SEARCH · Engineering Papers

Results for “algorithm complexity analysis”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRS2000

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAFT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAFT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗

NASA NTRS2003

On the Hilbert-Huang Transform Data Processing System Development

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The Fourier view of nonlinear mechanics that had existed for a long time, and the associated FFT (fairly recent development), carry strong a-priori assumptions about the source data, such as linearity and of being stationary. Natural phenomena measurements are essentially nonlinear and nonstationary. A very recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT) proposes a novel approach to the solution for the nonlinear class of spectrum analysis problems. Using the Empirical Mode Decomposition (EMD) followed by the Hilbert Transform of the empirical decomposition data (HT), the HHT allows spectrum analysis of nonlinear and nonstationary data by using an engineering a-posteriori data processing, based on the EMD algorithm. This results in a non-constrained decomposition of a source real value data vector into a finite set of Intrinsic Mode Functions (IMF) that can be further analyzed for spectrum interpretation by the classical Hilbert Transform. This paper describes phase one of the development of a new engineering tool, the HHT Data Processing System (HHTDPS). The HHTDPS allows applying the "T to a data vector in a fashion similar to the heritage FFT. It is a generic, low cost, high performance personal computer (PC) based system that implements the HHT computational algorithms in a user friendly, file driven environment. This paper also presents a quantitative analysis for a complex waveform data sample, a summary of technology commercialization efforts and the lessons learned from this new technology development.

Kizhner, Semion↗

NASA NTRS2004

Using Block-local Atomicity to Detect Stale-value Concurrency Errors

Data races do not cover all kinds of concurrency errors. This paper presents a data-flow-based technique to find stale-value errors, which are not found by low-level and high-level data race algorithms. Stale values denote copies of shared data where the copy is no longer synchronized. The algorithm to detect such values works as a consistency check that does not require any assumptions or annotations of the program. It has been implemented as a static analysis in JNuke. The analysis is sound and requires only a single execution trace if implemented as a run-time checking algorithm. Being based on an analysis of Java bytecode, it encompasses the full program semantics, including arbitrarily complex expressions. Related techniques are more complex and more prone to over-reporting.

Artho, Cyrille↗

NASA NTRS2012

The Validity Chlorophyll-a Estimation by Sun Induced Fluorescence in Estuarine Waters: An Analysis of Long-term (2003-2011) Water Quality Data from Tampa Bay, Florida (USA)

Satellite observation of phytoplankton concentration or chlorophyll-a is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chlorophyll-a inaccurate. Measurement of sun-induced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum, may provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite baseline algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms using a comprehensive long term in situ data set. In an unprecedented analysis of a long term (2003-2011) in situ monitoring data from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer (MODIS) against chlorophyll ]a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions within the estuary including water depth, distance from shore and structures and eight water quality parameters. From the 39 station for which data was derived, 22 stations showed significant correlations when the FLH product was matched with in situ chlorophyll-alpha data. The correlations (r2) for individual stations within Tampa Bay ranged between 0.67 (n=28, pless than 0.01) and-0.457 (n=12, p=.016), indicating that for some areas within the Bay, FLH can be a good predictor of chlorophyll-alpha concentration and hence a useful tool for the analysis of water quality. Overall, the results show a 106% increase in the validity of chlorophyll -a concentration estimates using FLH over the standard the blue-green OC3M algorithm. This analysis also illustrates that the correlations between FLH and in situ chlorophyll -a measurements increases with increasing water depth and distance of the monitoring sites from both the shore and structures. However, due to confounding factors related to the complexity of the estuarine system, a linear improvement in the FLH to chlorophyll ]a relationship was not clearly noted with increasing depth and distance from shore alone. Correlations of FLH with turbidity, nutrients (total nitrogen and total phosphorous) biological oxygen demand, salinity, sea surface temperature correlated positively with FLH concentrations, while dissolved oxygen and pH showed negative correlations. Principle component analyses are employed to further describe the relationships between the multivariate water quality parameters and the FLH product. The majority of sites with higher and very significant correlations (pless than 0.01) also showed high correlation values for nutrients, turbidity and biological oxygen demand. These sites were on average in greater than seven meters of water and over five kilometers from shore. A thorough understanding of the relationship between the MODIS FLH product and in situ water quality parameters will enhance our understanding of the accuracy MODIS fs global FLH algorithm and assist in optimizing its calibration for use in monitoring the quality of estuarine and coastal waters worldwide.

Moreno-Madrinan, Max Jacobo↗

DOE OSTI2018

Progress on Complex Langevin simulations of a finite density matrix model for QCD

We study the Stephanov model, which is an RMT model for QCD at finite density, using the Complex Langevin algorithm. Naive implementation of the algorithm shows convergence towards the phase quenched or quenched theory rather than to intended theory with dynamical quarks. A detailed analysis of this issue and a potential resolution of the failure of this algorithm are discussed. We study the effect of gauge cooling on the Dirac eigenvalue distribution and time evolution of the norm for various cooling norms, which were specifically designed to remove the pathologies of the complex Langevin evolution. The cooling is further supplemented with a shifted representation for the random matrices. Unfortunately, none of these modifications generate a substantial improvement on the complex Langevin evolution and the final results still do not agree with the analytical predictions.

Bloch, Jacques↗

NASA NTRSDate not supplied

Skin Friction Measurement on a Swept NACA 0015 Wing Using Oil Film Interferometry

An application of oil film interferometry (OFI) to measure skin friction on the 3D flow over an NACA 0015 airfoil with 30° of sweep is presented. Local flow direction must be known to apply OFI to complex 3D flows such as this. A recently developed surface flow vector extraction method was integrated into the OFI analysis algorithm. Surface flow vectors were used to calculate the surface streamlines and hence provided local flow direction to the OFI analysis. After calibration using photogrammetry, the surface flow vectors also enabled decomposition of the skin friction coefficient into different components (such as chordwise and spanwise). The presented method successfully measured skin friction at locations with different flow characteristics such as high skin friction regions, strong spanwise flow regions, and 3D flow separated regions. In the current OFI analysis, multiple interferogram images acquired at different times were analyzed for the same location. The multiple interferogram analysis enabled averaging, which reduced the scatter the skin friction data. The results presented herein demonstrate the capability of the current approach, thereby extending OFI skin friction measurements to complex 3D flows.

Skin friction measurement↗

NASA NTRSDate not supplied

Skin Friction Measurement on a Swept NACA 0015 Wing Using Oil Film Interferometry

Skin friction measurement↗

DOE OSTI2025

Spectral Clustering-Based Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. Here, this paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.

Nupur [Univ. of Tennessee, Knoxville, TN (United S↗

NASA NTRS1998

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Newman, Perry A.↗

NASA NTRS2005

BEAM Technology Flight Demonstration

As technologies advance, their growing complexity makes them harder to maintain. Detection methods for isolating and identifying impending problems are needed to balance this complexity. Through comparison of signal pairs from onboard sensors, the Beacon-based Exception Analysis For Multimissions (BEAM) algorithm can identify and help classify deviations in system operation from a data-trained statistical model. The goal of this task is to mature BEAM and validate its performance on a flying test bed. A series of F-18 flight demonstrations with BEAM monitoring engine parameters in real time was used to demonstrate in-the-field readiness. Captured F-18 and simulated F-18 engine data were used in model creation and training. The algorithm was then ported to the embedded system with a data buffering, file writing, and data-time-stamp monitoring shell to reduce the impact of embedded system faults on BEAM'S ability to correctly identify engine faults. Embedded system testing identified hardware related restrictions and contributed to iterative improvements in the code's runtime performance. The system was flown with forced engine flameouts and other pilot induced faults to simulate operation out of the norm. Successful detection of these faults, confirmed through post-flight data analysis, helped BEAM achieve TRL6.

Wang, David↗

DOE OSTI2020

Topology optimization of multiple deformable bodies in contact with large deformations

Previous works in topology optimization of structures with contact boundary conditions have concentrated on the two-dimensional rigid obstacle problem. This is because the contact analysis of multiple three-dimensional deformable bodies with meshes that are non-matching across the contact interface requires computationally complex contact algorithms beyond the scope of previous optimization investigations. Here, our research is devoted to addressing topology design problems with multiple deformable three-dimensional components in contact using state-of-the-art contact algorithms.

42 ENGINEERING↗

DOE OSTI2024

Random coordinate descent: A simple alternative for optimizing parameterized quantum circuits

Variational quantum algorithms rely on the optimization of parameterized quantum circuits in noisy settings. The commonly used back-propagation procedure in classical machine learning is not directly applicable in this setting due to the collapse of quantum states after measurements. Thus, gradient estimations constitute a significant overhead in a gradient-based optimization of such quantum circuits. This paper introduces a random coordinate descent algorithm as a practical and easy-to-implement alternative to the full gradient descent algorithm. This algorithm only requires one partial derivative at each iteration. Motivated by the behavior of measurement noise in the practical optimization of parameterized quantum circuits, this paper presents an optimization problem setting that is amenable to analysis. Under this setting, the random coordinate descent algorithm exhibits the same level of stochastic stability as the full gradient approach, making it as resilient to noise. The complexity of the random coordinate descent method is generally no worse than that of the gradient descent and can be much better for various quantum optimization problems with anisotropic Lipschitz constants. Theoretical analysis and extensive numerical experiments validate our findings. Published by the American Physical Society 2024

Ding, Zhiyan (ORCID:000000018863403X)↗

NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be owing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗

NASA NTRS2022

Compositional Measurements of Saturn's Upper Atmosphere and Rings From Cassini INMS: An Extended Analysis of Measurements From Cassini's Grand Finale Orbits

The Cassini spacecraft's final orbits sampled Saturn's atmosphere and returned surprisingly complex mass spectra from the Ion and Neutral Mass Spectrometer (INMS). Signal returned from the instrument included native Saturn species, as expected, as well as a significant amount of signal attributed to vaporized ices and higher mass organics believed to be flowing into Saturn's atmosphere from the rings. In this paper, we present an in-depth compositional analysis of the mass spectra returned from Cassini's last few orbits. We use a mass spectral deconvolution algorithm designed specifically to handle the complexities involved with unit resolution spaceflight mass spectrometry data to determine the relative abundance of species detected in the observations. We calculate the downward external flux and mass deposition rates of ring volatile species into Saturn's atmosphere and conclude that during these observations ring material was being deposited into Saturn's equatorial region at a rate on the order of 10(exp 4) kg/s.

Saturn↗

DOE OSTI2021

Probabilistic Deep Learning Approach to Automate the Interpretation of Multi-phase Diffraction Spectra

Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase mixtures. At the core of this algorithm lies an ensemble convolutional neural network trained on simulated diffraction spectra, which are systematically augmented with physics-informed perturbations to account for artifacts that can arise during experimental sample preparation and synthesis. In this work, larger perturbations associated with off-stoichiometry are also captured by supplementing the training set with hypothetical solid solutions. Spectra containing mixtures of materials are analyzed with a newly developed branching algorithm that utilizes the probabilistic nature of the neural network to explore suspected mixtures and identify the set of phases that maximize confidence in the prediction. Our model is benchmarked on simulated and experimentally measured diffraction spectra, showing exceptional performance with accuracies exceeding those given by previously reported methods based on profile matching and deep learning. We envision that the algorithm presented here may be integrated in experimental workflows to facilitate the high-throughput and autonomous discovery of inorganic materials.

36 MATERIALS SCIENCE↗

NASA NTRS1986

A new approach to the solution of boundary value problems involving complex configurations

A new approach for solving certain types of boundary value problems about complex configurations is presented. Numerical algorithms from such diverse fields as finite elements, preconditioned Krylov subspace methods, discrete Fourier analysis, and integral equations are combined to take advantage of the memory, speed and architecture of current and emerging supercomputers. Although the approach has application to many branches of computational physics, the present effort is concentrated in areas of Computational Fluid Dynamics (CFD) such as steady nonlinear aerodynamics, time harmonic unsteady aerodynamics, and aeroacoustics. The most significant attribute of the approach is that it can handle truly arbitrary boundary geometries and eliminates the difficult task of generating surface fitted grids.

Rubbert, P. E.↗

NASA NTRS2000

Stratospheric Temperature Trends from Small Rockets Between 1969-1995

Between 1958-1995 a significant number of small meteorological rocketsondes were launched by United States (US) agencies from as many as 30 sites to as few as 3-4 sites in 1995. Stratospheric temperature trends were derived for many of the sites for the period 1969-1995. Similar long-term trends also were derived using rocketsondes launched from sites of the Former Soviet Union (FSU). The advantage of these two particular sets of rocket temperature measurements is the internal consistency of the data. All measurements were made with the same instrument, i.e., Datasonde in the case of the US sites and the M100B in the case of the FSU sites. Data from each instrument type were processed using its unique reduction method. Thus, all data were processed in the same manner including the method of applying corrections (necessary because of thermal heating of the thermistor from the high fall velocities experienced and from radiation effects). Straight-line least squares fit to the data made to monthly-mean measurements gave a downward change of 2-3 K per decade. A more complex fitting algorithm would have resulted in finer results but the straight-line fit was adequate for the analysis presented. Trend data are presented for 50 km, 40 km, and 25 km altitude levels. Trends for the US and FSU sites are quite similar. The 25km (50-hPa) level data are compared with radiosonde temperatures. Temperature trends over the 25-year period is different at each of the sites and not always in the same direction.

Schmidlin, F. J.↗

NASA NTRS2012

A Standard Platform for Testing and Comparison of MDAO Architectures

The Multidisciplinary Design Analysis and Optimization (MDAO) community has developed a multitude of algorithms and techniques, called architectures, for performing optimizations on complex engineering systems which involve coupling between multiple discipline analyses. These architectures seek to efficiently handle optimizations with computationally expensive analyses including multiple disciplines. We propose a new testing procedure that can provide a quantitative and qualitative means of comparison among architectures. The proposed test procedure is implemented within the open source framework, OpenMDAO, and comparative results are presented for five well-known architectures: MDF, IDF, CO, BLISS, and BLISS-2000. We also demonstrate how using open source soft- ware development methods can allow the MDAO community to submit new problems and architectures to keep the test suite relevant.

Gray, Justin S.↗