Mohd Hazreek Zainal Abidin

Soil resistivity measurements to predict moisture content and density in loose and dense soil

In the past, most of the soil electrical resistivity charts were developed based on stand-alone geomaterial classification with minimal contribution to its relationship to some of geotechnical parameters. Furthermore, the values cited a very wide range of resistivity with sometimes overlapping values and having little significance to specific soil condition. As a result, it created some ambiguities during the interpretation of observations which were traditionally based on qualitative anomaly judgments of experts and experienced people. Hence, this study presents soil resistivity values based on laboratory experiment with a view to predict the soil moisture content and density in loose and dense soils. This study used a soil box and a resistivity meter to test a clayey silt soil, increasing its water usage from 1-3% based on 1500 gram of dry soil. All the moisture contents and density data were observed concurrently with 25 electrical soil resistance observations being made on the soil. All testing and formula used were in accordance with that specified in BS1377 (1990). It was apparent that the soil resistivity value was different under loose (L) and compact (C) condition with moisture content (w) and density (ρbulk) correlations being established as follows; ρbulk(C) = 2.5991ρ-0.037, ρbulk (L) = -0.111 ln (ρ) + 1.7605, w(L) = 109.98ρ-0.268, and w(C) = 121.88ρ-0.363 with determination coefficients, R2 that ranged between 0.69 0.89. This research therefore contributes a means of predicting these geotechnical parameters by related persons such as geophysicist, engineers and geologist who use these resistivity techniques in ground exploration.

Correlation Analysis Between Field Electrical Resistivity Value (ERV) and Basic Geotechnical Properties (BGP)

Past applications of electrical resistivity surveying have particularly focused on areas of subsurface ground investigations to locate boulder, bedrock, water table, etc. Traditionally, electrical resistivity surveys were directed by an expert geophysicist for data acquisition, processing and interpretation. The final outcome from the electrical resistivity technique was an anomaly image that helped describe and demarcate zones of challenging ground conditions. The anomalies highlighted uncertain geotechnical conditions that were often irregular and dependent on individual site condition, yielding a site-dependent electrical resistivity value (ERV) for the ground. This study therefore identifies co-relationships between ERV and some basic geotechnical properties (BGP) such as soil moisture content, grain size of geomaterial, density, porosity, void ratio, and Atterberg limit. Different soil samples were collected and tested under both field and laboratory conditions. Basic geotechnical properties of the samples were obtained immediately after the electrical resistivity measurements were made. It was shown that the electrical resistivity value was greatly influenced by the geotechnical properties, and thus the resistivity surveying technique is applicable to support and enhance the conventional stand-alone anomaly outcome that is traditionally used in ground investigation interpretation.

The monitoring and cementation behavior of electrokinetic stabilisation technique on batu pahat marine clay

This paper outlines the monitoring and soil fabric results from an experimental study of electrokinetic stabilisation (EKS) technique. The monitoring results were important in assessing the efficiency of the technique towards Batu Pahat marine clay. Two reactors were set up; 1.0 M of calcium chloride (CaCl2) and sodium silicate (Na2SiO3) as the electrolyte and stainless steel plates as the electrodes. EKS technique was continued for 21 days with a constant voltage gradient (50 V/m). This technique was performed in two phases where the alteration of EKS was the combination of stabilizers used. The combinations of stabilizers in phase 1 and 2 were CaCl2 - distilled water (DW) and CaCl2 - Na2SiO3, respectively. The technique was monitored using electric current, total inflow and outflow of electrolytes and pH of electrolytes. It showed fluctuated profiles of electric current for both phases, attributed by the introduction of calcium ions from the anode compartment. The inflow and outflow of electrolytes results showed that electromigration and electroosmosis occurred during EKS and it indicated the movement of anion and cation to the opposite direction. The pH of electrolytes kept constant value and balanced by electrolysis process at the cathode. Image of soil fabric for untreated and treated clay were presented where most images shows a flaky particles. The observation of those images indirectly explained the effect of cementation behavior of treated clay.

Soil moisture content and density prediction using laboratory resistivity experiment

Natural soils are an intimate mixture of solid, liquid and gas phases. This study establishes a correlation for moisture content and density of a soil with its electrical resistivity. In the past, most of the conventional geotechnical site investigation required bulky and heavy equipment to determine the geotechnical parameters necessary for design and construction purposes. Consequentially, time and cost of the project is increased especially when dealing with some difficult site such as on mountainous terrain. This study is based on laboratory soil box resistivity meter observations made on soils mixed with additions of consistent increments of 1-5 % of water to 1500 gram of remolded soils in loose condition. At least 24 repetitive resistivity test observations were made and the moisture content and soil density was determined concurrently for each of the tests. The observations showed that the electrical resistivity variation decreased in a curvilinear manner with increasing percentage of moisture content. A regression equation and coefficient of determination, R2 for moisture content against soil electrical resistivity value was established by moisture content, w = 152.87ρ-0.312 (ρ = soil electrical resistivity) and R2 = 0.7718 respectively. While a regression equation and R2 value for bulk density versus soil electrical resistivity value was observed to be ρbulk = -0.107 ln (ρ) + 1.7249 and 0.7016 respectively. Hence, a viable method is demonstrated where the electrical resistivity value was applicable and has a great potential for geotechnical data prediction of parameters such as moisture content and soil density.

The Influence of Basic Physical Properties of Soil on its Electrical Resistivity Value under Loose and Dense Condition

Electrical resistivity technique has become a famous alternative tool in subsurface characterization. In the past, several interpretations of electrical resistivity results were unable to be delivered in a strong justification due to lack of appreciation of soil mechanics. Traditionally, interpreters will come out with different conclusion which commonly from qualitative point of view thus creating some uncertainty regarding the result reliability. Most engineers desire to apply any techniques in their project which are able to provide some clear justification with strong, reliable and meaningful results. In order to reduce the problem, this study presents the influence of basic physical properties of soil due to the electrical resistivity value under loose and dense condition. Two different conditions of soil embankment model were tested under electrical resistivity test and basic geotechnical test. It was found that the electrical resistivity value (ERV, ρ) was highly influenced by the variations of soil basic physical properties (BPP) with particular reference to moisture content (w), densities (ρbulk/dry), void ratio (e), porosity (η) and particle grain fraction (d) of soil. Strong relationship between ERV and BPP can be clearly presents such as ρ ∞ 1/w, ρ ∞ 1/ρbulk/dry, ρ ∞ e and ρ ∞ η. This study therefore contributes a means of ERV data interpretation using BPP in order to reduce ambiguity of ERV result and interpretation discussed among related persons such as geophysicist, engineers and geologist who applied these electrical resistivity techniques in subsurface profile assessment.

The Influence of Electrical Resistivity Array on its Soil Electrical Resistivity Value

Electrical resistivity technique has become a popular alternative tool by the geotechnical engineers in subsurface investigation. This study presents the influence of soil electrical resistivity value (ERV) due to the different types of electrical resistivity array used in practice. The dissimilarity of ERV was become a popular debate by the engineers which posses less fundamental knowledge in this area. In the past, the theory of electrical resistivity technique was less being discovered by the engineer which creates lots of black boxes during the utilization of electrical resistivity method (ERM) in engineering purposes. Hence, the result which produced from the ERM was difficult to deliver in a sound of definitive ways due to lack of knowledge and experienced of most engineers. Hence, this study presents the influence of soil ERV due to the different types of array used with particular reference to as Dipole-dipole and Pole-dipole. A line of electrical resistivity imaging was performed on small embankment of sandy and lateritic soil with different types of array using ABEM SAS (4000) equipment. Three in line of soil samples were tested for moisture content (w) test immediately after the electrical resistivity data acquisition was completely measured. Moreover, particle size distribution test also was performed for all soil samples in order to support the findings. It was found that the ERV was never be the same for each types of array used even on the same particular location of the survey line. However, it was found that there was a consistent relationship between ERV and moisture content for both types of soil tested which can be represent by ERV 1/w. Hence, it was found that ERV produced was relative to the types of array used during the field measurement. Each types of array were applicable to be used in subsurface profiling and its selection was subjected to the target of interest.

Groundwater Seepage Mapping using Electrical Resistivity Imaging

In recent years, electrical resistivity method (ERM) has widely being applied as an alternative tool in engineering, environmental and archeological studies. A global image of groundwater seepage problem was difficult to obtained using conventional geotechnical method due to the efficiency of cost, time and result coverage. This study was conducted using electrical resistivity survey in order to investigate the potential of the problematic zone due to the groundwater seepage problem. ABEM SAS 4000 equipment set was used in during the resistivity data acquisition stage. Six (6) resistivity spread lines (SP) were performed across the slopes area using 2-D electrical resistivity imaging. The raw data was processed using RES2DINV and SURFER software for 2-D and 3-D subsurface image. Interpretation of electrical resistivity results was verified using the existing borehole and geochemistry results. Geochemistry results analyses were used Atomic Absorption Spectrometer (AAS) for determining cation and Ion Chromatography (IC) is for anions. Anion elements were studied consists of chloride, bicarbonate, nitrate and sulfate while cation elements consists of sodium, potassium, calcium and magnesium. All the elements were analyzed by using Piper Diagram to determine geochemistry facies in the groundwater. It was found that low resistivity value (ERV) which associated to groundwater (10 ~ 100 Ωm) can be found starts from the ground surface (0 m) to a greater (> 10 m) depth of the subsurface profile. The finding of the study water seepage can be categorized as Ca-HCO that indicator a typical of shallow fresh groundwater. The finding of the study is important to determine source process of water seepage on that area. This study has successfully demonstrates that the application of ERM with supporting borehole and geochemistry data was able to provide a comprehensive results due to the groundwater leakage detection.

The Soil-Water Characteristic Curve of Unsaturated Tropical Residual Soil

This study was conducted to determine the SWCC of unsaturated tropical residual soil in Kuala Lumpur, Malaysia. Undisturbed soil samples at five locations of high-risk slopes area were taken at a depth of 0.5 m using block sampler. In the determination of the SWCC, the pressure plate extractor with the capacity of 1500 kN/m2 has been used. The index properties of the soil such as natural moisture content, Atterberg limits, specific gravity, and soil classification are performed according to BS 1377: Part 2: 1990. The results of index properties show that the natural moisture content of the soil is between 36% to 46%, the plasticity index is between 10% - 26%, the specific gravity is between 2.51 - 2.61 and the soils is classified as silty organic clay of low plasticity. The SWCC data from the pressure plate extractor have been fitted with the Fredlund and Xing equation. The results show that the air entry value and residual matric suction for residual soils are in the range of 17 kN/m2 to 24 kN/m2 and 145 kN/m2 to 225 kN/m2 respectively. From the fitting curve, it is found that the average value of the Fredlund and Xing parameters such as a, n and m are in the range of 0.24-0.299, 1.7-4.8 and 0.142-0.440 respectively.

Optimizing Blasting’s Air Overpressure Prediction Model using Swarm Intelligence

Air overpressure (AOp) resulting from blasting can cause damage and nuisance to nearby civilians. Thus, it is important to be able to predict AOp accurately. In this study, 8 different Artificial Neural Network (ANN) were developed for the purpose of prediction of AOp. The ANN models were trained using different variants of Particle Swarm Optimization (PSO) algorithm. AOp predictions were also made using an empirical equation, as suggested by United States Bureau of Mines (USBM), to serve as a benchmark. In order to develop the models, 76 blasting operations in Hulu Langat were investigated. All the ANN models were found to outperform the USBM equation in three performance metrics; root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). Using a performance ranking method, MSO-Rand-Mut was determined to be the best prediction model for AOp with a performance metric of RMSE=2.18, MAPE=1.73% and R2=0.97. The result shows that ANN models trained using PSO are capable of predicting AOp with great accuracy.

Barren Acidic Soil Assessment using Seismic Refraction Survey

Seismic refraction method is one of the geophysics subsurface exploration techniques used to determine subsurface profile characteristics. From past experience, seismic refraction method is commonly used to detect soil layers, overburden, bedrock, etc. However, the application of this method on barren geomaterials remains limited due to several reasons. Hence, this study was performed to evaluate the subsurface profile characteristics of barren acidic soil located in Ayer Hitam, Batu Pahat, Johor using seismic refraction survey. The seismic refraction survey was conducted using ABEM Terraloc MK 8 (seismograph), a sledge hammer weighing 7 kg (source) and 24 units of 10 Hz geophones (receiver). Seismic data processing was performed using OPTIM software which consists of SeisOpt@picker (picking the first arrival and seismic configureuration data input) and SeisOpt@2D (generating 2D image of barren acidic soil based on seismic velocity (primary velocity, Vp) distribution). It was found that the barren acidic soil profile consists of three layers representing residual soil (Vp= 200-400 m/s) at 0-2 m, highly to completely weathered soil (Vp= 500-1800 m/s) at 3-8 m and shale (Vp= 2100-6200 m/s) at 9-20 m depth. Furthermore, result verification was successfully done through the correlation of seismic refraction data based on physical mapping and the geological map of the study area. Finally, it was found that the seismic refraction survey was applicable for subsurface profiling of barren acidic soil as it was very efficient in terms of time, cost, large data coverage and sustainable.