with your host…
Dr. Hyland
426, Lecture 2 - Questions Addressed
What are the life-cycle phases of a space mission and which phase and
point of view will we consider?
What are some systematic approaches to space system design and
analysis?
What approach will we take and what are the steps involved?
How will the class be organized to carry out these steps and what is
the schedule of events?
Suggested reading:
L&W, Chapter 1 (and Chaps. 2 and 3 for more detail)
The Space Mission Life Cycle - Four Phases
Concept exploration: The initial study phase that results in a broad
definition of the mission and its components
Detailed development: The formal design phase which results in a
detailed definition of the system components and, in larger programs,
development of test hardware or software.
Production and deployment: The construction of the ground and
flight hardware and launch of the first full constellation of satellites.
Operations and support: The day-to-day operation of the space
system, its maintenance and support, and finally its de-orbit or
recovery at the end of the mission life.
Various parties & constituencies:
Sponsor: The group that provides and controls the program budget
Operators: The group (typically an applied engineering organization) that
controls and maintains the space and ground assets
End users: Groups who receive and use the products and capability of the
space mission
Developer: The procuring agent, e.g. DOD, NASA or a commercial enterprise
In this class, we concentrate on the Concept Exploration Phase from the
point of view of the Contractor - Developer
Space Mission Analysis and Design Process
- The Eightfold Path Typical
Flow
Phase
Define
Objectives
Step
A. Define broad objectives and
constraints.
B. Estimate quantitative needs
and requirements.
Characterize
the Mission
C. Define alternative mission
concepts.
D. Identify system drivers for
each.
E. Characterize mission
concepts.
Evaluate the
Mission
F. Identify driving
requirements.
G. Evaluate mission utility
H. Define mission concept
(baseline)
Step A: Define Broad Objectives and Constraints
• Define what the mission needs to achieve. What are our
qualitative goals and why?
• The qualitative goals are summarized in the Mission
Statement - a 3 to 4 sentence, crisp and cogent statement
of overall goals.
• This is the all-important starting point. We need to
repeatedly refer back to the Mission Statement to ensure
we remain "on track".
• Usually, missions have several objectives. Besides the
primary objectives, there may be secondary objectives
that can be met by the defined set of equipment, or
additional objectives that may demand more equipment.
•Almost always, missions have a hidden agenda - which consists of secondary nontechnical, objective, frequently of a political, social or cultural nature.
Example:
To forestall existential threats to humanity, our mission is to develop self-sustaining,
self-propelled space habitats based on realistic technology. (Some hidden agendas:
Boost space activity, encourage public interest and support for space exploration,
imply economic benefits, etc.)
Step B: Estimate Quantitative Mission Needs and Requirements
•In contrast to Step A, this quantifies how well we wish to achieve the
broad objectives, given our needs, applicable technology and cost
constraints.
•These quantitative requirements should be subject to trade as we go
along. In the early stages of design, it is very important not to set
these requirements "in concrete".
•To transform mission objectives into requirements, look at three broad
areas:
oFunctional requirements, which define how well the system
must perform to meet its objectives.
oOperational requirements, which determine how the system operates and how
users interact with it to achieve its broad objectives.
oConstraints, which limit cost, schedule and implementation techniques
available to the system designer.
•Establishing top-level mission requirements is extremely difficult. Therefore,
we should be prepared to iterate the numerical requirements many times in the
design process.
•The first estimate of requirements should come from the goals and objectives
combined with some view of what is feasible. Then be prepared to iterate.
•Also, look at the "hidden agenda", which contains the implicit goals and
constraints.
Quantitative requirements – Interplanetary Vehicle / Space
habitat design
Example:
Habitat population capacity
=?
Amount of artificial gravity provided =?
Radiation shielding capability = ?
Resource extraction capability = ?
Total V capability without refueling = ?
Step C: Define Alternative Mission Concepts
As used here (as distinct from the usage in Larson and Wertz) a mission concept or
architecture is a broad sketch of how the mission will work plus a definition of each
of the principal components of a space mission:
Subject: The thing that interacts with or is sensed by the space payload.
Spacecraft or Space Segment: The self-contained portion that resides in space to carry out
the mission long-term, comprising:
Payload: The hardware and software that sense or interact with the subject.
Spacecraft Bus: Subsystems that support the payload by providing orbit and
attitude maintenance, power, command, telemetry and data handling, structure
and rigidity and temperature control.
Launch System: Includes the launch facility, launch vehicle and any upper stage
required to put the spacecraft in orbit as well as interfaces payload fairing and
ground support.
Orbit: The spacecraft's trajectory or path. Usually, there is an initial parking orbit, a
transfer orbit and final mission orbit.
Communications Architecture: The arrangement of components that satisfy the
mission's command, control and communication (C3) requirements.
Ground System: Fixed or mobile ground stations used to command and track the
s/c, receive and process data and distribute the information to operators and users.
Mission Operations and Timeline: The overall strategy and schedule for planning,
building, deployment, operations, replacement and end-of-life.
Process for Identifying Alternative Mission Concepts
Five Steps:
1. Identify the mission elements subject to trade
2. Identify the main options for each tradeable element
3. Construct a trade tree of available options.
4. Prune the trade tree by eliminating unrealistic combinations.
5. Look for other alternatives that could substantially influence how
we do the mission
Trade Tree – Basic Concept (illustrated by the manned asteroid mission )
Mission Phase
Alternatives for each mission phase
Launch
single
vehicle
Launchto-orbit
Earth
orbit to
Asteroid
vicinity
Proximity
Operations
Chemical
propulsion
Standoff
mode
Separate
vehicle and
crew
Low
thrust
Landing
mode
Chemical
propulsion
Assemble
mission onorbit
Low
thrust
Chemical
propulsion
Combo
Etc. …
Each line connecting one
“node” at each level marks
out a distinct design
Low
thrust
Trip Time
Propulsion
system mass
Solar sail
Electric
propulsion
Chemical
Tradeoffs – Choosing one branch of the tree (Earth orbit to
Asteroid vicinity)
The above diagrams showed fully branched trade trees – i.e., where each option at a
given level branches to all the possible options at the next level. In practice, only the
distinct alternatives at each level are shown. Using this convention, previous diagrams
look like:
Alternatives for each mission phase
Mission Phase
Launch to
orbit
Earth
orbit to
Apophis
vicinity
Proximity
operations
Launch single
vehicle
Separate
vehicle and
crew
Chemical
Propulsion
Standoff
mode
Assemble
mission onorbit
Low thrust
Landing
mode
A line connecting one option
at each level marks out a
distinct design
Combo
TRADES LIST
These suggested possibilities are not claimed to be comprehensive.
They are offered to help start the thought process
Mission Component/Issue
Design options
Fundamental objective(s) for a space
habitat
Permit the human species to survive
existential threats from the cosmos.
Attain prolonged space travel abilities
essential to the habitation of the solar
system
 Mine the solar system for the raw
materials needed by a space-faring,
society.
 Build the in-space infrastructure
needed to defend planet Earth
Forestall zero-G effects
 Exercise devices
 Vibration-based techniques
 Artificial gravity via centripetal
acceleration
TRADES LIST
These suggested possibilities are not claimed to be comprehensive.
They are offered to help start the thought process
Mission Component/Issue
Design options
Radiation protection
 Thick metallic shields
 Hydrogen-rich plastics
 Enclosure within superconducting
electromagnets
 Small permanent magnets
Population composition/psychological
factors




Exploration instrumentation
 Navigation cameras
 Laser range finders
 IR cameras
 Bolometers
 All of the above
Adult men and women only
Several generations
Composed of technical specialists
Each crew member cross-trained in
at least two disciplines
TRADES LIST
These suggested possibilities are not claimed to be comprehensive.
They are offered to help start the thought process
Mission Component/Issue
Design options
Habitat propulsion system
 Electric propulsion system
 Solar sail
 Nuclear
 Steam rocket
Proximity Operations
 Standoff ops only
 Equipped with lander
 Communication architecture


Direct to grnd. Links
Orbiting links
 Prox ops propulsion method
Spacecraft utilities
 Power source(s)
 Nuclear
 RTGs
 Solar-electric/batteries
 Communications system
 Computation and data handling
Step D. Identify System Drivers for Each Mission Concept
1. In any real system, overall cost and performance or the design
of detailed components are mainly influenced by a relatively small
number of key parameters or components (which the user or
designer can control) - called drivers
2. In this step, we identify the cost and performance drivers for
each alternative system concept.
3. For most missions, system drivers include the number of satellites,
altitude, power, instrument size and weight
4. In identifying the drivers, we must clearly determine whether we
are looking for drivers of performance, cost, schedule or risk.
5. The results of this step tell us where to put most of our effort
when we do detailed performance estimation for each mission
concept in the next step.
More on “Drivers”
There are two qualitatively distinct Characterizations of a system design:
Quality or Performance: Measures of how well the system performs its mission. “How good it
is going to be”.
Burden or Penalty: Usually summarized in the cost. Also: Schedule, risk. This is what we have
to pay in order to get the performance offered by the design.
In addition, both of these types of measurements have uncertainty attached to them. The
decision-maker needs to know: How good is it going to be; what’s the price, and how sure
are you of both?
Distinct from Quality and Burden (or Performance and cost) are design parameters – e.g. size
and power of communications antenna, size/weight of transponder unit, propulsion system
thrust, etc. Performance and cost describe the utility of the design and are functions of the
design parameters.
Design Drivers are those design parameters that most sensitively affect Performance or Cost
(or other selected measures of quality and burden). One says: “This parameter is a cost
driver” or “This is a performance driver”. Not: “Cost is a design driver”, etc.
Step E : Characterize Mission Concepts
1. This step defines in detail what the system is and does. We determine the power, weight
and pointing budgets and decide what to process on the ground or in space.
2. The objective here is to define the mission concepts in enough detail to allow
meaningful evaluations of effectiveness and the relative merits of the various concepts
and architectures.
Process for characterization: There are a variety of processes used - see Larson and
Wertz, Section 2.4 -- but, in the case of Mission to Apophis, we suggest you follow the
outline provided by the TECHNICAL APPROACH STUDY PRODUCTS LIST given in this
lecture
TECHNICAL APPROACH STUDY PRODUCTS LIST
1. Mission System Description (including at least the
following)
1.1 Launch components to LEO, integrate and
travel to operating station - Sequence of Events
1.2 Overview of all system elements
1.3 Mass lists and power requirements,
including at least current best estimate and
identification of mass and power growth
rationale for margin levels, power budgets
should identify power utilization and margins
during critical mission phases
1.4 Functionality
1.5 Block diagrams for system and critical
subsystems
(where appropriate)
1.6 Computing needs and margins
1.7 Degree of autonomy
1.8 Identification of all relevant margins, including
mass margin above expected mass including growth
contingency
1.9 Heritage assumptions
1.10 Critical interface properties
1.11 Robustness to off-nominal conditions
1.12 Redundancy, treatment of single point failures
2. Required Infrastructure
2.1 Deep Space Network tracking requirements
2.2 Requirements at Apophis(telecom network is one
example)
3. Operations
3.1 Operations concept
3.2 Operations development
3.3 Command & control team composition and
responsibilities
3.4 Operations margins (for example, up and
downlink system buffers and required data
download intervals)
3.5 Operations phase flow diagram showing data
and command flow to and from system
4. Technology
4.1 Assumed performance for advanced
technology elements and basis of assumptions
4.2 Fallback options if technology performance
is not achieved and impact
4.3 Required technology demonstrations
5. Cost and Schedule
5.1 Overall mission schedule including
development, integration and test, and
operations
5.2 Overall development cost, and cost
profile per development phase and per NASA
fiscal year
5.3 Assumptions regarding benefits from
duplicating systems flown in technology
demonstrations
5.4 Cost and schedule risk, cost
uncertainty
5.5 Basis of cost (nominal and
uncertainty) and cost estimating
methodology (analogy, parametric,
grass-roots are some examples)
5.6 Identify schedule and cost reserves
5.7 Cost elements (estimates not
required) for technology development and
demonstration and for mission operations
Step F: Identify Driving Requirements
 Having defined and characterized the alternative mission concepts, we return in this step
to our initial quantitative requirements and identify the driving requirements.
 These are the key requirements principally responsible for determining the cost and
complexity of the system.
 This step forces us to get a deep understanding of the relationships between the system
design drivers and the driving requirements. These are the all-important "pressure points" in
the design.
We can use this understanding to see how to improve chances of success by:
Striking a compromise in the initial requirements.
Finding potential technology advances in subsystems areas that relieve the system
drivers.
Identify new approaches that circumvent the drivers.
The end result of this step is to revisit the requirements in the light of the drivers and
revise as necessary.
The Mission Analysis Hierarchy
Analysis Type
Goal
Depth
Feasibility
Assessment
To establish whether an objective is achievable and its approximate
degree of complexity
Quick,
limited detail
Sizing Estimate
To estimate basic parameters such as size, weight, power or cost
Point Design
To demonstrate feasibility and establish a baseline for comparison
of alternatives
Trade Study
To establish the relative advantages of alternative approaches or
options
Performance
Assessment
To quantify performance parameters for a given system
Utility Assessment
To quantify how well the system can meet overall mission objectives
More
detailed,
complex
trades
Step H: Define Mission Concept (Baseline)
Having evaluated alternative designs and done a preliminary assessment of mission utility for each, we
select one or more system designs.
A baseline design is a consistent definition of the system that meets most or all of the mission objectives.
A consistent system definition is a single set of values for all of the system parameters that fit with each other
In designing a space system, many parameters are being defined and changed simultaneously.
The baseline provides a temporary milestone against which to measure progress.
It also allows us to limit the number of options that must be evaluated. Rather than looking at
all possible combinations and variations of parameters, it is much more feasible to look at the
impact of varying several of the more important parameters relative to one or two baseline designs.
As the system design matures, the baseline becomes firmer and eventually becomes the system
design.
Uncertainty and Prediction
See: N. N. Taleb, The Black Swan, Random House, 2010
History is dominated by Black Swan events. A Black Swan three attributes:
1. It lies outside the realm of regular expectations, because nothing in the past can convincingly
point to its possibility
2. It carries an extreme impact
3. Despite its outlier status, human nature makes us concoct explanations for it after the fact
Mediocristan
Extremistan
Mild randomness
Wild or super-wild randomness
The most typical member is mediocre
The most typical is either giant or dwarf
Winners get a small segment of the total pie
Example: Audience of an opera singer before the
gramophone
Winner takes all, almost always
Example: Today’s audience for an artist
Impervious to the Black Swan
Vulnerable to the Black Swan
Subject to physical constraints
No physical constraints on what a number can be
Corresponds to physical quantities, i.e., height
Corresponds to numbers, say, wealth
When you observe for a while you can get to
know what’s going on
It takes a long time to know what’s going on
Easy to predict from what you see and extend to
what you do not see
Hard to predict from past information
History crawls
History makes jumps
Uncertainty and Prediction
See: N. N. Taleb, The Black Swan, Random House, 2010
• We tend to both tunnel and think “narrowly” (epistemic
arrogance). We ignore “unknown unknowns”
• There is an ingrained tendency in humans to
underestimate outliers – or Black Swans
• Our prediction record is highly overestimated – many
people who think they can predict actually can’t
• Not only have forecasters generally failed dismally to
foresee the drastic changes brought about by
unpredictable discoveries, but incremental change has
turned out to be generally slower than forecasters
expected.
Uncertainty and Prediction
See: N. N.Taleb, The Black Swan, Random House, 2010
• Mediocristan model of the process of discovery: Someone sits
in a cubical and concocts the discovery according to a
timetable
• Classical model of real discovery: You search for what you
know (say, a new way to reach India) and find something you
didn’t know was there (America).
• Almost everything of consequence is the product of
serendipity
– Serendipity was coined in a letter by Hugh Walpole, who derived it
from a fairy tale, “The Three Princes of Serendip”. These princes “were
always making discoveries by accident or sagacity, of things which
they were not in quest of.”
• Example: In 1965 two radio astronomers at Bell Labs, New
Jersey, discovered the cosmic background microwave
radiation (which revived the big bang theory)
Uncertainty and Prediction
See: N. N.Taleb, The Black Swan, Random House, 2010
• Forecasting fallacies:
– First Fallacy: Neglecting variability. Taking a projection too seriously,
without heeding its accuracy.
• For planning purposes, the accuracy in your forecast matters far more than
the forecast itself.
• Don’t cross a river if it is four feet deep on average
– Second fallacy: Failing to take into account forecast degradation as the
projected period lengthens
• We tend to underestimate the difference between the near and far futures
• Look at forecasts made in 1975 about the prospects for the new millennium
– Third fallacy: Misunderstanding the random character of the variables
being forecast
• Owing to the Black Swan, these variables can accommodate far more
optimistic – or far more pessimistic – scenarios than are currently expected
• Statistics of Mediocristan = Gaussian. Statistics of Extremistan =
Mandelbrotian
Uncertainty and Prediction
See: N. N. Taleb, The Black Swan, Random House, 2010
• Some tips for dealing with uncertainty:
– At the start, try to imagine all possible design options. Don’t
commit prematurely to one option (based on linear
prediction).
– Build in redundancy (duplicative and functional redundancy)
– Tally up all “grey swans” (known unknowns), as well as
Mediocristan uncertainties.
– For each set of design options, try to identify the worst cases
(in Extremistan)
– Now identify the worst cases that produce the least damage.
This mini-max, robust design, is your design. It is armed
against uncertainty
– Be prepared for Black Swans (negative or positive)
Design Process and Class Teaming Arrangements
Phase
Define Objectives
Step
A. Define broad objectives
and constraints.
B. Estimate quantitative
needs and requirements.
Characterize the
Mission
C. Define alternative mission
concepts.
D. Identify system drivers for
each.
E. Characterize mission
concepts.
Evaluate the Mission
Class org./Activity
Up through midterm
Class forms Contractor Teams
(CT’s)
Up to midterm, each CT
defines one mission
concept and carries out
steps C through G.
Midterm to Final Review
PM and APM elected, Mission
Scientist selected,
Technical Groups formed
Refined execution of steps
E, F, G. and H
F. Identify driving
requirements.
G. Evaluate mission utility
H. Define mission concept
(baseline)
PTAR – Mission Concept
Downselect
(choice of baseline concept)
Baseline (point) Design
Roadmap of Technology
development
THE END