Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks

Rymarczyk, Tomasz; Król, Krzysztof; Kozłowski, Edward; Wołowiec, Tomasz; Cholewa-Wiktor, Marta; Bednarczuk, Piotr

doi:10.3390/en14238081

Cited by 8 publications

(4 citation statements)

References 53 publications

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“…In addition, we will lay the peculiarities of the HEAT 4.0 project as the basis for smart interaction between green heat energy producers and consumers [35][36][37][38], which integrates intelligent IT solutions into a new digital framework to achieve a holistic approach to district heating. HEAT 4.0 caters to the digital needs of the entire sector, from production site to distribution to end-users, creating synergies between the design, operation, maintenance, and supply of district heating.…”

Section: Innovative Solutions To Ensure Climate Policy In the Energy ...mentioning

confidence: 99%

Smart Transition to Climate Management of the Green Energy Transmission Chain

et al. 2022

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Climate challenges in recent decades have forced a change in attitude towards forms of environmental interaction. The International Climate Conference COP26 evidences the relevance of the climate issue at the global level in Glasgow (November 2021). A decrease in natural energy resources leads to a search for alternative energy sources. Given this, this article is devoted to studying the peculiarities of the transition to climate management of the green energy transmission chain based on the circular economy and smart technologies. This paper has used simulation modeling to develop an algorithm for applying a smart approach to climate management of the green energy transmission chain based on the work of Industry 4.0 technologies. The result of this modeling will be the importance of strengthening the ability to develop intersectoral partnerships to create climate-energy clusters based on a closed cycle of using energy resources and developing smart technologies. At the same time, it has been found that COVID-19 has changed the behaviour of energy consumers towards the transition to the use of energy from renewable sources that are carbon neutral. With this in mind, this article has assessed the climate capacity of industries to use green energy from renewable sources based on resource conservation (rational use of energy resources) and climate neutrality. The industries of Ukraine, which are the largest consumers of energy and, at the same time, significantly affected by climate change, were taken for the study: industry, transport, and agriculture. The methodology for determining the indicator of the climate capacity of sectors in the transition to green energy has been based on the correlation index (ratio) of the consumption indicator of various types of energy by industries (petroleum products; natural gas; biofuels and waste; electricity) and the indicator of gross value added of industries in pre-COVID-19 and COVID-19 conditions. The results have indicated that the use of energy from renewable sources (biofuels and waste) for the production of goods and services, as well as the economical nature of the provision of raw materials (biomass and faeces) are factors that ensure climate industry neutrality and enhance its climate capability. The prospects of such effects of assessing the climate capacity of sectors will be the basis for the rationale to develop intersectoral partnerships to create climate-energy clusters based on a closed cycle of using energy resources and developing smart technologies.

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Section: Innovative Solutions To Ensure Climate Policy In the Energy ...mentioning

confidence: 99%

Smart Transition to Climate Management of the Green Energy Transmission Chain

et al. 2022

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“…Six Sigma methodology is based on decision-making using data extracted from the process, its statistical analysis and continuous improvement. It can be used in two varieties: DMAIC (an acronym from the first letters of the words Define-Measure-Analyze-Improve-Control), which aims to improve the performance of business processes and will be discussed in more detail below, and DMADV (an acronym from the first letters of the words Define-Measure-Analyze-Design-Verify), to design new objects [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Production Process Capability Assessment for Non-Normal Data

et al. 2023

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The process quality capability indicators Cp and Cpk are widely used to measure process capability. Traditional metric estimation methods require process data to be explicit and normally distributed. Often, the actual data obtained from the production process regarding the measurements of quality features are incomplete and do not have a normal distribution. This means that the use of traditional methods of estimating Cp and Cpk indicators may lead to erroneous results. Moreover, in the case of qualitative characteristics where a two-sided tolerance limit is specified, it should not be very difficult. The problem arises when the data do not meet the postulate of normality distribution and/or a one-sided tolerance limit has been defined for the process. Therefore, the purpose of this article was to present the possibility of using the Six Sigma method in relation to numerical data that do not meet the postulate of normality of distribution. The paper proposes a power transformation method using multiple-criteria decision analysis (MCDA) for the asymmetry coefficient and kurtosis coefficient. The task was to minimize the Jarque–Bera statistic, which we used to test the normality of the distribution. An appropriate methodology was developed for this purpose and presented on an empirical example. In addition, for the variable after transformation, for which the one-sided tolerance limit was determined, selected process quality evaluation indices were calculated.

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“…A study of individual and collective consumption of photovoltaic energy for a fifthgeneration district heating network is presented in [25]. The results showed that due to the different seasonality between heating demand and photovoltaic energy production, the increase in own consumption due to distributed heat pumps is less than 10%.…”

Section: Introductionmentioning

confidence: 99%

Towards Climate Management of District Heating Enterprises’ Innovative Resources

et al. 2022

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Tracking the trend of restricted access to natural fossil energy resources determines the need to search for alternative energy sources, introducing energy-efficient technologies, and optimizing the energy supply system based on intelligent networks. Understanding district heating enterprises’ readiness to work with innovative renewable resources based on climate neutrality plays a unique role. Thus, this article is devoted to the study of the features of providing and determining the district heating enterprises’ capacity to integrate climate management of innovative resources to produce green thermal energy. The research methodology is based on a combination of systemic, process and cybernetic approaches to determining the resource sustainability of district heating enterprises for implementing climate innovations. The scientific novelty of the study lies in a comprehensive assessment of the ability of district heating enterprises to use renewable resources (biomass, waste, hydropower, solar energy, wind energy) for the production of thermal energy according to such indicators as: an indicator of balanced resource use, an indicator of climate neutrality and an indicator of economic feasibility. The results became the basis to apply the set-theoretical approach to calculate the district heating enterprises’ coefficient of resource sustainability, based on the climate management of innovative resources to produce green thermal energy. The innovation of the fuzzy sets method lies in achieving the set goal without the deep formation of a data dynamics series, particularly interval models. The added scientific value of the method to determine the resource sustainability of district heating enterprises is used to justify the feasibility of integrating climate management with the use of innovative resources through the diversification of renewable energy sources for thermal energy production. The prospects for such results are the basis for future research to develop intersectoral clustering enterprises in the green energy production chain based on a closed cycle of renewable energy resources.

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Application of Electrical Tomography Imaging Using Machine Learning Methods for the Monitoring of Flood Embankments Leaks

Cited by 8 publications

References 53 publications

Smart Transition to Climate Management of the Green Energy Transmission Chain

Smart Transition to Climate Management of the Green Energy Transmission Chain

A New Approach to Production Process Capability Assessment for Non-Normal Data

Towards Climate Management of District Heating Enterprises’ Innovative Resources

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