What is Computational Science and Engineering (CSE)?

Rocket technology has been a key element in making space flight possible. However, space flight is very expensive and advances in propulsion systems are necessary to reduce costs. Traditionally, aerospace engineers look for different rocket configurations and propellants for testing in a long and expensive process. A more efficient alternative is to simulate different rocket designs in a computer and determine which one meets the performance goals. Applied mathematics provides the tools to analyze the mathematical model that describe the physics and chemistry inside the rocket. Computer science provides the methods todetermine the best algorithm and infrastructure to run the simulation.

CSE is a multidisciplinary topic, involving much more than just programming. For it to be applied effectively, three types of knowledge are necessary: knowledge of the domain of application; knowledge of mathematical modeling; knowledge of efficient implementation techniques. Often this means that CSE is a team effort, each member of the team contributing his or her own particular expertise. CSE differs from mathematics or computer science in that analysis and methodologies are directed specifically at the solution of problem classes from science and engineering [1].

CSE graduates experience a much broader training in theoretical and computational methods than graduates of the traditional programs. This broad education greatly enhances the flexibility of the graduates at the time of choosing a career [2]. Some examples for career paths are:

**Weather and climate prediction**

Future energy and environmental strategies will require unprecedented accuracy and resolution for understanding how global changes are related to events on regional scales where the impact on people and the environment is the greatest [1].

**Aerospace and automotive design**

Since the early days of computing, computational simulation has been used in the performance analysis and design of aircraft and car components. As computations become more sophisticated and computers more powerful, computational simulation is used as an essential tool in the complete design process [1].

**Biology**

CSE technologies are rapidly becoming indispensable to the biological and medical sciences. Simulation plays a major role in the conceptual development of medical devices, both those used in diagnostic procedures (electromagnetic, ultrasonic, etc.) and in design of artificial organs (hearts, kidneys, etc.) [1].

**Public service**

The evaluation of realistic estimates for the probability for major disasters and the simulation of their consequences become more and more important [2].

**Banking and insurance**

Both for insurance companies and for private and public banks the computer-based evaluation of math finance models plays an increasingly important role. In both cases the simulation of stochastic processes is of interest, for instance for estimating the probability for the occurrence of damage, the compilation of risk profiles for portfolios or the determination of the fair value of derivatives and the associated risk hedging by suitable counter transactions [2].

Up to early 20th century, mankind had to rely on mathematical analysis and was very successful in giving birth to basic theories like electrodynamics, quantum mechanics, and quantum chromodynamics. However, models for nonlinear physics such as fluid dynamics, nuclear interactions, and phenomena involving many variables like phase transitions and nanoengineering are too complex to be handled analytically. The mathematical complexity became a problem for the rapid advance of such scientific fields.

During the late 20th century, the adoption of computers in the mainstream added tremendous leverage as tools to provide insights through simulation. The intellectual challenge to the present and the next generations of scientists and engineers is to achieve innovations and make breakthroughs at the frontiers of science and technology:

- frontier of extremely small scales (e.g. femtoworld, nanoworld)
- frontier of extremely large scales (e.g. astrophysics)
- frontier of extremely complex phenomena (e.g. life science, earth science, socio-economic dynamics)

At very small scales computer simulations can be used instead of actual experiments, which tend to be very expensive or impossible to arrange. Similarly at the very large scales, simulation is often the only feasible approach as it is not practical to use experiments at all. In the case of very complex processes there is often no agreed mathematical model or the available models are not amenable to analytical solution. In such cases, CSE allows rapid development of models and testing of hypotheses. Generally, computer simulations are often preferred as they allow to investigate the impact of varying model parameters and initial conditions, as well as providing meaningful visualizations of extremely complex data.

In addition to making fundamental advances in the sciences, CSE has been used successfully in industry in the development of new products. Private companies have reduced their research and development (R&D) costs by using CSE to streamline their operations. This gives them a competitive advantage that allows them to expand their markets and increase their revenue.