Dominant factors in MiniCone, CPT and pile correlations: A data‐based approach

The cone penetration test(CPT)contributes to the design and analysis of piles regarding geometry,installation effect,and pile capacity(shaft and toe resistance).MiniCone,as an alternative to CPT sounding,has been used to carry outfield and laboratory investigations by physical modeling.More tests can be practically carried out through light equipment and small soil mass,involving fewer errors caused by boundary conditions.Furthermore,it can be used for in situ testing,such as quality control,assessment of ground improvement,and subgrade characterization.A database comprising MiniCone and CPT records infield and physical modeling is proposed with a variety of cone diameters.The case study records in the database have been obtained from 140 tests compiled from data from 26 sources.The sources include the results of 20 physical modelings andfield data from six sites in 10 countries.The data comprise MiniCone and CPT cone tip resistance(qc),and sleeve friction(fs).The different cones are used in sandy,silty sand,and clayey soils via simple chambers(1 g),calibration chambers,and frustum confining vessels.In addition,correlations were found in penetration records in terms of physical modeling types,cone diameters,penetration rates,and soil densities.Moreover,qc and fs are related to capacities of pile toes and shafts using proper correlation coefficients less than unity,respectively.Correlations and dominant factors in geotechnical practice between MiniCone,CPT,and pile have been reviewed and discussed.

Dominating factors on well productivity and development strategies optimization in Weiyuan shale gas play, Sichuan Basin, SW China

Weiyuan shale gas play is characterized by thin high-quality reservoir thickness,big horizontal stress difference,and big productivity differences between wells.Based on integrated evaluation of shale gas reservoir geology and well logging interpretation of more than 20 appraisal wells,a correlation was built between the single well test production rate and the high-quality reservoir length drilled in the horizontal wells,high-quality reservoir thickness and the stimulation treatment parameters in over 100 horizontal wells,the dominating factors on horizontal well productivity were found out,and optimized development strategies were proposed.The results show that the deployed reserves of high-quality reservoir are the dominating factors on horizontal well productivity.In other words,the shale gas well productivity is controlled by the thickness of the high-quality reservoir,the high-quality reservoir drilling length and the effectiveness of stimulation.Based on the above understanding,the development strategies in Weiyuan shale gas play are optimized as follows:(1)The target of horizontal wells is located in the middle and lower parts of Longyi 11(Wei202 area)and Longyi 11(Wei204 area).(2)Producing wells are drilled in priority in the surrounding areas of Weiyuan county with thick high-quality reservoir.(3)A medium to high intensity stimulation is adopted.After the implementation of these strategies,both the production rate and the estimated ultimate recovery(EUR)of individual shale gas wells have increased substantially.

Changes in Climate Factors and Their Impacts on Wind Erosion Climatic Erosivity in Farming-pastoral Zone of Northern China

Climate change can affect wind erosion power and hence induce changes in wind erosion rates.In this study,the wind erosion climate factor(C-factor),proposed by the Food and Agriculture Organization of the United Nations,was used to assess the impact of changes in climate on wind erosion climatic erosivity.The Mann-Kendall test was employed to detect trends in the C-factor during the period of 1961–2017 in the farming-pastoral zone of northern China.Sensitivity analysis was used to determine the sensitivity of the C-factor to changes in key climate factors.Furthermore,a comparison of the contributions of different climate factors was carried out to understand their impact on changes in the C-factor.The results indicated that most of the surveyed region exhibited decreasing trends in wind speed at a confidence level of 90%,while maximum and minimum temperatures showed increasing trends throughout the study area.As a consequence of decreasing wind speed,the annual C-factor exhibited significant decreasing trends,with a mean slope of–0.58/yr.Seasonal analysis revealed that in most regions,the changes in the C-factor had significant decreasing trends in spring,winter,and autumn,while in more than two-thirds of the study area,no significant change trends in the C-factor were detected in summer at a confidence level of 90%.Sensitivity analysis showed that the C-factor was most sensitive to wind speed,and that the sensitivity coefficients from July to September were much higher than those in other months.Contribution analysis revealed that,for most stations,wind speed(with greater values of sensitivity coefficients)was the dominant factor in the change of C-factor,while for some stations,the minimum temperature made the most contribution to the C-factor’s change due to its dramatic changes during the study period.Although the minimum temperature sensitivity coefficient was the lowest of all the sensitivity coefficients,it is urgent to evaluate the expected impact of minimum temperature due to its possible changes in the future.

Hybrid data-driven framework for shale gas production performance analysis via game theory, machine learning, and optimization approaches

A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.

Drivers of coastal bacterioplankton community diversity and structure along a nutrient gradient in the East China Sea

Anthropogenic nutrient discharge poses widespread threats to coastal ecosystems and has increased environmental gradients from coast to sea. Bacterioplankton play crucial roles in coastal biogeochemical cycling, and a variety of factors af fect bacterial community diversity and structure. We used 16 S r RNA gene pyrosequencing to investigate the spatial variation in bacterial community composition(BCC) across five sites on a coast-of fshore gradient in the East China Sea. Overall, bacterial alpha-diversity did not diff er across sites, except that richness and phylogenetic diversity were lower in the of fshore sites, and the highest alpha-diversity was found in the most landward site, with Chl-abeing the main factor. BCCs generally clustered into coastal and of fshore groups. Chl-a explained 12.3% of the variation in BCCs, more than that explained by either the physicochemical(5.7%) or spatial(8.5%) variables. Nutrients(particularly nitrate and phosphate), along with phytoplankton abundance, were more important than other physicochemical factors, co-explaining 20.0% of the variation in BCCs. Additionally, a series of discriminant families(primarily affiliated with Gammaproteobacteria and Alphaproteobacteria), whose relative abundances correlated with Chl-a, DIN, and phosphate concentrations, were identified, implying their potential to indicate phytoplankton blooms and nutrient enrichment in this marine ecosystem. This study provides insight into bacterioplankton response patterns along a coast-of fshore gradient, with phytoplankton abundance increasing in the of fshore sites. Time-series sampling across multiple transects should be performed to determine the seasonal and spatial patterns in bacterial diversity and community structure along this gradient.

Identification of Dominant Climate Variables on Spatiotemporal Variation in Reference Evapotranspiration on the Loess Plateau,China

Reference evapotranspiration(ET_(0))is a vital component in hydrometeorological research and is widely applied to various aspects,such as water resource management,hydrological modeling,irrigation deployment,and understanding and predicting the influence of hydrologic cycle variations on future climate and land use changes.Quantifying the influence of various meteorological variables on ET_(0) is not only helpful for predicting actual evapotranspiration but also has important implications for understanding the impact of global climate change on regional water resources.Based on daily data from 69 meteorological stations,the present study analyzed the spatiotemporal pattern of ET_(0) and major contributing meteorological variables to ET_(0) from 1960 to 2017 by the segmented re-gression model,Mann-Kendall test,wavelet analysis,generalized linear model,and detrending method.The results showed that the annual ET_(0) declined slightly because of the combined effects of the reduction in solar radiation and wind speed and the increase in vapor pressure deficit(VPD)and average air temperature in the Loess Plateau(LP)during the past 58 yr.Four change points were detected in 1972,1990,1999,and 2010,and the annual ET_(0) showed a zigzag change trend of‘increasing-decreasing-increasing-decreasing-increasing’.Wind speed and VPD played a leading role in the ET_(0) changes from 1960 to 1990 and from 1991 to 2017,respectively.This study confirms that the dominant meteorological factors affecting ET_(0) had undergone significant changes due to global climate change and vegetation greening in the past 58 years,and VPD had become the major factor controlling the ET_(0) changes on the LP.The data presented herein will contribute to increasing the accuracy of predictions on future changes in ET_(0).

2001-2020年中国地表温度时空分异及归因分析

The variation of land surface temperature(LST)has a vital impact on the energy balance of the land surface process and the ecosystem stability.Based on MDO11C3,we mainly used regression analysis,GIS spatial analysis,correlation analysis,and center-of-gravity model,to analyze the LST variation and its spatiotemporal differentiation in China from 2001 to 2020.Furthermore,we employed the Geodetector to identify the dominant factors contributing to LST variation in 38 eco-geographic zones of China and investigate the underlying causes of its pattern.The results indicate the following:(1)From 2001 to 2020,the LST climate average in China is 9.6℃,with a general pattern of higher temperatures in the southeast and northwest regions,lower temperatures in the northeast and Qinghai-Tibet Plateau,and higher temperatures in plains compared to lower temperatures in mountainous areas.Generally,LST has a significant negative correlation with elevation,with a correlation coefficient of–0.66.China’s First Ladder has the most pronounced negative correlation,with a correlation coefficient of–0.76 and the lapse rate of LST is 0.57℃/100 m.(2)The change rate of LST in China during the study is 0.21℃/10 a,and the warming area accounts for 78%,demonstrating the overall spatial pattern a“multi-core warming and axial cooling”.(3)LST’s variation exhibits prominent seasonal characteristics in the whole country.The spatial distribution of average value in winter and summer differs significantly from other seasons and shows more noticeable fluctuations.The centroid trajectory of the seasonal warming/cooling area is close to a loop shape and displays corresponding seasonal reverse movement.Cooling areas exhibit more substantial centroid movement,indicating greater regional variation and seasonal variability.(4)China’s LST variation is driven by both natural influences and human activities,of which natural factors contribute more,with sunshine duration and altitude being key factors.The boundary trend between the two dominant type areas is highly consistent with the“Heihe-Tengchong Line”.The eastern region is mostly dominated by human activity in conjunction with terrain factors,while the western region is predominantly influenced by natural factors,which enhance/weaken the change range of LST through mutual coupling with climate,terrain,vegetation,and other factors.This study offers valuable scientific references for addressing climate change,analyzing surface environmental patterns,and protecting the ecological environment.

UAV-based spatial pattern of three-dimensional green volume and its influencing factors in Lingang New City in Shanghai,China

Three-dimensional green volume(TDGV)reflects the quality and quantity of urban green space and its provision of ecosystem services;therefore,its spatial pattern and the underlying influential factors play important roles in urban planning and management.However,little is known about the factors contributing to the spatial pattern of TDGV.In this paper,TDGV and land use intensity(LUI)extracted from high spatial resolution(0.05 m)remotely sensed data acquired by an unmanned aerial vehicle(UAV),anthropogenic factors^(1))and natural factors^(2))were utilized to identify the spatial pattern of TDGV and the potential influencing factors in Lingang New City,a rapidly developed coastal town in Shanghai.The results showed that most of the TDGV was distributed in the western part of this new city and that its spatial variations were significantly axial.TDGV corresponded well with the chronologies of land formation,urban planning,and construction in the city.Generalized least squares(GLS)analysis of TDGV(grid cell size:100×100 m)and its influencing factors showed that the TDGV in this new city was significantly negatively correlated with both LUI and distance from roads and significantly positively correlated with land formation time and distance from water.Distance from buildings did not affect TDGV.Additionally,the degree of influence decreased in the following order:distance from water>land formation time>distance from roads>LUI.These results indicate that the spatial pattern of TDGV in this new town was mainly affected by natural factors(i.e.,the distance from water and land formation time)and that the artificial disturbances caused by rapid urbanization did not decrease the regional TDGV.The main factors shaping the spatial distribution of TDGV in this city were local natural factors.Our findings suggest that the improvement in local soil and water conditions should be emphasized in the construction of new cities in coastal areas to ensure the efficient provision of ecological services by urban green spaces.

Elucidating dominant factors of PO43–, Cd2+ and nitrobenzene removal by biochar: A comparative investigation based on distinguishable biochars

Biochars produced from crab shell(CSB),oak sawdust(OB),Jeru salem artichoke tuber(JAB) and sorghum grain(SB) displayed distinguishable adsorption-related characteristics,such as specific surface area(SSA),ash content and acidic oxygen-containing functional groups(AFGs),which linked to the biochar adsorption mechanisms of most pollutants.Herein,PO4^3-,Cd^2+,and nitrobenzene(NB) were employed for adsorption by these biochars to elucidate the dominant factors for the adsorption.Adsorption performance of the three pollutants onto these four biochars varied considerably,as exemplified by the excellent adsorption of PO4^3- and Cd^2+ onto CSB(225.3 and 116.0 mg/g,respectively) as compared with onto the other three biochars(4.2-37.1 mg/g for P043-and 9.7-41.0 mg/g for Cd^2+).OB displayed the best adsorption of NB(72.0 mg/g),followed by SB(39.5 mg/g),JAB(31.1 mg/g),and CSB(23.6 mg/g).The kinetics and isotherm adsorption assessments couple with material characterization suggested that the sorption of selected pollutants on biochars was attributed to the multiple mechanisms involved,including coprecipitation,chemical bonds,cation exchange,physical absorption,and complexation.Further path analysis suggested that AFGs and ash content in biochars were more important than SSA with regards to pollutant removal,especially,with ash playing a crucial role in the removal of Cd2+ and PO43-,and AFGs being mainly re s ponsible for NB adsorption.These findings might offer guidance on the preparation or modification of biochar with a targeted function for pollutant removal through an understanding the dominant factors.

Dynamic modelling and simulation of a post-combustion CO_(2) capture process for coal-fired power plants

Solvent-based post-combustion capture technologies have great potential for CO_(2)mitigation in traditional coal-fired power plants.Modelling and simulation provide a low-cost opportunity to evaluate performances and guide flexible operation.Composed by a series of partial differential equations,first-principle post-combustion capture models are computationally expensive,which limits their use in real time process simulation and control.In this study,we propose a first-principle approach to develop the basic structure of a reduced-order model and then the dominant factor is used to fit properties and simplify the chemical and physical process,based on which a universal and hybrid post-combustion capture model is established.Model output at steady state and trend at dynamic state are validated using experimental data obtained from the literature.Then,impacts of liquidto-gas ratio,reboiler power,desorber pressure,tower height and their combination on the absorption and desorption effects are analyzed.Results indicate that tower height should be designed in conjunction with the flue gas flow,and the gas-liquid ratio can be optimized to reduce the reboiler power under a certain capture target.