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Test your basic knowledge |
ADM
Start Test
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 the definition of ROI?
The interest i such that 0=PE(i^)
Has a natural zero - is a cardinal scale
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
(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
2. 4 Measures of Dispersion
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
Active UTE (additive) - Product UTE (multiplicative)
Determine the design space - baseline Method: Morphological Matrix
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
3. Strengths of TOPSis...
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
(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) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
4. What does CDF stand for?
It can be continuous or discrete
is bottom- up - you look at certain technologies and see what improvements they offer
Technique for Order Preference by Similarity to Ideal Solution
Cumulative Distribution Function
5. Write down a formula for 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
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
F(x)=1/(s(2p)^(.5) )exp?(-(x-
Range is always between zero and 1 monotonically increasing
6. What is TIM? What is the size and what value can it take?
7. What is the definition of inflation?
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
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
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
Has a natural zero - is a cardinal scale
8. What are the parameters for a standard normal distribution?
Determine the design space - baseline Method: Morphological Matrix
The interest i such that 0=PE(i^)
PE(i)=?Ft
Mean =0 Variance =1
9. Why is learning curve used (or what is it?)
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) End result not intuitive (2) Heavily reliant on weights - which are subjective
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 space limits
10. How do you get the CDF from the PDF?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
X~N(0 -1)
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.
CDF= ?_(-8)^8
11. TIES
Technique for Order Preference by Similarity to Ideal Solution
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
is bottom- up - you look at certain technologies and see what improvements they offer
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
12. What is the goal of probabilistic design?
13. Direct Operating Costs
Technology space limits
Cost required to perform a function - without which the function cannot be performed. (e.g. fuel costs - pilot wages)
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
14. What are K- factors applied to?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
Technology space limits
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.
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.
15. TIES Step 6: Identify Technology
Technology space limits
(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
It can be continuous or discrete
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
16. What is another name for a normal distribution?
Is top- down - you aren't looking at specific technologies - you're just looking at what you need in the future
Gaussian Distribution
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
Range is always between zero and 1 monotonically increasing
17. Does TIES use MADM or MODM? Why?
A technique used to determine the best alternative with all interactions between the constraints. Used for product design.
Mean =0 Variance =1
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
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
18. What is the notation for a standard normal distribution?
P(between B and A)=F(B)-F(A)
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~N(0 -1)
Mean and variance
19. 3 Measures of Central Tendency (& Defs)
RDTE - Investment/Acquisition - Operations and Support - Disposal
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: the average - Median: The midpoint in the data - equal # of higher and lower values - Mode: Most common value
Does not have a natural zero - is a cardinal scale
20. What is satisficing - what is optimizing?
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) 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
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
Carry a diverse portfolio of technologies during conceptual design - Limit the number of technologies in the final design - Utilize only mature technologies (high TRL)
21. 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?
Sample size is 4 - the sample is the sum of the five dice.
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Fixed cost does not depend on production rate and/or size - Variable cost changes with production rate and/or size.
Has a natural zero - is a cardinal scale
22. $/RPM Equation
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
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.
(1) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
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
23. What is TRL? Range? What does a high TRL mean?
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
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
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Technology space limits
24. TIES Step 8: Selecting Technology
25. What is TCM? What is the size and what value can it take?
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
(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
(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
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
26. What can be done about uncertainty in requirement?
(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.
Regions 1 to 3.
RDTE - Investment/Acquisition - Operations and Support - Disposal
27. If you have two compatible mature technologies to infuse - or one not mature technology - which will have the most variance?
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.
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
28. What does TOPSIS stand for?
Technique for Order Preference by Similarity to Ideal Solution
#=2^n = 2^15
Technology Impact Matrix - for n tech & m metrics of interest - nxm matrix - has 'k' factor with degradation/improvement from baseline
(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
29. What is the definition of CDF?
It gives the probability that a value will be met or exceeded.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
(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
Central limit theorem
30. What are properties of a CDF?
RDTE - Investment/Acquisition - Operations and Support - Disposal
Range is always between zero and 1 monotonically increasing
#=2^n = 2^15
X~N(0 -1)
31. What are the different types of UTEs?
Active UTE (additive) - Product UTE (multiplicative)
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
Efficiency improves as better techniques are learned. As more efficient techniques are found - the learning curve begins to level off as incremental improvements decrease.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
32. What does the CLT state - be specific!
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
#=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
33. TIES Step 2: Design Space Conception
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.
Mean and variance
Determine the design space - baseline Method: Morphological Matrix
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
34. TIES Step 5: Feasible?
OEC = W1X/Xbsl + W2Nbsl/N
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
Central limit theorem
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
35. What does CLT stand for?
CDF= ?_(-8)^8
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
Central limit theorem
Determining how feasible your design is / if your current baseline (or a variation in geometry) can meet your customer requirements. Method: Monte Carlo
36. 8 Steps in TIES
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.
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
(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
It can be continuous or discrete
37. What is the equation for OEC if X is a benefit (maximize) and N is a cost (minimize)?
Technology space limits
OEC = W1X/Xbsl + W2Nbsl/N
The interest i such that 0=PE(i^)
Gaussian Distribution
38. What is probability density contour plot
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
(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?'
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
39. What are the four difference life cycle costs?
Sample size is 4 - the sample is the sum of the five dice.
(1) Easy to compute order of large # of alternatives (2) Gives specific ranking order
RDTE - Investment/Acquisition - Operations and Support - Disposal
MADM - since we are selecting from existing alternatives for technology infusion. Also - TOPSIS is a MADM technique.
40. What is the equation for the learning curve?
OEC = W1X/Xbsl + W2Nbsl/N
y = kx^n - y: production effort k: effort for first unit x: # of units n: learning factor
Consumer Price Index (CPI) measures the cost of an average 'basket of goods' a typical consumer would purchase.
Cumulative Distribution Function
41. Show and explain a pareto frontier
A pareto frontier represents points of a non - dominated solution based on preferences
It gives the probability that a value will be met or exceeded.
X~N(0 -1)
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
42. TIES Step 7: Assess Technology
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.
Regions 1 to 3.
Identified techs are now applied to the vehicle concepts and evaluated. Evaluation provided data/info to the decision - maker. Method: RSE: Response Surface Eqn.
43. What is the normal distribution that results from adding x+y and x[sub]y?
Convenient properties - Various physical - astronomic - and real life examples have roughly 'normal' behaviors - good approximation for measurements due to central limit theorem
Technique for Order Preference by Similarity to Ideal Solution
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.
X+Y and X-Y are normally distributed. - (X
44. Name the advantages of UTE.
P(between B and A)=F(B)-F(A)
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.
Required yield per revenue passenger TOC/(#OfSeats)(loadFactor)(distanceInMiles) loadFactor = % of seats filled w/ paying customers
Technology space limits
45. Weaknesses of TOPSis...
OEC = W1X/Xbsl + W2Nbsl/N
Technique for Order Preference by Similarity to Ideal Solution
X+Y and X-Y are normally distributed. - (X
(1) End result not intuitive (2) Heavily reliant on weights - which are subjective
46. interval scale
X~N(0 -1)
(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
Central limit theorem
47. What is the difference between price and cost?
Cost: investment required to produce and item - Price: amount required to purchase said item - Price = cost + profit/fee
(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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
The interest i such that 0=PE(i^)
48. What is the goal of robust design?
49. 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
Look at multiple weight scenarios and find techs that are robust regardless of where the emphasis is put.
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) Expanding ranges on engineering metrics (2) Relaxing customer requirements (3) Select a different concept space
50. With 15 technologies - what is the number of possible combinations?
To analytically answer 'What can be done to reduce the impact of sensitivities of objective to sources of uncertainty?'
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
#=2^n = 2^15
OEC = W1X/Xbsl + W2Nbsl/N