This study employed convolutional neural networks(CNNs)for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces.The image dataset covers 40 distinc...This study employed convolutional neural networks(CNNs)for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces.The image dataset covers 40 distinct rock mineral-types.Three CNN architectures(Simple model,SqueezeNet,and Xception)were evaluated to compare their performance and feature extraction capabilities.Gradient-weighted Class Activation Mapping(Grad-CAM)was employed to visualize the features influencing model predictions,providing insights into how each model distinguishes between mineral classes.Key discriminative attributes included texture,grain size,pattern,and color variations.Texture and grain boundaries were identified as the most critical features,as they were strongly activated regions by the best model.Patterns such as banding and chromatic contrasts further enhanced classification accuracy.Performance analysis revealed that the Simple model had limited ability to isolate fine-grained details,producing broad and less specific activations(0.84 test accuracy).SqueezeNet demonstrated improved localization of discriminative features but occasionally missed finer textural details(0.95 test accuracy).The Xception model outperformed the others,achieving the highest classification accuracy(0.98 test accuracy)by exhibiting precise and tightly focused activations,capturing intricate textures and subtle chromatic variations.Its superior performance can be attributed to its deep architecture and efficient depth-wise separable convolutions,which enabled hierarchical and detailed feature extraction.Results underscores the importance of texture,pattern,and chromatic features in accurate mineral classification and highlights the suitability of deep,efficient architectures like Xception for such tasks.These findings demonstrate the potential of CNNs in geoscience research,offering a framework for automated mineral identification in industrial and scientific applications.展开更多
The effect of tertiary flow length on asphalt concrete(AC) flow number(FN) has been studied in this paper. The standard FN test(AASHTO T378) designated by American Association of State Highway and Transportation Offic...The effect of tertiary flow length on asphalt concrete(AC) flow number(FN) has been studied in this paper. The standard FN test(AASHTO T378) designated by American Association of State Highway and Transportation Officials(AASHTO) is currently among the widely adopted test for assessing the rutting performance of AC mixtures. The standard adopts the Fracken model(FM) for fitting the permanent deformation curve(PDC), prior to FN estimation. The FN was observed to vary as tertiary flow progresses. The FM, along with other PDC models(MFM-1 and MFM-2) obtained by modifying the FM, was utilized to analyze and minimized this variation. Variation of FN resulted because of mathematization of the PDC data. Instead of representing the actual initiating point of permanent shear deformation of the strain data, estimated values of FN were observed to indicate the inflection points of the fitted parent curve. As per standard FN range suggested by AASHTO T378, the observed variation in FN leads to the situation, where a single asphalt mix specimen can be regarded as appropriate for two different traffic levels, depending on the tertiary flow point at which the test is terminated. Supplementary steps in the FN estimation methods were proposed for refinement of FN values. For the refinement and further standardization of FN value and FN test respectively, FN:T(flow number to test duration ratio) has been recognized as the key and most simple solution. Two potential options for employing FN:T in the estimation of FN have also been highlighted. Several important correlations have been reported herein as well. Comparatively, MFM-1 was found to be more robust in FN:T curve utilization than MFM-2 and FM.展开更多
Several previous studies have documented the progress in polymer modified asphalt binder with respect to materials'types and properties.However,limited or no effort was made to document findings on the laboratory ...Several previous studies have documented the progress in polymer modified asphalt binder with respect to materials'types and properties.However,limited or no effort was made to document findings on the laboratory preparation practices of polymer modified asphalt binder.Full and clear disclosure of asphalt blend preparation method is necessary for research continuity,reproducibility,and accurate adaptation by future studies for analogy and reliable conclusions.The laboratory preparation processes of various modified asphalt binders have been reviewed in this study.Factors affecting the optimal mixing of asphalt-polymer blends were summarized.The optimal mixing conditions associated with different asphalt modifiers were documented.Gap in the literature on the current practice for the preparation and reporting of various modified asphalt binder was discussed.Modifiers include styrene butadiene styrene(SBS),polyethylene(PE),waste tire rubber or crumb rubber(CR),ethylene vinyl acetate(EVA),sulfur,polyphosphoric acid(PPA),epoxy,polyurethane,nano-materials,etc.Currently,there is lack of modern innovative approached in the preparation of modified asphalt towards better performance.There is no clear standardized definition of term associated with asphalt binder preparation process.Given the limited and common types of polymers utilized for the modification of asphalt binder,it is possible to standardize the mixing procedure for several polymers.Doing so could ease research continuity and facilitates accurate comparison of new studies with earlier ones.展开更多
Contact angle(CA)is an important material characteristic in the field of pavement materials.It has been instrumental to the development of new and evolving research areas such as the adhesion of pavement components,hy...Contact angle(CA)is an important material characteristic in the field of pavement materials.It has been instrumental to the development of new and evolving research areas such as the adhesion of pavement components,hydrophobic and superhydrophobic concretes,etc.Yet,there are several inconsistencies between studies when it comes to the CA characterization of various pavement materials.This is in part due to the lack of sufficient research and proper documentation of existing knowledge on the CA characterization of pavement materials.This current study has documented and analyzed the processes of measuring the CA of various pavement materials.This includes sample preparation,test conditions,and recommended practices.Studies on the refinement of existing methods for the estimation of CA were also reviewed.The relationships between CA and various pavement and material performances were also reviewed.The increased need for resilient pavements calls for the search for new and effective material characteristics parameters.CA measurements have the potential to change how the properties of fresh cementitious mixes are being assessed.The sessile drop method offers more flexibility for characterizing the CA of pavement materials.The potential application of CA for the improvement and development of new material performance characteristics was discussed.Insights on ways to advance the evaluation of hydrophobic characteristics of pavements were outlined.For example,the use of de-ionized or distilled water for the assessment of hydrophobic properties of concrete does not reflect the moisture condition in the field.CA measurements at different water PH levels should be carried out to replicate the true service condition of the concretes.展开更多
基金support provided by Imam Abdulrah-man Bin Faisal University,Dammam,KSA,in carrying out this research.
文摘This study employed convolutional neural networks(CNNs)for the classification of rock minerals based on 3179 RGB-scale original microstructural images of undisturbed broken surfaces.The image dataset covers 40 distinct rock mineral-types.Three CNN architectures(Simple model,SqueezeNet,and Xception)were evaluated to compare their performance and feature extraction capabilities.Gradient-weighted Class Activation Mapping(Grad-CAM)was employed to visualize the features influencing model predictions,providing insights into how each model distinguishes between mineral classes.Key discriminative attributes included texture,grain size,pattern,and color variations.Texture and grain boundaries were identified as the most critical features,as they were strongly activated regions by the best model.Patterns such as banding and chromatic contrasts further enhanced classification accuracy.Performance analysis revealed that the Simple model had limited ability to isolate fine-grained details,producing broad and less specific activations(0.84 test accuracy).SqueezeNet demonstrated improved localization of discriminative features but occasionally missed finer textural details(0.95 test accuracy).The Xception model outperformed the others,achieving the highest classification accuracy(0.98 test accuracy)by exhibiting precise and tightly focused activations,capturing intricate textures and subtle chromatic variations.Its superior performance can be attributed to its deep architecture and efficient depth-wise separable convolutions,which enabled hierarchical and detailed feature extraction.Results underscores the importance of texture,pattern,and chromatic features in accurate mineral classification and highlights the suitability of deep,efficient architectures like Xception for such tasks.These findings demonstrate the potential of CNNs in geoscience research,offering a framework for automated mineral identification in industrial and scientific applications.
基金support provided by King Fahd University of Petroleum and Minerals (KFUPM)Dhahran KSAImam Abdulrahman Bin Faisal University,Dammam,KSA in carrying out this research。
文摘The effect of tertiary flow length on asphalt concrete(AC) flow number(FN) has been studied in this paper. The standard FN test(AASHTO T378) designated by American Association of State Highway and Transportation Officials(AASHTO) is currently among the widely adopted test for assessing the rutting performance of AC mixtures. The standard adopts the Fracken model(FM) for fitting the permanent deformation curve(PDC), prior to FN estimation. The FN was observed to vary as tertiary flow progresses. The FM, along with other PDC models(MFM-1 and MFM-2) obtained by modifying the FM, was utilized to analyze and minimized this variation. Variation of FN resulted because of mathematization of the PDC data. Instead of representing the actual initiating point of permanent shear deformation of the strain data, estimated values of FN were observed to indicate the inflection points of the fitted parent curve. As per standard FN range suggested by AASHTO T378, the observed variation in FN leads to the situation, where a single asphalt mix specimen can be regarded as appropriate for two different traffic levels, depending on the tertiary flow point at which the test is terminated. Supplementary steps in the FN estimation methods were proposed for refinement of FN values. For the refinement and further standardization of FN value and FN test respectively, FN:T(flow number to test duration ratio) has been recognized as the key and most simple solution. Two potential options for employing FN:T in the estimation of FN have also been highlighted. Several important correlations have been reported herein as well. Comparatively, MFM-1 was found to be more robust in FN:T curve utilization than MFM-2 and FM.
文摘Several previous studies have documented the progress in polymer modified asphalt binder with respect to materials'types and properties.However,limited or no effort was made to document findings on the laboratory preparation practices of polymer modified asphalt binder.Full and clear disclosure of asphalt blend preparation method is necessary for research continuity,reproducibility,and accurate adaptation by future studies for analogy and reliable conclusions.The laboratory preparation processes of various modified asphalt binders have been reviewed in this study.Factors affecting the optimal mixing of asphalt-polymer blends were summarized.The optimal mixing conditions associated with different asphalt modifiers were documented.Gap in the literature on the current practice for the preparation and reporting of various modified asphalt binder was discussed.Modifiers include styrene butadiene styrene(SBS),polyethylene(PE),waste tire rubber or crumb rubber(CR),ethylene vinyl acetate(EVA),sulfur,polyphosphoric acid(PPA),epoxy,polyurethane,nano-materials,etc.Currently,there is lack of modern innovative approached in the preparation of modified asphalt towards better performance.There is no clear standardized definition of term associated with asphalt binder preparation process.Given the limited and common types of polymers utilized for the modification of asphalt binder,it is possible to standardize the mixing procedure for several polymers.Doing so could ease research continuity and facilitates accurate comparison of new studies with earlier ones.
文摘Contact angle(CA)is an important material characteristic in the field of pavement materials.It has been instrumental to the development of new and evolving research areas such as the adhesion of pavement components,hydrophobic and superhydrophobic concretes,etc.Yet,there are several inconsistencies between studies when it comes to the CA characterization of various pavement materials.This is in part due to the lack of sufficient research and proper documentation of existing knowledge on the CA characterization of pavement materials.This current study has documented and analyzed the processes of measuring the CA of various pavement materials.This includes sample preparation,test conditions,and recommended practices.Studies on the refinement of existing methods for the estimation of CA were also reviewed.The relationships between CA and various pavement and material performances were also reviewed.The increased need for resilient pavements calls for the search for new and effective material characteristics parameters.CA measurements have the potential to change how the properties of fresh cementitious mixes are being assessed.The sessile drop method offers more flexibility for characterizing the CA of pavement materials.The potential application of CA for the improvement and development of new material performance characteristics was discussed.Insights on ways to advance the evaluation of hydrophobic characteristics of pavements were outlined.For example,the use of de-ionized or distilled water for the assessment of hydrophobic properties of concrete does not reflect the moisture condition in the field.CA measurements at different water PH levels should be carried out to replicate the true service condition of the concretes.
