NASA Tech Integration Georgia Tech Grand Challenge

Sample Presentation Title

Advisor: Dr. MavrisResearch Engineer: Dr. Pfaender

Project Manager: Matt Schmit Chief Engineer: Erik Viken2014 NASA Tech IntegrationGrand Challenge

23rd Annual External Advisory Board Review April, 2014 Atlanta, GA

Thank Sponsors Thank you to NASA and Mr. Robert A. Pearce for the opportunity to work on this projectSpecial thanks to:Advisors: Dr. Mavris and Dr. PfaenderPhD Students: Muhammed Hassan, and Matt LeVine

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Team OrganizationCase StudyProject OverviewModel Plan and RequirementsCase StudyModel Plan and RequirementsProject OverviewTeam OrganizationAgenda3Team OrganizationProject OverviewDescribe project objectivesProvide motivation for our workDiscuss findings from background researchMethodology of our ProcessDescribe goals of our toolOutline the process and assumptions of toolCase StudyDemonstration of toolConcluding RemarksSummarize work and resultsDiscuss future plans

Conclusions and Future WorkConclusions and Future Work

Team OrganizationProf. Dimitri MavrisFaculty AdvisorASDL

Mohammed HassanTechnical Advisor

Matthew LeVineTechnical Advisor

Matthew SchmitProject Manager

Erik Viken Chief Engineer

Charlotte Gill

Aubrey ClausseStephen Kim

Dr. Jens Holger PfaenderResearch Engineer

4Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam Organization

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Modeling Environment?Project Objectives5Develop an interface capable of quantifying NAS wide impact on CO2 emissions of:New technologiesNextGen operational techniquesLow-carbon propulsion & biofuelsProvide tool for evaluating most effective way to invest in the strategic thrusts Allow for real-time evaluation:Fuel BurnCO2 emissionsCapturing functional dependence between the dynamics of change and environmental impact:Given a set of changes, what will be the net impact?Given a specific environmental goal, how can I alter the dynamics to meet that goal?

Dynamics of ChangeSystem Level Environmental Impact1212MotivationMatt SchmitProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

Climate ChangeAnthropogenic greenhouse gases (GHG) are believed to be a major contributorWhy focus on CO2?Radiative forcingDirect correlation between temperature CO2 concentration

6Major GHG Include:

N2OCH4CO2Matt SchmitIncreasing heat trapping ability per moleculeIncreasing radiative forcing of GHG

[1]

[2]

Credit: IPCC [12]MotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

Radiative forcing, or climate forcing, is defined as the difference between the sunlight absorbed by Earth and the energy radiated back into spaceTypically quantified at the tropopause in units of watts per square meter of the Earths surface6

Global Carbon Cycle7Matt SchmitCarbon Cycle represents the fluctuation of Earths Carbon between sources and sinksMajor Carbon Sinks:Oceans Plant photosynthesisEarths crust Atmosphere Fossil fuel reservesMajor Carbon Emission Sources:Fossil fuelsNet land use changePlant respirationIPCC estimates that the amount of CO2 in the atmosphere is increasing by 14.8 billion tons a yearWithout fossil fuel emissions, CO2 concentration would decrease by 14.01 billion tons a year

MotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

Credit: IPCC [12]To achieve a balanced Carbon Cycle, fossil fuel emissions must be reduced by 51%

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CO2 Emissions in Aviation8Matt Schmit

[5]Recession

[4]No action takenNumber of Operations Steadily IncreasingRecessionMotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

[4]CO2 Emissions in Aviation9Matt SchmitThrust 3: Low Carbon Propulsion & BiofuelsThrust 2: NextGen / Efficient Flight Path ManagementThrust 1: Ultra-Efficient Aircraft Technologies

Which thrusts should be invested in order to achieve the desired reduction in CO2 emissions?MotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

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Thrust 1: Efficient Aircraft Technologies10Matt SchmitAchieve reduction in CO2 emissions by improving fuel efficiency of aircraftTechnologies will be pursued as long as they present an economic advantageWhat is the expected improvement?What is the reference point?When will the technology/aircraft be ready for entry into service?What is the scope of the application?Evolution of fleet must account for: aircraft retirements, replacements, and fleet growthRetired vehicles are replaced with newer ones (replacement vehicles)In addition, new vehicles are added to satisfy operational growth (according to forecast)Future fleet will be dominated by new-generation technology vehicles incorporating technologies from: CLEEN, ERA, and N+3

Airbus A320

Airbus A320Neo15% Improvement in Fuel EfficiencyExpected Starting 2016Seating capacity: 150 189 Range: up to 3,300 nmi

Baseline FleetFuture Fleet

RetiredVehiclesReplacementVehicles

Fleet Growth

MotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

Change word cominated10

Thrust 1: Efficient Aircraft Technologies11Matt SchmitFAA CLEEN (Continuous Lower Energy, Emissions, and Noise) Program (N+1 Vehicle)By 2015, Technology Readiness Level of 4 6 Adaptive Trailing EdgeCeramic Matrix Composite NozzleERA (Environmentally Responsible Aviation) Project (N+2 Vehicle)By 2020, Technology Readiness Level of 4 6 AFC Vertical TailFlow Control Concepts for Drag ReductionNASA (N+3 Concepts)By 2035, Technology Readiness Level of 4 6 Advanced vehicle conceptsHybrid electric distributed propulsionMotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

[16]Hybrid Wing-Body Advanced Concept

[17]Hybrid Electric Distribution Propulsion

[15]AFC Vertical Tail

[13]Adaptive Trailing Edge

[14]Ceramic Matrix Composite Nozzles

Drag Reduction via Laminar Flow

Time frame: http://www.aeronautics.nasa.gov/pdf/era_preproposal_n2_adv_vechicle2010.pdfNASA ERA technologies: http://www.aeronautics.nasa.gov/iasp/era/index.htmDrag reduction picture: https://www.aiaa.org/uploadedFiles/About-AIAA/Press-Room/Key_Speeches-Reports-and-Presentations/2012/Collier-NASA-AVC-AIAA-GEPC2-2.pdf11

These technologies allow for improved operational capabilities, but do not impact the fuel burn efficiency of aircraft.Flight management shift to smarter, satellite-based, digital technologies and new proceduresImprove throughput and airport capacity while maintaining safetyThrust 2: FAA NextGen Operations12Matt SchmitReduction in CO2 Emissions

Fuel Savings

[7]

[8]

[9]Data Communication (Data Comm)Digital data exchange between air traffic control and pilotsReduce Flight Time / Delays

Improved Operational Capabilities

[10]MotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam OrganizationAutomatic Dependent Surveillance-Broadcast (ADS-B) In/OutMore precise tracking leads to more direct routesNotable NextGen ProgramsImproved Operational CapabilitiesOptimized Profile Descent (OPD)Required Navigation Performance (RNP)

NextGen is the FAAs initiative to improve flight management operations. They plan to accomplish by transitioning the current system towards smarter, satellite-based technologies while improving flight routes. This will lead to increased safety, reduced delays, fuel savings, and decreased emissions.

On the right is a list of some of the significant NextGen programs. (Point out one or two that look interesting and just read the bullet)Data comm is a transition from verbal exchanges between pilots and controllers to digital messages projected onto the heads up displaysCSS-Wx is a unified weather database that pilots and controllers can access in order to keep up to date with the weather conditions in the NAS12

Thrust 3: Transition to Low-Carbon Propulsion 13Matt SchmitLow-Carbon propulsion options:Biofuels (Near term solution)Alternative fuel sources (Far term solution)BiofuelsConsider Well to Pump CO2 emissionsDrop-In fuelsCO2 reduction dependent on percent blend of mixture, and specific biofuel usedRequires fuel to be sustainableAlternative fuel sourcesNon Drop-In fuel alternativesHydrogenLiquefied Natural Gas (LNG)Hybrid Electric VehicleRequire extensive development as well as safety and design certification (available 2040 2050 timeframe)

[11]Fossil FuelsBiofuels

Boeing Phantom Eye

Boeing Sugar FreezeMotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

NASA Hybrid Electric Concept

The Roundtable on Sustainable Biomaterials is the standard of choice for the European Commission

Alternative jet fuel emits about the same amount of CO2 as conventional jet fuel when burned due to its chemical similarity to conventional jet fuel since it has to be made to be a drop in fuel. Companies can consider the lifecycle emissions of creating the biofuel to reduce the overall emissions into the atmosphere

While this allows some biofuels to have up to 80% less emissions than conventional fuel, the altitude of this fuel burn must be considered [1].

Critics of current EU biofuel policy say it is driving land-grabs in the developing world and diverting food crops to fuel use. Because of changes in land use, and resulting deforestation, first-generation biofuel is causing more CO2 to be released into the atmosphere than it saves through use as a fuel, it is alleged. Second-generation biofuel that is not derived from food crops should be incentivised in EU policy instead, say critics

Altitude: ***Alternative fuel emits the same amount of GHG as conventional jet fuel due to its chemical similarity, but some have worse effects at altitude, such as NOx.

***With CO2, it doesnt matter where the emissions take place-whether it be the tropics or the north pole, the impact is the same, which isnt the case for Nox emissions.

[1] IATA 2011 Report on Alternative Fuels. Montreal, Quebec, Canada: International Air Transport Association, 2013. 2013. Web. 2 Dec. 2014. .[2] RSB GHG Calculation Methodology. Roundtable on Sustainable Biofuels 2.1 (2011): n. pag. 12 July 2012. Web. 2 Dec. 2014. .[3] The High-altitude Effects of Non-CO2 Greenhouse Gases Caused by Aviation Are Still Uncertain, Say Scientists on GreenAir Online. GreenAir Online. N.p., 6 May 2008. Web. 02 Dec. 2014. .[4] Keating, David. Council Rejects Biofuel Compromise. European Voice. N.p., 12 Dec. 2013. Web. 02 Dec. 2014. .[5] Boeing SUGAR volt Hybrid Airplane. IEEE. May 2012. Web. 18 Oct. 2014.[6] Sustainable Aviation Fuel | Airbus, A Leading Aircraft Manufacturer. Airbus. N.p., n.d. Web. 02 Dec. 2014. .

Other considerations citations:http://lae.mit.edu/fueling-the-future-of-flight/

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Global Market Measures14Matt SchmitLast resort to fill in the gaps if desired CO2 reductions arent met in timeEconomic incentives to reduce carbon emissionsCarbon TaxCarbon pollution fee assessed to carbon content of fuelsFactored into airline ticket priceIncreased ticket price less passengers reduced operations reduced CO2 emissionsCarbon offsettingunit of carbon dioxide-equivalent (CO2e) that is reduced, avoided, or sequestered to compensate for emissions occurring elsewhere [19]i.e. planting forests to offset carbon emissionsMotivationProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsProject ObjectivesStrategic ThrustsTeam Organization

[4]

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Global Perspective of NAS Analysis and Forecasting15Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationStrategic InitiativesAircraft TechnologiesNextGenLow Carbon PropulsionCFD, Engine Modeling, Vehicle Sizing and Integration, Mission Profile Optimization, Air Traffic Models Finite Element AnalysisOperational Improvements Alternative Fuels/Propulsion Fuel Burn ReductionAero Technologies Fuel Burn ReductionM&S Environment

National Airspace M&S Environment

Vehicle Level Improvements

Decision MakingForecasted NAS ImpactFleet-Wide Fuel Burn Analysis and Forecasting Environment

Matt Schmit

Need for New Forecast Environment16Matt SchmitTrafficWeather ManagementOther factors

Variation Flight time and distanceLoitering timeTime on the ground Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationMost forecast tools utilize distance as metric to calculate fuel burnNo available database for actual flight distanceGreat circle distance is used, but not accurateDeterministic model

Use flight time as fuel burn metricPublically available databasesCapable of modeling with probabilistic approachModeling uncertainties:Uncertainties interact and propagate across fleetFlight time captures these uncertainties Can create probabilistic time model by segment

Uncertainties Exist:Variation in Flight Time: Must account for variation in flight times

Clear need to develop new, probabilistic forecasting environment.

Ramp to Ramp Time (min) Distance (mi)

Requirements for NAS wide assessment of future CO2 emissions:Determine current fleet networkDetermine probabilistic operational timesEstablish future networkModel impact of NextGen operation techniquesModel impact of future vehicle performanceModel impact of biofuelsEvaluate NAS wide CO2 emissionsArchitectural environment that satisfies the requirementsFuture Air Traffic Emissions Modeling EnvironmentEvaluate NAS Wide CO2 Emissions

7Model Plan and Requirements17Determine Current Fleet Network

1Determine Probabilistic Operational Times

2Establish Future Network

3Model NextGen Operation Techniques

4Model Impact of Biofuels

6Model Future Vehicle Performance

5Matt SchmitProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam Organization

Model Future Operations

Modeling Improvement

Evaluate CO2 Emissions

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Determine Probabilistic Operational TimesModel Impact of BiofuelsEstablish Future NetworkModel Future Vehicle PerformanceModel NextGen Operation TechniquesDetermine Current Fleet NetworkEvaluate NAS Wide CO2 Emissions

Matt SchmitProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationEvaluate NAS Wide CO2 Emissions

7Determine Current Fleet Network

1Determine Probabilistic Operational Times

2Establish Future Network

3Model NextGen Operation Techniques

4Model Impact of Biofuels

6Model Future Vehicle Performance

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Determine Probabilistic Operational TimesEstablish Future NetworkModel Future Vehicle PerformanceModel NextGen Operation TechniquesDetermine Current Fleet NetworkEvaluate NAS Wide CO2 Emissions

Aubrey ClausseProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 EmissionsModel Impact of Biofuels

Determine Current Fleet Network20Need a NAS wide performance model for:Taxi out timeAir timeTaxi in timePerformance model should be specific to aircraft class

On Time Performance DataAircraft Tail #OriginDestinationAir time, Taxi in, Taxi outN-Inquiry: FAA registry of aircraftTail number Specific aircraft type

Tail #OriginDestTaxi OutAir TimeTaxi InN525USATLBOS1910513N143DAATLLAX1625615N172AABOSORF1511010

Tail #Aircraft TypeN525US757-251N143DA767-332 N172AAA320-200

Aircraft TypeOriginDestTaxi OutAir TimeTaxi In757-251ATLBOS1910513767-332 ATLLAX1625615A320-200BOSORF1511010

Available Public DatabasesTime Breakdown:On Time Performance Data:N-Inquiry:Combined Database:Aubrey Clausse

Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 Emissions

Exemple of January 2012 ATL BOS

Bigger fonts on on chart

Aircraft type instead of class20

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Probabilistic Time Modeling 22Factors of influence on time performance

Classification neededAirport sizeAircraft classCreation of distribution databaseTaxi InTaxi Out Air TimeEnable to generate new flight timesBased on the current NAS systemNo new routes added Behavior of the NAS independent of the number of flight

Input Impacts:Fitting Distribution:Distribution Database Taxi OutGenerate New Flight Time:OriginDestClass1ATLBOS1200

Aubrey ClausseAirport Type of Aircraft Weather Queue ManagementOther factors

Probabilistic ApproachType of Aircraft AirportProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 Emissions

Show a chart that classifies aircraft types 22

Classification23Airport ClassificationCommercial Service AirportsPublic OwnedAt least 2,500 passengers per yearPrimary HubMore than 10,000 passengers per year

Aircraft ClassificationBased on previous work done at ASDL [18]Vehicle grouped by Fuel burned NOx emissionsSound Exposure Level

Aubrey ClausseNameLarge Hub Medium Hub Small Hub NonHub Primary Annual Passenger BoardingsNP > 1%NP< 1%NP>0.25%NP< 0.25 % NP> 0.05 %NP< 0.05%

Airport Classification DefinitionAircraft ClassificationAircraft ClassAcronymExample(s)Small Regional Jet SRJCRJ2-ER / ERJ 135Large Regional JetLRJCRJ-900 / ERJ 170Small Single Aisle SSAB737-7 / A319-1Large Single AisleLSAB737-9 / A320-2Small Twin Aisle STAB767-3 / A330-2 Large Twin Aisle LTAB777Very Large Aircraft VLAB747

Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 EmissionsClassifications represent averaged vehicle properties for a given group of similar aircraftNP = percentage of annual passenger boardings at a given airport

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Baseline network establishedTotal number of operation for every airport On Time Performance databaseTerminal Area Forecast Forecast future operations at every airportDemand driven forecastFares, regional demographics factors Local/National economic conditionsFratar Distribution AlgorithmDistribute total operations between origin and destination airports of networkIterative process Assumptions: Network structure stays the sameOperations based on growth of Origin and Destination

Future Network25

Baseline OperationsForecast Operations

OriginDestination

Total number of operations for every airport

OriginDestination

Total number of operations for every airportFratarDistributionAlgorithmAubrey ClausseProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam Organization

Generating Future Flight Times26Read in forecast for every yearNumber of flights per year for every OD pairGroup by aircraft classGenerate future flight and taxi timesFor each OD pairFor each class of aircraftBased on probabilistic models of NASOperational times are stored in Flight Time DatabaseAssumptions: Proportions of aircraft class flown between each OD pair are knownNext generations of vehicles introduced in future network replace aircraft of similar class

OriginDestinationNumber of FlightsATLBOS1200BOSLAS1500

Future Flight Forecast:OriginDestClass 1Class 4ATLBOS288912BOSLAS700800

OriginDestClassTaxi OutAir TimeTaxi InATLBOS1[10,15,...][97, 92,][5, 8,...]ATLBOS4[14,19,...][88, 95,][10, 12,...]BOSLAS3[8,18,...][132, 128,][7, 9,...]BOSLAS4[12,9,...][130, 142,][12, 15,...]

Flight Time Database:Forecast by Aircraft Class:

Aubrey ClausseProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 Emissions

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Modeling Impact of New Operations28Operation performances are modeled by:Probabilistic model Based on historical dataIntroducing operation improvement:Efficiency (mean) improvement Consistency (variance) improvement

Flexibility in implementation:Year of introductionAirport affectedClass of aircraft affected

Updated Operations Database

Taxi OutModel the NAS performance:Flexibility in implementation:

Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ImprovementFuture OperationsEvaluate CO2 EmissionsAubrey Clausse

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Modeling Future Vehicle Performance Impact30Modeling vehicle performance for each aircraft class:Air time: regression coefficients of fuel burn vs. air timeTaxi: idle fuel flow coefficients of engine (constant)Introducing performance improvement:Technology packagesContain fuel flow coefficients for each class of aircraftUser can specify new or additional set of technology packagesFlexibility in implementation:Year of introductionTechnology package usedPercentage of the fleet affected

Flexibility in implementation:


N+1

N+2

N+3Forecasting Environment

Fuel Flow Rates

Model Impact of Biofuels

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Assumptions for Modeling Biofuels32CO2 emissions of biofuels are dependent on control volumeFlight emissions identical to fossil fuelsTransportation, refining, and distribution processes comparable to fossil fuelsReceive Biomass Credit from feedstock growthFinal CO2 emissions reduced due to Biomass CreditCO2 reduction is function of biofuel percent blend and type of biofuel used Fuel burn is still identicalFlexibility in implementation:Type of biofuel usedYear of implementationBiofuel percent blend Percentage of the fleet using biofuel


Flight Emissions

Processing and Refining

Transport

Distribution

Feedstock Growth

Biomass Credits

Control VolumeFlexibility in implementation:CO2 emissions:

1. Report on availability: Lewis, Kristin, Shuchi Mitra, and Sheila Xu.Alternative Jet Fuel Scenario Analysis Report. Rep. no. DOT-VNTSC-FAA-12-01. U.S. Department of Transportation, Nov. 2012. Web. 14 Apr. 2015.

2. Report on CO2 emissions: Stratton, Russell W. "Life Cycle Assessment of Greenhouse Gas Emissions and Non-CO2 Combustion Effects from Alternative Jet Fuels." Thesis. Queen's University, 2008.DSpace@MIT. 23 June 2010. Web. 14 Apr. 2015.

3. http://www.airportsinternational.com/2010/09/greener-skies/47904. http://www.intechopen.com/source/html/42030/media/fig3.png32

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Evaluating NAS Wide CO2 Emissions34Apply operational performance changesAdjust efficiency/consistency of operationsGenerate flight and taxi times for all OD pairs for each yearCalculate NAS wide fuel burnFuel burn for a given flight is based on:Aircraft type (Performance)Stage time spent in each operational phase Summation across all OD pairs CO2 emissions is directly proportional to fuel burnApply reductions to CO2 emissions due to use of biofuels where applicable


Case Study35Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemoMatt SchmitCreated flight time probability distributions based on 2010 On Time Performance databaseUsed Fratar algorithm to forecast operations through 2050Used work previously done at ASDL to model flight performance of baseline aircraft fleetAircraft modeled in Environmental Design Space (EDS)Conducted a review of industry leaders and policy makersBased impacts and implementations of strategic thrust on their estimations

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Thrust 1: Efficient Aircraft Technologies36New technologies will be implemented on new vehiclesEntered as technology packages containing fuel burn for each class of aircraft

Boeings Market Outlook was used to predict the number of new aircraft per year [21]Includes number of replacement vehicles and fleet growth vehiclesDepending on the year, N+1, N+2 or N+3 goals were applied to find the fuel burn reduction

Fuel burn reductions applied relative to baseline fleetEDS physics based models used to calculate fuel burn of baseline fleetProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemoMatt Schmit

N+1 (2015)N+2 (2020)N + 3 (2025)Aircraft Fuel/Energy Consumption [22](rel. to 2005 best in class)-33%-50%-60%

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Thrust 2: FAA NextGen Operations37

Required Navigation PerformanceAllows aircraft to fly wind optimal routesCNA solutions and analysis conducted a study on flight time reductions when using 4-D flight routing

Optimized Profile Descent (OPD)Used effectively in NASUS Airways flight into Washington Reagan saved 70 gallons [9]

Can enter flight time reductions into toolFlight time reduction decreases total fuel burn, decreasing CO2 emissionsOPD modeled by converting fuel savings to a reduction in flight time

[23]Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemoMatt Schmit

[9]Optimized Profile DescentRequired Navigation Performance

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Thrust 3: Transition to Low-Carbon Propulsion 38201020152020Scenario0.00%10.00%23.40%

Percent ReplacementYearFT-CBTL (millions of gallons)HEFA-J (millions of gallons)2013124.2153.220201046.32673.7

AvailabilityProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemoMatt SchmitBiofuelsU.S. Department of Transportation study on use of biofuels through 2020 [20]Availability of biofuels Demand of biofuels (replacement over conventional jet fuel) Extrapolated to get estimations through 2050Modeled impact of two biofuels:Hydro-Processed Esters and Fatty Acids (HEFA)Fischer-Tropsch Coal/Biomass to Liquid (FT-CBTL)Not directly modeled yetAssumed notional values for CO2 reductionsAlternative Fuel Sources

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Demo of FATE39Matt SchmitProject OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemo

Proof of ConceptOur results indicate that new efficient aircraft technologies will have greatest impactModeling low-carbon propulsion will improve resultsEconomic measures are likely to be requiredFATE demonstrates a capabilityProbabilistic model of ramp-to-ramp flight timesUses inputs from high fidelity M&S toolsProvides real time feedback Results are only as reliable as inputsOur work based on public domain databasesImpacts based on industry predictions and forecasts Accuracy and fidelity of tool could be greatly improved if given access to better databases40Matt SchmitMethodology used in FATE is effective and viable for modeling NAS wide impact of strategic thrust on CO2 emissions.Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam OrganizationModeling ThrustsOverviewDemo

Need a case study. ERA technology already in LAB, gives a bottom up assessment

Get figures from NextGen and Biofuels in future40

[4]Conclusion and Future WorkFATE provides the capability to quantify and evaluate the NAS wide impact of: technologies, operational improvements, and biofuelsAid in determining which strategic thrusts to invest inProvides real-time estimations of CO2 emissionsFlexibility to add new components to tool

Future Work:Model low-carbon propulsion technologiesQuantify interaction between operations and technologiesAdd capability to vary assumptions to assess their impactsCapture economic measures through reduction in operations

41Matt Schmit

Inputs and Parameters

Base Fleet CompositionBase Flight OperationsTechnology PackagesBiofuel PackagesOutputs and Metrics

NAS Wide Fuel Burn through 2050NAS Wide CO2 Emissions through 2050Project OverviewCase StudyConclusions and Future WorkModel Plan and RequirementsTeam Organization

Questions?

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References"How Much Has the Global Temperature Risen in the Last 100 Years? | UCAR - University Corporation for Atmospheric Research." University Corporation for Atmospheric Research. National Center for Atmospheric Research, n.d. Web. 14 Mar. 2015. ."Global Climate Change Indicators." National Climate Data Center. National Oceanic and Atmospheric Administration, n.d. Web. 14 Mar. 2015. .IATA Technology Road Map." IATA Technology Roadmap. IATA, 4th Edition, June 2013. Web. 17 Oct. 2014.Rogers, M. M., Technical Challenges to Reducing Subsonic Transport Drag, National Aeronautics and Space Administration, URL:http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20120006660_2012004695.pdfGeorgia Tech paper on CO2 emissionshttp://www.theguardian.com/environment/2012/jan/16/greenhouse-gases-remain-air"How Plane Finder Works Using ADS-B."Planefindernet RSS. N.p., n.d. Web. 16 Oct. 2014. ."Performance Based Navigation (PBN)."NextGen Performance Based Navigation (PBN)(n.d.): n. pag. June 2013. Web. 16 Oct. 2014.NextGen Update 2014. Tech. Washington D.C.: Federal Aviation Administration, 2014. Print.https://www.faa.gov/about/office_org/headquarters_offices/ato/service_units/techops/atc_comms_services/datacomm/documentation/media/brochures/90818_DataComm_11x17_PRINT4.pdfhttp://www.qantas.com.au/travel/airlines/sustainable-aviation-fuel/global/enGunnar Myhre (Norway), Drew Shindell (Usa). Climate Change 2013: The Physical Science Basis. (n.d.): n. pag. IPCC. Interngovernmental Panel of Climate Change. Web. https://www.nasa.gov/press/2014/november/nasa-tests-revolutionary-shape-changing-aircraft-flap-for-the-first-time/ http://globalaviationreport.com/2014/12/23/boeing-2014-top-photos/ http://aviationweek.com/technology/757-ecodemo-focuses-laminar-and-active-flow http://www.nasa.gov/content/down-to-earth-future-aircraft-0/#.VSvthfnF-So http://www.slideshare.net/marcusforpresident2012/nasa-aviation-alternative-fuels-workshopMatthew J. LeVine, Amelia Wilson, Dr. Michelle Kirby and Prof. Dimitri Mavris : Development of Generic Vehicles for Fleet-Level Analysis of Noise and Emissions Tradeoffs, AIAA Aviation, 16-20 June 2014, Atlanta, GAhttp://www.wri.org/publication/bottom-line-offsets Lewis, Kristin, Shuchi Mitra, and Sheila Xu.Alternative Jet Fuel Scenario Analysis Report. Rep. no. DOT-VNTSC-FAA-12-01. U.S. Department of Transportation, Nov. 2012. Web. 14 Apr. 2015.Current Market Outlook. Boeing. Boeing, 2015. Web.Collier, Fay. Environmentally Responsible Aviation Project Real Solutions for Environmental Challenges Facing Aviation. AIAA. NASA, 2012. Web.

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Back up slides

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Probabilistic NAS Performance Model45

OriginDestinationAir-TimeRamp to Ramp TimeTaxi OutTaxi In

46Name of the person presenting this slide

Technology and Fuel Cost1973: Oil Embargo1975: Advanced Turboprop Project Announced1980 and 1981: Iranian Revolution and Iran-Iraq War1983: GE UDF unveiled1989: End of Program1986: UDF 1st test flight on 7J7

Crude Oil first purchase price: http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=F000000__3&f=ACrude oil price graph: http://www.eia.gov/totalenergy/data/monthly/pdf/sec9.pdf (page 2)

Articles on the matter: http://www.airspacemag.com/history-of-flight/the-short-happy-life-of-the-prop-fan-7856180/?no-isthttp://www.flightglobal.com/news/articles/whatever-happened-to-propfans-214520/http://www.sustainableaviation.co.uk/wp-content/uploads/open-rotor-engine-briefing-paper.pdf (page 4)

Pictures: First picture: http://blog.cafefoundation.org/quiet-may-be-the-new-black/Second Picture: http://mrlarry.org/serendipity/Third Picture: http://www.flightglobal.com/news/articles/whatever-happened-to-propfans-214520/47

Fratar AlgorithmIterative Growth Factor Method Two big assumptions:The previous pattern for flights between origin and destination pairs will remain the sameThe volume of trips will change according to the growth of the origin and destination airports

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Predicted traffic from airport i to airport j Previous year traffic from airport i to airport j From BTS dataGrowth factor:gi is the ratio of predicted future departures from airport i to previous year departures in airport igj is the ratio of predicted future arrivals from airport j to previous year arrivals in airport jPredictions come from TAF data, previous year operations are from BTS datadi= Total previous year departures at airport i ai= Total previous year arrivals at airport j tim=sum of all the traffic from airport I to airport m tjm=sum of all the traffic from airport I to airport mgm=growth factor airport mAll but gm are from BTS data. gm is found using TAF

Assumptions: http://www.tcd.ie/civileng/Staff/Brian.Caulfield/T2%20-%20Transport%20Modelling/Lecture%203.pdf48

NASA Tech Integration Georgia Tech Grand Challenge

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