Search NASA⌕ Search

SEARCH · Search NASA

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.

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

At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Determining Biosignatures by Complexity Analysis in Antarctic Cryptoendolithic Communities

One of the most difficult problems of life detection is that of identifying biosignatures across a wide range of scales using multiple co-registered probes. The technique should be of equal utility across a wide range of search spaces from remote sensors probing volumes of space or planetary surfaces, visual eye or camera searches across the surface of a rock in Antarctica, low resolution microscopic scanning of a rock or a space craft in situ, or high resolution electron microscope and computerized tomography scanning of geobiological samples. We describe here an approach to this problem which derives in large part from past work done in the area of astrophysics - namely the analysis of complexity in galactic signals by data compression methods. This approach is a radically new one for geobiology and astrobiology, and allows us to assess the complexity (and thus potential biogenicity) of an object being examined. This is done by considering the information within pixels of an image (regardless the sensor used to gather the information) as an energetic system capable of description in terms of classical thermodynamics. The image data space is searched by an algorithm that judges complexity via data compression (e.g., the more compressible it is, the less complex, and vice versa) and maximum entropy as originally outlined by Shannon. At present we are implementing methods to utilize images from multiple sensors gathering different kinds of information (e.g., visible gray-scale data, color analyses, UV fluorescence, chemical information, etc). We present here preliminary data from deep UV fluorescence and ESEM (Environmental Scanning Electron Microscope) images from a layered cryptoendolithic community of an Antarctic rock.

Storrie-Lombardi, M. C.↗
NASA NTRS2020

On the Use of Complexity Algorithms: a Cautionary Lesson from Climate Research

Complexity algorithms provide information about datasets which is radically different from classical moment statistics. Instead of focusing on the divergences from central values, they quantify other characteristics such as order, pattern repetitions, or the existence of attractors. However, those analyses must be done with the proper statistical treatment, which is, unfortunately, not always the case. In this contribution, I provide an example of the hazards of applying complexity measures without sufficient care by correcting a previously published analysis that aimed to quantify the complexity of climate. I clarify some misconceptions about the use of Sample Entropy and revise the incorrect assessments and conclusions drawn from the previous misapplication of the methods.

Delgado-Bonal, Alfonso↗
DOE OSTI2018

Variance Estimation in Monte Carlo Eigenvalue Simulations Using Spectral Analysis Method

Monte Carlo (MC) simulation is widely used to solve the eigenvalue form of the Boltzmann transport equation that mathematically represents the neutron transport process through complex multiplying (fissionable) systems. Monte Carlo eigenvalue simulation starts with an assumed fission source distribution and uses the fission sites from the previous iteration (cycle) as the starting source in the current iteration. Important system parameters (MC tallies) such as fuel pin-power distribution are estimated over several cycles after the convergence of the fission source distribution to a stationary distribution. However, the MC fission source iteration algorithm that uses fission source sites from the previous cycle introduces a cycle-to-cycle correlation. Monte Carlo simulations that do not account for the cycle-to-cycle correlation systematically underestimate the variance of the estimated system parameters (sample mean). This paper presents the relationship between the spectral density in the frequency domain at frequency zero and the variance of the sample mean. This paper introduces a novel method in the frequency domain for the MC variance estimation. For the three test problems used in this paper, researchers have observed that the new method results in an improvement of more than one order of magnitude to the standard deviation of the sample mean. The new method also compares favorably with the previously introduced batch, bootstrap, and covariance-adjusted methods when applied to the three test problems investigated in this paper. This new method does not require modification of the MC eigenvalue algorithm (power iteration), is code agnostic, and is therefore easy to use when implementing in any existing MC code. In conclusion, the new estimate can be calculated without saving tally results of all active/stationary cycles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Theory of Trotter Error with Commutator Scaling

The Lie-Trotter formula, together with its higher-order generalizations, provides a simple approach to decomposing the exponential of a sum of operators. Despite significant effort, the error scaling of such product formulas remains poorly understood. We develop a theory of Trotter error that overcomes the limitations of truncating the Baker-Campbell-Hausdorff expansion. Our analysis directly exploits the commutativity of operator summands, producing tighter error bounds for both real- and imaginary-time evolutions. Whereas previous work achieves similar goals for systems with geometric locality or Lie-algebraic structure, our approach holds in general. We give a host of improved algorithms for digital quantum simulation and quantum Monte Carlo methods, nearly matching or even outperforming the best previous results. Our applications include: (i) a simulation of second-quantized plane-wave electronic structure, nearly matching the interaction-picture algorithm of Low and Wiebe; (ii) a simulation of $k$-local Hamiltonians almost with induced one-norm scaling, faster than the qubitization algorithm of Low and Chuang; (iii) a simulation of rapidly decaying power-law interactions, outperforming the Lieb-Robinson-based approach of Tran et al.; (iv) a hybrid simulation of clustered Hamiltonians, dramatically improving the result of Peng, Harrow, Ozols, and Wu; and (v) quantum Monte Carlo simulations of the transverse field Ising model and quantum ferromagnets, tightening previous analyses of Bravyi and Gosset. We obtain further speedups using the fact that product formulas can preserve the locality of the simulated system. Specifically, we show that local observables can be simulated with complexity independent of the system size for power-law interacting systems, which implies a Lieb-Robinson bound nearly matching a recent result of Tran et al. Our analysis reproduces known tight bounds for first- and second-order formulas. We further investigate the tightness of our bounds for higher-order formulas. For quantum simulation of a one-dimensional Heisenberg model with an even-odd ordering of terms, our result overestimates the complexity by only a factor of $5$. Our bound is also close to tight for power-law interactions and other orderings of terms. This suggests that our theory can accurately characterize Trotter error in terms of both the asymptotic scaling and the constant prefactor.

quantum computing, numerical analysis↗
DOE OSTI2024

An open source knowledge graph ecosystem for the life sciences

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1987

Expert systems for space power supply - Design, analysis, and evaluation

The feasibility of applying expert systems to the conceptual design, analysis, and evaluation of space power supplies in particular, and complex systems in general is evaluated. To do this, the space power supply design process and its associated knowledge base were analyzed and characterized in a form suitable for computer emulation of a human expert. The existing expert system tools and the results achieved with them were evaluated to assess their applicability to power system design. Some new concepts for combining program architectures (modular expert systems and algorithms) with information about the domain were applied to create a 'deep' system for handling the complex design problem. NOVICE, a code to solve a simplified version of a scoping study of a wide variety of power supply types for a broad range of missions, has been developed, programmed, and tested as a concrete feasibility demonstration.

Cooper, Ralph S.↗
NASA NTRS2011

Improving Distributed Diagnosis Through Structural Model Decomposition

Complex engineering systems require efficient fault diagnosis methodologies, but centralized approaches do not scale well, and this motivates the development of distributed solutions. This work presents an event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, by using the structural model decomposition capabilities provided by Possible Conflicts. We develop a distributed diagnosis algorithm that uses residuals computed by extending Possible Conflicts to build local event-based diagnosers based on global diagnosability analysis. The proposed approach is applied to a multitank system, and results demonstrate an improvement in the design of local diagnosers. Since local diagnosers use only a subset of the residuals, and use subsystem models to compute residuals (instead of the global system model), the local diagnosers are more efficient than previously developed distributed approaches.

Bregon, Anibal↗
NASA NTRS2024

Revolutionary Vertical Lift Technology Lift + Cruise Concept Vehicle Powertrain Dynamic Model

The Lift + Cruise (L+C) is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This six-passenger vehicle has a conventional tube-and-wing configuration, but with eight lift rotors (four on each wing) and a pusher rotor on the tail. This arrangement allows it to take off and land vertically as well as fly like an airplane. This report presents a novel dynamic model of the L+C powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT), both of which are NASA-developed toolboxes, and together are capable of modeling hybrid-electric powertrain architectures. This research effort models the complex behavior of the powertrain at the mechanical timescale (15 to 20 ms). The model consists of a turboshaft engine, generator, direct current bus, energy storage management system, gearboxes, and electric propulsor systems coupled together to create a dynamic model that mimics the operation of the multidomain powertrain. Two control algorithms, designed to equalize the power consumed to the power produced, are compared to assess their practicality: (1) independent proportional-integral (PI) control and (2) linear quadratic integral regulator (LQIR) control. Simulation results highlight the key features present in the model and demonstrate its operation under the two control schemes.

revolutionary vertical lift technology↗
DOE OSTI2020

OPTIMAL CONTROL AND ENERGY-SAVING ANALYSIS OF COMMON PRESSURE RAIL ARCHITECTURES: HHEA & STEAM

In recent years several novel hydraulic architectures have been proposed with the intention of significantly increasing system efficiency. Two of these architectures, Steigerung der Energieeffizienz in der Arbeitshydraulik mobiler Arbeitsmaschinen (STEAM), and the Hybrid Hydraulic-Electric Architecture (HHEA), use a system of multiple common pressure rails (CPRs) to serve the multiple degrees-of-freedom of the machine. The key difference is that STEAM throttles hydraulic power from these rails while HHEA combines electric and hydraulic power to meet actuator demands. As a throttle-less architecture, HHEA is expected to save more energy than STEAM at the expense of added complexity. Therefore, it is useful to quantify this additional energy saving. Both systems have discrete operational choices corresponding to how the CPRs are utilized for each actuator. It is necessary to determine optimal operation for each of these architectures for analysis and fair comparison. Techniques for optimal operation of the HHEA have been developed previously from the Langrange multiplier method. Applying the same optimal control method to STEAM encountered some technical challenge leading to the optimal control algorithm not being able to satisfy certain constraints. The issue is analyzed and solved by adding noise to the optimization. Using this proposed algorithm, case studies are performed to compare the energy-saving potentials of STEAM and HHEA for two sizes of excavators and a wheel-loader performing representative duty cycles. The baseline is a standard load-sensing architecture. Results show that STEAM and HHEA can reduce energy consumption between 35-65% and 50-80% respectively

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Application of MAC-Europe AVIRIS data to the analysis of various alteration stages in the Landdmannalauger Hydrothermal Area (South Iceland)

In June 1991 extensive airborne remote sensing data-sets have been acquired over Iceland in the framework of the joint NASA/ESA Multisensor Airborne Campaign Europe (MAC-Europe). The study area is located within the Torfajokull central volcanic complex in South Iceland. This complex is composed by anomalously abundant rhyolitic acid volcanics, which underwent intensive hydrothermal alteration. Detailed studies of surface alteration of rhyolitic rocks in the area showed that all the major elements are leached as the rock is affected by complex mineralogical changes. Montmorillonite appears during the earliest stages of alteration. In the ultimate alteration product montmorillonite is absent and the rock consists mostly of amorphous silica, anatase, up to a volume of 50% kaolinite and variable amounts of native sulphur and pyrite. The case study presented shall endeavor to assess the potential of MAC-Europe AVIRIS and TMS data in determining a possible zonation of hydrothermal alteration in relationship to the active geo-thermal fields and structural features. To this end, the airborne data is analysed in comparison with laboratory spectral measurements of characteristics rock, soil, and vegetation samples collected in the study areaduring the summer of 1992. Various spectral mapping algorithms as well as unmixing approaches are tested and evaluated. Detailed geological and structural mapping as well as geochemical analysis of the main rock and soil types were performed to underpin the analysis of the airborne data.

Sommer, S.↗
DOE OSTI2018

Gradient-based optimization for regression in the functional tensor-train format

Predictive analysis of complex computational models, such as uncertainty quantification (UQ), must often rely on using an existing database of simulation runs. In this paper we consider the task of performing low-multilinear-rank regression on such a database. Specifically we develop and analyze an efficient gradient computation that enables gradient-based optimization procedures, including stochastic gradient descent and quasi-Newton methods, for learning the parameters of a functional tensor-train (FT). We compare our algorithms with 22 other nonparametric and parametric regression methods on 10 real-world data sets and show that for many physical systems, exploiting low-rank structure facilitates efficient construction of surrogate models. Here, we use a number of synthetic functions to build insight into behavior of our algorithms, including the rank adaptation and group-sparsity regularization procedures that we developed to reduce overfitting. Finally we conclude the paper by building a surrogate of a physical model of a propulsion plant on a naval vessel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Automated Hybrid Variance Reduction on Advanced Architectures in the Shift Monte Carlo Code

Monte Carlo transport methods are the most accurate schemes for solving problems with complex energy and spatial features, but they come with a high computational cost. Although hybrid methods have enabled the use of Monte Carlo transport for a large class of problems, they still require significant computing resources. Modern multicore CPUs with large numbers of compute cores and graphical processing units (GPUs) provide opportunities to optimize the memory and run-time costs of hybrid Monte Carlo methods. This paper documents the development and analysis of three Monte Carlo transport algorithms that support hybrid transport using the consistent adjoint-driven importance sampling (CADIS) and forward-weighted CADIS methods in the Shift Monte Carlo code: history-based transport using static and dynamic threading on multicore CPUs and event-based transport enabling weight window tracking on GPUs. The results are shown for two challenging hybrid problems on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. The results show that all three methods yield good performance and enable solutions of difficult fixed-source transport problems in less than 2 min on 20 nodes of Frontier. Dynamic threading was observed to give up to 20% better scaling behavior than static threading. Moreover, the AMD Instinct 250X GPU was found to give 9 to 11 times greater throughput per graphics compute die than the best CPU performance. In conclusion, additional opportunities for optimization of hybrid transport on GPUs are discussed.

Denovo↗
DOE OSTI2020

Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost

Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.

Li, Sibo (ORCID:000000021705844X)↗
NASA NTRS1991

Parallel computation of manipulator inverse dynamics

In this article, parallel computation of manipulator inverse dynamics is investigated. A hierarchical graph-based mapping approach is devised to analyze the inherent parallelism in the Newton-Euler formulation at several computational levels, and to derive the features of an abstract architecture for exploitation of parallelism. At each level, a parallel algorithm represents the application of a parallel model of computation that transforms the computation into a graph whose structure defines the features of an abstract architecture, i.e., number of processors, communication structure, etc. Data-flow analysis is employed to derive the time lower bound in the computation as well as the sequencing of the abstract architecture. The features of the target architecture are defined by optimization of the abstract architecture to exploit maximum parallelism while minimizing architectural complexity. An architecture is designed and implemented that is capable of efficient exploitation of parallelism at several computational levels. The computation time of the Newton-Euler formulation for a 6-degree-of-freedom (dof) general manipulator is measured as 187 microsec. The increase in computation time for each additional dof is 23 microsec, which leads to a computation time of less than 500 microsec, even for a 12-dof redundant arm.

Fijany, Amir↗
NASA NTRS1992

Frequency effects on the stability of a journal bearing for periodic loading

The stability of a journal bearing is numerically predicted when an unidirectional periodic external load is applied. The analysis is performed using a cavitation algorithm, which mimics the JFO theory by accounting for the mass balance through the complete bearing. Hence, the history of the film is taken into consideration. The loading pattern is taken to be sinusoidal and the frequency of the load cycle is varied. The results are compared with the predictions using Reynolds boundary conditions for both film rupture and reformation. With such comparisons, the need for accurately predicting the cavitation regions for complex loading patterns is clearly demonstrated. For a particular frequency of loading, the effects of mass, amplitude of load vibration and frequency of journal speed are also investigated.

Vijayaraghavan, D.↗
NASA NTRS1993

A comparison of refined models for flexible subassemblies

Interactions between structure response and control of large flexible space systems have challenged current modeling techniques and have prompted development of new techniques for model improvement. Due to the geometric complexity of envisioned large flexible space structures, finite element models (FEM's) will be used to predict the dynamic characteristics of structural components. It is widely accepted that these models must be experimentally 'validated' before their acceptance as the basis for final design analysis. However, predictions of modal properties (natural frequencies, mode shapes, and damping ratios) are often in error when compared to those obtained from Experimental Modal Analysis (EMA). Recent research efforts have resulted in the development of algorithmic approaches for model improvement, also referred to as system or structure identification.

Smith, Suzanne Weaver↗
NASA NTRS2001

Comparison of Modal Analysis Methods Applied to a Vibro-Acoustic Test Article

Modal testing of a vibro-acoustic test article referred to as the Aluminum Testbed Cylinder (ATC) has provided frequency response data for the development of validated numerical models of complex structures for interior noise prediction and control. The ATC is an all aluminum, ring and stringer stiffened cylinder, 12 feet in length and 4 feet in diameter. The cylinder was designed to represent typical aircraft construction. Modal tests were conducted for several different configurations of the cylinder assembly under ambient and pressurized conditions. The purpose of this paper is to present results from dynamic testing of different ATC configurations using two modal analysis software methods: Eigensystem Realization Algorithm (ERA) and MTS IDEAS Polyreference method. The paper compares results from the two analysis methods as well as the results from various test configurations. The effects of pressurization on the modal characteristics are discussed.

Pritchard, Jocelyn↗
NASA NTRS2011

Progress Toward Future Runway Management

The runway is universally acknowledged as a constraining factor to capacity in the National Airspace System (NAS). It follows that investigation of the effective use of runways, both in terms of selection and assignment, is paramount to the efficiency of future NAS operations. The need to address runway management is not a new idea; however, as the complexities of factors affecting runway selection and usage increase, the need for effective research in this area correspondingly increases. Under the National Aeronautics and Space Administration s Airspace Systems Program, runway management is a key research area. To address a future NAS which promises to be a complex landscape of factors and competing interests among users and operators, effective runway management strategies and capabilities are required. This effort has evolved from an assessment of current practices, an understanding of research activities addressing surface and airspace operations, traffic flow management enhancements, among others. This work has yielded significant progress. Systems analysis work indicates that the value of System Oriented Runway Management tools is significantly increased in the metroplex environment over that of the single airport case. Algorithms have been developed to provide runway configuration recommendations for a single airport with multiple runways. A benefits analysis has been conducted that indicates the SORM benefits include supporting traffic growth, cost reduction as a result of system efficiency, NAS optimization from metroplex operations, fairness in aircraft operations, and rational decision making.

Lohr, Gary W.↗