Crude Oil rose to 64.68 USD/Bbl on September 2, 2025, up 1.04% from the previous day. Over the past month, Crude Oil's price has fallen 2.44%, and is down 12.67% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on September of 2025.

Brent fiel am 29. August 2025 auf 67,45 USD/Bbl, ein Rückgang um 0,78% gegenüber dem Vortag. Im Laufe des letzten Monats ist der Preis von Brent um 6,93% gefallen und im Vergleich zum Vorjahr um 12,32% gesunken, basierend auf dem Handel eines Differenzkontrakts (CFD), der den Benchmark-Markt für diese Ware verfolgt. Diese Werte, historische Daten, Prognosen, Statistiken, Diagramme und ökonomische Kalender - Brent - Rohöl - Futures Contract - Preise.

Heating Oil rose to 2.31 USD/Gal on September 1, 2025, up 1.65% from the previous day. Over the past month, Heating Oil's price has fallen 0.45%, but it is still 1.17% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Heating oil - values, historical data, forecasts and news - updated on September of 2025.

This dataset contains computational fluid dynamics (CFD) simulations of oil jets and plumes, which were validated with experimental data conducted in an Ohmsett tank. This dataset supports the publication: Daskiran, Cosan, Fangda Cui, Michel C. Boufadel, Scott A. Socolofsky, Joseph Katz, Lin Zhao, Tanmay Ozgokmen, Brian Robinson, and Thomas King. 2021. Transport of oil droplets from a jet in crossflow: Dispersion coefficients and Vortex trapping. Ocean Modelling, 158, 101736. DOI: 10.1016/j.ocemod.2020.101736.

The present study deals with two-phase non-Newtonian pseudoplastic crude oil and water flow inside horizontal pipes simulated by ANSYS. The study helps predict velocity and velocity profiles, as well as pressure drop during two-phase crude-oil–water flow, without complex calculations. Computational fluid dynamics (CFD) analysis will be very important in reducing the experimental cost and the effort of data acquisition. Three independent horizontal stainless steel pipes (SS-304) with inner diameters of 1 in., 1.5 in., and 2 in. were used to circulate crude oil with 5, 10, and 15% v/v water for simulation purposes. The entire length of the pipes, along with their surfaces, were insulated to reduce heat loss. A grid size of 221,365 was selected as the optimal grid. Two-phase flow phenomena, pressure drop calculations, shear stress on the walls, along with the rate of shear strain, and phase analysis were studied. Moreover, velocity changes from the wall to the center, causing a velocity gradient and shear strain rate, but at the center, no velocity variation (velocity gradient) was observed between the layers of the fluid. The precision of the simulation was investigated using three error parameters, such as mean square error, Nash-Sutcliffe efficiency, and RMSE-standard deviation of observation ratio. From the simulation, it was found that CFD analysis holds good agreement with experimental results. The uncertainty analysis demonstrated that our CFD model is helpful in predicting the rheological parameters very accurately. The study aids in identifying and predicting fluid flow phenomena inside horizontal straight pipes in a very effective way.

Oil and gas flow from the Macondo255 wellhead were simulated using a large eddy simulation (LES) approach. This dataset includes the simulated oil and gas holdups (both along the radial and centerline direction), flow velocity, turbulence dissipation rate, and entrainment coefficient. The data was generated by CFD-LES approach using FLUENT software and post-processed by TECPLOT and Excel.

Urals Oil rose to 62.89 USD/Bbl on August 29, 2025, up 1.08% from the previous day. Over the past month, Urals Oil's price has fallen 8.38%, and is down 15.11% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Urals Crude.

Palm Oil rose to 4,474 MYR/T on September 2, 2025, up 2.22% from the previous day. Over the past month, Palm Oil's price has risen 6.88%, and is up 13.76% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Palm Oil - values, historical data, forecasts and news - updated on September of 2025.

oil supply to top ring and land pressure

Numerical experiments were conducted using an advanced high-resolution, non-hydrostatic 3D multi-phase model, incorporating capillary forces (ANSYS Fluent computational fluid dynamics software). These numerical simulations reproduced the spreading and contraction (due to the application of dispersant) of crude and machine oil on the surface of the water. These simulations were conducted from September to November 2015.

By integration of population balance VDROP-J model with computational fluid dynamics (CFD) simulation model of waves, the droplet formation under wave actions is simulated. The data supports the following publications.

Cui, Fangda, Cosan Daskiran, Thomas King, Brian Robinson, Kenneth Lee, Joseph Katz, and Michel C. Boufadel. 2020. Modeling oil dispersion under breaking waves. Part I: Wave hydrodynamics. Environmental Fluid Mechanics 20, 1527–1551. DOI: 10.1007/s10652-020-09753-7

Cui, Fangda, Lin Zhao, Cosan Daskiran, Kenneth Lee, Joseph Katz, and Michel C. Boufadel. 2020. Modeling oil dispersion under breaking waves. Part II: Coupling Lagrangian particle tracking with population balance model. Environmental Fluid Mechanics 20, 1553–1578. DOI: 10.1007/s10652-020-09759-1

Computational Fluid Dynamics (CFD) Simulation Tools Market Outlook

The global Computational Fluid Dynamics (CFD) simulation tools market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach USD 5.8 billion by 2032, growing at a CAGR of 9.5% during the forecast period. This growth is primarily driven by the increasing demand for high-fidelity simulations in various industries, including aerospace, automotive, and energy, which require sophisticated tools for fluid flow analysis and optimization.

One of the key growth factors driving the CFD simulation tools market is the rising need for precision in engineering designs and the growing complexity of systems. Modern engineering projects require accurate and detailed analyses to ensure efficiency and safety, which CFD tools can provide. These tools help in simulating the behavior of fluids and gases in various environments, allowing engineers to predict and enhance performance without the need for expensive and time-consuming physical prototypes. This adoption is particularly significant in industries like aerospace and automotive, where optimizing aerodynamic performance is crucial.

The increasing use of CFD tools in the energy sector is another significant factor contributing to market growth. With the global push towards renewable energy sources, CFD simulation tools are being extensively used to optimize the design and performance of wind turbines, solar panels, and other renewable energy systems. These tools help in analyzing and improving the efficiency of energy conversion processes, thereby supporting the transition to sustainable energy solutions. Additionally, the oil and gas industry also relies heavily on CFD tools to enhance exploration and production processes, further fueling market expansion.

Technological advancements in CFD software are also playing a critical role in market growth. The integration of artificial intelligence (AI) and machine learning (ML) algorithms into CFD tools has significantly enhanced their capabilities, allowing for more accurate and faster simulations. These advancements have expanded the applicability of CFD tools, enabling their use in more complex and varied scenarios. The continuous improvement in computational power and the development of user-friendly interfaces have made CFD tools more accessible to a broader range of users, from large corporations to small and medium-sized enterprises (SMEs).

The integration of FEA & CFD Simulation and Analysis Softwares has revolutionized the way engineers approach complex design challenges. These tools allow for a comprehensive analysis of both fluid dynamics and structural integrity, providing a holistic view of how different forces interact within a system. By combining finite element analysis (FEA) with computational fluid dynamics (CFD), engineers can simulate real-world conditions with greater accuracy, leading to more reliable and efficient designs. This integration is particularly beneficial in industries such as aerospace and automotive, where the interplay between aerodynamic forces and structural stresses is critical. As these industries continue to push the boundaries of innovation, the demand for integrated simulation solutions is expected to rise, further driving the growth of the market.

Regionally, North America holds a significant share of the CFD simulation tools market, driven by the presence of major aerospace, automotive, and energy companies. The region's strong focus on innovation and advanced technologies supports the adoption of CFD tools. Europe is another key market, particularly in the automotive and aerospace sectors. The Asia Pacific region is expected to witness the highest growth rate, attributed to the rapid industrialization and increasing investments in infrastructure and technology. The growing manufacturing sector in countries like China and India is also contributing to the increased demand for CFD simulation tools.

Component Analysis

The CFD simulation tools market can be segmented by component into software and services. The software segment holds the lion's share of the market, driven by the continuous development of advanced simulation tools that offer high precision and efficiency. These software solutions are designed to handle complex simulations, enabling users to model and analyze fluid dynamics scenarios accurately. The demand for software is particularly high in sectors like aerospace and automoti

Yearly citation counts for the publication titled "Pore-Scale Evaluation of Polymers Displacing Viscous Oil – Computational Fluid Dynamics Simulation of Micromodel Experiments".

This repository contains simulation cases conducted using OpenFOAM 5.x on a range of digital rocks. These cases are publicly accessible to researchers, providing all simulation results in the form of Excel datasets, plots, and codes for different scenarios.We hope that this repository will be a valuable resource for researchers, professors, and students alike.Mohammad Ghodsi Institute of Petroleum Engineering, University of Tehran

Interaction between the wind-driven shear and the wave-induced Stokes drift in the upper ocean leads to Langmuir circulation consisting of wind-aligned counter-rotating vortices. In inner-shelf regions up to 30 meters in depth undergoing strong wind and wave forcing during the passage of storms, Langmuir cells have been observed reaching the bottom of the water column while increasing in intensity and coherency (Gargett and Wells, 2007; Gargett and Savidge, 2020). These cells have been denoted as Langmuir supercells (LS) due to their significant impact on the turbulence dynamics throughout the entire water column and their distinct structure compared to ordinary Langmuir circulation in the upper ocean mixed layer. A Reynolds-averaged Eulerian formulation is developed resolving LS as a secondary component to the wind-driven mean shear current, and this formulation is combined with Lagrangian particle tracking to investigate oil droplet entrainment induced by the LS. The efficiency of the cells in mixing oil droplets of 500 microns throughout the water column is compared to wind-driven flow with 0.025 and 0.1 N/m^-2 forces. Characteristic timescales of the initial accumulation of oil droplets in submerged Stommel retention zones and the subsequent homogenization of the droplets about these zones are established. The dataset includes modeled particle trajectories for cases with a Langmuir number of 0.7 and wavelength to depth ratios of 4/3 and 6 and a y-z slice of the velocity field at x position 0.785398 at the final step of the model run. Also included are particle trajectory animations for wavelength/depth = 6, Langmuir number 0.5, and two different wind regimes. This dataset supports the publication: Perez, Anthony J., Fangda Cui, Juan Peñaloza-Gutierrez, Seyed Zeidi, Nityanand Sinha, Michel Boufadel, Carlowen A. Smith, David W. Murphy, and Andrés E. Tejada-Martínez. (2021). Simulation of vertical dispersion of oil droplets by Langmuir supercells through a Reynolds-averaged Eulerian formulation combined with Lagrangian particle tracking. Ocean Engineering, 235, 109043. doi:10.1016/j.oceaneng.2021.109043.

Global Computational Fluid Dynamics is segmented by Application (Aerospace, Automotive, HVAC, Oil & Gas, Biomedical Engineering), Type (Steady State, Transient, Thermal, Multiphase, Turbulence Models) and Geography(North America, LATAM, West Europe, Central & Eastern Europe, Northern Europe, Southern Europe, East Asia, Southeast Asia, South Asia, Central Asia, Oceania, MEA)

The Computational Fluid Dynamics (CFD) software market is experiencing robust growth, driven by increasing demand across diverse industries. The market, estimated at $5 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of around 10% through 2033, reaching approximately $12 billion. This expansion is fueled by several key factors: the rising adoption of CFD simulations in automotive and aerospace design for optimizing aerodynamics and fuel efficiency; the growing need for precise fluid flow modeling in the energy sector (oil & gas, renewable energy); and the increasing reliance on CFD in biomedical engineering for applications like drug delivery and cardiovascular simulations. Furthermore, advancements in high-performance computing (HPC) are enabling more complex and accurate simulations, further bolstering market growth. Major players like ANSYS, Siemens, and Dassault Systèmes are continuously investing in R&D to enhance software capabilities and expand their market reach. The trend toward cloud-based CFD solutions is also gaining momentum, offering enhanced accessibility and scalability. However, market growth is not without its challenges. High software costs and the need for specialized expertise to effectively utilize CFD tools pose significant barriers to entry for smaller companies. Furthermore, the complexity of certain simulations and the potential for inaccurate results if not properly validated can limit adoption in some sectors. Despite these restraints, the overall outlook for the CFD software market remains positive, with continued growth expected across various industries and geographic regions. The increasing availability of user-friendly interfaces and the integration of CFD with other engineering simulation tools are likely to further stimulate market expansion in the coming years.

Library of Wroclaw University of Science and Technology scientific output (DONA database)

The offshore structural analysis software market is experiencing robust growth, driven by the increasing demand for efficient and reliable solutions in the offshore oil and gas, renewable energy, and marine sectors. The market's expansion is fueled by several factors, including the rising complexity of offshore structures, stricter regulatory compliance requirements demanding rigorous analysis, and the ongoing need to optimize designs for cost-effectiveness and safety. The adoption of advanced simulation techniques, such as finite element analysis (FEA) and computational fluid dynamics (CFD), integrated within these software solutions, is a significant contributor to this growth. Key players like DNV GL AS, John Wood Group PLC, and Bentley Systems are leading the innovation in this space, constantly improving the accuracy and efficiency of their software through updates and feature enhancements. The market is segmented based on software type (e.g., FEA, CFD), application (e.g., offshore wind, oil & gas platforms), and deployment model (cloud-based vs. on-premise). The increasing adoption of cloud-based solutions is anticipated to further drive market growth due to accessibility and scalability benefits. While initial investment costs may be a restraint for smaller companies, the long-term return on investment through improved design accuracy and reduced risks significantly outweighs these costs. We project continued expansion in this sector with a notable contribution from the growing offshore wind energy market which necessitates sophisticated structural analysis for large-scale installations. The forecast period (2025-2033) suggests a continued upward trajectory for the offshore structural analysis software market. This growth will be driven by ongoing projects in offshore oil and gas exploration, the rapid expansion of offshore wind farms globally, and the increasing need for robust infrastructure to support ocean-based renewable energy sources. Furthermore, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into these software platforms is expected to enhance analytical capabilities, further improving design accuracy and reducing project timelines. Geographical expansion, particularly in Asia-Pacific regions experiencing rapid infrastructural development, will contribute substantially to market growth. While competition amongst established players is expected to intensify, the overall market outlook remains positive, indicating significant opportunities for both established players and emerging technology providers. This growth, however, needs to carefully navigate the challenges posed by fluctuating energy prices, economic uncertainty, and the need for continuous skill development to effectively utilize sophisticated software solutions.

We simulated the two-dimensional regular wave by using Computational Fluid Dynamics (CFD) and coupling the CFD data with Lagrangian Particle Tracking method to evaluate the transport of oil droplet with waves. The dataset was collected from the above mentioned numerical simulation, including the wave velocity, turbulent kinetic energy, eddy diffusivity and oil droplet trajectories. This dataset supports the publication: Golshan, R., Boufadel, M.C., Rodriguez, V.A., Geng, X., Gao, F., King, T., Robinson, B., & Tejada-MartÃnez, A.E. (2018). Oil Droplet Transport under Non-Breaking Waves: An Eulerian RANS Approach Combined with a Lagrangian Particle Dispersion Model. Journal of Marine Science and Engineering. 6(1), 7; doi: 10.3390/jmse6010007