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

A numerical study on the effect of variable wear coefficient on fretting wear characteristics

Fretting wear is a common phenomenon that happens between contact parts when there is an oscillatory relative movement. To investigate wear characteristics history in the fretting process, the finite element method (FEM) is commonly applied to simulate the fretting by considering the wear in the model. In most literature publications, the wear coefficient is considered as a constant, which is not a real case based on the experimental results. To consider the variation of wear coefficient, a double-linear model is applied in this paper, and the tribologically transformed structure (TTS) phase is considered in the study of the wear coefficient variation model. By using these models for variable wear coefficient for both flat and cylinder, the difference of wear characteristics, plastic strain, and stress between variable wear coefficient model (VWCM) and constant wear coefficient model (CWCM) are analyzed. The results show that the variable wear coefficient has no significant effect on the wear characteristic at the end of the process in the gross sliding regime. However, in the partial slip regime, the effect of variable wear coefficient on wear characteristics is significant. Due to the difference in contact geometry in the fretting process between VWCM and CWCM, the tangential and shear stress and equivalent plastic strain also show differences during the fretting process

IMAP: Intrinsically Motivated Adversarial Policy

Reinforcement learning agents are susceptible to evasion attacks during deployment. In single-agent environments, these attacks can occur through imperceptible perturbations injected into the inputs of the victim policy network. In multi-agent environments, an attacker can manipulate an adversarial opponent to influence the victim policy's observations indirectly. While adversarial policies offer a promising technique to craft such attacks, current methods are either sample-inefficient due to poor exploration strategies or require extra surrogate model training under the black-box assumption. To address these challenges, in this paper, we propose Intrinsically Motivated Adversarial Policy (IMAP) for efficient black-box adversarial policy learning in both single- and multi-agent environments. We formulate four types of adversarial intrinsic regularizers -- maximizing the adversarial state coverage, policy coverage, risk, or divergence -- to discover potential vulnerabilities of the victim policy in a principled way. We also present a novel Bias-Reduction (BR) method to boost IMAP further. Our experiments validate the effectiveness of the four types of adversarial intrinsic regularizers and BR in enhancing black-box adversarial policy learning across a variety of environments. Our IMAP successfully evades two types of defense methods, adversarial training and robust regularizer, decreasing the performance of the state-of-the-art robust WocaR-PPO agents by 34%-54% across four single-agent tasks. IMAP also achieves a state-of-the-art attacking success rate of 83.91% in the multi-agent game YouShallNotPass

Research on the vibration damping performance of hydro-pneumatic suspension of mine dump truck

The working environment of mine dump truck is relatively harsh, thus the suspension system with poor performance will directly affect driver's driving comfort and physical and mental health. An oil cylinder is one of the key components of the hydro-pneumatic suspension system, however, the high friction levels between cylinder and piston would lead to ‘friction locking’ phenomenon in the practical application. In order to improve the vibration damping performance of hydro-pneumatic suspension system and enhance the comfortability of whole vehicle, a 110 t mine dump truck was studied by theoretical and experimental method. The results of this study show that increasing the length of cylinder guide can effectively decrease the cylinder vibration transmission rate and improve the driving comfortability of vehicle