Assessing Alternative Fuels For Helicopter Operation

Assessing Alternative Fuels For Helicopter Operation
Alexiou, Tsalavoutas, Pons, Aretakis, Roumeliotis, Mathioudakis
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Assessing Alternative Fuels For Helicopter
Operation
Presented by
A. Alexiou
Laboratory of Thermal Turbomachines
National Technical University of Athens

Collaborative & Robust Engineering using
Simulation Capability Enabling Next Design Optimisation
Environmentally Compatible
Air Transport System
2
Acknowledgements

3
 INTRODUCTION
 MODELLING ASPECTS
o Mission Fuel Calculation
o Simulation Environment
o Helicopter-Engine Integrated Performance Model
o Alternative Fuels
 CASE STUDY
o Engine Performance for Jet-A
o Helicopter Performance for Jet-A
o Effects of Alternative Fuels on Performance
 SUMMARY & CONCLUSIONS
Contents

4
Introduction
Fuel Impact On Operating Costs
Year 2003 2005 2007 2009 2011
% of operating costs 14 22 28 26 30
Average price / barrel of crude ($) 28.8 54.5 73.0 62.0 110.0
Break even price / barrel ($) 23.4 51.8 82.2 55.4 112.5
Total fuel cost (bn $) 44 91 135 125 176
(http://www.iata.org/pressroom/facts_figures/fact_sheets/pages/fuel.aspx)

5
Introduction
(ACARE Beyond Vision 2020)
Global Man-Made CO2 Emissions

Introduction
6
World Annual Traffic
(Airbus GMF 2010-2029)

7
Introduction
IATA VISION 2050
Build a zero-emissions commercial aircraft within 50 years
Targets
• Carbon neutral growth from 2020
• 1.5% average annual improvement of fuel efficiency
• 50% reduction of CO2 emissions by 2050 relative to 2005 levels
Four-Pillar Strategy
• Technology (IATA target is for 10% of the fuel
used will be an alternative fuel by 2017)
• Operations
• Infrastructure
• Economic measures

Introduction
8
 Research is mainly focused on second or new generation
bio-fuels (e.g. algae, jatropha and camelina).
 Sustainable bio-fuels can reduce aviation’s net carbon
contribution on a full life-cycle basis (60-85%).
 Tests demonstrated that the use of bio-fuels as ‘drop-in’
fuels is technically sound and doesn’t require any major
adaptation of the aircraft.
 To date, aviation industry is cleared to use blends with up
to 50% ‘synthetic’ kerosene derived from coal, gas or biomass
and conventional jet fuel.

Introduction
9
Objective
Study the effect of alternative fuels on the
performance of a medium utility helicopter
Requirement
A helicopter mission analysis tool with the capability
to use different fuels

10
 INTRODUCTION
o Alternative Fuels
 CASE STUDY
Contents

11
H/C new
weight
6
Mission Fuel
7
H/C Specification
• Take-Off weight
• air bleed/power off-take
Air Intake losses
Exhaust losses
Mission definition
e.g. velocity, time for each
segment
 Oil & Gas
 SAR
Mission Fuel Calculation
ENGINE PERFORMANCE
MODEL
Fuel Flow
Rate 5
FUEL
MODEL
1
MISSION PROFILE
3
H/C operating
conditions
H/C requirements
(power, air cabin off
take, Nrotor)
2
H/C PERFORMANCE MODEL
4 -200
0
200
400
600
800
1000
1200
1400
1600
1800
0 10 20 30 40 50
Time (min)
Altitude
[m]

 Object-Oriented
 Steady State
 Transient
 Mixed-Fidelity
 Multi-Disciplinary
 Distributed
 Multi-point Design
 Off-Design
 Test Analysis
 Diagnostics
 Sensitivity
 Optimisation
 Deck Generation
12
Simulation Platform
PROOSIS (PRopulsion Object-Oriented SImulation Software)

13
Simulation Platform
 TURBO library
of gas turbine
components
 Industry-
accepted
performance
modelling
techniques
 Respects
international
standards in
nomenclature,
interface & OO
programming

14
Simulation Platform

15
Simulation Platform
Total helicopter power
 Main rotor power
 Induced
 Profile
 Fuselage
 Potential energy change
 Tail rotor power
 Customer power extraction
 Gearbox power losses

16
Integrated Model

17
Integrated Model
Engine Component

18
Integrated Model
Engine Component
Helicopter Component (black box or PROOSIS model)

Integrated
Helicopter-Engine
Component
19
Integrated Model
Engine Component
Helicopter Component (black box or PROOSIS model)

20
Alternative Fuels
FUEL H:C RATIO LHV (MJ/kg) DENSITY (kg/m3)
Jet-A 1.917 43.12 Ref. 801.0 Ref
Synjet (FT) 2.166 43.94 1.9% 762.4 -4.8%
S8 (FT-GTL) 2.169 43.90 1.8% 756.0 -5.6%
Jatropha Algae (HRJ) 2.119 44.20 2.5% 748.0 -6.6%
Blend
50% Jet-A + 50% Jatr.
2.017 43.70 1.34% 780.0 -2.6%
FT: Fischer-Tropsch
HRJ: Hydrotreated Renewable Jet
GTL: Gas-to-Liquid
 Low aromatics content
 Absence of natural anti-oxidants
 Low electrical conductivity
 Poor lubrication properties
 Erroneous fuel metering
 Accelerated wear of fuel system O-rings/seals
 Fuel degradation in long-term storage
 High pressure fuel pump wear
 Increased fire hazard
Biodiesel (Soybean) 1.855 38.00 -11.9% 880.0 9.9%

21
Alternative Fuels
FUEL H:C RATIO LHV (MJ/kg) DENSITY (kg/m3)
Jet-A 1.917 43.12 Ref. 801.0 Ref
Synjet (FT) 2.166 43.94 1.9% 762.4 -4.8%
S8 (FT-GTL) 2.169 43.90 1.8% 756.0 -5.6%
Jatropha Algae (HRJ) 2.119 44.20 2.5% 748.0 -6.6%
Blend
50% Jet-A + 50% Jatr.
2.017 43.70 1.34% 780.0 -2.6%
PROOSIS TURBO library uses 3-D tables to
calculate the caloric properties of the working fluid in
the engine model generated with the NASA CEA
software (no dissociation)
Biodiesel (Soybean) 1.855 38.00 -11.9% 880.0 9.9%

22
 INTRODUCTION
o Alternative Fuels
 CASE STUDY
Contents

23
Engine Performance
PARAMETER MCP TOP OEI30
Power Delivered [kW] 1056 1252 1437
Torque Delivered [Nm] 1681 1992 2287
Overall Pressure Ratio 11.6 12.6 13.3
Power Turbine Inlet Temperature [K] 977 1034 1108
Inlet Air Mass Flow Rate [kg/s] 4.6 4.8 4.94
Gas Generator Speed [rpm] 38946 40205 41700
Specific Fuel Consumption [kg/kWh] 0.280 0.271 0.269
Sea-level standard conditions

24
Engine Performance
PARAMETER MCP TOP OEI30
Power Delivered [kW] 1056 1252 1437
Torque Delivered [Nm] 1681 1992 2287
Overall Pressure Ratio 11.6 12.6 13.3
Power Turbine Inlet Temperature [K] 977 1034 1108
Inlet Air Mass Flow Rate [kg/s] 4.6 4.8 4.94
Gas Generator Speed [rpm] 38946 40205 41700
Specific Fuel Consumption [kg/kWh] 0.280 0.271 0.269
Sea-level standard conditions

0
200
400
600
800
1000
1200
220 230 240 250 260 270 280 290 300 310 320 330
PWSD
[kW]
Tamb [K]
0
1000
2000
3000
4000
5000
6000
7000
Altitude
Maximum Continuous Power (MCP) Rating
Engine Performance
25

Engine Performance
26
0
100
200
300
400
500
600
700
500 1000 1500 2000 2500
WF/(δ*θ
1/2
)
(kg/h)
PWSD/(δ*θ1/2) (kW)
MCP
TOP
OEI30

Engine Performance
27
0.25
0.35
0.45
0.55
0.65
0.75
0.85
0.95
50 250 450 650 850 1050 1250 1450
SFC
(kg/kW.h)
PWSD (kW)
MCP TOP OEI30

Helicopter Performance
28
PARAMETER SYMBOL VALUE UNITS
Maximum Take-off Weight MTOW 7400 kg
Weight Empty WE 4105 kg
Fixed Useful Load FUL 200 kg
Fuel Capacity VFu 1.45 m3
Number of Engines Neng 2 -
Number of Rotor Blades Nb 4 -
Main Rotor Diameter D 15.2 m
Main Rotor Blade Chord c 0.49 m
Main Rotor Solidity σ 0.08 -
Rotor Blade Tip Speed U 223 m/sec
Rotor Speed NR 280 rpm
Equivalent Flat Plate Area SCx 3.0 m2
Power Extraction Pex 10 kW

0
500
1000
1500
2000
2500
0 20 40 60 80 100
Power
Required
[kW]
True Airspeed [m/s]
5000 m
4000 m
3000 m
2000 m
1000 m
SL
MCP at SL
MCP at 5000 m
29
Jet-A / MTOW / STD

30
3500
4000
4500
5000
5500
6000
6500
7000
7500
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100
Max
Altitude
[m]
Max
Rate
of
Climb
[m/s]
True Airspeed [m/s]
Max Rate of Climb at 0 m
Max Rate of Climb at 2000 m
Max Altitude
Jet-A / MTOW / STD

31
0
0.05
0.1
0.15
0.2
0
100
200
300
400
500
600
700
0 20 40 60 80 100
Fuel
Flow
[kg/s]
Specific
Range
[m/kg]
True Airspeed [m/s]
Specific Range
Fuel Flow
Vbe Vbr
SR = Vx / Wfuel
Jet-A / MTOW / SL / STD

32
0
500
1000
1500
2000
2500
3000
3500
0 200000 400000 600000 800000
PAYLOAD
[kg]
RANGE [m]
Full Fuel Line
Jet-A

Effects of Alternative Fuels
33
Fixed PWSD (TOP for Jet-A)
Fixed XNH (TOP rating)

34
-4
-2
0
2
4
6
8
10
12
14
Synjet S8 (GTL) Jatropha/Algae
(HRJ)
50% JetA+50%
Jatr/Alg
Biodiesel
(Soybean)
WFu
%
Difference
from
JetA
PWSD at MCP for JetA
PWSD at TOP for JetA
PWSD at OEI30 for JetA

0
500
1000
1500
2000
2500
0 10 20 30 40 50 60
Altitude
[m]
Time [min]
35
Warm up at MCP [2’]
Take-Off [2’]
Climb at Vbe & Vz,max [2’]
Cruise at Vbr [40’]
Descent [4’]
Land [2’]

36
6800
6900
7000
7100
7200
7300
7400
7500
0 10 20 30 40 50 60
Helicopter
Weight
[kg]
Time [min]
JetA Synjet
S8 (GTL) Jatropha Algea
50% JetA + 50% JA Biodiesel
CRUISE
CLIMB
DESCENT
LAND
T/O

37
-4
-2
0
2
4
6
8
10
12
14
16
Synjet S8 (GTL) Jatropha Algea
(HRJ)
50% JetA + 50%
Jatr/Alg
Biodiesel
(Soybean)
%
Change
in
Mission
Fuel

-4
-2
0
2
4
6
8
10
12
14
16
Synjet S8 (GTL) Jatropha Algea
(HRJ)
50% JetA + 50%
Jatr/Alg
Biodiesel
(Soybean)
%
Change
in
Mission
Fuel
Full Tanks
Same GTOW
38

39
530
550
570
590
610
630
650
670
690
710
730
4400 4900 5400 5900 6400 6900 7400
Specific
Range
[m/kg]
Helicopter Weight [kg]
Jet-A Synjet
50% JetA +50% JA Biodiesel

0
500
1000
1500
2000
2500
500000 600000 700000
PAYLOAD
[kg]
RANGE [m]
JetA Synjet
50% JetA - 50% JA Biodiesel
40

41
 INTRODUCTION
o Alternative Fuels
 CASE STUDY
Contents

Summary & Conclusions
42
 An integrated performance model of a helicopter and its turboshaft
engine has been created in an object-oriented simulation environment to
study the effects of alternative fuels on helicopter operation.
 For the fuels considered in this study there are no significant effects
on the engine cycle compared to Jet-A except for the fuel flow rate that
changes according to the difference of each fuel’s lower heating value
from the reference one.
 Considering the helicopter in a mission, there is an added effect from
the differences in density between the fuels that modifies the helicopter’s
payload-range capability.
 Based on the modelling assumptions, the blended fuel appears at the
moment as the most suitable choice for the aspects considered in the
presented analysis (e.g. taking into account its effects on engine cycle
parameters and helicopter operational characteristics) but other
parameters should also be taken into account to allow for a more
complete assessment (e.g. economics of fuel production, emissions, etc.).

43
 The method presented herein can be further extended by including
models of other disciplines in the existing integrated model (e.g.
economics, noise and particulate emissions, etc.). This would allow the
required multi-disciplinary calculations (including design and
optimisation) to be performed in a single simulation environment with all
the associated benefits that such an approach offers (configuration
management control, transparent exchange of information between
modules, common modelling standards, flexible mathematical model
handling, etc.).

44
ATLAS
Aero-TooLs for Advanced Simulations

45
 Finally, by creating a library of specific aircrafts (rotary or fixed wing)
and a corresponding one with engines (turboshafts, turbofans, etc.) one
can perform such studies for various combinations of current and
future aircraft-engine models.
Library of Gas Turbine Engines

46
THANK YOU
Laboratory of Thermal Turbomachines
National Technical University of Athens

Assessing Alternative Fuels For Helicopter Operation

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