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saVVy engineering application framework for emission free product design 

saVVy is open source application software empowers emission free featured product design enabled at cloud using using learning surrogate Life cycle assessments on Artificial Neural Network, approach facilitates an integrated system design process, allowing the approximate and rapid assessment of environmental impact based on high-level information typically known in the conceptual design. Life-Cycle Assessment (LCA) is a "cradle-to-grave" approach for assessing the environmental performance of a product, process or service system from raw material acquisition through production, use and disposal.

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Surrogate Life Cycle Assessment method as alternative approach, relies on Artificial Neural Network trained high level product descriptors, without requiring the development of new model, and environmental performance data from pre-existing detailed life cycle assessment studies and related data.

The aerospace industry currently generates tremendous volumes of data throughout a product life cycle, but the data storage systems are not always designed to have their data extracted, much less at near real-time rates. The lack of analytically based methods for incorporating environmental aspects into product concepts motivated the development of the learning surrogate LCA concept

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saVVy   featured using  surrogate Life Cycle Assesment method

saVVy  design features and updates

saVVy featured used learning surrogate product life cycle assessment on artificial neural netwrok architecture

The approach facilitates an integrated system design process, allowing the approximate and rapid assessment of environmental impact based on high-level information typically known in the conceptual phase.

The learning process of the ANN begins when it is provided a set of product descriptors and corresponding detailed LCA results from previously analyzed existing products. The training algorithms adjust parameters within the network so that its output better emulates the actual environmental impact results of the training data products.

saVVy features full LCA on directly implememented surrogate model

Life-Cycle Assessment (LCA) is a "cradle-to-grave" approach for assessing the environmental performance of a product, process or service system from raw material acquisition through production, use and disposal.

The aerospace industry currently generates tremendous volumes of data throughout a product life cycle, but the data storage systems are not always designed to have their data extracted, much less at near real-time ratesANN is used in many applications of surrogate models due to its huge convenience available for problems with large amountof data. The principle behind surrogate modeling is that data at input and output is related through the pattern of the trained neural network.

ANN is used in many applications of surrogate models due to its huge convenience available for problems with large amount of data. It respectively reduced the average error and maximum error of Artificial Neural Network. Utilization of the ANN surrogate models facilitate the reliability-based cycle design optimization, which replaces the time-consuming probabilistic analysis based on Monte Carlo simulation

 Optimization design solution of presented methodology reasonably increases the aero engine performance redundancy to precisely reach the expected reliability of all concerned operating conditions.

saVVy  benefitts advantages of using surrogate modelling