Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parallel computing methodologies”

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.

At least 199 records · Page 11

Boundary Layer Protuberance Simulations in Channel Nozzle Arc-Jet

Two protuberance designs were modeled in the channel nozzle of the NASA Johnson Space Center Atmospheric Reentry Materials and Structures Facility with the Data-Parallel Line Relaxation computational fluid dynamics code. The heating on the protuberance was compared to nominal baseline heating at a single fixed arc-jet condition in order to obtain heating augmentation factors for flight traceability in the Boundary Layer Transition Flight Experiment on Space Shuttle Orbiter flights STS-119 and STS-128. The arc-jet simulations were performed in conjunction with the actual ground tests performed on the protuberances. The arc-jet simulations included non-uniform inflow conditions based on the current best practices methodology and used variable enthalpy and constant mass flow rate across the throat. Channel walls were modeled as fully catalytic isothermal surfaces, while the test section (consisting of Reaction Cured Glass tiles) was modeled as a partially catalytic radiative equilibrium wall. The results of the protuberance and baseline simulations were compared to the applicable ground test results, and the effects of the protuberance shock on the opposite channel wall were investigated.

Marichalar, J. J.↗

An Approach to Solving Enclosure Radiation Problems in A Multi-Physics Context

Thermal protection system analysis of complex features or damage sites can sometimes require modeling of high temperature enclosures. Implementing efficient and accurate view-factor algorithms required to model such problems is complex. The current work leverages the Non-equilibrium Radiation (NERO) software, which solves the radiation transport equation in a finite-volume scheme, to alleviating challenges often faced with view-factor calculations. By assuming heat transfer occurs only between grey bodies and that the medium is non-participating, computational cost of the method is significantly reduced. The enclosure physics are modeled through emitting and reflecting boundary conditions in NERO. The emitted radiative flux is dependent on the wall temperature which is a solution to the material response, obtained from Icarus, in this context. The Ares framework manages the time-advancement and exchange of the necessary data between the solvers. The surface energy balance is modified to account for the enclosure terms within the material response boundary condition. The methodology was verified against analytical solutions including radiating parallel plates, a hollow cylinder (shown in Fig. 1), and a hemisphere. Application of the methodology to inform the design of components of the Dragonfly system will be shown.

Ablation↗

Predicting nonequilibrium Green’s function dynamics and photoemission spectra via nonlinear integral operator learning

Understanding the dynamics of nonequilibrium quantum many-body systems is an important research topic in a wide range of fields across condensed matter physics, quantum optics, and high-energy physics. However, numerical studies of large-scale nonequilibrium phenomena in realistic materials face serious challenges due to intrinsic high-dimensionality of quantum many-body problems and the absence of time-invariance. The nonequilibrium properties of many-body systems can be described by the dynamics of the correlator, or the Green's function of the system, whose time evolution is given by a high-dimensional system of integro-differential equations, known as the Kadanoff–Baym equations (KBEs). The time-convolution term in KBEs, which needs to be recalculated at each time step, makes it difficult to perform long-time numerical simulation. In this paper, we develop an operator-learning framework based on recurrent neural networks (RNNs) to address this challenge. We utilize RNNs to learn the nonlinear mapping between Green's functions and convolution integrals in KBEs. By using the learned operators as a surrogate model in the KBE solver, we obtain a general machine-learning scheme for predicting the dynamics of nonequilibrium Green's functions. Besides significant savings per each time step, the new methodology reduces the temporal computational complexity from $O(N_t^3)$ to $O(N_t)$ where N t is the number of steps taken in a simulation, thereby making it possible to study large many-body problems which are currently infeasible with conventional KBE solvers. Through various numerical examples, we demonstrate the effectiveness of the operator-learning based approach in providing accurate predictions of physical observables such as the reduced density matrix and time-resolved photoemission spectra. Moreover, our framework exhibits clear numerical convergence and can be easily parallelized, thereby facilitating many possible further developments and applications.

97 MATHEMATICS AND COMPUTING↗

Multi-level Hierarchical Poly Tree computer architectures

Based on the concept of hierarchical substructuring, this paper develops an optimal multi-level Hierarchical Poly Tree (HPT) parallel computer architecture scheme which is applicable to the solution of finite element and difference simulations. Emphasis is given to minimizing computational effort, in-core/out-of-core memory requirements, and the data transfer between processors. In addition, a simplified communications network that reduces the number of I/O channels between processors is presented. HPT configurations that yield optimal superlinearities are also demonstrated. Moreover, to generalize the scope of applicability, special attention is given to developing: (1) multi-level reduction trees which provide an orderly/optimal procedure by which model densification/simplification can be achieved, as well as (2) methodologies enabling processor grading that yields architectures with varying types of multi-level granularity.

Padovan, Joe↗

Contextual subspace variational quantum eigensolver calculation of the dissociation curve of molecular nitrogen on a superconducting quantum computer

Abstract We present an experimental demonstration of the Contextual Subspace Variational Quantum Eigensolver on superconducting hardware. Calculating the potential energy curve of molecular nitrogen proves challenging for many conventional quantum chemistry techniques, since static correlation dominates in the dissociation limit. Our quantum simulations retain good agreement with the Full Configuration Interaction energy, outperforming all benchmarked single-reference wavefunction techniques in capturing the bond-breaking appropriately. Moreover, our methodology is competitive with multiconfigurational approaches but at a saving of quantum resource, meaning larger active spaces can be treated for a fixed qubit allowance. To achieve this result, we deploy an error mitigation/suppression strategy comprised of Dynamical Decoupling, Measurement-Error Mitigation and Zero-Noise Extrapolation. Circuit parallelization also provides passive noise-averaging and improves the effective shot yield to reduce the measurement overhead. Furthermore, we introduce a modified adaptive ansatz construction algorithm that incorporates hardware awareness into our variational circuits, minimizing the transpilation cost for the target qubit topology.

Physics↗

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗

A Cognitive-System Model for En Route Air Traffic Management

NASA Ames Research Center has been engaged in the development of advanced air traffic management technologies whose basic form is cognitive aiding systems for air traffic controller and flight deck operations. In the design and evaluation of such systems the dynamic interaction between the airborne aiding system and the ground-based aiding systems forms a critical coupling for control. The human operator is an integral control element in the system and the optimal integration of human decision and performance parameters with those of the automation aiding systems offers a significant challenge to cognitive engineering. This paper presents a study in full mission simulation and the development of a predictive computational model of human performance. We have found that this combination of methodologies provide a powerful design-aiding process. We have extended the computational model Man Machine Integrated Design and Analysis System (N13DAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems), operating aircraft airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require the representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. We have exercised this model in a multi-air traffic sector scenario with potential conflict among aircraft at and across sector boundaries. We have modeled the control situation as a multiple closed loop system. The inner and outer loop alerting structure of air traffic management has many implications that need to be investigated to assure adequate design. First, there are control and stability factors implicit in the design. As the inner loop response time approaches that of the outer loop, system stability may be compromised in that controllers may be solving a problem the nature of which has already been changed by pilot action. Second, information exchange and information presentation for both air and ground must be designed to complement as opposed to compete with each other. Third, the level of individual and shared awareness in trajectory modification and flight conformance needs to be defined. Fourth, the level of required awareness and performance impact of mixed fleet operations and failed-mode recovery must be explored.

Corker, Kevin M.↗

An Optimized Multicolor Point-Implicit Solver for Unstructured Grid Applications on Graphics Processing Units

In the field of computational fluid dynamics, the Navier-Stokes equations are often solved using an unstructuredgrid approach to accommodate geometric complexity. Implicit solution methodologies for such spatial discretizations generally require frequent solution of large tightly-coupled systems of block-sparse linear equations. The multicolor point-implicit solver used in the current work typically requires a significant fraction of the overall application run time. In this work, an efficient implementation of the solver for graphics processing units is proposed. Several factors present unique challenges to achieving an efficient implementation in this environment. These include the variable amount of parallelism available in different kernel calls, indirect memory access patterns, low arithmetic intensity, and the requirement to support variable block sizes. In this work, the solver is reformulated to use standard sparse and dense Basic Linear Algebra Subprograms (BLAS) functions. However, numerical experiments show that the performance of the BLAS functions available in existing CUDA libraries is suboptimal for matrices representative of those encountered in actual simulations. Instead, optimized versions of these functions are developed. Depending on block size, the new implementations show performance gains of up to 7x over the existing CUDA library functions.

Zubair, Mohammad↗

Advanced software integration: The case for ITV facilities

The array of technologies and methodologies involved in the development and integration of avionics software has moved almost as rapidly as computer technology itself. Future avionics systems involve major advances and risks in the following areas: (1) Complexity; (2) Connectivity; (3) Security; (4) Duration; and (5) Software engineering. From an architectural standpoint, the systems will be much more distributed, involve session-based user interfaces, and have the layered architectures typified in the layers of abstraction concepts popular in networking. Typified in the NASA Space Station Freedom will be the highly distributed nature of software development itself. Systems composed of independent components developed in parallel must be bound by rigid standards and interfaces, the clean requirements and specifications. Avionics software provides a challenge in that it can not be flight tested until the first time it literally flies. It is the binding of requirements for such an integration environment into the advances and risks of future avionics systems that form the basis of the presented concept and the basic Integration, Test, and Verification concept within the development and integration life cycle of Space Station Mission and Avionics systems.

Garman, John R.↗

A generic applications subroutine library for the MPP

A new methodology to increase the utility of the Massively Parallel Processor (MPP) was developed, and is presented as an addition to the current methods of using the MPP. This methodology provides for the development of an MPP side abstraction layer that is callable from any host side high level language. Routines in the abstraction layer have the option of using a powerful software tool for accessing the stager as virtual memory. An additional abstraction layer that allows for remote access to the MPP via DECnet is discussed. This integrated approach to programming the MPP is a valuable tool for the implementation of interactive user driver systems that require the computational capabilities of the MPP as well as a controlled user view. It is expected that this methodology will be used to integrate the MPP into many such systems, and thus promote greater use of the MPP by scientific researchers who are accustomed to user friendly environments.

Gough, Michael L.↗

Effects of displacement and rate saturation on the control of statically unstable aircraft

Methodologies are presented for the analysis and design of stability augmentation control laws for aircraft in which 'hard' displacement and rate limiting are significant. Candidate control laws are derived using the linear-quadratic (LQ) regulator. Analytical and computational estimates of the stability limits imposed by control saturation are presented using state trajectories with control limiting, as well as describing functions and eigenvalue computation. Analysis also includes an investigation of the interaction of the state-space saturation and stability boundaries for various choices of LQ weighting matrices. For minimum-energy control, the saturation and stability boundaries are shown to be parallel. In this case, there is a direct relation between the solution to the matrix Riccati equation and the aircraft's open-loop dynamics.

Hanson, G. D.↗

Injector Design Tool Improvements: User's manual for FDNS V.4.5

The major emphasis of the current effort is in the development and validation of an efficient parallel machine computational model, based on the FDNS code, to analyze the fluid dynamics of a wide variety of liquid jet configurations for general liquid rocket engine injection system applications. This model includes physical models for droplet atomization, breakup/coalescence, evaporation, turbulence mixing and gas-phase combustion. Benchmark validation cases for liquid rocket engine chamber combustion conditions will be performed for model validation purpose. Test cases may include shear coaxial, swirl coaxial and impinging injection systems with combinations LOXIH2 or LOXISP-1 propellant injector elements used in rocket engine designs. As a final goal of this project, a well tested parallel CFD performance methodology together with a user's operation description in a final technical report will be reported at the end of the proposed research effort.

Chen, Yen-Sen↗

Unconditionally stable concurrent procedures for transient finite-element analysis

A family of algorithms was outlined which would appear to be particularly well-suited for implementation in a parallel environment. This is due to the fact that for any partition of the mesh each subdomain in the partition can be processed over a time step simultaneously and independently of the rest. The method eliminates the need for assembling and factorizing large global arrays while retaining the unconditional stability properties of the algorithms used at the local level. To critically appraise the proposed methodology, two limiting cases were considered: element-by-element mesh partitions, and coarse mesh partitions. It was concluded that while the proposed methodology can be useful in sequential machines, it would appear to be promising as it bears on computation. It should also be emphasized that extensions of the method to nonlinear problems are possible.

Ortiz, Michael↗

Axisymmetric computational fluid dynamics analysis of Saturn V/S1-C/F1 nozzle and plume

An axisymmetric single engine Computational Fluid Dynamics calculation of the Saturn V/S 1-C vehicle base region and F1 engine plume is described. There were two objectives of this work, the first was to calculate an axisymmetric approximation of the nozzle, plume and base region flow fields of S1-C/F1, relate/scale this to flight data and apply this scaling factor to a NLS/STME axisymmetric calculations from a parallel effort. The second was to assess the differences in F1 and STME plume shear layer development and concentration of combustible gases. This second piece of information was to be input/supporting data for assumptions made in NLS2 base temperature scaling methodology from which the vehicle base thermal environments were being generated. The F1 calculations started at the main combustion chamber faceplate and incorporated the turbine exhaust dump/nozzle film coolant. The plume and base region calculations were made for ten thousand feet and 57 thousand feet altitude at vehicle flight velocity and in stagnant freestream. FDNS was implemented with a 14 species, 28 reaction finite rate chemistry model plus a soot burning model for the RP-1/LOX chemistry. Nozzle and plume flow fields are shown, the plume shear layer constituents are compared to a STME plume. Conclusions are made about the validity and status of the analysis and NLS2 vehicle base thermal environment definition methodology.

Ruf, Joseph H.↗

Parallel, Gradient-Based Anisotropic Mesh Adaptation for Re-entry Vehicle Configurations

Two gradient-based adaptation methodologies have been implemented into the Fun3d refine GridEx infrastructure. A spring-analogy adaptation which provides for nodal movement to cluster mesh nodes in the vicinity of strong shocks has been extended for general use within Fun3d, and is demonstrated for a 70 sphere cone at Mach 2. A more general feature-based adaptation metric has been developed for use with the adaptation mechanics available in Fun3d, and is applicable to any unstructured, tetrahedral, flow solver. The basic functionality of general adaptation is explored through a case of flow over the forebody of a 70 sphere cone at Mach 6. A practical application of Mach 10 flow over an Apollo capsule, computed with the Felisa flow solver, is given to compare the adaptive mesh refinement with uniform mesh refinement. The examples of the paper demonstrate that the gradient-based adaptation capability as implemented can give an improvement in solution quality.

Bibb, Karen L.↗

CEA2022: A Modernization of NASA Glenn’s Software CEA (Chemical Equilibrium with Applications)

The software program “Chemical Equilibrium with Applications” (CEA) is used to solve chemical equilibrium, and compute thermodynamic and transport properties of the resulting mixture, and also has special solvers dedicated to rocket, shock, and detonation problems. We have recently completed a full re-write of CEA with modernization and improvements, called “CEA2022”. In this paper, we will give an overview of CEA2022’s features, and discuss some of the fundamental equations used by CEA2022, as well as the fundamental assumptions, in order to provide users with a complete understanding of the software’s methodology. Several enhancements have been made to the software, including modern software development practices, interface improvements, and additional features. The feature enhancements include: running cases in parallel with thread safe solves, thermodynamic and transport database updates, and allowing for negative and inert reactants. In terms of interface improvements, we have made CEA a reusable library by adding APIs for multiple languages, including Python, Matlab, Excel, Fortran, and C. The subroutine interface allows for integration with other applications, including flow-solver integration (i.e. with CFD). We also compare results between CEA2022 and the previous version (CEA2) as a validation of the new software.

chemical equilibrium↗

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗

Unic Unstructured CFD Methodology Development

Base heating characteristics is crucial to the success and the overall performance of the X-33 engine. Base heating is important throughout the entire flight trajectory due to the aerospike engine design of X-33. The base region is surrounded by the hot-gas plume, which expands, circulates and impinges on the base. An advanced computation fluid dynamics method is employed in an effort to develop a robust, accurate and efficient tool for the X-33 base heating performance predictions. This computational tool is developed based on a Navier-Stokes flow solver, which is suitable for general complex geometry and includes turbulence, finite-rate chemistry, and radiation models. To fulfill the fast turnaround requirement as a design analysis tool, adaptive mesh refinement method and parallel-computing algorithm are also incorporated in the present model. Case study for the X-33 base-region fluid dynamics and heat transfer characteristics are presented.

Chen, Y. S.↗