Performance Evaluation of OpenFoam on Juelich Supercomputing Facilities (JURECA, JUWELS and JUSUF)

The Forschungszentrum Juelich is utilizing OpenFOAM to perform calculations for electrochemical devices such as electrolyzers and fuel cells. For some time now, improving the performance of the OpenFOAM software suite on HPC facilities has posed a challenge for users wanting to scale up problem sizes to several tens of million grid cells. To keep time-to-solution within reasonable limits, this requires scalability to many thousands of compute cores. Herein, we investigate the performance and scalability of the OpenFOAM-v1912 for the well-known motorbike benchmark test case, including a strong scaling study of the SimpleFoam solver at the Juelich supercomputing facilities (JUWELS, JURECA, JUSUF). Later we will consider in-house electrochemical models, with specialized solvers and domain decomposition techniques. JURECA was built in 2015 and utilizes a Haswell processor with 24 cores per node, JUWELS was built in 2018 based on a Skylake processor and with 48 cores per node, and JUSUF was built in 2020, based on an AMD EPYC 7742 with 128 cores per node. Scalability limits of up to 3000 and 1000 compute cores respectively is found for cases with and without writing data output to disk. It is shown that the impact of the output can be quite severe when using the default output generation option, but that this can be substantially mitigated by making use of the ADIOS library. By analysing the most time-consuming MPI function calls (collective and point-to-point), as well as the performance of the different MPI implementations, OPENMPI4.02, INTELMPI2018/2019 and PARASTATION-MPI5.4, further potential optimizations are identified. Finally, we discuss the newly added library “PETSc4FOAM” in OpenFoam in order to make use of external sparse linear solvers such as PETSc/Hypre

Performance Evaluation of OpenFOAM on Juelich Supercomputing Facilities (JURECA, JUWELS and JUSUF)

The Forschungszentrum Juelich is utilizing OpenFOAM to perform calculations for electrochemical devices such as electrolyzers and fuel cells. For some time now, improving the performance of the OpenFOAM software suite on HPC facilities has posed a challenge for users wanting to scale up problem sizes to several tens of million grid cells. To keep time-to-solution within reasonable limits, this requires scalability to many thousands of compute cores. Herein, we investigate the performance and scalability of the OpenFOAM-v1912 for the well-known motorbike benchmark test case, including a strong scaling study of the SimpleFoam solver at the Juelich supercomputing facilities (JUWELS, JURECA, JUSUF). Later we will consider in-house electrochemical models, with specialized solvers and domain decomposition techniques. JURECA was built in 2015 and utilizes a Haswell processor with 24 cores per node, JUWELS was built in 2018 based on a Skylake processor and with 48 cores per node, and JUSUF was built in 2020, based on an AMD EPYC 7742 with 128 cores per node. Scalability limits of up to 3000 and 1000 compute cores respectively is found for cases with and without writing data output to disk. It is shown that the impact of the output can be quite severe when using the default output generation option, but that this can be substantially mitigated by making use of the ADIOS library. By analysing the most time-consuming MPI function calls (collective and point-to-point), as well as the performance of the different MPI implementations, OPENMPI4.02, INTELMPI2018/2019 and PARASTATION-MPI5.4, further potential optimizations are identified. Finally, we discuss the newly added library “PETSc4FOAM” in OpenFoam in order to make use of external sparse linear solvers such as PETSc/Hypre

Biosurfactant Production by Lactic Acid Bacterium Pediococcus dextrinicus SHU1593 Grown on Different Carbon Sources: Strain Screening Followed by Product Characterization

Abstract The present study focused on producing and characterizing a type of biosurfactant (BS) derived from lactic acid bacteria (LAB) and its potential applications in pharmaceutical and food industries due to the preference of employing nonpathogenic organisms in bioprocesses. To this aim, several screening approaches were applied to identify an efficient BS-producing strain from a set of LAB, and Pediococcus dextrinicus SHU1593 was selected as the most operative one. The BS produced by P. dextrinicus was isolated and structurally characterized as a lipoprotein with an approximately equal ratio of lipids (~52% (w/w)) and proteins (47% (w/w)). It reduced the surface tension (ST) of phosphate-buffered saline (PBS) from 72.80 ± 0.10 to 39.01 ± 0.32 mN/m. The results also indicated the potential of developing low-cost strategies aimed at the production of efficient LAB-derived BSs which are structurally and quantitatively similar to the ones obtained from conventional media. Finally, given the physical and functional characterization (i.e. critical micelle concentration (CMC), emulsification index (%E24), stability, as well as antimicrobial and anti-adhesive activities) of the BS produced in the present study, it can be introduced as a promising candidate to be employed in plenty of areas in pharmaceutical and food industries

El efecto de la educación en video sobre la ansiedad y los signos vitales en pacientes sometidos a colonoscopia

Introduction & Background. Colonoscopy is one of the most important diagnostic methods for gastrointestinal disorders that due to its invasiveness, can cause fear and anxiety in patients. This increase in anxiety may be associated with decreased patient tolerance, changes in vital signs, and physiological complications. The aim of this study was to investigate the effect of video training on patients' anxiety as well as their vital signs in the colonoscopy procedure. Methods. This study was a one-group study before and after that was performed on a colonoscopy candidate referred to the colonoscopy unit of Sabzevar Vasei Hospital in 1399. the demographic information questionnaire and the Spielberger anxiety questionnaire were completed one day before the colonoscopy, and were recorded the patients' blood pressure, heart rate and respiration. then was shown to patients a ten-minute instructional video on laptop colonoscopy in a quiet environment. The patients' anxiety and vital signs were measured and recorded again on the day of the colonoscopy and immediately before the procedure, all steps of data registration and analysis were performed in SPSS software version 25. Results. The mean anxiety score of the study participants was 52.1 11 11.30 before the video training, which it was decreased to 45.6 10 10.8 (p <0.05) after the training (on the day of the colonoscopy procedure). also, blood pressure and pulse rate was decreased significantly after the intervention (p <0.05), but there was no significant difference in the number of breaths before and after the intervention (p> 0.05). Conclusion. as for the effectiveness of video training on reducing anxiety and vital signs in patients undergoing colonoscopy, it is recommended that be included video training as a non-pharmacological method in the care program of these patients.Introducción y antecedents. La colonoscopia es uno de los métodos de diagnóstico más importantes para los trastornos gastrointestinales que, por su invasividad, pueden causar miedo y ansiedad en los pacientes. Este aumento de la ansiedad puede estar asociado con una disminución de la tolerancia del paciente, cambios en los signos vitales y complicaciones fisiológicas. El objetivo de este estudio fue investigar el efecto del entrenamiento por video sobre la ansiedad de los pacientes, así como sus signos vitales en el procedimiento de colonoscopia. Métodos. Este estudio fue un estudio de un grupo antes y después de que se realizó en un candidato a colonoscopia remitido a la unidad de colonoscopia del Hospital Sabzevar Vasei en 1399. El cuestionario de información demográfica y el cuestionario de ansiedad de Spielberger se completaron un día antes de la colonoscopia, y se registraron la presión arterial, la frecuencia cardíaca y la respiración de los pacientes. luego se mostró a los pacientes un video instructivo de diez minutos sobre la colonoscopia portátil en un ambiente tranquilo. La ansiedad y los signos vitales de los pacientes se midieron y registraron nuevamente el día de la colonoscopia e inmediatamente antes del procedimiento, todos los pasos de registro y análisis de datos se realizaron en el software SPSS versión 25. Resultados. La puntuación media de ansiedad de los participantes del estudio fue 52,1 11 11,30 antes del entrenamiento con video, que se redujo a 45,6 10 10,8 (p <0,05) después del entrenamiento (el día del procedimiento de colonoscopia). además, la presión arterial y la frecuencia del pulso disminuyeron significativamente después de la intervención (p <0.05), pero no hubo diferencia significativa en el número de respiraciones antes y después de la intervención (p> 0.05). Conclusión. en cuanto a la efectividad del video entrenamiento para reducir la ansiedad y los signos vitales en pacientes sometidos a colonoscopia, se recomienda que se incluya el video entrenamiento como método no farmacológico en el programa de atención de estos pacientes

Implementing ICON in TSMP – Coupling strategy and applications

The ever increasing computational resources are leading to a refinement of grid spacing of atmospheric models as well as the possibility of large eddy simulation for real data applications. Thus, the land surface with its multi-scale heterogeneity related to e.g. land cover and soil moisture gains in importance in atmospheric modeling. The Terrestrial System Modeling Platform (TSMP) is a scale-consistent, highly modular fully integrated soil-vegetation-atmosphere modeling system for regional earth system modeling. TSMP is composed of an atmospheric model (ICON, COSMO), a land surface model (NCAR Community Land Model - CLM), and a subsurface flow model (ParFlow) coupled together using the OASIS3-MCT coupler. The model components can be configured to run standalone or coupled in various configurations and with different grid spacings for each model component. TSMP can be applied at scales ranging from field-scale to continental scale.In TSMP, we incorporated the numerical weather prediction and large eddy mode of the atmospheric numerical model ICON, developed by the German Weather Service (DWD) and Max-Planck Institute for Meteorology. Here, we present an overview about the development strategy along with technical and performance aspects arising from the coupling process. We provide insights in the boundary layer development originating from an improved physical treatment of the land surface as well as the 3D water transport in the (sub)surface model