Wax is an important factor that affects the durability of asphalt binder. In order to understand the molecular weight distribution and branching of wax on the moisture sensitivity of asphalt binder, pure wax-doped asphalt binders are prepared and the performance of model asphalt binders are evaluated by surface free-energy (SFE) and binder bond strength (BBS) tests. In addition, asphaltene is regarded as an additive in this study. The results show that the addition of eicosane, triacontane, squalane and asphaltene can reduce the moisture sensitivity of asphalt, but not necessarily improve its moisture-induced damage resistance. The physical hardening effect of high-wax asphalt and its model asphalt is stronger than that of the corresponding low-wax asphalt and its model asphalt, and its moisture sensitivity is weaker than that of the low-wax asphalt. For all the model asphalts, there is a good correlation between the cohesion work, cohesion POTS (pull-off tensile strength), POTS ratio (the BBS moisture sensitivity index) and ER (the SFE moisture sensitivity index). When using the BBS test to characterize the moisture sensitivity of high-wax asphalt, it is recommended to leave the sample for some time until it is physically hardened and stable. The strong moisture sensitivity of asphalt mixture is one of the main reasons for early distresses in asphalt pavement, such as grouting, spalling, looseness and potholes . The proThe wax in asphalt is a mixture of saturated n-alkanes and a small amount of isoalkanes, with carbon atom numbers ranging from 20 to 40 ,6. The w20H42 could significantly aggravate the thermoreversible aging performance of asphalt binder, while C30H66 and asphaltene have no similar effect.However, the existing studies only analyzed the effect of wax on the thermoreversible aging and moisture sensitivity of asphalt from a mixture point of view (mainly wax-based warm-mix additive), and had not studied it from the molecular weight distribution and branching of wax perspectives ,20. In oTo sum up, most of the existing studies on the wax of asphalt only focus on the wax-based mixture side, analyzing the effect of wax on the thermoreversible aging and moisture sensitivity of asphalt, but not the effect of the molecular weight distribution and branching of wax on the moisture sensitivity of asphalt binder. In view of this, this paper uses two mature moisture sensitivity testing methods, based on the surface free-energy (SFE) test and binder bond strength (BBS) test, to study the influence of the molecular weight distribution and the branching of wax on the moisture sensitivity of asphalt binder. In addition, because asphaltene has a strong polarity, it can explain the influence of wax on thermoreversible aging from the mechanism ,23, and In this paper, asphalt samples A and B are selected as the base asphalt. Sample A is a low-wax asphalt and is produced in Venezuela. Sample B is a high-wax asphalt and is produced in China. The base asphalt, with a different wax content, is selected to analyze the influence of its own wax content on moisture sensitivity. The main technical indices of asphalt A and B are shown in The number of carbon atoms of wax in asphalt is between 20 and 40 ,27. In tBBS tests started in the architectural coatings industry, and they can intuitively and conveniently measure the adhesive properties of materials in a short time. ASTM D4541  and AASHThe forming steps of the BBS specimen are as follows: (1) cleaning slate; (2) place the asphalt, drawing head and granite plate into a 150 °C oven to heat for 30 min; (3) take the asphalt out of the oven, drop it into the silica gel pad, and immediately press the drawing head onto the top of the asphalt, as shown in γ is defined as the work that the outside world needs to do when a unit surface area is generated on the surface of an object [LWγ and polarity components ABγ, as shown in Equations (1) and (2). Because asphalt is a viscous substance, it is difficult to ensure the same dripping quality of asphalt every time, and it is easy to draw wires during dripping. Therefore, in this paper, the DSA100 contact angle meter, produced by the KRUSS company, is used to test the contact angles of the distilled water and glycerin, and to form amide with the asphalt by the sessile-drop method. Then, the contact angles are brought into the Young–Dupre equation shown in Equation (3) to indirectly calculate the surface free-energy parameters of the asphalt [Surface free-energy n object . It cons asphalt . The SFEθ between the chemical reagents and the asphalt. The larger the contact angle θ, the more distant the mutual combination level between them, and vice versa, the closer they are, as shown in The test method of the contact angle is as follows: (1) Put the asphalt sample into a 160 °C oven and heat it to a flowing state; (2) soak the cleaned glass slide in hot asphalt for 4~5 s, then hang it vertically in the oven for 10 min, so that the excess asphalt drips freely; (3) after the glass slides are cured at room temperature for a certain period of time, the contact angle tester is used to test the contact angle γ, LWγ and ABγ represent surface free-energy, the dispersion component and polarity component, respectively; γ+, γ− and θ represents an acid component, basic component and contact angle, respectively. The lower corner marks S and L represent the asphalt and chemical reagents, respectively.In Equations (1)–(3), In this paper, ten kinds of model asphalt  are prepared by using two kinds of base asphalt and four kinds of additives, which are A/B, A/B + C20, A/B + C30, A/B + Sq and A/B + As, respectively. The BBS and SFE tests are used to test the moisture sensitivity parameters of the above ten kinds of model asphalt at room temperature and at the conditioning times of 1 h and 168 h, respectively. The parallel tests are all four groups. The specific test contents are shown in The wax in asphalt has obvious thermal sensitivity. It dissolves in asphalt at high temperatures and precipitates in the form of crystals at normal and low temperatures, which makes asphalt hard. Struik  named thValue (1 h) and Value (168 h) represent the moisture sensitivity parameter values of the conditioning times of 1 h and 168 h, respectively.In Equation (4), DPH is the abbreviation for the degree of physical hardening, and the closer its value is to 1, the smaller the physical hardening effect is, otherwise, the larger it is; The BBS test usually shows the cohesion failure of the asphalt–asphalt interface before moisture-induced damage occurs, and the adhesion failure of the asphalt–aggregate interface after 48 h of moisture-induced damage . TherefoFrom In this paper, according to AASHTO T283 , the ratIn Equation (5), Adhesion POTS represented POTS after moisture-induced damage, Cohesion POTS represented POTS before moisture-induced damage.In order to verify the accuracy of the BBS test, this paper analyzes the effects of the molecular weight distribution and the branching of wax and asphaltene on the moisture sensitivity of asphalt, based on SFE. The solution process of the surface free-energy moisture sensitivity parameter ER of asphalt is as follows: Equations (8)–(10) can be derived from Equations (6) and (7). By placing the surface free-energy parameters of asphalt, aggregate and water into Equations (8)–(10), the cohesion work of the asphalt itself, the adhesion work of the asphalt–aggregate interface (dry condition) and the adhesion work of the asphalt–aggregate interface (wet condition) can be obtained. The ER can be obtained by substituting the adhesion work under dry and wet conditions into Equation (11). The larger the ER, the smaller the moisture sensitivity, and on the contrary, the greater the moisture sensitivity. The aggregate is granite and the surface free-energy parameters are shown in Gij is the interfacial binding energy between two-phase materials, γij is the interfacial energy of two-phase materials, iγ is the surface energy of substance i, jγ is the surface energy of j, and Gikj is the interfacial binding energy of three-phase materials.In Equations (6) and (7), AA’W, AG’W, AWGW and ER are cohesion work, adhesion work in a dry condition, adhesion work in a wet condition and the moisture sensitivity index, respectively.In Equations (8)–(11), In order to study the correlation between the SFE and BBS tests in evaluating the moisture sensitivity of the molecular weight distribution and the branching of wax and asphaltene of the asphalt binder, two groups of parameters or indices, representing the same meaning in the two test methods, were analyzed. Among them, the cohesion POTS (BBS) and cohesion work (SFE) both characterize the degree of failure of the asphalt–asphalt interface, while the POTS ratio (BBS) and ER (SFE) both characterize the moisture sensitivity of asphalt.(1)The addition of n-eicosane, n-triacontane, squalane and asphaltene can reduce the moisture sensitivity of the base asphalt, but not necessarily improve its moisture-induced damage-resistance performance.(2)For the cohesion POTS, regarding the cohesion and adhesion work in dry conditions, physical hardening has the greatest influence on n-eicosane, followed by n-triacontane. However, squalane and asphaltene have no obvious influence.(3)The physical hardening effect of high-wax asphalt and its model asphalt is stronger than that of the corresponding low-wax asphalt and its model asphalt, and its moisture sensitivity is weaker than that of low-wax asphalt.(4)Different molecular weight distributions and the branching of waxes will have different effects on the moisture sensibility of the asphalt binder.In this paper, the BBS and SFE tests are used to study the effects of the wax molecular weight distribution and branching on the moisture sensitivity of asphalt. The following conclusions can be drawn:


GF/rubber composites have sound insulation characteristics, heat resistance, good corrosion resistance, and high mechanical strength. The compounding machine’s long working hours will inevitably wear the metal on the end face of the compounding machine. The wear of the end face metal will increase the gap between the chamber and the end face, which will lead to material leakage, reduce the mixing effect, and eventually affect the performance of GF/rubber composites. To ensure the implementation of GF/rubber composites, it is necessary to study the frictional wear behavior of GF/rubber composites on metals. In this paper, the effect of blending rubber with different amounts of GF on the frictional wear of metal on the end face was analyzed from the perspective of the formulation process, and the ratio of corrosion wear and abrasive wear was calculated for the first time. Glass fiber is a kind of material with excellent performance, which has many types, low price, and high mechanical strength. It is widely used in the reinforcement of polymer materials. The composites obtained by adding glass fibers have excellent properties. It has been reported that the composite material of glass fiber and rubber has good comprehensive properties and can improve its anti-skid performance ,2,3,4,5.Li Hong  reviewedYang Chuanqi  used theWang Wenjie  used glaChen Jiabin  preparedLv Fuling  preparedHao Qiangqiang  preparedThe preparation of GF/rubber composites is carried out in the compounding machine. With the development of GF/rubber composites, the use time of the compounding machine, which is the equipment for preparing GF/rubber composites, has increased dramatically, bringing about the wear and tear of the compounding machine. This paper studies the frictional behavior of GF/rubber composites with different ratios and end metals during the mixing process.The experimental equipment used in this experiment is shown in 2/g, 7–40 nm particle size, and solid powder, Solvay Silica Co., Ltd., ; GF diameter is 12–23 μm, length is 0.2–0.6 mm, and the surface is not treated.The following were used: Butadiene Rubber 9000 (BR9000), China Hainan Natural Rubber Industry Group Co., Ltd., ; Polymeric Styrene Butadiene Rubber (RC2557S), Dongguan Futai Rubber Trading Co., Ltd., ; Natural Rubber (TSR20), China Hainan Natural Rubber Industry Group Co., Ltd., ; Bis-[γ-(triethoxysilyl)propyl]tetrasulfide (TESPT), Antioxidant 4020, Zinc Oxide ZnO, Stearic Acid SAD, 1,3-Diphenylguanidine (DPG), accelerator CZ, and sulfur S, products of China Henan Longji Chemical Co., Ltd., ; Glass Fiber (GF), Wanlong Composite Materials Co., Ltd., ; Silica115MP has a specific surface area of 115 mThe GF/rubber composites were obtained after 5 min by mixing according to the mechanical compounding process in G’ curve with strain was obtained [This test was performed on the RPA 2000, and the test conditions were set as follows. The silica Durocher Stabilized Cool Down scan test conditions were 0.01 Hz scan frequency, 0.28–40% scan strain range, and 60 °C temperature, and the dynamic modulus obtained ,15,16,17(1) Payne effect: The phenomenon in which the elastic modulus of a filler compound decreases as the strain amplitude decreases ,19,20.(2) Silanization reaction index: Characterize the extent to which the silanization reaction proceeds. The calculation method is shown in The Hake mixer is shown in The CSM was parameterized before the experiment. The rotation speed of the CSM was the same as that of the Hake mixer, which was set to 70 r/min, the pressure was set to 5 N, and the friction time of the CSM was set to 30 min. Previous studies have shown that the most severe wear occurs at the end of the experiment, so the CSM temperature was set to 150 °C. The CSM friction and wear tester is shown in (3) Metal surface observation: The metal grinding head was placed on the stage and the LEXT OLS5000 3D microscope was used to emit a laser to scan the metal surface to obtain metal surface data ,27,28.(4) Dispersion: The rubber sample was tested with a DisperGRADER disperser, and the dispersion value was obtained through equipment analysis.The silanization reaction is divided into two steps, as shown in The forms of friction between GF/rubber composites and metals are mainly classified as abrasive and corrosive wear, and this study focuses on these two aspects:2 particles have the characteristics of extremely easy agglomeration, while SiO2 particles are complex and irregular surfaces, so SiO2 particle aggregates are the leading cause of abrasive metal wear [(1) SiOtal wear ,42,43,44(2) The high-temperature ethanol–water mixed vapor will cause corrosion wear to the metal.The stress–strain curves of GF/rubber composites with different ratios are shown in The data from 2 particles in the rubber matrix. This promotes the dispersion of SiO2 particles in the rubber matrix and reduces the number of SiO2 particle agglomerates. Therefore, the Payne effect of GF/rubber composites decreases with GF addition. GF is a spatial filamentous structure, which is easy to agglomerate with each other in the rubber matrix, which hinders the dispersion of SiO2 particles. Meanwhile, the total surface area decreases after GF accumulation, and the adsorption of SiO2 particles is weakened. All of this leads to an ever-increasing Payne effect.GF has a unique spatial structure, and its surface can adsorb SiOFrom The silylation reaction indices of GF/rubber composites with different ratios are shown in It can be seen from 2 particles are continuously adsorbed on the surface of GF, which promotes the dispersion of SiO2 particles and reduces the number of SiO2 particle agglomerates in the rubber matrix. SiO2 particles have high physical hardness. The SiO2 particle aggregates have complex and irregular shapes, making the composite material have serious friction against the metal during the friction process, and the friction coefficient is significant. When the content of GF in the rubber matrix exceeded 3 phr, the aggregates of SiO2 particles in the rubber matrix continued to increase, which made the friction between the composite material and the metal intensify during the friction process and the friction coefficient increased.It can be seen from It can be seen from 2 particles in the composite material without GF added, and the dispersion of SiO2 particles could not be promoted, so the metal wear was severe.From 2 particles were adsorbed on the surface of GF, which reduced the number of SiO2 particle agglomerates in the composites. The SiO2 particle aggregates have complex and irregular shapes, making the composites produce severe friction with the metal during the friction process. With the reduction of SiO2 particle agglomerates in the composites, the abrasive wear of the composites to metals was gradually weakened. With the increase of the degree of the silanization reaction, the amount of high-temperature ethanol–water vapor increased, which increased the proportion of corrosion wear.During the mixing process of the composites with 1 part of GF added, some SiO2 particles increased, and GF could adsorb more SiO2 particles, which better promoted the dispersion of SiO2 particles and further reduced the number of silica aggregates. Therefore, the GF/rubber composite with 1 phr of GF and the GF/rubber composite with 3 phr of GF had minor wear on the metal. As can be seen from When 3 phr of GF was added, the surface area of GF that could adsorb SiOThe abrasive wear amount of the metal grinding head is shown in No high-temperature steam was sprayed during this experiment, and there was no corrosion and wear of metal, so the data measured in this experiment were the amount of abrasive wear. As can be seen from 2 particles reached the maximum, and the SiO2 particles were best dispersed. Therefore, the GF/rubber composite with a 3 phr GF addition had the most significant degree of silanization reaction and the highest percentage of corrosion and wear. Compared with the experimental groups with 0, 1, 5, and 7 phr of GF added, the corrosion wear rate with 3 phr of GF increased by 115.2%, 56.4%, 116.8%, and 748%, respectively.The increase in the degree of silanization reaction increased the amount of high-temperature ethanol–water mixed vapor, which increased the proportion of corrosive wear. When the GF addition amount was 3 phr, the contact area between GF and SiO2 particles. As can be seen from 2 particles in the composite material increased continuously, and the wear of the composite material to the metal increased. This resulted in severe wear on the metal surface and increasing roughness variation.From 2 particles. With the increase of GF content in the composite matrix, the degree of the silanization reaction of the composite material first increased and then decreased. The amount of high-temperature ethanol–water mixed vapor corresponds to the degree of the silanization reaction. The proportion of abrasive wear of GF/rubber composites to metals decreased and then increased, and the proportion of corrosive wear increased and then decreased. With the increase of GF addition, the contact area between GF and SiO2 particles gradually increased, the dispersion of SiO2 particles was enhanced, the number of silica aggregates decreased, and the amount of GF/rubber composites to metal wear decreased. When the addition amount of GF was 3 phr, the GF/rubber composite had the lowest wear on metal. When the addition amount of GF exceeded 3 phr, there was a large amount of accumulation between GF, the contact area between GF and SiO2 particles gradually decreased, the dispersion of SiO2 particles decreased, the number of silica aggregates increased, and the wear amount of GF/rubber composites on metal increased. In the long run, the strengthening and transforming infrastructure in the Middle East and Asia-Pacific will increase the demand for GF. This study plays a vital role in reducing the wear of the internal mixer, improving the life of the internal mixer, and ensuring the performance of GF-modified rubber.This study found that GF has a large surface area, and its surface can adsorb nano-SiO


This causes two effects: one is the caprock swelling induced by the CO2 adsorption and the other is the caprock dehydration and shrinkage due to CO2–brine water two-phase flow. The competition of these two effects challenges the caprock sealing efficiency. To study the evolution mechanism of the caprock properties, a numerical model is first proposed to investigate the combined effects of CO2 adsorption-induced expansion and dehydration-induced shrinkage on the caprock sealing efficiency. In this model, the caprock matrix is fully saturated by brine water in its initial state and the fracture network has only a brine water–CO2 two-phase flow. With the diffusion of CO2 from the fractures into the caprock matrix, the CO2 sorption and matrix dehydration can alter the permeability of the caprock and affect the entry capillary pressure. Second, this numerical model is validated with a breakthrough test. The effects of the two-phase flow on the water saturation, CO2 adsorption on the swelling strain, and dehydration on the shrinkage strain are studied, respectively. Third, the permeability evolution mechanism in the CO2–brine water mixed zone is investigated. The effect of dehydration on the penetration depth is also analyzed. It is found that both the shale matrix dehydration and CO2 sorption-induced swelling can significantly alter the sealing efficiency of the fractured caprock.Carbon dioxide (CO The CO2 accumulates gradually from the reservoir to the bottom of the caprock layer during the sequestration process [2 gradually penetrates into the caprock layer [2 after the breakthrough of the caprock layer damages the safety of the storage reservoir. Therefore, the key issue to the CO2 geological sequestration is the caprock sealing stability and efficiency. How the dehydration of the shale matrix alters the sealing efficiency during the CO2–water displacement has not been well investigated so far [The potential leakage of the stored carbon dioxide from the caprock layers is an important environmental safety issue to the COrmations ,2. The neservoir ,4. Theseeservoir . The traeservoir ,7,8,9. Feservoir ,11. The  process ,13,14 anck layer ,16 and tck layer . The lead so far .2. These micropores are small in size and fully or partially saturated in the caprock layer [2–brine two-phase flow. Therefore, the combination of two-phase flow in the fractures, CO2 sorption and diffusion in the matrix, and the matrix dehydration makes up the main transport mechanisms [2 sorption and dehydration induce the swelling or shrinkage of the shale matrix and may modify the stability of the caprock sealing. A caprock layer may be highly fractured and heterogeneous, even at the depth of 4 km ,19. Macrck layer . The maick layer . Closelyck layer ,24. Theschanisms . Both th2 displaces the water in the matrix of the caprock. This change results in the shrinkage of the shale matrix, thus enlarges the aperture of the shale fractures and may enhance the caprock permeability [2 molecules onto their internal surfaces, thus inducing the swelling of the matrix and the closing of some fractures. The swelling of the caprock matrix is contributed by these two competitions of a dehydration-induced shrinkage and a sorption-induced swelling. The competition effects promote the self-limiting or self-enhancing change in the physical and mechanical properties of caprocks throughout the multi-physical interaction process [2 sorption and dehydration in the caprock matrix are the key issues in the evaluation of the caprock sealing efficiency. If the caprock is water saturated, the dehydration of the matrix may impact the caprock sealing efficiency. Some water-saturated minerals are fully swelled under in situ conditions ,26. The eability ,27. On t process . Hence, 2–brine water two-phase flow in the caprock layer is a multi-physical process [2–brine two-phase flow in the fractures, the gas diffusion in the caprock matrix, and the dehydration- and sorption-induced swelling are all included in this multi-physical process. The CO2 sorption/desorption, pore pressure, mechanical deformation or stress compaction, and geochemical reaction may be altered in these mechanical processes. The fractures are filled with the CO2–brine water two-phase flow. The two-phase flow may stimulate the local deformation of the caprock and change the wettability of the caprock and the entry capillary pressure of the fractures [2–rock interaction, thus altering the porosity and permeability of the caprock [2 sorption has an important impact on the stability of the caprock sealing. The results are variable with the organic compositions, types, and shale contents [2 penetration upward or the efficiency of the caprock sealing, but no publication exploring this is available presently.The CO process . The mecractures . In addi caprock ,31. The contents . Furthercontents . On the contents ,25. Ther2 adsorption-induced swelling and dehydration-induced shrinkage on the caprock sealing efficiency are investigated in this paper. First, a two-phase flow in the fractures, the diffusion processes for CO2–brine water in the shale matrix, and the mechanical compaction process of fractured caprock are represented in a conceptual model. Then, the porosity and permeability constitutive models with the effect of the dehydration process are developed, respectively. The entry capillary pressure is also expressed mathematically. These models together constitute a new coupled multi-physical model. It is an extension of our previous model for the efficiency of the caprock sealing [The combined effects of CO sealing ,24. Thir2 at the bottom of the caprock layer continuously increases with the CO2 accumulation from the storage reservoir. If the CO2 pressure is lower than the sum of the reservoir pressure and entry capillary pressure [2 migration. The Darcy flow starts once the gas pressure is over the sum of the reservoir pressure and the entry capillary pressure [2 displaces the pore water in the caprock layer. The disturbance mechanisms of caprock sealing induced by a two-phase flow stimulation are complex. The pressure of COpressure ,35, the 2 penetrates into the fractures [2 in the fracture network gradually diffuses into the shale matrix, water in the shale matrix will be replaced by CO2 and then enters the fractures. These two processes are usually diffusive and called sorption and dehydration, respectively. 2–brine water two-phase flow is observed only in the fracture network. However, due to the interaction between the shale caprock and CO2, the CO2 adsorbs into the matrix and water is then produced due to the dehydration [2 adsorption-induced swelling and dehydration-induced shrinkage  the propagation of gas front-induced mechanical process; (3) a CO2 diffusion and adsorption into the caprock matrix; (4) the water dehydration of the matrix; and (5) the geochemical reactions among CO2, water, and caprock [2–brine water two-phase flow in the fracture network is instantly started when the entry capillary pressure is run over. The diffusion, dehydration, and geochemical reaction processes may be long term, such as the span of geological time [Caprocks are a mostly fractured porous media which consist of fractures and a matrix. The fracture usually has a much lower entry capillary pressure than the shale matrix. The shale caprock of water-saturated is different from the shale gas reservoir. The pore water still remains in micropores after the COractures . As CO2 ydration . The matkage see . Therefo caprock . The fircal time .2–brine water displacement mechanism in a shale matrix block is depicted in 2–brine water two-phase flow. The phase pressures changed continuously with the two-phase flow process in the fracture network  is the ratio of water mass to solid mass as:Equation (4) is a relationship among the porosity, water content, and water saturation. Obviously, any change in one factor may induce a change in the other two. Further, the water loss in the shale matrix (or the dehydration process) may be not only from free water but also from some bonding water . At thisThis bonding water is usually regarded as a part of the solid particles. If this bonding water does not contribute to a shrinkage deformation, the water content of the shale matrix is revised as:(7) is able to describe this relationship.This matrix shrinkage is measured by the volumetric strain os shale  is preseThe porosity ratio is obtained as:Both the fractures and matrix contribute to the total deformation of the fractured shale see .The change in the fracture aperture is:Equation (10) can be reformulated as: The local fracture strain is derived as:The initial permeability of the fracture is expressed as the following cubic law:If fracture aperture Combining Equation (14) with Equation (13) yields the permeability ratio of the fracture as:In two-dimensional space, this permeability ratio is:2 containment capacity of the caprock and depends on both the pore geometry in the matrix and the CO2/brine water/rock wettability [2, and caprock. The caprock is initially water saturated. The entry capillary pressure  limits ttability . The entThe current aperture of a fracture is:It is equivalent between the aperture of a fracture and the representative radius of a pore in this paper. In the calculation of the entry capillary pressure in a fracture, i’ denotes the initial state. The interfacial tension and wettability are influenced by the pressure, temperature, or chemical reactions during CO2–brine water–rock contacting process [2 entry pressure is concluded as:Here, the subscript ‘ process . If thes2 after considering the effective strain.This is our new entry pressure of CO2 is denoted by:2 in the matrix at pressure 2 between the fractures and the shale matrix and is expressed as:The sorption rate of CO2 in the matrix.The diffusion time is defined as:The dehydration of the shale matrix is still assumed to follow a diffusion process . In thisThe diffusion time of water in the shale matrix is denoted as:e matrix . 2–brine water two-phase flow displacement is complicated in a porous media [26) and (24) have the same form. The COus media , but canus media :(26)dmbw2–brine water two-phase flow occurs in the fractures. CO2 is considered as the non-wetting phase, and the brine water is considered as the wetting phase. According to the mass conservation law, the governing equations of CO2 and brine water are obtained as follows.The COFor the brine water phase:2 has two unique features: (1) a strong compressibility in both free and supercritical states and (2) the existence of both free and absorbed phases in the fractures. Furthermore, the CO2 diffuses from the fractures into the matrix and displaces the pore water in the shale matrix. The mass of CO2, Being different from the brine water, the CO2 phase include a free-phase form (the first term), an absorbed form in the fracture network (the second term), and the mass exchange from the matrix (the third term).Equation (28) shows that the storage states of the CO2 phase:2 in the fracture network, respectively. The viscosity at in situ conditions is 2. 2. 2 in the fractures. 2, respectively. 2 and the shale caprock under the standard conditions, respectively. For the CObilities  of the b2 density, 2, respectively. 2. 2 pressure and temperature. The equation of the state gives the CO2, The pressure of COIntroducing the relationship between the capillary pressure and saturation yields the final form of two-phase flow governing equations in the fractures.For the brine water flow:2 flow:For the CO2. It is provided by the diffusion processes of free gas and absorption/adsorption process of adsorbed gas in the shale matrix Gui,Equation (36) shows that there are four sources of the body force: the body force induced by dehydration-swelling  state and a fully saturated without the dehydration  state. The time of the numerical calculation was 317 years (1010 s). 2–brine water two-phase flow process, two competitive factors result in the swelling or shrinkage of the shale matrix. 2 sorption with time. The observation point is located at 0.1 m away from the lower face. The CO2 diffusion causes the swelling of the shale matrix. At the same time, the dehydration process makes the shale matrix shrink, as shown in 2 sorption-induced swelling and the dehydration-induced shrinkage makes the permeability ratio slightly increase, then decrease, and finally reach a low value. The impacts of dehydration-induced shrinkage on the CO2 sorption-induced swelling and the dehydration-induced shrinkage. As the flow paths narrow down and even close under the action of the swelling, the permeability in the fractures will decrease and the penetration speed of the CO2–water front will slow down [2 diffusion can induce the shale matrix dehydration [2 diffusion. The worst case is to reopen the flow channels which are closing due to a full swelling of the shale matrix under in situ conditions. Such an increase in the apertures increases the permeability and penetration depth [2. 2–water front. After the two-phase flow, the permeability decreases by about 10% along the flow direction for the base case and approximately 6% from the contribution of dehydration. In this regard, the dehydration process has an effect on the swelling strain. In addition, the self-limiting/enhancing capacity has also been influenced. On this sense, it can be concluded that the strong dehydration within the caprock can significantly influence the caprock sealing. For the water-saturated caprock, the CO2 infiltration may cause the matrix dehydration [The self-limiting mechanism of caprock is complicated. This mechanism comes from the two competitions of the shale matrix swellings: the COlow down . If the ydration . This deon depth . This coydration . Therefo2 adsorption-induced swelling and dehydration-induced shrinkage on the permeability and entry capillary pressure of the fracture network were studied through this model. Particularly, the impact of the dehydration-induced shrinkage on the penetration depth was particularly studied. The following conclusions can be drawn from these investigations:A multi-physical coupling model was proposed to investigate the effects of dehydration and sorption on the efficiency of the caprock sealing. This model was further validated by a gas breakthrough test. The combined effects of COFirst, this multi-physical coupling model is a sound tool for the assessment of the sealing efficiency of caprock. It includes the capacity of our previous model in illustrating the physical and mechanical properties of caprock, such as the compaction deformation, gas flow, and sorption. It also expands its capacity, including the dehydration of the shale matrix and the porosity and permeability evolution in the fracture network due to the dehydration shrinkage and compaction.2–brine two-phase flow region and the gas sweeping region. These evolutions are the interaction results among the CO2 diffusion, mechanical compaction, two-phase flow, CO2 sorption-induced swelling, and dehydration-induced shrinkage. These interactions cause the effects of self-enhancing/limiting in these regions due to a swelling/shrinkage of the shale matrix. Second, the evolution mechanisms of the porosity and permeability are complicated and complex, particularly in the CO2 infiltration may cause the matrix’s dehydration from the water-saturated caprock. This matrix dehydration can induce the re-opening of some fractures, enhance the permeability, and reduce the efficiency of caprock sealing, thus being a potential risk for CO2 geological sequestration. Caprock dehydration is worthy of being carefully considered in the evaluation of the caprock sealing efficiency.Finally, the sorption-induced swelling and dehydration-induced shrinkage in the saturated shale caprock are two competitive factors to alter the efficiency of caprock sealing. A CO


Then, using a Fenton-like process, synthetic wastewater containing 100 to 500 mg/L amoxicillin antibiotic was investigated, and the effects of different parameters, such as the frequency (1 and 2 kHz), contact time (15 to 120 min), the concentration of hydrogen peroxide , the dose of zero-valent iron nanoparticles , and pH  were thoroughly studied. A pH of 3, hydrogen peroxide concentration of 3%, ultrasonic-wave frequency of 130 kHz, zero-valent iron nanoparticles of 0.5 g/L, and contaminant concentration of 100 mg/L were obtained as the optimal conditions of the combined US/H2O2/nZVI process. Under the optimal conditions of the combined process of zero-valent iron nanoparticles and hydrogen peroxide in the presence of ultrasonic waves, a 99.7% removal efficiency of amoxicillin was achieved in 120 min. The results show that the combined US/H2O2/nZVI process could be successfully used to remove environmental contaminants, including antibiotics such as amoxicillin, with a high removal percentage.High concentrations of antibiotics have been identified in aqueous media, which has diminished the quality of water resources. These compounds are usually highly toxic and have low biodegradability, and there have been reports about their mutagenic or carcinogenic effects. The aim of this study was to apply zero-valent iron-oxide nanoparticles in the presence of hydrogen peroxide and the sonolysis process for the removal of the amoxicillin antibiotic from aqueous media. In this study, zero-valent iron nanoparticles were prepared by an iron chloride reduction method in the presence of sodium borohydride (NaBH Drugs and related products have been considered a major concern in recent years and have drawn a lot of attention. Drugs treat or prevent microbial infections in humans and even animals. Pharmaceutical compounds such as antibiotics are detected in aqueous environments. These compounds are present in surface water, groundwater, wastewater, and even drinking water. Pharmaceutical compounds can be released into the environment in a variety of ways, such as through the pharmaceutical industry, hospital effluents, and human and animal feces. Typically, 3000 types of drugs are used in the UK , and theLow biological biodegradability , high toThe β-lactam group accounts for 65% of global antibiotics, among which the amoxicillin group is the most widely used . In Iran2O2/nZVI process to remove 2,4-dichlorophenoxyacetic acid [Zhou et al. used a combination of iron nanoparticles and the hydrogen peroxide process to remove 4-chlorophenol . Vahidi tic acid .2O2 combination process was investigated. Ultrasonic waves increase the oxidation and production of ferrous ions, which have more hollow spaces than zero-valent iron (Reaction 1). The generated ferrous ions react with hydrogen peroxide in the reaction medium and activate the production of hydroxyl radicals, which in turn oxidize the organic compounds (Reactions 1–2). This reaction is the so-called Fenton system. However, these reactions have some limitations, among which is the generation of intermediate products such as Fe(OOH)2+ (Reaction 5) and Fe(OH)2+ (Reaction 7). Ultrasonic waves, unlike iron, induce the generation of the hydroperoxy radical (•OOH) (Reaction 6) and hydroxyl radical (•OH) (Reaction 8) [Recently, a study was conducted on the activation of hydrogen peroxide with a pseudo-catalyst using powdered iron . In thisction 8) ,21. TherUnder optimum conditions, the generated ferric ions (Reaction 2) can react with the excess hydrogen peroxide (Reaction 5) or water (Reaction 7). Ferric ions also react with oxidase (Reaction 10) or metallic iron (Reaction 11) when they are converted to ferrous species, and this cycle continues.The above point clearly indicates that Fenton reactions are limited to the presence of iron cations in the intermediate reaction, as well as the ability of the intermediate reaction to regenerate and continuously produce the solute iron species. Research has shown that ultrasonic waves play a critical role in the dissolution of iron particles in a medium; therefore, the addition of zero-valent iron (for the generation of ferrous and ferric ions) and hydrogen peroxide  and ultrasonic irradiation induce complex redox reactions, which in turn cause the degradation of the antibiotic .AMX + In light of the issue of amoxicillin in hospital effluents and water resources and, ultimately, its effects on human health, the goal of the current study was to synthesize zero-valent iron nanoparticles, determine their characteristics, and combine them with hydrogen peroxide along with ultrasonic waves to investigate amoxicillin removal from aqueous solutions.The amoxicillin antibiotic and methanol were obtained from Sigma Aldrich , and hydrochloric acid was obtained from Scharlau Chemie . Hydrogen peroxide 30%, sulfuric acid 98%, sodium hydroxide, potassium iodide, sodium thiosulfate, and starch were purchased from CMC . Whatman filters with a pore size of 1.5 microns were obtained from Prolabo  to filter the samples.3) solution with a solution containing a reducing agent. The ferric chloride solution was prepared by dissolving 0.4 g of ferric chloride in 50 mL of deionized water. Then, in order to prepare the reducing agent solution, 0.6 g of sodium borohydride (NaBH4) was dissolved in 100 mL of deionized water. This solution (containing a reducing agent) was immersed in an ice bath before the ferric chloride solution was added dropwise with a flow rate of 0.13 mL/s using a microtube pump  and transmission electron microscope . The crystal structure of the nanoparticles was also determined by X-ray diffraction (XRD) using an XRD 3100 diffractometer . Moreover, the magnetic properties of the nanoparticles were determined using a 7410 Shore Lake vibrating-sample magnetometer.In this study, specific doses of zero-valent iron nanoparticles , different initial concentrations of AMX , and certain concentrations of hydrogen peroxide  were added to the reactor. The reaction times were varied , and pH was set to three values  . To prodRemoval of the interference of hydrogen peroxide in the COD assay:Hydrogen peroxide interferes in the COD test as follows .Cr2O7−2Although hydrogen peroxide is volatile on its own, its volatility can be reduced in synthetic samples by adding some substances. Consequently, the best way to eliminate the interference of hydrogen peroxide is to measure its residual concentration in the output samples and correct the COD. However, measurements of hydrogen peroxide in the output samples revealed that the residual amount of hydrogen peroxide was not significant. To remove hydrogen peroxide from the environment, different kinds of methods, including the usage of sodium thiosulfate or sodium borohydride, boiling, and incubation in a water bath at a temperature of 45 °C for 24 h, were considered .iC and Co are the initial and residual concentrations of AMX (mg/L).After the preparation of input and output samples of the reactor (centrifugation and passage through a 0.2 μm filter), the samples were injected into the HPLC device to determine the removal efficiency of amoxicillin. The amoxicillin antibiotic concentration was determined by HPLC  equipped with a UV detector (SPD-10 AV) at 420 nm using a mobile phase with a volume percentage of 95:5 of potassium dihydrogen phosphate and methanol. The peak corresponding to the standard graph obtained from the HPLC device is shown in Standard Methods for the Examination of Water and Wastewater book [The measurement of the final concentration of the amoxicillin antibiotic was the main criterion for evaluating the process. Test number 5220B in the book of standard methods was used to measure the COD parameter in the input and output samples of the reactor in order to detect the conversion rate and the removal efficiency of the amoxicillin contaminant. All experiments were performed according to the instructions of the ter book . The expIn this study, to evaluate the effect of the zero-valent iron nanoparticle dosage, values of 0.05, 0.1, and 0.5 g/L were selected. The obtained results are presented in Hydrogen peroxide is a parameter that influences the Fenton process. In this study, the effect of hydrogen peroxide on the oxidation of the amoxicillin antibiotic was investigated. In order to achieve the best process efficiency, the contaminant was exposed to different concentrations of hydrogen peroxide . As shown in The effect of initial pH values of 3, 5, and 11 was investigated in the presence of 100 mg/L amoxicillin, 3% hydrogen peroxide, ultrasonic waves of 130 kHz, and 0.5 g/L iron nanoparticles. As shown in 2O2 = 3%, pH = 3, and frequency = 130 kHz. The obtained results are shown in The effect of different concentrations of amoxicillin was also studied in the presence of nZVI = 0.5 g/L, H2O2/nZVI process was investigated. In order to study the effect of the combination of these processes on amoxicillin removal, the efficacy of each of these parameters was examined individually, and the results were compared with those of the combined process. The results are presented in 2O2 individually and the combination of each of them, and the results were compared with those of the combined method.In this study, the efficiency of the US/HStandard Methods Book [The efficiency of the nano-Fenton process in removing the COD of the amoxicillin antibiotic was also investigated. To measure the COD, the reflex method was used according to Experiment No. 5220B of the ods Book . The obtInvestigation of the effect of different dosages of iron nanoparticles. The highest removal of AMX obtained was 72% using 0.5 g/L zero-valent iron nanoparticles. The increase in the adsorbent surface or its availability to antibiotic molecules, which was obtained by increasing the adsorbent dose, increases the removal percentage [2O2 process [rcentage . In Ali rcentage .The same process . Zhang e process .Determination of the optimum dose of hydrogen peroxide. In order to achieve the best performance in amoxicillin removal, the contaminant was exposed to different doses of hydrogen peroxide . According to the results, the highest removal of 95% was achieved at a concentration of 3% and with the maximum time. Studies have shown that if excess hydrogen peroxide remains in the medium, the hydrogen peroxide itself reacts with the hydroxyl radicals, which in turn reduces the removal efficiency of the system [e system . Due to e system .Determination of the effect of pH changes. According to the diagrams and curves shown, the amount of contaminant removal increased dramatically at pH = 3 to 99.7%. However, the amount of contaminant removal decreased significantly at pH = 11. These results indicate that pH plays a critical role in system performance. The higher removal efficiency under acidic conditions for amoxicillin can be attributed to the generation of more OH radicals, which can rapidly oxidize the reactive AMX molecule [molecule . Zero-vamolecule . Studiesmolecule .Determination of the effect of frequency changes on system performance. The system performance was examined at a frequency of 5 kHz, and the results showed that the removal rate of the system was 90% at a frequency of 35 kHz. The findings demonstrate that changing the frequency from 130 kHz to 35 kHz at constant power has no significant effect on system performance; however, in this case, the efficiency of the system was reduced. The obtained results are consistent with the findings of Manousaki et al. [i et al. .Determination of the efficiency of the system at different concentrations of amoxicillin antibiotic. The results of evaluating the efficiency of the nano-Fenton process at different concentrations of amoxicillin showed that the removal rate was equal to 77.4%, 84.4%, and 99.7% at concentrations of 600 ppm, 300 ppm, and 100 ppm, respectively (Diagram 7). Since the production of hydroxyl radicals will remain constant under constant conditions, they will be consumed by increasing the amount of the contaminant in the radical environment. Therefore, the efficiency of the process will decrease with increasing concentrations of contaminants [2O2/NiO process decreases with the increase in the concentration of antibiotics [aminants . The resibiotics . Hung-Yeibiotics .Determination of the efficiency of the process in the absence of one of the parameters. In order to evaluate the effect of each factor used in the combined system, under optimum conditions, 100 mg/L of the contaminant was put into contact with ultrasonic waves alone, zero-valent iron nanoparticles alone, hydrogen peroxide alone, and the combination of two parameters in the absence of one of the parameters. The results showed that in the absence of ultrasonic waves, hydrogen peroxide, or zero-valent iron nanoparticles, even under acidic conditions, the system performance was significantly reduced. This difference in the system performance can be clearly observed by comparing the diagrams of US/H2O2/nZVI and H2O2/nZVI, which shows the critical role of ultrasonic waves in improving the efficiency of the system. Ultrasonic waves enable better mixing of zero-valent iron nanoparticles and more contact with hydrogen peroxide. In addition, ultrasonic waves increase the contact surface of zero-valent iron nanoparticles with hydrogen peroxide by creating tiny bubbles (cavitation). On the other hand, the absence of hydrogen peroxide in the medium results in the removal of hydroxyl radical sources . The absence of zero-valent iron nanoparticles, which are considered a major source of electrons, which are donated to hydrogen peroxide and produce hydroxide radicals, can cause the disruption and diminished removal efficiency of the amoxicillin antibiotic. The obtained results confirm the necessity of the presence of each of these parameters in the process .Determination of the system performance in COD removal. The COD test was performed to evaluate the efficiency of the system in converting the amoxicillin antibiotic to water and carbon dioxide, which was investigated in this study. The COD measurement was performed using the open reflex method according to Experiment No. B5220 of the Standard Methods Book [ods Book . As showods Book .2O2/nZVI process can be considered a promising candidate for the removal of the antibiotic.The aim of this study was to investigate the application of zero-valent iron oxide nanoparticles in the presence of hydrogen peroxide and the sonolysis process in the removal of the amoxicillin antibiotic from aqueous media. Zero-valent iron nanoparticles were successfully synthesized using the reduction method, and the results showed that the maximum system efficiency occurred at lower contaminant concentrations, under acidic conditions, in the presence of 0.5 g/L zero-valent iron nanoparticles and 3% hydrogen peroxide, and with maximum contact time. The results also indicate that the pH of the medium has a significant effect on increasing the system’s efficiency in the removal of the amoxicillin antibiotic. The presence of ultrasonic waves also has a significant effect on the system’s efficiency, so according to all of the results of this study, the combined US/H


Depressurization combined with brine injection is a potential method for field production of natural gas hydrate, which can significantly improve production efficiency and avoid secondary formation of hydrate. In this work, the experiments of hydrate production using depressurization combined with brine injection from a simulated excess-water hydrate reservoir were performed, and the effects of NaCl concentration on hydrate decomposition, temperature change, and heat transfer in the reservoir were investigated. The experimental results indicate that there is little gas production during depressurization in a excess-water hydrate reservoir, and the gas dissociated from hydrate is trapped in pores of sediments. The high-water production reduces the final gas recovery, which is lower than 70% in the experiments. The increasing NaCl concentration only effectively promotes gas production rate in the early stage. The final cumulative gas production and average gas production rate have little difference in different experiments. The NaCl concentration of the produced water is significantly higher than that which is in contact with hydrate in the sediments because the water produced by hydrate decomposition exists on the surface of undissociated hydrate. The high concentration of NaCl in the produced water from the reactor significantly reduces the promoting effect and efficiency of NaCl solution on hydrate decomposition. The injection of NaCl solution decreases the lowest temperature in sediments during hydrate production, and increases the sensible heat and heat transfer from environment for hydrate decomposition. The changes of temperature and resistance effectively reflect the distribution of the injected NaCl solution in the hydrate reservoir. Due to the increasing demand for energy and the increasing problem of environmental pollution, the development of new clean energy is the demand of the times. Natural gas hydrate widely exists in permafrost and seabed ,2, and iDuring gas production from hydrate reservoirs, hydrate is commonly dissociated in situ and gas is then produced ,11,12,13The combined method refers to the combined use of multiple production methods. The combined method can avoid the shortcomings of a single production method and improve production efficiency . For exaIn summary, depressurization combined with hot brine injection is a potential method for hydrate production in field. The reported research indicated that the concentration, temperature, injection rate of salt solution, and the contact area between salt solution and hydrate have significant impacts on the promoting effects. However, in the current research, there are still some disputes about the influence of salt concentration in different reservoirs, and the distribution and flow of injected salt solution in the reservoir are not clearly revealed. Furthermore, previous studies were mostly performed in the simulated hydrate reservoir with excess-gas ,26,27, wMethane gas (99.95%) was supplied by Guangzhou Shengying Chemical Co., Ltd. Deionized water with a resistivity of 18.25 mW/cm was prepared by ultrapure water equipment, which was produced by Nanjing Ultrapure Water Technology, Co., Ltd. . Sodium chloride with a purity of 99.8% was supplied by Aladdin Industrial Corporation. Silica sands with particle sizes from 250 to 380 μm were supplied by Shanghai McLean Biochemical Technology Co., Ltd. .The main steps of the hydrate formation were as follows: (1) The reactor was cleaned with deionized water and then dried. (2) 3250 g of dried quartz sands were tightly filled in the reactor, and the reactor was assembled and immersed into the water bath. (3) The reactor was flushed three times with pure methane gas to replace the air in the reactor. (4) The temperature of the water bath was adjusted to 20 °C, and 480 mL of deionized water was injected into the reactor at a rate of 20 mL/min. (5) The reactor was pressurized with methane gas to 18 MPa, and the temperature of water bath was kept at 20 °C for 5 h to confirm that the temperature and pressure in the reactor were stable. (6) The water bath temperature was adjusted to 8 °C to form hydrate until the pressure in the reactor dropped to 10.6 MPa. (7) NaCl solution (3.5 wt%) was injected into the reactor at a speed of 50 mL/min, and the production well was kept open to replace methane in the reactor by NaCl solution. The replacement process was ended until no methane gas released.After the hydrate formation, the hydrate was dissociated by depressurization combined with NaCl solution injection. The main steps were as follows: (1) The NaCl solution  was prepared and cooled to 8 °C. (2) The production well was opened to reduce the pressure in the reactor to 4.7 MPa. (3) 600 g NaCl solution was injected into the reactor from the bottom of the reactor at the rate of 20 g/min, and the production pressure was kept at 4.7 MPa during injection. When water production began, 5 mL of NaCl solution produced was taken to measure its concentration every 5 min during production. (4) When the temperature in the center of the reactor was higher than 7 °C, it was concluded that the hydrate had dissociated completely. During the hydrate formation and production, temperature, pressure, resistance, and other data were recorded every 20 s.In this study, three groups of hydrate production experiments of depressurization combined with injection of NaCl solutions with different concentrations were performed. After the depressurization, the temperatures at the measuring points of TA1, TB1, TC1, TA1′, TB1′, and TC1′, which are near the reactor wall, began to rise, indicating that a large amount of hydrate in these areas had been dissociated during depressurization, and the injected NaCl solution had little effect on the hydrate decomposition in these areas. In addition, the temperatures at TA2, TA3, and TA3′ also increased obviously, but the rising rate was lower than that near the reactor wall, which is because hydrate decomposition reduced the temperature increase rate. At measuring points of TB2, TB3, TB3′, TC2, TC3, and TC3′, the temperatures decreased gradually with the injection of NaCl solution. This indicates that the injected NaCl solution enhanced the NaCl concentration at the points of TB2, TB3, TB3′, TC2, and TC3, which were distributed in the middle and bottom layers. The increase of the NaCl concentration decreased the equilibrium temperature of hydrate at the same pressure, resulting in more sensible heat in the reservoir that could be used for hydrate decomposition, thus improving the gas production efficiency. The high conductivity of NaCl solution makes it possible to use the change of resistance in the reactor to reflect the distribution of NaCl solution. In order to better compare the resistance changes caused by NaCl solution injection, the ratio of the resistance during the NaCl solution injection to the resistance after depressurization were calculated to represent the changes of resistances at different measurement points in the reactor. In an excess-water hydrate reservoir, there is little gas production during depressurization and the gas dissociated from hydrate is trapped in pores of sediments. The high-water production reduces the final gas recovery, which was lower than 70% in the experiments, resulting in the weak influence of NaCl concentration on the final gas production.The increasing NaCl concentration effectively promotes gas production rate in the early stage. However, after a period of production, the gas production rate becomes similar in the experiments with different NaCl concentrations. The final cumulative gas production and average gas production rate had little difference in different experiments.The NaCl concentration of the produced water is significantly higher than that in contact with hydrate in the reactor due to the water produced by hydrate decomposition existing on the surface of undissociated hydrate. The high concentration of NaCl of produced water significantly reduces the promoting effect and efficiency of NaCl solution on hydrate decomposition. It is important to ensure that the injected salt solution can be more widely distributed in the hydrate reservoir and reduce the loss of salt solution caused by water production.The injection of NaCl solution decreases the lowest temperature during hydrate production and increases the sensible heat and heat transfer from environment for hydrate decomposition. The changes of temperature and resistance reflect the distribution of the injected NaCl solution in the hydrate reservoir.In this study, an excess-water hydrate reservoir was simulated, and the experiments of hydrate production using the method of depressurization combined with NaCl solution injection were performed. The effects of NaCl concentration on hydrate decomposition, temperature change, and heat transfer in the reservoir were investigated. The main conclusions are as follows:


Transportation agencies continuously and consistently work to improve the processes and systems for mitigating the impacts of roadway incidents. Such efforts include utilizing emerging technologies to reduce the detection and response time to roadway incidents. Vehicle-to-infrastructure (V2I) communication is an emerging transportation technology that enables communication between a vehicle and the infrastructure. This paper proposes an algorithm that utilizes V2I probe data to automatically detect roadway incidents. A simulation testbed was developed for a segment of Interstate 64 in St. Louis, Missouri to evaluate the performance of the V2I-based automatic incident detection algorithm. The proposed algorithm was assessed during peak and off-peak periods with various incident durations, under several market penetration rates for V2I technology, and with different spatial resolutions for incident detection. The performance of the proposed algorithm was assessed on the basis of the detection rate, time to detect, detection accuracy, and false alarm rate. The performance measures obtained for the V2I-based automatic incident detection algorithm were compared with California #7 algorithm performance measures. The California #7 algorithm is a traditional automatic incident detection algorithm that utilizes traffic sensors data, such as inductive loop detectors, to identify roadway events. The California #7 algorithm was implemented in the Interstate 64 simulation testbed. The case study results indicated that the proposed V2I-based algorithm outperformed the California #7 algorithm. The detection rate for the proposed V2I-based incident detection algorithm was 100% in market penetrations of 50%, 80%, and 100%. However, the California #7 algorithm’s detection rate was 71%. A component of intelligent transportation systems (ITSs), the incident management system, aims to mitigate the negative impacts of crashes. A 2007 study reported that incidents contributed to 25% of the congestion in the United States , and a 2Traditionally, traffic incidents came to be known in only a few different ways, the most common being reports from other drivers via phone to emergency numbers, such as 112 or 911. Other methods included receiving notice by police or other officials or notice by TMC operators via closed-circuit television (CCTV) monitoring . The advVehicle-to-infrastructure (V2I) communication is an emerging transportation technology that enables communication between a vehicle and the infrastructure. This paper explores the application of V2I data for automatic incident detection and contributes to the field of ITS and connected vehicles in the following ways: (1) This paper contributes to the ITS body of knowledge by developing a V2I-based incident detection algorithm. To the best of the authors’ knowledge, this is the first paper that investigates vehicle snapshots collected according to the Society of Automotive Engineers’ J2735 protocol for probe data collection on freeway facilities . (2) TheThe remainder of this paper is organized as follows. First, an overview of the V2I probe data is provided. Next, the state of the art in the simulation of V2I environments and AIDs is reviewed. Traffic incident management system architecture is briefly discussed. Then, the proposed methodology for the V2I-based incident detection is described, and performance measures for evaluating the proposed AID are defined. In the next two sections, the simulation testbed, the results obtained from the implementation of the proposed AID, and the California #7 algorithm are described. Finally, the findings of this research and directions for future research are discussed. Vehicle probe data in a V2I environment are collected and reported to traffic management centers and other ITS subsystems. Two of the elements of V2I that facilitate the data collected are on-board units (OBUs) and roadside equipment (RSE). OBUs are installed in vehicles and record vehicle activity data at certain intervals; recorded vehicle activities are referred to as snapshots. RSE is installed at interchanges and other locations to facilitate communication between vehicles and infrastructure. When a vehicle enters an RSE coverage area, the information stored in OBUs is transmitted to the RSE. The RSE may communicate relevant information to the OBUs. The standards for and format of V2I probe data are established in the SAE J2735 standard . VehicleIn this section, the state of the art in V2I simulation is reviewed, and an overview of incident detection methods is provided. Then, incident detection algorithms relevant to this paper are reviewed.Kianfar and Edara  proposedOlia et al.  proposedLin et al.  introducChen et al.  proposedLiu et al.  developeIncident detection algorithms are primarily classified into four categories: (1) pattern-based algorithms; (2) algorithms based on catastrophe theory; (3) statistical algorithms; and (4) artificial-intelligence-based algorithms . PatternHellinga and Knapp  proposedDeniz et al.  comparedNathanail et al.  proposedRossi et al.  proposedAsakura et al.  utilizedSun et al.  proposedWhile many researchers primarily focus on incidents, such as collisions between vehicles, Yoshida et al.’s  researchRizvi et al.  proposedLi et al.  proposedEvans et al.  proposedSun et al.  proposedIqbal et al.  evaluateWolfgram et al.  proposedThe review of the literature indicated that the application of V2I probe data for automatic incident detection had not been previously investigated. Iqbal et al. , and WolArchitecture Reference for Cooperative and Intelligent Transportation (ARC-IT)” consists of four views: (1) enterprise view; (2) functional view; (3) physical view; and (4) communication view [The incident detection algorithm proposed in this paper is a subsystem of the Advanced Traffic Management System (ATMS) and Advanced Traveler Information System (ATIS) of ITS. The fulfillment of tasks defined for various Information Technology (IT) subsystems depends on the cooperation of all the subsystems of the system . A systeion view . The algion view .In the next section, the proposed method for detecting incidents on the basis of V2I probe data is described.The methods section is organized into three subsections. In the first subsection, the proposed algorithm for automatic incident detection using V2I probe data is explained. Next, the performance measures for assessing the automatic incident detection algorithms are defined. In the third subsection, the California #7 AID is explained. The California #7 algorithm serves as a benchmark for evaluating the results obtained from the V2I-based algorithm. California #7 utilizes point-based data  to detect incidents.δ intervals. If the average speed and standard deviation are statistically different from those of the previous δ intervals, the algorithm identifies an incident. The AID algorithm is explained below. This algorithm is built on the work of Hellinga and Knapp [When an incident occurs on a freeway, it often results in the temporary closure of one or more travel lanes, thus creating a temporary bottleneck. Vehicles traveling on the lanes where the incident occurred must shift their path to open lanes, and vehicles traveling on open lanes must accommodate the merging vehicles. Lane-changing maneuvers conducted by vehicles result in a temporary change in their speed and are expected to increase the measures of the dispersion of speed near the location of an incident moments after it occurrs. The algorithm proposed in this paper aims to detect incidents on a freeway by analyzing vehicle speeds reported in V2I probe snapshots. The freeway is partitioned into virtual segments, and the average speed and standard deviation of speeds in segments during detection intervals are calculated. The length of the virtual segments represents the spatial resolution of the AID, and the detection interval represents the temporal resolution of the AID. The average and standard deviation of vehicle speeds on a segment are calculated from speeds obtained from snapshots of vehicles traveling on the segment during the time interval. The average speed and standard deviation at each segment during an interval are compared with the average speeds and standard deviations reported for the same segment in the previous nd Knapp , who utind Knapp  analyzedThe standard deviation of speeds of vehicles equipped with connected vehicle technology that are traveling on a segment is calculated according to (1):j at time interval i;j at interval i;k in segment j at time interval i;lth snapshot reported by vehicle k while traveling on segment j at time interval i;j at interval i.The mean of the standard deviation of speeds during the previous j;j in the previous The variance of the standard deviation of speed  and lognormal variance (6) of the standard deviation of speed for previous j as previously defined in (3);Z = Z-value for the confidence level;j for current time interval i + 1.Step 2: The average speed for the previous j in the time interval i + 1. In the next subsection, performance measures for evaluating the developed algorithm are described. Step 3: If the standard deviation of speed for the current interval is greater than the corresponding upper limit  is the number of instances in which an incident occurred and was detected by the algorithm. False positive (FP) is the number of instances in which no incident occurred on the freeway, but the algorithm incorrectly detected an incident. True negative (TN) is the number of instances in which no incident occurred on the freeway, and no incident was detected by the algorithm. False negative (FN) is the number of instances in which an incident occurred on the freeway but was not detected by the algorithm. Detection accuracy (DA) is the number of cases correctly detected by the algorithm divided by the total number of cases, as shown in Equation (9).The detection rate (DR) is the number of incidents correctly detected by the algorithm divided by the total number of incident cases. Time to detect (TTD), as the name implies, is the time interval between the moment an incident occurred and the moment when the incident was detected by the algorithm. Detection accuracy and the false alarm rate are calculated based on true positive, false positive, true negative, and false negative values. True positive (FAR) is the ratio of false positives to the total number of instances, as shown in Equation (10).The false alarm rate  measured at the upstream detector (r) at time interval (x) and occupancy measured at the downstream detector (r + 1) at time interval (x) to detect an incident that has occurred between upstream and downstream detectors. The California #7 algorithm computes the difference in occupancy  section of Interstate 64 in St. Louis, Missouri, USA was selected as the case study location. The freeway section was coded in the VISSIM traffic simulation software, and the SAE J2735 Dedicated Short Range Communications (DSRC) protocol for probe data collection was coded in MATLAB. The VISSIM COM interface was used to connect the traffic simulation models with the V2I probe data collection module in MATLAB. Ten real-world incidents that occurred on Interstate 64 were identified in the traffic management center data logs and were simulated in the model. The duration and coordinates of the incidents were obtained from the incident logs, and traffic volumes before, during, and after an incident were retrieved from traffic sensors located upstream of the incident location. Incidents were selected to represent diverse traffic patterns. The selected incidents occurred during peak and off-peak periods and during summer, fall, and winter. Traffic incidents were simulated in the testbed, and the V2I-based automatic incident detection algorithm was evaluated under various V2I market penetration rates, two different virtual segment lengths, and two different detection levels of confidence. The performance of the AID was investigated under four different levels of market penetration for OBU-equipped vehicles: 20%, 50%, 80%, and 100%. With regards to the length of virtual segments, the performance of the algorithm was investigated for 500 ft and 1000 ft virtual segments. Furthermore, the performance of the model with levels of confidence (Z) of 80% and 95% was investigated. The DA, DR, FAR, and TTD were reported for each simulation scenario. In general, when market penetration increased, the DA and FAR improved. This is not surprising because when the market penetration increases, the quality of probe data improves as more snapshots are reported to the V2I AID algorithm;The FAR and DA were not correlated with the length of the virtual segment. However, the TTD decreased from 1.7 min to 1.3 min when the virtual segment length was reduced from 1000 ft to 500 ft.It is worth mentioning that as the market penetration increased, the FAR increased. This is because an increase in the number of probe snapshots increased the number of FPs. However, the maximum observed FAR was less than 12%, which is considered desirable;Increasing the market penetration from 20% to 50% resulted in meaningful improvements in the DA; however, increasing market penetration from 50% to 100% did not have a significant impact on the DA. This trend is illustrated in When the market penetration increased from 20% to 50%, the TTD improved. However, when the market penetration increased from 50% to 80%, no meaningful improvements in the TTD were observed;The performance of the proposed V2I-based AID algorithm was compared with the performance of the California #7 algorithm. First, the California #7 algorithm was modeled in the simulation testbed and was calibrated for Interstate 64. Inductive loop detectors were in 500 ft intervals in the testbed. Ground truth data collected by the Missouri department of transportation traffic sensors were used to simulate traffic on 32 workdays on which no incidents occurred on Interstate 64. The data collected by simulation testbed inductive loop detectors were used to determine the thresholds of the California #7 algorithm according to the process described by Nathanail et al. . The T1 Next, incidents A to J were modeled in the testbed, and the V2I-based AID algorithm and California #7 algorithm were simulated. The V2I-based AID algorithm was modeled with virtual segments that were 500 ft long and with market penetration rates of 50%, 80%, and 100%. The TTD, FAR, and DR obtained for both algorithms are reported in For all three market penetration scenarios, the V2I-based AID algorithm’s DR was 100%, and the V2I-based AID algorithm consistently outperformed the California #7 algorithm. With regards to the FAR, the V2I-based AID algorithm outperformed the California #7 algorithm at the market penetration rates of 80% and 100%. However, the California #7 algorithm had a lower FAR than the V2I-based AID algorithm at 50% market penetration. Similarly, the TTD of the V2I-based AID algorithm at 50% market penetration was comparable to that of the California #7 algorithm, and when the market penetration was increased to 50% and 100%, the TTD improved by 39% and 50%, respectively.Traffic incidents are a source of non-recurrent congestion and may result in secondary crashes. The prompt detection of roadway incidents enables transportation agencies to employ a spectrum of strategies to mitigate the impacts of incidents and prevent additional crashes. AIDs enable transportation agencies to detect incidents on the roadway and implement the appropriate response automatically. Improving the performance of AIDs has an overall positive impact on incident clearance and the recovery process and reduces the environmental and economic costs of incidents. AIDs commonly utilize point sensors data, GPS and AVL data, and CCTV video feeds to detect incidents. This paper investigated the application of emerging sources of data—vehicle snapshots generated by OBUs—in the V2I environment for automatic incident detection. A novel V2I-based incident detection algorithm was proposed, and its performance was compared with a conventional AID algorithm. A simulation testbed of a segment of Interstate 64 in St. Louis, Missouri was developed, and real-world incidents were modeled to evaluate the performance of the proposed incident algorithm. The detection rate (DR), detection accuracy (DA), false alarm rate (FAR), and time to detect (TTD) were used to evaluate the proposed algorithm. A sensitivity analysis was conducted to assess the performance of the proposed algorithm under two confidence levels of 80% and 95%, four market penetrations of 20%, 50%, 80%, and 100%, and two different virtual freeway detection segments lengths of 500 ft and 1000 ft. The performance of the algorithm significantly improved when the market penetration was increased from 20% to 50%; however, the same level of benefit was not achieved when the market penetration was increased from 50% to 80% and 100%. The performance of the proposed V2I-based AID algorithm was compared with that of the California #7 algorithm. With market penetrations of 80% and 100%, the V2I-based AID algorithm significantly outperformed the California #7 algorithm.The V2I-based incident detection method proposed in this paper has several advantages and disadvantages. These strengths and weaknesses are discussed in the following two subsections.Unlike machine-learning-based incident detection algorithms, which are often black boxes, the algorithm proposed in this paper follows statistical principles. This statistics-based approach makes the algorithm explainable and straightforward to implement for practitioners. The algorithm does not rely on propriety codes and does not require the extensive training needed for machine learning methods. Another strength of the algorithm is that the incident detection segments are defined virtually. In the conventional incident detection methods, such as the California #7 algorithm, the detection segments are constrained between the physical location of the two consecutive sensors on the road. As such, additional sensors should be installed on the road to shorten the length of the detection segments. However, in the V2I-based approach, the detection segments are defined virtually, and their lengths can be adjusted from the TMC. This flexibility would allow transportation operators to adjust the lengths of the detection segments throughout the day based on the market penetration or volume for the vehicles equipped with OBUs. For example, during overnight hours, when traffic volume is low, the TMC operators can adjust the length of detection segments to be longer to improve the algorithm’s performance. Another potential advantage of the algorithm proposed in this paper is its ability to identify which lanes are blocked because of an incident. The SAE J2735 messages include the coordinates of vehicles. After an incident is detected by the algorithm, it is possible to analyze the latitudes and longitudes received from vehicles to determine where the lane changes maneuvers are occurring and from which lanes’ latitudes and longitudes are not received. This information could determine how many lanes are blocked as a result of an incident. It is worth mentioning this feature was not investigated in this paper and is suggested as a research topic for future studies. It should be noted that conventional incident detection algorithms are not able to determine which lanes are blocked due to an incident.The V2I-based incident detection method is not without disadvantages. For example, as illustrated in This paper investigated the application of an emerging source of data—vehicle snapshots generated by OBUs in the V2I environment—for automatic incident detection. A novel V2I-based incident detection algorithm was proposed, and its performance was compared with that of a conventional AID algorithm. Virtual incident detection segments were defined, and vehicle snapshots received from vehicles were analyzed to detect incidents. An incident was detected by comparing the standard deviation of speeds with the mean of the standard deviation of vehicle speeds in the previous detection intervals. The proposed algorithm was evaluated in a case study of a section of Interstate 64 in St. Louis, Missouri, USA, and the incident detection performance metrics were compared with the California #7 algorithm. The V2I-based algorithm significantly outperformed the California #7 algorithm at market penetrations of 80% or higher.In future research, it is recommended to evaluate V2I-based incident detection algorithms on arterial streets and other interrupted-flow facilities. It is also recommended to evaluate the V2I-based technologies against algorithms that utilize AVL and AVI data. Finally, it is recommended to develop AIDs that fuse V2I sensors’ data with conventional data sources to detect roadway incidents.