Effect of lognormal particle size distributions on particle spreading in additive manufacturing

Additive manufacturing (AM) has attracted much attention worldwide in various applications due to its convenience and flexibility to rapidly fabricate products, which is a key advantage compared to the traditional subtractive manufacturing. This discrete element method (DEM) study focusses on the impact of particle polydispersity during the particle spreading process on parameters that affect the quality of the final product, like packing and bed surface roughness. The particle systems include four lognormal particle size distribution (PSD) widths, which are benchmarked against the monodisperse system with the same mean particle diameter. The results reveal that: (i) the solid volume fraction of the initial packed particle bed in the delivery chamber increases then plateaus as the PSD width increases; (ii) regardless of PSD width, the solid volume fraction of the particle bed increases with spreading layer height before compression, but decreases with layer height after compression; (iii) the bed surface roughness increases with PSD width or layer height both before and after the compression of the spreading layer; (iv) the extent of increase in solid volume fraction during compression is correlated with the extent of decrease in bed surface roughness; and (v) the broader PSDs exhibit larger fluctuations of solid volume fraction of the particle bed and bed surface roughness due to greater variability in the arrangement of particles of different sizes. The results here have important implications on the design and operation of particle-based AM systems.     

Effects of particle sizes on performances of the multi-zone steam generator using waste heat in a bio-oil steam reforming hydrogen production system

Hydrogen production by bio-oil steam reforming is an advanced production technology. It is a good method of coupling waste heat utilization with bio-oil steam reforming to produce hydrogen, which increases the cleaning ability of the bio-oil steam reforming system. A multi-zone steam generator using waste heat has been proposed, which can produce the heat source and steam source of the hydrogen system. The DEM model of the multi-zone steam generator was set up. The model has been used to investigate the effects of particle sizes (40 mm–80 mm). With increasing particle size, the flow index and the flow uniformity gradually decrease, the vertical velocity gradient increases in the area on both side with the zone steam generator, and the vertical velocity fluctuation amplitude gradually increases. So, the hydrogen production decreases from the particle size increasing.     

Full and reduced-order H∞ filtering of Takagi–Sugeno fuzzy time-varying delay systems: Input–output approach

This article addresses the issue of delay-dependent H_∞ filtering design for TakagiŮSugeno fuzzy time-varying delay systems using the input–output approach. A three-term approximation model has been used to transform the original system into two interconnected subsystems. Since the nonquadratic Lyapunov–Krasovskii functional requires to deal with the membership function's (MF) time derivative, upper-bound inequalities have been added to the obtained conditions. Based on the scaled small gain theorem, nonquadratic Lyapunov–Krasovskii functional approach and considering the bounds of the MF time-derivative, the H_∞ full- and reduced-order filters are designed and then formulated in terms of linear matrix inequalities. Finally, illustrative examples are presented to demonstrate the validity of the proposed methods.     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.     

Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems

This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid. First, a smart grid discrete system model is established in view of D-LAAs. Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid. The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack). A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs. Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks. Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations.     

Modeling of compressive strength of cemented sandy soil

This paper attempted to show the application of particle swarm optimization in the prediction of the compressive strength of cement sandy soil from the curing period, porosity of sample and percentage of cement. The results of the study show that the unconfined compressive strength of the cement stabilized sandy soil increases with an increasing cement content curing time period. Moreover the compressive strength decreases with an increasing porosity. The compressive strength improvement due to cement treatment has a larger increase in samples with less porosity. In addition, particle swarm optimization algorithm is and accurate technique in estimation of compressive strength of cement stabilized sandy soil. In order to compare of existing correlations, a total number of 100 unconfined compressive tests and 15 scanning electron microscope tests have been conducted on cemented Babolsar sand. It can be concluded that compared to existing correlations models, particle swarm optimization algorithm models give more reliable prediction about compressive strength of cement satblized sandy soil. Moreover, the sensitivity analysis of the polynomial model shows that cement content and porosity have significant impact on predicting unconfined compressive strength.     

喷泉景观的造型设计与模型研究

在分析现有喷泉模拟的基础上，针对喷泉造型的研究相对较少的问题，进行了喷泉造型设计并建模。运用多种数学曲线、曲面方程建立了复杂特殊的喷泉造型模型，并分析喷泉粒子的运动特性建立了喷泉运动模型。采用Visual Studio为编程工具，结合OpenGL技术渲染场景，在Windows XP环境下开发了基于粒子系统的喷泉模拟系统，仿真效果真实。     

Sources and dynamics of semivolatile organic compounds in a single‐family residence in northern California

Semivolatile organic compounds (SVOCs) emitted from building materials, consumer products, and occupant activities alter the composition of air in residences where people spend most of their time. Exposures to specific SVOCs potentially pose risks to human health. However, little is known about the chemical complexity, total burden, and dynamic behavior of SVOCs in residential environments. Furthermore, little is known about the influence of human occupancy on the emissions and fates of SVOCs in residential air. Here, we present the first‐ever hourly measurements of airborne SVOCs in a residence during normal occupancy. We employ state‐of‐the‐art semivolatile thermal‐desorption aerosol gas chromatography (SV‐TAG). Indoor air is shown consistently to contain much higher levels of SVOCs than outdoors, in terms of both abundance and chemical complexity. Time‐series data are characterized by temperature‐dependent elevated background levels for a broad suite of chemicals, underlining the importance of continuous emissions from static indoor sources. Substantial increases in SVOC concentrations were associated with episodic occupant activities, especially cooking and cleaning. The number of occupants within the residence showed little influence on the total airborne SVOC concentration. Enhanced ventilation was effective in reducing SVOCs in indoor air, but only temporarily; SVOCs recovered to previous levels within hours.     

卷取温度对超低碳T-3CA第二相析出的影响

 为研究卷取温度对超低碳T-3 CA中第二相粒子析出行为的影响，采用金相、TEM等检测手段，分析了580、630、680 ℃ 3个典型卷取温度下超低碳T 3 CA中第二相粒子的析出特性，结果发现卷取温度越高，热轧形成的TiC粒子尺寸越粗大，分布越稀疏。结合相关动力学计算分析了卷取温度对TiC粒子沉淀析出时临界晶核尺寸、相对形核率、相对沉淀析出时间的影响。结果表明，随着卷取温度由580提高到680 ℃，TiC粒子沉淀析出时临界晶核尺寸增大约1.0 nm，相对形核率降低约1.0个数量级，相对沉淀析出孕育时间增大约0.8个数量级。     

一种新的多渐消因子容积卡尔曼滤波

将强跟踪思想引入容积卡尔曼滤波（cubature Kalman filter，CKF），建立强跟踪CKF能有效克服CKF在模型不确定、状态突变等情况下，滤波性能下降的问题。通过分析现有多渐消因子计算方法，发现它们均只利用了协方差矩阵的对角线元素，并没有考虑各个状态之间的相关性，不能充分发挥多渐消因子的优势。为此，本文提出渐消因子矩阵，基于正交原理推导渐消因子矩阵的求解方法，提出多渐消因子强跟踪CKF算法。多渐消因子强跟踪CKF算法突破了传统多渐消因子为向量的限制，也不再要求渐消因子取值要大于1。仿真验证了算法具有更好的滤波精度何鲁棒性，能更好的满足工程应用的要求。