New One‐Dimensional Search Iteration Algorithm and Engineering Application

Luo, Yi-Ping; Meng, Jinhao; Wang, Defa; Xue, Guobin

doi:10.1155/2021/7643555

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…'Golden' in GSSM refers to this method's use of the golden ratio to determine the search parameters [28] by searching for an optimised solution value using proportionally equal search intervals [29]. The choice of GSSM is due to its availability in the optimisation libraries prebuilt into Python and the simplicity of its fundamental concepts and application [30]. For some applications, it is also more accurate and faster to converge than Newton's method [30].…”

Section: Further Optimisation In Step (F) Of Initial Channel Offset D...mentioning

confidence: 99%

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Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Wilson

Gupta²,

Patel³

et al. 2023

Preprint

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Effective cooling systems for injection moulding (IM) tools are critical to reducing manufacturing costs & cycle time for the polymer parts that they produce. This work presents a novel automated methodology for designing conformal cooling channels (CCCs) for injection moulding (IM) tools. This is done through existing commercial moulding simulation tools interlinked with custom scripts that adjust CCC design in response to the spatial variability in global andlocal temperature at the mould tool-part interface (MTPI). Four mould tool designs for a hollow cylinder were developed and analysed via both numerical simulation and experiments. These include (i) conventional IM tool with straight-drilled cooling channels made of tool steel, (ii) a manually designed CCC system with stainless steel, (iii) copper-aluminium bronze ‘core’ andstainless steel ‘shell’ with CCCs identical to (ii), and (iv) stainless steel with a CCC system automatically designed using generative design (GD) driven by a genetic algorithm. Tool (ii) cooled the part faster than conventional tool with a manually designed CCC system (i) (3-5% predicted vs. 40% measured), as did tool (iii) with the bronze core (9-12% predicted vs. 40% measured). The GD-optimised CCC tool (iv) cooled fastest in both the predicted results (15-30%, 11-25% & 1.5-25% faster than (i), (ii) & (iii)) andmeasured results (70%, 50% & 50% for (i), (ii) & (iii)). The predicted MTPI temperatures were also lower for the GD-optimised tool (65%, 75% & 34% below (i), (ii) & (iii)). Therefore, the novel methodology proposed here for automatically designing IM tool CCCs achieves reduced (a) maximum andspatial variability in MTPI temperatures, (b) cooling time, and (c) warpage.

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Section: Further Optimisation In Step (F) Of Initial Channel Offset D...mentioning

confidence: 99%

“…The choice of GSSM is due to its availability in the optimisation libraries prebuilt into Python and the simplicity of its fundamental concepts and application [30]. For some applications, it is also more accurate and faster to converge than Newton's method [30].…”

Section: Further Optimisation In Step (F) Of Initial Channel Offset D...mentioning

confidence: 99%

Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Wilson

Gupta²,

Patel³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The iterative formula of this technique [1] is based on the ratios of two consecutive terms of Fibonacci sequence. Over the last few decades, a number of modifications of the Fibonacci search technique were done by the several researchers [2][3][4][5][6][7][8][9] by considering different aspects.…”

Section: Introductionmentioning

confidence: 99%

Extensions of Fibonacci Search Technique for One Dimensional Interval Optimization Problem

Rahman,

Khatun,

Bhunia

2023

Preprint

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Fibonacci Search Technique is one of the familiar iterative methods for solving one dimensional unconstrained optimization problem with highly non-linear/non-differentiable objective function. However, sometimes objective function becomes inexact/imprecise in nature due to the uncertainty. To deal with such imprecise problem, present article focuses on an extension of Fibonacci Search technique whose algorithm is developed based on interval order relations. In this work, first of all, two different types of optimizers (maximizer/minimizer) viz., c-L optimizer, c-r optimizer, of an interval valued function are introduced based on different order relations. After that a result regarding the relation between said optimizers are established. Then, Fibonacci search type algorithms are developed for all types of optimizers. Finally, the said algorithms are illustrated with a number of numerical examples.

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Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Wilson,

Gupta,

Patel

et al. 2024

Int J Adv Manuf Technol

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Effective cooling systems for injection moulding (IM) tools are critical to reducing manufacturing costs and cycle time for the polymer parts produced. This work presents a novel automated methodology for designing conformal cooling channels (CCCs) for IM tools via interlinking commercial moulding simulation tools with custom scripts. These scripts adjust CCC design in response to the spatial variability in global and local temperatures at the mould tool-part interface (MTPI) via generative design (GD). Four tool designs for manufacturing a simplified part were analysed numerically simulation and experimentally, including tools with either straight-drilled (non-conformal) cooling channels (tool steel), a manually designed CCC system (stainless steel or bronze alloy), or an automatically designed CCC system (stainless steel). While both manually designed CCC tools cool the part faster than the non-conformal tool (3–5% predicted vs. 40% measured for stainless steel and 9–12% predicted vs. 40% measured for bronze alloy), the GD-optimised CCC tool outperformed both (15–30% predicted faster cooling vs. 70% measured). The predicted MTPI temperature feature achieves reductions to both maximum and spatial variability in MTPI temperatures, which lead directly to significant reductions in manufacturing cycle time and polymer part warpage. These findings could have a major impact on the IM industry by reducing tool design costs and raw material waste via improving moulded part quality.

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New One‐Dimensional Search Iteration Algorithm and Engineering Application

Cited by 4 publications

References 13 publications

Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

Extensions of Fibonacci Search Technique for One Dimensional Interval Optimization Problem

Generative design of conformal cooling channels for hybrid-manufactured injection moulding tools

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