Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Helio Castro

Prof. PhD

University of Campinas

Brazil

Research Interests

Articles (19)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Collaborators (2)

Diogo Stuani Alves

Lecturer/Assistant Professor

University of Campinas

BRAZIL

View details

Onur Can Kalay

Texas Tech University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Helio Castro

Research Interests

Articles (19)

A comprehensive generalized dynamic model of planetary gearboxes for single- and dual-input configurations

A novel model of lubricated contact for spur gears

Comparison Between Regression and Surrogate Models Based on Bayesian Neural Network to Determine Shaft Crack Severity

Dynamic Analysis of Planetary Gearbox Failure Under Environment Uncertainties

Influence of Gear Mesh Transmission Error on the Identification of Tooth Root Cracks in the Sun Gear Based on the Dynamic Response of a Planetary Geared Rotor System

Modeling the Failure Rate of Redundant Refrigeration Compressors Considering Load Sharing Using Warranty Data

Probabilistic surrogate modeling for gas foil bearing stability

Rotor Dynamics Model Enhanced by Reliable Data-Driven Discrepancy Modeling

Uncertainty-Aware Probabilistic Reliability Algorithm for Capacitors Using Kriging-Based Electrothermal Modeling

Rotor System's Fault Parameter Quantification Using a Surrogate Model Considering Uncertainty

Effect of gear tooth root crack on the dynamic response of a planetary geared rotor system

A POWER SPECTRUM BAYESIAN SURROGATE MODEL FOR A GEARED PAIR WITH A CRACKED TOOTH

A new metric for reliable diagnosis of rotating machines applied to a multi-fault rotor using Bayesian neural networks

BAYESIAN NEURAL NETWORKS AND KRIGING MODELING FOR THE PREDICTION OF CRACK PROPAGATION IN ROTATING MACHINES CONSIDERING UNCERTAINTIES IN THE MODEL PARAMETERS

Effect of spur gear crack on rotor dynamic response

FAULT PARAMETER QUANTIFICATION WITH A BAYESIAN SURROGATE MODEL FOR COUPLING MISALIGNMENT IN A ROTOR SYSTEM

Reliability-Based Design Optimization Applied to a Rotor Supported by Hydrodynamic Bearings

Physics-guided neural networks applied in rotor unbalance problems

Verification and Validation of Rotating Machinery Using Digital Twin

Collaborators (2)

Diogo Stuani Alves

Onur Can Kalay

Make your next move.