Optimal experimental design of physical property measurements for optimal chemical process simulations

Chemical process simulations depend on physical properties, which are usually available through property models with parameters estimated from experiments. The required experimental effort can be reduced using the method of Optimal Experimental Design (OED). OED reduces number experiments by minimising expected uncertainty parameters. In chemical engineering, however, main purpose an experiment is not to determine minimum but simulate processes accurately. Therefore, this paper presents measurements resulting in most accurate simulations: c-optimal design (c-OED). c-OED aims minimise simulation results, linear propagation uncertain model. We use liquid-liquid equilibrium and diffusion thermodynamic economic performance metrics three solvent-based processes. all case studies, substantially for same accuracy compared state-of-the-art that neglects process. Our findings confirmed a Monte-Carlo designed Furthermore, we assess limits highly nonlinear models. Thus, work shows how successfully reduce tailoring designs