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Rock mass has typical pore structure, and the induced coupling effects of fluid and solid matrix appear in the disaster evolution process of deep energy exploitation and overground rock hydration. As a representative case, influenced by the water absorption environment, the surrounding rock and murals of Mogao Grottoes produce hydration diseases, which may be related to unclear interaction mechanisms between the surrounding rock and water. In this study, the self-developed physical experimental system for real-time experimental monitoring was applied to test the water absorption evolution behaviors of sandstone. The experimental results showed that the water evaporation of the rock sample during the process of water absorption could be measured through this well-designed physical experimental system, and the actual water absorption of the rock sample is the difference between the decrease of water in the water storage bucket, measured by the balance and the water evaporation in the process of experiment; by drawing the actual water absorption curve of the rock sample, the time when the water absorption of the rock sample reaches saturation could be determined accurately; and the curve of water absorption with time could be expressed as an exponential function. The experimental techniques and methods in this study provide a feasible research idea for studying the water absorption evolution behaviors and mechanisms of the surrounding rock weathering when it meets water, and have significance for revealing the disease mechanisms of the surrounding sandstone in Mogao Grottoes, China. [ABSTRACT FROM AUTHOR]

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Concrete facilities in the severe-cold areas of western China (salt lake environments and heavy saline soils) are seriously damaged by the multiple corrosion effects of freeze–thaw cycles and sulfate corrosion. Magnesium phosphate cement (MPC) cement-based material has become an ideal concrete structural component because of its superior performance. Because concrete structural repair materials are used in heavy-corrosion environments, their durability in those environments should also be considered. Regarding the salt-freezing resistance of MPC, the existing studies have all used a NaCl solution as the heat transfer medium. In addition to chlorine salt, sulfate, especially Na2SO4, is also common in typical use environments such as oceans, salt lakes, and groundwater. To evaluate the sulfate freeze–thaw resistance of potassium magnesium phosphate cement (MKPC) mortar, in this study the strength development, weight loss, and water absorption of MKPC mortar specimens subjected to different freeze–thaw cycles were tested and compared with those for Portland cement (P.O) mortar specimens of the same strength grade. The results showed that the P.O mortar specimen completely lost its strength after 75 cycles of rapid water freezing and thawing and 50 cycles of sodium sulfate solution (5%) freezing and thawing. However, the residual strength rating of the MKPC mortar specimen after 75 cycles of water freezing and thawing and 100 cycles of sodium sulfate solution freezing and thawing was higher than 75%. After 50 rapid freeze–thaw cycles in water and a 5% Na2SO4 solution, the P.O mortar specimen's mass loss exceeded the 5% failure standard, whereas the mass loss of the MKPC mortar specimens was much less than 5%. Before the freeze–thaw cycles, the water absorption of the P.O mortar specimen was close to 8 times that of the MKPC mortar specimen, and after 50 water freeze–thaw cycles and 25 sulfate solution freeze–thaw cycles, the water absorption reached 4.88% and 5.68%, respectively. However, after 225 freeze–thaw cycles in water and the sulfate solution, the water absorption rates of MKPC mortar specimens were 2.91% and 2.51% respectively. The test and analysis results show that the freeze–thaw resistance of MKPC mortar was much higher than that of Portland cement mortar specimens. Those results provide a prerequisite for applying and expanding the use of MKPC-based materials in severe-cold areas of western China (salt lake and heavily saline soil environments). [ABSTRACT FROM AUTHOR]

• Species mixing improved the water absorption of Pinus massoniana from shallow soils. • Species mixing reduced the water uptake proportion of P. massoniana from deep soils. • Plant rather than soil properties mainly regulated P. massoniana water uptake in well-watered conditions. Tree species mixtures have been identified as an effective strategy to cope with global climate change. Global climate change not only triggers extreme drought, but also stimulates extreme precipitation, resulting in frequent floods and subsequent tree mortality. However, previous studies concentrated primarily on the response of mixed species to extreme drought, with limited studies involving their response to extreme precipitation, especially at the regional scale. Here, we used δ D and δ 18O coupled with the MixSIAR model to analyze the water use pattern of Pinus massoniana between pure and mixed stands following different magnitudes of rainfall events across southern, central, and northern subtropical China. We further employed partial correlation analysis, variation partitioning analysis and a random forest model to discern the dominant factor affecting plant water absorption. Our results indicated that the proportion of water uptake by P. massoniana from the 0–40 cm soil layers in the mixed stand was significantly higher than that in the pure stand (56.5–81.4 % vs. 44.3–61.7 %), while the proportion of water uptake from the 60–100 cm soil layers exhibited the opposite pattern (9.0–25.0 % vs. 24.1–32.2 %), whether in light, moderate or heavy precipitation. Furthermore, our results revealed that the difference in P. massoniana water absorption between pure and mixed stands was mainly due to the shifts in plant attributes (i.e., root biomass, leaf biomass and predawn leaf water potential). These findings imply that mixed tree species distributions could optimize water uptake patterns by altering plant properties for interspecific niche complementarity, which could effectively increase forest water conservation. [ABSTRACT FROM AUTHOR]

Water and fertilizer are indispensable inputs to crop production in modern agriculture. Drought, water shortage and low efficient utilization of water have posed a great challenge on agricultural production and food security in China. New fertilizers with dual functions of water retention and slow release become significant to enhance the utilization efficiency of water, and thereby to ensure the sustainable development of agriculture. Therefore, previous studies on the new fertilizers have drawn much attention in water and fertilizer technology in recent years. This paper explores the preparation method of a novel water-retaining material that incorporated with nano-SiO2 for the slow-release fertilizer with water retention properties. A P(AA-AM)/SiO2 water-retaining composite was fabricated by in-situ polymerization in aqueous solution using acrylic acid (AA) and acrylamide (AM) as raw materials. A water-retaining slow-release fertilizer was then produced by the double-layer coating process. The mass ratio of acrylic acid (AA) and acrylamide (AM) was set as 3.5:1 to synthesize water-retaining materials. The initiator (potassium persulfate and sodium sulfite), crosslinking agent (N, N-methylenebisacrylamide), plasticizer (glycerol), and nano-SiO2 were added by 1%, 0.04%, 15%, and 2% in monomer mass, respectively. A drum coating process was selected to prepare the water-retaining slow-releasing fertilizer, where the inner coating layer was made of polyurethane, with the mass ratio of coating materials to the inner core of 3%, whereas the outer coating layer was P(AA-AM)/SiO2 water-retaining composite material, with a mass ratio to the core of 27%. Fourier Infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and thermogravimetry (TG) were used to characterize the microstructure, morphology and thermal stability of water-retaining materials. A filtration was selected to determine the water absorption of water-retaining material. Soil culture experiment was used to investigate the capacity of water-retaining and water-holding in the fabricated fertilizer. A water immersion method was utilized to explore nitrogen release properties of fertilizer at the temperature of 25℃. The results showed that the water absorption rates of composite materials with nano-SiO2 in deionized water and 0.9% NaCl aqueous solution were 152% and 87% higher than those of only P(AA-AM) materials, while the thermal stability was also significantly improved. SEM images and FTIR analysis indicated that nanoparticles of SiO2 were evenly dispersed into the P(AA-AM) composites, while the silicon hydroxyl groups on the surface of SiO2 increased the cross-linking density of water-retaining materials. Compared with the slow-release fertilizer without water-retaining layer, the water absorption rate and retention rate of slow-release fertilizer with water-retaining layer (after 25 days of incubation) increased by 25.5% and 47.2%, respectively, indicating the releasing duration of fertilizer was extended from 60 days to 72 days. The preparation method of water-retaining composite material that incorporated with nano-SiO2 and water-retaining slow-release fertilizers can provide excellent properties of water absorption and retaining, as well a high performance of slow release in soil. A mechanism of water-retaining was proposed to clarify the slow release of nutrients in the water-retaining material and water-retaining slow-release fertilizers. The findings can offer new insights into high efficiency fertilizers to enhance the utilization efficiency of water and fertilizers. [ABSTRACT FROM AUTHOR]

The objective was to analyse the water absorption and weakening of a Silurian argillite taken from the northwest of Hubei Province, China. Some experiments were conducted including measurement of the change in water absorption, the microstructure of the minerals, the porosity, and the strength of argillite samples, at different water absorptions, by scanning electron microscope, powder X-ray diffraction analysis, and needle penetration test. The results indicate that argillite was soaked in water for up to 0.5 days, water absorption rates were fast and the amount absorbed was large. At the same time, the rate of strength decrease was high and significant loss of strength was observed. Argillite soaked in water for 0.5 to 180 days had an increased water absorption at a slower rate, and the strength tended to be stable over time. The relationship between strength and water absorption was established: the strength decreases in the form of negative exponential function with increasing water absorption. Finally, the micro-mechanical model shows that, the decrease of attractive force of mineral grains and the increase in the force acting between mineral grains and the pore water are the main reason why this degree of water-weakening appeared in the argillite. [ABSTRACT FROM AUTHOR]

The utilization of construction waste soil to produce foamed concrete together with cement and a foaming agent is a promising method for waste recycling. Completely decomposed granite (CDG), which is widely available in southern China, was selected as a typical construction waste soil in foamed material production. The Taguchi method was applied to study the influence of various parameters on compressive strength, including cement dosage, CDG dosage, water to solid materials ratio (W/M), fine particles content, and gravel particles content. Analysis of variance (ANOVA) on a CDG-based sample showed that all factors have significant effects on compressive strength and the most effective parameter was cement dosage, followed in sequence by CDG dosage, W/M, gravel particles content, and fine particles content. However, only cement dosage and W/M influence the internal structure significantly during water/vacuum-immersion tests. The relationship between micro-pore structure and compressive strength suggested that with the decrease of open porosity, the compressive strength showed an increasing trend. This study reveals the possibility of CDG as a raw material for foamed lightweight soil and provides a technical reference of production procedure. [ABSTRACT FROM AUTHOR]

Calculating the water absorption in sublayers based on the on-site monitored water injection profile is the most accurate way to reflect the actual amount of water absorbed by subalyers. However, access to this profile data is scarce and limited due to its high cost of testing. As a result, some well blocks have tested some discontinuous profiles, but other well blocks do not have any profiles. Traditional machine learning can be applied to construct an intelligent surrogate model by training with historical injection profile. This well-trained model can be only used to make a good prediction for well blocks which contribute profile data, not applicable to well blocks without injection profile. In this study, a Joint Distribution Adaption based Extreme Gradient boosting transfer learning approach is presented to predict water absorption of sublayers in water injection well which do not have any injection profile. A handful of observations are obtained from source well block which has tested sufficient injection profiles. Joint Distribution Adaption is first conducted to transfer knowledge from source well block to the target well block which have no injection profile. The transferred dataset with new feature representation is used to constitute the training dataset for target well block. This transferred training dataset then can be feed into the Extreme Gradient Boosting model to construct a water absorption predictive model. The well-trained model can be applied to predicting water absorption of sublayers in injectors which do not have any water injection profile. The proposed approach is demonstrated by applying to two well blocks from SL oilfield, China. Demonstrated results imply that the proposed transfer learning method can be used to dividing water absorption of subalyers in injectors which have no water injection profile data. • The JDA based XGBoost transfer learning is proposed for predicting water absorption of sublayers in no profile injector. • The training dataset of target well block can be constructed by transfer knowledge from source well block. • The XGBoost model can be used to predict sublayer water absorption for target well after training with transferred dataset. • A hybrid genetic algorithm is developed to optimize hyperparameters of XGBoost model. • Transfer learning model provide a tool to allocate sublayer water absorption for injectors without water injection profile. [ABSTRACT FROM AUTHOR]

The sedimentary rhythm of Chinese oilfields is complicated and the heterogeneity is extremely strong. Allocating water absorption of each sublayer by dividing coefficient or numeric simulation cannot accurately reflect the actual water injection of the reservoir. Calculation based on water absorption profile monitored on site is the most commonly used method in oil field. However, access to these type of data is limited due to its cost and time related to acquisition. In this study, a machine learning approach was adopted to predict water absorption in sublayer based on geologic and production parameters of injectors and producers. On the one hand, it can save test costs. On the other hand, it can continuously predict water absorption of sublayers, and make up for water injection wells with insufficient injection profiles. A handful of training observations are obtained from on-site monitoring. Interwell connectivity is first conducted to identify connected producers for injectors. Introducing interwell connectivity helps to constitute predictor variables and yield significant improvements in feature selection. Connectivities in the well group are represented by similarity between injection sequence and production sequence, which is computed by Dynamic Time Warping. Average importance of predictors are then measured based on Mean Decrease Impurity, Mean Decrease Accuracy, and Ridge regression. Some relative important features are selected to consist the final predictors. The Extreme Gradient Boosting model is developed and then trained for making predictions given any set of observations. The proposed approach is validated by using actual field case from SL oilfield, China. Results show a significant correlation between predictions and actual value from on-site monitoring. • The Extreme Gradient Boosting method is introduced for modeling the amount of water absorbed by each sublayer in wellbore. • The model can learn to predict water absorption rate using geologic and production information. • Introducing of interwell connectivity is critical for increasing feature selection accuracy and prediction accuracy. • Ridge Regression and Random Forest provide a ranking of predictor variables. [ABSTRACT FROM AUTHOR]