Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

Effect of electrolysis superheat degree on anticorrosion performance of 5 Cu/（10NiO-NiFe2O4） cermet inert anode

5Cu/(10NiO-NiFe2O4) cermet inert anodes were prepared by cold-pressing and sintering process, and the effect of superheat degree of melting K3AlF6-Na3AlF6-AlF3 on their anticorrosion performance was studied under electrolysis conditions. The results show that, the fluctuation of cell becomes small with increasing of superheat degree, which is helpful to inhibit the formation of cathodic encrustation; the concentration of impurities from inert anode in bath goes up to certain degree, but it is far smaller than those in traditional high-temperature bath. Increasing the superheat degree of melting K3AlF6-Na3AlF6-AlF3 has unconspicuous effect on the contents of impurities in cathodic aluminum. The total mass fractions of Fe, Ni and Cu in aluminum are 15.38% and 15.09% respectively under superheat degree of 95 and 195 ℃. From micro-topography of anode used view, increasing the superheat degree can aggravate corrosion of metal Cu in inert anode, and has negative influence on electrical conductivity of electrode to some extent.     

基于互联网图像集的室外场景建模技术综述

目前在互联网上有海量的室外场景照片,它们不仅内容覆盖面广,对同一场景有大量不同视点和光照条件下的采样,而且获取成本很低.如何利用这些照片中包含的丰富场景信息,快速、方便地构造各种逼真的虚拟场景,是互联网迅猛发展给虚拟现实、计算机图形学和计算机视觉带来的新的研究课题之一.文中分析、总结了近年来国内外互联网图像的真实场景几何建模、自然光照建模和材质反射属性建模的最新研究进展,并对其未来的发展趋势提出了一些看法.     

环境荷载联合作用下海上风电结构动力响应分析

为研究海上风电结构在复杂的海洋环境中承受环境荷载(风、波、冰、流)的联合作用时,结构产生的剧烈的动力响应问题。文章以三脚架基础海上风电结构为研究对象,采用ANSYS有限元软件建立其整体模型并进行荷载(风、波、流和风、冰、流)联合作用下的静力校核,通过对环境荷载联合作用下的三脚架基础海上风电结构进行瞬态分析,掌握其动力响应的特性及规律。结果表明:三脚架基础结构的一、二阶自振频率均为0.285Hz,在所选风机允许的频率范围内,可以保证整体结构不会与风机转动发生共振;风荷载在风、波、流荷载联合作用下主导控制结构响应的稳态波动,冰荷载在风、冰、流荷载联合作用下主导控制结构的稳态振动过程;塔筒顶端呈现的位移和加速度响应均远大于三脚架基础顶端;环境荷载联合作用下结构动力响应是环境荷载单独作用下动力响应叠加的结果。     

Turbulent Details Simulation for SPH Fluids via Vorticity Refinement

A major issue in smoothed particle hydrodynamics (SPH) approaches is the numerical dissipation during the projection process, especially under coarse discretizations. High‐frequency details, such as turbulence and vortices, are smoothed out, leading to unrealistic results. To address this issue, we introduce a vorticity refinement (VR) solver for SPH fluids with negligible computational overhead. In this method, the numerical dissipation of the vorticity field is recovered by the difference between the theoretical and the actual vorticity, so as to enhance turbulence details. Instead of solving the Biot‐Savart integrals, a stream function, which is easier and more efficient to solve, is used to relate the vorticity field to the velocity field. We obtain turbulence effects of different intensity levels by changing an adjustable parameter. Since the vorticity field is enhanced according to the curl field, our method can not only amplify existing vortices, but also capture additional turbulence. Our VR solver is straightforward to implement and can be easily integrated into existing SPH methods.     

Digital twin modeling method based on biomimicry for machining aerospace components

High-performance aerospace component manufacturing requires stringent in-process geometrical and performance-based quality control. Real-time observation, understanding and control of machining processes are integral to optimizing the machining strategies of aerospace component manufacturing. Digital Twin can be used to model, monitor and control the machining process by fusing multi-dimensional in-context machining process data, such as changes in geometry, material properties and machining parameters. However, there is a lack of systematic and efficient Digital Twin modeling method that can adaptively develop high-fidelity multi-scale and multi-dimensional Digital Twins of machining processes. Aiming at addressing this challenge, we proposed a Digital Twin modeling method based on biomimicry principles that can adaptively construct a multi-physics digital twin of the machining process. With this approach, we developed multiple Digital Twin sub-models, e.g., geometry model, behavior model and process model. These Digital Twin sub-models can interact with each other and compose an integrated true representation of the physical machining process. To demonstrate the effectiveness of the proposed biomimicry-based Digital Twin modeling method, we tested the method in monitoring and controlling the machining process of an air rudder.     

Customer entrepreneurship on digital platforms: Challenges and solutions for platform business models

Drawing on the mixed methods of qualitative research and agent‐based simulation, this study examines: (a) how end‐users use digital platforms to become customer–entrepreneurs undertaking commercial activities on platforms; and (b) how platform providers can convert this customer entrepreneurship into a revenue stream. Considering that end‐users have traditionally been defined as passive and uncharged actors in platform business models, an in‐depth understanding of their commercial activities and the viable revenue model to monetize this emerging customer practice is warranted. Our qualitative study reveals that customer–entrepreneurs make substantial use of platform offerings to advertise their products; communicate with end‐consumers; and accept payments. These commercial activities are largely exercised for free on platforms, even though they could otherwise serve as a source of revenue. On this point, our simulation results identify two pricing models achieving the generation of nearly identical revenues over time. First, platform providers may charge both advertising and transaction fees, which maximize the survival of professional customer–entrepreneurs. Second, platform businesses may levy advertising fees only, which maximizes the survival of informal customer–entrepreneurs operating on a micro‐scale and part‐time basis. This study offers theoretical, methodological, and managerial implications for platform studies.     

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

This paper proposes a nodal ant colony optimization (NACO) technique to solve profit based unit commitment problem (PBUCP). Generation companies (GENCOs) in a competitive restructured power market, schedule their generators with an objective to maximize their own profit without any regard for system social benefit. Power and reserve prices become important factors in decision process. Ant colony optimization that mimics the behavior of ants foraging activities is suitably implemented to search the UCP search space. Here a search space consisting of optimal combination of binary nodes for unit ON/OFF status is represented for the movement of the ants to maintain good exploration and exploitation search capabilities. The proposed model help GENCOs to make decisions on the quantity of power and reserve that must be put up for sale in the markets and also to schedule generators in order to receive the maximum profit. The effectiveness of the proposed technique for PBUCP is validated on 10 and 36 generating unit systems available in the literature. NACO yields an increase of profit, greater than 1.5%, in comparison with the basic ACO, Muller method and hybrid LR-GA.     

基于滤波的SAR影像去噪方法分析

根据SAR(Synthetic Aperture Radar)影像相干噪声的特点,对现在广泛应用的各种抑制噪声的滤波方法如均值滤波、Frost滤波、增强型Lee滤波、Lee滤波、中值滤波等进行分析,并提出适合本研究区影像的基于小波变换的分量滤波处理去噪方法,利用均值、标准差、平滑指数、PM值、信息熵和平均梯度等评价指标对各种滤波去噪后的影像质量进行评价,并对去噪效果进行对比分析,证明本文所采用的滤波方法对SAR影像噪声有很好的抑制作用,并且较好的保存了图像纹理信息。     

选择性集成算法分类与比较

选择性集成是当前机器学习领域的研究热点之一。由于选择性集成属于NP"难"问题,人们多利用启发式方法将选择性集成转化为其他问题来求得近似最优解,因为各种算法的出发点和描述角度各不相同,现有的大量选择性集成算法显得繁杂而没有规律。为便于研究人员迅速了解和应用本领域的最新进展,本文根据选择过程中核心策略的特征将选择性集成算法分为四类,即迭代优化法、排名法、分簇法、模式挖掘法;然后利用UCI数据库的20个常用数据集,从预测性能、选择时间、结果集成分类器大小三个方面对这些典型算法进行了实验比较;最后总结了各类方法的优缺点,并展望了选择性集成的未来研究重点。