Updating of an Unmanned Aerial Vehicle Finite Element Model using Experimental Data

2015 ◽  
Author(s):  
Melissa Arras ◽  
Giuliano Coppotelli ◽  
Piergiovanni Marzocca ◽  
Antonio Simone Mezzapesa
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Finite Element Model ◽  
Unmanned Aerial Vehicle ◽  
Element Model ◽  
Aerial Vehicle

Verification of a Finite Element Model of an Unmanned Aerial Vehicle Wing Torque Box via Experimental Modal Testing

2012 ◽  
Author(s):  
Levent Unlusoy ◽  
Melin Sahin ◽  
Yavuz Yaman
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Unmanned Aerial Vehicle ◽  
Natural Frequencies ◽  
Element Model ◽  
Modal Testing ◽  
Mode Shapes ◽  
Resonance Frequencies ◽  
Aerial Vehicle ◽  
Experimental Modal Testing

In this study, the detailed finite element model (FEM) of an unmanned aerial vehicle wing torque box was verified by the experimental modal testing. During the computational studies the free-free boundary conditions were used and the natural frequencies and mode-shapes of the structure were obtained by using the MSC® Software. The results were then compared with the experimentally obtained resonance frequencies and mode-shapes. It was observed that the frequencies were in close agreement having an error within the range of 1.5–3.6%.

scholarly journals Investigation of the Thickness Differential on the Formability of Aluminum Tailor Welded Blanks

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 875
Author(s):  
Jie Wu ◽  
Yuri Hovanski ◽  
Michael Miles
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Numerical Model ◽  
Plastic Strain ◽  
Finite Element Model ◽  
Equivalent Plastic Strain ◽  
Element Model ◽  
Dome Height ◽  
Tailor Welded Blanks ◽  
Simulation Results

A finite element model is proposed to investigate the effect of thickness differential on Limiting Dome Height (LDH) testing of aluminum tailor-welded blanks. The numerical model is validated via comparison of the equivalent plastic strain and displacement distribution between the simulation results and the experimental data. The normalized equivalent plastic strain and normalized LDH values are proposed as a means of quantifying the influence of thickness differential for a variety of different ratios. Increasing thickness differential was found to decrease the normalized equivalent plastic strain and normalized LDH values, this providing an evaluation of blank formability.

Risk-Controlled Wellbore Stability Criterion Based on Machine Learning Assisted Finite Element Model

2021 ◽  
Author(s):  
Hussain AlBahrani ◽  
Nobuo Morita
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Finite Element ◽  
Finite Element Model ◽  
Stability Criterion ◽  
Element Model ◽  
Rock Failure ◽  
Wellbore Stability ◽  
Wellbore Instability ◽  
Conventional Methods

Abstract In many drilling scenarios that include deep wells and highly stressed environments, the mud weight required to completely prevent wellbore instability can be impractically high. In such cases, what is known as risk-controlled wellbore stability criterion is introduced. This criterion allows for a certain level of wellbore instability to take place. This means that the mud weight calculated using this criterion will only constrain wellbore instability to a certain manageable level, hence the name risk-controlled. Conventionally, the allowable level of wellbore instability in this type of models has always been based on the magnitude of the breakout angle. However, wellbore enlargements, as seen in calipers and image logs, can be highly irregular in terms of its distribution around the wellbore. This irregularity means that risk-controlling the wellbore instability through the breakout angle might not be always sufficient. Instead, the total volume of cavings is introduced as the risk control parameter for wellbore instability. Unlike the breakout angle, the total volume of cavings can be coupled with a suitable hydraulics model to determine the threshold of manageable instability. The expected total volume of cavings is determined using a machine learning (ML) assisted 3D elasto-plastic finite element model (FEM). The FEM works to model the interval of interest, which eventually provides a description of the stress distribution around the wellbore. The ML algorithm works to learn the patterns and limits of rock failure in a supervised training manner based on the wellbore enlargement seen in calipers and image logs from nearby offset wells. Combing the FEM output with the ML algorithm leads to an accurate prediction of shear failure zones. The model is able to predict both the radial and circumferential distribution of enlargements at any mud weight and stress regime, which leads to a determination of the expected total volume of cavings. The model implementation is first validated through experimental data. The experimental data is based on true-triaxial tests of bored core samples. Next, a full dataset from offset wells is used to populate and train the model. The trained model is then used to produce estimations of risk-controlled stability mud weights for different drilling scenarios. The model results are compared against those produced by conventional methods. Finally, both the FEM-ML model and the conventional methods results are compared against the drilling experience of the offset wells. This methodology provides a more comprehensive and new solution to risk controlling wellbore instability. It relies on a novel process which learns rock failure from calipers and image logs.

Biodynamics of Human Thorax With Body Armors Subject to Bullet Impact

2001 ◽  
Author(s):  
Y. W. Kwon ◽  
J. A. Lobuono
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Body Armor ◽  
Projectile Impact ◽  
Human Thorax ◽  
Trachea And Bronchi ◽  
Armor System ◽  
The Finite Element Model

Abstract The objective of this study is to develop a finite element model of the human thorax with a protective body armor system so that the model can adequately determine the thorax’s biodynamical response from a projectile impact. The finite element model of the human thorax consists of the thoracic skeleton, heart, lungs, major arteries, major veins, trachea, and bronchi. The finite element model of the human thorax is validated by comparing the model’s results to experimental data obtained from cadavers wearing a protective body armor system undergoing a projectile impact.

Predicting the Force Needed to Create a Compression Seal in an Ultra-Thin Elastoviscoplastic Membrane

2016 ◽  
Author(s):  
Patrick S. McNeff ◽  
Brian K. Paul
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Finite Element Model ◽  
Region Of Interest ◽  
Element Model ◽  
Depth Of Penetration ◽  
Percent Error ◽  
Hermetic Sealing ◽  
Good Repeatability ◽  
Hemodialysis Membrane

In this paper, a finite element model is developed, and experimentally validated, for predicting the force required to produce a compression seal between a polycarbonate sealing boss and a 25 μm thick elastoviscoplastic hemodialysis membrane. This work leverages previous efforts to determine the conditions for hermetic sealing in a microchannel hemodialyser fabricated using hot-embossed polycarbonate microchannel laminae containing sealing boss features. Methods are developed for mechanically characterizing the thin elastoviscoplastic hemodialysis membrane. Experimental data for assessing the depth of penetration into the membrane as a function of force show an R2 value of 0.85 showing good repeatability. The average percent error was found to be −8.0% with a range between −21.9% and 4.4% error in the strain region of interest.

Comparison of a finite element model of a tennis racket to experimental data

2009 ◽  
Vol 12 (2) ◽  
pp. 87-98 ◽  
Author(s):  
Tom Allen ◽  
Steve Haake ◽  
Simon Goodwill
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Finite Element Model ◽  
Element Model ◽  
Tennis Racket
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