Henry Ford's Model T is on the verge of its 107th Birthday. As we all know, the Model T was the first and most popular mass produced automobile in the world. The Model T was introduced on Oct. 1, 1908 and by 1921, Ford Model Ts accounted for over half of the world’s automobile production.
Multiscale Modeling is a broadly used term to describe any instance where a physical problem is solved by capturing a system’s behavior and important features at multiple scales, particularly multiple spatial and(or) temporal scales. For instance, the picture below is a temporal multiscale representation of the origins of life.
One of the greatest strengths of composites is their ability to be combined and used in an infinite number of ways. From race car monocoques, to space shuttle heat sheilds, to bottle openers.
For the last 5 years, industry experts have been predicting the upspike in carbon-fiber use. For the last 5 years they have been largely right.
What is considered a "composite" is always changing. Just as there is no single definition, there is also no single analytical method that can safely predict their dynamic behavior. The same way you can’t obtain ideal performance by using a single material throughout an entire car, you can’t expect to use a single analytical method to predict the behavior of all composites.
Rule of Mixtures is probably the most known, and widespread method of estimating composite properties. Its notoriety in composite design circles is also its main problem: Rule of Mixtures has been over used, and applied to cases that do not even come close to respecting its original, simplifying assumptions. If you wish to trust your analysis, it is essential to find out when it is OK, and (more importantly) NOT OK to use Rule of Mixtures. This article will describe what this rule really says, and will show some consequences of abusing this “rule of thumb” for composite behavior.
In 1899, William Ernest Metzger helped organize the first Detroit Auto Show, and since 1907 the show has been running annually.
In our last blog, we talked about the importance of learning from failure in materials testing. For better or worse, theoreticians have, in some ways, tried taken the burden of “learning from failure” off the plate of the common engineer. Instead, they try to capture the insights gained from failure into flexible analytical theories; theories that (theoretically) allow us to predict a parts behavior, without knowing anything more than some material properties and part dimensions. In computer science, this is known as abstraction.
The question is, Can composite failure theories sufficiently abstract all the nuance out of composite design? Do you need to understand the origins of a failure theory in order to use it properly?