What is he best known for?
The fields of study he is best known for:
- Statistics
- Mechanical engineering
- Mechanics
His primary areas of study are Uncertainty quantification, Uncertainty analysis, Experimental data, Verification and validation and Sensitivity analysis.
William L. Oberkampf combines subjects such as Numerical integration, Representation, Mathematical optimization and Conceptual model with his study of Uncertainty quantification.
His research in Experimental data intersects with topics in Experimental uncertainty analysis, Computational fluid dynamics, Verification and validation of computer simulation models, Measurement uncertainty and Computation.
His Verification and validation research is multidisciplinary, relying on both Reliability, Credibility and Management science.
His Reliability research includes themes of Range and Theoretical computer science.
His research investigates the connection between Sensitivity analysis and topics such as Propagation of uncertainty that intersect with issues in Random variable, Extrapolation, Applied mathematics and Computational science.
His most cited work include:
- Verification and validation. (818 citations)
- Verification and Validation in Computational Fluid Dynamics (730 citations)
- Verification and Validation in Scientific Computing (645 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Uncertainty quantification, Computational fluid dynamics, Verification and validation, Mechanics and Uncertainty analysis.
His Uncertainty quantification research is multidisciplinary, incorporating perspectives in Representation, Mathematical optimization and Modeling and simulation.
His Computational fluid dynamics study incorporates themes from Experimental data, Mechanical engineering, Nozzle, Fluid mechanics and Fluid dynamics.
His research integrates issues of Algorithm, Measurement uncertainty and Simulation in his study of Experimental data.
His work carried out in the field of Verification and validation brings together such families of science as Theoretical computer science, Software verification, Scientific software, Computational science and Verification and validation of computer simulation models.
His research in Uncertainty analysis is mostly concerned with Sensitivity analysis.
He most often published in these fields:
- Uncertainty quantification (28.33%)
- Computational fluid dynamics (25.00%)
- Verification and validation (23.33%)
What were the highlights of his more recent work (between 2006-2020)?
- Uncertainty quantification (28.33%)
- Verification and validation (23.33%)
- Scientific software (9.17%)
In recent papers he was focusing on the following fields of study:
His main research concerns Uncertainty quantification, Verification and validation, Scientific software, Computational science and Software engineering.
His work deals with themes such as Sensitivity analysis, Uncertainty analysis and Mathematical optimization, which intersect with Uncertainty quantification.
William L. Oberkampf works mostly in the field of Sensitivity analysis, limiting it down to concerns involving Propagation of uncertainty and, occasionally, Extrapolation, Measurement uncertainty, Experimental uncertainty analysis and Monte Carlo method.
The various areas that William L. Oberkampf examines in his Verification and validation study include Credibility, Conceptual model, Systems engineering, Application domain and Verification and validation of computer simulation models.
His Credibility research incorporates elements of Reliability, Management science, Modeling and simulation and Development.
His Verification and validation of computer simulation models research includes elements of Statistical hypothesis testing and Simulation.
Between 2006 and 2020, his most popular works were:
- Verification and Validation in Scientific Computing (645 citations)
- A comprehensive framework for verification, validation, and uncertainty quantification in scientific computing (412 citations)
- Model validation and predictive capability for the thermal challenge problem (203 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mechanical engineering
- Mechanics
William L. Oberkampf mainly investigates Uncertainty quantification, Uncertainty analysis, Computational fluid dynamics, Sensitivity analysis and Metric.
His Uncertainty quantification study combines topics in areas such as Capability Maturity Model, Modeling and simulation, Systems engineering and Industrial engineering.
His Uncertainty analysis study combines topics from a wide range of disciplines, such as Probabilistic logic, Representation, Artificial intelligence, Mathematical optimization and Calculus.
His Computational fluid dynamics research is multidisciplinary, incorporating elements of Direct numerical simulation and Experimental data.
His Sensitivity analysis research integrates issues from Extrapolation, Propagation of uncertainty and Computational science.
His studies in Computational science integrate themes in fields like Verification and validation, Credibility and Management science.
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