Modelling and Simulation for Aerial Refueling Automation Research for Manned and Unmanned Aircraft

LUBETA

Nicolas Fezans – DLR, Braunschweig – Inst. of Flight Systems with contributions from: T. Jann, T. Gerlach, D. Niedermeier, J. Hettwer, S. Lademann, J. Gotschlich, S. Schopferer, S. Lorenz, U. Durak, S. Geisbauer (DLR-AS)

DLRK 2016 (Deutscher Luft- und Raumfahrtkongress) Sept. 15th 2016 Braunschweig, Germany DLR.de • Chart 2 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Outline • Introduction on Air-to-Air Refueling

• Overview of on-going DLR research on air-to-air refueling automation

• Modeling activities: • Overview Hose-and-Drogue System • Aircraft (alone): • Future Military Transport Aircraft (FMTA) • Future Unmanned Aircraft (FUA) • Aerodynamic Interaction • Hose-and-Drogue Dynamics • Refueling System

• Simulation Infrastructure and Implementation • FMTA-FMTA including in the AVES Simulator • FMTA-FUA on the desktop

• Summary and Outlook DLR.de • Chart 3 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Air-to-Air Refueling – Overview

First air -to-air refueling above San Diego’s North Island on June, 27th 1923 (“Tangle -and-Grab” method)

RAF Museum (North of London)  DLR.de • Chart 4 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Air-to-Air Refueling – Overview Boom-and-receptacle

Probe-and-drogue (view from operator station)

Boom-Drogue Adapter (BDA) DLR.de • Chart 5 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Air-to-Air Refueling – Procedure • Various procedures standardized within the NATO  NATO Standard ATP-3.3.4.2 Air-to-Air Refueling (ATP56)

• Exact procedure expected to have no / very little influence on the performance evaluations made of the different automation strategies  only the so-called “RendezVous Alpha” is considered

• Flight point: FL200, VCAS = 260 kts

DLR.de • Chart 6 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

LUBETA: “Automation technologies for aerial refueling” DLR.de • Chart 7 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Overview Hose-and-Drogue System

• Tanker: always a “Future Military Transport Aircraft” (FMTA) as Tanker

• Receiver: either a second FMTA or a “Future Unmanned Aircraft” (FUA)

Cargo Hold Tank

Tank HDU Receiver Hose Hose Attachment Point Drogue Probe Tanker Drogue Attachment Point Probe Tip DLR.de • Chart 8 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016 Modeling – Aircraft – Future Military Transport Aircraft Extrapolation C-160-Data CFD-Computations Wind Tunnel Measurement

Real-time flight dynamical Analytical model of the FMTA Methods

Geometry Data Technical Specs.

Sidestick, Control Laws, Autopilot, System Simulation Multi-Body Actuator Models Landing Gear Huge increase of the number of implemented flight control functions ( all civil modes) DLR.de • Chart 9 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016 Modeling – Aircraft – Future Unmanned Aircraft

Kenngröße Daten Type Drohne Length 12.50 m Wingspan 20.12 m, sweep 17° Empty weight N/A Max Take Off Weight 5 220 kg Max Speed 740 km/h Cruise Speed N/A Basic Simulation Geometry Data Aerodynamic coefficients Service Ceiling 18 300 m Technical Specs. Propulsion Pratt & Whitney Canada PW545B- Adapted to FUA Thrust 17.7 bis 21.3 kN DLR.de • Chart 10 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Aerodynamic Interaction – Wind Field (1/3) • Box with finer mesh for conservation of the downstream flow characteristics • Refinements also for bow wave effect

FMTA ~ 2 x Semispan

4 x Fuselage length

Refined mesh • Spoiler efficiency (various deflections) ~ 2.3 x Semispan DLR.de • Chart 11 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Aerodynamic Interaction – Wind Field (2/3)

• Flow field directly extracted by the “end-users” from the volume solution • Different domains and solutions are being tested  goal: capture the important effects without having to carry extremely large tables

Preliminary rough-order of magnitude for the extracted data size Domain size: xb = -200 … 20, yb = 0 …80, zb = -40 … 40 around 2.36 Million points Resolution: 2 m in xb direction; 0,5 m in yb und zb direction (file size around 225 MB) DLR.de • Chart 12 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Aerodynamic Interaction – Wind Field (3/3)

• Significant upwash induced just behind the ramp (first part of the hose)

• Even if the refueling probe is quite long, a quite significant bow wave will affect the drogue (+ strong local gradient) slice at x = -30 m

slice at y = 0 m slice at x = -40 m DLR.de • Chart 13 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016 Modeling – Aero. Interaction – ∆ Forces and Moments

Aerodynamic Parameters (if parameterized)

Aerodynamic Actuators (e.g. control Model Valid only for surface deflections) Homogeneous Flow conditions (AMVHF) Propulsion (e.g. for (possibly with propeller slipstream effects) internal states) Forces & + Moments Inertial Motion

Aerodynamic + Model Extension for Inhomogeneous Flow conditions (AMEIF) Wind Field AMVHF / AMEIF Often called Wind Field (possibly with internal states) Splitter Aerodynamic Interaction Model Aerodynamic Model Valid also for (AIM) Inhomogeneous Flow conditions (AMVIF) (possibly with internal states, e.g. for delays and dynamics) DLR.de • Chart 14 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016 Modeling – Aero. Interaction – ∆ Forces and Moments

Aerodynamic Parameters (if parameterized)

Aerodynamic + Model Extension for Inhomogeneous Flow conditions (AMEIF) Example of aerodynamic interaction Wind Field AMVHF / AMEIF Wind Field (possibly with with a wake vortex using a “strip method” internal states) Splitter

Aerodynamic Model Valid also for Inhomogeneous Flow conditions (AMVIF) (possibly with internal states, e.g. for delays and dynamics) DLR.de • Chart 15 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016 Modeling – Hose-and-Drogue Dynamics (1/2)

• Models of the hose and drogue dynamic behavior

• Simple model Hose (massless straight bar)

Hose Drum Unit / Pod

Drogue (pont mass + aero properties)

• Multi-body model Hose (lumped masses + bars + aero) Hose Drum Unit / Pod

Drogue (Complex solid + aero properties)

DLR.de • Chart 16 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Hose-and-Drogue Dynamics (2/2) HDU

Hose Force & Moment Attachment Point Drogue Force & Moment Hose Drum Unit

Control TANKER Weight & Balance Hose HDU motion 3D Vis Aircraft motion Fuel Force & Drogue flow Moment motion 3D Vis Drogue Wind & Tank & Fuel Environment 3D Vis Management

Fuel flow Force & Drogue Moment motion Force & Moment Probe Force & Moment Weight &Balance Contact RECEIVER Aircraft motion Probe motion model

3D Vis DLR.de • Chart 17 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Modeling – Refueling System

AAR Panel phase 00

preset 88888 kg kg reset offload 88888 total offload 88888 kg

rcvr ff cmd 88 true 88 kg/s tank ff cmd 88 true 88 kg/s % tank level 000 stowed

lights contact rewind

fake trail full trail DLR.de • Chart 18 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Simulation Infrastructure: FMTA (T) – FMTA (R) (1/2)

• Simulation ported to the DLR AVES Simulator • A320 cockpit is used for the receiver • A320 displays are used as they are but with two specialized ECAM pages • Engine Monitoring (Upper-ECAM) • Flight Controls (Lower-ECAM) • Logic and protections (stall, overspeed, etc.) are adapted to the FMTA characteristics DLR.de • Chart 19 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Simulation Infrastructure: FMTA (T) – FMTA (R) (1/2)

• Simulation ported to the DLR AVES Simulator • A320 cockpit is used for the receiver • A320 displays are used as they are but with two specialized ECAM pages • Engine Monitoring (Upper-ECAM) • Flight Controls (Lower-ECAM) • Logic and protections (stall, overspeed, etc.) are adapted to the FMTA characteristics DLR.de • Chart 20 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Simulation Infrastructure: FMTA (T) – FMTA (R) (1/2)

• Simulation ported to the DLR AVES Simulator • A320 cockpit is used for the receiver • A320 displays are used as they are but with two specialized ECAM pages • Engine Monitoring (Upper-ECAM) • Flight Controls (Lower-ECAM) • Logic and protections (stall, overspeed, etc.) are adapted to the FMTA characteristics DLR.de • Chart 21 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Simulation Infrastructure: FMTA (T) – FMTA (R) (2/2)

Receiver Cockpit Virtual Tanker Cockpit 3D Environment Receiver (real Hardware) (Emulated with LabView) Tanker

Motion

Interface Interface Displays Instructor and Displays Computer Computer (PFD/ND/ECAM) Operator Station (PFD/ND/ECAM) (Receiver) (Tanker)

System System Simulation Simulink / Compiled Model Simulation Receiver Drogue/Hose Tanker Model + Model Aerodynamic Interaction Guidance & Control Logic, Guidance & Control Logic, Controllers Controllers State Machine, MCDU, State Machine, MCDU, Flight Management System Flight Management System Guidance, Navigation & Control Module (GNCM) Guidance, Navigation & Control Module (GNCM) DLR.de • Chart 22 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Simulation Infrastructure: FMTA (T) – FUA (R)

• Automated procedure in accordance to manual piloted procedure • A state machine calls specific controller modes for each phase of the refueling mission • Phases are defined by entry and exit conditions which ensure a stable flight condition or a fallback solution DLR.de • Chart 23 > Modelling and Simulation for AAR Automation Research > N. Fezans > DLRK 2016, Braunschweig, Germany > Sept. 15th 2016

Summary and Outlook • General overview of the modelling and simulation activities performed at DLR for hose-and-drogue AAR research

• First step and enabler for the AAR automation research being performed for manned and unmanned receiver aircraft.

• Probably the most comprehensive effort outside the US: • on the modelling and simulation of the air-to-air refueling maneuvers • and on the flight control assistance / automation technologies.

A lot more is coming within the next months and years

Thank you for your attention! Questions?