Suspension of a Single Sphere in a Stirred Tank with Transitional Flow

ACKNOWLEDGEMENT The authors gratefully acknowledge the financial support from Scientific Research and Technology Development Projects of China National Petroleum Corporation (No.2020B-2512).Peer reviewe

Accelerating the transition to a renewable energy powered grid in Nigeria.

Nigeria is plagued with electricity challenges which have had devastating economic implications with an annual loss of $26.2bn (World Bank 2020b) coupled with climate consequences, thereby stalling sustainable development. Currently, electricity is mainly generated from fossil fuels and supplied through the grid. However, just around 40% of the Nigerian population are connected to the national grid and are faced with incessant interruptions and blackouts. Consequently, the nation has the largest energy access deficit in the world as 85 million Nigerians do not have access to grid electricity (World Bank 2020b). Renewable energy (RE) has been identified to address the challenges of energy poverty and growing demand in the country. Therefore, the government created various strategies, policies, programmes, and regulations to encourage and facilitate the transition. Though Nigeria possesses abundant renewable energy sources, including solar and wind power, this to date have largely remained untapped

Using Google’s Mobility Data to understand park visitation during the COVID-19 pandemic: A note of caution

The COVID-19 pandemic has dramatically impacted park visitation around the globe. In an effort to un-derstand the factors influencing these changes, nu-merous attempts have been made to use big data to monitor changes in park use (e.g., Venter et al., 2020). Google\u27s Community Mobility Reports repre-sent a dataset with significant potential in this re-gard. Released in April 2020, these reports were gen-erated on the hypothesis that aggregated, anony-mized data could be helpful [to] make critical deci-sions to combat COVID-19 (Fitzpatrick & DeSalvo, 2020, para. 1). The heading on the reports\u27 website asks browsers to see how your community is mov-ing around differently due to COVID-19 (Google 2020b). The data released through the reports are generated from aggregated, anonymized sets of data from [Google] users who have turned on the Lo-cation History setting, which is off by default (Google 2020b)

The Locus Algorithm IV: Performance metrics of a grid computing system used to create catalogues of optimised pointings

This paper discusses the requirements for and performance metrics of the the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,779 quasars. Initial operational tests indicated a need for a software system to analyse the data and a High Performance Computing system to run that software in a scalable manner. Practical assessments of the performance of the software in a serial computing environment were used to provide a benchmark against which the performance metrics of the HPC solution could be compared, as well as to indicate any bottlenecks in performance. These performance metrics indicated a distinct split in the performance dictated more by differences in the input data than by differences in the design of the systems used. This indicates a need for experimental analysis of system performance, and suggests that algorithmic complexity analyses may lead to incorrect or naive conclusions, especially in systems with high data I/O overhead such as grid computing. Further, it implies that systems which reduce or eliminate this bottleneck such as in-memory processing could lead to a substantial increase in performance

Implications of a "Fast Radio Burst" from a Galactic Magnetar

A luminous radio burst was recently detected in temporal coincidence with a hard X-ray flare from the Galactic magnetar SGR 1935+2154 with a time and frequency structure consistent with cosmological fast radio bursts (FRB) and a fluence within a factor of $\lesssim 10$ of the least energetic extragalactic FRB previously detected. Although active magnetars are commonly invoked FRB sources, several distinct mechanisms have been proposed for generating the radio emission which make different predictions for the accompanying higher frequency radiation. We show that the properties of the coincident radio and X-ray flares from SGR 1935+2154, including their approximate simultaneity and relative fluence $E_{\rm radio}/E_{\rm X} \sim 10^{-5}$, as well as the duration and spectrum of the X-ray emission, are consistent with extant predictions for the synchrotron maser shock model. Rather than arising from the inner magnetosphere, the X-rays are generated by (incoherent) synchrotron radiation from thermal electrons heated at the same shocks which produce the coherent maser emission. Although the rate of SGR 1935+2154-like bursts in the local universe is not sufficient to contribute appreciably to the extragalactic FRB rate, the inclusion of an additional population of more active magnetars with stronger magnetic fields than the Galactic population can explain both the FRB rate as well as the repeating fraction, however only if the population of active magnetars are born at a rate that is at least two-orders of magnitude lower than that of SGR 1935+2154-like magnetars. This may imply that the more active magnetar sources are not younger magnetars formed in a similar way to the Milky Way population (e.g. via ordinary supernovae), but instead through more exotic channels such as superluminous supernovae, accretion-induced collapse or neutron star mergers.Comment: 21 pages, 9 figures; submitted to ApJL; comments welcome

Reinforcement Learning Based on Real-Time Iteration NMPC

Reinforcement Learning (RL) has proven a stunning ability to learn optimal policies from data without any prior knowledge on the process. The main drawback of RL is that it is typically very difficult to guarantee stability and safety. On the other hand, Nonlinear Model Predictive Control (NMPC) is an advanced model-based control technique which does guarantee safety and stability, but only yields optimality for the nominal model. Therefore, it has been recently proposed to use NMPC as a function approximator within RL. While the ability of this approach to yield good performance has been demonstrated, the main drawback hindering its applicability is related to the computational burden of NMPC, which has to be solved to full convergence. In practice, however, computationally efficient algorithms such as the Real-Time Iteration (RTI) scheme are deployed in order to return an approximate NMPC solution in very short time. In this paper we bridge this gap by extending the existing theoretical framework to also cover RL based on RTI NMPC. We demonstrate the effectiveness of this new RL approach with a nontrivial example modeling a challenging nonlinear system subject to stochastic perturbations with the objective of optimizing an economic cost.Comment: accepted for the IFAC World Congress 202