This study aims to investigate the efiect of the mesoscopic characteristics of mineral powder fillers on the rutting resistance of asphalt mortar.Extraction and sieving tests were used to obtain the buton rock asphalt...This study aims to investigate the efiect of the mesoscopic characteristics of mineral powder fillers on the rutting resistance of asphalt mortar.Extraction and sieving tests were used to obtain the buton rock asphalt(BRA)ash with particle size smaller than 0.075 mm,which is consistent with that of the conventional mineral powder.The mesoscopic characteristics of BRA ash and conventional mineral powder were measured by SEM image analysis and the osmotic free pressure water method.Mesoscopic structure models of structural and free asphalts in mortar were obtained.The 70#matrix asphalt was used to prepare two kinds of asphalt mortar with BRA ash and conventional mineral powders fillers.The rutting factor of the two asphalt mortars was tested by dynamic shear test(DSR).Test results show that the ash extracted from BRA has a similar mesoscopic classification with the conventional mineral powder.Still,its fractal dimensions are larger,indicating the particles in BRA ash have more complex shapes and rougher surfaces,which is beneficial for forming structural asphalt and subsequently increasing the rutting factor(G*/sinδ),i e,improving the rutting resistance of the asphalt mortar.展开更多
Rutting of asphalt pavements is a crucial design criterion in various pavement design guides. A good road transportation base can provide security for the transportation of oil and gas in road transportation. This stu...Rutting of asphalt pavements is a crucial design criterion in various pavement design guides. A good road transportation base can provide security for the transportation of oil and gas in road transportation. This study attempts to develop a robust artificial intelligence model to estimate different asphalt pavements’ rutting depth clips, temperature, and load axes as primary characteristics. The experiment data were obtained from19 asphalt pavements with different crude oil sources on a 2.038km long full-scale field accelerated pavement test track(Road Track Institute, RIOHTrack) in Tongzhou, Beijing. In addition,this paper also proposes to build complex networks with different pavement rutting depths through complex network methods and the Louvain algorithm for community detection. The most critical structural elements can be selected from different asphalt pavement rutting data, and similar structural elements can be found. An extreme learning machine algorithm with residual correction(RELM) is designed and optimized using an independent adaptive particle swarm algorithm. The experimental results of the proposed method are compared with several classical machine learning algorithms, with predictions of average root mean squared error(MSE), average mean absolute error(MAE), and a verage mean absolute percentage error(MAPE) for 19 asphalt pavements reaching 1.742, 1.363, and 1.94% respectively. The experiments demonstrate that the RELM algorithm has an advantage over classical machine learning methods in dealing with non-linear problems in road engineering. Notably, the method ensures the adaptation of the simulated environment to different levels of abstraction through the cognitive analysis of the production environment parameters. It is a promising alternative method that facilitates the rapid assessment of pavement conditions and could be applied in the future to production processes in the oil and gas industry.展开更多
As a byproduct of the steelmaking process,significant amounts of hazardous electric arc furnace dust(EAFD)are produced.Utilizing the solidification/stabilization technology with asphalt mix is one way to safeguard the...As a byproduct of the steelmaking process,significant amounts of hazardous electric arc furnace dust(EAFD)are produced.Utilizing the solidification/stabilization technology with asphalt mix is one way to safeguard the environment from its negative effects.Rutting was used as an indicator to assess the asphalt mixture with EAFD since it is an important factor in pavement design.This study’s major goal is to ascertain how EAFD affects the rutting of asphalt-concrete mixtures.To evaluate the ideal asphalt content,the Marshall test method was applied to asphalt-concrete mixtures.EAFD was added to the asphalt cement in four different volume percentages as a binder addition.Then,using the Universal Testing Machine,participants were exposed to a replica of the rutting test(UTM).Experiments were conducted at 25℃,40℃ and 55℃,and at frequencies of 1 Hz,4 Hz and 8 Hz.Rutting was measured for each specimen.Test results showed that rut depth has a negative correlation with EAFD%and a positive correlation with temperature.The use of EAFD has dual advantages,protecting the environment from the adverse impact of EAFD and reducing the cost of asphalt mix without jeopardizing pavement performance.展开更多
Nowadays asphalt pavement structure bearing is not the main subject for pursuers to study.Comparatively,the pavement performance is more important and emphasized.Based on this,rutting and cracking analysis is introduc...Nowadays asphalt pavement structure bearing is not the main subject for pursuers to study.Comparatively,the pavement performance is more important and emphasized.Based on this,rutting and cracking analysis is introduced into pavement optimization.A optimization model based on these two considerations is also established.The genetic algorithms (GAs) is adopted to solve the model.It is an intellective method.This research provides a new idea and technique for asphalt pavement structure optimization.展开更多
基金Funded by the National Natural Science Foundation of China(No.51978088)。
文摘This study aims to investigate the efiect of the mesoscopic characteristics of mineral powder fillers on the rutting resistance of asphalt mortar.Extraction and sieving tests were used to obtain the buton rock asphalt(BRA)ash with particle size smaller than 0.075 mm,which is consistent with that of the conventional mineral powder.The mesoscopic characteristics of BRA ash and conventional mineral powder were measured by SEM image analysis and the osmotic free pressure water method.Mesoscopic structure models of structural and free asphalts in mortar were obtained.The 70#matrix asphalt was used to prepare two kinds of asphalt mortar with BRA ash and conventional mineral powders fillers.The rutting factor of the two asphalt mortars was tested by dynamic shear test(DSR).Test results show that the ash extracted from BRA has a similar mesoscopic classification with the conventional mineral powder.Still,its fractal dimensions are larger,indicating the particles in BRA ash have more complex shapes and rougher surfaces,which is beneficial for forming structural asphalt and subsequently increasing the rutting factor(G*/sinδ),i e,improving the rutting resistance of the asphalt mortar.
基金supported by the Analytical Center for the Government of the Russian Federation (IGK 000000D730321P5Q0002) and Agreement Nos.(70-2021-00141)。
文摘Rutting of asphalt pavements is a crucial design criterion in various pavement design guides. A good road transportation base can provide security for the transportation of oil and gas in road transportation. This study attempts to develop a robust artificial intelligence model to estimate different asphalt pavements’ rutting depth clips, temperature, and load axes as primary characteristics. The experiment data were obtained from19 asphalt pavements with different crude oil sources on a 2.038km long full-scale field accelerated pavement test track(Road Track Institute, RIOHTrack) in Tongzhou, Beijing. In addition,this paper also proposes to build complex networks with different pavement rutting depths through complex network methods and the Louvain algorithm for community detection. The most critical structural elements can be selected from different asphalt pavement rutting data, and similar structural elements can be found. An extreme learning machine algorithm with residual correction(RELM) is designed and optimized using an independent adaptive particle swarm algorithm. The experimental results of the proposed method are compared with several classical machine learning algorithms, with predictions of average root mean squared error(MSE), average mean absolute error(MAE), and a verage mean absolute percentage error(MAPE) for 19 asphalt pavements reaching 1.742, 1.363, and 1.94% respectively. The experiments demonstrate that the RELM algorithm has an advantage over classical machine learning methods in dealing with non-linear problems in road engineering. Notably, the method ensures the adaptation of the simulated environment to different levels of abstraction through the cognitive analysis of the production environment parameters. It is a promising alternative method that facilitates the rapid assessment of pavement conditions and could be applied in the future to production processes in the oil and gas industry.
文摘As a byproduct of the steelmaking process,significant amounts of hazardous electric arc furnace dust(EAFD)are produced.Utilizing the solidification/stabilization technology with asphalt mix is one way to safeguard the environment from its negative effects.Rutting was used as an indicator to assess the asphalt mixture with EAFD since it is an important factor in pavement design.This study’s major goal is to ascertain how EAFD affects the rutting of asphalt-concrete mixtures.To evaluate the ideal asphalt content,the Marshall test method was applied to asphalt-concrete mixtures.EAFD was added to the asphalt cement in four different volume percentages as a binder addition.Then,using the Universal Testing Machine,participants were exposed to a replica of the rutting test(UTM).Experiments were conducted at 25℃,40℃ and 55℃,and at frequencies of 1 Hz,4 Hz and 8 Hz.Rutting was measured for each specimen.Test results showed that rut depth has a negative correlation with EAFD%and a positive correlation with temperature.The use of EAFD has dual advantages,protecting the environment from the adverse impact of EAFD and reducing the cost of asphalt mix without jeopardizing pavement performance.
文摘目的 :评价目前临床上常用的两种诊断幽门螺杆菌 (HP)感染方法的敏感性、特异性。方法 :对 186例因消化道症状就医的老年患者行胃镜检查 ,同时行13 C 尿素呼气试验 ( 13 C UBT) ,快速尿素酶 (RUT)试验检查 ,用活检钳钳取胃窦黏膜组织行病理学检查。结果 :13 C UBT较RUT检查的敏感性、特异性高。结论 :13 C UBT和RUT具有安全、简便、可靠、无创的特点 ,是较好的HP检测方法 ,对于老年病人13 C
文摘Nowadays asphalt pavement structure bearing is not the main subject for pursuers to study.Comparatively,the pavement performance is more important and emphasized.Based on this,rutting and cracking analysis is introduced into pavement optimization.A optimization model based on these two considerations is also established.The genetic algorithms (GAs) is adopted to solve the model.It is an intellective method.This research provides a new idea and technique for asphalt pavement structure optimization.
