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Algorithms and statistical analysis for linear structured weighted total least squares problem

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geodesy and geodynamics 2024年第2期15卷 177-188页

作者： Jian Xie Tianwei Qiu Cui Zhou Dongfang Lin Sichun Long School of earth Science and Spatial information Engineering Hunan University of Science and TechnologyXiangtan 411201China College of Science Central South University of Forestry and TechnologyChangsha 410018China National-Local Joint Engineering Laboratory of geo-spatial information Technology Hunan University of Science and TechnologyXiangtan 411201China

Weighted total least squares(WTLS)have been regarded as the standard tool for the errors-in-variables(EIV)model in which all the elements in the observation vector and the coefficient matrix are contaminated with random ***,in many geodetic applications,some elements are error-free and some random observations appear repeatedly in different positions in the augmented coefficient *** is called the linear structured EIV(LSEIV)*** kinds of methods are proposed for the LSEIV model from functional and stochastic *** the one hand,the functional part of the LSEIV model is modified into the errors-in-observations(EIO)*** the other hand,the stochastic model is modified by applying the Moore-Penrose inverse of the cofactor *** algorithms are derived through the Lagrange multipliers method and linear *** estimation principles and iterative formula of the parameters are proven to be *** first-order approximate variance-covariance matrix(VCM)of the parameters is also derived.A numerical example is given to compare the performances of our proposed three algorithms with the STLS ***,the least squares(LS),total least squares(TLS)and linear structured weighted total least squares(LSWTLS)solutions are compared and the accuracy evaluation formula is proven to be feasible and ***,the LSWTLS is applied to the field of deformation analysis,which yields a better result than the traditional LS and TLS estimations.

关键词： Linear structured weighted total least squares Errors-in-variables Errors-in-observations Functional modelmodification Stochastic model modification Accuracyevaluation

Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations

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Science China(Technological Sciences) 2024年第6期67卷 1907-1922页

作者： YE Xiao ZHU HongHu WANG Jia ZHENG WanJi ZHANG Wei SCHENATO Luca PASUTO Alessandro CATANI Filippo School of earth Sciences and Engineering Nanjing UniversityNanjing210023China Department of geosciences University of PadovaPadova35131Italy School of geosciences and Info-Physics Central South UniversityChangsha410083China Department of information Engineering University of PadovaPadova35131Italy National Research Council-Research institute for geo-Hydrological Protection(CNR-IRPI) Padova35127Italy

Synergistic multi-factor early warning of large-scale landslides is a crucial component of geohazard prevention and mitigation efforts in reservoir *** forecasting and early warning based on surface displacements have been widely ***,the lack of direct subsurface real-time observations limits our ability to predict critical hydrometeorological conditions that trigger landslide *** this paper,we leverage subsurface strain data measured by high-resolution fiber optic sensing nerves that were installed in a giant reservoir landslide in the Three Gorges Reservoir(TGR)region,China,spanning a whole hydrologic year since February *** spatiotemporal strain profile has preliminarily identified the slip zones and potential drivers,indicating that high-intensity short-duration rainstorms controlled the landslide kinematics from an observation *** the time lag effect,we reexamined and quantified potential controls of accelerated movements using a data-driven approach,which reveals immediate response of landslide deformation to extreme rainfall with a zero-day *** identify critical hydrometeorological rules in accelerated movements,accounting for the dual effect of rainfall and reservoir water level variations,we thus construct a landslide prediction model that relies upon the boosting decision tree(BDT)algorithm using a dataset comprising daily rainfall,rainfall intensity,reservoir water level,water level fluctuations,and slip zone strain time *** results indicate that landslide acceleration is most likely to occur under the conditions of mid-low water levels(i.e.,57.9 mm and rainfall intensity>24.4 mm/h).Moreover,this prediction model allows us to update hydrometeorological thresholds by incorporating the latest monitoring *** on the shoulder of this landslide case,our study informs a practical and reliable path

关键词： slow-moving landslide fiber-optic monitoring subsurface strain hydrometeorological threshold extreme weather

Chronological Study of Coal-seam Water and its Implication on Gas Production in the South Qinshui Basin

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Acta geologica Sinica(English Edition) 2024年第1期98卷 207-219页

作者： CHEN Biying FANG Lujia LANG Yunchao XU Sheng LIU Congqiang ZHANG Luyuan HOU Xiaolin institute of Surface-earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China institute of earth Environments Chinese Academy of SciencesXi’an 710061China

The knowledge of the residence time of formation water is fundamental to understanding the subsurface flow and hydrological *** better identify the origin and evolution of coal seam water and its impact on gas storage and production,this study collected coalbed methane co-produced water in the southeast Qinshui Basin and detected chemical and isotopic compositions,especially 36Cl and 129I *** calculated tracer ages of 129I(5.2–50.6 Ma)and 36Cl(0.13–0.76 Ma)are significantly younger than the age of coal-bearing formation(Pennsylvanian-Cisuralian),indicating freshwater recharge after coal *** model that utilises 129I/I and 36Cl/Cl ratios to constrain the timing of recharge and the proportion of recharge water reveals that over 60%of pre-anthropogenic meteoric water entered coal seams since 10 Ma and mixed with residue initial deposition water,corresponding to the basin inversion in *** spatial distribution of major ion concentrations reveals the primary recharge pathway for meteoric water from coal outcrops at the eastern margin to the basin *** study demonstrates the occurrence of higher gas production rates from wells that accept water recharge in recent times and suggests the possible potential of the non-stagnant zones for high gas production.

关键词： CBM co-produced water iodine-129 chlorine-36 water chemistry Qinshui Basin

Extreme value theory applied to the auroral electrojet indices

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earth and Planetary Physics 2024年第2期8卷 375-381页

作者： Si Chen Hong Yuan Yong Wei Guang Yang FengZheng Yu Aerospace information Research institute Chinese Academy of SciencesBeijing 100094China Key Laboratory of earth and Planetary Physics Institute of Geology and GeophysicsChinese Academy of SciencesBeijing 100029China College of earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China

The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high *** and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various *** research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value *** fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time ***,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are *** a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly *** is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.

关键词： auroral electrojet indices extreme value theory extreme events

Druse Calcite Crystals Formed by Mesoproterozoic Paleo-earthquake Activity in the Northern Margin of the North China Craton

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Journal of earth Science 2024年第2期35卷 514-524页

作者： Yueshuang Du Zhiguang Zhou Guosheng Wang Chen Wu Wenchao Xu School of earth Sciences and Resources China University of GeosciencesBeijing100083China Key Laboratory of Continental Collision and Plateau Uplift Institute of Tibetan Plateau Researchand Center for Excellence in Tibetan Plateau Earth SciencesChinese Academy of SciencesBeijing100101China No.1 institute of geological and Mineral Resources Survey Henan Bureau of Geo-Exploration&Mineral DevelopmentLuoyang471000China

The Meso-neoproterozoic Bayan Obo rift is located along the northern margin of the North China Craton,and was associated with the break-up of the Columbia *** rift evolution,syn-sedimentary deformation occurred due to tectonic activity and *** events are recorded in the Jianshan Formation of the Bayan Obo Group,Inner Mongolia,as soft sediment deformation structures in the central Bayan Obo *** calcite crystals and collapse breccias in the Jianshan Formation may provide information on the rift *** druse calcite crystals are idiomorphic-columnar in shape and associated with graphite,pyrite,and quartz.δ^(13)C values of the graphite are−20‰,indicative of biogenic deoxygenation and formation in *** druse calcite crystals are inorganic in origin and formed in water at a temperature of 55℃,based on calciteδ^(13)C andδ^(18)O *** calcite grew in paleo-caves containing fault breccias,with heat derived from *** such,the druse calcite crystals are important evidence for seismic *** collapse breccias(i.e.,fault breccias)and other indicators of slip show that displacement occurred from NE to SW,which is different from the paleocurrent direction in the Jianshan *** thickness of the collapse breccia is∼200 m,which represents the height of the fault *** strike of the fault scarp was NE-SW,based on the distribution of the collapse *** Bayan Obo and Yanliao rifts experienced rapid NW-SE extension,and developed similar deformation structures at ca.1.6 Ga related to break-up of the Columbia supercontinent.

关键词： North China Craton druse calcite crystals paleo-earthquake activity collapse breccia Bayan Obo rift Proterozoic

X-ray-activated Bi^(3+)/Pr^(3+)co-doped LiYgeo_4 phosphor with UV and NIR dual-emissive persistent luminescence

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Journal of Rare earths 2024年第5期42卷 955-961,I0005页

作者： Xianggui Yin Hongyun Zhong Lin Liu Junpeng Shi Xia Sun Yun Zhang State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou350002China Xiamen Key Laboratory of Rare earth Photoelectric Functional Materials Xiamen Institute of Rare Earth MaterialsHaixi InstituteChinese Academy of SciencesXiamen361021China Fujian Science and Technology Innovation Laboratory for Optoelectronic information of China Fuzhou350108China

X-ray-activated luminescence materials have broad application prospects in photodynamic therapy of deep *** them,X-ray-activated persistent luminescence materials(PLMs)exhibiting multiple emission peaks have drawn extensive attention for the ir capacity to achieve a combination of bioimaging and therapeutic ***,we developed a novel PLM,LiYgeo_4:Bi^(3+),Pr^(3+),that simultaneously exhibits UV and NIR dual persistent luminescence(PersL)emissions after irradiation by *** material can be re peatedly excited by X-ray and emits similar lumine scence intensity every time,which shows good PersL *** addition,LiYgeo_4:Bi^(3+),Pr^(3+)exhibits photostimulated PersL properties by stimulation with a red light-emitting diode(LED)or NIR laser after long-term *** work provides a new choice of X-ray-excited PLMs with UV and NIR dual emission and the novel phosphor shows promise as a potential candidate for the integration of treatment and diagnosis of deep tumors.

关键词： Co-doping X-ray-activated Dual emissions Persistent luminescence Rare earths

A novel(Sm_(0.2)Eu_(0.2)Gd_(0.2)Ho_(0.2)Yb_(0.2))CrO_(3)high-entropy ceramic nanofiber as a negative temperature coefficient thermistor

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Journal of Rare earths 2024年第10期42卷 1937-1942页

作者： Weijun Zhao Meng Zhang Liyan Xue Kaixian Wang Fan Yang Jiuping Zhong Heng Chen School of Materials Sun Yat-sen UniversityShenzhen518107China Xiamen institute of Rare earth Materials Haixi InstituteChinese Academy of SciencesXiamen361021China Xiamen Key Laboratory of Rare earth Photoelectric Functional Materials Xiamen Institute of Rare Earth MaterialsHaixi InstituteChinese Academy of SciencesXiamen361021China Fujian Science&Technology Innovation Laboratory for Optoelectronic information of China Fuzhou350108China Advanced Energy Science and Technology Guangdong Laboratory Huizhou516003China Sichuan Jcc Rare earth Metals New Material Co. Ltd.Chengdu610000China

The electrical properties of high-entropy ceramics(HECs)have been extensively studied in recent years due to their unique structural characteristics and fascinating functional properties induced by entropy *** high-entropy(Sm_(0.2)Eu_(0.2)Gd_(0.2)Ho_(0.2)Yb_(0.2))CrO_(3)(HE-RECrO_(3))nanofibers were prepared by electro *** work demonstrates that HE-RECrO_(3)nanofibe rs were successfully synthesized at a low temperature(800℃),which is approximately 400℃lower than the temperatures at which chromate ceramics were synthesized via the sol-gel method and the solid-state reaction *** resistivity of HE-RECrO_(3)nanofibers decreases exponentially with increasing temperature from 25 to600℃.The logarithm of the resistivity is linearly related to the inverse of the temperature,confirming the negative temperature coefficient property of HE-RECrO_(3)*** B_(25/50)value of the HERECrO_(3)nanofibers reaches 4072 *** conclusion,HE-RECrO_(3)nanofibers are expected to be potential candidates for negative-temperature-coefficient(NTC)thermistors.

关键词： Rare earths High-entropy ceramics Ceramic fiber materials Negative temperature coefficient thermistors

Numerical evaluations on the fluid production in the in-situ conversion of continental shale oil reservoirs

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Petroleum Science 2024年第4期21卷 2485-2501页

作者： Zhao-Bin Zhang Maryelin Josefina Brice?o Montilla Shou-Ding Li Xiao Li Jian-Peng Xing Yan-Zhi Hu Key Laboratory of Shale Gas and geoengineering Institute of Geology and Geophysics Chinese Academy of Sciences institute of earth Sciences Chinese Academy of Sciences College of earth and Planetary Sciences University of Chinese Academy of Sciences institute of Energy Peking University

In-situ conversion presents a promising technique for exploiting continental oil shale formations,characterized by highly fractured organic-rich rock. A 3D in-situ conversion model, which incorporates a discrete fracture network, is developed using a self-developed thermal-flow-chemical(TFC) *** of the model elucidates the in-situ conversion process in three stages and defines the transformation of fluids into three distinct outcomes according to their end stages. The findings indicate that kerogen decomposition increases fluid pressure, activating fractures and subsequently enhancing permeability. A comprehensive analysis of activated fracture permeability and heating power reveals four distinct production modes, highlighting that increasing heating power correlates with higher cumulative fluid production. Activated fractures, with heightened permeability, facilitate the mobility of heavy oil toward production wells but hinder its cracking, thereby limiting light hydrocarbon ***, energy efficiency research demonstrates the feasibility of the in-situ conversion in terms of energy utilization, especially when considering the surplus energy from high-fluctuation energy sources such as wind and solar power to provide heating.

关键词： In-situ conversion Continental shale oil Natural fracture network TFC model

Economic Risk Assessment of Future Debris Flows by Machine Learning Method

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International Journal of Disaster Risk Science 2024年第1期15卷 149-164页

作者： Chenchen Qiu Lijun Su Alessandro Pasuto Giulia Bossi Xueyu Geng School of Engineering University of WarwickCoventry CV47ALUK Key Laboratory of Mountain Hazards and earth Surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Research institute for geo-Hydrological Protection(IRPI-CNR) National Research Council of ItalyPadova 35127Italy

A reliable economic risk map is critical for effective debris-flow ***,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its *** estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability *** selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every *** debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual *** employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate ***,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical ***,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and *** economic loss of elements at risk was calculated based on physical vulnerabilities and their economic ***,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow *** this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on *** results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire *** findings can provide a scientific support for the effective mitigation of future debris flows.

关键词： Economic risk Future debris fows Gyirong Zangbo Basin Machine learning model Physical vulnerability matrix Southwest Tibet,China