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For the first time, we investigated species composition, phytoplankton community structure, and hydrochemical parameters in the artificial cooling reservoir of a major thermal power plant (TPP) in northeastern Europe located in the Pechora River basin (Komi Republic). Our research, conducted during June and August, revealed a total of 81 species of algae and cyanobacteria, with cyanobacteria predominating. Among these cyanobacteria and microalgae (Bacillariophyta and Chlorophyta), algae that serve as reliable indicators of water quality were identified. The assessment of water quality based on abundance and species composition of indicator phytoplankton species revealed that the waters of the Pechorskoe Reservoir belong to the III class (β-mesosaprobic or moderately polluted). This indicates that water quality is satisfactory, and the reservoir retains the ability to self-purify. The power plant's discharges heat the surface layers, increasing plankton communities' diversity, abundance, and biomass. Such stable warming in the upper layers throughout the season, uncommon for natural water bodies in the north, results in a slight increase in the trophic status of the studied reservoir, supported by hydrochemical analysis. These results provide valuable information about ecosystem functioning under temperature increasing for predicting changes in the phototrophic biota of small northern reservoirs facing the impacts of climate change. [ABSTRACT FROM AUTHOR]

Background. The relevance of the article is due to its practical significance for solving the problems of operational safety of ammunition located at storage facilities, when it is necessary to know the time of explosion of products. The article proposes a developed analytical model for determining the permissible exposure time for ammunition to damaging environmental factors (lightning and landscape fire). Materials and methods. Modeling of the process of emergency situations during the explosion of standard or promising ammunition with low-sensitivity explosive compositions under external thermal influence can be described by a Markov random process scheme with a countable number of states. The use of the Markov model makes it possible to apply a well-developed and proven mathematical apparatus and obtain a deliberately reliable result due to the rather strict restrictions adopted. Results and conclusions. Thus, the developed analytical model for determining the permissible exposure time for ammunition to damaging environmental factors can be used to predict the operational safety of products in storage or in the assembly and repair production of arsenals for complex storage of missiles and ammunition. The obtained algorithm for determining the permissible time of exposure to damaging environmental factors on ammunition is advisable to use in the development of promising ammunition with low-sensitivity explosive compositions.

[Display omitted] • BIPV envelope design optimization is a complex, time-consuming process. • ANN serves as an efficient surrogate model for BIPV performance prediction. • The NSGA-II algorithm effectively optimizes multiple BIPV envelope design objectives. • The proposed framework supports rapid BIPV envelope design optimization during the detailed design phase. • Computational time is significantly reduced by the surrogate-based MOO framework while balancing energy, cost, and comfort. By integrating renewable energy systems (RESs) into buildings, Building-Integrated Photovoltaics (BIPV) reshape the demand–supply relationship, offering substantial benefits such as reduced energy usage, lower greenhouse gas emissions, improved indoor comfort, and architectural enhancement. However, designing optimal BIPV systems involves balancing multiple parameters and conflicting objectives, making it a complex, computationally intensive process. This study proposes a data-driven optimization framework to enhance BIPV envelope design during the detailed design phase. The novelties of this research lie in 1) the use of Artificial Neural Networks (ANN) as a surrogate model for rapid prediction, and 2) a multi-objective optimization (MOO)framework tailored for BIPV design at the detailed design phase. The proposed framework integrates ANN-based predictive modelling with an NSGA-II optimization component to generate optimal BIPV configurations efficiently. Implemented in Python, this approach is validated through a benchmark case study in Melbourne, demonstrating its effectiveness in reducing computational demands while achieving balanced energy, economic, and indoor comfort performance. This research advances sustainable building design by addressing gaps in current optimization frameworks and providing practical tools for architects and designers, promoting the wider adoption of BIPV solutions with significant computational savings. [ABSTRACT FROM AUTHOR]

The focus on green efficient schools is increasing globally. Both private and public-school buildings in the UAE are considered high energy consumers, using significant amounts of energy to maintain a comfortable thermal environment for students. Unfortunately, the designs of these schools have overlooked traditional passive design solutions such as courtyard design and orientation, which can improve internal thermal conditions while minimizing energy consumption. Therefore, this research aims to examine and emphasize the thermal impact of courtyard design and orientation in five existing public schools, with the goal of incorporating these considerations into future green school designs. The research utilized a qualitative approach, employing ENVI-met software to analyze the thermal effects of the schools' orientations. The findings indicated that the case studies exhibited varying temperatures based on the orientation and configuration of their courtyards. Furthermore, the research identified the optimal school building courtyard, which belonged to the UPA-fin school. This design featured north-facing, semi-opened courtyard that blocked hot winds, with rectangular shape oriented east-west, and specific proportions for courtyard area to plot area 26%, and to building area 40%. Compared to the poorest school courtyard design KAT, UPA-fin recorded temperature reductions of 1.7 °C and 1.8 °C on 21st September and March respectively. • The orientation of the schools' courtyards can affect their thermal performance. • The effect of the courtyard's orientation depends on the courtyard ratio size, courtyard type and number. • Considering the design and the courtyards orientation in vital to have better thermal performance for school buildings. • Th courtyards' orientation affects the closed courtyards less than the semi opened courtyards. [ABSTRACT FROM AUTHOR]