scholarly journals Effective Elastic Properties of 3D Carbon-Carbon Composites at High Temperature

1996 ◽  
Vol 5 (2) ◽  
pp. 096369359600500
Author(s):  
X.D. He ◽  
J.C. Han ◽  
S.Y. Du
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Elastic Modulus ◽  
High Temperature ◽  
Finite Element Model ◽  
Tensile Properties ◽  
Elastic Properties ◽  
Element Model ◽  
Carbon Composites ◽  
Fiber Spacing

This paper describes a mini-finite element model for evaluation of high temperature elastic modulus of 3D C/C composite and the variation of tensile properties with substrate parameters such as xy-woven layers, fiber boundles and fiber spacing was analyzed. The results predicted suit the experimental data well.

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.

scholarly journals Effect of spatial distribution of fibers on elastic properties of unidirectional carbon/carbon composites

2021 ◽  
Vol 309 ◽  
pp. 01214
Author(s):  
M.V.N Mohan ◽  
Ramesh Bhagat Atul ◽  
Vijay Kumar Dwivedi
Keyword(s):  
Finite Element ◽  
Spatial Distribution ◽  
Elastic Properties ◽  
Element Model ◽  
Experimental Methods ◽  
Design Stage ◽  
Carbon Composites ◽  
Numerical Predictions ◽  
Numerical Finite Element ◽  
Very High

Carbon/Carbon composites finds its applications in several high temperature applications in the field of Space, Aviation etc. Designing of components or sub systems with carbon/carbon composites is a challenging task. It requires prediction of elastic properties with a very high accuracy. The prediction can be normally done by analytical, numerical or experimental methods. At the design stage the designers resort to numerical predictions as the experimental methods are not feasible during design stage. Analytical methods are complex and difficult to implement. The designers use numerical methods for prediction of elastic properties using Finite Element Modeling (FEM). The spatial distribution of fibers in matrix has an effect on results of prediction of elastic constants. The generation of random spatial distribution of fibers in representative volume element (RVE) challenging. The present work is aimed at study of effect of spatial distribution of fiber in numerical prediction of elastic properties of unidirectional carbon/carbon composites. MATLAB algorithm is used to generate the spatial distribution of fibers in unidirectional carbon/carbon composites. The RVE elements with various random fiber distributions are modeled using numerical Finite element Model using ABAQUS with EasyPBC plugin. The predicted elastic properties have shown significant variation to uniformly distributed fibers.

Proposal of a new low-cycle fatigue life model for cast iron with room temperature calibration involving mean stress and high-temperature effects

2019 ◽  
Vol 233 (14) ◽  
pp. 5056-5073 ◽  
Author(s):  
Cristiana Delprete ◽  
Raffaella Sesana
Keyword(s):  
Finite Element ◽  
Cast Iron ◽  
High Temperature ◽  
Finite Element Model ◽  
Life Prediction ◽  
Low Cycle Fatigue ◽  
Element Model ◽  
Mean Stress ◽  
Exhaust Manifold ◽  
Cycle Fatigue

The paper presents and discusses a low-cycle fatigue life prediction energy-based model. The model was applied to a commercial cast iron automotive exhaust manifold. The total expended energy until fracture proposed by the Skelton model was modified by means of two coefficients which take into account of the effects of mean stress and/or mean strain, and the presence of high temperature. The model was calibrated by means of experimental tests developed on Fe–2.4C–4.6Si–0.7Mo–1.2Cr high-temperature-resistant ductile cast iron. The thermostructural transient analysis was developed on a finite element model built to overtake confidentiality industrial restrictions. In addition to the commercial exhaust manifold, the finite element model considers the bolts, the gasket, and a cylinder head simulacrum to consider the corresponding thermal and mechanical boundary conditions. The life assessment performance of the energy-based model with respect the cast iron specimens was compared with the corresponding Basquin–Manson–Coffin and Skelton models. The model prediction fits the experimental data with a good agreement, which is comparable with both the literature models and it shows a better fitting at high temperature. The life estimations computed with respect the exhaust manifold finite element model were compared with different multiaxial literature life models and literature data to evaluate the life prediction capability of the proposed energy-based model.

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