Athenea Engineering sciences journal

Mathematical model to evaluate the stresses and strains of oil strings in transient state

2025-04-08T08:22:43+00:00

This study presents the development of a mathematical model to assess the performance of oil strings during the drilling process of a reservoir, considering the dynamic conditions and operational characteristics of the equipment during its functions, and taking into account the mechanical properties of API K55 steel. The research resulted in a set of equations that model the behavior of stresses and deformations experienced by the oil tools when transmitting torque, facilitating the opening of the reservoir. A finite element analysis was conducted to evaluate the structural behavior of the strings and to estimate the time required to reach permanent deformations, as well as the time before failure occurs.

A study of the mechanical and electrical properties of the cortical bone based on age, biochemical factors and Nernst equation

2025-04-08T08:22:23+00:00

Development of a smart vest with vibrotactile feedback for postural correction

2025-04-08T08:22:13+00:00

Musculoskeletal disorders caused by poor posture affect occupational health. In this study, the workstations of administrative personnel were evaluated using the RULA method, yielding a risk level of 2, which indicates the need for ergonomic adjustments. To mitigate this risk, a vibrotactile postural feedback vest was designed, based on an Arduino platform and an accelerometer sensor to measure the user's lateral (ax) and frontal (az) inclinations. The system employs the Seeed Studio XIAO ESP32 S3 microcontroller, an MPU6050 sensor, and vibration actuators for correction signals. A three-phase protocol was implemented: (1) familiarization, (2) practice to identify stimuli, and (3) prolonged evaluation. The results showed that the inclinations remained within the correction range, and the frequency of corrections decreased, indicating that users autonomously adjusted their posture, thereby reducing the risk of musculoskeletal disorders.

Development of intelligent systems for labor conflict management: An approach from industrial engineering and organizational sociology

2025-04-08T08:22:33+00:00

The development of the intelligent system for labor conflict management was carried out with the aim of improving the identification, prevention, and resolution of conflicts in organizational environments through the use of advanced artificial intelligence tools and social network analysis. The system was designed to detect conflict patterns, generate automated solutions, and dynamically adjust its responses using machine learning techniques, natural language processing, and graph theory analysis. The methodology included a detailed analysis of the organizational structure, the application of a survey to assess perceptions and workplace dynamics, and the implementation of a continuous feedback system to enhance the system’s performance. Network analysis enabled the identification of key employees with high social influence and the detection of critical points within the organizational structure, while sentiment analysis and automated responses strengthened the system’s ability to resolve conflicts efficiently. The results showed a significant improvement in conflict detection accuracy (from 60% to 90%), a 30% reduction in the number of reported conflicts, and an increase in employee satisfaction (from 60% to 88%). The improvement in the work environment and the system’s ability to adapt to different organizational settings confirmed the effectiveness and scalability of the implemented solution.