The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Murat E Sozer - One of the best experts on this subject based on the ideXlab platform.
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constraints on monitoring Resin Flow in the Resin transfer molding rtm process by using thermocouple sensors
Composites Part A-applied Science and Manufacturing, 2007Co-Authors: Goker Tuncol, Murat Danisman, Alper Kaynar, Murat E SozerAbstract:Abstract In this study, a thermocouple sensor system was used to monitor the Resin transfer molding (RTM) process. These sensors are low-cost and durable; and they do not disturb the Resin Flow. They can be used if the inlet Resin is either hotter or colder than the mold walls. In experiments of this study, much of the hot Resin’s internal energy was transferred to cold mold walls by conduction, when the mold parts were made of a material with high thermal conductivity, such as aluminum. A mathematical model based on 1D Flow and 2D unsteady energy conservation was developed to investigate the heat transfer between Resin and mold walls. The numerical solution of this model is in qualitative agreement with the results of our experiments. The thermocouple sensor system developed is more useful with the following process parameters: low thermal conductivity of mold material, high Resin Flow rate, high temperature difference between inlet Resin and initial mold walls, and high specific heat of Resin. However, for the typical use of RTM materials and typical injection parameters, thermocouples should not be preferred over other sensor types and should be used with caution due to the shortcomings investigated in this study.
Goker Tuncol - One of the best experts on this subject based on the ideXlab platform.
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constraints on monitoring Resin Flow in the Resin transfer molding rtm process by using thermocouple sensors
Composites Part A-applied Science and Manufacturing, 2007Co-Authors: Goker Tuncol, Murat Danisman, Alper Kaynar, Murat E SozerAbstract:Abstract In this study, a thermocouple sensor system was used to monitor the Resin transfer molding (RTM) process. These sensors are low-cost and durable; and they do not disturb the Resin Flow. They can be used if the inlet Resin is either hotter or colder than the mold walls. In experiments of this study, much of the hot Resin’s internal energy was transferred to cold mold walls by conduction, when the mold parts were made of a material with high thermal conductivity, such as aluminum. A mathematical model based on 1D Flow and 2D unsteady energy conservation was developed to investigate the heat transfer between Resin and mold walls. The numerical solution of this model is in qualitative agreement with the results of our experiments. The thermocouple sensor system developed is more useful with the following process parameters: low thermal conductivity of mold material, high Resin Flow rate, high temperature difference between inlet Resin and initial mold walls, and high specific heat of Resin. However, for the typical use of RTM materials and typical injection parameters, thermocouples should not be preferred over other sensor types and should be used with caution due to the shortcomings investigated in this study.
S.g. Advani - One of the best experts on this subject based on the ideXlab platform.
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Real-time sensing and control of Resin Flow in liquid injection molding processes
Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207), 1998Co-Authors: S. Parthasarathy, S.c. Mantell, K.a. Stelson, S. Bickerton, S.g. AdvaniAbstract:This paper presents results from an experimental investigation into real-time sensing and control of Resin Flow in an Resin transfer molding (RTM) process. The objective of the research was to develop intelligent process control methodologies using in-situ sensors and process models, for real-time control of the RTM process. The real time control of the RTM process enables an increase in throughput, high yields, low defects, and consistent repeatability of quality between the parts. We concentrated on controlling the Resin Flow using multiple injection ports and vent locations. The results from the preliminary investigations indicate the feasibility of implementing real-time control on the RTM production floor.
Ryosuke Matsuzaki - One of the best experts on this subject based on the ideXlab platform.
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three dimensional reconstruction of Resin Flow using capacitance sensor data assimilation during a liquid composite molding process a numerical study
Composites Part A-applied Science and Manufacturing, 2015Co-Authors: Masayuki Murata, Akira Todoroki, Ryosuke Matsuzaki, Yoshihiro Mizutani, Yoshiro SuzukiAbstract:Abstract Liquid composite molding (LCM) is a method to manufacture fiber-reinforced composites, where dry fabric reinforcement is impregnated with a Resin in a molding apparatus. However, the inherent process variability changes Resin Flow patterns during mold filling, which in turn may cause void formation. We propose a method to reconstruct three-dimensional Resin Flow in LCM, without embedding sensors into the composite structure. Capacitance measured from pairs of electrodes on molding tools and the stochastic simulation of Resin Flow during an LCM process are integrated by a sequential data assimilation method based on the ensemble Kalman filter; then, three-dimensional Resin Flow and permeability distribution are estimated simultaneously. The applicability of this method is investigated by numerical experiments, characterized by different spatial distributions of permeability. We confirmed that changes in Resin Flow caused by spatial permeability variations could be captured and the spatial distribution of permeability could be estimated by the proposed method.
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Resin Flow monitoring for VaRTM by an approach integrating electrical measurements and numerical simulation
Design Manufacturing and Applications of Composites, 2013Co-Authors: M. Murata, Akira Todoroki, Ryosuke Matsuzaki, Yasuhiro MizutaniAbstract:Vacuum assisted Resin Transfer Molding (VaRTM) is widely used for molding of composite structures. However, ensuring complete impregnation of the Resin into fiber materials is difficult and it sometimes causes the formation of un-impregnated regions, called dry spots. Due to the poor quality of a VaRTM process, its application is currently limited. Therefore, monitoring of the Resin Flow during the process is necessary to predict and prevent the formation of dry spots. This paper presents a method to observe Resin impregnation in a VaRTM process without embedding sensors into composite structures. Planar-shaped sensor electrodes arranged on a molding tool are used to measure electrical capacitance values from pairs of the electrodes. These measurements are combined with the numerical simulations of a VaRTM process to estimate the state of the Resin impregnation. This method is based on the ensemble Kalman filter (EnKF), known as a sequential data assimilation technique. The proposed method was examined by a numerical experiment. In the numerical experiment, the Resin-impregnated region and the permeability distribution of a fiber preform were estimated concurrently and it was confirmed that the decrease of Flow velocity in a low permeability region could be estimated.
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Full-field monitoring of Resin Flow using an area-sensor array in a VaRTM process
Composites Part A: Applied Science and Manufacturing, 2011Co-Authors: Ryosuke Matsuzaki, Akira Todoroki, Seiji Kobayashi, Yoshihiro MizutaniAbstract:Conventional Resin Flow monitoring relies on point measurements even if using grid sensing, and it is difficult to estimate an accurate Flow front or defect figuration. The current work investigates full-field monitoring of Resin Flow during a vacuum-assisted Resin transfer molding (VaRTM) process using an area-sensor array. The squared area sensors are aligned as a matrix on a thin polyimide film without any un-sensing space; thus the film measures the full-field Flow monitoring, and does not miss a dry spot that may occur anywhere on the film. To identify the precise Flow front and dry spots, the impregnated area is estimated by minimizing the residual sum of squares between the measured and estimated impregnated area ratios. To demonstrate the applicability of the proposed method, the area-sensor array is applied to monitoring a VaRTM Resin Flow on glass fiber reinforced plastic (GFRP) and foam-cored structures. As a result, the precise figurations of the Flow front and the dry spot were successfully estimated in real time.
Yoshihiro Mizutani - One of the best experts on this subject based on the ideXlab platform.
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three dimensional reconstruction of Resin Flow using capacitance sensor data assimilation during a liquid composite molding process a numerical study
Composites Part A-applied Science and Manufacturing, 2015Co-Authors: Masayuki Murata, Akira Todoroki, Ryosuke Matsuzaki, Yoshihiro Mizutani, Yoshiro SuzukiAbstract:Abstract Liquid composite molding (LCM) is a method to manufacture fiber-reinforced composites, where dry fabric reinforcement is impregnated with a Resin in a molding apparatus. However, the inherent process variability changes Resin Flow patterns during mold filling, which in turn may cause void formation. We propose a method to reconstruct three-dimensional Resin Flow in LCM, without embedding sensors into the composite structure. Capacitance measured from pairs of electrodes on molding tools and the stochastic simulation of Resin Flow during an LCM process are integrated by a sequential data assimilation method based on the ensemble Kalman filter; then, three-dimensional Resin Flow and permeability distribution are estimated simultaneously. The applicability of this method is investigated by numerical experiments, characterized by different spatial distributions of permeability. We confirmed that changes in Resin Flow caused by spatial permeability variations could be captured and the spatial distribution of permeability could be estimated by the proposed method.
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Full-field monitoring of Resin Flow using an area-sensor array in a VaRTM process
Composites Part A: Applied Science and Manufacturing, 2011Co-Authors: Ryosuke Matsuzaki, Akira Todoroki, Seiji Kobayashi, Yoshihiro MizutaniAbstract:Conventional Resin Flow monitoring relies on point measurements even if using grid sensing, and it is difficult to estimate an accurate Flow front or defect figuration. The current work investigates full-field monitoring of Resin Flow during a vacuum-assisted Resin transfer molding (VaRTM) process using an area-sensor array. The squared area sensors are aligned as a matrix on a thin polyimide film without any un-sensing space; thus the film measures the full-field Flow monitoring, and does not miss a dry spot that may occur anywhere on the film. To identify the precise Flow front and dry spots, the impregnated area is estimated by minimizing the residual sum of squares between the measured and estimated impregnated area ratios. To demonstrate the applicability of the proposed method, the area-sensor array is applied to monitoring a VaRTM Resin Flow on glass fiber reinforced plastic (GFRP) and foam-cored structures. As a result, the precise figurations of the Flow front and the dry spot were successfully estimated in real time.