<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>flow assurance &#8211; Science</title>
	<atom:link href="https://scienmag.com/tag/flow-assurance/feed/" rel="self" type="application/rss+xml" />
	<link>https://scienmag.com</link>
	<description></description>
	<lastBuildDate>Mon, 05 Oct 2026 14:21:54 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>

<image>
	<url>https://scienmag.com/wp-content/uploads/2024/07/cropped-scienmag_ico-32x32.jpg</url>
	<title>flow assurance &#8211; Science</title>
	<link>https://scienmag.com</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">73899611</site>	<item>
		<title>Nanoclay-Boosted Polymer Additive Slashes Waxy Crude Oil Pour Points by 30 Degrees</title>
		<link>https://scienmag.com/nanoclay-boosted-polymer-additive-slashes-waxy-crude-oil-pour-points-by-30-degrees/</link>
		
		<dc:creator><![CDATA[Neil Sanderson]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 14:21:54 +0000</pubDate>
				<category><![CDATA[Chemistry]]></category>
		<category><![CDATA[cost-effective]]></category>
		<category><![CDATA[Egyptian petroleum research innovations]]></category>
		<category><![CDATA[flow assurance]]></category>
		<category><![CDATA[Herschel-Bulkley model]]></category>
		<category><![CDATA[montmorillonite nanoclay]]></category>
		<category><![CDATA[montmorillonite nanoclay applications]]></category>
		<category><![CDATA[nanoclay-based pour point depressants]]></category>
		<category><![CDATA[nanoclay-enhanced flow properties]]></category>
		<category><![CDATA[nanoclay-polymer nanocomposite additives]]></category>
		<category><![CDATA[nanocomposite]]></category>
		<category><![CDATA[nanotechnology in petroleum industry]]></category>
		<category><![CDATA[pipeline transport]]></category>
		<category><![CDATA[polymer nanocomposites for crude oil viscosity reduction]]></category>
		<category><![CDATA[pour point depressant]]></category>
		<category><![CDATA[pour point depression in heavy crude oils]]></category>
		<category><![CDATA[rheology]]></category>
		<category><![CDATA[vinyl acetate copolymer]]></category>
		<category><![CDATA[vinyl acetate-octadecyl acrylate copolymer use in oil flow]]></category>
		<category><![CDATA[viscosity reduction]]></category>
		<category><![CDATA[wax crystallization]]></category>
		<category><![CDATA[waxy crude oil]]></category>
		<category><![CDATA[waxy crude oil flow improvement]]></category>
		<category><![CDATA[waxy crude oil pipeline flow management]]></category>
		<category><![CDATA[yield stress]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=238404</guid>

					<description><![CDATA[Researchers in Egypt have shown that hybridizing a vinyl acetate–based copolymer with montmorillonite nanoclay produces liquid nanocomposite additives that cut waxy crude oil pour points by 30 degrees Fahrenheit, reduce viscosity by up to 84 percent, and remain fully effective after 55 days of aging.]]></description>
										<content:encoded><![CDATA[<p>Waxy crude oil is one of the petroleum industry&#8217;s most stubborn adversaries. When temperatures drop, the paraffin waxes dissolved in these crudes begin to crystallize, interlock, and form a three-dimensional gel network that can immobilize an entire pipeline. For operators in Egypt and other regions where high-wax crudes dominate, this means costly heating, pigging operations, and chemical dosing simply to keep oil moving. Now, a team of researchers at the Egyptian Petroleum Research Institute and Zagazig University has reported a nanocomposite additive that dramatically improves the flow behavior of waxy crude oils, and the numbers they present are striking enough to draw attention well beyond the polymer chemistry community.</p>
<p>Writing in Polymer Bulletin, the group led by M. A. Sayed, Fathy Yassin, Hamza Baghi, and A. A. Ragab describes how montmorillonite (MMT) nanoclay can be hybridized with a vinyl acetate–octadecyl acrylate (VA/ODA) copolymer to create a family of liquid nanocomposite pour point depressants, abbreviated LNPPDs. The team formulated six variants with different nanoclay loadings and tested them on two Egyptian waxy crude oils, comparing the hybrids against the neat liquid polymer depressant, designated LPPD-H, that lacked any nanoclay. The central finding is that the clay-polymer synergy is not a marginal refinement but a step change in performance.</p>
<p>The headline result concerns pour point, the lowest temperature at which oil will still flow under defined test conditions. For the first crude, Oil-A, the untreated pour point stood at a punishing 75 degrees Fahrenheit, a temperature that would render the oil effectively immobile during winter transport without intensive heating. Treatment with the hybrid additive LNPPD-5, which carries 1.5 percent nanoclay, pushed the pour point down to 45 degrees Fahrenheit, a reduction of 30 degrees. At the same time, dynamic viscosity at 73 degrees Fahrenheit fell by 84 percent, meaning the treated oil required far less pumping energy to move through a pipeline.</p>
<p>The second crude told a complementary story. With Oil-B, the best-performing formulation, LNPPD-3 containing 0.75 percent nanoclay, achieved a 96.3 percent reduction in yield value. Yield stress is arguably the more engineer-critical parameter: it measures the force needed to restart flow in a gelled pipeline after a shutdown. A near-total collapse of yield value implies that a pipeline filled with treated Oil-B could be restarted with a small fraction of the pressure that would otherwise be required, which translates directly into avoided downtime and avoided emergency intervention.</p>
<p>To move beyond single-point measurements, the researchers subjected their rheological data to mathematical modeling using the Herschel-Bulkley model, the standard constitutive equation for fluids that combine a yield stress with shear-thinning behavior. The fitted parameters revealed a significant reduction in the consistency index, K, which quantifies the overall resistance of the fluid to flow. Equally important, the flow behavior shifted toward Newtonian character, meaning the treated oils behaved more like simple liquids whose viscosity is independent of shear rate. For pipeline designers, Newtonian behavior is far easier to model and predict than the complex, time-dependent flow of gelled waxy crude, so this shift represents a genuine gain in operational confidence.</p>
<p>The mechanism behind the synergy is rooted in the complementary roles of the two components. Vinyl acetate–octadecyl acrylate copolymers belong to a well-studied class of pour point depressants: the long octadecyl acrylate side chains are structurally similar to the paraffin molecules in the oil, allowing the polymer to co-crystallize with growing wax crystals, while the polar vinyl acetate groups disrupt the regularity of the crystal lattice. The result is smaller, more dispersed wax crystals that fail to interlock into a percolating gel. Montmorillonite, a layered silicate clay that exfoliates into nanoscale platelets, adds a second dimension to this intervention. The platelets provide enormous surface area on which wax crystallization can be nucleated and dispersed, and they act as physical barriers that impede the growth and aggregation of wax crystals, reinforcing the structural disruption initiated by the polymer.</p>
<p>Perhaps the most persuasive aspect of the study is its treatment of durability. Additives that perform well in fresh laboratory samples sometimes lose effectiveness over weeks of storage as polymers age, aggregates form, or the additive partitions away from the wax phase. The Egyptian team therefore ran long-term stability tests, and the outcome was unambiguous: the developed LNPPDs retained their full efficiency after 55 days of aging. For an industry in which additives must survive extended storage in tanks, blending facilities, and dosing systems before ever reaching the pipeline, this aging result may matter as much as the headline performance figures.</p>
<p>The work also fills a methodological gap that the authors identify in the existing literature. While nanoparticles of many kinds, including silica, graphene oxide, magnetite, and carbon nanotubes, have been grafted or blended with polymeric depressants in recent years, the field has lacked systematic mathematical modeling of the copolymer-nanoclay synergy. By anchoring their performance claims in Herschel-Bulkley parameter analysis across six systematically varied nanoclay loadings, the researchers offer a framework that other laboratories can adopt to compare nanocomposite depressants on a quantitative rather than anecdotal basis. The observation that the optimal nanoclay content differed between the two crudes, 1.5 percent for Oil-A and 0.75 percent for Oil-B, underscores that formulation must be tuned to the specific wax content and composition of each crude rather than applied as a universal recipe.</p>
<p>The commercial logic of the approach is also notable. The additives are described as liquid nanocomposite pour point depressants, and the underlying copolymer platform was previously developed by the same group as an energy-saving liquid formulation for waxy crude. Liquid additives avoid the solvent-handling and dissolution steps associated with solid or waxy depressant products, simplifying field deployment. Because the nanoclay component is montmorillonite, an abundant and inexpensive natural mineral, the incremental cost of the hybridization strategy is likely modest relative to the savings achievable through reduced heating, reduced pumping power, and fewer gel-remediation events.</p>
<p>Flow assurance remains one of the largest hidden operating costs in the global oil industry, and every degree of pour point depression and every percentage point of viscosity reduction compounds across thousands of kilometers of pipeline. If the Egyptian results can be replicated at field scale on other high-wax crudes, hybrid polymer-nanoclay additives could become a standard tool in the flow-assurance toolkit, sitting alongside thermal management and mechanical pigging. The study demonstrates that sometimes the most effective way to improve a mature technology is not to replace it but to reinforce it, one nanometer-thick clay platelet at a time, with a mineral that has been sitting underfoot all along.</p>
<p><strong>Subject of Research:</strong> Nanoclay-polymer hybrid pour point depressants for improving the flow of waxy crude oil</p>
<p><strong>Article Title:</strong> Synergistic effect of MMT nanoclay on vinyl acetate-based copolymer for enhanced pour point temperature and rheological behavior in waxy crude oils</p>
<p><strong>Article References:</strong> Sayed, M. A., Yassin, F., Baghi, H., &amp; Ragab, A. A. (2026). Synergistic effect of MMT nanoclay on vinyl acetate-based copolymer for enhanced pour point temperature and rheological behavior in waxy crude oils. <em>Polymer Bulletin, 83</em>(12), Article 668. <a href="https://doi.org/10.1007/s00289-026-06732-8" rel="noopener noreferrer">https://doi.org/10.1007/s00289-026-06732-8</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s00289-026-06732-8" rel="noopener noreferrer">10.1007/s00289-026-06732-8</a></p>
<p><strong>Keywords:</strong> waxy crude oil, pour point depressant, montmorillonite nanoclay, vinyl acetate copolymer, rheology, Herschel-Bulkley model, yield stress, flow assurance, nanocomposite, viscosity reduction, wax crystallization, pipeline transport</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">238404</post-id>	</item>
		<item>
		<title>High-Order Flux Reconstruction Method Brings Sharper Simulations to Two-Phase Pipeline Flow</title>
		<link>https://scienmag.com/high-order-flux-reconstruction-method-brings-sharper-simulations-to-two-phase-pipeline-flow/</link>
		
		<dc:creator><![CDATA[Audrey Campbell]]></dc:creator>
		<pubDate>Sat, 03 Oct 2026 18:42:04 +0000</pubDate>
				<category><![CDATA[Technology and Engineering]]></category>
		<category><![CDATA[advanced numerical techniques for fluid dynamics]]></category>
		<category><![CDATA[application of flux reconstruction in two-phase flow]]></category>
		<category><![CDATA[computational fluid dynamics]]></category>
		<category><![CDATA[computational methods for oil and gas transport]]></category>
		<category><![CDATA[flow assurance]]></category>
		<category><![CDATA[flux reconstruction]]></category>
		<category><![CDATA[high-fidelity pipeline flow simulations]]></category>
		<category><![CDATA[high-order flux reconstruction method]]></category>
		<category><![CDATA[hMLP limiter]]></category>
		<category><![CDATA[hyperbolicity]]></category>
		<category><![CDATA[numerical simulation]]></category>
		<category><![CDATA[oil industry]]></category>
		<category><![CDATA[oil industry pipeline modeling]]></category>
		<category><![CDATA[pipelines]]></category>
		<category><![CDATA[pressure and phase velocity prediction in pipelines]]></category>
		<category><![CDATA[SIMPLE algorithm]]></category>
		<category><![CDATA[stability of multiphase flow models]]></category>
		<category><![CDATA[staggered grid]]></category>
		<category><![CDATA[two-fluid four-equation model]]></category>
		<category><![CDATA[two-fluid model]]></category>
		<category><![CDATA[two-fluid model stability improvements]]></category>
		<category><![CDATA[two-phase flow]]></category>
		<category><![CDATA[two-phase flow in oil pipelines]]></category>
		<category><![CDATA[two-phase pipeline flow simulation]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=231402</guid>

					<description><![CDATA[Brazilian researchers have, for the first time, applied a very high-order Flux Reconstruction method to the two-fluid four-equation pipeline model, achieving sharper and more stable two-phase flow predictions than industry-standard schemes.]]></description>
										<content:encoded><![CDATA[<p>Every day, thousands of kilometers of steel pipelines carry mixtures of oil, water, and gas from deep wells to processing facilities, and the engineers who manage them rely on computer simulations to predict what is happening inside. A new study published in Results in Engineering reports the first successful application of a very high-order numerical technique, known as the Flux Reconstruction (FR) method, to the one-dimensional two-fluid four-equation model that underpins many commercial pipeline simulators. The work, led by Anderson V. do Nascimento and colleagues at Brazilian research institutions, demonstrates that the approach can deliver markedly sharper predictions of pressure, phase velocities, and volume fractions than the first-order schemes still common in industry, while remaining stable in situations that have historically destabilized two-fluid models.</p>
<p>The two-fluid four-equation model is a compact mathematical description of two-phase flow in which each phase, for example liquid and gas, obeys its own conservation equations for mass and momentum, but both phases share a single pressure field. This shared-pressure assumption makes the model relatively easy to implement and computationally affordable, which is why variants of it appear in reactor safety codes such as RELAP, TRAC, and CATHARE, and in pipeline simulators used across the oil industry. However, the formulation carries a well-known mathematical weakness: when two fluids flow together under a common pressure with different velocities, the system of equations can lose a property called hyperbolicity. This loss is tied to the physical Kelvin-Helmholtz instability and renders the underlying problem ill-posed, producing violent non-physical oscillations that can destroy a simulation.</p>
<p>To tame this instability, the researchers incorporated an artificial interfacial pressure-difference term based on the CATHARE model, a formulation originally developed for nuclear thermal-hydraulics. This term introduces a controlled amount of numerical diffusion that keeps the equations well-behaved without requiring manual tuning of an adjustable shape parameter, an advantage over the alternative Toumi model. The team also combined the high-order spatial method with a staggered-grid arrangement, in which scalar quantities such as pressure and density are stored at cell centers while velocities live on cell faces. This classic layout prevents a troublesome pressure-velocity decoupling phenomenon, and the authors coupled it with the semi-implicit SIMPLE algorithm, a robust pressure-correction procedure widely used in practical flow solvers.</p>
<p>The Flux Reconstruction method itself is an elegant framework developed by H.T. Huynh in 2007. Within each control volume, the solution is represented by a polynomial of chosen degree, and the fluxes are reconstructed as continuous functions across the domain by applying correction functions at element interfaces, informed by an approximate Riemann solver. A remarkable feature of FR is its unifying character: by swapping correction functions, it can recover simplified versions of the Nodal Discontinuous Galerkin, Spectral Volume, and Spectral Difference methods, and even generate new schemes. Compared with the popular Discontinuous Galerkin approach, FR requires fewer volumetric integration operations, making it computationally lighter, and its minimal inter-element connectivity favors parallel scalability on modern hardware.</p>
<p>In the new implementation, the researchers evaluated polynomial degrees from P1 to P3, corresponding to formal accuracy from second to fourth order for smooth solutions, with P2 and P3 classified as very high order. Two correction functions were tested, one yielding an FR-NDG variant and the other an FR-SD variant. A key technical innovation lies in how the staggered grids communicate: instead of the low-order interpolations that conventional finite-volume schemes require, variables are transferred between the primal and dual grids directly through the FR polynomial reconstructions, preserving the high-order spatial representation throughout the calculation. Non-physical oscillations near steep fronts are controlled by the hierarchical Multidimensional Limiting Process, or hMLP limiter, and time integration uses a third-order Total Variation Diminishing Runge-Kutta scheme with a dynamically adjusted time step.</p>
<p>The team validated the framework on five benchmark problems of escalating difficulty. The first, a smooth non-linear transport problem derived from the inviscid Burgers equation, isolated the spatial discretization from the complexities of two-fluid physics. The results confirmed that the FR schemes achieved convergence rates close to their theoretical asymptotic orders, with the P3 variants approaching fourth-order accuracy, while the First-Order Upwind method, the workhorse of commercial one-dimensional pipeline simulators, lagged far behind. In cost-benefit terms, the FR-NDG-P3 scheme delivered the best accuracy per unit of CPU time, and the FR-NDG variant consistently edged out its FR-SD counterpart on this particular problem.</p>
<p>The second and third benchmarks introduced genuine two-phase discontinuities. In the moving-discontinuity case, a sharp front in the gas volume fraction is advected through a horizontal pipe, and in the classical water faucet problem, water accelerates downward under gravity through air in a vertical duct, creating a shock-like front. On both tests, all FR variants outperformed MUSCL, a standard second-order scheme, with the FR-NDG-P1 results already more accurate. A pointwise error analysis for the water faucet problem at a fixed location showed the First-Order Upwind scheme erring by 13.30 percent, MUSCL by 6.41 percent, and the FR formulations by roughly 5 to 6 percent, using only 64 control volumes. Notably, those FR errors were comparable to or better than values previously reported in the literature on a mesh ten times finer.</p>
<p>Perhaps the most intriguing finding came from a hyperbolicity analysis of the water faucet case. By computing the eigenvalues of the governing system along the pipe, the researchers identified regions where the eigenvalues turn complex, signaling local loss of hyperbolicity. They found that the high-order FR reconstruction detects the onset of these non-hyperbolic conditions earlier and over a wider region than the lower-order MUSCL scheme, because the polynomial reconstruction is more sensitive to incipient gradients. Rather than being a defect, the authors argue this makes the FR framework useful as a diagnostic tool for locating the ill-posed regions inherent to the single-pressure two-fluid model, while the stabilization mechanisms keep the solution stable and physically consistent even where complex eigenvalues appear.</p>
<p>The final two cases pushed the method toward industrial reality. In a downward vertical annular flow of oil and water with wall and interfacial friction, the in-house solver reproduced pressure, water velocity, and oil volume fraction profiles from the commercial simulator ALFAsim with maximum relative errors of just 1.55, 0.2, and 0.7 percent respectively, differences the authors attribute mainly to differing empirical friction closures rather than the numerics. The closing feasibility study simulated a kilometer-long vertical well in which a sudden increase in water cut propagates upward, a scenario of direct relevance to petroleum production. Using only 128 control volumes, the FR solutions tracked the front predicted by a refined ALFAsim run with 7,500 control volumes, with L1 errors between 0.138 and 0.170 percent, whereas ALFAsim on the same coarse mesh deviated by about 2.35 percent, and front positions agreed within roughly 1.5 to 3.4 meters versus 5.5 meters for the coarse commercial run.</p>
<p>The study&#8217;s authors caution that comparisons with ALFAsim must be interpreted carefully, since the two simulators rely on different physical and closure models, but the overall message is clear: very high-order Flux Reconstruction can dramatically reduce numerical diffusion and mesh requirements in two-phase pipeline simulation. For an industry where flow assurance failures, from hydrate plugs to slug transients, translate into enormous financial and environmental costs, a method that resolves sharp fronts on coarse grids is more than an academic curiosity. The team now plans to extend the framework to thermal effects, flow-pattern prediction, and automatic h-p adaptation, steps that could eventually bring this class of high-fidelity simulation into routine engineering practice.</p>
<p><strong>Subject of Research:</strong> Very high-order Flux Reconstruction numerical simulation of one-dimensional two-fluid four-equation two-phase flow in pipelines</p>
<p><strong>Article Title:</strong> Numerical simulation of the 1-D two-fluid four-equation model in pipelines using the very high order flux reconstruction (FR) method</p>
<p><strong>Article References:</strong> Nascimento, A. V. D., Silva, C. E., Silva, G. M. D., Freitas, T. C., Fontes, R. A., Silva, M. T. D., Silva, J. D. M., Lyra, P. R., Antunes, A. R., &amp; Carvalho, D. K. D. (2026). Numerical simulation of the 1-D two-fluid four-equation model in pipelines using the very high order flux reconstruction (FR) method. <em>Results in Engineering, 32</em>, Article 113206. <a href="https://doi.org/10.1016/j.rineng.2026.113206" rel="noopener noreferrer">https://doi.org/10.1016/j.rineng.2026.113206</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1016/j.rineng.2026.113206" rel="noopener noreferrer">10.1016/j.rineng.2026.113206</a></p>
<p><strong>Keywords:</strong> flux reconstruction, two-fluid model, two-phase flow, pipelines, computational fluid dynamics, hyperbolicity, SIMPLE algorithm, staggered grid, hMLP limiter, oil industry, flow assurance, numerical simulation</p>
]]></content:encoded>
					
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">231402</post-id>	</item>
	</channel>
</rss>
