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Goals of today’s meeting

Goals of today’s meeting. Present and discuss research results and plans Discuss how to better work together Discuss results and ideas for education and outreach Discuss budget Prepare for CPS PI meeting (August 10-12, DC). Schedule. 9-9.45: Claire Tomlin , ActionWebs Overview

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Goals of today’s meeting

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  1. Goals of today’s meeting • Present and discuss research results and plans • Discuss how to better work together • Discuss results and ideas for education and outreach • Discuss budget • Prepare for CPS PI meeting (August 10-12, DC)

  2. Schedule 9-9.45: Claire Tomlin, ActionWebs Overview 10-10.45: Shankar Sastry, Closing the loop around sensor networks 11-11.45: HamsaBalakrishnan: CPS and Air Transportation 12-12.30: Lunch 12.30-1.15: Edward Lee: Hybrid and embedded systems 1.30-2.15: David Culler: CPS and buildings 2.30-2.50: Kristen Gates: CPS Education 3.00-4.20: Students and Postdocs(EleftheriosMatsikoudis, Wei Zhang, Anil Aswani) 4.20-5: Discussion and next steps

  3. Energy efficient air transportation systems • In 2007, domestic air traffic delays cost the US economy $41 billion • 24% of arrivals at least 15 min late (avg. delay: 46 min) • ~20% of total domestic flight time was delay • 1,565 flights delayed on the ground (not at gate) for over 3 hours

  4. Energy efficient, high productivity buildings • 40% total energy consumption, 72% electricity usage • Isolated subsystems, not much modeling • Better operations needed

  5. ActionWebs Observe and infer with a viewpoint to planning and modifying action: • Dealing with uncertainty • Tasking sensors • Programming the ensemble • Multiple objectives • Embedding humans

  6. Research projects • Optimization of Traffic Flow in the National Airspace System (Wei Zhang, MaryamKamgarpour) • System Identification combining physics-based models and data (Anil Aswani, Jeremy Gillula) • Localization in buildings (Michael Vitus, Wei Zhang) • Game-theoretic routing of GPS-Assisted Vehicles for Energy Efficiency (Anil Aswani) • Estimation and control of discrete time stochastic hybrid systems (Jerry Ding, Alessandro Abate) • Designing automation that works well with humans (Haomiao Huang)

  7. Goals of today’s meeting • Present and discuss research results and plans • Discuss how to better work together • ActionWebs Seminar: Tuesdays 4-5pm? • Discuss results and ideas for education and outreach • CPS Education Workshop (August 12, DC) http://cyberphysicalsystems.org/cpsew • Intro textbook for undergrad class http://LeeSeshia.org • Robotics, undergrads, and high school students • Discuss budget • Prepare for CPS PI meeting (August 10-12, DC)

  8. Environmental impacts of air transportation • Aviation is responsible for 3% of total global carbon emissions • Aircraft contribute about 12% of CO2 emissions from the transportation sector • According to the European Union, international aviation is one the largest growing contributors to CO2 emissions, having increased 87% between 1990 and 2004 • The aviation sector was responsible for 187.5 million metric tons of CO2 emissions in the US in 2007 (about 3% of total emissions) [Balakrishnan] [Commission of the European Communities, 2006; EPA 2007]

  9. Surface emissions from taxiing aircraft • In 2007, aircraft in the US spent over 63 million minutes taxiing in to their gates, and over 150 million minutes taxiing out to their runways • An estimated 6 million tons of CO2, 45,000 tons of CO, 8,000 tons of NOx and 4,000 tons of hydrocarbons are emitted annually by aircraft taxiing out for departure • These flights burn fuel and contribute to emissions at low altitudes, and adversely impact local air quality • Taxi-out emissions correspond to about 5% of the fuel burn and emissions from aircraft operations • How do we optimize surface traffic movement to reduce aircraft emissions from taxi processes? [FAA ASPM database; Balakrishnan et al. 2008]

  10. Aircraft taxi trajectories from surface surveillance data

  11. Effect of stopping and starting while taxiing • Potential fuel burn impact from stopping on the surface No significant impact

  12. Estimate impact of different taxi profiles • ICAO emissions databank assumes that aircraft taxi at a constant throttle setting of 7% • Using CFDR data (from Swiss Air) corresponding to taxi profiles of various aircraft, we • Developed a regression model for fuel burn, that considers the baseline fuel burn and the impact of stop-start events • Stop-start impact: Estimate of the form “The extra fuel burn from a start-stop event is equivalent to x additional minutes of taxi time” • Developed a (linear) regression model between fuel burn and throttle settings • Conducted above analysis for 9 aircraft types Fuel burn = Baseline fuel burn rate*(taxi time) + (Stop-start impact)*(# of stop-start events)

  13. Minimizing fuel burn impacts of aircraft trajectories Surface surveillance Surface surveillance Flight data recorder Flight data recorder (archival data) Identification of hybrid system model of taxi trajectory Identification of fuel burn model Multi-objective control of taxi trajectories (real-time data)

  14. Analyzing Benefits of Continuous Descent Approach (CDA) Objective: Study fuel benefits of implementing CDA in the current airspace structure Analysis Approach Take current aircraft arrival trajectories Move the constant altitude (Level) section to a high altitude [Kamgarpour]

  15. Results on Airport Savings Scope of the Study 5 days of data for ATL, SFO, LAX airports 4 days of data for DFW, 1 day of data for JFK

  16. Energy efficient Buildings [Culler]

  17. MCM2 ~42 circuits each LP2D 225 LP2C 225 HP7A 400 LP2B 225 HP7A 400 LP2D 225 LP2C 225 HP6A 100 LP2B 225 LP2J 225 HP6A 100 LP2I 225 LP2H 225 LP2G 225 LP2E 225 LP2F 225 LP2K 225 LP2C 225 HP5A 400 LP5B 225 LP2J 225 HP5A 400 LP2I 225 LP2H 225 LP2G 225 LP2E 225 LP2F 225 LP2D 225 LP2C 225 LP2K 225 HP4A 400 LP4B 225 LP2J 225 HP4A 400 LP2I 225 LP2H 225 LP2G 225 LP2E 225 LP2F 225 LP2D 225 2500 A 120/208 3 phase LP2C 225 1200 A 277/480 3 phase HP3A 400 LP3B 225 HP3A 400 LP2E 225 LP2D 225 LP2G 225 LP2C 225 LP2F 225 LP2A 800 LP2B 225 HP2A 600 LP1A 400 LP1B 400 HP1A 400 HP1A 400 MCM1 2x Chiller 2x Substation 12 KV dist. Structural: Soda Electrical Lighting Pumps Fans Machine rooms Classrooms Offices

  18. Testbeds • Future air transportation systems testbed • Connections with NASA Ames (SDO, separation assurance), NASA Langley (safety) • Simulators (FACET, ACES), actual flight data (CFDR) • Mobile sensor net testbed • Buildings • Berkeley campus: Soda, Cory, Sutardja Dai, California Halls • LBL (DOE2)

  19. Education and Outreach • Cyber-physical systems science (CPSS) • Curriculum development at Berkeley/MIT • Outreach • Robotics at the RFS • Curriculum development at SJSU • SUPERB-CSS • Research Experience for Teachers (RET) [Gates]

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