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At least 55 records · Page 3

A deterministic particle method for one-dimensional reaction-diffusion equations

We derive a deterministic particle method for the solution of nonlinear reaction-diffusion equations in one spatial dimension. This deterministic method is an analog of a Monte Carlo method for the solution of these problems that has been previously investigated by the author. The deterministic method leads to the consideration of a system of ordinary differential equations for the positions of suitably defined particles. We then consider the time explicit and implicit methods for this system of ordinary differential equations and we study a Picard and Newton iteration for the solution of the implicit system. Next we solve numerically this system and study the discretization error both analytically and numerically. Numerical computation shows that this deterministic method is automatically adaptive to large gradients in the solution.

Mascagni, Michael↗

An Extended Lagrangian Method

A unique formulation of describing fluid motion is presented. The method, referred to as 'extended Lagrangian method,' is interesting from both theoretical and numerical points of view. The formulation offers accuracy in numerical solution by avoiding numerical diffusion resulting from mixing of fluxes in the Eulerian description. The present method and the Arbitrary Lagrangian-Eulerian (ALE) method have a similarity in spirit-eliminating the cross-streamline numerical diffusion. For this purpose, we suggest a simple grid constraint condition and utilize an accurate discretization procedure. This grid constraint is only applied to the transverse cell face parallel to the local stream velocity, and hence our method for the steady state problems naturally reduces to the streamline-curvature method, without explicitly solving the steady stream-coordinate equations formulated a priori. Unlike the Lagrangian method proposed by Loh and Hui which is valid only for steady supersonic flows, the present method is general and capable of treating subsonic flows and supersonic flows as well as unsteady flows, simply by invoking in the same code an appropriate grid constraint suggested in this paper. The approach is found to be robust and stable. It automatically adapts to flow features without resorting to clustering, thereby maintaining rather uniform grid spacing throughout and large time step. Moreover, the method is shown to resolve multi-dimensional discontinuities with a high level of accuracy, similar to that found in one-dimensional problems.

Liou, Meng-Sing↗

Development of Numerical Extended Hydrodynamics for Transition-Regime Non-Equilibrium Flows Encountered in Semiconductor Manufacturing Processes

Six months of funding was received for the proposed three year research program (funding for the period from March 1, 1997 to August 31, 1997). Although the official starting date for the project was March 1, 1997, no funding for the project was received until July 1997. In the funded research period, considerable progress was made on Phase I of the proposed research program. The initial research efforts concentrated on applying the 10-, 20-, and 35-moment Gaussian-based closures to a series of standard two-dimensional non-reacting single species test flow problems, such as the flat plate, couette, channel, and rearward facing step flows, and to some other two-dimensional flows having geometries similar to those encountered in chemical-vapor deposition (CVD) reactors. Eigensystem analyses for these systems for the case of two spatial dimensions was carried out and efficient formulations of approximate Riemann solvers have been formulated using these eigenstructures. Formulations to include rotational non-equilibrium effects into the moment closure models for the treatment of polyatomic gases were explored, as the original formulations of the closure models were developed strictly for gases composed of monatomic molecules. The development of a software library and computer code for solving relaxing hyperbolic systems in two spatial dimensions of the type arising from the closure models was also initiated. The software makes use of high-resolution upwind finite-volumes schemes, multi-stage point implicit time stepping, and automatic adaptive mesh refinement (AMR) to solve the governing conservation equations for the moment closures. The initial phase of the code development was completed and a numerical investigation of the solutions of the 10-moment closure model for the simple two-dimensional test cases mentioned above was initiated. Predictions of the 10-moment model were compared to available theoretical solutions and the results of direct-simulation Monte Carlo (DSMC) calculations. The first results of this study were presented at a meeting last year.

Groth, Clinton P. T.↗

Advanced Data Acquisition Systems with Self-Healing Circuitry

Kennedy Space Center's Spaceport Engineering & Technology Directorate has developed a data acquisition system that will help drive down the cost of ground launch operations. This system automates both the physical measurement set-up function as well as configuration management documentation. The key element of the system is a self-configuring, self-calibrating, signal-conditioning amplifier that automatically adapts to any sensor to which it is connected. This paper will describe the core technology behind this device and the automated data system in which it has been integrated. The paper will also describe the revolutionary enhancements that are planned for this innovative measurement technology. All measurement electronics devices contain circuitry that, if it fails or degrades, requires the unit to be replaced, adding to the cost of operations. Kennedy Space Center is now developing analog circuits that will be able to detect their own failure and dynamically reconfigure their circuitry to restore themselves to normal operation. This technology will have wide ranging application in all electronic devices used in space and ground systems.

Larson, William E.↗

A Novel Four-Node Quadrilateral Smoothing Element for Stress Enhancement and Error Estimation

A four-node, quadrilateral smoothing element is developed based upon a penalized-discrete-least-squares variational formulation. The smoothing methodology recovers C1-continuous stresses, thus enabling effective a posteriori error estimation and automatic adaptive mesh refinement. The element formulation is originated with a five-node macro-element configuration consisting of four triangular anisoparametric smoothing elements in a cross-diagonal pattern. This element pattern enables a convenient closed-form solution for the degrees of freedom of the interior node, resulting from enforcing explicitly a set of natural edge-wise penalty constraints. The degree-of-freedom reduction scheme leads to a very efficient formulation of a four-node quadrilateral smoothing element without any compromise in robustness and accuracy of the smoothing analysis. The application examples include stress recovery and error estimation in adaptive mesh refinement solutions for an elasticity problem and an aerospace structural component.

Tessler, A.↗

Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

Neural Networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper summarizes efforts at NASA's Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.

Patrick, M. Clinton↗

Modifications to Axially Symmetric Simulations Using New DSMC (2007) Algorithms

Several modifications aimed at improving physical accuracy are proposed for solving axially symmetric problems building on the DSMC (2007) algorithms introduced by Bird. Originally developed to solve nonequilibrium, rarefied flows, the DSMC method is now regularly used to solve complex problems over a wide range of Knudsen numbers. These new algorithms include features such as nearest neighbor collisions excluding the previous collision partners, separate collision and sampling cells, automatically adaptive variable time steps, a modified no-time counter procedure for collisions, and discontinuous and event-driven physical processes. Axially symmetric solutions require radial weighting for the simulated molecules since the molecules near the axis represent fewer real molecules than those farther away from the axis due to the difference in volume of the cells. In the present methodology, these radial weighting factors are continuous, linear functions that vary with the radial position of each simulated molecule. It is shown that how one defines the number of tentative collisions greatly influences the mean collision time near the axis. The method by which the grid is treated for axially symmetric problems also plays an important role near the axis, especially for scalar pressure. A new method to treat how the molecules are traced through the grid is proposed to alleviate the decrease in scalar pressure at the axis near the surface. Also, a modification to the duplication buffer is proposed to vary the duplicated molecular velocities while retaining the molecular kinetic energy and axially symmetric nature of the problem.

Liechty, Derek S.↗

A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

Bhaduri, Kanishka↗

Detection and Height Measurement of Tenuous Clouds and Blowing Snow in ICESat-2 ATLAS Data

Tenuous atmospheric layers, such as high, thin cirrus clouds and blowing snow over Antarctica, play an important role in the climate system, affecting energy fluxes between the Earth and the atmosphere. Our knowledge of the structure of the atmosphere is largely derived from atmospheric satellite measurements. Yet tenuous layers can be hard to detect in satellite lidar data, especially in daylight data characterized by high solar background. In this study, we introduce an approach to detect tenuous atmospheric layers in the atmospheric lidar measurements of NASA's ICESat-2. The density-dimension algorithm for ICESat-2 atmospheric data (DDA-atmos) identifies atmospheric layers while automatically adapting to different background conditions of night, twilight, and daylight data. This capability, demonstrated for tenuous clouds and blowing snow, offers a data-based solution to an important climate modeling problem. Atmospheric layer boundaries, detection confidence, and density fields resultant from the DDA-atmos are reported in ICESat-2 atmospheric data product ATL09.

Ute Herzfeld↗

Automatic Boundary-Layer Adaptation of Structured Grids in VULCAN-CFD

In supersonic and hypersonic flow computations, well-resolved boundary layers are essential for accurate quantification of surface heating and transition prediction, particularly via linear stability analysis. Grid design for hypersonic flows with shocks, boundary-layer separation, and/or complex mean flow features incorporating spanwise/azimuthal inhomogeneities is a difficult issue. In comparison to a manual grid adaptation procedure, an autonomous grid adaptation technique offers significant improvements in computing time and solution quality. The VULCAN-CFD solver already includes a validated procedure for automatic adaption of structured grids to the bow shock. The present focus is on implementing an automatic boundary-layer adaptation capability in VULCAN-CFD that adapts structured, multiblock grids to both the bow shock and the boundary layer at the same time. The boundary-layer adaptation algorithm allows the user to specify the number of cells within the boundary layer, along with the input parameters used for detecting the edge of the boundary layer, namely, the variable used in the edge detection criterion,the edge detection method, the detection direction, and the relaxation factor used during the morphing of the grid. The algorithm automatically distributes grid points along the wall-normal direction to achieve a smooth variation in grid spacing from the edge of the boundary layer to a"junction" location within the outer part of the grid. Illustrative results are presented for three different high-speed configurations: the two-dimensional flow over a cylinder at Mach 17.6 and unit Reynolds number of Re=0.38x10^6 m^-1, the axisymmetric flow over a cone-cylinder-flare model at Mach 6.0 and Re = 10.5×10^6 m^-1, and the three-dimensional flow over a blunt, 7-degree half-angle cone at 5-degree angle of attack in a Mach 9.79 flow with Re = 17.1×10^6 m^-1. The automated boundary-layer adaptation is shown to provide an adequate grid topology that is aligned with the bow shock in the outer part of the grid and also resolves the viscous boundary-layer region close to the surface.

boundary layer transition↗

Method and system for spatial data input, manipulation and distribution via an adaptive wireless transceiver

A method and system for spatial data manipulation input and distribution via an adaptive wireless transceiver. The method and system include a wireless transceiver for automatically and adaptively controlling wireless transmissions using a Waveform-DNA method. The wireless transceiver can operate simultaneously over both the short and long distances. The wireless transceiver is automatically adaptive and wireless devices can send and receive wireless digital and analog data from various sources rapidly in real-time via available networks and network services.

Wang, Ray↗

Off-policy deep reinforcement learning with automatic entropy adjustment for adaptive online grid emergency control

Electric overloading conditions and contingencies put modern power systems at risk of voltage collapse and blackouts. Load shedding is crucial to maintain voltage stability for grid emergency control. However, the rule- or model-based schemes rely on accurate dynamic system models and face considerable challenges in adapting to various operating conditions and uncertain event occurrences. Here, to address these issues, this paper proposes a novel deep reinforcement learning (DRL)-based voltage stability control algorithm with automatic entropy adjustment (AEA) for grid emergency control. Various dynamic network components for complex system operations are modeled to construct the DRL environment. An off-policy soft actor-critic architecture is developed to maximize the expected reward and policy entropy simultaneously. The AEA mechanism is proposed to facilitate the policy maximum entropy procedure, and the proposed method can automatically provide effective discrete and continuous actions against various fault scenarios. Our approach accomplishes high sampling efficiency, scalability, and auto-adaptivity of the control policies under high uncertainties. Comparative studies with the existing DRL-based control methods in IEEE benchmarks indicate salient performance improvement of the proposed method for dynamic system emergency control.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using Multi-threading for the Automatic Load Balancing of 2D Adaptive Finite Element Meshes

In this paper, we present a multi-threaded approach for the automatic load balancing of adaptive finite element (FE) meshes The platform of our choice is the EARTH multi-threaded system which offers sufficient capabilities to tackle this problem. We implement the adaption phase of FE applications oil triangular meshes and exploit the EARTH token mechanism to automatically balance the resulting irregular and highly nonuniform workload. We discuss the results of our experiments oil EARTH-SP2, on implementation of EARTH on the IBM SP2 with different load balancing strategies that are built into the runtime system.

Heber, Gerd↗

Automated Unstructured Grid Adaptation on a Strut Fuel Injector at Hypervelocity Flow Conditions

Computational fluid dynamics (CFD) analysis is presented with the use of an automated unstructured grid adaptation tool on a strut fuel injector at hypervelocity flow conditions. The analysis was carried out with the VULCAN-CFD solver using Reynolds-averaged simulations (RAS). The hypervelocity flow conditions match the high Mach number flow of the experiments conducted as part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). The current work utilizes an automated grid adaptation tool recently implemented into VULCAN-CFD, and explores this tool’s ability to solve high-speed mixing problems. Simulation results obtained using the unstructured adaptive grid approach are compared to those on a user generated structured grid. These results are evaluated by analyzing how efficiently comparable fidelity results are obtained from both adapted and structured simulations. In addition, two adaptation strategies were used to explore the impact on the final solution. In the current work, the unstructured grid adaptation tool automatically generates unstructured grids and performs adaptation of the grid based on a Hessian error estimate of a specified flow field parameter. Multiple adaptations were executed using each run strategy with the one-dimensional values of the mixing efficiency used to determine grid convergence and for comparison with the structured grid simulation results. It was found that the unstructured adaptive grid simulations were able to produce results that matched closely with those on structured grids using far fewer grid cells, and thus, requiring far less computational time to reach the solution. It was also discovered that the adaptation run strategy influenced the total number of grid cells and the efficiency with which a final grid-adapted solution was reached. Overall, the investigation demonstrated that the automated unstructured grid adaptation tool implemented in VULCAN-CFD is capable of accurately and efficiently solving complex highspeed mixing problems using only a fraction of the grid cells required to obtain comparable results using a user-generated structured grid.

grid adaptation↗

Automated Unstructured Grid Adaptation on a Strut Fuel Injector at Hypervelocity Flow Conditions

Computational fluid dynamics (CFD) analysis is presented with the use of an automated unstructured grid adaptation tool on a strut fuel injector at hypervelocity flow conditions. The analysis was carried out with the VULCAN-CFD solver using Reynolds-averaged simulations (RAS). The hypervelocity flow conditions match the high Mach number flow of the experiments conducted as part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). The current work uses an automated grid adaptation tool recently implemented in VULCAN-CFD, and explores this tool’s ability to solve highspeed mixing problems. Simulation results obtained using the unstructured adaptive grid approach are compared to those on a user-generated structured grid. These results are evaluated by analyzing how efficiently comparable fidelity results are obtained from both adapted and structured simulations. In addition, two adaptation strategies were used to explore the impact on the final solution. In the current work, the unstructured grid adaptation tool automatically generates unstructured grids and performs adaptation of the grid based on a Hessian error estimate of a specified flowfield parameter. Multiple adaptations were executed using each run strategy with the one-dimensional values of the mixing efficiency used to determine grid convergence and for comparison with the structured grid simulation results. It was found that the unstructured adaptive grid simulations were able to produce results that matched closely with those on structured grids using far fewer grid cells, and thus, requiring far less computational time to reach the solution. It was also discovered that the adaptation run strategy influenced the total number of grid cells and the efficiency with which a final grid-adapted solution was reached. Furthermore, motivated by the grid convergence index (GCI) used for structured grid simulations, a grid convergence estimate (GCE) was developed and demonstrated for the grid adaptation. Overall, the investigation demonstrated that the automated unstructured grid adaptation tool implemented in VULCAN-CFD is capable of accurately and efficiently solving complex high-speed mixing problems with only a fraction of the grid cells required to obtain comparable results on a user-generated structured grid.

hypersonics↗

Automated Unstructured Grid Adaptation on a Strut Fuel Injector at Hypervelocity Flow Conditions

Computational fluid dynamics (CFD) analysis is presented with the use of an automated unstructured grid adaptation tool on a strut fuel injector at hypervelocity flow conditions. The analysis was carried out with the VULCAN-CFD solver using Reynolds-averaged simulations (RAS). The hypervelocity flow conditions match the high Mach number flow of the experiments conducted as part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center (LaRC). The current work uses an automated grid adaptation tool recently implemented in VULCAN-CFD, and explores this tool’s ability to solve highspeed mixing problems. Simulation results obtained using the unstructured adaptive grid approach are compared to those on a user-generated structured grid. These results are evaluated by analyzing how efficiently comparable fidelity results are obtained from both adapted and structured simulations. In addition, two adaptation strategies were used to explore the impact on the final solution. In the current work, the unstructured grid adaptation tool automatically generates unstructured grids and performs adaptation of the grid based on a Hessian error estimate of a specified flowfield parameter. Multiple adaptations were executed using each run strategy with the one-dimensional values of the mixing efficiency used to determine grid convergence and for comparison with the structured grid simulation results. It was found that the unstructured adaptive grid simulations were able to produce results that matched closely with those on structured grids using far fewer grid cells, and thus, requiring far less computational time to reach the solution. It was also discovered that the adaptation run strategy influenced the total number of grid cells and the efficiency with which a final grid-adapted solution was reached. Furthermore, motivated by the grid convergence index (GCI) used for structured grid simulations, a grid convergence estimate (GCE) was developed and demonstrated for the grid adaptation. Overall, the investigation demonstrated that the automated unstructured grid adaptation tool implemented in VULCAN-CFD is capable of accurately and efficiently solving complex high-speed mixing problems with only a fraction of the grid cells required to obtain comparable results on a user-generated structured grid.

hypersonics↗