A5063272192- Probabilistic and Robust Engineering Design
- Advanced Multi-Objective Optimization Algorithms
- Structural Health Monitoring Techniques
- Optimal Experimental Design Methods
- Topology Optimization in Engineering
- Non-Destructive Testing Techniques
- Machine Fault Diagnosis Techniques
- Fatigue and fracture mechanics
- Fault Detection and Control Systems
- Composite Structure Analysis and Optimization
- Infrastructure Maintenance and Monitoring
- Manufacturing Process and Optimization
- Model Reduction and Neural Networks
- Reliability and Maintenance Optimization
- Systems Engineering Methodologies and Applications
- BIM and Construction Integration
- Advanced Battery Technologies Research
- Engineering Diagnostics and Reliability
- Advanced Numerical Analysis Techniques
- Risk and Safety Analysis
- Nuclear Engineering Thermal-Hydraulics
- Technology Assessment and Management
- Spacecraft and Cryogenic Technologies
- Scientific Measurement and Uncertainty Evaluation
- Gear and Bearing Dynamics Analysis
Institut Clément Ader
2015-2024
Institut Superieur de l'Aeronautique et de l'Espace (ISAE-SUPAERO)
2018-2024
Université Toulouse III - Paul Sabatier
2013-2023
Université de Toulouse
2013-2023
Centre National de la Recherche Scientifique
2017-2023
Universitatea Națională de Știință și Tehnologie Politehnica București
2023
Instituto de Aeronáutica e Espaço
2018
National Council for Scientific Research
2018
IMT Mines Albi
2012-2017
University of Florida
2006-2014
Covers advancements in spacecraft and tactical strategic missile systems, including subsystem design application, mission analysis, materials structures, developments space sciences, processing manufacturing, operations, applications of technologies to other fields.
Design analysis and optimization based on high-fidelity computer experiments is commonly expensive. Surrogate modeling often the tool of choice for reducing computational burden. However, even after years intensive research, surrogate still involves a struggle to achieve maximum accuracy within limited resources. This work summarizes advanced yet simple statistical tools that help. We focus four techniques with increasing popularity in design automation community: (i) screening variable...
SUMMARY Topology optimization of large scale structures is computationally expensive, notably because the cost solving equilibrium equations at each iteration. Reduced order models by projection, also known as reduced basis models, have been proposed in past for alleviating this cost. We propose here a new method coupling with topology to improve efficiency structures. The novel approach based on constructing fly, using previously calculated solutions equations. thus adaptively constructed...
Airframe maintenance is traditionally performed at scheduled stops. The decision to repair a fuselage panel based on fixed crack size threshold, which allows ensure the aircraft safety until next stop. With progress in sensor technology and data processing techniques, structural health monitoring (SHM) systems are increasingly being considered aviation industry. SHM track state continuously, leading possibility of planning an actual rather than schedule. This paper builds upon model-based...
Low-fidelity analytical models are often used at the conceptual aircraft design stage. Because of uncertainties on these and their corresponding input variables, deterministic optimization may achieve under-design or over-design. Therefore it is important to already consider stage in order avoid inefficient then costly time over runs due re-design. This paper presents a procedure for reliable robust an phase. Uncertainties model variables taken into account probabilistic setting. More...
The basic formulation of the least-squares method, based on L2 norm residuals, is still widely used today for identifying elastic constants aerospace materials from experimental data. While this method often works well, methods that can benefit statistical information, such as Bayesian may sometimes be more accurate. We seek situations with significant difference between material properties identified by two methods. For a simple three-bar truss example we illustrate three in which approach...
Deep learning methods have promoted the vibration-based machinery fault diagnostics from manual feature extraction to an end-to-end solution in past few years and exhibited great success on various tasks. However, this is based assumptions that sufficient labeled data are available, training testing same distribution, which normally difficult satisfy practice. To overcome issue, we propose a multistage deep convolutional transfer method (MSDCTL) aimed at transferring capabilities new working...
of the maximum bottom face temperature is needed. The finite element model used to evaluate depended on 15 parameters interest for design. A small number assumptions simplified thermal equations, allowing easy nondimensionalization, which together with a global sensitivity analysis showed that mainly depends only two nondimensional parameters. These were selected be variables response surface approximation temperature, was constructed using simulations from original nonsimplified model....