Multi-Discipline Design Analysis & Optimization (MDAO) Tom
Harwick MDAO Cost Engineer Concept & Preliminary Design
Engineering Cost models & Methods Northrop Grumman, El Segundo,
CA ICEAA Conference, March 18, 2015, SMC (Fort McArthur), San
Pedro, CA Approved for public release; distribution unlimited. NGAS
case 15-0255 dated 2/19/15.
Slide 2
MDAO Cost Modeling Topics Objectives of MDAO (What, Why) MDAO
Overview Model Center (Phoenix Integration), & Cost Models
Design-of-Experiments (DOE) Simulation Process within MDAO
Conclusions Approved for public release; distribution unlimited.
NGAS case 15-0255 dated 2/19/15.
Slide 3
MDAO at Northrop Grumman Aerospace Systems (NGAS) A way of
tying together design, modeling, simulation and analysis multi-
disciplinary tools to understand the Big Picture May be applied to
Sys-of-Sys, Systems design and Subsystems design Problems Automates
our tools for improved cost effectiveness in engineering design,
modeling, simulation & analysis processes Understand how
variance in input variables affect output variables Topology Trades
( A vs. B, which is better? ) Sizing Trades ( how big should A 1,A
2,A 3,A 4 be to make A work) Optimality Trades (what collection of
A 1,A 2,A 3,A 4 forms the best design?) Uncertainty / Robustness
Trades ( what is the impact of uncertainty in terms of system
performance? feasibility? ) Approved for public release;
distribution unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 4
ModelCenter used to link CATIA with data bases &
engineering analysis Configuration Aerodynamics Propulsion Mass
Properties Low Observables System Options: Can support team
co-located (similar to ICE) or distributed Can be deployed
throughout any linked network environment and, can be deployed
& installed in any isolated compartment Provides infrastructure
across sector integrating common tools and best practices for
affordability and first-time engineering quality in a collaborative
environment Loads & Dynamics Stability & Control
SubsystemsPerformance Structures ModelCenter Aircraft Design &
Analysis Ops Analysis & Life Cycle Cost MDAO Infrastructure
Systematically links CAD and Analytical Systems with LCC and OA
Manufacturing & Assembly Operations & Support Life-Cycle
Cost OA Mission Effectiveness Collaboration Sys Document Mgmt
Analysis Library Approved for public release; distribution
unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 5
Picture of CATIA Model Performing an Iteration within Model
Center (Performance/Design/Cost) CATIA model is Embedded within the
Design Models in Model Center Approved for public release;
distribution unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 6
1.Problem Definition (Requirements, Constraints, Independent
Variables & KPPs) 2.Concept Development (sizing) how big and
what type, e.g. wing/body/tail, flying wing, biplane, etc.
3.Parametric Model Development (configuration) Develop parametric
CAD model that integrates key driving geometric considerations:
wetted area, aspect ratio, t/c, weapons bay, propulsion
integration, fuel volumes, avionics, mission systems, subsystems,
VMS, (SWAP), etc.... 4.Identify Discipline Models, Fidelity levels,
Model Interfaces and V&V - N^2 Diagram (I/O) includes: Cost,
Propulsion, Structures, Aerodynamics, Mass Properties, Performance,
5.Design Space Exploration, Sensitivity Analysis, Constraint
Assessment and Optimization Trade Studies - lead to proposed
preferred configuration(s) for further detailed analysis MDAO (MBE)
based Design & Analysis Cycle (DAC) Process Summary Customers,
Stakeholders and Suppliers C E B G F K L D H I J Radius (nm) A 1.
Problem Definition (Requirements, Independent Variables and KPPs)
2. Concept Development (Sizing) Design Space Exploration
Configuration Selection Discipline Review 5. Design Space
Exploration, Sensitivities & Optimization (Optimization) 3.
Parametric Model Development (Configuration) Preferred
Configuration(s) KPP W/S 4. Identify Discipline Models, Fidelity,
Interfaces and V&V (N 2 Diagram) Approved for public release;
distribution unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 7
Create Cost Model (Object) in Model Center - with Interfaces to
other Engineering Design Models (Objects) Select Cost Model
Determine cost sensitivity required, inputs & outputs, and
accuracy Lower fidelity: Excel model, Higher fidelity: PRICE, or
SEER, Create a Model Center Plug-in for the Cost Model Generate a
Case Study that specifies the MDO Inputs/Outputs Wrap cost model
(create cost model plug-in) Models similar to SEER-H, PRICE (True
Planning) generally require vendor support Excel plug-ins
(order-zero) can be created by the MDO team within Model Center
(with some training and experience) Interface / link the Cost Model
within the other Engineering Disciplines (e.g. using the N^2
Diagram) Populate & Test the Plug-in Model with simple test
data Populate the Plug-in with Real World problem & perform
Design-of- Experiments (DOE) Approved for public release;
distribution unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 8
True Planning Cost Model - Select Hardware Model to become
Plug-in Major Hardware cost drivers include: Weight, Engineering
Complexity, Manufacturing Complexity, Quantity, Learning Curve,
Reliability, Operational & Support Costs Approved for public
release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 9
True Planning Cost Model - Select Software Model to become
Plug-in The COCOMO Family of models is depicted below (Barry Boehms
COnstructive COsting MOdel) Major Software (COCOMO) cost drivers
include: Sizing (new, adapted SLOC, Auto-code), Cost Drivers
(People, Process, Tools, Project Complexity) Approved for public
release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 10
Cost Models Are Linked to the MDAO (N^2) Models (Including
Cost, Propulsion, Structures, Mass Properties,) Cost Models are
linked to the MDO, N^2 Diagram (Data Connectivity). User can select
between Higher Fidelity and Lower Fidelity Cost Model. (Lower
Fidelity Cost Models execute Faster than Higher Fidelity Models)
Cost Switch (High, Low Fidelity) High Fidelity Cost Models True
Planning Cost Model Engineering Design, Performance Models Approved
for public release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 11
Populating the TruePlanning plug-in Plug-ins are populated
prior to performing a Design-of-Experiments. TruePlanning has a
relatively easy to use Filter Structure to populate the plug-in
(variables) Approved for public release; distribution unlimited.
NGAS case 15-0255 dated 2/19/15.
Slide 12
Populated True Planning plug-in The True Planning Object
(plug-in) imported cost Variables must include desired Inputs /
Outputs. This data is available when performing (DOEs) True
Planning File (Instance) Approved for public release; distribution
unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 13
Generation of MDO Trade Space -Design-of-Experiments (DOE)
Summary Within Model Center, conduct DOE: Select Design &
Response variables Select Ranges of Design variables (Low, High)
Select the DOE sampling method Perform Simulations Analyze DOE
Results Examine Trade Space Data Set Constraints to separate
Feasible from Infeasible Solutions Focus on Affordable solutions,
within best performance space Approved for public release;
distribution unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 14
DOE Experiment Setup in Model Center (Illustrative) The Design
trade space is a Combination of the Design Variables Ranges (Low,
High) Specified in the DOE Experiment. Design Variables (example):
Max-Take-Off-Weight, Wing sweep, Wing Area, Engine-scale, Percent
of Payload used. Response Variables: Cost, Empty Weight,
Mission-Time, Range. Approved for public release; distribution
unlimited. NGAS case 15-0255 dated 2/19/15.
Slide 15
DOE Sample Results with Objectives applied Infeasible designs
e.g. Time-on-station Constraint setting x DOE Sample shows Feasible
Designs Blue (best) to Red (worst), and infeasible solutions shown
in Gray. (Infeasible designs, e.g.: defined as less than x hours
Time-on-Station, or Range requirement, using the Constraint setting
Development Cost vs. Empty Weight Production Cost vs. Empty Weight
Empty Weight Development Cost Production Cost Approved for public
release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 16
Cost Affordability in Design Objectives, Constraints Chart
shows Objectives Controls set to Minimize cost (Development,
Production, and Operations & Support) Cost Objectives allow
& depict ranking of designs by cost (Scatter Matrix).
Constraints are used to exclude Infeasible solutions (range, etc.)
Define Objectives step Define Constraints step Minimize Cost
(importance ranking) Cost Variable(s) Constraint Approved for
public release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 17
DOE Results showing Cost, Variable (Scatter) Relationships -
Blue best designs, red worst designs Infeasible data points
eliminated. Each Design Results can be Identified with Design
Comparison chart. Includes Design & Response (Cost) Variable
data profiles. Development Cost vs. Empty Weight Rows: MTOW Wing-
Sweep Wing-area Engine- Scale % P/L Empty- Weight CFL Mission- Time
Approved for public release; distribution unlimited. NGAS case
15-0255 dated 2/19/15.
Slide 18
Best Valued (KPP, Cost) Designs The top designs using Model
Centers Define Objectives (Cost Minimized), and define Constraints
(e.g. Mission Time Less than 10 Hours) (Example Data) Approved for
public release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 19
DOE Designs Ranked by LCC Cost, FOMs: e.g. Top Set of Designs
from an Affordability Perspective 11 Cost Ranking of Designs
Relative Cost, Constant Year 2011, M$ Affordable Designs Can be
Ranked, Identified from large DOE Design Sample. Least Cost Design
set can be compared (intersected) with Best Technical Design set.
(Example Data) Approved for public release; distribution unlimited.
NGAS case 15-0255 dated 2/19/15.
Slide 20
Cost Model part of N-Squared: -Lower Fidelity Cost Model
-TruePlanning, COCOMO (higher fidelity) - Scope: NRE, REC cost,
Operations & Support (LCC) Cost model major drivers: -Hardware
(Empty weight, Technical Complexity) -Software (Software size,
Complexity) -Flight Test (Flight Test Points) -Production
(Manufacturing Complexity, Quantity, Rate of Production, Learning
curve) N-Squared cost model interfaces: -Mass properties
(structure, propulsion, avionics) -Sub-systems weight (and density)
Cost Model role in DOE: Cost model output parameters part of
Response parameters in Design-of-Experiments (for each observation)
Cost Models MDAO Interface - Using Model Center (Phoenix
Integration) Approved for public release; distribution unlimited.
NGAS case 15-0255 dated 2/19/15.
Slide 21
Summary Cost Model Evaluation Criteria MDAO environment
compatibility Cost models must have a (stable) plug-in to allow
translation of model inputs via Model Center to the cost model.
Ability of cost model to perform DOEs (must create numeric
translation tables for non-numeric inputs). If no, are the number
translation tables user friendly? The cost model needs to interface
to the N^2 -particularly the Mass Properties (MDAO inputs) Cost
models should be portable (MDAO lab, projects, etc.) Approved for
public release; distribution unlimited. NGAS case 15-0255 dated
2/19/15.
Slide 22
Summary Cost Model Compared MDAO environment compatibility
Industry cost model have flexible WBS Excel cost models have
inflexible WBS (WBS list changes require numerous link edit changes
Verbal scales need to be translated to Integers. Interpretation of
output can be more complex Descriptive inputs convertible to
numeric input within Excel. No issue Can perform up to 500- design
(DOE designs) Can perform up to 10,000+ design (DOE designs)
Difficult to move from Concept design to Preliminary design
Facilitates movement from Concept to Preliminary design Requires a
mass properties model interface, e.g. using Excel Excel readily
incorporates interface Component part of the Excel MDO model
Useable for trade studies and bid / proposalOnly useable for design
trade studies Approved for public release; distribution unlimited.
NGAS case 15-0255 dated 2/19/15.
