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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Global field reconstruction from sparse sensors with Veronoi tessellation-assisted deep learning

Achieving accurate and robust global situational awareness of a complex time-evolving field from a limited number of sensors has been a longstanding challenge. This reconstruction problem is especially difficult when sensors are sparsely positioned in a seemingly random or unorganized manner, which is often encountered in a range of scientific and engineering problems. Moreover, these sensors can be in motion and can become online or offline over time. The key leverage in addressing this scientific issue is the wealth of data accumulated from the sensors. As a solution to this problem, we propose a data-driven spatial field recovery technique founded on a structured grid-based deep-learning approach for arbitrary positioned sensors of any numbers. It should be noted that the naïve use of machine learning becomes prohibitively expensive for global field reconstruction and is furthermore not adaptable to an arbitrary number of sensors. In the present work, we consider the use of Voronoi tessellation to obtain a structured-grid representation from sensor locations enabling the computationally tractable use of convolutional neural networks. One of the central features of the present method is its compatibility with deep-learning based super-resolution reconstruction techniques for structured sensor data that are established for image processing. The proposed reconstruction technique is demonstrated for unsteady wake flow, geophysical data, and three-dimensional turbulence. The current framework is able to handle an arbitrary number of moving sensors, and thereby overcomes a major limitation with existing reconstruction methods. The presented technique opens a new pathway towards the practical use of neural networks for real-time global field estimation.

Fukami, Kai↗
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part I: Lagrangian and indirect Euler AMR algorithms

Many applications of physics and engineering involve wide ranges of time and spatial scales. The numerical simulation of localized small scales such as shock waves and material interfaces requires a large number of computational cells in these regions. For these applications, Lagrangian and Arbitrary-Lagrangian-Eulerian (ALE) related methods are engaging since the moving mesh feature naturally brings mesh cells on shock discontinuities and material interfaces are carefully captured. In addition, Adaptive-Mesh-Refinement (AMR) strategies aim to optimize computational resources by concentrating finer mesh cells only in areas of interest while using coarser cells elsewhere. A key but challenging AMR requirement consists in efficiently distributing the computational effort to achieve high accuracy without the prohibitive computational costs associated with uniformly fine grids. Here, in this document, the coupling of the p4est AMR library with a cell-centered Lagrangian scheme is presented with the goal to perform reliable 3D Lagrangian-AMR and indirect Euler-AMR multi-material simulations. In particular, it is shown that starting from a 3D indirect ALE code, the memory management and load balancing requirements can be delegated to an external library (here the p4est library) to unlock ALE-AMR capabilities. First, we present a strategy to transcribe the octant-based connectivity of the 3D AMR framework with that of an unstructured mesh of polygonal cells used in Lagrangian hydrodynamics. Then, we show how refinement and coarsening operations must be adapted to the particular Lagrangian framework to ensure the conservation of volume during those steps. Finally, several numerical test cases are presented that demonstrate the capabilities of the Lagrangian-AMR and indirect Euler-AMR algorithms.

3D cell-centered Lagrangian numerical scheme↗
DOE OSTI2022

Irrigation Modernization Task 4: Accelerating Energy Solutions (FY2022 Final Report)

This report offers insights on energy solutions for irrigation modernization that serve the needs of farmers as well as residents and industry in the local community. Solutions are found in the irrigation districts where local generation from renewable energy sources – solar, hydro, and wind – can be combined with energy storage and customer loads. These combined resources configured in microgrids can lower costs during peak loads and provide resiliency by maintaining electricity supply during outages. The goal of this project, as stated in the FY2022 AOP, is to promote realization of energy solutions that are tailored to physical location, community, infrastructure, and energy value streams. Further, it is to develop examples of how to increase value of, and overcome barriers to, energy solutions in the context of irrigation modernization. In pursuit of that goal, the project looked at options for: 1) Reducing the cost of energy consumed in irrigation systems, 2) Increasing the revenue from surplus power generation, and 3) Deploying new power generation configured as part of a local microgrid. Potential solutions to reducing energy costs and increasing surplus power revenue revolve around addressing regulatory and legal constraints tied to how power is purchased by and sold to the irrigator or irrigation district. Some headway was made in identifying barriers and ways to push utilities to be more accommodating to distributed energy sources; however, for the most part, real progress hinges on changes at the regulatory and legislative level. Deployment of local, renewable generation systems can be implemented provided the economics of the project and the location are favorable. In concert with Famers Conservation Alliance and Energy Trust of Oregon, a number of approaches were studied in the past year, including off-grid solar powered pumps, grid-tied community solar projects, and in-conduit canal hydropower systems. Ultimately three viable projects were identified: 1) North Unit Irrigation District/City of Redmond, Oregon Critical Facility Microgrid – offers combined in-conduit hydro and solar power generation. 2) Wallowa County/Joseph, Oregon Irrigation System Upgrades – centered on upgrades to a non-powered dam that will add a turbine as well as in-conduit power in canal feeders downstream. 3) Medford, Oregon Wastewater Treatment Plant Biogas Cogeneration System – centered on building out biogas storage and grid upgrades to power the plant, sell excess power, and provide emergency backup power (supplanting a diesel generator). Each of these projects has characteristics that broaden the understanding of the value of microgrids employing renewable energy to achieve resiliency and net-zero carbon goals. The first two projects are centered on new hydropower systems. Although the Medford project is only tangentially tied to an irrigation district, it was selected for study analysis as it was the only one mature enough (with sufficient data) to complete an analysis within this project year. Thus, we chose to move forward developing a case study, in concert with the Community Water-Power Resilience project, to demonstrate a method for evaluating such projects. Essentially, this case study serves as a template for studies to be carried out next year that more directly involve irrigation system hydropower, e.g., the project at the Wallowa County/Joseph, Oregon Irrigation System. Lastly, it is recognized that the locations and case studies in this report are all located in Oregon. We recognize this as a limitation. While the intent is not to ignore other states or regions, this result is driven by the fact that we have cultivated a collaboration with non-profit entities in Oregon that focus on these topics – Farmers Conservation Alliance and Energy Trust of Oregon. These partners were central to identifying projects that may be good fits for this program. A goal in the coming year is to establish collaboration with entities in other states/regions that, similarly, can connect us to potential projects in their geographic area. The potential benefits from the WPTO’s support for demonstration projects as energy solutions in irrigation districts include: (1) Alternative power supplies for communities and farms using renewable, carbon-free energy resources, (2) Cost savings for electricity for communities and farms, (3) Resiliency of power supplies for critical loads when electricity from the grid is not available, (4) Resiliency of power supplies for critical infrastructure in the event of catastrophic events, and (5) Demonstration of irrigation modernization projects that provide resilience and a reduced carbon footprint to irrigation districts and nearby communities. These deployments can serve as vanguards/archetypes spurring similar projects in other districts and states.

13 HYDRO ENERGY↗
DOE OSTI2026

What Technical Choices Matter to Characterize Heat Wave and Cold Snap Events in Support of Bulk Power Grid Reliability Studies?

Extreme weather events, such as Heat Waves (HW) and Cold Snaps (CS), pose significant risks to the power grid. The United States (U.S.) Federal Energy Regulatory Commission Order No. 896 mandates regional coordination standards that account for extreme thermal events. However, the lack of a universal definition for extreme thermal events may lead to inconsistent compliance efforts among neighboring entities, undermining the reliability of the transmission system. This study directly addresses this challenge by systematically evaluating how varying technical choices in defining HW and CS fundamentally impact the characterization and ranking of extreme events for power grid reliability studies. We used 12 event definitions and multiple temperature spatial aggregation approaches to construct historical (1980–2024) regional extreme thermal event libraries across North American Electric Reliability Corporation (NERC) subregions in the conterminous U.S. We examined the sensitivity of event characteristics (e.g., duration, frequency, intensity, and spatial coverage) to different definitions. While some definitions produced similar libraries and top event rankings, definitions based on moving-window-averaged temperatures yielded markedly different characteristics. Spatial aggregation methods had minimal impact on heat wave or cold snap intensity, frequency and duration but significantly influenced spatial coverage. The top events identified across different aggregation methods were consistent, but their ranking order varied. These findings offer critical insights for characterizing and selecting extreme thermal events and for supporting local and cross-regional coordination as required by reliability standards.

Wan, Heng [Pacific Northwest National Laboratory (↗
NASA NTRS2017

GTOC9: Methods and Results from the Jet Propulsion Laboratory Team

The removal of 123 pieces of debris from the Sunsynchronous LEO environment is accomplished by a 10-spacecraft campaign wherein the spacecraft, flying in succession over an 8-yr period, rendezvous with a series of the debris objects, delivering a de-orbit package at each one before moving on to the next object by means of impulsive manoeuvres. This was the GTOC9 problem, as posed by the European Space Agency. The methods used by the Jet Propulsion Laboratory team are described, along with the winning solution found by the team. Methods include branch-and-bound searches that exploit the natural nodal drift to compute long chains of rendezvous with debris objects, beam searches for synthesising campaigns, ant colony optimisation, and a genetic algorithm. Databases of transfers between all bodies on a fine time grid are made, containing an easyto- compute yet accurate estimate of the transfer V . Lastly, a final non-linear programming optimisation is performed to ensure the trajectories meet all the constraints and are locally optimal in initial mass.

Sims, Jon↗
NASA NTRS1994

Three-dimensional hydrodynamic Bondi-Hoyle accretion. 2: Homogeneous medium at Mach 3 with gamma = 5/3

We investigate the hydrodynamics of three-dimensional classical Bondi-Hoyle accretion. Totally absorbing spheres of varying sizes (from 10 down to 0.01 accretion radii) move at Mach 3 relative to a homogeneous and slightly perturbed medium, which is taken to be an ideal gas (gamma = 5/3). To accommodate the long-range gravitational forces, the extent of the computational volume is 32(exp 3) accretion radii. We examine the influence of numerical procedure on physical behavior. The hydrodynamics is modeled by the 'piecewise parabolic method.' No energy sources (nuclear burning) or sinks (radiation, conduction) are included. The resolution in the vicinity of the accretor is increased by multiply nesting several (5-10) grids around the sphere, each finer grid being a factor of 2 smaller in zone dimension that the next coarser grid. The largest dynamic range (ratio of size of the largest grid to size of the finest zone) is 16,384. This allows us to include a coarse model for the surface of the accretor (vacuum sphere) on the finest grid, while at the same time evolving the gas on the coarser grids. Initially (at time t = 0-10), a shock front is set up, a Mach cone develops, and the accretion column is observable. Eventually the flow becomes unstable, destroying axisymmetry. This happens approximately when the mass accretion rate reaches the values (+/- 10%) predicted by the Bondi-Hoyle accretion formula (factor of 2 included). However, our three-dimensional models do not show the highly dynamic flip-flop flow so prominent in two-dimensional calculations performed by other authors. The flow, and thus the accretion rate of all quantities, shows quasi-periodic (P approximately equals 5) cycles between quiescent and active states. The interpolation formula proposed in an accompanying paper is found to follow the collected numerical data to within approximately 30%. The specific angular momentum accreted is of the same order of magnitude as the values previously found for two-dimensional flows.

Ruffert, Maximilian↗
NASA NTRS1990

Algebraic grid generation with boundary orthogonality control

This paper presents a new approach in applying the blending function method to the generation of structured finite-difference meshes. It is shown that the surface equation developed by Coons (1967) can be easily adapted to generate two-dimensional meshes, and its extension to hyperspace allows the construction of three-dimensional meshes. The robust method in its basic form blends among the boundary curves/surfaces conforming to their intrinsic slopes. When parameter-controlled boundary-slope corrections are introduced, it is possible to establish varying degrees of orthogonality along the boundaries. Additional controls are made possible by moving points in the parameter space, which affects the movement of points in the physical space. The combination of these controls provides a simple and yet powerful means for exploiting the blending-function method to satisfy the needs of practical CFD applications. Results from a validation program for two-dimensions are shown for a variety of geometries.

Luh, Raymond Ching-Chung↗
NASA NTRS1976

Diffusion analysis for two-phase metal-matrix composite

Diffusion controlled filament matrix interaction in a metal matrix composite, where the filaments and matrix comprise a two phase binary alloy system, was mathematically modeled. The problem of a diffusion controlled, two phase moving interface by means of a one dimensional, variable grid, finite difference technique was analyzed. Concentration dependent diffusion coefficients and equilibrium solubility limits were used, and the change in filament diameter and compositional changes in the matrix were calculated as a function of exposure time at elevated temperatures. With the tungsten nickel (W-Ni) system as a model composite system, unidirectional composites containing from 0.06 to 0.44 initial filament volume fraction were modeled. Compositional changes in the matrix were calculated by superposition of the contributions from neighboring filaments. Alternate methods for determining compositional changes between first and second nearest neighbor filaments were also considered. The results show the relative importance of filament volume fraction, filament diameter, exposure temperature, and exposure time as they affect the rate and extent of filament matrix interaction.

Tenney, D. R.↗
NASA NTRSDate not supplied

Markov Decision Process based Trajectory Planning for UAVs under Uncertain Wind Conditions

In this paper we propose a Markov Decision Process (MDP) algorithm for path-planning of Unmanned Aviation Vehicles (UAVs) under varying wind conditions. Solutions to path-planning for UAVs are becoming increasingly necessary as autonomous UAVs continue to enter commercial and government spaces. Path-planning is inherently challenging, as UAVs needs to account for dynamically changing flying conditions such as weather, obstacle or no-fly zones, degraded vehicle health and off-nominal battery power consumption. Machine learning methods such as Markov Decision Process (MDPs) have the potential to revolutionize how vehicles navigate in such uncertain environments. Previous papers have demonstrated the use of MDPs to optimize UAV path-planning for energy consumption under time-varying wind distribution. In this study, UAV trajectories from a pre-determined waypoint to target cell, will be computed on a 7X7 grid environment by optimizing parameters for mission assurance and safety limits in addition to the energy consumption, and operation time. The UAV navigates the grid by taking actions to move in either of the eight cardinal and intercardinal directions, under constant thrust profile. The next state of the UAV is calculated by considering its action, transition probability, obstacle cells and the wind speed magnitude and direction. Both constant and stochastic wind will be considered in this paper, the parameters being extracted from real wind measurements in proximity to an experimental UAV flight. One of the studies to be demonstrated in this paper is that as the unmanned airspace gets more complex with multiple vehicles and environmental uncertainties, trade-offs between energy consumption, operation time, risk tolerance, and mission assurance needs to be made. Further, MDPs are capable of fast computation of UAV trajectories under varying wind, hence making them suitable for in-flight path planners.

decision-making↗
NASA NTRS1994

An experiment in hurricane track prediction using parallel computing methods

The barotropic model is used to explore the advantages of parallel processing in deterministic forecasting. We apply this model to the track forecasting of hurricane Elena (1985). In this particular application, solutions to systems of elliptic equations are the essence of the computational mechanics. One set of equations is associated with the decomposition of the wind into irrotational and nondivergent components - this determines the initial nondivergent state. Another set is associated with recovery of the streamfunction from the forecasted vorticity. We demonstrate that direct parallel methods based on accelerated block cyclic reduction (BCR) significantly reduce the computational time required to solve the elliptic equations germane to this decomposition and forecast problem. A 72-h track prediction was made using incremental time steps of 16 min on a network of 3000 grid points nominally separated by 100 km. The prediction took 30 sec on the 8-processor Alliant FX/8 computer. This was a speed-up of 3.7 when compared to the one-processor version. The 72-h prediction of Elena's track was made as the storm moved toward Florida's west coast. Approximately 200 km west of Tampa Bay, Elena executed a dramatic recurvature that ultimately changed its course toward the northwest. Although the barotropic track forecast was unable to capture the hurricane's tight cycloidal looping maneuver, the subsequent northwesterly movement was accurately forecasted as was the location and timing of landfall near Mobile Bay.

Song, Chang G.↗
NASA NTRS2008

Remote Sensing

Remote sensing is measuring something without touching it. Most methods measure a portion of the electro-magnetic spectrum using energy reflected from or emitted by a material. Moving the instrument away makes it easier to see more at one time. Airplanes are good but satellites are much better. Many things can not be easily measured on the scale of an individual person. Example - measuring all the vegetation growing at one time in even the smallest country. A satellite can see things over large areas repeatedly and in a consistent way. Data from the detector is reported as digital values for a grid that covers some portion of the Earth. Because it is digital and consistent a computer can extract information or enhance the data for a specific purpose.

Rickman, Douglas↗
NASA NTRS1990

Evolution of midplate hotspot swells: Numerical solutions

The evolution of midplate hotspot swells on an oceanic plate moving over a hot, upwelling mantle plume is numerically simulated. The plume supplies a Gaussian-shaped thermal perturbation and thermally-induced dynamic support. The lithosphere is treated as a thermal boundary layer with a strongly temperature-dependent viscosity. The two fundamental mechanisms of transferring heat, conduction and convection, during the interaction of the lithosphere with the mantle plume are considered. The transient heat transfer equations, with boundary conditions varying in both time and space, are solved in cylindrical coordinates using the finite difference ADI (alternating direction implicit) method on a 100 x 100 grid. The topography, geoid anomaly, and heat flow anomaly of the Hawaiian swell and the Bermuda rise are used to constrain the models. Results confirm the conclusion of previous works that the Hawaiian swell can not be explained by conductive heating alone, even if extremely high thermal perturbation is allowed. On the other hand, the model of convective thinning predicts successfully the topography, geoid anomaly, and the heat flow anomaly around the Hawaiian islands, as well as the changes in the topography and anomalous heat flow along the Hawaiian volcanic chain.

Liu, Mian↗
DOE OSTI2022

A Multifaceted Analysis of Chemical-Absorption Heat Pump Technology for Integrated Energy Systems

Integrated Energy Systems (IES) research and development is essential for improving the economic usage of lowcarbon energy sources such as nuclear power, solar, and wind in the U.S. An ideal IES uses various energy sources and delivers energy to the power grid and industry as efficiently as possible. As part of this effort, there are many opportunities to use low-carbon energy for industries requiring process heat for production of many chemicals and fuels [1]. Currently, industries only have the option to burn CO2 emitting fuels or use resistance heaters for this process heat. Using resistance heaters is one way to electrify a process, allowing for low-carbon energy sources to be used, but is an inefficient method unless temperatures exceed 1000?C. Heat pumps have long been used to provide efficient heating or cooling by moving heat instead of generating it. More traditional heat pumps such as vapor compression heat pumps and absorption heat pumps are limited to temperatures below 300?C due to refrigerant and component material limits. However, chemical heat pumps have been investigated as an option for pumping heat at temperatures above 600?C [2], making the heat more applicable to many more chemical and fuel production processes.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗
NASA NTRS2002

Lattice Boltzmann Equation On a 2D Rectangular Grid

We construct a multi-relaxation lattice Boltzmann model on a two-dimensional rectangular grid. The model is partly inspired by a previous work of Koelman to construct a lattice BGK model on a two-dimensional rectangular grid. The linearized dispersion equation is analyzed to obtain the constraints on the isotropy of the transport coefficients and Galilean invariance for various wave propagations in the model. The linear stability of the model is also studied. The model is numerically tested for three cases: (a) a vortex moving with a constant velocity on a mesh periodic boundary conditions; (b) Poiseuille flow with an arbitras~y inclined angle with respect to the lattice orientation: and (c) a cylinder &symmetrically placed in a channel. The numerical results of these tests are compared with either analytic solutions or the results obtained by other methods. Satisfactory results are obtained for the numerical simulations.

Bouzidi, MHamed↗
NASA NTRS2001

Grid Convergence of High Order Methods for Multiscale Complex Unsteady Viscous Compressible Flows

Grid convergence of several high order methods for the computation of rapidly developing complex unsteady viscous compressible flows with a wide range of physical scales is studied. The recently developed adaptive numerical dissipation control high order methods referred to as the ACM and wavelet filter schemes are compared with a fifth-order weighted ENO (WENO) scheme. The two 2-D compressible full Navier-Stokes models considered do not possess known analytical and experimental data. Fine grid solutions from a standard second-order TVD scheme and a MUSCL scheme with limiters are used as reference solutions. The first model is a 2-D viscous analogue of a shock tube problem which involves complex shock/shear/boundary-layer interactions. The second model is a supersonic reactive flow concerning fuel breakup. The fuel mixing involves circular hydrogen bubbles in air interacting with a planar moving shock wave. Both models contain fine scale structures and are stiff in the sense that even though the unsteadiness of the flows are rapidly developing, extreme grid refinement and time step restrictions are needed to resolve all the flow scales as well as the chemical reaction scales.

Sjoegreen, B.↗
NASA NTRS1995

Optimization of Time-Dependent Particle Tracing Using Tetrahedral Decomposition

An efficient algorithm is presented for computing particle paths, streak lines and time lines in time-dependent flows with moving curvilinear grids. The integration, velocity interpolation and step-size control are all performed in physical space which avoids the need to transform the velocity field into computational space. This leads to higher accuracy because there are no Jacobian matrix approximations or expensive matrix inversions. Integration accuracy is maintained using an adaptive step-size control scheme which is regulated by the path line curvature. The problem of cell-searching, point location and interpolation in physical space is simplified by decomposing hexahedral cells into tetrahedral cells. This enables the point location to be done analytically and substantially faster than with a Newton-Raphson iterative method. Results presented show this algorithm is up to six times faster than particle tracers which operate on hexahedral cells yet produces almost identical particle trajectories.

Kenwright, David↗
NASA NTRS1992

Adaptive explicit and implicit finite element methods for transient thermal analysis

The application of adaptive finite element methods to the solution of transient heat conduction problems in two dimensions is investigated. The computational domain is represented by an unstructured assembly of linear triangular elements and the mesh adaptation is achieved by local regeneration of the grid, using an error estimation procedure coupled to an automatic triangular mesh generator. Two alternative solution procedures are considered. In the first procedure, the solution is advanced by explicit timestepping, with domain decomposition being used to improve the computational efficiency of the method. In the second procedure, an algorithm for constructing continuous lines which pass only once through each node of the mesh is employed. The lines are used as the basis of a fully implicit method, in which the equation system is solved by line relaxation using a block tridiagonal equation solver. The numerical performance of the two procedures is compared for the analysis of a problem involving a moving heat source applied to a convectively cooled cylindrical leading edge.

Probert, E. J.↗