CEMay 14

Numerical Optimization of Planar Nozzle Shapes for Fused Deposition Modeling

arXiv:2511.214497.4h-index: 3
Predicted impact top 58% in CE · last 90 daysOriginality Synthesis-oriented
AI Analysis

For FDM practitioners, this provides a systematic comparison showing that simple angle optimization is sufficient for pressure-loss reduction, avoiding complex designs that hinder manufacturability.

This work optimizes nozzle shapes for FDM to minimize pressure loss, finding that simple angle-based optimization achieves most of the pressure reduction (with two local minima) while spline-based parametrization offers marginal additional gains but reduces manufacturability.

Purpose: In fused deposition modeling (FDM), the nozzle plays a critical role in enabling high printing speeds while maintaining precision. Despite its importance, most applications still rely on standard nozzle designs. This work investigates the influence of nozzle geometry on pressure loss inside the nozzle, a key factor in high-speed printing performance. Design/methodology/approach: We focus on optimizing the nozzle shape to minimize the pressure loss and establish a framework that allows both simple angle-based optimization and more advanced spline-based parametrization. To model the polymer melt flow, we use a Giesekus model to account for viscoelastic effects. Findings: For angle-based optimization, the pressure-loss objective exhibits two local minima: one associated with smooth flow and another with pronounced recirculation regions inside the nozzle. While the latter yields a lower pressure drop, such flow patterns are generally undesirable due to increased residence times and the associated risk of material degradation and nozzle clogging. The splinebased parametrization results in only marginal additional reductions in pressure loss compared to angle optimization, while decreasing the manufacturability of the nozzle considerably. Originality/value: This paper presents a comparative study of FDM nozzle shape optimization using a Giesekus model. We introduce a flexible optimization framework that accommodates both simple and advanced geometric parametrizations. The main contribution is the systematic comparison between angle- and spline-based parametrizations across materials and extrusion velocities, showing that most of the achievable pressure-loss reduction is already captured by the simpler and more manufacture-ready angle optimization.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes