Moisture Content Of Material Research Articles

A framework for determining the optimal moisture content of high-speed railway-graded aggregate materials based on the lab vibration compaction method

The Lab Vibration Compaction Method (LVCM) has been demonstrated to be the most effective method for compacting High-Speed Railway Graded Aggregate (HRGA). The Optimal Moisture Content (OMC) of LVCM is traditionally determined using the Heavy Hammer Compaction Method (HHCM). However, the differing compaction mechanisms of these two methods raise questions regarding the applicability of the OMC determined by HHCM. To address this issue, a novel assessment method was developed to evaluate the compaction quality of specimens in LVCM from both physical and mechanical perspectives (e.g., ρdn, Krb, and K20). Through a series of vibration compaction tests, the physical and mechanical properties of HRGA specimens were explored for various moisture contents in order to define the OMC. Additionally, three Hybrid Machine Learning (ML) models (PSO-ANN, PSO-SVM, and PSO-RF) were trained using experimentally obtained data and relevant HRGA material features to predict the OMC. The results indicate that the Critical Moisture Content (CMC) index can serve as a standard criterion for determining the OMC in LVCM and that HRGA materials with CMC possess desirable strength and load-bearing capacity. Furthermore, the experimental data suggested that graded and water abrasion features of HRGA materials significantly affect the CMC. The PSO-ANN model has the highest predictive accuracy with R2 = 0.94, MSE = 0.141, and MAE = 0.28 and the lowest uncertainty with U95 = 1.028 and Tstat = 2.816 compared to other hybrid ML models. The findings of this study hold significant implications for advancing the widespread implementation and utilization of the Lab Vibration Compaction Method (LVCM).

Sustainable Use of Biochar, Poultry and Cattle Manure for the Production of Organic Granular Fertilizers

In agricultural activities, there is an increasing need for organic fertilizers to use nature-friendly materials used to fertilize the soil. Farmers have been using granular organic fertilizers made from composted or dried manure of cattle, poultry, pigs, ash, bone meal, and other materials for some time, but the quantities of these organic fertilizers are not large. Biochar is also being intensively studied as a material to improve soil quality and plant growth and reduce greenhouse gas emissions from soil. The suitability of cattle manure compost, poultry manure, biochar, and their combinations for granular fertilizers was analyzed in this work. The preparation of biochar for granulation may have differences compared to other organic materials due to the moisture content, fractional composition, bulk density, and other parameters of the granulated material, so this work examines the physical–mechanical and chemical properties of cattle and poultry manure and biochar raw material and the final granulated product. Research has found that the fractional composition of raw materials under investigation manure and biochar was up to 2 mm. The moisture content of the studied raw material varied from 8.97% in the case of poultry manure to 25.11% in the case of cattle manure compost. The lowest moisture content was obtained due to additional drying. The addition of biochar reduces the granule density in investigated cases. Poultry manure granules were the most mechanically stable, with a semi-static stability of 382.6 ± 78.08 N. After the addition of biochar, weaker binding properties were determined in the experimental granules. Analysis of the composition of elements shows that these granules can be used for fertilization or soil improvement. High concentrations of nitrogen (N), phosphorus (P), and potassium (K) were detected in the granules. The obtained results showed that it is appropriate to enrich the manure granules with biochar.

Application of Rapid Identification and Determination of Moisture Content of Coptidis Rhizoma From Different Species Based on Data Fusion.

For thousands of years, traditional Chinese medicine (TCM) has been clinically proven, and doctors have highly valued the differences in utility between different species. This study aims to replace the complex methods traditionally used for empirical identification by compensating for the information loss of a single sensor through data fusion. The research object of the study is Coptidis rhizoma (CR). Using spectral optimization and data fusion technology, near infrared (NIR) and mid-infrared (MIR) spectra were collected for CR. PLS-DA (n = 134) and PLSR (n = 63) models were established to identify the medicinal materials and to determine the moisture content in the medicinal materials. For the identification of the three species of CR, the mid-level fusion model performed better than the single-spectrum model. The sensitivity and specificity of the prediction set coefficients for NIR, MIR, and data fusion qualitative models were all higher than 0.95, with an AUC value of 1. The NIR data model was superior to the MIR data model. The results of low-level fusion were similar to those of the NIR optimization model. The RPD of the test set of NIR and low-level fusion model was 3.6420 and 3.4216, respectively, indicating good prediction ability of the model. Data fusion technology using NIR and MIR can be applied to identify CR species and to determine the moisture content of CR. It provides technical support for the rapid determination of moisture content, with a fast analysis speed and without the need for complex pretreatment methods. This study is the first to introduce spectral data fusion technology to identify CR species. Data fusion technology is feasible for multivariable calibration model performance and reduces the cost of manual identification. The moisture content of CR can be quickly evaluated, reducing the difficulty of traditional methods.

Experimental study on the effect of salt on the water absorption characteristic of cement mortar

Coastal buildings are exposed to salt spray environments for prolonged periods of time, and salt accumulates in the building walls. The effect of salt on the water absorption characteristics of the material is unclear and requires further investigation of the coupled heat and moisture transfer processes in coastal building walls. To address this issue and quantify this effect, cement mortar specimens were pretreated, and a capillary water absorption experiment was conducted on a salt-containing cement mortar to obtain the laws of the water absorption coefficient and capillary saturation moisture content with salt content. In addition, equations for fitting the water absorption coefficient and capillary saturation moisture content of salt-containing materials were established by integrating the salt impact factors proposed in this study. The obtained results showed that as the salt content increased, the water absorption coefficient first increased and then decreased, with a peak increase of 7.5% compared to that of the control group. The capillary saturation moisture content gradually decreased with increasing salt content, decreasing by 15.8% at the maximum salt content. Combined with scanning electron microscopy (SEM) observations of microstructural changes in specimens containing different amounts of salt, it was inferred that the dominant factors affecting the water absorption characteristics would be different when the salt content of the material was varied. In addition, the optimal formulae for the water absorption coefficient and capillary saturation moisture content of salt-containing materials were obtained.

Effect of Moisture Content and Particle Size on Characteristics of Fuel Pellets Using Flat Die Type Pelleting Machine

Fuel pellets are a popular form of biomass energy due to their high energy density, ease of handling, and reduced emissions. The quality of fuel pellets is influenced by various factors, including the moisture content and particle size of the raw materials (Soybean straw and cotton stalk) used during the pelletization process. In this study, the effect of moisture content and particle size on the characteristics of fuel pellets produced using a flat die type pelleting machine was investigated. Different moisture content levels (ranging from 20 to 30%) and particle sizes (ranging from 4 to 8 mm) were used to pelletize a biomass feedstock. The pellet characteristics, including pellet durability, bulk density and water resistance and energy consumption were evaluated. The results showed that both moisture content and particle size significantly influenced the characteristics of the fuel pellets as well as energy consumption. Based on the findings, an optimal moisture content of 25% and particle size of 6 mm were determined for producing fuel pellets with desirable characteristics and low energy consumption was required using the flat die type pelleting machine. These results can provide valuable insights for biomass pellet producers and researchers in optimizing the pelletization process to achieve high-quality fuel pellets with improved properties.

Application of the microwave method for measuring the moisture content of bulk materials in complex metallurgical processes

Application of the microwave method for measuring the moisture content of bulk materials in complex metallurgical processes

Thermal Conductivity of Insulation Material: Effect of Moisture Content and Wet-Drying Cycle

The insulation materials are widely used in petrochemical, power engineering and other industries. The thermal insulation materials play an important role in the energy saving of district heating systems and in the building sector. In this work, the thermal conductivity of rock wool with different levels of moisture content and density of the insulation material was investigated by an experimental method. Experimental studies were carried out on rock wool from three different manufacturers. The effect of the wetting and drying cycle on thermal conductivity and density of the insulating material is analyzed. The thermal conductivity of the insulating material was measured using the guarded hot plate method. It was found that the thermal conductivity of insulating materials significantly affected the moisture content. The increase in thermal conductivity was from 1.33 to 4.42 times, depending on the density and the manufacturer of the rock wool. The wetting and drying cycles increase the thermal conductivity and density of the insulating material up to 2 and 2.5 times, respectively.

Characterization Of Soil For Road Shoulders Mixed With Reclaimed Asphalt Pavement Waste

The use of recovered asphalt pavement can reduce the amount of new bitumen and aggregates used in pavement construction and rehabilitation (RAP). RAP is a waste product that results from the removal of an old or damaged pavement surface. Although it has been used since the 1970s, and numerous recommendations for using RAP in the new mixture have been made, there are only a few research available. Because the materials used are recycled, it is also cost-effective and environmentally friendly. The purpose of this study is to characterize soil that has been blended with reclaimed asphalt pavement (RAP) for use on the local road shoulder. RAP is one of the rehabilitation procedures used to repair a deteriorated surface by removing the upper pavement and replacing it with new pavement. According to earlier study, mixing dirt with different materials improves the finding. The goals of this study are to establish the material qualities of soil and RAP, determine the optimum moisture content of material and degree of compaction for road shoulders, and determine the appropriate mix proportion of soil and RAP for road shoulders using the California Bearing Ratio (CBR) test. The Atterberg limit, liquid limit, and plastic limit for soil were evaluated on a sample of soil and RAP. For soil and RAP, a sieve analysis was performed. Compaction tests for soil and RAP were carried out with a mixture of 10S, 2S8RAP, 4S6RAP, 6S4RAP, 8S2RAP, and 10RAP, as well as CBR tests for soil and RAP. . According to the results of the laboratory test, 20% of RAP (8S2RAP) had a better-mixed proportion for the road shoulder. As a result, repurposed materials like RAP can be used as road shoulder material. 
 Keywords: reclaimed asphalt, reuse of Asphalt,

Capillary Pressure Determination Using Thermodynamic Desorption Isotherms and Porosity Measurements

AbstractCharacterization of fluid flow in porous media depends on the capillary pressure. Experimental investigations on the capillary pressure are complicated and require advanced monitoring technologies. The objective of this study is to determine the capillary pressure by employing desorption isotherms measurements and using the Kelvin equation. The desorption isotherms curves were determined by the gravimetric method. The capillary pressure is presented as a function of the material's level of saturation, which is linked to the material moisture content and total porosity. Investigations were conducted over three types of clays to give classical behavior of their capillary pressure curves. The obtained results were compared with those of the literature concluding the reliability of the employed method to achieve good capillary pressure curve predictions.

Durability assessment of brick and stone structures in engineering surveys

Introduction. According to the main legal acts of the Russian Federation that regulate the procedure of inspection and monitoring of buildings and structures, the technical statement should include the results obtained during the studies and calculations of possible temporal variations. However, these results are virtually absent in the monitoring technical documentation presented today. In the case of brickwork, this is primarily due to the lack of reliable methods for durability surveys. For example, the formation of salts in the brick material can affect its durability. Such reactions are considered as the side reactions of the second type, i.e., reactions caused by external effects.Aim. To develop an engineering technique for assessing the durability of a brick material on the basis of a mathematical model.Materials and methods. The article presents the results obtained in a survey of a free-standing brick building, as part of the “GES-2” Moscow multifunctional complex built in 1906, using the developed techniques. The process of brick material destruction is considered according to the laws of physical chemistry and described by a multi-stage process.Results. The developed technique for assessing the durability of building ceramics can be additionally used to assess the residual durability of a historical building brick material.Conclusion. During the durability assessment of building walls made of ceramic masonry materials, it is necessary to take into account not only the frost resistance, but also the chemical destruction of materials. It is proposed to supplement the masonry inspection technique outlined in GOST 31937-2011 with the following items: sampling rules for the subsequent determination of the moisture content in structural materials with a statement of the requirements for equipment; sampling rules for the subsequent determination of the material residual durability, including the technique for calculating residual durability.

Characterisation of soil-like material restored from landfill mining activities in Indian cities

ABSTRACT This paper demonstrates the characteristics of soil-like material extracted from the landfill mining activity at the Ariyamangalam dump yard, located in Tiruchirappalli city of southern India. The landfill mining waste was collected and characterised for contaminant potential, thereby its suitability for reuse applications offsite. Soil-like materials of size fractions finer than 2 mm have been assessed for their physico-chemical characteristics and compared the acceptability criterion with the drinking standard IS 10500: 2012. Total soluble solids and closely associated parameters have been determined in the water extract from soil-like materials and local soils and compared with the international regulatory standards for reuse acceptability. From the total heavy metal concentration of soil-like material and local soil, three different pollution indices, namely contamination ratio, geo-accumulation index, and enrichment factor, have been identified and categorised soil-like material as low contaminated for lead; low to moderately contaminated for chromium, nickel, and iron; moderately contaminated for manganese; and moderately to strongly contaminated for copper and zinc. The organic and moisture content of soil-like material was reported as 22 and 19.6%, whereas the local soil showed 2.4 and 1.5%, respectively. Due to its enormous organic content, soil-like materials pose as less efficient in utilising offsite applications without primary treatment.

Online Machine Vision-Based Modeling during Cantaloupe Microwave Drying Utilizing Extreme Learning Machine and Artificial Neural Network

Online microwave drying process monitoring has been challenging due to the incompatibility of metal components with microwaves. This paper developed a microwave drying system based on online machine vision, which realized real-time extraction and measurement of images, weight, and temperature. An image-processing algorithm was developed to capture material shrinkage characteristics in real time. Constant-temperature microwave drying experiments were conducted, and the artificial neural network (ANN) and extreme learning machine (ELM) were utilized to model and predict the moisture content of materials during the drying process based on the degree of material shrinkage. The results demonstrated that the system and algorithm operated effectively, and ELM provided superior predictive performance and learning efficiency compared to ANN.

KARAKTERISTIK PENGERINGAN CABAI RAWIT (Capsicum Frutescens L) MENGGUNAKAN ALAT PENGERINGAN HYBRID TIPE RAK1)

ABSTRACT
 
 Chili plants are an agricultural commodity with great potential in Indonesia. The price of agricultural products is greatly influenced by the availability of materials in the market if the available goods are much less than the demand, the price will soar and vice versa. Therefore, to maintain chili peppers so that they can last for a long period of time it is necessary to carry out preservation in the form of drying. The temperature distribution during the drying process of cayenne pepper starts from the highest air temperature of each shelf, namely 13:00 with a temperature of 55,100C material temperature at 13:00 with a temperature of 55,400C, a collector temperature at 13:00 with a temperature of 63,800C and an ambient temperature of 360C. Air humidity greatly affects the drying process. The process of observing 46-hour air humidity, relatively low humidity occurs at 35 o'clock with the lower shelf hovering around 21.30%, the middle rack hovering around 14.30% hour to 46, the upper rack hovering around 13.40% while the environmental Rh hovering around 57.90% at 20 o'clock. The length of time for drying cayenne pepper using a rack-type hybrid dryer takes a span of 36 hours with the moisture content of cayenne pepper material on shelf 1 of 7.14%, shelf 2 of 7.14% while shelf 3 of 14.04%. The drying rate of cayenne pepper lower shelf, middle rack and upper rack is 11.61%/hour, 11.61%/hour and 2.91%/hour, respectively.

Thermal conductivity assessment of moist building insulation material using a Heat Flow Meter apparatus

Thermal conductivity is one of the most important parameters of building insulation materials. This parameter is dependent on the temperature, and on the moisture content for hygroscopic materials. When measured by steady-state methods (with the HFM device and the guarded hot plates), moisture will migrate from the hot side to the cold, influencing the measured heat flux and, thus, the measured thermal conductivity. This study aims to analyze the effects of moisture transfer on the thermal conductivity measurement of wet hygroscopic light building insulation material (namely wood fiber insulation). Several experiments are performed on instrumented samples to evaluate the influence of parameters like the thickness, the mean moisture content, the mean temperature, or the temperature gradient on the measured heat flux, on the temperature and relative humidity distributions and on the time to reach hygrothermal equilibrium. Particularly, the measurement errors made when shortening the experiment are discussed and the moisture dependence of true thermal conductivity is evaluated experimentally by considering the notions of apparent and diffusive thermal conductivities. Last, by using a validated heat and moisture transfer model, this dependency is compared to the one predicted by the methods proposed in the standards EN 12664 or ISO 10051.

Measuring systems in technologies of automated humidity control

This paper examines intelligent humidity sensors (transducers) as a component of an automated process control system that converts a controlled physical quantity into a measured signal for further processing in an automatic device, as well as mathematical models of intelligent support for bulk material moisture meters. It is demonstrated that one method for increasing the efficiency of the functioning of quality meters for various bulk materials is the development of conceptual foundations and their practical implementation in the construction of express devices capable of measuring grain and grain materials. The interaction of intelligent support measuring tools in technologies for automated moisture control in technological processes and control is investigated. The microwave method is recommended for monitoring the moisture content of grain and grain materials, as well as their metrological characteristics.

The Two Stage Moisture Diffusion Model for Non-Fickian Behaviors of 3D Woven Composite Exposed Based on Time Fractional Diffusion Equation

The moisture diffusion behaviors of 3D woven composites exhibit non-Fickian properties when they are exposed to a hydrothermal environment. Although some experimental works have been undertaken to investigate this phenomenon, very few mathematical works on non-Fickian moisture diffusion predictions of 3D woven composites are available in the literature. To capture the non-Fickian behavior of moisture diffusion in 3D woven composites, this study first utilized a time fractional diffusion equation to derive the percentage of moisture content of a homogeneous material under hydrothermal conditions. A two-stage moisture diffusion model was subsequently developed based on the moisture diffusion mechanics of both neat resin and 3D woven composites, which describes the initial fast diffusion and the long-term slow diffusion stages. Notably, the model incorporated fractional order parameters to account for the nonlinear property of moisture diffusion in composites. Finally, the weight gain curves of neat resin and the 3D woven composite were calculated to verify the fractional diffusion model, and the predicted moisture uptake curves were all in good agreement with the experimental results. It is important to note that when the fractional order parameter α < 1, the initial moisture uptake will become larger with a later slow down process. This phenomenon can better describe non-Fickian behavior caused by initial voids or complicated structures.

Evaluating the use of machine learning for moisture content prediction in base and subgrade layers

Subgrade moisture content significantly influences soil strength and pavement bearing capacity. Pavement moisture content varies greatly throughout the year, especially in cold regions. Thus, having a better understanding of seasonal variation in moisture content in the pavement is needed to be developed. This research aims to apply machine learning models to predict the moisture content of unbound materials in the pavement. Unfrozen volumetric moisture content measurements recorded at the Integrated Road Research Facility test road in Edmonton, Alberta were used to train machine learning models to predict moisture content at depths within 2.7 m of the road surface. Machine learning models were implemented based on three parameters of pavement temperature, day of the year and depth. The results from the machine learning model were compared with a statistical model and showed higher accuracy than the existing model, indicating that machine learning models could enhance moisture content prediction in the pavement.

Evaluation of machine learning approach for base and subgrade layer temperature prediction at various depths in the presence of insulation layers

ABSTRACT To protect pavement in cold regions, insulation layers have been used in pavement construction. The insulation layer blocks the heat exchange, resulting in different pavement temperature distributions at different layers. Pavements in cold regions are subject to frost heave, thaw weakening, and freeze–thaw cycling, and the moisture content of unbound materials is affected by the temperature of the pavement. Therefore, the base and subgrade temperature can affect the pavement performance, and the insulation layer influences the performance of the pavement. This work aims to demonstrate the capability of the machine learning method to predict the pavement temperature of the base and subgrade layers in the presence of insulation layers. Pavement temperature measured from sensors embedded in the pavement at the IRRF test road and environmental factors collected from a weather station were used to train machine learning models. The results obtained from machine learning models indicated that the air temperature and day of the year were the most robust input prediction parameters at each depth. Machine learning models outperformed the existing model and proved that it could be a method to improve pavement temperature prediction with insulation layers, especially when the base layer temperature is below 0°C.

Dynamic identification of brick masonry semi-circular arches due to temperature and moisture

This paper presents the effects of changes in temperature and moisture content on the dynamic properties of semi-circular arches made of clay brick and gypsum mortar constructed and tested in the laboratory. First, the mechanical properties of the materials used were determined by experimental tests. Operational Modal Analysis was then performed for each condition to measure natural frequencies, mode shapes, and modal damping ratios. An empirical equation for estimating the natural frequencies of the studied arch at different material moisture contents was proposed using the obtained results from experimental tests. Finally, the Finite Element Model Updating Method (FEMU) was applied to calibrate some of the material mechanical properties in modelled arches. In contrast to the effect of moisture, temperature changes showed a difficulty to interpret effect on the dynamic properties of the arch. On the other hand, Poisson's ratio did not affect the dynamic behaviour of the specimen.

Exploring Effective Bio-Cover Materials for Mitigating Methane Emission at a Tropical Landfill

Methane emission and oxidation in different bio-cover materials, i.e., sandy loam, compost, and stabilized wastes, were investigated at a municipal solid waste landfill in Thailand. The bio-cover was purged with extracted landfill gas while methane reduction through biological oxidation was studied. The moisture content in bio-cover materials was maintained with natural rainwater during the wet period and leachate irrigation during the dry period. Methane emissions were found to vary between media and were influenced by rainfall. The methane loading rates of the bio-cover varied from 8.2–20.3 mol/m3/d, being higher during the dry period. Methane removal rates at the bottom part of the biofilter (0.4–0.6 m depth), the most active zone, were found to be from 6.4–10.9 and 7.8–11.4 mol/m3/d during wet and dry periods. The highest methane removals were found in the lower part of sandy loam, followed sequentially by compost and stabilized wastes. Nevertheless, compost had the highest methane oxidation capacities and greater methanotroph population compared to sandy loam and stabilized wastes. Methanotroph type I was found to predominate during the dry period, whereas methanotroph type II was predominant during the wet period.