82 research outputs found
AUTHOR CORRECTION - ERS International Congress 2019:highlights from Best Abstract awardees
No full textLorna E. Latimer, Marieke Duiverman, Mahmoud I. Abdel-Aziz, Gulser Caliskan, Sara M. Mensink-Bout, Alberto Mendoza-Valderrey, Aurelien Justet, Junichi Omura, Karthi Srikanthan, Jana De Brandt. Breathe 2019; 15: e143–e149. This article from the December 2019 issue of Breathe was published with an error in the name of one of the authors. The corrected author list is shown above. The article has been corrected and republished online.</p
Supporting a decarbonised hydrogen economy
No full textThe flyer has been developed to enhance the visibility of the JRC laboratory activities in hydrogen technologies. It is aimed to the public and the JRC visitors. It presents the JRC capabilities for testing the safety, performance and durability of hydrogen systems and components essential in the development of the hydrogen economy: from water electrolysers used for hydrogen production to hydrogen pipelines, high-pressure gas storage tanks and fuel cells used in hydrogen fuel cell cars, trucks, buses, trains and boats.JRC.C.1 - Battery and Hydrogen Technologie
Parametrized cosmological mass maps dataset
No full textParametrized cosmological mass maps dataset
This dataset consists of the non-tomographic training and testing set without noise and intrinsic alignments.
It was introduced in the following paper
Fluri, Janis, et al. "Cosmological constraints with deep learning from KiDS-450 weak lensing maps." Physical Review D 100.6 (2019): 063514.
Furthermore, this dataset is released with the following paper:
Perraudin, Nathanaël, et al. "Emulation of cosmological mass maps with conditional generative adversarial networks." arXiv preprint arXiv:2004.08139 (2020).
Code related to this dataset can be found in https://renkulab.io/projects/nathanael.perraudin/darkmattergan
Description
The simulation grid consists of different cosmologies assuming a flat LambdaCDM universe.
Each of these 57 configurations was run with different values of Omega_m and sigma_8, resulting in the following parameter grid.| Omega_m, sigma_8
0.101, 1.304
0.102, 1.125
0.103, 0.947
0.120, 1.178
0.123, 1.006
0.127, 0.836
0.137, 1.230
0.142, 1.063
0.148, 0.900
0.154, 1.281
0.156, 0.741
0.161, 1.119
0.169, 0.961
0.171, 1.331
0.178, 0.807
0.179, 1.173
0.188, 1.019
0.189, 0.659
0.196, 1.225
0.199, 0.870
0.207, 1.075
0.212, 0.727
0.219, 0.930
0.225, 1.129
0.227, 0.591
0.233, 0.791
0.238, 0.988
0.250, 0.658
0.254, 0.852
0.257, 1.043
0.269, 0.534
0.271, 0.723
0.273, 0.910
0.291, 0.601
0.291, 0.783
0.292, 0.966
0.311, 0.842
0.312, 0.664
0.314, 0.487
0.330, 0.898
0.332, 0.724
0.335, 0.552
0.352, 0.782
0.356, 0.614
0.370, 0.838
0.376, 0.673
0.382, 0.510
0.395, 0.730
0.402, 0.570
0.413, 0.784
0.421, 0.628
0.431, 0.475
0.440, 0.683
0.450, 0.533
0.458, 0.737
0.469, 0.589
0.487, 0.643
Each zip file in the dataset corresponds to 1 of these combinations and contains 12 files containing 1000 images.
The source galaxy redshift distribution corresponding to these maps is the full, non-tomographic redshift distribution n(z) from Fluri et. al.
The projected matter distribution was pixelised into images of size 128px x 128px, which correspond to 5deg x 5deg of the sky.
Eventually, the resulting dataset consists of 57 sets of 12'000 sky convergence maps for a total of samples.
Citations
If you use this dataset, please cite:
@article{perraudin2020emulation,
title={Emulation of cosmological mass maps with conditional generative adversarial networks},
author={Perraudin, Nathana{\"e}l and Marcon, Sandro and Lucchi, Aurelien and Kacprzak, Tomasz},
journal={arXiv preprint arXiv:2004.08139},
year={2020}
}
and
@article{fluri2019cosmological,
title={Cosmological constraints with deep learning from KiDS-450 weak lensing maps},
author={Fluri, Janis and Kacprzak, Tomasz and Lucchi, Aurelien and Refregier, Alexandre and Amara, Adam and Hofmann, Thomas and Schneider, Aurel},
journal={Physical Review D},
volume={100},
number={6},
pages={063514},
year={2019},
publisher={APS}
CO Desorption Kinetics under Conditions of Relevance to PEM Fuel Cells Operating with Reformate Gas
No full textThe kinetics of the CO desorption process have been investigated on a PtRu/C anode using isotopic exchange experiments under conditions of relevance to PEM fuel cells operating with reformate gas. Desorption rate constants have been determined experimentally for a wide range of concentrations (100-1000 ppm) and temperatures (25-150°C) and have been extrapolated to one order of magnitude lower CO concentration range between 10 and 100 ppm, which is directly relevant to PEMFC operating with reformate gas. The results are discussed with relation to the CO tolerance issue at the PEM fuel cell anode and to the development of more accurate models for PEM fuel cells operating with reformate gas.JRC.DDG.F.2 - Cleaner energ
CO Desorption Kinetics at Concentrations and Temperatures Relevant to PEM Fuel Cells Operating with Reformate Gas and PtRu/C Anodes
No full textThe kinetics of the CO desorption process have been determined using isotopic exchange experiments at concentrations and temperatures relevant to PEM fuel cells operating with reformate gas and commercial carbon supported platinum-ruthenium alloy anodes. The CO desorption kinetics have been studied as a function of CO concentration, temperature and flow rate. Desorption rate constants have been determined experimentally for a wide range of concentrations (100-500ppm) and temperatures (25-150°C) and have been extrapolated to one order of magnitude lower CO concentration range between 10 and 100ppm, which is directly relevant to PEM fuel cells operating with reformate gas. The desorption rates measured for the 100-500ppm CO concentration range appear to be significantly larger than previously published CO oxidation data, suggesting that the CO desorption process plays a more significant role in determining the equilibrium CO coverage at the fuel cell anode than the electrochemical CO oxidation process. The proposed desorption rate values at the lower 10-100ppm CO concentration range and at relevant temperatures are believed to be of added value for the modelling of PEM fuel cells operating with reformate gas and PtRu/C anodes, since significantly different empirical values have been used up to now for the modelling of the CO desorption process. The variation of the apparent Arrhenius parameters as a function of CO concentration provides also some insight into the CO poisoning effect and the underlying adsorption/desorption processes.JRC.DDG.F.2 - Cleaner energ
Non-noble Catalysts Cut Fuel Cell Costs (2007-2010) - FCAnode project
No full textThe cost of noble-metal catalyst systems for proton exchange membrane fuel cells (PEMFC) is driving research to find less expensive non-noble alternatives.JRC.F.2 - Cleaner energ
FCANODE - Non-Noble Catalysts for Proton Exchange Membrane Fuel Cell Anodes
No full textThe FCANODE project is funded by the EC FP6, under the Specific Targeted Research Project Action. Its aim is to take up the materials development for Proton Exchange Membrane Fuel Cells (PEMFC) by replacing the expensive platinum based catalysts by cheaper non-noble metal based nanoparticulate catalysts. This could reduce significantly the cost of the fuel cells and bring them closer towards full commercialisation.JRC.F.2 - Cleaner energ
A historical analysis of safety of hydrogen transport technologies based on incidents records
No full textTransport of hydrogen for industrial and aerospace applications is occurring since several decades, specially in the US. Several scientific reviews of these technologies from a safety point of view date back to the previous century. In a period in which a strengthening of the hydrogen supply chain is taking place, with expected scaling up of production, transport and use, it is worth to analyse the return of experience provided by available incidents descriptions. This work is based on the most recent dataset of the Hydrogen Incidents and Accidents Database (HIAD) managed by the European Commission’s Joint Research Centre and focuses on two of the three incumbent hydrogen transportation technologies: compressed hydrogen tube trailers and liquid hydrogen tanker (hydrogen pipelines are presented in paper ID134). The paper presents basic statistics and analyses the cause-consequence relationship, discussing also the limitations of the methodological approach. The study confirms the high degree of safety characterised by the transport of liquid hydrogen in cryogenic tanks, with a low reported number of ignited releases. Despite the fact that transport by tube trailers has led in some cases to a more severe set of consequences, the observed impact from accidents on human health and environment appears to be lower for both transport technologies discussed in this work, when compared to other parts of the hydrogen supply and value chain.JRC.C.1 - Battery and Hydrogen Technologie
Cosmological N-body simulations: a challenge for scalable generative models: Tensorflow checkpoints
No full text<p><strong>Tensorflow checkpoints: Cosmological N-body simulations: a challenge for scalable generative models</strong></p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper <strong>Cosmological N-body simulations: a challenge for scalable generative models</strong> by Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<pre><code>@inproceedings{perraudin2019cosmological,
title = {Cosmological N-body simulations: a challenge for scalable generative models},
author = {Nathana\"el, Perraudin and Ankit, Srivastava and Kacprzak, Tomasz and Lucchi, Aurelien and Hofmann, Thomas and R{\'e}fr{\'e}gier, Alexandre},
year = {2019},
archivePrefix = {arXiv},
eprint = {1908.05519},
url = {https://arxiv.org/abs/1908.05519},
}
</code></pre>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
<p>This corresponds to the Tensorflow checkpoints for the experiments in the paper<br>
**Cosmological N-body simulations: a challenge for scalable generative models** by<br>
Nathanaël Perraudin, Ankit Srivastava, Aurelien Lucchi, Tomasz Kacprzak, Thomas Hofmann, Alexandre Refregier, Adam Amara.</p>
<p>Please check the assotiated github page <a href="https://github.com/nperraud/3DcosmoGAN">https://github.com/nperraud/3DcosmoGAN</a> for additional information.</p>
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