Descripción del proyecto
Un método avanzado para probar estructuras compuestas complejas
El proyecto D-STANDART, financiado con fondos europeos, tiene por objeto desarrollar métodos rápidos y eficientes para modelizar la durabilidad de estructuras compuestas a gran escala con disposiciones arbitrarias en condiciones realistas. Sus investigadores emplearán muestras genéricas para crear nuevas metodologías que permitan determinar los parámetros de los materiales relacionados con su durabilidad ante cargas repetidas. Los modelos de alta fidelidad deberían ayudar a simular el crecimiento de defectos en varias capas a múltiples escalas en función de la velocidad y la carga repetida. El uso de modelos sustitutos de inteligencia artificial debería ayudar a acelerar el desarrollo, la adopción y la comercialización de componentes avanzados. Se identificarán dos casos de uso relevantes para la industria aeroespacial y las energías renovables a fin de validar el rendimiento de durabilidad modelizado de las estructuras compuestas.
Objetivo
Advanced composite manufacturing is becoming crucial in the global sustainable drive for a climate-neutral future as enabler of light-weight structures in, for example, the aerospace and wind energy sector. Their increased relevance has raised the importance of damage tolerance and durability of composite structures, currently dealt with time-consuming and inaccurate techniques. Hence the objective of D-STANDART is to develop fast and efficient methods to model the durability of large-scale composite structures with arbitrary lay-ups under realistic conditions (loads, environment).
New test methodologies will be developed using generic specimens to correctly quantify material parameters that determine the durability of composites under cyclical loading. Material characterisation will be used in high-fidelity models to simulate defect growth in various lay-ups and at various scales as a function of cyclical loading and rate. To apply these models in an industrial design environment, D-STANDART will make use of Artificial Intelligence (AI) surrogate models, trained using test data from the project and historical test data to easily adapt to different design parameters and complex lay-ups, thereby accelerating the development, uptake, and commercialisation of advanced components. Two use cases have been selected to validate the modelled durability performance both in the aerospace and renewable energy sectors. Furthermore, circularity and sustainability will be assessed via dedicated life-cycle assessment, life cycle costing and cost-benefit analysis.
This 36-month €5.6M valued action involves, 9 partners (3 universities, 2 RTOs, 2 industry, and 2 SMEs) from four countries (United Kingdom, The Netherlands, Germany, and France). The consortium will be supported by an Advisory Board formed of 6 End users embracing the value chain to validate requirements, guide on relevant approach to certification, and finally support results uptake, in tight alignment with EMCC.
Ámbito científico
Palabras clave
Programa(s)
Convocatoria de propuestas
HORIZON-CL4-2022-RESILIENCE-01
Consulte otros proyectos de esta convocatoriaRégimen de financiación
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
1059 CM Amsterdam
Países Bajos