Analysis of the best roughness surface based on the bearing area curve theory

An in-depth study of friction and wear requires analysis of the surface morphologies and contact status of friction pairs in mechanical systems. The bearing area curve is introduced for the calculation of wear, and combined with the concept of repositioning. The application of fast calculation of wear amount and improved three-dimensional characterization of a bearing area curve is achieved by this new method. The best roughness surface is used as the target surface to extract the target bearing area curve. The influence of microtexture parameters on the bearing area curve is studied to determine the optimal microtexture parameters. The test results show that a matching texture surface has a short run-in time and the lowest friction coefficient after stabilization among the surfaces studied herein, and the presence of a texture changes the wear mechanism from the original adhesive wear to abrasive wear and improves the tribological performance. The best texture parameters and laser process parameters are determined, which provide new ideas for the optimal design of surface topography.

Prediction of Contact and Lubrication Characteristics of Micro-textured Surface Under Thermal Line Contact EHL

In this study, a method combining numerical surface generation technology and three-dimensional hot-line contact EHL is employed to evaluate the contact characteristics of micro-textured surfaces under high-load line contact. Based on numerical simulation, the film thickness, film pressure, friction coefficient and surface flashing temperature of the virtual texture surface with different cross-sectional shapes and sizes are studied. On this basis, the subsurface stress at the contact point is calculated by the DC-FFT algorithm. The results show that, compared with a smooth surface, the micro-textures of different shapes all increase the average oil film thickness of the surface and reduce the friction coefficient, but at the same time lead to an increase in the contact stress of the surface. By changing the width and depth of the texture, the maximum film pressure has changed by 11.4 and 18.5%, respectively.

Improvement of N-Type Crystalline Silicon Solar Cell Performance Using Novel Texturization Method.

Texturization of diamond cut crystalline silicon wafers undergoes a great difficulty due to deep saw marks on all over the surface of the wafer which makes hindrance to manufacture high efficiency solar cell. Textural result is not satisfactory after conventional texturization by potassium hydroxide (KOH)-isopropyl alcohol (IPA) followed by the saw damage removal by sodium hydroxide (NaOH) aqueous solution. The non-uniform texture surface has been observed with noticeable spots on the wafer surface. Surface texturization of diamond cut silicon wafer has been improved after introducing a new method in this paper. Small amount of surfactant along with KOH-IPA solution and curtailing saw damage removal step created better textural result than conventional texturization method. Optimize etching solution exhibited excellent anisotropic etching which eventually paved to improve solar cell characteristics than conventional surface texturing. About 15% efficiency is found for conventional texturization in diamond cut wafers while above 19% efficiency was found for our proposed method. Batch process compatibility has been studied using stainless steel container instead of commercially available borosil glass bath.

Physicochemical Properties and Sensory Acceptability of a Next-Generation Functional Chocolate Added with Omega-3 Polyunsaturated Fatty Acids and Probiotics

In this study, a milk chocolate formulation was developed to serve as vehicle of Omega-3 (ω3) polyunsaturated fatty acids (PUFAs) and probiotics (L. plantarum 299v and L. rhamnosus GG). Fish oil (FO) was incorporated in chocolate as a source of ω3 PUFAs. Probiotics (Prob) and FO were added during tempering, obtaining chocolates with 76.0 ± 5.2 mg (FO1) or 195.8 ± 6.5 mg (FO2) of ω3 PUFAs, and >1 × 106 CFU of Prob per chocolate portion (12 g). The physicochemical properties (rheological analysis, texture, surface instrumental color, aw, and fatty acid profile), and sensory acceptability of the formulations were determined. Prob and FO generated a decrease in L* and white index (WI) values. Except for Prob + FO2, all treatments showed a decrease in aw. Rheological parameters of FO1 and Prob + FO1 presented the most similar behavior as compared with the control. Prob or FO1 addition did not affect the overall consumer’s acceptability of chocolate; and when both nutraceuticals were combined (Prob + FO1) the product showed adequate overall acceptability. FO2 formulations were not considered adequate to maintain physicochemical properties and sensory acceptability of chocolate. Results indicated that milk chocolate is a suitable vehicle for delivering ω3 PUFAs and Prob, which are essential to enhance cognitive development in children.

Classificação e mapeamento da textura superficial do solo a partir de dados de sensoriamento remoto e análise discriminante, na região de Volta Grande do Rio Uruguai – Brasil

Medir e avaliar componentes e propriedades de solo são geralmente procedimentos que envolvem custo e consumo de tempo. A escassez de amostragem de dados em campo é geralmente compensada por resultados de predição e modelagem cujos procedimentos são conhecidos como mapeamento preditivo de solo. O objetivo deste trabalho é obter um mapa da textura superficial do solo na região de Volta Grande do Rio Uruguai (SC/RS-Brasil) por meio de amostragem granulométrica (44 pontos), reflectância espectral do solo (141 pontos) no sensor MSI (Sentinel-2), modelagem estatística preditiva (Análise Discriminante) e interpolação (IDW). A metodologia aplicada baseia-se na obtenção de funções discriminantes para aplicação de um classificador estatístico que, a partir dos dados espectrais de solo, seja capaz de discriminar a textura em areia, silte e argila. Os resultados da análise discriminante mostraram que (i) a textura do solo foi classificada no modelo a uma acurácia de 71% conforme Índice de Kappa; (ii) as frações silte e areia mostraram-se próximas tanto em termos de assinatura espectral como em teores (g/kg) obtidos em laboratório; (iii) houve predomínio de argila corroborando a característica litológica de área basáltica. Por permitir a verificação de quais variáveis independentes (reflectância) mais contribuem para a resposta da variável dependente (granulometria), este método pode ser útil para indicar as faixas espectrais que podem ser usadas na aplicação de uma técnica de regressão para predição granulométrica.Classification and Mapping of the surface-based soil texture through Remote Sensing Data and Discriminant Analysis in the region of Volta Grande do Rio Uruguai – BrazilA B S T R A C TMeasuring and evaluating soil components and properties are often costly and time-consuming procedures. Prediction and modelling, whose procedures are known as predictive soil mapping, are useful for solving the lack of field data sampling. The objective of this work is to map the surface-based soil texture in the region of Volta Grande do Rio Uruguay (SC / RS-Brazil) by using soil particle-size sampling (44 points) or soil granulometry, soil spectral reflectance (141 points) in the MSI sensor (Sentinel-2), predictive statistical modelling (Discriminant Analysis) and IDW interpolation. The methodology aims to find discriminant functions to obtain a statistical classifier that, based on soil spectral data, is able to discriminate the soil texture (surface-based) in terms of sand, silt and clay. The results showed that (i) the statistical model classified the soil texture at an accuracy of 71% according to the Kappa Index; (ii) silt and sand were similar both in terms of spectral signature and of content (g/kg); (iii) there was a predominance of clay corroborating the lithological characteristic of the basaltic area. Discriminant Analysis provides a basis to identify which independent variables (reflectance) contribute most to the response of the dependent variable (soil texture). Thus, the studied method can be useful to indicate the spectral ranges in regression models for predicting soil texture at locations not sampled.Keywords: multivariate statistics, spectral, soil particle size, Sentinel-2, interpolation.

Predominance of eyes and surface information for face race categorization

Faces can be categorized in various ways, for example as male or female or as belonging to a specific biogeographic ancestry (race). Here we tested the importance of the main facial features for race perception. We exchanged inner facial features (eyes, mouth or nose), face contour (everything but those) or texture (surface information) between Asian and Caucasian faces. Features were exchanged one at a time, creating for each Asian/Caucasian face pair ten facial variations of the original face pair. German and Korean participants performed a race classification task on all faces presented in random order. The results show that eyes and texture are major determinants of perceived biogeographic ancestry for both groups of participants and for both face types. Inserting these features in a face of another race changed its perceived biogeographic ancestry. Contour, nose and mouth, in that order, had decreasing and much weaker influence on race perception for both participant groups. Exchanging those features did not induce a change of perceived biogeographic ancestry. In our study, all manipulated features were imbedded in natural looking faces, which were shown in an off-frontal view. Our findings confirm and extend previous studies investigating the importance of various facial features for race perception.

Physicochemical, mineralogy, and thermo-kinetic characterisation of newly discovered Nigerian coals under pyrolysis and combustion conditions

In this study, the physicochemical, microstructural, mineralogical, thermal, and kinetic properties of three newly discovered coals from Akunza (AKZ), Ome (OME), and Shiga (SHG) in Nigeria were examined for potential energy recovery. Physicochemical analysis revealed high combustible but low levels of polluting elements. The higher heating values ranged from 18.65 MJ/kg (AKZ) to 26.59 MJ/kg (SHG). Microstructure and mineralogical analyses revealed particles with a rough texture, surface, and glassy lustre, which could be ascribed to metals, quartz, and kaolinite minerals. The major elements (C, O, Si, and Al), along with minor elements (Ca, Cu, Fe, K, Mg, S, and Ti) detected are associated with clays, salts, or the porphyrin constituents of coal. Thermal analysis showed mass loss (ML) ranges from 30.51% to 87.57% and residual mass (RM) from 12.44% to 69.49% under combustion (oxidative) and pyrolysis (non-oxidative) TGA conditions due to thermal degradation of organic matter and macerals (vitrinite, inertinite and liptinite). Kinetic analysis revealed the coals are highly reactive under the oxidative and non-oxidative conditions based on the Coats–Redfern Model. The activation energy (Ea) ranged from 23.81 to 89.56 kJ/mol, whereas the pre-exponential factor (ko) was from 6.77 × 10–4/min to 1.72 × 103/min under pyrolysis and combustion conditions. In conclusion, the coals are practical feedstocks for either energy recovery or industrial applications.