Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “FLUID FLOW”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

The effect of fluid flow due to the crystal-melt density change on the growth of a parabolic isothermal dendrite

The Ivantsov (1947) analysis of an isolated isothermal dendrite (with zero surface tension) growing into a supercooled liquid is extended to include the effects of the fluid flow due to volume contraction or expansion upon solidification. For an axisymmetric paraboloidal dendrite, an analytic solution to the Navier-Stokes equations is obtained. The magnitude of the flow is proportional to the relative density change epsilon, and the flow becomes negligible far from the surface of the dendrite. The temperature field consistent with this flow can also be found explicitly. The well-known expression that relates the dimensionless supercooling to the Peclet number in the absence of fluid flow is modified for nonzero epsilon, but the effect is of order epsilon and hence is seen to be minor for most values of epsilon and dimensionless supercooling that occur in practice.

Mcfadden, G. B.↗
NASA NTRS2013

Generating a Simulated Fluid Flow Over an Aircraft Surface Using Anisotropic Diffusion

A fluid-flow simulation over a computer-generated aircraft surface is generated using a diffusion technique. The surface is comprised of a surface mesh of polygons. A boundary-layer fluid property is obtained for a subset of the polygons of the surface mesh. A pressure-gradient vector is determined for a selected polygon, the selected polygon belonging to the surface mesh but not one of the subset of polygons. A maximum and minimum diffusion rate is determined along directions determined using a pressure gradient vector corresponding to the selected polygon. A diffusion-path vector is defined between a point in the selected polygon and a neighboring point in a neighboring polygon. An updated fluid property is determined for the selected polygon using a variable diffusion rate, the variable diffusion rate based on the minimum diffusion rate, maximum diffusion rate, and angular difference between the diffusion-path vector and the pressure-gradient vector.

Rodriguez, David L.↗
DOE OSTI2014

Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic Fracturing in Shale Gas Systems and Electromagnetic Geophysical Monitoring of Fluid Migration

We investigate fracture propagation induced by hydraulic fracturing with water injection, using numerical simulation. For rigorous, full 3D modeling, we employ a numerical method that can model failure resulting from tensile and shear stresses, dynamic nonlinear permeability, leak-off in all directions, and thermo-poro-mechanical effects with the double porosity approach. Our numerical results indicate that fracture propagation is not the same as propagation of the water front, because fracturing is governed by geomechanics, whereas water saturation is determined by fluid flow. At early times, the water saturation front is almost identical to the fracture tip, suggesting that the fracture is mostly filled with injected water. However, at late times, advance of the water front is retarded compared to fracture propagation, yielding a significant gap between the water front and the fracture top, which is filled with reservoir gas. We also find considerable leak-off of water to the reservoir. The inconsistency between the fracture volume and the volume of injected water cannot properly calculate the fracture length, when it is estimated based on the simple assumption that the fracture is fully saturated with injected water. As an example of flow-geomechanical responses, we identify pressure fluctuation under constant water injection, because hydraulic fracturing is itself a set of many failure processes, in which pressure consistently drops when failure occurs, but fluctuation decreases as the fracture length grows. We also study application of electromagnetic (EM) geophysical methods, because these methods are highly sensitive to changes in porosity and pore-fluid properties due to water injection into gas reservoirs. Employing a 3D finite-element EM geophysical simulator, we evaluate the sensitivity of the crosswell EM method for monitoring fluid movements in shaly reservoirs. For this sensitivity evaluation, reservoir models are generated through the coupled flow-geomechanical simulator and are transformed via a rock-physics model into electrical conductivity models. It is shown that anomalous conductivity distribution in the resulting models is closely related to injected water saturation, but not closely related to newly created unsaturated fractures. Our numerical modeling experiments demonstrate that the crosswell EM method can be highly sensitive to conductivity changes that directly indicate the migration pathways of the injected fluid. Accordingly, the EM method can serve as an effective monitoring tool for distribution of injected fluids (i.e., migration pathways) during hydraulic fracturing operations

02 PETROLEUM↗
DOE OSTI2019

TOUGH-UDEC: A simulator for coupled multiphase fluid flows, heat transfers and discontinuous deformations in fractured porous media

A numerical simulator entitled TOUGH-UDEC is presented for the assessment of coupled thermal-hydraulic-mechanical processes in fractured porous media. Two existing well-established codes, TOUGH2 and UDEC, are coupled to model multiphase fluid flows, heat transfers, and discontinuous deformations in fractured porous media by means of discrete fracture representation. TOUGH2 is widely used for the modeling of heat transfers and multiphase multicomponent fluid flows, and UDEC is a well-known distinct element code for rock mechanics. The two codes are solved sequentially, with coupling parameters passed to each equation at specific intervals. After solving thermal-hydraulic equations within the TOUGH2 code, pressure and temperature information is imported into the UDEC model. Upon solving the mechanical equation within the UDEC code the calculated fracture apertures are converted to the equivalent permeability and porosity values for a TOUGH2 flow analysis. The solution is calculated by iteratively following an explicit sequence for numerical efficiency. Verifications are presented to demonstrate the capabilities of the coupled TOUGH-UDEC simulator. Three application examples of (1) shear dilation due to increased pore pressure, (2) thermal stress and (3) CO 2 injection, show that the new simulator can be an effective tool for geoengineering applications involving shear activation of fractures and faults.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

Uncertainty quantification of computational fluid dynamics (CFD) simulations is a complicated procedure which still relies in many cases on engineering judgment and factors of safety. This is in part because the computational cost of measuring the simulation's sensitivity to all meaningful parameters (e.g., body surface roughness) and hyperparameters (e.g., subiteration convergence criterion) is intractable for even a single simulation. Reduced-order modeling dramatically lowers this computational cost of simulating fluid flows, but usually only where similar data is already available. In this work, fluid reduced-order models are utilized to quantify a flow's sensitivity to certain physical parameters for the purposes of improved uncertainty quantification. Characteristic observability and sensitivity are both explored. The resulting sensitivity quantifications enable more informed CFD frameworks and more rigorous uncertainty bounds on the resulting data.

uncertainty quantification↗
NASA NTRSDate not supplied

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

Uncertainty quantification of computational fluid dynamics (CFD) simulations is a complicated procedure which still relies in many cases on engineering judgment and factors of safety. This is in part because the computational cost of measuring the simulation's sensitivity to all meaningful parameters (e.g., body surface roughness) and hyperparameters (e.g., subiteration convergence criterion) is intractable for even a single simulation. Reduced-order modeling dramatically lowers this computational cost of simulating fluid flows, but usually only where similar data is already available. In this work, fluid reduced-order models are utilized to quantify a flow's sensitivity to certain physical parameters for the purposes of improved uncertainty quantification. Characteristic observability and sensitivity are both explored. The resulting sensitivity quantifications enable more informed CFD frameworks and more rigorous uncertainty bounds on the resulting data.

uncertainty quantification↗
DOE OSTI2020

An embedded 3D fracture modeling approach for simulating fracture-dominated fluid flow and heat transfer in geothermal reservoirs

In this paper, we describe an efficient modeling approach, named embedded discrete fracture method (EDFM), for incorporating arbitrary 3D, discrete fractures, such as hydraulic fractures or faults, into modeling fracture-dominated fluid flow and heat transfer in fractured geothermal reservoirs. This technique allows 3D discrete fractures to be discretized independently from surrounding rock volume and inserted explicitly into a primary fracture/matrix grid, generated without including 3D discrete fractures in prior. An effective computational algorithm is developed to discretize these 3D discrete fractures and construct local connections between 3D fractures and fracture/matrix grid blocks representing the surrounding rock volume. The constructed gridding information on 3D fractures is then added to the primary grid. This embedded fracture modeling approach can be directly implemented into a developed geothermal reservoir simulator via the integral finite difference (IFD) method or with TOUGH2 technology. This embedded fracture modeling approach is very promising and computationally efficient to handle realistic 3D discrete fractures with complicated geometries, connections, and spatial distributions. Compared with other fracture modeling approaches, it avoids cumbersome 3D unstructured, local refining procedures, and increases computational efficiency by simplifying Jacobian matrix size and sparsity, while maintaining enough accuracy. Several numeral simulations are presented to demonstrate the utility and robustness of the proposed technique. Our numerical experiments show that this approach captures all the key patterns about fluid flow and heat transfer dominated by fractures in these cases. Thus, this approach is readily available to the simulation of fractured geothermal reservoirs with both artificial and natural fractures.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Evaluation of RANS vs. LES simulation of fluid flow through 3 × 3 rod bundle with a simple spacer grid as a precursor to coupled fluid–structure interaction simulations

The research literature on Computational Fluid Dynamics (CFD) of coolant flow through rod bundles with spacer-grids and mixing vanes is replete, ranging from high fidelity Large Eddy Simulation (LES)/Direct Numerical Simulation (DNS) simulations to Reynolds-Averaged Navier–Stokes (RANS) modeled studies. The mixing of flow between subchannels and the pressure drop through the bundle are fundamental quantities useful for comparing and evaluating CFD methods. Less commonly observed and compared are the forces exerted onto the structure by the fluid. The present study seeks to evaluate the use of RANS simulations for predicting the structural response to fluid flow. Wall resolved RANS simulations are benchmarked against LES simulations of fluid flow at a Reynolds number of 15,000 through a 3 × 3 fuel rod bundle with a simple spacer grid. Velocity line-plots are compared showing good agreement between RANS and LES results, ascertaining that the former is capable of capturing the essential time-averaged velocity profile. Additionally, the distribution of forces on the spacer grid and fuel rods are collected as a function of time and space. The RANS methods are evaluated using the frequency and magnitude of the fluctuating forces on various portions of the structure as compared to LES. In conclusion, the power spectral density evaluation of the models reveal underprediction of force amplitude on the rod walls by RANS and also discrepancy in the prediction of high frequency spectra, especially in the immediate vicinity of spacer-grid structure, which may be attributed to the lack of random turbulence fluctuation or insufficient modeling of small-scale eddies in RANS simulation.

FIV↗
NASA NTRS2003

Results of the Workshop on Two-Phase Flow, Fluid Stability and Dynamics: Issues in Power, Propulsion, and Advanced Life Support Systems

The Two-phase Flow, Fluid Stability and Dynamics Workshop was held on May 15, 2003 in Cleveland, Ohio to define a coherent scientific research plan and roadmap that addresses the multiphase fluid problems associated with NASA s technology development program. The workshop participants, from academia, industry and government, prioritized various multiphase issues and generated a research plan and roadmap to resolve them. This report presents a prioritization of the various multiphase flow and fluid stability phenomena related primarily to power, propulsion, fluid and thermal management and advanced life support; and a plan to address these issues in a logical and timely fashion using analysis, ground-based and space-flight experiments.

McQuillen, John↗
NASA NTRS2003

Performance of WPA Conductivity Sensor during Two-Phase Fluid Flow in Microgravity

The Conductivity Sensor designed for use in the Node 3 Water Processor Assembly (WPA) was based on the existing Space Shuttle application for the fuel cell water system. However, engineering analysis has determined that this sensor design is potentially sensitive to two-phase fluid flow (gadliquid) in microgravity. The source for this sensitivity is the fact that gas bubbles will become lodged between the sensor probe and the wall of the housing without the aid of buoyancy in l-g. Once gas becomes lodged in the housing, the measured conductivity will be offset based on the volume of occluded gas. A development conductivity sensor was flown on the NASA Microgravity Plan to measure the offset, which was determined to range between 0 and 50%. Based on these findings, a development program was initiated at the sensor s manufacturer to develop a sensor design fully compatible with two-phase fluid flow in microgravity.

Carter, Layne↗
NASA NTRS1966

System proportions fluid-flow in response to demand signals

Control system provides proportioned fluid flow rates in response to demand signals. It compares a digital signal, representing a flow demand, with a reference signal to yield a control voltage to one or more solenoid valves connected to orifices of a predetermined size.

Source record↗
NASA NTRS1976

System for measuring Reynolds in a turbulently flowing fluid

A system for measuring momentum flux in a turbulently flowing fluid includes: a sensing apparatus for dynamically sensing the mainstream and the cross velocity components of the fluid, a transducer operative to provide two electrical output signals representative of the velocity components in the mainstream and in the cross direction, and signal processors to derive the Reynolds stress wave and the Reynolds stress.

Cheng, D. Y.↗
NASA NTRS1997

Method and Apparatus for Measuring Fluid Flow

Method and apparatus for making measurements on fluids related to their complex permeability are disclosed. A microwave probe is provided for exposure to the fluids. The probe can be non-intrusive or can also be positioned at the location where measurements are to be made. The impedance of the probe is determined. in part. by the complex dielectric constant of the fluids at the probe. A radio frequency signal is transmitted to the probe and the reflected signal is phase and amplitude detected at a rapid rate for the purpose of identifying the fluids. Multiple probes may be selectively positioned to monitor the behavior of the fluids including their flow rate. Fluids may be identified as between two or more different fluids as well as multiple phases of the same fluid based on differences between their complex permittivities.

Arndt, G. Dickey↗