PSI - Issue 57

Available online at www.sciencedirect.com Available online at www.sciencedirect.com Available online at www.sciencedirect.com

ScienceDirect

Procedia Structural Integrity 57 (2024) 718–730 Structural Integrity Procedia 00 (2023) 000–000 Structural Integrity Procedia 00 (2023) 000–000

www.elsevier.com / locate / procedia www.elsevier.com / locate / procedia

© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0 ) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers. Keywords: Fatigue; Reliability; Monte Carlo; Design Of Experiments (DOE); Reduced Order Modelling (ROM); Weibull Abstract Across all industries, it is becoming increasingly necessary to qualify components based on their reliability and risk of failure. This paper considers how the existing design, simulation, verification, and validation process, may be enhanced to o ff er significant improvements in predicted confidence. Particular attention is paid to simulating the variability and uncertainty of fatigue life predictions. This allows simulation to be better verified using evidence from fewer qualification tests. The paper highlights the need for additional low-cost measurements during qualification testing, and a need to test to failure. It considers how Reduced Order Modelling, Design of Experiments, and statistical reliability analysis, are used in simulating the variability and uncertainty of fatigue failure. It demonstrates how simulation and physical tests mutually benefit one another, and concludes with a case study comparing simulated variability and uncertainty with the values measured in a typical qualification test. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers. Keywords: Fatigue; Reliability; Monte Carlo; Design Of Experiments (DOE); Reduced Order Modelling (ROM); Weibull Fatigue Design 2023 (FatDes 2023) Achieving high confidence in fatigue reliability by quantifying the e ff ects of uncertainty Andrew Halfpenny a , Amaury Chabod b, ∗ , Balaje Thumati c , TudorMiu a a Hottinger Bruel & Kjaer UK Ltd. AMP Technology Centre, Brunel Way, Catcli ff e, S60 5WG, UK. b Hottinger Bruel & Kjaer France, 2-4 rue Benjamin Franklin, 94370 Sucy-en-brie, France c Hottinger Bruel & KjaerUSA Abstract Across all industries, it is becoming increasingly necessary to qualify components based on their reliability and risk of failure. This paper considers how the existing design, simulation, verification, and validation process, may be enhanced to o ff er significant improvements in predicted confidence. Particular attention is paid to simulating the variability and uncertainty of fatigue life predictions. This allows simulation to be better verified using evidence from fewer qualification tests. The paper highlights the need for additional low-cost measurements during qualification testing, and a need to test to failure. It considers how Reduced Order Modelling, Design of Experiments, and statistical reliability analysis, are used in simulating the variability and uncertainty of fatigue failure. It demonstrates how simulation and physical tests mutually benefit one another, and concludes with a case study comparing simulated variability and uncertainty with the values measured in a typical qualification test. Fatigue Design 2023 (FatDes 2023) Achieving high confidence in fatigue reliability by quantifying the e ff ects of uncertainty Andrew Halfpenny a , Amaury Chabod b, ∗ , Balaje Thumati c , TudorMiu a a Hottinger Bruel & Kjaer UK Ltd. AMP Technology Centre, Brunel Way, Catcli ff e, S60 5WG, UK. b Hottinger Bruel & Kjaer France, 2-4 rue Benjamin Franklin, 94370 Sucy-en-brie, France c Hottinger Bruel & KjaerUSA

1. Introduction 1. Introduction

In the aerospace, automotive, and power generation industries, it is becoming increasingly necessary to qualify components based on their reliability or risk of failure. For example, all new EVs (Electric Vehicles) sold in the US require an 8-year or 100,000 mile (160,000 km) battery warranty. EV batteries are complex mechanical structures that support dynamic masses, and transmit loads and vibration through thousands of joints and components. Fatigue failure therefore presents a significant risk to the overall reliability of the battery system. The design requirement over a population of EVs is expressed in terms of a statistical reliability target, for example: In the aerospace, automotive, and power generation industries, it is becoming increasingly necessary to qualify components based on their reliability or risk of failure. For example, all new EVs (Electric Vehicles) sold in the US require an 8-year or 100,000 mile (160,000 km) battery warranty. EV batteries are complex mechanical structures that support dynamic masses, and transmit loads and vibration through thousands of joints and components. Fatigue failure therefore presents a significant risk to the overall reliability of the battery system. The design requirement over a population of EVs is expressed in terms of a statistical reliability target, for example:

∗ Corresponding author. Tel.: + 33-6134-04974 E-mail address: amaury.chabod@hbkworld.com ∗ Corresponding author. Tel.: + 33-6134-04974 E-mail address: amaury.chabod@hbkworld.com

2452-3216 © 2024 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers 10.1016/j.prostr.2024.03.078 2210-7843 © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers. 2210-7843 © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http: // creativecommons.org / licenses / by-nc-nd / 4.0 / ) Peer-review under responsibility of the scientific committee of the Fatigue Design 2023 organizers.