Scientific Computing: Computational science

Are you familiar with Computational science? I didn't really know about it one week ago. So far, I have to admit that I am still a layman. In this post, I will show you what I learned about it recently from definition, application, and process.

Firstly, what is Computational science? Computational science(also scientific computing, scientific computation) is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It uses mathematics and computers to explore "real world" problems in science.

Second, where do we apply Computational science? Problem domains for computational science/scientific computing include: Numerical simulations, Model fitting and data analysis, and Computational  optimization. 
Computational Science complements, but does not completely replace, field experimentation in scientific  research.
It is ideally suited to exploration of problems which are too expensive, too dangerous, too difficult to control...for experimentation in the field. For example, we can use it to reconstruct  and understand known events such as earthquake, tsunamis, and other natural disasters.

Finally, Computational Science Process.  When we use Computational science to solve problems, we firstly construct working model. And then we need to build mathematical behavioral model with the help of working model. The next step is to create computational model. Finally, we can get results/conclusion according to the analysis from computational model. The image below shows the whole process.

In sum, Computational science is an important tool in modern scientific research. Especially, we can use it to imitate special scenarios like earthquake and sub-atomic particle behavior. The cost will be huge to reconstruct these scenes without it.

Computational science is an useful and interesting field. Let's learn and discuss it together.

reference: Journal of Computational Science, Wiki