In recent years, the volatile supply of electricity from the wind and photovoltaic sectors has increased worldwide. Owing to the massive expansion of renewable energy sources, it is becoming increasingly important for thermal power plants to respond to this. One method to achieve this flexibility is to integrate a thermal battery. This is directly integrated into the cycle of a thermal power plant as a high-pressure storage unit. Water under a high pressure (up to 60 bar) was used as the storage medium. This work deals with the model development, optimization, and validation of such a high-pressure storage system. The validation of the simulations was based on experimental data. These originated from a real test facility with a high-pressure storage tank at the Zittau/Görlitz University of Applied Sciences. Furthermore, the control of the storage tank (charge and discharge) was addressed, and the topic of discretization in the model at very low flow velocities within the storage tank was discussed. Finally, the influence of the tank wall is discussed.
This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could support the development of innovative AI solutions. It also examines use cases of classical AI that can empower research and development in quantum technologies, with a focus on quantum computing and quantum sensing. The purpose of this white paper is to provide a long-term research agenda aimed at addressing foundational questions about how AI and quantum computing interact and benefit one another. It concludes with a set of recommendations and challenges, including how to orchestrate the proposed theoretical work, align quantum AI developments with quantum hardware roadmaps, estimate both classical and quantum resources - especially with the goal of mitigating and optimizing energy consumption - advance this emerging hybrid software engineering discipline, and enhance European industrial competitiveness while considering societal implications.
Objective During the COVID-19 pandemic, there was an increase in health-related anxiety and stress levels. The extent of COVID-19-specific anxiety and correlations with well-being are being investigated. Methods In 2021, N=321 participants in the Saxon Longitudinal Study were asked about COVID-19-specific fears, life satisfaction and physical and mental well-being using a questionnaire. Results N=109 people (34.6%) reported pronounced COVID-19-specific fears. Correlations between COVID-19-specific fears and psychological well-being, physical well-being, life satisfaction and perceived state of health were determined. In summary, people with strong COVID-19-specific fears were significantly more stressed. Conclusion COVID-19-specific fears can be associated with physical and psychological complaints. It is important to identify vulnerable population groups.
This paper analyses the acceptance of augmented reality (AR) technologies in technical education based on the Technology Acceptance Model (TAM3) by Venkatesh and Bala (2008). The use of AR technologies, such as the Microsoft HoloLens 2 head-mounted display, has the potential to facilitate innovative teaching and learning methods. The utilisation of multimedia visualisation, remote service for the location-independent integration of expert knowledge and the possibility of hand interaction and voice control presents new avenues for exploration in the domains of learning and production. To investigate the acceptance of AR in the education and industry context, a total of fourteen individuals from both sectors were surveyed following a workshop. The survey focused on the following constructs of the Technology Acceptance Model 3 (TAM3): Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment, Job Relevance, Behavioural Intention and Computer Self-Efficacy. The findings of this study provide initial insights into the acceptance limits and potential uses of AR technologies and make recommendations for their implementation in various contexts. In order to enhance the reliability of the results, it is recommended that the study will be repeated with larger samples and that the long-term effects of AR use will be investigated in order to develop sustainable implementation strategies.
The influence of a defined impurity on the network characteristics of vitrimers made from an epoxidized eugenol derivative and various dicarboxylic acids is reported. One major characteristic of the monomer is the fact that it is not “clean” but rather is a mixture of the mono and diepoxidized eugenol derivatives. Mixtures like this could be thought to be representative of many technical grade compounds and the current system therefore serves as a model system to evaluate the effect of epoxide mixtures on the synthesis and the properties of the final vitrimers. The vitrimer preparation is found to be not affected by the different epoxy fractions, but in terms of the properties, there is an effect on the glass transition temperature both with the type of dicarboxylic acid but also with the level of epoxy functionalities present in the system. In spite of this, the ability of the vitrimer to perform the exchange reaction is not affected and all vitrimers can be reshaped or reprocessed showing that the processing is not affected by the changes in epoxy purity.
