Prediction of air voids of asphalt layers by intelligent algorithm

To study the upper body characteristics of young men, the body circumference, length, width, thickness, and angle of young men aged 18–25 and 26–35 years were collected to comprehensively characterize the concave and convex features of the front, back, and side of the human body. The Cuckoo Search-Density Peak intelligent algorithm was used to extract the feature factors of the upper body of men, and to cluster them. To verify the effectiveness of the intelligent algorithm, the clustering results of Cuckoo Search-Density Peak, Density Peak, Particle Swarm Optimization-Density Peak algorithm, Ant Colony Optimization-Density Peak algorithm, Genetic Algorithm-Density Peak algorithm, and Artificial Bee Colony-Density Peak algorithm were evaluated by Silouette and F-measures, respectively. The results show that the Cuckoo Search-Density Peak algorithm has the best clustering results and is superior to other algorithms. There are some differences in somatotype characteristics and somatotype indexes between young men aged 18–25 and 26–35 years.

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Intelligent optimization of EV comfort based on a cooperative braking system

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/09544070211004461 ◽

2021 ◽

pp. 095440702110044

Author(s):

Lingying Zhao ◽

Min Ye ◽

Xinxin Xu

Keyword(s):

System Model ◽

Regenerative Braking ◽

Coupling Mechanism ◽

Intelligent Algorithm ◽

Distribution Strategy ◽

Braking System ◽

Logic Diagram ◽

Braking Torque ◽

Braking Force ◽

The Time Domain

To address the comfort of an electric vehicle, a coupling mechanism between mechanical friction braking and electric regenerative braking was studied. A cooperative braking system model was established, and comprehensive simulations and system optimizations were carried out. The performance of the cooperative braking system was analyzed. The distribution of the braking force was optimized by an intelligent method, and the distribution of a braking force logic diagram based on comfort was proposed. Using an intelligent algorithm, the braking force was distributed between the two braking systems and between the driving and driven axles. The experiment based on comfort was carried out. The results show that comfort after optimization is improved by 76.29% compared with that before optimization by comparing RMS value in the time domain. The reason is that the braking force distribution strategy based on the optimization takes into account the driver’s braking demand, the maximum braking torque of the motor, and the requirements of vehicle comfort, and makes full use of the braking torque of the motor. The error between simulation results and experimental results is 5.13%, which indicates that the braking force’s distribution strategy is feasible.

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A GPR-Based Pavement Density Profiler: Operating Principles and Applications

Remote Sensing ◽

10.3390/rs13132613 ◽

2021 ◽

Vol 13 (13) ◽

pp. 2613

Author(s):

Nectaria Diamanti ◽

A. Peter Annan ◽

Steven R. Jackson ◽

Dylan Klazinga

Keyword(s):

Asphalt Pavement ◽

Wave Impedance ◽

Asphalt Mixtures ◽

Void Content ◽

Air Voids ◽

New Instrument ◽

Pavement Engineering ◽

And Performance ◽

Air Void ◽

Air Void Content

Density is one of the most important parameters in the construction of asphalt mixtures and pavement engineering. When a mixture is properly designed and compacted, it will contain enough air voids to prevent plastic deformation but will have low enough air void content to prevent water ingress and moisture damage. By mapping asphalt pavement density, areas with air void content outside of the acceptable range can be identified to predict its future life and performance. We describe a new instrument, the pavement density profiler (PDP) that has evolved from many years of making measurements of asphalt pavement properties. This instrument measures the electromagnetic (EM) wave impedance to infer the asphalt pavement density (or air void content) locally and over profiles.

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Optimising the Complex Refractive Index Model for Estimating the Permittivity of Heterogeneous Concrete Models

Remote Sensing ◽

10.3390/rs13040723 ◽

2021 ◽

Vol 13 (4) ◽

pp. 723

Author(s):

Hossain Zadhoush ◽

Antonios Giannopoulos ◽

Iraklis Giannakis

Keyword(s):

Refractive Index ◽

Shape Factor ◽

Complex Refractive Index ◽

Fdtd Method ◽

Air Voids ◽

Water Fraction ◽

Index Model ◽

General Complex ◽

Ground Penetrating ◽

Fine Tune

Estimating the permittivity of heterogeneous mixtures based on the permittivity of their components is of high importance with many applications in ground penetrating radar (GPR) and in electrodynamics-based sensing in general. Complex Refractive Index Model (CRIM) is the most mainstream approach for estimating the bulk permittivity of heterogeneous materials and has been widely applied for GPR applications. The popularity of CRIM is primarily based on its simplicity while its accuracy has never been rigorously tested. In the current study, an optimised shape factor is derived that is fine-tuned for modelling the dielectric properties of concrete. The bulk permittivity of concrete is expressed with respect to its components i.e., aggregate particles, cement particles, air-voids and volumetric water fraction. Different combinations of the above materials are accurately modelled using the Finite-Difference Time-Domain (FDTD) method. The numerically estimated bulk permittivity is then used to fine-tune the shape factor of the CRIM model. Then, using laboratory measurements it is shown that the revised CRIM model over-performs the default shape factor and provides with more accurate estimations of the bulk permittivity of concrete.

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