4. Comprehensive Technical Objectives: Shock Dominated Flows Define existing canonical expts to validate simulations Define and execute new canonical expts to validate simulations and physics models. Innovative BCs. Temporal tailoring of flow for design. Maintain living canon of expts. with well defined validation and performance metrics for simulations Thrust Area Near Term (2010) Mid Term (2020) Far Term (2030) Canonical Configurations - Blunt Body - Sharp Double Cone - Base Flows - Generic Scramjet FP - SBLI in channel - Hypersonic Piston Implement grid adaptation until user-specified convergence is achieved - Blunt Body: couple radiation effects, auto grid adaptation - Sharp Double Cone : coupled ablation - Base Flows: Coupled ablation, LES/DES methods - Blunt Body: couple transition estimation, multi-domain capability in Knudsen number - Sharp Double Cone : include transition estimation - Base Flows: Extend to transition estimation, radiation effects and multi-domain in Knudsen number Interactions - Flexible Ballute - Flat Plate - Fin - Bodies in Rel. Motion - Jet into Cross Flow - Flexible Ballute: User specified grid adaptation - Flat Plate - increased physical fidelity in all areas - Bodies in Rel. Motion: include equil. gas thermophysics - Flexible Ballute: coupled radiation, subscale models, generalized Kn range - Flat Plate - multi-domain Kn range - Bodies in Rel. Motion: noneq. gas thermophysics, unsteady sim., auto grid adapt - Flexible Ballute: fully coupled gas and mat'l physical response , auto grid adaptation - Flat Plate - fully resolved in gas physics, auto grid adaptation - Bodies in Rel. Motion: noneq. gas physics, subscale turb models, auto grid adapt Surface Effects - Microramps, Bleed, - Porous Wall, etc. Equil gas sim. for steady solutions Noneq. gas in unsteady soln w. user specified grid adapt Fully resolved turbulent scales Plasma Flow Noneq. gas sim with user specified grid adapt Incl unsteady solutions and auto grid adapt Incl Coupled radiation and fully resolved turb scales for generalized physical domain

5. Comprehensive Technical Objectives: Shock Dominated Flows Physics Complexity 1 - Perfect Gas 2 - Equilibrium Gas 3 - Thermochemical Nonequilibrium and/or Ionization 4 - Coupled Ablation 5 - Coupled Radiation 6 - Coupled Aero-Thermo-Elastic Material Response Knudsen Number Range 1 - Applicable in single domain, possible extensions using slip boundary conditions 2 - Multi-domain applicability enabled in single problem across manually specified interface 3 - Generalized equation set or automated, adaptive application of appropriate equation sets. Turbulence models 1 - Reynolds Averaged Navier Stokes (RANS) 2 - Unsteady RANS (URANS) 3 - Subscale models: (DES), and (LES) 4 - Coupled stability equations to predict transition 5 - Fully-resolved scales: (DNS) Adaptive simulation, automated uncertainties - (ASAU) 0 - Some automated adaptation 1 - Grid adaptation (enrichment, coarsening, alignment) proceeds automatically until user specified grid convergence error is attained. 2 - Grid adaptation proceeds automatically and uncertainties derived from physical model parameters are published. Thrust Area Near Term Mid Term Far Term Canonical Configurations Blunt Body ( 4 1 1 0 ) Sharp Double Cone ( 3 1 1 0 ) Base Flows ( 3 1 1 0 ) Generic Scramjet FP ( 3 1 1 0 ) SBLI in channel ( 3 1 1 0 ) Hypersonic Piston ( 3 1 1 0 ) ( 4 1 1 1 ) ( 3 1 1 1 ) ( 3 1 1 1 ) ( 3 2 1 1 ) ( 3 2 1 0 ) ( 3 2 1 0 ) ( 5 1 1 2 ) ( 4 1 1 1 ) ( 4 3 2 1 ) ( 3’ 2 1 1 ) ( 5 4 3 2 ) ( 4 4 1 2 ) ( 5 4 3 2 ) ( 3 3 1 2 ) ( 3 3 1 2 ) ( 3’ 2 1 2 ) Interactions Flexible Ballute ( 3 1 1 0 ) Flat Plate - Fin ( 2 2 1 0 ) Bodies in Rel. Motion ( 1 1 1 0 ) Jet into cross flow ( 3 1 1 0 ) ( 3 1 1 1 ) ( 3 3 1 1 ) ( 2 1 1 1 ) ( 3 1 3 1 ) ( 5 3 3 1 ) ( 3 3 2 1 ) ( 3 2 1 2 ) ( 3 1 3 1 ) ( 6 5 3 2 ) ( 3 5 3 2 ) ( 3 3 1 2 ) ( 3 5 3 2 ) Surface Effects Microramps, Bleed, Porous Wall, etc. ( 1 1 1 0 ) ( 2 1 1 1 ) ( 3 2 1 2 ) ( 3 5 1 2 ) Plasma Flow ( 3 1 1 0 ) ( 3 1 1 1 ) ( 3 2 1 2 ) ( 5 5 3 2 ) Define existing canonical expts to validate simulations Define and execute new canonical expts to validate simulations and physics models. Innovative BCs. Temporal tailoring of flow for design. Maintain living canon of expts. with well defined validation and performance metrics for simulations

7. Comprehensive Technical Objectives: Supersonic Combustion Thrust Area Near Term (2010) Mid Term (2020) Far Term (2030) Physical and Chemical Process Characterization Simultaneous - CARS/Rayleigh measurements (T,V species) Non-equilibrium plasmas (ignition and flame holding) Fuel characterization via surrogates On-board flight-capable diagnostics General thermodynamic, kinetic, & transport characterization of fuels. Coupled Subsonic/supersonic flame-holding control. Well characterized combustor environments for all relevant scales. Characterization of anisotropic turbulence mechanisms. Characterization of coupled mixing/heat release effects. Modeling and Simulation Tools Variable turbulent Pr, Sc models. EASM RANS turbulence models. Hybrid RANS-LES Novel algorithms & grid gen. Component (fuel injector) LES Combustor LES LES with enhanced reduced models. Multiphase combustion simulations Quantified uncertainties Time-dependent mode transition prediction Full flow path LES Component-level DNS Scaling “Laws” Database development for “1X” class components. Database development for “10X” class propulsion systems. Quantified uncertainties for “1X” class database. Development of multi-parameter scaling tools. Accurate extrapolation of ground-to-flight data (“100X”) Advanced Experimental Techniques Development of high resolution LITA in cold-flow environments Unification of experimentation, M&S, and diagnostics. Multiplexed tunable diode absorption spectroscopy (TDLAS) TDLAS tomography for combustion efficiency assessment in realistic environments. In-situ mass flow measurements. 2-D and 3-D multi-parameter measurements (PLIF, Raman) for P, T, Velocity. In-situ time-resolved multi-parameter measurements (combustion efficiency, skin friction, heat transfer, thrust) Active Control Thermal control via regenerative cycle. Exploration of optimal control approaches (AI vs. model-based) Combustion control via regulated fueling. Identification of instrumentation needs for control strategies. Optimized aero/propulsion system performance via fault tolerant control algorithms. Propulsion Airframe Integration Establishment of operability margins for inlet-combustor interactions. Application of external burning. Implement alternatives to control surfaces (i.e. MHD) Validated design tools and databases for efficient aero/propulsion integration.