A5089894989- Probabilistic and Robust Engineering Design
- Advanced Multi-Objective Optimization Algorithms
- Fatigue and fracture mechanics
- Structural Health Monitoring Techniques
- Risk and Safety Analysis
- Fault Detection and Control Systems
- Reliability and Maintenance Optimization
- Optimal Experimental Design Methods
- Concrete Corrosion and Durability
- Model Reduction and Neural Networks
- Nuclear Engineering Thermal-Hydraulics
- Manufacturing Process and Optimization
- Ultrasonics and Acoustic Wave Propagation
- Infrastructure Maintenance and Monitoring
- Multi-Criteria Decision Making
- Wind and Air Flow Studies
- Mechanical Behavior of Composites
- Structural Response to Dynamic Loads
- Non-Destructive Testing Techniques
- Slime Mold and Myxomycetes Research
- Bayesian Modeling and Causal Inference
- Software Reliability and Analysis Research
- Additive Manufacturing and 3D Printing Technologies
- Geophysical Methods and Applications
- Complex Network Analysis Techniques
Vanderbilt University
2016-2025
Vanderbilt Health
2023
Rockfield (United Kingdom)
2023
Southwest University
2017
Xi'an Jiaotong University
2016
Idaho National Laboratory
2014-2016
Jacobs (United States)
2016
Sandia National Laboratories California
2010
Oxford University Press (United Kingdom)
2007
New York University Press
2007
Many engineering applications are characterized by implicit response functions that expensive to evaluate and sometimes nonlinear in their behavior, making reliability analysis difficult. This paper develops an efficient method accurately characterizes the limit state throughout random variable space. The begins with a Gaussian process model built from very small number of samples, then adaptively chooses where generate subsequent samples ensure is accurate vicinity state. resulting sampled...
Current airframe health monitoring generally relies on deterministic physics models and ground inspections. This paper uses the concept of a dynamic Bayesian network to build versatile probabilistic model for diagnosis prognosis in order realize digital twin vision, it illustrates proposed method by an aircraft wing fatigue crack growth example. The integrates various aleatory (random) epistemic (lack knowledge) uncertainty sources prediction. In diagnosis, is used track evolution...
Current surrogate modeling methods for time-dependent reliability analysis implement a double-loop procedure, with the computation of extreme value response in outer loop and optimization inner loop. The computational effort procedure is quite high even though improvements have been made to improve efficiency This paper proposes single-loop Kriging (SILK) method analysis. used current completely removed proposed method. A single model built purpose assessment. Training points random...
Non-parametric system identification has been widely applied in structural health monitoring and damage detection based on measured response data. However, the presence of noise data significantly affects accuracy identification. A dilemma is that it not possible to know with any measure certainty whether how much are corrupted by noise. This paper develops a Bayesian discrete wavelet packet transform denoising approach investigates effects The integration hypothesis testing analysis. It...