scholarly journals Prediction of the optimum asphalt content using artificial neural networks

10.30544/579 ◽  
2021 ◽  
Author(s):  
Kareem Mohamed Mousa Othman ◽  
Hassan Abdelwahab
Keyword(s):  
Mix Design ◽  
Average Error ◽  
Aggregate Gradation ◽  
Asphalt Mixes ◽  
New Approach ◽  
Marshall Test ◽  
Asphalt Mix ◽  
Asphalt Content ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

The performance of the asphalt mix is significantly influenced by the optimum asphalt content (OAC). The asphalt content is responsible for coating the aggregate surface and filling the voids between the aggregate particles. Thus, the aggregate gradation has a significant influence on the required asphalt content. The Marshall design process is the most common method used for estimating the OAC, and this process is called the asphalt mix design. However, this method is time consuming, labor intensive, and its results are subjected to variations. Thus, this paper employs the artificial neural network (ANN) to estimate the OAC from the aggregate gradation for the two most common gradations used in asphalt mixes in Egypt (3D, 4C). Results show that the proposed ANN can predict the OAC with a coefficient of correlation of 0.98 and an average error of 0.026%. As a result, a new approach for the Marshall test can be adopted using results of the proposed ANN, and only three specimens, instead of fifteen, are prepared and tested for estimating the remaining parameters. This approach saves the time, effort, and resources required for estimating the OAC. Additionally, the ANN was validated with previously developed models, and the ANN shows promising results.

Application of Stress Absorbing Layer in Project

2014 ◽  
Vol 587-589 ◽  
pp. 1095-1099
Author(s):  
Hai Zhan Li
Keyword(s):  
Mix Design ◽  
Construction Technology ◽  
Aggregate Gradation ◽  
Modified Asphalt ◽  
Asphalt Mix ◽  
Asphalt Content ◽  
Cracking Mechanism ◽  
Absorbing Layer ◽  
S Model ◽  
Sbs Modified Asphalt

To study the anti-cracking mechanism of stress absorbing layer. This paper, which determines the parameter of the sand asphalt mix design of AC-5 and proceeds the mix design, is based on Xinyang freeway (The bid section 1 of Huazhuang-Xincai section). Asphalt content is tested by ignition oven asphalt content test.Screening aggregate recovered from ignition oven asphalt content test .Using roughness, thickness, compaction in field evaluation.The results show that the positive S model of aggregate gradation and reasonable construction temperature and construction technology are contributed to anti-cracking of stress absorbing layer.The impermeable SBS modified asphalt stress absorbing layer could prevent the base and subgrade from eroding.

Critical Review of Voids in Mineral Aggregate Requirements in Superpave

1998 ◽  
Vol 1609 (1) ◽  
pp. 21-27 ◽  
Author(s):  
Prithvi S. Kandhal ◽  
Kee Y. Foo ◽  
Rajib B. Mallick
Keyword(s):  
Film Thickness ◽  
Mix Design ◽  
Rational Approach ◽  
Asphalt Mixes ◽  
Mineral Aggregate ◽  
Superpave Gyratory Compactor ◽  
Asphalt Mix ◽  
Compactive Effort ◽  
Asphalt Content ◽  
Asphalt Film

Reports of increased difficulties in meeting the minimum voids in mineral aggregate (VMA) requirements have surfaced with the recent use of Superpave volumetric mix design. The low VMA of Superpave mixes generally can be contributed to the increased compactive effort by the Superpave gyratory compactor. This has led to the increased use of coarser asphalt mixes (gradations near the lower control points). However, the minimum VMA requirements in Superpave volumetric mix design for these coarse mixes are the same as those developed for the dense mixes designed by the Marshall method. Literature review has indicated that the rationale behind the minimum VMA requirement was to incorporate at least a minimum permissible asphalt content into the mix to ensure its durability. Studies have shown that asphalt mix durability is directly related to asphalt film thickness. Therefore, the minimum VMA should be based on the minimum desirable asphalt film thickness instead of on a minimum asphalt content because the latter will be different for mixes with different gradations. Mixes with coarse gradation (and, therefore, a low surface area) have difficulty meeting the minimum VMA requirement based on minimum asphalt content despite thick asphalt films. A rational approach based on a minimum asphalt film thickness has been proposed and validated. The film thickness approach represents a more direct, equitable, and appropriate method of ensuring asphalt mix durability, and it encompasses various mix gradations.

A New Approach to Image Reconstruction in Positron Emission Tomography Using Artificial Neural Networks

1998 ◽  
Vol 09 (01) ◽  
pp. 71-85 ◽  
Author(s):  
A. Bevilacqua ◽  
D. Bollini ◽  
R. Campanini ◽  
N. Lanconelli ◽  
M. Galli
Keyword(s):  
Positron Emission Tomography ◽  
Simulated Data ◽  
Emission Tomography ◽  
Source Distribution ◽  
New Approach ◽  
High Data ◽  
Positron Emission ◽  
Physical Effects ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

This study investigates the possibility of using an Artificial Neural Network (ANN) for reconstructing Positron Emission Tomography (PET) images. The network is trained with simulated data which include physical effects such as attenuation and scattering. Once the training ends, the weights of the network are held constant. The network is able to reconstruct every type of source distribution contained inside the area mapped during the learning. The reconstruction of a simulated brain phantom in a noiseless case shows an improvement if compared with Filtered Back-Projection reconstruction (FBP). In noisy cases there is still an improvement, even if we do not compensate for noise fluctuations. These results show that it is possible to reconstruct PET images using ANNs. Initially we used a Dec Alpha; then, due to the high data parallelism of this reconstruction problem, we ported the learning on a Quadrics (SIMD) machine, suited for the realization of a small medical dedicated system. These results encourage us to continue in further studies that will make possible reconstruction of images of bigger dimension than those used in the present work (32 × 32 pixels).

scholarly journals A Method to Quantify Reclaimed Asphalt Pavement Binder Availability (Effective RAP Binder) in Recycled Asphalt Mixes

2019 ◽  
Vol 2673 (1) ◽  
pp. 205-216 ◽  
Author(s):  
Fawaz Kaseer ◽  
Edith Arámbula-Mercado ◽  
Amy Epps Martin
Keyword(s):  
Asphalt Pavement ◽  
Economic Benefits ◽  
Binder Content ◽  
Mix Design ◽  
Void Content ◽  
Reclaimed Asphalt Pavement ◽  
Asphalt Mixes ◽  
Reclaimed Asphalt ◽  
State Highway ◽  
Asphalt Mix

State highway agencies recognize the environmental and economic benefits of utilizing reclaimed asphalt pavement (RAP) in asphalt mixes. Currently, most agencies assume all of the RAP binder content is available for mix design purposes. However, the percentage of available or effective RAP binder in the asphalt mix is usually less than 100% and not quantified, which could yield dry asphalt mix with a high air void content, potentially leading to premature distress. The term available or effective RAP binder refers to the binder that is released from the RAP, becomes fluid, and blends with virgin binder under typical mixing temperatures. This study proposes a method to estimate the RAP binder availability factor (BAF) which can be used to adjust the virgin binder content in RAP mixes to ensure that the mix design optimum binder content is achieved. In this method, asphalt mixes were prepared so that, after mixing and conditioning, the RAP material can be separated from the virgin aggregate, which allows for a thorough evaluation of the extent of RAP binder availability in the asphalt mix. This method was verified in a preliminary experiment and then used to estimate the BAF of RAP from different sources, and a correlation between RAP BAF and the high temperature performance grade (PG) of each RAP source was established. Finally, factors affecting the RAP BAF were also evaluated such as mixing temperature, conditioning period, the use of recycling agents (or rejuvenators), and the method of adding the recycling agent to the mix.

Minimum Voids in Mineral Aggregate in Hot-Mix Asphalt Based on Gradation and Volumetric Properties

1996 ◽  
Vol 1545 (1) ◽  
pp. 75-79 ◽  
Author(s):  
John A. Hinrichsen ◽  
John Heggen
Keyword(s):  
Hot Mix Asphalt ◽  
Heavy Traffic ◽  
Field Application ◽  
Mix Design ◽  
Volumetric Properties ◽  
Aggregate Gradation ◽  
Mineral Aggregate ◽  
Traffic Loads ◽  
Recent Developments ◽  
Asphalt Mix

The use of voids in mineral aggregate (VMA) criteria for proper mix design of hot-mix asphalt is a time-honored and fairly successful tool. Recent developments in the field of asphalt mix design have encouraged the use of mixtures with a coarse aggregate structure to resist the effect of heavy traffic loads. By using the equations presented, which account for both aggregate gradation and the volumetric properties of the materials, the mix designer is able to judge the proper VMA requirement for each unique blend of materials. By applying the new equations, the most economical mix may be selected without great risk of reduced durability. Supporting data from field application are presented to illustrate the use of the equations.

Validation of Performance-Based Specifications for Surface Asphalt Mixtures in Virginia

2021 ◽  
pp. 036119812110566
Author(s):  
Jhony Habbouche ◽  
Ilker Boz ◽  
Stacey D. Diefenderfer
Keyword(s):  
Field Performance ◽  
Performance Criteria ◽  
Mix Design ◽  
Asphalt Mixes ◽  
Performance Predictions ◽  
Asphalt Mix ◽  
Current Threshold ◽  
Test Threshold ◽  
Virginia Department ◽  
Threshold Criteria

The Virginia Department of Transportation (VDOT), like many owner agencies, is interested in ways to facilitate the increased durability of asphalt mixes in an effort to make its roadway network more sustainable, longer lasting, and more economical. The balanced mix design (BMD) method proposes to address this through the incorporation of performance criteria into mix design and acceptance. VDOT has committed to the implementation of the BMD method in an effort to improve asphalt mix performance. The purpose of this study was to continue advancing efforts toward implementation of BMD through the evaluation of 13 asphalt mixes using performance-indicating laboratory tests, validation of the initial performance tests selected for BMD use, and validation of the initial test threshold criteria. Based on the results, the asphalt pavement analyzer (APA) rut test, indirect tensile cracking test (IDT-CT), and Cantabro test were found suitable for continued use in BMD. The current threshold criteria for all three tests were found reasonable based on additional mix testing. The study recommends that APA rut test and IDT-CT results should be compared and correlated to fundamental rutting and cracking tests, respectively, as well as to performance predictions obtained from mechanistic-empirical pavement design simulations, and to field performance for full assurance that test threshold values are appropriate. It was further recommended to evaluate the Cantabro, IDT-CT, and APA rut tests to determine acceptable variability and establish precision statements.

scholarly journals Evaluation and Validation of Characterization Methods for Fatigue Performance of Asphalt Mixes for Western Australia

2013 ◽  
Vol 723 ◽  
pp. 75-85 ◽  
Author(s):  
Ainalem Nega ◽  
Hamid Nikraz ◽  
Colin Leek ◽  
Behzad Ghadimi
Keyword(s):  
Western Australia ◽  
Tensile Modulus ◽  
Fatigue Performance ◽  
Pavement Performance ◽  
Aggregate Gradation ◽  
Asphalt Mixes ◽  
Characterization Methods ◽  
The Road ◽  
Asphalt Mix ◽  
Study Laboratory

The determination of appropriate pavement thickness using laboratory determined parameters is one of the key issues facing the road manager. Five different types of asphalt mixes were produced in laboratory to modify pavement performance mixture. The main objective of this study is to evaluate the characterization methods for fatigue performance of asphalt mixes to Western Australia road. In this study, laboratory test for indirect tensile modulus, dynamic creep, wheel tracking and aggregate gradation tests were taken to analyze each asphalt mixtures for a design traffic road. The results and analysis showed that AC20-75 asphalt mix blow is the most effective and efficient in pavement performance than the other asphalt mixes. AC14-75 was the second in rank to strengthen and durability of asphalt pavement. All asphalt mixes in this study can be used to strength and stable the overall stiffness of pavement, and modification rank can be described as AC20-75 Blow > AC14-75 Blow > AC14-50 Blow > AC7-50 Blow > SMA7-50 Blow in this research.

Study on the Effectiveness Evaluation of the Weapon Equipment Based on Artificial Neural Network

2014 ◽  
Vol 926-930 ◽  
pp. 3262-3265
Author(s):  
Feng Gao ◽  
Fei Song ◽  
Guo Qing Huang ◽  
Mao Yang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Bp Neural Network ◽  
Learning Algorithm ◽  
Effectiveness Evaluation ◽  
Matlab Toolbox ◽  
New Approach ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Better Than

A new approach to weapons and equipment effectiveness evaluation based on artificial neural network (ANN) performs better than traditional method, which is in view of the complex relationship between the effectiveness and many factors that influence the evaluation. The structure and learning algorithm of BP neural network is evaluated the fighters’ air-to-air combat capability. The evaluation is accomplished by a two-layer BP neural network and MATLAB toolbox. The simulation results show that the artificial neural network have better generalization ability and approximation performance for continuous function, which is valuable in weapons and equipment effectiveness evaluation application.

Estimating bearing capacity of shallow foundations by artificial neural networks

2017 ◽  
Vol 3 (4) ◽  
pp. 151
Author(s):  
Mustafa Aytekin
Keyword(s):  
Bearing Capacity ◽  
Ultimate Bearing Capacity ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Average Error ◽  
Large Set ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Capacity Data

In this study, the Artificial Neural Network, ANN is applied to data extracted from a large set of random data created by using Terzaghi and Meyerhof formulae. By using MS Excel, 3750 sets of data for Terzaghi's equation, 4000 for Meyerhof's equation were generated. A simulated ANN was trained on a subset of bearing capacity data, and the performance was tested on the remaining data. The performances of the ANN models were compared to Terzaghi and Meyerhof results. ANN models were as accurate as the other techniques in estimating the ultimate bearing capacity. The models estimated the ultimate bearing capacity with an average error of around 1% of the value obtained from Terzaghi and Meyerhof equations, and the coefficient of determination (r2) was almost equal to 1. Their sensitivity and specificity is dependent on the function and the algorithm used in the training process. Validation subset is crucial in preventing the over-fitting of the ANN models to the training data. ANN models are potentially useful technique for estimating the bearing capacity of the soil. Large training data sets are needed to improve the performance of data-derived algorithms, in particular ANN models.

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