Solid-Liquid Equilibrium Prediction for Binary Mixtures of Ar, O2, N2, Kr, Xe, and CH4 using the LJ-SLV-EoS

International audienceIn a previous paper, authors used molecular simulation data for Lennard-Jones fluids for the regression of the binary interaction parameters of the LJ-SLV-EoS. The binary interaction parameters of the EoS have been expressed as simple functions of the ratios σ11/σ22 and ε11/ε22. This procedure allows obtaining a qualitative prediction of the solid-liquid phase behavior of mixtures composed of simple fluids. This work presents the predicted phase diagrams including solid phases for binary mixtures composed of argon, oxygen, nitrogen, krypton, xenon, and methane. Predictions are in qualitative agreement with the phase behavior documented by the experimental data available from the literature. The adopted procedure allows producing a qualitative reasonable phase diagram for mixtures knowing the Lennard-Jones parameters of the mixture components. The comparison with literature data shows that the adopted procedure is suitable for predicting the solid-liquid behavior of the mixture, distinguishing among eutectic, solid solution, solid-liquid azeotrope

Tricriticalities and Quantum Phases in Spin-Orbit-Coupled Spin-11 Bose Gases

We study the zero-temperature phase diagram of a spin-orbit-coupled Bose-Einstein condensate of spin $1$, with equally weighted Rashba and Dresselhaus couplings. Depending on the antiferromagnetic or ferromagnetic nature of the interactions, we find three kinds of striped phases with qualitatively different behaviors in the modulations of the density profiles. Phase transitions to the zero-momentum and the plane-wave phases can be induced in experiments by independently varying the Raman coupling strength and the quadratic Zeeman field. The properties of these transitions are investigated in detail, and the emergence of tricritical points, which are the direct consequence of the spin-dependent interactions, is explicitly discussed.Comment: 6 pages, 2 figures + Supplemental Material. Revised version, published in PR

Clathrate equilibrium data for CO 2 +N 2 mixtures with TBAB, TBAF, CP, TBAB+CP, TBAF+CP promoters

International audienceCarbon Dioxide capture and sequestration (CCS) is nowadays an important area of research for alleviating CO 2 emissions worldwide. According to [1], CO 2 is globally the largest pollutant to which the global warming is attributed. Consequently, hydrates can become of great importance as they form the basis for a new technology that concerns CO 2 capture from flue gases (hydrate crystallization). In this work hydrate equilibrium data measured at the Centre Thermodynamic of Processes in MINES ParisTech (France) are presented as part of a collaborative project funded by the Danish Technical Research Council. More particularly, in this study experimental results for hydrate dissociation with several promoters are presented. The isochoric method is used to determine the gas hydrate dissociation points. Different CO 2 +N 2 gas mixtures were used with presence of promoters such as tetra-butylammonium bromide (TBAB), tetra-butylammonium fluoride (TBAF), cyclopentane (CP) and mixtures of TBAB and TBAF with CP. The combination of TBA halides with CP was inspired by [2] as it came out synergetic effect that enhances promotion between TBAB (5% w/w) and CP (5% v/v). The results have shown synergetic effect for 20% w/w TBAB+CP (5% v/v) and partly (>30 bar) for 5% w/w TBAF+CP (5% v/v). Concerning experiments with pure promoter, there is excellent consistency between our results and literature for different gas mixtures and promoter concentrations. Moreover, they exhibit very good agreement with existing literature

Fast pyrolysis of Miscanthus x Giganteus in an IR heated reactor

International audienceIntensive research on Miscanthus x Giganteus (MG), a large perennial grass, has been achieved in the last ten years because of its known advantages for farmers (high yield, low input, perennial crop, easy harvesting…) [refs 1,2,3,4]. MG is often considered as a good candidate to produce renewable energy. As lignocellulosic feedstock, MG could also serve to produce chemicals. This approach is far less present in the literature. Because logistics costs could affect the attractiveness of MG, pyrolysis is an interesting technology for energy densification [ref 4]. Therefore the present work describes the pyrolysis of Miscanthus x Giganteus. It is well know that pyrolysis products are solids, liquids and gas. Low residence time, enhanced by high heating rates and high flow rates, favors the production of liquids. A temperature range between 450 and 550°C is also recommended to limit gas formation. A new pyrolysis apparatus designed to achieve fast pyrolysis via infrared heating and low residence time is described. Process conditions are varied for temperature, particle size, N 2 flow rate and preheating effect. Pyrolysis temperature should be the most influential parameter upon the yield and properties of bio-oil. Tests are performed at different levels of power and duration. Temperature is measured in the border and in the center of the reactor because of the presence of radial gradients. The highest bio-oil yield and corresponding temperature profiles are presented. The effect of process conditions on bio-oil yield is assessed. The bio-oil composition is analyzed by GCMS. The results are compared with a direct analysis of MG by Py-GCMS. The bio char is characterized in terms of calorific value with respect to the raw MG High Heating Value (HHV). Furthermore, on the one hand the outlet gas composition is analyzed by online infrared spectroscopy which gives an indication of potential use as secondary source of energy. On the other hand the porosity of the bio-solid products is estimated by BET low-temperature adsorption method for further valorization purpose of pyrolysis products. Highlights: 1) New experimental results on Miscanthus x Giganteus pyrolysis are presented. 2) Characterization of every product thus resource potential is evaluated. 3) Comparison of Py-GCMS with lab scale pyrolysis of MG is performed. References: 1) Anissa Khelfa, Victor Sharypov, Gisèle Finqueneisel, Jean Victor Weber J. Anal. Appl. Pyrolysis 84 (2009) 84–88, Catalytic pyrolysis and gasification of Miscanthus Giganteus: Haematite (Fe2O3) a versatile catalyst

Photothermally-induced disordered patterns of corneal collagen revealed by SHG imaging

The loss of organization of the corneal collagen lattice induced by photothermal effects was analyzed by using second-harmonic generation (SHG) imaging. Porcine cornea samples were treated with low-power laser irradiation in order to get localized areas of tissue disorganization. The disorder induced within the irradiated area of corneal stroma was quantified by means of Discrete Fourier Transform, auto-correlation and entropy analyses of the SHG images. Polarization modulated SHG measurements allowed to probe the changes in the structural anisotropy of sub-micron hierarchical levels of the stromal collagen. Our results emphasize the great potential of the SHG imaging to detect subtle modifications in the collagen assembly. The proposed analytical methods may be used to track several genetic, pathologic, accidental or surgical-induced disorder states of biological tissues

Hydrate equilibrium data for the CO₂ + N₂ system with the use of tetra-n-butylammonium bromide (TBAB), cyclopentane (CP) and their mixture

International audienceCarbon Dioxide capture and sequestration (CCS) is nowadays an important area of research for decreasing CO 2 emissions worldwide. Hydrates can become of great importance in the future as they form the basis for a new technology that can be used for CO 2 capture from flue gases (hydrate crystallization). In this work hydrate equilibrium data are measured and compared with literature data. In particular, experimental results for hydrate dissociation with several promoters are presented. The isochoric method is used to determine the gas hydrate dissociation points. Different CO 2 +N 2 gas mixtures were used with presence of promoters such as tetra-n-butylammonium bromide (TBAB), cyclopentane (CP) and mixtures of TBAB with CP. The novelty of this work is the combination of promoters, TBAB and CP, which under certain conditions induced greater pressure reduction in comparison to pure TBAB results. Concerning experiments with pure promoters, there is excellent consistency between our results and literature results for different gas mixtures and promoter concentrations. Finally, experimental uncertainties for temperature, pressure, and molar composition are also presented

Phase equilibrium data for the hydrogen sulphide + methane system at temperatures from 186 to 313 K and pressures up to about 14 MPa

International audienceIsothermal vapour–liquid equilibrium data have been measured for the methane–hydrogen sulphide (CH4 + H2S) binary system at five temperatures from 186.25 to 313.08 K, and pressures between 0.043 and 13.182 MPa. The experimental method used in this work is of the static–analytic type, taking advantage of two pneumatic capillary samplers (RolsiTM, Armines’ patent) developed in the CTP laboratory. The data were obtained with the following maximum expanded uncertainties (k = 2): u(T) = 0.06 K, u(P) = 0.006 MPa and the maximum uncertainty for compositions u(x, y) = 0.010 for molar compositions. The data have been satisfactorily represented with the classical Peng and Robinson equation of state

Equipement pour la mesure sans contact du poids d'un équipage mobile

Équipement pour la mesure sans contact du poids d’un équipage mobile L’invention concerne un équipement pour la mesure sans contact du poids d’un équipage mobile en translation selon un axe vertical Z, ledit équipage mobile comportement un aimant permanent APM aimanté selon ledit axe Z et des moyens pour assurer la lévitation magnétique dudit équipage mobile, ledit moyen de lévitation étant associé à un moyen de mesure de la force exercée entre ledit équipage mobile et ledit moyen de lévitation. Ledit moyen de lévitation est un aimant permanent, aimanté APF selon ledit axe Z, en opposé à l’aimantation dudit aimant permanent mobile APM, lesdits aimants APM et APF étant alignés selon ledit axe vertical Z par l’intermédiaire d’un guide non magnétique traversant ledit équipage mobile, ledit guide étant animé d’un mouvement vibratoire comprenant au moins une composante radiale

HEURISTIC MODELING OF THERMOPHYSICAL PROPERTIES OF PURE FLUIDS AND MIXTURES THROUGH INNOVATIVE METHODS

The subject of the present Ph.D. thesis is constituted by the development and application of innovative modeling techniques for the representation of the thermophysical properties of fluids. The thermophysical properties are divided into thermodynamic properties, related to states of thermodynamic equilibrium and to transformation processes between two equilibrium conditions, and transport properties, concerning systems in a non-uniform state and then affected by transport phenomena; among these, thermal conductivity has been here considered. The knowledge of the thermophysical properties of pure fluids and mixtures is an absolutely crucial need for the design and the optimization of any equipment in the process industry. The thermophysical properties have to be known in dependence on the controlling variables with a precision as high as possible: errors in the values of the required properties can propagate throughout the entire calculation with amplification effects, yielding wrong design and driving away from the optimal operating conditions. The purpose of this thesis work is to set up modeling techniques able to represent the thermophysical properties with a precision comparable with the experimental uncertainty of the experimental measurements of the properties themselves reducing at the same time the required experimental effort. The proposed modeling techniques are based on a heuristic approach, that get the functional representation of a physical dependence directly from a properly organized data base; the effectiveness of the developed heuristic techniques is fundamentally based on the use of the artificial neural network, which have the characteristic of universal function approximators. The development and application of a heuristic modeling technique to produce equations of state (EoS) in the fundamental form for the representation of thermodynamic properties of pure fluids and mixture are presented in the first part of this thesis work. The modeling technique here proposed for the representation of the thermodynamic properties is based on the extended corresponding states (ECS) principle. The basic idea of the ECS model consists in the distortion of the independent variables of the EoS of the reference fluid to transform it into the EoS of the interest fluid. If the simple two-parameter corresponding states principle should work exactly, no tuning distortion would be necessary; since this is not the case, two tuning functions, indicated as shape functions, are then individually required to exactly match the ECS model with a known thermodynamic surface of the interest fluid. The basic requirements of the ECS technique are the fulfillment of a conformality condition between the reference and the target fluid, and the availability of an accurate equation of state in terms of Helmholtz energy for the reference fluid. In the case that either the conformality condition is not verified among the fluids of a same family or no component of the family, whose fluids are supposed to share a conformality condition, disposes of a DEoS, the discussed ECS method cannot in general be effectually applied. In the model proposed in this thesis the ‘correction’ through the variables distortion is performed on a simple EoS representing, even if roughly, the target fluid itself. In other words a simple EoS for the same target fluid is the starting point for the development of a DEoS through the variables distortion, avoiding in this way any problem about the conformality condition fulfillment. It would be then no more necessary to dispose of a ‘reference fluid’, following the classical interpretation of the ECS theory, but rather of only a ‘reference equation’, whose precision is enhanced, or ‘extended’, through the application of the shape functions. Hence the name of extended equation of state (EEoS) chosen to indicate this new modeling method. The shape functions have to be regressed forcing the model to represent known values of experimentally accessible thermodynamic quantities; in the present model their functional formulation is heuristically obtained applying a multilayer feed-forward neural network (MLFN) as universal function approximator. The new approach is constituted by a general fitting procedure in which a mathematical form of the surface has to be ‘spread’ on known values of it and of its derivatives, overcoming the problems presented by the two traditional ECS approaches, i.e., the local solution and the continuous solution. The proposed modeling technique comes from the combination of the EEoS method with the neural networks and then it can be concisely indicated as EEoS-NN model. The EEoS-NN model allows to obtain for the fluid of interest a DEoS in the default fundamental form which allows to calculate any thermodynamic quantity through mathematical derivations only. In order to set up the method and to test its potentialities, data generated from a DEoS for each target fluid are used instead of experimental data, so that the model performances are not hindered by error noise and uneven data distribution. Moving from generated data, the capability of the proposed method has been verified both for pure fluids and for mixtures. A group of pure alkanes, haloalkanes, and strongly polar substances has been considered; the results obtained for these fluids are very promising. The same is valid for the five binary mixtures and two ternary mixtures of haloalkanes here studied. In the case of pure fluids it has been also verified that slightly more than 100 density points evenly distributed in the pressure-density-temperature plane and with low experimental error can be a sufficient input for the model development, allowing to reduce the experimental efforts. The promising performances for the proposed model based on generated data leads to the possibility to reliably develop DEoSs in the EEoS-NN format directly from experimental data. The EEoS-NN technique was then applied to draw DEoSs for the pure fluids sulfur hexafluoride (SF6) and 2-propanol (iC3H8O) directly from the available data sets of the target fluids. The DEoS for SF6 is valid for the liquid, vapor and supercritical region in the ranges from the triple-point temperature at about 223.6 K up to 625 K and for pressures up to 60 MPa, with the exclusion of a region close to the critical point in case of caloric property calculation. The representation of the available experimental data is satisfactory for all the considered properties; in fact the deviations of the equation from the data are comparable with the ascribed uncertainties of the experimental sources. One of the advantages of the EEoS-NN method, shown for the fluid sulfur hexafluoride, is that the data set on which to base the regression procedure can include only density and coexistence values, getting in the meantime a satisfactory performance also for the other properties. The DEoS for iC3H8O is valid for the liquid, vapor and supercritical region for temperatures from 280 up to 600 K and for pressures up to 50 MPa. Due to the substantial lack of data in the near critical region and the non-specialization of this DEoS in representing such region very close to the critical point the present equation is not suggested to be used within a region very close to the critical point. The representation of the available experimental data is satisfactory for all the considered properties; in fact the deviations of the equation from the data are comparable with the realistic uncertainties of the experimental sources for this fluid. The results obtained for the fluid 2-propanol demonstrate that the EEoS-NN modeling method is completely reliable to develop highly effective DEoSs even if the experimental data situation for the fluid is not completely favorable. This aspect is particularly valuable in the case a DEoS is required for engineering applications where the economy of the experimental effort and the representation accuracy have to be met through a suitable compromise. The pointed out features make the EEoS-NN technique a useful tool for the process analysis and optimization. To prove the potential of the cited technique as a tool to study real processes typical of the chemical industry the system propylene + 2-propanol + water has been chosen as an exemplification case. The objective is therefore to investigate the possibility to use the EEoS-NN technique to study the energetic optimization of the extraction process of 2-propanol from aqueous solutions using propylene as solvent. This system has been chosen after a screening of the literature data because it seems to present a favorable phase equilibrium behavior for an extraction operation. Furthermore, the propylene + 2-propanol + water system is thermodynamically strongly deviating from ideal behavior due to several causes as the strong polarity of the components, their association behavior, etc., which increases a lot the difficulties of a complete and accurate thermodynamic representation. For such a reason the set up of a DEoS for this system is an interesting challenge from a scientific point of view, being the first case in which a dedicated equation of state is developed for a strongly deviating ternary mixture. The experimental data available from the literature for the ternary mixture are vapor-liquid equilibrium (VLE) and liquid-liquid equilibrium (LLE). In order to set up a semi-predictive thermodynamic model of the ternary mixture to study its phase behavior, vapor-liquid-liquid equilibrium (VLLE) measurements have been performed. Excess enthalpy measurements have also been carried out for the ternary mixture and for the 2-propanol + water binary mixture in order to obtain a good temperature dependence in the semi-predictive model, constituted of a Peng-Robinson cubic EoS with Wong-Sandler mixing rules and a modified UNIQUAC model to represent the excess Gibbs energy. This model has been used to investigate the phase equilibrium behavior of the ternary mixture from a qualitative point of view. This is a necessary preliminary step to efficiently plan an experimental campaign of measurements suitable to set up a DEoS of the ternary mixture in the EEoS-NN format. The chosen range of interest for the extraction operation is from about 300 to 350 K in temperature, up to 10 MPa in pressure and it extends up to the pure fluids in composition. The properties to be measured in the selected range in order to set up the DEoS are density and phase equilibria. Some isobaric heat capacity measurements are also required to validate the model capability to correctly predict the caloric properties in the range of interest. Density data have been produced using a vibrating tube densimeter (VTD) for the pure 2-propanol, for the propylene + 2-propanol mixture, for the 2-propanol + water mixture and for the propylene + 2-propanol + water mixture. Bubble pressure data were also determined using the VTD for the propylene + 2-propanol mixture and for the propylene + 2-propanol + water mixture. At present the experimental work is still in progress and phase equilibrium and isobaric heat capacity data have to be carried out. This experimental work, together with the development of a DEoS for the propylene + 2-propanol + water mixture, will constitute the extension of this thesis work. Once a thermodynamic model in EEoS-NN format will be obtained, it will be possible to link it with a process simulator, studying the better operative conditions for the 2-propanol extraction process. The development and application of a heuristic modeling technique to produce dedicated equations for the representation of the thermal conductivity of pure fluids is presented in the second part of this thesis work. The proposed model is based on the ECS principle, but the shape functions are got in a continuous analytical form expressed by a universal function approximator, i.e. a neural network, through regression of thermal conductivity data. This innovative approach, named ECS-NN, allows to overcome the problems in obtaining the scale factors presented by the two traditional ECS approaches for transport properties, i.e., the local solution and the continuous solution. The potentiality of the ECS-NN modeling technique for thermal conductivity has been shown with application to both values generated from existing models and experimental values. Assuming R134a as reference fluid, two dedicated thermal conductivity equations have been regressed for carbon dioxide and R152a from the available experimental data. The obtained results are very encouraging; in fact the proposed technique yields thermal conductivity equations that represent the experimental values in the liquid, vapor and supercritical regions within their experimental accuracy; moreover, the method is able to satisfactorily model the strong critical enhancement of thermal conductivity in the near-critical region. The performance change of the model has been studied varying the number of experimental data in the training procedure, showing that about two hundred data points, regularly distributed on the thermal conductivity-temperature-density surface of the target fluid, are sufficient to draw a very precise equation, with evident saving of experimental efforts. Summarizing, the present Ph.D. thesis has shown the effectiveness of the application of heuristic techniques to both thermodynamic and transport property modeling, as a valid alternative to the techniques that are at present adopted. The proposed methods, exploiting the prediction capability of the neural networks, allow to reduce the experimental effort, yielding at the same time equations representing the data within their experimental uncertainties. This feature makes the developed methods suitable tools for the design and optimization of unit operations of the industrial processes.L’argomento di questa tesi di Dottorato è lo sviluppo e l’applicazione di tecniche modellistiche innovative per la rappresentazione di proprietà termofisiche di fluidi. Le proprietà termofisiche sono divise in proprietà termodinamiche, riguardanti stati di equilibrio termodinamico e processi di trasformazione tra due condizioni di equilibrio, e proprietà di trasporto, riguardanti sistemi in stato non uniforme e quindi caratterizzate da fenomeni di trasporto; tra queste è stata qui trattata la conduttività termica. La conoscenza delle proprietà termofisiche di fluidi puri e miscele è un requisito assolutamente fondamentale nella progettazione ed ottimizzazione di qualsiasi apparecchiatura nell’industria di processo. Le proprietà termofisiche devono essere conosciute in dipendenza delle variabili controllanti con una precisione il più elevata possibile: errori nel valore delle proprietà richieste possono propagarsi attraverso l’intero calcolo amplificandosi, dando luogo ad una progettazione scorretta ed allontanando dalle condizioni operative ottimali. Lo scopo di questa tesi è lo sviluppo di tecniche modellistiche capaci di rappresentare le proprietà termofisiche con un’accuratezza comparabile con l’incertezza sperimentale delle misure stesse, riducendo allo stesso tempo il lavoro sperimentale. Le tecniche modellistiche proposte sono basate su un approccio euristico, che deriva la rappresentazione funzionale di una dipendenza fisica direttamente da una appropriata base di dati; l’efficacia delle tecniche euristiche sviluppate è basata sull’utilizzo delle reti neurali artificiali, che hanno la caratteristica di essere approssimatori universali di funzione. Lo sviluppo e l’applicazione di tecniche modellistiche di natura euristica atte a produrre equazioni di stato (EoS) in forma fondamentale per la rappresentazione delle proprietà termodinamiche di fluidi puri e miscele sono trattati nella prima parte di questa tesi. La tecnica modellistica qui proposta per la rappresentazione delle proprietà termodinamiche è basata sul principio degli stati corrispondenti estesi (ECS). L’idea alla base del modello ECS consiste nella distorsione delle variabili indipendenti della EoS del fluido di riferimento trasformandola nella EoS del fluido di interesse. Se il principio degli stati corrispondenti a due parametri fosse esatto non sarebbero necessari aggiustamenti delle variabili indipendenti, ma poiché questo non è verificato sono richieste due funzioni distorcenti, chiamate shape function, per far corrispondere il modello ECS con una superficie termodinamica nota del fluido d’interesse. Per l’applicazione della tecnica ECS deve essere verificata la condizione di conformality tra il fluido di riferimento ed il fluido target, e l’esistenza di un’accurata equazione di stato espressa in forma di energia libera di Helmholtz per il fluido di riferimento. Nel caso in cui la condizione di conformality tra i fluidi non sia verificata, o nessun fluido della famiglia che si suppone presenti una condizione di conformality con il fluido di interesse disponga di una DEoS, il metodo ECS non può essere applicato efficacemente. Nel modello presentato in questa tesi la ‘correzione’ ottenuta attraverso la distorsione delle variabili è applicata ad un’equazione semplice che rappresenta, anche se approssimativamente, lo stesso fluido target. In altre parole, una EoS semplice per il fluido target stesso è il punto di partenza per lo sviluppo di una DEoS per mezzo della distorsione delle variabili, evitando in questo modo il vincolo costituito dalla necessità di soddisfare la condizione di conformality. Non è più quindi necessario disporre di un ‘fluido di riferimento’, come nell’interpretazione classica della teoria ECS, ma piuttosto solo di una ‘equazione di riferimento’, la cui precisione è aumentata, o ‘estesa’, per mezzo dell’applicazione delle shape function. Di qui deriva il nome di extended equation of state (EEoS) scelto per indicare questa nuova tecnica modellistica. Le shape function devono essere regredite forzando il modello a rappresentare valori noti delle grandezze termodinamiche sperimentalmente accessibili; nel modello proposto la loro forma funzionale è ottenuta in modo euristico utilizzando una multilayer feed-forward neural network (MLFN) come approssimatore universale di funzione. La nuova tecnica è costituita da una procedura di fitting in cui la forma matematica della superficie di deve essere ‘spalmata’ su valori noti della stessa e delle sue derivate, superando i problemi che derivano dai due approcci ECS convenzionali, cioè la local solution e la continuous solution. La tecnica modellistica proposta deriva dalla combinazione del metodo EEoS con le reti neurali ed è quindi brevemente indicata come EEoS-NN. Il modello EEoS-NN permette di ottenere per il fluido di interesse una DEoS in forma fondamentale che consente di calcolare ogni proprietà termodinamica attraverso il solo utilizzo di operazioni di derivazione. Allo scopo di mettere a punto il metodo e di testare le sue potenzialità, sono stati scelti alcuni fluidi target per i quali sono stati utilizzati valori generati da una DEoS preesistente al posto dei dati sperimentali, in modo tale che la performance del modello non sia compromessa dall’error noise e dalla distribuzione irregolare dei dati. Utilizzando dati generati la performance del modello è stata verificata per fluidi puri e per miscele. E’ stato considerato un gruppo di fluidi puri comprendenti alcani, aloalcani, e sostanze fortemente polari; in ogni caso i risultati ottenuti sono molto promettenti. La stessa considerazione può essere fatta per le cinque miscele binarie e le due miscele ternarie di aloalcani studiate. Nel caso di fluidi puri è stato anche verificato che un numero poco superiore a 100 punti di densità regolarmente distribuiti sul piano pressione-densità-temperatura e caratterizzati da un basso errore sperimentale possono essere un input sufficiente per lo sviluppo del modello, permettendo di ridurre il lavoro sperimentale usualmente necessario per l’ottenimento di una DEoS. Le promettenti prestazioni ottenute della tecnica modellistica applicata ai dati generati conducono alla possibilità di mettere a punto delle DEoS in forma EEoS-NN utilizzando direttamente dati sperimentali. La tecnica EEoS-NN è stata quindi utilizzata per produrre la DEoS per i fluidi puri esafluoruro di zolfo (SF6) e 2-propanolo (iC3H8O) direttamente dai dati sperimentali dei due fluidi. La DEoS per il fluido SF6 è valida nel liquido, vapore e supercritico dalla temperatura del punto triplo, a circa 223.6 K, fino a 625 K e per pressioni fino a 60 MPa, con l’esclusione della regione prossima al punto critico nel caso delle proprietà caloriche. La precisione con cui il modello rappresenta i dati è da considerarsi soddisfacente per tutte le proprietà termodinamiche, infatti le deviazioni dell’equazione dai dati sono confrontabili con l’incertezza attribuita alle fonti sperimentali. Uno dei vantaggi del metodo EEoS-NN, evidenziato nell’applicazione al fluido esafluoruro di zolfo, è che la procedura di regressione della DEoS può essere basata su una base dati comprendente solo valori di densità e coesistenza, ottenendo allo stesso tempo una rappresentazione accurata anche delle altre proprietà. La DEoS per il fluido iC3H8O è valida nel liquido, vapore e supercritico per temperature da 280 a 600 K e per pressioni fino a 50 MPa. A causa della mancanza di dati nella regione prossima al punto critico e della non-specializzazione della forma funzionale di questa DEoS nella rappresentazione delle proprietà termodinamiche nelle immediate vicinanze del punto critico l’utilizzo della presente equazione è sconsigliato nella suddetta regione. La rappresentazione delle proprietà termodinamiche è soddisfacente per tutte le proprietà considerate, infatti le deviazioni dell

Le projet collaboratif de conception du respirateur médical MVM

International audienc