Date of Award

Spring 5-11-2019

Level of Access

Open-Access Thesis

Degree Name

Master of Science (MS)


Chemical Engineering


Douglas W Bousfield

Second Committee Member

Andre Khalil

Third Committee Member

Peter Stechlinski


On the surface, paper appears simple, but closer inspection yields a rich collection of chaotic dynamics and random variables. Predictive simulation of paper product properties is desirable for screening candidate experiments and optimizing recipes but existing models are inadequate for practical use. We present a novel structure simulation and generation system designed to narrow the gap between mathematical model and practical prediction. Realistic inputs to the system are preserved as randomly distributed variables. Rapid fiber placement (~1 second/fiber) is achieved with probabilistic approximation of chaotic fluid dynamics and minimization of potential energy to determine flexible fiber conformations. Resulting digital packed structures, storable in common formats, return basic properties and provide a flexible platform for subsequent analysis and prediction. Simulated results are validated through comparison with experimental handsheet measurements. Good agreement with thickness measurements are obtained and possible uses of simulated structures for more enhanced property prediction are discussed.