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1. TIES Step 8: Selecting Technology

2. Name the advantages of UTE.
Allows designer to assess feasibility of design
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.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

3. Write down a formula for a normal distribution
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Gaussian Distribution
X~N(0 -1)
F(x)=1/(s(2p)^(.5) )exp?(-(x-

4. What is the goal of probabilistic design?

5. What is satisficing - what is optimizing?
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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

6. What does CDF stand for?
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
Cumulative Distribution Function

7. Strengths of TOPSis...
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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.

8. What is the equation for present equivalent value? Define variables.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
PE(i)=?Ft

9. 3 Measures of Central Tendency (& Defs)
Cumulative Distribution Function
(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
(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
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

10. MODM
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
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.

11. What are the different types of UTEs?
Mean and variance
Active UTE (additive) - Product UTE (multiplicative)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Mean =0 Variance =1

12. Direct Operating Costs
Has a natural zero - is a cardinal scale
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
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

13. $/RPM Equation
Does not have a natural zero - is a cardinal scale
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Active UTE (additive) - Product UTE (multiplicative)

14. Why do we use a sample?
Central limit theorem
Has a natural zero - is a cardinal scale
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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

15. What is the notation for a standard normal distribution?
CDF= ?_(-8)^8
X~N(0 -1)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

16. In what regions of the graph is UTE applicable?
It gives the probability that a value will be met or exceeded.
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Regions 1 to 3.
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD

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

18. Assumptions Used in TOPSis...
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
#=2^n = 2^15
Has a natural zero - is a cardinal scale

19. What two variables are necessary to define a normal distribution?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Technology space limits
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.
Mean and variance

20. TIF

21. What is the equation for the learning curve?
Range is always between zero and 1 monotonically increasing
No way to tell without more information. It depends on the relation between s12+s22 and s32
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor

22. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(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.

23. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
X+Y and X-Y are normally distributed. - (X
Central limit theorem
A pareto frontier represents points of a non - dominated solution based on preferences

24. Other than infusing technologies - how can you create design space?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)

25. Ratio scale
Has a natural zero - is a cardinal scale
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Regions 1 to 3.
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

26. What are K- factors applied to?
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
Central limit theorem
Gaussian Distribution
Technology space limits

27. What is the definition of ROI?
The interest i such that 0=PE(i^)
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
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.

28. TIES
is bottom- up - you look at certain technologies and see what improvements they offer
Regions 1 to 3.
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
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo

29. What does the CLT state - be specific!
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

30. 3 Probabilistic Design Methods
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration

31. How is inflation measured?

32. TIES Step 2: Design Space Conception
Cumulative Distribution Function
Determine the design space - baseline Method: Morphological Matrix
RDTE - Investment/Acquisition - Operations and Support - Disposal
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

33. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Regions 1 to 3.

34. What is the normal distribution that results from adding x+y and x[sub]y?
X+Y and X-Y are normally distributed. - (X
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
PE(i)=?Ft

35. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
No way to tell without more information. It depends on the relation between s12+s22 and s32
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
OEC = W1X/Xbsl + W2Nbsl/N
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

36. What is probability density contour plot
Does not have a natural zero - is a cardinal scale
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
Gaussian Distribution
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

37. If you have a two values on a CDF what is the probability of getting a value between them?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
P(between B and A)=F(B)-F(A)
(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
Mean and variance

38. What can be done about uncertainty in requirement?
OEC = W1X/Xbsl + W2Nbsl/N
RDTE - Investment/Acquisition - Operations and Support - Disposal
Regions 1 to 3.
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

39. What is the difference between price and cost?
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(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

40. 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
is bottom- up - you look at certain technologies and see what improvements they offer
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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

41. 8 Steps in TIES
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.
#=2^n = 2^15
(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

42. 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.
Range is always between zero and 1 monotonically increasing
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
#=2^n = 2^15

43. 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.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
PE(i)=?Ft

44. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
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?'
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

45. What is TCM? What is the size and what value can it take?
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.
#=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

46. TIES Step 3: Model and Simulation
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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
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

47. What are the parameters for a standard normal distribution?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Mean =0 Variance =1
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

48. Does TIES use MADM or MODM? Why?
X+Y and X-Y are normally distributed. - (X
P(between B and A)=F(B)-F(A)
#=2^n = 2^15
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

49. What are the three snapshots of UTE?
Technique for Order Preference by Similarity to Ideal Solution
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.
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) 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

50. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
A pareto frontier represents points of a non - dominated solution based on preferences
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
CDF= ?_(-8)^8
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective