Systematic improvement in Tong's B-type water drive method

Tong's B-type water drive method was proposed as early as the 1970s and has been widely applied in the dynamic prediction and effective evaluation of oilfield development.Through extensive applications and studies,many researchers found that the statistical constants in the formula of the Tong's B-type water drive method(also referred to as the Tong's B-type formula)are not applicable to multiple types of reservoirs,especially low-permeability ones,due to the limited range of reservoir types when the formula was conceived.Moreover,they put forward suggestions to improve the Tong's B-type formula,most of which focused on the research and calculation of the first constant in the formula.For oilfields in the development stages of high or ultra-high water cuts,it is widely accepted that different types of reservoirs have different limit water cuts.This understanding naturally makes it necessary to further modify the Tong's B-type formula.It is practically significant to establish the water drive formula and cross plot considering that the two constants in the formula vary with reservoir type.By analyzing the derivation process and conditions of the Tong's B-type formula,this study points out two key problems,i.e.,the two constants 7.5 and 1.69 in the formula are not applicable to all types of reservoir.Given this,this study establishes a function between key reservoir parameters and the first constant and another function between key reservoir parameters and recovery efficiency.Based on the established two functions and considering that different types of oil reservoir have different limit water cuts,this study develops an improved Tong's B-type formula and prepares the corresponding improved cross plot.The results of this study will improve the applicability and accuracy of Tong's B-type water drive method in predicting the trend of water cut increasing for different types of oil reservoirs.

Evaluation of soil erosion vulnerability in Hubei Province of China using RUSLE model and combination weighting method

Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.

Research on the design method for uniform wear of shield cutters in sand-pebble strata

During shield tunneling in highly abrasive formations such as sand–pebble strata,nonuniform wear of shield cutters is inevitable due to the different cutting distances.Frequent downtimes and cutter replacements have become major obstacles to long-distance shield driving in sand–pebble strata.Based on the cutter wear characteristics in sand–pebble strata in Beijing,a design methodology for the cutterhead and cutters was established in this study to achieve uniform wear of all cutters by the principle of frictional wear.The applicability of the design method was verified through three-dimensional simulations using the engineering discrete element method.The results show that uniform wear of all cutters on the cutterhead could be achieved by installing different numbers of cutters on each trajectory radius and designing a curved spoke with a certain arch height according to the shield diameter.Under the uniform wear scheme,the cutter wear coefficient is greatly reduced,and the largest shield driving distance is increased by approximately 47%over the engineering scheme.The research results indicate that the problem of nonuniform cutter wear in shield excavation could be overcome,thereby providing guiding significance for theoretical innovation and construction of long-distance shield excavation in highly abrasive strata.

A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road.Traffic Sign Recognition System(TSRS)is one of themost important components ofADAS.Among the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time.Accordingly,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules.Firstly,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured frames.Secondly,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise recognition.In addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting technique.Through rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,respectively.Furthermore,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

Influence of adverse weather on drivers’ perceived risk during car following based on driving simulations

Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers'perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment.An expressway road scenario was built in a driving simulator.Eleven types of weather conditions,including clear sky,four levels of fog,four levels of rain and two levels of snow,were designed.Furthermore,to simulate the carfollowing behavior,three car-following situations were designed according to the motion of the lead car.Seven car-following indicators were extracted based on risk homeostasis theory.Then,the entropy weight method was used to integrate the selected indicators into an index to represent the drivers'perceived risk.Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk,and the coefficients were considered as indicators.The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior.Drivers'perceived risk tends to increase with the worsening weather conditions.Under conditions of extremely poor visibility,such as heavy dense fog,the measured drivers'perceived risk is low due to the difficulties in vehicle operation and limited visibility.

Force Control Compensation Method with Variable Load Stiffness and Damping of the Hydraulic Drive Unit Force Control System

Each joint of hydraulic drive quadruped robot is driven by the hydraulic drive unit（HDU）, and the contacting between the robot foot end and the ground is complex and variable, which increases the difficulty of force control inevitably. In the recent years, although many scholars researched some control methods such as disturbance rejection control, parameter self-adaptive control, impedance control and so on, to improve the force control performance of HDU, the robustness of the force control still needs improving. Therefore, how to simulate the complex and variable load characteristics of the environment structure and how to ensure HDU having excellent force control performance with the complex and variable load characteristics are key issues to be solved in this paper. The force control system mathematic model of HDU is established by the mechanism modeling method, and the theoretical models of a novel force control compensation method and a load characteristics simulation method under different environment structures are derived, considering the dynamic characteristics of the load stiffness and the load damping under different environment structures. Then, simulation effects of the variable load stiffness and load damping under the step and sinusoidal load force are analyzed experimentally on the HDU force control performance test platform, which provides the foundation for the force control compensation experiment research. In addition, the optimized PID control parameters are designed to make the HDU have better force control performance with suitable load stiffness and load damping, under which the force control compensation method is introduced, and the robustness of the force control system with several constant load characteristics and the variable load characteristics respectively are comparatively analyzed by experiment. The research results indicate that if the load characteristics are known, the force control compensation method presented in this paper has positive compensation effects on the load characteristics variation, i.e., this method decreases the effects of the load characteristics variation on the force control performance and enhances the force control system robustness with the constant PID parameters, thereby, the online PID parameters tuning control method which is complex needs not be adopted. All the above research provides theoretical and experimental foundation for the force control method of the quadruped robot joints with high robustness.

A Two-stage Tuning Method of Servo Parameters for Feed Drives in Machine Tools

Based on the evaluation of dynamic performance for feed drives in machine tools, this paper presents a two-stage tuning method of servo parameters. In the first stage, the evaluation of dynamic performance, parameter tuning and optimization on a mechatronic integrated system simulation platform of feed drives are performed. As a result, a servo parameter combination is acquired. In the second stage, the servo parameter combination from the first stage is set and tuned further in a real machine tool whose dynamic performance is measured and evaluated using the cross grid encoder developed by Heidenhain GmbH. A case study shows that this method simplifies the test process effectively and results in a good dynamic performance in a real machine tool.

The Practice Research of Task Driving Method in Basic Teaching of Information Technology

Purpose： It is used for judging the advantages and disadvantages of information technology foundation course teaching in health vocational colleges. Method： In teaching, it takes the two classes of 2012 grade nursing major as the experiment object. The comparison class adopts traditonal and speaking-practice combination teaching method and the experiment class adopts task-driving teaching method. When the semester finishes, it conducts testing andd questionnaire survey, collecting the relevant data, analyzing the changes of students in the aspects of performance, learning interest and attitude, autonomous learning consciousness and ability after experiment class adopting new teaching methods. Result： The exam performance of experiment class is obviously higher than the comparison class, and the experiment class has an obvious improvement in the aspects of learning interest, autonomous learning consciousness and ability, and the difference has statistical significance. Conclusion： The task driving teaching method is suitable for the status of information foundation teaching in health vocational colleges, which improves students＇ performance significantly and is good for students＇ learning interest and enthusiasm, obtaining good classroom effect. Also, it makes students＇ autonomous learning consciousness and ability improve greatly.

基于平纵组合的山区高速公路连续下坡路段行车安全评价方法

受制于地理和经济条件,山区高速公路在建设中不可避免会存在连续下坡路段,其中平纵组合路段对车辆稳定性和安全性提出了更高的要求。为分析山区高速公路连续下坡平纵组合路段的行车安全,利用西南山区高速公路数据,以80 km/h的设计速度,在连续下坡路段的不同位置、不同平纵组合工况构建了驾驶仿真实验。根据驾驶者的心理数据、车辆速度变化数据和横向偏移数据推出综合评价指标;将综合评价指标与平曲线半径和纵坡进行相关性分析;再通过累计频率图划分评价阈值;提出了基于平纵组合的连续下坡路段行车安全评价方法,并依托评价方法提出了连续下坡路段坡顶、坡中和坡底位置的平纵组合设计建议值;并以西南山区某高速公路为例对该评价方法进行了应用与验证。研究结果表明:该方法能为高速公路连续下坡路段的行车安全评价提供有效的参考依据。

基于优化地理探测器的生态环境质量驱动力分析

[目的]克服生态环境质量(EQI)演化驱动因子在离散化过程中的随机性和主观性,优化传统地理探测器。[方法]利用相等间隔法、分位数法、自然断点法、几何间隔法和标准差法5种离散方法,对重庆市22项EQI演化驱动因子进行离散化,并结合地理探测器确定各因子的合理离散法与分类数,从而探究各驱动因子的驱动力大小和各驱动因子间交互模式。[结果](1)2005—2020年重庆市EQI处于I、Ⅲ和Ⅳ级的区县数量占比减少0.211,处于Ⅱ和V级的区县数量占比上升0.211,总体呈下降趋势,在空间上呈由西北向东南走向的梯度分布特征。(2)研究中各离散方法适用性排序为:自然断点法>几何间隔法>分位数法>相等间隔法>标准差法。不同因子适用的离散方法各异,应根据因子数据特征择优选取离散方法。(3)识别出影响重庆市EQI演化的关键驱动因子4个(0.37~0.49),主要驱动因子13个(0.14~0.33)、次要驱动因子4个(0.05~0.13)和其他因子1个(0.04),各驱动因子间交互作用均为双重增强或非线性增强。[结论]合理的离散化可以一定程度上克服连续数据离散化过程中的随机性和主观性,从而优化重庆市EQI演化驱动力探测结果。

基于任务驱动的多糖制备工艺对其黏弹性影响综合实验教学设计

基于科教融合和成果导向(OBE)教育理念,将生化领域的前沿科技成果转化为教学实验,培养学生的科研创新素质。引入科研项目“多糖的制备工艺对其黏弹性能的影响”并贯穿教学全过程,引导学生查阅文献并讨论“耐温耐盐、环境友好新型驱油剂开发”的热点问题,拓宽学生的学术视野,培养学生文献查阅能力;鼓励学生根据自己的知识体系设计个性化实验方案,培养学生分析问题、解决问题的能力;指导学生探究利用盐醇析法和Sevage法制备多糖的工艺并计算其得率,采用红外和紫外光谱对样品进行表征,探究不同制备工艺对黏弹性及驱替效果的影响,帮助学生搭建“生物—化工—能源”多学科知识体系,提升实践创新能力;开展数据分析、方案评价和成果路演,锻炼学生的科研探究能力。

基于领航-跟随法的多机器人编队控制

编队控制是多机器人系统研究的核心问题之一,具有广泛的研究价值。针对编队问题,通过对轮式差分驱动机器人运动模型进行分析,并设计相应的控制器。在传统的领航-跟随模型上,引入“虚拟机器人”,将跟随者机器人对领航者机器人的轨迹跟踪转换为跟随者对“虚拟领航者”的轨迹跟踪。首先,预设定实际领航者机器人的行进路径,由实际领航者引导运动方向的运动轨迹被视为主轨迹,虚拟机器人通过数据产生参考点从而生成参考轨迹,跟随者机器人通过对参考轨迹的跟踪与“虚拟领航者”构成轨迹误差跟踪系统。然后通过Lyapunov的控制理论验证控制器的理论可行性,最后在MATLAB/Simulink仿真平台进行实验,通过改变控制参数来使机器人形成相应的期望队形,在较短的时间内,跟随机器人对参考轨迹的跟踪误差趋向于0且速度收敛,验证了编队系统的可行性。

中国绿色创新效率空间关联网络特征及其驱动因素研究

运用基于序列DEA的SE-U-SBM模型测度我国30个省份2007—2019年绿色创新效率,利用修正的引力模型和社会网络分析方法解构了我国省际绿色创新效率的空间关联特征,并借助QAP方法探讨了绿色创新效率空间关联网络的驱动因素。研究结果显示:(1)我国省际绿色创新效率上升趋势明显,呈现东部>中部>西部的空间分布格局。(2)中国绿色创新效率的空间关联呈现出复杂的多线程空间网络关联关系,省际绿色创新效率的关联性不断加强,空间关联网络稳定性进一步增强,东部省份大多属于净溢出板块,中西部省份为相对受益板块。(3)地理距离、城镇化水平差异、人力资本差异、财政分权差异、相近的R&D投入强度和资源禀赋差异是影响我国绿色创新效率空间关联网络形成与发展的重要驱动因素,对绿色创新效率空间关联网络具有显著的促进作用。应着力推动要素市场化改革,破除区域市场分割和行政壁垒,加强区域政策协调性,实现绿色创新效率协同提升。

基于DPSIR模型的秦岭北麓陕西城市群水安全评估及驱动因子识别

水安全评估是水资源开发利用与区域发展的基础。为了加强秦岭北麓陕西城市群可持续建设,助力秦岭“中央水塔”绿色发展,基于DPSIR模型构建秦岭北麓陕西城市群水安全评估体系,结合主客观综合赋权法与模糊综合评价法对区域2011~2021年水安全进行评估分级,并利用灰色关联度法分析其水安全的驱动因子。结果表明:秦岭北麓陕西城市群2011~2021年水安全状态变化具有一致性,波动中稳步提升。西安市水安全等级相较宝鸡市、渭南市上升趋势显著,于2021年转为无警状态;宝鸡市一直保持低警状态,而渭南市长期处于中警状态。陕西城市群的水安全状态及发展趋势与人均GDP、年降水量、人均用水量等10个驱动因子密切相关,其中经济因子是水安全等级呈现一致性的根本保证,社会和生态因子则是造成水安全差异性的主要原因。

船式拖拉机直线工作参数优选研究

为提高船式拖拉机驱动性能,以单轮叶为研究对象,结合离散元法搭建了仿真模型与土槽试验平台,分析单轮叶与土壤的直线作业机理。验证仿真模型的有效性后,从单轮叶与土壤作业过程出发,对单轮叶直线作业过程受力进行了分析,发现单轮叶推进力和支撑力均随着转过角度的增加呈现先增加后降低的趋势变化。以单轮叶推进力和扭矩作为评价指标,探究单轮叶工作参数对驱动性能的影响规律,通过多因素法得到最佳的工作参数组合。研究结果表明:最优工作参数组合为入土角度11°、入土深度147mm、前进速度1.6m/s,此时轮叶推进力为172.51N、扭矩为69.82N·m,优化后的单轮叶推进力提高了40.82N,扭矩下降了34.77N·m。土槽试验表明:优化后的单轮叶损耗功率降低明显,驱动性能得到了有效提高,结果为船式拖拉机工作参数选择提供了理论依据。

以岗位胜任力为导向的中医脑病住院医师规范化培训教学探析

以岗位胜任力为导向的理论和方法用于住院医师规范化培训,是提升临床医师专业素质和培养合格医疗人才的关键方法。如何运用有效的手段提升中医脑病住院医师规范化培训学员的岗位胜任力仍需要进一步探索与研究。本文基于脑病科住培医师培训实践,构建授课教学法(LBL)-案例教学法(CBL)-问题教学法(PBL)-研究教学法(RBL)“四轨并驱”的教学策略,提出以岗位胜任力为导向的中医脑病住培医师的培训方法,以期提高中医脑病专业住培医师的岗位胜任力,从而为临床锻炼出更为优秀的医疗队伍,使之更加符合新时代医疗工作的要求,也更好地提升中医住院医师的整体水平。

智慧农业发展水平测度及驱动力比较——基于产业融合的视角

基于国际与国内区域投入产出表,从产业融合视角对智慧农业发展水平进行度量,并开展国际、国内区域的比较。结果显示:中国智慧农业的发展与发达国家相比存在较大差距,机械化及数字化相关产业对农业的发展的驱动效果偏低;我国智慧农业发展区域异质性明显,山西等地科研服务类产业驱动力偏低,而内蒙古等地则数字化驱动力不足。应大力提升农业数字化发展水平、提升农业从业人员基本素质、加速突破核心关键性技术,制定具有区域特征的发展策略。

北方寒冷地区交通碳排放驱动因素分析

北方地区气候寒冷,交通工具燃油效率低、车内加热需求增加及路面积雪结冰等复杂道路条件导致交通碳排放增加。因此,有必要针对寒冷地区的交通碳排放驱动因素进行分析,识别关键因素,并有针对性地降低碳排放。以典型北方寒冷地区黑龙江省为例,采用Tapio脱钩测度模型及GDIM因素分解法对2006—2021年黑龙江省交通行业碳排放驱动因素展开分析,分解得到8个驱动因素并发现其脱钩状态呈现“强脱钩-扩张负脱钩-强脱钩”,其中交通产值碳强度和单位交通行业产值的能耗促进脱钩,交通行业总产值和总周转量阻碍脱钩;另外交通行业总产值、能源消耗量对碳排放有较强的促进作用,交通产值碳强度和单位交通行业产值的能耗对碳排放有较强的抑制作用。

机场群场面碳排放时空特征和驱动因素分析

以减少场面碳排放为目标,为航空器滑行路径优化提供理论依据,对川渝地区机场群场面碳排放量的时空特征及驱动因素进行了分析,并提出相应的减排策略。基于历史航班数据采用局部空间关联指数时间路径模型对机场群场面碳排放的时空特征进行了分析,得出机场群场面碳排放的空间结构动态趋势;利用对数平均狄氏指数分解法对天府机场场面碳排放的驱动因素进行驱动效应分析,得到场面碳排放受客均座位数和城市连通数作用显著的结论。所提方法为机场场面滑行路径优化以及航班时刻的合理调整提供了理论研究基础,也可为机场相关单位提供节能减排策略的依据。

智能网联汽车超车路径规划方法

针对自动驾驶车辆超车路径规划的问题,本文提出改进的人工势场法并引入相对速度构建新的引力势场和斥力势场.建立道路边界势场规范行车区域,对障碍物的影响距离进行分段解决局部极值问题,将自动驾驶车辆动力学相关约束融入人工势场法建立超车路径行驶势场模型.选取重庆市内环快速路为试验路网原型,利用无人机以及定点摄像等数据采集方法进行实地调查,并采用MATLAB/Simulink,CarSim和PreScan进行联合仿真分析.实验结果表明:相比传统的人工势场法,在前车静止、前车匀速、前车减速这3种条件下的超车路径曲率分别降低了85.07%,62.69%和83.86%,横向加速度均小于0.13m/s^(2),改进后的路径规划算法可成功实现平稳超车,驾乘人员的舒适性上有显著提升.