Measurement Of Moisture Content Research Articles

Wood Moisture-Content Measurement Accuracy of Impregnated and Nonimpregnated Wood.

The influence of the impregnation process of pine wood (Pinus sylvestris L.) samples on the electrical resistance changes and the moisture-content measurement accuracy is presented in this paper. In this study, the resistances of impregnated and nonimpregnated green pine timber harvested from northern Poland were compared. An impregnation method based on a vacuum-pressure chamber was used. Copper salts were applied as the impregnated solutions. The obtained results of the electrical resistance comparison showed a dependence of wood resistance on the moisture content. Higher conductivity occurred in impregnated wood samples filled with copper salt compared with wood samples without impregnation. Noticeable differences in the electrical resistance values were observed when the wood moisture content was significantly above the Fibre Saturation Point (FSP).

Sandy soil moisture content measurement method based on heated fiber Bragg grating

Actively heated optical fiber method (AHFO) based on fiber Bragg grating (FBG) temperature measurement technology has been continuously applied in soil moisture monitoring due to its advantages such as good durability, quasi-distribution, and small size. The FBG alumina ceramic tube sensor with symmetrical internal heating is used to design a laboratory model. By changing the inner capillary tube, a continuous function was used to fit the calibration relationship between the temperature rise and the volumetric water content, and the influence of different heating times on the calibration relationship was analyzed. Laboratory test studies have shown that the capillary tube with a low thermal conductivity material inside can help improve the sensor’s ability to resolve volumetric water content. The calibration relationship under short-time heating also has a high correlation, and it can also reduce the impact on the soil environment. The research results are of great significance for improving the measurement accuracy of the AHFO method and the improvement of the test method.

Measuring shrinkage of undisturbed soil peds

AbstractMethods to measure shrinkage curves typically either disturb natural aggregate structure or include difficult or slow volume measurement techniques. Additionally, most shrinkage curves are obtained by serial measurement of a few samples. We obtained shrinkage curves by collecting rapid, one‐off measurements of volume and moisture content for each of 200 undisturbed peds extracted from a field soil, taking measurements as peds slowly dried in the laboratory. The large sample size increased robustness of the shrinkage curve parameter estimates to noise generated by this rapid measurement technique, but a much smaller sample would have resulted in similar parameter estimates.

Acoustic surface impedance of sandy shores

This work presents an effort to characterize the relationship between moisture content and acoustic surface impedance of sandy soils. This effort is part of a larger project seeking to model long-range acoustic transmission loss over coastal areas. Previous studies were done to measure moisture content along the shore and collect samples for bench-testing with an impedance tube. This work seeks to build on those experiments by performing in situ acoustic surface impedance measurements with an omnidirectional sound source and two microphone receivers. These measurements follow the protocol set forth by the ANSI/ASA S1.18 and are recorded at multiple distances from the water on the shore. At each measurement location, sand samples are collected for gravimetric moisture analysis. Atmospheric conditions and ambient noise level are also recorded in accordance with the standard. These results demonstrate the variation of sand surface impedance from the fully saturated swash zone to nominally dry sand.

Measurement of the moisture content in woodchips through capacitive sensing and data driven modelling

In this paper, a helical capacitive sensor is developed to measure the moisture content (MC) in woodchips. Firstly, based on the orthogonal test method, the structure of the capacitive sensor is optimized to obtain the best possible uniform sensitivity. Then, the effect of the type and random distribution of woodchips on the capacitive MC measurement is investigated. Finally, three different algorithms, including support vector machine, random forest and deep neural network, are employed to establish the data driven models. Experimental results demonstrate that the proposed system is capable of measuring the MC in woodchips with absolute error within ±5%. The generalization capability is verified using the cedarwood with three size ranges, with R2, RMSE and MAE of 0.95, 1.69% and 1.28%, respectively. The absolute error of the predicted MC in cedarwood over the range 24.3% and 25.2% is found to be within ±2% for a range of packing densities.

Characterization of Pectin-Based Gels: A 1H Nuclear Magnetic Resonance Relaxometry Study.

Rare sugars are monosaccharides and their derivatives that are not commonly found in nature. d-Allulose is a rare sugar that is C-3 epimer of fructose and presents an alternative to sucrose with potential health benefits. In this study, different amounts of sucrose, d-allulose, and soy protein isolate (SPI) were used to prepare a set of pectin gels. The effect of these ingredients on the gels was studied at both a molecular level, by 1H nuclear magnetic resonance (NMR) relaxometry, and a macroscopic level, through the assessment of viscoelastic properties as well as hardness and moisture content measurements. The NMR dispersion profiles were analyzed considering relaxation mechanisms associated with rotational and translational diffusion motions of mono- and disaccharides as well as bound water molecules. Significant variations of the local diffusion coefficient for the studied formulations were evidenced by the model fitting analysis. The viscosity trends observed within each group of samples having the same amount of SPI were mostly in agreement with the diffusion coefficients obtained from the NMR relaxometry. The observed discrepancies could be explained considering hardness and moisture content results, which put into evidence the fact that decreasing the moisture (mainly free water) affects the macroscopic properties of the systems, such as hardness and viscosity, but not the local diffusion processes probed by NMR relaxometry. These findings show the importance of combining both micro- and macroscopic information to analyze the different properties of food products.

Estimate of Precision of Thermogravimetric Method of Measuring Moisture Content: Estimate of Precision and Effectiveness Gained with the Use of the Method in the Agro-Industrial Complex

Estimate of Precision of Thermogravimetric Method of Measuring Moisture Content: Estimate of Precision and Effectiveness Gained with the Use of the Method in the Agro-Industrial Complex

Capacitive Online Corn Moisture Content Sensor Considering Porosity Distributions: Modeling, Design, and Experiments

An online corn moisture content measurement device would be a key technology for providing accurate feedback information for industrial drying processes to enable the dynamic tracking and closed-loop control of the process. To overcome the problem of large measurement error caused by the characteristics of the corn flow state and the pore distribution when a parallel plate capacitor is applied to the online moisture content measurement process, in this study, we summarized the constraint conditions of the sensor’s structure parameters by mathematical modeling and calculated the optimal sensor design size. Moreover, the influence of porosity variation on moisture content measurement was studied by using the designed sensor. In addition, a mathematical model for calculating corn moisture content was obtained for the moisture content range of 14.7% to 26.4% w.b., temperature of 5 °C to 35 °C, and porosity of 38.4% to 44.6%. The results indicated that the fluctuation in the online moisture content measurement value was obviously reduced after the porosity compensation. The absolute error of the measured moisture content value was −0.62 to 0.67% w.b., and the average of absolute values of error was 0.32% w.b. The main results provide a theoretical basis and technical support for the development of intelligent industrial grain–drying equipment.

Development and verification of coupled hydro-mechanical analysis for rainfall-induced shallow landslides

To improve the performance of rainfall-based shallow landslide warning systems, a coupled hydro-mechanical analysis framework that integrates mechanical slope analysis and hydraulic infiltration is proposed. The limit equilibrium approach for infinite slopes of unsaturated soil is coupled with 1D infiltration analysis to evaluate the transient stability of the soil mass. A hybrid testing process that combines the calculations of stress and hydraulic boundaries near the sliding surface and an element testing system capable of simulating both the stress and hydraulic states on the element boundaries was developed to verify the coupled hydro-mechanical theory. The element-level modeling reveals that the proposed coupled hydro-mechanical analysis is adequate to predict the sliding depth and time of shallow landslides. Furthermore, a time-dependent warning framework based on subsurface moisture content measurements is proposed as an alternative to rainfall-based approaches for early warning of shallow landslides.

Haptic and Aesthetic Properties of Heat-Treated Modified Birch Wood

This paper deals with the effect of heat treatment on the selected physical properties of birch wood. Five stages of heat treatment were used, ranging from 160 °C to 200 °C, in 10 °C increments, having a peak treatment duration of 3 h for each level. Primarily, changes in thermal characteristics, namely conductivity, diffusivity, effusivity, volume heat capacity, changes in colour and gloss parameters, mass loss due to modification and different moisture content in wood under given equilibrium climatic conditions, were monitored. The ISOMET 2114 analyser was used to measure the thermal characteristics. The measurement principle of this analyser is based on the analysis of the thermal response of the analysed material to pulses of heat flow. Measurements of colour, gloss, density and moisture content were carried out according to harmonised EN standards. The aim was to experimentally verify the more or less generally known more positive perception of heat-treated wood, both by touch and sight, i.e., the warmer perception of darker brown shades of wood. In terms of thermal characteristics, the most interesting result is that they gradually decrease with increasing treatment temperature. For example, at the highest treatment temperature of 200 °C, there is a decrease in thermal conductivity by 20.2%, a decrease in volume heat capacity by 15.0%, and a decrease in effusivity by 17.7%. The decrease in thermal conductivity is nearly constant at all treatment levels, specifically at this treatment temperature, by 6.0%. The fact mentioned above is positive in terms of the tactile perception of such treated wood, which can have a positive effect, for example, in furniture with surface application of heat-treated veneers, which are perceived positively by the majority of the human population visually or as a cladding material in saunas. In this context, it has been found that the thermal modification at the above-mentioned treatment temperature of 200 °C results in a decrease in brightness by 44.0%, a decrease in total colour difference by 38.4%, and a decrease in gloss (at an angle of 60°) by 18.2%. The decrease in gloss is only one essential negative aspect that can be addressed by subsequent surface treatment. During the heat treatment, there is also a loss of mass in volume, e.g., at a treatment temperature of 200 °C and subsequent conditioning to an equilibrium moisture content in a conditioning chamber with an air temperature of 20 ± 2 °C and relative humidity of 65 % ± 5%, there was a decrease by 7.9%. In conclusion, the experiments clearly confirmed the hypothesis of a positive perception of heat-treated wood in terms of haptics and aesthetics.

Sensitivity of PR2 Capacitance Soil Moisture Meter for Irrigation Scheduling

Accurate soil moisture content measurement is essential for designing a robust irrigation scheduling and integrated water resources management (I.W.R.M.). Capacitance-based sensors have widely been used to monitor soil moisture at different measuring depths coupled with continuous and instantaneous outputs. This study's objective was to evaluate the PR2 capacitance moisture meter's performance on mineral and organic soil water content. The outputs of PR2 in m3 /m3 and vol.% were compared with gravimetrically measured soil moisture. The R.M.S.E. measurement at Site A at the first and second replicates increased from 0.49% to 0.67%. In contrast, the r2 value of 0.99 was obtained for the two replications when comparing the soil moisture content observed from gravimetric measurement and the automated outputs from the PR2 Probe soil monitor. The R.M.S.E. values were 0.48%, and 1.32% were estimated for the first and second replications at Site B. The result indicates that the PR2 Profile Probe could be a reliable alternative to other time-consuming, complex computer algorithms for accurate point measurement of soil moisture.

Sensitivity of PR2 Capacitance Soil Moisture Meter for Irrigation Scheduling

Accurate soil moisture content measurement is essential for designing a robust irrigation scheduling and integrated water resources management (I.W.R.M.). Capacitance-based sensors have widely been used to monitor soil moisture at different measuring depths coupled with continuous and instantaneous outputs. This study’s objective was to evaluate the PR2 capacitance moisture meter’s performance on mineral and organic soil water content. The outputs of PR2 in m3/m3 and vol.% were compared with gravimetrically measured soil moisture. The R.M.S.E. measurement at Site A at the first and second replicates increased from 0.49% to 0.67%. In contrast, the r2 value of 0.99 was obtained for the two replications when comparing the soil moisture content observed from gravimetric measurement and the automated outputs from the PR2 Probe soil monitor. The R.M.S.E. values were 0.48%, and 1.32% were estimated for the first and second replications at Site B. The result indicates that the PR2 Profile Probe could be a reliable alternative to other time-consuming, complex computer algorithms for accurate point measurement of soil moisture.

Comparison of Four Methods for Vertical Extrapolation of Soil Moisture Contents from Surface to Deep Layers in an Alpine Area

The accurate estimation of moisture content in deep soil layers is usually difficult due to the associated costs, strong spatiotemporal variability, and nonlinear relationship between surface and deep moisture content, especially in alpine areas (where complications include extreme heterogeneity and freeze-thaw processes). In an effort to identify the optimal method for this purpose, this study used measurements of soil moisture content at three depths (4, 10, and 20 cm) in the upper parts of the Babao River basin in the Qilian Mountains, Northwest China. These measurements were collected in the HiWATER (Heihe watershed allied telemetry experimental research) program to test four vertical extrapolation methods: exponential filtering (ExpF), linear regression (LR), support vector regression (SVR), and the application of a type of artificial neural network, the radial basis function (RBF). SVR provided the best predictions, in terms of the lowest root mean squared error and mean absolute error values, for the 10 and 20 cm layers from surface layer (4 cm) measurements. However, the data also confirmed that freeze-thawing is an important process in the study area, which makes the infiltration process more complex and highly variable over time. Thus, we compared the vertical extrapolation methods’ performance in each of the four periods with differing infiltration characteristics and found significant among-period differences in each case. However, SVR consistently provided the best estimates, and all methods provided better estimates for the 10 cm layer than for the 20 cm layer.

Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy.

Moisture content during nixtamalization can be accurately predicted from NIR spectroscopy when coupled with a support vector machine (SVM) model, is strongly modulated by the environment, and has a complex genetic architecture. Lack of high-throughput phenotyping systems for determining moisture content during the maize nixtamalization cooking process has led to difficulty in breeding for this trait. This study provides a high-throughput, quantitative measure of kernel moisture content during nixtamalization based on NIR scanning of uncooked maize kernels. Machine learning was utilized to develop models based on the combination of NIR spectra and moisture content determined from a scaled-down benchtop cook method. A linear support vector machine (SVM) model with a Spearman's rank correlation coefficient of 0.852 between wet laboratory and predicted values was developed from 100 diverse temperate genotypes grown in replicate across two environments. This model was applied to NIR spectra data from 501 diverse temperate genotypes grown in replicate in five environments. Analysis of variance revealed environment explained the highest percent of the variation (51.5%), followed by genotype (15.6%) and genotype-by-environment interaction (11.2%). A genome-wide association study identified 26 significant loci across five environments that explained between 5.04% and 16.01% (average = 10.41%). However, genome-wide markers explained 10.54% to 45.99% (average = 31.68%) of the variation, indicating the genetic architecture of this trait is likely complex and controlled by many loci of small effect. This study provides a high-throughput method to evaluate moisture content during nixtamalization that is feasible at the scale of a breeding program and provides important information about the factors contributing to variation of this trait for breeders and food companies to make future strategies to improve this important processing trait.

Calibration and comparison of two moisture content measurement methods for in situ monitoring of beech laminated veneer lumber

ABSTRACT A timber bridge constructed in 1815 was renovated in 2018, wherein the load-bearing system was reinforced with beech laminated veneer lumber (LVL) elements. Beech LVL is primarily found in dry and heated structures (Service Class 1). Although the material of this bridge would not be directly exposed to weather, it would be exposed to outdoor relative humidity ranging between 50% in spring and 90% or higher in autumn (Service Class 2). Thus, the moisture content development in the reinforcements was monitored to observe the response of the material under such conditions. The moisture content was measured using both sorptive and electrical resistance methods. The relationship between the electrical resistance of the material to moisture content and sorption isotherms was determined through laboratory experiments. Thereafter, the derived relationships were used to determine the moisture content measured on the bridge over a period of two years. Consequently, the two measurement methods resulted in overlapping of moisture content values, which remained within safe levels and are expected to be maintained in future. The overlapping moisture content measurements validated that either of the monitoring methods could be independently deployed to obtain reliable results.

Moisture Distribution during Water Absorption of Ordinary Portland Cement Mortars Obtained with Low-Field Unilateral Magnetic Resonance.

Moisture distribution in cement-based materials is important from the durability point of view. In the present study, a portable three-magnet array with an elliptical surface radio frequency coil was used to undertake magnetic resonance measurements of moisture content in ordinary Portland cement mortar and concrete samples. Measurements along the length of the samples during capillary water absorption produced moisture content profiles that were compared with reference profiles acquired using a magnetic resonance imaging instrument. Profiles obtained with the three-magnet array were similar in shape and in penetration depth to those acquired with magnetic resonance imaging. The correlation coefficient between the moisture content measured with both techniques was r2 = 0.97. Similar values of saturated permeability of the mortars with identical w/c ratio were computed with the Hydrus 1D software based on the moisture content profiles. Additionally, inverse Laplace transformation of the signal decays provided the water-filled pore size distribution in saturated and unsaturated regions of the samples. The three-magnet array was successfully used to acquire nuclear magnetic resonance signal from a concrete sample, which was not possible with the magnetic resonance imaging instrument using the single-point imaging technique.

A GIS-based approach for identifying suitable sites for rainwater harvesting technologies in Kasungu District, Malawi

A GIS-based approach for identifying suitable sites for rainwater harvesting (RWH) technologies was developed and applied in Kasungu District, Malawi. Data were obtained from reports, socio-economic survey documents of the area and maps. Field surveys were conducted in the villages of Chipala Extension Planning Area (EPA), in order to identify and evaluate the performance of existing RWH interventions, and determine factors for locating suitable areas for RWH. Observed soil moisture content was used to assess the water retention performance of the prevalent RWH technologies: contour tied ridging and soil mulching. A GIS-based Soil Conservation Service Curve Number (SCS-CN) method was used to map runoff potential for areas with RWH technologies, using physical factors of rainfall, land use, soil type and slope to estimate runoff potential. This was then integrated in a GIS database, with social-economic factors in the form of household income level and environmental factors, including impacts of implementing RWH, to determine the suitability of land areas for RWH in Kasungu District. One way analysis of variance (ANOVA) was used to test the impact of identified technologies by comparing the moisture content measurements for each of the identified technologies at 5% level of significance. The ANOVA results showed a statistically significant difference in the moisture measurements for the three technologies identified (P < 0.05). The RWH suitability map for the study area showed that 0.2% of the area considered had very high potential, 33.5% high, 55.9% moderate, 10.1% marginal and 0.3% not suitable for in-field RWH. The model was verified by locating the existing RWH on the suitability map obtained from GIS: 81% of RWH were located in the highly and moderately suitable areas whilst only 13% were located in areas of low suitability. Hence the developed model can reliably be used to predict potential areas for RWH.

Heat and Mass Transfer Modeling to Predict Temperature Distribution during Potato Frying after Pre-Treatment with Pulsed Electric Field.

Based on unsteady state heat conduction, a mathematical model has been developed to describe the simultaneous heat and moisture transfer during potato frying. For the first time, the equation was solved using both enthalpy and Variable Space Network (VSN) methods, based on a moving interface defined by the boiling temperature of water in a potato disc during frying. Two separate regions of the potato disc namely fried (crust) and unfried (core), were considered as heat transfer domains. A variable boiling temperature of the water in potato discs was required as an input parameter for the model as the water is evaporated during frying, resulting in an increase in the soluble solid concentration of the potato sample. Pulsed electric field (PEF) pretreatment prior to frying had no significant effect on the measured moisture content, thermal conductivity or frying time compared to potatoes that did not receive a PEF pretreatment. However, a PEF pretreatment at 1.1 kV/cm and 56 kJ/kg reduced the temperature variation in the experimentally measured potato center by up to 30%. The proposed heat and moisture transfer model based on unsteady state heat conduction successfully predicted the experimental measurements, especially when the equation was solved using the enthalpy method.

Ammonium perchlorate moisture quantitative detection using terahertz spectroscopy combined with chemometrics

Ammonium perchlorate (AP) occupies an important position in solid propellants. However, the increase of moisture content in AP will seriously affect its combustion performance and mechanical properties, resulting in the abnormal use of solid propellants, which may bring serious security risks. There are very few studies on the accurate measurement of AP moisture content, which makes this study of great value and significance. In this paper, the optical parameters of aqueous AP samples were measured by terahertz time domain spectroscopy. Combined with chemometrics, five quantitative prediction models were constructed. The results show that the absorption coefficient based genetic algorithm optimized extreme learning machine model has the best prediction results. This method can achieve accurate prediction for moisture content below 0.1%, and its absolute error is less than 0.001%, and the prediction error of the external verification model of different groups of samples is less than 0.06%. This study provides a reliable basis for rapid, accurate and non-destructive detection of the moisture content of ammonium perchlorate and similar substances.

Synthesis of a linear static function for grain moisture meter with capacitive sensors

Moisture content is a grain quality factor, a parameter which changes during the processes of storage and processing and determines consumer properties of different food products. OIML organization in its international recommendation OIML R59 “Moisture Meters for Cereal Grain and Oilseeds” restricts maximal permissible value of moisture meters uncertainty to not more than 3% of relative full scale error. Main task of the research is in receiving linear static function for the grain moisture meter with four capacitive sensors. Method of Least Squares and general linear regression instruments had been used for that purpose. Analyzing the graphs of modified static function for different moist substances it was possible to say that it happened to be far more effective than initial static function and the static function received from a first-order polynomial after the LS method implementation. Root mean estimator was calculated for initial static function, the static function received with the LS method and static function, received after general linear regression implementation as an integral difference between nominal and calculated values of moisture content. Corresponding root mean estimator values were 1.3062%, 1.1616% and 0.4158%, that proves the effectiveness of a static function modified with the general linear regression instruments. Keywords: moisture content measurement; capacitive moisture meter; reference channel; capacitive sensor; linear static function