Zobrazeno 1 - 10
of 4 028
pro vyhledávání: '"Model Identification"'
Autor:
Julen Bacaicoa, Mikel Hualde-Otamendi, Mikel Merino-Olagüe, Aitor Plaza, Xabier Iriarte, Carlos Castellano-Aldave, Alfonso Carlosena
Publikováno v:
Data in Brief, Vol 57, Iss , Pp 111126- (2024)
This paper presents a publicly available dataset designed to support the identification (characterization) and performance optimization of an ultra-low-frequency multidirectional vibration energy harvester. The dataset includes detailed measurements
Externí odkaz:
https://doaj.org/article/b2e1cf5486ab4ef0b96c3b5ec30a297b
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
In the study of PAM (McKibben-type pneumatic artificial muscle)-driven bipedal robots, it is essential to investigate whether the intrinsic properties of the PAM contribute to achieving stable robot motion. Furthermore, it is crucial to determine if
Externí odkaz:
https://doaj.org/article/f40bb204a8aa48eabfec1956d8c4188a
Publikováno v:
Yuanzineng kexue jishu, Vol 58, Iss 4, Pp 952-960 (2024)
The mathematical model of a radio frequency (RF) system incorporates crucial characteristic parameters of an RF cavity, including the cavity bandwidth, the resonant frequency, and Lorentz force detuning factors, which is very important for the cavity
Externí odkaz:
https://doaj.org/article/acaa0e6607934818b968c7514856c414
Publikováno v:
Aircraft Engineering and Aerospace Technology, 2023, Vol. 96, Issue 1, pp. 175-183.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AEAT-05-2023-0145
Publikováno v:
Heliyon, Vol 10, Iss 9, Pp e29764- (2024)
The parameter identification of failure models for composite plies can be cumbersome, due to multiple effects as the consequence of brittle fracture. Our work proposes an iterative, nonlinear design of experiments (DoE) approach that finds the most i
Externí odkaz:
https://doaj.org/article/43a79a8d5b384581b9ecc19362464a7a
Publikováno v:
Kongzhi Yu Xinxi Jishu, Iss 6, Pp 32-39 (2023)
Aiming at the motion state coupling and model non-linearity of remotely operated vehicle (ROV) caused by the asymmetric structural layout of ROV and changes of center of gravity and center of buoyancy, this paper proposes a model identification algor
Externí odkaz:
https://doaj.org/article/8820738c827b42328d5f9e0c9a7666b2
Autor:
Andreas Moser, Valentin Kaisermayer, Daniel Muschick, Christopher Zemann, Markus Gölles, Anton Hofer, Daniel Brandl, Richard Heimrath, Thomas Mach, Carles Ribas Tugores, Thomas Ramschak
Publikováno v:
International Journal of Sustainable Energy, Vol 42, Iss 1, Pp 1063-1078 (2023)
Buildings with floor heating or thermally activated building structures offer significant potential for shifting the thermal load and thus reduce peak demand for heating or cooling. This potential can be realised with the help of model predictive con
Externí odkaz:
https://doaj.org/article/c2227599c444455d84c23eb54ea170f3
Publikováno v:
Journal of Sensor and Actuator Networks, Vol 13, Iss 5, p 49 (2024)
The integration of vehicle-to-grid (V2G) technology into smart energy management systems represents a significant advancement in the field of energy suppliers for Industry 4.0. V2G systems enable a bidirectional flow of energy between electric vehicl
Externí odkaz:
https://doaj.org/article/a56bac7bd1a84102a4df8b8d64a72f57
Publikováno v:
مجله علوم و فنون هستهای, Vol 44, Iss 3, Pp 130-139 (2023)
One of the essential systems for the upgrade of Damavand Tokamak is the automatic control of the vacuum vessel pressure profile. This research performs the identification, modeling, and control of the vacuum chamber pressure in Damavand Tokamak. As a
Externí odkaz:
https://doaj.org/article/de853394b0ca4622b7edbe542ab9e251
Publikováno v:
Shipin gongye ke-ji, Vol 44, Iss 16, Pp 306-312 (2023)
The electronic nose technology with 10 sensor channels was used to determine and analyze the flavor components of red Zanthoxylum bungeanum from 6 different major producing areas in China, including Hanyuan Zanthoxylum bungeanum, for the identificati
Externí odkaz:
https://doaj.org/article/a1f6056e1a244dd89bbbc5b782315f1b