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This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.

1. 3 Probabilistic Design Methods
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
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.
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.


2. Show and explain a pareto frontier
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
A pareto frontier represents points of a non - dominated solution based on preferences
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.


3. TIES
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
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
is bottom- up - you look at certain technologies and see what improvements they offer
X~N(0 -1)


4. Weaknesses of TOPSis...
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Does not have a natural zero - is a cardinal scale
Allows designer to assess feasibility of design
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


5. In what regions of the graph is UTE applicable?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
P(between B and A)=F(B)-F(A)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Regions 1 to 3.


6. What is the goal of robust design?

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7. TIES Step 5: Feasible?
P(between B and A)=F(B)-F(A)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo


8. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Allows designer to assess feasibility of design
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


9. What is probability density contour plot
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
It can be continuous or discrete
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
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


10. What is TCM? What is the size and what value can it take?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Range is always between zero and 1 monotonically increasing
Allows designer to assess feasibility of design
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


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

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12. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
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
Has a natural zero - is a cardinal scale
No way to tell without more information. It depends on the relation between s12+s22 and s32


13. TIF

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14. What is another name for a normal distribution?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Gaussian Distribution
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


15. Name the advantages 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
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.
Determine the design space - baseline Method: Morphological Matrix
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.


16. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
P(between B and A)=F(B)-F(A)
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


17. $/RPM Equation
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.


18. TIES Step 6: Identify Technology
Allows designer to assess feasibility of design
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
(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
The interest i such that 0=PE(i^)


19. TIES Step 1: Problem Definition
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.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
OEC = W1X/Xbsl + W2Nbsl/N
P(between B and A)=F(B)-F(A)


20. interval scale
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
Does not have a natural zero - is a cardinal scale
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
PE(i)=?Ft


21. 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
is bottom- up - you look at certain technologies and see what improvements they offer
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)


22. What is the normal distribution that results from adding x+y and x[sub]y?
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
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)
X+Y and X-Y are normally distributed. - (X


23. How is inflation measured?

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24. MODM
(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
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
Mean =0 Variance =1
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


25. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
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.
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
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD


26. What is TRL? Range? What does a high TRL mean?
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
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
Active UTE (additive) - Product UTE (multiplicative)
(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


27. If you have a two values on a CDF what is the probability of getting a value between them?
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.
Central limit theorem
X+Y and X-Y are normally distributed. - (X


28. TIES Step 3: Model and Simulation
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Regions 1 to 3.


29. What is the definition of inflation?
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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Determine the design space - baseline Method: Morphological Matrix


30. 3 Measures of Central Tendency (& Defs)
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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
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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


31. What does CDF stand 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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Cumulative Distribution Function
(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


32. 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.
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 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


33. Does TIES use MADM or MODM? Why?
Gaussian Distribution
Has a natural zero - is a cardinal scale
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.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.


34. What are the four difference life cycle costs?
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Technology space limits
RDTE - Investment/Acquisition - Operations and Support - Disposal


35. TIES Step 4: Investigate Design Space
Regions 1 to 3.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


36. With 15 technologies - what is the number of possible combinations?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
#=2^n = 2^15
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.


37. What are properties of a CDF?
The interest i such that 0=PE(i^)
Gaussian Distribution
No way to tell without more information. It depends on the relation between s12+s22 and s32
Range is always between zero and 1 monotonically increasing


38. Indirect Operating Cost
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
(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)


39. 8 Steps in TIES
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
It can be continuous or discrete
(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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.


40. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
#=2^n = 2^15
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.


41. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
(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
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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.


42. What are the three snapshots of UTE?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
(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^n = 2^15
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


43. MADM
Allows designer to assess feasibility of design
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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.


44. Other than infusing technologies - how can you create design space?
Technique for Order Preference by Similarity to Ideal Solution
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Cumulative Distribution Function
To analytically answer 'How much design margin is really necessary?'


45. Why are scaling parameters important?
#=2^n = 2^15
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
X~N(0 -1)


46. What does CLT stand for?
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
Central limit theorem
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


47. What can management do to mitigate the risk associated with infusing new technologies?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
CDF= ?_(-8)^8
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


48. 4 Measures of Dispersion
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.
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
Gaussian Distribution
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


49. Why use uniform dist for input variables (Gap Analysis)
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
Allows designer to assess feasibility of design
RDTE - Investment/Acquisition - Operations and Support - Disposal


50. Why is the normal distribution useful or important?

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