Papers by Balaji Jayaraman
Cold Heavy Oil Production with Sand (CHOPS) is a well-known primary heavy oil recovery method. In... more Cold Heavy Oil Production with Sand (CHOPS) is a well-known primary heavy oil recovery method. In CHOPS, a key mechanism of production is the formation of wormholes. Wormholes are believed to be nearly cylindrical zones of high permeability that originate from production wells when sand is produced along with the oil. A multi-scale modelling approach based on the multiphase material point method (MMPM) has been applied to the problem of developing a general predictive capability for CHOPS and wormhole growth. The MMPM is a Lagrangian-Eulerian methodology which permits simulation of multiphase flow problems with fluid-structure interaction in which there is substantial material deformation, damage and failure. MMPM is applied to the problem of simulating the growth of a wormhole in unconsolidated sand with live oil including the effect of foamy oil and sand failure. The simulation results show general features such as asymmetry and slugging. Comparison with experimental data for wormhole length with time was favourable. Up-scaling of the method is required to make predictions on the well to field scale. For this purpose, an up-scaled pressure-field-driven scheme has been developed to predict wormhole network structure. It is hypothesized that a pressure-field-based approached is adequate for a macroscopic simulation with resolution above the length scale of the wormhole tips at which the tensor nature of the failure mechanics are more important. The model includes a generalized sand failure criterion that couples with a non-linear pressure equation and foamy oil and sand flow equations. The model resolves separate wormhole regions emerging from the CHOPS pilot well. Robust history matching of commercial pilot production data is provided as partial model validation.
Glow discharge at atmospheric pressure using a dielectric barrier discharge can induce fluid flow... more Glow discharge at atmospheric pressure using a dielectric barrier discharge can induce fluid flow, and operate as an actuator for flow control. In this paper, we simulate the physics of a 2-D asymmetric actuator operating in Helium gas using a high-fidelity first principles-based numerical modeling approach to help improve our understanding of the physical mechanisms associated with such actuators. Fundamentally, there are two processes in the two half-cycles of the actuator operation, largely due to the difference in mobility between faster electrons and slower ions, and the geometric configurations of the DBD/electrodes. The first half-cycle is characterized by the deposition of the slower ion species on the insulator surface while the second half-cycle by the deposition of the electrons at a faster rate. A power-law (cubic) dependence on the voltage for the resulting force is observed, which indicates that larger force can be generated by increasing the amplitude. Furthermore, one can enhance the effectiveness of the actuator, by either increasing the peak value of the periodic force generation or by increasing the asymmetry between the voltage half-cycles or both. Overall, the increase in the lower electrode size, applied voltage and dielectric constant tends to contribute to the first factor, and the decrease in frequency of applied voltage tends to contribute to the second factor. However, the complex interplay between the above factors determines the actuator performance.
Journal of Physics: Conference Series
Realistic atmospheric turbulence–wind farm interactions during coastal low-level jet (LLJ) events... more Realistic atmospheric turbulence–wind farm interactions during coastal low-level jet (LLJ) events are captured using high-fidelity, mesoscale-driven large eddy simulations (LES) to understand wind turbine loads, wakes and overall performance. The simulation has been carried out using the ExaWind aeroelastic solver, AMR-Wind. The simulations have been compared against a baseline unstable case matching the wind speed, wind direction and TI at hub-height location. Results indicate that the LLJ has negative impacts on the turbine hub and tower loads, and opens up potential avenues for design load mitigation strategies.
Bulletin of the American Physical Society, Nov 22, 2016
LEE, NCAR-LES of the "canonical" daytime atmospheric boundary layer (ABL) over flat topography is... more LEE, NCAR-LES of the "canonical" daytime atmospheric boundary layer (ABL) over flat topography is developed as an equilibrium ABL with steady surface heat flux, Q 0 and steady unidirectional "geostrophic" wind vector V g above a capping inversion. A strong inversion layer in daytime ABL acts as a "lid" that sharply separates 3D "microscale" ABL turbulence at the O(10) m scale from the quasi-2D "mesoscale" turbulent weather eddies (O(100) km scale). While "canonical" ABL is equilibrium, quasi-stationary and characterized statistically by the ratio of boundary layer depth (z i) to Obukhov length scale (−L), the real mesoscale influences (U g and Q 0) that force a true daytime ABL are nonstationary at both diurnal and sub-diurnal time scales. We study the consequences of this non-stationarity on ABL dynamics by forcing ABL LES with realistic WRF simulations over flat Kansas terrain. Considering horizontal homogeneity, we relate the mesoscale and geostrophic winds, U g and V g , and systematically study the ABL turbulence response to non-steady variations in Q 0 and U g. We observe significant deviations from equilibrium, that manifest in many ways, such as the formation of "roll" eddies purely from changes in mesoscale wind direction that are normally associated with increased surface heat flux.
AIAA Scitech 2019 Forum, 2019
The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical ... more The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical applications in both engineering and geophysical settings. Significant work continues to be reported in the roughness regime at high Reynolds numbers where the cumulative effect of surface undulations on the averaged and integrated turbulence quantities (e.g. flow drag) is well documented. Even for such cases, the surface topology plays an important role for transitional roughness Reynolds numbers that is hard to characterize. In this work, we attempt to develop a bottom up understanding of the mechanisms underlying turbulence generation and transport, particularly within the region of the turbulent boundary layer (TBL) affected by the surface i.e. surface layer or roughness sublayer. This way, we relate surface characteristics with turbulence generation mechanisms, Reynolds stress transport and the resulting drag increase. To this end, we perform a suite of direct numerical simulations ...
Journal of Physics: Conference Series
This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising f... more This paper explores realistic nonstationary atmospheric boundary layer (ABL) turbulence arising from nonstationarity at the mesoscale, particularly within offshore low-level jets with implications to offshore wind farms, using high-fidelity multiscale large-eddy simulations (LES). To this end, we analyzed the single-point turbulence statistical structure of a North-Atlantic offshore LLJ event simulated using high-resolution LES (AMR-Wind). The nonstationary LLJ is simulated using a mesoscale-to-microscale coupled (MMC) simulation procedure involving data assimilation of mesoscale velocity and temperature data from the Weather Research and Forecasting (WRF) model. Unlike the assimilation of mesoscale velocity data into the LES, the direct assimilation of temperature profiles had a strong impact on turbulence stratification, thereby causing erroneous predictions of turbulence both above and within the jet layer. Various approaches to mitigate this effect have resulted in multiple (fou...
2018 Fluid Dynamics Conference, 2018
Bulletin of the American Physical Society, 2018
history dependence of the material. However, large deformation or flow of the material requires a... more history dependence of the material. However, large deformation or flow of the material requires an Eulerian description. Numerically, different descriptions of the material result in different codes and applications. Unsatisfactory results have been reported by many modelers using both methods. For instance, element deletion scheme is used in the finite element method, a Lagrangian description, to eliminate the highly distorted elements, which results in artificial reduction of inertia from the problem. In codes using the finite volume method, an Eulerian descriptions, how to advect brittle damage of the material is a significant issue. To address these issues we use the material point method, which uses Lagrangian material points and Eulerian mesh simultaneously. Improvements are made to the original material point method for our applications. It is found that the improvements are critically important to granular flows results from brittle damage of the material, while it is marginally important to ductile materials.
23rd AIAA Computational Fluid Dynamics Conference, 2017
SPE Offshore Europe Conference and Exhibition, 2019
This paper presents our progress in developing, testing, and implementing a Ubiquitous Sensing Ne... more This paper presents our progress in developing, testing, and implementing a Ubiquitous Sensing Network (USN) for real-time monitoring of methane emissions. This newsensor technology supports environmental management of industrial sites through a decision support system. Upon detection of specific inputs, data is processed before passing it on for appropriate actions (Data→Insight→Actions). The technology integrates wireless methane sensor nodes, weather sensors, edge-based devices and is powered by a self- contained solar-battery powered system. A cloud-based data analytics IoT solution is included for handling continuous sensor monitoring. A sample of results from an in-house simulated well site are presented within the body of this paper. Preliminary predictions seem to correlate well with the true emission rate as indicated by the proximity of the predictions to the forty-five-degree line. Running more tests should allow us to further estimate the error distribution as well as the prediction interval width and the overall emission rate prediction trend. The initial results demonstrate that the developed technology can quantify the emission rate (scfh) within 1% and 45% error, and a localization error within six feet to fifty feet given a test area of 10,000 square feet. This integrated solution is being ruggedized and the analytics are being optimized for continuous monitoring of methane emissions at customer sites for safety, product loss prevention, and regulatory compliance.
Computers & Fluids, 2019
Data-driven Markov linear models of nonlinear fluid flows using maps of the state into a sparse f... more Data-driven Markov linear models of nonlinear fluid flows using maps of the state into a sparse feature space are explored in this article. The underlying principle of low-order models for fluid systems is identifying maps to a feature space where the system evolution (a) is simpler and efficient to model accurately and (b) the state can be recovered accurately from the features through inverse mapping. Such methods are useful when real-time models are needed for online decision making from sensor data. The Markov linear approximation is popular as it allows us to leverage the well established linear systems machinery. Examples include the Koopman operator approximation techniques and evolutionary kernel methods in machine learning. The success of these models in approximating nonlinear dynamical systems is tied to the effectiveness of the feature map in accomplishing both (a) and (b) above as long as the system provides a feasible prediction horizon using data. We assess this by performing an in-depth study of two different classes of sparse linear feature transformations of the state: (i) a pure data-driven POD-based projection that uses left singular vectors of the data snapshots-a staple of common Koopman approximation methods such as Dynamic Mode Decomposition (DMD) and its variants such as extended DMD; and (ii) a partially data-driven sparse Gaussian kernel (sGK) regression (a mean sparse Gaussian Process (sGP) predictor). The sGK/sGP regression equivalently represents a projection onto an infinite-dimensional basis characterized by a kernel in the inner product reproducing kernel Hilbert space (RKHS). We are particularly interested in the effectiveness of these linear feature maps for long-term prediction using limited data for three classes of fluid flows with escalating complexity (and decreasing prediction horizons) starting from a limit-cycle attractor in a cylinder wake followed by a transient wake evolution with a shift in the base flow and finally, a continuously evolving buoyant Boussinesq mixing flow with no well-defined base state. The results indicate that a purely data-driven POD map is good for full state reconstruction as long as the basis remains relevant to the predictions whereas the more generic sparse Gaussian Kernel (sGK) basis is less sensitive to the evolution of the dynamics but prone to reconstruction errors from lack of parsimony. Contrastingly, the sGK-maps outperform POD-based maps in learning the transient nonlinear evolution of the state for the same feature dimension in systems that contain a welldefined attractor(s). Consequently, both POD and sGK-maps require additional layer(s) to help mitigate these shortcomings. For example, POD-maps require nonlinear functional extensions for improved feature space predictions whereas sGK-maps require dimensionality reduction to balance the large feature dimension needed for accurate full state reconstruction. However, both classes of multilayer feature maps fail to predict the highly evolving buoyant mixing flow for very different reasons.
AIAA Scitech 2019 Forum, 2019
2018 Fluid Dynamics Conference, 2018
Journal of Maxillofacial and Oral Surgery, 2021
Neurofibromas are benign tumours originating from the peripheral nerve sheath mainly the endoneur... more Neurofibromas are benign tumours originating from the peripheral nerve sheath mainly the endoneurium. The lesion can occur in a solitary form or as multiple tumours associated with neurofibromatosis (NF-1), which is also known as von Recklinghausen’s disease. Intraosseous neurofibromas are exceedingly rare with only less than 50 cases reported in the literature. We report a case of paediatric neurofibroma of the mandible which is even more rare with only 9 cases reported so far. Hence, systematic and thorough investigations are mandatory to correctly diagnose and plan appropriate treatment for intraosseous neurofibroma because of the rarity of the lesion in the paediatric age group. The clinical presentations, diagnostic challenges and treatment plan with a thorough review of literature have been addressed in this case report. The purpose of this paper is to present a case of pediatric intraosseous neurofibroma and to stress the importance of considering such a rare lesion in the differential diagnosis of jaw lesions, especially in children to reduce functional and aesthetic morbidity.
Bulletin of the American Physical Society, 2016
WANG, Georgia Tech-Following disintegration of a drug tablet, a cloud of particles 10-200 µm in d... more WANG, Georgia Tech-Following disintegration of a drug tablet, a cloud of particles 10-200 µm in diameter enters the small intestine where drug molecules are absorbed into the blood. Drug release rate depends on particle size, solubility and hydrodynamic enhancements driven by gut motility. To quantify the interrelationships among dissolution, transport and wall permeability, we apply lattice Boltzmann method to simulate the drug concentration field in the 3D gut released from polydisperse distributions of drug particles in the "fasting" vs. "fed" motility states. Generalized boundary conditions allow for both solubility and gut wall permeability to be systematically varied. We apply a local 'quasi-steady state' approximation for drug dissolution using a mathematical model generalized for hydrodynamic enhancements and heterogeneity in drug release rate. We observe fundamental differences resulting from the interplay among release, transport and absorption in relationship to particle size distribution, luminal volume, motility, solubility and permeability. For example, whereas smaller volume encourages higher bulk concentrations and reduced release rate, it also encourages higher absorption rate, making it difficult to generalize predictions. Supported by FDA.
Data-driven modeling for nonlinear fluid flows using sparse convolution-based mapping into a feat... more Data-driven modeling for nonlinear fluid flows using sparse convolution-based mapping into a feature space where the dynamics are Markov linear is explored in this article. The underlying principle of low-order models for fluid systems is identifying convolutions to a feature space where the system evolution (a) is simpler and efficient to model and (b) the predictions can be reconstructed accurately through deconvolution. Such methods are useful when real-time models from sensor data are needed for online decision making. The Markov linear approximation is popular as it allows us to leverage the vast linear systems machinery. Examples include the Koopman operator approximation techniques and evolutionary kernel methods in machine learning. The success of these models in approximating nonlinear dynamical systems is tied to the effectiveness of the convolution map in accomplishing both (a) and (b) mentioned above. To assess this, we perform in-depth study of two classes of sparse con...
The denominator is impacted by spatio-temporal variability through the continual movements in sec... more The denominator is impacted by spatio-temporal variability through the continual movements in sectional and whole blade performance around design points in blade pitch and rotor performance around design points in rotor yaw as the local and rotor-averaged wind vector changes in both magnitude and direction as turbulence eddies pass through the rotor plane. These impacts can be significant, for example, when blade sectional angles-of-attack exceed the threshold for attached blade boundary layer flow, an intermittent process that contributes to temporal rotor moment modulations that could contribute significantly to degradation of average power depending on the changing stability state of the lower troposphere during its diurnal and seasonal cycles, and depending on the level and sophistication of controls that modulate the relationships between variabilities in wind turbine parameters (blade pitch, generator torque) and spatio-temporal variabilities in wind velocity vector over the p...
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Papers by Balaji Jayaraman