齐大山铁矿南帮含水构造带探测研究

为解决采空区突发涌水给矿山安全生产带来的安全威胁,以齐大山铁矿为研究对象,以高密度电阻率法含水构造带理论模型的正演模拟研究为基础,运用高密度电阻率法对采场南帮含水构造带的异常范围进行了圈定;运用瞬变电磁法进行了二次探测,并对高密度电阻率法所圈定的异常范围进行了验证。研究表明:含水构造带显示为低阻异常特征,在高密度电阻率法探测成果图中显示的两处低阻异常与含水构造带理论模型的正演模拟结果一致;同时,在瞬变电磁法探测成果图中显示的低阻区域均在高密度电阻率法所圈定的低阻异常范围内,二者相互验证,这两处低阻异常均为含水构造带的地球物理异常特征的显示,表明采用高密度电阻率法和瞬变电磁法组合识别技术可实现对隐伏含水构造带的先导性探测。     

Forward contracts in electricity markets and capacity investment: A simulation study

This simulation study analyzes the effect of the introduction of forward markets to mitigate cyclical price behavior in electricity markets from a dynamic extended Cobweb model. We pay particular attention to the effect of lags in investment decisions and the effect of not fully replacing retired capacity in electricity markets. In line with previous research, the introduction of forward markets decreases price variability in comparison to a spot market. However, we also observe that lags in investment decisions and the failure to fully replace retired capacity create capacity investments cycles even in the presence a forward market.     

塔里木盆地哈拉哈塘地区二叠系火成岩体对下伏地层地震成像影响

塔里木盆地哈拉哈塘地区二叠系发育大规模火山活动，为准确了解厚层火山岩对下伏地层地震成像的影响，在实际钻测井资料及三维地震资料的基础上，建立寒武系—白垩系简化地质模型，并采用有限差分法求解弹性波波动方程，开展波动方程正演模拟，真实还原地震成像过程，明确二叠系火成岩体对下伏地层地震成像的影响，以期对哈拉哈塘地区古生界油气勘探开发起到一定的借鉴作用。结果表明：高速、高密度的二叠系英安岩对下伏地层地震成像有屏蔽作用，下伏地层反射波振幅强度相对于覆盖区外围明显减弱；由于岩性的横向突变，致使其下伏地层的地震成像形态发生明显变形及构造异常，而并非断裂带或火山通道的地震响应；杂乱反射带及火成岩下伏区域奥陶系大型缝洞集合体波场复杂，成像速度较难准确求取，存在偏移假象，“串珠状”地震反射难以收敛。     

A closed loop supply chain under retail price and product quality dependent demand

The importance of remanufacturing of used products, maintaining the same quality as new ones has been widely recognized in practice. In this paper, we address a closed loop supply chain where the manufacturer manufactures a product with a decent quality acceptable to customers, and sells it through a retailer in the market. A third party collects the used products from consumers and sends to the manufacturer. The manufacturer re-manufactures the used product and the quality of remanufactured product is the same as that of the manufactured one. For such a closed loop supply chain, we construct five different scenarios – centralized, decentralized or Nash game and three different Stackelberg games, led by the manufacturer, retailer and third party respectively. We compare the optimal results to find out the best decentralized scenario out of the four mentioned. A numerical example is taken to study the impacts of product quality on demand as well as optimal decisions and investigate sensitivity of some key model-parameters.     

Enhanced hollow fiber membrane performance via semi-dynamic layer-by-layer polyelectrolyte inner surface deposition for nanofiltration and forward osmosis applications

The layer-by-layer (LBL) polyelectrolyte deposited membranes have drawn increasing attention in various applications due to the ease of selective layer formation and their stability and versatility. In this study, the LBL deposition was performed at the inner surface of the polyethersulfone (PES) hollow fiber substrate to form composite nanofiltration (NF) membrane. The semi-dynamic deposition procedure was adopted with the aid of syringes. The newly developed inner deposited (id-LBL) membranes were then tested in NF and forward osmosis (FO) applications and the performance were compared with outer surface deposition as well as some literature data. The id-LBL membranes could not only withstand higher operating pressure but also possess superior hardness rejection especially in high concentration mixed salt solutions (more than 95% rejection to Mg²⁺ and Ca²⁺ in a 5000 ppm total dissolved salt (TDS) mixture under 4.8 bar). As for the FO process, with only two layer deposition, the id-LBL membranes also demonstrated significant performance improvement with increased water flux (up to 70 L/m² h using 0.5 M MgCl₂ as draw solution in active layer facing draw solution configuration) and reduced salt leakage (around 0.5 g/m² h using 1 M MgCl₂ draw solution in active layer facing feed water configuration). This study suggests that for hollow fiber substrate, the inner surface is more suitable for the formation of the selective layer via LBL deposition than the outer surface.     

Investigation on removing recalcitrant toxic organic polluters in coking wastewater by forward osmosis

Investigation was made on the efficiency of two commercial membranes in removing via forward osmosis (FO) the low molecular weight organic compounds typical of coking wastewater. The membranes were supplied by Poten and HTI companies. The organics in the simulated coking water were indole and pyrridine. Under FO mode, the rejection to the organics by Poten membrane was around 50%, whereas that for HTI membrane was obviously higher, ranging from 65% to 74%. The response of the two membranes in terms of Water flux and reverse salt flux (RSF) towards changing feed/draw solution (DS) flow rates in FO mode showed similar tendency, but different degree. Generally, the flux in FO using HTI membranes was lower. For HTI membrane, FO operated with pressure retarded osmosis (PRO) mode was also performed and the overall rejection of the organics was slightly lower than that in FO mode. In the long term FO test within 15 days, both Poten and HTI membranes displayed flux reduction and rejection enhancement. But the variation with Poten membrane was much more obvious. Discussion was carried out about the reasons and the mechanisms behind the FO performance difference between two membranes and the variation in flux and rejection with operation conditions. Characterizations by SEM, FTIR, AFM, XRD and XPS were tried to support the proposed explanations.     

Physics-informed deep learning for one-dimensional consolidation

Neural networks with physical governing equations as constraints have recently created a new trend in machine learning research.In this context,a review of related research is first presented and discussed.The potential offered by such physics-informed deep learning models for computations in geomechanics is demonstrated by application to one-dimensional(1D)consolidation.The governing equation for 1D problems is applied as a constraint in the deep learning model.The deep learning model relies on automatic differentiation for applying the governing equation as a constraint,based on the mathematical approximations established by the neural network.The total loss is measured as a combination of the training loss(based on analytical and model predicted solutions)and the constraint loss(a requirement to satisfy the governing equation).Two classes of problems are considered:forward and inverse problems.The forward problems demonstrate the performance of a physically constrained neural network model in predicting solutions for 1D consolidation problems.Inverse problems show prediction of the coefficient of consolidation.Terzaghi’s problem,with varying boundary conditions,is used as a numerical example and the deep learning model shows a remarkable performance in both the forward and inverse problems.While the application demonstrated here is a simple 1D consolidation problem,such a deep learning model integrated with a physical law has significant implications for use in,such as,faster realtime numerical prediction for digital twins,numerical model reproducibility and constitutive model parameter optimization.     

基于空间六自由度机械臂的逆运动学数值解法

针对解析法只能用于特殊构型的机械臂且求解过程复杂、计算量大的问题,提出一种适用于大多数串联型机械臂的数值迭代逆运动学求解方法.利用该方法,求解自主研发的空间六自由度机械臂的运动学逆解,并通过仿真证明该方法的可靠性.     

运输类飞机全机操纵系统功能检查试验技术研究及应用

运输类飞机驾驶舱位于机头内部,常规的试验加载设备难以固定,在全机操纵系统功能检查试验中如何准确地模拟飞行员对机械操纵装置加载成为该类试验亟待解决的问题。为了达到考核飞机结构静强度的同时实现舵面的功能检查,提出一种全新的全机静力试验舵面功能检查试验技术。通过驾驶盘双向大转角加载技术、基于响应的载荷谱自动切换技术及多向转角实时监测技术等模拟飞行员操纵过程及舵面受载情况,获得操纵力曲线及舵面响应曲线,成功解决了试验中的加载、控制及测量问题。最后以大型灭火/水上救援水陆两栖飞机操纵系统功能检查试验为研究对象,采用新方法顺利完成了试验,因此该方法满足试验要求。     

The Flexible Rare Event Sampling Harness System (FRESHS)

We present the software package FRESHS (http://www.freshs.org) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms.