ADM

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1. What is probability density contour plot
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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
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
(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


2. How do you get the CDF from the PDF?
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
To analytically answer 'How much design margin is really necessary?'
CDF= ?_(-8)^8


3. What is the definition of ROI?
The interest i such that 0=PE(i^)
(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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
CDF= ?_(-8)^8


4. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD


5. Show and explain a pareto frontier
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
A pareto frontier represents points of a non - dominated solution based on preferences
Technique for Order Preference by Similarity to Ideal Solution


6. What is the goal of robust design?

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7. Name the advantages of UTE.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


8. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Mean =0 Variance =1
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.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem


9. With 15 technologies - what is the number of possible combinations?
PE(i)=?Ft
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
#=2^n = 2^15
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population


10. 3 Measures of Central Tendency (& Defs)
Has a natural zero - is a cardinal scale
It can be continuous or discrete
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
F(x)=1/(s(2p)^(.5) )exp?(-(x-


11. Indirect Operating Cost
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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


12. What are the three snapshots of UTE?
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.
Sample size is 4 - the sample is the sum of the five dice.
CDF= ?_(-8)^8
(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


13. Weaknesses of TOPSis...
P(between B and A)=F(B)-F(A)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Sample size is 4 - the sample is the sum of the five dice.


14. What does CLT stand for?
#=2^n = 2^15
It can be continuous or discrete
Central limit theorem
Active UTE (additive) - Product UTE (multiplicative)


15. 4 Measures of Dispersion
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-


16. $/RPM Equation
(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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.
Active UTE (additive) - Product UTE (multiplicative)


17. What can be done about uncertainty in requirement?
P(between B and A)=F(B)-F(A)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
PE(i)=?Ft


18. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
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
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
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.


19. TIES Step 4: Investigate Design Space
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.
Mean and variance
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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.


20. TIES Step 3: Model and Simulation
(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
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
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
F(x)=1/(s(2p)^(.5) )exp?(-(x-


21. What is the definition of inflation?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
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


22. What is the equation for present equivalent value? Define variables.
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
PE(i)=?Ft
#=2^n = 2^15
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.


23. 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
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Cumulative Distribution Function


24. What two variables are necessary to define a normal distribution?
Cumulative Distribution Function
No way to tell without more information. It depends on the relation between s12+s22 and s32
Mean and variance
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.


25. What are the four difference life cycle costs?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
RDTE - Investment/Acquisition - Operations and Support - Disposal
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
No way to tell without more information. It depends on the relation between s12+s22 and s32


26. What does CDF stand for?
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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Cumulative Distribution Function
Active UTE (additive) - Product UTE (multiplicative)


27. What is the difference between price and cost?
Has a natural zero - is a cardinal scale
It gives the probability that a value will be met or exceeded.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.


28. TIES
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Provide for rapid trade- off capability between the three elements and search for feasible solutions - Allow graphical visualization of the combined space - Address mission requirements ambiguity and technology uncertainty.
OEC = W1X/Xbsl + W2Nbsl/N
is bottom- up - you look at certain technologies and see what improvements they offer


29. What is satisficing - what is optimizing?
Range is always between zero and 1 monotonically increasing
OEC = W1X/Xbsl + W2Nbsl/N
Allows designer to assess feasibility of design
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.


30. 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)
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
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


31. Why is the normal distribution useful or important?

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32. TIES Step 6: Identify Technology
(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
Sample size is 4 - the sample is the sum of the five dice.
(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
The interest i such that 0=PE(i^)


33. What is the notation for a standard normal distribution?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
X~N(0 -1)
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.
(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


34. TIES Step 5: Feasible?
Cumulative Distribution Function
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Technology space limits


35. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
(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
OEC = W1X/Xbsl + W2Nbsl/N
Central limit theorem


36. What is TRL? Range? What does a high TRL mean?
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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
X+Y and X-Y are normally distributed. - (X
Mean =0 Variance =1


37. You have a group of 5 dice. You roll the groups and sum the results of the 5 dice 4 times. What is the sample size? What are you sampling?
To analytically answer 'How much design margin is really necessary?'
Sample size is 4 - the sample is the sum of the five dice.
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


38. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
It can be continuous or discrete
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
To analytically answer 'How much design margin is really necessary?'
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


39. Why are scaling parameters important?
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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


40. What does TOPSIS stand for?
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Technique for Order Preference by Similarity to Ideal Solution


41. Define fixed cost and variable cost.
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
Range is always between zero and 1 monotonically increasing
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


42. What is the goal of probabilistic design?

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43. Why is learning curve used (or what is it?)
The interest i such that 0=PE(i^)
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor


44. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
Range is always between zero and 1 monotonically increasing
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline


45. TIF

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46. In what regions of the graph is UTE applicable?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Does not have a natural zero - is a cardinal scale
Regions 1 to 3.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


47. TIES Step 7: Assess Technology
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Mean =0 Variance =1
RDTE - Investment/Acquisition - Operations and Support - Disposal


48. What is TIM? What is the size and what value can it take?

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49. Does TIES use MADM or MODM? Why?
is bottom- up - you look at certain technologies and see what improvements they offer
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Does not have a natural zero - is a cardinal scale


50. Ratio scale
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Has a natural zero - is a cardinal scale
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.