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At least 559 records · Page 31

Stochastic tensor contraction for quantum chemistry

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.

Chemical Physics (physics.chem-ph)↗

Low cost programmable multisimulator facility

A prototype, low cost multisimulator facility consisting of a DEC LSI-11 host computer and multiple desk top simulators is reported. The facility includes a main-frame system, a voice system, and a multi-cab system which consists of a flight panel, a host subsystem, and a flight simulator system. Software components are described, and the simulator computer, which provides flight dynamics, a path predictor, and navigation and data communications is discussed. The system may be computationally upgraded by specification of the DEC LSI-11/23, thus obtaining at least a two-fold increase in real-time computational power.

Kreifeldt, J. G.↗

Spectral decontamination of a real-time helicopter simulation

Nonlinear mathematical models of a rotor system, referred to as rotating blade-element models, produce steady-state, high-frequency harmonics of significant magnitude. In a discrete simulation model, certain of these harmonics may be incompatible with realistic real-time computational constraints because of their aliasing into the operational low-pass region. However, the energy is an aliased harmonic may be suppressed by increasing the computation rate of an isolated, causal nonlinearity and using an appropriate filter. This decontamination technique is applied to Sikorsky's real-time model of the Black Hawk helicopter, as supplied to NASA for handling-qualities investigations.

Mcfarland, R. E.↗

Application of finite element substructuring to composite micromechanics

Finite element substructuring is used to predict unidirectional fiber composite hygral (moisture), thermal, and mechanical properties. COSMIC NASTRAN and MSC/NASTRAN are used to perform the finite element analysis. The results obtained from the finite element model are compared with those obtained from the simplified composite micromechanics equations. A unidirectional composite structure made of boron/HM-epoxy, S-glass/IMHS-epoxy and AS/IMHS-epoxy are studied. The finite element analysis is performed using three dimensional isoparametric brick elements and two distinct models. The first model consists of a single cell (one fiber surrounded by matrix) to form a square. The second model uses the single cell and substructuring to form a nine cell square array. To compare computer time and results with the nine cell superelement model, another nine cell model is constructed using conventional mesh generation techniques. An independent computer program consisting of the simplified micromechanics equation is developed to predict the hygral, thermal, and mechanical properties for this comparison. The results indicate that advanced techniques can be used advantageously for fiber composite micromechanics.

Caruso, J. J.↗

Simulation of proton-induced energy deposition in integrated circuits

A time-efficient simulation technique was developed for modeling the energy deposition by incident protons in modern integrated circuits. To avoid the excessive computer time required by many proton-effects simulators, a stochastic method was chosen to model the various physical effects responsible for energy deposition by incident protons. Using probability density functions to describe the nuclear reactions responsible for most proton-induced memory upsets, the simulator determines the probability of a proton hit depositing the energy necessary for circuit destabilization. This factor is combined with various circuit parameters to determine the expected error-rate in a given proton environment. An analysis of transient or dose-rate effects is also performed. A comparison to experimental energy-disposition data proves the simulator to be quite accurate for predicting the expected number of events in certain integrated circuits.

Fernald, Kenneth W.↗

Wind Code Application to External Forebody Flowfields with Comparisons to Experimental Results

The WIND Code, a general purpose Navier-Stokes solver, has been utilized to obtain supersonic external flowfield Computational Fluid Dynamics (CFD) solutions over an axisymmetric, parabolic forebody with comparisons made to wind tunnel experimental results. Various cases have been investigated at supersonic freestream conditions ranging from Mach 2.0 to 3.5, at 0 deg and 3 deg angles-of-attack, and with either a sharp-nose or blunt-nose forebody configuration. Both a turbulent (Baldwin-Lomax algebraic turbulence model) and a laminar model have been implemented in the CFD. Obtaining the solutions involved utilizing either the parabolized- or full-Navier-Stokes analyses supplied in WIND. Comparisons have been made with static pressure measurements, with boundary-layer rake and flowfield rake pitot pressure measurements, and with temperature sensitive paint experimental results. Using WIND's parabolized Navier-Stokes capability, grid sequencing, and the Baldwin-Lomax algebraic turbulence model allowed for significant reductions in computational time while still providing good agreement with experiment. Given that CFD and experiment compare well, WIND is found to be a good computational platform for solving this type of forebody problem, and the grids developed in conjunction with it will be used in the future to investigate varying freestream conditions not tested experimentally.

Frate, F. C.↗

Linear Static Structural and Vibration Analysis on High-Performance Computers

Parallel computers offer the opportunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on a massively-parallel computers hereafter referred to as Scalable High Performance Computers (SHPC) for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. Models of high speed civil transport). The goal of this research is to develop new efficient technique which extend structural analysis to SHPC and make large-scale structural analyses tractable.

Baddourah, Majdi↗

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗

Three approaches to reliability analysis

It is noted that current reliability analysis tools differ not only in their solution techniques, but also in their approach to model abstraction. The analyst must be satisfied with the constraints that are intrinsic to any combination of solution technique and model abstraction. To get a better idea of the nature of these constraints, three reliability analysis tools (HARP, ASSIST/SURE, and CAME) were used to model portions of the Integrated Airframe/Propulsion Control System architecture. When presented with the example problem, all three tools failed to produce correct results. In all cases, either the tool or the model had to be modified. It is suggested that most of the difficulty is rooted in the large model size and long computational times which are characteristic of Markov model solutions.

Mesh networks↗

Machine Learning-Based Model Predictive Control of Two-Time-Scale Systems

In this study, we present a general form of nonlinear two-time-scale systems, where singular perturbation analysis is used to separate the dynamics of the slow and fast subsystems. Machine learning techniques are utilized to approximate the dynamics of both subsystems. Specifically, a recurrent neural network (RNN) and a feedforward neural network (FNN) are used to predict the slow and fast state vectors, respectively. Moreover, we investigate the generalization error bounds for these machine learning models approximating the dynamics of two-time-scale systems. Next, under the assumption that the fast states are asymptotically stable, our focus shifts toward designing a Lyapunov-based model predictive control (LMPC) scheme that exclusively employs the RNN to predict the dynamics of the slow states. Additionally, we derive sufficient conditions to guarantee the closed-loop stability of the system under the sample-and-hold implementation of the controller. A nonlinear chemical process example is used to demonstrate the theory. In particular, two RNN models are constructed: one to model the full two-time-scale system and the other to predict solely the slow state vector. Both models are integrated within the LMPC scheme, and we compare their closed-loop performance while assessing the computational time required to execute the LMPC optimization problem.

97 MATHEMATICS AND COMPUTING↗

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗

A unified approach for the application of general perturbation theories to the artificial satellite problem

An Encke-type method is developed as well as a variation of parameters method, both of which use a non-Keplerian reference orbit. The regularized time is used in the numerical integration and the optimum value of n is found for each type of orbit investigated. Accuracy and computation time comparisons are made with a classical Cowell method. It should be noted that the element formulations developed and tested were found to be exceptionally numerically stable in the sense that it was possible to achieve numerical consistency order of very long integration periods - a property not available with the Cowell formulation - and therefore these formulations may be helpful for high precision calculations.

Alfriend, K. T.↗

A vortex-lattice method for the calculation of the nonsteady separated flow over delta wings

An analysis is made of the wake structure and the forces on a delta wing as it undergoes nonsteady motion, wherein the flow separates at the leading edge. Comparisons of these predictions with existing experimental and theoretical data for the nonsteady linear and nonlinear motions indicate good agreement. It was found that the time-dependent, wake-shedding numerical procedure applied here for the wake rollup and the lift force calculation resulted in considerable saving of computer time over methods using the iterative wake rollup procedure. Calculated results for various motions of the delta wing, including the plunging motion, are presented for both the separated and the attached flow cases.

Levin, D.↗

Specular and direct radiative loads on space structure

The use of special models for trusses, and of fast graphical computational techniques, are discussed to reduce the computation times of intersurface radiation loads and specularly reflected radiation. The conditions under which the One-Dimensional approximation can be used, and the computation of the obstructed view factors for arbitrary surfaces, including the One-Dimensional surface, are considered using both contour and double area integration. The Adaptive Ray Tracing method is found to be very fast for surface configurations and obstruction densities typical of space structures, and it is shown to be best suited to views of J from I which are relatively simple and cover only a few subareas of S.

Emery, A. F.↗

Reconstruction of coded aperture images

Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

Bielefeld, Michael J.↗

Flowfield computation of entry vehicles

The equations governing the multidimensional flow of a reacting mixture of thermally perfect gasses were derived. The modeling procedures for the various terms of the conservation laws are discussed. A numerical algorithm, based on the finite-volume approach, to solve these conservation equations was developed. The advantages and disadvantages of the present numerical scheme are discussed from the point of view of accuracy, computer time, and memory requirements. A simple one-dimensional model problem was solved to prove the feasibility and accuracy of the algorithm. A computer code implementing the above algorithm was developed and is presently being applied to simple geometries and conditions. Once the code is completely debugged and validated, it will be used to compute the complete unsteady flow field around the Aeroassist Flight Experiment (AFE) body.

Prabhu, Dinesh K.↗

Evaluating Performance of Components

Parallel Component Performance Benchmarks is a computer program developed to aid the evaluation of the Common Component Architecture (CCA) - a software architecture, based on a component model, that was conceived to foster high-performance computing, including parallel computing. More specifically, this program compares the performances (principally by measuring computing times) of componentized versus conventional versions of the Parallel Pyramid 2D Adaptive Mesh Refinement library - a software library that is used to generate computational meshes for solving physical problems and that is typical of software libraries in use at NASA s Jet Propulsion Laboratory.

Katz, Daniel↗

Precision Departure Release Capability (PDRC) Integration, Evaluation and Transition

NASA's Precision Departure Release Capability (PDRC) research activity is assessing the use of surface trajectory-based takeoff (OFF) time estimates for en route domain departure scheduling in Call For Release situations. Current aircraft departure release times computed by an Air Traffic Management decision support tool to meet Call For Release constraints are based on coarse estimates of aircraft OFF times. Uncertainty in OFF time estimates may result in missed opportunities to merge into an overhead stream and lost throughput. However, technology exists to improve OFF time estimates by using more accurate aircraft trajectory predictions available in NextGen airport surface management decision support tools. PDRC findings are expected to be broadly applicable to NextGen integrated arrival/departure/surface implementations. For concept development and evaluation purposes this research activity integrates NASA's Surface Management System (SMS) OFF time prediction capabilities with Traffic Management Advisor (TMA) departure scheduling functions. PDRC field evaluations are being conducted at the North Texas (NTX) Research Station. The NASA/FAA Integrated Arrival/Departure/Surface Research Transition Team is using PDRC as a pathfinder for developing technology transfer mechanisms and procedures.

Engelland, Shawn A.↗