What is he best known for?
The fields of study he is best known for:
- Composite material
- Geotechnical engineering
- Mechanical engineering
Trilok Singh mainly focuses on Geotechnical engineering, Artificial neural network, Compressive strength, Rock mass classification and Rock mechanics.
When carried out as part of a general Geotechnical engineering research project, his work on Shear strength is frequently linked to work in Index, therefore connecting diverse disciplines of study.
He has researched Artificial neural network in several fields, including Vibration, Particle velocity and Explosive material.
His work carried out in the field of Compressive strength brings together such families of science as Fatigue limit, Point and Strain rate.
His Rock mass classification study combines topics from a wide range of disciplines, such as Landslide, Slope stability, Slope stability analysis and Factor of safety.
His biological study spans a wide range of topics, including Cohesion, Friction angle, Matrix and Thermomechanical analysis.
His most cited work include:
- Estimation of elastic constant of rocks using an ANFIS approach (250 citations)
- Prediction of blast-induced ground vibration using artificial neural network (232 citations)
- A correlation between P-wave velocity, impact strength index, slake durability index and uniaxial compressive strength (200 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Geotechnical engineering, Rock mass classification, Slope stability, Mining engineering and Artificial neural network.
His Geotechnical engineering research is multidisciplinary, incorporating perspectives in Compressive strength and Stability.
His Compressive strength study integrates concerns from other disciplines, such as Ultimate tensile strength and Rock mechanics.
His study connects Excavation and Rock mass classification.
His studies in Mining engineering integrate themes in fields like Coal mining and Coal.
His Artificial neural network study deals with Particle velocity intersecting with Explosive material.
He most often published in these fields:
- Geotechnical engineering (40.70%)
- Rock mass classification (13.57%)
- Slope stability (10.80%)
What were the highlights of his more recent work (between 2017-2021)?
- Geotechnical engineering (40.70%)
- Slope stability (10.80%)
- Landslide (9.55%)
In recent papers he was focusing on the following fields of study:
Trilok Singh spends much of his time researching Geotechnical engineering, Slope stability, Landslide, Rock mass classification and Composite material.
Trilok Singh studied Geotechnical engineering and Finite element method that intersect with Numerical analysis.
His work deals with themes such as Mining engineering, Residual and Instability, which intersect with Slope stability.
His research integrates issues of Natural, Probabilistic logic, Safety factor and Natural hazard in his study of Landslide.
His Ultimate tensile strength research is multidisciplinary, incorporating elements of Oil shale, Acoustic emission, Compressive strength, Scanning electron microscope and Fracture toughness.
His Compressive strength research is multidisciplinary, relying on both Porosity, Mean squared error, Mean absolute percentage error, Coefficient of determination and Adaptive neuro fuzzy inference system.
Between 2017 and 2021, his most popular works were:
- Stabilizing the Efficiency Beyond 20% with a Mixed Cation Perovskite Solar Cell Fabricated in Ambient Air under Controlled Humidity (186 citations)
- Sulfate‐Assisted Interfacial Engineering for High Yield and Efficiency of Triple Cation Perovskite Solar Cells with Alkali‐Doped TiO2 Electron‐Transporting Layers (87 citations)
- Experimental study to examine the independent roles of lime and cement on the stabilization of a mountain soil: A comparative study (42 citations)
In his most recent research, the most cited papers focused on:
- Composite material
- Mechanical engineering
- Statistics
Trilok Singh mostly deals with Geotechnical engineering, Perovskite, Ultimate tensile strength, Compressive strength and Composite material.
His study in Landslide, Rock mass classification and Hydrogeology falls under the purview of Geotechnical engineering.
His work investigates the relationship between Rock mass classification and topics such as Deformation modulus that intersect with problems in Rock mechanics.
His Perovskite research includes themes of Thin film, Nanotechnology and Energy conversion efficiency.
His Compressive strength study also includes
- Linear regression, Artificial neural network, Adaptive neuro fuzzy inference system, Cohesion and Acoustic emission most often made with reference to Coefficient of determination,
- Stability most often made with reference to Mean absolute percentage error.
His Composite material research incorporates themes from Thermal and Atmospheric temperature range.
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