Einfluss komplexer Oberflächenstrukturen auf das aerodynamische Verlustverhalten von Turbinenbeschaufelungen

Der Einsatz von Gasturbinen für den Antrieb von Flugzeugen wird aufgrund der hohen Leistungsdichte und Wirkungsgrade auch in den kommenden Jahrzehnten ohne Alternative sein. Dabei nimmt die Bedeutung von ökonomischen und ökologischen Aspekten stark zu. Um die Betriebskosten von Gasturbinen zu reduzieren, ist ein Weg bereits während der Produktion und Reparatur die Wechselwirkung von Fertigungsprozessen und funktionalen Eigenschaften zu berücksichtigen. Ein großes Potential die Reparaturkosten zu senken liegt in der Wartung von Hochdruckturbinenschaufeln, die aufgrund hoher thermischer und mechanischer Belastung einem hohen Verschleiß unterliegen. Durch eine geschickte, lokale Reparatur von Turbinenschaufeln, kann die Reparaturzeit gesenkt werden. Besondere Bedeutung kommt bei der Reparatur der Oberflächenbeschaffenheit der Turbinenschaufeln zu, da durch Oberflächenrauheiten der Wirkungsgrad signifikant gesenkt wird. Für eine geschickte und effiziente Reparatur ist daher die Kenntnis über die Wechselwirkung von Oberflächenrauheiten mit den lokalen Strömungsbedingungen entlang der Schaufeloberfläche notwendig. Ein Merkmal betriebsbeanspruchter Turbinenschaufeln ist eine lokale Inhomogenität in der Höhe, der Dichte und Anordnung von Rauheitselementen auf Turbinenschaufeln. Aus Messungen von Oberflächenstrukturen betriebsbeanspruchter Turbinenschaufeln ergibt sich eine charakteristische Rauheitsverteilung, die besonders große Rauheitshöhen an der Vorderkante aufweist. Die Parametrisierung erfolgt mit Hilfe der äquivalenten Sandkornrauheit, um eine dreidimensionale Topographie in einen skalaren Kennwert zu überführen. Zur quantitativen Beschreibung der Isotropie bzw. Anisotropie der Oberflächenrauheiten wird ein Anisotropie-Parameter ΛA eingeführt. In dieser Arbeit werden experimentelle Untersuchungen zum Einfluss lokaler und komplexer Oberflächenstrukturen auf das aerodynamische Verlustverhalten von Turbinenbeschaufelungen durchgeführt. Dafür wird eine Schaufel ausgelegt, die eine ähnliche aerodynamische Belastung aufweist wie der Mittenschnitt einer Hochdruckturbinenschaufel eines modernen Flugtriebwerks. Aus den Rauheitsmessungen werden Oberflächenmodelle abgeleitet und auf der Turbinenschaufel appliziert. Aus Grenzschicht- und Nachlaufmessungen sowie Messungen der Profildruckverteilung folgt, dass Rauheiten im Wesentlichen den Reibungswiderstand beeinflussen. Abhängig von der Rauheitsposition auf der Schaufel ergeben sich stark unterschiedliche Verluständerung bis zu einer Erhöhung der Profilverluste von 11%. Mit Hilfe Direkter Numerischer Simulationen (DNS) erfolgt eine Klärung der Ursachen der Verlustentstehung von Rauheiten in der turbulenten Grenzschicht. Dabei zeigt sich, dass durch Oberflächenrauheiten lokale Druckgradienten in die Grenzschicht induziert werden, welche die Stabilität kohärenter Wirbelstrukturen beeinflussen. Zusätzlich wird eine empirische Rauheitsfunktion anhand von Messwerten aus der Literatur hergeleitet. Dies ist notwendig, da viele technische Rauheiten Höhen von k8+ ≤ 20 aufweisen, die vorhandenen Rauheitsfunktionen für diesen Bereich jedoch keine allgemeingültigen Ergebnisse liefern. Eine Verifikation der allgemeinen Gültigkeit der neuen Rauheitsfunktion erfolgt mittels der DNS verschiedener Oberflächen. Aus den Ergebnissen dieser Arbeit folgt, dass unter Berücksichtigung der Wechselwirkung der lokalen Strömungsbedingungen mit Oberflächenstrukturen eine lokale Schaufelreparatur möglich ist. In Bereichen stark beschleunigter Strömungen kann die Oberflächenrauheit aus aerodynamischer Sichte vernachlässigt werden. Dadurch ist eine Senkung der direkten Betriebskosten von Gasturbinen über eine Reduzierung der Reparaturzeit möglich

Potential Contributors to Increased Pulmonary Embolism Hospitalizations During the COVID-19 Pandemic: Insights From the German-Wide Helios Hospital Network

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany. Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016–2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016–2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression. Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112–2,236 (total 8,717) in the corresponding 2016–2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05–1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07–1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09–1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02–1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood −576) was with a window size of 4 days, i.e., average COVID-19 infections 14–17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12–1.29, P < 0.01). Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016–2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE

Assessment of Modern RANS Models for the C3X Vane Film Cooling Prediction

The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS

Effect of purge air on rotor endwall heat transfer of an axial turbine

In order to gain in cycle efficiency, turbine inlet temperatures tend to rise, posing the challenge for designers to cool components more effectively. Purge flow injection through the rim seal is regularly used in gas turbines to limit the ingestion of hot air in the cavities and prevent overheating of the disks and shaft bearings. The interaction of the purge air with the main flow and the static pressure field of the blade rows results in a non-homogenous distribution of coolant on the passage endwall which poses questions on its effect on endwall heat transfer. A novel measurement technique based on infrared thermography has been applied in the rotating axial turbine research facility LISA of the Laboratory for Energy Conversion (LEC) of ETH Zürich. A 1.5 stage configuration with fully three-dimensional airfoils and endwall contouring is integrated in the facility. The effect of different purge air mass flow rates on the distribution of the heat transfer quantities has been observed for the rated operating condition of the turbine. Two-dimensional distributions of Nusselt number and adiabatic wall temperature show that the purge flow affects local heat loads. It does so by acting on the adiabatic wall temperature on the suction side of the passage until 30% of the axial extent of the rotor endwall. This suggests the possibility of effectively employing purge air also as rotor platform coolant in this specific region. The strengthening of the secondary flows due to purge air injection is observed, but plays a negligible role in varying local heat fluxes. For one test case, experimental data is compared to high-fidelity, unsteady Reynolds-Averaged Navier–Stokes simulations performed on a model of the full 1.5 stage configuration

Potential Contributors to Increased Pulmonary Embolism Hospitalizations During the COVID-19 Pandemic: Insights From the German-Wide Helios Hospital Network

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany. Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016–2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016–2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression. Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112–2,236 (total 8,717) in the corresponding 2016–2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05–1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07–1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09–1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02–1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood −576) was with a window size of 4 days, i.e., average COVID-19 infections 14–17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12–1.29, P < 0.01). Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016–2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE

Potential Contributors to Increased Pulmonary Embolism Hospitalizations During the COVID-19 Pandemic: Insights From the German-Wide Helios Hospital Network

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany. Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016–2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016–2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression. Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112–2,236 (total 8,717) in the corresponding 2016–2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05–1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07–1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09–1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02–1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood −576) was with a window size of 4 days, i.e., average COVID-19 infections 14–17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12–1.29, P < 0.01). Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016–2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE

Data_Sheet_1_Changing trends of patient characteristics and treatment pathways during the COVID-19 pandemic: A cross-sectional analysis of 72,459 inpatient cases from the German Helios database.DOCX

BackgroundThis study compared patient profiles and clinical courses of SARS-CoV-2 infected inpatients over different pandemic periods.MethodsIn a retrospective cross-sectional analysis, we examined administrative data of German Helios hospitals using ICD-10-codes at discharge. Inpatient cases with SARS-CoV-2 infection admitted between 03/04/2020 and 07/19/2022 were included irrespective of the reason for hospitalization. All endpoints were timely assigned to admission date for trend analysis. The first pandemic wave was defined by change points in time-series of incident daily infections and compared with different later pandemic phases according to virus type predominance.ResultsWe included 72,459 inpatient cases. Patients hospitalized during the first pandemic wave (03/04/2020–05/05/2020; n = 1,803) were older (68.5 ± 17.2 vs. 64.4 ± 22.6 years, p ConclusionCharacteristics and outcomes of inpatients with SARS-CoV-2 infection changed throughout the observational period. An ongoing evaluation of trends and care pathways will allow for the assessment of future demands.</p

SARS-CoV-2 infection in chronic kidney disease patients with pre-existing dialysis: description across different pandemic intervals and effect on disease course (mortality)

Purpose Patients suffering from chronic kidney disease (CKD) are in general at high risk for severe coronavirus disease (COVID-19) but dialysis-dependency (CKD5D) is poorly understood. We aimed to describe CKD5D patients in the different intervals of the pandemic and to evaluate pre-existing dialysis dependency as a potential risk factor for mortality. Methods In this multicentre cohort study, data from German study sites of the Lean European Open Survey on SARS-CoV-2-infected patients (LEOSS) were used. We multiply imputed missing data, performed subsequent analyses in each of the imputed data sets and pooled the results. Cases (CKD5D) and controls (CKD not requiring dialysis) were matched 1:1 by propensity-scoring. Effects on fatal outcome were calculated by multivariable logistic regression. Results The cohort consisted of 207 patients suffering from CKD5D and 964 potential controls. Multivariable regression of the whole cohort identified age (> 85 years adjusted odds ratio (aOR) 7.34, 95% CI 2.45-21.99), chronic heart failure (aOR 1.67, 95% CI 1.25-2.23), coronary artery disease (aOR 1.41, 95% CI 1.05-1.89) and active oncological disease (aOR 1.73, 95% CI 1.07-2.80) as risk factors for fatal outcome. Dialysis-dependency was not associated with a fatal outcome-neither in this analysis (aOR 1.08, 95% CI 0.75-1.54) nor in the conditional multivariable regression after matching (aOR 1.34, 95% CI 0.70-2.59). Conclusions In the present multicentre German cohort, dialysis dependency is not linked to fatal outcome in SARS-CoV-2-infected CKD patients. However, the mortality rate of 26% demonstrates that CKD patients are an extreme vulnerable population, irrespective of pre-existing dialysis-dependency