The Icing Encounter Flight Simulator is one part of the Smart Icing System project at the University of Illinois at Urbana-Champaign. The goal of the Smart Icing System project is to develop technology necessary to improve the safety of aircraft flying in icing conditions. The icing simulator is used as a platform to integrate different components of the Smart Icing System and to test the effectiveness of the components. To create an Icing Encounter Flight Simulator, functionality and Smart Icing System components were added to the FlightGear flight simulator, an open source flight simulator available on the internet. A reconfigurable aircraft model, an autopilot, and an icing model were some of the functionality added to FlightGear. Smart Icing System components integrated into the simulator include the neural-network-based icing characterization, envelope protection system, ice protection system, and an Ice Management System enhanced glass cockpit. To ensure a real-time simulation, computationally extensive processes have been distributed over several computers linked together by a local network. A tailplane stall scenario and a roll upset scenario have been designed to demonstrate the effectiveness of the Smart Icing System components on a nonlinear aerodynamics model of a DHC-6 Twin Otter aircraft in clean and iced conditions.

The Icing Encounter Flight Simulator is one part of the Smart Icing Systems project at the University of Illinois at Urbana-Champaign. From the Smart Icing Systems project, an ice management system was designed that would sense and characterize ice, notify the pilot, and if necessary take measures to ensure the safety of the aircraft. The icing simulator was used as a platform to integrate and test different components of the Smart Icing System. To create an Icing Encounter Flight Simulator, functionality and Smart Icing System components were added to the FlightGear flight simulator. Functionality added to FlightGear include a reconfigurable aircraft model and an icing model, and Smart Icing System components added include an envelope protection system and a glass cockpit enhanced with ice management system features. To ensure a real-time simulation, computationally intensive processes were distributed over several desktop computers linked together through a local network. In order to demonstrate the effectiveness of the Smart Icing System components, two fictional but historically motivated icing scenarios were developed and tested with a simulated DeHavilland DHC-6 Twin Otter, specifically, a tailplane stall event during a steep descent and a roll upset event during an emergency approach. Introduction A S part of the Smart Icing Systems (SIS) project [1,2] at the University of Illinois at Urbana-Champaign, the Icing Encounter Flight Simulator (IEFS) [3][4][5] integrates various SIS components in a simulated aircraft icing environment. The SIS project was started to investigate measures that would help keep the aircraft safe during an icing encounter. To do this an ice management system (IMS) was devised that would sense and characterize the presence of ice, notify the pilot, and ensure the safety of the aircraft. To test and demonstrate the IMS, the IEFS was designed to integrate the different aspects of the SIS project such as the flight dynamics model, autopilot [6], aircraft icing model [7,8], icing characterization routine [9], envelope protection system (EPS) [10], and human factors [11].Instead of creating a new flight simulator for this project, it was decided to adapt an existing simulator. The simulator chosen was the FlightGear flight simulator (FGFS) x for its open source and modular code. Added to FlightGear were a reconfigurable aircraft model, autopilot, and an icing model. Other aspects of the SIS such as the ice weather model, EPS, ice protection system (IPS), neural-networkbased icing characterization, and the IMS-enhanced glass cockpit were integrated into the IEFS. Several components of the IEFS became too computationally intensive to run on a single desktop PC, and so to ensure real-time simulations, the IEFS was divided into different modules to be run over a local area network. The resulting distributed simulator contains six modules: flight dynamics model (FlightGear with the autopilot and icing model), SIS support code (ice weather model, EPS, and IPS), neural-network-based icing charac...

Natural aggregation processes such as the familiar flocking of birds have been accurately modeled using a simple, decentralized controller. Variations on this "boid" controller typically involve three or more control laws, each with an associated control gain and sensor range. In this paper, the boid controller is fitted with an additional rule designed to produce aerodynamically-efficient formations, such as those exploited by migratory birds and hypothetical unmanned aerial vehicles. A simple genetic algorithm is then used to optimize the control parameters for minimum power consumption in a flock of simulated birds. This report focuses on the development and utility of the flocking simulator as a fitness function for the GA. Preliminary results indicate that average power consumption can be significantly reduced with the modified, optimized boid controller.

As part of the Smart Icing System (SIS) project at the University of Illinois at Urbana-Champaign, the Icing Encounter Flight Simulator (IEFS) integrates various SIS components in a simulated aircraft icing environment. The IEFS combines a customized version of FlightGear, an open-source flight simulator, with a suite of SIS support software using multiple desktop PCs connected through a local area network. The resulting simulation integrates most SIS concepts for testing and demonstration purposes. To this end, two fictional but historically-motivated icing scenarios are used to illustrate the various SIS interventions capable of preventing icing events. Specifically, a tailplane stall event during a steep descent and a roll upset event during an emergency approach are considered. During each scenario, multiple SIS intervention points are examined.