• Advances in aircraft and spacecraft science
• /
• v.11 no.1
• /
• pp.33-53
• /
• 2024

This paper presents a comprehensive investigation into the optimization of Flight Management Systems (FMS) with a particular emphasis on data processing efficiency by conducting a comparative study with conventional methods to edge-computing technology. The objective of this research is twofold. Firstly, it evaluates the performance of FMS navigation systems using conventional and edge computing methodologies. Secondly, it aims to extend the boundaries of knowledge in edge-computing technology by conducting a rigorous analysis of terrain data and its implications on flight path optimization along with communication with ground stations. The study employs a combination of simulation-based experimentation and algorithmic computations. Through strategic intervals along the flight path, critical parameters such as distance, altitude profiles, and flight path angles are dynamically assessed. Additionally, edge computing techniques enhance data processing speeds, ensuring adaptability to various scenarios. This paper challenges existing paradigms in flight management and opens avenues for further research in integrating edge computing within aviation technology. The findings presented herein carry significant implications for the aviation industry, ranging from improved operational efficiency to heightened safety measures.

• Earthquakes and Structures
• /
• v.27 no.3
• /
• pp.209-226
• /
• 2024

The susceptibility of Reinforced Concrete (RC) buildings to earthquake-induced damage is a critical concern, primarily attributed to their inadequate seismic performance. The existing earthquake-resistant design code of India prescribes guidelines to minimize seismic damage but does not provide any means for evaluating the actual seismic performance and damage. To ascertain the seismic performance of the structures quantitatively, it is crucial to classify damage into measurable damage states. Damage Index (DI) acts as an important tool for this purpose. Among various procedures for computation of DI, the modified Park and Ang Damage Index appears to be highly accurate. However, the major drawback of this method is that it is lengthy and time-consuming. On the other hand, structural performances can be evaluated using various performance parameters such as interstory drift ratio (IDR), inelastic deformation, etc., as described in FEMA-356 and ASCE-41 17. The present study explores the correlation between seismic DI and structural performance in RC frame buildings designed according to IS code. Sixteen building models, incorporating diverse configurations, are examined using nonlinear static and time history analyses. A simplified equation is developed by regression analysis to predict DI based on IDR, offering a computationally efficient alternative. Validation tests are done to confirm the equation's accuracy. Furthermore, a unified damage scale integrating DI and seismic performance is also proposed for seismic damage evaluation of buildings designed by IS code.

• Ocean Systems Engineering
• /
• v.13 no.4
• /
• pp.367-384
• /
• 2023

Herein, we present the design and development of an efficient finite element analysis model for thermal plate forming in shipbuilding. Double curvature shells in the ship building industries are primarily formed through the thermal forming technique. Thermal forming involves heating of steel plates using heat sources like oxy-acetylene gas torch, laser, and induction heating, etc. The differential expansion and contraction across the plate thickness cause plastic deformation and bending of plates. Thermal forming is a complex forming technique as the plastic deformation and bending depends on many factors such as peak temperature, heating and cooling rate, depth of heated zone and many other secondary factors. In this work, we develop an efficient finite element analysis model for the thermo-mechanical analysis of thermal forming. Different simulations are reported to study the effect of various parameters affecting the process. Temperature dependent properties are used in the analysis and the finite element analysis model is used to identify the critical flame velocity to avoid recrystallization of plate material. A spring connected plate is modeled for structural analysis using spring elements and that helps in identifying the resultant shapes of various thermal forming patterns. Finally, detailed simulation results are reported to establish the efficacy, applicability and efficiency of the designed and developed finite element analysis model.

• Geomechanics and Engineering
• /
• v.39 no.1
• /
• pp.27-41
• /
• 2024

Accurately estimating the performance of tunnel boring machines (TBMs) is crucial for mitigating the substantial financial risks and complexities associated with tunnel construction. Machine learning (ML) techniques have emerged as powerful tools for predicting non-linear time series data. In this research, six advanced meta-heuristic optimization algorithms based on long short-term memory (LSTM) networks were developed to predict TBM penetration rate (TBM-PR). The study utilized 1125 datasets, partitioned into 20% for testing, 70% for training, and 10% for validation, incorporating six key input parameters influencing TBM-PR. The performances of these LSTM-based models were rigorously compared using a suite of statistical evaluation metrics. The results underscored the profound impact of optimization algorithms on prediction accuracy. Among the models tested, the LSTM optimized by the particle swarm optimization (PSO) algorithm emerged as the most robust predictor of TBM-PR. Sensitivity analysis further revealed that the orientation of discontinuities, specifically the alpha angle (α), exerted the greatest influence on the model's predictions. This research is significant in that it addresses critical concerns of TBM manufacturers and operators, offering a reliable predictive tool adaptable to varying geological conditions.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.663-668
• /
• 2024

This paper applies statistical analysis methods in the time domain to the fault diagnosis of wafer transfer robots, and proposes a methodology to discern the critical characteristics of vibration and torque signals. Subsequently, principal component analysis (PCA) is applied to diminish the data's dimensionality, followed by the development of a fault diagnosis algorithm utilizing Euclidean distance and Hotelling's T-square statistics. The algorithm establishes decision boundaries to categorize failure states based on the observed data. Our findings indicate that data classification incorporating velocity parameters enhances diagnostic accuracy. This approach serves to enhance the precision and efficacy of fault diagnosis.

• Safety and Health at Work
• /
• v.15 no.2
• /
• pp.123-128
• /
• 2024

Background: Coal miners are highly prone to occupational health risks, such as black lung disease. This study aims to assess the prevalence of black lung disease and the factors associated with black lung disease among coal miners in Asia. Method: This systematic review, conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, searched through the scientific literature of the following databases: EBSCO, ScienceDirect, PubMed, and Scopus. We selected articles that studied black lung disease among coal miners from 48 countries in Asia and were published between 2014 and 2023. Article quality was evaluated using the Critical Appraisal Skills Program. Result: The seven articles that we review studied a total of 653,635 coal miners from various types of coal mines from three countries in Asia. Of these miners, 59,998 experienced black lung disease. Black lung disease is prevalent among 9.18% of coal miners in Asia, which is approximately four times higher than the worldwide prevalence. Common factors that influence black lung disease in Asia include age, years of dust exposure, smoking, drinking, working types, and sizes of mines, type of mines, respiratory functions, spirometry parameters, tenure, lack of attention to occupational health, inefficient surveillance, and weak occupational health service. Conclusion: Although the prevalence of black lung disease among coal miners in Asia is considerably high, it can be addressed through effective prevention measures, monitoring, control, and case reporting.

• Journal of the Korean Society of Visualization
• /
• v.22 no.2
• /
• pp.44-54
• /
• 2024

This study investigates the effectiveness of using a plasma actuator for active control of turbulent flow around a finite square cylinder. The primary objective is to analyze the impact of plasma actuators on flow separation and wake region characteristics, which are critical for reducing drag and suppressing vortex-induced vibrations. Direct Numerical Simulation (DNS) was employed to explore the flow dynamics at various operational parameters, including different actuation frequencies and voltages. The proposed methodology employs a neural network trained using the Proximal Policy Optimization (PPO) algorithm to determine optimal control policies for plasma actuators. This network is integrated with a computational fluid dynamics (CFD) solver for real-time control. Results indicate that this deep reinforcement learning (DRL)-based strategy outperforms existing methods in controlling flow, demonstrating robustness and adaptability across various flow conditions, which highlights its potential for practical applications.

• Journal of Powder Materials
• /
• v.31 no.4
• /
• pp.302-307
• /
• 2024

This study explored the process-structure-property (PSP) relationships in Ti-6Al-4V alloys fabricated through direct energy deposition (DED) additive manufacturing. A systematic investigation was conducted to clarify how process variables-specifically, manipulating the cooling rate and energy input by adjusting the laser power and scan speed during the DED process-influenced the phase fractions, pore structures, and the resultant mechanical properties of the samples under various processing conditions. Significant links were found between the controlled process parameters and the structural and mechanical characteristics of the produced alloys. The findings of this research provide foundational knowledge that will drive the development of more effective and precise control strategies in additive manufacturing, thereby improving the performance and reliability of produced materials. This, in turn, promises to make significant contributions to both the advancement of additive manufacturing technologies and their applications in critical sectors.

• Steel and Composite Structures
• /
• v.52 no.6
• /
• pp.657-662
• /
• 2024

In the present analysis, the buckling behavior of smart beams integrated into racket frames for enhancing player control was examined by numerical solutions and sinusoidal shear deformation theory. The smart beam under consideration is subjected to an external voltage in the thickness direction. The integration of this smart material into the structure of the racket should optimize performance, improving the racket's stability and responsiveness during play. In this, an accurate representation of complex shear effects is made by using a sinusoidal shear deformation theory, while the solution of the resulting governing equations is made by numerical methods. The critical buckling loads and the characteristics of deformation obtained through the analysis provide insight into some design parameters controlling and influencing stability. Obtained results are validated with other published works. The length and thickness of the beam, elastic medium, boundary condition, and influence of external voltages have been represented for buckling load in the structure. These results will help in designing smart racket frames using smart beams to provide more precision and control for the players in an intelligent way.

• Tuberculosis and Respiratory Diseases
• /
• v.70 no.3
• /
• pp.199-205
• /
• 2011

Social welfare services for respiratory-disabled persons in Korea are offered based on the respiratory impairment grade, which is determined by 3 clinical parameters; dyspnea, forced expiratory volume in 1 second ($FEV_1$), and arterial oxygen tension. This grading system has several limitations in the objective assessment of respiratory impairment. We reviewed several guidelines for the evaluation of respiratory impairment and relevant articles. Then, we discussed a new grading system with respiratory physicians. Both researchers and respiratory physicians agreed that pulmonary function tests are essential in assessing the severity of respiratory impairment, forced vital capacity (FVC), $FEV_1$ and single breath diffusing capacity ($DL_{co}$) are the primarily recommended tests. In addition, we agreed that arterial blood gas analysis should be reserved for selected patients. In conclusion, we propose a new respiratory impairment grading system utilizing a combination FVC, $FEV_1$ and $DL_{co}$ scores, with more social discussion included.