Cone Index Research Articles

Tire mobility numbers and vehicles performance evaluation based on empirical approaches

The wheel mobility number is a dimension less parameter that has a great and effective influence on prediction the off-road wheeled vehicle’s performance. The wheel mobility number is affected by soil strength, vehicle’s weight, and tires geometry. Different types of published wheel mobility numbers were collected and theoretically investigated to compare their vehicle performance. The major goal of this paper is to investigate the impact of tires parameters on vehicle mobility. For this, the tire geometry was measured using experimental testing at various tires inflation pressures. A theoretical comparison is carried out to the investigate the effect of soil cone index, tire geometry and vehicle weight on mobility numbers. The theoretical results are arranged in three worked zones and the vehicle performance in terms of net traction and tractive efficiency using empirical approaches were predicted. A comparison between predicted results and published results gives a good correlation.

Effects of Tractor and Soil Parameters on the Depth of the Permanent Traffic Lanes in Controlled Traffic Farming Systems

One of the basic requirements for controlled traffic farming (CTF) is the precise motion of all agricultural equipment on permanent traffic lanes (PTL). Tractors of machine-tractor units are then equipped with a GNSS (global navigation satellite) RTK (real-time kinematic) system, even though in many parts of the world, and Europe as well, satellite navigation is not yet used. In this case, for implementation of the CTF system, it needs to lay such PTL tracks that would be sufficiently visible, especially when using the CTF system in multi-year agricultural crop cultivation. The PTL track depth is influenced by both tractor and soil parameters and, in this paper, this influence is studied considering the dimensionless π-terms of the similarity theory. To obtain a greater depth of PTL tracks (h), the soil cone index must be low. The low density of the soil is important, even if its effect on the parameter h is less than that of the soil cone index. A greater depth of PTL tracks is also obtained by increasing the inflation pressure in the tractor tires. Ballasted wheels are the least effective for increasing the value of the parameter h.

Veris 3100 Application for Determining the Fertility of Rice Fields Before Land Preparation

Agriculture 4.0 demands the continuous development of technology and science in agriculture. Agriculture 4.0 applies the use of the latest technology to increase efficiency in agriculture both in terms of on-farm and off-farm. Provision of fertilizers and plant nutrients is an important factor in plant growth, but the fertilizer and nutrient needs of each block of the plant have different amounts depending on the condition of the soil condition and environment such as local climate. Generally physical and chemical measurements of soil done in laboratory which are laborious in sampling, takes a long time for analysis and costly. Nowadays there are some EC, PH, moisture sensor based on probe. However, this method cannot give results in real time also. Electrical conductivity of the soil (EC) has closed relation with physical and chemical properties of soil. Veris-3100 is one instrument that can measure EC for those purposes. This paper describes the correlation of measured EC by Veris-3100 and spot measurements of soil bulk density, cone index, pH and measured EC by probes.

Determine Field and Machine Operating Condition of Rice Combine Harvester to Minimize Grain Loss

Paddy can be harvested by a manual or mechanization metode. Mechanization harvesting also use some of machinery, one of example is rice combine harvester. This research has a goal to test performance of this machine in condition of field when the machine operates to know that it is worth or not to use based on national standard. The results of this research show that the field has a dry bulk density value 0.9 g/cc with 5.55 kgf/cm2 of cone index, water content is about 72.52 % and 65.49 % of soil’s porosity. Field efficiency of this machine is around 77.12 % with 915.28 kg/h of harvest capacity and 2.07 % of harvest losses. The capacity of hay disposal unit is about 170.4 kg/h with 97.69 % of grain cleanliness level. The slip that happened is about 8.01 % with actual velocity 0.535 m/s and 1.02 liter/h of fuel consumption. All of that are compared and evaluated with SNI 8185-2015 and the results show that this machine is worth to use in that area. Based on teority measurement on traction unit, this machine has rolling resistance around 121.6 kg from total weight, and has a critical traction around 532 kg and it has a rimpull value about 1525.15 kg.

A Global Path Planning Method for Unmanned Ground Vehicles in Off-Road Environments Based on Mobility Prediction

In a complex off-road environment, due to the low bearing capacity of the soil and the uneven features of the terrain, generating a safe and effective global route for unmanned ground vehicles (UGVs) is critical for the success of their motion and mission. Most traditional global path planning methods simply take the shortest path length as the optimization objective, which makes it difficult to plan a feasible and safe route in complex off-road environments. To address this problem, this research proposes a global path planning method, which considers the influence of terrain factors and soil mechanics on UGV mobility. First, we established a high-resolution 3D terrain model with remote sensing elevation terrain data, land use and soil type distribution data, based on a geostatistical method. Second, we analyzed the vehicle mobility by the terramechanical method (i.e., vehicle cone index and Bakker’s theory), and then calculated the mobility cost based on a fuzzy inference method. Finally, based on the calculated mobility cost, the probabilistic roadmap method was used to establish the connected matrix and the multi-dimensional traffic cost evaluation matrix among the sampling nodes, and then an improved A* algorithm was proposed to generate the global route.

Smart Computing Techniques for Predicting Soil Compaction Criteria under Realistic Field Conditions

The primary objective of this paper was to develop an artificial neural network (ANN) simulation environment and mathematical models for predicting with high accuracy soil compression parameters. The experiments were conducted at the College of Agriculture - University of Basra, located at Garmat Ali, the soil was silty clay loam. The factors that were investigated are moisture content (14 and 24%), tillage depths (0, 15, 30, 45, and 50 cm) forward speeds (0.57, 0.94, and 1.34 m.s-1) and tire pressures (50, 100, and 150 kPa). ANN environment was developed with the back propagation algorithm using MATLAB software with various structures and training algorithms. Design Expert software utilized to evaluate the studied parameters and produce mathematical models. The results showed that all studied parameters had a significant effect on soil physical properties including bulk density and cone index. The effects of the studied factors on bulk density were depth > moisture content > forward speed, > tire pressure (6% 4%, 2.4%, 2%, respectively). Whereas, the order of the investigated factors based on their effects on cone index were depth > moisture content > tire pressure > forward speed (6%, 4%, 2.4% and 2%, respectively). The best model for predicting the bulk density under different field conditions was the 4-8-1 architecture. Levenberg-Marquardt (Trainlm) produced outstanding performance with an MSE of 0.00226 and R2 of 0.986. Moreover, this performance was occurring at an epoch of 100. For predicting cone index, the best performance was achieved by Levenberg-Marquardt (trainlm) in 85 epochs, giving minimum MSE equal to 0.005112 and greater (R2) equal to 0.967 during the training process. Thus, the optimal structure for predicting cone index was 4-7-1.

Multi-Sensor Approach Combined with Pedological Investigations to Understand Site-Specific Variability of Soil Properties and Potentially Toxic Elements (PTEs) Content of an Industrial Contaminated Area

A combination of indirect soil investigation by proximal soil sensors (PSS), based on geophysical (ARP, EMI), physical (Cone Index –CI– by ultrasound penetrometry) and spectrometric (γ-rays) techniques, as well as pedological surveys, was applied in the field to assess the spatial variability of soil pollution and physical degradation in an automobile-battery recycling plant in southern Italy. Five homogeneous zones (HZs) were identified by the PSS and characterized by soil profiles. CI measurements and field analysis showed clear features of physical (i.e., soil compaction, massive structure) degradation. XRF in situ (on profiles) analysis using portable equipment (pXRF) showed Pb, Cd and As concentrations exceeding the contamination thresholds provided by the Italian regulation for industrial land use up to 20 or 100 cm of depth. Hence, a validation procedure, based on pXRF field survey, was applied to the PSS approach used for the HZs identification. High consistency was found between the HZs and the PTEs in the most contaminated areas. Significant negative Pearson correlation coefficients were found between γ-rays dose rate and Pb, Cu, Zn, As and Ni; positive ones were found between γ-rays and autochthonous lithogenic elements (V, Ti, Mn, K, Sr, Nb, Zr, Rb, Th), confirming that higher radionuclide activity correlated with lower pollution levels.

Soil Compaction from Wheel Traffic under Three Tillage Systems

Agricultural fields are usually subjected to high amounts of traffic from field operations. The influence of traffic on sandy loam soil in three tillage systems were investigated in a field experiment. The field was located in a Canadian prairie region. In the experiment, the treatments were three tillage systems: no-tillage, disc tillage, and spring-tine tillage. Following tillage operations, field plots were trafficked with one pass of a sub-compact tractor. Soil properties were measured before and after the traffic to examine the effects of tillage systems and wheel traffic. For the effects of the tillage systems on the soil bulk density, soil shear strength, soil surface resistance, and soil cone index, the no-tillage system had higher values for all the soil properties when compared with the disc and spring-tine tillage systems. The plant (canola) population density ranged from 18.2 plants/m2 to 34.9 plants/m2, with the no-tillage having the lowest plant densities. For the effects of wheel traffic, one pass of the tractor in the disc and spring-tine tillage plots resulted in a 2.7% and 17.4% reduction in soil moisture content, respectively. After wheel traffic, the average soil shear strength for the disc and spring-tine systems were still significantly lower than the no-tilled system. Sinkages of 40 and 50 mm were observed for the spring-tine and disc tillage systems, respectively. The results of this study highlight the importance of preventing the demerits of soil compaction induced by wheel traffic after tillage operations.

Effects of subsoiling tillage on structure, permeability, and crop yields on compacted Solonetzic and Chernozemic dryland soils in Western Canada

Compaction induced by field wheel traffic and dense layers in the subsoil may adversely alter soil structure, impede soil aeration, restrict water infiltration and nutrient uptake, and inhibit plant root development, negatively affecting plant yields. Reclaiming compacted Chernozemic and Solonetzic soils with hardpan B horizons may be possible through subsoiling operations to loosen the soil to depth, e.g. ~0.30 m. The objective of this study was to evaluate the effect of subsoiling on soil physical properties and plant yield in wheel traffic compacted and non-compacted Chernozemic and Solonetzic soils in southern Saskatchewan Canada. Subsoiling increased air permeability in the compacted Chernozemic soil from 4.5x10-7 m sec-1 to 2.9x10-6 m sec-1. In the compacted Solonetzic soil, subsoiling significantly decreased soil cone index to 1579 kPa compared to 2376 kPa in the non-subsoiled treatment. Crop yields (hard red spring wheat, dry peas) in the two years following the treatment were similar among tillage and compaction treatments in the Chernozemic soil. However, subsoiling of the compacted Solonetzic soil resulted in a seed yield increase of canola of ~ 1000 kg ha-1 in the first year of study and no treatment effect in the second year when wheat was grown. Overall, subsoiling of the compacted soils tended to improve soil physical properties, especially in the Solonetzic soils.

Soil Sustainability: Analysis of the Soil Compaction under Heavy Agricultural Machinery Traffic in Extensive Crops

Crop establishment depends mostly on the soil preparation and sowing methods used. Our main goal was to evaluate soil compaction and its effects on wheat (Triticum aestivum L.) and soybean (Glycine max L.) yields and seedling emergence with two different tillage methods: no-tillage (NT) and conventional tillage (CT). The study was done in the Western Pampas Region during three cropping seasons. The soil of the study site is a Mollisol. The variables measured were: (1) cone index (CI), (2) dry bulk density (DBD), (3) seedling emergence (SE), and (4) crops yield (CY). For both crops, seedling emergence was slower in NT than in CT, but results were similar 22 days after sowing. After 3 years, the results show that in NT the DBD and CI reached values of 1653 kg m−3 and 3210 kPa, respectively (between 275 and 300 mm). While in CT the values of DBD and CI reached were 1540 kg m−3 and 2300 kPa respectively at the same depth. The highest yields were found in CT (3.31 and 4.10 tons/ha−1, for soybean and wheat, respectively) compared to NT (2.91 and 3.53 tons/ha−1). Topsoil horizon has to be tilled to improve crop yields. In spite of the high number of equipment passes in CT, both tillage systems caused subsoil compaction.

Optimisation and modelling of draft and rupture width using response surface methodology and artificial neural network for tillage tools

Context Soil–tool interaction modelling and optimisation reduce manufacturing costs and energy requirements for precision tillage equipment design. Diverse tillage tools have been designed to reduce draft requirements and desirable soil disturbance, but this is not fully understood. Aims The current study investigated the effects of tool width, cone index, depth, and forward speed on draft with corresponding rupture width in order to develop response surface methodology (RSM) and artificial neural network (ANN) models and compared them to other models in order to predict draft and rupture width. Methods Experiments were carried out in a soil bin with a vertisol, and rupture width was measured using an image processing technique. Key results Using RSM, the optimum values for minimum draft with maximum rupture width within a range of independent variables were found to be 100 mm tool width, 600 kPa cone index, 141.63 mm tillage depth, and 3 km/h forward speed. For predicting the draft, the coefficients of determination (R2) for ANN and RSM models were 0.997 and 0.987, respectively; for rupture width prediction, R2 were 0.921 and 0.976. Conclusions Developed ANN and RSM models of draft and rupture width were better than other analytical or numerical models, and both models’ predictions were in good agreement with experiment values within the range of ±5% uncertainty. Implications The developed models can be used to predict the draft and soil disturbance requirements of tillage tools and design precision tillage tools.

Floristic Composition: Dynamic Biodiversity Indicator of Tree Canopy Effect on Dryland and Improved Mediterranean Pastures

Montado is a characteristic ecosystem of the Mediterranean region. The adequate management of this silvo-pastoral ecosystem requires good understanding of the effect of factors such as tree canopy, fertilization and soil amendment on pasture growth. The main objectives of this work were: (1) to evaluate the effect of tree canopy on soil characteristics and pasture productivity and quality; and (2) to test floristic composition assessment as a bio-indicator of soil improvements (amendment and fertilization) in each study area (under and outside tree canopy). Topsoil was characterized at the beginning of the project (October 2015) and at the end of the experiments (spring 2020). Soil parameters obtained by electronic sensors (soil moisture content, soil cone index and surface temperature) were monitored monthly during the 2017/2018 pasture vegetative cycle. Pasture productivity, quality and floristic composition were evaluated every two years (2016, 2018 and 2020) in the spring flowering period. The results of the floristic inventory were submitted to a multilevel pattern analysis (Indicator Species Analysis, ISA). Pasture biodiversity was evaluated based on the calculation of richness indices. This study showed a positive effect of tree canopy on soil fertility and pasture quality (e.g., CP). Pasture productivity, on the other hand, was higher in areas outside tree canopy. The great potential of ISA as a tool for identification of bio-indicator species was also demonstrated. Pasture species were identified as ecological and dynamic attributes characteristic of each study area, before and after soil amendment and fertilization.

Experimental evaluation of cone index gradient as a metric for the prediction of wheel performance in reduced gravity

Traversing granular regolith in reduced gravity remains a challenge for wheeled rovers. Earth-based testing cannot fully predict rover mobility as it precludes gravity’s effects on the soil. The simulant GRC-1 was designed to account for this by matching cone penetrometer readings from Apollo; the assumption is that replicating the cone penetrometer response of lunar soil will also replicate its response to vehicle loading. Cone penetrations were performed in GRC-1 at three densities in 1-g and 1/6-g aboard parabolic flights producing effective lunar-g. A fourfold decrease in cone index gradient (G) was seen in 1/6-g, indicating significantly reduced shear strength. Wheel experiments in GRC-1 in 1/6-g at one density and two slip values were compared to 1-g experiments at a lower density producing the same G value. In 1-g, drawbar pull was 44% higher and sinkage was 13.5% lower, indicating that the assumption made during the creation of GRC-1 was not quite correct, and that caution should be exercised when interpreting results obtained with this simulant. At the loosest possible density in 1-g, drawbar pull was still 24% higher than in lunar-g; sinkage was 76% higher. Future experiments utilizing a stronger simulant in lunar-g are outlined to elaborate upon these findings.

Zero and controlled traffic improved soil physical conditions and soybean yield under no-tillage

Soil compaction can negatively affect a range of soil hydraulic, biogeochemical and plant physiological processes. A study conducted in Luján (Argentina) investigated the effect of three traffic treatments (zero, controlled, and random traffic) on soil physical properties and soybean yield over a period of eight years. The soil at the site (Typic Argiudoll) had been managed under continuous no-tillage for nine years. Field-wheeled areas under controlled and random traffic management were 3309 m2 ha−1 or 33.1% and 4622 m2 ha−1 or 46.2%, respectively. ‘Random’, non-controlled traffic farming represented the standard mechanisation management practice. The three traffic treatments relied on commercially available (unmodified) farm equipment. Results showed that soil cone Index (depth range: 0–450 mm) increased in the order: zero (1.90 ± 0.31 MPa) > controlled (2.46 ± 0.19 MPa) > random (3.75 ± 0.21 MPa) traffic, respectively, which therefore explained treatment differences in root biomass. Water infiltration rates decreased significantly with increased traffic footprint (by up to 35% in random traffic), which therefore reduced plant available water and influenced crop performance. Grain yields with zero traffic were fairly consistent between-years, but increased with controlled traffic (which progressively approached the yields achieved with zero traffic) and decreased in random traffic at average rates of 33 and 29 kg ha−1 per year, respectively. Treatment differences in grain yield widened in drier compared with wetter years when plant growth and yield were less constrained by water availability. An average yield penalty of ≈ 30% was recorded in random traffic relative to the other treatments. Gross income with random traffic was USD787 per ha, which compared to USD1179 and USD1116 per ha with zero and controlled traffic, respectively. The proposed approaches to mitigating adverse effects of compaction on crop productivity, sustainability and profitability appear to be cost-effective options and may be adopted when fully-matched machinery is not available. There is potential for future development of controlled traffic farming in Argentina.

EFFECT OF TRACTOR WHEEL TRAFFIC ON SELECTED SOIL PHYSICAL PROPERTIES

The increasing use of agricultural machines in most mechanized farming fields has led to amplified soil compaction levels due to wheel traffic. Since wheel traffic is still underestimated, the main objective of this research was to determine the effect of wheel traffic on soil physical properties. This research determined the effect of wheel traffic on bulk density, soil texture, porosity, infiltration rate, hydraulic conductivity, and cone index using a field experiment at Egerton University Tatton Farm. A walking tractor was used to provide traffic loads. The experiment was conducted in a completely randomized design (CRD) with three weight applications and three traffic locations. The treatments were 1.72 kN (one tractor pass), 5.15 kN (three tractor passes) and 8.09 kN (five tractor passes) and three traffic locations, which are traffic on rows (TR), traffic between rows (TB) and traffic on the entire row (TE), replicated three times. Average moisture contents of the soil for depth ranges of 0 to 15 cm, 16 to 30 cm and 31 to 45 cm were recorded as 23%, 25% and 27%, respectively. The applied weight significantly increased bulk density and cone index but decreased infiltration rate, hydraulic conductivity and porosity. Bulk density increased by 17%, 15% and 8%, cone index increased by 44%, 10% and 7%, and porosity decreased by 25%, 23% and 36% for the three depth ranges after the three weight treatments were applied, respectively. Hydraulic conductivity decreased from 65.2 cm/day, 50.98 cm/day, and 34.05 cm/day to 13.95 cm/day, while infiltration rates decreased from 0.047 cm/min, 0.031 cm/min, and 0.018 cm/min. TE had the highest bulk density as compared to TB and TR. Analysis of variance indicated changes in weight applied, traffic location, and depth with significant effects on soil properties at a 5% level of confidence. It was concluded that wheel traffic causes soil compaction at varying levels depending on the applied weight, thus affecting the soil physical properties. This suggests that decreased and controlled wheel traffic could be a promising way to alleviate soil compaction.

A comprehensive approachfor off-road trafficability evaluation and development of modified equation for estimation of RCI to assessregional soil variation using geospatial technology

The information of terrain is highly valuable as the accuracy of decision maker depends on input data for taking the correct decision. For planning of any successful off-road movement, the terrain information plays the vital role. This paper describes the state of art of off-road trafficability leading from the contributing factors, Instruments for measurements and trafficability mapping techniques in chronological order. In modern times, the number & type of tracked or wheeled vehicles, has increased many times, therefore off-road trafficability for operation planning became a complex task to handle. The accuracy and reliability of measurements involved in trafficability will play a major role for any successful operation. Off-road trafficability shows the capacity of soil required for vehicular movement. Remolding Cone Index (RCI) indicates the soil's capability for off-road movement. In this study, the area was divided in equal small grids for ease of computation of RCI. Geospatial technology provides the platform to determine the locations of observation points as well as the extrapolation of information of inaccessible area using geospatial tools and techniques. RCI values were computed for each grid and also measured with cone penetrometer in the field. R2 value for observation values was determined for different soils present in the area to check the accuracy of measurements and then based on observed value and computed value, R squared (coefficient of determination) values (0.7754 and 0.4867) were evaluated for both study areas to get the idea about relevance, reliability and accuracy. Residual RCI (RRCI), difference of computed & observed was also analyzed for different soils for different moisture conditions. Based on thisanalysis, a modified equation was developed for different type of soils present in the study area. This development will pave the way to compute the RCI accurately, which will be used to assess the off-road trafficability of other areas in similar manner. Therefore, this study is useful to assess the regional variation of soil behavior towards trafficability based on modified equation.

Fundamental study on underwater trafficability for tracked vehicle

In recent years, water disasters have increased in Japan. In water disaster, remote controlled vehicles which work for disaster recovery must run in water environment. Since underwater ground is likely to be soft, the vehicle has a risk of stuck. If a vehicle gets stuck at disaster sites, rescue work is difficult because it is not easily to access to that area. We must make a method for judging whether to run or not. For this purpose, we must quantitatively clarify the relationship between the trafficability and the strength, bearing capacity, etc. of underwater ground. We measured the cone index of underwater ground. From results, we confirmed that fragile layer was formed on the surface layer in underwater ground. We measured drawbar pull of a tracked carrier in test field. As a result, maximum drawbar pull of underwater ground was lower than on the ground. After slip occurs, drawbar pull of underwater ground was smaller than ground significantly.

Combined Effect of Disc Coulters and Operational Speeds on Soil Disturbance and Crop Residue Cutting under No-Tillage System in Soil Bin

In the present study, a residue cutting system comprising of different disc coulters (plain, notch, curved teeth, cutter bar and star wheel) was developed and its performance was evaluated under no-tillage system in soil bin. The performance of residue cutting system was evaluated by performing a total of 135 experiments (including replications) in soil bin (black cotton soil, moisture content: 16.8–18.4% db and cone index: 1600±100 kPa) using forward speeds of 0.56, 0.83 and 1.11 m∙s−1 under the crop residues of rice (8 t∙ha−1), wheat (8 t∙ha−1) and maize (16 t∙ha−1). The effects of disc coulters and operational speeds on performance parameters viz. penetration depth, top width, soil disturbance and residue cutting were investigated. For all type of disc coulters, penetration depth and top width were found in the range of 5–10 and 0.6–5.7 cm, respectively. The least soil disturbance was observed for star wheel disc coulter under maize residue. The operational speeds of 0.56 and 1.11 m∙s−1 favored lesser soil disturbance. The highest mean residue cutting was observed for star wheel disc coulter (98.15%) followed by notched (84.12%), curved teeth (75.82%), plain (61.82%) and cutter bar blade disc coulter (52.12%). The change in forward speed did not produce significant effect on residue cutting. Star wheel disc coulter was effective in cutting of medium to heavy residue loads of rice, wheat and maize crops along with minimal soil disturbance.

Application of spatio-temporal data in site-specific maize yield prediction with machine learning methods

In order to meet the requirements of sustainability and to determine yield drivers and limiting factors, it is now more likely that traditional yield modelling will be carried out using artificial intelligence (AI). The aim of this study was to predict maize yields using AI that uses spatio-temporal training data. The paper has advanced a new method of maize yield prediction, which is based on spatio-temporal data mining. To find the best solution, various models were used: counter-propagation artificial neural networks (CP-ANNs), XY-fused Querynetworks (XY-Fs), supervised Kohonen networks (SKNs), neural networks with Rectangular Linear Activations (ReLU), extreme gradient boosting (XGBoost), support-vector machine (SVM), and different subsets of the independent variables in five vegetation periods. Input variables for modelling included: soil parameters (pH, P2O5, K2O, Zn, clay content, ECa, draught force, Cone index), micro-relief averages, and meteorological parameters for the 63 treatment units in a 15.3 ha research field. The best performing method (XGBoost) reached 92.1% and 95.3% accuracy on the training and the test sets. Additionally, a novel method was introduced to treat individual units in a lattice system. The lattice-based smoothing performed an additional increase in Area under the curve (AUC) to 97.5% over the individual predictions of the XGBoost model. The models were developed using 48 different subsets of variables to determine which variables consistently contributed to prediction accuracy. By comparing the resulting models, it was shown that the best regression model was Extreme Gradient Boosting Trees, with 92.1% accuracy (on the training set). In addition, the method calculates the influence of the spatial distribution of site-specific soil fertility on maize grain yields. This paper provides a new method of spatio-temporal data analyses, taking the most important influencing factors on maize yields into account.

Accelerated carbonation of alkaline construction sludge by paper sludge ash-based stabilizer and carbon dioxide

Construction sludge frequently has high alkalinity after its generation or during the intermediate treatment process. The aim of this study is to experimentally investigate the potential of combining accelerated carbonation and a paper sludge ash-based stabilizer (PSAS) to neutralize the alkalinity of construction sludge in a short period and to improve its strength for use as a recycled material. The experimental results indicate that the addition of a PSAS significantly granulated the alkaline sludge, and once granulated, the PSAS successfully accelerated the pH neutralization of the alkaline sludge. It was also found that the decrease in dry density ρd and the degree of saturation Sr of the PSAS-treated sludge was able to reduce the period required for the pH neutralization, tN. The decrease in ρd is thought to allow fresh CO2 gas to penetrate the specimen more easily. However, if Sr is below a certain limit, it does not strongly facilitate the reduction of tN. This implies that pH neutralization cannot be accelerated when the amount of water in the sludge is below a certain level. Moreover, it was found that mean particle diameter D50 also affected tN. The strength development of the PSAS-treated sludge was evaluated using a series of cone index tests. It was found that the strength of the alkaline sludge without the PSAS was significantly decreased by accelerated carbonation, but was significantly increased even after accelerated carbonation when the PSAS was present. Due to the porosities of the remaining PS ash particles, most of the contribution of the water absorption and retention performance of the PSAS to the strength development of the PSAS-treated sludge was secured after accelerated carbonation. In addition, the granulated particles of the PSAS-treated sludge retained their granular shape to some extent. Therefore, it is presumed that the friction and interlocking of the particles did not decrease significantly. It was also found that, after carbonation, the qc of the PSAS-treated sludge increased more rapidly than that of the alkaline sludge without the PSAS. A further detailed examination of the test results showed that under air-curing conditions, the qc of the treated sludge with accelerated carbonation increased relatively gradually compared to that of the treated sludge without accelerated carbonation.