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Wyniki wyszukiwania dla: TURBINE LINEAR REGRESSION MACHINE LEARNING OPTIMIZATION ORC
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Load effect impact on the exploitation of concrete machine foundations used in the gas and oil industry
PublikacjaMachine foundations is a critical topic in the gas and oil industry, which design and exploitation require extensive technical knowledge. Machine foundations are the constructions which are intended for mounting on it a specific type of machine. The foundation has to transfer dynamic and static load from machine to the ground. The primary difference between machine foundations and building foundations is that the machine foundations...
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Olgun Aydin Dr
OsobyOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Senior Data Scientist in PwC Poland, gives lectures in Gdansk University of Technology in Poland and member of WhyR? Foundation. Olgun is a very big fan of R and author of the book called “R Web Scraping Quick Start Guide” , two video courses are called “Deep Dive into Statistical Modelling using R” and “Applied Machine Learning and Deep...
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Uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych
PublikacjaW pracy omówiono uczenie maszynowe do samoorganizacji systemów rozproszonych w zastosowaniach gospodarczych ze szczególnym uwzględnieniem sieci neuronowych do predykcji finansowych oraz szacowania ratingu przedsiębiorstw. Oprócz sieci neuronowych, istotną rolę w przygotowaniu i testowaniu informatycznych systemów finansowych może pełnić programowanie genetyczne. Z tego powodu omówiono uczenie maszynowe w aplikacjach konstruowanych...
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Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
PublikacjaCurrent computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning,...
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Joint workshop on Multimodal Interaction and Related Machine Learning Algorithms (now ICMI-MLMI)
Konferencje -
Design analysis of combined gas-vapour micro power plant with 30 kW air turbine
PublikacjaThe article presents basic results of the design analysis of a combined gas-vapour micro power plant with a waste-heat boiler without exhaust reheat, working in the vapour section in the Organic Rankine Cycle (ORC) system. The analysis concerned working media most frequently used in those types of power plants and planned to be used in future. The object of the analysis was a micro power plant with a 30 kW gas (air) turbine for...
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Design analysis of combined gas-vapour micro power plant with 30 kW air turbine
PublikacjaThe article presents basic results of the design analysis of a combined gas-vapour micro power plant with a waste-heat boiler without exhaust reheat, working in the vapour section in the Organic Rankine Cycle (ORC) system. The analysis concerned working media most frequently used in those types of power plants and planned to be used in future. The object of the analysis was a micro power plant with a 30 kW gas (air) turbine for...
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Review of the Complexity of Managing Big Data of the Internet of Things
PublikacjaTere is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing feld of the Internet of Tings (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description...
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Rotordynamic characteristics of a chamber seal
PublikacjaThe paper presents the results of numerical and experimental investigations into pressure forces generated in a turbine labyrinth seal of a modernized type. The experiments were performed on a single-stage air model turbine of the impulse type. The experiments were performed on a single-stage air model turbine of the impulse type. The experimental data were compared with theoretical results obtained by means of CFD Fluent Code....
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SHORT REVIEW AND 3-D FEM ANALYSIS OF BASIC TYPES OF FOUNDATION FOR OFFSHORE WIND TURBINES
PublikacjaSome problems of the foundations of offshore wind turbines are considered in this paper. A short review is presented on the two basic types of foundations, i.e. monopiles and gravity foundations, including their basic features and applications as well as general design considerations. Also, some issues regarding analysis are discussed, including geotechnical problems and modelling techniques. A numerical model of offshores turbine...
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Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublikacjaPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
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Real-time hybrid model of a wind turbine with doubly fed induction generator
PublikacjaIn recent years renewable sources have been dominating power system. The share of wind power in energy production increases year by year, which meets the need to protect the environment. Possibility of conducting, not only computer simulation, but also laboratory studies of wind turbine operation and impact on the power system and other power devices in laboratory conditions would be very useful. This article presents a method...
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublikacjaThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
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Strategic Flexibility as a Mediator in Relationship between Managerial Decisions and Organizational Learning: Ambidexterity Perspective
PublikacjaPurpose: The purpose of the article is to determine strategic flexibility in the relationship between managerial decisions and organizational learning. The analyses are conducted in the ambidexterity convection. Design/Methodology/Approach: The study was conducted at a textile company. The company is a leader in the textile recycling industry in Poland. Empirical data were collected using the PAPI technique. The survey questionnaire...
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Planning optimised multi-tasking operations under the capability for parallel machining
PublikacjaThe advent of advanced multi-tasking machines (MTMs) in the metalworking industry has provided the opportunity for more efficient parallel machining as compared to traditional sequential processing. It entailed the need for developing appropriate reasoning schemes for efficient process planning to take advantage of machining capabilities inherent in these machines. This paper addresses an adequate methodical approach for a non-linear...
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Monitoring of n-butanol vapors biofiltration process using an electronic nose combined with calibration models
PublikacjaMalodours, by definition, are generally unpleasant, nuisance smells that are a mixture of volatile chemical compounds which can be perceptible even at low concentrations. Due to the more frequent occurrence of odour nuisance associated with the odour sensations, and thus the need to remove them from the air, deodorization techniques are commonly used. Biofiltration is one of the methods of reducing odorants in the air stream. In...
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Artificial Neural Networks as an architectural design tool- generating new detail forms based on the Roman Corinthian order capital
PublikacjaThe following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital....
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Task Assignments in Logistics by Adaptive Multi-Criterion Evolutionary Algorithm with Elitist Selection
PublikacjaAn evolutionary algorithm with elitist selection has been developed for finding Pareto-optimal task assignments in logistics. A multi-criterion optimization problem has been formulated for finding a set of Pareto- optimal solutions. Three criteria have been applied for evaluation of task assignment: the workload of a bottleneck machine, the cost of machines, and the numerical performance of system. The machine constraints have...
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Resource productivity and environmental degradation in EU-27 countries: context of material footprint
PublikacjaThis study explores the relationship between the resource productivity and environmental degradation in European Union-27 countries. This study tests this relationship in context of high, moderate, and low material footprint sub-samples; these samples are formed utilizing the expectation–maximization machine learning algorithm. Using the panel data set of EU-27 countries from 2000 to 2020, linear and non-linear autoregressive distributed...
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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublikacjaResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Analysing selection of low-temperature medium for cogeneration micro power plant
PublikacjaThe article analyses the ORC system working with dry and wet low-boiling media which are most frequently used in installations of this type. Two types of cycles were examined, which were the cycle with heat regeneration for dry media: fc72, hfe7100, R227ea, R245fa, R423a and R600a, and the cycle without heat regeneration for wet media: R11, R12, R134a, R718 and 507a. The calculations were performed for the assumed required thermal...
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Analysing selection of low-temperature medium for cogeneration micro power plant
PublikacjaThe article analyses the ORC system working with dry and wet low-boiling media which are most frequently used in installations of this type. Two types of cycles were examined, which were the cycle with heat regeneration for dry media: fc72, hfe7100, R227ea, R245fa, R423a and R600a, and the cycle without heat regeneration for wet media: R11, R12, R134a, R718 and 507a. The calculations were performed for the assumed required thermal...
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Comparative Analysis of Text Representation Methods Using Classification
PublikacjaIn our work, we review and empirically evaluate five different raw methods of text representation that allow automatic processing of Wikipedia articles. The main contribution of the article—evaluation of approaches to text representation for machine learning tasks—indicates that the text representation is fundamental for achieving good categorization results. The analysis of the representation methods creates a baseline that cannot...
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Globalisation and world economic poverty: The significance of hidden dimensions
PublikacjaThe aim of our research is to examine how individual dimensions of globalization affect economic poverty in the World. for this, regression models are estimated with FGT0 or FGT1 poverty measures as dependent variables and KOF indices of globalization as despendent variables. The poverty indices are estimated for 119 countries' income didtributions assuming log-normality and using Gini estimates from the WID2 database and GDP/capita...
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Three-dimensional geographically weighted inverse regression (3GWR) model for satellite derived bathymetry using Sentinel-2 observations
PublikacjaCurrent trends of development of satellite derived bathymetry (SDB) models rely on applying calibration techniques including analytical approaches, neuro-fuzzy systems, regression optimization and others. In most of the cases, the SDB models are calibrated and verified for test sites, that provide favourable conditions for the remote derivation of bathymetry such as high water clarity, homogenous bottom type, low amount of sediment...
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Book Review
PublikacjaActing over the last three decades as an Editor and Associate Editor for a number of international journals in the general area of cybernetics and AI, as well as a Chair and Co-Chair of numerous conferences in this field, I have had the exciting opportunity to closely witness and to be actively engaged in the stimulating research area of machine learning and its important augmentation with deep learning techniques and technologies. From...
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Exergy Losses in the Szewalski Binary Vapor Cycle
PublikacjaIn this publication, we present an energy and exergy analysis of the Szewalski binary vapor cycle based on a model of a supercritical steam power plant. We used energy analysis to conduct a preliminary optimization of the cycle. Exergy loss analysis was employed to perform a comparison of heat-transfer processes, which are essential for hierarchical cycles. The Szewalski binary vapor cycle consists of a steam cycle bottomed with...
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Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects
PublikacjaWastewater treatment is an important topic for improving water quality and environmental protection, and artificial intelligence has become a powerful tool for wastewater treatment. This work provides research progress and a literature review of artificial intelligence applied to wastewater treatment based on the visualization of bibliometric tools. A total of 3460 publications from 2000 to 2023 were obtained from the Web of Science...
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Comparative study of selected fluids for use in supercritical Organic Ranking Cycles
PublikacjaIn view of increasing interest in improving energy efficiency of energy conversion devices, there is an increasing requirement of combined production of heat and electricity as well as demand for increased implementation of renewable energy resources. The micro cogenerative units utilizing the Organic Rankine Cycle are focusing the attention of many research centres around the world. In the present paper calculations of ORC cycles...
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Failure of cold-formed beam: How does residual stress affect stability?
PublikacjaIn machine industry, stresses are often calculated using simple linear FEM analysis. Occasional failures of elements designed in such a way require recomputation by means of more sophisticated methods, eg. including plasticity and non-linear effects. It usually leads to investigation of failure causes and improvement of an element in order to prevent its unwanted behavior in the future. The study presents the case where both linear...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Experimental determination of general characteristic of internal combustion engine using mobile test bench connected via Power Take-Off unit
PublikacjaThe general characteristics of the engine include information about the regions of the engine's operating area that are most efficient, where specific fuel consumption reaches the smallest values. Economic operation based on those characteristics can contribute to a significant reduction of fuel consumption and consequently less pollutant emissions and lower costs. The paper presents an experimental method of determination of general...
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The Influence of Cooperation on the Operation of an MPC Controller Pair in a Nuclear Power Plant Turbine Generator Set
PublikacjaThe paper discusses the problem of cooperation between multiple model predictive control (MPC) systems. This approach aims at improving the control quality in electrical energy generation and forms the next step in a series of publications by the authors focusing on the optimization and control of electric power systems. Cooperation and cooperative object concepts in relation to a multi MPC system are defined and a cooperative control...
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Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management
PublikacjaDesign of modern antenna systems heavily relies on numerical opti-mization methods. Their primary purpose is performance improvement by tun-ing of geometry and material parameters of the antenna under study. For relia-bility, the process has to be conducted using full-wave electromagnetic (EM) simulation models, which are associated with sizable computational expendi-tures. The problem is aggravated in the case of global optimization,...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublikacjaThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublikacjaIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublikacjaIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Intensification of catechin extraction from the bark of Syzygium cumini using ultrasonication: Optimization, characterization, degradation analysis and kinetic studies
PublikacjaCatechin is a prominent polyphenolic component that possesses various medicinal properties. Present work communicates the intensification and optimization of catechin extraction from the bark of Syzygium cumini tree using stirred reactor, soxhlet, ultrasonic bath, and ultrasonic horn technique. The optimization of several parameters such as type of solvent, solid to solvent ratio (1:100 w/v), speed of agitation (300 RPM), extraction...
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Determination of benzo(a)pyrene content in PM10 using regression methods
PublikacjaThe paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P concentration...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublikacjaThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublikacjaThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
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Optimisation of turbine shaft heating process under steam turbine run-up conditions
PublikacjaAn important operational task for thermal turbines during run-up and run-down is to keep the stresses in the structural elements at a right level. This applies not only to their instantaneous values, but also to the impact of them on the engine lifetime. The turbine shaft is a particularly important element. The distribution of stresses depends on geometric characteristics of the shaft and its specific locations. This means a groove manufactured...
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Reduced-cost constrained miniaturization of wideband antennas using improved trust-region gradient search with repair step
PublikacjaIn the letter, an improved algorithm for electromagnetic (EM)-driven size reduction of wideband antennas is proposed. Our methodology utilizes variable-fidelity EM simulation models, auxiliary polynomial regression surrogates, as well as multi-point response correction. The constraint handling is implicit, using penalty functions. The core optimization algorithm is a trust-region gradient search with a repair step added in order...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublikacjaThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Anomaly Detection in Railway Sensor Data Environments: State-of-the-Art Methods and Empirical Performance Evaluation
PublikacjaTo date, significant progress has been made in the field of railway anomaly detection using technologies such as real-time data analytics, the Internet of Things, and machine learning. As technology continues to evolve, the ability to detect and respond to anomalies in railway systems is once again in the spotlight. However, railway anomaly detection faces challenges related to the vast infrastructure, dynamic conditions, aging...
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Zagospodarowanie ciepła odpadowego z biogazowych agregatów kogeneracyjnych w oczyszczalni ścieków = Waste heat utilisation from cogeneration set in sewage plant
PublikacjaW pracy opisano koncepcję współpracy biogazowych modułów kogeneracyjnych z niskotemperaturowym obiegiem parowym. Proponowana modernizacja pozwoliłaby na wykorzystanie entalpii fizycznej spalin, tym samym zwiększając sprawność urządzeń wytwarzających ciepło i energię elektryczną. Tego typu rozwiązanie umożliwiłoby częściowe pokrycie zapotrzebowania własnego na energię elektryczną, generując oszczędności w przedsiębiorstwie. W artykule...
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Zagospodarowanie ciepła odpadowego z biogazowych agregatów kogeneracyjnych w oczyszczalni ścieków
PublikacjaW pracy opisano koncepcję współpracy biogazowych modułów kogeneracyjnych z niskotemperaturowym obiegiem parowym. Proponowana modernizacja pozwoliłaby na wykorzystanie entalpii fizycznej spalin, tym samym zwiększając sprawność urządzeń wytwarzających ciepło i energię elektryczną. Tego typu rozwiązanie umożliwiłoby częściowe pokrycie zapotrzebowania własnego na energię elektryczną, generując oszczędności w przedsiębiorstwie. W artykule...