Evaluation of the Aging of Styrene-Butadiene-Styrene Modified Asphalt Binder with Different Polymer Additives

A wide variety of polymer additives have been widely used in recent years. However, the effect of different polymer additives on the durability of asphalt binders has not been investigated thoroughly. To evaluate the aging property of styrene-butadiene-styrene (SBS) asphalt binder with different polymer additives, three polymer modifiers, namely high modulus modifier (HMM), anti-rutting agent (ARA), and high viscosity modifier (HVM), were added to it. First, the Thin Film Over Test (TFOT) and Pressure Aging Vessel (PAV) was performed on the asphalt binders. The rheological properties of the four asphalt binders before and after aging were then checked by the Dynamic Shear Rheometer Test (DSR). The chemical compositions of the asphalt binders were determined by the Fourier Transform Infrared Spectrometer (FTIR) test. Several aging indicators were adopted to reflect the aging degree of the asphalt binders. The results show that when polymer additives are added to the SBS asphalt binder, the complex modulus, storage modulus, loss modulus, and rutting factor substantially increase and the phase angle decreases. All the test parameters become higher after aging. The phase angle of the SBS asphalt binder is the highest at both unaged and aged states, while its other parameters values are the smallest. Moreover, the Carbonyl Aging Indicator (CAI) of SBS with polymer additives becomes lower under both TFOT and PAV conditions, indicating that polymer additives can improve the aging resistance of SBS asphalt, of which HVM modifies the aging resistance best. Complex Modulus Aging Indicator (CMAI) and Storage Modulus Aging Indicator (SMAI) have the best correlation coefficients with CAI, and the two aging indicators can be used to predict the aging degree of polymer modified asphalt binders.

A Dynamic Anomaly Detection Approach Based on Permutation Entropy for Predicting Aging-Related Failures

Software aging is a phenomenon referring to the performance degradation of a long-running software system. This phenomenon is an accumulative process during execution, which will gradually lead the system from a normal state to a failure-prone state. It is a crucial challenge for system reliability to predict the Aging-Related Failures (ARFs) accurately. In this paper, permutation entropy (PE) is modified to Multidimensional Multi-scale Permutation Entropy (MMPE) as a novel aging indicator to detect performance anomalies, since MMPE is sensitive to dynamic state changes. An experiment is set on the distributed database system Voldemort, and MMPE is calculated based on the collected performance metrics during execution. Finally, based on MMPE, a failure prediction model using the machine learning method to reveal the anomalies is presented, which can predict failures with high accuracy.

Correlation Between Transmittance and LWIR Apparent Emissivity of Soda-Lime Glass During Accelerated Aging Test for Solar Applications

In solar power plants, both in photovoltaic (PV) and concentrated ones, the electrical output is a key parameter for the development of solar energy. To ensure relevant predictability of electrical output, the durability of photovoltaic panels or concentrating systems has to be warranted. The assessment of the optical performance durability of the front glass throughout the lifetime of the solar power plant involves using a nondestructive method in the field without disrupting the energy generation of such systems. The aim of this work is to experiment a new accurate nondestructive method to evaluate the aging impact of glass used in solar energy conversion systems. The results bring out a correlation between the apparent emissivity, used as an aging indicator, in a spectral bandwidth of 8–12 μm and the integrated transmittance in the visible range, i.e., 400–800 nm for a float glass of 2 mm thickness aged under damp heat (DH). The optical characterizations of the soda-lime glass exposed to the DH test highlight the relevance of apparent emissivity used like a nondestructive aging indicator. The sensitivity coefficient of apparent emissivity, which is defined as the ratio of partial derivative of integrated transmittance (δT) to the partial derivative of apparent emissivity (δε), reaches 3.83, meaning that the apparent emissivity is three times more sensitive than the integrated transmittance for the case study.