1. Benjamin Welle Stanford University Grant Soremekun Phoenix Integration Geometry, Structural, Thermal, and Cost Trade-Off Studies using Process Integration and Design Optimization Improving Multi-Disciplinary Building Design

2. An academic research center within the Civil and Environmental Engineering department at Stanford University: Research focus is on the Virtual Design and Construction (VDC) of Architecture – Engineering – Construction (AEC) projects in collaboration with our industry partners Introduction to the Center for Integrated Facility Engineering (CIFE)

3. Conceptual Phase – Model Based Design Overview The time required for model-based structural and energy performance analysis feedback means few (if any) alternatives are evaluated before a decision is made. Objective Develop/utilize a platform to integrate CAD and analysis tools for design exploration and optimization that:  Can interface with commonly used design tools in AEC industry  Can support the following:  Software automation  Software integration  Data visualization  Simplification of running of trade studies  Provides a robust, flexible and extensible environment Intuition Providing designers with this platform will allow them to systematically explore larger design space more efficiently and better understand those design spaces, resulting in higher performance and cost-effective design solutions.

4. Multidisciplinary Optimization Process

5. Energy and Daylighting Optimization Process

6. Proof of Concept Case Study: Classroom Design Variables  Building orientation (0)  Building length (L)  Window to wall ratio (W)  Structural steel sections Constraints  Fixed floor area  Structural safety  Daylighting performance Objectives  Minimize first cost for structural steel  Minimize lifecycle operating costs for energy L O steel frame column beam girder Window to Wall Ratio Orientation

7. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved 13 year history Provide process integration and design optimization (PIDO) software and services to customers in aerospace, defense, civil, oil and gas, financial Evolved out of a research program at Virginia Tech Office locations  Philadelphia, PA (Corporate)  Blacksburg, VA (R&D)  California (Sales)  North East (Sales) World-wide sales in North America, Europe, and Asia Phoenix Integration

8. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved Phoenix Value Proposition 1.Improve your decision making capability  Automate runs of existing tools to quickly gather information  Apply intelligent algorithms to identify the best solutions 2.Manage design data  Knowledge Capture, Search and Reuse  Collaboration and Synchronization  Data Pedigree/Traceability

9. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved AoA: Analysis of Alternatives CAIV: Cost As an Independent Variable SoS: Systems of Systems DFSS: Design for Six Sigma MDO: Multi-Disciplinary Optimization ModelCenter Parameter Sweeps, DOE, Monte Carlo, Optimization, Add your own… Run Matrix Multi-Disciplinary Trade Studies Process Results

10. Energy Model

11. Impact of Design Variables on Energy Performance  Design of Experiments (DoE) allow for the visualization of the design space and an understanding of variable sensitivity and performance trends.  The design space can be explored from a wide range of perspectives, including general trends using surface plots, actual data points using glyphs, and sensitivity data using bar charts Orientation (deg) Total Lifecycle Operating Costs ($/ 30 years) Most Efficient Less Efficient Length (mm) Total Lifecycle Operating Costs vs. Orientation and Length

12. Total Window Area Total Operating Cost Total Wall Area Impact of Design Variables on Energy Performance (cont’d) Total Lifecycle Operating Costs vs. Total Wall Area and Total Window Area

13. Optimization vs. DoE Results for Energy and Daylighting Performance DoE- 1882 simulations Optimization-93 simulations Optimum areas of design space  The correlation between the optimum designs using DOE and the optimizer was extremely high. Simulation time to achieve optimum designs was reduced by 95%. Total Life-cycle Costs ($/ 30 years) Total Life-cycle Operating Costs vs. Orientation and Length Orientation (deg) Length (mm)

14. Multi-Disciplinary Model Size of Design Space: 55,000,000 MDO Run: 5600 (0.01%) Time: 34 hours Design Variables Building orientation 0-180 deg, 10 deg inc Building length 4-14m, 1m inc Window to wall ratio 0.1 to 0.9, 0.1 inc Structural steel sections Girders (65 types) Columns (7 types) Beams (65 Types

15. Structural Cost vs. Energy Cost with Pareto Front Pareto Optimal Designs for Classroom MDO Structural First Cost vs. Energy Lifecycle Cost Structural Cost ($) Lifecycle Energy Cost ($/ 30 years)

16. Pareto Optimal Designs for Classroom MDO Building Length vs. Energy Lifecycle Cost

17. Pareto Optimal Designs for Classroom MDO Building Length vs. Structural Cost

18. MDO Optimization of Structural vs. Energy Performance Optimal Designs with Varying Objectives

19. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved Forest Flager Grant Soremekun Stadium Roof Structural Optimization Studies

20. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved ModelCenter Web Browser Compute Cluster Multi-processor Server Spare Computers Analysis Library Analysis Execution Trade Study Archive Soon: Bill of Analysis Accelerating Design Studies

21. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved Preliminary CenterLink Results Load balance Energy Plus Trade Study  90 Energy Plus Analyses  Single Machine –Run Time: 50 minutes  CenterLink –4 Machines (Quad 4 processors) –Run Time: 7 minutes

22. DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2007 Phoenix Integration, Inc. All Rights Reserved DESIGN PROCESS OPTIMIZATION INTEGRATION TRADES SIMULATION VISUALIZATION www.phoenix-int.com © Copyright 2008 Phoenix Integration, Inc. All Rights Reserved Stanford Cluster 16 Blade Compute Cluster Dual Core / Quad 4 (128 nodes) Installed Jan / Feb - 09

23. Current and Future Work General:  Make software wrappers more robust / flexible  More complex building types, Case Studies (ARUP, SOM, Gensler, Burro Happold, AKT)  Topology changes  Parallel computing to reduce trade study run times Energy:  Variable constructions, locations, HVAC equipment, internal loads, schedules, etc.  Developing a scriptwrapper to handle any DP geometry (or from any other BIM tool) and convert it to EP syntax (no macros) Daylighting:  Developing a Radiance wrapper with support from Zack Rogers  Combine SPOT and DAYSIM engines to calculate dynamic daylighting metrics  Automatic sensor grid generation, using construction data from EP  Each room will become a separate Radiance run, and an include file will be generated for EP  Developing methodology using translucent windows to reduce simulation time CFD:  Developing a Fluent wrapper with auto-meshing using Gambit for space temperature stratification, air velocity distribution, and mean radiant temperature  Construction properties and surface temperatures taken from EP  Variable diffuser locations