Test your basic knowledge |

ADM

Instructions:

Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can study here.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.

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. What two variables are necessary to define a normal distribution?
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
No way to tell without more information. It depends on the relation between s12+s22 and s32
Mean and variance
It can be continuous or discrete

2. With 15 technologies - what is the number of possible combinations?
#=2^n = 2^15
X~N(0 -1)
Central limit theorem
To analytically answer 'How much design margin is really necessary?'

3. 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) 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
Cumulative Distribution Function

4. TIES Step 8: Selecting Technology

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

5. What is the definition of CDF?
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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
It gives the probability that a value will be met or exceeded.
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)

6. Why is learning curve used (or what is it?)
Mean =0 Variance =1
OEC = W1X/Xbsl + W2Nbsl/N
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

7. How do you get the CDF from the PDF?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
F(x)=1/(s(2p)^(.5) )exp?(-(x-
CDF= ?_(-8)^8

8. Why do we use a sample?
#=2^n = 2^15
Range is always between zero and 1 monotonically increasing
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

9. $/RPM Equation
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
#=2^n = 2^15
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers

10. Name the advantages of UTE.
Regions 1 to 3.
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.
A technique used to determine the best alternative with all interactions between the constraints. Used for product 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.

11. What is the equation for present equivalent value? Define variables.
PE(i)=?Ft
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
P(between B and A)=F(B)-F(A)
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.

12. TIF

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

13. What is probability density contour plot
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.
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.
Mean =0 Variance =1

14. What does TOPSIS stand for?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Technique for Order Preference by Similarity to Ideal Solution
It can be continuous or discrete

15. TIES Step 7: Assess Technology
(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
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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
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. Assumptions Used in TOPSis...
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
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
No way to tell without more information. It depends on the relation between s12+s22 and s32
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln

17. 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)
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
CDF= ?_(-8)^8

18. 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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Range is always between zero and 1 monotonically increasing
P(between B and A)=F(B)-F(A)

19. MODM
X+Y and X-Y are normally distributed. - (X
#=2^n = 2^15
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.

20. interval scale
Does not have a natural zero - is a cardinal scale
Central limit theorem
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(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

21. 4 Measures of Dispersion
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
(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. TIES Step 4: Investigate Design Space
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
It can be continuous or discrete
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.
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value

23. Define fixed cost and variable cost.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

24. 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?
A pareto frontier represents points of a non - dominated solution based on preferences
Regions 1 to 3.
Sample size is 4 - the sample is the sum of the five dice.
Technique for Order Preference by Similarity to Ideal Solution

25. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Determine the design space - baseline Method: Morphological Matrix
OEC = W1X/Xbsl + W2Nbsl/N
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

26. What are the four difference life cycle costs?
A pareto frontier represents points of a non - dominated solution based on preferences
RDTE - Investment/Acquisition - Operations and Support - Disposal
Regions 1 to 3.
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.

27. TIES Step 6: Identify Technology
#=2^n = 2^15
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
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) 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

28. What is the definition of ROI?
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
Has a natural zero - is a cardinal scale
The interest i such that 0=PE(i^)
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)

29. What is the normal distribution that results from adding x+y and x[sub]y?
X+Y and X-Y are normally distributed. - (X
PE(i)=?Ft
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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.

30. What can be done about uncertainty in requirement?
(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
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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.

31. What are properties of a CDF?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Range is always between zero and 1 monotonically increasing
The interest i such that 0=PE(i^)
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.

32. Indirect Operating Cost
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
(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
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.

33. Ratio scale
Has a natural zero - is a cardinal scale
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
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.
It gives the probability that a value will be met or exceeded.

34. TIES Step 1: Problem Definition
Cumulative Distribution Function
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
Mean =0 Variance =1

35. What are the parameters for a standard normal distribution?
Mean =0 Variance =1
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.

36. 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
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
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

37. Does TIES use MADM or MODM? Why?
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
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
Does not have a natural zero - is a cardinal scale

38. 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
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
PE(i)=?Ft

39. Write down a formula for a normal distribution
Central limit theorem
(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-
is bottom- up - you look at certain technologies and see what improvements they offer

40. TIES Step 3: Model and Simulation
A pareto frontier represents points of a non - dominated solution based on preferences
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
X+Y and X-Y are normally distributed. - (X
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population

41. What are K- factors applied to?
Technology space limits
is bottom- up - you look at certain technologies and see what improvements they offer
Central limit theorem
To analytically answer 'How much design margin is really necessary?'

42. Other than infusing technologies - how can you create design space?
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
PE(i)=?Ft
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space

43. 3 Probabilistic Design Methods
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Sample size is 4 - the sample is the sum of the five dice.

44. What does CLT stand for?
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Central limit theorem
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
Technology space limits

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

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

46. TIES
Gaussian Distribution
is bottom- up - you look at certain technologies and see what improvements they offer
Cumulative Distribution Function
CDF= ?_(-8)^8

47. Show and explain a pareto frontier
The interest i such that 0=PE(i^)
Active UTE (additive) - Product UTE (multiplicative)
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

48. What is the goal of probabilistic design?

Warning: Invalid argument supplied for foreach() in /var/www/html/basicversity.com/show_quiz.php on line 183

49. What is TCM? What is the size and what value can it take?
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
X+Y and X-Y are normally distributed. - (X
RDTE - Investment/Acquisition - Operations and Support - Disposal
Mean and variance

50. In what regions of the graph is UTE applicable?
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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Regions 1 to 3.
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.