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Results for “state decomposition”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Decomposition and state variable feedback control of elastic robotic systems

Energy-efficient, lightweight robot arms for space applications have considerable structural flexibility. An approach to control of a class of flexible robotic systems is presented. A control law is derived which decouples the joint-angle motion from the flexible motion and, in addition, asymptotically decomposes the elastic dynamics into two subsystems. This allows the design of an elastic mode stabilizer independently based on lower order models representing structural flexibility. The closed-loop system is shown to be globally asymptotically stable and robust to uncertaintly in system parameters. Simulation results show that the combination of nonlinear decoupling and elastic stabilization permits rapid, accurate tracking of large joint angle commands with well damped elastic response, in spite of space vehicle motion and payload uncertainty.

Singh, S. N.↗
DOE OSTI2023

Privacy-Preserving Robust Consensus for Distributed Microgrid Control Applications

Consensus-based distributed control has been proposed for coordinating distributed energy resources (DERs) in microgrids (MGs). As one key component, distributed average observers are used to estimate the average of a group of reference signals (e.g., voltage, current, or power). State-of-the-art distributed average observers could lead to loss of privacy due to information exchange on the communication channels. The DERs' reference signals, which contain private information, could be inferred by an eavesdropper. In this article, a privacy-preserving distributed average observer is proposed that is based on robust consensus and uses the state decomposition method to preserve privacy. Compared to the existing methods, the proposed observer does not require the knowledge of the reference signal's derivative and gives accurate and smooth estimation, and is thus applicable for MG distributed control applications. A detailed analysis regarding the convergence and privacy properties of the proposed observer is presented. Here, the proposed observer is implemented on hardware controllers and validated in the context of distributed MG control applications through hardware-in-the-loop (HIL) tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

On the decomposition of synchronous state mechines using sequence invariant state machines

This paper presents a few techniques for the decomposition of Synchronous State Machines of medium to large sizes into smaller component machines. The methods are based on the nature of the transitions and sequences of states in the machine and on the number and variety of inputs to the machine. The results of the decomposition, and of using the Sequence Invariant State Machine (SISM) Design Technique for generating the component machines, include great ease and quickness in the design and implementation processes. Furthermore, there is increased flexibility in making modifications to the original design leading to negligible re-design time.

Hebbalalu, K.↗
NASA NTRS2000

Uncertainty Analysis of Decomposing Polyurethane Foam

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Hobbs, Michael L.↗
DOE OSTI2024

Quantum Tensor-Product Decomposition from Choi-State Tomography

The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt or tensor-product decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the operator level are harder to extract in the quantum computational framework because of the exponential nature of sample complexity. Here, we present an algorithm for unbalanced partitions into a small subsystem and a large one (the environment) to compute the tensor-product decomposition of a unitary the effect of which on the small subsystem is captured in classical memory, while the effect on the environment is accessible as a quantum resource. This quantum algorithm may be used to make predictions about operator nonlocality and effective open quantum dynamics on a subsystem, as well as for finding low-rank approximations and low-depth compilations of quantum circuit unitaries. We demonstrate the method and its applications on a time-evolution unitary of an isotropic Heisenberg model in two dimensions. Published by the American Physical Society 2024

Mansuroglu, Refik (ORCID:000000017352513X)↗
NASA NTRS1988

An approach to solving large reliability models

This paper describes a unified approach to the problem of solving large realistic reliability models. The methodology integrates behavioral decomposition, state trunction, and efficient sparse matrix-based numerical methods. The use of fault trees, together with ancillary information regarding dependencies to automatically generate the underlying Markov model state space is proposed. The effectiveness of this approach is illustrated by modeling a state-of-the-art flight control system and a multiprocessor system. Nonexponential distributions for times to failure of components are assumed in the latter example. The modeling tool used for most of this analysis is HARP (the Hybrid Automated Reliability Predictor).

Boyd, Mark A.↗
NASA NTRS2024

The Relationship Between Volatile Element Abundances and Iron Carrying Capacity in Lunar Volcanic and Impact Vapors

The highly volatile elements (e.g. H, C, S, Cl) released during lunar volcanism provide important insights into the bulk volatile composition of the Moon. Once erupted, some fraction of the species containing these elements may have migrated to the poles where they could have become sequestered in shadowed cold traps such as those found near the lunar South pole. The volatiles trapped in the lunar South pole are of great interest to the upcoming Artemis missions, which will be operating nearby and could sample some of those materials. Volcanic vapor deposits in the polar regions might also be supplemented by volatiles from other sources both exogenous (i.e. comets) and endogenous (i.e. remobilization of lunar volatiles by impact). Characterizing these endogenous sources is challenging because the highly volatile elements often leave little trace behind in the rocks themselves, which are inherently refractory by nature. Minerals are found on vug, vesicle, or fracture surfaces that have characteristics consistent with phases formed via direct deposition of a vapor, as opposed to crystallization from a liquid or via solid state decomposition. One common vapor-deposited species is metallic Fe, typically observed as subhedral to euhedral crystals found on vug or vesicle walls in mare basalts and on select breccia clast surfaces in regolith soil samples returned from the Moon. A particularly striking example is seen below in Fig. 1, where numerous Fe crystals are deposited onto the wall of a vug in Apollo 17 basalt sample 71036. Euhedral Fe crystals are not very common in Apollo breccia samples, though this may be from the limited number of systematic searches that have been performed. However, when Fe crystals are found, they can occur in extremely high abundance(e.g., sample 15402 which was specifically selected because of its numerous Fe crystals, was found to have a clast with 477 euhedral Fe crystals in a 570 x 570 μm area). What struck us as interesting about this was not only that it takes a large amount of Fe to make these crystal-rich deposits, but also that these crystal-rich deposits are not ubiquitous, and therefore they must be controlled by some aspect of their depositional conditions that varies. Since those conditions are inherently difficult to investigate and are critically interesting, we used thermochemical modeling as a tool to investigate the relationship between vapor-deposited Fe and various intensive and extensive parameters. We assumed that a high abundance of Fe in the vapor is required to form these crystals, thus the mass of Fe in the vapor was used to determine the plausibility of the vapor-deposited, euhedral Fe crystals observed in Apollo samples.

thermodynamics↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗
NASA NTRS1989

A Study of Strong Stability of Distributed Systems

The strong stability of distributed systems is studied and the problem of characterizing strongly stable semigroups of operators associated with distributed systems is addressed. Main emphasis is on contractive systems. Three different approaches to characterization of strongly stable contractive semigroups are developed. The first one is an operator theoretical approach. Using the theory of dilations, it is shown that every strongly stable contractive semigroup is related to the left shift semigroup on an L(exp 2) space. Then, a decomposition for the state space which identifies strongly stable and unstable states is introduced. Based on this decomposition, conditions for a contractive semigroup to be strongly stable are obtained. Finally, extensions of Lyapunov's equation for distributed parameter systems are investigated. Sufficient conditions for weak and strong stabilities of uniformly bounded semigroups are obtained by relaxing the equivalent norm condition on the right hand side of the Lyanupov equation. These characterizations are then applied to the problem of feedback stabilization. First, it is shown via the state space decomposition that under certain conditions a contractive system (A,B) can be strongly stabilized by the feedback -B(*). Then, application of the extensions of the Lyapunov equation results in sufficient conditions for weak, strong, and exponential stabilizations of contractive systems by the feedback -B(*). Finally, it is shown that for a contractive system, the first derivative of x with respect to time = Ax + Bu (where B is any linear bounded operator), there is a related linear quadratic regulator problem and a corresponding steady state Riccati equation which always has a bounded nonnegative solution.

Cataltepe, Tayfun↗
NASA NTRS2013

Goal-Function Tree Modeling for Systems Engineering and Fault Management

This paper describes a new representation that enables rigorous definition and decomposition of both nominal and off-nominal system goals and functions: the Goal-Function Tree (GFT). GFTs extend the concept and process of functional decomposition, utilizing state variables as a key mechanism to ensure physical and logical consistency and completeness of the decomposition of goals (requirements) and functions, and enabling full and complete traceabilitiy to the design. The GFT also provides for means to define and represent off-nominal goals and functions that are activated when the system's nominal goals are not met. The physical accuracy of the GFT, and its ability to represent both nominal and off-nominal goals enable the GFT to be used for various analyses of the system, including assessments of the completeness and traceability of system goals and functions, the coverage of fault management failure detections, and definition of system failure scenarios.

Johnson, Stephen B.↗
DOE OSTI2024

Effect of the Chemical States of Copper on Methanol Decomposition and Oxidation

Here, the decomposition and oxidation reactions of CH 3 OH over metallic Cu(100) and Cu 2 O-covered Cu(100) surfaces are studied using a combination of in-situ ambient-pressure X-ray photoelectron spectroscopy, Auger electron spectroscopy, and density functional theory calculations. We identify the sequential chemical transformation pathways from bond cleavage to the formation of intermediates and final products under operational conditions. Accumulative surface adsorption of CH 3 O species on metallic Cu(100) impedes the decomposition of CH 3 OH. Co-dosing on metallic Cu(100) with low pressures of 1·10 -4 Torr CH 3 OH + 1·10 -4 Torr O 2 results in partial oxidation of CH 3 OH, where the chemisorbed O ads reduces surface sites available for CH 3 O adsorption, decreasing the surface activity for CH 3 OH decomposition. In contrast, the Cu 2 O overlayer formed under the elevated pressures of 0.33 Torr CH 3 OH + 0.66 Torr O 2 promotes the total oxidation of CH 3 OH into the final products of CO 2 and H 2 O, arising from the active reaction 2 between lattice O within Cu 2 O and intermediates of CH 3 O, CH 2 O, HCOO, and CO. Despite the more favorable O-H bond scission, C-O bond scission also occurs to result in surface accumulation of CH x on metallic Cu(100), blocking active sites for decomposition reactions of CH 3 OH and CH 3 O. By comparison, the CH x species on the Cu 2 O-covered Cu(100) undergo oxidation into CO 2 and H 2 O with lattice O in the Cu 2 O overlayer, thereby freeing active sites for the total oxidation of CH 3 OH. These results highlight the distinct roles of metallic Cu and Cu 2 O in the pathways of CH 3 OH decomposition and oxidation reactions, offering practical insights for the design of Cu-based catalysts with tailored reactivity and selectivity.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Solid State Multinuclear Magnetic Resonance Investigation of Electrolyte Decomposition Products on Lithium Ion Electrodes

Solid electrolyte interphase (SEI) formation in lithium ion cells prepared with advanced electrolytes is investigated by solid state multinuclear (7Li, 19F, 31P) magnetic resonance (NMR) measurements of electrode materials harvested from cycled cells subjected to an accelerated aging protocol. The electrolyte composition is varied to include the addition of fluorinated carbonates and triphenyl phosphate (TPP, a flame retardant). In addition to species associated with LiPF6 decomposition, cathode NMR spectra are characterized by the presence of compounds originating from the TPP additive. Substantial amounts of LiF are observed in the anodes as well as compounds originating from the fluorinated carbonates.

Li-ion battery electrolytes↗
NASA NTRS2002

Automating CPM-GOMS

CPM-GOMS is a modeling method that combines the task decomposition of a GOMS analysis with a model of human resource usage at the level of cognitive, perceptual, and motor operations. CPM-GOMS models have made accurate predictions about skilled user behavior in routine tasks, but developing such models is tedious and error-prone. We describe a process for automatically generating CPM-GOMS models from a hierarchical task decomposition expressed in a cognitive modeling tool called Apex. Resource scheduling in Apex automates the difficult task of interleaving the cognitive, perceptual, and motor resources underlying common task operators (e.g. mouse move-and-click). Apex's UI automatically generates PERT charts, which allow modelers to visualize a model's complex parallel behavior. Because interleaving and visualization is now automated, it is feasible to construct arbitrarily long sequences of behavior. To demonstrate the process, we present a model of automated teller interactions in Apex and discuss implications for user modeling. available to model human users, the Goals, Operators, Methods, and Selection (GOMS) method [6, 21] has been the most widely used, providing accurate, often zero-parameter, predictions of the routine performance of skilled users in a wide range of procedural tasks [6, 13, 15, 27, 28]. GOMS is meant to model routine behavior. The user is assumed to have methods that apply sequences of operators and to achieve a goal. Selection rules are applied when there is more than one method to achieve a goal. Many routine tasks lend themselves well to such decomposition. Decomposition produces a representation of the task as a set of nested goal states that include an initial state and a final state. The iterative decomposition into goals and nested subgoals can terminate in primitives of any desired granularity, the choice of level of detail dependent on the predictions required. Although GOMS has proven useful in HCI, tools to support the construction of GOMS models have not yet come into general use.

GOMS↗