The lateral pressure coefficient at rest of expansive soils in landfill at various vertical stresses and moisture contents

When expansive soils in the original location are artificially transferred to landfill in different seasons,and subject to engineering activities afterwards,the corresponding deformation and stability of retaining structures become unpredictable.This necessitates the determination of lateral pressure coefficient at rest(k_(0) value)for expansive soils in landfill.Considering compaction,excavation of expansive soils,as well as construction of landfill in different seasons,series of stepwise loading and unloading consolidation tests at various moisture contents were carried out in this work to explore the evolution characteristics of k_(0) value and assess the dependence of k_(0) value on vertical stress and moisture content.Besides,scanning electron microscope(SEM)was used to track the change in microstructural features with vertical stresses.The results indicated that the k_(0) value of expansive soil shows a pronounced nonlinearity and is inextricably linked with vertical stress and moisture content,based on which a prediction formula to estimate the variation in k_(0) value with vertical stress during loading stage was proposed;there is a significant exponential increase in k_(0) value with overconsolidation ratio(OCR)during unloading stage,and OCR dominates the release of horizontal stress of expansive soil;SEM results revealed that with an increase in vertical stress,the anisotropy of expansive soil microstructure increases dramatically,causing a significant directional readjustment,which is macroscopically manifested as an initially rapid increase in k_(0) value;but when vertical stress increases to a critical value,the anisotropy of microstructure increases marginally,indicating a stable orientation occurring in the soil microstructure,which causes the k_(0) value to maintain a relatively stable value.

Feasibility of measuring moisture content of green sand by a low frequency multiprobe detector based on dielectric characteristics

Green sand is a mixture of silica sand,bentonite,water and coal powder,and other additives.Moisture content is an important index to characterize the properties of green sand.Based on the dielectric characteristics of green sand and transmission line theory,a method for rapidly measuring the moisture content of green sand by means of a low frequency multiprobe detector was proposed.A system was constructed,where six detectors with different arrangements and probes were designed.The experimental results showed that the voltage difference of transmission line increases with the increasing frequency before 29 MHz while decreases after 35 MHz.A voltage difference platform occurs in the range of 29-35 MHz,which is suitable for measuring the moisture content due to its insensitivity to frequency.The electric field intensity gradually decreases with the increase of the probe depth,and the intensity of central probe is always greater than that of the edge probe.When the distance of the probe away from the sand sample surface is 80 mm,the electric field intensity of the edge probe is found to be very weak.The optimal excitation frequency for measuring the moisture content of green sand is 29-33 MHz.The optimal detector is the one with one center probe and three edge probes,and their lengths are 80 mm and 60 mm,respectively.The distance between the center and edge probes is 25 mm,and the diameter of probes is 5 mm.Taking the voltage difference of transmission line,bentonite content,coal powder content and compactability as parameters of the input layer,and the moisture content as a parameter of the output layer,a three-layer BP artificial neural network model for predicting the moisture content of green sand was constructed according to the experimental results at 33 MHz.The prediction error of the model is not higher than 3.3% when the moisture content of green sand is within the range of 3wt.%-7wt.%.

Modelling the dead fuel moisture content in a grassland of Ergun City,China

The dead fuel moisture content(DFMC)is the key driver leading to fire occurrence.Accurately estimating the DFMC could help identify locations facing fire risks,prioritise areas for fire monitoring,and facilitate timely deployment of fire-suppression resources.In this study,the DFMC and environmental variables,including air temperature,relative humidity,wind speed,solar radiation,rainfall,atmospheric pressure,soil temperature,and soil humidity,were simultaneously measured in a grassland of Ergun City,Inner Mongolia Autonomous Region of China in 2021.We chose three regression models,i.e.,random forest(RF)model,extreme gradient boosting(XGB)model,and boosted regression tree(BRT)model,to model the seasonal DFMC according to the data collected.To ensure accuracy,we added time-lag variables of 3 d to the models.The results showed that the RF model had the best fitting effect with an R2value of 0.847 and a prediction accuracy with a mean absolute error score of 4.764%among the three models.The accuracies of the models in spring and autumn were higher than those in the other two seasons.In addition,different seasons had different key influencing factors,and the degree of influence of these factors on the DFMC changed with time lags.Moreover,time-lag variables within 44 h clearly improved the fitting effect and prediction accuracy,indicating that environmental conditions within approximately 48 h greatly influence the DFMC.This study highlights the importance of considering 48 h time-lagged variables when predicting the DFMC of grassland fuels and mapping grassland fire risks based on the DFMC to help locate high-priority areas for grassland fire monitoring and prevention.

A distributed measurement method for in-situ soil moisture content by using carbon-fiber heated cable

Moisture content is a fundamental physical index that quantifies soil property and is closely associatedwith the hydrological, ecological and engineering behaviors of soil. To measure in-situ soil moisturecontents, a distributed measurement system for in-situ soil moisture content （SM-DTS） is introduced.The system is based on carbon-fiber heated cable （CFHC） technology that has been developed to enhancethe measuring accuracy of in-situ soil moisture content. Using CFHC technique, a temperature characteristicvalue （Tt） can be defined from temperatureetime curves. A relationship among Tt, soil thermalimpedance coefficient and soil moisture content is then established in laboratory. The feasibility of theSM-DTS technology to provide distributed measurements of in-situ soil moisture content is verifiedthrough field tests. The research reported herein indicates that the proposed SM-DTS is capable ofmeasuring in-situ soil moisture content over long distances and large areas.

Performance evaluation of two types of heated cables for distributedtemperature sensing-based measurement of soil moisture content

Distributed temperature sensing(DTS)using heated cables has been recently developed for distributed monitoring of in-situ soil moisture content.In this method,the thermal and electrical properties of heated cables have a significant influence on the measurement accuracy of soil moisture content.In this paper,the performances of two heated cables,i.e.the carbon-fiber heated cable(CFHC)and the metalnet heated cable(MNHC),are studied in the laboratory.Their structures,uniformity in the axial direction,measurement accuracy and suitability are evaluated.The test results indicate that the MNHC has a better uniformity in the axial direction than CFHC.Both CFHC and MNHC have high measurement accuracy.The CFHC is more suitable for short-distance measurement(500 m),while the MNHC can be used for longdistance measurement(>500 m).

Estimating Wheat Grain Protein Content Using Multi-Temporal Remote Sensing Data Based on Partial Least Squares Regression

Estimating wheat grain protein content by remote sensing is important for assessing wheat quality at maturity and making grains harvest and purchase policies. However, spatial variability of soil condition, temperature, and precipitation will affect grain protein contents and these factors usually cannot be monitored accurately by remote sensing data from single image. In this research, the relationships between wheat protein content at maturity and wheat agronomic parameters at different growing stages were analyzed and multi-temporal images of Landsat TM were used to estimate grain protein content by partial least squares regression. Experiment data were acquired in the suburb of Beijing during a 2-yr experiment in the period from 2003 to 2004. Determination coefficient, average deviation of self-modeling, and deviation of cross- validation were employed to assess the estimation accuracy of wheat grain protein content. Their values were 0.88, 1.30%, 3.81% and 0.72, 5.22%, 12.36% for 2003 and 2004, respectively. The research laid an agronomic foundation for GPC （grain protein content） estimation by multi-temporal remote sensing. The results showed that it is feasible to estimate GPC of wheat from multi-temporal remote sensing data in large area.

Measurement of lumber moisture content based on PCA and GSSVM

Lumber moisture content(LMC) is the important parameter to judge the dryness of lumber and the quality of wooden products.Nevertheless the data acquired are mostly redundant and incomplete because of the complexity of the course of drying,by interference factors that exist in the dryness environment and by the physical characteristics of the lumber itself.To improve the measuring accuracy and reliability of LMC,the optimal support vector machine(SVM) algorithm was put forward for regression analysis LMC.Environmental factors such as air temperature and relative humidity were considered,the data of which were extracted with the principle component analysis method.The regression and prediction of SVM was optimized based on the grid search(GS) technique.Groups of data were sampled and analyzed,and simulation comparison of forecasting performance shows that the main component data were extracted to speed up the convergence rate of the optimum algorithm.The GS-SVM shows a better performance in solving the LMC measuring and forecasting problem.

Influence of soil moisture content on pullout properties of Hippophae rhamnoides Linn. roots

Plant root system plays an important role in preventing soil erosion and improving slope stability.However,its performance is significantly affected by soil moisture content,and the role of soil moisture in root reinforcement is not fully understood.In this study,the influence of soil moisture on root pullout properties was studied by experiments.Vertical in-situ pullout tests under four different levels of soil matric suction(12 kPa,18 kPa,24 kPa,30 kPa)were carried out on roots of sea buckthorn plants(Hippophae rhamnoides Linn.)which were artificially cultivated for 7 months.Diameter and length of the root system of sea buckthorn were investigated.The results showed that a very significant correlation was observed between root diameter(D)and root length(L)(P<0.01),and root diameter decreased with soil depth.When soil bulk density was constant,peak pullout force(F)and friction coefficient of root-soil interface(μ)decreased with increasing gravimetric soil moisture content in power functions.Soil moisture content significantly affected root pullout resistance because the increase of soil moisture content decreased the friction coefficient between the roots and soil.Root diameter at breakage point(Db)and length of root segment left in soil(Lb)were increased with soil moisture content.In addition,peak pullout force of the roots increased in a power function with root diameter at the soil surface(D0)and in a linear function with total root length(L).The results provided an experimental basis for quantifying the effects of soil moisture content on soil reinforcement by plant roots.

Study on the Relationship between.the Moisture Content of Brown Rice and Milling Characteristics

An experiment about rice milling was made to study on the relationship between the different moisture content of brown rice and the energy consumption, the broken rice rate, the crack rate and the head rice yield. It could be concluded that the head rice yield increased at first falls and then along with the raise of moisture content and it could reach the maximum 70.78% when moisture content was 15.5%; the energy consumption of rice milling decreased along with the increase of moisture contents; the broken rice rate fell at first and then increased along with the raise of moisture contents and it could reach the minimum 4.28% when the moisture content was 15.5%.

Does nitrogen application rate affect the moisture content of corn grains?

Nitrogen fertilizer application is an important measure to obtain high and stable corn yield,and the moisture content of corn grains is an important factor affecting the quality of mechanical grain harvesting.In this study,four different nitrogen fertilizer treatments from 0 to 450 kg ha^(–1) pure nitrogen were set for a planting density of 12.0×10^(4) plants ha^(–1) in 2017 and 2018,and 18 different nitrogen fertilizer treatments from 0 to 765 kg ha^(–1) pure nitrogen were set for planting densities of 7.5×10^(4) and 12.0×10^(4) plants ha^(–1) in 2019,to investigate the effect of nitrogen application rate on the moisture content of corn grains.Under each treatment,the growth of corn,leaf area index(LAI)of green leaves,grain moisture content,and grain dehydration rate were measured.The results showed that,as nitrogen application increased from 0 to 765 kg ha^(–1),the silking stage was delayed by about 1 day,the maturity stage was delayed by about 1–2 days,and the number of physiologically mature green leaves and LAI increased.At and after physiological maturity,the extreme difference in grain moisture content between different nitrogen application rates was 1.9–4.0%.As the amount of nitrogen application increased,the corn grain dehydration rate after physiological maturity decreased,but it did not reach statistical significance between nitrogen application rate and grain dehydration rate.No significant correlation was observed between LAI at physiological maturity and grain dehydration rate after physiological maturity.In short,nitrogen application affected the grain moisture content of corn at and after physiological maturity,however,the difference in grain moisture content among different nitrogen application rates was small.These results suggest that the effect of nitrogen application on the moisture content of corn grains should not be considered in agricultural production.

Nondestructive testing method of wood moisture content based on a planar capacitance sensor model

For our research, a new hybrid experimental-computational method is presented. We applied a least squares fitting method （LSFM） to reconstruct the wood moisture content （WMC） from the data measured with a planar capacitance sensor. A boundary element method （BEM） was used to compute the relationship between capacitance and the dielectric constant. A functional relationship between MC and the dielectric constant was identified by LSFM. The agreement of this final computation result with the experimental data indicates that this method can be used to estimate the WMC quickly and effectively with engineering analysis. Compared with popular statistical methods, a large number of experiments are avoided, some costs of testing are reduced and the efficiency of testing is enhanced.

Effects of Powdery Mildew on 1 000-Kernel Weight, Crude Protein Content and Yield of Winter Wheat in Three Consecutive Growing Seasons

In order to clarify the impact posed by wheat powdery mildew （Blumeria graminis f. sp. tritici） on the yield and yield components in different epidemic seasons, field trials were conducted in three growing seasons, 2009-2010, 2010-2011 and 2011-2012, in Langfang City, Hebei Province, China. The relationships between 1000-kernel weight, crude protein content of grain and yield and disease index （DI）, as well as area under disease progress curve （AUDPC） were studied. The models of the percentage of loss of 1000-kernel weight, crude protein content and yield were constructed using DI at critical point （CP） of growth stages （GS） and AUDPC in the three growing seasons, respectively. The CPs for estimating 1 000-kernel weight, crude protein content of grain and yield of wheat caused by powdery mildew were GS 11.1, GS 10.5.3 and GS l 0.5.3, respectively. Models based on DI at CP to estimate the percentage of loss of 1000-kernel weight, crude protein content of grain and yield were better than models based on AUDPC. And models of the percentage of loss of 1000-kernel weight, crude protein content and yield for 2011-2012 season were significant different from these for 2009-2010 and 2010-2011 seasons. These results indicated that besides powdery mildew, weather conditions also had influence on 1 000-kernel weight, crude protein content of grain and yield loss of wheat when powdery mildew occurred.

Prediction model of moisture content of dead fine fuel in forest plantations on Maoer Mountain,Northeast China

Preventing and suppressing forest fires is one of the main tasks of forestry agencies to reduce resource loss and requires a thorough understanding of the importance of factors affecting their occurrence.This study was carried out in forest plantations on Maoer Mountain in order to develop models for predicting the moisture content of dead fine fuel using meteorological and soil variables.Models by Nelson(Can J For Res 14:597-600,1984)and Van Wagner and Pickett(Can For Service 33,1985)describing the equilibrium moisture content as a function of relative humidity and temperature were evaluated.A random forest and generalized additive models were built to select the most important meteorological variables affecting fuel moisture content.Nelson’s(Can J For Res 14:597-600,1984)model was accurate for Pinus koraiensis,Pinus sylvestris,Larix gmelinii and mixed Larix gmelinii—Ulmus propinqua fuels.The random forest model showed that temperature and relative humidity were the most important factors affecting fuel moisture content.The generalized additive regression model showed that temperature,relative humidity and rain were the main drivers affecting fuel moisture content.In addition to the combined effects of temperature,rainfall and relative humidity,solar radiation or wind speed were also significant on some sites.In P.koraiensis and P.sylvestris plantations,where soil parameters were measured,rain,soil moisture and temperature were the main factors of fuel moisture content.The accuracies of the random forest model and generalized additive model were similar,however,the random forest model was more accurate but underestimated the effect of rain on fuel moisture.

Effect of steam pretreatment on wood moisture content and characteristics of vacuum drying

The effects of high temperature steam pretreatment on the change in wood moisture content （MC） and characteristics of vacuum drying were investigated in this study. Poplar and manchurian walnut woods were pretreated with high temperature steam at 100~C and 140~C, prior to vacuum drying. A comparison of the characteristics of vacuum drying between steam pretreated wood and untreated wood was carried out. The results show that during steam pretreatment, the MC of wood decreased within a few hours. The reduction of MC varied with the temperature; the higher the temperature, the faster the MC dropped. During the vacuum drying stage, the rates of drying ofpretreated samples were higher than those of untreated samples when MC was below the fiber saturation point. Furthermore, the total drying time of samples treated at a steam temperature of 140~C was lower than that of untreated samples. Therefore, a vacuum procedure after steam pretreatment can effectively shorten the drying time when drying wood.

Theoretical modeling of the effects of temperature and moisture content on the acoustic velocity of Pinus resinosa wood

To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical propagation characteristics of the acoustic waves in the wood mixture and the differences in velocity among various media(including ice,water,pure wood or oven-dried wood),theoretical relationships of temperature,MC,and AWV were established,assuming that the samples in question were composed of a simple mixture of wood and water or of wood and ice.Using the theoretical model,the phase transition of AWV in green wood near the freezing point(as derived from previous experimental results) was plausibly described.By comparative analysis between theoretical and experimental models for American red pine(Pinus resinosa) samples,it was established that the theoretically predicted AWV values matched the experiment results when the temperature of the wood was below the freezing point of water,with an averageprediction error of 1.66%.The theoretically predicted AWV increased quickly in green wood as temperature decreased and changed suddenly near 0 °C,consistent with the experimental observations.The prediction error of the model was relatively large when the temperature of the wood was above the freezing point,probably due to an overestimation of the effect of the liquid water content on the acoustic velocity and the limited variables of the model.The high correlation between the predicted and measured acoustic velocity values in frozen wood samples revealed the mechanisms of temperature,MC,and water status and how these affected the wood(particularly its acoustic velocity below freezing point of water).This result also verified the reliability of a previous experimental model used to adjust for the effect of temperature during field testing of trees.

Development of Steel Slag-Based Solidification/Stabilization Materials for High Moisture Content Soil

To solve the problems of high moisture content,high viscosity,and poor engineering mechanical properties of soil,this paper using with steel slag(SS)and desulfurization ash(DS)as initial raw materials,realizing the coop-erative treatment of solid waste and solidification of silt soil.The synergistic utilization of SS and DS can reduce the production cost of curing agent and promote its own consumption.According to blended cement of various SS contents and inspected compressive strength performances,the most suitable raw materials ratio was selected.The best formula for this curing agent is cement:steel slag=3:7 with 5%DS,and its 28-day compressive strength can reach 30 MPa.The experiment shows that the effect of DS and Na_(2)SO_(4) reagent with the same quality on early compressive strength improvement of cement and SS system is not much different.In this study,the mineral composition and microstructure of different gel system blocks were characterized by XRD,SEM and EDX,and a large number of webbed structures were found in the SEM test,which was not seen in previous studies.Besides,unconfined compressive strength(UCS),water resistance,and toxic characteristic leaching procedure(TCLP)were used to evaluate silt solidified soil properties.The results demonstrated that the solidified silt could meet not only the standard of general subgrade;but also has a partial stabilization effect of heavy metal ions.

Effect of moisture content on the ultrasonic acoustic properties of wood

We determined the ultrasonic velocity and en- ergy attenuation value of three tree species （basswood, elm, and fir） 1 per tree in different moisture content levels, using RSM-SY5 ultrasonic testing instrument, and analyzed the regularity of ultrasonic velocity and energy attenuation values with moisture content, respectively. The ultrasonic velocity of the three species decreased as moisture content increased, with the turning point at 32 % of moisture content. When the moisture content was more than 32 %, the growth curve of ultrasonic wave velocity was flattened. The moisture contents of all three species increased under the any point moisture content of 1-60 %. The differen- tiation degrees of energy attenuation value of three species were higher than the corresponding ultrasonic wave ve- locity, when the moisture content was less than 15 %. The differentiation degrees of the energy attenuation value of three species was higher than the corresponding ultrasonic velocity, when the moisture content was more than 15 %.

Influence of Moisture Content,Variety and Parboiling on Milling Quality of Rice Grains

The effects of moisture content （8%, 10%and 12%）, variety （Tarom and Fajr） and parboiling on milling quality of rice as a function of milling recovery （MR）, head rice yield （HRY）, degree of milling （DOM） and whiteness were investigated. The parboiled grains was prepared with three soaking temperatures of 25 oC, 50 oC and 75 oC and three steaming times of 10, 15 and 20 min. As a result of parboiling, the increasing rates of MR and HRY values were 7.8%and 14.3%for Tarom and 9.8%and 10.0%for Fajr, respectively, and the decreasing rates for DOM and whiteness were 6.6%and 10.8%for Tarom and 6.8% and 10.5% for Fajr, respectively. Moreover, decreasing moisture content to 8%maximized MR （75.8% for Tarom and 74.3% for Fajr） and HRY （65.8% for Tarom and 57.0% for Fajr） while increasing that to 12%revealed maximum values of DOM （6.1%for Tarom and 6.2%for Fajr） and whiteness （24.8%for Tarom and 28.2%for Fajr）.

Investigating spatial and temporal variations of soil moisture content in an arid mining area using an improved thermal inertia model

Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content（SMC）. In this study, the spatial and temporal variations of SMC from 2001 to 2015 at two spatial scales（i.e., the Shendong coal mining area and the Daliuta Coal Mine） were analyzed using an improved thermal inertia model with a long-term series of Landsat TM/OLI（TM=Thematic Mapper and OLI=Operational Land Imager） data. Our results show that at large spatial scale（the Shendong coal mining area）, underground mining activities had insignificant negative impacts on SMC and that at small spatial scale（the Daliuta Coal Mine）, underground mining activities had significant negative impacts on SMC. Trend analysis of SMC demonstrated that areas with decreasing trend of SMC were mainly distributed in the mined area, indicating that underground mining is a primary cause for the drying trend in the mining region in this arid environment.

Diurnal variation models for fine fuel moisture content in boreal forests in China

Studying diurnal variation in the moisture content of fine forest fuel(FFMC)is key to understanding forest fire prevention.This study established models for predicting the diurnal mean,maximum,and minimum FFMC in a boreal forest in China using the relationship between FFMC and meteorological variables.A spline interpolation function is proposed for describing diurnal variations in FFMC.After 1 day with a 1 h field measurement data testing,the results indicate that the accuracy of the sunny slope model was 100%and 84%when the absolute error was<3%and<10%,respectively,whereas the accuracy of the shady slope model was 72%and 76%when the absolute error was<3%and<10%,respectively.The results show that sunny slope and shady slope models can predict and describe diurnal variations in fine fuel moisture content,and provide a basis for forest fire danger prediction in boreal forest ecosystems in China.