Novel, yet similar: A similarity-assisted product family design approach for structural aero-engine components

The aviation industry is in a state of transformation. The climate crisis has amplified the need to innovate, and consequently manufacturers in the aviation industry need to investigate new and more sustainable design concepts. This is challenging, because there is no obvious replacement for kerosene-fueled aero-engines, though there are multiple technologies in development that may potentially take its place. Examples of such technologies include electric or hybrid-electric propulsion, or combustion engines fueled by hydrogen or synthetic sustainable aviation fuels. This increases the challenge for manufacturers, who must deal with high technological uncertainty. At the same time, manufacturers need to assert that the cost of realization is feasible for new aero-engine component designs, while also fulfilling the requirements for safety and performance. There is therefore a need for methods and tools that will assist designers in making fast and efficient design evaluations, to enable the exploration of large design spaces at reduced costs and lead-times.To make design space exploration more efficient, a similarity-assisted design space exploration method is proposed. This method provides increased trustworthiness in design space exploration results, while also highlighting opportunities for reuse of knowledge and other assets from legacy designs. Additionally, a software tool for automatically generating aero-engine structural components has been developed. This software enriches all generated geometries with information used to facilitate automated manufacturability analysis, as well as evaluation of structural performance. By utilizing the automated geometry generation tool in conjunction with the proposed design space exploration method, designers can quickly and efficiently evaluate the manufacturability and structural performance of novel concepts

A similarity-assisted multi-fidelity approach to conceptual design space exploration

In conceptual design studies engineers typically utilize data-based surrogate models to enable rapid evaluation of design objectives that otherwise would be too computationally expensive and time-consuming to simulate. Due to the computationally expensive simulations, the data-based surrogate models are often trained using small sample sizes, resulting in low-fidelity models which can produce results that are not trustworthy. To mitigate this issue, a similarity-assisted design space exploration method is proposed. The similarity is measured between design points that have been evaluated through lower-fidelity data-based surrogate models and design points that have been evaluated using higher-fidelity physics-based simulations. This similarity information can then be used by design engineers to better understand the trustworthiness of the data produced by the low-fidelity surrogate models. Our numerical experiments demonstrate that such a similarity measurement can be used as an indicator of the trustworthiness of the lower-fidelity model predictions. Moreover, a second similarity metric is proposed for measuring the similarity of new designs to legacy designs, thus highlighting the potential to reuse knowledge, analysis models, and data. The proposed method is demonstrated by means of an aero-engine structural component conceptual design study. An open-source software tool developed to assist in data visualization is also presented

DERIVE AND INTEGRATE SUSTAINABILITY CRITERIA IN DESIGN SPACE EXPLORATION OF ADDITIVE MANUFACTURED COMPONENTS

Additive manufacturing has the potential to decrease the climate impact of aviation by providing more light-weight designs. Sustainability is however required to be assessed from a systemic view, including all lifecycle phases, and from a social, ecologic, and economic dimension. This is however challenging in early phase design, where also a large design space need to be explored. A case study is carried out with an aerospace company where two candidate engineering design tools are combined to address this. The integration of these two engineering tools are applied on a Turbine Rear Structure, and shows promising results in enabling a systemic view of sustainability to be integrated and assessed in early phase design space explorations of additive manufactured components. It is recommended that the integration between the two tools is further established and validated

The impact of specialized software on concept generation

Software implementations of traditional engineering design methods can potentially enrich the original methods. A study was conducted to better understand how concept generation can be facilitated using software. Participants of the study were asked to generate concepts using either specialized software, or by using traditional means, for applying function-means modeling and morphological matrices. A concept concretization metric was used to evaluate the results, which indicated that there are both positive and negative aspects of performing concept generation using specialized software

Morpheus: The Development and Evaluation of a Software Tool for Morphological Matrices

The Morphological Matrix is a well-known and established method for synthesising concepts in engineering design. With the aim to improve its applicability, the method has been implemented into a software tool, which then has been introduced in engineering courses at Chalmers University of Technology. In this paper, the tool and its most important functions are presented and discussed, along with experiences from its use in design projects. It was demonstrated that the tool can ease the process of creating and modifying morphological matrices. Furthermore, the tool demonstrated the ability to generate and keep track of large quantities of solutions, which has previously been difficult as morphological matrices are typically hand drawn or created using an Excel sheet. However, less desired effects were encountered as the tool was perceived by some students as more of a screening and down-selection method, rather than as a tool for synthesising concepts. The learnings and the way forward in education and the industrial context are discussed