微电流电解对尿素降解的机理及影响因素研究

采用微电流电解技术对模拟游泳池水中的尿素进行降解处理,探索了电解对尿素的去除机理,研究了电流密度和氯离子浓度等因素对电解去除尿素效果的影响。结果表明:以钌钛和不锈钢分别做阳极和阴极材料,当水溶液中有较高浓度的氯离子存在时,电解过程中产生的活性氯使得尿素被氧化,尿素降解产物中无氨氮、氯胺等二次污染物,尿素极有可能通过电解生成了N2等气体挥发到空气中。电流密度和氯离子浓度对尿素的去除效率有很大影响,随着电流密度和氯离子浓度的增加,尿素去除效率逐渐上升。在500 mg/L的氯离子浓度条件下,电流密度为12 m A/cm2时,电解处理30 min时尿素去除率可达99.5%。将微电流电解技术应用于游泳池水中的尿素去除,无需添加电解质,即能达到较高的尿素去除效果,采用该技术对游泳池水中的尿素进行降解去除完全可行。     

广西糖料蔗小管出流灌溉方式不同灌溉定额研究成果分析

通过小管出流灌溉方式,采用不同灌溉定额:150 m3/亩、250 m3/亩、350 m3/亩,研究不同灌溉定额条件下糖料蔗的出苗率、分蘖率、株高、茎粗、叶面积、蔗汁锤度、水分生存率、水分利用效益等糖料蔗生长指标。试验证明:糖料蔗对养分的吸收强度不仅与养分在土壤中的存在状态有关,还与甘蔗不同生长阶段的土壤水分、湿度有关。糖料蔗在不同的生长阶段对灌水量也有不同的要求,在不同时期对糖料蔗进行有效、合理的灌水,对糖料蔗的生长发育起着极其重要的作用。而在250 m3/亩灌溉定额条件下,更能促进糖料蔗的生长发育,从而提高糖料蔗的品质形状和产量。     

Physically Meaningful Rendering using Tristimulus Colours

In photorealistic image synthesis the radiative transfer equation is often not solved by simulating every wavelength of light, but instead by computing tristimulus transport, for instance using sRGB primaries as a basis. This choice is convenient, because input texture data is usually stored in RGB colour spaces. However, there are problems with this approach which are often overlooked or ignored. By comparing to spectral reference renderings, we show how rendering in tristimulus colour spaces introduces colour shifts in indirect light, violation of energy conservation, and unexpected behaviour in participating media. Furthermore, we introduce a fast method to compute spectra from almost any given XYZ input colour. It creates spectra that match the input colour precisely. Additionally, like in natural reflectance spectra, their energy is smoothly distributed over wide wavelength bands. This method is both useful to upsample RGB input data when spectral transport is used and as an intermediate step for corrected tristimulus‐based transport. Finally, we show how energy conservation can be enforced in RGB by mapping colours to valid reflectances.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Photoelasticity Raycasting

We present a novel physically‐based method to visualize stress tensor fields. By incorporating photoelasticity into traditional raycasting and extending it with reflection and refraction, taking into account polarization, we obtain the virtual counterpart to traditional experimental polariscopes. This allows us to provide photoelastic analysis of stress tensor fields in arbitrary domains. In our model, the optical material properties, such as stress‐optic coefficient and refractive index, can either be chosen in compliance with the subject under investigation, or, in case of stress problems that do not model optical properties or that are not transparent, be chosen according to known or even new transparent materials. This enables direct application of established polariscope methodology together with respective interpretation. Using a GPU‐based implementation, we compare our technique to experimental data, and demonstrate its utility with several simulated datasets.     

A Dimension‐reduced Pressure Solver for Liquid Simulations

This work presents a method for efficiently simplifying the pressure projection step in a liquid simulation. We first devise a straightforward dimension reduction technique that dramatically reduces the cost of solving the pressure projection. Next, we introduce a novel change of basis that satisfies free‐surface boundary conditions exactly, regardless of the accuracy of the pressure solve. When combined, these ideas greatly reduce the computational complexity of the pressure solve without compromising free surface boundary conditions at the highest level of detail. Our techniques are easy to parallelize, and they effectively eliminate the computational bottleneck for large liquid simulations.     

Implicit Formulation for SPH‐based Viscous Fluids

We propose a stable and efficient particle‐based method for simulating highly viscous fluids that can generate coiling and buckling phenomena and handle variable viscosity. In contrast to previous methods that use explicit integration, our method uses an implicit formulation to improve the robustness of viscosity integration, therefore enabling use of larger time steps and higher viscosities. We use Smoothed Particle Hydrodynamics to solve the full form of viscosity, constructing a sparse linear system with a symmetric positive definite matrix, while exploiting the variational principle that automatically enforces the boundary condition on free surfaces. We also propose a new method for extracting coefficients of the matrix contributed by second‐ring neighbor particles to efficiently solve the linear system using a conjugate gradient solver. Several examples demonstrate the robustness and efficiency of our implicit formulation over previous methods and illustrate the versatility of our method.     

Stabilization of Fractional‐Order Linear Systems with State and Input Delay

This paper describes a variable structure control for fractional‐order systems with delay in both the input and state variables. The proposed method includes a fractional‐order state predictor to eliminate the input delay. The resulting state‐delay system is controlled through a sliding mode approach where the controller uses a sliding surface defined by fractional order integral. Then, the proposed control law ensures that the state trajectories reach the sliding surface in finite time. Based on recent results of Lyapunov stability theory for fractional‐order systems, the stability of the closed loop is studied. Finally, an illustrative example is given to show the interest of the proposed approach.     

A Maximum Principle via Malliavin calculus for combined stochastic control and impulse control of forward‐backward systems

We consider a combined stochastic control and impulse control problem of forward‐backward systems driven by Lévy processes, where both the system coefficients and the objective performance functional are allowed to be random, non‐Markovian; the information available to the controller is partial information. Applying a Malliavin calculus approach, we derive a maximum principle for this control problem, where the adjoint processes are explicitly represented by the parameters and the states of the system. Finally, we give two examples of applications. © 2015 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd     

Networked Estimation of Multi‐Agent Systems Subject to Faults and Unreliable Information

In this paper, a novel framework for networked estimation of multi‐agent systems subject to presence of actuator faults is proposed. This framework is developed based on the notion of sub‐observers where within a group of sub‐observers each sub‐observer estimates certain states that are conditioned on a given input, output, and other state information. We model the overall estimation process by a weighted estimation (WE) digraph. By selecting an appropriate path in the WE digraph, an assigned supervisor can select and configure a set of sub‐observers to successfully estimate all the system states. In the presence of large intermittent disturbances, noise, and faults certain sub‐observers may become invalid, and consequently the supervisor reconfigures the set of sub‐observers by selecting a new path in the estimation digraph such that the impacts of these uncertainties are confined to only the local estimators. This will prevent the propagation of uncertainties on the estimation performance of the entire multi‐agent system. Simulation results provided for a five satellite formation flight system in deep space confirm the validity and applicability of our proposed analytical work.