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Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design

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aerospace design case studies

  • Yolanda Mack 5 ,
  • Tushar Goel 6 ,
  • Wei Shyy 7 &
  • Raphael Haftka 8  

Part of the book series: Studies in Computational Intelligence ((SCI,volume 51))

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Balabanov VO, Giunta AA, Golovidov O, Grossman B, Mason W, Watson LT, Haftka RT (1999), Reasonable design space approach to response surface ap- proximation. J Aircraft 36:1:308-315

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Goel T, Vaidyanathan R, Haftka RT, Queipo NV, Shyy W, Tucker PK (2004) Response surface approximation of Pareto optimal front in multi-objective opti- mization. In: 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany NY, Paper No. 2004-4501

He B, Ghattas O, Antaki JF (1997) Computational Strategies for Shape Optimization of Time-Dependent Navier-Stokes Flows. Technical Report CMU- CML-97-102, Computational Mechanics Lab, Department of Civil and Envir- onmental Engineering, Carnegie Mellon University

Huber, F (2001) Turbine aerodynamic design tool development. In: Space Trans- portation Fluids Workshop, Marshall Space Flight Center, AL

Kim S, Leoviriyakit K, Jameson A (2003) Aerodynamic Shape and Planform Optimization of Wings Using a Viscous Reduced Adjoint Gradient Formula. Sec- ond M.I.T. Conference on Computational Fluid and Solid Mechanics at M.I.T, Cambridge, MA

Kontoravdi C, Asprey SP, Pistikopoulos EN. Mantalaris A (2005). Application of Global Sensitivity Analysis to Determine Goals for Design of Experiments - An Example Study on Antibody-producing Cell Cultures, Biotechnol Progr (in press).

Madsen JI, Shyy W, Haftka RT (2000) Response surface techniques for diffuser shape optimization. AIAA J 38:1512-1518

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Papila N, Shyy W, Griffin L, Huber F, Tran K. (2000) Preliminary des- ign optimization for a supersonic turbine for rocket propulsion. In: AIAA/ SAE/ASME/ASEE 35 th Joint Propulsion Conference, Paper No. 2000-3242

Papila N, Shyy W, Griffin L, Dorney DJ (2002) Shape optimization of supersonic turbines using global approximation methods. J Propulsion and Power 18:509- 518

Queipo N, Haftka RT, Shyy W, Goel T, Vaidyanathan R (2005) Surrogate-Based Analysis and Optimization. Accepted for publication in Prog in Aero Sci

Rodriguez DL (2002) A Multidisciplinary Optimization Method for Designing Boundary Layer Ingesting Inlets. 9th AIAA/ISSMO Symposium on Multidisci- plinary Analysis and Optimization, Atlanta, Georgia, AIAA paper 2002-5665

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Vaidyanathan R, Papila N, Shyy W, Tucker KP, Griffin LW, Haftka RT, Fitz-Coy N (2000) Neural network and response surface methodology for rocket engine component optimization. In: 8 th AIAA/USAF/NASA/ISSMO Sympo- sium on Multidisciplinary Analysis and Optimization, Long Beach, CA, Paper No. 2000-4480

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Mechanical and Aerospace Engineering Department, University of Florida, 231 MAE-A, 116250, 32611-6250, Gainesville, FL, USA

Yolanda Mack

Tushar Goel

Dept. of Aerospace Engineering, University of Michigan, 1320 Beal Avenue, 48109-2140, Ann Arbor, MI, USA

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Yew-Soon Ong

Honda Research Institute Europe, Carl-Legien-Str 30, 63073, Offenbach am Main, Germany

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Mack, Y., Goel, T., Shyy, W., Haftka, R. (2007). Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design. In: Yang, S., Ong, YS., Jin, Y. (eds) Evolutionary Computation in Dynamic and Uncertain Environments. Studies in Computational Intelligence, vol 51. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49774-5_14

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Aerospace America Illustration

Thor works with aiaa to create the leading resource for astronautic and aeronautic industry coverage in both print and digital formats., technical illustrations and print covers.

Aerospace America is an award-winning print and digital publication serving the fast-paced global aerospace industry. In order to keep up with the constant evolution of this client's fast-paced industry, Aerospace America highly prioritizes illustrations of complex concepts. Visualizations enable ediors to show rather than tell. Because each print production cycle unfolds over the course of just two weeks, a method for rapidly executing these ideas is critical.

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Case study examines new product development in the fast fashion industry

by David Bradley, Inderscience

fashion

In the world of fast fashion, new product development (NPD) is the main option for companies hoping to maintain relevance and competitiveness in an ever-changing market. NPD is a multifaceted process and covers the generation of ideas, design and implementation of those ideas, prototype and product testing, and eventual launch of a new product on to the market with the aim of capitalizing on emerging market opportunities and addressing consumer needs.

According to an article written by Duong Quang Hao, Ngoc-Hien Do, and Duc Duy Nguyen of Ho Chi Minh City University of Technology in Vietnam published in the International Journal of Services and Operations Management , NPD is a complex process and demands a lot of company resources. This is particularly true in industries marked by rapid shifts in consumer preferences and short product lifecycles, such as fashion.

However, an alternative approach to NPD has emerged that puts the focus on strategic integration of competitor analysis and customer feedback. This can allow a company to streamline the development processes and improve its competitiveness, especially in the world of start-up ventures.

A useful tool on this overall streamlining process is the competitor profile matrix (CPM) method. This allows companies to identify and analyze their main competitors. They can dissect their best-selling products to work out what are the important customer preferences at a given time. This initial step in the new NPD process gives them a template for understanding the changing market and allows them to stitch together their own product ideas.

Once ideas are sewn up, the wily company might then engage directly with its target customer base to gain feedback and gauge preferences. By opting for a customer-centric approach, they can ensure that their new product features and functionalities are going to be welcomed by the market. This will then mitigate the risk of pushing products that end up hemmed in by more competitive offerings and so remain on the fringes of the fashion patchwork rather than becoming the chic pieces everyone wants to be seen to wear.

While the approach is tailored for start-ups in the fast fashion sector, a similar iterative methodology might also be used across other industries. The strategic integration of competitor analysis and customer feedback into the NPD process offers a pragmatic approach to the modern marketplace.

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