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At least 199 records · Page 11

R-Matrix Analysis of the Neutron-Induced Cross Sections on 143 Nd Measured at LANSC [Slides]

An established use of R-Matrix codes is being implemented at LANSCE. There are unique features accessible with detectors at LANSCE that can be used to perform more complete R-Matrix analysis. Further, Spin separation is a powerful technique that can be applied in DANCE measurements. Additionally, a unique method to measure transmission with DICER is being undertaken. Transmission and capture data were analyzed in this work. The study can be extended to other channels. The results of the 143 Nd data are presented in this work. New resonances found in this work: 21 compared to ENDF/B-VIII.0 and JEFF-3.3, and 24 compared to JENDL-5. Wrong spin assignment in 23 resonances in ENDF/B-VIII.0, 25 in JEFF-3.3 and 26 in JENDL-5. The 143 Nd and 147,149 Sm have been analyzed. Exciting future for new measurements and analysis!

97 MATHEMATICS AND COMPUTING↗

Plasma-fluidic hybrid display

Fluidic logic elements to control firing and extinction of plasma matrix display system cells with constant electrical power supply

Hilborn, E. H.↗

Some recent advances in numerical methods in structural dynamics

The purpose of this paper is to present some recent developments in the area of numerical dynamic analysis of large structural systems. The first part of the paper is devoted to the finite dynamic element method, a new concept in the discretization of a continuum, the adoption of which effects considerable reduction in the number of degrees of freedom for a required solution accuracy, when compared with the usual finite element method. This is followed by a brief description of eigenproblem solution techniques, for the free vibration analysis of both rotating and nonrotating structures, that fully exploit the associated matrix sparsity. Together, these techniques constitute a powerful tool for the free vibration and subsequent dynamic response analysis of complex practical structures.

Gupta, K. K.↗

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis - Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Bednarcyk, Brett A.↗

Temporal Evolution of the Nanostructure and Phase Compositions in a Model Ni-Al-Cr Alloy

In a Ni-5.2 Al-14.2 Cr at.% alloy with moderate solute supersaturations and a very small gamma/gamma prime lattice parameter misfit, the nanostructural and compositional pathways during gamma prime(L12) precipitation at 873 K are investigated using atom-probe tomography, conventional transmission electron microscopy, and hardness measurements. Nucleation of high number densities (N(sub v) greater than 10(sup 23) per cubic meters) of solute-rich precipitates (mean radius = [R] = 0.75 nm), with a critical nucleus composition of Ni-18.3 plus or minus 0.9 Al-9.3 plus or minus 0.7 Cr at.%, initiates between 0.0833 and 0.167 h. With increasing aging time (a) the solute concentrations decay in spheroidal precipitates ([R] less than 10 nm); (b) the observed early-stage coalescence peaks at maximum N(sub v) in coincidence with the smallest interprecipitate spacing; and (c) the reaction enters a quasi-stationary regime where growth and coarsening operate concomitantly. During this quasi-stationary regime, the c (face-centered cubic)-matrix solute supersaturations decay with a power-law dependence of about -1/3, while the dependencies of [R] and N(sub v) are 0.29 plus or minus 0.05 and -0.64 plus or minus 0.06 at a coarsening rate slower than model predications. Coarsening models allow both equilibrium phase compositions to be determined from the compositional measurements. The observed early-stage coalescence is discussed in further detail.

Sudbrack, Chantal K.↗

A Framework for Performing Multiscale Stochastic Progressive Failure Analysis of Composite Structures

A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.

Bednarcyk, Brett A.↗

Electric Field Activated Shape Memory Polymer Composite

Provided is an electrically activated shape memory polymer composite capable of thermal shape reformation using electric power to heat the composite through its matrix glass transition temperature. The composite includes an adaptable polymer matrix component using a diglycidyl ether resin, at least one substantially well-dispersed conductive or magnetic nano-filler component, and at least one elastic, laminated layer. Also provided are methods of preparing the composite and methods of activating the composite. A shape reformation of the composite is triggered by applying an electric field at DC and/or at a frequency above about 1.mu.Hz for a sufficient time.

Kang, Jin Ho↗

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers

Neuromorphic computers offer the opportunity for low-power, efficient computation. Though they have been primarily applied to neural network tasks, there is also the opportunity to leverage the inherent characteristics of neuromorphic computers (low power, massive parallelism, collocated processing and memory) to perform non-neural network tasks. Here, we demonstrate how an approach for performing sparse binary matrix-vector multiplication on neuromorphic computers. We describe the approach, which relies on the connection between binary matrix-vector multiplication and breadth first search, and we introduce the algorithm for performing this calculation in a neuromorphic way. We validate the approach in simulation. Finally, we provide a discussion of the runtime of this algorithm and discuss where neuromorphic computers in the future may have a computational advantage when performing this computation.

Schuman, Catherine↗

Low-observability matrix completion

An example device includes at least one processor configured to receive electrical parameter values corresponding to at least one first location within a power network. The at least one processor is further configured to determine, using matrix completion and based on the at least one electrical parameter value, an estimated value of at least one unknown electrical parameter. The at least one unknown electrical parameter corresponds to a second location within the power network. The at least one processor is also configured to cause at least one device within the power network to modify operation based on the estimated value of the at least one unknown electrical parameter.

Bernstein, Andrey↗

The Lightweight Integrated Solar Array and Transceiver (LISA-T): Second Generation Advancements and the Future of SmallSat Power Generation

This paper describes the second generation advancements of the Lightweight Integrated Solar Array and Transceiver (LISA-T) currently being developed at NASA's Marshall Space Flight Center. LISA-T is a launch stowed, orbit deployed array on which thin-film photovoltaic and antenna elements are embedded. Inherently, small satellites are limited in surface area, volume, and mass allocation; driving competition between power, communications, and GN&C (guidance navigation and control) subsystems. This restricts payload capability and limits the value of these low-cost satellites. LISA-T is addressing this issue, deploying large-area arrays from a reduced volume and mass envelope - greatly enhancing power generation and communications capabilities of small spacecraft. A matrix of options are in development, including planar (pointed) and omnidirectional (non-pointed) arrays. The former is seeking the highest performance possible while the latter is seeking GN&C simplicity. In both cases, power generation ranges from tens of watts to several hundred with an expected specific power >250W/kg and a stowed power density >200kW/m(sub 3). Options for leveraging both high performance, 'typical cost' triple junction thin-film solar cells as well as moderate performance, low cost cells are being developed. Alongside, both UHF (ultra high frequency) and S-band antennas are being integrated into the array to move their space claim away from the spacecraft and open the door for omnidirectional communications and electronically steered phase arrays.

Carr, John A.↗

First Year Wilkinson Microwave Anisotropy Probe(WMAP) Observations: Data Processing Methods and Systematic Errors Limits

We describe the calibration and data processing methods used to generate full-sky maps of the cosmic microwave background (CMB) from the first year of Wilkinson Microwave Anisotropy Probe (WMAP) observations. Detailed limits on residual systematic errors are assigned based largely on analyses of the flight data supplemented, where necessary, with results from ground tests. The data are calibrated in flight using the dipole modulation of the CMB due to the observatory's motion around the Sun. This constitutes a full-beam calibration source. An iterative algorithm simultaneously fits the time-ordered data to obtain calibration parameters and pixelized sky map temperatures. The noise properties are determined by analyzing the time-ordered data with this sky signal estimate subtracted. Based on this, we apply a pre-whitening filter to the time-ordered data to remove a low level of l/f noise. We infer and correct for a small (approx. 1 %) transmission imbalance between the two sky inputs to each differential radiometer, and we subtract a small sidelobe correction from the 23 GHz (K band) map prior to further analysis. No other systematic error corrections are applied to the data. Calibration and baseline artifacts, including the response to environmental perturbations, are negligible. Systematic uncertainties are comparable to statistical uncertainties in the characterization of the beam response. Both are accounted for in the covariance matrix of the window function and are propagated to uncertainties in the final power spectrum. We characterize the combined upper limits to residual systematic uncertainties through the pixel covariance matrix.

Hinshaw, G.↗

A geometric theory for the QR, LU and power iterations.

Consideration of the task of computing the invariant subspaces of a given matrix. For this purpose the LU, QR, treppen and bi-iterations have been presented, used, and studied more or less independently of the old-fashioned power method. Each of these methods generates implicitly a sequence of subspaces which determines the convergence properties of the method. The iterations differ in the way in which a basis is constructed to represent each subspace. This aspect largely determines the usefulness of the method. It is shown that the first four iterations produce exactly the same sequence of subspaces as do direct and inverse iteration started from appropriate subspaces. Their convergence properties are therefore the same, and a complete geometric convergence theory is presented in terms of the power method. It is shown that Hessenberg matrices are associated with ideal starting spaces.

Parlett, B. N.↗

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗

A Measurement-Based Adaptive Voltage Regulation Method Considering Topology Changes

This paper proposes an online adaptive data-driven distributed energy resource (DER) dispatch optimization method for voltage control considering topology changes. By using a local sensitivity factor (LSF)-enabled voltage control, traditional DER control can be reformulated into a linear programming (LP) problem, leading to faster computation speeds. Power injection alteration and topology changes are two common operational changes in the distribution network that can affect the LSF and voltage control performance. To address this issue, a robust estimation method is developed to adjust the sensitivity matrix at each time step for the time-varying power injection changes. When topology changes occur, only the allocated predominant LSF submatrices are updated based on measurement data, allowing for a fast adaptation to the system reconfiguration. Results obtained from a real distribution feeder in Southern California demonstrate its robustness as compared to traditional volt-var control and constant LSF matrix dispatch control methods.

DERs↗

Complementarity and the unitarity of the black hole S -matrix

Recently, Akers et al. proposed a non-isometric holographic map from the interior of a black hole to its exterior. Within this model, we study properties of the black hole S-matrix, which are in principle accessible to observers who stay outside the black hole. Specifically, we investigate a scenario in which an infalling agent interacts with radiation both outside and inside the black hole. Because the holographic map involves postselection, the unitarity of the S-matrix is not guaranteed in this scenario, but we find that unitarity is satisfied to very high precision if suitable conditions are met. If the internal black hole dynamics is described by a pseudorandom unitary transformation, and if the operations performed by the infaller have computational complexity scaling polynomially with the black hole entropy, then the S-matrix is unitary up to corrections that are superpolynomially small in the black hole entropy. Furthermore, while in principle quantum computation assisted by postselection can be very powerful, we find under similar assumptions that the S-matrix of an evaporating black hole has polynomial computational complexity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗

Effects of Fiber/Matrix Interface and its Composition on Mechanical Properties of Hi Nicalon/Celsian Composites

Fiber-reinforced ceramic matrix composites (CMC) are prospective candidate materials for high temperature structural applications in aerospace, energy conservation, power generation, nuclear, petrochemical, and other industries. At NASA Lewis, we are investigating celsian matrix composites reinforced with various types of silicon carbide fibers. The objective of the present study was to investigate the effects of fiber/matrix interface and its composition on the mechanical properties of silicon carbide (Hi-Nicalon) fiber-reinforced celsian matrix composites.

Bansal, Narottam P.↗

An Ensemble Approach to Computationally Efficient Radiological Anomaly Detection and Isotope Identification

Radiological source search is a challenging task involving detection and identification of weak sources in a constantly changing radiological background. As of now, many radiological source detection algorithms have been proposed; however, their computational complexity, and hence reliance on power intensive processing units inhibit low-power applications of radiological source search systems. In this work, we introduce the anomaly filter (AF) algorithm; a computationally light, yet effective time-series source detection algorithm based on exponential weighted moving average (EWMA) and Poisson deviance statistics. Then, we demonstrate that the proposed algorithm can be used in ensemble with other more computationally intensive source detection and identification algorithms to achieve both increased detection performance and reduced power consumption. The proposed AF algorithm and the ensemble algorithms were thoroughly benchmarked against several existing source detection and identification algorithms. The results show that the AF algorithm outperforms existing conventional source detection algorithms, and the ensemble approach improves the overall performance of existing source detection and isotope identification algorithms. Furthermore, the AF algorithm and the Non-negative Matrix Factorization approach based source identification (NMF-ID) algorithm were combined and implemented on a singleboard microcontroller and the power consumption was measured. This ensemble algorithm reduced the power consumption of the NMF-ID algorithm almost by a factor of 100, while improving the detection performance of the overall system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗