It's common knowledge that heat causes things to expand. That's why running warm water over a jar lid can make it easier to loosen. Heating stuck nuts on bolts can also make them easier to remove.
Non-uniform heating of materials causes deflection. The sites where heat is applied expands and the cooler parts remain the same. The most interesting application of this that I've personally seen is how some car turn signals work. There is a little metal wafer with a heating coil running down one side. When you turn on the turn signal this coil heats up and within a little less than a second it warps the wafer (just like the rod does in my video but much more dramatically) so that it closes an electrical connection and lights up the turning signals on the outside of the car. Since the heating coil is bypassed by this, it rapidly cools down and the heat goes away causing the wafer to return to it's original shape. This disconnects the circuit, the coil heats up, and the cycle starts over. When I first took apart one of these relays I was astounded that they hadn't used solid state electronics. It just seemed that electronics would be a better way of doing this and far more predictable. But, after some contemplation, the wafer coil setup is probably cheaper to make and it's not like car turning signals need clock like accuracy anyway. If it works, it works; why change it.
Sometimes I think we succumb to the desire to change things because we have identified a better solution. But without looking at the original requirements and weighing the cost, this can turn into a waste of time and effort. I'm not saying that we shouldn't look for better solutions, but it's a good idea to make sure than in the context of the application and it's mission that they actually are in fact better. The most recent examples of this are people moving to cloud analytic frameworks and nosql. Most business intelligence data that I've interacted with isn't that big. Maybe a few hundred thousand records. Certainly some is larger, and everyone wants to crunch social media data which is certainly gigantic. But if your BI data can fit on a single hard drive or even in the ram of a single computer then by all means stick with a simple setup! This is pretty much anything less than a Terabyte of data... which is pretty much everybody. If you really need to figure out what people on twitter or facebook are saying about you, subscribe to services that analyse social media for you, or... use the native functionality of the social media services themselves. Strategy trumps technology in every BI scenario that I can think of. Sometimes yesterdays technology can support today's mission just fine.