dataesr/scientific-paragraphs-categorization huggingface dataset:
Shallow water equations are discretized using a finite-differences method in space and time (FDTD). Pressure and velocity fields are evaluated on uniform separate grids according to Arakawa's C-grid  (Arakawa, 1972). Partial derivatives are approximated using upwind finite-differences  (Mader, 2004). Time integration is performed using the iterated Crank-Nicholson scheme. No viscosity terms are taken in account in our simulations. The only parameters of this second model are the bathymetry (space step and depth resolution) and the time step. The tsunami-code was largely validated through extensive benchmarks in the framework of the work package 1 of the TANDEM research project  (Violeau and TANDEM, 2016). In this work  (Antoshchenkova et al. , 2016) , all simulations were performed on the same bathymetric grid with a space resolution of 2' (~3.
Meta-models design Even if LHS design is the most employed for the construction of Gaussian meta-models such as kriging, in this work we used as design database the numerical results issued from the preliminary research  (Antoshchenkova et al. , 2016) , for many reasons. First, the variation range of the seismic source input-parameters (Table  5 ) is very large and permits to cover the bibliography analysis associated to the Lisbon tsunami  (Antoshchenkova et al. , 2016; Imbert et al. , 2015)  and to the AGFZ earthquakes registered in earthquakes catalogues. Thus, if correctly estimated, meta-models will be able to reproduce the model behaviour for a large range of variations of the seismic inputs parameters, which is consistent with the objectives of the study (to simulate a wide range of possible tsunami scenarios).
Second, except for some numerical tests reported in previous studies  (Iooss et al. , 2010) , at the moment, no theoretical results give the type of initial design leading to the best fitted meta-model in terms of meta-model predictions. Finally, in this way, meta-models can be built directly, without any complementary (and costly) numerical runs. In this sense, another design database as LHS will be employed only if the meta-models accuracy is not judged satisfactory, according to the test-criteria presented in the previous paragraph and used for the training and validation sets. In order to build the design database, fault parameters as defined in section 3. 1 were sampled randomly and independently, using uniform distributions  (Antoshchenkova et al. , 2016). This design database is a matrix which associates to a given combination of fault parameters the maximum simulated water height at each point of the numerical grid and also at some selected given locations called gauges.
The maximum tsunami water height is the relevant parameter when estimating tsunami hazard and it is more synthetic than the water height at a specific time which allows reducing the amount of output data. The original database was previously filtered in order to exclude the faults deeper than 60 km, which is not realistic for the study site. The resulting design database contains 5839 scenarios split in a training set of 4672 scenarios and a testing set of 1167 tsunamis scenarios, used for the meta-model validation and the residual analysis. The water height characteristics associated to these tsunamis scenarios are reported in Table  3. Finally, the meta-models are built for four French Atlantic Gauges (see Figure  3  and Table  2 ), using the opensource R-packages DiceKriging  (Roustant et al.
Meta-models evaluation As reported in the section 2. The computation of the correlation coefficient shows a good agreement between the original model results and meta-models, for the four selected gauges (see Table  4  and Figure  5 ). R 2 -values are generally high (the minor values for La Rochelle, of 76%, is satisfying), even if we can observe that the strongest water height from the original model are slightly underestimated by the meta-models for the validation-set data base (Figure  5 ). Considering the strong differences (Table  3 ) between the "maximum" water height and the " m + 2 m " water height of the design database ( m and  m being, respectively, the mean and the standard deviation of the tsunami water height), which indicate that the lower water height are largely represented in the design database, it is not surprising that the meta-models predictions are more accurate for lower tsunami height than for extreme water height.
These results are confirmed by the computation of the frequency distribution of the absolute residuals (the modulus of Eq. 14) and of the density frequency distribution of the relative residuals (Eq. 14), as reported in Table  4  and Figure  4. This analysis shows that the residuals are normally distributed with mean zero (" r ") and lower standard deviation (" r "), which is satisfying according to  (Jarque and Bera, 1980) , and that the maximum residuals are high for the fourth gauges (Table  4 ), probably for the reasons reported above. In conclusion, the residuals analysis confirms that, globally, the meta-models constructed for the four French Atlantic gauges are able to reproduce the model behaviour (the residuals are globally low with the "2 r " of few centimetres), and they can be used for the construction of the numerical tsunami database.
Building the tsunamis database for the French Atlantic Gauges Starting from the validated meta-models we finally build a database of tsunamis generated by the AGFZ at four French Atlantic Gauges. Because the modelled area encompass different seismotectonic domains, the overall AGFZ area was split into two main seismic source zones in order to feed the meta-model database. This was done to represent an oceanic domain to the West where normal to transtensive earthquakes mainly occur within a thin oceanic crust and a continental domain to the East where reverse to transpressive earthquakes mainly occur on a thickened oceanic to continental crust  (Buforn et al. , 1988; Molinari and Morelli, 2011; Cunha et al. , 2012). As a first order analysis, we considered the oceanic domain (hereafter called oceanic shelf) west of the 10°W meridian and the continental domain (hereafter called continental shelf) east of this meridian, coinciding roughly with the base of the continental slope facing the Portuguese coastline.
We finally filtered the resulting database according to an aspect-ratio criterion, allowing the ratio between length and the width of the faults not to exceed the value of 10, which correspond to an upper bound of what is observed in nature  (Mc Calpin, 2009). The final database contains nearly 50,000 tsunami scenarios, resulting of earthquake magnitudes varying from 6. 7 to 9. 3 (Table  5 ), which is consistent with the magnitude range of the design database. This resulting global database (Table  5 ) is composed by the union of the oceanic and the continental databases scenarios. The tsunamis height characteristics associated to the four gauges are reported in Table  6. It must be noted that the maximum tsunamis height of the global database are lower than tsunamis height of the design database and that the convergence of statistics (mean water height) is largely achieved, as reported in Figure  6.
In conclusion, the built tsunamis database (the global database) should represent most of the possible tsunamis generated by the AGFZ (the oceanic and the continental shelf). It is analysed in the next section with a focus on THA. In addition, for the critical analysis of this global numerical database obtained through uncertainty quantification, we decided to complement our study with two specific and nearly deterministic scenarios recognized as possible sources of the Lisbonne 1755 earthquake, namely the Gorringe and Horseshoe structures  (Buforn et al. , 1988; Stich et al. , 2007; Cunha et al. , 2012; Duarte et al. , 2013; Grevemeyer et al. , 2017). Both structures were modelled taking into account available maps  (Cunha et al. , 2012; Duarte et al. , 2013)  and fault parameters  (Stich et al.
, 2007; Grevemeyer et al. , 2017)  summarized in considering their location (Figure  3 ). Similarly, fault parameters are considered uniformly distributed and are randomly sampled in their range of variation (Table  5 ), for a total of nearly 10,000 tsunami scenarios. Results from these nearly deterministic scenarios (Table  6 ) will be utilized in order to complement the critical analysis of the results obtained from the global database.
Results from Uncertainty Quantification As reported in the introduction, the objective of this work is to evaluate the benefits of uncertainty quantification for the improvement of the THA. The tsunami height frequency distribution of each considered tsunamigenic source is reported and compared in Figure  8  for each gauge. It can be observed that the tsunamis heights generated by the oceanic shelf are globally lower than the tsunamis generated by the other sources. This effect seems more marked for the southern gauges, which is coherent with the analysis performed with the Sobol index. Moreover, the strongest tsunamis of the global database are globally generated by the continental shelf for both the southern and the northern gauges. From an engineering point of view, the tsunami hazard can be directly deducted from Figure  8  (black line).
Secondly, considering the roughly approximation of the earthquake input parameters (and the consequently wide range of seismic magnitude distribution) used for the construction of the global database, this hazard level appears more conservative in a context of THA. The robustness of this choice is analysed in the next sections. Especially, it is of interest to analyse the strongest tsunamis of the numerical database (see section 4. 3) and to evaluate if this hazard level is robust with respect to results which could be obtained with a more classical scenario-based approach (see section 4. 4).
Focus on the strongest tsunamis of the numerical database As reported in Table  7 , there are strong differences between the maximum simulated tsunami height and the " m + 2 m " water height of the out-put frequency distribution chosen as hazard level in this study, for all the gauges of the numerical database. As a consequence, from a methodological point of view, and with the objective of assessing the tsunami hazard level from the uncertainty quantification study, it is of interest to analyse these extreme tsunami scenarios. The objective of this analysis is to answer to the central question "which confidence level should be retained for assessing the tsunami hazard from uncertainty quantification and why?" With this aim, we first analysed the magnitude frequency distribution "M w " of the tsunami scenarios of the global database (grey curve in Figure  9a ) with respect to the magnitude of the earthquakes generating tsunamis higher than the proposed hazard level for each gauge (coloured lines in Figure  9a ).
The objective of this analysis is to understand to which magnitude are associated the strongest tsunami heights. This is a global analysis based on the global tsunami database. It must be noted that the sample size for each gauge is not the same and that the tsunamis from the oceanic shelf are underrepresented considering that the maximum magnitude associated to these seismic scenarios is around 8. 5 (see Table  5 ). Globally, the strongest tsunami heights correspond to the strongest seismic events of the database (Figure  9a ). Especially, more than 80% of the tsunami heights higher than the chosen hazard level (" m + 2 m ") are associated to a seismic magnitude higher than 8. 5. These tsunamis events completely represent the tail of the earthquake magnitude distribution (the grey histogram in the Figure  9a ).
Place of a Lisbon-like 1755 tsunami scenario in the numerical database As reported in the introduction, the deterministic THA approach offers simple, directly relatable events or scenarios describing different possible characteristics of the event. The tsunami hazard is assessed by means of considering particular source scenarios (usually maximum credible scenario) and the maximum tsunami height is generally retained as hazard level. A more sophisticated method was recently proposed by  (Roshan et al. , 2016). The authors tested around 300 tsunamis scenarios in a magnitude range [8 -9. 5] associated to various faults potentially impacting the Indian coast. Finally, the authors suggested that an appropriate water level for hazard assessment (e. g. mean value or mean plus sigma value) should be retained.
, 2013)  or  (Grevemeyer et al. , 2017)  and summarized in Table  5. These two scenarios were chosen in order to evaluate the global tsunami database, which was designed by roughly zoning continental and oceanic shelves. In fact, the tsunami hazard induced by the Horseshoe scenario, located at the limit between these two zones of the global database, may be partly contained in the continental contribution of the database. On the contrary, the Gorringe scenario represents a pure "Continental" scenario within the Oceanic zone, hence excluded by the global database. The magnitude range associated to these tsunamis scenarios varies from 7. 7 to 8. 9 and the hazard level associated to these faults corresponds to the " m " modelled water height. This hazard level for the scenario-based approach was arbitrarily chosen, considering that the philosophy of this kind of approach is to take into account only the worst possible scenarios.
In this sense, according to the previous work from  Roshan et al. (2016) , we also proposed to take into account the "mean" modelled water height. In Table  7  we summarized the tsunami hazard height (the modelled " m +2 m " water height) of the global database for each gauge with the associated uncertainty (corresponding to the residuals +/-2 r ). Similarly, the hazard level was computed for the scenarios corresponding to the Gorringe faults and the Horseshoe faults, considering the modelled " m " water height. The results of this analysis indicate that the strongest tsunamis are globally generated by the Gorringe bank. Nevertheless, it also must be noted that the proposed hazard level from the total database is representative of the scenarios based tsunamis once the uncertainty associated to meta-model predictions is considered (see Figure  10 ).
Conclusions and perspectives The research presented in this paper, mainly methodological, was performed in order to test the interest of using an uncertainty quantification approach for the assessment of the tsunami hazard generated by earthquakes. The methodology is based on the use of kriging meta-models built following numerical simulations performed in a precedent research activity  (Antoshchenkova et al. , 2016). The meta-models were tested and validated through a series of statistical indicators (correlation coefficient, residuals analysis, MSE). These performance-tests allowed us to conclude that, even if the maximum residuals (differences between model and meta-model results) are very high for the four gauges (see Table  4 ), the metamodels are able to reproduce the model behaviour and they can be used for the construction of the numerical tsunami database.
, 2016) , which are strongly limited by the number of tsunamis scenarios they can consider and do not allow to explore, in a rigorous and complete way, the tsunamigenic potential of a seismic zone. Our approach proposes a completely new philosophy for THA and can be considered as an extension of the previous innovative work from  (Roshan et al. , 2016) , which first improves the classical deterministic approach by focusing its analysis on some selected earthquake source parameters. The numerical database (of nearly 50,000 tsunamis scenarios) allowed exploring the numerous uncertainties related to the characteristics of the AGFZ and most of the possible tsunamis scenarios should be represented. Moreover, this methodology of exploration of the tsunamigenic potential also permits to show some "unexpected" result: for instance, the strong oceanic scenarios impacting the northern gauges are not associated to the stronger seismic magnitudes; such result may not be identifiable through a classical deterministic approach.
Considering the rough zonation of the AGFZ and the shape of the magnitude frequency distribution of the tsunami heights, we proposed to attribute to each French Gauge a tsunamis hazard equal to the modelled tsunami height " m +2 m " with an associated uncertainty equal to the residual "+/-2 r ". This criterion was tested through a comparison with the tsunamis exceeding this hazard level (paragraph 4. 3) and with the tsunamis generated by a Lisbon-like 1755 earthquake (paragraph 4. 4). The latter representing a comparison between the global results from UQ and a more classical scenariobased approach. Globally, the hazard level issued by the total database seems robust and representative of the tsunamis from each single sub-zone once the uncertainty of numerical results is considered (see Figure  10 ), at least for French gauges off the Atlantic coast.
However, it must be noted that the choice of the hazard level is arbitrary and that further studies are necessary to validate this value. Moreover, the global database proposed in this study was built using the Monte-Carlo method and by considering that the seismic source input parameters are independent and uniformly distributed. Thus, an improvement of the methodology should consist in taking into account the dependencies between the seismic source parameters in the UQ and GSA steps. In conclusion, as reported in the introduction, the aim of this study was to illustrate the benefits of a methodology through a case study, which is not an operational assessment of tsunami hazard along the French Atlantic Coast. In fact, 5 tsunami hazard is analysed only off the French Atlantic Coast and by using, as input data for meta-model's construction, the deterministic simulations performed with a rough computation grid-resolution of 2'' degrees (~3.
Residuals on the testing database Residual analysis and R2 respect to the validation set. 6. 7 -9. 3 6. 7 -8. 3 6. 8 -9. 3 7. 7 -8. 9 7. 7 -8. 9 6. 7 -9. 3 Table  5 : Summary of the variation range of the seismic source input parameters for the design, the oceanic, the continental database and for the tsunami scenarios associated to the Gorringe bank and the Horseshoe bank (hypothesis from  (Duarte et al. , 2013)  and  (Grevemeyer et al. , 2017) ). *The global database is composed by the scenarios simulated with the metamodels (more then 50,000 tsunamis scenarios) for the construction of the oceanic and the continental database. **Seismic source parameters are assumed uniformly distributed and are randomly sampled for the construction of the Global database. 10.
Nat. Hazards Earth Syst. Sci. Discuss. , https://doi. org/10. 5194/nhess-2018-142 Manuscript under review for journal Nat. Hazards Earth Syst. Sci. Discussion started: 28 May 2018 c Author(s) 2018. CC BY 4. 0 License. numerical database constructed through uncertainty quantification. The objective of this analysis is to understand if the tsunamis height generated by a Lisbon-like earthquake are included, or not, in the range of the " m +2 m " water height of the global database.
23. 10 Nat. Hazards Earth Syst. Sci. Discuss. , https://doi. org/10. 5194/nhess-2018-142 Manuscript under review for journal Nat. Hazards Earth Syst. Sci. Discussion started: 28 May 2018 c Author(s) 2018. CC BY 4. 0 License. data base (Amari et al. , 1997): 1) Training set (80% of initial database scenarios)2) Validation set (20% of initial database scenarios).
Maximum water height associated to the construction (or design) database (data from (Antoshchenkova et al. , 10 2016)); ,  and Max correspond to the mean, standard-deviation and maximum modelled values. Nat. Hazards Earth Syst. Sci. Discuss. , https://doi. org/10. 5194/nhess-2018-142 Manuscript under review for journal Nat. Hazards Earth Syst. Sci. Discussion started: 28 May 2018 c Author(s) 2018. CC BY 4. 0 License.
Maximum water height associated to global database;  m ,  m and Max m correspond to the mean, standard-deviation and maximum modelled values. Nat. Hazards Earth Syst. Sci. Discuss. , https://doi. org/10. 5194/nhess-2018-142 Manuscript under review for journal Nat. Hazards Earth Syst. Sci. Discussion started: 28 May 2018 c Author(s) 2018. CC BY 4. 0 License. Nat. Hazards Earth Syst. Sci. Discuss. , https://doi. org/10. 5194/nhess-2018-142 Manuscript under review for journal Nat. Hazards Earth Syst. Sci. Discussion started: 28 May 2018 c Author(s) 2018. CC BY 4. 0 License.
Acknowledgments This study was performed through a cooperative research between the  Institut for Radioprotection and Nuclear Safety (IRSN)  and the  CEA , in the framework of the  French ANR-TANDEM research project. The authors want to thank  ENS Paris and particularly the Geology Laboratory  for their technical support on this project. We acknowledge especially  Eric Calais  for the availability of a part of team's cluster and  Pierpaolo Dubernet  for the help he offers to install Promethee. The present 5 work also benefits from the inputs of  Miss Hend Jebali  and  Dr. David Imbert  and from the valuable technical assistance of  Dr. Maria Lancieri ,  Dr. Yann Richet  and  Miss Ludmila Provost , who provided valuable technical assistance. Nat. Hazards Earth Syst. Sci. Discuss. , https://doi.
Nuclear data evaluation files in the ENDF6 format provide mean values and associated uncertainties for physical quantities relevant in nuclear physics. Uncertainties are denoted as D in the format description, and are commonly understood as standard deviations. Uncertainties can be completed by covariance matrices. The evaluations do not provide any indication on the probability density function to be used when sampling. Three constraints must be observed: the mean value, the standard deviation and the positivity of the physical quantity. MENDEL code generally uses positively truncated Gaussian distribution laws for small relative standard deviations and a lognormal law for larger uncertainty levels (>50%). Indeed, the use of truncated Gaussian laws can modify the mean and standard deviation value.
For some data, in particular independent neutron fission yields and some microscopic cross sections, the relative standard deviation can be high (more than 50%), and Gaussian laws naturally lead to negative occurrences, which is not acceptable for those physical quantities. Three constraints must therefore be respected when sampling: positivity of the physical quantity; its mean value; and its standard deviation. Often the positively truncated Gaussian law is used, which takes into account positivity but introduces a bias in the mean value and the standard deviation. Furthermore, it is not symmetric around the mean value. MENDEL  [5] , is the new generation of the CEA code system for nuclear fuel cycle studies. Its depletion solver is provided to the transport code systems APOLLO3 ®  [6]  and TRIPOLI-4 ®  [7].
Inspired by the abilities of contemporary autonomous vehicles to navigate with a high degree of effectiveness, the INSPEX Project 1 seeks to minaturise the sensing and processing technology involved, to produce devices which can help navigate within an environment in a smart way, enabling their use in a wide variety of applications. The project is focused on producing an advanced prototype for a device which can be attached to a VIB person's white cane, and which, through the use of a variety of minaturised sensors, and of the processing of their data via sophisticated algorithms, can offer the user a richer palette of information about the environment than the use of the unadorned white cane alone could furnish. The various strands contributing to the project are overviewed, and the prospects for further enhancements are contemplated.