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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.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Hierarchical modeling for reliability analysis using Markov models

Markov models represent an extremely attractive tool for the reliability analysis of many systems. However, Markov model state space grows exponentially with the number of components in a given system. Thus, for very large systems Markov modeling techniques alone become intractable in both memory and CPU time. Often a particular subsystem can be found within some larger system where the dependence of the larger system on the subsystem is of a particularly simple form. This simple dependence can be used to decompose such a system into one or more subsystems. A hierarchical technique is presented which can be used to evaluate these subsystems in such a way that their reliabilities can be combined to obtain the reliability for the full system. This hierarchical approach is unique in that it allows the subsystem model to pass multiple aggregate state information to the higher level model, allowing more general systems to be evaluated. Guidelines are developed to assist in the system decomposition. An appropriate method for determining subsystem reliability is also developed. This method gives rise to some interesting numerical issues. Numerical error due to roundoff and integration are discussed at length. Once a decomposition is chosen, the remaining analysis is straightforward but tedious. However, an approach is developed for simplifying the recombination of subsystem reliabilities. Finally, a real world system is used to illustrate the use of this technique in a more practical context.

Fagundo, Arturo↗
NASA NTRS1995

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

Bradshaw, G. A.↗
NASA NTRS1995

Testing higher-order Lagrangian perturbation theory against numerical simulations. 2: Hierarchical models

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of scales. The Lagrangian theory of gravitational instability of Friedmann-Lemaitre cosmogonies is compared with numerical simulations. We study the dynamics of hierarchical models as a second step. In the first step we analyzed the performance of the Lagrangian schemes for pancake models, the difference being that in the latter models the initial power spectrum is truncated. This work probed the quasi-linear and weakly non-linear regimes. We here explore whether the results found for pancake models carry over to hierarchical models which are evolved deeply into the non-linear regime. We smooth the initial data by using a variety of filter types and filter scales in order to determine the optimal performance of the analytical models, as has been done for the 'Zel'dovich-approximation' - hereafter TZA - in previous work. We find that for spectra with negative power-index the second-order scheme performs considerably better than TZA in terms of statistics which probe the dynamics, and slightly better in terms of low-order statistics like the power-spectrum. However, in contrast to the results found for pancake models, where the higher-order schemes get worse than TZA at late non-linear stages and on small scales, we here find that the second-order model is as robust as TZA, retaining the improvement at later stages and on smaller scales. In view of these results we expect that the second-order truncated Lagrangian model is especially useful for the modelling of standard dark matter models such as Hot-, Cold-, and Mixed-Dark-Matter.

Melott, A. L.↗
NASA NTRS1997

Hierarchical Parallelism in Finite Difference Analysis of Heat Conduction

Based on the concept of hierarchical parallelism, this research effort resulted in highly efficient parallel solution strategies for very large scale heat conduction problems. Overall, the method of hierarchical parallelism involves the partitioning of thermal models into several substructured levels wherein an optimal balance into various associated bandwidths is achieved. The details are described in this report. Overall, the report is organized into two parts. Part 1 describes the parallel modelling methodology and associated multilevel direct, iterative and mixed solution schemes. Part 2 establishes both the formal and computational properties of the scheme.

Padovan, Joseph↗
NASA NTRS1992

Multicast Routing of Hierarchical Data

The issue of multicast of broadband, real-time data in a heterogeneous environment, in which the data recipients differ in their reception abilities, is considered. Traditional multicast schemes, which are designed to deliver all the source data to all recipients, offer limited performance in such an environment, since they must either force the source to overcompress its signal or restrict the destination population to those who can receive the full signal. We present an approach for resolving this issue by combining hierarchical source coding techniques, which allow recipients to trade off reception bandwidth for signal quality, and sophisticated routing algorithms that deliver to each destination the maximum possible signal quality. The field of hierarchical coding is briefly surveyed and new multicast routing algorithms are presented. The algorithms are compared in terms of network utilization efficiency, lengths of paths, and the required mechanisms for forwarding packets on the resulting paths.

Shacham, Nachum↗
NASA NTRS1999

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗
NASA NTRS1999

Hierarchical Approach to 'Atomistic' 3-D MOSFET Simulation

We present a hierarchical approach to the 'atomistic' simulation of aggressively scaled sub-0.1 micron MOSFET's. These devices are so small that their characteristics depend on the precise location of dopant atoms within them, not just on their average density. A full-scale three-dimensional drift-diffusion atomistic simulation approach is first described and used to verify more economical, but restricted, options. To reduce processor time and memory requirements at high drain voltage, we have developed a self-consistent option based on a solution of the current continuity equation restricted to a thin slab of the channel. This is coupled to the solution of the Poisson equation in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison to the full self-consistent solution. At low drain voltage, a single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. In this case, the current is calculated by solving the current continuity equation in a drift approximation only, also in a thin slab containing the MOSFET channel. The regions of applicability for the different components of this hierarchical approach are illustrated in example simulations covering the random dopant-induced threshold voltage fluctuations, threshold voltage lowering, threshold voltage asymmetry, and drain current fluctuations.

Asenov, Asen↗
NASA NTRS1998

Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree

Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. this paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called Temporal Hierarchical Index Tree, which utilizes the temporal coherence that exists in a time-varying field and adoptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CID simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.

Shen, Han-Wei↗
NASA NTRS1995

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Menasce, Daniel A.↗
NASA NTRS2004

Hierarchical Discrete Event Supervisory Control of Aircraft Propulsion Systems

This paper presents a hierarchical application of Discrete Event Supervisory (DES) control theory for intelligent decision and control of a twin-engine aircraft propulsion system. A dual layer hierarchical DES controller is designed to supervise and coordinate the operation of two engines of the propulsion system. The two engines are individually controlled to achieve enhanced performance and reliability, necessary for fulfilling the mission objectives. Each engine is operated under a continuously varying control system that maintains the specified performance and a local discrete-event supervisor for condition monitoring and life extending control. A global upper level DES controller is designed for load balancing and overall health management of the propulsion system.

Yasar, Murat↗
NASA NTRS2006

Improvement in Recursive Hierarchical Segmentation of Data

A further modification has been made in the algorithm and implementing software reported in Modified Recursive Hierarchical Segmentation of Data (GSC- 14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The output of a prior version of the software contained artifacts, including spurious segmentation-image regions bounded by processing-window edges. The modification for suppressing the artifacts, mentioned in the cited article, was addition of a subroutine that analyzes data in the vicinities of seams to find pairs of regions that tend to lie adjacent to each other on opposite sides of the seams. Within each such pair, pixels in one region that are more similar to pixels in the other region are reassigned to the other region. The present modification provides for a parameter ranging from 0 to 1 for controlling the relative priority of merges between spatially adjacent and spatially non-adjacent regions. At 1, spatially-adjacent-/spatially- non-adjacent-region merges have equal priority. At 0, only spatially-adjacent-region merges (no spectral clustering) are allowed. Between 0 and 1, spatially-adjacent- region merges have priority over spatially- non-adjacent ones.

Tilton, James C.↗
NASA NTRS2006

Using Heaps in Recursive Hierarchical Segmentation of Data

A modification to increase processing speed has been made in the algorithm and implementing software reported in Modified Recursive Hierarchical Segmentation of Data (GSC-14681-1), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 51. That software performs recursive hierarchical segmentation of data having spatial characteristics (e.g., spectral-image data). The segmentation process includes an iterative subprocess, in each iteration of which it is necessary to determine a best pair of regions to merge [merges being justified by one or more measure(s) similarity of pixels in the regions]. In the previously reported version of the algorithm and software, the choice of a best pair of regions to merge involved the use of a fully sorted list of regions. That version was computationally inefficient because a fully sorted list is not needed: what is needed is only the identity of the pair of regions characterized by the smallest measure of dissimilarity. The present modification replaces the use of a fully sorted list with the use of data heaps, which are computationally more efficient for performing the required comparisons among dissimilarity measures. The modification includes the incorporation of standard and modified functions for creating and updating data heaps

Tilton, James C.↗
NASA NTRS2011

Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

Choi, Sang Hyouk↗
NASA NTRS2012

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗
NASA NTRS2019

A Distributed Hierarchical Framework for Autonomous Spacecraft Control

Future human space missions for exploring beyond low Earth orbit are in the conceptual design stage. One such mission describes a habitat in cis-lunar orbit that is visited by crew periodically, others describe missions to Mars. These missions have one important thing in common: the need for autonomy on the spacecraft. This need stems from the latency and bandwidth constraints on communications between the vehicle and ground control. A variable amount of autonomy may be necessary whether the spacecraft has crew on board or not. Spacecraft are complex systems that are engineered as a collection of subsystems. These subsystems work together to control the overall state of the spacecraft. As such, solutions that increase the autonomy of the spacecraft (called autonomous functions) should respect both the independence and interconnectedness of the spacecraft subsystems. This distributed and hierarchical approach to system monitoring and control is a key idea in the Modular Autonomous Systems Technology (MAST) framework. The MAST framework enables a component-based architecture that provides interfaces and structure to developing autonomous technologies. The framework enforces a distributed, hierarchical architecture for autonomous control systems across subsystems, systems, elements, and vehicles. An example autonomous system was implemented in this framework and tested using realistic spacecraft software and hardware simulations. This paper will discuss the framework, tests conducted, results, and future work.

Badger, Julia M.↗
NASA NTRSDate not supplied

Hierarchical Control of Distributed Battery Energy Storage System in a DC Microgrid

This paper presents a novel hierarchical control approach of a DC microgrid (DCMG) which is supplied by a distributed battery energy storage system (BESS). With this approach, all battery units distributed in the BESS can be controlled to discharge with accurate current sharing and state-of-charge (SoC) balancing. Similar to other hierarchical control approaches used in DCMGs, this approach consists of three levels: (1) primary control, (2) secondary control and (3) tertiary control. This work includes defining a unit control error (UCE) at the secondary control level and evaluating current sharing weights at tertiary control level. A centralized controller at secondary control level is designed to detect the UCEs of each battery unit, and to restore the average voltage of a DCMG and control battery current sharing simultaneously. The distributed battery units share the load current in a DCMG based on weights. These weights are evaluated at the tertiary control level based on battery SoCs. The approach’s effectiveness was confirmed in digital simulation tests with the same simulation model as used in the NASA AMPS Modular Hardware Emulator.

Jing Zhang↗
NASA NTRS2020

A Novel Parsing-based Approach for Verification of Hierarchical Plans

Hierarchical Task Networks were proposed as amethod to describe plans by decomposition of tasks to subtasksuntil primitive tasks, actions, are obtained. Valid plans –sequences of actions – must adhere both to causal dependenciesbetween the actions and to the structure given by the decompositionof the goal task. Plan verification aims at finding if a givenplan is valid, that is, if it is causally consistent and it can beobtained by decomposition of some task. The paper describes anovel parsing-based approach for hierarchical plan verificationthat is orders of magnitude faster than existing methods.

Bercher, Pascal↗
NASA NTRSDate not supplied

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗