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Near-Space Station-Keeping Performance of a Large Notional Airship Dave Schmidt Professor Emeritus Dept. Mechanical Near-Space Station-Keeping Performance of a Large Notional Airship Dave Schmidt Professor Emeritus Dept. Mechanical & Aerospace Engineering University of Colorado at Colorado Springs dschmidt@uccs. edu 719 262 -3580 www. uccs. edu/~sansrl as presented at the SAE ACGSC Williamsburg, VA October 12, 2006 Partially Sponsored by the Army Space & Missile Defense Battle Lab

Outline of the Presentation Near Space What is “Near Space”? Why Are We Interested Outline of the Presentation Near Space What is “Near Space”? Why Are We Interested in It? Is it Feasible? - Key Problem - Long-Duration Station Keeping Wind Environment Aerodynamics - Drag Guidance & Control in Turbulence Solar - Powered Propulsion Station - Keeping Power Analysis Summary & Conclusions

Typical “Mission” Communication Or Observation Example Space. Based Solution to Wide-Area Surveillance What if Typical “Mission” Communication Or Observation Example Space. Based Solution to Wide-Area Surveillance What if We Could Place a Sensor at a Lower Altitude and Keep It There?

Persistent Surveillance Key Persistent (24/7) Communication and/or Surveillance Platform Persistent Surveillance Key Persistent (24/7) Communication and/or Surveillance Platform

Desirable Near-Space Platform Characteristics • Persistent 24/7, multi-month, all-weather capability • You can bring Desirable Near-Space Platform Characteristics • Persistent 24/7, multi-month, all-weather capability • You can bring it down and fix it… • Low-cost platform, rapid reconstitution of capabilities • Improved performance of most space sensors • “Local” control • …. . • This is the Promise of Near Space

Where Is Near-Space? 37, 160 km MEO Space GEO 21, 000 km LEO 100 Where Is Near-Space? 37, 160 km MEO Space GEO 21, 000 km LEO 100 – 1000 km Air Near-Space 100 km (327, 000 ft) 20 km (60, 000 ft) 20 km Surface SATCOM GPS Iridium

US Near-Space Efforts (Selected) NASA USAF (98, 863 feet – World Record) Helios NM US Near-Space Efforts (Selected) NASA USAF (98, 863 feet – World Record) Helios NM State Univ Advanced Aerobody Payload: 220 - 500 lbs Altitude: 50 -98 K feet Duration: > 1 week AFRL Payload: <1000 lbs Altitude: 60 – 100 K feet Duration: 3 months Army/MDA High Altitude Airship Payload: 4 K – 12 K lbs Altitude: 65 K to 85 K Duration: 1 month (near-term) 3 - 5 yrs (objective) Free Balloons >2, 500 flights since 1951 Payload: up to 7000 lbs Altitude: Up to 140, 000 feet “Ascender” Maneuvering Vehicle Payload: 100 -1000 lbs Altitude: 80 – 120 k feet Duration: 4 -10 days UCCS Weather Research Payload: 6 lbs Altitude: 100 K feet

International Efforts to Develop Near-Space Platforms United States Canada United Kingdom Germany Israel South International Efforts to Develop Near-Space Platforms United States Canada United Kingdom Germany Israel South Korea Japan Malaysia

Outline of the Presentation Near Space What is “Near Space”? Why Are We Interested Outline of the Presentation Near Space What is “Near Space”? Why Are We Interested in It? Is it Feasible? Key Problem - Long-Duration Station Keeping Select a Typical Vehicle for Analysis Model Wind Environment Model the Aerodynamics Model Solar - Powered Propulsion Perform Station - Keeping Power Analysis Assess Feasibility - Identify Possibilities Summary & Conclusions

Key Issue - Station Keeping Objective: Remain on Station in Presence of Winds Issue: Key Issue - Station Keeping Objective: Remain on Station in Presence of Winds Issue: On-Board Power Available vs Power Required Requires Assessments of

Notional Airship Investigated Vehicle Characteristics: Volume = 6. 1 x 106 ft 3 Length Notional Airship Investigated Vehicle Characteristics: Volume = 6. 1 x 106 ft 3 Length = 450 ft Width = 100 ft WOEW = 30, 000 lbs Solar-electric powered Electric motors/propellers Payload Power = 3 k. W Performance Req’m’ts: Operating Altitude - 65, 000 ft Endurance ~ 1 Year Maintain Position in Winds

Wind Analysis White Sands (EPZ) and Akron (PIT) (32. 5 deg North, 106. 5 Wind Analysis White Sands (EPZ) and Akron (PIT) (32. 5 deg North, 106. 5 West), (41 deg North, 81. 5 deg West)

Statistical Wind Modeling STATISTICS: Possible “Sweet Spots” Year 2004 Wind Variation: White Sands (EPZ) Statistical Wind Modeling STATISTICS: Possible “Sweet Spots” Year 2004 Wind Variation: White Sands (EPZ) and Akron (PIT)

Monthly vs Annual Wind Statistics Annual Stats (2004) Monthly Stats (2004) White Sands (July) Monthly vs Annual Wind Statistics Annual Stats (2004) Monthly Stats (2004) White Sands (July) Akron Speed (kts) White Sands Akron Speed (kts) 50 15. 7 kts 13. 4 kts 50 27. 4 kts 34. 4 kts 95 31. 4 kts 35 kts 95 35. 5 kts 68. 5 kts 99 38. 6 kts 47. 5 kts 99 38. 4 kts 85. 6 kts P Winds (Dec) Key Points: Monthly Variations Can Be Significant, and Probability distribution is key, not just means

Altitude, K ft Dryden Turbulence Model • Frequency Spectra RMS Turbulence Intensity, fps Altitude, K ft Dryden Turbulence Model • Frequency Spectra RMS Turbulence Intensity, fps

Aerodynamic Drag Estimation Drag Power Required • UCCS Low-Speed Tunnel • Lift-Drag Force Balance Aerodynamic Drag Estimation Drag Power Required • UCCS Low-Speed Tunnel • Lift-Drag Force Balance • Body geometry L/D = 3. 9 • Re. L = 1. 3 x 105 (Low) • Turbulence Grid Needed • Mmax = 0. 045 (50 fps, 30 kts) Airship Model in Tunnel Test Section Drag = (1/2 V 2) CDAref CD - Empirically & Experimentally Determined

Airship Dynamics Modeling Non-dimensional Aero Coefficients and Mass Properties From Nagabhushan & Tan (1995) Airship Dynamics Modeling Non-dimensional Aero Coefficients and Mass Properties From Nagabhushan & Tan (1995) Mass Properties Scaled Apparent Masses Scaled Static Stability Restored Roll DOF Ignored Sluggish, Heavily Damped Response

Station Keeping In Turbulence Steady Wind, VWind Plus u and v Gusts u g Station Keeping In Turbulence Steady Wind, VWind Plus u and v Gusts u g vg Objective: Drive Position Error To Zero In Presence Of Wind Gusts X Desired Position (Looking From Above) Y Error X Error Y Motion Decomposition: Vehicle Relative to Steady Air Mass Relative to Inertial Gust Superimposed on Steady Air Mass

Guidance & Control Architecture GPS Based Wind Gusts (turbulence) Controls. Inertial Thrust & Position Guidance & Control Architecture GPS Based Wind Gusts (turbulence) Controls. Inertial Thrust & Position Velocity Fin Defl. Desired Position - Guidance Algorithm - Attitude Controller Vehicle Dynamics Kinematics Control laws synthesized via classical loop shaping Allows for assessment of maneuver-power required

Closed-Loop Time Responses Position Error X, ft Time Responses Position Error Y, ft Heading Closed-Loop Time Responses Position Error X, ft Time Responses Position Error Y, ft Heading deg Surge velocity u, fps Lateral velocity v, fps Yaw rate r, deg/sec Thrust t, lbs Rudder defl. r, deg Time, sec

Stochastic Control-Power Assessment Linear Closed-Loop Dynamic System (BW) + Turbulence Model Lyapunov Equation Response Stochastic Control-Power Assessment Linear Closed-Loop Dynamic System (BW) + Turbulence Model Lyapunov Equation Response Covariance Matrix Y

Maneuver-Thrust Required Severe Turbulence Increased Control Bandwidth Note: To Keep rms Position Error < Maneuver-Thrust Required Severe Turbulence Increased Control Bandwidth Note: To Keep rms Position Error < 1000 ft Requires 20 lbs Thrust rms Increasing Total rms Station Keeping Thrust Required ~6%

Pulling it All Together # Wind Statistics and Probability Distributions # Aerodynamic Drag Models Pulling it All Together # Wind Statistics and Probability Distributions # Aerodynamic Drag Models # Maneuver Power Required Solar Geometric Effects Vehicle geometry - large airship Geo latitude Diurnal and seasonal effects Energy-Subsystem Efficiencies Power Available Versus Power Required

Average Solar Insolation Available Purple = Akron (k. W) Blue = White Sands (k. Average Solar Insolation Available Purple = Akron (k. W) Blue = White Sands (k. W) Includes Effects of Day Length Sun Angles

Diurnal & Vehicle Geometry Effects 1. 0 N-S 0. 8 Fraction 0. 6 Of Diurnal & Vehicle Geometry Effects 1. 0 N-S 0. 8 Fraction 0. 6 Of Useful Area 0. 4 E-W 0. 41 Ave NS 0. 32 Ave EW 0. 2 0 0 10 Hour of Day 20

Airship Power System Schematic Solar Incident Energy Payload Auxiliary Systems Solar Cells Energy Storage Airship Power System Schematic Solar Incident Energy Payload Auxiliary Systems Solar Cells Energy Storage Power Mgmt. Options: Instant Usage - - Store Then Use Motors Propellers = Energy Conversion

Power Required vs Available (Mean (P=0. 5) by Month Excess Ave. Power in Feb. Power Required vs Available (Mean (P=0. 5) by Month Excess Ave. Power in Feb. Ave. Power Deficit

Power Required vs. Power Available Monte Carlo Simulations Variation from random velocity 600 Battery Power Required vs. Power Available Monte Carlo Simulations Variation from random velocity 600 Battery Power, k. W*hrs battery type: all to battery Cd: 0. 12 capacity: 600 k. Wh month: Feb motor efficiency: 80% solar cell efficiency: 6% battery efficiency: 60% 500 400 Ave. Excess Power >0 300 200 100 0 0 no power available 1 2 3 days Time, days 4 5 6

Summary of Key Results • Near-Space Offers Promise In Communication and Surveillance Missions - Summary of Key Results • Near-Space Offers Promise In Communication and Surveillance Missions - Cost-Effectiveness, Reliability, Flexibility, Persistence • Key Feasibility Issues Include Power Limitations and Wind Vulnerability This Airship Predicted to Have Insufficient Average Power at Akron in December. Average Excess Power Available - Necessary, But Not Sufficient Condition to Assure Viability – More Detailed Analysis Required. Also, Probable Insufficient Power at Akron in Other Months, Due to “Gambler’s Ruin” Phenomenon. Large Seasonal Variation in Winds - Wind Statistics & Distribution Power Required vs. Power Available - Out of Phase Power Balance Very Sensitive to Wind Speed (~V 3), Drag Coefficient, and Power-system Efficiencies (linear multiplicative dependence)

Conclusions Based on Results This Vehicle is Very Power Limited The Vehicle Could Not Conclusions Based on Results This Vehicle is Very Power Limited The Vehicle Could Not Remain Aloft for a Year in Winds Like Akron’s Slight Change in Power-system Efficiencies - Large Change in Results -- Payoff from Additional Technological Advancements In Particular, Novel Long-Term Power Storage Technology Would Have High Payoff Other Vehicle Configurations Need Similar Assessment, To Determine Sensitivity of Results to Vehicle Configuration

Back Up Slides Back Up Slides

Potential Fields of View At Sub-Orbital Altitudes 80, 000 feet 60, 000 feet 700 Potential Fields of View At Sub-Orbital Altitudes 80, 000 feet 60, 000 feet 700 Miles 600 Miles

Near Space Potentially Offers An Alternative Cost-effective, persistent wide area surveillance, communications, etc. This Near Space Potentially Offers An Alternative Cost-effective, persistent wide area surveillance, communications, etc. This is Why There is Interest

Rudder Control-Power Required Increased Control Bandwidth Note: To Keep rms Position Error < 1000 Rudder Control-Power Required Increased Control Bandwidth Note: To Keep rms Position Error < 1000 ft Requires 9 deg Rudder rms