Facultad de Ingeniería - CampGDL

City
Guadalajara
Country
MX
Parent Organisation

Filters

Settings

Now showing 1 - 10 of 707
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Effect of 3D printing by fused deposition modelling on the microstructural and macrostructural properties of acrylonitrile butadiene styrene, polylactic acid and polyamide 12
    (SAGE Publications, 2025-09-16)
    Acevedo-Parra, H. R.  
    ;
    Tapia, Fidencio  
    ;
    J.A. Guerrero de León
    ;
    Jorge H. Díaz A.
    ;
    S.L. Rodríguez-Reyna
    The objective of this research was to find a relationship between the microstructural and macrostructural properties of polylactic acid, acrylonitrile butadiene styrene and polyamide 12 (PA12) when processed using fused deposition modelling. The crystallinity, enthalpy of crystallization (ΔHc), glass transition temperature (Tg) and Young's modulus (E) were evaluated. The results showed that crystallinity increased for all materials after the 3D printing process, leading to an increase in ΔHcand a decrease in Tg, particularly in PA12. This variation in microstructural properties resulted in a significant decrease in Young's modulus, indicating a reduction in the stiffness of the printed materials. The research suggests that an increase in crystalline material volume, resulting from polymer chain rearrangement during 3D printing, reduces the energy required for thermal softening and decreases the material's rigidity. © The Author(s) 2025
      35
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      10
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    New Detection Paradigms to Improve Wireless Sensor Network Performance under Jamming Attacks
    (2019)
    Del-Valle-Soto, Carolina  
    ;
    Carlos Mex-Perera
    ;
    Ivan Aldaya
    ;
    Fernando Lezama
    ;
    Juan Arturo Nolazco-Flores
    <jats:p>In this work, two new self-tuning collaborative-based mechanisms for jamming detection are proposed. These techniques are named (i) Connected Mechanism and (ii) Extended Mechanism. The first one detects jamming by comparing the performance parameters with respect to directly connected neighbors by interchanging packets with performance metric information, whereas the latter, jamming detection relays comparing defined zones of nodes related with a collector node, and using information of this collector detects a possible affected zone. The effectiveness of these techniques were tested in simulated environment of a quadrangular grid of 7 × 7, each node delivering 10 packets/sec, and defining as collector node, the one in the lower left corner of the grid. The jammer node is sending packets under reactive jamming. The mechanism was implemented and tested in AODV (Ad hoc On Demand Distance Vector), DSR (Dynamic Source Routing), and MPH (Multi-Parent Hierarchical), named AODV-M, DSR-M and MPH-M, respectively. Results reveal that the proposed techniques increase the accurate of the detected zone, reducing the detection of the affected zone up to 15% for AODV-M and DSR-M and up to 4% using the MPH-M protocol.</jats:p>
      1  9Scopus© Citations 10
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Data-Driven Modeling of Battery-Based Energy Storage Systems
    (2025)
    Edgar D. Silva-Vera
    ;
    Jesus E. Valdez-Resendiz
    ;
    Rosas-Caro, Julio  
    ;
    Gerardo Escobar
    ;
    D. Guillen
      20
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Scopus© Citations 15  1  2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Evaluation of the Scaling Factor Bias Influence on the Probability of Collapse Using <i>S</i><sub><i>a</i></sub>(<i>T</i><sub>1</sub>) as the Intensity Measure
    (2019)
    Dávalos, Héctor  
    ;
    Eduardo Miranda
    <jats:p> Amplitude scaling is a common approach to modify recorded ground motions to achieve a desired intensity level. The possible bias introduced by scaling the amplitude of ground motions when using the first-mode spectral ordinate as the intensity measure is evaluated using intensity-based analyses. This study evaluates whether upward scaling introduces bias in lateral displacement demands, but more importantly, in the probability of collapse. The latter, which is of utmost importance, has received little attention in previous studies. Analyses were conducted using degrading single-degree-of-freedom and multiple-degree-offreedom systems with different fundamental periods of vibration and normalized strengths subjected to different sets of recorded accelerograms requiring different scale factors to reach a target intensity. The results demonstrate that this type of amplitude scaling introduces a bias in which lateral displacement demands and collapse estimates are increasingly overestimated with an increasing scale factor and that the bias is strongly dependent on the period and lateral strength of the system. Furthermore, the bias is considerably larger in collapse risk estimates. </jats:p>
      2  8Scopus© Citations 65
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      18
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Neural networks-based modeling of compressive stress in expanded polystyrene foams: A focus on bead size parameters
    (2024)
    Melvin I. Pech-Mendoza
    ;
    Rodríguez-Sánchez, Alejandro E.
    ;
    Héctor Plascencia-Mora
    <jats:p> Expanded polystyrene is used in diverse applications, notably for protective and structural purposes. Its cushioning and mechanical strength excel under compressive loads, especially when optimally designed. A key factor influencing its compressive stress is the initial density, which plays a significant role in determining the material’s mechanical properties. This aspect is primarily determined by the bead size distribution. Although there is a vast body of literature on modeling the stress response of expanded polystyrene, there is limited emphasis on predictions that account for this factor, which is also relevant for the manufacturing of the material. Recent literature has emphasized the capability of artificial neural networks in predicting the compressive behaviors of expanded polystyrene, incorporating various factors. In this study, artificial neural network models were used to predict the compressive stress responses of polystyrene foams, with a focus on bead size distribution parameters. Specimens of two distinct initial densities were examined using micrographs to identify bead diameters and distributions, which were then used as model inputs. Compression tests on these specimens were conducted at two different rates. The collected data facilitated the development of predictive models for the material’s compressive behavior. The model predictions closely match experimental findings, with error metrics showing deviations &lt;3% compared to the experimental data. This highlights the utility of artificial neural networks in modeling the compressive behavior of polystyrene foams, particularly when bead size and related parameters are considered. </jats:p>
    Scopus© Citations 2  2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
      2  12Scopus© Citations 32
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Visual Servoing Using Sliding-Mode Control with Dynamic Compensation for UAVs’ Tracking of Moving Targets
    (2024)
    Christian P. Carvajal
    ;
    Víctor H. Andaluz
    ;
    José Varela-Aldás
    ;
    Flavio Roberti
    ;
    Del-Valle-Soto, Carolina  
    <jats:p>An Image-Based Visual Servoing Control (IBVS) structure for target tracking by Unmanned Aerial Vehicles (UAVs) is presented. The scheme contains two stages. The first one is a sliding-model controller (SMC) that allows one to track a target with a UAV; the control strategy is designed in the function of the image. The proposed SMC control strategy is commonly used in control systems that present high non-linearities and that are always exposed to external disturbances; these disturbances can be caused by environmental conditions or induced by the estimation of the position and/or velocity of the target to be tracked. In the second instance, a controller is placed to compensate the UAV dynamics; this is a controller that allows one to compensate the velocity errors that are produced by the dynamic effects of the UAV. In addition, the corresponding stability analysis of the sliding mode-based visual servo controller and the sliding mode dynamic compensation control is presented. The proposed control scheme employs the kinematics and dynamics of the robot by presenting a cascade control based on the same control strategy. In order to evaluate the proposed scheme for tracking moving targets, experimental tests are carried out in a semi-structured working environment with the hexarotor-type aerial robot. For detection and image processing, the Opencv C++ library is used; the data are published in an ROS topic at a frequency of 50 Hz. The robot controller is implemented in the mathematical software Matlab.</jats:p>
    Scopus© Citations 4  14