What is he best known for?
The fields of study he is best known for:
- Statistics
- Geotechnical engineering
- Finite element method
D. V. Griffiths mostly deals with Finite element method, Geotechnical engineering, Random field, Monte Carlo method and Slope stability.
His Finite element method study is concerned with the larger field of Structural engineering.
The various areas that he examines in his Geotechnical engineering study include Stability, Soil mechanics and Spatial variability.
His Random field study combines topics from a wide range of disciplines, such as Probabilistic logic, Probabilistic analysis of algorithms, Retaining wall and Standard deviation.
His biological study spans a wide range of topics, including Stochastic process, Limit state design, Serviceability, Normal distribution and Shallow foundation.
His research in Slope stability intersects with topics in Factor of safety and Computer simulation.
His most cited work include:
- SLOPE STABILITY ANALYSIS BY FINITE ELEMENTS (1180 citations)
- Probabilistic slope stability analysis by finite elements (543 citations)
- Programming the finite element method (487 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Geotechnical engineering, Finite element method, Structural engineering, Random field and Probabilistic logic.
His study in Geotechnical engineering focuses on Slope stability in particular.
His work investigates the relationship between Finite element method and topics such as Mathematical analysis that intersect with problems in Mixed finite element method.
He has included themes like Modulus, Spatial correlation, Material properties and Standard deviation in his Random field study.
D. V. Griffiths studies Probabilistic logic, namely Probabilistic analysis of algorithms.
His studies in Monte Carlo method integrate themes in fields like Stochastic process, Permeability and Probabilistic method.
He most often published in these fields:
- Geotechnical engineering (63.87%)
- Finite element method (43.87%)
- Structural engineering (19.03%)
What were the highlights of his more recent work (between 2014-2021)?
- Geotechnical engineering (63.87%)
- Finite element method (43.87%)
- Spatial variability (14.84%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Geotechnical engineering, Finite element method, Spatial variability, Probabilistic logic and Random field.
The study incorporates disciplines such as Reliability, Structural engineering and Stability in addition to Geotechnical engineering.
His Finite element method study combines topics in areas such as Erosion, Levee and Piping.
His studies deal with areas such as Coefficient of variation and Applied mathematics as well as Probabilistic logic.
His Random field study incorporates themes from Spatial correlation and Mathematical analysis.
His Slope stability research includes themes of Factor of safety and Monte Carlo method.
Between 2014 and 2021, his most popular works were:
- Reliability-based geotechnical design in 2014 Canadian Highway Bridge Design Code (64 citations)
- Reliability-based geotechnical design in 2014 Canadian Highway Bridge Design Code (64 citations)
- Determining an appropriate finite element size for modelling the strength of undrained random soils (42 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Geotechnical engineering
- Mechanical engineering
D. V. Griffiths focuses on Geotechnical engineering, Random field, Slope stability, Slope stability analysis and Probabilistic logic.
His Geotechnical engineering research incorporates elements of Limit state design, Civil engineering, Spatial variability, Sampling and Reliability.
His Random field research is multidisciplinary, incorporating elements of Finite element method, Interpolation, Data point, Geostatistics and Monte Carlo method.
Finite element method is a subfield of Structural engineering that D. V. Griffiths studies.
His Slope stability study integrates concerns from other disciplines, such as Shear strength and Parametric statistics.
His Probabilistic logic research is multidisciplinary, relying on both Coefficient of variation, Applied mathematics and Shear strength.
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