Thermodynamic Phase Change Research Articles

Electron iso-density surfaces provide a thermodynamically consistent representation of atomic and molecular surfaces

The surface area of atoms and molecules plays a crucial role in shaping many physiochemical properties of materials. Despite its fundamental importance, precisely defining atomic and molecular surfaces has long been a puzzle. Among the available definitions, a straightforward and elegant approach by Bader describes a molecular surface as an iso-density surface beyond which the electron density drops below a certain cut-off. However, so far neither this theory nor a decisive value for the density cut-off have been amenable to experimental verification due to the limitations of conventional experimental methods. In the present study, we employ a state-of-the-art experimental method based on the recently developed concept of thermodynamically effective (TE) surfaces to tackle this longstanding problem. By studying a set of 104 molecules, a close to perfect agreement between quantum chemical evaluations of iso-density surfaces contoured at a cut-off density of 0.0016 a.u. and experimental results obtained via thermodynamic phase change data is demonstrated, with a mean unsigned percentage deviation of 1.6% and a correlation coefficient of 0.995. Accordingly, we suggest the iso-density surface contoured at an electron density value of 0.0016 a.u. as a representation of the surface of atoms and molecules.

Modeling and simulation of the cavitation phenomenon in turbopumps

This paper presents a model for simulating a two-phase flow involving cavitation and condensation, focusing on its application to turbopump flows. The model is derived by extending Kapila's approach, which incorporates thermal and free energy relaxation terms, to compressible multiphase flow equations in a rotating reference frame. The numerical method employed is a finite volume approach based on the Godunov scheme, ensuring pressure equilibrium and total energy conservation through a relaxation step. The model utilizes separate Equations of State (EOS) for the liquid and vapor phases, with the experimental saturation curve, expressed as psat(T), being the only parameter needed for cavitation modeling. To broaden its applicability beyond axial pumps, a specific Riemann solver is developed to couple rotating and non-rotating regions within the flow domain. The thermodynamic phase change process is validated using simple cases, and the model is further utilized to simulate water flows in a turbopump inducer. The characteristic curve of the pump is obtained in the non-cavitating regime for several mass flow rates conditions, and the model is successfully assessed in severe cavitation conditions, demonstrating the performance breakdown caused by vapor pockets. The modeling also provides detailed flow descriptions, including analysis of vapor pockets and their impact on blade pressure loading.

On the lattice Boltzmann method and its application to turbulent, multiphase flows of various fluids including cryogens: A review

Cryogenic fluids are used in a myriad of different applications not limited to green fuels, medical devices, spacecraft, and cryoelectronics. In this review, we elaborate on these applications and synthesize recent lattice Boltzmann methods (LBMs) including collision operators, boundary conditions, grid-refinement techniques, and multiphase models that have enabled the simulation of turbulence, thermodynamic phase change, and non-isothermal effects in a wide array of fluids, including cryogens. The LBM has reached a mature state over the last three decades and become a strong alternative to the conventional Navier–Stokes equations for simulating complex, rarefied, thermal, multiphase fluid systems. Moreover, the method's scalability boosts the efficiency of large-scale fluid flow computations on parallel clusters, including heterogeneous clusters with graphics card-based accelerators. Despite this maturity, the LBM has only recently experienced limited use in the study of cryogenic fluid systems. Therefore, it is fitting to emphasize the usefulness of the LBM for simulating computationally prohibitive, complex cryogenic flows. We expect that the method will be employed more extensively in the future owing to its simple representation of molecular interaction and consequently thermodynamic changes of state, surface tension effects, non-ideal effects, and boundary treatments, among others.

Potential of Mid‐tropospheric Water Vapor Isotopes to Improve Large‐Scale Circulation and Weather Predictability

AbstractRecent satellite techniques have uncovered detailed tropospheric water vapor isotope patterns on a daily basis, yet the significance of water isotopes on weather forecasting has remained largely unknown. Here, we perform a proof‐of‐concept observing system simulation experiment to show that mid‐tropospheric water isotopes observed by the Infrared Atmospheric Sounding Interferometer (IASI) can substantially improve weather forecasts through non‐local impacts on the convective heating structure and large‐scale circulation. Assimilating IASI isotopes can improve wind, humidity, and temperature fields by more than 10% at mid‐troposphere compared to only assimilating conventional non‐isotopic observations. These improvements are about two‐thirds of assimilating simultaneous IASI water vapor observations. The improvements can be attributed more to thermodynamic (phase change) effects than dynamic (transport) effects of water isotopes. Furthermore, isotopic observations produce additional 3%–4% improvements to the fields constrained by the conventional observations and simultaneous IASI water vapor observations, demonstrating the unique characteristics of water isotopes.

Laser Sintering Control for Metal Additive Manufacturing by PDE Backstepping

Metal additive manufacturing (AM) has been intensively advanced due to numerous industrial applications, such as automobiles, aerospace, consumer electronics, and medical devices. The dynamics of the melt pool via laser sintering for metal AM has been studied by means of the thermodynamic phase change model known as the “Stefan problem”. In this article, we develop a control design for the laser power to drive the depth of the melt pool to the desired set point. The governing equation is described by a partial differential equation (PDE) defined on a time-varying spatial domain, which is dependent on the PDE state, and the optical penetration of the laser energy affects the PDE dynamics in the domain as well as at the surface boundary. First, we design the full-state feedback control law utilizing the entire spatial profile of the temperature in the melt pool and the moving interface position. The closed-loop system is proven to satisfy some conditions to validate the physical model, and its origin is shown to be exponentially stable. Next, we propose an observer-based output feedback control law by reconstructing the temperature profile with the availability of only the measured interface position and prove the analogous properties of the closed-loop system. Numerical simulation for a controller designed on a single-phase Stefan model is conducted on a more complex and realistic two-phase Stefan model, which incorporates the cooling effect from the solid phase. In addition, a bias in the interface location measurement is considered. The numerical results illustrate the robustness of the proposed feedback. By lowering the initial temperature in the solid and by increasing the interface sensor bias to more extreme levels, which leads to the controller’s failure (where the failure is exhibited through the entire metal freezing and the melt pool disappearing), we explore the limits of how much uncertainty our control law can handle.

Analysis of the Thermodynamic Phase Transition of Tracked Convective Clouds Based on Geostationary Satellite Observations

AbstractClouds are liquid at temperature greater than 0°C and ice at temperature below −38°C. Between these two thresholds, the temperature of the cloud thermodynamic phase transition from liquid to ice is difficult to predict and the theory and numerical models do not agree: Microphysical, dynamical, and meteorological parameters influence the glaciation temperature. We temporally track optical and microphysical properties of 796 clouds over Europe from 2004 to 2015 with the space‐based instrument Spinning Enhanced Visible and Infrared Imager on board the geostationary METEOSAT second generation satellites. We define the glaciation temperature as the mean between the cloud top temperature of those consecutive images for which a thermodynamic phase change in at least one pixel is observed for a given cloud object. We find that, on average, isolated convective clouds over Europe freeze at −21.6°C. Furthermore, we analyze the temporal evolution of a set of cloud properties and we retrieve glaciation temperatures binned by meteorological and microphysical regimes: For example, the glaciation temperature increases up to 11°C when cloud droplets are large, in line with previous studies. Moreover, the correlations between the parameters characterizing the glaciation temperature are compared and analyzed and a statistical study based on principal component analysis shows that after the cloud top height, the cloud droplet size is the most important parameter to determine the glaciation temperature.

Finite-size scaling analysis of protein droplet formation.

The formation of biomolecular condensates inside cells often involve intrinsically disordered proteins (IDPs), and several of these IDPs are also capable of forming dropletlike dense assemblies on their own, through liquid-liquid phase separation. When modeling thermodynamic phase changes, it is well known that finite-size scaling analysis can be a valuable tool. However, to our knowledge, this approach has not been applied before to the computationally challenging problem of modeling sequence-dependent biomolecular phase separation. Here we implement finite-size scaling methods to investigate the phase behavior of two 10-bead sequences in a continuous hydrophobic-polar protein model. Combined with reversible explicit-chain Monte Carlo simulations of these sequences, finite-size scaling analysis turns out to be both feasible and rewarding, despite relying on theoretical results for asymptotically large systems. While both sequences form dense clusters at low temperature, this analysis shows that only one of them undergoes liquid-liquid phase separation. Furthermore, the transition temperature at which droplet formation sets in is observed to converge slowly with system size, so that even for our largest systems the transition is shifted by about 8%. Using finite-size scaling analysis, this shift can be estimated and corrected for.

Non-contact in situ microwave material measurements for high temperature process monitoring.

Non-contact real time microwave measurement and signal analysis techniques to extract high temperature material parameters from the mono-static reflections gathered by a compact air cooled corrugated horn are presented in this work. Non-contact in situ microwave measurements gathered over 20-24 GHz inside a closed furnace were processed to identify the thermodynamic phase change temperature of metal and glass melts. The melting point of aluminum alloy and glass transition of a borosilicate glass matrix extracted from the time gated and processed microwave measurements were in good agreement with differential scanning calorimetry measurements. Thus, the ability to measure high temperature material process parameters using non-contact microwave measurements is demonstrated.

Summary of the Faraday Discussion on New memory paradigms: memristive phenomena and neuromorphic applications.

The Faraday Discussion on New memory paradigms: memristive phenomena and neuromorphic systems was held from October 15-17 on the campus of the Rheinisch-Westfälische Technische Hochschule Aachen University, or RWTH Aachen University, under the auspices of the Royal Society of Chemistry. The Discussion brought together over 100 experts and students from over 20 different countries to present, question, and debate the latest breakthroughs in a field that is exhibiting dramatic growth. There were a large number of excellent oral presentations and posters covering the topics of the Discussion, and the conversations among the participants were lively and informative. The first day and a half encompassed the experimental characterization and analysis of memristors for which the primary resistive switching mechanisms involved electrochemical metallization, chemical valence transformation, or thermodynamic phase change, which illustrated the diversity of the physical properties that can be harnessed for building memristive systems. The final half-day of the Discussion was devoted to synaptic and neuromorphic functions of memristors, which have been growing explosively in the past few years and demonstrate that resistive switching is important for much more than a non-volatile memory, but can also be utilized for learning and computation. The high quality of the presentations and discussions in this section demonstrated that this new research area has been solidly launched and we can expect significant advancements and real applications within a few years as new discoveries from biology are incorporated into neuromorphic hardware. I will not attempt to recapitulate the content of all of the sessions here, since the papers collected for this Faraday Discussions volume speak more eloquently for themselves than I can affect. What I hope to accomplish is to point out a few general concepts that arose when considering multiple papers together, especially during the discussions, and point out a particularly novel concept that deserves special attention.

Exploring a Multiphysics Resolution Approach for Additive Manufacturing

Metal additive manufacturing (AM) is a fast-evolving technology aiming to efficiently produce complex parts while saving resources. Worldwide, active research is being performed to solve the existing challenges of this growing technique. Constant computational advances have enabled multiscale and multiphysics numerical tools that complement the traditional physical experimentation. In this contribution, an advanced discrete–continuous concept is proposed to address the physical phenomena involved during laser powder bed fusion. The concept treats powder as discrete by the extended discrete element method, which predicts the thermodynamic state and phase change for each particle. The fluid surrounding is solved with multiphase computational fluid dynamics techniques to determine momentum, heat, gas and liquid transfer. Thus, results track the positions and thermochemical history of individual particles in conjunction with the prevailing fluid phases’ temperature and composition. It is believed that this methodology can be employed to complement experimental research by analysis of the comprehensive results, which can be extracted from it to enable AM processes optimization for parts qualification.

Gas Transport Model in Organic Shale Nanopores Considering Langmuir Slip Conditions and Diffusion: Pore Confinement, Real Gas, and Geomechanical Effects

Nanopores are extremely developed and randomly distributed in shale gas reservoirs. Due to the rarefied conditions in shale strata, multiple gas transport mechanisms coexist and need further understanding. The commonly used slip models are mostly based on Maxwell slip boundary condition, which assumes elastic collisions between gas molecules and solid surfaces. However, gas molecules do not rebound from solid surfaces elastically, but rather are adsorbed on them and then re-emitted after some time lag. A Langmuir slip permeability model was established by introducing Langmuir slip BC. Knudsen diffusion of bulk phase gas and surface diffusion of adsorbed gas were also coupled into our nanopore transport model. Considering the effects of real gas, stress dependence, thermodynamic phase changes due to pore confinement, surface roughness, gas molecular volume, and pore enlargement due to gas desorption during depressurization, a unified gas transport model in organic shale nanopores was established, which was then upscaled by coupling effective porosity and tortuosity to describe practical SGR properties. The bulk phase transport model, single capillary model, and upscaled porous media model were validated by data from experimental data, lattice Boltzmann method or model comparisons. Based on the new gas transport model, the equivalent permeability of different flow mechanisms as well as the flux proportion of each mechanism to total flow rate was investigated in different pore radius and pressure conditions. The study in this paper revealed special gas transport characteristics in shale nonopores and provided a robust foundation for accurate simulation of shale gas production.

Investigations of effect of phase change mass transfer rate on cavitation process with homogeneous relaxation model

Abstracts The super high fuel injection pressure and micro size of nozzle orifice has been an important development trend for the fuel injection system. Accordingly, cavitation transient process, fuel compressibility, amount of non-condensable gas in the fuel and cavitation erosion have attracted more attention. Based on the fact of cavitation in itself is a kind of thermodynamic phase change process, this paper takes the perspective of the cavitation phase change mass transfer process to analyze above mentioned phenomenon. The two-phase cavitating turbulent flow simulations with VOF approach coupled with HRM cavitation model and U-RANS of standard k-e turbulence model were performed for investigations of cavitation phase change mass transfer process. It is concluded the mass transfer time scale coefficient in the Homogenous Relaxation Model (HRM) representing mass transfer rate should tend to be as small as possible in a condition that ensured the solver stable. At very fast mass transfer rate, the phase change occurs at very thin interface between liquid and vapor phase and condensation occurs more focused and then will contribute predictably to a more serious cavitation erosion. Both the initial non-condensable gas in fuel and the fuel compressibility can accelerate the cavitation mass transfer process.

Numerical Study on the Effect of Thermodynamic Phase Changes on CO2 Leakage

Due to the concerns about the effect of greenhouse gases on the climate, Geologic CO2 storage is a very active area of research. One of the biggest risks associated with such projects is the possibility of leakage. Detrimental environmental consequences present a need to study potential leakage scenarios. Stored CO2 may leak if possible leakage pathways are available and favorable. Pressure and temperature decrease from the leakage source to the surface. Below the CO2 saturation pressure, liquid condensation of the CO2 occurs. At even lower temperatures and pressures, in the presence of water, hydrate formation occurs. CO2-hydrate forms when free water is available and the temperature is below 283 K and pressure is below 647 psi. During leakage, decreases in the temperature and pressure results in a CO2 phase change that affects the leakage flux. The purpose of this study is to estimate the leakage flux for different scenarios taking thermodynamic phase changes into account.A numerical model with coupled mass and energy balances was developed and used to estimate the flux as a function of time. Due to wide temperature and pressure changes over the course of the simulation, an accurate fluid properties model is required to reduce fluid properties related errors. Multi-parameter Span-Wagner equation of state for CO2 is used to achieve this. The numerical model allows for CO2 to exist in gas, liquid and hydrate phases. Hydrate formation was modelled using the van der Waals-Platteeuw model. Heat flux from the surroundings play an important role in effecting a phase change. Example calculations indicate a cyclical nature of the leakage flux under certain conditions. These calculations indicate the importance pressure of the leakage source (aquifer), the amount of water in the pathway (fracture/faults), the geothermal gradient and the surface temperature besides the thickness and the permeability of the fracture.

Detecting CO2 leakage around the wellbore by monitoring temperature profiles: A scoping analysis

Leakage through abandoned wells represents one of the greatest risks to secure storage of CO2 in geologic formations. In this work, we evaluate the feasibility of using temperature as an indicator for detecting leakage in and around wellbores. Numerical simulation tools are used to simulate temperature propagation both along and around the wellbore when leakage occurs. Typical overall heat transfer coefficient of formation rock is applied to quantify heat dissipation from the fluids leaked in well. We have tested the cases of CO2 phase only and the mixture of CO2 and brine. Thermodynamic phase change of CO2 throughout the wellbore depth is accounted by an equation-of-state. Both vertical and slant (off-shore) wells are examined. Our results indicate that strong temperature variation is observed within 100 m from borehole and then virtual hot layers circulating the fluid column within 3 m radius are formed. However, differences from the ambient temperatures are not significant. The hot CO2 column loses heat in 70 m of well depth from reservoir compared to 50 m height in the case of CO2/brine mixture.

Riemann‐Hilbert Problems for the Shapes Formed by Bodies Dissolving, Melting, and Eroding in Fluid Flows

The classical Stefan problem involves the motion of boundaries during phase transition, but this process can be greatly complicated by the presence of a fluid flow. Here we consider a body undergoing material loss due to either dissolution (from molecular diffusion), melting (from thermodynamic phase change), or erosion (from fluid‐mechanical stresses) in a fast‐flowing fluid. In each case, the task of finding the shape formed by the shrinking body can be posed as a singular Riemann‐Hilbert problem. A class of exact solutions captures the rounded surfaces formed during dissolution/melting, as well as the angular features formed during erosion, thus unifying these different physical processes under a common framework. This study, which merges boundary‐layer theory, separated‐flow theory, and Riemann‐Hilbert analysis, represents a rare instance of an exactly solvable model for high‐speed fluid flows with free boundaries.© 2017 Wiley Periodicals, Inc.

Developing magnetofunctionality: Coupled structural and magnetic phase transition in AlFe2B2

Understanding correlations between crystal structure and magnetism is key to tuning the response of magnetic materials systems that exhibit large functional effects in response to small excursions in magnetic field or strain. To this end, temperature-dependent structure-magnetic property correlations are reported in samples of AlFe2B2 with the orthorhombic AlMn2B2-type layered structure as it traverses a thermally-hysteretic first-order magnetic phase change at a transition temperature of Tt = 280 K. Temperature-dependent x-ray diffraction carried out in the temperature range 200 K ≤ T ≤ 298 K reveals that the a and b lattice parameters increase by 0.2% and 0.1% respectively upon heating, while the c lattice parameter decreases by 0.3%, providing a conserved unit cell volume through Tt. A very small volumetric thermal expansion coefficient 4.4 × 10−6/K is determined in this temperature range that is one order of magnitude smaller than that of aluminum and only slightly larger than that of Invar. The latent heat of transformation associated with this magnetostructural phase transformation is determined as 4.4 J/g, similar to that of other magnetostructural materials. Overall, these features confirm a first-order thermodynamic phase change in the AlFe2B2 system that emphasizes strong coupling between the magnetic spins and the lattice to support potential magnetofunctional applications for energy transformation and harvesting.

Aerosol impacts on cloud thermodynamic phase change over East Asia observed with CALIPSO and CloudSat measurements

AbstractImpacts of aerosols on subfreezing cloud thermodynamic phase change over East Asia are studied by using 4 year combined CloudSat radar and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar measurements. The mean occurrence frequencies of supercooled‐liquid, mixed‐phase, and glaciated clouds over East Asia are 10.4%, 10.3%, and 16.9%, respectively. Over northwest of East Asia (32–44°N, 75–100°E), subfreezing clouds are dominated by glaciated clouds with a mean relative cloud fraction (RCF) of ~60% and over southeast (16–32°N, 95–120°E) are dominated by supercooled‐liquid clouds with a mean RCF of ~50%. Although cloud top temperature (CTT) differences contribute largely to the thermodynamic phase differences, northwest of East Asia has ~20% larger glaciated (smaller mixed‐phase) RCFs than those of southeast at the same CTT. Seasonal anomalies of glaciated and mixed‐phase RCFs correlate well with the seasonal variations of dust occurrence frequency. In addition, subfreezing clouds associated with mineral dust contain approximately 5%, 10%, and 20% larger glaciated (smaller mixed‐phase) RCFs than those associated with polluted dust, smoke, and background aerosols at any given CTT. It is suggested that dust impacts on subfreezing clouds over East Asia by providing abundant effective ice nuclei to glaciate mixed‐phase clouds, although the impacts of large‐scale dynamics and water supply mechanisms cannot be ruled out.

Effect of Thermodynamic Phase Changes on CO2 leakage

Abstract Due to the concerns about the effect of greenhouse gases on the climate, Geologic CO 2 storage is a very active area of research. One of the biggest risks associated with such projects is the possibility of leakage. Detrimental environmental consequences present a need to study potential leakage scenarios. Stored CO 2 may leak if possible leakage pathways are available and favourable. Pressure and temperature decrease from the leakage source to the surface. Below the CO 2 saturation pressure, liquid condensation of the CO 2 occurs. At even lower temperatures and pressures, in the presence of water, hydrate formation occurs. CO 2 -hydrate forms when free water is available and the temperature is below 283 K and pressure is below 647 psi. During leakage, decreases in the temperature and pressure results in a CO 2 phase change that affects the leakage flux. The purpose of this study is to estimate the leakage flux for different scenarios taking thermodynamic phase changes into account. An analytical model was built to predict steady state leakage flux taking the phase transitions into account. Several important limiting assumptions were required to perform these calculations. A numerical model with coupled mass and energy balances was developed and used to estimate the flux under less restrictive assumptions than the analytical model. Hydrate formation was modelled using the Van der Waals-Platteeuw model. Example analytical calculations indicate that for a uniform permeability pathway the CO 2 leakage flux decreases by a factor of about two due to CO 2 condensation and about three when hydrate forms compared with the isothermal leakage rate. These calculations illustrate the importance of the pressure and temperature of the leakage source (aquifer) and the amount of water in the pathway (fault) among other variables. Example numerical calculations indicate a cyclical nature of the leakage flux under certain conditions. Hydrate formation results in partial to complete blockage of the fault until melted.

Nature of the Supercritical Mesophase

It has been reported that at temperatures above the critical there is no “continuity of liquid and gas”, as originally hypothesized by van der Waals [1]. Rather, both gas and liquid phases, with characteristic properties as such, extend to supercritical temperatures [2]-[4]. Each phase is bounded by the locus of a percolation transition, i.e. a higher-order thermodynamic phase change associated with percolation of gas clusters in a large void, or liquid interstitial vacancies in a large cluster. Between these two-phase bounds, it is reported there exists a mesophase that resembles an otherwise homogeneous dispersion of gas micro-bubbles in liquid (foam) and a dispersion of liquid micro-droplets in gas (mist). Such a colloidal-like state of a pure one-component fluid represents a hitherto unchartered equilibrium state of matter besides pure solid, liquid or gas. Here we provide compelling evidence, from molecular dynamics (MD) simulations, for the existence of this supercritical mesophase and its colloidal nature. We report preliminary results of computer simulations for a model fluid using a simplistic representation of atoms or molecules, i.e. a hard-core repulsion with an attraction so short that the atoms are referred to as “adhesive spheres”. Molecular clusters, and hence percolation transitions, are unambiguously defined. Graphics of color-coded clusters show colloidal characteristics of the supercritical mesophase. We append this Letter to Natural Science with a debate on the scientific merits of its content courtesy of correspondence with Nature (Appendix).

Gas/Condensate Wellbore Modeling Using a Fundamental Approach

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 102479, "Gas/Condensate Wellbore Modeling Using a Fundamental Approach," by A.A. Sadegh, SPE, J.S. Zaghloul, and M.A. Adewumi, SPE, Pennsylvania State U., prepared for the 2006 SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24–27 September. Multiphase flow in the wellbore poses a challenge for production engineers because characterizing the prevailing flow regime determines which pressure-drop calculation method is appropriate. The problem is complicated further when the flowing fluid under-goes phase changes. A model was developed that comprises a flow-pattern-detection routine, a hydrodynamic model, and an equation-of-state-based phase-behavior package. Introduction As the demand for energy rises, production companies are exploring and exploiting more-complex reservoir systems. It is necessary to optimize production and conserve the natural drive mechanisms within those reservoirs. The production system comprises the reservoir, near-wellbore region, wellbore, and the surface production facility. Optimization of this system requires accurate prediction of pressure drop in the wellbore. However, single-phase flow seldom occurs in the wellbore. More commonly, multiphase flow prevails in the wellbore as well as in gas- and oil-transmission and -distribution pipelines. The engineering calculations required to design and operate these systems are complicated by several physical phenomena. These phenomena include flow-regime transitions, turbulence, and thermodynamic phase changes with pressure and temperature. Hence, the use of empirical correlations that are based on limited laboratory or field data often leads to erroneous predictions. Many tools used by production engineers are based on empirical correlations. The approach taken in developing these models was to generate an extensive database by varying parameters thought to affect pressure drop. These parameters include gas-flow rate, liquid-flow rate, pipe diameter, fluid viscosities, and liquid surface tension. The pressure-drop data then are correlated to dimensionless groups according to relevant variables. However, this approach cannot be extrapolated safely to predict situations for which the actual well parameters are outside the range of data initially used to develop the correlation. Additionally, it was observed that different pressure gradients arose for a varied distribution of the flowing phases in the pipe. The regime transitions also were a function of the physical parameters of the flow system under consideration. Therefore, it is necessary to predict the prevailing flow regime and then use a pressure-drop prediction method suitable for that particular flow regime. Flow of gas/condensate, in addition to the complexities inherent in all two-phase-flow modeling, is further complicated with retrograde condensation. The in-situ liquid fraction may change with a change in pressure, temperature, or fluid composition. This problem requires incorporating compositional modeling in predicting fluid splits and gas and liquid properties. It is necessary to integrate hydrodynamic modeling with hydrocarbon-phase-behavior modeling and flow-regime-transition determination to obtain reasonable predictions. The intent of this research was to address the challenges of accurately predicting pressure drop, liquid holdup, and fluid compositions for gas/condensate wells.