Investigation of ballistic performance on 3D compound structure fabric by finite element analysis

Ballistic performance and moldability are two important properties for 3D curved-surface ballistic applications. However, these two properties are contradictory to each other and impossible to improve at the same time, which is a technical issue that needs to be solved urgently in the research for ballistic materials for 3D curved-surface ballistic applications. In order to solve this issue, a new 3D compound structure fabric has been developed as part of our former research and has been shown to provide better ballistic performance with equivalent moldability compared to 3D angle-interlock fabric—a well-known 3D material for 3D curved-surface ballistic applications. Nevertheless, the ballistic performance of this new fabric itself is not clear, and further research is necessary. In this study, the ballistic performance of this new 3D compound structure fabric was investigated via the finite element analysis (FEA) model to examine energy absorption and penetration resistance. A ballistic test was also carried out to verify the results of the FEA model, and this demonstrated that the theoretical model was consistent with the experimental results.

FEA model based cautious automatic optimal shape control for fuselage assembly

In a half fuselage assembly process, shape control is vital for achieving ultra-high precision assembly. To achieve better shape adjustment, we need to determine the optimal location and force of each actuator to push and pull a fuselage to compensate for its initial shape distortion. The current practice achieves this goal by solving a surrogate model based optimization problem. However, there are two limitations of this surrogate model based method: (1) Low efficiency: Collecting training data for surrogate modeling from many FEA replications is time-consuming. (2) Non-optimality: The required number of FEA replications for building an accurate surrogate model will increase as the potential number of actuator locations increases. Therefore, the surrogate model can only be built on a limited number of prespecified potential actuator locations, which will lead to sub-optimal control results. To address these issues, this paper proposes an FEA model based automatic optimal shape control (AOSC) framework. This method directly loads the system equation from the FEA simulation platform to determine the optimal location and force of each actuator. Moreover, the proposed method further integrates the cautious control concept into the AOSC system to address model uncertainties in practice. The case study with industrial settings shows that the proposed Cautious AOSC method achieves higher control accuracy compared to the current industrial practice.

Research on Lightweight of Docking Structure Based on ANSYS

The docking structure has broad application prospects in the construction of tower assembly. However, the docking structure has a relatively large quality, which has a greater impact on the operations of high-altitude workers. This paper studies the impact force on docking structure during the docking process. The finite element analysis (FEA) model of the docking structure and the tower section is established and the impact force of the docking structure under various wording conditions is calculated. Based on the calculation results of the impact force the lightweight research of the docking structure is carried out and the optimization constraint conditions are proposed. The simulation model is established by ANSYS and the optimization design of guiding tools and vertical limit tools are completed by adjusting the structural parameters. After the optimization design, the docking structure is trial-produced and tested. Through the method of FEA and experiment, a butting device that meets the requirements of strength and rigidity and is lighter in weight is obtained. Compared with the existing docking structure, the weight of the optimized docking structure is reduced by about 39%. The research results can provide a reference for the design of the docking structure.

Vibration Analysis of Deep Groove Ball Bearing using Finite Element Analysis and Dimension Analysis

Condition monitoring of rotor dynamic is recognized as an advanced preventative maintenance technique for fault-free operation. Faulty bearings in rotating machines may cause severe problems and even untimely breakdowns. This work demonstrates the power of the finite element analysis (FEA) model and dimension analysis technique (DAT) to analyze the effect of the depth and slope angle of surface faults on the bearing contact characteristic. Experimentation is performed to investigate the vibration characteristics of ball bearings. The FEA, DAT, and experimentation show that vibration amplitude is a vital function of surface fault size. The current approach of FEA with DAT reflects their reliability and accuracy for the diagnosis of rotor systems. The present method was found effective in predicting vibration amplitude and defect frequency within acceptable error.

Drilling in the Digital Age: Sensors in Bit and Underreamer Improves Future BHA Design Offshore Mexico

Downhole vibration is the primary cause of low Rate of Penetration (ROP), and severe vibration causes Bottom Hole Assembly (BHA) tool failure; it is especially apparent during Hole Enlargement While Drilling (HEWD) due to multiple points of cutter contact with the formation at the bit and the underreamer. Electronic, high data rate sensors, embedded in the 17-1/2 in. bit and the 22 in. underreamer, generated detailed insights on the location, mechanism, and magnitude of downhole vibration. Time-based downhole vibration logs from the sensors were plotted alongside mudlogging data. Finite Element Analysis (FEA) models were run using actual drilling parameters to simulate downhole conditions and provide a baseline model for further optimization. Sensor data was isolated for each of the bit and underreamer to better understand the individual and combined vibration mechanisms during hole enlargement while drilling operations. The FEA model was then used to optimize BHA configuration and underreamer placement that result in the largest drilling parameter window for future BHAs. The data from sensors showed that whirl occurred when the bit entered sandstone bodies and the underreamer was still in shale. The data also showed that when the bit was in shale and the underreamer in sandstone, the underreamer experienced stick slip which induced stick slip at the bit. The BHA dynamics model run with actual drilling parameters showed a narrow drilling window with multiple critical vibration points at the same rotation speed (RPM). A new BHA was developed for the next well with a wider drilling window and less critical vibration points for the same RPM. The analysis identified key operational mitigations when stick slip or whirl are encountered. This work leveraged technology and insights generated from data to shorten the learning curve and improve operations after just one well. In a drilling age where operations are becoming increasingly complex, relying on surface data is no longer enough.

Shape Optimization of Discontinuous Armature Arrangement PMLSM for Reduction of Thrust Ripple

The aim of this paper is to present the optimal design process and an optimized model for a discontinuous armature arrangement permanent magnet linear synchronous motor (PMLSM). The stator tooth shapes are optimized to reduce detent force. When the shape of the stator is changed to reduce the detent force, the saturation magnetic flux density and the back electromotive force characteristics change. Multi-objective optimization is used to search for the local lowest point that can improve the detent force, saturation magnetic flux density, and back EMF characteristics. To reduce the detent force generated at the outlet edge, a trapezoidal auxiliary tooth was installed and the performance was analyzed. The experiment’s response surface methodology is used as an optimization method and all the experimental samples are obtained from finite-element analysis. The validity of this method is verified by comparing the optimized FEA model to the initial FEA model.

LiftShip

This paper describes the benefits of automating Finite Element Analysis (FEA) model generation and analysis in support of large complex structural lifting, handling, turning, and to present the FEA results in a clear and concise configuration for the stakeholders.

Validation of Finite Element Analysis of a selfexpanding polymeric microstent for treatment of Fallopian tube occlusions

Proximal occlusion of the Fallopian tube is one of the most common causes of female infertility. Due to the occlusion, the passage of the fallopian tubes is no longer given. Basically, there are two options for patients affected by this condition: cost-intensive in vitro fertilization (IVF) or surgery. The pregnancy rates of approximately 50% achieved with current treatment options are not satisfying. In this work, we present a Finite Element Analysis (FEA) model of a previously reported optimized microstent design for minimally invasive therapy of proximal tubal occlusion. Based on experimental investigations, the material model was set up and the simulation was validated. Comparison of the mechanical performance as an application related critical load case was in a good agreement. In this work, the proof of concept for the FEA model and the material model were carried out. In the future, the simulation will be used for further load cases such as the investigation of the bending stiffness and radial force and for the design optimization.