Combined Prediction Method for Thermal Conductivity of Asphalt Concrete Based on Meso-Structure and Renormalization Technology

Pavement temperature field affects pavement service life and the thermal environment the near road surface; thus, is important for sustainable pavement design. This paper developed a combined prediction method for the thermal conductivity of asphalt concrete based on meso-structure and renormalization technology, which is critical for determining the pavement temperature field. The accuracy of the combined prediction method was verified by laboratory experiments. Using the tested and proven model, the effect of coarse aggregate type, shape, content, spatial orientation, air void of asphalt concrete, and steel fiber on the effective thermal conductivity was analyzed. The analysis results show that the orientation angle and aspect ratio of the aggregate have a combined effect on thermal conductivity. In general, when the aggregate orientation is parallel with the heat conduction direction, the effective thermal conductivity of asphalt concrete in that direction tends to be greater. The effective thermal conductivity of asphalt concrete decreases with the decrease of coarse aggregate content or steel fiber content or with the increase of porosity, and it increases with the increase of the effective thermal conductivity of coarse aggregate.

Multi-Source Information Monitoring Test of Fractured Rock Mass Destruction Characteristics and Sensitivity Analysis of Precursor Phenomena

The accuracy of the monitoring information is particularly important for exploring fractured rock mass deformation and failure mechanisms and precursor characteristics. Appropriate monitoring methods can not only timely and effectively reflect the failure laws of fractured rock masses but also play an early warning role. To explore more reasonable monitoring methods, uniaxial compression experiments and real-time non-destructive monitoring on prefabricated fractured rock specimens through DIC, AE, and IRT were conducted; the strain field, temperature field, ringing frequency, standard deviation, etc. were analyzed; and correlation between the three methods in the information of audience was explored. The results show the following. (1) The failure evolution process of fractured rock mass can be divided into four stages. DIC can detect the initiation and propagation of cracks near the fractures of the specimen at the earliest stages. (2) The order of occurrence of precursor phenomena in multi-source monitoring information is different, which is vertical strain field > shear strain field > horizontal strain field > temperature field > ringing times. (3) The dispersion degree of standard deviation of each field is obviously different; the infrared temperature field is greater, but the strain field and temperature field show the same trend. (4) There are obvious precursors before the specimen is on the verge of instability; acoustic emission detected two consecutive increases in the cumulative number of ringing before destruction, which means the most obvious precursors. The research results can provide a theoretical basis for the precursory information capture and damage early warning of the fractured rock mass destruction process.

Simulation of Concrete in Winter with Self-Limiting Heating Band

In order to investigate the temperature distribution and cracking risk of concrete in winter under the combined action of heating zone and air layer, the analytical calculation method of early age concrete temperature field of concrete component under the combined action of self-limiting temperature band, cement hydration and air layer was established by taking concrete prism with self-limiting temperature band as an example. The model is applied to calculate and analyze the temperature distribution of concrete under different boundary conditions and different additional thermal field modes. The results show that: Under the conditions of internal layout, surface layout and thermal insulation layer outside the formwork, all components reach the critical strength after heating and curing for three days, which indicates that the heating band can provide temperature conditions for concrete curing in winter. Comparing the temperature field of different layout positions of heating belt, the uniformity of temperature field of heating belt outside the formwork is better than the other two layout methods.

Research on the End-Face Distribution of Rotational Molding Heating Gun Based on Numerical Simulation Method

The distribution of heating gun ends plays a decisive role in the sidewall properties of finished rotomolded products. To obtain the optimal distribution of the end face of a rotational molding heating gun, the temperature response of the end-face mold under heating gun heating was investigated, and an analysis method based on numerical simulation is proposed. The FDS (fire dynamics simulator) was used to construct a heating model of the heating gun, simulate and obtain a heatmap of the temperature field distribution of a heating gun of Φ30–70 mm, and determine the optimal diameter and heating distance of the heating gun. ANSYS was used to establish the thermal response model of the heat-affected mold, which was combined with the mold structure and thermophysical properties of steel. A temperature field distribution on the inner wall surface of Φ30, Φ50, and Φ70 mm heating guns when heating at each diameter of the end face was obtained and the distribution position of the end face of each diameter heating gun was determined. ANSYS was used to establish the thermal response model of the end-face mold and obtain the temperature field distribution of the inner wall surface of the end-face mold. The size of the heat-affected area of each diameter heating gun was combined, the end-face heating gun distribution was optimized, and the optimal heating gun end-face distribution was obtained. An experimental platform was built, and a validation experiment was set up. Through the analysis and processing of the data of three experiments, the temperature variation curve of each diameter on the inner surface of the end-face mold was obtained. We compare and analyze the simulation and experimental results to determine the feasibility of the FDS + ANSYS method and the correctness and accuracy of the simulation model and the results.

Probing ultra-light axion dark matter from 21 cm tomography using Convolutional Neural Networks

We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21 cm radio observations around the epoch of reionization (EoR). We show that the axion as the dominant dark matter component has a significant impact on the reionization history due to the suppression of small scale density perturbations in the early universe. This behavior depends strongly on the mass of the axion particle. Using numerical simulations of the brightness temperature field of neutral hydrogen over a large redshift range, we construct a suite of training data. This data is used to train a convolutional neural network that can build a connection between the spatial structures of the brightness temperature field and the input axion mass directly. We construct mock observations of the future Square Kilometer Array survey, SKA1-Low, and find that even in the presence of realistic noise and resolution constraints, the network is still able to predict the input axion mass. We find that the axion mass can be recovered over a wide mass range with a precision of approximately 20%, and as the whole DM contribution, the axion can be detected using SKA1-Low at 68% if the axion mass is M X < 1.86 × 10-20 eV although this can decrease to M X < 5.25 × 10-21 eV if we relax our assumptions on the astrophysical modeling by treating those astrophysical parameters as nuisance parameters.