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.
This article examines Henryk Sienkiewicz’s proto-racist distinction between the gentry and the commoners in his novel With Fire and Sword (1883–1884). This division, which is believed to be part of the divine world order, credits the commoners with an inferior humanity. It is founded on a set of essentialist beliefs – that social class is inherited, that ‘noble blood’ confers superiority, and that physiognomy bespeaks high birth (you can tell a noblemen or noblewoman by their physical appearance). As the article claims, Sienkiewicz allows no room for a voice questioning those beliefs, let alone exposing their class-bound arbitrariness.