Results for “simulation types and techniques” — Page 5

DOE OSTI2021

A Review of Lattice-Boltzmann Models Coupled with Geochemical Modeling Applied for Simulation of Advanced Waterflooding and Enhanced Oil Recovery Processes

To maintain economic profit and improve the oil production efficiency after the primary and secondary production phase, advanced waterflooding techniques such as low salinity waterflooding in carbonate reservoirs have been investigated in numerical simulations, laboratory experiments, and field pilot tests. Multiple underlying mechanisms have been proposed based on these studies, and they are still under debate. Various numerical modeling approaches are introduced, but there exists a lack of a pore-scale comprehensive modeling scheme to fully understand the processes. Lattice-Boltzmann method (LBM) is a type of numerical fluid flow modeling technique that shows capabilities and flexibilities in modeling pore-scale fluid flow to integrate physical–chemical processes within complex structures. The intrinsic feature of LBM makes it a promising framework for simulating advanced waterflooding due to its flexibility, accuracy, and parallel efficiency. LBM works either by itself for solving reactive transport problems or by coupling with a third-party reaction solver. This review mainly introduces the LBM fluid flow and reactive transport capabilities and the concept and modeling approaches to simulate advanced waterflooding techniques. Meanwhile, an evaluation of the coupled LBM models for enhanced oil recovery (EOR) simulations is discussed with future research challenges and directions concluded.

02 PETROLEUM↗

DOE OSTI2022

Accelerated radiation transport modeling techniques for pencil beam computed tomography using gamma rays

Monte Carlo radiation transport modeling studies were performed for a compact, and high-resolution gamma-ray computed tomography system designed for imaging irradiated nuclear fuel. The system comprises a 60 Co source – chosen for its highly penetrating 1173 keV and 1332 keV gamma rays – a pair of high-aspect-ratio pencil beam collimators, and an inorganic scintillator detector. Here two acceleration methods are proposed to rapidly model a transmission type gamma-ray tomography system. The first, a variance reduction technique, is based on performing Monte Carlo simulations with a monodirectionally-biased source, sampled from a characteristic sub-volume of the full source volume. The second acceleration method is based on the deterministic calculations using the Beer–Lambert law and detector response characteristics. Comparison of simulations using acceleration approaches with analog simulations of the fully isotropic, full-volume equivalent, show that the Monte Carlo variance reduction technique gives quantitatively accurate predictions for large collimator aspect ratios while the deterministic calculations are semi-quantitative but converge close to the correct result as the collimator aspect ratio increases. As such, these techniques can be used to reduce the computational cost in generating simulated radiographs and tomographs by several orders of magnitude. Experimental validation efforts are currently underway and will be demonstrated in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Cold-front (D01)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Cold-front (D02)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Sea-breeze (D01)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

DOE OSTI2022

Simulated wind speed and initial conditions over the WFIP2 region: Sea-breeze (D02)

The purpose of this work is to assess the sensitivity of the forecast for turbine height wind speed to initial condition (IC) uncertainties over the Columbia River Gorge and Columbia River Basin for two typical weather phenomena: a local thermal gradient induced by a marine air intrusion and passage of a cold front. The Weather Research and Forecasting (WRF) model data assimilation system (WRFDA) was used to generate ensemble ICs from the North American Regional Analysis (NARR) for the WRF model initialization. The simulated turbine-height wind speeds were categorized into four types using the self-organizing map (SOM) technique. This work advances understanding of IC uncertainties impacts on wind speed forecasts and locates the high-impact regions.

17 WIND ENERGY↗

NASA NTRS1987

Summary of investigations of engine response to distorted inlet conditions

A survey is presented of experimental and analytical experience of the NASA Lewis Research Center in engine response to inlet temperature and pressure distortions. Results of experimental investigations and analytical modeling are reviewed together with a description of the hardware and the techniques employed. Distortion devices successfully simulated inlet distortion, and knowledge was gained on compression system response to different types of distortion. A list of NASA research references is included.

Biesiadny, Thomas J.↗

NASA NTRS1992

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗

NASA NTRS1993

Simulation modeling for long duration spacecraft control systems

The use of simulation is described and it is contrasted to analytical solution techniques for evaluation of analytical reliability models. The role importance sampling plays in simulation of models of this type was also discussed. The simulator tool used for our analysis is described. Finally, the use of the simulator tool was demonstrated by applying it to evaluate the reliability of a fault tolerant hypercube multiprocessor intended for spacecraft designed for long duration missions. The reliability analysis was used to highlight the advantages and disadvantages offered by simulation over analytical solution of Markovian and non-Markovian reliability models.

Boyd, Mark A.↗

NASA NTRS2005

Prediction of Mechanical Properties of Polymers With Various Force Fields

The effect of force field type on the predicted elastic properties of a polyimide is examined using a multiscale modeling technique. Molecular Dynamics simulations are used to predict the atomic structure and elastic properties of the polymer by subjecting a representative volume element of the material to bulk and shear finite deformations. The elastic properties of the polyimide are determined using three force fields: AMBER, OPLS-AA, and MM3. The predicted values of Young s modulus and shear modulus of the polyimide are compared with experimental values. The results indicate that the mechanical properties of the polyimide predicted with the OPLS-AA force field most closely matched those from experiment. The results also indicate that while the complexity of the force field does not have a significant effect on the accuracy of predicted properties, small differences in the force constants and the functional form of individual terms in the force fields determine the accuracy of the force field in predicting the elastic properties of the polyimide.

Odegard, Gregory M.↗

NASA NTRS1990

Aeolian Removal of Dust Types from Photovoltaic Surfaces on Mars

Dust elevated in local or global dust storms on the Martian surface could settle on photovoltaic (PV) surfaces and seriously hamper their performance. Using a recently developed technique to apply a uniform dust layer, PV surface materials were subjected to simulated Martian winds in an attempt to determine whether natural aeolian processes on Mars would sweep off the settled dust. Three different types of dust were used. The effects of wind velocity, angle of attack, height above the Martian surface, and surface coating material were investigated. It was found that arrays mounted on an angle of attack approaching 45 deg show the most efficient clearing. Although the angular dependence is not sharp, horizontally mounted arrays required much higher wind velocities to clear off the dust. From this test it appears that the arrays may be erected quite near the ground, but previous studies have suggested that saltation effects can be expected to cause such arrays to be covered by soil if they are set up less than about a meter from the ground. Particle size effect appear to dominate over surface chemistry in these experiments, but additional tests are required to confirm this.

Gaier, James R.↗

NASA NTRS1990

Aeolian Removal of Dust Types from Photovoltaic Surfaces on Mars

Dust elevated in local or global dust storms on the Martian surface could settle on photovoltaic (PV) surfaces and seriously hamper their performance. Using a recently developed technique to apply a uniform dust layer, PV surface materials were subjected to simulated Martian winds in an attempt to determine whether natural Aeolian processes on Mars would sweep off the settled dust. Three different types of dust were used; an optical polishing powder, basaltic "trap rock", and iron (III) oxide crystals. The effects of wind velocity, angle of attack, height above the Martian surface, and surface coating material were investigated. It was found that arrays mounted with an angle of attack approaching 45 degrees show the most efficient clearing. Although the angular dependence is not sharp, horizontally mounted arrays required significantly higher wind velocities to clear off the dust. From this test it appears that the arrays may be erected quite near the ground, but previous studies have suggested that saltation effects can be expected to cause such arrays to be covered by soil if they are set up less than about a meter from the ground. Particle size effects appear to dominate over surface chemistry in these experiments, but additional tests are required to confirm this. Providing that the surface chemistry of Martian dusts is not drastically different from simulated dust and that gravity differences have only minor effects, the materials used for protective coatings for photovoltaic arrays may be optimized for other considerations such as transparency, and chemical or abrasion resistance. The static threshold velocity is low enough that there are regions on Mars which experience winds strong enough to clear off a photovoltaic array if it is properly oriented. Turbulence fences proved to be an ineffective strategy to keep dust cleared from the photovoltaic surfaces.

Gaier, James R.↗

NASA NTRS1988

In-flight simulation investigation of rotorcraft pitch-roll cross coupling

An in-flight simulation experiment investigating the handling qualities effects of the pitch-roll cross-coupling characteristic of single-main-rotor helicopters is described. The experiment was conducted using the NASA/Army CH-47B variable stability helicopter with an explicit-model-following control system. The research is an extension of an earlier ground-based investigation conducted on the NASA Ames Research Center's Vertical Motion Simulator. The model developed for the experiment is for an unaugmented helicopter with cross-coupling implemented using physical rotor parameters. The details of converting the model from the simulation to use in flight are described. A frequency-domain comparison of the model and actual aircraft responses showing the fidelity of the in-flight simulation is described. The evaluation task was representative of nap-of-the-Earth maneuvering flight. The results indicate that task demands are important in determining allowable levels of coupling. In addition, on-axis damping characteristics influence the frequency-dependent characteristics of coupling and affect the handling qualities. Pilot technique, in terms of learned control crossfeeds, can improve performance and lower workload for particular types of coupling. The results obtained in flight corroborated the simulation results.

Watson, Douglas C.↗

DOE OSTI2022

Heat pulse testing at monitoring wells to estimate subsurface fluid velocities in geological CO 2 storage

Monitoring the injected CO 2 during geological CO 2 storage (GCS) is essential to assure containment and identify CO 2 leakage. Here in this work, a new approach is introduced to estimate the evolution of the downhole fluid velocity at a monitoring well and identify CO 2 arrival time using in-well heat pulse/tracer test. The proposed technique involves using a downhole heater to generate a series of heat pulses and measuring their corresponding temperature response. The surface temperature of the downhole heater is controlled by the supplied electrical power and the heat loss by convection to the surroundings. Convective heat transfer is well described using Newton's law of cooling in which the temperature difference between the heater and the surrounding fluids drives the heat transfer, for which the convection heat transfer coefficient (h) controls the magnitude of heat loss. Among various factors that control h, it depends on the type of the flowing fluid and its velocity. Through analyzing the measured temperature at different heat pulses, the changes in h - due to mobilization of the in-situ brine or CO 2 arrival - can be estimated. Consequently, the velocity of the flowing fluid across the heater can be obtained. Since heat transfer by convection is sensitive to the type of the surrounding fluid, intrusion of CO 2 can be detected from the relatively higher surface temperature obtained at CO 2 arrival. Churchill and Bernstein (1977)'s correlation is adopted to estimate the change of fluid velocity in terms of the change in h. To demonstrate the validity of the proposed technique, the results are applied and validated against those of COMSOL Multiphysics simulation tool for single-phase brine (before CO 2 arrival) and single-phase CO 2 (after CO 2 arrival). The observed temperature heating is sensitive to the flowing fluid velocity and fluid type. The temperature signal observed at CO 2 arrival is large and easily detectable using temperature monitoring tool which provides reliable indication for tracking CO 2 arrival at monitoring wells compared with passive temperature monitoring. The results obtained using the proposed technique agree very well with the numerical results obtained from the simulation tool with a maximum estimation error of 7 percent.

02 PETROLEUM↗

NASA NTRS2002

A Statistical Comparison of PSC Model Simulations and POAM Observations

A better knowledge of PSC composition and formation mechanisms is important to better understand and predict stratospheric ozone depletion. Several past studies have attempted to compare modeling results with satellite observations. These comparisons have concentrated on case studies. In this paper we adopt a statistical approach. POAM PSC observations from several Arctic winters are categorized into Type Ia and Ib PSCs using a technique based on Strawa et al. The discrimination technique has been modified to employ the wavelengths dependence of the extinction signal at all wavelengths rather than only at 603 and 10 18 nm. Winter-long simulations for the 1999-2000 Arctic winter have been made using the IMPACT model. These simulations have been constrained by aircraft observations made during the SOLVE/THESEO 2000 campaign. A complete set of winter-long simulations was run for several different microphysical and PSC formation scenarios. The simulations give us perfect knowledge of PSC type (Ia, Ib, or II), composition, especially condensed phase HNO3 which is important for denitrification, and condensed phase H2O. Comparisons are made between the simulation and observation of PSC extinction at 1018 rim versus wavelength dependence, winter-long percentages of Ia and Ib occurrence, and temporal and altitude trends of the PSCs. These comparisons allow us to comment on how realistic some modeling scenarios are.

Strawa, A. W.↗

NASA NTRS1994

Temperature Field During Flame Spread over Alcohol Pools: Measurements and Modelling

A principal difference between flame spread over solid fuels and over liquid fuels is, in the latter case, the presence of liquid-phase convection ahead of the leading edge of the flame. The details of the fluid dynamics and heat transfer mechanisms in both the pulsating and uniform flame spread regimes were heavily debated, without resolution, in the 1960s and 1970s; recently, research on flame spread over pools was reinvigorated by the advent of enhanced diagnostic techniques and computational power. Temperature fields in the liquid, which enable determination of the extent of preheating ahead of the flame, were determined previously by the use of thermocouples and repetitive tests, and suggested that the surface temperature does not decrease monotonically ahead of the pulsating flame front, but that there exists a surface temperature valley. Recent predictions support this suggestion. However, others' thermocouple measurements and the recent field measurements using Holographic Interferometry (HI) did not find a similar valley. In this work we examine the temperature field using Rainbow Schlieren Deflectometry (RSD), with a measurement threshold exceeding that of conventional interferometry by a factor of 20:1, for uniform and pulsating flame spread using propanol and butanol as fuels. This technique was not applied before to flame spread over liquid pools, except in some preliminary measurements reported earlier. Noting that HI is sensitive to the refractive index while RSD responds to refractive index gradients, and that these two techniques might therefore be difficult to compare, we utilized a numerical simulation, described below, to predict and compare both types of field for the uniform and pulsating spread regimes. The experimental data also allows a validation of the model at a level of detail greater than has been attempted before.

Miller, Fletcher J.↗

DOE OSTI2022

Defect identification in simulated Bragg coherent diffraction imaging by automated AI

X-ray Bragg coherent diffraction imaging is a powerful technique for operando and in situ materials characterization and provides a unique means of quantifying the influence of one-dimensional (1D) and two-dimensional (2D) material defects on material response. However, obtaining full images from raw x-ray diffraction data is nontrivial and computationally intensive, precluding real-time experimental feedback. Here, we present a machine learning approach to identify the presence of crystalline line defects (edge and screw) in samples from the raw, 2D, coherent diffraction data without the need for image reconstruction through iterative phase retrieval. Further, we compare different approaches to designing neural networks for this application and demonstrate the potential of automated ML (autoML) approaches.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Simulation and analysis of natural rain in a wind tunnel via digital image processing techniques

It is desired to simulate natural rain in a wind tunnel in order to investigate its influence on the aerodynamic characteristics of aircraft. Rain simulation nozzles have been developed and tested at JPL. Pulsed laser sheet illumination is used to photograph the droplets in the moving airstream. Digital image processing techniques are applied to these photographs for calculation of rain statistics to evaluate the performance of the nozzles. It is found that fixed hypodermic type nozzles inject too much water to simulate natural rain conditions. A modification uses two aerodynamic spinners to flex a tube in a pseudo-random fashion to distribute the water over a larger area.

Aaron, K. M.↗