Rigid polyurethane foam (RPUF) composites with triphenyl phosphate (TPhP), aluminum trihydrate (ATH), and zinc borate (ZnB) alone, as well as their binary blends, were prepared via a one-shot process. The amount of flame retardant (FR) or FR blend was varied from 10 to 50% by polyol weight percentage, and the weight fraction of the blends was also fixed at 40%. The effects of additives on thermal insulation, mechanical, and flame retardancy properties of the composites were investigated. Thermal conductivity of the neat foam (RPUF) decreased from 22.53 to 21.04-21.58 mW m −1 K −1 . The compressive strength of foams displayed an increase with increasing the amount of TPhP, ATH, and ZnB till 40% by weight. The limited oxygen index values of all foams increased and the flame spread rates of all foams significantly decreased. It was also observed that the flame was self-extinguished in some cases. The cone calorimeter test results indicated that the FR additives improved the flame retardancy of the RPUF. INDTRODUCTIONRigid polyurethane foams (RPUFs) are one of the most consumed polymeric materials to a great extent. They have wide range applications in insulation, transportation, building construction, domestic appliance, automobile industry, and many others because of their high closed-cell content, low thermal conductivity, high strength with low weight, good shock absorption, and so on. 1-3 Nowadays, humanity is under threat because of limited energy resources in the world. In that case, RPUFs possessing low thermal conductivity values come into prominence because RPUFs are one of the unique materials for thermal insulation. RPUFs predominantly contain closed-cell structures, and in the closed-cell structures of foams, a blowing agent constituting the gas is trapped during production. The thermal conductivity of an RPUF is strongly affected by this blowing agent. The lower thermal conductivity of the blowing agent causes the lower thermal conductivity of RPUF. 4,5 When RPUFs compare with the conventional thermal insulating materials such as brick, concrete, wood, glass fiber, and so on, the conventional materials need to be used at much higher thickness in an attempt to match the insulation performance of 50 mm RPUF, for instance, ranging from 1720 mm for brick, 200 mm for wood, and 80 mm for polystyrene. The excellent thermal insulation property of RPUFs is not the only parameter making RPUFs one of the most used engineering materials but also their high mechanical strength with low weight and their easy processability make it as an interesting material. 6,7 For example, RPUF is one of the most important structural element of the refrigerators' skeleton besides providing high insulation for home refrigerators.However, as in the case of a majority of polymeric materials, RPUF is also easily combustible. As a matter of fact that, it is more combustible than other materials because of its rigid cellular and organic structure, additionally, it contains flammable, explosive gases in its closed cells. During the burnin...

The physical characteristics of a fiber determine its processing behavior, production efficiency and finally yarn and fabric quality. Therefore, predicting the quality characteristics of yarns, such as the tensile properties from the raw material properties, was the main purpose of many studies in the last century. In addition to raw material processing conditions, preparation stages, machine parameters and the spinning method also have considerable effects on the yarn properties. Generally two approaches were used in these studies for predicting yarn quality from fiber and yarn characteristics:• an empirical and statistical approach; and • a theoretical or analytical approach. 1The empirical and statistical approach to establishing a relationship between fiber and yarn quality characteristics has been the most popular method during the second half of the twentieth century. Fast and accurate measurement of fiber properties by means of high volume instruments (HVI) and more powerful computers are the two main reasons for this tendency. With this method, important fiber and yarn properties can be measured for a range of samples and by using these results empirical relationships have been established by means of statistical analysis. One of the Abstract The main aim of the present study was to predict the most important yarn quality characteristics derived from cotton fiber properties that were measured by means of an HVI system. With this aim 15 different cotton blends were selected from different spinning mills in Turkey. The cotton fibers were processed in the short staple spinning line at Ege University Textile and Apparel Research-Application Center and were spun into ring yarns (20s, 25s, 30s and 35s). Each count was spun at three different coefficients of twist (α e 3.8, α e 4.2 and α e 4.6). Linear multiple regression methods were used for the estimation of yarn quality characteristics. Yarn count, twist and roving properties all had considerable effects on the yarn properties and therefore these parameters were also selected as predictors. After the goodness of fit statistics very large R 2 (coefficient of multiple determination) and adjusted R 2 values were observed. Furthermore, analysis of variance tables showed that our equations were significant at the α = 0.01 significance level.

The use of flame retardants (FRs) to improve the flame retardancy but also having good insulation and mechanical properties of rigid polyurethane foam (RPUF) has become significant due to the increasing demand in both the industry and academia. In the present study, a series of RPUF composites containing expandable graphite (EG), ammonium pentaborate (APB) octahydrate, and their binary blends were prepared with one‐shot and free‐rise methods. The effects of FRs on the FR and physical‐mechanical properties of RPUFs were investigated. The results show that both EG and APB could improve the flame retardancy of RPUFs and reduced the smoke production. The FR effect of EG was better than APB and more importantly, synergistic effect was found between EG and APB. The best results were obtained by the foam in the composition of 15E and 5A. The cone calorimeter test results showed that the peak heat release rate (pHRR) and total smoke release (THR) of 15E/5A foam were lower than the foams of 20E and 20A. The pHRR and THR values of 15E/5A foam decreased about 57.5% and 42.8% compared to the neat RPUF, respectively. Total smoke production (m2) also reduced about 77.0% by 20E and 83.6% by 15E/5A foams. Thermogravimetric analysis indicates that the char residue of 15E/5A foam increased to 39.5%, which provided better flame retardancy. The foam composites have high compressive strength (105‐150 kPa) and low thermal conductivity values (19.9‐21.3 mW/mK). While the thermal conductivity of 15E/5A foam increased by 0.5%, its compressive strength increased by 6.1%.

In this study artificial neural network (ANN) models have been designed to predict the ring cotton yarn properties from the fiber properties measured on HVI (high volume instrument) system and the performance of ANN models have been compared with our previous statistical models based on regression analysis. Yarn count, twist and roving properties were selected as input variables as they give significant influence on yarn properties. In experimental part, a total of 180 cotton ring spun yarns were produced using 15 different blends. The four yarn counts and three twist multipliers were chosen within the range of Ne 20-35 and e 3.8-4.6 respectively. After measuring yarn tenacity and breaking elongation, evaluations of data were performed by using ANN. Afterwards, sensitivity analysis results and coefficient of multiple determination (R 2 ) values of ANN and regression models were compared. Our results show that ANN is more powerful tool than the regression models.