The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
Martin Guay - One of the best experts on this subject based on the ideXlab platform.
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Proportional-integral extremum seeking for vapor compression systems
2016 American Control Conference (ACC), 2016Co-Authors: Daniel J. Burns, Christopher R. Laughman, Martin GuayAbstract:In this paper, we optimize vapor compression system power consumption through the application of a newly-developed proportional-integral extremum seeking controller (PI-ESC) that converges at the same timescale as the process. This method modifies the control law to include terms proportional to the estimated gradient, but this modification of the control law requires a more sophisticated gradient estimator in order to avoid bias. We develop a PI-ESC for which this bias is eliminated. PI-ESC is applied to the problem of Compressor Discharge temperature setpoint selection for a vapor compression system where setpoints are automatically determined so that power consumption is minimized. The vapor compression system operates with a regulating feedback controller configured to drive the Compressor Discharge temperature to setpoints selected by the PI-ESC, and we use a physics-based simulation model to demonstrate that power consumption is minimized dramatically faster than by traditional perturbation-based methods.
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ACC - Proportional-integral extremum seeking for vapor compression systems
2016 American Control Conference (ACC), 2016Co-Authors: Daniel J. Burns, Christopher R. Laughman, Martin GuayAbstract:In this paper, we optimize vapor compression system power consumption through the application of a newly-developed proportional-integral extremum seeking controller (PI-ESC) that converges at the same timescale as the process. This method modifies the control law to include terms proportional to the estimated gradient, but this modification of the control law requires a more sophisticated gradient estimator in order to avoid bias. We develop a PI-ESC for which this bias is eliminated. PI-ESC is applied to the problem of Compressor Discharge temperature setpoint selection for a vapor compression system where setpoints are automatically determined so that power consumption is minimized. The vapor compression system operates with a regulating feedback controller configured to drive the Compressor Discharge temperature to setpoints selected by the PI-ESC, and we use a physics-based simulation model to demonstrate that power consumption is minimized dramatically faster than by traditional perturbation-based methods.
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Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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ACC - Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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Realtime Optimization of MPC Setpoints using Time-Varying Extremum Seeking Control for Vapor Compression Machines
2014Co-Authors: Walter K. Weiss, Daniel J. Burns, Martin GuayAbstract:Recently, model predictive control (MPC) has received increased attention in the HVAC community, largely due to its ability to systematically manage constraints while optimally regulating signals of interest to setpoints. For example, in a common formulation of an MPC control problem for variable Compressor speed vapor compression machines, the setpoints often include the zone temperature and the evaporator superheat temperature. However, the energy consumption of vapor compression systems has been shown to be sensitive to these setpoints. Further, while superheat temperature is often preferred because it can be easily correlated to heat exchanger efficiency (and therefore cycle efficiency), direct measurement of superheat is not always available. Therefore, identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts setpoints provided to a model predictive controller. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates—a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using an MPC controller with setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Further, because the required cooling capacity (and therefore Compressor speed) is a function of measured and unmeasured disturbances, the optimal Compressor Discharge temperature setpoint must vary according to these conditions. We show that the energy optimal Discharge temperature is tracked with the time-varying extremum seeking algorithm in the presence of disturbances.
Daniel J. Burns - One of the best experts on this subject based on the ideXlab platform.
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Proportional-integral extremum seeking for vapor compression systems
2016 American Control Conference (ACC), 2016Co-Authors: Daniel J. Burns, Christopher R. Laughman, Martin GuayAbstract:In this paper, we optimize vapor compression system power consumption through the application of a newly-developed proportional-integral extremum seeking controller (PI-ESC) that converges at the same timescale as the process. This method modifies the control law to include terms proportional to the estimated gradient, but this modification of the control law requires a more sophisticated gradient estimator in order to avoid bias. We develop a PI-ESC for which this bias is eliminated. PI-ESC is applied to the problem of Compressor Discharge temperature setpoint selection for a vapor compression system where setpoints are automatically determined so that power consumption is minimized. The vapor compression system operates with a regulating feedback controller configured to drive the Compressor Discharge temperature to setpoints selected by the PI-ESC, and we use a physics-based simulation model to demonstrate that power consumption is minimized dramatically faster than by traditional perturbation-based methods.
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ACC - Proportional-integral extremum seeking for vapor compression systems
2016 American Control Conference (ACC), 2016Co-Authors: Daniel J. Burns, Christopher R. Laughman, Martin GuayAbstract:In this paper, we optimize vapor compression system power consumption through the application of a newly-developed proportional-integral extremum seeking controller (PI-ESC) that converges at the same timescale as the process. This method modifies the control law to include terms proportional to the estimated gradient, but this modification of the control law requires a more sophisticated gradient estimator in order to avoid bias. We develop a PI-ESC for which this bias is eliminated. PI-ESC is applied to the problem of Compressor Discharge temperature setpoint selection for a vapor compression system where setpoints are automatically determined so that power consumption is minimized. The vapor compression system operates with a regulating feedback controller configured to drive the Compressor Discharge temperature to setpoints selected by the PI-ESC, and we use a physics-based simulation model to demonstrate that power consumption is minimized dramatically faster than by traditional perturbation-based methods.
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Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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ACC - Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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Realtime Optimization of MPC Setpoints using Time-Varying Extremum Seeking Control for Vapor Compression Machines
2014Co-Authors: Walter K. Weiss, Daniel J. Burns, Martin GuayAbstract:Recently, model predictive control (MPC) has received increased attention in the HVAC community, largely due to its ability to systematically manage constraints while optimally regulating signals of interest to setpoints. For example, in a common formulation of an MPC control problem for variable Compressor speed vapor compression machines, the setpoints often include the zone temperature and the evaporator superheat temperature. However, the energy consumption of vapor compression systems has been shown to be sensitive to these setpoints. Further, while superheat temperature is often preferred because it can be easily correlated to heat exchanger efficiency (and therefore cycle efficiency), direct measurement of superheat is not always available. Therefore, identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts setpoints provided to a model predictive controller. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates—a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using an MPC controller with setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Further, because the required cooling capacity (and therefore Compressor speed) is a function of measured and unmeasured disturbances, the optimal Compressor Discharge temperature setpoint must vary according to these conditions. We show that the energy optimal Discharge temperature is tracked with the time-varying extremum seeking algorithm in the presence of disturbances.
Walter K. Weiss - One of the best experts on this subject based on the ideXlab platform.
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Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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ACC - Realtime setpoint optimization with time-varying extremum seeking for vapor compression systems
2015 American Control Conference (ACC), 2015Co-Authors: Daniel J. Burns, Walter K. Weiss, Martin GuayAbstract:In many formulations of controller architectures for variable-speed vapor compression machines, evaporator superheat temperature is commonly selected as a regulated variable due to its correlation with cycle efficiency. Further, the superheat temperature setpoint is conveniently taken as a constant value over the wide range of operating conditions. However, direct measurement of superheat is not always available, and estimates of superheat have limited robustness. Therefore identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts Compressor Discharge temperature setpoints in order to optimize energy efficiency. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates-a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Experiments are performed demonstrating Discharge temperature optimization from 72°C to 62°C for a particular set of experimental conditions where the power consumption is decreased from 525 W to 450 W, resulting in an increase in observed coefficient of performance (COP) of 14%.
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Realtime Optimization of MPC Setpoints using Time-Varying Extremum Seeking Control for Vapor Compression Machines
2014Co-Authors: Walter K. Weiss, Daniel J. Burns, Martin GuayAbstract:Recently, model predictive control (MPC) has received increased attention in the HVAC community, largely due to its ability to systematically manage constraints while optimally regulating signals of interest to setpoints. For example, in a common formulation of an MPC control problem for variable Compressor speed vapor compression machines, the setpoints often include the zone temperature and the evaporator superheat temperature. However, the energy consumption of vapor compression systems has been shown to be sensitive to these setpoints. Further, while superheat temperature is often preferred because it can be easily correlated to heat exchanger efficiency (and therefore cycle efficiency), direct measurement of superheat is not always available. Therefore, identifying alternate signals in the control of vapor compression machines that correlate to efficiency is desired. In this paper, we consider a model-free extremum seeking algorithm that adjusts setpoints provided to a model predictive controller. While perturbation-based extremum seeking methods have been known for some time, they suffer from slow convergence rates—a problem emphasized in application by the long time constants associated with thermal systems. Our method uses a new algorithm (time-varying extremum seeking), which has dramatically faster and more reliable convergence properties. In particular, we regulate the Compressor Discharge temperature using an MPC controller with setpoints selected from a model-free time-varying extremum seeking algorithm. We show that the relationship between Compressor Discharge temperature and power consumption is convex (a requirement for this class of realtime optimization), and use time-varying extremum seeking to drive these setpoints to values that minimize power. The results are compared to the traditional perturbation-based extremum seeking approach. Further, because the required cooling capacity (and therefore Compressor speed) is a function of measured and unmeasured disturbances, the optimal Compressor Discharge temperature setpoint must vary according to these conditions. We show that the energy optimal Discharge temperature is tracked with the time-varying extremum seeking algorithm in the presence of disturbances.
Predrag Stojan Hrnjak - One of the best experts on this subject based on the ideXlab platform.
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characteristics of oil annular mist flow in the Compressor Discharge pipe
International Journal of Refrigeration-revue Internationale Du Froid, 2019Co-Authors: Jiu Xu, Predrag Stojan HrnjakAbstract:Abstract Oil is essential to the Compressor, but oil brings side effects on the heat exchanger performance. It is preferred to reduce the amount of oil circulating in the system and retain the oil in the Compressor for both reliability and efficiency reasons. Oil leaves the compression chamber in the form of mist. Oil droplets are propelled by refrigerant vapor flow and form a developing annular-mist flow in the Discharge pipe, as droplets gradually attach to the inner wall. In this paper, a video-based method to quantify the oil flow in the Compressor Discharge pipe is presented. Oil droplet size, oil droplet velocity, oil film thickness, and oil film wave velocity are measured at different mass flow rates and Compressor speed. The measurements show a variety of oil flow parameters as functions of distance along the Discharge pipe. The impact of system flow rate, Compressor type, and oil properties are also discussed. The characteristics of oil Discharged by the Compressor provide essential information for oil separator design and optimization. The research approach also has the potential to be applied in other multiphase studies.
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Flow visualization and CFD simulation of impinging oil separator for Compressors.
2018Co-Authors: Jiu Xu, Predrag Stojan HrnjakAbstract:Oil is needed for most of the Compressors in HVAC industry but oil circulating in the system is unfavorable for the heat exchanger performance and cycle efficiency. A common solution for the oil issue is separating oil at the Compressor Discharge and returning it back to the Compressor. For compactness, oil separation structure integrated into the Compressor is more and more popular than traditional external oil separator. Therefore, analytical tools and design guidelines of oil separation structure is important, especially for irregular geometry and realistic flow condition at the Compressor Discharge. As one of the major mechanisms of droplet separation, impinging separation mechanism is studied by flow visualization and CFD simulation in this paper. The video of oil mist flowing through the baffles and plates is captured by a high-speed camera and analyzed quantitatively. CFD simulation is carried out for investigating the flow field and performance of impinging separator. Refrigerant vapor is calculated in the first step and discrete phase model is used to track the droplet movement in the second step. Droplet size distribution and overall separation efficiency are used to validate the CFD simulation results. Both flow visualization and CFD simulation provide useful tools for oil separator design. The results and conclusions from this study give useful guidelines about how to reduce the oil circulation ratio by designing better oil separator for the Compressor.
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oil flow at the scroll Compressor Discharge visualization and cfd simulation
IOP Conference Series: Materials Science and Engineering, 2017Co-Authors: Jiu Xu, Predrag Stojan HrnjakAbstract:Oil is important to the Compressor but has other side effect on the refrigeration system performance. Discharge valves located in the Compressor plenum are the gateway for the oil when leaving the Compressor and circulate in the system. The space in between: the Compressor Discharge plenum has the potential to separate the oil mist and reduce the oil circulation ratio (OCR) in the system. In order to provide information for building incorporated separation feature for the oil flow near the Compressor Discharge, video processing method is used to quantify the oil droplets movement and distribution. Also, CFD discrete phase model gives the numerical approach to study the oil flow inside Compressor plenum. Oil droplet size distributions are given by visualization and simulation and the results show a good agreement. The mass balance and spatial distribution are also discussed and compared with experimental results. The verification shows that discrete phase model has the potential to simulate the oil droplet flow inside the Compressor.
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quantification of flow and retention of oil in Compressor Discharge pipe
International Journal of Refrigeration-revue Internationale Du Froid, 2017Co-Authors: Jiu Xu, Predrag Stojan HrnjakAbstract:This paper presents a new method to measure the oil retention and oil circulation ratio (OCR) in the Compressor Discharge pipe based on oil film thickness, oil film average velocity, oil droplet size, oil droplet velocity, and system mass flow rate. Oil flow parameters are quantified based on visualization using high-speed camera and video processing techniques. The estimated oil retention and oil circulation ratio results are compared quantitatively with the results from sampling measurements under different Compressor speed and Compressor types. The agreement between video results and sampling measurements verify the accuracy of this innovative method, which can also be applied in other annular-mist flow analysis. It also shows that most of the oil exists in film by mass while oil droplets contributes more to the oil mass flow rate because oil droplets travel in a much higher speed.
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Oil flow at the scroll Compressor Discharge: Visualization and CFD simulation
IOP Conference Series: Materials Science and Engineering, 2017Co-Authors: Jiu Xu, Predrag Stojan HrnjakAbstract:© Published under licence by IOP Publishing Ltd. Oil is important to the Compressor but has other side effect on the refrigeration system performance. Discharge valves located in the Compressor plenum are the gateway for the oil when leaving the Compressor and circulate in the system. The space in between: the Compressor Discharge plenum has the potential to separate the oil mist and reduce the oil circulation ratio (OCR) in the system. In order to provide information for building incorporated separation feature for the oil flow near the Compressor Discharge, video processing method is used to quantify the oil droplets movement and distribution. Also, CFD discrete phase model gives the numerical approach to study the oil flow inside Compressor plenum. Oil droplet size distributions are given by visualization and simulation and the results show a good agreement. The mass balance and spatial distribution are also discussed and compared with experimental results. The verification shows that discrete phase model has the potential to simulate the oil droplet flow inside the Compressor.
Yongchan Kim - One of the best experts on this subject based on the ideXlab platform.
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Numerical study on the optimal design of injection-hole geometries of a twin rotary Compressor in a liquid injection heat pump
Applied Thermal Engineering, 2017Co-Authors: Yongseok Jeon, Sang Hun Lee, Wonuk Kim, Jongho Jung, Yongchan KimAbstract:In a liquid injection heat pump, it is very essential to control the Compressor Discharge temperature without wet-compression problems at extreme outdoor conditions. The objective of this study was to optimize the injection-hole geometries of a liquid injection heat pump in order to prevent the risk of wet-compression while reducing Compressor Discharge temperature at overload cooling conditions. In this study, a simulation model for predicting the performance of a liquid injection heat pump was developed and validated. The optimum injection-hole geometries were determined to obtain the maximum multiplication ratio, which led to a lower instant injection mass flow rate in terms of R- and θ-directional positions. In addition, the injection-hole diameter was minimized to prevent wet-compression while obtaining the target injection mass flow rate. The Discharge temperature of the optimized Compressor was decreased by 9.2 °C over the baseline Compressor while maintaining the same risk for wet-compression at the overload cooling test condition.
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Cooling performance of a variable speed CO2cycle with an electronic expansion valve and internal heat exchanger
International Journal of Refrigeration, 2007Co-Authors: Honghyun Cho, Changgi Ryu, Yongchan KimAbstract:The cooling performance of a CO2cycle must be improved to develop a competitive air-conditioning system with the conventional air-conditioners using HFCs. In this study, the cooling performance of a variable speed CO2cycle was measured and analyzed by varying the refrigerant charge amount, Compressor frequency, EEV opening, and length of an internal heat exchanger (IHX). The basic CO2system without the IHX showed the maximum cooling COP of 2.1 at the Compressor Discharge pressure of 9.2 MPa and the optimum normalized charge of 0.282. The cooling COP decreased with the increase of Compressor frequency at all normalized charges. The optimum EEV opening increased with Compressor frequency. Simultaneous control of EEV opening and Compressor frequency allowed optimum control of the Compressor Discharge pressure. The optimal Compressor Discharge pressure of the modified CO2cycle with the IHX was reduced by 0.5 MPa. The IHX increased the cooling capacity and COP of the CO2cycle by 6.2-11.9% and 7.1-9.1%, respectively, at the tested Compressor frequencies from 40 to 60 Hz. © 2006 Elsevier Ltd and IIR.