The Experts below are selected from a list of 48 Experts worldwide ranked by ideXlab platform
Minking K Chyu - One of the best experts on this subject based on the ideXlab platform.
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optimization of the hole distribution of an effusively cooled surface facing non uniform Incoming Temperature using deep learning approaches
International Journal of Heat and Mass Transfer, 2019Co-Authors: Li Yang, Minking K ChyuAbstract:Abstract External cooling technologies such as transpiration cooling and effusion cooling are ideal thermal protection strategies for hot section components. Conventional cooling structures were not capable to adaptively fit non-uniform Incoming Temperature loads due to the limit in modelling and designing tools. The present study established an optimization workflow to adjust the hole distribution of an effusively cooled porous plate. A Conditional Generative Adversarial Neural Network model was developed to model the high dimensional and non-linear mapping between the surface profile and the surface Temperature of a series of effusively cooled plates. Computational Fluid Dynamics was utilized to provide data samples for the training of the model. With careful testing and validation of the trained model, the neural network model was integrated with Genetic Algorithms to search for optimal structures that can uniformly cool the plate to a proper Temperature level. Results obtained from the modeling efforts indicated a good capability of the neural network model to reconstruct the cooling effectiveness distribution on the external surface of the porous plates. Integrated with this low cost machine learning model, the GA approach successfully identified several optimized structures which fit well with the thermal loads induced by non-uniform Incoming gas temperate. Surface Temperature variation of the porous plates was reduced by around 50% as compared to the structure with a regular hole array. These attempts of introducing deep learning to external cooling in the present study were successful and future work could further focus on generalization of the modelling and enhancement of the robustness of the optimization approach.
Fotis Paschos - One of the best experts on this subject based on the ideXlab platform.
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Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Sensor Applications Experimentation and Logistics, 2010Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environments status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end systems use are also presented and discussed.
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SENSAPPEAL - Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, 2009Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environment’s status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end system’s use are also presented and discussed.
Li Yang - One of the best experts on this subject based on the ideXlab platform.
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optimization of the hole distribution of an effusively cooled surface facing non uniform Incoming Temperature using deep learning approaches
International Journal of Heat and Mass Transfer, 2019Co-Authors: Li Yang, Minking K ChyuAbstract:Abstract External cooling technologies such as transpiration cooling and effusion cooling are ideal thermal protection strategies for hot section components. Conventional cooling structures were not capable to adaptively fit non-uniform Incoming Temperature loads due to the limit in modelling and designing tools. The present study established an optimization workflow to adjust the hole distribution of an effusively cooled porous plate. A Conditional Generative Adversarial Neural Network model was developed to model the high dimensional and non-linear mapping between the surface profile and the surface Temperature of a series of effusively cooled plates. Computational Fluid Dynamics was utilized to provide data samples for the training of the model. With careful testing and validation of the trained model, the neural network model was integrated with Genetic Algorithms to search for optimal structures that can uniformly cool the plate to a proper Temperature level. Results obtained from the modeling efforts indicated a good capability of the neural network model to reconstruct the cooling effectiveness distribution on the external surface of the porous plates. Integrated with this low cost machine learning model, the GA approach successfully identified several optimized structures which fit well with the thermal loads induced by non-uniform Incoming gas temperate. Surface Temperature variation of the porous plates was reduced by around 50% as compared to the structure with a regular hole array. These attempts of introducing deep learning to external cooling in the present study were successful and future work could further focus on generalization of the modelling and enhancement of the robustness of the optimization approach.
Elias S. Manolakos - One of the best experts on this subject based on the ideXlab platform.
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Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Sensor Applications Experimentation and Logistics, 2010Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environments status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end systems use are also presented and discussed.
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SENSAPPEAL - Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, 2009Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environment’s status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end system’s use are also presented and discussed.
Evangelos Logaras - One of the best experts on this subject based on the ideXlab platform.
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Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Sensor Applications Experimentation and Logistics, 2010Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environments status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end systems use are also presented and discussed.
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SENSAPPEAL - Wireless Sensor Network Application for Fire Hazard Detection and Monitoring
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, 2009Co-Authors: Elias S. Manolakos, Evangelos Logaras, Fotis PaschosAbstract:Hazard detection systems are sophisticated tools that can help us detect and prevent environmental disasters. The role of a well designed environmental hazard detection system based on a Wireless Sensor Network (WSN) is to continuously monitor and report the environment’s status by sampling relevant physical parameters (e.g. Temperature), but at a rate that can be adapted dynamically to the criticality of the current situation, so that precious energy is conserved as much as possible and communication bandwidth is not wasted, both preconditions that need to be met for a scalable WSN application. We have designed and built a small-scale prototype of such a WSN system for fire detection and monitoring based on inexpensive in-house developed wireless sensor nodes. These nodes combine an AVR Butterfly microcontroller demonstration kit with an Xbee wireless Zigbee transceiver. The emphasis of the work reported here is on the software designed for the fire hazard detection application. We discuss the embedded computing strategy developed for the in-field sensor nodes that allows them to adjust their mode of operation (i.e. their sampling and reporting rates) dynamically and in an autonomous manner depending on the area prevailing conditions. We also discuss the functionality of the software running on the central node (PC) that is used to initialize the WSN system, synchronize nodes, monitor their status by maintaining an active registry, adjust parameters at any time, inspect real-time plots of the Incoming Temperature reports of selected nodes to monitor emerging trends and patterns etc. Several examples of the end-to-end system’s use are also presented and discussed.
