Least Squares One-Class Support Tensor Machine

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.

Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

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.

A polyoxometalate redox flow battery: functionality and upscale

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.

The capillary pressure curves from upscaling interfacial and unsaturated flows in porous layers with vertical heterogeneity

We provide the capillary pressure curves p_(c)(s)as a function of the effective saturation s based on the theoretical framework of upscaling unsaturated flows in vertically heterogeneous porous layers proposed recently(Z.Zheng,Journal of Fluid Mechanics,950,A17,2022).Based on the assumption of vertical gravitational-capillary equilibrium,the saturation distribution and profile shape of the invading fluid can be obtained by solving a nonlinear integral-differential equation.The capillary pressure curves p_(c)(s)can then be constructed by systematically varying the injection rate.Together with the relative permeability curves k_(rn)(s)that are already obtained.One can now provide quick estimates on the overall behaviours of interfacial and unsaturated flows in vertically-heterogeneous porous layers.

结合UPSCALING技术与对象多特征的土地利用/覆盖信息提取研究

应用SPOT融合数据,以北京密云地区为例,提出了整合Upscaling技术与对象多特征方法的新思路,通过基于半变异函数的空间变异特征分析,建立了面向对象多特征与多分辨率数据集的多尺度分类决策树,并对自动分类效率进行了初步探讨。

Arbitrary Scale Super Resolution Network for Satellite Imagery

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.

Designing and Performance Evaluation of Biochar Production in a Top-Lit Updraft Up-scaled Gasifier

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.

Numerical investigation of dual-porosity model with transient transfer function based on discrete-fracture model

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.

A Method for Upscaling Genetic Parameters of CERES-Rice in Regional Applications

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.

Study on a Dual Embedded Discrete Fracture Model for Fluid Flow in Fractured Porous Media

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.

Recent progress in laser texturing of battery materials: a review of tuning electrochemical performances, related material development, and prospects for large-scale manufacturing

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.

New dynamic permeability upscaling method for flow simulation under depletion drive and no-crossflow conditions

The main purpose of upscaling in reservoir simulation is to capture the dynamic behavior of fine scale models at the coarse scale. Traditional static or dynamic methods use assumptions about the boundary conditions to determine the upscaled properties, in this paper, we show that the upscaled properties are strongly dependent on the flow process observed at the fine scale. We use a simple no- crossflow depletion drive process and demonstrate that an upscaled property is not a constant value. Instead, if the goal is to match the performance of the fine scale model, the upscaled permeability changes with time. We provide an analytical solution to determine the upscaled permeability and present the value of upscaled permeability under limiting conditions. Our equation suggests that it is possible that upscaled value can fall outside the range of fine scale values under certain conditions. We show that for pseudo steady state flow, using common averaging methods like arithmetic or even geometric averaging methods can lead to optimistic results. We also show that the no-crossflow solution is significantly different than crossflow solution at late times. We validate our method by comparing the results of the method with flow simulation results in two and multi-layered models.

Dendritic spine density changes and homeostatic synaptic scaling:a meta-analysis of animal studies

Mechanisms of homeostatic plasticity promote compensatory changes of cellular excitability in response to chronic changes in the network activity.This type of plasticity is essential for the maintenance of brain circuits and is involved in the regulation of neural regeneration and the progress of neurodegenerative disorders.One of the most studied homeostatic processes is synaptic scaling,where global synaptic adjustments take place to restore the neuronal firing rate to a physiological range by the modulation of synaptic receptors,neurotransmitters,and morphology.However,despite the comprehensive literature on the electrophysiological properties of homeostatic scaling,less is known about the structural adjustments that occur in the synapses and dendritic tree.In this study,we performed a meta-analysis of articles investigating the effects of chronic network excitation(synaptic downscaling)or inhibition(synaptic upscaling)on the dendritic spine density of neurons.Our results indicate that spine density is consistently reduced after protocols that induce synaptic scaling,independent of the intervention type.Then,we discuss the implication of our findings to the current knowledge on the morphological changes induced by homeostatic plasticity.

Understanding the precursor chemistry for one-step deposition of mixed cation perovskite solar cells by methylamine route

Upscaling perovskite solar cell fabrication is one of the key challenges in the pathway for commercialization.The slow evaporation of frequently used solvents(DMF or DMSO) limits the fast perovskite layer crystallization,hindering their implementation in large scale deposition methods.Alternatively,methylamine-based precursors have demonstrated rapid crystallization,leading to uniform and specular films.Nonetheless,their application has been limited to MAPbI3 perovskites with limited efficiency and stability.In this work,we report the requirements for stabilizing α-phase of mixed cation perovskites with high amount of formamidinium by using a methylamine-based precursor.We found that even though,there are many methods for incorporating the methylamine(MA) in precursors or films;the MA content determines stabilization of the α-phase and therefore the viscous-solution route is the only method to incorporate high amounts of MA.At low amounts of MA,perovskite tend to crystallize in 1D dimensional FA_(3)(MA)PbI5 phases due to the incomplete solvation of the PbI6-clusters.In contrast,high MA ratio induces a full solvation of the clusters,leading to a rapid crystallization and a full stabilization of the active 3D α-phase.These results open a window in the development and understanding of new precursors for the fabrication of high efficient,stable and scalable perovskite devices.

Data-Driven Upscaling of Orientation Kinematics in Suspensions of Rigid Fibres

Describing the orientation state of the particles is often critical in fibre suspension applications.Macroscopic descriptors,the so-called second-order orientation tensor(or moment)leading the way,are often preferred due to their low computational cost.Closure problems however arise when evolution equations for the moments are derived from the orientation distribution functions and the impact of the chosen closure is often unpredictable.In this work,our aim is to provide macroscopic simulations of orientation that are cheap,accurate and closure-free.To this end,we propose an innovative data-based approach to the upscaling of orientation kinematics in the context of fibre suspensions.Since the physics at the microscopic scale can be modelled reasonably enough,the idea is to conduct accurate offline direct numerical simulations at that scale and to extract the corresponding macroscopic descriptors in order to build a database of scenarios.During the online stage,the macroscopic descriptors can then be updated quickly by combining adequately the items from the database instead of relying on an imprecise macroscopic model.This methodology is presented in the well-known case of dilute fibre suspensions(where it can be compared against closure-based macroscopic models)and in the case of suspensions of confined or electrically-charged fibres,for which state-of-the-art closures proved to be inadequate or simply do not exist.

Simultaneous upscaling of two properties of reservoirs in one dimension using adaptive bandwidth in kernel function method

Upscaling of primary geological models with huge cells, especially in porous media, is the first step in fluid flow simulation. Numerical methods are often used to solve the models. The upscaling method must preserve the important properties of the spatial distribution of the reservoir properties. An grid upscaling method based on adaptive bandwidth in kernel function is proposed according to the spatial distribution of property. This type of upscaling reduces the number of cells, while preserves the main heterogeneity features of the original fine model. The key point of the paper is upscaling two reservoir properties simultaneously. For each reservoir feature, the amount of bandwidth or optimal threshold is calculated and the results of the upscaling are obtained. Then two approaches are used to upscaling two properties simultaneously based on maximum bandwidth and minimum bandwidth. In fact, we now have a finalized upscaled model for both reservoir properties for each approach in which not only the number of their cells, but also the locations of the cells are equal. The upscaling error of the minimum bandwidth approach is less than that of the maximum bandwidth approach.

Muddy interlayer forecasting and an equivalent upscaling method based on tortuous paths: A case study of Mackay River oil sand reservoirs in Canada

Based on the abundant core data of oil sands in the Mackay river in Canada,the termination frequency of muddy interlayers was counted to predict the extension range of interlayers using a queuing theory model,and then the quantitative relationship between the thickness and extension length of muddy interlayer was established.An equivalent upscaling method of geologic model based on tortuous paths under the effects of muddy interlayer has been proposed.Single muddy interlayers in each coarse grid are tracked and identified,and the average length,width and proportion of muddy interlayer in each coarse grid are determined by using the geological connectivity tracing algorithm.The average fluid flow length of tortuous path under the influence of muddy interlayer is calculated.Based on the Darcy formula,the formula calculating average permeability in the coarsened grid is deduced to work out the permeability of equivalent coarsened grid.The comparison of coarsening results of the oil sand reservoir of Mackay River with actual development indexes shows that the equivalent upscaling method of muddy interlayer by tortuous path calculation can reflect the blocking effect of muddy interlayer very well,and better reflect the effects of geological condition on production.

Sensitivity-based upscaling for history matching of reservoir models

Simulation of reservoir flow processes at the finest scale is computationally expensive and in some cases impractical.Consequently,upscaling of several fine-scale grid blocks into fewer coarse-scale grids has become an integral part of reservoir simulation for most reservoirs.This is because as the number of grid blocks increases,the number of flow equations increases and this increases,in large proportion,the time required for solving flow problems.Although we can adopt parallel computation to share the load,a large number of grid blocks still pose significant computational challenges.Thus,upscaling acts as a bridge between the reservoir scale and the simulation scale.However as the upscaling ratio is increased,the accuracy of the numerical simulation is reduced;hence,there is a need to keep a balance between the two.In this work,we present a sensitivity-based upscaling technique that is applicable during history matching.This method involves partial homogenization of the reservoir model based on the model reduction pattern obtained from analysis of the sensitivity matrix.The technique is based on wavelet transformation and reduction of the data and model spaces as presented in the 2Dwp-wk approach.In the 2Dwp-wk approach,a set of wavelets of measured data is first selected and then a reduced model space composed of important wavelets is gradually built during the first few iterations of nonlinear regression.The building of the reduced model space is done by thresholding the full wavelet sensitivity matrix.The pattern of permeability distribution in the reservoir resulting from the thresholding of the full wavelet sensitivity matrix is used to determine the neighboring grids that are upscaled.In essence,neighboring grid blocks having the same permeability values due to model space reduction are combined into a single grid block in the simulation model,thus integrating upscaling with wavelet multiscale inverse modeling.We apply the method to estimate the parameters of two synthetic reservoirs.The history matching results obtained using this sensitivity-based upscaling are in very close agreement with the match provided by fine-scale inverse analysis.The reliability of the technique is evaluated using various scenarios and almost all the cases considered have shown very good results.The technique speeds up the history matching process without seriously compromising the accuracy of the estimates.

Multiscalar Geomorphometric Generalization for Soil-Landscape Modeling by Random Forest: A Case Study in the Eastern Amazon

Multiscalar topography influence on soil distribution has a complex pattern that is related to overlay of pedological processes which occurred at different times, and these driving forces are correlated with many geomorphologic scales. In this sense, the present study tested the hypothesis whether multiscale geomorphometric generalized covariables can improve pedometric modeling. To achieve this goal, this case study applied the Random Forest algorithm to a multiscale geomorphometric database to predict soil surface attributes. The study area is in phanerozoic sedimentary basins, in the Alter do Chão geological formation, Eastern Amazon, Brazil. The multiscale geomorphometric generalization was applied at general and specific geomorphometric covariables, producing groups for each scale combination. The modeling was run using Random Forest for A-horizon thickness, pH, silt and sand content. For model evaluation, visual analysis of digital maps, metrics of forest structures and effect of variables on prediction were used. For evaluation of soil textural classifications, the confusion matrix with a Kappa index, and the user’s and producer’s accuracies were employed. The geomorphometry generalization tends to smooth curvatures and produces identifiable geomorphic representations at sub-watershed and watershed levels. The forest structures and effect of variables on prediction are in agreement with pedological knowledge. The multiscale geomorphometric generalized covariables improved accuracy metrics of soil surface texture classification, with the Kappa Index going from 43% to 62%. Therefore, it can be argued that topography influences soil distribution at combined coarser spatial scales and is able to predict soil particle size contents in the studied watershed. Future development of the multiscale geomorphometric generalization framework could include generalization methods concerning preservation of features, landform classification adaptable at multiple scales.

Micromechanical testing and property upscaling of planetary rocks:A critical review

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.