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.

7 August, 2015

I haven’t got very big hands, quite the opposite in fact, so it’s not as if I spend an inordinate amount of time standing there with my just washed hands under a convective hand dryer in a public/office toilet (who has these things at home anyway?). Whenever I do though I’m always wondering whether I’m doing it right.  Should I rotate my hands, leave them in one position, if so, which position? Why didn’t they teach these things at school? I’ve got better things to do than just stand here wishing there were some paper towels to dry my hands with instead. What’s the fastest way to dry your hands under such a dryer? Just the sort of question that can be answered with FloEFD, MCAD embedded CFD (computational fluid dynamics) at its best.


HandArrowsAirTempPlanePlotAlways a good idea to deconstruct a question to ensure it is answered correctly. What does ‘dry’ mean? In terms of hand drying I found out that it is  common to consider a hand dry when it has lost 90% of the initial water that was clinging to the skin. FloEFD has a neat ‘water film’ feature where the amount of water on a surface can be simulated, including the transient effects of evaporation and condensation. A transient simulation requires an initial condition of the thickness of the water film when drying commences. I chose 25 microns (though I did find references of anything up to 100 micron water film thickness after hands are submerged and retracted from a water bath).

I modelled just a single hand at 10 different orientations and tracked the reduction in water film mass over time when the hand was placed under a hot convective flow. The relative reduction of these orientations, together with a comparison of the drying rate when the hand rotated, is shown in the graph below (click to enlarge):

WaterFilmMassVsTime

When the hand is vertically orientated it reaches the 90% dry condition fastest (Design Point 10). Both sides of the wet hand are well dried by the hot air stream that passes over both sides at once. The slowest drying is when the hand is near horizontal (Design Point 7). Here the back of the hand is very well shielded from the hot air and, although the water mass initially decreases quickly (as the palm of the hand gets all the drying) the back of the hand takes much longer.

Further insight into the drying process can be seen when animating the reduction in water film thickness over time, red represents a thick water film, blue represents dry skin:

The fingers dry first due to their large surface area in proportion to their volume, the palm finishing last.

I had assumed that a rotating hand would dry quickest, this was not the case. Although more hand surface area is apparent to the hot air flow in a given time period, it doesn’t stay still long enough for the water film to heat up to aid drying. Sure, in the end it’s the fastest for complete drying, but by that time you could be back at the bar enjoying your next beer.

So, next time you’re drying your hands keep them vertical, be patient and use the time to consider whether it’s more environmentally friendly to use an electric convective hand dryer or paper towels (if available).

If you want to try out FloEFD now, sign up for a cloud based trial: http://www.mentor.com/products/mechanical/product-eval/floefd-standalone-vlab

7th August 2015, Ross-on-Wye

, , , , , ,

1 July, 2015

Holiday themed simulation blogs are very de rigueur of late so I thought I’d jump on the bandwagon in time for the July 4th independence day celebrations in the US. A series of events led up to the Declaration of Independence from Great Britain in 1776, one of the more notable being the Boston Tea Party that occurred on December 13th 1773. The tea ships the Dartmouth, the Eleanor and the Beaver, moored in Boston harbour, were boarded by a group of some 130 men who proceeded to dump all of their 342 chests of tea into the water. I’ve been to a few wild parties in my time but this party might have trumped them all.


TeaPotTea is a quintessentially British drink. It is rather symbolic, and maybe of no surprise, that the act of dumping such a British cargo was a key part of the American Revolution. The reason was not primarily associated with the high tax being levied, more that the tax should not have been levied without representation of the American colonies in the British parliament. The British parliament was not amused, toughened its stance and imposed other punitive laws. The American colonies were even less amused and the rest, as they say, is history.

CoolDownAfternoon tea was a social event for the (British) upper classes in the C17th and C18th, held at 4pm and involving a pot of tea with some cake. The brewing of the tea in a tea pot is essential. Not long enough and the brew is weak, too long and the brew will be too cool and over stewed. So, with a tenuous skip and a jump to tie in some CFD simulation I thought I’d study how a pot of tea cools down, using our FloEFD general purpose CFD tool.

FloEFD works within an MCAD environment, easily allowing 3D CAD geometry to be studied for its thermal and air flow behaviour. A transient analysis, where the water in the pot starts at 100degC, shows how the temperature (liquid, air and solid pot) reduces over time as the energy stored in the water convects, conducts and radiates out to the ambient.

PotMeshAll CFD codes require a mesh of tessellated volumes to be created, covering all the model. The meshing in FloEFD takes a so called ‘boundary last’ approach, where a volume mesh is created first then, using an octree subdivision method, the mesh is refined to capture solid/solid and solid/fluid interfaces. Very little user interaction is required to prep this automated meshing feature. The quality of the mesh elements (Cartesian in nature, but split into multiple control volumes at solid interfaces for accurate surface representation) results in highly assured convergence when the governing equations are integrated over them and iteratively solved.

Post processing allows the complex liquid and air flow patterns to be studied and appreciated.

PotPaths

One thing FloEFD excels at is the ability to represent complex geometric features, be it cluttered assemblies or small gaps, due to the meshing approach and a unique treatment for the resolution of the convective boundary layers. A small gap between the lid and the tea pot is automatically resolved, the thermal insulation of the lid seen in the resulting temperature distribution, here after a few minutes of the cool down:

HotPotA recently added post precessing feature is the ability to plot streamlines using a line integral convolution approach (very Van Gogh, a little bit Munch), click to enlarge:

PotStreamLinesAs a Brit I have mixed feelings about July 4th. Sure, the British empire is long dead and even the Commonwealth seems less relevant today than it did even a decade or so ago. We all live in a global village now so in some ways are closer together than ever, in other ways as disparate as we’ve ever been throughout history. Either way, happy July 4th American cousins!

1st July 2015, Hampton Court, Great Britain

, , , , ,

30 April, 2015

The additive design methodology itself is quite straightforward. It is however highly repetitive. Perform a simulation, identify a maximum temperature location, extend the geometry at that point, if thermal efficiency decreases then repeat. To appreciate and to evolve the approach I began by manually performing a number of the initial steps myself. Solve in FloTHERM, sort the the ‘Max Solid-Fluid Surface Temperature’ column in the Tables post processing window, note the face of that cuboid that was hottest, copy+paste that cuboid to abut that face, solve on, etc. etc. All very RSI inducing, completely boring but absolutely essential ahead of implementing a fully automated approach to do the same.


ExcelFrontEndBack in the day most of the Visual Basic I learnt was done so by recording a macro in Excel, examining the recorded script, shoving a loop round it to do some successive operations on a range of data, that type of thing. A little learning goes a long way. Even with admittedly rudimentary coding skills I was able to write a VBA script, using Excel as a front end, that automated this additive design simulation based methodology. It wouldn’t have been possible without the ability to drive FloTHERM from an external source, create a ready to solve model, command line solve it, extract results out of command line generated .csv files, regenerate the ready to solve model, etc. We opened up FloTHERM’s data model a few years ago, Byron explains more in this blog. This enabled this level of automation to be achieved.

CodeFragmentCore to the scripting is the creation of a ready to solve FloTHERM model in XML format. We install a set of VBA subroutines that take the pain out of writing the raw XML directly. These subroutines can be called, passing arguments such as cuboid size, location, material, the subroutines do the actual writing.

Around 6500 sequential FloTHERM simulations were conducted to form the heatsink. Sounds a lot but when you consider each one starts from where the previous ended and the solve time for each is only a few minutes, total elapsed time wasn’t unmanageable. My only effort (after the code was written, refactored and debugged) was pressing the ‘Grow That Heatsink’ button in the Excel front end then, when the process has finished, using FloTHERM’s automation capability to graphically un-hide each cuboid in order to capture the following animation:

3yearsgrowth

This is just one example of what can be achieved with FloTHERM automation. To discover other opportunities check out Byron’s webinar, introducing both our FloXML and FloSCRIPT technologies.

30th May 2014, Ross-on-Wye

, , , ,

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:

Chamfered3D

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

, , , ,

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.

Year2

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'(?)

Year3

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.

, , , ,

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):

Year1

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

, , , , ,

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

, , ,

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.

MeltTime

(Click to Show Transient Animation)

CarMelt

(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.

CarTemperatures

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.

, , ,

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.

    MagGrdTs

SurfaceTempss

  • “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

, , , , , , ,

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

, , , , ,

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.

Follow Robin

Latest News from Robin

  • Loading tweets...

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