Resultados totales (Incluyendo duplicados): 45556
Encontrada(s) 4556 página(s)
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/131938
Dataset. 2019

MODELS_CASES_1-6

  • Vives i Costa, Jordi|||0000-0003-3854-775X
Numerical Model for a 19th Century Hydrometric (Case 1: 1000 L/s inlet flow). Aquests datasets són els models numèrics que corresponen als 6 casos de simulacions fetes amb el software de CFD anomenat Flow3D.

DOI: http://hdl.handle.net/2117/131938, https://dx.doi.org/10.5821/data-2117-131938-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/131938
HANDLE: http://hdl.handle.net/2117/131938, https://dx.doi.org/10.5821/data-2117-131938-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/131938
PMID: http://hdl.handle.net/2117/131938, https://dx.doi.org/10.5821/data-2117-131938-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/131938
Ver en: http://hdl.handle.net/2117/131938, https://dx.doi.org/10.5821/data-2117-131938-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/131938

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/365018
Dataset. 2022

ULTIMATE LOAD OF RANDOMLY SAMPLED STAINLESS STEEL FRAMES UNDER GRAVITY PLUS WIND LOADS

  • Arrayago Luquin, Itsaso|||0000-0002-0054-9322
  • Rasmussen, Kim J.R.
  • Zhang, Hao
Data was generated using the general purpose finite element software ABAQUS and performing advanced nonlinear analyses. The database is comprised of ultimate load factors corresponding to different random samples of six different nominal stainless steel frames under gravity and wind load combinations. The values of the random variable assignments are given for each case. The full details of the finite element model can be found in: Arrayago, I.; Rasmussen, K.J.R.; Zhang, H. System-based reliability analysis of stainless steel frames subjected to wind loads. "Structural Safety", July 2022, vol. 97, art. No. 102211. DOI: https://doi.org/10.1016/j.strusafe.2022.102211

DOI: http://hdl.handle.net/2117/365018, https://dx.doi.org/10.5821/data-2117-365018-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/365018
HANDLE: http://hdl.handle.net/2117/365018, https://dx.doi.org/10.5821/data-2117-365018-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/365018
PMID: http://hdl.handle.net/2117/365018, https://dx.doi.org/10.5821/data-2117-365018-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/365018
Ver en: http://hdl.handle.net/2117/365018, https://dx.doi.org/10.5821/data-2117-365018-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/365018

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/364349
Dataset. 2022

SELECTIVELY TARGETING TUMORIGENICITY IN OSTEOSARCOMA

  • Tornin Cavielles, Juan|||0000-0002-7676-3958
  • Mateu Sanz, Miguel|||0000-0001-5117-6071
  • Rey, Verónica
  • Murillo, Dzohara
  • Huergo, Carmen
  • Rodríguez, Aida
  • Rodríguez, René
  • Canal Barnils, Cristina|||0000-0002-3039-7462
Data associated with the study called "Selectively targeting tumorigenicity in osteosarcoma". Each file corresponds to the raw data of one of the figures of the paper

DOI: http://hdl.handle.net/2117/364349, https://dx.doi.org/10.5821/data-2117-364349-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/364349
HANDLE: http://hdl.handle.net/2117/364349, https://dx.doi.org/10.5821/data-2117-364349-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/364349
PMID: http://hdl.handle.net/2117/364349, https://dx.doi.org/10.5821/data-2117-364349-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/364349
Ver en: http://hdl.handle.net/2117/364349, https://dx.doi.org/10.5821/data-2117-364349-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/364349

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/362987
Dataset. 2022

INFLUENCE OF THE IMPERFECTION DIRECTION ON THE STRENGTH OF STEEL AND STAINLESS STEEL FRAMES [DATASET]

  • Arrayago Luquin, Itsaso|||0000-0002-0054-9322
  • Rasmussen, Kim J.R.
This file includes finite element simulation data (ultimate load factors) carried out on 60 steel and stainless steel frames, including regular and irregular frame configurations with different section sizes. Ultimate load factors corresponding to different initial imperfection combinations are included.

DOI: http://hdl.handle.net/2117/362987, https://dx.doi.org/10.5821/data-2117-362987-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/362987
HANDLE: http://hdl.handle.net/2117/362987, https://dx.doi.org/10.5821/data-2117-362987-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/362987
PMID: http://hdl.handle.net/2117/362987, https://dx.doi.org/10.5821/data-2117-362987-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/362987
Ver en: http://hdl.handle.net/2117/362987, https://dx.doi.org/10.5821/data-2117-362987-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/362987

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/189334
Dataset. 2020

TOWARD THE NEW GENERATION OF SURGICAL MESHES WITH 4D RESPONSE: SOFT, DYNAMIC AND ADAPTABLE [DATASET]

  • Lanzalaco, Sonia|||0000-0002-8604-5095
  • Turón Dols, Pau
  • Weis, Christine
  • Mata, Christian
  • Planas Cuchi, Eulàlia|||0000-0002-7053-3959
  • Alemán Llansó, Carlos|||0000-0003-4462-6075
  • Armelín Diggroc, Elaine Aparecida|||0000-0002-0658-7696
These data are associated to the paper with the same title and are structured according to the figures in the paper. These data correspond to the research results of the WP3 of the European Project 4D-POLYSENSE., The present dataset reports the scientific results corresponding to a scientific study where a bidimensional (2D) polypropylene flexible mesh material has been converted into a fourth dimension (4D) dynamic system. The platform is composed by a fibres of isotactic polypropylene (iPP) mesh coated with thermosensitive poly(N-isopropylacrylamide-co-N,N'-methylene bis(acrylamide) (PNIPAAm-co-MBA) hydrogel, and undergoes variations in its geometry by reversible folding/unfolding behaviour. Folding and unfolding motion in aqueous solution of bilayer and monolayer systems composed by two or one layer of hydrogel, respectively, are reported in the present dataset. Furthermore, an infrared thermographic camera and an optical microscope were used to evaluate the macroscopic and microscopic structure stimulus response in air. Additionally, PP-g-PNIPAAm meshes showed an increase in the mechanical properties (bursting strength) with respect to the uncoated mesh.

DOI: http://hdl.handle.net/2117/189334, https://dx.doi.org/10.5821/data-2117-189334-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/189334
HANDLE: http://hdl.handle.net/2117/189334, https://dx.doi.org/10.5821/data-2117-189334-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/189334
PMID: http://hdl.handle.net/2117/189334, https://dx.doi.org/10.5821/data-2117-189334-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/189334
Ver en: http://hdl.handle.net/2117/189334, https://dx.doi.org/10.5821/data-2117-189334-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/189334

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353774
Dataset. 2021

DATASET 5ROUTINGMETRICS VANET BCN

  • Lemus Cárdenas, Leticia
  • Mezher, Ahmad Mohamad|||0000-0003-3263-0122
  • Aguilar Igartua, Mónica|||0000-0002-6518-888X
We have created a representative dataset based on the collection of different traffic metrics from VANET simulations in urban scenarios. The five collected metrics that compose the dataset used to train and test our ML-based forwarding algorithm are available bandwidth, distance to destination, vehicles’ density, MAC layer losses, and vehicle’s trajectory. Notice that those metrics are gathered by the vehicles from the beacons periodically interchanged with the vehicles in their neighborhood (i.e., with vehicles within their transmission range). This way, nodes have local knowledge of the VANET, according to the decentralized nature inherent in VANETs.

DOI: http://hdl.handle.net/2117/353774, https://dx.doi.org/10.5821/data-2117-353774-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353774
HANDLE: http://hdl.handle.net/2117/353774, https://dx.doi.org/10.5821/data-2117-353774-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353774
PMID: http://hdl.handle.net/2117/353774, https://dx.doi.org/10.5821/data-2117-353774-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353774
Ver en: http://hdl.handle.net/2117/353774, https://dx.doi.org/10.5821/data-2117-353774-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353774

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/106182
Dataset. 2017

DADES GLOBALS DE LA RECERCA A LA CATALUNYA CENTRAL

  • Universitat Politècnica de Catalunya. Campus de Manresa. Biblioteca
Aportació de dades globals de la recerca a la Catalunya Central, facilitades per la majoria d’institucions membres de l’observatori.

Proyecto: //
DOI: http://hdl.handle.net/2117/106182
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/106182
HANDLE: http://hdl.handle.net/2117/106182
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/106182
PMID: http://hdl.handle.net/2117/106182
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/106182
Ver en: http://hdl.handle.net/2117/106182
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/106182

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/168964
Dataset. 2019

HIGH PRESSURE ROLL CRUSHER MODELLING

  • Anticoi Sudzuki, Hernán Francisco|||0000-0003-4316-5203
Using a previous mechanical characterization of two types of material, several lab-test work have been done. The data shows the particle size distribution of these tests, all the inputs and the model simulation presented in the related paper to this data base. The new mathematical approach use the operative conditions and the feed particle size distribution to obtain a product, which is compared with the lab-test results, An improved approach is presented to model the product particle size distribution resulting from grinding in high-pressure roll crusher with the aim to be used in standard high-pressure grinding rolls (HPGR). This approach uses different breakage distribution function parameter values for a single particle compression condition and a bed compression condition. Two materials were used for the experiments; altered Ta-bearing granite and a calc-silicate tungsten ore. A set of experiments was performed with constant operative conditions, while varying a selected condition to study the influence of the equipment set-up on the model. The material was comminuted using a previously determined specific pressing force, varying the feed particle size, roll speed and the static gap. A fourth group of experiments were performed varying the specific pressing force. Experimental results show the high performance of the comminution in a high-pressure environment. The static gap was the key in order to control the product particle size. A mathematical approach to predict the product particle size distribution is presented and it showed a good fit when compared to experimental data. This is the case when a narrow particle size fraction feed is used, but the fit became remarkably good with a multi-size feed distribution. However, when varying the specific pressing force in the case of the calc-silicate material, the results were not completely accurate. The hypothesis of simultaneous single particle compression and bed compression for different size ranges and with different parameters of the distribution function was probed and reinforced by various simulations that exchanged bed compression parameters over the single particle compression distribution function, and vice versa.

DOI: http://hdl.handle.net/2117/168964, https://dx.doi.org/10.5821/data-2117-168964-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/168964
HANDLE: http://hdl.handle.net/2117/168964, https://dx.doi.org/10.5821/data-2117-168964-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/168964
PMID: http://hdl.handle.net/2117/168964, https://dx.doi.org/10.5821/data-2117-168964-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/168964
Ver en: http://hdl.handle.net/2117/168964, https://dx.doi.org/10.5821/data-2117-168964-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/168964

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353437
Dataset. 2021

VELOCITY PROFILE DISTRIBUTION IN STEEP CHANNELS WITH LOW RELATIVE SUBMERGENCE CONDITIONS

  • Marin-Esteve, Blanca|||0000-0002-3468-5234
  • Bateman Pinzón, Allen|||0000-0001-9980-6554
  • Sosa Pérez, Raul
The data have been acquired during the experimental campaign carried out in the Steep Slope Flume at Morphodynamics Laboratory I of the GITS group in BarcelonaTech-Universtitat Politècnica de Catalunya. Data published here comprise the measurements carried out in the laboratory related with velocity profiles in steep channels with low relative submergence. Flume slope ranged between 2-10% and same bed material had been used (a basaltic gravel of 1.45 mm of main diameter) for all the experiments. 30 experiments were carried out with 165 velocity profile measurements.

DOI: http://hdl.handle.net/2117/353437, https://dx.doi.org/10.5821/data-2117-353437-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353437
HANDLE: http://hdl.handle.net/2117/353437, https://dx.doi.org/10.5821/data-2117-353437-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353437
PMID: http://hdl.handle.net/2117/353437, https://dx.doi.org/10.5821/data-2117-353437-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353437
Ver en: http://hdl.handle.net/2117/353437, https://dx.doi.org/10.5821/data-2117-353437-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/353437

UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/333712
Dataset. 2020

COOPERATIVE LEARNING FOR END-TO-END DELAY MODELING IN MULTI-DOMAIN NETWORKS [DATASET]

  • Ruiz Ramírez, Marc|||0000-0001-6429-6347
  • Velasco Esteban, Luis Domingo|||0000-0002-7345-296X
This dataset has been used to generate part of the results included in the manuscript: "Cooperative Learning for End-to-End Delay Modeling in Multi-Domain Networks", submitted to IEEE Transactions on Network and Service Management (TNSM) at the time of publication of this dataset. The dataset contains synthetic end-to-end (e2e) delay and traffic measurements for multidomain paths established in a network consisting in three domains. Paths traverse either two or three domains. Besides e2e monitoring data, routing information of the paths and the models used to compute the delay introduced for each domain (i.e. intra-domain delay components of total e2e delay) are provided. Traffic and delay data were synthetically generated according to the CURSA-SQ methodology. For further details about it, please refer to the following reports: "The Logistic Queue Model", Tech. Rep. UPC-DAC-RR-GEN-2020-1 (Available online: https://people.ac.upc.edu/lvelasco/docs/research/UPC-DAC-RR-GEN-2020-1.pdf) and "Validation of the CURSA-SQ Methodology", Tech. Rep. UPC-DAC-RR-GEN-2020-2 (Available online: https://people.ac.upc.edu/lvelasco/docs/research/UPC-DAC-RR-GEN-2020-2.pdf)

Proyecto: //
DOI: http://hdl.handle.net/2117/333712, https://dx.doi.org/10.5821/data-2117-333712-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/333712
HANDLE: http://hdl.handle.net/2117/333712, https://dx.doi.org/10.5821/data-2117-333712-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/333712
PMID: http://hdl.handle.net/2117/333712, https://dx.doi.org/10.5821/data-2117-333712-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/333712
Ver en: http://hdl.handle.net/2117/333712, https://dx.doi.org/10.5821/data-2117-333712-1
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/333712

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