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At least 1,387 records · Page 77

Fault diagnosis and fault tolerant control for T-S fuzzy stochastic distribution systems subject to sensor and actuator faults

The problem of fault diagnosis (FD) and fault tolerant control (FTC) for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control (SDC) systems subject to sensor and actuator faults is discussed in this paper. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/fault diagnosis observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant (FT) controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.

42 ENGINEERING↗

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗

Modeling a Hypothetical {sup 170}Tm Source for Brachytherapy Applications

Purpose: To perform absorbed dose calculations based on Monte Carlo simulations for a hypothetical {sup 170}Tm source and to investigate the influence of encapsulating material on the energy spectrum of the emitted electrons and photons. Methods: GEANT4 Monte Carlo code version 9.2 patch 2 was used to simulate the decay process of {sup 170}Tm and to calculate the absorbed dose distribution using the GEANT4 Penelope physics models. A hypothetical {sup 170}Tm source based on the Flexisource brachytherapy design with the active core set as a pure thulium cylinder (length 3.5 mm and diameter 0.6 mm) and different cylindrical source encapsulations (length 5 mm and thickness 0.125 mm) constructed of titanium, stainless-steel, gold, or platinum were simulated. The radial dose function for the line source approximation was calculated following the TG-43U1 formalism for the stainless-steel encapsulation. Results: For the titanium and stainless-steel encapsulation, 94% of the total bremsstrahlung is produced inside the core, 4.8 and 5.5% in titanium and stainless-steel capsules, respectively, and less than 1% in water. For the gold capsule, 85% is produced inside the core, 14.2% inside the gold capsule, and a negligible amount (<1%) in water. Platinum encapsulation resulted in bremsstrahlung effects similar to those with the gold encapsulation. The range of the beta particles decreases by 1.1 mm with the stainless-steel encapsulation compared to the bare source but the tissue will still receive dose from the beta particles several millimeters from the source capsule. The gold and platinum capsules not only absorb most of the electrons but also attenuate low energy photons. The mean energy of the photons escaping the core and the stainless-steel capsule is 113 keV while for the gold and platinum the mean energy is 160 keV and 165 keV, respectively. Conclusions: A {sup 170}Tm source is primarily a bremsstrahlung source, with the majority of bremsstrahlung photons being generated in the source core and experiencing little attenuation in the source encapsulation. Electrons are efficiently absorbed by the gold and platinum encapsulations. However, for the stainless-steel capsule (or other lower Z encapsulations) electrons will escape. The dose from these electrons is dominant over the photon dose in the first few millimeter but is not taken into account by current standard treatment planning systems. The total energy spectrum of photons emerging from the source depends on the encapsulation composition and results in mean photon energies well above 100 keV. This is higher than the main gamma-ray energy peak at 84 keV. Based on our results, the use of {sup 170}Tm as a brachytherapy source presents notable challenges.

07 ISOTOPE AND RADIATION SOURCES↗

Dynamic characteristics of double-barrier nanostructures with asymmetric barriers of finite height and widths in a strong ac electric field

The theory of the interaction of a monoenergetic flow of injected electrons with a strong high-frequency ac electric field in resonant-tunneling diode (RTD) structures with asymmetric barriers of finite height and width is generalized. In the quasi-classical approximation, electron wavefunctions and tunneling functions in the quantum well and barriers are found. Analytical expressions for polarization currents in RTDs are derived in both the general case and in a number of limiting cases. It is shown that the polarization currents and radiation power in RTDs with asymmetric barriers strongly depend on the ratio of the probabilities of electron tunneling through the emitter and collector barriers. In the quantum mode, when δ = ɛ − ɛ{sub r} = ħω ≪ Γ (ɛ is the energy of electrons injected in the RTD, ħ is Planck’s constant, ω is the ac field frequency, ɛ{sub r} and Γ are the energy and width of the resonance level, respectively), the active polarization current in a field of E ≈ 2.8ħω/ea (e is the electron charge and a is the quantum-well width) reaches a maximum equal in magnitude to 84% of the direct resonant current, if the probability of electron tunneling through the emitter barrier is much higher than that through the collector barrier. The radiation-generation power at frequencies of ω = 10{sup 12}–10{sup 13} s{sup −1} can reach 10{sup 5}–10{sup 6} W/cm{sup 2} in this case.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancing Least-Squares Finite Element Methods Through a Quantity-of-Interest

Here, we introduce an approach that augments least-squares finite element formulations with user-specified quantities-of-interest. The method incorporates the quantity-of-interest into the least-squares functional and inherits the global approximation properties of the standard formulation as well as increased resolution of the quantity-of-interest. We establish theoretical properties such as optimality and enhanced convergence under a set of general assumptions. Central to the approach is that it offers an element-level estimate of the error in the quantity-of-interest. As a result, we introduce an adaptive approach that yields efficient, adaptively refined approximations. Several numerical experiments for a range of situations are presented to support the theory and highlight the effectiveness of our methodology. Notably, the results show that the new approach is effective at improving the accuracy per total computational cost.

97 MATHEMATICS AND COMPUTING↗

Adaptive Time Step Control for Multirate Infinitesimal Methods

Multirate methods have been used for decades to temporally evolve initial-value problems in which different components evolve on distinct time scales, and thus use of different step sizes for these components can result in increased computational efficiency. Generally, such methods select these different step sizes based on experimentation or stability considerations. For problems that evolve on a single time scale, adaptivity approaches that strive to control local temporal error are widely used to achieve numerical results of a desired accuracy with minimal computational effort, while alleviating the need for manual experimentation with different time step sizes. However, there is a notable gap in the publication record on the development of adaptive time step controllers for multirate methods. In this paper, we extend the single-rate controller work of Gustafsson [ACM Trans. Math. Software, 20 (1994), pp. 496-517] to the multirate method setting. Specifically, we develop controllers based on polynomial approximations to the principal error functions for both the "fast" and "slow" time scales within multirate infinitesimal (MRI) methods. We additionally investigate a variety of approaches for estimating the errors arising from each time scale within MRI methods. We then numerically evaluate the proposed multirate controllers and error estimation strategies on a range of multirate test problems, comparing their performance against an estimated optimal performance. Through this work, we combine the most performant of these approaches to arrive at a set of multirate adaptive time step controllers that robustly achieve desired solution accuracy with minimal computational effort.

97 MATHEMATICS AND COMPUTING↗

Parameter Optimization Toolbox for NS-3 network optimization, NS-3 Parameter Optimization Framework [SWR-18-60]

This simulation-based parameter optimization framework is proposed to tune parameters of different types of communication networks using ns-3 to achieve the optimal network performance. It consists of three main components: an ns-3 packet reporting module; a sampler running simulations with all possible parameter sets for the input parameter variables by using a parallel executor at each generation; and a hybrid optimization algorithm for tuning configurable parameters of hybrid designs and application parameter variables. The proposed hybrid metaheuristic optimization algorithm combines an evolutionary algorithm with a gradient descent function to quickly achieve an approximate globally optimum solution. This software is designed to be used in a multi-core processing Linux environment and run over a long duration of time. The execution time varies depending mainly upon the nature of the ns-3 configuration being simulated. This software includes a custom ns-3 QoS measurement application which must be included with the ns-3 source code during installation of the software.

Hasandka, Adarsh↗

A Data-Driven Approach for High-Impedance Fault Localization in Distribution Systems [SWR-24-13]

This software provides a data-driven approach for efficiently identifying high impedance faults (HIFs) in distribution systems. To tackle the nonlinearity of the voltage current trajectory of HIFs, we first formulate linear least squares problems to approximate the trajectory with piecewise functions. Then we collect the function features of all segments as inputs and use the support vector machine approach to efficiently identify HIFs at different locations.

Zhou, Yuqi↗

Bayesian Monte Carlo Evaluation Framework for Imperfect Nuclear Data

Bayesian evaluation of resolved resonance region (RRR) nuclear data has historically been carried out using the generalized least squares (GLS) formalism, as implemented in, e.g., SAMMY. We have recently developed a prototype of Bayesian Monte Carlo (BMC) evaluation framework, implemented using a Markov Chain Monte Carlo (MCMC) method with a Metropolis-Hastings (MH) acceptance criterion. This was done in order to remove the approximations underlying the conventional GLS evaluations, namely, the linear approximation, and the approximation that all probability density functions (PDFs) are of the normal kind. Recent works by others have used similar stochastic approaches to quantify cross section uncertainties from ENDF evaluated co-variances, and/or, from integral benchmark data, but those have not been conceived as an evaluation framework like the one presented here.

97 MATHEMATICS AND COMPUTING↗

Laser-driven high-resolution MeV x-ray tomography

The need for high-resolution MeV x-ray tomography to observe the three-dimensional structure of dense, large-sized objects is rapidly increasing for the non-destructive evaluation of critical additively manufactured parts, national security, and other applications. We report a demonstration of high-resolution MeV computed tomography of a dense, large object with a laser-driven x-ray source. A record detector-limited MeV radiograph resolution of < 200 µm as determined with the Bennett approximation of the point spread function was achieved by irradiating millimeter-thick tungsten targets with 300 TW femtosecond laser pulses at a 0.5 Hz repetition rate. A tungsten alloy step wedge spectrometer indicates that the peak of the x-ray emission is between 1 and 2 MeV, with an endpoint energy of 19 MeV. To illustrate the radiographic imaging capability of the system, a tomographic reconstruction of a nickel superalloy turbine blade ( maximum $ρr$ = 139 g/cm 2 ) with sub-millimeter resolution was performed using 2160 individual radiographs. The small x-ray source size opens the prospect of extremely high-resolution tomographs of large, dense objects. This laser-driven approach has major advantages for non-destructive evaluation.

47 OTHER INSTRUMENTATION↗

Modeling X-Ray Thomson Scattering Spectra of Warm Dense Matter

Warm dense matter (WDM) is sometimes described as a \solid density plasma" where neither weakly coupled plasma theory nor condensed matter theory are applicable. More specifically, WDM has densities of ~ 0:1 - 50 times solid density, temperatures of ~ 1 - 100 eV, is partially ionized, globally neutral, has strongly correlated particles (due to interactions), and partial electron degeneracy. In nature, WDM may be found in the interiors of planets such as Jupiter or in the envelopes of white dwarf stars, and in man-made processes such as inertial confinement fusion (ICF), WDM exists as a transient state of matter. To model these physical systems, the equation of state as well as opacity, conductivity, and diffusion coefficients must be known. Experimentally WDM is probed with an experimental technique known as X-Ray Thomson Scattering (XRTS). In such an experiment X-rays photons are scattered off of WDM and the resulting photons are measured at a given solid angle. The resulting spectrum gives information on the density and temperature of WDM, but a model of WDM and the scattering experiment is often required to interpret the results. As a result, these experiments also serve as a method of validation for potential models of WDM. The work presented here focuses on the model of WDM proposed by Starrett and Saumon and a model for scattering based off of Chihara’s work. The model proposed by Starrett and Saumon is an average-atom model that is coupled with a two component plasma model, hereafter referred to as an AA+TCP model. The AA+TCP model is an ab initio model with no free parameters, only requiring knowledge of the element under investigation, the density, and the temperature. The outputs from the model completely determine all the input parameters needed for Chihara’s structure function (chemical potential, elastic feature, screening potential, bound-state wavefunctions, and free wavefunctions), which in turn determines the double differential scattering cross-section of the experiment. This approach to determining the outcome of an XRTS experiment parallels that of Johnson, et al., but expands the work in many respects. For example, the AA+TCP model completely determines all the input parameters to the structure function; hence no ad hoc approximations are necessary to close the system. Also, the free-electron feature and the bound-free feature are modified to include collisions and occupation of free electron states, respectively.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

(e,e’p) study of momentum distribution ratios in A=3 nuclei

We report the first measurement of the (e,e’p) reaction cross-section ratio for 3 He relative to 3 H, with missing momentum range of 40 ≤ p miss ≤ 550 MeV/c, at large momentum transfer $\langle$Q2$\rangle$≈ 1.9 (GeV/c) 2 and x B > 1. The data is compared with calculations performed within the plane-wave impulse approximation (PWIA) using realistic spectral functions and momentum distributions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive Methods for Radial Basis Functions

Radial basis functions (RBFs) are a powerful tool for constructing high-order accurate reduced representations of scattered data in arbitrary dimension and on manifolds. We present a method of constructing data approximations in which we utilize a functional tail to capture a global background profile and a RBF neural network (NN) to capture the smaller-scale features. In the RBF NN the RBF centers, matrix shape parameters were selected adaptively for each RBF. We also utilized a geodesic notion of distance on the manifold on which the data lies, e.g., the spherical geodesic for data on the sphere. Although each of these ideas have been been investigated separately in previous works, their combination into a single algorithm is novel. We defined a machine learning problem in which these properties are learned to minimize the data reduction error. We demonstrate the algorithm for applications of scattered data reduction in the plane and on the sphere.

97 MATHEMATICS AND COMPUTING↗

The Vera C. Rubin Observatory Data Preview 1

We present Rubin Data Preview 1 (DP1), the first data from the National Science Foundation–Department of Energy Vera C. Rubin Observatory, comprising raw and calibrated single-epoch images, coadds, difference images, detection catalogs, and ancillary data products. DP1 is based on 1792 optical–near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera (LSSTComCam) on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile in late 2024. DP1 covers ∼15 deg 2 distributed across seven roughly equal-sized noncontiguous fields, each independently observed in six broad photometric bands, ugrizy. The median FWHM of the point-spread function across all bands is approximately 1"14, with the sharpest images reaching about 0." 58. The 5σ point-source depths for coadded images in the deepest field, the Extended Chandra Deep Field South, are u = 24.55, g = 26.18, r = 25.96, i = 25.71, z = 25.07, and y = 23.1. Other fields are no more than 2.2 mag shallower in any band, where they have nonzero coverage. DP1 contains approximately 2.3 million distinct astrophysical objects, of which 1.6 million are extended in at least one band in coadds, and 431 solar system objects, of which 93 are new discoveries. DP1 is approximately 3.5 TB in size and is available to Vera C. Rubin Observatory data rights holders via the Rubin Science Platform, a cloud-based environment for the analysis of petascale astronomical data. While small compared to future LSST releases, its high quality and diversity of data support a broad range of early science investigations ahead of full operations in 2026.

Ground-based astronomy↗

A Simulation-based Method for Correcting Mode Coupling in CMB Angular Power Spectra

Modern cosmic microwave background (CMB) analysis pipelines regularly employ complex time-domain filters, beam models, masking, and other techniques during the production of sky maps and their corresponding angular power spectra. However, these processes can generate couplings between multipoles from the same spectrum and from different spectra, in addition to the typical power attenuation. Within the context of pseudo-C ℓ based, MASTER-style analyses, the net effect of the time-domain filtering is commonly approximated by a multiplicative transfer function, F ℓ , that can fail to capture mode mixing and is dependent on the spectrum of the signal. To address these shortcomings, we have developed a simulation-based spectral correction approach that constructs a two-dimensional transfer matrix, ${J}_{{\ell }{\ell }^{\prime} }$, which contains information about mode mixing in addition to mode attenuation. We demonstrate the application of this approach on data from the first flight of the Spider balloon-borne CMB experiment.

79 ASTRONOMY AND ASTROPHYSICS↗

MISO - Mixed Integer Surrogate Optimization

MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.

Mueller, Juliane↗

Energy density functional and sensitivity of energies of giant resonances to bulk nuclear matter properties

The development of a modern and more realistic nuclear energy density functional (EDF) for accurate predictions of properties of nuclei is the subject of enhanced activity, since it is very important for the study of properties of nuclear matter (NM), giant resonances and, in particular, of properties of rare nuclei with unusual neutron-to-proton ratios. Here, we provide a short review of the current status of the nuclear EDF and the theoretical results obtained for properties of nuclei and nuclear matter. We will first describe a method for determining the parameters of the EDF, associated with the Skyrme type effective interaction, by carrying out a Hartree-Fock based fit to extensive set of data of ground state properties and constraints. Next we will describe the fully self-consistent Hartree-Fock (HF) based random-phase-approximation (RPA) theory for calculating the strength functions S(E) and centroid energies E CEN of giant resonances and the folding model (FM) distorted wave Вorn approximation (DWBA) to calculate the excitation cross section of giant resonances by α scattering. Then we will provide results for: (i) the Skyrme parameters of the KDE0v1 EDF; (ii) consequences of violation of self-consistently in HF-based RPA; (iii) FM-DWBA calculation of excitation cross section; (iv) values of the E CEN of isoscalar and isovector giant resonances of multipolarities L=0–3 for a wide range of spherical nuclei, using 33 EDFs associated with standard form of the Skyrme type interactions, commonly employed in the literature; and (v) the sensitivities E CEN of the giant resonances to bulk properties of NM. We also determine constraints on NM properties, such as the incompressibility coefficient and effective mass, by comparing with experimental data on E CEN of giant resonances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗