Introducing Top of the World

Tall buildings are one of the main reasons I chose to become a structural engineer. One of the ways this interest expresses itself is that whenever I find myself in a new city, I try to make it to the highest floor possible of the tallest building I can find. Seeing the tiny cars and people a thousand feet below never gets old to me.

In most cases, these photos involve an observation deck in a famous skyscraper, but in other cases a little more creativity is involved, as you’ll see. I have now done this in a number of cities across the world, so I thought I’d create a new category on this blog for archiving these photos.

And don’t worry, this website is not going to turn into a blog of pictures of myself. I’m only planning on posting these top-of-skyscraper photos once a month or so.

Unexpected results are good

It’s good to encounter results you don’t expect. Isaac Asimov famously said:

The most exciting phrase to hear in science, the one that heralds new discoveries, is not “Eureka” but “That’s funny…”

As you gain more expertise, you become better at anticipating experimental or numerical outcomes. But at the same time, research is exploration, which I think means regularly encountering things that don’t initially make sense. You have to pay attention to the story told by the data, and sometimes your biased expectation gets in the way of you truly grasping what it’s saying. Accepting that the truth you seek runs deeper than your mental model of it is a healthy form of humility.

Unexpected results mean you actually stand to learn something new. The faster you learn to appreciate unexpected results—instead of trying to force them into your existing paradigm—the better. Especially pay attention to results that only seem slightly off—I have gained significant insights from small deviations from my expectation that I initially assumed were inconsequential, but proved fascinating or important upon further reflection.

PDF syncing in Sublime Text for LaTeX on Windows

I have moved all of my work back onto a Windows box recently, which means completing overhauling my LaTeX setup. I know there are a lot of integrated environments for LaTeX on Windows, but I prefer a straight text editor. Coming from Textmate, I landed on Sublime Text 2.

Sublime comes with a LaTeX bundle already installed (which has syntax highlighting and a number of other bells and whistles), but it takes a bit more elbow grease to achieve two-way syncing with a PDF viewer and use XeTeX. I couldn’t find anywhere else on the web that exactly details this process and confirms that it works, so for anyone searching for the solution (and for myself next time), here is how I got it working:

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Enough Python to keep me happy

When I started programming in Python several years ago, I liked it so much that I thought I wouldn’t work anywhere in the future that didn’t develop primarily using it. Now, my perspective has shifted.

Very little of my deliverable research output is Python code. Yet, I program in Python almost every day. Whether it’s writing a data filter, a parser with regular expressions, an optimization routine, a plotting utility … I have a growing library of personal software that I rely on heavily to get things done.

What I found is that as long as I am using Python to augment my workflows and solve odd problems, I can tolerate a lot of friction in other areas of my professional life. Using Python as my personal computational platform is a pressure valve in my toolchain. It’s enough to keep me happy.

This realization was incredibly freeing. It removes a massive constraint on potential work environments and sets me up to wield a powerful secret weapon in nearly any firm (design/software/research) in my discipline.

See also: The Python Paradox by Paul Graham and Python is a Voluntary Language by John D. Cook.

Problem to be solved

The other day I completed a difficult and uncertain benchmark in my PhD, the sort of step that tested the viability of one of the major features of my research.

During the several weeks leading up to this, I encountered some of the hardest problems that I’ve faced so far. The thing that surprised me was that after each problem presented itself, I was able to not only identify its source but also a solution, usually quickly even. After I went through this several times, I realized: these are nothing more than problems to be solved. What was I so worried about?

Expect to encounter difficulty, but also expect that you will prevail against it. If you are doing interesting work, you will be brought to a standstill by problems that stretch your understanding and threaten your belief in your expertise. Don’t shrink back from these, but rely on your training and move forward confidently. This is pragmatic optimism.

Your saw is sharp enough, and you may actually be on the verge of a better insight than you expected.

Burj Dubai finite element model

My wife and I love to travel off the beaten path, a practice which has brought us to Dubai on several occasions. Being a structural engineer, getting to witness the progress of the Burj Dubai (now Burj Khalifa) at several stages during its construction has been an obvious highlight. Here is a photograph I took from a friend’s apartment during our last visit in 2008:

To say that the Burj Khalifa makes a striking impression on the skyline is an incredible understatement. It is imposing and inspiring.

Several years ago, I implemented a new meshing algorithm in our finite element software. I needed an interesting test case so I decided to mesh a typical floor plan from the Burj Dubai to evaluate my algorithm. I thought it might be interesting to share the results here.

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Dealing with temperamental scientific models

Finite element models can be temperamental. I have a model at this moment that is producing incredibly accurate results. So good in fact that if they were someone else’s results I might be tempted to wonder if they were “post-processed”.

About an hour ago, the solution (quasi-Newton) was diverging half way through—now it soldiers right through the last solution step. I do not know what changed. I prefer a slightly more deterministic process.

In the words of one of the leaders in my specific niche of nonlinear finite element analysis to me at a recent conference:

NLFEA is an art, not a science.

This means building, calibrating, and validating models requires a lot of TLC. You’ll feel like it should just work, that you shouldn’t have to go through all this tedium. But today—in 2012—this is reality.

How to digitize a graph on Windows

I have written before about how to digitize a graph on a Mac. Numerical analysts regularly need to plot the response of numerical models against experimental results only accessible via plots embedded in pdf files. This applies not only to older raster documents, but also to vector-based pdf files. Until researchers begin making more data publicly available, this is a problem we have to contend with.

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Reading research papers on the iPad

One of the driving factors behind my decision to buy the new iPad was the experience of reading academic papers using the new retina display. It has not disappointed. As previously stated, beyond a few inches from my face, it basically looks laser print quality to me. Both single- and double-column journal articles are perfectly legible. To get a feel for the resolution of a typical pdf (single/double columns), check out the full size images below:

Screenshots:

Two weeks with the new iPad

A few weeks ago I pulled the trigger on the new iPad (the 3rd generation). I have a lot to say that will surely span several posts. In this first one, I want to talk about why I went this route and my initial impressions.

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