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Match each statement with the correct term.
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1. What is the notation for a standard normal distribution?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
M&S environment is needed to facilitate rapid assessments with minimal time and monetary expenditures of the alternative concepts identified in the Morphological Matrix Method: DoE
X~N(0 -1)
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P

2. What is the goal of probabilistic design?

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3. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
No way to tell without more information. It depends on the relation between s12+s22 and s32
OEC = W1X/Xbsl + W2Nbsl/N
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

4. What is TRL? Range? What does a high TRL mean?
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Sample size is 4 - the sample is the sum of the five dice.
M&S environment is needed to facilitate rapid assessments with minimal time and monetary expenditures of the alternative concepts identified in the Morphological Matrix Method: DoE

5. Write down a formula for a normal distribution
Central limit theorem
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn

6. Direct Operating Costs
CDF= ?_(-8)^8
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Range is always between zero and 1 monotonically increasing
Central limit theorem

7. Why do we use a sample?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Range: Gives the magnitude of the spread - min and max - Variance: Indicates how spread out the data is - Skewness: Indicates if the distribution is biased - Kurtosis: Peakness
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

8. MODM
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P
F(x)=1/(s(2p)^(.5) )exp?(-(x-
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

9. What does CDF stand for?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Cumulative Distribution Function
Does not have a natural zero - is a cardinal scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

10. TIES Step 6: Identify Technology
To analytically answer 'How much design margin is really necessary?'
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn

11. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
P(between B and A)=F(B)-F(A)
Regions 1 to 3.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

12. What is the goal of robust design?

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13. TIES Step 7: Assess Technology
OEC = W1X/Xbsl + W2Nbsl/N
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Determine the design space - baseline Method: Morphological Matrix
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

14. How is inflation measured?

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15. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
Select final tech comb. For any multi attribute - constraint - or criteria problem - the selection of the 'best' family of alternatives is inherently subjective. Various selection techniques are used to provide decision maker with extensive info. Met
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

16. If you have a two values on a CDF what is the probability of getting a value between them?
No way to tell without more information. It depends on the relation between s12+s22 and s32
RDTE - Investment/Acquisition - Operations and Support - Disposal
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
P(between B and A)=F(B)-F(A)

17. What are the different types of UTEs?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean =0 Variance =1
Active UTE (additive) - Product UTE (multiplicative)

18. What is the difference between price and cost?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
CDF= ?_(-8)^8

19. What is the definition of CDF?
Mean and variance
Range is always between zero and 1 monotonically increasing
It gives the probability that a value will be met or exceeded.
No way to tell without more information. It depends on the relation between s12+s22 and s32

20. Other than infusing technologies - how can you create design space?
X~N(0 -1)
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
X+Y and X-Y are normally distributed. - (X
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)

21. Assumptions Used in TOPSis...
Mean and variance
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Sample size is 4 - the sample is the sum of the five dice.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

22. Weaknesses of TOPSis...
Does not have a natural zero - is a cardinal scale
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
As you add n number of identical & independent distributions (IIDs) together - as n --> inf - the resulting distribution will be normal - regardless of the shape of the IIDs
is bottom- up - you look at certain technologies and see what improvements they offer

23. What is the definition of ROI?
Technology space limits
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
The interest i such that 0=PE(i^)

24. 8 Steps in TIES
Technique for Order Preference by Similarity to Ideal Solution
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology

25. What is satisficing - what is optimizing?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Mean and variance
X~N(0 -1)
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.

26. What is TCM? What is the size and what value can it take?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each

27. TIES Step 8: Selecting Technology

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28. What is the definition of inflation?
To analytically answer 'How much design margin is really necessary?'
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Optimizing - finds the set of criteria that maximizes or minimizes a design criteria or several design criteria - Satisficing - finds the conditions where the constraints or requires are met but no optimization occurs.
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available

29. TIES Step 4: Investigate Design Space
Trying to determine the metric values for any combination of design variables/ what the metrics are as a function of design variables Method: RSE: Response Surface Eqn.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

30. Show and explain a pareto frontier
Cumulative Distribution Function
A pareto frontier represents points of a non - dominated solution based on preferences
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
P(between B and A)=F(B)-F(A)

31. interval scale
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Does not have a natural zero - is a cardinal scale
A probability density contour plot is a visualization method for Joint probability density function (a 2D representation). Their shapes (contour shapes) tell if the metric analyzed in each axis are correlated or not (Circular -> no correlation) (elli

32. MADM
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
The interest i such that 0=PE(i^)
Has a natural zero - is a cardinal scale
A technique that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.

33. 3 Measures of Central Tendency (& Defs)
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Determine the design space - baseline Method: Morphological Matrix
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

34. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P
Select final tech comb. For any multi attribute - constraint - or criteria problem - the selection of the 'best' family of alternatives is inherently subjective. Various selection techniques are used to provide decision maker with extensive info. Met
Gaussian Distribution

35. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
Determine the design space - baseline Method: Morphological Matrix
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

36. What does CLT stand for?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Central limit theorem
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem

37. Ratio scale
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Has a natural zero - is a cardinal scale
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Technology Readiness Level Ranges 1-9 - where 1 means that the basic principle have been observed and reported and 9 means the technology has had successful missions A high tech means the technology is pretty developed and should be (or is) ready for

38. TIES Step 1: Problem Definition
The interest i such that 0=PE(i^)
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn
Range: Gives the magnitude of the spread - min and max - Variance: Indicates how spread out the data is - Skewness: Indicates if the distribution is biased - Kurtosis: Peakness
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

39. What are the three snapshots of UTE?
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P
Active UTE (additive) - Product UTE (multiplicative)
Does not have a natural zero - is a cardinal scale
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

40. What is the normal distribution that results from adding x+y and x[sub]y?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

41. Does TIES use MADM or MODM? Why?
Scaling parameters photographically scale the size of the vehicle to take full advantage of technology -(e.g. increase CL -> Can decrease S -> Decreases D -> Decreases Fuel Consumed -> etc...) This assumes that the physics of the problem remains the
Mean =0 Variance =1
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

42. Define fixed cost and variable cost.
OEC = W1X/Xbsl + W2Nbsl/N
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
Does not have a natural zero - is a cardinal scale

43. What is another name for a normal distribution?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
The interest i such that 0=PE(i^)
Gaussian Distribution
Regions 1 to 3.

44. What are properties of a CDF?
The interest i such that 0=PE(i^)
Range is always between zero and 1 monotonically increasing
Mean =0 Variance =1
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P

45. TIES Step 2: Design Space Conception
M&S environment is needed to facilitate rapid assessments with minimal time and monetary expenditures of the alternative concepts identified in the Morphological Matrix Method: DoE
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Technique for Order Preference by Similarity to Ideal Solution
Determine the design space - baseline Method: Morphological Matrix

46. TIES Step 3: Model and Simulation
(1) Identify potential technologies that may improve technical & economical feasibility (2) Establish physical compatibility rules for diff techs (3) Determine expected impact (improvements and degradations) to systems of interest Method: TRL - Techn
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Range: Gives the magnitude of the spread - min and max - Variance: Indicates how spread out the data is - Skewness: Indicates if the distribution is biased - Kurtosis: Peakness
M&S environment is needed to facilitate rapid assessments with minimal time and monetary expenditures of the alternative concepts identified in the Morphological Matrix Method: DoE

47. What are K- factors applied to?
Technology space limits
Technology Compatability Matrix - For n techs - is nxn matrix - Tells whether the intersecting technologies are compatible - It only has 0s and 1s - 0 means the technologies are not compatible with each other - 1 means techs are compatible with each
(1) Problem def - (2) Design space conception (3) Model and Simulation (4) Investigate Design Space (5) Feasible? (6) Identify Technologies (7) Evaluate Technologies (8) Select Technology
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

48. 3 Probabilistic Design Methods
Inflation is the decrease in the buying power/value of money. It is caused by the when amount of available money changes wrt amount of product/services available
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
(1) Mission Requirements - Input: Mission metrics and requirements Output: Delta response for requirements (2) Design Variables - Input: Geometric and economic design variables Output: Delta response for design variable - (3) Technologies Input: P

49. What can be done about uncertainty in requirement?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Central limit theorem
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
F(x)=1/(s(2p)^(.5) )exp?(-(x-

50. What is the equation for the learning curve?
Range: Gives the magnitude of the spread - min and max - Variance: Indicates how spread out the data is - Skewness: Indicates if the distribution is biased - Kurtosis: Peakness
A pareto frontier represents points of a non - dominated solution based on preferences
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cumulative Distribution Function