Thermal response analysis and parameter prediction of additively manufactured polymers

Moslemi, Navid; Abdi, Behzad; Gohari, Soheil; Sudin, Izman; Atashpaz-Gargari, E.; Redzuan, Norizah; Ayob, Amran; Burvill, Colin; Su, Meini; Arya, Farid

doi:10.1016/j.applthermaleng.2022.118533

Cited by 17 publications

(3 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Numerical simulation of the hot-melt extrusion process of the base PEEK material is performed with COMSOL on the basis of the rolling process to form the fittings [21,22]. The simulation process assumes that PEEK does not exhibit any change in volume during melting and solidification, and the melted PEEK has a constant, uniform velocity throughout the modeling area.…”

Section: Hot-melt Pultrusion Of Rodsmentioning

confidence: 99%

Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming

Yan,

Li,

Geng

et al. 2024

Materials

View full text Add to dashboard Cite

A crimping and pultruding forming process for truss rods using Carbon Fiber (CF)/Polyether–Ether–Ketone (PEEK) prepreg tape as the raw material is proposed to address the problem of continuous manufacturing of space trusses on orbit. The proposed process provides material rods for continuous truss manufacturing. Through numerical simulation and experimental verification, the effects of relevant parameters on the forming process are determined, an efficient method of rod curl pultrusion, in-rail, equal material forming is proposed, and the structural configuration of the rod curl pultrusion forming mold is determined. The equivalent macroscopic mechanical properties of unidirectional CF/PEEK prepreg strips are considered, and the rod-forming process is investigated. Rod samples with different process parameters are prepared, and several tests are conducted on them. The results show that the forming load pull is negatively correlated with the temperature at the same forming speed, and forming speed is positively correlated with the forming load pull at a certain temperature. Temperature and speed affect the surface quality of the rod, the density of the material filling, and the mechanical properties of the rod. The optimal forming process parameters are determined through numerical simulation and experimental verification. The developed molding technology has the advantages of high efficiency, low energy consumption, and high integration. It reduces manufacturing costs and improves manufacturing efficiency, so it can serve as a new and effective solution for the manufacturing of high-performance truss rods in the aerospace field.

show abstract

Section: Hot-melt Pultrusion Of Rodsmentioning

confidence: 99%

Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming

Yan,

Li,

Geng

et al. 2024

Materials

View full text Add to dashboard Cite

show abstract

“…[27][28][29][30][31][32] Some notable exceptions combine studies of thermomechanical properties and ML. [33][34][35][36] This is particularly the case for mechanical performance and architecture.…”

mentioning

confidence: 99%

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

et al. 2023

View full text Add to dashboard Cite

Attaining optimum structural ceramic designs calls for an extensive search in a vast design space. Herein, the thermomechanical properties of interlocked ceramics are evaluated and an approach to assist their design under thermal shock loading is proposed. A combination of finite‐element (FE) and machine learning (ML) methods is used to simulate behaviors of systems and then to sweep the vast domain of input combinations to determine the best‐performing designs, respectively. First, FE modeling is done using a limited number of interlocking architectures with different design parameters via Comsol Multiphysics. The simulation data is used for training ML algorithms. Of the examined ML algorithms, Gaussian process regression (GPR), extreme gradient boosting (XGB), and neural networks (NN) more accurately predict the thermomechanical responses of the interlocking ceramics. After validation, the combination of FE and ML approaches is applied to thermal shielding and heat sink applications to find the optimal interlocked ceramics in terms of minimal out‐of‐plane deformation and maximal heat absorption, respectively. The results show the success of the approach in finding optimum designs in a space of more than 2 million cases. The striking success of the ML approach implies its promising potential for predicting physical properties of ceramics.

show abstract

“…En los procesos de moldeo por inyección tradicionales, el proceso de enfriamiento se produce más lentamente y casi simultáneamente en todo el volumen de la pieza, en cambio el proceso FDM se realiza capa a capa, sufriendo el material un rápido enfriamiento durante su deposición para posteriormente sufrir sucesivos recalentamientos durante la deposición de cada línea adyacente. Estos ciclos de calentamiento-enfriamiento van a tener gran influencia en la cristalinidad final del polímero y van a producir una reducción de las propiedades mecánicas de la pieza fabricada mediante FDM, y van a acumular tensiones internas en el material [81]. Otra diferencia importante entre ambos procesos es debida a que en el moldeo por inyección el termoplástico es sometido a una elevada presión, lo que lo ayuda a compactarse y elimina anisotropías en la pieza obtenida [82].…”

Section: Comparación Entre El Materials Procesado Por Fdm Y Por Molde...unclassified

Análisis y mejora del comportamiento dimensional de termoplásticos impresos en 3D mediante modelado por deposición fundida sometidos a un proceso de tratamiento térmico

Cerezo¹

View full text Add to dashboard Cite

show abstract

Thermal response analysis and parameter prediction of additively manufactured polymers

Cited by 17 publications

References 72 publications

Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming

Research and Validation of CF/PEEK-Based Truss Rod Crimping and Pultruding Process for On-Orbit Isoform Forming

Combining Finite Element and Machine Learning Methods to Predict Structures of Architectured Interlocking Ceramics

Análisis y mejora del comportamiento dimensional de termoplásticos impresos en 3D mediante modelado por deposición fundida sometidos a un proceso de tratamiento térmico

Contact Info

Product

Resources

About