dataesr/scientific-paragraphs-categorization huggingface dataset:
Evidently, the absence of the key compounds in the database leads to an inaccurate molecular representation of the mixture. Depending on the type of mixture that is considered, a different molecular library has to be selected. The database is therefore created from qualitative analytical information and expert knowledge. As mentioned in Section 4. 1. 1, advanced analytical techniques can provide molecular-level information. This information can be a qualitative identification of the molecules for light mixtures, such as gasoline, or the identification of the molecular structures for more complex feedstocks, such as middle distillates or vacuum gas oils. Thus, the predefined database can be defined as a set of molecules, as proposed by  Allen and Liguras (1991)  or as a library of molecular structures, such as the SOL (Structure Oriented Lumping) approach proposed by  Quann and Jaffe (1992)  or the MTHS (Molecular Type and Homologous Series) method proposed by Peng (1999) and  Zhang (1999).
Whatever the predefined database, the pure component properties of its compounds are required. For light compounds, pure component properties are often available in thermophysical properties databases, such as the NIST Chemistry WebBook  (Linstrom and Mallard, 2015) , TRC  (Frenkel et al. , 2000)  or the DIPPR  (Daubert and Danner, 1989). If the pure component properties are not available, they can be calculated either by inspection of the structure of the molecule, to assess chemical formula and molecular weight, by correlations, or by group contribution methods, which are frequently used to estimate normal boiling points, densities, and critical properties  (Benson, 1976; Benson and Cohen, 1993; Constantinou and Gani, 1994; de Oliveira et al. , 2013a; Hudebine and Verstraete, 2011; Joback and Reid, 1987; Marrero-Morejón and Pardillo-Fontdevila, 1999).
Once the database of compounds is defined and the analytical and physical constraints have been set up, the mole fraction of each compound needs to be determined. This is generally done by minimizing the difference between the available quantitative analytical data and the properties calculated from the composition of the synthetic mixture. Even using linear mixing rules, the estimation of the mole fractions is often an ill-defined problem because the number of unknowns (mole fractions) largely exceeds the number of observables (analytical data). To reduce the number of unknowns, several techniques have been proposed in the literature. Allen and Liguras (1991)  apply a constrained Simplex method to minimize a weighted criterion using the enthalpies of formation of the molecules as weights, yet respecting analytical constraints.
Jaffe et al. (2005)  suggest the minimization of a specific criterion using a Lagrange multiplier method. Zhang and co-workers  (Ahmad et al. , 2011; Aye and Zhang, 2005; Peng, 1999; Wu and Zhang, 2010; Zhang, 1999)  developed an approach to estimate the mole fractions of a mixture from their overall properties by interpolating into a database of well-characterized mixtures. Recently, Pyl and coworkers  (Pyl et al. , 2011)  use the parameterized probability functions to describe the distribution of mole fractions in the compounds. The deterministic molecular reconstruction approach is the most efficient of the reconstruction methods. Its conception is based on a large set of analytical data and few assumptions are needed concerning the presence or absence of a compound in a mixture. Moreover, this method is usually quite fast in determining a molecular composition of a mixture.
However, this approach suffers from two shortcomings. Firstly, the development of the predefined databases is a very time-consuming and expensive task because of the advanced analytical tools that are needed to obtain the molecular information. Of course, once these databases are created, the determination of the molecular composition of new mixtures is fast, but the initial analytical work remains an extremely limiting factor. Secondly, this approach cannot be applied to the very complex mixtures for which no analytical technique is currently powerful enough to identify the chemical structure of the most abundant chemical species contained in these mixtures. This is typically the case for petroleum residues or biomass fractions.
11). The maximization of the criterion is performed by combining the Lagrange multiplier method and the conjugate gradient optimization method. This method was successfully applied to LCO gas oils  (Hudebine, 2003) , FCC gasolines  (Hudebine and Verstraete, 2011)  and steam cracking naphthas  (Van Geem et al. , 2007). E ¼ À X N j¼1 x j lnðx j Þ ð 9Þ with X N j¼1 x j ¼ 1 ð10Þ and  Illustration of the SR method for creating an asphaltene molecule  (Neurock et al. , 1994). F k x ð Þ ¼ P k k ¼ 1; K ð11Þ where E represents Shannon's information entropy, N is the number of molecules present in the predefined database of molecules, x j represents the mole fraction of molecule j, x is the vector of mole fractions x j , P k is the value of analytical property k, F k is the mixing rule for analytical property k, and K is the number of analytical properties or constraints.
In order to extend the REM method to more complex mixtures, IFPEN developed a two-step reconstruction (SR-REM) method in which REM has been coupled to a SR method  (Hudebine and Verstraete, 2004; Hudebine, 2003). The SR method is first applied to generate an equimolar database of molecules that are typical for a given mixture. The REM method is then used to improve the mixture properties of the previously generated set of molecules by modifying their molar fractions. The SR-REM method overcomes the drawbacks of both reconstruction methods. The SR method is a very constrained method that creates an equimolar mixture, by generating molecules that are always typical of the studied mixture due to the use of specific molecular attributes and building rules based on analytical information and expert knowledge, but at final convergence, it only approaches the analytical data.
In contrast, the REM method is a fast technique to obtain a mixture whose properties closely match the analytical data, but it needs a particularly well-defined initial set of molecules  (Hudebine and Verstraete, 2004). Two different SR-REM algorithms were developed at IFPEN: a direct algorithm and an indirect SR-REM algorithm (de  Oliveira, 2013; de Oliveira et al. , 2013a,c; Hudebine and Verstraete, 2004). The direct SR-REM algorithm (Fig. 9a ) consists of applying the SR and REM methods as two consecutives steps to reconstruct a mixture. Thus, an equimolar database of molecules is generated for each studied mixture which is then submitted to REM method to improve the mixture properties. However, as SR step of this reconstruction method uses a MC approach to generate its initial set of molecules, the direct SR-REM still remains a computationally-demanding algorithm.
The indirect SR-REM algorithm (Fig. 9b ) was therefore developed and may be applied when a large number of mixtures of a given type need to be represented. The idea behind this algorithm is to generate a large reference database of representative molecules for a type of mixture once and for all. Subsequently, only the REM step is employed, requiring only a few seconds of CPU time. For each mixture, the REM step starts from this reference database to obtain a new set of molecules whose properties are very close to those of the mixture to be represented. All synthetic mixtures will now contain the same molecules as the reference database, but with modified mole fractions. The SR-REM method was developed for and validated on LCO gas oils  (Hudebine and Verstraete, 2004; de Oliveira et al. , 2012; López Abelairas et al.
According to their classification, empirical methods are based on pre-established reaction libraries and expert systems. Examples of such databases were already underway in the 1960s  (Vleduts, 1963)  and continue to be developed  (Ihlenfeldt and Gasteiger, 1996). Semi-formal techniques are based on heuristic algorithms that generate reactions, either overall reactions or elementary steps, in a network from a few basic reaction types, but do not have selection procedures to remove improbable reactions from the set of conceivable solutions. Formal techniques generate the various elementary steps at the mechanistic level by taking into account the physical and chemical description of the molecule, and select the most probable elementary steps to be retained in the final network from all possible steps.
The developed algorithms were inserted in the École Polytechnique de Montréal 2D RANS code NSCODE. Verification of the interpolation schemes were made in Pigeon  47  and the methods robustness was shown for a multi-element airfoil slat/gap optimization problem. 48 ❡ ❡ ★ ★ ★ ★ ★ ★ ★ ★ ❍ ❍ ❍ ✏ ✏ ✏ ✏ ✏ ✡ ✡ ✡ ✡ ✡ 'receptor' cell center 'donor' cell center B A C M A C B D P M Q e 2.
In this context, the DES (Detached Eddy Simulation 76 ), DDES (Delayed Detached Eddy Simulation 77 ) and IDDES (Improved Delayed Detached Eddy Simulation 78 ) approaches have been implemented. An example of DDES around a supercritical wing using NSMB can be found in the AIAA paper by Grossi et al  79  , in the context of the European research program ATAAC, Advanced Turbulence simulations for aerodynamic application challenges, http://cfd. mace. manchester. ac. uk/twiki/bin/view/ATAAC/WebHome. A considerable improvement of the detached eddy simulation has been accomplished within NSMB by implementing the OES modelling in the URANS part of the DES and DDES in case of fixed and moving bodies including fluid-structure interaction  7, 80. The DDES-OES modelling has been coupled with the ALE -Arbitrary Lagrangian-Eulerian Method 81 accounting for mesh movement and deformation during the fluid-structure interaction process for moving/deforming configurations.
V. C. Results Rime icing is simulated on a NACA23012 airfoil and compared with experimental result from Broeren et al. 98  The O-grid mesh is generated by NS-GRID software presently developed by Ecole Polytechnique de Montreal. NS-GRID is an elliptic smoothing mesh generation code that control orthogonality, skewness and spacings via control functions. 91 The NACA23012 mesh has a chord of c = 1. 828m and contains 512 × 256 cells divided into two blocks with a farfield extended to 50 chords. The parameters of the simulations are an angle of attack of 2. 0 • , the Mach number is M a = 0. 24, the Reynolds number is Re = 12. 60 × 10 6 , the freestream temperature is T = 247. 85K, the median droplet diameter is d = 30µm, the liquid water content is LW C ∞ = 0. 55g/m 3 and the total icing time is 600s.
Here, only results concerning the effect of initial conditions are discussed. The dataset is as listed in table 1, all referring to the medium mesh and using the steady solver with the SA-Edwards turbulence model. The trend of the lift coefficient is plotted in figure  26  for the three initial conditions. The difference between the initial conditions occurs only after α = 21 o. After this angle-of-attack, the lift is overpredicted with the results initialized from freestream, whereas the opposite occurs with the initial condition set at 16 degrees. The global trend of the lift differs from that observed in the experiment. The stall curve presents a drought around 20 degrees before the maximum lift for all initial conditions. An examination of the wing surface pressure distributions shows that this drought is related to the fuselage/wing junction.
VII. Recent developments for hypersonic flow simulations NSMB code was from the start of its development designed for use for hypersonic applications (in particular re-entry space vehicles). NSMB includes different levels of chemistry modeling for Air, CO2 and N2. Available models for air consider 5, 7, 11 or 13 chemical species, and a large number of non-equilibrium chemistry models are available, among them the models of Park 1989,  106  Park 1993,  107  Park 2001,  108  Gar-diner  109  and Dunn and Kang 110 are available. For all these models the equilibrium constants for the chemical reactions are computed using the polynomials provided in the references. Chemical equilibrium can be computed using polynomials (TGAS 111 /VGAS 112 ), or by calculating the chemical composition for equilibrium.
Rigid-Rotor and Harmonic Oscillator models have been implemented -Multi-temperature lookup tables for high fidelity models based on quantum mechanics -High fidelity curve fits, and in particular the NASA 7 and 9 coefficient polynomial data bases • Multicomponent Transport Properties -Use of collision integrals for each collision pair of species in the mixture -Wilke, Gupta-Yos, Armaly-Sutton and Blottner mixture rules -State of the art methods to solve the system, LDLT for direct solution and Conjugate-Gradient for iterative solution • Finite Rate Chemistry in Thermal Non-equilibrium • A highly robust Multiphase Equilibrium solver (not used by NSMB). In the next phase of the project an engineering model will be developed to account for both carbonbased TPS ablation and catalysis. These models will be updated and refined using experiments carried out at the Von Karman Institute in Belgium.
VIII. Conclusion Since the last AIAA paper describing the NSMB solver 1 , the NSMB developpers consortium has been reduced but the development of the this code is still on-going and many major improvements have been performed in the last few years : an fully automatic chimera method for moving bodies, an icing model, many turbulence models for unsteady flows and new models for hypersonic flows. All these developments have been successfully applied to various flow configuration allowing the NSMB solver to be one of the most powerfull research CFD solver in Europe.
3. 1. 1 Verrous logiciels Différents serveurs OPC peuvent être déployés et utilisés afin de répondre aux exigences du sujet présenté dans cet article (CODRA Composer OPCServer, Matrikon OPC, Resolvica OPC, SV OPC. ). Ces serveurs font l'objet de comparatifs dans différentes revues consacrées à l'informatique industrielle depuis plusieurs années. Notre choix s'est porté sur une solution proposée par Iconics [10], société internationale qui commercialise des environnements de développement répondant aux problématiques de la Fig. 3  avec différents "packages". Cette solution fonctionnera en partenariat avec le serveur PhoenixContact. AX-Server. 21 afin d'associer l'ensemble des Items. Pour pouvoir lier les différents clients au serveur OPC, il faut également installer le logiciel Cogent DataHub  [11].
Cogent DataHub permettra d'associer via le serveur OPC Iconics, les clients n°2, 3 et 4 (Fig. 4 ). Le client n°2 utilise un logiciel du pack Office. Différents essais relatifs à l'application ont été validés avec des versions différentes (XP-Pro, 2010-Pro et 2013-Pro). Cependant, il faut apporter une attention particulière pour les versions 32bits ou 64bits. Le client n°3 utilise la version de Matlab R2014a avec la toolbox OPC. Le client n°4 supporte le système d'exploitation Androïd. C'est une tablette de type grand public. La communication avec les différents services hébergés dans l'ordinateur relié au réseau s'effectue à partir du routeur Wifi qui aura été préalablement configuré (Fig. 4 ).
DEVELOPPEMENT ET UTILISATION DES DIFFERENTS CLIENTS L'objectif de cet article n'est pas de présenter l'ensemble des résultats issus de nos différents tests. Les résultats significatifs pour les quatre clients sont présentés ci-dessous. Ils apportent de nombreux éclaircissements sur les outils disponibles sur "étagère" et ce que nous pouvons en faire pédagogiquement avec nos étudiants. Pour permettre un lien dynamique entre les informations émanant du terrain (Entrées-Sorties, …) et la solution de "reporting" avec Excel, il faut au préalable s'affranchir de plusieurs couches logicielles associées à des paramètres. La première couche consiste à lancer le serveur OPC adéquat. L'ordinateur utilisé dans le cas présent, dispose de plusieurs serveurs installés dans un environnement de contrôle et de configuration : ICONICS OPC DataSpy.
Le client n°3 La Toolbox OPC de Matlab (R2014a) permet de fournir une connexion aux serveurs OPC DA 12 et OPC HDA 13. Cette connexion permet de lire, écrire et enregistrer des contenus d'Items à partir de différents périphériques tels que, les systèmes de contrôle-commande distribués, les systèmes de surveillance et d'acquisition de données… Le client n°3 peut donc récupérer des informations issues de notre application. Il pourra également par la suite et si besoin, effectuer de nombreux traitements algorithmiques spécifiques déjà implémentés. La Fig. 17    La Fig. 18  présente les résultats sous Simulink (à noter que les essais n'ont pas été menés au même moment que les essais précédents). Afin de qualifier la démarche de travail, la campagne de mesures a également été menée sur une plage temporelle de 120 secondes.
CONCLUSION ET PERSPECTIVES Cet article tente de présenter différents aspects fondamentaux en matière d'environnement de type SCADA. La solution matérielle utilisée n'est pas classique (Bluetooth à vocation industrielle), même si les solutions opérationnelles à destination des applications industrielles sans fil sont aujourd'hui et depuis quelques années nombreuses (modem radio, pont Ethernet wireless, Zigbee, XBee Pro…). Cette première approche de travail à vocation pédagogique dispose de plusieurs avantages : montrer et démontrer les spécificités d'un client-serveur OPC ; montrer que le logiciel Excel peut réaliser assez simplement des animations dynamiques permettant une possible orientation d'application d'Interface Homme-Machine. Ce travail permet également d'aborder la gestion des mots de passe, gestion difficile à organiser dans un monde en très grande partie numérique aujourd'hui.
Néanmoins et au-delà de la configuration matérielle (sujet de travail à part entière), nous montrons que pour aboutir au résultat, il faut respecter un ensemble de procédures et de compétences liées au métier de l'informatique industrielle. Ce travail est proposé à nos étudiants de licence professionnelle Supervision des Automatismes et des Réseaux sous la forme d'un mini-projet d'une durée de 12 heures. L'intégralité de la partie matérielle est à leur disposition. L'ensemble des logiciels est installé sur 7 postes de travail (montés en réseau). Chaque binôme devra : -développer l'application hébergée dans l'API (A), sous PC WORX (V6. 0 SP2), répondant au cahier des charges de la Fig. 7 , -déclarer l'ensemble des Items OPC (Tableau 1), -déclarer un client sous Cogent-DataHub, -développer la solution de "reporting" sous Excel, -développer un client sous Matlab, -effectuer une campagne de mesures en validant l'intégralité du dispositif.
Unlike CUDA, which is only available for NVIDIA GPUs, OpenCL allows access to multicore accelerators of many brands. We will not describe here the philosophy of OpenCL and the full details of the DG implementation, but refer readers to previous works  [20, 24]. We have also implemented an OpenMP version of the same algorithm for use when OpenCL is not available and for verication and comparisons. The resulting software schnaps can be found at schnaps. gforge. inria. fr. In contrast to our previous works we have also provided additional features, such as a macrocell strategy for managing the DG mesh: the connectivity of the mesh is described at a macro level with H20 quadratic hexahedrons 2 with control points on each vertex and in the middle of each edge, allowing for curved elements in physical space via a non-linear transformation.
This allowed us to successfully validate the Vlasov-Poisson implementation in SELALIB. The SL/FE method was able to use much larger time-steps than the nite volume method, making the SL/FE method more ecient for the test cases considered. The schnaps DG solver, which we present at an early stage of development, has more stringent time-step stability constraints, but is able to accommodate more complex geometry than a standard SL/FE method. schnaps also makes use of the OpenCL programming language to make use of GPUs and co-processor boards, which may allow for a higher degree of parallelization. Complex geometries and unstructured, high order meshes can be more easily handled with the DG method.
Future Work The SL/FE method, implemented in the SELALIB library, is part of an established software project. Future work for the SL/FE method includes implementation in 3D and the addition of a gyrokinetic (eg drift kinetic) model in order to capture complex ow regimes while mitigating the eects of the curse of dimensionality. The DG method, implemented in schnaps, is in an earlier stage of development. In it current state, it can be used to solve general hyperbolic conservation equations in two and three dimensions, and is parallelized with OpenMP and OpenCL. However, the parallelization is optimal when the number of conserved quantities (eg the number of velocities) is small, and we expect to be able to achieve much better performance by modifying the parallelism and improving the coalescence of memory access when dealing with the Vlasov equations with a large number of degrees of freedom in velocity.
Convergence Results We have implemented the s-step BiCGStab, and the split orthonormalized s-step BiCGStab (Algorithm 4) whereby the monomial bases P 2s+1 and R 2s are first built and then orthonormalized separately using MKL's (Math Kernel Library) QR factorization. We have also implemented the corresponding modified versions, whereby one iteration of BiCGStab is performed before building the first 4s+1 bases vectors. These algorithms are developed in MCG Solver  [18, 19] , a C++ based software package developed by IFPEN to provide linear solver algorithms for its industrial simulators in reservoir simulation, basin simulation or in engine combustion simulation. Table  3  shows the convergence results for the s-step BiCG-Stab versions on the matrices introduced previously with tolerance tol = 10 À8 except for the SPE10 matrix (tol = 10 À4 ).
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Using the inner networks (RT, SZ and KIT1, Fig. 1 ),  Lehujeur et al. (2015)  showed that the strong phase distortions can cause errors on tomographic maps of up to 30 per cent at 2 s period. In the following we address the feasibility of correcting this first order effect to extract the correct spatial variation of Rayleigh wave velocity. Rejecting station pairs with an interstation distance shorter than 2 or 3 wavelengths would reduce the effect of the phase distortions on the tomographic maps, but would severely decrease the amount of available data. In our case, rejecting station pairs closer than two wavelengths would remove 80 per cent of the dataset at 3 s of period (wavelength ∼7. 3 km) and 96 per cent at 4 s (wavelength ∼10. 4 km). Instead of rejecting data, we propose to interpret all the NCFs by taking the noise directivity into account.