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Simulation, Experimentation, and Calculation: Which is Best?

28/4/2025

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You’ve probably already thought about the answer to that question. I hope you at least believe that one of these three is essential—rather than relying solely on instinct or heuristics for all your engineering decisions. Most, however, haven’t thought about each of the three in enough detail to fully grasp the implications and limitations of each approach.
Picture
Ideally, at this point, you’re thinking about first principles. Indeed, each of these three represents a different way of applying first principles. So let’s consider how you can best use them for your first principles.
ExperimentationIt’s hard to argue with reality. And that’s what experimentation offers. If the experiment fails, it doesn’t matter if your calculations or simulations say it should work. Experimental outcomes are the ultimate judge.
The issue with experimentation from an engineering perspective is that it always "works"—even if you aren’t aware of what’s important.
You can’t choose to ignore or suppress key variables. They’re always present and always have a value, whether you’ve thought about them or not.
You might set all the key variables you think are important, but there are still others you’ve set inadvertently—because reality has already given them values. That means you might believe you’ve experimentally found a solution to your problem, but when you implement it, an issue arises. Why? Because you were unaware of a key variable—and its value during implementation differs enough from what it was during your experimentation to cause a failure.
Experimentation won’t alert you to your ignorance of key variables until it’s too late.
An example I mentioned in my book involves an engineer designing a device to control water flow for watering plants. Their experimentally developed design worked, but once the system was implemented, variations in temperature—and thus viscosity—rendered it useless. The engineer had conducted all the experiments at roughly the same temperature. Since they didn’t realize how temperature-sensitive viscosity is, they didn’t factor it into their tests—and reality had silently set that variable for them.
CalculationCalculations have the advantage of forcing you to account for all key variables. The formulae you use have been developed after considerable attention by experts who have identified the important variables at play. If the engineer in the earlier example had taken the time to read up on the theory and find the appropriate formula, they would have learned how critical viscosity is. Then, while looking up viscosity values to put in the formula, they would have seen how much viscosity changes with temperature.
Formulae also reveal opportunities for optimization. You can see which variables are raised to a higher power and thus offer more "bang for your buck." You can also work out whether variables should be increased or decreased to maximize your output—which isn’t always obvious. Sometimes, you can even deduce if an optimum point exists.
However, there aren’t always formulae available for your exact situation.
Consider again the water control device: what if it had an outlet orifice that was non-standard, and the engineer couldn’t find a discharge coefficient for it to plug into the formula?
Experimentation could be an answer—but it might be time-consuming if multiple variants had to be fabricated and tested.
SimulationObviously the newest of the three, simulation is almost like a mix of the other two.
Simulation can come very close to reality—assuming it’s a well-developed system—and it can force you to specify all variable values, forcing you to note all those at play.
However, some simulation systems “help” you by asking you to specify a material instead of individual material properties. Thus, you might find yourself back in the same situation: unaware of all the important variables, and unaware of which ones are best to adjust for optimization.
Also, simulations still rely on limiting assumptions. Often, we must simplify systems for the sake of usability. So your simulation might not be a perfect representation of what you’re actually working on.
While simulation can offer tremendous benefits when it comes to testing ideas and improving systems, it’s still not a silver bullet.
What to Do Then?It’s likely clear to you by now that you need to use all three—experimentation, calculation, and simulation—if you want the insights, speed, and confirmation needed to find the optimum solution. Beware of any engineer who suggests you should focus on one and ignore the others.
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​Which race has the best inventions?

14/4/2025

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Or – do we really invent anything?

4 people who are the same, but different race showing how we can all be inventive
Different races, same potential. Innovation doesn’t live in our genes—it lives in our environment.
If you have read my book on how to be a Global Engineer, then you will recall that I cited an interview with the rapper Azealia Banks. In this interview, she noted the stereotype that Africans have not invented anything because history is taught to focus on white history (and the associated inventions). You can see that excerpt of the interview below - go to 36:37.
You will note two things:
  1. She notes that there are things that were invented in Africa that are often assumed to have been invented elsewhere.
  2. She gets very emotional about it because of the effect it can have on people when they are told (even if only implicitly) that they are from a less inventive race.
This brings us to the topic of how the way technological history is taught to you. And how that could affect the way you assume (maybe even only unconsciously) your race affects your inventiveness – or how you might assume others’ inventiveness might be affected by their race.
You can imagine how someone not from the stereotypically inventive race would have limiting beliefs about their own inventive ability. Further, you can imagine how people would assume others could be less inventive if they themselves are from the stereotypically inventive race.
Both above assumptions are anathema to being a global engineer. And neither assumption is actually supported by reality.
If you read How we Got to Now by Steve Johnson and Guns, Germs and Steele by Jared Diamond, then you will realise two things:
  1. Invention is limited by your environment more than it is by your ability.
  2. Each invention is a result of prior inventions and often shows up in multiple places independently, but under similar conditions.
That means, effectively, we are not the bold inventors driving innovation forward – as we like to think we are – but the mechanism by which one technology provides the need or opportunity for the next.
When you take on this perspective, you no longer think of some latent ability within us (one that could be more common in some races than others) that brings about innovation. Instead, you think of us following a process that is the means by which technology evolves form one invention to the next.
With this perspective, where we see innovation as a product of the situation (including prior innovations), we no longer have to worry about our race – or even our sex, nationality, or any other innate properties of a person – as an indicator of inventiveness. Instead, we simply focus on the processes that allow for ingenuity in ourselves and others. That’s the expectation a global engineer has of themselves and others.
Get the 10 minute audio summary of the book here.

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Can Engineers Save Trump?

7/4/2025

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Or: It’s Economists vs. Engineers

Engineers Vs Economists
​The recent tariffs announced by the Trump administration—imposed on pretty much every other country in the world—have drawn a lot of criticism from economists.
And from other countries.
And from his domestic opponents.
But could things look different from an engineering perspective?
In this piece, I’m going to cover why economists are so opposed to tariffs—and then explore whether there might actually be an engineering opportunity we have not yet noticed.
​
Why Economists Hate Tariffs
Tariffs are supposed to protect local industries and jobs. Intuitively, that seems great—cut out foreign competition, and locals get to keep their jobs. Or, in Trump’s case, bring jobs back.
But in the current U.S. context, two things complicate that picture:
  1. Low unemployment
  2. A strong currency with high purchasing power
That means if jobs are going to be brought to the U.S., then companies need to do two difficult things:
  1. Pay more than they would in another country, to match U.S. dollar purchasing power; and
  2. Pay even more again to lure people away from the jobs they already have—because most Americans already are employed.
So any product made in the U.S. under this model comes at a higher cost. And those higher costs get passed on to customers.
And there is evidence of how tariffs do actually put prices up. But not in living memory for many. One of the few places where people in a developed economy can recall the effects of tariffs is Australia. In the 1970’s Australia was only just introducing colour T.V. But this was stifled by tariffs. The tariffs were there to protect the local radio and television manufacturing industry – but the effect was that a colour T.V. would cost around 9 weeks’ pay. Australians were not impressed, but they still wanted their colour T.V. Tariffs dropped from around 180% to 35% to 5%. A lot of industries were lost, but a lot of things became affordable. You can watch a 17 minute video on this topic below.
Adam Smith, almost the first of classical economics, argued over 200 years ago against tariffs — even retaliatory ones — because they only hurt your own citizens.
 
Can Engineering Offer an Alternative?
All of this assumes that the technology of production stays the same. That’s a key point. It’s essentially a zero-sum view.
But what if innovation could shift the game entirely?
In my book, I argue that engineers—when thinking about economics—should be Schumpeterian. Joseph Schumpeter believed that real economic growth doesn’t come from reshuffling jobs or trade balances. It comes from innovation. From finding ways to do more with less. That’s how societies get richer. Fewer people needed to make a car, a fridge, or a bag of doughnuts. More output per person.
But innovation doesn’t just happen. It needs a driver.
And unfortunately, fear has often been one of the most effective motivators.
Take WWII. It produced radar, jet engines, penicillin, and kickstarted the computing revolution. Or the space race—another fear-fueled scramble—gave us satellites, advanced materials, and a cascade of spin-off technologies we now take for granted.
Even in peacetime, we’ve seen what can happen under pressure. During COVID, I was part of a project that turned an empty office space into a factory. And thousands of ventilators were built in a matter of months.
So here's the question: what if the fear of tariffs and economic stagnation could be channeled into a national innovation push? Could the U.S. become dramatically more productive—not by avoiding the cost of labour, but by needing less of it?
 
Why Hasn’t This Happened Already?
We have the tools. Automation, AI, robotics—these technologies exist. As an engineer, you’ve probably noticed just how much day-to-day human labour could already be automated. Diagnosing illnesses. Servicing vehicles. Even preparing food.
So why haven’t we gone all-in?
Two reasons, I think:
  1. Economists tend to default to comparative advantage
    They prefer frameworks where countries do what they’re “best” at. That often leads to outsourcing and doesn’t put much value on building new capabilities.
  2. It’s just plain hard to imagine an economy without people
    Let’s be honest. The idea of a society where most of us are no longer “needed” economically is both utopian and hard to believe. I must confess, I struggle to envision how it would work.
 
The Trump Thought Experiment
But imagine the benefits if Trump rallied resources to develop this kind of innovation to make as many people as possible redundant. There would be ample people to take on these jobs he wishes to bring into the U.S. And, what’s more, there would be a huge increase in the amount of production per person. The wealth increase would be phenomenal. This would then set an example for the rest of the globe. And all would then enjoy an increase in wealth when they did the same thing.
But that would require two things:
  1. Fear
  2. Imagination
Not a common combination.

What’s the takeaway?
The above does seem fanciful. Like I said, I can’t imagine an economy free of people. I think it would make for an excellent challenge for economists though. But still, it helps us think about just how much we could improve things if we really focused on seriously on eliminating the need for us.
And who knows, there are times when history takes a turn no-one saw coming
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    Author

    Clint Steele is an expert in how engineering skills are influenced by your background and how you can enhance them once you understand yourself. He has written a book on the - The Global Engineer - and this blog delves further into the topic.

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