Simulation-driven mold geometry optimization for corrugated pipes – Maximum strength with minimum material input

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Corrugated pipes are light in weight, but strong and flexible with considerably lower material demand compared to rigid pipes. The mechanical properties are mainly determined by the wall thickness distribution that is majorly governed by the mold geometry and the blowing parameters. Prediction of the wall-thickness distribution and subsequently achievable mechanical performance are one of the most critical aspects when designing a corrugated pipeline. Due to the scarcity of resources and cost pressure, efficient use of raw material is of increasing importance. It is therefore desired to produce corrugated pipes that meet the standards and requirements of the customer with minimal raw material input. To address these issues, first, multi-dimensional regression models for predicting the wall thickness distribution in corrugated pipes as function of the mold geometry and initial parison thickness were developed via symbolic regression modelling based on genetic programming. These models are based on a parametrically driven numerical blow molding simulation study. To ensure the reliability and performance of the created pipe geometry, the next step was to perform a finite element (FE) mechanical analysis and evaluate the ring stiffness of the pipe indicating of pipe strength. The obtained simulation results provide a correlation between the mold geometry and the mechanical strength of the corrugated pipe. These results will help to develop guidelines for producing a lightweight corrugated pipe that has the required mechanical performance with minimal material need, thus making an important contribution to sustainability and resource conservation.
Original languageEnglish
Title of host publicationAIP Conf. Proc. 2884, 040004 (2023)
Number of pages5
Volume2884
Edition1
DOIs
Publication statusPublished - 19 Oct 2023

Publication series

NameAIP Conference Proceedings
ISSN (Print)0094-243X

Fields of science

  • 205 Materials Engineering
  • 205011 Polymer engineering
  • 102009 Computer simulation
  • 102033 Data mining
  • 104018 Polymer chemistry
  • 502059 Circular economy
  • 205012 Polymer processing
  • 104019 Polymer sciences
  • 502058 Digital transformation

JKU Focus areas

  • Digital Transformation
  • Sustainable Development: Responsible Technologies and Management

Cite this