Simultaneous design of non-Newtonian lubricant and surface texture using surrogate-based multiobjective optimization

Lee, Yong Hoon; Schuh, Jonathon K.; Ewoldt, Randy H.; Allison, James T.

doi:10.1007/s00158-019-02201-1

Cited by 9 publications

(6 citation statements)

References 40 publications

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“…These studies are primarily analyses focused on insights into cause and effect rather than the inverse problem of design, yet they lay the groundwork for possible design questions related to optimal rheology. This is a challenging task that will require concepts of codesign (Lee et al 2019), since the microswimmer shape and locomotion kinematics (gait) also create design freedom that couples with fluid rheology to result in locomotion.…”

Section: Which Complexity Comes First?mentioning

confidence: 99%

“…With few exceptions (see the sidebar titled Boger Fluid Design and Decoupled Rheology), normal stress is accompanied by shear thinning, and increasing the N 1 effect increases the overall viscosity, which may be undesirable. This trade-off was considered from a design perspective with hydraulic thrust bearings (Figure 4b) by Lee et al (2019), whose results are shown in Figure 6. Their study applied realistic model selection, surrogate modeling, and multiobjective design methods to consider codesign of both the fluid rheology and the thrust-bearing surface topography.…”

Section: Boger Fluid Design and Decoupled Rheologymentioning

confidence: 99%

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Designing Complex Fluids

Ewoldt

2022

Annu. Rev. Fluid Mech.

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Taking a small step away from Newtonian fluid behavior creates an explosion in the range of possibilities. Non-Newtonian fluid properties can achieve diverse flow objectives, but the complexity introduces challenges. We survey useful rheological complexity along with organizing principles and design methods as we consider the following questions: How can non-Newtonian properties be useful? What properties are needed? How can we get those properties? Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 54 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Section: Which Complexity Comes First?mentioning

confidence: 99%

Section: Boger Fluid Design and Decoupled Rheologymentioning

confidence: 99%

Designing Complex Fluids

Ewoldt

2022

Annu. Rev. Fluid Mech.

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“…In recent years, the use of textured surfaces to reduce friction and improve the antiwear properties of tribological couplings has been gaining popularity [13][14][15]. Laser surface texturing is widely used in the industry, and its positive effects have been theoretically predicted and experimentally confirmed [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

A Method for Mathematical Modeling of Hydrodynamic Friction of Plunger Pairs with Consideration of Microgeometry

2023

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The fuel injection system heavily relies on the high-pressure fuel pump, which plays a critical role in its overall performance. The fuel pump plunger is subjected to high levels of stress and experiences irregular lubrication during dynamic loads, causing premature wear. In the industrial sector, laser surface micro-texturing has been utilized to reduce friction and enhance anti-wear properties, and its positive impact has been supported by both theoretical and experimental evidence. This article presents a method for determining the hydromechanical characteristics of plunger pairs under conditions of hydrodynamic friction. The microgeometry of friction surfaces was taken into account through the cavitation effect of the lubricating fluid, described by the modified Reynolds equation. Software was developed according to the proposed method. The developed software can be used to analyze the contacting surfaces of plunger pairs and evaluate their tribotechnical characteristics based on the microgeometry parameters of the friction surfaces. The article also discusses the impact of the microgeometry parameters on the quality criteria of the hydromechanical characteristics of the plunger pairs. Computational examples are given for the analysis of contacting surfaces of plunger pairs separated by a lubrication layer. The technical characteristics are evaluated depending on the parameters of the microgeometry of the roughness of the friction surfaces. The influence of the microgeometry parameters on the quality criteria of the hydromechanical characteristics of the plunger pairs is presented.

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“…Zhou et al constructed a smoother error function to fit the target parameters and the physical properties of the material [11]. Among the above methods, the inverse analysis method based on optimization theory is widely used in the geotechnical field and has achieved good application results [12,13]. Different methods have their own advantages and disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Parameter Determination Method of Soil Constitutive Model Based on Machine Learning

Song

Liu

Jiang

et al. 2022

Wireless Communications and Mobile Computing

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In order to better determine the model parameters and improve the safety and stability of construction, an optimized identification method of constitutive model parameters with improved RCGA is proposed by combining the current optimization theory. The experimental results indicate that the improved RCGA algorithm proposed in the study has stronger recognition capabilities and optimization effects than the traditional NSGA-II algorithm and determine the parameters of the constitutive model more accurately. Moreover, it is found that the parameters obtained by the proposed improved algorithm have validity and accuracy, when parameter P 0 ′ = 50 kPa, comparing the obtained optimal parameters with the real laboratory clay parameters.

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Simultaneous design of non-Newtonian lubricant and surface texture using surrogate-based multiobjective optimization

Cited by 9 publications

References 40 publications

Designing Complex Fluids

Designing Complex Fluids

A Method for Mathematical Modeling of Hydrodynamic Friction of Plunger Pairs with Consideration of Microgeometry

Parameter Determination Method of Soil Constitutive Model Based on Machine Learning

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