- Engineering Workflow Automation
- Design Space Exploration
Optimization using a 1-D Simulation tool
Author: Ceyhun Sahin, Application Engineer, Noesis Solutions
Engineering design is becoming more complex – it typically produces a myriad of surprises once the design process begins. Digital engineering transformation is not only enabling the designers and engineers resolve this complexity, but also the companies to meet the expectations of leveraging resources in an economical manner and keeping up competitive standards. When it comes to the tactics of engineering designing, there are multiple options, even more so with the technological advancements. In this era, designers can create a virtual product and understand how their products respond to various parameters and 1-D simulation models are often considered the starting point of a design process.
In this blogpost, we will discuss the advantages of introducing a 1-D simulation model in the early stages of design process. Let’s consider the example of designing a gas ejector to be used in a fuel cell system (Figure 1), that will replace an anode gas recirculation compressor. It will take a lot of time, resources, and computational power to run just one 3-D compressible flow simulation to design a gas ejector so that we can supply the right amount of steam to the reformer while keeping up the pressure levels required by the system. And now multiply it by 100s of design alternatives. Considering the complexity of and the resources needed for 3D modeling, one will want to extensively explore only a very few designs. This is where 1-D simulation plays a key role.
A powerful 1-D model of system behavior can provide valuable insights into system performance and function thus guiding the designers and engineers through the design process. However, a 1-D model is a Blackbox, and the result will not be a field data or a curve but a single data point. This creates a need for additional post-processing to combine results from several 1-D simulations.
Advantages of Optimization using a 1-D simulation tool:
Optimization in the early stages of the design process via 1-D simulation models helps the designer:
Going back to the example of a gas ejector, the goal was to find optimal diameter sets and analyze the properties of the flow. We have two objectives in this stage of the design - high pressure at the reformer exit and sufficient steam (high steam-to-carbon ration) in the reformer. With an ideal ejector design, the fuel will be processed at one shot without substantial drop in pressure levels so that the fuel cell will operate at its design condition. The ultimate advantage of such an ejector is eliminating a high-maintenance BoP (Balance of Plant) component. The two aforementioned targets which contradict with each other can be best tackled with multi-objective optimization (MOO).
In this case study, we will explore an Excel Macro running a 1-D model for gas ejectors using Optimus, an automation and optimization tool by Noesis Solutions. With Optimus, the designer will be able to gain insights into system performance and function to understand how their products respond to various parameters, thus guiding them through the design process.
A 1-D model in Excel Macro is created to run in two modes – design and analysis modes. In the design mode, we calculate the required diameters for a selected operating point. We have automated this design process in Optimus to have a quick access to several ejector designs. With the range of applicable diameters, we use the OptInOpt, feature from Optimus, to understand the response of each gas ejector with fixed geometrical features to different flow conditions and thus study the designs under off-design operation.
The OptInOpt feature enables the user to run one Optimus workflow, along with the input files and the constraints defined in that workflow, in another Optimus workflow, with new relevant inputs and constraints for the new objectives. These results will enable the user to extract meaningful insights and understand how their product design will behave and respond to various constraints that are defined throughout the process.
From the Pareto Front shown above (Figure 2), we can see the compromise between supplying sufficient pressure to the reformer and pre-processing the fuel at once, thanks to the high steam-to-carbon ratio in the reformer. This enables the designer to see the feasibility of a no-moving, passive BoP component over a compressor, which requires power input and high maintenance.
The correlation scatter plot (Figure 3) gives insights to the users about the possibility to under-design the ejector for the primary and secondary flows to increase the back pressure operation range and to under-design it for the ejector back pressure to gain in the entrainment ratio. This gives the designer a basic understanding of the feasible design criteria that can be explored.
With Optimus, we can not only easily integrate Excel Macro, but various other Simulation tools, which makes the entire design process versatile. Using Optimus to automate your 1-D simulation tool has various advantages. The tool is very user-friendly, Pareto Front, Scatter Plot, and many other post-processing tools are accessible with just one click and results can be viewed at once. With Opt-in-Opt more complexity is added with minimum effort, providing value to the engineers and designers by quickly guiding them to pick their starting point for more complex processes.
At Noesis Solutions, we aim to enable innovation for our partners throughout the engineering design process, creating a competitive advantage for their products, while leveraging their resources in an economical way. Email us at email@example.com to know more about our solutions, services, and products.
For more details about this case study, watch this webinar - https://www.noesissolutions.com/webinars/muti-objective-optimization-using-1d-simulation-tool
About Noesis Solutions:
Established in 2003, Noesis Solutions, a trusted digital engineering innovation partner, has empowered customers adopt a transformational strategy that resolves their toughest multi-disciplinary engineering challenges of today. Our continuously evolving product portfolio, state-of-the-art technology, and unmatched customer services enable customers transform the way they build their products in a much faster and an efficient manner.
Noesis Solutions is a majority-owned subsidiary of Cybernet Systems, a leading provider of multi-domain CAE solutions covering a vast range of engineering problems. Headquartered in Leuven, Belgium, Noesis Solutions operates through a network of subsidiaries and representatives in key locations around the world.
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