Spannungsoptimierung von Pressverbänden mit additiv gefertigten Naben – Numerische und experimentelle Untersuchungen

Kröger, J.; Binz, Hansgeorg; Wagner, M.

doi:10.51202/9783181023372-199

Cited by 4 publications

(8 citation statements)

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“…Section 3.1). Simple geometric optimization options already exist (Leidich, 1983;Kollmann, 1984), but these suffer from various disadvantages (Kröger et al, 2018) (cf. Section 3.2).…”

Section: Discussionmentioning

confidence: 99%

“…In the event of an extreme drop in pressure within the joint, the joint may even slip. Previous research work, such as (Blacha, 2009;Krautter et al, 2015;Kröger et al, 2018), has already developed a variety of solutions for the optimization of shrink fits. However, these approaches are not yet suitable for general application due to their high complexity and lack of general calculation approaches; they often represent only approximate iterative solutions, and their application is time-consuming.…”

Section: Problem Statement and Objectivementioning

confidence: 99%

“…DI/DO, L/DI) that influence the stiffness of the shrink fit can also influence the stress increase. The results in (Figure 2) based on research completed in (Kröger et al, 2018) illustrates the effects of different geometric dimensions on the stress increase.…”

Section: Stress Condition On Cylindrical Shrink Fitsmentioning

confidence: 99%

“…In addition, the trend toward higher utilization of material properties in terms of higher power densities and lightweight design causes reductions in the existing safety margins previously contributed by the ductility of hub materials; thus failures due to excessive stress can occur here also. Simple approaches to reduce stress peaks (see Section 3.2) do not offer sufficient solutions to this problem (Kollmann, 1984;Kröger et al, 2018;Mather et al, 1972). However, complex adjustments of the shaft outer or hub inner contour can achieve the goal of eliminating undesirable variations of the pressure within the joint and/or the failure-critical principal stress.…”

Section: Concretization Of the Problem And Requirements For An Aimentioning

confidence: 99%

“…Figure 7, center). In order to validate the gained results, a proven indirect method (Ulrich et al, 2016;Kröger et al, 2018;Kröger et al, 2020) was chosen, since there is no direct method to measure the pressure within the interstice. This indirect method compares the diameter expansion of the hub within the experiment and the numerical calculation.…”

Section: Table 1 Overview Of Defined Valuesmentioning

confidence: 99%

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An AI-Based Approach to Optimize Stress in Shrink Fits

2022

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The present analytical design of shrink fits typically results in an uneven stress condition that can lead to failure in a variety of manners. With increasing loads and the use of brittle materials, the optimization of the stresses in the shrink fit hence becomes increasingly necessary. Currently existing approaches do not solve the problem satisfactorily or increase the manufacturing and design effort. This paper therefore considers the implementation of an AI-based stress optimization using reinforcement learning, which performs stress optimization by geometrically contouring the interstice.

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“…Section 3.1). Simple geometric optimization options already exist (Leidich, 1983;Kollmann, 1984), but these suffer from various disadvantages (Kröger et al, 2018) (cf. Section 3.2).…”

Section: Discussionmentioning

confidence: 99%

Section: Problem Statement and Objectivementioning

confidence: 99%

Section: Stress Condition On Cylindrical Shrink Fitsmentioning

confidence: 99%

Section: Concretization Of the Problem And Requirements For An Aimentioning

confidence: 99%

Section: Table 1 Overview Of Defined Valuesmentioning

confidence: 99%

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An AI-Based Approach to Optimize Stress in Shrink Fits

2022

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Investigations on design limits and improved material utilization of press-fit connections using elastic-plastic design

Falter

Binz

Kreimeyer

2023

Applications in Engineering Science

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Artificial Intelligence Techniques for Improving Cylindrical Shrink-Fit Shaft-Hub Couplings

et al. 2023

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Due to the continuous progress in information technology, complex problems of machine elements can be investigated using numerical methods. The focus of these investigations and optimizations often aims to reduce the stresses that occur or to increase the forces and torques that can be transmitted. Interference fit connections are an essential machine element for drive technology applications and are characterized by their economical fabrication. The transmission of external loads over a large contact surface between the shaft and hub makes it less vulnerable to impact loads. These advantages contrast with disadvantages such as the limited transmittable power, the risk of friction fatigue, and stress peaks at the hub edges, which can lead to undesirable and sudden failure, especially in the case of brittle hub materials. Analytical approaches already exist for optimizing these connections, which are expensive, time-consuming, and complex, so a high degree of expert knowledge is required to apply these methods in practice successfully. This paper presents a novel method using the example of optimizing the pressure distribution in the interface of a shrink-fit connection.

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Spannungsoptimierung von Pressverbänden mit additiv gefertigten Naben – Numerische und experimentelle Untersuchungen

Cited by 4 publications

References 0 publications

An AI-Based Approach to Optimize Stress in Shrink Fits

An AI-Based Approach to Optimize Stress in Shrink Fits

Investigations on design limits and improved material utilization of press-fit connections using elastic-plastic design

Artificial Intelligence Techniques for Improving Cylindrical Shrink-Fit Shaft-Hub Couplings

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