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Article
Publication date: 2 May 2023

Taha Sheikh and Kamran Behdinan

This paper aims to present a geometrical void model in conjunction with a multiscale method to evaluate the effect of interraster distance, bead (raster) width and layer height…

Abstract

Purpose

This paper aims to present a geometrical void model in conjunction with a multiscale method to evaluate the effect of interraster distance, bead (raster) width and layer height, on the voids concentration (volume) and subsequently calculate the final mechanical properties of the fused deposition modeling parts at constant infill.

Design/methodology/approach

A geometric model of the voids inside the representative volume element (RVE) is combined with a two-scale asymptotic homogenization method. The RVEs are subjected to periodic boundary conditions solved by finite element (FE) to calculate the effective mechanical properties of the corresponding RVEs. The results are validated with literature and experiments.

Findings

Bead width from 0.2 to 0.3 mm, reported a decrease of 25% and 24% void volume for a constant layer height (0.1 and 0.2 mm – 75% infill). It is reported that the void’s volume increased up to 14%, 32% and 36% for 75%, 50% and 25% infill by varying layer height (0.1–0.2  and 0.3 mm), respectively. For elastic modulus, 14%, 9% and 10% increase is reported when the void’s volume is decreased from 0.3 to 0.1 mm at a constant 75% infill density. The bead width and layer height have an inverse effect on voids volume.

Originality/value

This work brings values: a multiscale-geometric model capable of predicting the voids controllability by varying interraster distance, layer height and bead width. The idealized RVE generation slicer software and Solidworks save time and cost (<10 min, $0). The proposed model can effectively compute the mechanical properties together with the voids analysis.

Details

Rapid Prototyping Journal, vol. 29 no. 8
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 15 December 2022

Taha Sheikh and Kamran Behdinan

This paper aims to present a hierarchical multiscale model to evaluate the effect of fused deposition modeling (FDM) process parameters on mechanical properties. Asymptotic…

96

Abstract

Purpose

This paper aims to present a hierarchical multiscale model to evaluate the effect of fused deposition modeling (FDM) process parameters on mechanical properties. Asymptotic homogenization mathematical theory is developed into two scales (micro and macro scales) to compute the effective elastic and shear modulus of the printed parts. Four parameters, namely, raster orientation, layer height, build orientation and porosity are studied.

Design/methodology/approach

The representative volume elements (RVEs) are generated by mimicking the microstructure of the printed parts. The RVEs subjected to periodic boundary conditions were solved using finite element. The experimental characterization according to ASTM D638 was conducted to validate the computational modeling results.

Findings

The computational model reports reduction (E1, ∼>38%) and (G12, ∼>50%) when porosity increased. The elastic modulus increases (1.31%–47.68%) increasing the orthotropic behavior in parts. Quasi-solids parts (100% infill) possess 10.71% voids. A reduction of 11.5% and 16.5% in elastic modulus with layer height is reported. In total, 45–450 oriented parts were highly orthotropic, and 0–00 parts were strongest. The order of parameters affecting the mechanical properties is porosity > layer height > raster orientation > build orientation.

Originality/value

This study adds value to the state-of-the-art terms of construction of RVEs using slicing software, discarding the necessity of image processing and study of porosity in FDM parts, reporting that the infill density is not the only measure of porosity in these parts.

Details

Rapid Prototyping Journal, vol. 29 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 6 July 2015

Hyeong-Uk Park, Jae-Woo Lee, Joon Chung and Kamran Behdinan

The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design optimization…

Abstract

Purpose

The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design optimization methods. Reliability-Based Design Optimization (RBDO), Possibility-Based Design Optimization (PBDO) and Robust Design Optimization (RDO) methods were developed to handle uncertainties of design optimization. The RBDO method is found suitable for uncertain parameters when sufficient information is available. On the other hand, the PBDO method is proposed when uncertain parameters have insufficient information. The RDO method can apply to both cases. The RBDO, PBDO and RDO methods were considered with the Multidisciplinary Design Optimization (MDO) method to generate conservative design results when low fidelity analysis tools are used.

Design/methodology/approach

Methods combining MDO with RBDO, PBDO and RDO were developed and have been applied to a numerical analysis and an aircraft conceptual design. This research evaluates and compares the characteristics of each method in both cases.

Findings

The RBDO result can be improved when the amount of data concerning uncertain parameters is increased. Conversely, increasing information regarding uncertain parameters does not improve the PBDO result. The PBDO provides a conservative result when less information about uncertain parameters is available.

Research limitations/implications

The formulation of RDO is more complex than other methods. If the uncertainty information is increased in aircraft conceptual design case, the accuracy of RBDO will be enhanced.

Practical implications

This research increases the probability of a feasible design when it considers the uncertainty. This result gives more practical optimization results on a conceptual design level for fabrication.

Originality/value

It is RBDO, PBDO and RDO methods combined with MDO that satisfy the target probability when the uncertainties of low fidelity analysis models are considered.

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