Numerical Optimization of Nozzle Shapes for Fused Deposition Modeling

2025-11-26

AI Summary

In high-speed fused deposition modeling (FDM), nozzle geometry critically influences melt flow pressure loss, yet existing studies predominantly rely on conventional, fixed-geometry designs. Method: This work establishes a flexible shape optimization framework parameterized by both taper angle and B-spline profiles, integrated with a temperature-dependent shear-thinning viscosity model and an isothermal viscoelastic constitutive model. Comprehensive numerical simulations and comparative analyses are conducted across multiple processing conditions. Results: Under the viscous model, the optimal half-taper angle exhibits strong sensitivity to feed rate; viscoelastic effects markedly reduce this sensitivity. B-spline parameterization yields only marginal pressure drop reduction (<2%), confirming the engineering validity of simplified angular parameterization. The study demonstrates that constitutive model selection fundamentally governs the nozzle optimization trajectory, providing both theoretical insight and practical methodology for rational design of high-speed FDM nozzles.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Machine Learning: Optimization

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

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 sim- ple angle-based optimization and more advanced spline-based parametrization. To model the polymer melt flow, we compare two constitutive descriptions commonly employed in the literature: a temperature-dependent, shear-thinning viscous model and an isothermal viscoelastic model. Findings: For the viscous model, the optimal half-opening angle exhibits a strong dependence on the feeding rate, with higher rates favoring half-opening angles near 30°, whereas lower rates are more efficient at larger angles. In con- trast, the viscoelastic model predicts a weaker dependence of the optimal angle on the feeding rate. For both models, spline-based parametrization yields only marginal improvements over angle optimization in terms of reducing pressure loss. Originality/value: This paper presents a comparative study of FDM nozzle shape optimization using different simulation models. We introduce a flexible optimization framework that accommodates both simple and advanced geomet- ric parametrizations. The results highlight the impact of model choice on the optimal nozzle geometry and provide support for improving nozzle design in high-speed printing applications.

Problem

• Optimizing nozzle geometry to minimize pressure loss in FDM
• Comparing viscous and viscoelastic models for polymer melt flow
• Developing a flexible framework for nozzle shape parametrization

Innovation

• Optimized nozzle shape using angle and spline parametrization
• Compared viscous and viscoelastic polymer melt flow models
• Flexible framework for minimizing pressure loss in nozzles