Post-irradiation hardness of resin-modified glass ionomer cements and a polyacid-modified composite resin

This study examined the post-irradiation hardness of resin-modified glass ionomer cements and a polyacid-modified composite resin using a digital microhardness tester. Change in hardness of these materials over a period of 6 months was compared to that of conventional glass ionomer cements and a composite resin. With the exception of the composite resin, all materials showed a significant increase in hardness over 24 h after their initial set. Dual-cure resin-modified glass ionomer cements showed decreased hardness with increased storage time in saline at 37°C. Results suggest that the addition of resins to glass ionomer cements does not improve initial hardness and does not negate the acid-base reaction of conventional cements. Resin addition may, however, lead to increased water sorption and decreased hardness.     

A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumer electrical appliances classification

The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the V-I trajectory. The classification algorithm performs cropping and image pyramid reduction of the V-I trajectory plot template images before utilizing the principal component analysis (PCA) and the k-nearest neighbor (k-NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through V-I trajectory-based load signature images by utilizing a multi-stage classification algorithm methodology. The contribution of this paper is in utilizing the “k-value,” the number of closest data points to the nearest neighbor, in the k-NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.     

A generic approach of integrating 3D models into virtual manufacturing

Various 3D modeling software has been developed for design and manufacturing.Most of the commercially available software uses native file formats,which may not be able to be read or understood by other...     

A systematic approach to ON-OFF event detection and clustering analysis of non-intrusive appliance load monitoring

The aim of non-intrusive appliance load monitoring (NIALM) is to disaggregate the energy consumption of individual electrical appliances from total power consumption utilizing non-intrusive methods. In this paper, a systematic approach to ON-OFF event detection and clustering analysis for NIALM were presented. From the aggregate power consumption data set, the data are passed through median filtering to reduce noise and prepared for the event detection algorithm. The event detection algorithm is to determine the switching of ON and OFF status of electrical appliances. The goodness-of-fit (GOF) methodology is the event detection algorithm implemented. After event detection, the events detected were paired into ON-OFF pairing appliances. The results from the ON-OFF pairing algorithm were further clustered in groups utilizing the K-means clustering analysis. The K-means clustering were implemented as an unsupervised learning methodology for the clustering analysis. The novelty of this paper is the determination of the time duration an electrical appliance is turned ON through combination of event detection, ON-OFF pairing and K-means clustering. The results of the algorithm implementation were discussed and ideas on future work were also proposed.     

郑州某超高层空调系统设计

简要介绍郑州市某栋综合体超高层的冷热源,空调、采暖、通风、防排烟、节能环保及计量,同时讨论空调水系统压力分区,冷冻水大温差。     

HIGH-PROTEIN RICE-SOYA BREAKFAST CEREAL

The effect of three particle sizes and three different percentages of full-fat soya flour was studied for development of a high-protein rice-soya based reakfast cereal. Proximate analysis, essential amino acid profile, percentage water-holding capacity (WHC), crispiness and sensory evaluations were carried out for formulated flakes. The substitutions of 10, 20 and 30% full-fat soya flour for rice flour achieved good essential amino acid profiles but only the formuations with 20 and 30% soya flour qualified as high-protein flakes as reflected by their protein-calorie ratios (PCR) of approximately 15 and 19, respectively. The WHC of flakes was not affected by the percentage of soya flour used for the coarse (710 μm) and the medium (500 μm) particle size soya flour. The WHC of flakes formulated from fine (355 μm) particle size soya flour increased with the percentage of soya flour used. Crispness of flakes generally decreased with increasing percentage of soya flour at the 20 and 30% level. An inversely proportional relationship between crispiness and the particle size of soya flour was observed at the 30% level of substitution. Panelists did not show any trend in the overall preference of flakes developed.     

A generic approach of integrating 3D models into virtual manufacturing

Various 3D modeling software has been developed for design and manufacturing.Most of the commercially available software uses native file formats,which may not be able to be read or understood by other software.This paper deals with the development of a generic approach of a 3D model conversion program for virtual manufacturing(VM),using a lexical analyzer generator Lex and the Open Graphic Library(OpenGL).The program is able to convert 3D mesh data between four universal file formats,i.e.,Stereolithography(STL),Virtual Reality Modeling Language(VRML),eXtensible Markup Language(XML),and Object(OBJ).Simple assembly functions can be applied to the imported models.The quaternion angle is used for object rotation to overcome the problem of gimbal lock or a loss of one degree of rotational freedom.The program has been validated by importing the neutral format models into the program,applying the transformation,saving the new models with a new coordinate system,and lastly exporting into other commercial software.The results showed that the program is able to render and re-arrange accurately the geometry data from the different universal file formats and that it can be used in VM.Therefore,the output models from a VM system can be transferred or imported to another VM system in a universal file format.     

可靠性、可用性与可维修性分析在LNG接收站产能预测中的应用

LNG设施通常包括天然气液化、LNG储运及运输等。在中国天然气供应链对经济民生影响重大。天然气供应链或供应系统中关键设备的非计划及计划性维修导致的天然气供应中断,都可能造成巨大的经济损失。本项目应用可靠性、可用性及可维修性(RAM)分析方法对于液化天然气储备库及附属设施的可靠性指标进行评估,定量分析LNG供应链中关键设备的失效及维修时间对于整个供应链可靠性指标的影响。RAM分析可以用来预测在指定的运行周期内整个LNG供应链的运行绩效。RAM分析辨识关键设备的失效模式,确定失效数据,并采取Monte Carlo的模拟计算,获得LNG供应链或系统中,关键设备失效对于可靠性指标影响。本文通过国内某LNG储备库项目的RAM分析,应用以Monte Carlo模拟为基础的系统可靠性分析软件ReliaSuite^®,评估LNG储备库系统设计能否满足可靠性指标。并且对LNG储运设施的卸料臂进行了失效模式及关键性影响分析(FMECA)。通过对LNG储备库各子系统对于项目整体可靠性的贡献进行敏感性分析,找到影响项目整体可靠性的瓶颈及解决方案。