Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show ...Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show that hydrogen addition advances ignition tim- ing and enhances peak pressure and temperature. A brief analysis of chemical kinetics of methane blending hydrogen is also performed in order to investigate the scope of its appli- cation, and the analysis suggests that OH radical plays an important role in the oxidation. Hydrogen addition increases NOx while decreasing HC and CO emissions. Exhaust gas recir- culation （EGR） also advances ignition timing; however, its effects on emissions are generally the opposite. By adjusting the hydrogen addition and EGR rate, the ignition timing can be regulated with a low emission level. Investigation into zones suggests that NOx is mostly formed in core zones while HC and CO mostly originate in the crevice and the quench layer.展开更多
The optimization of multi-zone residential heating,ventilation,and air conditioning(HVAC)control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads.Deep r...The optimization of multi-zone residential heating,ventilation,and air conditioning(HVAC)control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads.Deep reinforcement learning(DRL)methods have recently been proposed to address the HVAC control problem.However,the application of single-agent DRL formulti-zone residential HVAC controlmay lead to non-convergence or slow convergence.In this paper,we propose MAQMC(Multi-Agent deep Q-network for multi-zone residential HVAC Control)to address this challenge with the goal of minimizing energy consumption while maintaining occupants’thermal comfort.MAQMC is divided into MAQMC2(MAQMC with two agents:one agent controls the temperature of each zone,and the other agent controls the humidity of each zone)and MAQMC3(MAQMC with three agents:three agents control the temperature and humidity of three zones,respectively).The experimental results showthatMAQMC3 can reduce energy consumption by 6.27%andMAQMC2 by 3.73%compared with the fixed point;compared with the rule-based,MAQMC3 andMAQMC2 respectively can reduce 61.89%and 59.07%comfort violation.In addition,experiments with different regional weather data demonstrate that the well-trained MAQMC RL agents have the robustness and adaptability to unknown environments.展开更多
As buildings evolve to meet the challenges of energy efficiency and indoor comfort,phase change materials(PCM)emerge as a promising solution due to their ability to store and release latent heat.This paper explores th...As buildings evolve to meet the challenges of energy efficiency and indoor comfort,phase change materials(PCM)emerge as a promising solution due to their ability to store and release latent heat.This paper explores the transformative impact of incorporating PCMon the hygrothermal dynamics of multi-zone constructions.The study focuses on analyzing heat transfer,particularly through thermal conduction,in a wall containing PCM.A novel approach was proposed,wherein the studied system(sensitive balance)interacts directly with a latent balance to realistically define the behavior of specific humidity and mass flow rates.In addition,a numerical model implemented in MATLAB software has been developed to investigate the effect of integrating PCM on the hygrothermal balances inside the building.The obtained results indicate a consistent response in internal temperatures,specific humidity,and mass flow rates,with temperature differences ranging from 5℃to 13℃and a maximum phase shift of 13 h.In addition,the findings provided valuable insights into optimizing the design and performance of multi-zone constructions,offering a sustainable pathway for enhancing building resilience and occupant well-being.展开更多
In this paper,a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro poresecomplex fracture networks-wellbore durin...In this paper,a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro poresecomplex fracture networks-wellbore during the development of shale reservoirs by means of horizontal well fracturing.First,hydraulic fractures were induced by means of Brazilian splitting tests.Second,the forms of the hydraulic fractures inside the rock samples were observed by means of X-ray CT scanning to measure the opening of hydraulic fractures.Third,based on the multi-scale unified flowing model,morphological description of fractures and gas flowing mechanism in the matrixecomplex fracture networkewellbore,the productivity equation of single-stage horizontal well fracturing which includes diffusion,slipping and desorption was established.And fourthly,a productivity prediction model of horizontal well multi-stage fracturing in the shale reservoir was established considering the interference between the multi-stage fracturing zones and the pressure drop in the horizontal wellbore.The following results were obtained.First,hydraulic fractures are in the form of a complex network.Second,the measured opening of hydraulic fractures is in the range of 4.25-453 mm,averaging 112 mm.Third,shale gas flowing in different shapes of fracture networks follows different nonlinear flowing laws.Forth,as the fracture density in the strongly stimulated zones rises and the distribution range of the hydraulic fractures in strongly/weakly stimulated zones enlarges,gas production increases gradually.As the interference occurs in the flowing zones of fracture networks between fractured sections,the increasing amplitude of gas production rates decreases.Fifth,when the length of a simulated horizontal well is 1500 m and the half length of a fracture network in the strongly stimulated zone is 100 m,the productivity effect of stage 10 fracturing is the best.Therefore,it is necessary to control fracturing degree reasonably and optimize fracturing parameters,so as to provide a theoretical support for the optimization design of shale gas reservoir fracturing.展开更多
Heating,ventilation,and air conditioning(HVAC)systems consume a significant amount of energy to maintain thermal comfort and indoor air quality in buildings,which results in high operational costs.Reinforcement learni...Heating,ventilation,and air conditioning(HVAC)systems consume a significant amount of energy to maintain thermal comfort and indoor air quality in buildings,which results in high operational costs.Reinforcement learning is an effective method for controlling HVAC systems.However,in large and complex HVAC systems,traditional reinforcement learning algorithms often face the challenges of slow training speed and poor convergence performance.This paper proposes a multi-objective optimization control method based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,which aims to minimize HVAC energy consumption while ensuring optimal thermal comfort and indoor air quality in each zone.Using a multi-zone office building with fan coil units and a dedicated outdoor air system as a case study,we developed an EnergyPlus-Python co-simulation platform.The proposed control method was employed during both the heating and cooling seasons to independently control the temperature setpoints and fresh airflow in different zones of the office building.The simulation results from both the heating and cooling seasons demonstrate that the MADDPG control method exhibits faster convergence during training and excellent learning capabilities,allowing it to adapt effectively to changes in environmental conditions and implement appropriate control actions.Under similar indoor thermal comfort and air quality conditions,the MADDPG control method consumes less energy than the traditional reinforcement learning method,it saves 24.1%of energy during the heating season and 8.9%during the cooling season compared to the rule-based control method.Additionally,by adjusting the reward function in the MADDPG algorithm,it is possible to flexibly balance energy consumption,thermal comfort,and air quality preferences,demonstrating the algorithm’s strong applicability.展开更多
A finite element analysis(FEA)model is developed for the chemical-mechanical polishing(CMP)process on the basis of a 12-in five-zone polishing head.The proposed FEA model shows that the contact stress non-uniformity i...A finite element analysis(FEA)model is developed for the chemical-mechanical polishing(CMP)process on the basis of a 12-in five-zone polishing head.The proposed FEA model shows that the contact stress non-uniformity is less dependent on the material property of the membrane and the geometry of the retaining ring.The larger the elastic modulus of the pad,the larger contact stress non-uniformity of the wafer.The applied loads on retaining ring and zone of the polishing head significantly affect the contact stress distribution.The stress adjustment ability of a zone depends on its position.In particular,the inner-side zone has a high stress adjustment ability,whereas the outer-side zone has a low stress adjustment ability.The predicted results by the model are shown to be consistent with the experimental data.Analysis results have revealed some insights regarding the performance of the multi-zone CMP.展开更多
This research focuses on modeling a multi-zone circulating reactor(MZCR)in the polypropylene production process.In these reactors,designed for polyolefin production,small catalyst particles(20–300μm)initiate polymer...This research focuses on modeling a multi-zone circulating reactor(MZCR)in the polypropylene production process.In these reactors,designed for polyolefin production,small catalyst particles(20–300μm)initiate polymerization in the presence of monomer gas.The reactor consists of two main regions:the riser and the downer.The riser operates in the fast fluidization and the downer is in the moving bed regime.Employing the two-fluid model with the Eulerian-Eulerian approach,the dynamics of both solid and gas phases were modeled by applying Newton's laws of motion and assuming spherical particles.The population balance of particles within the reactor was also coupled with the equations of motion.The simultaneous solution of these equations provides valuable insights into particle and fluid behavior,revealing trends such as the growth of polymer particles.Furthermore,the impact of various operating conditions was explored.This study also examined the effects of design parameters(gas inlet velocity,average inlet diameter,and temperature)on the system performance.For instance,it was shown that in the case where the solid circulation flux is 30 kg/(m^(2) s)the velocity of particles in the bed increases from 0.4 at the inlet to 1.1 m/s in the fully developed zone,when it is 43 kg/(m^(2) s)the velocity of particles increases from 0.3 to 1.4 m/s,and when it is 55 kg/(m^(2) s),it is increased from 0.22 to 1.5 m/s.Additionally,trends in particle size distribution based on temperature adjustments were revealed.This study showed that higher temperatures accelerate the polymerization reaction rate,promoting faster growth kinetics and the formation of larger particles.展开更多
基金This work was supported by the Natural Science Foundation of Anhui Province （No.090412030）.
文摘Ignition timing control is of great importance in homogeneous charge compression ignition engines. The effect of hydrogen addition on methane combustion was investigated using a CHEMKIN multi-zone model. Results show that hydrogen addition advances ignition tim- ing and enhances peak pressure and temperature. A brief analysis of chemical kinetics of methane blending hydrogen is also performed in order to investigate the scope of its appli- cation, and the analysis suggests that OH radical plays an important role in the oxidation. Hydrogen addition increases NOx while decreasing HC and CO emissions. Exhaust gas recir- culation （EGR） also advances ignition timing; however, its effects on emissions are generally the opposite. By adjusting the hydrogen addition and EGR rate, the ignition timing can be regulated with a low emission level. Investigation into zones suggests that NOx is mostly formed in core zones while HC and CO mostly originate in the crevice and the quench layer.
基金supported by Primary Research and Development Plan of China(No.2020YFC2006602)National Natural Science Foundation of China(Nos.62072324,61876217,61876121,61772357)+2 种基金University Natural Science Foundation of Jiangsu Province(No.21KJA520005)Primary Research and Development Plan of Jiangsu Province(No.BE2020026)Natural Science Foundation of Jiangsu Province(No.BK20190942).
文摘The optimization of multi-zone residential heating,ventilation,and air conditioning(HVAC)control is not an easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads.Deep reinforcement learning(DRL)methods have recently been proposed to address the HVAC control problem.However,the application of single-agent DRL formulti-zone residential HVAC controlmay lead to non-convergence or slow convergence.In this paper,we propose MAQMC(Multi-Agent deep Q-network for multi-zone residential HVAC Control)to address this challenge with the goal of minimizing energy consumption while maintaining occupants’thermal comfort.MAQMC is divided into MAQMC2(MAQMC with two agents:one agent controls the temperature of each zone,and the other agent controls the humidity of each zone)and MAQMC3(MAQMC with three agents:three agents control the temperature and humidity of three zones,respectively).The experimental results showthatMAQMC3 can reduce energy consumption by 6.27%andMAQMC2 by 3.73%compared with the fixed point;compared with the rule-based,MAQMC3 andMAQMC2 respectively can reduce 61.89%and 59.07%comfort violation.In addition,experiments with different regional weather data demonstrate that the well-trained MAQMC RL agents have the robustness and adaptability to unknown environments.
基金supported in entire part by the Biomaterials and Transport Phenomena LaboratoryAgreementNo.30303-12-2003,at theUniversity of Medea.
文摘As buildings evolve to meet the challenges of energy efficiency and indoor comfort,phase change materials(PCM)emerge as a promising solution due to their ability to store and release latent heat.This paper explores the transformative impact of incorporating PCMon the hygrothermal dynamics of multi-zone constructions.The study focuses on analyzing heat transfer,particularly through thermal conduction,in a wall containing PCM.A novel approach was proposed,wherein the studied system(sensitive balance)interacts directly with a latent balance to realistically define the behavior of specific humidity and mass flow rates.In addition,a numerical model implemented in MATLAB software has been developed to investigate the effect of integrating PCM on the hygrothermal balances inside the building.The obtained results indicate a consistent response in internal temperatures,specific humidity,and mass flow rates,with temperature differences ranging from 5℃to 13℃and a maximum phase shift of 13 h.In addition,the findings provided valuable insights into optimizing the design and performance of multi-zone constructions,offering a sustainable pathway for enhancing building resilience and occupant well-being.
文摘In this paper,a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro poresecomplex fracture networks-wellbore during the development of shale reservoirs by means of horizontal well fracturing.First,hydraulic fractures were induced by means of Brazilian splitting tests.Second,the forms of the hydraulic fractures inside the rock samples were observed by means of X-ray CT scanning to measure the opening of hydraulic fractures.Third,based on the multi-scale unified flowing model,morphological description of fractures and gas flowing mechanism in the matrixecomplex fracture networkewellbore,the productivity equation of single-stage horizontal well fracturing which includes diffusion,slipping and desorption was established.And fourthly,a productivity prediction model of horizontal well multi-stage fracturing in the shale reservoir was established considering the interference between the multi-stage fracturing zones and the pressure drop in the horizontal wellbore.The following results were obtained.First,hydraulic fractures are in the form of a complex network.Second,the measured opening of hydraulic fractures is in the range of 4.25-453 mm,averaging 112 mm.Third,shale gas flowing in different shapes of fracture networks follows different nonlinear flowing laws.Forth,as the fracture density in the strongly stimulated zones rises and the distribution range of the hydraulic fractures in strongly/weakly stimulated zones enlarges,gas production increases gradually.As the interference occurs in the flowing zones of fracture networks between fractured sections,the increasing amplitude of gas production rates decreases.Fifth,when the length of a simulated horizontal well is 1500 m and the half length of a fracture network in the strongly stimulated zone is 100 m,the productivity effect of stage 10 fracturing is the best.Therefore,it is necessary to control fracturing degree reasonably and optimize fracturing parameters,so as to provide a theoretical support for the optimization design of shale gas reservoir fracturing.
基金this study was sponsored by the National Natural Science Foundation of China(Grant Number:52278103)the Natural Science Foundation-Departmental Joint Fund of Hunan Province,China(Grant Number:2023JJ60570).
文摘Heating,ventilation,and air conditioning(HVAC)systems consume a significant amount of energy to maintain thermal comfort and indoor air quality in buildings,which results in high operational costs.Reinforcement learning is an effective method for controlling HVAC systems.However,in large and complex HVAC systems,traditional reinforcement learning algorithms often face the challenges of slow training speed and poor convergence performance.This paper proposes a multi-objective optimization control method based on the multi-agent deep deterministic policy gradient(MADDPG)algorithm,which aims to minimize HVAC energy consumption while ensuring optimal thermal comfort and indoor air quality in each zone.Using a multi-zone office building with fan coil units and a dedicated outdoor air system as a case study,we developed an EnergyPlus-Python co-simulation platform.The proposed control method was employed during both the heating and cooling seasons to independently control the temperature setpoints and fresh airflow in different zones of the office building.The simulation results from both the heating and cooling seasons demonstrate that the MADDPG control method exhibits faster convergence during training and excellent learning capabilities,allowing it to adapt effectively to changes in environmental conditions and implement appropriate control actions.Under similar indoor thermal comfort and air quality conditions,the MADDPG control method consumes less energy than the traditional reinforcement learning method,it saves 24.1%of energy during the heating season and 8.9%during the cooling season compared to the rule-based control method.Additionally,by adjusting the reward function in the MADDPG algorithm,it is possible to flexibly balance energy consumption,thermal comfort,and air quality preferences,demonstrating the algorithm’s strong applicability.
基金supported by the Science Fund for Creative Research Groups (Grant No. 51021064)the National Natural Science Foundation of China (Grant No. 51205226)the China Postdoctoral Science Foundation (Grant No. 2012M510420)
文摘A finite element analysis(FEA)model is developed for the chemical-mechanical polishing(CMP)process on the basis of a 12-in five-zone polishing head.The proposed FEA model shows that the contact stress non-uniformity is less dependent on the material property of the membrane and the geometry of the retaining ring.The larger the elastic modulus of the pad,the larger contact stress non-uniformity of the wafer.The applied loads on retaining ring and zone of the polishing head significantly affect the contact stress distribution.The stress adjustment ability of a zone depends on its position.In particular,the inner-side zone has a high stress adjustment ability,whereas the outer-side zone has a low stress adjustment ability.The predicted results by the model are shown to be consistent with the experimental data.Analysis results have revealed some insights regarding the performance of the multi-zone CMP.
文摘This research focuses on modeling a multi-zone circulating reactor(MZCR)in the polypropylene production process.In these reactors,designed for polyolefin production,small catalyst particles(20–300μm)initiate polymerization in the presence of monomer gas.The reactor consists of two main regions:the riser and the downer.The riser operates in the fast fluidization and the downer is in the moving bed regime.Employing the two-fluid model with the Eulerian-Eulerian approach,the dynamics of both solid and gas phases were modeled by applying Newton's laws of motion and assuming spherical particles.The population balance of particles within the reactor was also coupled with the equations of motion.The simultaneous solution of these equations provides valuable insights into particle and fluid behavior,revealing trends such as the growth of polymer particles.Furthermore,the impact of various operating conditions was explored.This study also examined the effects of design parameters(gas inlet velocity,average inlet diameter,and temperature)on the system performance.For instance,it was shown that in the case where the solid circulation flux is 30 kg/(m^(2) s)the velocity of particles in the bed increases from 0.4 at the inlet to 1.1 m/s in the fully developed zone,when it is 43 kg/(m^(2) s)the velocity of particles increases from 0.3 to 1.4 m/s,and when it is 55 kg/(m^(2) s),it is increased from 0.22 to 1.5 m/s.Additionally,trends in particle size distribution based on temperature adjustments were revealed.This study showed that higher temperatures accelerate the polymerization reaction rate,promoting faster growth kinetics and the formation of larger particles.
