Description of Work

The scientific and technological enhancements offered by the RBF4AERO techniques, that are completely innovative in the aeronautical environment, require a convincing verification process before entering the industrial practice.

For this reason, the Project work plan develops a robust industrial-based process divided into three principal tasks:

 

 

  1. Benchmark Technology Infrastructure Development

The novel methodological procedure for the computational-driven optimization proposed in the Project implies the development of an appropriate infrastructure to build up the optimization environment and enable the simulation of test cases of industrial relevance. The RBF4AERO Benchmark Technology Infrastructure is the integrated system properly designed to develop the RBF4AERO Benchmark Technology (optimization environment) and then to make the RBF4AERO process usable by the professional industrial user. Specifically, this system mainly addresses dedicated software (SW) items and necessary HW (platform).

  1. Benchmark Technology Verification

Preliminary verification of results accuracy will be achieved on published state of the art reference applications or on available industrial based cases. For these evaluations, both background knowledge and experimental data available in the literature as well as that produced within the project will be exploited. Verification against well documented geometries and proprietary models will be carried out for a set of preliminarily identified study cases.

  1. Benchmark Technology Numerical Testing

Successively, the optimization procedure on a set of real-world demanding industrial applications will be carried out and numerically validated by the Project End Users. Critical analysis of the numerical predictions of morphed configurations with respect to the baseline will be supported and complemented by experimental outputs provided within the Project for both external and internal aerodynamics cases. Finally, the effectiveness as well as the efficiency of the overall RBF4AERO optimization procedure is expected to be extensively characterized.

The overall RBF4AERO project work is distributed over 7 work packages (WP) for a total of 24 sub-tasks. The first 5 WP are concerned with technical issues, whereas WP6 and WP7 respectively deal with dissemination and exploitation, and Consortium management.

 

WP1 - End Users Requirements and Technical design Specifications

The purpose of WP1 is to elaborate the whole set of specifications documents for the development, testing, and verification of the proposed research project.

WP2 - Benchmark Technology Infrastructure Implementation

The principal scope of WP2 is the physical implementation of the RBF4AERO Benchmark Technology Infrastructure conceived to efficiently perform shape optimization analyses. This system, in detail, addresses specific software (SW) items which are demanded to be developed and integrated to satisfy the operational requirements of the Project.

WP3 - Experimental Tests Development

The WP3 mainly focuses on the setting-up and development of testing cases selected according to the significance degree addressed by the Project End Users. Testing cases will consider applications which are not fully characterized by published or in-house available data, with the purpose to produce experimental evidence to be compared in WP5 with numerical outputs of the optimal morphed configurations.

WP4 - Numerical Optimization Analyses on Reference Models

The aim of this WP is to develop a first set of computational studies mainly on the native developed infrastructure, in view of testing the effectiveness and reliability of the proposed optimization procedure on numerical models characterized by low- medium-size computational mesh models.

WP5 - Benchmark Technology Procedure Verification and Testing

In this second computational task, intensive trials will be performed on identified applications of industrial interest. Moreover, this task will prove the capability of the proposed approach in managing very large computation models, and, on the other hand, to quantify the morphing efficiency in terms of computing solution performance and morphing action.