Modelling Robust Design Problems via Conic Optimization

This thesis deals with optimization problems with uncertain data. Uncertainty here means that the data is not known exactly at the time when its solution has to be determined. In many models the uncertainty is ignored and a representative nominal value of the data is used. The uncertainty may be due to measurement or modelling errors or simply...

Towards robust design optimization of automotive turbocharger rotor-bearing systems

In the competitive automotive market, the performance of turbochargers is constantly being pushed towards their theoretical optimum. One of the key components of the turbocharger is the rotor-bearing system, which determines the friction losses and noise output and furthermore affects the overall turbocharger efficiency, reliability and cost. In...

Value of information in closed-loop reservoir management

Over the past decades, many technological advances have unlocked new opportunities to boost efficiency in the oil and gas industry (e.g., complex well drilling, injection of advanced chemicals, sophisticated instrumentation). The real engineering challenge is to apply these technologies in the best possible way for each particular case. This...