In this paper, we performed an analysis of the 500 most relevant scientific articles published since 2018, concerning machine learning methods in the field of climate and numerical weather prediction ...using the Google Scholar search engine. The most common topics of interest in the abstracts were identified, and some of them examined in detail: in numerical weather prediction research—photovoltaic and wind energy, atmospheric physics and processes; in climate research—parametrizations, extreme events, and climate change. With the created database, it was also possible to extract the most commonly examined meteorological fields (wind, precipitation, temperature, pressure, and radiation), methods (Deep Learning, Random Forest, Artificial Neural Networks, Support Vector Machine, and XGBoost), and countries (China, USA, Australia, India, and Germany) in these topics. Performing critical reviews of the literature, authors are trying to predict the future research direction of these fields, with the main conclusion being that machine learning methods will be a key feature in future weather forecasting.
Abstract This study aimed to investigate the potential differences in the match running performance of professional soccer players 5 min. before scoring and conceding a goal in the Polish ...Ekstraklasa. The sample consisted of 278 matches with 570 goals scored during official matches of the 2022/23 Polish Ekstraklasa season. All data was collected utilising the computerised multiple-camera optical tracking system TRACAB. Total distance covered (TD), standing distance (StD; < 0.72 km h −1 ), walking distance (WD; 0.73–7.2 km h −1 ), jogging distance (JG; 7.21–14.4 km h −1 ), running distance (RD; 14.41–19.8 km h −1 ), high-speed running distance (HSR; 19.81–25.2 km h −1 ) and sprinting distance (SprD; > 25.2 km h −1 ) were analysed in 5-min intervals prior to a goal scored for both teams. The employed linear mixed models showed that all examined match-running performance metrics were higher in teams that scored a goal compared to teams that conceded a goal. Within 5 min before scoring a goal in Polish Ekstraklasa matches, the scoring team produced significantly greater TD (∆ 95%CI 256.8–300.4 m; p = 0.001), WD (∆ 95%CI 52.3–95.8 m; p = 0.001), JG (∆ 95%CI 100.5–144.1 m; p = 0.001) and RD (∆ 95%CI 16.2–59.8 m; p = 0.001) compared to the conceding team, although no differences were found for HSR and SprD. These results demonstrate the enhanced identification potential of key physical performance factors influencing goal scoring in the Polish Ekstraklasa, thereby optimising the training process and improving overall performance. To enhance the effectiveness of soccer training, coaching and performance staff should consider this study's findings, that indicate an increase in the volume of medium- and low-intensity running efforts preceding a goal.
Needs and demands of contemporary engineering stimulate continuous and intensive development of design methods. Topology optimization is a modern approach which has been successfully implemented in a ...daily engineering design practice. Decades of progress resulted in numerous applications of topology optimization to many research and engineering fields. Since the design process starts already at the conceptual stage, innovative, efficient, and versatile topology algorithms play a crucial role. In the present study, the concept of the original heuristic topology generator is proposed. The main idea that stands behind this proposal is to take advantage of the colliding bodies phenomenon and to use the governing laws to derive original Cellular Automata rules which can efficiently perform the process of optimal topologies generation. The derived algorithm has been successfully combined with ANSYS, a commercial finite element software package, to illustrate its versatility and to make a step toward engineering applications. Based on the results of the tests performed, it can be concluded that the proposed concept of the automaton mimicking colliding bodies may be an alternative algorithm to other existing topology generators oriented toward engineering applications.
Although well-recognized in the fields of structural and material design and widely present in engineering literature, topology optimization still arouses a high interest within research communities. ...Moreover, it is observed that the development of innovative, efficient and versatile methods is one of the most important issues stimulating progress within the topology optimization area. Following this activity, in the present study, a concept of a hybrid algorithm developed in order to generate optimal structural topologies of minimal compliance is presented. The hybrid algorithm is built based on two existing approaches. The first one makes use of the formal optimality criterion, whereas the second one utilizes a special heuristic rule of design variables updating. The main idea that stands behind the concept of the present proposal is to take the advantage of both algorithms capabilities. In a numerical implementation of the hybrid algorithm, the design variables are updated at each iteration step using both approaches, and the solution with a lower objective function value is selected for the next iteration. The numerical tests of the generation of minimal compliance structures have been performed for chosen structures including a real engineering one. It has been confirmed that the proposed hybrid technique based on switching between the considered rules allows the final structures having lower values of compliance as compared with the results of an application of basic algorithms running separately to be obtained. Moreover, based on promising results of the tests performed, one can consider the proposed concept of a hybrid algorithm as an alternative for other existing topology generators.
Although structural topology optimization has been developing for decades, it still plays a leading role within the area of engineering design. Solving contemporary design problems coming from ...industry requires the implementation of efficient methods and approaches. This stimulates research progress in the development of novel and versatile topology optimization algorithms. To follow these modern trends, an original topology generator has been elaborated and finally built as a Cellular Automaton with original update rules. The motivation for building the algorithm in this way came from the idea of utilizing the benefits of local compliances sorting. This is conducted on two levels: on the global level, the monotonic function mapping local compliances distribution is defined based on their sorted values; on the local level, for each cell, the compliances are sorted within the cell neighborhood. The three largest absolute values are selected, and these are the basis from which to formulate Cellular Automata update rules. These original rules can efficiently control the generation of structural topologies. This technique is somewhat inspired by the grey wolf optimizer strategy, wherein the process of updating design variables refers to the positions of the three best fitted wolves. It is proposed that we refer to the topology algorithm that benefits from the adaptation of sorted compliances optimization as TABASCO. The developed algorithm is a modified version of the flexible Cellular Automata one presented previously. The implemented extension, regarding the local level cell sorting, allows us to improve the resulting compliance values. The advantages of the algorithm, both from numerical and practical engineering points of view, as compared to the others developed within the field, may be gathered as follows: the algorithm works based on simple update rules, i.e., its numerical implementation is not complicated; it does not require gradient computations; filtering techniques are not needed; and it can easily be combined with professional structural analysis programs which allow engineering applications. The developed topology generator has been linked with ANSYS to show that it can be incorporated into a commercial structural analysis package. This is especially important with respect to the engineering implementations.
Kraków, Poland, is a city with poor air quality, located in the large Wisła (Vistula) valley, and affected by a foehn wind from the Tatra Mountains. We analyzed 14 long episodes of the foehn from the ...periods Sep 2017 - Apr 2018 and Sep 2018 - Apr 2019. Data used included measurements of PM
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(i.e. particulate matter with an aerodynamic diameter up to 10 µm) concentrations) concentrations, air temperature and relative humidity, wind speed and direction from ground stations and mast measurements up to 100 m a.g.l., along with model analysis results. A non-operational configuration of the AROME CMC (the Application of Research to Operations at Mesoscale canonical model configuration) 1 km x 1 km was applied. A conceptual model concerning the impact of a foehn on urban air pollution was developed. The occurrence of a particular effect of a foehn on the PM
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spatial-temporal pattern depends on its mode of transfer through the city: a. a foehn flows above the valley where a strong cold air pool and a return flow can be found; b. a foehn enters the valley from the eastern, wider part or from the valley top and destroys the cold air pool; c. gravity waves generated by a foehn are strong enough to enter the western narrower part of the valley and cause large spatial differences in turbulence parameters within the city. The first transfer mode worsens air pollution dispersion conditions throughout the city and leads to large increases in PM
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levels (from below 50 to 150-200 µg⋅m
−3
), the second mode improves dispersion and leads to large decreases in PM
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levels (from 150-200 to below 50 µg⋅m
−3
) throughout the city, and the third generates large spatial differences in PM
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levels (50-70 µg⋅m
−3
) within the city. There is no single effect of a foehn on air pollution dispersion conditions.
The role of renewable energy sources in the Polish power system is growing. The highest share of installed capacity goes to wind and solar energy. Both sources are characterized by high variability ...of their power output and very low dispatchability. Taking into account the nature of the power system, it is, therefore, imperative to predict their future energy generation to economically schedule the use of conventional generators. Considering the above, this paper examines the possibility to predict day-ahead wind power based on different machine learning methods not for a specific wind farm but at national level. A numerical weather prediction model used operationally in the Institute of Meteorology and Water Management–National Research Institute in Poland and hourly data of recorded wind power generation in Poland were used for forecasting models creation and testing. With the best method, the Extreme Gradient Boosting, and two years of training (2018–2019), the day-ahead, hourly wind power generation in Poland in 2020 was predicted with 26.7% mean absolute percentage error and 4.5% root mean square error accuracy. Seasonal and daily differences in predicted error were found, showing high mean absolute percentage error in summer and during daytime.
Despite decades of progress, structural topology optimization is still one of the most important areas of engineering optimal design. The intensive research within this area has been stimulated by ...the development of efficient methods and algorithms on one side and the needs and demands of contemporary engineering on the other. Over the years, the practical aspect of topology optimization has become one of the most significant issues within the design community. Simultaneously, the range of design applications has been broadening. Among many research areas where topology optimization is present, attention has been paid to the design of multi-material structures. The gradation of the material properties has a significant influence on the final layout of the structure, so this problem can be treated as an extension of the classical task of the topology optimization of structures made of a material with uniform distributions of properties. While working with multi-material structures, the important role plays an interface between parts made of materials with different properties. In this paper, the implementation of interfaces made of functionally graded materials (FGM) is proposed. A functionally graded interface means that continuous and smooth changes of properties are assigned to a particular direction from one material surface to another. This paper presents the idea of topology optimization of graded multi-material structures using a simple, fast convergent technique based on the Cellular Automata approach. The proposal is to take the advantage of the versatility of efficient professional finite element-based structural analysis software and the simplicity of the original heuristic topology generator, to build a tool for the optimization of FGM structures as well as multi-material structures including the FGM interface.
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