Introduction for the Special Issue on Beyond the Hypes of Geospatial Big Data: Theories, Methods, Analytics, and Applications

We live in the era of ‘Big Data’. In particular, Geospatial data, whether captured through remote sensors (e.g., satellite imagery) or generated from large-scale simulations (e.g., climate change models) have always been significantly large in size. Over the last decade however, advances in instrumentation and computation has seen the volume, variety, velocity, and veracity of this data increase exponentially. Of the 2.5 quintillion (1018) bytes of data that are generated on a daily basis across the globe, a large portion (arguably as much as 80%) is found to be geo-referenced. Therefore, this special issue is dedicated to the innovative theories, methods, analytics, and applications of geospatial big data

Multiscale analysis of the effect of debris on fretting wear process using a semi-concurrent method

Fretting wear is a phenomenon, in which wear happens between two oscillatory moving contact surfaces in microscale amplitude. In this paper, the effect of debris between pad and specimen is analyzed by using a semi-concurrent multiscale method. Firstly, the macroscale fretting wear model is performed. Secondly, the part with the wear profile is imported from the macroscale model to a microscale model after running in stage. Thirdly, an effective pad's radius is extracted by analyzing the contact pressure in order to take into account the effect of the debris. Finally, the effective radius is up-scaled from the microscale model to the macroscale model, which is used after running in stage. In this way, the effect of debris is considered by changing the radius of the pad in the macroscale model. Due to the smaller number of elements in the microscale model compared with the macroscale model containing the debris layer, the semi-concurrent method proposed in this paper is more computationally efficient. Moreover, the results of this semi-concurrent method show a better agreement with experimental data, compared to the results of the model ignoring the effect of debris