Optimization of a thermal manufacturing process: Drawing of optical fibers

Cheng, Xu; Jaluria, Yogesh

doi:10.1016/j.ijheatmasstransfer.2005.03.012

Cited by 29 publications

(8 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, higher fiber quality reduces wastage and again saves costs and energy. All these quantities may be combined into a single composite objective function [17]. Otherwise, mutiobjective optimization, leading to Pareto frontiers, may be undertaken.…”

Section: Optical Fiber Drawingmentioning

confidence: 99%

Optimization of Thermal Systems to Reduce Energy Consumption and Environmental Effect

Jaluria¹

2019

TI-IJES

Self Cite

View full text Add to dashboard Cite

Thermal systems, which are based on heat and mass transfer, fluid flow and thermodynamics, arise in a wide variety of applications. It has become critical to optimize thermal processes in order to reduce energy consumption and the environmental effect, while increasing the productivity and product quality. This paper discusses the optimization of thermal systems in order to achieve the best output with respect to energy and the environment. Systems from several important application areas, such as manufacturing, thermal management of electronics, and heat rejection are considered. These systems are generally quite complex due to variable material properties, uncertainties, combined transport mechanisms, complex domains and boundary conditions, and multiscale phenomena. Therefore, the modelling and simulation of these systems is quite involved and considerable care is needed to obtain accurate results. Simulation results, along with experimental data, are used for prediction of the behaviour of systems, as well as their design and optimization. The paper focuses on the reduction in energy and material consumption and the environmental effect. However, it is also important to enhance the output and improve the quality of the product obtained. The important aspects that must be considered and the approaches that may be adopted are discussed in detail. In most practical situations, several objectives are of interest and multi-objective design optimization is necessary. Results for a few important systems are presented in order to illustrate the basic approach.

show abstract

Section: Optical Fiber Drawingmentioning

confidence: 99%

Optimization of Thermal Systems to Reduce Energy Consumption and Environmental Effect

Jaluria¹

2019

TI-IJES

Self Cite

View full text Add to dashboard Cite

show abstract

“…Later computational research efforts adopted more sophisticated computational schemes for the prediction of neck-down profile formation which is interactively associated with the two-dimensional axisymmetric thermal modeling of radiative preform heating and convective flow of purge gas inside the draw furnace (Cheng and Jaluria, 2005;Chen and Jaluria, 2009;Lee et al, 2006;Mawardi and Pitchumani, 2010;Kim et al,, 2012). The other approach in predicting neck-down profile was to treat the glass preform deformation as free surface flow which profile was determined by kinematic condition (Wei et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…The other approach in predicting neck-down profile was to treat the glass preform deformation as free surface flow which profile was determined by kinematic condition (Wei et al, 2004). In addition to developing the efficient numerical methods, some computational investigations focused on several important process characteristics such as effects of draw furnace geometry (Cheng and Jaluria, 2002), process optimization by various design parameters (Cheng and Jaluria, 2005), effects of adding dopant (Yan and Pitchumani, 2006;Chen and Jaluria, 2009), and the role of helium addition in argon-based purge gas (Kim et al,, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, the preform diameter in the previous theoretical and computational studies of glass fiber drawing has been limited to less than 5 cm in 1990s (Imoto et al, 1989;Lee and Jaluria, 1997;Choudhury and Jaluria, 1998) and less than 10 cm in 2000s (Cheng and Jaluria, 2005;Wei et al, 2004;Kim et al, 2012). Therefore, it would be necessary to investigate the size effects of enlarged preform on every aspect of drawing process (such as formation of neck-down profile, draw tension, fiber cooling) as well as the validity of modeling approaches, while the fiberoptics industries are constantly demanding stable process techniques with larger sized preform at higher drawing speed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Numerical modeling and analysis of glass fiber drawing process from large sized silica preform

Kim

Choi

Kwak

et al. 2017

JTST

View full text Add to dashboard Cite

As fiberoptics industries have been attempting to use a silica preform of larger diameter in order to reduce facility down time and increase optical fiber manufacturing productivity, this computational study investigates how the use of large sized preform in sized up draw furnace affects high speed glass fiber drawing process. Present computational model for glass fiber drawing simulations employs iterative scheme between one-dimensional momentum balance model for neck-down profile of heated and softened preform and two-dimensional axisymmetric thermo-fluid computations of convective and radiative heat transport for preform heating and purge gas flow inside muffle tube. Prediction of preform neck-down shape for 10 cm diameter preform has been verified with measured profile from actual optical fiber drawing test. The effects of larger preform diameter up to 20 cm are appreciated and discussed on temperature distribution of preform and drawn glass fiber and fiber draw tension. This study also shows that fine control of heating condition is necessary to maintain proper amount of draw tension in high precision glass fiber drawing.

show abstract

“…In each step of the optimization procedure, the search direction in terms of optimization variables has to be found [17][18][19]. The cycle continues until the merit function is sufficiently small.…”

Section: Introductionmentioning

confidence: 99%

Support vector machine firefly algorithm based optimization of lens system

et al. 2014

View full text Add to dashboard Cite

Lens system design is an important factor in image quality. The main aspect of the lens system design methodology is the optimization procedure. Since optimization is a complex, nonlinear task, soft computing optimization algorithms can be used. There are many tools that can be employed to measure optical performance, but the spot diagram is the most useful. The spot diagram gives an indication of the image of a point object. In this paper, the spot size radius is considered an optimization criterion. Intelligent soft computing scheme support vector machines (SVMs) coupled with the firefly algorithm (FFA) are implemented. The performance of the proposed estimators is confirmed with the simulation results. The result of the proposed SVM-FFA model has been compared with support vector regression (SVR), artificial neural networks, and generic programming methods. The results show that the SVM-FFA model performs more accurately than the other methodologies. Therefore, SVM-FFA can be used as an efficient soft computing technique in the optimization of lens system designs.

show abstract

Optimization of a thermal manufacturing process: Drawing of optical fibers

Cited by 29 publications

References 23 publications

Optimization of Thermal Systems to Reduce Energy Consumption and Environmental Effect

Optimization of Thermal Systems to Reduce Energy Consumption and Environmental Effect

Numerical modeling and analysis of glass fiber drawing process from large sized silica preform

Support vector machine firefly algorithm based optimization of lens system

Contact Info

Product

Resources

About