Creep compliance of the hot-mix asphalt (HMA) is a primary input of the current pavement thermal cracking prediction model used in the US. This paper discusses a process of training an Artificial Neural Network (ANN) to correlate the creep compliance values obtained from the Indirect Tension (IDT) with similar values obtained on small HMA beams from the Bending Beam Rheometer (BBR). In addition, ANNs are also trained to predict HMA creep compliance from the creep compliance of asphalt binder and vice versa using the BBR setup. All trained ANNs exhibited a very high correlation of 97 to 99 percent between predicted and measured values. The binder creep compliance functions built on the ANN-predicted discrete values also exhibited a good correlation when compared with the laboratory experiments. However, the simulation of trained ANNs on the independent dataset produced a significant deviation from the measured values which was most likely caused by the differences in material composition, such as aggregate type and gradation, presence of recycled additives, and binder type.

Shape memory polymers (SMP) are new multifunctional materials raising increasing interest in various functional applications. Among them, polyurethane shape memory polymers (PU-SMP) are particularly attractive due to their combination of shape memory, high strength and biocompatible properties. Developing new applications for PU-SMP requires comprehensive research on their characteristics. This work involved investigating the structure and mechanical behavior as well as characterizing the energy storage and dissipation of a thermoplastic PU-SMP with a glass transition temperature (Tg) of 25_C during tensile loading-unloading. The process of energy storage and dissipation in the PU-SMP was investigated based on the stress-strain curves recorded by a quasi-static testing machine and the temperature changes, accompanying the deformation process, obtained by using a fast and sensitive infrared camera. The results showed that the thermomechanical behavior of the examined PU-SMP depends significantly on the strain rate. At a higher strain rate, there are higher stress and related temperature changes, which lead to greater energy dissipation. However, the energy storage values estimated during the deformation process turned out to be not significant, indicating that the work supplied to the PU-SMP structure during loading is mainly converted into heat. It should also be noted that the structural investigation revealed no crystalline phase in the investigated PU-SMP.

High-temperature plastic properties of heat-resistant stainless steel X15CrNiSi 20-12 were assessed on the basis of hot tensile tests and nil strength tests. The results were supported by metallographic analyses using SEM and EDX analysis. The formability of the investigated steel can be divided into roughly three temperature areas. In the temperature range of 900°C to about 1050°C, formability was negatively affected by precipitation of carbide particles at grain boundaries. As the temperature rose to 1200°C, these particles dissolved, resulting in an increase in formability. Further temperature increases resulted in a relatively steep drop in formability caused by overheating of the material. The nil ductility temperature of 1280°C and the nil-strength temperature of 1362°C were determined. The Plastic and strength properties of the investigated material were compared with the deformation behavior of the reference steel X5CrNi 18-10, which shows a significantly wider range of suitable forming temperatures.