Thermomechanical Fatigue Analysis of Cylinder Head

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Summary. We discuss a methodology for systematically using an Simulation Process and Data Management (SPDM) platform in product development. The purpose of this paper is to get the reader acquianted with the concept and the importance of such an approach. The target is to base product development on clearly defined targets and requirements in different phases of the product development lifecycle. This is achieved by means of a data-centered approach where all data is retained in a digital form in the platform. Instead of reporting, users are provided with different views to the same data. We will discuss how a static document-based validation system can be replaced by a common validation data platform. In addition, we aim to base the validation requirements on a reliability analysis workflow.In this case, the platform is used not only to handle the simulation data but to encompass the whole product validation scope. To this end, the fundamental concept of our data management approach is to couple the requirements directly to the simulations and handle all the design decision data together with the simulations using these to drive the design.The motivation for the activity is a dramatic reduction in product development time based on a possibly longer concept phase but less iterations during the detail design phase. Future developments will include moving also the physical testing data and coupling that with the corresponding simulations and validation requirements.

Section: Simulation Process and Data Management Solutionmentioning

confidence: 99%

Wärtsilä Digital Design Platform

Könnö¹,

Tienhaara²,

Frondelius³

2017

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“…Wilson acknowledged that crack initiation is often controlled by nonmetallic inclusions but the strain age hardening retards the stage I crack propagation by suppression of the plastic zone. Understanding the strain age hardening will become more important in future, especially for applications like cylinder heads [13].…”

Section: Strain Age Hardeningmentioning

confidence: 99%

Brief review on high-cycle fatigue with focus on non-metallic inclusions and forming

Vaara¹,

Mäntylä²,

Frondelius³

2017

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Summary. Professor Y. Murakami has been a dominant figure in the field of fatigue, pinpointing the most important things for research. However, in order to further improve the prediction methods, knowing the history, discussions and decisions in the fatigue community are necessary. This paper aims to give a brief and historical review on various high-cycle fatigue phenomena focused around non-metallic inclusions and forming.

“…Sequential D-optimal design has been used in this work for choosing the next test level. This way the amount of information from tests is maximized and the precision of further analyses [14,5,9] increases in the product design process [7]. Bayesian statistics is seen as a natural tool for this kind of problem providing an easy way of introducing engineering prior knowledge and uncertainty to the mathematical model (see Model section for more).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Sequential Experimental Design for Fatigue Tests

Väntänen¹,

Vaara²,

Aho³

et al. 2017

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Summary.A Bayesian sequential experimental design for fatigue testing based on D-optimality and a non-linear continuous damage model was implemented. The model has two asymptotes for the number of cycles to failure: the fatigue limit and the ultimate tensile strength. With the introduction and stochastic handling of these asymptotes, the D-optimal design accounts naturally for the whole range of reasonable testing levels. Sequential design ensures that all the available data is used efficiently while choosing the next test level.