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ADM
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Study First
Subject
:
engineering
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 is TRL? Range? What does a high TRL mean?
To analytically answer 'How much design margin is really necessary?'
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 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
Range is always between zero and 1 monotonically increasing
2. What does CDF stand for?
Cumulative Distribution Function
The interest i such that 0=PE(i^)
X+Y and X-Y are normally distributed. - (X
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
3. What is TCM? What is the size and what value can it take?
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 'How much design margin is really necessary?'
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 that determines the best alternative based on a multi- attribute utlity function which is closest to hypothetical best solution. Used for product selection.
4. What are K- factors applied to?
Technology space limits
To analytically answer 'How much design margin is really necessary?'
X~N(0 -1)
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
5. What is the normal distribution that results from adding x+y and x[sub]y?
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
Technology space limits
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
6. TIES Step 4: Investigate Design Space
Gaussian 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
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.
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
7. What is the goal of robust design?
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8. 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.
No way to tell without more information. It depends on the relation between s12+s22 and s32
Sample size is 4 - the sample is the sum of the five dice.
9. 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
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
(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
To analytically answer 'How much design margin is really necessary?'
10. How is inflation measured?
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11. What is TIM? What is the size and what value can it take?
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12. Name two uncertainties accounted for by UTE. What metric does UTE use to quantify this risk?
#=2^n = 2^15
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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
13. Define fixed cost and variable cost.
It gives the probability that a value will be met or exceeded.
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
F(x)=1/(s(2p)^(.5) )exp?(-(x-
14. 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.
Gaussian Distribution
X+Y and X-Y are normally distributed. - (X
CDF= ?_(-8)^8
15. Why are scaling parameters important?
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
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
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
16. TIES
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
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)
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
17. Why is the normal distribution useful or important?
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18. Why use uniform dist for input variables (Gap Analysis)
OEC = W1X/Xbsl + W2Nbsl/N
Gaussian Distribution
Central limit theorem
Allows designer to assess feasibility of design
19. Assumptions Used in TOPSis...
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Cumulative Distribution Function
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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.
20. 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
Has a natural zero - is a cardinal scale
A pareto frontier represents points of a non - dominated solution based on preferences
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
21. $/RPM Equation
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
X+Y and X-Y are normally distributed. - (X
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
(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
22. How do you get the CDF from the PDF?
CDF= ?_(-8)^8
RDTE - Investment/Acquisition - Operations and Support - Disposal
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
23. Weaknesses of TOPSis...
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
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 used to determine the best alternative with all interactions between the constraints. Used for product design.
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
24. 3 Probabilistic Design Methods
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
Chosen alternative should be closest to positive ideal soln - and farthest from neg ideal soln
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) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
25. TIES Step 3: Model and Simulation
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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
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
26. In what regions of the graph is UTE applicable?
Regions 1 to 3.
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
(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
27. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
OEC = W1X/Xbsl + W2Nbsl/N
A sample is a subset of a population. We use samples because we very rarely have the resources to test/examine an entire population
To analytically answer 'How much design margin is really necessary?'
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
28. What is the difference between price and cost?
Technology space limits
A pareto frontier represents points of a non - dominated solution based on preferences
Sample size is 4 - the sample is the sum of the five dice.
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
29. TIF
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30. TIES Step 1: Problem Definition
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
The first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
31. Does TIES use MADM or MODM? Why?
(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.
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
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
32. What is the notation for a standard normal distribution?
Technology space limits
P(between B and A)=F(B)-F(A)
X~N(0 -1)
(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. What is probability density contour plot
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
Gaussian Distribution
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
34. What two variables are necessary to define a normal distribution?
(1) Sophisticated Analysis Code + Monte Carlo (2) Metamodel/Response Surface + Monte Carlo (3) Sophisticated Analysis Code + Fast Probability Integration
X~N(0 -1)
Mean and variance
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
35. 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
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
Technology Impacts Requirements uncertainty (creep/change) - Quantified by probability of success/satisfaction: P(success)
36. Indirect Operating Cost
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
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 related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
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
37. 4 Measures of Dispersion
Mean =0 Variance =1
It gives the probability that a value will be met or exceeded.
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
Central limit theorem
38. What are the four difference life cycle costs?
F(x)=1/(s(2p)^(.5) )exp?(-(x-
RDTE - Investment/Acquisition - Operations and Support - Disposal
Cost related to function - but not explicitly necessary. (e.g. attendant wages - advertising)
P(between B and A)=F(B)-F(A)
39. What is the definition of CDF?
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
It gives the probability that a value will be met or exceeded.
40. 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
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
RDTE - Investment/Acquisition - Operations and Support - Disposal
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
41. What is the definition of ROI?
The interest i such that 0=PE(i^)
Has a natural zero - is a cardinal scale
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 pareto frontier represents points of a non - dominated solution based on preferences
42. Is CDF discrete or continuous - if it is discrete give the continuous equivalent - if it continuous give the discrete equivalent.
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.
Active UTE (additive) - Product UTE (multiplicative)
It can be continuous or discrete
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
43. TIES Step 5: Feasible?
OEC = W1X/Xbsl + W2Nbsl/N
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
Gaussian Distribution
44. MODM
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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 technique used to determine the best alternative with all interactions between the constraints. Used for product design.
To analytically answer 'How much design margin is really necessary?'
45. What are properties of a CDF?
P(between B and A)=F(B)-F(A)
X~N(0 -1)
Range is always between zero and 1 monotonically increasing
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
46. What is satisficing - what is optimizing?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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.
47. What are the three snapshots of UTE?
No way to tell without more information. It depends on the relation between s12+s22 and s32
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
(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
48. Write down a formula for a normal distribution
F(x)=1/(s(2p)^(.5) )exp?(-(x-
(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 first step is defining the problem - mapping customer requirements to engineering metrics. Method: QFD
Mean: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
49. What can management do to mitigate the risk associated with infusing new technologies?
Allows designer to assess feasibility of design
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
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 pareto frontier represents points of a non - dominated solution based on preferences
50. What are the parameters for a standard normal distribution?
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.
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Mean =0 Variance =1
Sample size is 4 - the sample is the sum of the five dice.