United States, September 15, 2011
Uncertainty quantification has become a critical feature of a computational
methodologies which will be utilized within an engineering design process.
The purpose of this two-day ERCOFTAC-organized short course is to bring
some the most promising approaches and developments in this field to the
attention of researchers and engineers.
Description:
Uncertainty quantification is a new paradigm in industrial analysis and design
as it aims at taking into account the presence of numerous uncertainties
affecting the behavior of physical systems. Dominating uncertainties can be
either be operational (such as boundary conditions) and/or geometrical
resulting from unknown properties, such as tip clearances of rotating
compressor blades or from manufacturing tolerances.
Whether bringing a new product from conception into production or operating
complex plant and production processes, commercial success rests on careful
management and control of risk in the face of many interacting uncertainties.
For example a new aircraft or aero-engine must be designed and engineered
within a given time frame and budget to meet a given set of performance
requirements, and then manufactured at unit cost and rates that meet an
overall business plan. Todays fiercely competitive market and increasingly
stringent regulatory environment is such that there is very little margin of
error. Failure to appreciate, understand and appropriately manage risks
inevitably results in severe financial penalties, and even irrevocable damage to
reputation.
Historically, chief engineers and project managers have estimated and
managed risk using mostly human judgment founded upon years of
experience and heritage. As the 21st century begins to unfold, the design and
engineering of products as well as the control of plant and process are
increasingly relying on computer models and simulation. This era of virtual
design and engineering opens the opportunity to deal with uncertainty in a
systematic formal way by which sensitivities to various uncertainties can be
quantified and understood, and designs and processes optimized so as to be
robust against such uncertainties. Human judgment will always play an
important role, but leading companies in many fields of engineering are
increasingly aware of these possibilities and uncertainty quantification is
beginning to feature strongly in their strategic aspirations. Thus this is a very
opportune moment to introduce a two- day awareness course on this
emerging topic. The aim is to share the aspirations and requirements of
leading companies in the fields of aerospace, energy, transport and chemical
process; review emerging methods and techniques and how these are being
deployed; and define the current state-of-the-art and map out-near term
future possibilities.
Uncertainty quantification has become a critical feature of a computational
methodologies which will be utilized within an engineering design process.
There has been considerable progress in this field at both the national and
international level. The purpose of this two-day hort course is to bring some
the most promising approaches and developments in this field to the
attention of researchers and engineers from academia, industry and research
laboratories.
A recent development has been a short course arranged by Dr. Charles Hirsch
of Belgium, who has organized an ERCOFTAC short course, Uncertaintly
Management and Quantification in Industrial Analysis and Design, which was
delivered in Munich, Germany on March 3-4, 2011. This course is being
brought to the US research community by the National Institute of Aerospace.
Speakers:
Prof. Charles Hirsch, Numeca International, Belgium
Prof. Anthony Hutton, Chairman, ERCOFTAC, UK
Dr. Alberto Pasanisi, EDF, France
Dr. Bernhard Eisfeld, DLR, Germany
Dr. Jacques Peter, ONERA, France
Dr. Gilbert Roge, Dassault-Aviation, France
Dr. Thomas Zang, NASA Langley Research Center, USA
Dr. Andrew Booker, The Boeing Company, USA
Prof. George Karniadakis, Brown University, USA
Dr. Karl Alexander, Rolls Royce, USA
