ADM

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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. Why is the normal distribution useful or important?

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2. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
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


3. What is the goal of robust design?

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4. What is the goal of probabilistic design?

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5. What are the different types of UTEs?
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
The interest i such that 0=PE(i^)
A pareto frontier represents points of a non - dominated solution based on preferences
Active UTE (additive) - Product UTE (multiplicative)


6. What is probability density contour plot
Active UTE (additive) - Product UTE (multiplicative)
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
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
It gives the probability that a value will be met or exceeded.


7. 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
Regions 1 to 3.
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.


8. 3 Probabilistic Design Methods
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Determine the design space - baseline Method: Morphological Matrix
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
It can be continuous or discrete


9. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Gaussian Distribution
Sample size is 4 - the sample is the sum of the five dice.


10. $/RPM Equation
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
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


11. Assumptions Used in TOPSis...
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
To analytically answer 'How much design margin is really necessary?'
RDTE - Investment/Acquisition - Operations and Support - Disposal
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln


12. Direct Operating Costs
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
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) 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. What are the three snapshots of UTE?
A pareto frontier represents points of a non - dominated solution based on preferences
(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
The interest i such that 0=PE(i^)
#=2^n = 2^15


14. Why do we use a sample?
Active UTE (additive) - Product UTE (multiplicative)
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
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


15. 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)
X~N(0 -1)
Allows designer to assess feasibility of 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


16. What does CDF stand for?
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.
Cumulative Distribution Function
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
Sample size is 4 - the sample is the sum of the five dice.


17. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
Cumulative Distribution Function
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
It can be continuous or discrete
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


18. TIF

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19. Write down a formula for a normal distribution
(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-
Has a natural zero - is a cardinal scale
Sample size is 4 - the sample is the sum of the five dice.


20. TIES Step 8: Selecting Technology

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21. 8 Steps in TIES
Regions 1 to 3.
(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
No way to tell without more information. It depends on the relation between s12+s22 and s32
Has a natural zero - is a cardinal scale


22. Strengths of TOPSis...
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
#=2^n = 2^15


23. Name the advantages of UTE.
is bottom- up - you look at certain technologies and see what improvements they offer
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.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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


24. What does the CLT state - be specific!
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
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
OEC = W1X/Xbsl + W2Nbsl/N


25. MADM
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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 Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)


26. How is inflation measured?

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27. Other than infusing technologies - how can you create design space?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
It gives the probability that a value will be met or exceeded.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space


28. Why use uniform dist for input variables (Gap Analysis)
X~N(0 -1)
Allows designer to assess feasibility of design
RDTE - Investment/Acquisition - Operations and Support - Disposal
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)


29. What are the four difference life cycle costs?
(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
X+Y and X-Y are normally distributed. - (X
RDTE - Investment/Acquisition - Operations and Support - Disposal
Determine the design space - baseline Method: Morphological Matrix


30. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
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
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.


31. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
Has a natural zero - is a cardinal scale
Central limit theorem
It gives the probability that a value will be met or exceeded.


32. What are properties of a CDF?
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.
RDTE - Investment/Acquisition - Operations and Support - Disposal
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective


33. What is the definition of ROI?
Mean and variance
F(x)=1/(s(2p)^(.5) )exp?(-(x-
No way to tell without more information. It depends on the relation between s12+s22 and s32
The interest i such that 0=PE(i^)


34. What is the normal distribution that results from adding x+y and x[sub]y?
X~N(0 -1)
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
X+Y and X-Y are normally distributed. - (X
P(between B and A)=F(B)-F(A)


35. TIES Step 4: Investigate Design Space
No way to tell without more information. It depends on the relation between s12+s22 and s32
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.
#=2^n = 2^15
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.


36. Why are scaling parameters important?
Range is always between zero and 1 monotonically increasing
P(between B and A)=F(B)-F(A)
Gaussian Distribution
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


37. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
No way to tell without more information. It depends on the relation between s12+s22 and s32
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
OEC = W1X/Xbsl + W2Nbsl/N


38. What are K- factors applied to?
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.
Technology space limits
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
#=2^n = 2^15


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

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40. 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
OEC = W1X/Xbsl + W2Nbsl/N
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
Mean and variance


41. In what regions of the graph is UTE applicable?
(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
Regions 1 to 3.
P(between B and A)=F(B)-F(A)
X~N(0 -1)


42. What is another name for a normal 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.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. 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


43. What is the definition of inflation?
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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) 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


44. What is the notation for a standard normal distribution?
Central limit theorem
X~N(0 -1)
(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.


45. Why is learning curve used (or what is it?)
P(between B and A)=F(B)-F(A)
It gives the probability that a value will be met or exceeded.
Mean and variance
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.


46. What is the equation for present equivalent value? Define variables.
A pareto frontier represents points of a non - dominated solution based on preferences
PE(i)=?Ft
Allows designer to assess feasibility of design
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


47. 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?
PE(i)=?Ft
Technique for Order Preference by Similarity to Ideal Solution
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


48. What can be done about uncertainty in requirement?
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
#=2^n = 2^15
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
The interest i such that 0=PE(i^)


49. MODM
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
Has a natural zero - is a cardinal scale
CDF= ?_(-8)^8
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.


50. Does TIES use MADM or MODM? Why?
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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-
Cumulative Distribution Function