Turbine Blades for Reusable Liquid Rocket Engines (LRE) - Numerical Fatigue Life Investigation

Abstract

Reusability of LREs in Europe is increasingly attracting the attention of scientific community and industry with leading projects such as THEMIS, CALLISTO (reusable demonstrators for vertical take-off and landing (VTVL)) and Ariane Next -all powered by the reusable cryogenic Oxygen/Methane (LOX/LCH4) engine "Prometheus". To enable further expansion and cost-effectiveness of the reusability technology for future liquid rocket engines (LREs), research on critical engine components such as turbopumps is crucial. Therefore, within our research we focus on the turbine blade investigation for reusable LRE applications including high cycle fatigue (HCF) and low cycle fatigue (LCF). Validation of defined applied analytical and numerical techniques is established through the Liquid Upper stage deMonstrator ENgine (LUMEN)'s, developed at DLR Lamplodshausen for enhanced expertise in the complete cycle operation for various engine applications, as well as to empower validation studies of the operational conditions to which turbopump components, such as turbine blades, are subjected.Turbine blades are exposed to large thermo-mechanical cyclic strains emerging from an increased temperature driving gas combined with a fast start-up sequence as well as a large rotational speed -essential for acquiring high performance and structural mass efficiency for LREs. Therefore, in addition to bending & torsion as well as thermal gradient and centrifugal forces, it is critical to consider creep effects in durability studies.To forecast the turbine blade fatigue life, analytical (0-D) and numerical approaches for a selected test case are studied. Within the proposed method, a BLISK is assessed for the most severe loading condition considering HCF load by a modified Goodman method, along with a Coffin-Manson based approach for LCF contribution. Each operational cycle under constant maximum loading condition is applied to study the creep effect. As a result, an enhanced fatigue life prediction method including both creep and fatigue conditions for a turbine blade is obtained. TABLE OF CONTENTS 1. INTRODUCTION .