Framework to manage multiple goals in community-based energy sharing network in smart grid

Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.     

Study of metal assisted anisotropic chemical etching of silicon for high aspect ratio in crystalline silicon solar cells

Textured surface is commonly used to enhance the efficiency of silicon solar cells by reducing the overall reflectance and improving the light scattering. In this study, a comparison between isotropic and anisotropic etching methods was investigated. The deep funnel shaped structures with high aspect ratio are proposed for better light trapping with low reflectance in crystalline silicon solar cells. The anisotropic metal assisted chemical etching (MACE) was used to form the funnel shaped structures with various aspect ratios. The funnel shaped structures showed an average reflectance of 14.75% while it was 15.77% for the pillar shaped structures. The average reflectance was further reduced to 9.49% using deep funnel shaped structures with an aspect ratio of 1:1.18. The deep funnel shaped structures with high aspect ratios can be employed for high performance of crystalline silicon solar cells.     

Strain engineering for thermal conductivity of single-walled carbon nanotube forests

We perform classical molecular dynamics simulations to investigate the mechanical compression effect on the thermal conductivity of the single-walled carbon nanotube (SWCNT) forest, in which SWCNTs are closely aligned and parallel with each other. We find that the thermal conductivity can be linearly enhanced by increasing compression before the buckling of SWCNT forests, but the thermal conductivity decreases quickly with further increasing compression after the forest is buckled. Our phonon mode analysis reveals that, before buckling, the smoothness of the inter-tube interface is maintained during compression, and the inter-tube van der Waals interaction is strengthened by the compression. Consequently, the twisting-like mode (good heat carrier) is well preserved and its group velocity is increased by increasing compression, resulting in the enhancement of the thermal conductivity. The buckling phenomenon changes the circular cross section of the SWCNT into ellipse, which causes effective roughness at the inter-tube interface for the twisting motion. As a result, in ellipse SWCNTs, the radial breathing mode (poor heat carrier) becomes the most favorable motion instead of the twisting-like mode and the group velocity of the twisting-like mode drops considerably, both of which lead to the quick decrease of the thermal conductivity with further increasing compression after buckling.     

Fabrication and microwave absorption properties of magnetite nanoparticle–carbon nanotube–hollow carbon fiber composites

Absorbents with “tree-like” structures, which were composed of hollow porous carbon fibers (HPCFs) acting as “trunk” structures, carbon nanotubes (CNTs) as “branch” structures and magnetite (Fe₃O₄) nanoparticles playing the role of “fruit” structures were prepared by chemical vapor deposition technique and chemical reaction. Microwave reflection loss, permittivity and permeability of Fe₃O₄–CNTs–HPCFs composites were investigated in the frequency range of 2–18 GHz. It was proven that prepared absorbents possessed the excellent electromagnetic wave absorbing performances. The bandwidth with a reflection loss less than −15 dB covers a wide frequency range from 10.2 to 18 GHz with the thickness of 1.5–3.0 mm, and the minimum reflection loss is −50.9 dB at 14.03 GHz with a 2.5 mm thick sample layer. Microwave absorbing mechanism of the Fe₃O₄–CNTs–HPCFs composites is concluded as dielectric polarization and the synergetic interactions exist between Fe₃O₄ and CNTs–HPCFs.     

(S)-6-乙烯基-2,2'-二甲氧基-1,1'-联萘的合成

以S-1,1'-联二苯酚为起始原料,通过多步反应合成了标题化合物。该联萘酚通过羟基保护、傅克酰基化、羰基的还原和卤代烃的消除反应制备得到目标产物。对实验条件进行了适当改进,找到了较好的合成条件,并用1HNMR和13CNMR对各步产物进行了表征。     

Electromagnetic shielding properties of iron oxide impregnated kenaf bast fiberboard

The electromagnetic shielding effectiveness of kenaf fiber based composites with different iron oxide impregnation levels was investigated. The kenaf fibers were retted for removing the lignin and extractives from the fibers and magnetized. Using the unsaturated polyester and the magnetized fibers, kenaf fiber based composites were manufactured by the compression molding process. The transmission energies of the composites were characterized when the composite samples were exposed under the irradiation of electromagnetic (EM) wave with a variable frequency from 9 GHz to 11 GHz. Using the Scanning Electron Microscope (SEM), the iron oxide nanoparticles were observed on the surfaces and inside the micropore structures of single fibers. As the Fe content increased from 0% to 6.8%, 15.9% and 18.0%, the total surface free energy of kenaf fibers with the magnetizing treatments increased from 44.8 mJ/m² to 46.1 mJ/m², 48.8 mJ/m² and 53.0 mJ/m², respectively, while the modulus of elasticity reduced from 2875 MPa to 2729 MPa, 2487 MPa and 2007 MPa, respectively. Meanwhile, the shielding effectiveness was increased from 30–50% to 60–70%, 65–75% and 70–80%, respectively.     

Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.