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In the design of satellite systems, it is essential to control the satellite’s position for various reasons, either to have correct communication with a ground station or to make connections with other satellites. In the same way, the positioning of a satellite poses a significant challenge since its behavior is non-linear; due to these issues, several test benches have been developed for the satellite’s position problem. In this review, there will be a journey from the rise of the space age to the latest advances in technology for emulating the satellite’s dynamics.

The assessment of didactic effect is the most important in evaluating the effectiveness of training simulators. Modern methods of training specialists have shown that the most applicable at present is the step-by-step formation of skills and abilities. The methodology of obtaining the value of a complex indicator that takes into account the degree of influence of didactic possibilities realized in training simulators on the reduction of training time based on the methods of expert evaluation, the method of selecting the main component, convolution of single indicators into private ones and selection of the type of its function of a private indicator

An interview with Paige E. Martin, user training team lead at Australia's Climate Simulator, is presented. Among other things, Martin discusses her career trajectory that illustrates the dynamic nature of post-academic pathways in oceanography, her job responsibilities, and the importance of networking and adaptability in navigating career challenges, advocating for a balance between professional aspirations and personal life.

The study analyzes computer modeling tools intended for use in educational and scientific contexts. The concept of modeling as a method of research and a teaching tool is examined, the emphasis is placed on computer modeling. It is shown how physical laws, particularly Coulomb’s law, can be studied through modeling. The study uses pre-made simulators, spreadsheets, mathematical packages, as well as our own software in Object Pascal and Python. Experimental testing has confirmed the effectiveness of computer modeling in teaching natural sciences. A survey of students and teachers showed interest in further use of simulation tools in the educational process.

Given the factors such as safety, profitability, and environmental concerns at stake, operator training is an everlasting and vital process in the process industry. An inevitable need for skilled operators in the chemical industry leads to search for novel and effective training methodologies. Consequently, dynamic simulation techniques have been considered as a tool to educate and train inexperienced personnel as expected by the industry. Traditional training methodologies are hardly sufficient to instruct the operators for seldom-occurring perilous situations. Conventional operator training simulators (OTS) are generally effective, but they lack to give operators the actual feel of the scenarios. Training effectiveness can be enhanced by providing operators with a sense of realism. Therefore, integration of OTS with virtual reality (VR-OTS) certainly comes out to be an alternative. VR-OTS can replicate emergency conditions, accidents, and investigate safety protocols. In this work, we discuss the need for virtual reality (VR) in OTS, merits of VR-OTS, and the role of training assessment methods. Contributions of OTS Authors’ in process industry from year 2000 to mid-2017 are reviewed and discussed extensively. The review shows that VR-OTS provides tangible benefits over its conventional counterparts in terms of improved safety of plant, increased productivity, and environmental protection. Finally, this paper outlines future scopes that the current researcher may consider to focus for the increased and improved VR-OTS usage.

We describe Global Atmosphere 7.0 and Global Land 7.0 (GA7.0/GL7.0), the latest science configurations of the Met Office Unified Model (UM) and the Joint UK Land Environment Simulator (JULES) land surface model developed for use across weather and climate timescales. GA7.0 and GL7.0 include incremental developments and targeted improvements that, between them, address four critical errors identified in previous configurations: excessive precipitation biases over India, warm and moist biases in the tropical tropopause layer (TTL), a source of energy non-conservation in the advection scheme and excessive surface radiation biases over the Southern Ocean. They also include two new parametrisations, namely the UK Chemistry and Aerosol (UKCA) GLOMAP-mode (Global Model of Aerosol Processes) aerosol scheme and the JULES multi-layer snow scheme, which improve the fidelity of the simulation and were required for inclusion in the Global Atmosphere/Global Land configurations ahead of the 6th Coupled Model Intercomparison Project (CMIP6).In addition, we describe the GA7.1 branch configuration, which reduces an overly negative anthropogenic aerosol effective radiative forcing (ERF) in GA7.0 whilst maintaining the quality of simulations of the present-day climate. GA7.1/GL7.0 will form the physical atmosphere/land component in the HadGEM3–GC3.1 and UKESM1 climate model submissions to the CMIP6.

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators 1 , 2 . Unlocking the full potential of such systems towards this goal requires flexible initial state preparation, precise time evolution and extensive probes for final state characterization. Here we present a quantum simulator comprising 69 superconducting qubits that supports both universal quantum gates and high-fidelity analogue evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. This hybrid platform features more versatile measurement capabilities compared with analogue-only simulators, which we leverage here to reveal a coarsening-induced breakdown of Kibble–Zurek scaling predictions 3 in the XY model, as well as signatures of the classical Kosterlitz–Thouless phase transition 4 . Moreover, the digital gates enable precise energy control, allowing us to study the effects of the eigenstate thermalization hypothesis 5 , 6 – 7 in targeted parts of the eigenspectrum. We also demonstrate digital preparation of pairwise-entangled dimer states, and image the transport of energy and vorticity during subsequent thermalization in analogue evolution. These results establish the efficacy of superconducting analogue–digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics. A hybrid analogue–digital quantum simulator is used to demonstrate beyond-classical performance in benchmarking experiments and to study thermalization phenomena in an XY quantum magnet, including the breakdown of Kibble–Zurek scaling predictions and signatures of the Kosterlitz–Thouless phase transition.

This study aims to provide framework for considering fidelity in the design of simulator training. Simulator fidelity is often characterised as the level of physical and visual similarity with real work settings, and the importance of simulator fidelity in the creation of learning activities has been extensively debated. Based on a selected literature review and fieldwork on ship simulator training, this study provides a conceptual framework for fidelity requirements in simulator training. This framework is applied to an empirical example from a case of ship simulator training. The study identifies three types of simulator fidelity that might be useful from a trainer’s perspective. By introducing a framework of technical , psychological and interactional fidelity and linking these concepts to different levels of training and targeted learning outcomes, the study demonstrates how the fidelity of the simulation relates to the level of expertise targeted in training. The framework adds to the body of knowledge on simulator training by providing guidelines for the different ways in which simulators can increase professional expertise, without separating the learning activity from cooperative work performance.

This paper introduces a calibration method for the simulated distance of automotive millimeter-wave radar target simulators (RTS). The basic concepts and working principles of automotive millimeter-wave radar and RTS are briefly described. A calibration method based on the group delay function of a vector network analyzer (VNA) is elaborated. Experiments were conducted to validate the feasibility of the method, and the uncertainty of the measurement results was evaluated. Finally, issues encountered during the calibration process and important considerations are summarized, and pathways for establishing a traceability chain are discussed.

The Internet of Things (IoT) has emerged as an important concept, bridging the physical and digital worlds through interconnected devices. Although the idea of interconnected devices predates the term “Internet of Things”, which was coined in 1999 by Kevin Ashton, the vision of a seamlessly integrated world of devices has been accelerated by advancements in wireless technologies, cost-effective computing, and the ubiquity of mobile devices. This study aims to provide an in-depth review of existing and emerging IoT simulators focusing on their capabilities and real-world applications, and discuss the current challenges and future trends in the IoT simulation area. Despite substantial research in the IoT simulation domain, many studies have a narrow focus, leaving a gap in comprehensive reviews that consider broader IoT development metrics, such as device mobility, energy models, Software-Defined Networking (SDN), and scalability. Notably, there is a lack of literature examining IoT simulators’ capabilities in supporting renewable energy sources and their integration with Vehicular Ad-hoc Network (VANET) simulations. Our review seeks to address this gap, evaluating the ability of IoT simulators to simulate complex, large-scale IoT scenarios and meet specific developmental requirements, as well as examining the current challenges and future trends in the field of IoT simulation. Our systematic analysis has identified several significant gaps in the current literature. A primary concern is the lack of a generic simulator capable of effectively simulating various scenarios across different domains within the IoT environment. As a result, a comprehensive and versatile simulator is required to simulate the diverse scenarios occurring in IoT applications. Additionally, there is a notable gap in simulators that address specific security concerns, particularly battery depletion attacks, which are increasingly relevant in IoT systems. Furthermore, there is a need for further investigation and study regarding the integration of IoT simulators with traffic simulation for VANET environments. In addition, it is noteworthy that renewable energy sources are underrepresented in IoT simulations, despite an increasing global emphasis on environmental sustainability. As a result of these identified gaps, it is imperative to develop more advanced and adaptable IoT simulation tools that are designed to meet the multifaceted challenges and opportunities of the IoT domain.