Robert Roszak

The global share of energy consumption by data centers has reached the level of several percent and continues to rise. For this reason, ensuring optimal energy efficiency of the cooling process in data centers is an essential matter. As most data centers are air-cooled, it is required to investigate an airflow pattern inside as well as the accompanying heat transfer phenomena to assess the efficiency of the cooling process of the object. What is more, the thermal state of a server room as well as its power consumption often has a transient nature not only due to turbulent airflow inside but also because of dynamically changing servers’ load and time-varying output conditions of the coolers as a consequence of their control algorithms. That is why it is necessary to use transient modeling to get a deep and complete insight into the nature of the airflow and heat transfer phenomena in a server room and the resulting energy usage. A technique which allows modeling of the airflow and heat transfer in a detailed, volumetric way is computational fluid dynamics (CFD). Unfortunately, employing CFD for complex models especially in a transient manner can become a tedious process for an engineer and a challenging task for computational resources. In this paper we present a framework which is designed for automatic numerical heat transfer analysis of data center objects, using in the backend OpenFOAM, a well-known open-source CFD toolkit. Besides the automation process, the presented framework includes the implementation of transient models of active server room equipment and modeling of their energy usage as well as support for using high performance computing (HPC) systems equipped with SLURM queuing system. The software description is followed by a presentation of its application for a study of a hypothetical server room. A transient scenario of rapid application of servers’ load is simulated, including an energy consumption analysis of cooling devices.

Additive manufacturing (AM) is dynamically developing and finding applications in different industries. The quality of input material is a part of the process and of the final product quality. That is why understanding the influence of powder reuse on the properties of bulk specimens is crucial for ensuring the repeatable AM process chain. The presented study investigated the possibility of continuous reuse of AlSi7Mg0.6 powder in the laser powder bed fusion process (LPBF). To date, there is no study of AlSi7Mg0.6 powder reuse in the LPBF process to be found in the literature. This study aims to respond to this gap. The five batches of AlSi7Mg0.6 powder and five bulk LPBF samples series were characterised using different techniques. The following characteristics of powders were analysed: the powder size distribution (PSD), the morphology (scanning electron microscopy—SEM), the flowability (rotating drum analysis), and laser light absorption (spectrophotometry). Bulk samples were characterised for microstructure (SEM), chemical composition (X-ray fluorescence spectrometry—XRF), porosity (computed tomography—CT) and mechanical properties (tensile, hardness). The powder was reused in subsequent processes without adding (recycling/rejuvenation) virgin powder (collective ageing powder reuse strategy). All tested powders (powders P0–P4) and bulk samples (series S0–S3) show repeatable properties, with changes observed within error limits. Samples manufactured within the fifth reuse cycle (series S4) showed some mean value changes of measured characteristics indicating initial degradation. However, these changes also mostly fit within error limits. Therefore, the collective ageing powder reuse strategy is considered to give repeatable LPBF process results and is recommended for the AlSi7Mg0.6 alloy within at least five consecutive LPBF processes.