Optimizing turbofan designs is challenging because of the need to deal with both aerodynamic and structural performance. While designing a fan with high performance and efficiency is important, strength and reliability of the structure are also critical. Further, integrating parametric CAD, CFD and stress analysis is not a trivial task and usually takes extensive effort.
In this project SmartDO and ANSYS were utilized together to optimize a turbofan. The technical services team at SmartDO’s developer, FEA-Opt Technology, helped the customer build a parametric model with ANSYS DesignModeler, construct the CFX and mechanical analysis block, and integrate SmartDO with ANSYS Workbench. SmartDO was able to increase the mass flow of the fan by almost 14% while slightly reducing the maximum stress under aerodynamic and structural loading. These results showed promising possibilities for further design development. Continue reading →
Discussions of how to simulate early in product development fixate too often on FEA, overlooking the power of systems modeling and 0D/1D simulation for studying, exploring and optimizing designs at the beginning of projects, when product geometry is seldom available for 3D CAE but engineering decision-making can have its greatest impact and leverage on project success. Continue reading →
For engineering organizations, where does innovation come from?
When we put that question to EPC firms serving the process and power industries, the most frequent answer was “our projects” and the people working directly in project execution. Forty percent of respondents said their firms’ most important source of innovation is the discovery and application of new technologies and approaches by discipline leads, engineers and managers seeking solutions to pressures and exigencies in a specific project or program.
In second place was “anywhere and everywhere”—27% said innovation at base is a function of their organizations’ culture, and thus can arise from any area in the firm.
In third place was the IT department, named as the top source of innovation by 17% of respondents. While not quite the picture painted in some CIO-oriented publications, these findings align with what our research and others’ suggests is an evolving role for the CIO’s office: to provide enabling infrastructure in support of digital technology initiatives that, more and more, originate from the project execution centers of engineering, manufacturing and construction enterprises. Continue reading →
Design space exploration as an engineering formalism originated in the embedded-systems industry as a set of methodologies for hardware/software co-design, configuration of software product lines, and real-time software synthesis. “The set of all possible design alternatives for a system is referred to as a design-space, and design-space exploration (DSE) is the systematic exploration of the elements in a design-space” (Saxena and Karsai, “Towards a Generic Design Space Exploration Framework,” Proceedings of 2010 IEEE 10th International Conference on Computer and Information Technology).
In mechanical engineering, design space exploration is rooted in the technological domain often referred to as process integration and design optimization, or PIDO, first identified and defined (Jenkins, Daratech, 2001) as software and methods to help:
Automate and manage the setup and execution of digital simulation and analysis;
Integrate/coordinate analysis results from multiple disciplines and domains to produce a more holistic model of product performance; and
Optimize one or more aspects of a design by iterating analyses across a range of parameter values toward specified target conditions.
Design optimization is the search for a structural design that is optimal in one or more respects. In all the various methods available for optimization, the design is guided to satisfy operating limits imposed on the response of the structure, and by further limits on the values that the structural parameters can assume. The power of numerical optimization is its ability to rationally and rapidly search through alternatives for the best possible design(s). Continue reading →
Automating the search for solutions to engineering problems can take either of two broad approaches: design exploration or design optimization. Practitioners making technology choices need to understand which tools do one, which do the other, and which approach best fits their needs. A global roster of commercially available design exploration and optimization software appears at the end of this post.Continue reading →
Technology business strategy for 21st-century engineering practice