Dr. Manoj Khandelwal
Associate Professor, Mining Engineering
Dr Manoj Khandelwal has an established research profile in mining engineering and is recognised as a leading expert in the areas of mining geomechanics and rock blasting. Dr Khandelwal’s research interests also include environmental geotechnology, slope stability and ground control.
Manoj has a number of prestigious awards and completed research and consultancy projects in his area of expertise. He is also an organising/technical committee member for a number of international conferences. Manoj is an Australian Endeavour Fellow and member of the Australasian Institute of Mining and Metallurgy, Society for Mining, Metallurgy and Exploration, USA, and Mining Engineers Association of India. He has published more than 100 research papers and is on the editorial board of more than 25 refereed international journals.
Manoj joined Federation University Australia in 2015 and is currently Senior Lecturer in mining engineering. He obtained his PhD from the Indian Institute of Technology, India in 2007.
A comparative analysis of hybrid RF models for efficient lithology prediction in hard rock tunneling using TBM working parameters
Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review
Dynamic compression mechanical properties of sandstone supported by Thin Spray-On Liner
Enhanced multi-task learning models for pile drivability prediction: Leveraging metaheuristic algorithms and statistical evaluation
Experimental and numerical investigation on crack propagation for a zigzag central cracked Brazilian disk
Experimental test and PFC3D simulation of the effect of a hole on the tensile behavior of concrete: A comparative analysis of four different hole shapes
Genetic justification of COVID-19 patient outcomes using DERGA, a novel data ensemble refinement greedy algorithm
Impact of Velocity of Detonation and Charge per Bank Cubic Meters on Flyrock Throw Prediction Using Support Vector Machine
Occurrence mechanism and prevention technology of rockburst, coal bump and mine earthquake in deep mining
Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India
Predictive modelling for coal abrasive index: Unveiling influential factors through Shallow and Deep Neural Networks
Slope stability analysis considering fully saturated poro-elasto-plasticity by an image-based scaled boundary finite element approach
Adaptive phase-field modelling of fracture propagation in poroelastic media using the scaled boundary finite element method
Application of KRR, K-NN and GPR Algorithms for Predicting the Soaked CBR of Fine-Grained Plastic Soils
Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation
A true triaxial strength criterion for rocks by gene expression programming
Comparative Evaluation of Empirical Approaches and Artificial Intelligence Techniques for Predicting Uniaxial Compressive Strength of Rock
Comparison and application of top and bottom air decks to improve blasting operations
Estimating the mean cutting force of conical picks using random forest with salp swarm algorithm
Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method
Image based probabilistic slope stability analysis of soil layer interface fluctuations with Brownian bridges
Knowledge mapping of research progress in blast-induced ground vibration from 1990 to 2022 using CiteSpace-based scientometric analysis
Order of Intermittent Rock Fractured Surfaces
Performance Evaluation of Rockburst Prediction Based on PSO-SVM, HHO-SVM, and MFO-SVM Hybrid Models
Prediction of blast-induced air overpressure using a hybrid machine learning model and gene expression programming (GEP): A case study from an iron ore mine
Quantifying the cohesive strength of rock materials by roughness analysis using a domain based multifractal framework
Sensitivity analysis on blast design parameters to improve bench blasting outcomes using the Taguchi method
Stability prediction of underground entry-type excavations based on particle swarm optimization and gradient boosting decision tree
The Lithium-Ion Battery Recycling Process from a Circular Economy Perspective—A Review and Future Directions
A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting
A study on environmental issues of blasting using advanced support vector machine algorithms
Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations
Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine...
Computing Elastic Moduli of Igneous Rocks Using Modal Composition and Effective Medium Theory
COSMA-RF: New intelligent model based on chaos optimized slime mould algorithm and random forest for estimating the peak cutting force of conical picks
Cross-correlation stacking-based microseismic source location using three metaheuristic optimization algorithms
Development of the scaled boundary finite element method for image-based slope stability analysis
Effect of multiple loading rates on uniaxial compressive strength of rock
Experimental investigation and theoretical analysis of indentations on cuboid hard rock using a conical pick under uniaxial lateral stress
Feasibility Study and Design of an Underground Entry/Access Structure at an Underground Gold Mine
Intermittency of Rock Fractured Surfaces: A Power Law
Investigating the Slurry Fluidity and Strength Characteristics of Cemented Backfill and Strength Prediction Models by Developing Hybrid GA-SVR and PSO-SVR
Mineral Composition and Grain Size Effects on the Fracture and Acoustic Emission (AE) Characteristics of Rocks Under Compressive and Tensile Stress
Mineral Texture Identification Using Local Binary Patterns Equipped with a Classification and Recognition Updating System (CARUS)
Mine-to-crusher policy: Planning of mine blasting patterns for environmentally friendly and optimum fragmentation using Monte Carlo simulation-based multi-objective grey wolf optimization approach
Novel approach to evaluate rock mass fragmentation in block caving using unascertained measurement model and information entropy with flexible credible identification criterion
Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration
Accurate prediction of ground vibration caused by blasting has always been a significant issue in...
Prediction of Blast-Induced Ground Vibration at a Limestone Quarry: An Artificial Intelligence Approach
Preface
Simultaneous slope design optimisation and stability assessment using a genetic algorithm and a fully automatic image-based analysis
Six Novel Hybrid Extreme Learning Machine–Swarm Intelligence Optimization (ELM–SIO) Models for Predicting Backbreak in Open-Pit Blasting
Spatially Variable Coal Slope Stability Analysis using Image-Based Scaled Boundary Finite Element Method
SPATIALLY VARIABLE COAL SLOPE STABILITY ANALYSIS USING IMAGE-BASED SCALED BOUNDARY FINITE ELEMENT METHOD
Stability evaluation of dump slope using artificial neural network and multiple regression
The present paper focuses on designing an artificial neural network (ANN) model and a multiple...
Stability prediction of a natural and man-made slope using various machine learning algorithms
Stability Prediction of Residual Soil and Rock Slope Using Artificial Neural Network
Utilization Methods and Practice of Abandoned Mines and Related Rock Mechanics under the Ecological and Double Carbon Strategy in China—A Comprehensive Review
A case study of grinding coarse 5 mm particles into sand grade particles less than 2.36 mm
This paper presents the viability study of utilising a rod or ball mill to grind a ‘5 mm grit’ to...
A Combination of Expert-Based System and Advanced Decision-Tree Algorithms to Predict Air-Overpressure Resulting from Quarry Blasting
This study combined a fuzzy Delphi method (FDM) and two advanced decision-tree algorithms to...
An evolutionary adaptive neuro-fuzzy inference system for estimating field penetration index of tunnel boring machine in rock mass
Field penetration index (FPI) is one of the representative key parameters to examine the tunnel...
Application of Slope Mass Rating and Kinematic Analysis Along Road Cut Slopes in the Himalayan Terrain
Developing a hybrid model of Jaya algorithm-based extreme gradient boosting machine to estimate blast-induced ground vibrations
Blasting is still being considered to be one the most important applicable alternatives for...
Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization
The advance rate (AR) of a tunnel boring machine (TBM) under hard rock conditions is a key...
Evaluation and Assessment of Blast-Induced Ground Vibrations in an Underground Gold Mine: A Case Study
Intelligent modeling of blast-induced rock movement prediction using dimensional analysis and optimized artificial neural network technique
For maximum metal recovery, considering the movement of ore and waste during the blasting process...
Intelligent Techniques for Prediction of Drilling Rate for Percussive Drills in Topically Weathered Limestone
Low amplitude fatigue performance of sandstone, marble, and granite under high static stress
Abstract: Fatigue tests under high static pre-stress loads can provide meaningful results to...
Performance of Hybrid SCA-RF and HHO-RF Models for Predicting Backbreak in Open-Pit Mine Blasting Operations
Prediction and Assessment of Rock Burst Using Various Meta-heuristic Approaches
One of the utmost severe mining catastrophes in underground hard rock mines is rock burst...
Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms
The main purpose of blasting operation is to produce desired and optimum mean size rock...
Prediction of Rockburst Using Supervised Machine Learning
Proposing a novel comprehensive evaluation model for the coal burst liability in underground coal mines considering uncertainty factors
Coal burst is a severe hazard that can result in fatalities and damage of facilities in...
Rock-Burst Occurrence Prediction Based on Optimized Naïve Bayes Models
Rock-burst is a common failure in hard rock related projects in civil and mining construction and...
Stress–strain relationship of sandstone under confining pressure with repetitive impact
Abstract: A series of triaxial repetitive impact tests were conducted on a 50-mm-diameter split...
Assessing cohesion of the rocks proposing a new intelligent technique namely group method of data handling
In this study, evaluation and prediction of rock cohesion is assessed using multiple regression...
Early age properties of alkali-activated cement and class G cement under different saturation conditions in oil well applications
This experimental study evaluates the early-age properties of one-part alkali-activated cement...
Effects of a proper feature selection on prediction and optimization of drilling rate using intelligent techniques
One of the important factors during drilling times is the rate of penetration (ROP), which is...
Experimental investigations on mechanical performance of rocks under fatigue loads and biaxial confinements
In this research, a series of biaxial compression and biaxial fatigue tests were conducted to...
Optimization of blasting design in open pit limestone mines with the aim of reducing ground vibration using robust techniques
Blasting operations create significant problems to residential and other structures located in...
Stability prediction of Himalayan residual soil slope using artificial neural network
In the past decade, advances in machine learning (ML) techniques have resulted in developing...
Waveform features and failure patterns of hollow cylindrical sandstone specimens under repetitive impact and triaxial confinements
In underground engineering practice, the surrounding rocks are subjected to a nonuniform stress...
An experimental study on tensile characteristics of granite rocks exposed to different high-temperature treatments
Investigation of temperature dependent tensile strength characteristics of rocks provides...
Implementing an ANN model optimized by genetic algorithm for estimating cohesion of limestone samples
Shear strength parameters such as cohesion are the most significant rock parameters which can be...
Prediction of index properties of different rocks using non-destructive testing
Index properties of rocks are vital in the planning and design of geo-mining structures. It is a...
An expert system based on hybrid ICA-ANN technique to estimate macerals contents of Indian coals
Coal, as an initial source of energy, requires a detailed investigation in terms of ultimate...
Classification and regression tree technique in estimating peak particle velocity caused by blasting
Blasting is a widely used technique for rock fragmentation in surface mines and tunneling...
Development of a precise model for prediction of blast-induced flyrock using regression tree technique
Drilling and blasting is the predominant rock fragmentation method in open-cast mines and civil...
Function development for appraising brittleness of intact rocks using genetic programming and non-linear multiple regression models
Brittleness of rock is one of the most critical features for design of underground excavation...
Study of crack propagation in concrete under multiple loading rates by acoustic emission
It is of great importance to investigate the effect of multiple loading rates on the crack...
A new model based on gene expression programming to estimate air flow in a single rock joint
This paper is aimed to introduce and validate a gene expression programming (GEP) model to...
Prediction of Drillability of Rocks with Strength Properties Using a Hybrid GA-ANN Technique
The purpose of this paper is to provide a proper, practical and convenient drilling rate index...
Risk Assessment and Prediction of Flyrock Distance by Combined Multiple Regression Analysis and Monte Carlo Simulation of Quarry Blasting
Flyrock is considered as one of the main causes of human injury, fatalities, and structural...
A Dimensional Analysis Approach to Study Blast-Induced Ground Vibration
The prediction of ground vibration is of great importance in the alleviation of the detrimental...
A Method to Improve Transparency of Electronic Election Process without Identification
Differential evolution algorithm for predicting blast induced ground vibrations
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Evaluation of dump slope stability of a coal mine using artificial neural network
Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting
One of the most significant environmental issues of blasting operations is ground vibration,...
Geophysical Characterization of Salinity Ingress in Surka Mining Lease Area of Gujarat, India
Salinity ingress is refers to the process of salt water invading areas which previously contained...
Software feasibility study to transform complex scientific written knowledge to a clear, rationale and simple language
The effect of simplification based on words and their role in approving or rejecting articles
An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran
Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects...
Application of soft computing in predicting rock fragmentation to reduce environmental blasting side effects
In the blasting operation, risk of facing with undesirable environmental phenomena such as ground...
Artificial Neural Network as a Tool for Backbreak Prediction
Backbreak is one of the destructive side effects of the blasting operation. Reducing of this...
Assessment of Maximum Explosive Charge Used Per Delay in Surface Mines
Evaluation of safe explosive charge in surface mines using artificial neural network
The present paper mainly deals with the prediction of maximum explosive charge used per delay...
Application of an Expert System to Predict Maximum Explosive Charge Used Per Delay in Surface Mining
The present paper mainly deals with the prediction of maximum explosive charge used per delay (Q...
Backbreak prediction in the Chadormalu iron mine using artificial neural network
Backbreak is one of the unfavorable blasting results, which can be defined as the unwanted rock...
Behaviour of Brittle Material in Multiple Loading Rates Under Uniaxial Compression
It is of great importance to investigate the effect of loading rate on the behaviour of brittle...
comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak
Correlating P-wave Velocity with the Physico-Mechanical Properties of Different Rocks
In mining and civil engineering projects, physico-mechanical properties of the rock affect both...
Effect of strain rate on strength properties of low-calcium fly-ash-based geopolymer mortar under dry condition
This paper presents the mechanical and elastic properties of inorganic polymer mortar under...
Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network
The purpose of this article is to evaluate and predict blast-induced ground vibration at Shur...
Evaluation of effect of blast design parameters on flyrock using artificial neural networks
Flyrock, the propelled rock fragments beyond a specific limit, can be considered as one of the...
Prediction of backbreak in open-pit blasting operations using the machine learning method
Backbreak is an undesirable phenomenon in blasting operations. It can cause instability of mine...
Prediction of flyrock in open pit blasting operation using machine learning method
Flyrock is one of the most hazardous events in blasting operation of surface mines. There are...
Prediction of sea water intrusion for mining activity in close precincts of sea shore
The mining lease area of Surka [District Bhavnagar, Gujarat (India)] is located within 6-12 km...
An intelligent approach to evaluate drilling performance
In this paper, an attempt has been made to predict the rate of penetration (ROP) of rocks by...
Application of an Expert System for the Assessment of Blast Vibration
The purpose of this article is to evaluate and predict the blast induced ground vibration using...
Application of an expert system to predict thermal conductivity of rocks
In this paper, an attempt has been made to predict the thermal conductivity (TC) of rocks by...
Application of geogrids in waste dump stability: a numerical modeling approach
Geosynthetic is widely used to reinforce the weak rock mass, mine waste dump, soil slopes road...
Application of neural networks for the prediction of rock fragmentation in Chadormalu iron mine
Most open-pit mining operations employ blasting for primary breakage of the in-situ rock mass....
Artificial neural network for prediction of air flow in a single rock joint
In this paper, an attempt has been made to evaluate and predict the air flow rate in triaxial...
Prediction of Safe Charge to Protect Surrounding Structures Using Support Vector Machine
The present paper mainly with deals the prediction of safe explosive charge used per delay (Q...
Soft Computing Approach to Evaluate and Predict Blast Vibrations
Drilling and blasting is one of the most economical methods used for the exploitation of economic...
Validation of RMR-based support design using roof bolts by numerical modeling for underground coal mine of Monnet Ispat, Raigarh, India-a case study
In underground coal mines, a lot of major fatalities have occurred due to roof fall in the newly...
A correlation between Schmidt hammer rebound numbers with impact strength index, slake durability index and P-wave velocity
The main objective of this study was to establish statistical relationship between Schmidt hammer...
Application of soft computing to predict blast-induced ground vibration
In this study, an attempt has been made to evaluate and predict the blast-induced ground...
Blast-induced ground vibration prediction using support vector machine
Ground vibrations induced by blasting are one of the fundamental problems in the mining industry...
Laboratory Investigations for the Role of Flushing Media in Diamond Drilling of Marble
Marble is used as a natural stone for decorative purposes from ages. Marble is a crystalline...
Predicting elastic properties of schistose rocks from unconfined strength using intelligent approach
Elastic properties of rocks play a major and crucial role for the design of any engineering...
Prediction of blast-induced air overpressure using support vector machine
Prediction of blast-induced air overpressure (AOP) is very complicated and intricate due to the...
Prediction of thermal conductivity of rocks by soft computing
The transfer of energy between two adjacent parts of rock mainly depends on its thermal...
Superiority of neural networks for pillar stress prediction in bord and pillar method
Estimation of pillar stress is a crucial task in underground mining. This is used to determine...
A review on existing opencast coal mining methods within Australia
Currently almost 65 % of the coal in Australia is being produced by opencast mining methods....
Artificial neural networks as a valuable tool for well log interpretation
rtificial neural networks (ANNs) are rapidly gaining popularity in the area of oil exploration....
Correlating index properties of rocks with P-wave measurements
The determination of index properties of rock, such as Cerchar Abrasivity Index, Shore Hardness,...
Enhancing diamond drilling performance by the addition of non-ionic polymer to the flushing media
Drilling is a most important and crucial operation in the excavation industries. With the...
Evaluation and prediction of blast induced ground vibration using support vector machine
We present the application of Support Vector Machine (SVM) for the prediction of blast induced...
Evaluation and prediction of blast-induced ground vibration using support vector machine
[No abstract available]
Geological and geotechnical aspects of underground coal mining methods within Australia
About one quarter of the coal produced in Australia is by underground mining methods. The most...
Prediction of macerals contents of Indian coals from proximate and ultimate analyses using artificial neural networks
Coal, a prime source of energy needs in-depth study of its various parameters, such as proximate...