Development process/General areas (MDJ)



AAE 451

Systems Definition Review

Group 6

John Collins

Chad Davis

Chris Fles

Danny Sze Ling Lim

Justin Rohde

Ryan Schulz

Ronald Wong

Yusaku Yamashita

Contents

Executive Summary 3

1. Review of Business Case 4

2. Current Design Requirements 5

3. Trade Studies 6

4. Concept Generation (Pugh’s Method) 19

5. Selected Concepts 23

6. Preliminary Layout 27

7. Fuel Choice 33

8. Constraint Models 35

9. Aircraft Characteristics and Comparisons 37

10. Conclusion 37

11. Appendix 38

12. References 69

13. Merit Pool 70

Executive Summary

The current outlook on the world’s fuel supply shows the possibility of nearing peak oil within the next few decades. This situation will drive up the cost of fuel to possibly unattainable prices. The occurrence of peak oil, however, will not eliminate the need for individuals to travel and for business to work fluidly. This report assesses the feasibility of creating an aircraft that is capable of safely and efficiently operating on an alternative fuel.

The design team believes that a market exists for a small to medium sized propeller driven aircraft. The market to which this could be sold to consists primarily of air taxi services, air charter operations, and corporate flight departments. The concept aircraft could also be sold for uses in cargo, medical, and evacuation roles. The primary markets exist not only in the United States, but also in Europe and Asia.

The team feel that the best way to effectively capture a portion of these markets is through the development of a small single turboprop aircraft. It will be capable of carrying six passengers and two crew members on a 600 nautical mile trip. With the capability of using runways as short as 2,100 feet, the aircraft will be able to utilize a multitude of airports providing more convenient point to point service.

A main focus of this design will be to maintain affordability and low cost of the aircraft. A lower acquisition cost and operating cost will positively affect both the operator and end-user of the aircraft, which will in turn bolster sales. Through the use of trade studies and concept generation and selection process (Pugh’s method), a design has been chosen to suit these criteria. This report also outlines potential interior layout, as well as alternative fuels available for our propulsion requirements.

The combination of an alternative fuel aircraft, a new and broad market, and effective utilization of the many advanced design tools available today will make the aircraft a successful competitor.

1. Review of Business Case

Energy forecasts provided by Energy Information Administration (EIA) and ExxonMobil reflect the best case scenario for future petroleum prices. Figure below demonstrates that with external factors, the price trend is likely to rise for the next 30 years:

[pic]

The current aim is to enter the market around the year 2018, when the alternative fuels become competitive.

Overall, the acquisition and operating costs of the alternative fuel based aircraft need to be very strict in order to compete in the current market. Currently, market data shows direct operating costs for light turboprops are around $500-$600 per hour, while small jet aircraft cost approximately $1,500-$1800 per hour. However, this includes aging aircraft such as the KingAir C90s designed in the 1970s, and with the advancement in technology, these figures are likely to decrease. In terms of acquisition costs, the alternative fuel aircraft would need a purchase price of about $1.6M if it was propeller driven aircraft or about $1.8M if it is a jet aircraft.

2. Current Design Requirements

The current design requirements are:

|Cabin Capacity |2 crew + 6 passengers |

|Cruise Range (nm) |600 |

|Cruise Speed (kts) |> 250 |

|T/O distance (ft) |< 2100 |

|Acquisition Cost ($M) |< 1.8 |

|DOC ($/hr) |< 550 |

Table 1 - Current Design requirements

These values were obtained from the QFD matrix and verified using the trade studies discussed in section 4. They represent the limits on which further design processes will be based.

Figure 1 below shows a typical design mission profile:

3. Trade Studies

Trade Studies:

The trade studies conducted for this report had two major impacts on the design process. First, the trade studies provided justification for the design requirements that any conceptual designs need to meet, as well as improving the accuracy of the design requirements that were derived from the QFD Matrix. The second major effect of the trade studies was the justification of the ratings made during Pugh’s Method in section 4.

Initial Sizing:

In order to conduct the trade studies, an initial sizing code needed to be created to determine the aircraft weight based off of characteristics such as L/Dmax, specific fuel consumption, and empty weight fraction. The sizing code uses the aircraft characteristics and the design mission profile to calculate weight fractions for different segments of the flight based off of an initial guess, and then returns the calculated aircraft weight using Equation 1 below. The calculated value then becomes the initial guess in an iterative process to determine the actual aircraft gross weight.

[pic] Equation 1

The aircraft characteristics such as specific fuel consumption and L/Dmax are determined using estimates from historical data of aircraft of the same size and type, as well as from the competing aircraft database.

The empty weight fraction is determined by using a linear regression of the historical empty weight fractions for aircraft of the same size and type. The empty weight fractions for light business jets, single turboprop aircraft, and twin turboprop aircraft were determined as a function of gross takeoff weight using Equation 2, where A and B are constants determined from the linear regression. The constants for the single turboprop aircraft and the light turbofan aircraft are shown in the MATLAB Code Appendix.

[pic] Equation 2

The fuel fraction is the function of each of the weight fractions of the design mission segments. Many of the weight fractions are taken from historical values such as warm-up, takeoff, and landing. Other mission segments, such as climb, cruise, and loiter, have weight fractions that are entirely dependent on the mission profile. Because turbofan and turboprop aircraft have very different climb, cruise, and loiter performance and conditions, it is important to accurately calculate these weight fractions in order to better distinguish between these two classes of aircraft for Pugh’s Method. The climb weight fraction is based on Mach number. Turbofan aircraft climb to higher altitudes and higher Mach numbers than turboprop aircraft, so the turbofan aircraft will burn more fuel as can be seen in Equation 3. The cruise and loiter weight fractions are based on the Breguet range equation and the endurance equation and are shown in Equation 4 and Equation 5, respectively. Turbofan and turboprop aircraft also fly at different L/D values, and this is accounted for in the sizing code. Once the mission segment weight fractions are calculated, the fuel fraction is determined using Equation 6, which makes an allowance for trapped fuel.

[pic] Equation 3

[pic] Equation 4

[pic] Equation 5

[pic] Equation 6

Once the aircraft gross weight is calculated, further studies can be conducted. Aircraft acquisition and direct operating costs (DOC’s) can be determined with a linear regression similar to the empty weight fraction. Equation 7 shows the cost model, which is based on aircraft gross weight, range, and speed. The constants A, B, C, and D are based on the linear regression for each aircraft type, and are different for the acquisition costs and DOC’s. The values for the cost regressions are shown in the MATLAB Code Appendix.

[pic] Equation 7

Trade Study Analysis:

The results of the trade studies can be seen in their entirety in the Trade Study Appendix.

The trade studies show clear trends in aircraft gross weight, acquisition cost, and DOC as values such as specific fuel consumption, range, and speed, are varied. The results of the trade studies were critical in determining whether turbofan or turboprop aircraft were the best choice for our mission, and certain design criteria were also created from the studies as well.

When the range of the mission was varied, the aircraft gross weight increased significantly, while the DOC per hour increased slightly for turbofan aircraft, and almost not at all for turboprop aircraft. The trend for the acquisition cost shows a decrease in cost as range increases, but this is entirely based on the linear regression of similar aircraft, and in the case of very light jets (VLJ’s), there are only a few examples so the data fidelity is in question. The true acquisition cost probably follows the gross weight calculation, which is affected by the mission profile and not the cost regression.

The trends for acquisition cost, DOC per hour, and gross weight for turbofan and turboprop aircraft are exactly opposite. The turboprop aircraft had lower costs and weights as the speed decreased while the turbofan aircraft had lower DOC’s per hour, gross weight, and thus acquisition costs, as the cruise speed was increased. If the turboprop aircraft operates at 250 knots and the turbofan aircraft operates at 350 knots, the turbofan aircraft will save the passengers 30 minutes after a flight of 600 nautical miles. This shows that while the costs may decrease for slower flying turboprop aircraft, customers expect a timely arrival, and flying slower than 250 knots will give a significant edge to turbofan powered aircraft. As the speed of the turbofan aircraft increased, the costs decreased, but the cost reduction was diminishing. This is most likely due to the fact that turbofan aircraft have higher optimal cruise speeds than turboprops. Flying faster is more cost effective for turbofan aircraft until the Mach number reaches a certain point where the increased drag causes more problems. Turbofan aircraft of our size typically operate at 350 knots and an altitude of 30,000 feet. Figure 2 and Figure 3 show the gross weight trends for range and speed.

[pic]

Figure 2 - Turbofan Range and Speed Trade Study

[pic]

Figure 3 - Turboprop Range and Speed Trade Study

At the time the study was conducted, the exact fuel type and engine had not been selected, so the specific fuel consumption was varied to create design requirements for the fuel type and engine. For both the turboprop and turbofan aircraft, a specific fuel consumption greater than 0.7 lbf/(lbm∙hr) resulted in aircraft gross weights, acquisition costs, and DOC’s that were too high to remain competitive in the current market, as can be seen in Figure 4 and Figure 5. Similarly, aircraft with an L/Dmax ratio less than 12 could not remain competitive, which may show that aircraft with canards will have an advantage over conventional aircraft.

Figure 4 - Turbofan Range and SFC Trade Study

Figure 5 - Turboprop Range and SFC Trade Study

Overall, significant performance issues between turboprop and turbofan aircraft were observed. Twin turboprop aircraft had the highest gross weights, acquisition costs, and DOC’s. Based on the trade studies, single turboprop aircraft are significantly more cost efficient and have similar performance capabilities when compared to twin turboprop and turbofan aircraft. From the trade study analysis, the single turboprop aircraft is optimal for the current design mission. However, the public perception of propeller driven aircraft is not based on efficiency, and factors other than efficiency and performance also determine which aircraft best suites the customers needs. This is discussed further in Pugh’s Method.

FLOPS

FLOPS optimization software was used in conjunction with the regression models to investigate the variation of operating cost with the cruise altitude at various cruise speeds using existing aircraft database. Three aircraft with different power plants were used to initiate the FLOPS software. The King Air C90 was used model the twin turboprops; the Pilatus PC-12 was used to model single turboprops and the Eclipse 500 was used to model the very light jets.

By varying the cruise altitudes and cruise speeds in the FLOPS input file, the operating costs were obtained and plotted using excel. As there were many uncertainties with the input into FLOPS, only the trends predicted by FLOPS of the operating costs were noted as the exact values were highly inaccurate. A 5% uncertainty error in the operating costs was also introduced into the very light jets model as a safeguard against overly cautious performance data obtained from the manufacturers’ website.

TWIN TURBOPROP

Operating Cost versus Speed

[pic]

Figure 6 - Operating cost versus cruise speeds at 10,000 ft over various ranges

• It can be observed that as the range increases the operating costs also increased.

• The operating cost decreases as speed increases and is at the lowest at mach 0.5 (320 knots).

Operating Cost versus Different Cruising Altitude

[pic]

Figure 7 - Operating cost versus cruise altitude at mach 0.45 over various ranges

[pic]

Figure 8 - Operating cost versus cruise altitude at mach 0.5 over various ranges

• It can be observed that as the range increases the operating costs also increased.

• Above 10,000 feet the variation of operating cost with altitude is minimal. However acquisition cost might increase at higher altitude due to pressurization requirements.

• Cruise Altitude ~ 10,000 feet, Cruise Speed ~ 320 Knots

SINGLE TURBOPROP

Operating Cost versus Different Cruising Altitude

[pic]

Figure 9 - Operating cost versus cruise altitude at mach 0.3 over various ranges

[pic]

Figure 10 - Operating cost versus cruise altitude at mach 0.4 over various ranges

• It can be observed again that as the range increases the operating costs also increased.

• The variation of operating cost with altitude is minimal. However acquisition cost might increase at higher altitude due to pressurization requirements.

• Cruise Altitude ~ 10,000 feet, Cruise Speed ~ 255 Knots

VERY LIGHT JETS

Operating Cost versus Speed

[pic]

Figure 11 - Operating cost versus cruise speeds at 30,000 ft over various ranges

• It can be observed that as the range increases the operating costs also increased.

• The operating cost decreases as speed increases and is at the lowest at mach 0.55 (325 knots).

Operating Cost versus Different Cruising Altitude

[pic]

Figure 12 - Operating cost versus cruise altitude at mach 0.51 over various ranges

[pic]

Figure 13. Operating cost versus cruise altitude at mach 0.55 over various ranges

• It can be observed again that as the range increases the operating costs also increased.

• 30,000 feet is the optimum cruise altitude for the very light jet model.

• Cruise Altitude ~ 30,000 feet, Cruise Speed ~ 325 Knots

SUMMARY

[pic]

Figure 14 - Comparison of Operating cost for the Different Power Plants

• Operating cost of twin turboprop is the highest regardless of the range.

• Operating cost for the single turboprop is the least regardless of the range.

4. Concept Generation

Pugh’s Method

The aim of Pugh’s method is to select the best concept design for our market sector. The approach used was to first gather potential designs by brainstorming. These were then compared against important criteria that would define a successful product.

Since the future of air charter/air taxi/corporate flight departments require an affordable means of travel, criteria are grouped under the categories of acquisition and operating costs.

The individual characteristics of each concept is rated as either positive (+), negative (-), or same (s) in comparison to the benchmark aircraft (Beechcraft King Air C90). The design mission requirements define the lower limits set for each criterion. A concept can better these limits if they operate at a higher efficiency. For example, given the airspeed is set at 250 kts, a jet variant can fly at 350 kts if it is consuming less fuel at that speed.

| |3rd iteration - concepts to be carried forward |Single pusher |Single |2 fuselage |

| | |engine, Canards,|puller, |mounted (jet)|

| | |wings (far |conventional,|engines, mid |

| | |back), vertical |low wing, mid|wing, high |

| | |stabiliser |tail |tail |

| | |(tail) | | |

| | | |15 |1 |13 |

| |Desirable Characteristics/Criteria |  |  |  |

|op cost |Performance |Range |s |s |s |

|Canards, wings (far back), vertical stabiliser|+ |0 |2 |3 |

|(tail), single pusher engine | | | | |

| |S |14 |10 |

|GTOW |6800 lb |10000 lb |6800 lb |

|W/S (wing loading) |32 lb/ft2 |40 lb/ft2 |32 lb/ft2 |

|S (wetted wing area) |212 ft2 |250 ft2 |212 ft2 |

|AR |7.6 |8 |7.6 |

|b (wing span) |40 ft 1 in |44 ft 7 in |40 ft 1 in |

|P/W (power to weight) - props |P/W = 0.088 |T/W = 0.155 |P/W = 0.088 |

|T/W (thrust to weight) – turbofans/jets | | | |

|STO |2100 ft |2100 ft |2100 ft |

|VCruise |250 kts |350 kts |250 kts |

|Acquisition cost |$1.65 million |$1.85 million |$1.65 million |

|Direct Operating cost |100LL - $350/hr |$550/hr |100LL - $350/hr |

| |Biodiesel - $468/hr | |Biodiesel - $468/hr |

Table 3 - Concept Predicted Performance Values

Both acquisition and direct operating costs are calculated using regression models obtained from the aircraft database. (See appendix for the MATLAB code and graphs)

Biodiesel fuel is projected to burn 20% more than traditional 100LL fuel, thus with the assumption of a 20% additional pricing when compared to current fuels, a 44% increase in direct operating cost is added to give $468 for the turboprops.

Upon further discussion, turbofans are rejected based on the fact that the DOC costs are higher than the single turboprop designs and the wing loading are higher than required. Therefore, only concept 1 and concept 15 will be considered in the next phase.

5. Preliminary Layout

Fuselage Design

The operational characteristics of our aircraft are;

- Standard 6 passengers

- Canard

- Single Turboprop

- Pusher

- Lower Dihedral wing

(Tail configuration is not specified yet)

[pic]

Figure 16 – Group VI Preliminary Fuselage Design

Why Canard?

The typical aircraft configuration includes all control surfaces aft the main wing. The difference between the horizontal control surface being located forward or aft of the main wing lies in the relative area of the control surface, as well as the location of the center of gravity of the aircraft.

Advantages of Canard

- Stall of the main wing may be virtually eliminated with careful design. The properly designed canard will stall before the main wing, rotating the nose downward and restoring lift as the velocity increases.

- Both the fore and aft surfaces provide lift in the same sense. When properly trimmed they are capable of higher lift-to-drag ratios, having superior range compared with conventional aircraft. The foreplane lift is additive, in the same direction as the wing, helping to rotate the aircraft into the attitude required for lift off, unlike a conventional machine with the tail plane and elevator at the back.

Disadvantages of Canard

- The rear engine location of pusher airplanes is somewhat less desirable than a forward location. The propeller operates in a more turbulent airflow (caused by airflow over the wings), which decreases propeller efficiency.

- The main wing becomes less efficient because it operates in the wake of the canard, thus lowering the available maximum lift.

- Sizing of the canard is more difficult and has a larger effect on the stability of the aircraft than a tail configuration.

Dimension

[pic]

Figure 17 - External Fuselage Dimension

The preliminary dimensions of the six-passenger single turboprop pusher aircraft are shown in Figure 17 above. The numbers are approximate, and may vary depending on engine size. Winglets may also be utilized in the final design, eliminating the need to a vertical tail.

|Group VI Aircraft |　 |Single Turbo Prop Avg. |　 |

|Total Length |35-40ft |Avg. Total Length |34.7 ft |

|Wing Span |40 ft |Avg. Wing Span |43.55 ft |

|Overall Height |17 ft |Avg. Overall Height |N/A |

|Tail Height |12 ft |Avg. Tail Height |12.5 ft |

|Fuselage Height |5 ft |Avg. Fuselage Height |4.8 ft |

|Wing Area |212 ft2 |Avg. Wing Area |228.4 ft2 |

|Cabin Volume |330 ft3 |Avg. Cabin Volume |258 ft3 |

Table 6: Comparison of Group VI Aircraft and Average Single Turboprop Dimensions

As in Table 6 above, the aircraft dimensions are very similar to most other six-to-eight passenger single turboprop aircraft. The main advantage the aircraft has over competing models is the significant increase in cabin volume – an important factor in passenger comfort. However, our aircraft successfully minimizes the total wing dimensions. Therefore, total drag acting on aircraft is the same.

Nose and Tail Dimensions

The fuselage cone is normally a smooth transition from the maximum fuselage cross section to the “end of the fuselage. When the ‘fineness ratio’ of this cone is too low, there will be a large base drag penalty although the fuselage weight may be reduced. When the ‘fineness ratio’ of this cone is too large, there will be a large friction drag penalty as well as a large weight penalty. It will be obvious that a long fuselage cone tends to increase the tail moment arm thereby reducing required tail area and vice versa. The decision on the fuselage cone fineness ratio is given as below.

For Nose Cone

[pic]

Eq .1

For Tail Cone

[pic]

Eq. 2

Based on equations above efficient nose and tail length can be calculated. For our case, since our target D (height of Fuselage) is 5 feet tall, nose cone length should be approximately 10 feet, and Tail cone length should be approximately 15 feet. For canard pusher aircraft case, the engine of the aircraft has to be in the tail section, so that that tail length should be little longer and wider than usual.

Human Factors

For many years the weight of the average man was 170lb (77kg); the western Caucasian male is heavier and bulkier than his pre-World War II counterpart. Racial variations in human size and shape can make a considerable difference to weight and balance calculations and to fuselage proportions. The average weight today is nearer 180lb to 200lb clothed, with deviation of plus or minus 14%. Measurements also vary by plus or minus 5%.

The bulkier the pilot or passenger, the greater the attention must be paid to legroom and space for movement. This should include movement while seated, and the ability to interact with other passengers during flight.

[pic]

Figure 19 - Seat Configuration

Above is the seat configuration of our aircraft. The minimum width of fuselage of fuselage for a single seat (or tandem) airplane is 24-in (0.61m). A side by side arrangement for large occupants must be at least 40-in internally (1.02m), while 42-in (1.1m) is common. The widest and most comfortable cockpit was 47-in (1.2m) internally. The narrowest is 38-in with a mere hand-hitting distance from seat to roof of 34-in (0.87m). If an airplane has a cabin with an aisle between the seats, aisle width should not be less than 6-in (our aircraft aisle width is around 20 to 24-in).

Wing Position

Low-winged airplanes provide a better arrangement when agility is required, because they tend to have good fields of view in the direction of turn and manoeuvre. The wings blanket downward view somewhat in straight and level flight. They generate more favourable ground effect on take off and landing. Low wing structure is also useful anchorage and stowage for landing gear, which can be made shorter and lighter. Deeper spars can often be used, by incorporating them into seat structure, without increasing the depth of fuselage needed for a high winged airplane with a wing of the same thickness.

Cabin Design

Selection of cabin cross section is critical to passenger comfort and to weight and wetted area. The fuselage cross section in Figure 19 is a typical “circular” cabin section which is usually good for pressurization. Because of the human anatomy it will be discovered that the fuselage will become rather bulky. This is the reason why the fuselage cross section of smaller general aviation airplanes is more or less rectangular.

[pic]

Figure 19 – Cross-sectional View of Cabin Configuration

[pic]

Figure 20 - Top View of Cabin Configuration

Typical spacing of each seat is around 34” to 36” for passenger aircraft. As shown in Figure 5, 40” of spacing should provide passengers more legroom and comfort during flight. The thickness of the fuselage is typically 1 to 4 in. This depends on whether the aircraft is pressurized or not.

Cabin Variation

Standard

- 2 pilots

- 6 passengers

- Baggage space in between cockpit and cabin

Maximum:

8 people (w/ baggage)

Executive

- 2 Pilots

- 4 Executive Passengers

- Baggage compartment in between cockpit and cabin.

Maximum:

6 People (w/ baggage)

Economy

- 1 Pilot

- 8 passengers

- No Baggage compartment

Maximum:

9 people (w/o Baggage)

6. Fuel Choice

Alternative Fuels

The group examined the properties of several different alternative fuels for use in twin piston, single turboprop, and twin turbofan driven aircraft. The advantages and disadvantages of the best choices will be discussed below.

Ethanol Blend - AGE85

AGE85 (Aviation Grade Ethanol) is a well established and tested ethanol based alternative fuel. It is specifically blended for cold starting, which makes it an ideal fuel for use in aviation where fuel line and carburetor icing must be avoided. It also burns much cleaner than traditional aviation fuels.

The major disadvantage of AGE85 and other ethanol-based fuels is its dangerous effects on fuel system components. Ethanol may react with seals or lines, causing corrosion. Significant modification of these parts would be necessary if an ethanol based fuel were to be used. Furthermore, ethanol has a lower energy density than traditional aviation based fuels. Lastly, the research with AGE85 has been primary focused on driving piston aircraft performance.

Pure Biodiesel – B100

Biodiesel is made mostly from soybean oils, and contains no petroleum products. Because of this, availability and affordability of biodiesel would not be directly affected by the world-wide petroleum markets. This is an important economic advantage in a situation where petroleum becomes prohibitively expensive. B100 already has a significant production infrastructure, so the availability of the fuel would not be in question. Other advantages of biodiesel include the fact that diesel reduces engine wear, is comparatively safe to store and transport, and has some of the lowest harmful emissions of any of the alternative fuels studied.

There are two major disadvantages for B100. The first is its high freezing and cloud points, as seen in Table 6. This causes problems for both operation and shipping of the fuel. Electric heaters would have to be used on the fuel tanks and engines during storage of the aircraft, and the shipping costs of the fuel would be significantly higher in cold-weather climates. The other major disadvantage is the reduced energy content. As Table 7 shows, the energy density of B100 is almost 18% lower than it is for traditional aviation fuels. Beyond the high freezing point and clouding point, researchers have discovered a problem with using soybean-based biodiesel due to the limitations in growing soybeans fast enough to produce the required fuel needed for the number of flights required.

| |No. 2 Diesel (petrol) |B100 (pure biodiesel) |

|Cloud Point (F) |-9 |35 |

|Pour Point (F) |-17 |32 |

Table 6 – Temperature Characteristics of Alternative Fuels

| |Jet-A |Avgas |No. 2 Diesel (petrol) |B100 (pure biodiesel) |

|Heat of Combustion (Btu/gal) |123099 |115480 |131295 |117093 |

|Density (lb/gal) |6.676 |6.092 |7.079 |7.328 |

|energy density by mass (Btu/lb) |18439 |18956 |18547 |15979 |

Table 7 – Comparison of Alternative Fuels to Existing Fuels

Biodiesel Blend – B20 & others

B20 and other like fuels are blends of petroleum-based diesel fuels with pure biodiesel. Blending biodiesel with petroleum-based diesel relieves some of the problems with pure biodiesel. The freezing point is lower, and the energy density is higher than biodiesel making it a more feasible choice.

However, the production of B20 still involves mostly petroleum. Therefore, B20 can not be considered a renewable fuel, and the price of the fuel would change with the petroleum market, which would be a major disadvantage when petroleum is expensive.

BioJet Fuel

The University of South Dakota is currently developing a bio-matter based fuel that has very desirable properties. Freezing is not a problem for this fuel, as it operates normally down to -75 F. It has very low emissions, and little modification would be needed to run in current turbofan engines. This BioJet fuel would be the ideal choice for an alternatively fueled aircraft.

However, this fuel is only in the experimental phase, and no infrastructure for the production and distribution exists. Designing an aircraft around these obstacles could be a large risk.

Figure 21 summarizes the advantages and disadvantages of each fuel type.

[pic]

Figure 21 - Pros & Cons of Alternative Fuels

After examining the potential alternative fuel options, we have chosen engines with performance ratings similar to the Pratt & Whitney PT6A-42 engines. The PT6A-42 has 850shp and weighs 403 lbs. With our TSFC of .5671, our fuel tanks will hold 200 gallons of fuel weighing approximately 1,350 lbs.

7. Constraint Models

In order to estimate the optimum design values for thrust-to-weight ratio and wing loading for the aircraft, constraint diagrams were constructed using limits for important stages of flight. These included takeoff, landing, cruise, ceiling, maximum range, and minimum power. Equations 5.8, 5.9, 5.11, 5.13, and 5.14 (Raymer) were used in these calculations. The design space is found in the area bounded by the constraint curves. Specifically, the thrust-to-weight ratio must be greater than or equal to any point along the takeoff, cruise, and ceiling curves for a given wing loading. Also, the wing loading must be less than or equal to that required for landing, maximum range, and minimum power.

Several preliminary assumptions have also been made in order to construct these diagrams. Because many of the design parameters have yet to be determined, typical values were taken from the course text. These values are given in Table 8 below. Additionally, it was assumed that engine power decreases with altitude in direct proportion to density.

The constraint diagrams for the three initial concepts are given in Figure 22. The constraints for maximum range and minimum power do not appear in the diagram, as the corresponding wing loadings lie far outside that of the landing constraint. The shaded area of the figure is the design range. Any set of thrust-to-weight ratio and wing loading values within this shaded area will satisfy the design requirements for the aircraft.

| |Turboprop |Turbojet |

|CD0 |.02 |.015 |

|CLmax |1.5 |1.5 |

|e |.8 |.8 |

|ηp |.8 |N/A |

|AR |7.6 |8 |

Table 8 - Parameters Used in Constraint Models

|[pic] |[pic] |

Figure 22 - Constraint Diagrams

8. Aircraft Characteristics and Comparisons

|  |Concept 15 |Socata TBM 700[iv] |Pilatus PC 12[v] |

|GTOW |6800 lb |6578 lb |9920 lb |

|W/S (wing loading) |32 lb/ft2 |33.9 lb/ft2 |lb/ft2 |

|S (wetted wing area) |212 ft2 |193.8 ft2 |277.8 ft2 |

|AR |7.6 |8.97 |9.85 |

|b (wing span) |40 ft 1 in |41ft 7 in |52 ft 3 in |

|P/W (power to weight) - props |P/W = 0.088 |P/W = 0.106 |P/W = 0.121 |

|STO |2100 ft |2133 ft |2300 ft |

|VCruise |250 kts |243 kts |232 kts |

|Acquisition cost |$1.65 million |$ 2 million |$ 2.8 million |

|Direct Operating cost |100LL - $350/hr |$425/hr |$400/hr |

| |Biodiesel - $468/hr | | |

Table 9 - Aircraft Comparison

9. Conclusion

A global market exists for a small to medium sized propeller driven aircraft, primarily aimed at operators such as air taxi services, air charter operations, and corporate flight departments. The market suggests a demand in aircraft capable of carrying six passengers and two crew members on a 600 nautical mile trip. A capability of using runways as short as 2,100 ft will also open a multitude of airports providing more convenient point to point service.

The benefit of such an aircraft will be realized not only in the United States, but in the European and Asian markets as well. An initial design mission is drawn from the customer attributes and subsequent analysis with the QFD matrix. Extensive trade studies were used to justify the design requirements and the ratings given in the Pugh’s Method. The aircraft characteristics of the final concept and competing aircraft are shown in Table 9.

Furthermore, the increasing uncertainty about the future of petroleum based fuels will create a need for alternative means of transportation. The new market will need to offer flexible point-to-point air transportation at low cost and high efficiency. In addition, awareness of global climate change will result in a larger demand for more environmentally friendly fuel sources. This study has determined that the aviation industry will be adaptable to such change, and aircraft represented by Concept 15 will meet the needs of a changing market.

10. Appendix:

1. Jet Trade Study Appendix

Figure 1 – Jet Gross Weight vs. Range and Speed 39

Figure 2 – Jet Acquisition Cost vs. Range and Speed 39

Figure 3 – Jet Gross Weight vs. Range and L/Dmax 40

Figure 4 – Jet Acquisition Cost vs. Range and L/Dmax 40

Figure 5 – Jet Gross Weight vs. Range and SFC 41

Figure 6 – Jet Acquisition Cost vs. Range and SFC 41

Figure 7 – Jet Gross Weight vs. Range and Number of Passengers 42

Figure 8 – Jet Acquisition Cost vs. Range and Number of Passengers 42

Figure 9 – Jet Gross Weight vs. Speed and SFC 43

Figure 10 – Jet Acquisition Cost vs. Speed and SFC 43

Figure 11 – Jet Operating Costs/Hour vs. Range and Speed 44

Figure 12 – Jet Operating Costs/Hour vs. Range and SFC 44

[pic]

Figure 1 – Jet Gross Weight vs. Range and Speed

[pic]

Figure 2 – Jet Acquisition Cost vs. Range and Speed

[pic]

Figure 3 – Jet Gross Weight vs. Range and L/Dmax

[pic]

Figure 4 – Jet Acquisition Cost vs. Range and L/Dmax

[pic]

Figure 5 – Jet Gross Weight vs. Range and SFC

[pic]

Figure 6 – Jet Acquisition Cost vs. Range and SFC

[pic]

Figure 7 – Jet Gross Weight vs. Range and Number of Passengers

[pic]

Figure 8 – Jet Acquisition Cost vs. Range and Number of Passengers

[pic]

Figure 9 – Jet Gross Weight vs. Speed and SFC

[pic]

Figure 10 – Jet Acquisition Cost vs. Speed and SFC

[pic]

Figure 11 – Jet Operating Costs/Hour vs. Range and Speed

[pic]

Figure 12 – Jet Operating Costs/Hour vs. Range and SFC

2. Single Turboprop Trade Study Appendix

Figure 1 – Single Turboprop Gross Weight vs. Range and Speed 46

Figure 2 – Single Turboprop Acquisition Cost vs. Range and Speed 46

Figure 3 – Single Turboprop Gross Weight vs. Range and L/Dmax 47

Figure 4 – Single Turboprop Acquisition Cost vs. Range and L/Dmax 47

Figure 5 – Single Turboprop Gross Weight vs. Range and SFC 48

Figure 6 – Single Turboprop Acquisition Cost vs. Range and SFC 48

Figure 7 – Single Turboprop Gross Weight vs. Range and Number of Passengers 49

Figure 8 – Single Turboprop Acquisition Cost vs. Range and Number of Passengers 49

Figure 9 – Single Turboprop Gross Weight vs. Speed and SFC 50

Figure 10 – Single Turboprop Acquisition Cost vs. Speed and SFC 50

Figure 11 – Single Turboprop Operating Costs/Hour vs. Range and Speed 51

Figure 12 – Single Turboprop Operating Costs/Hour vs. Range and SFC 51

[pic]

Figure 1 – Single Turboprop Gross Weight vs. Range and Speed

[pic]

Figure 2 – Single Turboprop Acquisition Cost vs. Range and Speed

[pic]

Figure 3 – Single Turboprop Gross Weight vs. Range and L/Dmax

[pic]

Figure 4 – Single Turboprop Acquisition Cost vs. Range and L/Dmax

[pic]

Figure 5 – Single Turboprop Gross Weight vs. Range and SFC

[pic]

Figure 6 – Single Turboprop Acquisition Cost vs. Range and SFC

[pic]

Figure 7 – Single Turboprop Gross Weight vs. Range and Number of Passengers

[pic]

Figure 8 – Single Turboprop Acquisition Cost vs. Range and Number of Passengers

[pic]

Figure 9 – Single Turboprop Gross Weight vs. Speed and SFC

[pic]

Figure 10 – Single Turboprop Acquisition Cost vs. Speed and SFC

[pic]

Figure 11 – Single Turboprop Operating Costs/Hour vs. Range and Speed

[pic]

Figure 12 – Single Turboprop Operating Costs/Hour vs. Range and SFC

3. Twin Turboprop Trade Study Appendix

Figure 1 – Twin Turboprop Gross Weight vs. Range and Speed 53

Figure 2 – Twin Turboprop Acquisition Cost vs. Range and Speed 53

Figure 3 – Twin Turboprop Gross Weight vs. Range and L/Dmax 54

Figure 4 – Twin Turboprop Acquisition Cost vs. Range and L/Dmax 54

Figure 5 – Twin Turboprop Gross Weight vs. Range and SFC 55

Figure 6 – Twin Turboprop Acquisition Cost vs. Range and SFC 55

Figure 7 – Twin Turboprop Gross Weight vs. Range and Number of Passengers 56

Figure 8 – Twin Turboprop Acquisition Cost vs. Range and Number of Passengers 56

Figure 9 – Twin Turboprop Gross Weight vs. Speed and SFC 57

Figure 10 – Twin Turboprop Acquisition Cost vs. Speed and SFC 57

Figure 11 – Twin Turboprop Operating Costs/Hour vs. Range and Speed 58

Figure 12 – Twin Turboprop Operating Costs/Hour vs. Range and SFC 58

[pic]

Figure 1 – Twin Turboprop Gross Weight vs. Range and Speed

[pic]

Figure 2 – Twin Turboprop Acquisition Cost vs. Range and Speed

[pic]

Figure 3 – Twin Turboprop Gross Weight vs. Range and L/Dmax

[pic]

Figure 4 – Twin Turboprop Acquisition Cost vs. Range and L/Dmax

[pic]

Figure 5 – Twin Turboprop Gross Weight vs. Range and SFC

[pic]

Figure 6 – Twin Turboprop Acquisition Cost vs. Range and SFC

[pic]

Figure 7 – Twin Turboprop Gross Weight vs. Range and Number of Passengers

[pic]

Figure 8 – Twin Turboprop Acquisition Cost vs. Range and Number of Passengers

[pic]

Figure 9 – Twin Turboprop Gross Weight vs. Speed and SFC

[pic]

Figure 10 – Twin Turboprop Acquisition Cost vs. Speed and SFC

[pic]

Figure 11 – Twin Turboprop Operating Costs/Hour vs. Range and Speed

[pic]

Figure 12 – Twin Turboprop Operating Costs/Hour vs. Range and SFC

4. MATLAB and FLOPS Code Appendix

60. Jet Parameter Setup Function

61. Single Turbo Parameter Setup Function

62. Design Mission Weight Fraction Analyses

63. Constraint Diagram Functions

65. Trade Study Plot Functions

66. FLOPS Input Data – Twin Turboprop

67. FLOPS Input Data – Single Turboprop

68. FLOPS Input Data – VLJ

Note: The functions that generate the plots are long and repetitive, so they are not included in this appendix. They are available in the AAE 451 restricted access folder for Group 6 on the course webpage, in the folder labelled SDR MATLAB Code.

1. Jet Parameter Setup

% Jet Aircraft

clear all

clc

% Aircraft Parameters

Type = 1; % (0 = Prop) (1 = Jet)

np = 6; % Number of Passengers

nc = 2; % Number of Crew

L_Dm = 15; % L/Dmax (Raymer)

Cc = 0.7; % Cruise SFC (Raymer)

Cl = 0.6; % Loiter SFC (Raymer)

w0_g = 9000; % Gross Weight Estimate (lbs)

ar = 8.0; % Aspect Ratio

e = 0.8; % Oswald Efficiency

cdo = 0.015; % Zero Lift Drag

c = Cc; % SFC

clmax = 1.5; % CLmax

altc = 30000; % Cruise Altitude

u = 0.3; % Landing Rolling Friction

% Empty Weight Fraction we/w0 = A*w0^B

A = 1.59; % Raymer

B = -0.10; % Raymer

% Cost Model Constants [Cost = (w0^a)*(R^b)*(V^c)*exp(d)]

a = 1.4532;

b = -1.4285;

c = -0.4833;

d = 12.9303;

% dollars per flight hour

a2 = 1.3726;

b2 = -0.3169;

c2 = -0.3331;

d2 = -2.3700;

Reg(1) = A; Reg2(1) = A;

Reg(2) = B; Reg2(2) = B;

Reg(3) = a; Reg2(3) = a2;

Reg(4) = b; Reg2(4) = b2;

Reg(5) = c; Reg2(5) = c2;

Reg(6) = d; Reg2(6) = d2;

% Mission Parameters

V = 350; % Speed (knots)

R = 600; % Range(nm)

E = 45; % Loiter Time(min)

% Crew and Passenger Weights

wc = 150; % Crew Weight (per person) (lbs)

wct = wc*nc;

wp = 200; % Passenger Weight (per person) (lbs)

wpt = wp*np;

wt = wct + wpt; % Total Crew and Passenger Weight (lbs)

[w0,wf,co] = mission(R,Cc,E,Cl,L_Dm,w0_g,V,wt,Type,Reg);

fprintf('\nAircraft Gross Weight: %.0f lbs\n', w0)

fprintf('\nAircraft Acquisistion Cost: $%.3f million\n\n', co);

2. Single Prop Parameter Setup

% Single Prop Aircraft

clear all

% Aircraft Parameters

Type = 0; % (0 = Prop) (1 = Jet)

np = 6; % Number of Passengers

nc = 2; % Number of Crew

L_Dm = 15; % L/Dmax (Raymer)

Cc = 0.7; % Cruise SFC (Raymer) (lb/hr/bhp)

Cl = 0.6; % Loiter SFC (Raymer) (lb/hr/bhp)

w0_g = 9000; % Gross Weight Estimate (lbs)

ar = 7.6; % Aspect Ratio

e = 0.8; % Oswald Efficiency

cdo = 0.02; % Zero Lift Drag

c = Cc; % SFC

clmax = 1.5; % CLmax

altc = 20000; % Cruise Altitude

u = 0.3; % Landing Rolling Friction

% Empty Weight Fraction [we/w0 = A*w0^B]

A = 0.2705; % Regression

B = 0.0792; % Regression

% Cost Model Constants [Cost = (w0^a)*(R^b)*(V^c)*exp(d)]

a = 1.0693;

b = 0.1149;

d = 0.2657;

c = 0.7100;

% dollars per flight hour

a2 = 0.3762;

b2 = -0.0899;

c2 = 1.2038;

d2 = -3.5266;

Reg(1) = A; Reg2(1) = A;

Reg(2) = B; Reg2(2) = B;

Reg(3) = a; Reg2(3) = a2;

Reg(4) = b; Reg2(4) = b2;

Reg(5) = c; Reg2(5) = c2;

Reg(6) = d; Reg2(6) = d2;

% Mission Parameters

V = 240; % Speed (knots)

R = 600; % Range(nm)

E = 45; % Loiter Time(min)

% Crew and Passenger Weights

wc = 150; % Crew Weight (per person) (lbs)

wct = wc*nc;

wp = 200; % Passenger Weight (per person) (lbs)

wpt = wp*np;

wt = wct + wpt; % Total Crew and Passenger Weight (lbs)

[w0,wf,co] = mission(R,Cc,E,Cl,L_Dm,w0_g,V,wt,Type,Reg);

fprintf('\nAircraft Gross Weight: %.0f lbs\n', w0)

fprintf('\nAircraft Acquisistion Cost: $%.3f million\n\n', co);

3. Design Mission Weight Fraction Analysis

function [w0,wf,co] = mission(R,Cc,E,Cl,L_Dm,w0_g,V,wt,Type,Reg);

% Unit Conversions

V = V.*1.6878; % Speed (ft/sec)

R = R.*6076.1155; % Range (ft)

E = E.*60; % Loiter Time(sec)

% Aircraft Type

if (Type == 0)

% Propeller Aircraft

np = 0.8; % Propeller Efficiency (Raymer)

L_Dc = L_Dm; % Cruise L/D (Raymer)

L_Dl = 0.866.*L_Dm; % Loiter L/D (Raymer)

Cc = Cc.*V./(550.*np)./3600; % Cruise SFC (1/sec)

Cl = Cl.*V./(550.*np)./3600; % Cruise SFC (1/sec)

M = 0.325; % Cruise Mach Number

else

% Turbofan Aircraft

L_Dc = 0.866.*L_Dm; % Cruise L/D (Raymer)

L_Dl = L_Dm; % Loiter L/D (Raymer)

Cc = Cc./3600; % Cruise SFC (1/sec)

Cl = Cl./3600; % Cruise SFC (1/sec)

M = 0.595; % Cruise Mach Number

end

w0_1 = 0;

w0_2 = w0_g;

while (abs(w0_2-w0_1)> 1.0)

w0_1 = w0_2;

w1_w0 = 0.970; % Warmup and Takeoff (Raymer)

w2_w1 = 1.0065-0.0325*M; % Climb (Raymer) 6.9

w3_w2 = exp(-R.*Cc./V./L_Dc); % Berguet Range Equation

w4_w3 = 0.990; % Descent (Raymer)

w5_w4 = 0.990; % Missed Approach (Raymer)

w6_w5 = 0.985; % Climb (Raymer)

w7_w6 = 0.960; % 200nm Cruise (Raymer)

w8_w7 = exp(-E.*Cl./L_Dl); % Endurance Equation

w9_w8 = 0.990; % Descent (Raymer)

w10_w9 = 0.995; % Landing (Raymer)

w10_w0 = w1_w0.*w2_w1.*w3_w2.*w4_w3.*w5_w4.*...

w6_w5.*w7_w6.*w8_w7.*w9_w8.*w10_w9;

wf_w0 = 1.01.*(1-w10_w0); % Fuel Fraction

we_w0 = Reg(1).*w0_1.^Reg(2); % Gross Weight (Estimated)

w0_2 = (wt)./(1-wf_w0-we_w0); % Gross Weight (Calculated)

end

w0 = w0_2; % Gross Weight (Converged)

wf = wf_w0.*w0; % Fuel Weight

V = V./1.6878; R = R./6076.1155;

co = (w0.^Reg(3)).*(R.^Reg(4)).*(V.^Reg(5)).*exp(Reg(6));

co = co./(1e6); % Cost ($Millions)

end

4. Constraint Analysis Generation

% Constraint Analysis

g=32.2; rhosl=.002378;pi=3.14159;

wos= linspace(1,150,150);

k = 1/(pi*ar*e);

emax = 1/(2*sqrt(k*cdo));

% Take-Off Constraint

beta = 1;

alt = 0;

d = 2100;

sigma = density(alt);

alpha = thrust(alt);

towto = (1.1^2)*(beta^2.)*wos/(alpha*sigma*rhosl*g*clmax*d);

% Cruise Speed Constraint

beta = 1;

alt = altc;

v = V;

v = v*1.6878;

sigma = density(alt);

alpha = thrust(alt);

q = 0.5*sigma*rhosl*(v^2.);

towc = (beta/alpha)*(q*cdo./(beta*wos)+ k*beta*wos/q);

% Cruise Altitude Constraint

beta = 1;

alt = altc;

sigma = density(alt);

alpha = thrust(alt);

towa = beta/(emax*alpha)*ones(size(wos));

% Landing

beta = 1;

alt = 0;

sigma = density(alt);

rhol = rhosl*sigma;

wosl = g*d*rhol*clmax*u/((1.15^2)*beta);

towl = linspace(0,0.5,500);

figure()

hold all

plot(wos,towto)

plot(wos,towc)

plot(wos,towa)

plot(wosl,towl,'-c')

axis([0 75 0 0.5])

title(' Constraint Analysis ')

xlabel(' W/S - Wing Loading (lb/ft^2)')

ylabel(' T/W - Thrust to Weight Ratio ')

legend('Take-Off','Cruise Speed','Cruise Altitude','Landing')

grid on;

function alpha=thrust(h)

% **** Thrust model ****

% returns the ratio of thrust to sea level thrust

alpha = density(h);

function sigma=density(altitude)

% note sigma returns sigma ratio - sigma

% calculate properties for the standard atmosphere

Ts=518.69;

rhos=.0023769;

Ps=2116.2;

g0=32.2;

R=1716.;

a1=-.00356;

h1=36150;

T1=389.99;

a2=.001631;

h2=82300;

if (altitudeh1 & altitudeh2)

T= T1 + a2*(altitude-h2);

sigma1=(T1/Ts).^(-(g0/(a1*R)+1));

sigma2=exp(-g0/(R*T1)*(h2-h1))*sigma1;

sigma=(T/T1).^(-(g0/(a2*R)+1))*sigma2;

return

end

end

5. Trade Study Plot Generation

% Trade Studies

close all

% Plot Generation (0 = No) (1 = Yes)

Plot1 = 0; % Trade Study (Range and Speed)

Plot2 = 0; % Trade Study (Range and L/Dmax)

Plot3 = 0; % Trade Study (Range and SFC)

Plot4 = 0; % Trade Study (Range and Number of Passengers)

Plot5 = 0; % Trade Study (Speed and SFC)

Plot6 = 0; % Trade Study (Fuel Weight vs. Range and Speed)

Plot7 = 0; % Trade Study (DOC vs. Range and Speed)

Plot8 = 0; % Trade Study (DOC vs. Range and SFC)

Plot20 = 0; % Variation Study

% Variation of Parameters

Rs = linspace(400,800,20); % Range(nm)

Vs = 200:25:350; % Speed (knots)

Ccs = 0.3:0.1:0.8; % Cruise SFC (lb/hr/bhp)

L_Dms = 10:2.5:17.5; % L/Dmax

nps = 2:1:8; % Number of Passengers

wp = 200; % Passenger Weight (per person) (lbs)

wpts = nps.*wp;

wts = wct + wpts; % Total Crew and Passenger Weight (lbs)

% Trade Studies

if(Plot1 == 1);rv(Rs,Cc,E,Cl,L_Dm,w0_g,Vs,wt,Type,Reg);else;end;

if(Plot2 == 1);rld(Rs,Cc,E,Cl,L_Dms,w0_g,V,wt,Type,Reg);else;end;

if(Plot3 == 1);rSFC(Rs,Ccs,E,Cl,L_Dm,w0_g,V,wt,Type,Reg);else;end;

if(Plot4 == 1);rwt(Rs,Cc,E,Cl,L_Dm,w0_g,V,wts,Type,Reg);else;end;

if(Plot5 == 1);vSFC(R,Ccs,E,Cl,L_Dm,w0_g,Vs,wt,Type,Reg);else;end;

if(Plot6 == 1);w_wf(Rs,Cc,E,Cl,L_Dm,w0_g,Vs,wt,Type,Reg);else;end;

if(Plot7 == 1);doc_rv(Rs,Cc,E,Cl,L_Dm,w0_g,Vs,wt,Type,Reg2);else;end;

if(Plot8 == 1);doc_rSFC(Rs,Ccs,E,Cl,L_Dm,w0_g,V,wt,Type,Reg2);else;end;

% Variation Study

N = 100; % Number of Variations per Parameter

dv = 0.5; % Variation Range (+/-) Fraction

dvh = 1+dv; dvl = 1-dv;

Rs = linspace(dvl*R,dvh*R,N); % Range(nm)

Vs = linspace(dvl*V,dvh*V,N); % Speed (knots)

Ccs = linspace(dvl*Cc,dvh*Cc,N); % Cruise SFC (lb/hr/bhp)

L_Dms = linspace(dvl*L_Dm,dvh*L_Dm,N); % L/Dmax

nps = linspace(dvl*np,dvh*np,N); % Number of Passengers

wpts = nps.*wp;

wts = wct + wpts; % Total Crew and Passenger Weight (lbs)

wt = [wt wct];

if(Plot20 == 1);

var(R,Rs,V,Vs,Cc,Ccs,L_Dm,L_Dms,wt,wts,E,Cl,w0_g,Type,Reg);

else;end;

% Note: The functions that generate these plots are long and repetitive, so they are not included in this appendix. They are available in the AAE 451 restricted access folder for Group 6 on the course webpage, in the folder labeled SDR Matlab Code.

FLOPS Model Generation:

Twin Turboprop Input

TWIN TURBOPROP EXAMPLE for AAE 451, Spring 2006

Run a full analysis including costs - caution, costs may not be accurate for

twin turboprop

$OPTION

IOPT=1, IANAL=3, ICOST=1,

$END

Enter fuselage dimensions assume all pax

are first class, use two wing-mounted engines

Tails are specified with volume coefficients and default parameters

Empty weight reduced, appears FLOPS equations over-predict twin turboprop

$WTIN

WF=5.0, DF=5.0, XL=35.5,

FPITCH=24., NFABR=1, NTABR=0, NEW=2,

NEF=0, FULFMX=2573.,NPF=6, NPT=0, NFLCR=2, NSTU=0, NGALC=0,

THRSO=550., EWMARG=-0.1,FCOMP=1.,

$END

Maintain constant wing loading, thrust/weight ratio, and

modified tail volume coefficients based on existing twin turboprop.

$CONFIN

GW=10000.0, DESRNG=800.,

AR=8.5, WSR=35., TWR=.30,

TCA=.14, TR=0.44, SWEEP=0.,

HTVC=0.975, VTVC=0.1,

VCMN=0.5, CH=5000.,

$END

Moderate technology wing

$AERIN

AITEK=1., FLTO=2100.,

$END

Calculate cost information, starting development year 2006, fuel price Feb 2006

use 100 percent first class seating, production run 300 a/c

$COSTIN

DEVST=2006., DYEAR=2006, FUELPR=3.50, NPOD=2, PLMQT=2014., Q=300.,

$END

Generate engine deck in cycle analysis module and

extrapolate to get consistent flight idle data

$ENGDIN

IDLE=1, IGENEN=1, MAXCR=1, NGPRT=0,

$END

Generate a turboprop engine, use default prop performance via ETAPRP

$ENGINE

IENG=4, IPRINT=0,

OPRDES=29.5, TETDES=2660.0, ETAPRP=0.840, SHPOWA=60.0,

$END

Size aircraft for specified range, fly minimum fuel-to-climb,

optimum altitude for cruise Mach, and max L/D descent

$MISSIN

IFLAG=2, IRW=1,

TAXOTM=10., TAKOTM=0.4, TAXITM=10., TIMMAP=5.,

ITTFF=1, FWF=-1., RESRFU=0.05, THOLD=.05,

$END

START

CLIMB

CRUISE

DESCENT

END

Single Turboprop Input

SINGLE TURBOPROP EXAMPLE for AAE 451, Spring 2006

Run a full analysis including costs - caution, costs may not be accurate for

twin turboprop

$OPTION

IOPT=1, IANAL=3, ICOST=1,

$END

Enter fuselage dimensions assume all pax

are first class, use two wing-mounted engines

Tails are specified with volume coefficients and default parameters

Empty weight reduced, appears FLOPS equations over-predict twin turboprop

$WTIN

WF=5.0, DF=5.0, XL=47.25,

FPITCH=24., NFABR=1, NTABR=0, NEW=0,

NEF=1, FULWMX=23.,NPF=6, NPT=0, NFLCR=2, NSTU=0, NGALC=0,

THRSO=500., EWMARG=-.05,FCOMP=1.,NETAW = 1,HHT = 1.,

$END

Maintain constant wing loading, thrust/weight ratio, and

modified tail volume coefficients based on existing twin turboprop.

$CONFIN

GW=10000.0, DESRNG=600.,

AR=10.2, WSR=35., TWR=.195,

TCA=.14, TR=0.44, SWEEP=0.,

HTVC=0.975, VTVC=0.1,

VCMN=0.4, CH=20000.,

$END

Moderate technology wing

$AERIN

AITEK=1.5, FLTO=2100.,

$END

Calculate cost information, starting development year 2006, fuel price Feb 2006

use 100 percent first class seating, production run 300 a/c

$COSTIN

DEVST=2006., DYEAR=2006, FUELPR=3.50, NPOD=2, PLMQT=2014., Q=300.,

$END

Generate engine deck in cycle analysis module and

extrapolate to get consistent flight idle data

$ENGDIN

IDLE=1, IGENEN=1, MAXCR=1, NGPRT=0,

$END

Generate a turboprop engine, use default prop performance via ETAPRP

$ENGINE

IENG=4, IPRINT=0,

OPRDES=29.5, TETDES=2660.0, ETAPRP=0.840, SHPOWA=60.0,

$END

Size aircraft for specified range, fly minimum fuel-to-climb,

optimum altitude for cruise Mach, and max L/D descent

$MISSIN

IFLAG=2, IRW=1,

TAXOTM=10., TAKOTM=0.4, TAXITM=10., TIMMAP=5.,

ITTFF=1, FWF=-1., RESRFU=0.05, THOLD=.05,

$END

START

CLIMB

CRUISE

DESCENT

END

Very Light Jets Input

SUBSONIC VL JET EXAMPLE for AAE 451, Spring 2006

Run a full analysis including costs

$OPTION

IOPT=1, IANAL=3, ICOST=1,

$END

Enter fuselage dimensions assume all pax

are first class, use two fuselage-mounted engines

Tails are specified with volume coefficients and default parameters

$WTIN

WF=6.0, DF=6.0, XL=50.0,

FPITCH=24., NFABR=1, NTABR=0,

NEF=2, FULWMX=29.,NPF=6, NPT=0, NFLCR=2, NSTU=0, NGALC=0,

THRSO=7000.,

$END

Maintain constant wing loading, thrust/weight ratio, and

modified tail volume coefficients.

$CONFIN

GW=18000.0, DESRNG=2000.,

AR=8., WSR=50., TWR=.40,

TCA=.11, TR=0.27, SWEEP=25.,

HTVC=1.6, VTVC=0.2,

VCMN=0.74, CH=41000.,

$END

Moderate technology wing

$AERIN

AITEK=1.5, FLTO=2100.,

$END

Calculate cost information, starting development year 2006, fuel price Feb 2006

use 100 percent first class seating, production run 300 a/c

$COSTIN

DEVST=2006., DYEAR=2006, FUELPR=3.50, NPOD=2, PLMQT=2014., Q=300.,

$END

Generate engine deck in cycle analysis module and

extrapolate to get consistent flight idle data

$ENGDIN

IDLE=1, IGENEN=1, MAXCR=1, NGPRT=0,

$END

Generate a separate flow turbofan with two compressor

components and let the optimum bypass ratio be computed

$ENGINE

IENG=2, IPRINT=0,

OPRDES=29.5, FPRDES=1.67, TETDES=2660.0,

$END

Size aircraft for specified range, fly minimum fuel-to-climb,

optimum altitude for cruise Mach, and max L/D descent

$MISSIN

IFLAG=2, IRW=1,

TAXOTM=10., TAKOTM=0.4, TAXITM=10., TIMMAP=5.,

ITTFF=1, FWF=-1., RESRFU=0.05, THOLD=.05,

$END

START

CLIMB

CRUISE

DESCENT

END

[pic][pic][pic]

-----------------------

12. References

[i] Eclipse 500 specifications:



[ii] Citation Mustang specifications:

!*35¡¢£­®¹º»¼ØÙÚõêõêõßõßõêõнõ²•}•l_T_*[pic]B*[iv]OJQJU[pic]phÿhTchê/?OJQJhTchê/?0JOJQJ!jhTchê/?0JOJQJU[pic]/hTchê/?5?CJOJQJaJmHnHsH tH 8jhTchê/?5?CJOJQJU[pic]aJmHnHsH tH hÉBh-#5

[v] Pilatus PC12 specifications:



[vi] Corporate aursearch international inc



[vii] Wikipedia



13. Merit Pool

|Team Member |Merit |

|John Collins |15.5 |

|Chad Davis |13.5 |

|Chris Fles |12.5 |

|Danny Sze Ling Lim |14.5 |

|Justin Rohde |13.5 |

|Ryan Schulz |0 |

|Ronald Wong |15.5 |

|Yusaku Yamashita |15.0 |

|Total |100 |

-----------------------

Table 5 - Pugh's Method, 2nd Iteration

Table 4 - Pugh's Method, 1st Iteration

(a) Concept 1

(b) Concept 13

(c) Concept 15

Figure 1 - Design Mission Profile

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