Excess pore pressure behavior and evolution in deep coalbed methane reservoirs

Deep coalbed methane(DCBM),an unconventional gas reservoir,has undergone significant advancements in recent years,sparking a growing interest in assessing pore pressure dynamics within these reservoirs.While some production data analysis techniques have been adapted from conventional oil and gas wells,there remains a gap in the understanding of pore pressure generation and evolution,particularly in wells subjected to large-scale hydraulic fracturing.To address this gap,a novel technique called excess pore pressure analysis(EPPA)has been introduced to the coal seam gas industry for the first time to our knowledge,which employs dual-phase flow principles based on consolidation theory.This technique focuses on the generation and dissipation for excess pore-water pressure(EPWP)and excess pore-gas pressure(EPGP)in stimulated deep coal reservoirs.Equations have been developed respectively and numerical solutions have been provided using the finite element method(FEM).Application of this model to a representative field example reveals that excess pore pressure arises from rapid loading,with overburden weight transferred under undrained condition due to intense hydraulic fracturing,which significantly redistributes the weight-bearing role from the solid coal structure to the injected fluid and liberated gas within artificial pores over a brief timespan.Furthermore,field application indicates that the dissipation of EPWP and EPGP can be actually considered as the process of well production,where methane and water are extracted from deep coalbed methane wells,leading to consolidation for the artificial reservoirs.Moreover,history matching results demonstrate that the excess-pressure model established in this study provides a better explanation for the declining trends observed in both gas and water production curves,compared to conventional practices in coalbed methane reservoir engineering and petroleum engineering.This research not only enhances the understanding of DCBM reservoir behavior but also offers insights applicable to production analysis in other unconventional resources reliant on hydraulic fracturing.

基于变形力监测数据的残余应力场推断和表征方法

残余应力是材料的基本属性之一,与零件的几何形状、尺寸稳定性和疲劳寿命直接相关。针对具有高精度要求的大型零件,其残余应力场的准确测量和预测一直是一个挑战。目前的残余应力场测量技术可以分为基于应变的破坏性方法和基于射线、声波等物理量的非破坏性方法,但均受限于测量效率和精度,且难以得到工件的整体残余应力场。针对以上问题,本文提出了一种基于加工过程中的变形力监测数据推断工件整体残余应力场的新方法。本方法通过能够反映去除材料后不平衡残余应力场整体效应的变形力推断零件的残余应力场。利用虚功原理建立了变形力与残余应力场之间的力学关系,并引入正则化方法求解整体残余应力场。理论验证和实际实验测试结果均表明,该方法对于大型结构件的残余应力场测量具有可靠的精度和灵活性。在数字化和智能制造的趋势下,该方法的基本原理为利用加工监测数据预测和补偿由残余应力引起的零件加工变形提供了重要参考。

Advanced Data Collection and Analysis in Data‑Driven Manufacturing Process

The rapidly increasing demand and complexity of manufacturing process potentiates the usage of manufacturing data with the highest priority to achieve precise analyze and control,rather than using simplified physical models and human expertise.In the era of data-driven manufacturing,the explosion of data amount revolutionized how data is collected and analyzed.This paper overviews the advance of technologies developed for in-process manufacturing data collection and analysis.It can be concluded that groundbreaking sensoring technology to facilitate direct measurement is one important leading trend for advanced data collection,due to the complexity and uncertainty during indirect measurement.On the other hand,physical model-based data analysis contains inevitable simplifications and sometimes ill-posed solutions due to the limited capacity of describing complex manufacturing process.Machine learning,especially deep learning approach has great potential for making better decisions to automate the process when fed with abundant data,while trending data-driven manufacturing approaches succeeded by using limited data to achieve similar or even better decisions.And these trends can demonstrated be by analyzing some typical applications of manufacturing process.

High-Speed EMUs:Characteristics of Technological Development and Trends

1.A worldwide history of high-speed trains High-speed railway(HSR)is defined by the International Union of Railways(UIC)as new lines with design speeds above 250 kmh1 and upgraded existing lines with speeds of up to 200 kmh1[1].In China,HSR is defined as new passenger-dedicated lines designed for electric multiple unit(EMU)trains running at a speed of 250 kmh1 or above(actual or reserved),with an initial operation speed not lower than 200 kmh1[2].The worldwide development of HSRs and high-speed EMUs can be roughly divided into three stages:initial operation,line platform expansion,and rapid development.

An mHealth intervention to improve medication adherence among patients with coronary heart disease in China: Development of an intervention

Objectives:With this study,we aimed to develop a mobile technology(mHealth)intervention to improve medication adherence among patients with coronary heart disease(CHD).Methods:The study was conducted in two phases with CHD patients from a Cardiology Department of a hospital located in China.Each phase was independent from the other.Phase 1 tested the integration of the two apps-"WeChat"and"BB Reminder"-as an mHealth intervention.All participants received the same educational materials via WeChat every two days.Participants in the experimental group received a reminder from BB Reminder for every dose of their medications.The duration of Phase 1 was 30 days for each participant.Phase 2 refined the intervention,in which educational materials were sent every five days rather than every two days,and medication-taking reminders were sent daily rather than every dose.Results:In Phase 1,an mHealth intervention was developed by integrating two mobile apps.In Phase 2,medication adherence increased at 30-day follow-up in both groups compared to baseline.At the 30-day follow-up,the mean of the decrease in medication non-adherence score in the experimental group(M=1.35,SD=2.18,n=36)was more than the decrease in control group(M=0.69,SD=1.58,n=36),which means the medication adherence improved more in the experimental group.Conclusion:The feasibility of using mHealth to remind CHD patients to take their medications is high.

Fatigue Characterization on a Cast Aluminum Beam of a High-Speed Train Through Numerical Simulation and Experiments

The cast aluminum beam is a key structure for carrying the body-hung traction motor of a high-speed train;its fatigue property is fundamental for predicting the residual life and service mileage of the structure.To characterize the structural fatigue property,a finite element-based method is developed to compute the stress concentration factor,which is used to obtain the structural fatigue strength reduction factors.A full-scale fatigue test on the cast aluminum beam is designed and implemented for up to ten million cycles,and the corresponding finite element model of the beam is validated using the measured data of the gauges.The results show that the maximum stress concentration occurs at the fillet of the supporting seat,where the structural fatigue strength reduction factor is 2.45 and the calculated fatigue limit is 35.4 MPa.Moreover,no surface cracks are detected using the liquid penetrant test.Both the experimental and simulation results indicate that the cast aluminum beam can satisfy the service life requirements under the designed loading conditions.

A non-uniform allowance allocation method based on interim state stiffness of machining features for NC programming of structural parts

For thin-walled parts,uniform allowance to each machining surface is allocated by the traditional machining method.Considering the sequence of the adjacent machining features,it may cause poor stiffness for some side walls due to a minor wall thickness,which may cause the deformation of the final formed parts to be large,or deduce machining efficiency for some machining features due to too thick remains.In order to address this issue,a non-uniform allowance allocation method based on interim state stiffness of machining features for the finishing of thin-walled structural parts is proposed in this paper.In this method,the interim state model of machining features is constructed according to the machining sequence of the parts,and the stiffness of the side wall is taken as the evaluation index to allocate reasonable allowance value to the corresponding machining surface to ensure the stiffness requirement of the parts in the machining process.According to the finite element simulation results,the non-uniform allowance allocation method proposed in this paper can effectively improve the stiffness of the parts and reduce the deformation of the parts,when compared with the traditional uniform allowance machining method.

An Initial Residual Stress Inference Method by Incorporating Monitoring Data and Mechanism Model

Initial residual stress is the main reason causing machining deformation of the workpiece,which has been deemed as one of the most important aspects of machining quality issues.The inference of the distribution of initial residual stress inside the blank has significant meaning for machining deformation control.Due to the principle error of existing residual stress detection methods,there are still challenges in practical applications.Aiming at the detection problem of the initial residual stress field,an initial residual stress inference method by incorporating monitoring data and mechanism model is proposed in this paper.Monitoring data during machining process is used to represent the macroscopic characterization of the unbalanced residual stress,and the finite element numerical model is used as the mechanism model so as to solve the problem that the analytic mechanism model is difficult to establish;the policy gradient approach is introduced to solve the gradient descent problem of the combination of learning model and mechanism model.Finally,the initial residual stress field is obtained through iterative calculation based on the fusing method of monitoring data and mechanism model.Verification results show that the proposed inference method of initial residual stress field can accurately and effectively reflect the machining deformation in the actual machining process.

Reinforcement learning method for machining deformation control based on meta-invariant feature space

Precise control of machining deformation is crucial for improving the manufacturing quality of structural aerospace components.In the machining process,different batches of blanks have different residual stress distributions,which pose a significant challenge to machining deformation control.In this study,a reinforcement learning method for machining deformation control based on a meta-invariant feature space was developed.The proposed method uses a reinforcement-learning model to dynamically control the machining process by monitoring the deformation force.Moreover,combined with a meta-invariant feature space,the proposed method learns the internal relationship of the deformation control approaches under different stress distributions to achieve the machining deformation control of different batches of blanks.Finally,the experimental results show that the proposed method achieves better deformation control than the two existing benchmarking methods.

A numerical investigation on deep shale gas recovery

In recent years,exploration and development of deep shale gas(at a burial depth of 3,500-4,500 m)has become a hotspot in the industry.However,the state of gas storage and transporting mechanism for deep shale gas under high pressure and temperature have not been thoroughly explored,compared with its shallower counterpart.A numerical model for deep shale gas recovery considering multi-site nonisothermal excess adsorption has been established and applied using Finite Element Method.Results from the simulation reveal the following.(1)Excess desorption significantly impacts early-stage performance of deep shale gas well;the conventional way for shallower shale gas development,in which the density of adsorbed gas is not distinguished from that of free gas,overestimates the gas in place(GIP).(2)Although thermal stimulation can speed up the desorption and transporting of deep shale gas,the incremental volume of produced gas,which is impacted not only by seepage velocity but also density of gas,is insignificant,far from expectation.Only an additional 2.03%of cumulative gas would be produced under treatment temperature of 190C and initial reservoir temperature of 90C in a period of 5 years.(3)Matrix porosity,which can be measured on cores in laboratory and/or estimated by using well logging and geophysical data,is the most favorable parameter for deep shale gas recovery.With 60%increase in matrix porosity,an extra 67.25%shale gas on a daily base would be recovered even after 5-year depletion production;(4)Production rate for gas wells in shale reservoirs at 3,500 m and 4,500 m deep would be raised by 5.4%in a 5-year period if the depth of target interval would increase by 340 m without thermal treatment according to the numerical model proposed in the study.

Food-Borne Poisoning Accident from Amanitin Toxin in Wild Mushrooms—Xingtai City,Hebei Province,China,2023

What is already known about this topic?Fatal poisonings caused by wild mushrooms containing amanita toxins pose a significant threat in the southern regions of China.These toxins primarily induce gastrointestinal symptoms initially,which are then followed by potentially life-threatening acute liver damage.What is added by this report?This report contributes to the existing knowledge on these cases of poisoning by documenting the second occurrences in Hebei Province and the first occurrences in Xingtai City.Five individuals reported consuming wild mushrooms from the same origin,and laboratory tests confirmed the presence ofα-amanitin in their blood samples.What are the implications for public health practice?This underscores the risk associated with the collection and consumption of amanita toxin-containing mushrooms in Hebei.It is important to note that the identification of toxic and non-toxic mushrooms should not solely rely on personal experience or appearance.

Learning neural operators on Riemannian manifolds

Learning mappings between functions(operators)defined on complex computational domains is a common theoretical challenge in machine learning.Existing operator learning methods mainly focus on regular computational domains,and have many components that rely on Euclidean structural data.However,many real-life operator learning problems involve complex computational domains such as surfaces and solids,which are non-Euclidean and widely referred to as Riemannian manifolds.Here,we report a new concept,neural operator on Riemannian manifolds(NORM),which generalises neural operator from Euclidean spaces to Riemannian manifolds,and can learn the operators defined on complex geometries while preserving the discretisation-independent model structure.NORM shifts the function-to-function mapping to finite-dimensional mapping in the Laplacian eigenfunctions’subspace of geometry,and holds universal approximation property even with only one fundamental block.The theoretical and experimental analyses prove the significant performance of NORM in operator learning and show its potential for many scientific discoveries and engineering applications.

Rapid intelligent evaluation method and technology for determining engineering rock mass quality

The evaluation of engineering rock mass quality is fundamental work for the engineering activities of rock mass.The increasing scale of rock mass engineering necessitates higher intelligence,timeliness,and accuracy in engineering rock mass quality evaluation.As the core aspects of engineering rock mass quality evaluation,the structural characteristics,mechanical characteristics,and quality classification of rock mass have been innovated in recent years.The non-contact measurement technology for rock mass structure and rapid interpretation of rock mass structure information enables the intelligent extraction and analysis of rock mass structure parameters.The modular backpack laboratory system of rock mechanics provides an effective means to acquire rock mechanical parameters on-site conveniently.The theory of statistical mechanics of rock mass(SMRM)integrates various factors such as the rock mass properties,geological environment,and engineering disturbance,providing a theoretical basis for accurately evaluating the weakening and anisotropy of rock mass.The cloud computing platform established based on SMRM can provide technical support for the rapid calculation of rock mass parameters and instant evaluation of the rock mass quality.The development of intelligent evaluation method and technology is altering the conventional technical state of qualitative and semi-quantitative evaluation of engineering rock mass quality,supporting the realization of rock mass engineering construction with intellectualization and informatization.

Insights into the mechanism of the deterioration of mainstream partial nitritation/anammox under low residual ammonium

Residual ammonium is a critical parameter affecting the stability of mainstream partial nitritation/anammox(PN/A), but the underlying mechanism remains unclear. In this study,mainstream PN/A was established and operated with progressively decreasing residual ammonium. PN/A deteriorated as the residual ammonium decreased to below 5 mg/L, and this was paralleled by a significant loss in anammox activity in situ and an increasing nitrite oxidation rate. Further analysis revealed that the low-ammonium condition directly decreased anammox activity in situ via two distinct mechanisms. First, anammox bacteria were located in the inner layer of the granular sludge, and thus were disadvantageous when competing for ammonium with ammonium-oxidizing bacteria(AOB) in the outer layer. Second, the complete ammonia oxidizer(comammox) was enriched at low residual ammonium concentrations because of its high ammonium affinity. Both AOB and comammox presented kinetic advantages over anammox bacteria. At high residual ammonium concentrations,nitrite-oxidizing bacteria(NOB) were effectively suppressed, even when their maximum activity was high due to competition for nitrite with anammox bacteria. At low residual ammonium concentrations, the decrease in anammox activity in situ led to an increase in nitrite availability for nitrite oxidation, facilitating the activation of NOB despite the dissolved oxygen limitation(0.15–0.35 mg/L) for NOB persisting throughout the operation. Therefore, the deterioration of mainstream PN/A at low residual ammonium was primarily triggered by a decline in anammox activity in situ. This study provides novel insights into the optimized design of mainstream PN/As in engineering applications.

信息化建设能够提升企业创新能力吗?——来自“两化融合试验区”的证据

本文基于2003—2015年A股上市公司数据,首次借助“两化融合试验区”的准自然实验,利用双重差分法评估了信息化建设对企业创新能力提升的影响。研究发现:信息化建设显著改善了企业专利质量,促进发明专利而非“短平快”的实用新型和外观设计专利显著增长。信息化建设仅提高了企业发明专利的产出效率,对其申请质量改善的影响并不明显。信息化建设主要通过机会识别、创新平台建设以及创新组织形式这三个渠道为企业创新活动赋能。

基于磁性纳米流体的中温太阳能吸收与光热转换性能

纳米流体基直接式吸收器被认为是进一步提高太阳能热利用效率的重要替代方案,但针对具有较高能源品位的中温太阳能吸收与光热转化性能的研究却较少.为促进中温太阳能光热的规模化应用,本文提出一种较为实用的中温磁性纳米流体基直接式吸收器吸收体系的使用方法.首先,通过“两步法”制备一种导热油基Co@NC中温磁性纳米流体,并利用其优异的光学吸收性能,在大功率模拟太阳光照射下获得较高温度的流体;然后,基于磁分离技术将Co@NC纳米颗粒与导热油基液分离,获得具有较高温度的纯基液;再经过换热器热交换过程得到所需要的各种较高温液体,在5个太阳辐射下,纳米流体最高温度可达120.37℃.该方法实现了较高的光热转换效率,同时可有效解决因纳米流体的不稳定性而引发沉降的问题,为促进纳米流体在太阳能中温热利用中的新发展提供了一种方案.

Expression of human cytomegalovirus components in the brain tissues of patients with Rasmussen＇s encephalitis

Rasmussen's encephalitis(RE) is a rare and severe progressive epileptic syndrome with unknown etiology. Infection by viruses, including human cytomegalovirus(HCMV), has been speculated to be a potential trigger for RE. However, no viral antigens have been detected in the brains of patients with RE; thus, a possible clinical linkage between viral infections and RE has not been firmly established. In this study, we evaluated the expression of HCMV pp65 antigen in brain sections from 26 patients with RE and 20 non-RE patients by immunohistochemistry and in situ hybridization, and assessed the associations between HCMV infection and clinical parameters.Elevated expression of HCMV pp65 protein and DNA was observed in 88.5%(23/26) and 69.2%(18/26) of RE cases, respectively. In the non-RE group, HCMV pp65 antigen was detected only in two cases(10%), both of which were negative for DNA staining. Additionally, the intensity of HCMV pp65 staining was correlated with a shorter duration of the prodromal stage, younger age of seizure onset, and more severe unilateral cortical atrophy. Elevated expression of HCMV pp65 was observed in RE brain tissue and was correlated with the clinical features of RE disease. In summary, our results suggested that HCMV infection may be involved in the occurrence and progression of RE disease. Thus, further studies are needed to determine whether early treatment with anti-HCMV antibodies could modulate the course of RE.

Five-axis flank milling tool path generation with curvature continuity and smooth cutting force for pockets

In order to ensure machining stability,curvature continuity and smooth cutting force are very important so as to meet the constraints of both cutting force and kinematics of machine tools.For five-axis flank milling,it is difficult to meet both of the constraints because tool path points and tool axis vectors interact with each other.In this paper,multiple relationships between tool path points and tool axis vectors with cutting force and kinematics of machine tools are established,and the strategies of corner-looping milling and clothoidal spirals are combined so as to find feasible solutions under both of the constraints.Tool path parameters are iterated by considering the maximum cutting force and the feasible range of the tool axis vector,and eventually a curvature continuity five-axis flank milling tool path with smooth cutting force is generated.Machining experimental results show that the conditions of cutting force are satisfied,vibration during the process of machining is reduced,and the machining quality of the surface is improved.

Experimental and computational assessment of 1,4-Dioxane degradation in a photo-Fenton reactive ceramic membrane filtration process

The present study evaluated a photo-Fenton reactive membrane that achieved enhanced 1,4-Dioxane removal performance.As a common organic solvent and stabilizer,1,4-Dioxane is widely used in a variety of industrial products and poses negative environmental and health impacts.The membrane was prepared by covalently coating photocatalyst of goethite(α-FeOOH)on a ceramic porous membrane as we reported previously.The effects of UV irradiation,H_(2)O_(2)and catalyst on the removal efficiency of 1,4-Dioxane in batch reactors were first evaluated for optimized reaction conditions,followed by a systematical investigation of 1,4-Dioxane removal in the photo-Fenton membrane filtration mode.Under optimized conditions,the 1,4-Dioxane removal rate reached up to 16%with combination of 2 mmol/L H_(2)O_(2)and UV365 irradiation(2000µW/cm^(2))when the feed water was filtered by the photo-Fenton reactive membrane at a hydraulic retention time of 6 min.The removal efficiency and apparent quantum yield(AQY)were both enhanced in the filtration compared to the batch mode of the same photo-Fenton reaction.Moreover,the proposed degradation pathways were analyzed by density functional theory(DFT)calculations,which provided a new insight into the degradation mechanisms of 1,4-Dioxane in photo-Fenton reactions on the functionalized ceramic membrane.

Digital and global lithologic mapping of the Moon at a 1:2,500,000 scale

Scientific knowledge of lunar lithologies was first acquired in the 1960s-1970s.The space race between the United States(U.S.)and Soviet Union has promoted numerous manned and robotic lunar exploration missions.Utilizing datasets from these missions,the first series of lunar geologic maps was prepared and published by the U.S.Geological Survey(USGS)The definition of lunar geological features in these maps was mostly based on morphological characteristics but lacked lithological constraints owing to the incompleteness of the compositional datasets avail-able.After two decades of silence,a new era of lunar exploration began in the 1990s when the Galileo spacecraft flew by the Moon during its gravity-assisted maneuvers.The very successful orbital missions,the Clementine and Lunar Prospector(LP),provided the first global geochemical and mineralogical(multispectral,gamma ray,neutron,etc.)datasets of the lunar surface.