As human-beings, our differences are what makes us unique (if I may quote the Seek Discomfort crew – “What makes you different is what makes you beautiful”). For turbomachines, this sentiment also rings true. We design different turbomachines because we have varied roles, needs and constraints for them. To that effect, there is no universally best turbine, compressor, or pump. Therefore, figuring out which set of “skills” a turbomachine should have is the key role of a design engineer so that they may effectively capture and estimate performances of the machine they will work on early on while having the certitude this is the best that can be done.
Generative design is one of these recent buzzwords that characterizes an approach to the design of components (or systems) that has been around for quite some time already. Rather than producing one geometry for one value of each input (such as boundary conditions, flow coefficients, number of stages, etc.), generative design allows you to create thousands of designs within minutes that you can review, compare, and filter to select the one that best suits your needs. Let’s look at an example of an axial turbine design process comparing traditional preliminary design vs. generative design.
Approach 1 or what most companies call Traditional Preliminary Design, is to look in textbooks and previous examples of what a given turbine for that application “should” look like. It may involve things like using Ns-Ds diagrams, load-to-flow diagrams, blade speed ratio vs. isentropic velocity ratio correlations, scaling/trimming existing designs, etc. These have served their purpose well enough, but they have their limitations which make them fairly challenging to really innovate. Such limitations include previous experience/data being restricted to a given fluid, relative clearance size, given configuration, lack of secondary flows, etc. A summary of a traditional preliminary design workflow (familiar to too many engineers) is presented below.
Now, we know that changing (ahem, improving) your workflow is not always easy. But growth happens through discomfort and switching to a generative design approach does NOT mean rebuilding everything your team has done in the past. What it effectively gives you is the confidence that the input parameters you finalized will provide not only the desired performance but the best ones that can be achieved (and it saves time too…a lot of time). From there, you can use these inputs in your current design software or you can continue the design process in our design platform, AxSTREAM® (meaning you can add generative design capabilities upstream of your existing workflow or replace parts/all of that workflow depending on what makes the most sense for you). You can pay your engineers to do engineering work, instead of visiting online libraries and guessing input parameters in hope they will find the needle in the haystack. Or, with generative design, you kind of look for haystacks and shake them until the needle falls off.