Fluid Properties Research Articles

Provenance analysis of rock crystal artefacts from Palaeolithic sites in Moravia (East Central Europe) – a comparative extended approach

The Bohemian Massif and the Alps are regions that are generally known for their rock crystal artefacts and the study thereof. The most important archaeological findspots in the Czech Republic are the Palaeolithic sites at Nová Dědina (East Moravia) and in Žitný Cave (Moravian Karst), which yielded numerous rock crystal artefacts. The study of fluid inclusions as sensitive objects reflecting the conditions of their formation was included in the research. Subsequently, natural sites with the occurrence of rock crystals were selected as potential extraction sites, and a comparative study was carried out. The methodological approach has been completed using microthermometry, Raman spectrometry, EPMA and stable isotopic studies of oxygen. The best match of the fluid inclusion assemblage resulted from samples from the Bory-Cyrilov area (West Moravia, the Moldanubicum geological unit) as the rock crystal source for the Nová Dědina Aurignacian site. Unfortunately, no natural sample that would match the artefacts from the Žitný Cave was discovered in terms of the investigated properties. Certain features of the artefacts suggest a possible origin in the Tauern Window region. The inaccessibility of the Alps during large parts of the Palaeolithic and the properties of fluids may point more to the source area of the Moldanubicum. The applied methodological approach clearly shows that the combination of the methods used and the interpretation of their data defines the formation conditions and provides essential information for a discussion of the provenance of the raw material used for rock crystal artefacts.

Bridging the lab- to field-scale solutions of Navier–Stokes equations to study seawater intrusion in fractures

Abstract Scale effects and mass continuity loss may affect upscaling methods that couple sequential model simulation outputs by increasing computational domains and upscaling equations coefficients or averaging representative volumes. We propose an innovative method unaffected by scale effect errors and based on ‘similarity criteria’ (SC) to upscale solutions of Navier–Stokes equations (NSEs) from the laboratory scale to a portion of the investigated aquifer. SC utilises real-world physical quantities such as forces and fluid properties (i.e. viscosity and density) to downscale a field-scale flow. Stationarity between real world (i.e. prototype) and downscaled fluid dynamics is ensured by the similarity of forces, strengths, lengths, and times of the designed building, which can be accurately reproduced in a lab-scaled model. We leverage the SC theory to apply NSEs to unsteady variable salinity water flow into the freshwater of individual fractures of coastal aquifers. Numeric simulations are conducted in an ‘in silico’ downscaled model ten times smaller than the field-scale target aquifer. The proposed SC analysis generates solutions and identifies key factors affecting the progress of seawater intrusion. Upscaled solutions of the NSEs through ‘in silico’ experiments remain largely unaffected by scale effects, producing maps of salt iso-concentration from sea intrusion and of velocity vectors. These NSE field-scale solutions cannot be obtained easily at a field scale and reveal that local small obstacles to the flow in a fracture can block sea inland advancement. Minimal discrepancies (6%) in a simulated iso-concentration contour of 10 g/l inland advancement suggest further studies to improve upscaling performances of the SC method.

Flexible Microfluidic Devices for Tunable Formation of Double Emulsion.

Double emulsions are highly structured dispersion systems that generate double-layered droplets. Double emulsions offer an effective platform for encapsulating liquid samples. Multilayer protection, controlled release of encapsulated materials, and stability make double emulsions superior to single emulsions in handling sensitive liquid samples. This technology is widely used in biology, food technology, cosmetics, and environmental sciences. Microfluidic emulsification is a promising method for producing highly monodisperse double-emulsion droplets with a high encapsulation efficiency. Well-controlled adjustment of the core size and shell thickness is critical for applications of double emulsions. Changing the flow rates of the fluid phases is the most straightforward method to control the emulsion sizes. However, monodisperse double-emulsions can only be generated within a small range of flow rates. Thus, producing monodisperse double emulsions with a wide size range without changing the device design or drastically altering the fluid properties is challenging. Here, we demonstrate a facile method to generate monodisperse double-emulsion droplets with tunable core size and shell thickness without changing the flow rates of the fluid phases. To address this challenge, we developed a proof-of-concept flexible and stretchable microfluidic device capable of controlling core size, shell thickness, and generation frequency by adjusting channel dimensions and stretching the microfluidic device. We incorporated three stretching cases to assess the feasibility of controlling the generation process of the double emulsion. We demonstrated that stretching increases the core size and shell thickness and decreases the generation frequency. Experimental results showed an ∼84% increase in core volume and an ∼23% increase in shell volume by applying ∼16% device strain. This innovative approach significantly advances the field of droplet-based microfluidics, providing on-site, real-time tunability for the generation of double-emulsion droplets with high precision and reproducibility.

Numerical investigations on the performance analysis of multiple fracturing horizontal wells in enhanced geothermal system

The development of geothermal energy through enhanced geothermal systems (EGS) often encounters challenges such as fluid short-circuiting, water loss, and insufficient connectivity. This study presents a time-dependent seepage and heat exchange model for the formation–wellbore–fluid system during the heat extraction process. Taking the Fenton Hill HDR project as a case study, this paper investigates the influence of formation characteristics, wellbore design, and injected fluid properties on heat transfer efficiency. Furthermore, a multi-well EGS utilizing multiple fracturing horizontal wells (MFHW) is proposed, and its production temperature is compared with two types of double-well EGS. The findings reveal that within the horizontal segment of the double-well EGS, an optimal output of 3.4 MW can be achieved at an injection rate of 30 kg/s. Additionally, the extraction temperature shows a positive correlation with factors such as heat production and electrical power generation. In the MFHW project, optimizing heat production potential can be accomplished by increasing the number of perforation fractures, enhancing artificial fracture spacing, improving the perforation angle, extending the horizontal segment, reducing well diameter, and employing a longer vertical heat insulation pipe with lower thermal conductivity. Finally, a comparative analysis of various development models indicates that two-injection-one-production multi-well EGS model exhibits superior performance, with its heat production being twice as efficient as that of one-injection-one-production double-well EGS model.

A mathematical approach to the role of chemical reactions and temperature-dependent fluid properties on the peristaltic transport of non-Newtonian Ree-Eyring fluid in a nonuniform channel

BackgroundIn industries, peristalsis is vital for transporting sensitive or corrosive fluids through tubes without direct contact with mechanical parts. It ensures precise flow control in applications like pharmaceuticals, food processing, and chemical handling, while slip conditions enhance efficiency by reducing boundary friction. The current study explores the peristaltic transport of Ree-Eyring fluid through a non-uniform channel, focusing on temperature-dependent fluid properties such as viscosity and thermal conductivity, which are vital in modelling biological and industrial applications.Mathematical ModelThe flow is modelled using momentum, energy, and mass transfer equations with slip conditions at the walls. The governing nonlinear equations are simplified using low Reynolds numbers and long-wavelength approximations and are non-dimensionalized for analysis. Analysis of the chemical reaction is also considered in the current study.Solution MethodologyA regular perturbation technique is applied to solve the nonlinear equations. MATLAB R2023a is used to visualize the impact of critical parameters like velocity, temperature, concentration, and streamlines under varying physical conditions. Parametric analysis is performed for pertinent parameters.Important ResultsThe analysis shows that variable viscosity increases velocity profiles while variable thermal conductivity reduces the velocity profiles. These findings provide valuable insights into the effects of temperature-dependent properties on the flow dynamics of biological fluids and industrial systems. Also, the chemical reaction rate is diminished by an increase in the homogeneous reaction parameter, while an increase in the heterogeneous reaction parameter accelerates it.Novelty of the studyThe study addresses a novel investigation of peristaltic flow in Ree-Eyring fluid with temperature-dependent fluid properties. The research contributes to both the theoretical understanding of non-Newtonian peristaltic flow and the practical applications in biological and industrial systems, where variable fluid properties play a crucial role. This research optimizes industrial processes employing non-Newtonian fluids to improve performance and efficiency in polymer synthesis and biomedical applications. This study advances theoretical knowledge and gives practical solutions that could improve real-world applications.

Review of Methods for Judging Reservoir Fluid Properties

Sand formation has good reservoir conditions due to its relatively developed porosity and permeability and well developed pore throats. After the reservoir is divided from the drilling geological profile, the next step of logging interpretation is to determine the oil, gas and water properties of each reservoir. The oil-bearing property of reservoir can be measured by its saturation, which can be divided into water saturation and oil-bearing saturation. Water saturation refers to the percentage of water-bearing void volume in total void volume of rock, usually expressed as Sw; oil-bearing saturation refers to the percentage of oil-bearing void volume in rock, expressed as Sh. Saturation is usually expressed as percentage ( %). Under ideal conditions, the sum of hydrocarbon saturation and water saturation in reservoir pores is 1 (or 100%). Therefore, water saturation is usually used to describe hydrocarbon bearing of reservoir, and it is particularly important to judge reservoir fluid properties. When logging data are applied, natural potential logging, triple laterolog, neutron gamma logging and ordinary resistivity logging are usually used to judge oil and water layers.

Predictive model for non-Newtonian droplet impact on moving solid surfaces

We have developed a refined predictive model for the spreading dynamics of non-Newtonian droplets impacting both stationary and moving surfaces. Using numerical simulations, the key physical mechanisms, including inertial spreading, shear-thinning effects, and capillary stabilization, were identified and integrated into the model. The model extends classical Newtonian frameworks by incorporating the time-dependent and shear-rate-dependent rheological properties of non-Newtonian fluids. The numerical framework employs the volume of fluid method combined with dynamic contact angle modeling to resolve interface dynamics and wetting behavior. Comparisons with experimental data for shear-thinning droplets (e.g., Parafilm-M at We = 24 and We = 94) demonstrated strong agreement within a 3% margin of error, confirming the model's accuracy. Notably, the model successfully captures anisotropic spreading induced by surface motion, a phenomenon neglected in prior studies. Notably, the model accurately captured anisotropic spreading induced by surface motion, a phenomenon neglected in existing frameworks. The results highlight the model's robustness in generalizing across trained and untrained conditions, emphasizing its applicability for industrial processes such as inkjet printing, spray coating, and pharmaceutical droplet deposition. This work establishes a comprehensive framework for understanding and predicting the complex dynamics of non-Newtonian droplet impacts.

Evaluation of rheological properties of guar gum-based fracturing fluids enhanced with hydroxyl group bearing thermodynamic hydrate inhibitors.

Evaluation of rheological properties of guar gum-based fracturing fluids enhanced with hydroxyl group bearing thermodynamic hydrate inhibitors.

Fluid propagation and protein adsorption patterns in porous nitrocellulose membranes for lateral flow assays

Lateral flow assays (LFAs) have caught new attention in recent years due to extensive use in the containment of the COVID-19 pandemic. Especially the protein and fluid interactions with the nitrocellulose membrane structure are yet to be fully investigated, which affect the fluid and protein distribution of the test and control lines differently due to different adsorptive properties of fluids and proteins. Therefore, the relationship between fluid spread and protein distribution, respectively, and structure needs systematic evaluation. Two procedures were developed based on passive adsorption of complementary fluorescent dyes to investigate these phenomena. These procedures enabled three-dimensional visualization of the membrane structure, fluid as well as the protein spreading, respectively. Confocal laser scanning microscopy was applied after depositing picoliter and nanoliter volumes of the printing buffers containing fluorophore-labeled proteins (immunoglobulin G) and Oregon Green™ 488 onto the membrane using a high precision micro dispenser. The resulting data were correlated with the membrane's tortuosity and permeability. Inverse-proportional dependencies for the lateral spread of the fluid and protein adsorption with the structural parameters were observed. Additionally, surfactants [polysorbate 80 (PS80) and sodium dodecylbenzenesulfonate (SDBS), both at 0.1%] were added individually to the buffers, and the spread of the liquids was evaluated. Both surfactants increase the similarities between fluid and protein shape compared to the reference data. While SDBS increases the general lateral spread, PS80 does increase the penetration depth of the protein into the membrane, which could lead to reduced signal in LFAs.

Multiphase Flowmeter System Automates Remote Monitoring

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 222068, “Automated Remote Metering Monitoring,” by Renaud Caulier, TotalEnergies. The paper has not been peer reviewed. _ Subsea multiphase flowmeters (MPFMs) are essential for measuring the production rates of oil, water, and gas and providing reliable forecasts for future operations. Since the initial stages of their development, significant advancements have been made in both the methodology and tools used to monitor MPFMs. This paper presents functionalities of the monitoring tool that the operator has developed and implemented as well as plans and challenges. Data Analysis The highlighted tool is a Web-based application, meaning that no installation to personal computers is needed. The tool allows different levels of access rights, ranging from visitor to developer or administrator. At the time of writing, almost 200 personnel use the application on a regular basis. The tool is connected to a system that retrieves and stores data from the data historian at regular intervals, usually every hour. The data includes various parameters related to production. Before performing any calculation on the data, the tool analyses each data point to identify any missing, frozen, or overranged values that could affect the accuracy and reliability of the results. If any issues are detected, the tool raises an alarm and notifies the user. The tool also connects to other databases that contain information relevant to production analysis. It has the functionality to perform specific calculations such as backup calculation of flow rates. These calculations are then written back to the data historian for further use and reference (Fig. 1). Development The core of the system consists of various scripts designed for multiple functionalities ranging from simple arithmetic operations, such as adding two flow rates or performing decay calculations for a gamma source, to more-complex iterative calculations, such as allocation by uncertainty. Python 2 and 3 are the programming languages used, with development conducted in-house. Templates have been created for each type of flowmeter and then deployed easily for new assets. This language also offers the possibility of integrating artificial intelligence solutions such as extreme gradient boosting for the implementation of virtual flowmeters. Thermodynamic Calculation The tool embeds a link to a thermodynamic simulator through dedicated Python functions. The software was developed by a previous founding entity of the operator known as Basic Element of Standard Thermodynamics (BEST). BEST includes advanced operations in petroleum evaluation, compositional grading in reservoirs, production steady-state multiphase flow, robust multiphase flash algorithms, and classical pressure/volume/temperature package functionalities, all embedded as unit operations. The basic architecture of the software is a flow sheet allowing a sequence of unit operation calculations in a similar way to a conventional surface process simulator. The sequencing algorithm handles the flow-material loops with the usual convergence methods in the domain. The software allows calculation, at any location of the process plant, of fluid properties useful for flowmeter configuration. The same BEST tool also is used for MPFM sizing, using expected reservoir simulation profiles in standard conditions and converting them into operating conditions at the MPFM location.

Molecular structure and fluid properties of native and enzymatically cross-linked caseins after spray drying

Molecular structure and fluid properties of native and enzymatically cross-linked caseins after spray drying

Interdiffusion in microfluidic interface rotation between two laminarly flowing liquids of different densities

Targeted and rapid mixing is a common task in microfluidic devices. Owing to their small dimensions, flows in micromixers are laminar, and mixing is primarily diffusion driven. Y-mixers, which have two inlet channels and one mixing channel, are particularly well studied. In these channels, interface-reorientation can occur: the interface tilts from a side-by-side flow to a top-to-bottom flow. This impacts mixing performance and may complicate product extraction. Studies have demonstrated that the density gradient between fluids and the interdiffusion of solutes affect the interface-reorientation. However, systematic experimental research considering both influences is lacking. Traditional experimental methods, such as confocal fluorescence microscopy, struggle to provide highly resolved and marker-free measurements of interdiffusion constants. These methods rely on added markers, and it remains uncertain whether these impact fluid properties. In this work, we employ confocal Raman microscopy as a quantitative, highly resolved, and marker-free method to simultaneously measure the interdiffusion constants and interface orientation in situ. Isopropanol:water, deuterated water:water, and ethanol:water in 3-dimensional (3D)-printed microfluidic Y-channels were measured. A general model for interface-reorientation, considering densities and interdiffusion, is derived using the Buckingham pi theorem. Diffusion positively affects the interface rotation rate. The diffusion constants below which the diffusive influence can be neglected are on the order of 1.0×10−10 to 15.2×10−10 m2/s. A fundamental comprehension of interface-reorientation is essential for the strategic engineering of microfluidic devices, the selection of optimal fluid systems, and the precise determination of external parameters, such as fluid flow velocity. Applications include membraneless fuel cells, chemical processing cells, in-channel surface functionalization, and in-channel micropatterning.

Heat and mass transfer characteristics in peristaltic Rabinowitsch nano-fluid passing through a non-uniform tube with temperature dependent variable fluid properties

Heat and mass transfer characteristics in peristaltic Rabinowitsch nano-fluid passing through a non-uniform tube with temperature dependent variable fluid properties

Hybrid radiation hydrodynamics scheme with adaptive gravity-tree-based pseudo-particles

Abstract H ii regions powered by ionizing radiation from massive stars drive the dynamical evolution of the interstellar medium. Fast radiative transfer methods for incorporating photoionization effects are thus essential in astrophysical simulations. Previous work by Petkova et al. established a hybrid radiation hydrodynamics (RHD) scheme that couples Smoothed Particle Hydrodynamics (SPH) to grid-based Monte Carlo Radiative Transfer (MCRT) code. This particle-mesh scheme employs the Exact mapping method for transferring fluid properties between SPH particles and Voronoi grids on which the MCRT simulation is carried out. The mapping, however, can become computationally infeasible with large numbers of particles or grid cells. We present a novel optimization method that adaptively converts gravity tree nodes into pseudo-SPH particles. These pseudo-particles act in place of the SPH particles when being passed to the MCRT code, allowing fluid resolutions to be temporarily reduced in regions which are less dynamically affected by radiation. A smoothing length solver and a neighbour-finding scheme dedicated to tree nodes have been developed. We also describe the new heating and cooling routines implemented for improved thermodynamic treatment. We show that this tree-based RHD scheme produces results in strong agreement with benchmarks, and achieves a speed-up that scales with the reduction in the number of particle-cell pairs being mapped.

Measurement of fluid viscosity based on pressure-driven flow digital-printed microfluidics.

Viscosity is an important characteristic of fluids. Microfluidics has shown significant advantages in the viscosity measurement of biopharmaceuticals, especially in meeting the needs of low sample volumes and accurately controlling microscale fluids. However, the viscosity chip of the traditional straight channel structure has limitations, and the processing technology is also facing challenges. In this study, a variable cross-section microfluidic chip structure was designed and successfully manufactured by photocuring 3D printing technology. A digital-printed (DP) microfluidic viscometer was realized by a pressure-driven flow combined with optical imaging. The device measures the change in sample viscosity with shear rate by recording the change in pressure and flow velocity with time. The whole experiment requires only 25 μl of reagents per time, and the single experiment time is less than 2 minutes, which not only reduces the consumption of samples dramatically, but also improves the efficiency of the experiment significantly. Compared with commercial viscometers, our measurements are accurate and capable of supporting non-Newtonian fluids. The proposed platform provides good cost-effectiveness and operational simplicity and lays the methodological foundation for viscosity measurements of more complex properties of fluids.

Exploration of variable fluid properties in a pressure gradient driven generalized vortex flow dynamics using numerical approach

Motivation: Vortex flow, which refers to the movement of fluid around an axis called a vortex line, finds applications in designing aircraft wings, mixing processes in chemical, and pharmaceutical processes, and understanding flows around tornadoes and cyclones. Background: Previous research on variable properties has demonstrated they are crucial in scenarios with significant temperature gradients. Methodology: This paper looks at the boundary layer developments under a generalized vortex flow considering temperature-dependent fluid properties. The generalized vortex represents the far-field tangential velocity in a power-law format and can be simplified to two specific cases: (i) rigid-body rotation and (ii) potential vortex. For mathematical analysis, two distinct variable viscosity models are employed, where a correlation between viscosity and temperature is inversely linear, while the other one is on the exponential temperature dependency model. Numerical Method: A highly robust and convenient built-in tool of MATLAB known as bvp5c is implemented to present exact similarity analyses of the models. Main Findings: The study concludes that velocity profiles obtained under variable physical properties are lower than those calculated with constant properties. Moreover, when liquid properties are considered, the solution curves from the two variable viscosity models show a close resemblance. Thicker thermal diffusion layers and reduced boundary heat flux are associated with increased values of the power law parameter.

Heat Transfer in Unsteady Flow of Third-Grade Fluid Over a Flat Rigid Plate with Porous Medium

This study investigates the heat transfer characteristics of an unsteady flow of a third-grade fluid over a flat rigid plate embedded in a porous medium. The governing equations, including the momentum and energy equations, are derived based on the assumptions of incompressible fluid and negligible body forces. Analytical methods are employed to solve the coupled non-linear equations. The effects of various parameters, such as the porosity of the medium, thermal conductivity, and the non-Newtonian fluid properties, on the velocity, temperature profiles, and skin friction are discussed extensively. The results provide insights into optimizing heat transfer processes in engineering applications, including polymer processing and geothermal systems.

MHD rotating flow of a viscous fluid with heat sink and Prabhakar fractional derivative

The unsteady hydromagnetic free convection flow of rotating incompressible viscous fluids across an infinite moving plate with fractional thermal transportation is explored in the presence of heat source, Hall current and slip velocity effects. The Laplace transform method is used to convert the controlling PDEs corresponding to the temperature and velocity profiles into linear ODEs. To get the results, the classical model is modified to a fractional-order model using constitutive relations of the generalized Fourier’s law for heat flux. After making the equations dimensionless, solutions to the energy and velocity equations may be found. Graphs are plotted to check the insight of physical characteristics. Moreover, the Mittag-Leffler kernel is most affected. The memory of temperature improved by using generalized Mittag-Leffler kernel in comparison of exponential kernel. Some graphical representations of the temperature and velocity were created using the software application Mathcad. As a result, it is found that with the application of a generalized Mittag-Leffler kernel, the thermal and momentum boundary layers as well as the memory of fluid properties can be enhanced for larger values of the fractional parameter.

IMPROVING THE PREDICTIVE CAPABILITY OF EMPIRICAL HEAT TRANSFER CORRELATIONS FOR HYDROGEN INTERNAL COMBUSTION ENGINES

Abstract Hydrogen internal combustion is widely considered a viable technology to achieve near-zero tailpipe CO2 and NOx emissions for difficult-to-electrify applications due to the maturity of ICE technology and production facilities. 1D/0D modelling is a valuable tool for engine development due to its relatively low computational requirements, but hydrogen combustion models still require further development. A large factor is gas-to-wall heat transfer, which is higher for hydrogen combustion due to higher flame temperatures and shorter quenching distance. For accurate prediction of in-cylinder temperatures, and therefore combustion rates and knock propensity, a well calibrated heat transfer model is essential. This paper evaluates existing heat transfer models against previously published experimental cylinder pressure and heat flux data from a Cooperative Fuel Research (CFR) engine with hydrogen Port Fuel Injection (PFI). A new heat transfer correlation is developed, utilising a new fluid properties correlation to better represent the change in viscosity and conductivity with changing hydrogen concentration. Recent developments in 0D turbulence models improve the characteristic velocity calculation, which is augmented with a combustion term. This model is tested against a second dataset from the CFR engine with lambda from 1.0 - 4.0 and compression ratios of 9 - 13, showing improved performance versus previously published models. Whilst the new model provides more consistent results during combustion for variations in lambda and compression ratio, it requires improvement in its prediction of heat loss during expansion, and further validation at higher engine speeds and different engine configurations.

Reservoir Fluid PVT High-Pressure Physical Property Analysis Based on Graph Convolutional Network Model

In this paper, the high-pressure physical property analysis of reservoir fluid PVT (pressure–volume–temperature) was studied to improve the accuracy and efficiency of reservoir fluid property prediction. Due to the limitations of traditional laboratory measurement and theoretical model prediction methods, the graph convolutional network (GCN) model was introduced in this paper, and the enhanced ChebNet model was used to analyze the complex relationship between the high pressure physical property parameters. The key parameters such as bubble point pressure, volume coefficient, and crude oil viscosity were accurately predicted by using Chebyshev polynomial approximation and the matrix product optimization ChebNet model, which was constructed to represent the high pressure physical property parameters and their relationships. The experimental results showed that compared with linear regression, linear discrimination, random forest, and ordinary ChebNet models, the enhanced ChebNet model introduced in this paper presented significant advantages in evaluation indicators, and the AUC value reached the optimal value. This paper provides a new perspective and method for reservoir fluid PVT high-pressure physical property analysis and explores a new possibility for the application of graph convolutional networks in oil and gas exploration and development.