Deni Hidayatulloh’s Post

noCnX Technologies Engineering's Simulation Expertise: Comprehensive Pump Analysis: Our dedicated engineering teams at noCnX Technologies Engineering possess unparalleled simulation capabilities across a wide spectrum of pump types. With a proven track record in the field, we leverage cutting-edge technology and industry-leading software to provide precise and thorough pump analysis. Whether it's centrifugal, reciprocating, diaphragm, or any other pump design, our simulations ensure optimal performance, efficiency, and reliability. From initial design validation to troubleshooting existing systems, trust noCnX Technologies Engineering for in-depth pump simulation expertise that meets the most demanding engineering challenges. #PumpSimulation #EngineeringAnalysis #FluidDynamics #SimulationExpertise #PumpEfficiency #EngineeringSolutions #MechanicalSimulation #EngineeringInnovation #SimulationTechnology #PumpDesign #FluidMechanics #EngineeringExcellence #PumpPerformance #EngineeringSimulations #noCnXEngineering #PumpAnalysis #DesignValidation #SystemOptimization #EngineeredSolutions #ReliabilityTesting https://lnkd.in/dtckYUM3

🚨Diagnostic Fracture Injection Test (DFIT) 🚨Ken Nolte said: “If you don’t do this, and do it right, don’t even think of using a numerical simulator for frac design.” 💡Design and execute the test correctly to get usable results 📍High enough rate 📍Short pump time 📍Clean, simple fluid 💡Identify the correct flow regimes for analysis and apply the appropriate methods, plots, and equations 💡Be honest about the results and don’t force interpretations that are not supported by the data 💡Don’t fall for “new” “advanced” unproven or fallacious interpretation methods #petroleumengineering #hydraulicfracturing #stimulation #reservoirengineering #optimization #training #oilandgas #frac

Optimizing design by harnessing the power of CFD simulation. #powergeneration,#bluehydrogen#hydrogenstorage#lngfacility

fluid flow (fluent) #cfd Analysis of venturimeter in #Ansys

This is a transient CFD simulation by Eulerian method with k-e turbulence model for three-phase flow of air, oil, and water in a tank; initially, the water is at the bottom, oil in the middle, and air on top because of gravity.   There is a small orifice on the bottom of the tank, through which air and oil enter the tank alternatively in 1 m/s at an interval of 1s.   The video below shows the distribution of density (Left side) and the oil superficial velocity (Right side) at different times.   This multiphase CFD simulation has many applications, such as to drug delivery, oil industry, and chemical-, nuclear-, and mechanical engineering, etc. #cfd #computationalfluiddynamics #multiphase flow #twopahse flow #drugdelivery #oilindustry #offshoreengineering #chemicalengineering #nuclearengineering #mechanicalengineering Read more about CFD simulations in many different industries: 👉 http://www.advanceddo.com

3D Modeling of Saturation and Depletion of Fluids, with mudloggig gases C1 to C5 integrating wireline, PVT, petrophysical and production data.

CFD simulation of monoethylene glycol and water mixing in a Hele-Shaw cell with variable Turbulent Schmidt Number troughout the domain Monoethylene glycol (MEG) is widely used as a thermodynamic inhibitor in oil and gas pipelines. Its effectiveness lies in its ability to shift hydrate equilibrium conditions, moving them away from the typical pressure-temperature conditions found in pipelines. This capability allows for complete or partial avoidance of hydrate formation, ensuring smoother and safer pipeline operations. For this CFD simulation, a custom MEG-water mixture viscosity model was used in function of the MEG volume fraction, and a different Turbulent Schmidt Number was used in different sections of the cell. Also, a custom molecular diffusivity model was used. The simulation was done using Ansys CFX. The MEG volume fraction was measured 5 minutes after the injection ended at 24 points within the cell, and the results were compared to those from an experiment conducted in a real Hele-Shaw cell in NUEM - Multiphase Flow Research Center. The average error was about 3%. This leads us to believe that the turbulent Schmidt Number should vary troughout the domain. However, we couldn't find any papers addressing this issue to date. #CFD #FluidDynamics #Simulation #Engineering #HeleShawCell #MonoethyleneGlycol #WaterMixing #Research #Innovation #OilAndGas #PipelineSafety

Simulation analysis of gas–solid flow characteristics and water evaporation in flue gas semi-dry desulphurization process based on CPFD method

Simulation Performance Improvement hints Known convergence problems · Negative value of 1/Bg due to negative pressure · Extrapolation of PVT Table - Provide additional undersaturated lines - Fix negative compressibility issue · Saturation pressure for initialization are out of PVT data range. · Gas viscosity does not honor monotonicity · Mixed PVT regions. · Wells need to be provided realistic BHP during History Matching phase Solution: a. PVT clean up • Ensure monotonicity (gas viscosity) • Add undersaturated lines to prevent extrapolation • Extend PVT data to cover simulation pressure range b. Realistic BHP during history match period • Reassigning realistic BHP limit to all wells • Check if there are wells are operating at very low BHP • Thus, the change reduces production and causes vector change at HM level c. Remove TUNING • TUNING has to be used with care as it has to be designed case specific • Removing TUNING returns stability of results and there is no more negative pressure observe in the grid. d. Deactivate PVT mixing cells : • Deactivating these cells in this case does not impact vector change. e. Optimizing domain partitioning • Domain partitioning in simulator has to be optimized.

🌪️💡 Exploring New Frontiers in CFD modeling: The Importance of CFD Simulation Using DPM Models for Predicting Erosion in Pipelines and Equipment 💡🌪️ When it comes to designing and operating pipeline systems and equipment in challenging environments such as those found in the oil and gas industry, mining, or chemical processes, accurately predicting the effects of erosion is crucial. This is where Computational Fluid Dynamics (CFD) simulation with Discrete Phase Models (DPM) shines. 🔍 What is CFD simulation with DPM models? CFD is a powerful tool that allows us to model and analyze the behavior of fluids in complex systems. By introducing DPM models, we can track the movement and impact of solid particles suspended in the fluid flow. This is essential for understanding how erosion occurs and how it can affect the integrity of pipelines and equipment over time. 🛠️ Why is CFD simulation with DPM models important? -> Accuracy in erosion prediction: By considering the interaction between solid particles and the fluid, DPM models enable more precise prediction of erosion locations and wear rates over time. -> Design optimization: With the ability to simulate different operational scenarios and equipment geometries, we can optimize the design to minimize the impact of erosion.. -> Cost and risk reduction: Identifying potential erosion issues during the design or operational phase allows for preventive measures to be taken, reducing costs associated with unplanned maintenance and minimizing equipment failure risks. #CFDSimulation #DPMModels #PipelineErosion #Engineering #Industry