newton and Leibniz and we find such concepts being being applied in a fluid dynamics context. From a heat transfer perspective heat energy also tends to flow from where it is to where it isn’t, from where it is hot to where it is cold. An equilibrium will be reached. As humans we love energy, we can do lots of interesting things with it. We constantly endeavor to get all those Joules to do our bidding, including storing them for later use, which is many ways can be like trying to corral cats.

So it took a couple of hours to heat (a point in) the water tank to 60degC. As sure as eggs those Joules aren’t going to hang around. They will leak out and in their wake they will  leave the water at the same temperature as the ambient in which the water tank sits. Let’s take a qualitative look at how insulation surrounding the tank plays a role in delaying the inevitable.

I personally don’t have a material thermal conductivity tester to hand (but sure, we do offer one in the form of our DynTIM). So far in this study I’ve assumed the insulation on my tank is expanded polyurethane type foam with a very low conductivity of 0.03 W/mK, that’s about 6000 times better at keeping the heat in compared to Aluminium. What if it wasn’t as good an insulator? What if it was say, 0.24 W/mK about that of cotton. Let’s compare and contrast how the heat leaves and the water cools when using these different insulation materials. Good insulation on the left, not so good on the right, the temp range is from 25 to 62 degC. The simulation simply carried on from the end of the warm-up, but with the power to the heater element turned off and the resulting change in temperature simulated over the next 10 hours:


The water at the top of the boiler certainly remains hotter for longer which is why the hot water extract pipe is always higher up in the tank. Seen even more clearly if we look at how the volume of water that is greater than (an arbitrary) 54.5 degC shrinks over that time:


TeaCosySo, from a design perspective, having understood where the heat is leaving you could consider investigating shifting some of the insulation to the top of the tank, where the energy in the hot water tends to gather. There’s always room for improvement. Actually not always, a tea pot with a tea cosy on is as perfect an insulated object as you’ll ever find and although it might be improved from a thermal perspective, its quintessential Britishness is timeless :)

9th January 2014, Ross-on-Wye

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Meet Robin Bornoff

With a mechanical engineering background and CFD foundation, I have 20 years of experience in the field of electronics cooling design and simulation. Beyond my vocation I enjoy making my own cider, appreciating fractals and prime numbers, running (slowly) and will only ever read Sci-Fi.

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Upcoming Appearances

  • Semi-Therm 2015
    March 15-19: An Additive Design Heatsink Geometry Topology Identification and Optimization Algorithm; Lifetime Estimation of Power Electronics Modules Considering the Target Application