The Colour of Textiles when Wet The Relationship between Wet and Dry Reflectance Values for Common Textile Materials

The colour of a dyed textile material immersed in water can be related to its colour in the dry state. The results of wet and dry colour measurements on a variety of textile materials are presented. An empirical equation is developed, relating wet and dry reflectance values for the common textile fibres. The equation varies with fibre type, but it is independent of colour. The equation also varies with fibre decitex and pigment content, but it is thought that this may be due to the design of the apparatus. Some work has also been done on some dyes which exhibit abnormal wet–to–dry colour changes. The paper does not prove wet assessment to be practicable, but it goes some way towards that objective, and reports sighting experiments which may benefit other workers in the field.     

The study of colour fastness of commercial microencapsulated photoresponsive dye applied on cotton,cotton/polyester and polyester fabric using a pad‐dry‐cure process

Commercial microencapsulated photoresponsive dye was applied on cotton, polyester/cotton and polyester fabric using a pad‐dry‐cure process. Colour fastness of the photoresponsive fabrics to washing, wet cleaning, dry cleaning, rubbing and light was investigated. The CIELAB colour values of the fabrics before and after testing were measured using a reflectance spectrophotometer, and the colour differences were calculated to evaluate the fastness properties. The fabrics had better colour fastness to wet cleaning and washing than to dry cleaning. The fabrics showed higher colour fastness to wet than to dry rubbing. The photoresponsiveness of the fabrics decreased with prolonged exposure time to artificial light due to low photostability of the microcapsules.     

Artificial neural networks for colour prediction in leather dyeing on the basis of a tristimulus system

Computer‐assisted colour prediction and quality control have become increasingly important to the dyeing process in many consumer goods manufacturing industries, including textile and leather. The most challenging aspect concerns dye recipe prediction for the production of the required shade on a given substrate. Computer recipe prediction based on the conventional and widely used Kubelka–Munk model often fails under a variety of conditions. In the present investigation, an attempt has been made to develop an artificial neural network model to predict colour in terms of tristimulus values (X, Y, Z) given the concentration of dyes. An artificial neural network model was trained with 300 pairs of known input vectors, i.e. dye concentrations, and output vectors, i.e. colour parameters, using a backpropagation algorithm. The artificial neural network topology consists of three neurons in the input layer to represent the concentration of dyes, three neurons in the output layer to represent the tristimulus values X, Y, and Z, and five neurons in the hidden layer with a log‐sigmoid transfer function. The artificial neural network results showed a good level of colour prediction during the training and testing phase. The results also indicate that the artificial neural network has the potential to give better predictive performance than the conventional Kubelka–Munk model.     

Decomposition and nutrient release from pruning residues of two indigenous agroforestry species during the wet and dry seasons

The decomposition of leaves from Cordia africana Lam. and Albizia gummifera G. F.Gmel was investigated during the wet and dry seasons at Wondo Genet (Ethiopia). Litterbags of leaves were buried in soils under farmland and shaded-coffee agroforestry systems. Residual matter was recovered after 4, 8, 12, and 16 weeks and analysed for nitrogen (N), phosphorus (P), potassium (K), cellulose, lignin, soluble polyphenol and condensed tannin content. Mass-loss and release of N, polyphenols and condensed tannins were greater from Albizia leaves than from Cordia leaves, suggesting that a high polyphenol content does not necessarily retard decomposition. The rates of mass loss and release of the majority of leaf constituents were considerably faster during the wet season than during the dry season. Lignin decomposition, however, proceeded more rapidly during the dry season, and no significant seasonal differences were observed for polyphenol decomposition. The decomposition kinetics of most leaf components during the wet season were best described by a single-exponential model, but a quadratic model provided the best fit during the dry season. Initial leaf chemistry and season were important decomposition factors, while land-use effects were negligible. However, land-use effects showed distinct seasonal differences, with leaf litter decomposing more rapidly in soil under shaded-coffee than under farmland management, especially during the wet season. This study also demonstrated that polyphenol content does not show the predictive effects it has been attributed to have and that other constituents, such as condensed tannins, would be better suited for this purpose.     

酪素基rGO复合乳液的制备及其对皮革阻燃增强效果的研究

为制备具有增强阻燃效果的皮革涂饰材料,本研究首先以天然石墨为原料,采用Hummers法制备氧化石墨烯,并采用NaBH4对其进行还原得到还原氧化石墨烯（rGO）。通过FTIR,XRD和TEM等对其进行表征。结果表明,成功制备了rGO纳米材料。随后,采用物理共混法将rGO引入天然蛋白质酪素体系,制备酪素基rGO复合乳液并将其应用于皮革涂饰,对涂饰后革样的阻燃性能、力学性能和耐干湿擦性能进行测试。结果表明,当rGO的含量为酪素体系溶质质量的0.5%时,与未含rGO的酪素体系相比,涂饰后革样的燃烧速率下降47.2%,极限氧指数（LOI）由24.2%增加至26.3%,热释放速率（HRR）下降53.1%,总热释放率（THR）也有所降低。rGO的引入对涂饰后革样的力学性能和耐干湿擦性能影响不大。     

Colouring of opaque ceramic glaze with zircon pigments: Formulation with simplified Kubelka-Munk model

In this study a simplified Kubelka-Munk model is proposed for colour matching purposes. Opaque glazes were prepared to determine the absorption optical constants from the reflectance curves measured with a spectrophotometer. After the physical and chemical characterization of the glaze components (frit and pigments), to analyze the spectrophotometric results a simplification of the Kubelka-Munk model was suggested. To experimentally verify the model, two target green colour were reproduced in laboratory by adding in an opaque glaze a yellow praseodymium-doped zircon ((Zr,Pr)SiO₄) and blue vanadium-doped zircon ((Zr,V)SiO₄) pigments. The results were in good agreement with the experimental reflectance curves and the prediction of colour green glazes was possible with a reduced number of experiments.     

Colour in ceramic glazes: Efficiency of the Kubelka–Munk model in glazes with a black pigment and opacifier

In this study the efficiency of the Kubelka–Munk model (already known and consolidated in other industrial sectors) was evaluated in the prediction of the colour of an opaque ceramic glaze obtained by a mixture of black pigment (spinel Ni–Fe–Cr) and zircon opacifier (ZrSiO₄). Glazes with different percentages of black pigment and opacifier were prepared to determine the absorption and scattering optical constants from the reflectance curves measured with a spectrophotometer. After the physical and chemical characterization of the glaze components (frit, pigment and opacifier), suggestions for the adaptation of the Kubelka–Munk model were made to facilitate the experimental procedure of analysis. The result obtained with the adapted Kubelka–Munk model was in good agreement with the experimental reflectance curves. The reproduction of the desired colour was possible with a reduced number of experiments and the model made it possible to correlate the colour with the added pigments concentration facilitating the formulation step.     

70kg模拟焦炉炼焦焦炭转鼓强度分析

简述了70kg模拟焦炉试验情况,通过对焦炭转鼓强度(DI11550)影响因素的分析,得出单种煤的变质程度指标(干燥无灰基挥发分Vdaf或镜质组随机平均反射率Rran)、煤的惰性物含量及黏结指数是影响DI11550的主要因素。通过多参数回归分析,得出了单种煤炼焦焦炭转鼓强度的预测模型。     

A novel approach to using neural networks to predict the colour of fibre blends

This work is concerned with the colour prediction of viscose fibre blends, comparing two conventional prediction models (the Stearns–Noechel model and the Friele model) and two neural network models. A total of 333 blended samples were prepared from eight primary colours, including two‐, three‐, and four‐colour mixtures. The performance of the prediction models was evaluated using 60 of the 333 blended samples. The other 273 samples were used to train the neural networks. It was found that the performance of both neural networks exceeded the performance of both conventional prediction models. When the neural networks were trained using the 273 training samples, the average CIELAB colour differences (between measured and predicted colour of blends) for the 60 samples in the test set were close to 1.0 for the neural network models. When the number of training samples was reduced to only 100, the performance of the neural networks degraded, but they still gave lower colour differences between measured and predicted colour than the conventional models. The first neural network was a conventional network similar to that which has been used by several other researchers; the second neural network was a novel application of a standard neural network where, rather than using a single network, a set of small neural networks was used, each of which predicted reflectance at a single wavelength. The single‐wavelength neural network was shown to be more robust than the conventional neural network when the number of training examples was small.     

An investigation into water marking and colour change in tussah silk fabric during moisture absorption

This study investigates the phenomena of water marking and colour change in tussah silk fabric. Fully wetting the fabric and applying a small amount of moisture (by steaming) both result in changes in the fabric's optical properties: fully wetting causes a decrease in the reflectance of the fibre surface, while exposure to small amounts of moisture results in an increase. Lustre changes (reflectance variations) of tussah fabrics after wet or steam treatments are macroscopic effects of changes in the optical reflectance of the fibres and indicate that the visual colour differences in the fabric following water marking or colour change result from structural changes in the fibres.     

Prediction of depth of shade of a dyed polyester fabric based on fibre fineness and fabric structure

A colour prediction model containing four parameters of dye concentration, fibre fineness, fabric roughness and dye parameter is developed. The model can predict the shade depth of a dyed polyester fabric. The relationship among these factors and shade depths of dyed polyester fabrics was investigated to elucidate the role of fibre fineness and fabric structure on surface reflectance and colour efficiency. The shades of several additional dyed samples were measured and compared against the predicated values to validate the accuracy and performance of the model. The results showed that the predicated depths of shade matched the experimental data to a good extent.     

皮革黑LR-N染色性能及染色工艺的研究

本文利用色度色差分析及紫外可见吸收光谱等研究了非偶氮皮革专用新型染料一皮革黑LR-N的 染色性能。结果表明,皮革黑LR-N渗透性好,所染皮革黑度好,耐干/湿摩擦牢度高,适于正面革及轻涂 饰革的染色,本文还制定了单独用皮革黑LN-R染黑色革的工艺。     

Colour Measurement and Colour Tolerance in the Plastics Industry

The limited use, within the plastics industry, of colour-difference units is discussed. The requirements and calibration of measuring instruments, with particular reference to plastics, are stated, together with details of reference and calibration standards. Identification and estimation of colorants is carried out with the Comic analogue computer handling a modified Kubelka—Munk function of the spectrophotometric reflectance curve. Although the scatter component of this function varies with the opacity of the moulding, the variation can be predicted and its effect nullified. The correction of a first prediction for a new colour is done through the computer by means of the differences in tristimulus values, as measured by means of a colorimeter, between the predicted recipe and the required colour. An extension of this method for colour control in production is explained. The colour tolerances achieved by instrumental control in the production of thermosetting plastics are stated in terms of the deviation (in MacAdam units) from standard. The colour gamut over which measurement may usefully be applied is prescribed. Finally, some problems associated with measurement are described, together with their solutions.     

Vacuum contact drying of free flowing mechanically agitated particulate materialVakuum-kontakttrocknung von rieselfähigem,mechanisch durchmischtem Granulat

The drying rate of packed and mechanically agitated beds heated by immersed surfaces is controlled by the contact heat transfer resistance at the surface followed by the heat penetration resistance of the wet bulk. Both resistances can be predicted from model equations with sufficient accuracy. The contact resistance and the bulk penetration resistance for packed beds follow from physical properties, while the prediction of the bulk penetration resistance for mechanically agitated beds requires the introduction of an empirical parameter, the so-called mixing number, in order to describe the random particle motion. The mixing number was found to lie between 2 and 25, depending on the dryer type as well as on the Froude number. It is identical for dry and for wet beds.     

Recovery of reflectance spectra from CIE tristimulus values using a progressive database selection technique

A procedure for creating efficient reflectance spectra from CIE tristimulus colour values is described using a modified linear model. By fixing certain criteria based on colour difference values, the proposed technique preliminarily selects a series of suitable samples from a main data set containing the reflectance values of a large number of different coloured samples, based on the colour specifications of a given sample. In this way, a series of different databases containing the reflectance values of confirmed samples relating to the particular samples are formed. Then, a well-known principal components linear model is applied using three basis functions. This operation yields higher cumulative variances in comparison with the original database, having the same number of basis vectors. The performance of the proposed method is evaluated using a different collection of samples and the resulting spectra show considerable improvements in terms of root mean square error as well as colour difference values under different illuminants.     

Preparation and properties of emulsifier/N‐methylpyrrolidone‐free crosslinkable waterborne polyurethane–acrylate emulsions for footwear adhesives. I. Effect of the acrylic monomer content

Stable emulsions of emulsifier/N‐methylpyrrolidone‐free crosslinkable waterborne polyurethane–acrylates (C‐WBPUAs) with various acrylic monomer contents (0, 10, 20, and 30 wt %) for footwear adhesive materials were successfully prepared in this study. The effects of the acrylic monomer content on the shelf stability, mean particle size, and viscosity of the C‐WBPUA emulsions; the tensile properties and dynamic mechanical thermal properties of the C‐WBPUA film samples; and the adhesive strengths between the upper (synthetic leather) and the sole (ethylene vinyl acetate rubber) in both the dry and wet states of the formulated adhesives (C‐WBPUA emulsion–thickener–hardener) were examined. The adhesive strengths of the formulated adhesives for footwear (leather–sole) in both the dry and wet states increased with increasing acrylic monomer content up to 20 wt %; after this, they almost levelled off. Thus, C‐WBPUA20 and C‐WBPUA30, where the number indicates the acrylic monomer content, can be recommended as high‐performance adhesive materials for footwear. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43758.     

Adhesion of Self-Compacting Overlays Applied to Different Concrete Substrates and Its Prediction by Fuzzy Logic

An experimental and analytical study was performed to evaluate the adhesion between concrete and overlays using five different substrate surfaces and six different mixtures of self-compacting concrete and mortar. Saw cut surfaces of high strength concrete slabs were used as substrate. After the application of self-compacting concrete or mortar layers to dry, saturated surface dry, saturated surface wet, dry with bonding grout, and saturated with bonding grout surfaces of concrete slabs, they were covered with wet hessian and polythene sheets for curing. At the age of 28 days, friction-transfer tests were performed to evaluate the adhesion. The results indicate that while dry and saturated wet surfaces produced the lowest bond strength, the application of cement bonding grout improved the bond strength significantly. The results also showed that despite the noticeable correlations between the adhesion and the results of different flow tests, aggregate/cement ratio, fly ash/cement ratio, compressive strength, and water/powder ratio, the effect of the other constituents of the employed self-compacting overlays on their adhesion were not so significant. In order to predict the adhesion of self-compacting mixtures applied to concrete substrates, a fuzzy logic model was also devised. The results obtained from the fuzzy logic prediction model were compared with the average results of the friction-transfer method and found to be in very close agreement. The results show that fuzzy logic can be used to predict adhesion of self-compacting overlays.     

低成本湿法合成革用聚酯型耐水解聚氨酯树脂的合成

以苯酐聚酯二元醇(PS)、聚己内酯多元醇(PCL)、1,4-丁二醇(BDO)、二苯甲烷二异氰酸酯(MDI)等为原料,合成了湿法革用聚氨酯树脂.分别研究了PS相对分子质量、PCL用量、硬段含量等对聚氨酯树脂膜的模量及其耐水解性能的影响.结果表明,PS和PCL复配可以制得耐水解性能优异,且成本较低的湿法合成革用聚氨酯树脂.     

Analysis and prediction of indoor air pollutants in a subway station using a new key variable selection method

A new key variable selection and prediction model of IAQ that can select key variables governing indoor air quality (IAQ), such as PM₁₀, CO₂, CO, VOCs and formaldehyde, are suggested in this paper. The essential problem of the prediction model is the question of which of the original variables are the most important for predicting IAQ. The next issue is determining the number of key variables that should be ranked. A new index of discriminant importance in the projection (DIP) of Fisher??s linear discriminant (FLD) is suggested for selecting key variables of the prediction models with multiple linear regression (MLR) and partial least squares (PLS), as well as for ranking the importance of input measurement variables on IAQ prediction. The prediction models were applied to a real IAQ dataset from telemonitoring data (TMS) in a metro system. The prediction results of the model using all variables were compared with the results of the model using only key variables of DIP. It shows that the use of our new variable selection method cannot only reduce computational effort, but will also enhance the prediction performances of the models.     

CAR系统的回归分析法应用及其他

作者和他的合作者开发的计算机辅助试验研究系统（简称CAN系统）是一个试验设计的专门应用软件，由正交试验法和回归分析法两大部分组成，以一个三变量多性能指标的丁精橡胶配方设计（三元二次回归模型）为例，说明了CAR系统回归分析法部分的回归试验设计、回归方程的获取与显著性检验、预测和优选配方等试验设计功能和其他情况，并且结合这个实例讨论了应用回归分析法有时被忽视的几个基本问题：回归方程的显著性检验，重复试验和拟合检验，回归系数的显著性检验，对食不显著项回归方程的处理，剩余标准高差，回归正交设计和自变量编码等。