Search
Didn't find any results in this catalog!
But we have some results in other catalogs.Search results for: TURBINE LINEAR REGRESSION MACHINE LEARNING OPTIMIZATION ORC
-
Impact of rotor geometry optimization on the off-design ORC turbine performance
PublicationThe paper describes the method of CFD based Nelder-Mead optimization of a 10 kW single-stage axial turbine operating in an ORC system working on R7100. The total-to-static isentropic efficiency is defined as an objective function. Multi-point linear regression is carried out to determine the significance of the objective function arguments and to pick up the set of particular variables and characteristic quantities (e.g. flow angles)...
-
Domestic ORC micro-CHP combined with a commercial gas boiler
PublicationThe chapter presents the results of experimental studies conducted during the launch of the first in Poland demonstration prototype of the micro ORC coupled to a domestic gas boiler. The accomplished studies indicated the possibility for the ORC module to work with such boiler (autonomous source of heat) with a prototype single-stage axial micro turbine as the expansion machine. Confirmation of that fact has been delineated in...
-
Analysis of Organic Rankine Cycle efficiency and vapor generator heat transfer surface in function of the reduced pressure
PublicationIn the paper presented is analysis of the influence of reduced pressure on efficiency and heat transfer area of vapor generator of Organic Rankine Cycle (ORC) in case of subcritical and supercritical parameters of operation. Compared are two cases of subcritical and supercritical ORC featuring a similar arrangement of heat source supply and heat removal, that is featuring the same temperatures of working fluid before the turbine,...
-
Multi-objective optimization of the ORC axial turbine for a waste heat recovery system working in two modes: cogeneration and condensation
PublicationDue to the demand of the district heating network and electric power grid ORC turbines can operate in the condensation and cogeneration modes. This approach requires the design of an expander which is characterized by high efficiency in each mode of operation. The paper is devoted to a multi-objective efficiency optimization of a one stage axial ORC turbine working on MM (Hexamethyldisiloxane). An Implicit Filtering algorithm (IF)...
-
Ireneusz Czarnowski Prof.
PeopleIRENEUSZ CZARNOWSKI is a graduate of the Faculty of Electrical Engineering at Gdynia Maritime University. He gained a doctoral degree in the field of computer science at Poznan University of Technology and a postdoctoral degree in the field of computer science at Wroclaw University of Science and Technology. Since 1998 is associated with Gdynia Maritime University, currently is a professor of computer science in the Department...
-
TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublicationTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
-
Machine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects
PublicationMachine Learning Assisted Interactive Multi-objectives Optimization Framework: A Proposed Formulation and Method for Overtime Planning in Software Development Projects Hammed A. Mojeed & Rafal Szlapczynski Conference paper First Online: 14 September 2023 161 Accesses Part of the Lecture Notes in Computer Science book series (LNAI,volume 14125) Abstract Software development project requires proper planning to mitigate risk and...
-
Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
-
Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...
-
Machine learning applied to acoustic-based road traffic monitoring
PublicationThe motivation behind this study lies in adapting acoustic noise monitoring systems for road traffic monitoring for driver’s safety. Such a system should recognize a vehicle type and weather-related pavement conditions based on the audio level measurement. The study presents the effectiveness of the selected machine learning algorithms in acoustic-based road traffic monitoring. Bases of the operation of the acoustic road traffic...