Saline aquifers are the most popular waste and CO_(2)injection and storage reservoirs worldwide.This project proposes that several optimal injection positions should be investigated as hydraulic pressure-focused posit...Saline aquifers are the most popular waste and CO_(2)injection and storage reservoirs worldwide.This project proposes that several optimal injection positions should be investigated as hydraulic pressure-focused positions,in order to relieve the high demands of pump performance.The comprehensive indices(F_(i))representing the injectivity of different burial depths were obtained by using information entropy,based on the mercury injection experimental data of 13 rock samples.The results demonstrated that the burial depths of No.4,No.1 and No.2 in the Liujiagou Formation were the most suitable positions for hydraulic focused injection,which means the upper 30 m thickness could be regarded as the hydraulic focused range in the saline aquifer with an average thickness of 400 m.In addition,some laboratory experiments and in situ tests were carried out for the purpose of certifying and analyzing results,including SEM,XRD,brittleness index and logging.The results suggested that the rock samples at the No.4,No.1 and No.2 burial depth ranges have loose microstructure,weak cementation,as well as dual pores and fractures.The lithology is mainly quartz and feldspar,but the clay mineral content is high(10%-25%),which is positive for dissolution.The lithology is suitable for hydraulic fracturing to form extended cracks and micro-fissures during high-TDS(total dissolved solids)mine water injection,because of the high brittleness index.Finally,a theoretical and technical framework for high-TDS mine water injection was established,based on operating pilot engineering.Some theoretical defects and drawbacks learned from the field practices were summarized and solutions proposed.The research in this study could provide guidance and a paradigm for the inexpensive treatment of high-TDS mine water by injection and storage.展开更多
With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order ...With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.展开更多
Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to ...Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.展开更多
基金supported by the National Key Research and Development Program of China(No.2023YFC3012103 and No.2019YFC1805400)the National Science Foundation of Jiangsu Province,China(No.BK20210524)+1 种基金the National Natural Science Foundation of China(No.42202268 and No.42172272)the Fundamental Research Funds for the Central Universities,China(No.2020ZDPY0201)。
文摘Saline aquifers are the most popular waste and CO_(2)injection and storage reservoirs worldwide.This project proposes that several optimal injection positions should be investigated as hydraulic pressure-focused positions,in order to relieve the high demands of pump performance.The comprehensive indices(F_(i))representing the injectivity of different burial depths were obtained by using information entropy,based on the mercury injection experimental data of 13 rock samples.The results demonstrated that the burial depths of No.4,No.1 and No.2 in the Liujiagou Formation were the most suitable positions for hydraulic focused injection,which means the upper 30 m thickness could be regarded as the hydraulic focused range in the saline aquifer with an average thickness of 400 m.In addition,some laboratory experiments and in situ tests were carried out for the purpose of certifying and analyzing results,including SEM,XRD,brittleness index and logging.The results suggested that the rock samples at the No.4,No.1 and No.2 burial depth ranges have loose microstructure,weak cementation,as well as dual pores and fractures.The lithology is mainly quartz and feldspar,but the clay mineral content is high(10%-25%),which is positive for dissolution.The lithology is suitable for hydraulic fracturing to form extended cracks and micro-fissures during high-TDS(total dissolved solids)mine water injection,because of the high brittleness index.Finally,a theoretical and technical framework for high-TDS mine water injection was established,based on operating pilot engineering.Some theoretical defects and drawbacks learned from the field practices were summarized and solutions proposed.The research in this study could provide guidance and a paradigm for the inexpensive treatment of high-TDS mine water by injection and storage.
文摘With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.
文摘Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.
