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1. What is probability density contour plot
It gives the probability that a value will be met or exceeded.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

2. What is the definition of CDF?
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
To analytically answer 'How much design margin is really necessary?'
It gives the probability that a value will be met or exceeded.
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

3. What does CLT stand for?
Central limit theorem
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
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
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'

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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

5. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
P(between B and A)=F(B)-F(A)

6. 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
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.
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
Cumulative Distribution Function

7. What is satisficing - what is optimizing?
is bottom- up - you look at certain technologies and see what improvements they offer
CDF= ?_(-8)^8
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.
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

8. TIES Step 7: Assess Technology
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 and variance
The interest i such that 0=PE(i^)
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

9. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
It can be continuous or discrete
OEC = W1X/Xbsl + W2Nbsl/N
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

10. Define fixed cost and variable cost.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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.
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
RDTE - Investment/Acquisition - Operations and Support - Disposal

11. 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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

12. In what regions of the graph is UTE applicable?
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
A pareto frontier represents points of a non - dominated solution based on preferences
Regions 1 to 3.
PE(i)=?Ft

13. Show and explain a pareto frontier
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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
A pareto frontier represents points of a non - dominated solution based on preferences

14. Why is learning curve used (or what is it?)
Mean =0 Variance =1
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.
PE(i)=?Ft

15. What are K- factors applied to?
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Technology space limits
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

16. TIES Step 8: Selecting Technology

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17. TIES Step 2: Design Space Conception
Determine the design space - baseline Method: Morphological Matrix
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
It gives the probability that a value will be met or exceeded.
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

18. What is the goal of probabilistic design?

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19. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
X+Y and X-Y are normally distributed. - (X
Mean and variance
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
No way to tell without more information. It depends on the relation between s12+s22 and s32

20. 8 Steps in TIES
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
X+Y and X-Y are normally distributed. - (X
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
(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

21. What can be done about uncertainty in requirement?
(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
No way to tell without more information. It depends on the relation between s12+s22 and s32
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

22. Strengths of TOPSis...
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
#=2^n = 2^15
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

23. MADM
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.
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
(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
X~N(0 -1)

24. 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
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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

25. Why are scaling parameters important?
Does not have a natural zero - is a cardinal scale
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
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

26. How do you get the CDF from the PDF?
The interest i such that 0=PE(i^)
CDF= ?_(-8)^8
Allows designer to assess feasibility of design
Mean and variance

27. What can management do to mitigate the risk associated with infusing new technologies?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
It can be continuous or discrete
The interest i such that 0=PE(i^)
Cumulative Distribution Function

28. 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
Does not have a natural zero - is a cardinal scale
RDTE - Investment/Acquisition - Operations and Support - Disposal
Technology space limits

29. What does TOPSIS stand for?
is bottom- up - you look at certain technologies and see what improvements they offer
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Gaussian Distribution
Technique for Order Preference by Similarity to Ideal Solution

30. What are properties of a CDF?
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
is bottom- up - you look at certain technologies and see what improvements they offer
Range is always between zero and 1 monotonically increasing

31. Ratio scale
To analytically answer 'How much design margin is really necessary?'
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Has a natural zero - is a cardinal scale
OEC = W1X/Xbsl + W2Nbsl/N

32. TIES Step 5: Feasible?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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
(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

33. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
P(between B and A)=F(B)-F(A)
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
Allows designer to assess feasibility of design

34. Weaknesses of TOPSis...
It can be continuous or discrete
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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
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

35. If you have a two values on a CDF what is the probability of getting a value between them?
Technology space limits
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 sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
P(between B and A)=F(B)-F(A)

36. What is the definition of inflation?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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
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.

37. What two variables are necessary to define a normal distribution?
It gives the probability that a value will be met or exceeded.
Mean and variance
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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

38. What is another name for a normal distribution?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
No way to tell without more information. It depends on the relation between s12+s22 and s32
Gaussian Distribution
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.

39. Direct Operating Costs
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Active UTE (additive) - Product UTE (multiplicative)
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order

40. What is the equation for the learning curve?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Determine the design space - baseline Method: Morphological Matrix
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
RDTE - Investment/Acquisition - Operations and Support - Disposal

41. What are the four difference life cycle costs?
RDTE - Investment/Acquisition - Operations and Support - Disposal
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Central limit theorem

42. 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
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
Sample size is 4 - the sample is the sum of the five dice.

43. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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.

44. 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)
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
Has a natural zero - is a cardinal scale

45. What is the difference between price and cost?
Cumulative Distribution Function
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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

46. interval scale
(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
Has a natural zero - is a cardinal scale
Does not have a natural zero - is a cardinal scale
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

47. TIES Step 3: Model and Simulation
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
PE(i)=?Ft
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

48. What does CDF stand for?
X~N(0 -1)
Range is always between zero and 1 monotonically increasing
Cumulative Distribution Function
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

49. TIES Step 4: Investigate Design Space
X+Y and X-Y are normally distributed. - (X
RDTE - Investment/Acquisition - Operations and Support - Disposal
Determine the design space - baseline Method: Morphological Matrix
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.

50. Name the advantages of UTE.
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.
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.
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

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