Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard ...Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.展开更多
The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity ...The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.展开更多
The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather...The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather-driven simulation of hourly power mismatches between generation and load, we explore the interplay between geographical resource complementarity and energy storage strategies. Solar and wind resources are considered at variable spatial scales across Europe and related to the Swiss load curve, which serve as a typical demand side reference. The optimal spatial distribution of renewable units is further assessed through a parameterized optimization method based on a genetic algorithm. It allows us to explore systematically the effective potential of combined integration strategies depending on the sizing of the system, with a focus on how overall performance is affected by the definition of network boundaries. Upper bounds on integration schemes are provided considering both renewable penetration and needed reserve power capacity. The quantitative trade-off between grid extension, storage and optimal wind-solar mix is highlighted.This paper also brings insights on how optimal geographical distribution of renewable units evolves as a function of renewable penetration and grid extent.展开更多
基金Supported by the National High Technology Research and Development Program of China(2014AA041803)the National Natural Science Foundation of China(61320106009)
文摘Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.
基金supported by the National Natural Science Foundation of China(Grant No.U2330208).
文摘The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.
文摘The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather-driven simulation of hourly power mismatches between generation and load, we explore the interplay between geographical resource complementarity and energy storage strategies. Solar and wind resources are considered at variable spatial scales across Europe and related to the Swiss load curve, which serve as a typical demand side reference. The optimal spatial distribution of renewable units is further assessed through a parameterized optimization method based on a genetic algorithm. It allows us to explore systematically the effective potential of combined integration strategies depending on the sizing of the system, with a focus on how overall performance is affected by the definition of network boundaries. Upper bounds on integration schemes are provided considering both renewable penetration and needed reserve power capacity. The quantitative trade-off between grid extension, storage and optimal wind-solar mix is highlighted.This paper also brings insights on how optimal geographical distribution of renewable units evolves as a function of renewable penetration and grid extent.
