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At least 739 records · Page 41

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗

MUSiC: a model-unspecific search for new physics in proton–proton collisions at $\sqrt{s} = 13\,\text {TeV} $

Results of the Model Unspecific Search in CMS (MUSiC), using proton–proton collision data recorded at the LHC at a centre-of-mass energy of 13TeV, corresponding to an integrated luminosity of 35.9 fb -1 , are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Equation of State Optimization and Uncertainty Quantization: Implementation in the LANL EOS Production Code OpenSesame

We detail the approaches of particle swarm optimization and Bayesian inference through Markov chain Monte Carlo for equation of state development. This work includes formulation of the modeling for the equation of state, numeric optimization of the parametric models via particle swarm optimization, and generation of probability distributions of equations of state from Markov chain Monte Carlo.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An active optimal control strategy of rotor vibrations using external forces

An active control strategy for lateral rotor vibrations using external forces is proposed. An extended state observer is used to reconstruct the full states and the unbalance distribution. An optimal controller which accommodates persistent unbalance excitation is derived with feedback of estimated states and unbalances. Numerical simulations were conducted for two separate four degree of freedom rotor systems. These simulations indicated that the proposed strategy can achieve almost complete vibration cancellation. This was shown to be true even when the number of external control forces was less than the system order so long as coordinate coupling was present. Both steady state and transient response at a constant speed are presented.

Zhu, W.↗

Calculation of the Pressure Distribution on Bodies of Revolution in the Subsonic Flow of a Gas: Axially Symmetrical Flow - Part 1

The present report concerns a method of computing the velocity and pressure distributions on bodies of revolution in axially symmetrical flow in the subsonic range. The differential equation for the velocity potential Phi of a compressible fluid motion is linearized tn the conventional manner, and then put in the form Delta(Phi) = 0 by affine transformation. The quantity Phi represents the velocity potential of a fictitious incompressible flow, for which a constant superposition of sources by sections is secured by a method patterned after von Karman which must comply with the boundary condition delta(phi)/delta(n) = 0 at the originally specified contour. This requirement yields for the "pseudo-stream function" psi a differential equation which must be fulfilled for as many points on the contour as source lengths are assumed. In this manner, the problem of defining the still unknown source intensities is reduced to the solution of an inhomogeneous equation system. The pressure distribution is then determined with the aid of Bernoulli's equation and adiabatic equation of state. Lastly, the pressure distributions in compressible and incompressible medium are compared on a model problem.

Bilharz, Herbert↗

Probabilistic Damage Characterization Using the Computationally-Efficient Bayesian Approach

This work presents a computationally-ecient approach for damage determination that quanti es uncertainty in the provided diagnosis. Given strain sensor data that are polluted with measurement errors, Bayesian inference is used to estimate the location, size, and orientation of damage. This approach uses Bayes' Theorem to combine any prior knowledge an analyst may have about the nature of the damage with information provided implicitly by the strain sensor data to form a posterior probability distribution over possible damage states. The unknown damage parameters are then estimated based on samples drawn numerically from this distribution using a Markov Chain Monte Carlo (MCMC) sampling algorithm. Several modi cations are made to the traditional Bayesian inference approach to provide signi cant computational speedup. First, an ecient surrogate model is constructed using sparse grid interpolation to replace a costly nite element model that must otherwise be evaluated for each sample drawn with MCMC. Next, the standard Bayesian posterior distribution is modi ed using a weighted likelihood formulation, which is shown to improve the convergence of the sampling process. Finally, a robust MCMC algorithm, Delayed Rejection Adaptive Metropolis (DRAM), is adopted to sample the probability distribution more eciently. Numerical examples demonstrate that the proposed framework e ectively provides damage estimates with uncertainty quanti cation and can yield orders of magnitude speedup over standard Bayesian approaches.

Warner, James E.↗

Experimental investigation of a simple distortion index utilizing steady-state and dynamic distortions in a Mach 2.5 mixed-compression inlet and turbofan engine

A wind tunnel investigation was conducted to determine the amplitude and spatial distribution of steady-state and dynamic distortion produced in an inlet with 45 percent of the overall supersonic area contraction occurring internally. It was found that the inlet support strut location and/or the overboard bypass flow rate has a significant effect on the spatial distribution of distortion. Because of this effect the majority of the stall points exhibited four-per-revolution patterns of distortion. Data from this test were used to formulate a simple index that combines steady-state and dynamic distortions. Distortion results obtained with this index correlated well with exhaust nozzle area. It is shown that the exhaust nozzle area of a TF30-P-3, as modified for use in this test, can be controlled in a scheme to avoid engine stall. A considerable increase in engine distortion tolerance can be achieved by opening the 7th-stage bleed. The engine exhibited higher tolerance to distortion for multiple patterns of distortion per-revolution than for a one-per-revolution pattern of distortion.

Costakis, W. G.↗

Magic state distillation from entangled states

We report that magic can be distributed non-locally in many-body entangled states, such as the low energy states of condensed matter systems. Using the Bravyi-Kitaev magic state distillation protocol, we find that non-local magic is distillable and can improve the distillation outcome. We analyze a few explicit examples and show that spin squeezing can be used to convert non-distillable states into distillable ones. Our analysis also suggests that the conventional product input states assumed by magic distillation protocols are extremely atypical among general states with distillable magic. It further justifies the need for studying a diverse range of entangled inputs that yield magic states with high probability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Visualization of Noisy and Less Noisy Computational Basis States in Quantum Computing

Quantum computing technology holds substantial promise as a reliable computational paradigm. However, current noisy intermediate scale quantum (NISQ) systems, are significantly impacted by noise originating from hardware inconsistencies. This noise causes errors and lowers output fidelity. So we must find which basis states cause errors. However, there are two main challenges in analyzing noise corresponding to basis states. First, the noise distribution data is high dimensional in nature, thereby making its analysis challenging. Second, although functional box plots have been used in the state of the art research to understand such a high dimensional data, they suffer from clutter and occlusion issues because of overplotting. In this study, we introduce an innovative visualization pipeline to address the aforementioned challenges to provide a clear depiction of noisy and less-noisy basis states. Specifically, our proposed visualization pipeline comprises three stages namely, low dimensional embedding, clustering, and violin plot visualization, to reduce visual clutter and effectively analyze high-dimensional noise distribution data. Our analysis uses quantum machine learning (QML) circuits as case study for drawing a distinction between noisy and less noisy basis states.

Senapati, Priyabrata [Kent State University]↗

Departures of the electron energy distribution from a Maxwellian in hydrogen. I - Formulation and solution of the electron kinetic equation. II - Consequences

The problem of calculating the steady-state free-electron energy distribution in a hydrogen gas is considered in order to study departures of that distribution from a Maxwellian at sufficiently low degrees of ionization. A model kinetic equation is formulated and solved analytically for the one-particle electron distribution function in a steady-state partially ionized hydrogen gas, and it is shown that the formal solution can be accurately approximated by using the WKB method. The solutions obtained indicate that the high-energy tail of the distribution is susceptible to distortion by imbalanced inelastic collisions for ionization fractions not exceeding about 0.1 and that such departures from a Maxwellian can lead to significant changes in the collisional excitation and ionization rates of ground-state hydrogen atoms. Expressions for the electron-hydrogen collision rates are derived which explicitly display their dependence on the hydrogen departure coefficients. The results are applied in order to compare self-consistent predictions with those based on the a priori assumption of a Maxwellian distribution for models of the thermal ionization equilibrium of hydrogen in the optically thin limit, spectral-line formation by a gas consisting of two-level atoms, and radiative transfer in finite slabs by a gas of four-level hydrogen atoms.

Shoub, E. C.↗

Line Profile of H Lyman-Beta Emission from Dissociative Excitation of H2

A high-resolution ultraviolet spectrometer was employed for a measurement of the H Lyman-Beta(H L(sub Beta)) emission Doppler line profile at 1025.7 A from dissociative excitation of H2 by electron impact. Analysis of the deconvolved line profile reveals the existence of a narrow central peak, less than 30 mA full width at half maximum (FWHM), and a broad pedestal base about 260 mA FWHM. Analysis of the red wing of the line profile is complicated by a group of Wemer and Lyman rotational lines 160-220 mA from the line center. Analysis of the blue wing of the line profile gives the kinetic-energy distribution. There are two main kinetic-energy components to the H(3p) distribution: (1) a slow distribution with a peak value near 0 eV from singly excited states, and (2) a fast distribution with a peak contribution near 7 eV from doubly excited states. Using two different techniques, the absolute cross section of H L(sub Beta)p is found to be 3.2+/-.8 x 10(exp -19)sq cm at 100-eV electron impact energy. The experimental cross-section and line-profile results can be compared to previous studies of H(alpha) (6563.7 A) for principal quantum number n=3 and L(sub alpha)(1215.7 A) for n=2.

Ajello, Joseph M.↗

Solid State Remote Power Controllers for high voltage DC distribution systems

Presently, hybrid Remote Power Controllers (RPC's) are in production and prototype units are available for systems utilizing 28VDC, 120VDC, 115VAC/400 Hz and 230VAC/400 Hz. This paper describes RPC development in a new area of application: HVDC distribution systems utilizing 270/300VDC. Two RPC current ratings, 1 amp and 2 amps, were selected for development as they are adequate to control 90% of projected system loads. The various aspects and trade-offs encountered in circuit development are discussed with special focus placed on the circuits that see the duress of the high dc potentials. The comprehensive evaluation tests are summarized which confirmed the RPC compliance with the specification and with system/load compatibility requirements. In addition, present technology status and new applications are summarized.

Billings, W. W.↗

Solid State Light Evaluation in the U.S. Lab Mockup

This document constitutes the publication of work performed by the Space Human Factors Laboratory (mail code SF5 at the time) at the Johnson Space Center (JSC) in the months of June and July of 2000. At that time, the Space Human Factors Laboratory was part of the Space Human Factors Branch in the Flight Projects Division of the Space and Life Directorate. This report was originally to be a document for internal consumption only at JSC as it was seen to be only preliminary work for the further development of solid state illumination for general lighting on future space vehicles and the International Space Station (ISS). Due to funding constraints, immediate follow-on efforts were delayed and the need for publication of this document was overcome by other events. However, in recent years and with the development and deployment of a solid state light luminaire prototype on ISS, the time was overdue for publishing this information for general distribution and reference. Solid state lights (SSLs) are being developed to potentially replace the general luminaire assemblies (GLAs) currently in service in the International Space Station (ISS) and included in designs of modules for the ISS. The SSLs consist of arrays of light emitting diodes (LEDs), small solid state electronic devices that produce visible light in proportion to the electrical current flowing through them. Recent progressive advances in electrical power-to-light conversion efficiency in LED technology have allowed the consideration of LEDs as replacements for incandescent and fluorescent light sources in many circumstances, and their inherent advantages in ruggedness, reliability, and life expectancy make them attractive for applications in spacecraft. One potential area of application for the SSLs in the U.S. Laboratory Module of the ISS. This study addresses the suitability of the SSLs as replacements for the GLAs in this application.

Maida, James c.↗

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗

Coherent manipulation of graph states composed of finite-energy Gottesman-Kitaev-Preskill-encoded qubits

Graph states are a central resource in measurement-based quantum information processing. In the photonic qubit architecture based on Gottesman-Kitaev-Preskill (GKP) encoding, the generation of high-fidelity graph states composed of realistic, finite-energy approximate GKP-encoded qubits thus constitutes a key task. We consider the finite-energy approximation of GKP-qubit states given by a coherent superposition of shifted finite-squeezed vacuum states, where the displacements are Gaussian distributed. We present an exact description of graph states composed of such approximate GKP qubits as a coherent superposition of a Gaussian ensemble of randomly displaced ideal GKP-qubit graph states. Using standard Gaussian dynamics, we track the transformation of the covariance matrix and the mean-displacement vector elements of the Gaussian distribution of the ensemble under tools such as GKP-Steane error-correction and fusion operations that can be used to grow large high-fidelity GKP-qubit graph states. The covariance matrix elements capture the noise in the graph state due to the finite-energy approximation of GKP qubits, while the mean displacements relate to the possible absolute shift errors on the individual qubits arising conditionally from the homodyne measurements that are a part of these tools. Our work thus pins down an exact coherent error model for graph states generated from truly finite-energy GKP qubits, which can shed light on their error-correction properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗