Engineering Design Iteration Challenges
Engineering design is inherently iterative. Achieving demanding performance, efficiency, and reliability targets requires continual refinement. Engineers are often tasked with optimizing complex geometries and flow environments, where even small shape modifications can deliver substantial gains—or introduce unexpected performance issues.
Traditional design workflows rely heavily on manual modifications and time-consuming CFD simulations, often leading to extended development timelines and increased resource consumption. The need for rapid, data-driven design changes without excessive computational overhead is a persistent challenge in industrial engineering environments.
Gradient-based optimization, when paired with the adjoint solver, offers a step-change improvement in CFD-based design iteration. The adjoint solver in Ansys Fluent enables engineers to automatically determine the sensitivity of performance objectives (such as pressure drop, flow uniformity, or drag/lift) with respect to shape changes, reducing the number of simulations required for optimization.
By computing gradients for all design variables in a single solve, the adjoint method accelerates the optimization loop, provides clear guidance on which geometric changes matter most, and enables engineers to converge on superior designs with less trial and error. This approach is especially beneficial in industry applications, where reducing development cycles can significantly impact time-to-market and operational efficiency.
These are the main steps for the gradient-based optimization in Fluent
We first need to set up the primary CFD simulation by establishing geometry, mesh, boundary conditions, and solving for the initial flow solution.
Fluent has a gradient-based Optimizer tool that automates the design-iteration process for shape optimization, allowing us to achieve a specified target objective without manually repeating each step for every design iteration.
Fluent’s integrated workflow enables direct geometry modification based on these sensitivities, allowing engineers to iteratively morph the shape to meet target performance—without exporting to separate CAD or CFD tools. Final validation is then performed by running a full CFD solution on the optimized configuration, confirming the performance gains before committing to physical prototyping or production.
The gradient-based optimization and adjoint solver are used to modify the bend pipe shape for a reduction in pressure drop along the pipe from inlet to outlet. These three videos demonstrate the workflow
Video 1: Adjoint solver
Video 2: Optimize the pipe design
Video 3: Design iterations
Engineers using the adjoint solver in Ansys Fluent should begin with a high‑quality mesh, a validated baseline CFD solution, and clear objective functions and constraints. They then apply Fluent’s shape morphing, automation, and sensitivity analyses to iterate quickly, identify key design drivers, and validate results with engineering judgment and experimental data to get robust, manufacturable designs. In mining, energy, and heavy equipment, embedding this adjoint workflow in existing simulation processes speeds design iteration, cuts physical prototyping costs, and delivers products optimized for real operating conditions while supporting collaboration, compliance, reliability, and operational performance.
Ozen Engineering Inc. leverages its extensive consulting expertise in CFD, FEA, thermal, optics, photonics, and electromagnetic simulations to achieve exceptional results across various engineering projects, addressing complex challenges like stirred mixing systems using Ansys software.
We offer support, mentoring, and consulting services to enhance the performance and reliability of your systems. Trust our proven track record to accelerate projects, optimize performance, and deliver high-quality, cost-effective results for both new and existing stirred mixing systems. For more information, please visit https://ozeninc.com.