SEARCH · Search NASA
Results for “Local Method”
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.
Multi-regime mixing modeling for local extinction and re-ignition in turbulent non-premixed flame by using LES/FDF method
Local extinction and re-ignition occur in turbulent non-premixed combustion when the Damköhler number is not large enough and the combustion is not fully mixing controlled. The occurrence of local extinction introduces locally extinguished flame holes followed by a premixed flame propagation toward the hole center to potentially reignite the flame. The co-existence of the non-premixed and premixed combustion regimes complicates the modeling since traditional combustion models are mostly for a single regime. In this work, we examine the effect of multi-regime mixing modeling in the transported filtered density function (FDF) method on the predictions of local extinction and reignition. Predictions of local extinction and reignition remain a challenge for the FDF method despite the progress made in the past. To account for the multi-regime combustion, two different mixing timescale models for non-premixed and premixed combustion are combined. A flame index based on the gradients of fuel and oxidizer is used to define a weighting factor to blend the two mixing timescale models. A turbulent jet non-premixed flame with substantial local extinction, the Sydney piloted jet flame L, is adopted as a test case to examine the performance of the multi-regime model in large-eddy simulation/FDF modeling. It is found that the traditional non-premixed mixing timescale model when combined with the modified Curl mixing leads to global extinction for the Sydney flame L without the presence of the premixed combustion regime. After accounting for the multi-regime combustion with proper detection of the different combustion regimes, the predictions for the flame statistics and the amount of local extinction are significantly improved. Furthermore, it suggests the need of including multi-regime combustion for the predictions of local extinction and re-ignition in turbulent non-premixed combustion configurations.
Validation of the strike point position estimation with the local expansion method for MAST upgrade on the DIII-D tokamak
A local expansion method has been proposed for estimating the strike point position for the advanced divertor configuration on the MAST Upgrade tokamak. The paper discusses the application and assesses the performance of the technique on a long-legged divertor plasma configuration on an operating device - the DIII-D tokamak. A comparison of the spatial location of the outer strike point estimated with the local expansion method against the plasma boundary reconstruction and divertor diagnostics on the DIII-D tokamak is reported. A good agreement with the equilibrium reconstruction and diagnostic data is achieved with respect to estimation of the spatial location of the outer strike point for the long-legged divertor plasma discharge.
A sixth order Mehrstellen scheme with an application to the Method of Local Corrections for the 3D Poisson equation
We present a sixth order finite difference scheme for Poisson’s equation when discretized with the compact 27-point stencil based on Mehrstellen corrections of the forcing function term f. Our approach results in a sixth order accurate solution error as opposed to a fourth-order error imposed by the classical Mehrstellen correction for the 19-point and 27-point stencils. The present study is a continuation of former work of Spotz and Carey (1996) on compact finite difference schemes for Poisson’s equation where sixth order convergence may be obtained under the assumption that the fourth order derivatives of f are determined analytically. Specifically, we show that sixth order convergence can still be attained when only values of f at grid points are available. The sixth order Mehrstellen scheme is further coupled with a Method of Local Corrections (MLC) 3D Poisson solver improving to sixth order accuracy the results reported in Kavouklis and Colella (2019). The MLC test case considered involves an adaptive grid that comprises 7.5 billion cells.
Dual-Domain Material Point method with Local Stress Difference for Fragmentation
Explore the source record for details and available documents.
Temperature locale sensors and related methods
Temperature locale sensors include an enclosure defining a sealed volume with a phase-change material therein at a known pressure. The phase-change material is formulated to exhibit a gas-to-solid phase change, without condensing to a liquid phase, at the known pressure and a targeted temperature, i.e., the material's “deposition temperature.” The phase-change material—while at least partially in gaseous form, either initially or after sublimation—is exposed to an environment with temperatures varying by location, including a maximum temperature above the phase-change material's deposition temperature and other temperatures at or below the deposition temperature. The gaseous phase-change material, in a location at the deposition temperature, solidifies from its gaseous phase to form solid grain deposits on a surface within the enclosure of the sensor. The solid deposits precisely identify the location of the specific, targeted deposition temperature.
A divergence-free constrained magnetic field interpolation method for scattered data
An interpolation method to evaluate magnetic fields, given its unstructured and scattered magnetic data, is presented. The method is based on the reconstruction of the global magnetic field using a superposition of orthogonal functions. The coefficients of the expansion are obtained by minimizing a cost function defined as the L2 norm of the difference between the ground truth and the reconstructed magnetic field evaluated on the training data. The divergence-free condition is incorporated as a constraint in the cost function, allowing the method to achieve arbitrarily small errors in the magnetic field divergence. An exponential decay of the approximation error is observed and compared with the less favorable algebraic decay of local splines. Compared to local methods involving computationally expensive search algorithms, the proposed method exhibits a significant reduction of the computational complexity of the field evaluation, while maintaining a small error in the divergence even in the presence of magnetic islands and stochasticity. Finally, applications to the computation of Poincaré sections using data obtained from numerical solutions of the magnetohydrodynamic equations in toroidal geometry are presented and compared with local methods currently in use.
Improvement of the AC orbit bump method of local kick factor measurement using reference bunches
Here we have improved the AC orbit bump technique of local kick factor measurement. This technique, developed at NSLS-II a few years ago, is based on local sine-wave excitation of the electron beam by four fast correctors adjacent to the impedance location. By implementing reference bunches and the time gate function of beam position monitors, we are now able to measure the AC orbits of bunches with different intensities simultaneously. This improvement allows us to obtain the impedance-driven orbit distortion in a single measurement, significantly improving the measurement accuracy and reducing the measurement time.
Comparative Study of the Performance of Seismic Waveform Denoising Methods Using Local and Near-Regional Data.
Abstract not provided.
Comparative Study of the Performance of Seismic Waveform Denoising Methods Using Local and Near-Regional Data.
Abstract not provided.
Application of the Eulerian-Lagrangian Point Mass Particle Method to Localized Chemical and Aerosol Processes in the Atmosphere
Explore the source record for details and available documents.
Vision-based localization for cooperative robot-CNC hybrid manufacturing
Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.
First-principles residual resistivity using a locally self-consistent multiple scattering method
The locally self-consistent multiple scattering (LSMS) method can perform efficient first-principles calculations of systems with a large number of atoms. Here, in this paper, we combine the Kubo-Greenwood equation with LSMS, enabling us to calculate the first-principles residual resistivity of large systems. This has been implemented in the open-source code LSMS . We apply this method to selected pure elements and binary random alloys. The results compare well with experiment, and with values obtained from a first-principles effective medium technique (the Korringa-Kohn-Rostoker coherent potential approximation). We discuss future applications of this method to complex systems where other methods are not applicable.
Localization of fluorescent targets in deep tissue with expanded beam illumination for studies of cancer and the brain
Imaging fluorescence through millimeters or centimeters of tissue has important in vivo applications, such as guiding surgery and studying the brain. Often, the important information is the location of one of more optical reporters, rather than the specifics of the local geometry, motivating the need for a localization method that provides this information. We present an optimization approach based on a diffusion model for the fast localization of fluorescent inhomogeneities in deep tissue with expanded beam illumination that simplifies the experiment and the reconstruction. We show that the position of a fluorescent inhomogeneity can be estimated while assuming homogeneous tissue parameters and without having to model the excitation profile, reducing the computational burden and improving the utility of the method. We perform two experiments as a demonstration. First, a tumor in a mouse is localized using a near infrared folate-targeted fluorescent agent (OTL38). This result shows that localization can quickly provide tumor depth information, which could reduce damage to healthy tissue during fluorescence-guided surgery. Second, another near infrared fluorescent agent (ATTO647N) is injected into the brain of a rat, and localized through the intact skull and surface tissue. This result will enable studies of protein aggregation and neuron signaling.
Demystifying Piecewise and Localized Scatter Correction Methods
Multiplicative scatter is a common source of noise in near-infrared spectroscopy and other related instrumental techniques. A wide variety of methods are commonly used for the correction of multiplicative scatter. However, the majority of such methods assume that the parameters that describe the scatter are constant throughout the measured spectrum, which is often not the case. This work investigates a family of methods that perform scatter correction using local regions of neighboring wavelengths in order to better account for wavelength-dependent scattering. The methods in question are piecewise standard normal variate, localized standard normal variate, piecewise multiplicative scatter correction, and localized multiplicative scatter correction. This work describes the theoretical and algorithmic foundations of the family of local region-based scatter correction methods and compares their application and optimization at a qualitative and quantitative level using several datasets.
Learning local equivariant representations for large-scale atomistic dynamics
Abstract A simultaneously accurate and computationally efficient parametrization of the potential energy surface of molecules and materials is a long-standing goal in the natural sciences. While atom-centered message passing neural networks (MPNNs) have shown remarkable accuracy, their information propagation has limited the accessible length-scales. Local methods, conversely, scale to large simulations but have suffered from inferior accuracy. This work introduces Allegro, a strictly local equivariant deep neural network interatomic potential architecture that simultaneously exhibits excellent accuracy and scalability. Allegro represents a many-body potential using iterated tensor products of learned equivariant representations without atom-centered message passing. Allegro obtains improvements over state-of-the-art methods on QM9 and revMD17. A single tensor product layer outperforms existing deep MPNNs and transformers on QM9. Furthermore, Allegro displays remarkable generalization to out-of-distribution data. Molecular simulations using Allegro recover structural and kinetic properties of an amorphous electrolyte in excellent agreement with ab-initio simulations. Finally, we demonstrate parallelization with a simulation of 100 million atoms.
An extension of the localized artificial diffusivity method for immiscible and high density ratio flows
The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.
A splice method for local-to–nonlocal coupling of weak forms
Here, we propose a method to couple local and nonlocal diffusion models. By inheriting desirable properties such as patch tests, asymptotic compatibility and unintrusiveness from related splice and optimization-based coupling schemes, it enables the use of weak (or variational) formulations, is computationally efficient and straightforward to implement. We prove well-posedness of the coupling scheme and demonstrate its properties and effectiveness in a variety of numerical examples.