Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key p...Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key process causing severe weather,but its activities on the monsoon coast are less understood because of the lack of fine-resolution datasets.For the first time,we present the climatology of UCG on a typical monsoon coast using kilometer-mesh radar data from southern China.The UCG undergoes pronounced subseasonal and diurnal variations in the early-summer rainy season.The subseasonal UCG increase is attributed to the onshore flows shifting from easterlies in April to monsoon southwesterlies in June.UCG becomes vigorous following summer monsoon onset,with hotspots near windward coastal mountains.Daytime UCG first peaks near noontime along coastal land,where onshore flows are destabilized by boundary-layer heating and mountains.Afternoon inland peaks and off-coast minimums are recognized due to land–sea thermal contrast and sea-breeze circulation.Nighttime UCG is revived at the coast by nocturnally enhanced southerlies,followed by offshore activity as the convergence of land-breeze northerlies shifts seaward.The UCG thus responds strongly to changing atmospheric conditions,land heating/cooling,and thermally driven local circulations.Our results may help clarify the predictability of monsoon coastal convection.展开更多
Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durabil...Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durability are indispensable steps for industrial application but have been scarcely reported thus far.Here,we report a ZrO_(2)/Al_(2)O_(3) pack catalyst that possesses strong metal oxide-support interactions,a porous structure,active and stable Zr-O-Al coordination,promoted proton transfer and a 40.7% decrease in the energy activation of carbamate decomposition,which significantly accelerates CO_(2) desorption kinetics.The upscale experiment and cost evaluation based on industrial flue gas revealed that the use of packing catalysts can reduce energy consumption by 27.56% and optimize the overall cost by 10.49%.The active sites present excellent stability in alkaline solvents.This work is the first to investigate the ability of high-technology readiness(technology readiness level at 6(TRL 6))for catalytic aminesolvent regeneration,providing valuable insights for potential applications involving efficient CO_(2) capture with catalyst assistance.展开更多
Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented...Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.展开更多
While redox flow batteries carry a large potential for electricity storage,specifically for regenerative energies,the current technology-prone system-the all-vanadium redox flow battery-exhibits two major disadvantage...While redox flow batteries carry a large potential for electricity storage,specifically for regenerative energies,the current technology-prone system-the all-vanadium redox flow battery-exhibits two major disadvantages:low energy and low power densities.Polyoxometalates have the potential to mitigate both effects.In this publication,the operation of a polyoxometalate redox flow battery was demonstrated for the polyoxoanions[SiW_(12)O_(40)]^(4-)(SiW_(12))in the anolyte and[PV_(14)O_(42)]^(9-)(PV14)in the catholyte.Emphasis was laid on comparing to which extent an upscale from 25 to 1400 cm^(2) membrane area may impede efficiency and operational parameters.Results demonstrated that the operation of the large cell for close to 3 months did not diminish operation and the stability of polyoxometalates was unaltered.展开更多
Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computati...Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computationally expensive and time-consuming.Upscaling methods are commonly used to coarsen the fine-scale geological model,with global flow-based upscaling methods generally demonstrating the highest accuracy.However,since these methods require solving flow equations over the global domain,which is still time-consuming,their applications are typically limited to cases where the coarse model is reused repeatedly(e.g.,history matching or optimization).To overcome these limitations,this study develops a novel deep learning(DL)-based upscaling framework for the simulation of CO_(2)injection into saline aquifers.The framework incorporates convolutional neural networks(CNNs),Transformer encoders,and Fourier neural operators(FNOs)to construct surrogate models for upscaled well index,permeability,relative permeability,and capillary pressure.A preprocessing procedure is first applied to address the issue of inaccurate upscaled parameters,which are typically caused by weak flow conditions in traditional upscaling computations.Then the surrogate models are trained using relevant local information,and the trained surrogate models are used to replace traditional numerical upscaling computations,enabling instantaneous and parallel predictions of upscaled parameters.Two representative flow patterns(left-to-right and bottom-to-top)are considered to evaluate the framework's performance.The results demonstrate that the DL-based framework significantly improves computational efficiency,achieving a speedup factor of approximately 1133 times compared to traditional upscaling methods.Additionally,it maintains or even enhances simulation accuracy,as the surrogate models correct inaccurate upscaled parameters.展开更多
One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification ...One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification problem for second-order tensor data. Traditional vector-based one-class classification methods such as one-class support vector machine (OCSVM) and least squares one-class support vector machine (LSOCSVM) have limitations when tensor is used as input data, so we propose a new tensor one-class classification method, LSOCSTM, which directly uses tensor as input data. On one hand, using tensor as input data not only enables to classify tensor data, but also for vector data, classifying it after high dimensionalizing it into tensor still improves the classification accuracy and overcomes the over-fitting problem. On the other hand, different from one-class support tensor machine (OCSTM), we use squared loss instead of the original loss function so that we solve a series of linear equations instead of quadratic programming problems. Therefore, we use the distance to the hyperplane as a metric for classification, and the proposed method is more accurate and faster compared to existing methods. The experimental results show the high efficiency of the proposed method compared with several state-of-the-art methods.展开更多
Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representat...Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representative samples for conventional macroscale rock mechanics experiments(macro-RMEs).This critical review discusses recent advances in microscale RMEs(micro-RMEs)techniques and the upscaling methods for extracting mechanical parameters.Methods of mineralogical and microstructural analyses,along with non-destructive mechanical techniques,have provided new opportunities for studying planetary rocks with unprecedented precision and capabilities.First,we summarize several mainstream methods for obtaining the mineralogy and microstructure of planetary rocks.Then,nondestructive micromechanical testing methods,nanoindentation and atomic force microscopy(AFM),are detailed reviewed,illustrating the principles,advantages,influencing factors,and available testing results from literature.Subsequently,several feasible upscaling methods that bridge the micro-measurements of meteorite pieces to the strength of the intact body are introduced.Finally,the potential applications of planetary rock mechanics research to guiding the design and execution of space missions are environed,ranging from sample return missions and planetary defense to extraterrestrial construction.These discussions are expected to broaden the understanding of the microscale mechanical properties of planetary rocks and their significant role in deep space exploration.展开更多
Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and e...Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.展开更多
There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the...There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the impact of the sampling strategy on model accuracy still need to be resolved.In this study,we first corrected the bias arising from upscaling the LG-AGB map to match the spatial resolution of Landsat observations.Subsequently,the stratified random sampling method was used to select training samples from the corrected LG-AGB map(cLG-AGB)for the Random Forest(RF)regression model.The RF model features were extracted from the Landsat observations and auxiliary data.The impact of strata numbers on model accuracy was explored during the sampling process.Finally,independent validation was conducted using in situ measurements.The results indicated that:(1)about 68% of the biases can be corrected in the up-scale transformation;(2)compared to no stratification,a three-strata model achieved a 6.5% improvement in AGB estimation accuracy while requiring a 37.8% reduction in sample size;(3)the black locust forest had a low saturation point at 60.52±4.46 Mg/ha AGB and 72.4%AGB values were underestimated and the remaining were overestimated.In summary,our study provides a framework to harmonize near-surface LiDAR and satellite data for AGB estimation in plantation forest ecosystems with small patch sizes and fragmented distribution.展开更多
Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.I...Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.In addition,since ground terminals have various resolutions and real-time playing requirements,it is essential to achieve arbitrary scale super-resolution(SR)of satellite images.In this paper,we propose an arbitrary scale SR network for satellite image reconstruction.First,we propose an arbitrary upscale module for satellite imagery that can map low-resolution satellite image features to arbitrary scale enlarged SR outputs.Second,we design an edge reinforcement module to enhance the highfrequency details in satellite images through a twobranch network.Finally,extensive upsample experiments on WHU-RS19 and NWPU-RESISC45 datasets and subsequent image segmentation experiments both show the superiority of our method over the counterparts.展开更多
A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model exten...A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.展开更多
The Original Belonio Rice Husk Gasifier (OBRHG), initially of height of 0.6 m, diameter of 0.15 m and thickness of 0.025 m was tested for biochar production through air gasification of rice husk (RH) and the design wa...The Original Belonio Rice Husk Gasifier (OBRHG), initially of height of 0.6 m, diameter of 0.15 m and thickness of 0.025 m was tested for biochar production through air gasification of rice husk (RH) and the design was upscaled to height of 1.65 m, diameter of 0.85 m and thickness of 0.16 m. A total of 27 experiments were conducted to monitor the gasifier performance and the system can operate with the centrifugal blower operating at a power input of 155 W and a maximum flow rate of 1450 m3/hr regulated according to the air requirement. Building the UBRHG is simple and inexpensive to fabricate and with the fairly satisfactory performance and ease of construction along with the convenience of operation, the UBRHG with RH as feed would find abundant avenues of applications in a rural setting for biochar production alongside thermal, mechanical and electrical energy delivery.展开更多
Based on the characteristics of fractures in naturally fractured reservoir and a discrete-fracture model, a fracture network numerical well test model is developed. Bottom hole pressure response curves and the pressur...Based on the characteristics of fractures in naturally fractured reservoir and a discrete-fracture model, a fracture network numerical well test model is developed. Bottom hole pressure response curves and the pressure field are obtained by solving the model equations with the finite-element method. By analyzing bottom hole pressure curves and the fluid flow in the pressure field, seven flow stages can be recognized on the curves. An upscaling method is developed to compare with the dual-porosity model （DPM）. The comparisons results show that the DPM overestimates the inter-porosity coefficient ）, and the storage factor w. The analysis results show that fracture conductivity plays a leading role in the fluid flow. Matrix permeability influences the beginning time of flow from the matrix to fractures. Fractures density is another important parameter controlling the flow. The fracture linear flow is hidden under the large fracture density. The pressure propagation is slower in the direction of larger fracture density.展开更多
One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show...One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show that geochemistry, especially mineralization, plays an important role in rendering the faults as conduits for CO_2 movement while others show that mineralization due to CO_2 injection can result in seep migration and flow diversion. Therefore, understanding the changes in reservoir properties due to pore alterations is important to ensure safe long term CO_2 storage in the subsurface. We study the changes in the Representative Elementary Volume（REV） of a rock due to reactive kinetics over a time, using a statistical approach and pore-scale CO_2-rock interactiondata.The goal of this study is to obtain the REV of a rock property that accounts for pore-scale changes over time due to reactive kinetics, and we call this as spatiotemporal REV. Scale-up results suggest that the REV changes with time when CO_2-rock interaction is considered. It is hypothesized that the alteration in pore structure introduces more heterogeneity in the rock, and because of this the magnitude of REV increases. It is possible that these noticeable changes in REV at pore-scale may have an impact when analyzed at the reservoir scale.展开更多
Traditional electrode manufacturing for lithium-ion batteries is well established,reliable,and has already reached high processing speeds and improvements in production costs.For modern electric vehicles,however,the n...Traditional electrode manufacturing for lithium-ion batteries is well established,reliable,and has already reached high processing speeds and improvements in production costs.For modern electric vehicles,however,the need for batteries with high gravimetric and volumetric energy densities at cell level is increasing;and new production concepts are required for this purpose.During the last decade,laser processing of battery materials emerged as a promising processing tool for either improving manufacturing flexibility and product reliability or enhancing battery performances.Laser cutting and welding already reached a high level of maturity and it is obvious that in the near future they will become frequently implemented in battery production lines.This review focuses on laser texturing of electrode materials due to its high potential for significantly enhancing battery performances beyond state-of-the-art.Technical approaches and processing strategies for new electrode architectures and concepts will be presented and discussed with regard to energy and power density requirements.The boost of electrochemical performances due to laser texturing of energy storage materials is currently proven at the laboratory scale.However,promising developments in high-power,ultrafast laser technology may push laser structuring of batteries to the next technical readiness level soon.For demonstration in pilot lines adapted to future cell production,process upscaling regarding footprint area and processing speed are the main issues as well as the economic aspects with regards to CapEx amortization and the benefits resulting from the next generation battery.This review begins with an introduction of the three-dimensional battery and thick film concept,made possible by laser texturing.Laser processing of electrode components,namely current collectors,anodes,and cathodes will be presented.Different types of electrode architectures,such as holes,grids,and lines,were generated;their impact on battery performances are illustrated.The usage of high-energy materials,which are on the threshold of commercialization,is highlighted.Battery performance increase is triggered by controlling lithium-ion diffusion kinetics in liquid electrolyte filled porous electrodes.This review concludes with a discussion of various laser parameter tasks for process upscaling in a new type of extreme manufacturing.展开更多
To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions...To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.展开更多
Simulation of fluid flow in the fractured porous media is very important and challenging.Researchers have developed some models for fractured porous media.With the development of related research in recent years,the p...Simulation of fluid flow in the fractured porous media is very important and challenging.Researchers have developed some models for fractured porous media.With the development of related research in recent years,the prospect of embedded discrete fracture model(EDFM)is more and more bright.However,since the size of the fractures in the actual reservoir varies greatly,a very fine grid should be used which leads to a huge burden to the computing resources.To address this challenge,in the present paper,an upscaling based model is proposed.In this model,the flow in large-scale fractures is directly described by the EDFM while that in the small-scale fractures is upscaled through local simulation by EDFM.The EDFM is used to simulate the large-and small-scale fractures independently two times,so the new model is called dual embedded discrete fracture model(D-EDFM).In this paper,the detailed implementation process of D-EDFM is introduced and,through test cases,it is found the proposed model is a feasible method to simulate the flow in fractured porous media.展开更多
We present a rigorous homogenization approach for elcient computation of a class of physical problems in a one-dimensional periodic heterogeneous material. This material is represented by a spatially periodic array of...We present a rigorous homogenization approach for elcient computation of a class of physical problems in a one-dimensional periodic heterogeneous material. This material is represented by a spatially periodic array of unit cells with a length of More specifically, the method is applied to the diffusion, heat conduction, and wave propagation problems. Heterogeneous materials can have arbitrary position-dependent continuous or discontinuous materials properties （for example heat conductivity） within the unit cell. The final effective model includes both effective properties at the leading order and high-order contributions due to the microscopic heterogeneity. A dimensionless heterogeneity parameter ~ is defined to represent high-order contributions, shown to be in the range of [-1/12, 0], and has a universal expression for all three problems. Both effective properties and heterogeneity parameter 13 are independent oft, the microscopic scale of heterogeneity. The homogenized solution describing macroscopic variations can be obtained from the effective model. Solution with sub-unit-cell accuracy can be constructed based on the homogenized solution and its spatial derivatives. The paper represents a general approach to obtain the effective model for arbitrary periodic heterogeneous materials with position-dependent properties.展开更多
We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upsca...We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upscaling issues for heterogeneous materials. The dispersion relation for each problem is first expressed in the general form where the frequency co （or wavenumber k） is expanded in terms of the wavenumber k （or frequency ω）. A general homogenization model can be directly obtained with any given dispersion relation. Next step we study the unit cell of the heterogeneous material and derive the exact dispersion relation. The final homogenized equations include both leading order terms （effective properties） and high order contributions that represent the effect of the microscopic heterogeneity on the macroscopic behavior. That effect can be lumped into a single dimensionless heterogeneity parameter β, which is bounded between -1/12≤β≤ 0 and has a universal expression for all three problems. Numerical examples validate the proposed method and demonstrate a significant computational saving.展开更多
基金the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030004)the National Natural Science Foundation of China(Grant Nos.42275002 and 42275006)+1 种基金the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.ZDJ2024-01 and ZDJ2024-25)the Science and Technology Planning Project of Guangdong Province(Grant No.2023B1212060019).
文摘Active atmospheric convection on the monsoon coast is crucial for the Earth’s climate system.In particular,the upscale convective growth(UCG)from ordinary isolated convection to organized convective system is a key process causing severe weather,but its activities on the monsoon coast are less understood because of the lack of fine-resolution datasets.For the first time,we present the climatology of UCG on a typical monsoon coast using kilometer-mesh radar data from southern China.The UCG undergoes pronounced subseasonal and diurnal variations in the early-summer rainy season.The subseasonal UCG increase is attributed to the onshore flows shifting from easterlies in April to monsoon southwesterlies in June.UCG becomes vigorous following summer monsoon onset,with hotspots near windward coastal mountains.Daytime UCG first peaks near noontime along coastal land,where onshore flows are destabilized by boundary-layer heating and mountains.Afternoon inland peaks and off-coast minimums are recognized due to land–sea thermal contrast and sea-breeze circulation.Nighttime UCG is revived at the coast by nocturnally enhanced southerlies,followed by offshore activity as the convergence of land-breeze northerlies shifts seaward.The UCG thus responds strongly to changing atmospheric conditions,land heating/cooling,and thermally driven local circulations.Our results may help clarify the predictability of monsoon coastal convection.
基金supported by the National Natural Science Foundation of China(52300134 and 22106084)the China Postdoctoral Science Foundation(2022TQ0175,2023M741931,and 2022T150350).
文摘Catalytic amine-solvent regeneration has been validated as an energy-saving strategy for CO_(2) chemisorption by boosting reaction kinetics under mild conditions.The upscale performance evaluation and longterm durability are indispensable steps for industrial application but have been scarcely reported thus far.Here,we report a ZrO_(2)/Al_(2)O_(3) pack catalyst that possesses strong metal oxide-support interactions,a porous structure,active and stable Zr-O-Al coordination,promoted proton transfer and a 40.7% decrease in the energy activation of carbamate decomposition,which significantly accelerates CO_(2) desorption kinetics.The upscale experiment and cost evaluation based on industrial flue gas revealed that the use of packing catalysts can reduce energy consumption by 27.56% and optimize the overall cost by 10.49%.The active sites present excellent stability in alkaline solvents.This work is the first to investigate the ability of high-technology readiness(technology readiness level at 6(TRL 6))for catalytic aminesolvent regeneration,providing valuable insights for potential applications involving efficient CO_(2) capture with catalyst assistance.
基金the financial support from the National Science Foundation of China(No.52374063 and No.52204065)the Natural Science Foundation of Shandong Province,China(No.ZR2023ME049 and No.ZR2021JQ18)the Fundamental Research Funds for the Central Universities,China(24CX06017A)。
文摘Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.
文摘While redox flow batteries carry a large potential for electricity storage,specifically for regenerative energies,the current technology-prone system-the all-vanadium redox flow battery-exhibits two major disadvantages:low energy and low power densities.Polyoxometalates have the potential to mitigate both effects.In this publication,the operation of a polyoxometalate redox flow battery was demonstrated for the polyoxoanions[SiW_(12)O_(40)]^(4-)(SiW_(12))in the anolyte and[PV_(14)O_(42)]^(9-)(PV14)in the catholyte.Emphasis was laid on comparing to which extent an upscale from 25 to 1400 cm^(2) membrane area may impede efficiency and operational parameters.Results demonstrated that the operation of the large cell for close to 3 months did not diminish operation and the stability of polyoxometalates was unaltered.
基金partially supported by the National Natural Science Foundation of China(Nos.52334001,U24B200085)the Science Foundation of China University of Petroleum,Beijing(No.2462025XKBH012)。
文摘Numerical simulation is an essential technique for CO_(2)geological storage operations.However,highresolution geological models typically consist of a large number of grid blocks,making numerical simulations computationally expensive and time-consuming.Upscaling methods are commonly used to coarsen the fine-scale geological model,with global flow-based upscaling methods generally demonstrating the highest accuracy.However,since these methods require solving flow equations over the global domain,which is still time-consuming,their applications are typically limited to cases where the coarse model is reused repeatedly(e.g.,history matching or optimization).To overcome these limitations,this study develops a novel deep learning(DL)-based upscaling framework for the simulation of CO_(2)injection into saline aquifers.The framework incorporates convolutional neural networks(CNNs),Transformer encoders,and Fourier neural operators(FNOs)to construct surrogate models for upscaled well index,permeability,relative permeability,and capillary pressure.A preprocessing procedure is first applied to address the issue of inaccurate upscaled parameters,which are typically caused by weak flow conditions in traditional upscaling computations.Then the surrogate models are trained using relevant local information,and the trained surrogate models are used to replace traditional numerical upscaling computations,enabling instantaneous and parallel predictions of upscaled parameters.Two representative flow patterns(left-to-right and bottom-to-top)are considered to evaluate the framework's performance.The results demonstrate that the DL-based framework significantly improves computational efficiency,achieving a speedup factor of approximately 1133 times compared to traditional upscaling methods.Additionally,it maintains or even enhances simulation accuracy,as the surrogate models correct inaccurate upscaled parameters.
文摘One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification problem for second-order tensor data. Traditional vector-based one-class classification methods such as one-class support vector machine (OCSVM) and least squares one-class support vector machine (LSOCSVM) have limitations when tensor is used as input data, so we propose a new tensor one-class classification method, LSOCSTM, which directly uses tensor as input data. On one hand, using tensor as input data not only enables to classify tensor data, but also for vector data, classifying it after high dimensionalizing it into tensor still improves the classification accuracy and overcomes the over-fitting problem. On the other hand, different from one-class support tensor machine (OCSTM), we use squared loss instead of the original loss function so that we solve a series of linear equations instead of quadratic programming problems. Therefore, we use the distance to the hyperplane as a metric for classification, and the proposed method is more accurate and faster compared to existing methods. The experimental results show the high efficiency of the proposed method compared with several state-of-the-art methods.
基金supported by China Postdoctoral Science Foundation(No.2023TQ0247)Shenzhen Science and Technology Program(No.JCYJ20220530140602005)+2 种基金the Fundamental Research Funds for the Central Universities(No.2042023kfyq03)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515111071)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(No.GZB20230544).
文摘Knowledge of the mechanical behavior of planetary rocks is indispensable for space explorations.The scarcity of pristine samples and the irregular shapes of planetary meteorites make it difficult to obtain representative samples for conventional macroscale rock mechanics experiments(macro-RMEs).This critical review discusses recent advances in microscale RMEs(micro-RMEs)techniques and the upscaling methods for extracting mechanical parameters.Methods of mineralogical and microstructural analyses,along with non-destructive mechanical techniques,have provided new opportunities for studying planetary rocks with unprecedented precision and capabilities.First,we summarize several mainstream methods for obtaining the mineralogy and microstructure of planetary rocks.Then,nondestructive micromechanical testing methods,nanoindentation and atomic force microscopy(AFM),are detailed reviewed,illustrating the principles,advantages,influencing factors,and available testing results from literature.Subsequently,several feasible upscaling methods that bridge the micro-measurements of meteorite pieces to the strength of the intact body are introduced.Finally,the potential applications of planetary rock mechanics research to guiding the design and execution of space missions are environed,ranging from sample return missions and planetary defense to extraterrestrial construction.These discussions are expected to broaden the understanding of the microscale mechanical properties of planetary rocks and their significant role in deep space exploration.
基金financial support provided by the Future Energy System at University of Alberta and NSERC Discovery Grant RGPIN-2023-04084。
文摘Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.
基金supported by the National Natural Science Foundation of China[grant numbers 41471419 and 31971579].
文摘There is a growing interest in leveraging LiDAR-generated forest Aboveground Biomass(LG-AGB)data as a reference to retrieve AGB from satellite observations.However,the biases arising from the upscaling process and the impact of the sampling strategy on model accuracy still need to be resolved.In this study,we first corrected the bias arising from upscaling the LG-AGB map to match the spatial resolution of Landsat observations.Subsequently,the stratified random sampling method was used to select training samples from the corrected LG-AGB map(cLG-AGB)for the Random Forest(RF)regression model.The RF model features were extracted from the Landsat observations and auxiliary data.The impact of strata numbers on model accuracy was explored during the sampling process.Finally,independent validation was conducted using in situ measurements.The results indicated that:(1)about 68% of the biases can be corrected in the up-scale transformation;(2)compared to no stratification,a three-strata model achieved a 6.5% improvement in AGB estimation accuracy while requiring a 37.8% reduction in sample size;(3)the black locust forest had a low saturation point at 60.52±4.46 Mg/ha AGB and 72.4%AGB values were underestimated and the remaining were overestimated.In summary,our study provides a framework to harmonize near-surface LiDAR and satellite data for AGB estimation in plantation forest ecosystems with small patch sizes and fragmented distribution.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 91738302,Grant 62102423,Grant 61671332,and Grant U1736206in part by the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University under Grant 17E03.
文摘Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.In addition,since ground terminals have various resolutions and real-time playing requirements,it is essential to achieve arbitrary scale super-resolution(SR)of satellite images.In this paper,we propose an arbitrary scale SR network for satellite image reconstruction.First,we propose an arbitrary upscale module for satellite imagery that can map low-resolution satellite image features to arbitrary scale enlarged SR outputs.Second,we design an edge reinforcement module to enhance the highfrequency details in satellite images through a twobranch network.Finally,extensive upsample experiments on WHU-RS19 and NWPU-RESISC45 datasets and subsequent image segmentation experiments both show the superiority of our method over the counterparts.
基金supported by the National High-Tech Research & Development Program of China (No. 2009AA062802) the Fundamental Research Funds for the Central Universities of China (No. 12CX06001A)Shandong Provincial Natural Science Foundation, China (No. ZR2011DQ011)
文摘A new method of multi-scale modeling and display of geologic data is introduced to provide information with appropriate detail levels for different types of research. The multi-scale display mode employs a model extending existing 2D methods into 3D space. Geologic models with different scales are organized by segmenting data into orthogonal blocks. A flow diagram illustrates an octree method for upscaling between blocks with different scales. Upscaling data from the smallest unit cells takes into account their average size and the Burgers vector when there are mismatches. A geocellular model of the Chengdao Reservoir of the Shengli Oilfield, China is taken as an illustrative case, showing that the methods proposed can construct a multi-scale geologic model correctly and display data from the multi-scale model effectively in 3D.
文摘The Original Belonio Rice Husk Gasifier (OBRHG), initially of height of 0.6 m, diameter of 0.15 m and thickness of 0.025 m was tested for biochar production through air gasification of rice husk (RH) and the design was upscaled to height of 1.65 m, diameter of 0.85 m and thickness of 0.16 m. A total of 27 experiments were conducted to monitor the gasifier performance and the system can operate with the centrifugal blower operating at a power input of 155 W and a maximum flow rate of 1450 m3/hr regulated according to the air requirement. Building the UBRHG is simple and inexpensive to fabricate and with the fairly satisfactory performance and ease of construction along with the convenience of operation, the UBRHG with RH as feed would find abundant avenues of applications in a rural setting for biochar production alongside thermal, mechanical and electrical energy delivery.
基金Project supported by the National Natural Science Foundation of China(No.5140232)the National Science and Technology Major Project(No.2011ZX05038003)the China Postdoctoral Science Foundation(No.2014M561074)
文摘Based on the characteristics of fractures in naturally fractured reservoir and a discrete-fracture model, a fracture network numerical well test model is developed. Bottom hole pressure response curves and the pressure field are obtained by solving the model equations with the finite-element method. By analyzing bottom hole pressure curves and the fluid flow in the pressure field, seven flow stages can be recognized on the curves. An upscaling method is developed to compare with the dual-porosity model （DPM）. The comparisons results show that the DPM overestimates the inter-porosity coefficient ）, and the storage factor w. The analysis results show that fracture conductivity plays a leading role in the fluid flow. Matrix permeability influences the beginning time of flow from the matrix to fractures. Fractures density is another important parameter controlling the flow. The fracture linear flow is hidden under the large fracture density. The pressure propagation is slower in the direction of larger fracture density.
基金supported by the Center for Frontiers of Subsurface Energy Security (CFSES), UT Austinfunded by Basic Energy Sciences at the U.S.Department of Energy
文摘One of the potential risks associated with subsurface storage of CO_2 is the seepage of CO_2 through existing faults and fractures. There have been a number of studies devoted to this topic. Some of these studies show that geochemistry, especially mineralization, plays an important role in rendering the faults as conduits for CO_2 movement while others show that mineralization due to CO_2 injection can result in seep migration and flow diversion. Therefore, understanding the changes in reservoir properties due to pore alterations is important to ensure safe long term CO_2 storage in the subsurface. We study the changes in the Representative Elementary Volume（REV） of a rock due to reactive kinetics over a time, using a statistical approach and pore-scale CO_2-rock interactiondata.The goal of this study is to obtain the REV of a rock property that accounts for pore-scale changes over time due to reactive kinetics, and we call this as spatiotemporal REV. Scale-up results suggest that the REV changes with time when CO_2-rock interaction is considered. It is hypothesized that the alteration in pore structure introduces more heterogeneity in the rock, and because of this the magnitude of REV increases. It is possible that these noticeable changes in REV at pore-scale may have an impact when analyzed at the reservoir scale.
基金The research to anode material development received funding from the German Research Foundation(DFG,project No.392322200)the development of cathode materials and upscaling strategies was funded by the Federal Ministry of Education and Research(Project NextGen-3DBat,03XP0198F).
文摘Traditional electrode manufacturing for lithium-ion batteries is well established,reliable,and has already reached high processing speeds and improvements in production costs.For modern electric vehicles,however,the need for batteries with high gravimetric and volumetric energy densities at cell level is increasing;and new production concepts are required for this purpose.During the last decade,laser processing of battery materials emerged as a promising processing tool for either improving manufacturing flexibility and product reliability or enhancing battery performances.Laser cutting and welding already reached a high level of maturity and it is obvious that in the near future they will become frequently implemented in battery production lines.This review focuses on laser texturing of electrode materials due to its high potential for significantly enhancing battery performances beyond state-of-the-art.Technical approaches and processing strategies for new electrode architectures and concepts will be presented and discussed with regard to energy and power density requirements.The boost of electrochemical performances due to laser texturing of energy storage materials is currently proven at the laboratory scale.However,promising developments in high-power,ultrafast laser technology may push laser structuring of batteries to the next technical readiness level soon.For demonstration in pilot lines adapted to future cell production,process upscaling regarding footprint area and processing speed are the main issues as well as the economic aspects with regards to CapEx amortization and the benefits resulting from the next generation battery.This review begins with an introduction of the three-dimensional battery and thick film concept,made possible by laser texturing.Laser processing of electrode components,namely current collectors,anodes,and cathodes will be presented.Different types of electrode architectures,such as holes,grids,and lines,were generated;their impact on battery performances are illustrated.The usage of high-energy materials,which are on the threshold of commercialization,is highlighted.Battery performance increase is triggered by controlling lithium-ion diffusion kinetics in liquid electrolyte filled porous electrodes.This review concludes with a discussion of various laser parameter tasks for process upscaling in a new type of extreme manufacturing.
基金supported by the National Natural Science Foundation of China (Grant Nos. 30370815 and 30470332)
文摘To upscale the genetic parameters of CERES-Rice in regional applications, Jiangsu Province, the second largest rice producing province in China, was taken as an example. The province was divided into four rice regions with different rice variety types, and five to six sites in each region were selected. Then the eight genetic parameters of CERES-Rice, particularly the four parameters related to the yield, were modified and validated using the Trial and Error Method and the local statistical data of rice yield at a county level from 2001 to 2004, combined with the regional experiments of rice varieties in the province as well as the local meteorological and soil data （Method 1）. The simulated results of Method 1 were compared with those of other three traditional methods upscaling the genetic parameters, i.e., using one-site experimental data from a local representative rice variety （Method 2）, using local long-term rice yield data at a county level after deducting the trend yield due to progress of science and technology （Method 3）, and using rice yield data at a super scale, such as provincial, ecological zone, country or continent levels （Method 4）. The results showed that the best fitness was obtained by using the Method 1. The coefficients of correlation between the simulated yield and the statistical yield in the Method 1 were significant at 0.05 or 0.01 levels and the root mean squared error （RMSE） values were less than 9% for all the four rice regions. The method for upscaling the genetic parameters of CERES-Rice presented is not only valuable for the impact studies of climate change, but also favorable to provide a methodology for reference in crop model applications to the other regional studies.
基金supported by National Natural Science Foundations of China(Grant Nos.51706021,51936001 and 51804033)the Beijing Youth Talent Support Program(Grant No.CIT&TCD201804037)+1 种基金Joint Project of the Beijing Natural Science Foundation and the Beijing Municipal Education Commission(Grant No.KZ201810017023)the Great Wall Scholar program(Grant No.CIT&TCD20180313).
文摘Simulation of fluid flow in the fractured porous media is very important and challenging.Researchers have developed some models for fractured porous media.With the development of related research in recent years,the prospect of embedded discrete fracture model(EDFM)is more and more bright.However,since the size of the fractures in the actual reservoir varies greatly,a very fine grid should be used which leads to a huge burden to the computing resources.To address this challenge,in the present paper,an upscaling based model is proposed.In this model,the flow in large-scale fractures is directly described by the EDFM while that in the small-scale fractures is upscaled through local simulation by EDFM.The EDFM is used to simulate the large-and small-scale fractures independently two times,so the new model is called dual embedded discrete fracture model(D-EDFM).In this paper,the detailed implementation process of D-EDFM is introduced and,through test cases,it is found the proposed model is a feasible method to simulate the flow in fractured porous media.
文摘We present a rigorous homogenization approach for elcient computation of a class of physical problems in a one-dimensional periodic heterogeneous material. This material is represented by a spatially periodic array of unit cells with a length of More specifically, the method is applied to the diffusion, heat conduction, and wave propagation problems. Heterogeneous materials can have arbitrary position-dependent continuous or discontinuous materials properties （for example heat conductivity） within the unit cell. The final effective model includes both effective properties at the leading order and high-order contributions due to the microscopic heterogeneity. A dimensionless heterogeneity parameter ~ is defined to represent high-order contributions, shown to be in the range of [-1/12, 0], and has a universal expression for all three problems. Both effective properties and heterogeneity parameter 13 are independent oft, the microscopic scale of heterogeneity. The homogenized solution describing macroscopic variations can be obtained from the effective model. Solution with sub-unit-cell accuracy can be constructed based on the homogenized solution and its spatial derivatives. The paper represents a general approach to obtain the effective model for arbitrary periodic heterogeneous materials with position-dependent properties.
文摘We present a general homogenization method a periodic heterogeneous material with piecewise constants for diffusion, heat conduction, and wave propagation in The method is relevant to the frequently encountered upscaling issues for heterogeneous materials. The dispersion relation for each problem is first expressed in the general form where the frequency co （or wavenumber k） is expanded in terms of the wavenumber k （or frequency ω）. A general homogenization model can be directly obtained with any given dispersion relation. Next step we study the unit cell of the heterogeneous material and derive the exact dispersion relation. The final homogenized equations include both leading order terms （effective properties） and high order contributions that represent the effect of the microscopic heterogeneity on the macroscopic behavior. That effect can be lumped into a single dimensionless heterogeneity parameter β, which is bounded between -1/12≤β≤ 0 and has a universal expression for all three problems. Numerical examples validate the proposed method and demonstrate a significant computational saving.
