• Energy Research
• Closed Access close
• Open Source close
• US close
• ZENODO close

Global demand for electrical energy is in constant growth because of the constant increase in the number of inhabitants and the economy growth. This paper presents the way the increasing demand for energy and the constant increase in the capacity of power plant production systems exacerbates the working conditions of the system parts and leads to the remaining working life reduction. Efficient operation of thermal power plants is the basis of economical production of electricity based on combustion of lignite. Ventilation mill as such is one of the basic equipment in thermal power plants which work has a significant impact on the level of energy efficiency. This paper presents the complexity of the optimization problem of the different thermal power plants and the system demands to use multidisciplinary research. However, any optimization of an energy plant, such as a ventilation mill, in this case, represents a unique approach to the problem of operating efficiency of the plant, and as such it asks for many new requirements and solutions. This paper also presents the way for solving this complex problem by using detail analyses of work of system of ventilation mill and dust channel by analysing the period of failures. This paper describes the following: the usages of CFD numerical simulation in FLUENT software for determining the working conditions in ventilation mill and dust channel; possibilities for use the process of coating damaged parts with wear resistance material and procedure for selection and coating on real working parts; analyses of damaged coated working parts of ventilation mill after testing in exploitation condition; data analysis of working parts before and after coating, time and time and resource saving. One of the main goals is to analyse the damaged coated working parts of ventilation mill after testing in exploitation condition.

When attempting to avoid global warming, individuals often face a social dilemma in which, besides securing future benefits, it is also necessary to reduce the chances of future losses. In this manuscript, we introduce a simple approach to address this type of dilemmas, in which the risk of failure plays a central role in individual decisions. This model can be shown to capture some of the essential features discovered in recent key experiments, while allowing one to extend in non-trivial ways the experimental conditions to regions of more practical interest. Our results suggest that global coordination for a common good should be attempted by segmenting tasks in many small to medium sized groups, in which perception of risk is high and uncertainty in collective goals is minimized. Moreover, our results support the conclusion that sanctioning institutions may further enhance the chances of coordinating to tame the planet's climate, as long as they are implemented in a decentralized and polycentric manner.

(Uploaded by Plazi for the Bat Literature Project) Amazonian forests play a key role in the global carbon cycle, but there is much uncertainty about the quantity and distribution of carbon stored in these forests. We quantified total aboveground dry biomass (TAGB) in undisturbed central Amazonian rainforests, based on detailed estimates of all live and dead plant material within 20 1 ha plots spanning an extensive (ca. 1000 km2) study area. TAGB values in our study area were very high, averaging 397:7 Æ 30:0 Mg haÀ1. The most important component of aboveground biomass was large (!10 cm diameter-at-breast-height (DBH)) trees, which comprised 81.9% of TAGB, followed by downed wood debris (7.0%), small trees, saplings, and seedlings (<10 cm DBH; 5.3%), lianas (2.1%), litter (1.9%), snags (1.5%), and stemless palms (0.3%). Among large trees, aboveground biomass was greatest in intermediate-sized (20–50 cm DBH) stems (46.7% of TAGB), with very large (!60 cm DBH) trees also containing substantial biomass (13.4% of TAGB). There were no significant correlations between large tree biomass and that of any other live or dead biomass component. An analysis based on the variability of our samples suggested that just 3–4 randomly positioned 1 ha plots would be sufficient to provide a reasonable estimate of mean TAGB in a landscape such as ours (with 95% confidence intervals being <10% of the mean). This suggests that efforts to quantify Amazon forest biomass should be extensive rather than intensive; researchers should sample many geographically separate areas with a few plots each, rather than sampling a small number of areas more intensively.

AbstractThe tropical forests of the Congo Basin and Gulf of Guinea harbor some of the greatest terrestrial and aquatic biological diversity in the world. However, our knowledge of the rich biological diversity of this region and the evolutionary processes that have shaped it remains limited, as is our understanding of the capacity for species to adapt or otherwise respond to current and projected environmental change. In this regard, research efforts are needed to increase current scientific knowledge of this region's biodiversity, identify the drivers of past diversification, evaluate the potential for species to adapt to environmental change and identify key populations for future conservation. Moreover, when evolutionary research is combined with ongoing environmental monitoring efforts, it can also provide an important set of tools for assessing and mitigating the impacts of development activities. Building on a set of recommendations developed at an international workshop held in Gabon in 2011, we highlight major areas for future evolutionary research that could be directly tied to conservation priorities for the region. These research priorities are centered around five disciplinary themes: (1) documenting and discovering biodiversity; (2) identifying drivers of evolutionary diversification; (3) monitoring environmental change; (4) understanding community and ecosystem level processes; (5) investigating the ecology and epidemiology of disease from an evolutionary perspective (evolutionary epidemiology). Furthermore, we also provide an overview of the needs and priorities for biodiversity education and training in Central Africa.

The viability and accuracy of large-eddy simulation (LES) with wall modeling for high Reynolds number complex turbulent flows is investigated by considering the flow around a circular cylinder in the supercritical regime. A simple wall stress model is employed to provide approximate boundary conditions to the LES. The results are compared with those obtained from steady and unsteady Reynolds-averaged Navier–Stokes (RANS) solutions and the available experimental data. The LES solutions are shown to be considerably more accurate than the RANS results. They capture correctly the delayed boundary layer separation and reduced drag coefficients consistent with experimental measurements after the drag crisis. The mean pressure distribution is predicted reasonably well at ReD=5×105 and 106. However, the Reynolds number dependence is not captured, and the solution becomes less accurate at increased Reynolds numbers.

a Centro de Biologia Molecular e Ambiental, Universidade do Minho, 4710-057 Braga, Portugal b Departamento de Matematica e Aplicacoes, Universidade do Minho, 4710-057 Braga, Portugal c ATP-Group, CMAF, Instituto para a Investigacao Interdisciplinar, 1649-003 Lisboa, Portugal d INESC-ID and Instituto Superior Tecnico, Universidade de Lisboa, Taguspark, 2744-016 Porto Salvo, Portugal e Centro de Fisica da Universidade do Minho, 4710-057 Braga, Portugal

Magnetodynamic wireless power transfer (WPT), also known as electrodynamic wireless power transfer, is a low-frequency WPT technology based on an electromechanical receiver comprising a permanent magnet moving in a coil. Because of the low-frequency field, this technology is safe around humans and enables transfer through conductive media. In this paper, we focus on the design and the optimization of the power receiver with advanced modelling methods. Two operating modes, namely a continuously rotating mode and a resonant mode, targeting high-power-density and mid-range power transfer respectively, are investigated and compared to previous versions. The fabricated 25-cm3 receiver presents substantial improvements in terms of transferred power (3.3W) and power density (x7) compared to previous receivers in the same conditions of fields.

This paper presents a comparison of a Reinforcement-Learning (RL) based wave energy conversion controller against standard reactive damping and model predictive control (MPC) approaches, in the presence of modeling errors. Wave energy converters (WECs) are under the influence of many non-linear hydrodynamic forces, yet for ease and expediency, it is common to formulate linear WEC models and control laws. Therefore it is expected that significant modeling errors may be present, which may degrade model-based control performance. Model-free RL approaches to control may offer a significant advantage in robustness to modeling errors, in that the model is learned by the controller by experience. It is shown that, for an annual average sea state, RL-based controllers can outperform model-based control – reactive control and MPC – by 19% and 16%, respectively, when significant modeling error is present. Furthermore, compared to similar studies of RL-based control, the proposed model can reduce the training time from 8.4 hr to 1.5 hr.© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@openaccessbutton.org.