Towards an EDSL to enhance good modelling practice for non-linear stochastic discrete dynamical models Application to plant growth models

International audienceA computational formalism is presented that structures a C++ library which aims at the modelling, simulation and statistical analysis of stochastic non-linear discrete dynamical system models. Applications concern the development and analysis of general plant growth models

Cost effective and Non-intrusive occupancy detection in residential building through machine learning algorithm

Residential and commercial buildings consume more than 40% of energy and 76% of electricity in the U.S. Buildings also emit more than one-third of U.S. greenhouse gas emissions, which is the largest sector. A significant portion of the energy is wasted by unnecessary operations on heating, ventilation, and air conditioning (HVAC) systems, such as overheating/overcooling or operation without occupants. Wasteful behaviors consume twice the amount of energy compared to energy-conscious behaviors. Many commercial buildings utilize a building management system (BMS) and occupancy sensors to better control and monitor the HVAC and lighting system based on occupancy information. However, the complicated installation process of occupancy sensors and their long payback period have prevented consumers from adopting this technology in the residential sector. Hence, I explored a method to detect the presence of an occupant and utilize it to reduce energy wasting in residential buildings. Existing methods of occupancy detection often focus on directly measure occupancy information from environmental sensors. The validity of such a sensor network highly depends on the room configurations, so the approach is not readily transferrable to other residential buildings. Instead of direct measurement, the proposed scheme detects the change of occupancy in a building. The new scheme implements machine learning methods based on a sequence of human activities that happens in a short period. Since human activities are similar regardless of house floorplan, such an approach may lead to readily transferrable to other residential buildings. I explored three types of human activity sensor to detect door handle touch, water usage, and motion near the entrance, which are highly correlated with the change of occupancy. The occupancy change is not only based on one single human activity, it also depends on a series of human activities that happen in a short period, called event. As the events have different durations and cannot be readily applicable to existing machine learning models due to varying input matrix sizes. Hence, I devised a fixed format to summarize the event regardless of the total duration of the event. Then I used a machine learning model to identify the occupancy change based on the event data. The saving potential of occupancy driven thermostat is about 20 % of energy in residential buildings. However, the actual saving impact in any given house can vary significantly from the average value due to the large variety of residential buildings. Existing building simulation tools did not readily consider the random nature of occupancy and users’ comfort. For this reason, I explored a co-simulation platform that integrates an occupancy simulator, a cooling/heating setpoint control algorithm, a comfort level evaluator, and a building simulator together. I explored the annual energy saving impact of an occupancy-driven thermostat compare with a conventional thermostat. The simulation had been repeated in five U.S. cities (Fairbanks, New York City, San Francisco, Miami, and Phoenix) with distinctive climate zones

Conceptual Modeling of a Quantum Key Distribution Simulation Framework Using the Discrete Event System Specification

Quantum Key Distribution (QKD) is a revolutionary security technology that exploits the laws of quantum mechanics to achieve information-theoretical secure key exchange. QKD is suitable for use in applications that require high security such as those found in certain commercial, governmental, and military domains. As QKD is a new technology, there is a need to develop a robust quantum communication modeling and simulation framework to support the analysis of QKD systems. This dissertation presents conceptual modeling QKD system components using the Discrete Event System Specification (DEVS) formalism to assure the component models are provably composable and exhibit temporal behavior independent of the simulation environment. These attributes enable users to assemble and simulate any collection of compatible components to represent QKD system architectures. The developed models demonstrate closure under coupling and exhibit behavior suitable for the intended analytic purpose, thus improving the validity of the simulation. This research contributes to the validity of the QKD simulation, increasing developer and user confidence in the correctness of the models and providing a composable, canonical basis for performance analysis efforts. The research supports the efficient modeling, simulation, and analysis of QKD systems when evaluating existing systems or developing next generation QKD cryptographic systems

DEVS Framework for Modelling, Simulation, Analysis, and Design of Hybrid Systems

We make the case that Discrete Event System Specification (DEVS) is a universal formalism for discrete event dynamical systems (DEDS). DEVS offers an expressive framework for modelling, design, analysis and simulation of autonomous and hybrid systems. We review some known features of DEVS and its extensions. We then focus on the use of DEVS to formulate and synthesize supervisory level controllers. 1 Introduction Formal treatment of discrete event dynamical systems is receiving ever more attention[5]. Work on a mathematical foundation of discrete event dynamic modeling and simulation began in the 70s [13, 14, 16] when DEVS (discrete event system specification) was introduced as an abstract formalism for discrete event modeling. Because of its system theoretic basis, DEVS is a universal formalism for discrete event dynamical systems (DEDS). Indeed, DEVS is properly viewed a short-hand to specify systems whose input, state and output trajectories are piecewise constant[17]. The step-lik..