Cross-Functional Test to Explore the Determination Method of Meso-Parameters in the Discrete Element Model of Asphalt Mixtures

In order to obtain more accurate parameters required for the simulation of asphalt mixtures in the discrete element method (DEM), this study carried out a series of cross-functional asphalt mixture experiments to obtain the DEM simulation meso-parameters. By comparing the results of simulation and actual experiments, a method to obtain the meso-parameters of the DEM simulation was proposed. In this method, the numerical aggregate profile was obtained by X-ray CT scanning and the 3D aggregate model was reconstructed in MIMICS. The linear contact parameters of the aggregate and the Burgers model parameters of the asphalt mastic were obtained by nanoindentation technology. The parameters of the parallel bonding model between the aggregate and mastic were determined by the macroscopic tensile adhesion test and shear bond test. The results showed that the meso-parameters obtained by the macroscopic experiment provide a basis for the calibration of DEM parameters to a certain extent. The trends in simulation results are similar to the macro test results. Therefore, the newly proposed method is feasible.

Optical Property Model for Cirrus Clouds Based on Airborne Multi-Angle Polarization Observations

We present an improved remote sensing technique to infer an optimal habit/shape model for ice particles in cirrus clouds using multi-angle polarimetric measurements at 865 nm made by the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI) instrument. The common method of ice model inference is based on intensity (total reflectivity) measurements, which is generally not applicable to optically thin ice clouds (i.e., cirrus clouds) where single scattering dominates. The new approach is able to infer an ice model in clouds with optical thicknesses smaller than 5. The improvement is made by first assuming the optical thickness retrieved using total reflectivity. Subsequently, the polarized reflectivity is calculated based on look-up tables generated from simulated polarized reflectances computed for cirrus clouds in conjunction with eight ice particle models. The ice particle model that leads to the closest fit to the measurements is regarded as the optimal ice particle model. Additionally, an alternative method is applied that does not consider polarized reflectivity. These two methods are applied to a data sample as a proof-of-concept study where AirMSPI observed a single cirrus layer. In this case study, the hexagonal column aggregate model works for most pixels both with and without considering polarized reflectivities. The retrieval cost function is high when the camera pairs with large zenith angles are included in the retrievals. This result suggests that further studies will be necessary to have a better understanding of all eight selected ice particle models at scattering angles smaller than 100°.

Discrete Element Simulation Analysis of Biaxial Mechanical Properties of Concrete with Large-Size Recycled Aggregate

Concrete made with large-size recycled aggregates is a new kind of recycled concrete, where the size of the recycled aggregate used is 25–80 mm, which is generally three times that of conventional aggregate. Thus, its composition and mechanical properties are different from that of conventional recycled concrete and can be applied in large-volume structures. In this study, recycled aggregate generated in two stages with randomly distributed gravels and mortar was used to replace the conventional recycled aggregate model, to observe the internal stress state and cracking of the large-size recycled aggregate. This paper also investigated the mechanical properties, such as the compressive strength, crack morphology, and stress–strain curve, of concrete with large-size recycled aggregates under different confining pressures and recycled aggregate incorporation ratios. Through this research, it was found that when compared with conventional concrete, under the confining pressure, the strength of large-size recycled aggregate concrete did not decrease significantly at the same stress state, moreover, the stiffness was increased. Confining pressure has a significant influence on the strength of large-size recycled aggregate cocrete.

Analysis of the Behavior of Abstractions in Two Urban Micro-Basins of the City of Cuenca (Ecuador), through an Aggregate Model

Several cities in developing countries are challenging the permanent process of urbanization. This generates a great disturbance on the hydrological response of the urbanized area during rainfall events, which can cause floods. Among the disturbances that urbanized basins may suffer, it is found that variations in rain losses (hydrological abstractions) can be estimated by the named volumetric runoff coefficient (CVOL) methodology. In the present study, this methodology is used in an attempt to estimate the hydrological abstraction of two nearby urbanized basins, with different degrees of impermeability, located in the city of Cuenca in Ecuador. The data for that analysis were collected between April and May of 2017. The results obtained indicate that the micro-basin with the largest impervious area presents the higher initial hydrological losses, the higher rate of decrease in abstractions, and the higher stormwater runoff flows per unit area. In addition, the abstractions found in the two urban micro-basins show great sensitivity to the maximum rainfall intensity and do not relate to the antecedent soil moisture. These results demonstrate the importance of having higher pervious surfaces in urbanized areas because they lead to reduce negative impacts associated with increased stormwater runoff on impervious surfaces.

Quantum Chemical Simulation of the Qy Absorption Spectrum of Zn Chlorin Aggregates for Artificial Photosynthesis

Zn chlorin (Znchl) is easy to synthesize and has similar optical properties to those of bacteriochlorophyll c in the nature, which is expected to be used as a light-harvesting antenna system in artificial photosynthesis. In order to further explore the optical characteristics of Znchl, various sizes of a parallel layered Znchl-aggregate model and the THF-Znchl explicit solvent monomer model were constructed in this study, and their Qy excited state properties were simulated by using time-dependent density functional theory (TDDFT) and exciton theory. For the Znchl monomer, with a combination of the explicit solvent model and the implicit solvation model based on density (SMD), the calculated Qy excitation energy agreed very well with the experimental one. The Znchl aggregates may be simplified to a Zn36 model to reproduce the experimental Qy absorption spectrum by the Förster coupling theory. The proposed Znchl aggregate model provides a good foundation for the future exploration of other properties of Znchl and simulations of artificial light-harvesting antennas. The results also indicate that J-aggregrates along z-direction, due to intermolecular coordination bonds, are the dominant factor in extending the Qy band of Znchl into the near infrared region.

Quantifying the Model Risk Inherent in the Calibration and Recalibration of Option Pricing Models

We focus on two particular aspects of model risk: the inability of a chosen model to fit observed market prices at a given point in time (calibration error) and the model risk due to the recalibration of model parameters (in contradiction to the model assumptions). In this context, we use relative entropy as a pre-metric in order to quantify these two sources of model risk in a common framework, and consider the trade-offs between them when choosing a model and the frequency with which to recalibrate to the market. We illustrate this approach by applying it to the seminal Black/Scholes model and its extension to stochastic volatility, while using option data for Apple (AAPL) and Google (GOOG). We find that recalibrating a model more frequently simply shifts model risk from one type to another, without any substantial reduction of aggregate model risk. Furthermore, moving to a more complicated stochastic model is seen to be counterproductive if one requires a high degree of robustness, for example, as quantified by a 99% quantile of aggregate model risk.