1,721,118 research outputs found
Detailed Structural Calculation and Mechanical Measurement of the Insertion Device Support Structure for ELETTRA
No full textOttimizzazione di profili aerodinamici in schiera: confronto fra metodologie tradizionali e algoritmi di ricerca genetica
No full textA hybrid numerical optimisation technique based on Genetic and Feasible Direction Algorithms for multipoint helicopter rotor blade design
No full textA tool for helicopter rotor blade design to improve performance and reduce rotor dynamics loads as well as aeroacoustic noise i presented. The optimization procedure is based on a genetic algorithm and a feasible direction technique. The former is used as a global optimizer, whereas the latter is used to refine the solution. The comprehensive analysis codes used to compute rotor performance, noise and loads are an Augusta proprietary code and CAMRAD-JA. Applications of this methodology to a twin engine light helicopter in different operative conditions are illustrated and discussed using both geometrical and structural parameters as design variables and different choices of the multi constrained objective function
AI tools in the design process of industrial products
No full textAbstract. The definition of Artificial Intelligence that can be found
on the pages of Wikipedia is the intelligence exhibited by machines or
software which clearly has a rather broad and vague meaning that in
many circumstances has been misunderstood.
I would therefore focus more on Artificial Intelligence Tools, i.e. the spectrum
of mathematical procedure that can be used to gain, explore and
exploit knowledge during a design process.
To gain knowledge means to probe design opportunities in a systematic
way in order to collect sufficient data to be able to understand and predict
product behaviour. To explore knowledge means to be able to drive
automatically through the design options using optimization techniques.
To exploit knowledge means to be able to take rational decisions about
the configuration of a product to be produced.
All these actions can be performed by means of software components
based on AI-related tools: Neural networks, Evolutionary Computing,
Classifier Systems just to name a few.
In the development of decision support software for design optimization
there is not one technique that would prevail but a blending of tools,
including more traditional mathematical algorithms, that contribute to
the finding of the best design configuration.
In this presentation a selection of industrial application form transportation
industry to consumer goods will be used to showcase the use of AItools
in daily design activity while possible future needs will be identified
by looking at the opportunity offered by collaborative environments
Robust design, approximation methods and self organizing map techniques for MDO problems
No full text
Computational modeling: valuable tool or math exercise?
Full text linkABSTRACT
Optimization techniques have been used in engineering design for decades maximizing a specific performance metric, ultimately cost of a product for a given performance. As a matter of fact most accepted theories of market efficiency for the past half century have focused on the single objective of maximizing the profit. The well known concept of Pareto Frontier has been used mainly to explain that at high risk corresponds a high reward and therefore any “non dominated” solution is equivalent.
More recently it has become widely accepted that a multi-objective approach is necessary for a more efficient decision making process about product development with sustainability in mind.
However a number of numerical technologies commonly grouped under the term “design optimization” can be used not only for product design but also to improve the quality in the modeling cof complex phenomena.
The design practice has therefore become an iterative process where decision making is performed on the basis of the compromise solutions quantitatively determined or estimated and the optimization methods are used for building the model, design a component or with high ambition face the product design at system level.
Through the description of practical examples the use of optimization for model calibration, for component design and finally for product design will be illustrated
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