December 1, 2014 – We are pleased to announce the PhD dissertation defense for Michael Georgescu!
Date: Thursday, December 4, 2014
Time: 9:00am
Location: Materials Research Lab (MRL), Room 2048
Title: Analysis of Systems in Buildings using Spectral Koopman Operator Methods
Abstract:This work presents a viewpoint for analyzing data-based systems using an operator-theoretic approach based on the Koopman operator. In particular we focus on problems emerging from building systems analysis; a setting where systems are high-dimensional and described by large data-sets (either measured or generated from simulation), but for which equations describing the system often cannot be expressed analytically. In the building setting, natural cycles of operations exist that are driven by occupancy, plug load schedules and environmental conditions. Using properties of the Koopman operator, building data can be decomposed into spatial-temporal modes, and from these modes, characteristics of data can be studied at varying time-scales. In particular we present a variety of novel analysis techniques based on spectral properties of the Koopman operator that can be applied to a variety of applications ranging from the monitoring/visualization, model order reduction, and model calibration of building systems. Each chapter is dedicated to one specific application and the tools developed for it. Numerous examples are presented to illustrate the capabilities of the developed framework.
Date: Thursday, December 4, 2014
Time: 9:00am
Location: Materials Research Lab (MRL), Room 2048
Title: Analysis of Systems in Buildings using Spectral Koopman Operator Methods
Abstract:This work presents a viewpoint for analyzing data-based systems using an operator-theoretic approach based on the Koopman operator. In particular we focus on problems emerging from building systems analysis; a setting where systems are high-dimensional and described by large data-sets (either measured or generated from simulation), but for which equations describing the system often cannot be expressed analytically. In the building setting, natural cycles of operations exist that are driven by occupancy, plug load schedules and environmental conditions. Using properties of the Koopman operator, building data can be decomposed into spatial-temporal modes, and from these modes, characteristics of data can be studied at varying time-scales. In particular we present a variety of novel analysis techniques based on spectral properties of the Koopman operator that can be applied to a variety of applications ranging from the monitoring/visualization, model order reduction, and model calibration of building systems. Each chapter is dedicated to one specific application and the tools developed for it. Numerous examples are presented to illustrate the capabilities of the developed framework.