dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgement The authors wish to thank colleagues from  JRC-Karlsruhe and CNRS-IPNO  for help and valuable discussions. This work was carried out with the  European Commission  financial support in the  Horizon 2020 framework program , under the collaborative projects "SAMOFAR", grant agreement number  661891  -SAMOFAR: A  Paradigm Shift in Nuclear Reactor Safety  with the  Molten Salt Fast Reactor and "SAMOSAFER", grant  agreement number  847527  -SAMOSAFER:  Severe Accident Modelling and Safety Assessment for Fluid-fuel Energy Reactors.
The peak in turbulent velocity is reached at a radial distance of 2 nozzle diameters, inside of the impingement zone. Wood  34  used a wall jet to model a thunderstorm downburst (air jet impacting with the ground). The velocity profiles were measured at different radial locations of the wall jet. Normalizing the curves with the parameters V re (maximum radial velocity at a given radial location) and Z 1/2 (half-thickness, where the velocity is half of V re ), it was seen that the profiles become stable (approximately self-similar) after a distance of 1. 5 D n from the central axis of the jet. Equation (  5 ) was found to adequately fit the normalized data from. 34 It was valid also for the data obtained at 0. 5 D n and 5 D n. V V re = 1. 55 z Z1 2 1 6 1 -erf 0. 70 z Z1 2 ( 5 ) Where V is the velocity at height z and "erf" is the error function, defined by: erf (x) = 2 π √ ∫ x 0 e -t 2 dt (6).
Acknowledgement The study was funded by the  Ministry of Education and Research  through  UEFISCDI  [project no. TE 123/2018-BACTERIOSENS  and project no. 255PED/2020 TOXINSENS ). The authors thank  Dr. Bogdan Trica  and  Dr. Elvira Alexandrescu  from  INCDCP-ICECHIM Bucharest  for the morphology analysis.
Characterization The following methods were used to identify the prepared Cubased catalyst. The crystalline phases of the nanopowders were identied by X-ray diffraction (XRD) (D2 Phaser, Bruker) with Cu Ka radiation (l ¼ 0. 15418 nm), a working voltage of 30 kV, and working current of 10 mA. Aer the diffraction studies, the obtained data were analyzed in MDI JADE 5. 0 soware and compared with the JCPDS card database. Scanning electron microscopy (FE-SEM, JEOL, JSM-7610F) was used to observe the surface morphology of the nanopowder. The working voltage was 30 kV and the working power was 10 mA. The particle size and morphology were identied by transmission electron microscopy (TEM) (Japan Electron Optic Co. Ltd. , JEOLTM, JEM-2100F, Tokyo, Japan) at an operating voltage of 200 kV and pressure of 10 À8 Pa.
Acknowledgements This research was funded by the  Ministry of Science and Technology of Taiwan  ( MOST 108-2221-E-027-056 ,  MOST 109-2221-E-027-068- ,  MOST 109-2222-E-027-001- and  MOST 109-2221-E-027-059- ) and the  National Taipei University of Technology-University of Science and Technology Beijing Joint Research Program  ( NTUT-USTB-105-7 ). The authors are grateful to the  Precision Research and Analysis Center of the National Taipei University of Technology (NTUT)  for providing the measurement facilities.
Acknowledgments The authors acknowledge  Pierre Alcouffe  and the  Consortium Lyon Saint-Etienne de Microscopie (CLYM ,  FED 4092 ) for the access to the microscopes. This work was supported by a grant overseen by the  French National Research Agency (ANR)  as part of the  "Investissements d'Avenir" Program  ( ANE-ITE-002-01 ). This manuscript is in honor of the 50 year anniversary of the  French Polymer Group (Groupe Français des Polymères -GFP ). This work is also dedicated to  Professor Jean-Pierre PASCAULT , famous scientist of thermosetting polymers. He was a friend of ours.
ACKNOWLEDGMENTS We acknowledge the work of  Wanqing Zhang  and  Andrea Yeap  for their assistance with experiments. Research funding for this project awarded to M. S. T. , E. M. , and Z. -X. L. is from the  Australian Research Council  (grant  DP190100827 ). Elements of this research used equipment from the  Queensland node of Metabolomics Australia  funded by  Bioplatforms Australia , an  NCRISfunded initiative.
Acknowledgement The experimental work was supported by the  French research agency  ( Association Nationale de la Recherche et de la Technologie ANRT ),  Renault S. A. , and PPRIME Institute during the Ph. D. thesis of  M. Ben Houidi  (CIFRE N: 384/2010 ). The simulation work was supported by  King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR)  with funds given to the  Clean Combustion Research Center. We acknowledge funding from the  KAUST Clean Fuels Consortium  and its member companies.
Every 2D diffraction image was converted to 1D powder diffraction pattern using the nDTomo and PyFAI soware package  66, 67  with implemented trimmed mean lter (10%)  68  to remove the artefacts due to hot spots of (single) crystalline material. The data integration was performed with fast GPU processing. 69 The reconstructed images were obtained using the ltered back projection algorithm. The collected data were corrected in respect to synchrotron current. The analysis of diffraction data was performed with Topas 5 soware. 70 he XRD mapping measurements (i. e. YZ grid) were collected with 40 mm translation step, 500 mm z step and 50 ms of exposure time. Each XRD map consisted of 150 columns (translation steps across the reactor) and 14 rows (z steps). Time of measurement for one complete XRD map was $5 min.
In the case of the last reaction mixture (POX3), only ve XRD-CT datasets were collected due to experimental time limitations. Fig. 8  shows the distribution maps of CeO 2 , Pd-Ni and graphite, based on normalised scale factors, as well as the distribution of lattice parameter and crystallite size of metallic Ni. The changes of note include the disappearance of the Pd-Ni phase, which is quite noticeable at the end of POX1 reaction and occurs predominantly at the reactor inlet (Fig. S17  in the ESI †). The Pd-Ni peak was seen to continuously shi towards higher scattering angles during the reaction, at the same time becoming broader and of lower intensity. This phenomenon could be explained through the temperature-driven incorporation of Ni in the Pd-Ni structure resulting in the formation of a large spread of solid solutions with different Ni/Pd ratios  85, 86  (Fig.
e. particles cracking) and density (i. e. particle expansion) (Fig. S25 -S26 in the ESI †). Therefore, the apparent overall decrease in scattering signal intensity of all other catalyst components during the POX2 and POX3 reaction mixture is associated with a decrease in the density of the catalyst particles. To gain further insight into the evolution of graphite and Ni crystallite size, a binary mask was created for each dataset based on the ZrO 2 distribution maps presented in Fig. 10A  and applied to the graphite and Ni crystallite size maps. The average values for each dataset were calculated and the results are plotted in Fig. 10B. It can be clearly seen that the graphite forms and grows predominantly at the regions of the catalyst particles where CeO 2 -ZrO 2 is absent. However, it can also be seen that although CeO 2 -ZrO 2 can provide enhanced resistance to graphite it cannot prevent its growth (Fig.
NiAl 2 O 4. Although the structures of Al 2 O 3 , NiO and NiAl 2 O 4 possess overlapping reections (Fig. 3, bottom panel), when using the Rietveld analysis it was possible to identify the presence of the NiAl 2 O 4 phase and the corresponding disappearance of NiO 36 (see Fig. S5 in the ESI †). Aer reaching 800 C, three XRD-CT datasets were collected at different positions in catalyst bed: reactor inlet, middle of.
Acknowledgements Dorota Matras  and  Antonis Vamvakeros  were supported through funding received from the  European Union   Horizon 2020 research and innovation programme  under grant agreement no. 679933  ( MEMERE  project). Andrew M. Beale  acknowledges  EPSRC  (grants  EP/R026815/1  and  EP/S016481/1 ). We acknowledge the  European Synchrotron Radiation Facility  for beamtime.
Numerical database • Hertz-Chandrasekhar solution A Monte-Carlo simulation tool has been developed in MATLAB© to create computational volumes where droplets are uniformly randomly distributed in a 3D cube. The mean droplet number density ( 3 ), the number of droplet (  ) and the side length of the computational volume (  ) can vary according to the desired configuration. The analysis makes also appear a mean number of droplets per unit surface or, in other words, a mean surface density number  2.
Conclusions The Mie scattering measurement technique implemented on the PROMETHEE experimental test rig provides two-dimensional images when a three-dimensional flow is observed, which induced some bias. In this paper, results of numerical simulations obtained from a Monte-Carlo code and from DNS-DPS of isotropic uniformly turbulent two phase flow simulations have been processed in order to evaluate these biases. It was found that the 3D restriction bias generates a maximal error of 10 % on the mean and standard deviation of dnn but it decreases when the droplet number density increases. Moreover, for both uniformly randomly spatial distribution and preferential segregation distribution, the distributions are similar in two and three dimensions. Further work will be done to extend theses numerical results on the experimental data and to extend the research about the influence between laser sheet thickness, length scale turbulence and droplets clusters/voids size.
Acknowledgments The work has been realized thanks to the partial financial support of the " Région Occitanie ". The numerical simulations were performed on the supercomputer Olympe (CALMIP) using time available under project  P0111  and on the supercomputer Occigen (CINES) under the allocation  A0082B0612. Nomenclature : droplet density number : mean nearest-neighbour inter-droplet distance : standard deviation of nearest-neighbour inter-droplet distance : dimensionless mean nearest-neighbour inter-droplet distance : dimensionless standard deviation of nearest-neighbour inter-droplet distance.
For gamma-IAD (dose 100 Gy), one spectra accumulation was applied, for alpha-IAD (estimated dose 12 Gy), 16 accumulations were performed. For the two samples, each after gamma and alpha irradiation, the spectra were measured at different time after exposure at several values of mw power. Between measurements, the samples were stored in a dark place in closed tubes in ambient room conditions. One day after irradiation, when the spectra are stabilized after aging, measurements were performed for all six samplesthe three samples after gamma irradiation and the three samples after alpha irradiation. For the analysis and processing of the spectra of IAD, a computer program was used created in the language Visual Basic (Microsoft). It was based on the early developed program, which uses the nonlinear leastsquares method with Marquard-Levenberg modification  (Marquardt, 1963)  to fit an experimental spectrum by a simulated spectrum in analytical form and used for dose determination in tooth enamel  (Ivannikov et al.
Acknowledgements This work is supported by the  Russian Foundation for Basic Research  [grant numbers  15-58-45050 IND_a ,  16-04-01276  A]; and the  Ministry of Education and Science of Kazakhstan  [N • AP05135470]. We are very grateful to the research group of  E. Sagstuen  ( M. Heydari ,  E. Malinen ,  E. Hole ) ( University of Oslo ) for possibility to use their simulated spectra of components of alanine radicals.
49297 Å). Samples were loaded in 0. 2 mm capillaries and data was collected (step size = 0. 0036°) in transmission mode using a Mythen II detector. The exact wavelength and instrument resolution parameters were determined from LaB 6 powder (NIST) and Si standard (Si 640d) sample measurements recorded under identical conditions. Neutron diffraction experiments were carried out on the highresolution D2B neutron diffractometer at the Institut Laue-Langevin (ILL, Grenoble, France) using a monochromatic neutron beam with a wavelength of λ = 1. 594 Å. In situ high-temperature neutron powder diffraction experiments were performed using a standard niobium furnace operated under vacuum conditions (10 -4 -10 -3 mbar) and data was recorded at three different temperatures, 25 °C (RT, fresh), 1350 °C, 1000 °C, and a repeated measurement at 25 °C (RT, after cooling).
The counting time for collecting each pattern was 5-6 h. Rietveld structural refinement of data was performed using the FullProf Suite software. [55] The peak profiles were modelled using a pseudo-Voigt function. Scale factor, atomic positions, occupancies, isotropic (synchrotron XRD), and anisotropic (neutron diffraction) atomic displacement parameters at different temperatures were refined. BVS calculations were carried out to estimate the valence (oxidation state) of atoms and further to validate the correctness of the structural model. [56, 57] igh-resolution scanning transmission electron microscopy, HAADF-STEM images and STEM-EDS elemental maps and analysis were obtained using a FEI Titan Themis (300 kV) equipped with a hexapole-type aberration corrector for a scanning transmission electron microscope (CEOS DCOR) and a super EDX system.
In addition to the cooling water circulation, cold compressed air was blown onto the IR-furnace heating elements and the outer quartz tube to avoid overheating. The gas flow rates of Ar (99. 998%), CO 2 (99. 995%), and synthetic air were controlled by electronic mass flow controllers (Bronkhorst, EL-FLOW). The LabView (National Instruments) software platform was used to operate electronic mass flow controllers and actuated valves (Swagelok) along with program automation and data acquisition, thus controlling desired gas flow rates in "mL min -1. " A pressure sensor (PSE54, SMC) measured the differential pressure of the reaction gas stream at the exit of the furnace. The product gas leaving the inner quartz tube was continuously analyzed using a Siemens Ultramat 23 gas analyzer. The Ultramat 23 used herein was equipped with a 3-component gas analyzer, comprising of an electrochemical O 2 sensor (0-5 vol%) and two IR-active gas detectors for CO (0-2 vol%) and CO 2 (20-100 vol%).
Acknowledgements The authors acknowledge financial support by the  Swiss National Science Foundation  (SNSF, Grant Nr. 200021-162435/1 ), the  European Union 's  Horizon 2020 research and innovation programme  (Project  SFERA-III -Grant Nr. 823802 ), and the  University of Zurich Research Priority Program (URPP) for Solar Light to Chemical Energy Conversion (LightChEC). The authors would like to thank  Dr. Nicola Casati  ( MS-SLS, PSI ) for help with the synchrotron XRD measurements.
He has successfully supervised 16 Ph. D. students. He has published more than 290 scientific articles, H-index 39 (Google Scholar). Citations 2632 (Scopus), and 3333(Google Scholar). He has been the Coordinator of the H2020 MSCA-ITN network and a Research Partner for FP7, H2020, ESA, EIT-Health, and IT manufacturing projects. His research interests include electrochemomechanically active polymer composite materials, computational materials, ion-polymer batteries, robotics, and space applications. Saoni Banerji received the M. Sc. degree in electronics from Nanyang Technological University (NTU), Singapore, in 2014, and the Ph. D. degree in electronics engineering from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, in 2017, with an FI AGAUR grant from the Catalonian government in the fields of microelectromechanical systems (MEMS) design and circuits and designing control architectures for MEMS sensor signal conditioning.
Acknowledgments The authors would like to thank  T. Quirante  and  N. Vieira-Nobre  from  Akira Technologies  for providing the geometry and operating conditions, and  N. Buffaz  and  A. Paillassa  from  Safran Helicopter Engines  for their technical support on the generation of the reduced-count geometry of the compressor and for performing its respective Reynolds-Averaged Navier-Stokes simulations. The authors are also grateful to  G. Exilard  and  S. Richard  from  Safran Helicopter Engines  for his help during the setup of the perforations in the combustion chamber.
Funding: The authors acknowledge the financial support from the  CNRS  through the  MITI interdisciplinary programs (PRIME 2020 :  ExtraMet  project), the  Agence Nationale de la Recherche  through the  RECALL  project ( ANR-20-CE04-0007 ), the  SILEXE  project ( ANR-13-CDII-0010 ) and the  Labex Project CheMISyst  ( ANR-10-LABX-05-01 ).
To maintain the constant temperature k B T = ϵ, the system was coupled to a Langevin thermostat with γ = 0. 1τ -1 , where τ = σ(m/ϵ) 1/2 and m is the monomer mass. The equations of motion of the system were integrated with the time step Δt = 0. 005τ. MD simulations were performed using the HOOMD-blue simulation package  50, 51  on graphics processing units (GPU's). A typical MD run consisted of an equilibration phase with 10 7 integration time steps and a subsequent up to 10 8 steps long production phase. During a production run, monomer densities ρ(z) were measured on an equidistant grid along the z-axis with the step Δz = 0. 01σ, whereas polymer center-of-mass densities ρ CM (z) and polymer conformational properties (see Section 5) with the step Δz = 0. 1σ.
The main contributions of the present work can be summarized as follows:• A finite element framework devoted to both 2D and 3D multiphase flows with non-Newtonian materials is presented and applied to viscoplastic dam-breaks for which inertial effect are negligible; • New 2D and 3D viscoplastic dam-break simulations for both cylindrical and prismatic columns are performed for a wide range of initial column aspect ratio (1-20) and Bingham number (0. 003-0. 3). New viscoplastic dam-break experiments are equally carried out using Carbopol, Mayonnaise, and Ketchup. These new numerical/experimental results contribute to the enrichment of the literature database; • The presented numerical results are explored through energy budget analyses, which clearly indicate the existence of three different spreading regimes: (1) a plastic regime; (2) a mixed visco-plastic regime; and (3) a viscous regime; • The identified dam-break regimes are expressed by energybudget-based scaling laws through which both the final front position and the final column height are predicted; • By manipulating the new scaling laws mentioned above, it is shown that the experimental/numerical results carried out for the present work, as well as those obtained from the literature, collapse along a single trajectory according to which both the final front position and the final column height are functions of (.
Acknowledgements We would like to thank  Mrs. Camila Borgo  for her great help with the experiments performed here, as well as  Prof. Malcolm R. Mackley  ( University of Cambridge ) and  Dr. Simon A. Butler  ( University of Cambridge ) for some of the rheological measurements displayed in Table 2, and  Dr. P. Saramito  and  Dr. P. -Y. Lagrée  for fruitful discussions. We also would like to acknowledge support from the  FUI   COMCEPT  project, France and thank the  PSL Research University, France  for its support under the  program 'Investissements d'Avenir ' launched by the  French Government  and implemented by  ANR  with the reference  ANR-10-IDEX-0001-02 PSL.
1 Bn - 1 11 The main contributions of the present work can be summarized as follows:• A finite element framework devoted to both 2D and 3D multiphase flows with non-Newtonian materials is presented and applied to viscoplastic dam-breaks for which inertial effect are negligible; • New 2D and 3D viscoplastic dam-break simulations for both cylindrical and prismatic columns are performed for a wide range of initial column aspect ratio (1-20) and Bingham number (0. 003-0. 3). New viscoplastic dam-break experiments are equally carried out using Carbopol, Mayonnaise, and Ketchup. These new numerical/experimental results contribute to the enrichment of the literature database; • The presented numerical results are explored through energy budget analyses, which clearly indicate the existence of three different spreading regimes: (1) a plastic regime; (2) a mixed visco-plastic regime; and (3) a viscous regime; • The identified dam-break regimes are expressed by energybudget-based scaling laws through which both the final front position and the final column height are predicted; • By manipulating the new scaling laws mentioned above, it is shown that the experimental/numerical results carried out for the present work, as well as those obtained from the literature, collapse along a single trajectory according to which both the final front position and the final column height are functions of (.
Indeed, temporal tracking, which is made possible by the high acquisition frequency, allows for a good reconstruction of the fields during a cycle. Parametric interpolation is, however, limited by this type of measurement, which can only retain a limited number of cycles; the convergence of average speeds is not sufficient in this case. The interpolation can also be done between 2D velocity fields to reconstruct a 3D field  [33]. In this experimental study, 2D PIV data that was measured from a transparent engine was used. The flow was observed several times at a given instant of the cycle for different VVT offsets. The 300 observations allowed for obtaining a representative mean velocity field of the flow and thus created usable reconstructed fields after parametric interpolation. The paper is organized as follows.
The spatial resolution was about 68 µm/pixel. The synchronization of these devices was performed using a controller (Dantec Synchronizer) that took the signal of the engine encoder as input. The measurement started after the rotation speed of the engine was stable. It then took 300 pairs of images corresponding to 300 engine cycles at the desired crank angle. An adaptive cross-correlation PIV algorithm from Dantec DynamicStudio software is used to process the pairs of images. The interrogation area went from 32 × 32 to 64 × 64 pixels according to the particle density and a grid step size of 16 × 16 pixels is used. For each instantaneous velocity field, 71 × 59 instantaneous velocity vectors were finally provided with a spatial resolution of 1. 08 mm.
Interpolation As noted above, the first six modes of the POD could be used to reconstruct the mean velocity field of the tumble motion with good accuracy. The objective of interpolation is to generate the mean field for a VVT offset value outside the POD database decomposition for values different than {0, 10, 20, 30}. In order to validate the method, additional measure- ments were taken for θ VVT = 25, which was a value outside the POD decomposition. As a reminder, the new POD basis was calculated at each crank angle of the experimental plan (Table  1 ) for θ VVT = {0, 10, 20, 30}. Supplementary fields were measured for θ VVT = 25 • CA at three angles θ = {130, 220, 270}. Therefore, it was possible to compare the average field measured for this value of VVT to the interpolated field using the POD.
Three interpolation methods were compared: linear, polynomial (pchip in Matlab) and spline (piecewise-defined function with polynomials) interpolation. Figure  13  shows the evolution of the average coefficients of the POD that were interpolated by following these three methods. As in the previous section, the center position and rotation rate of the tumble were used to compare mean and interpolated fields. Table  3  presents the results for the interpolation at θ VVT = 25 • CA. We observed that the linear interpolation gave the best results. Differences in the center position are low with a maximum deviation of 2 points for the y value of the 270 • CA flow field. The mean error in the tumble rotation rate was 4. 16%. Therefore, the interpolation provided a good estimation of the mean field.