AGS Booster Beam-based Main Quadrupole Transfer Function Measurements
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43 PARTICLE ACCELERATORS↗
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Results for “transfer functions”
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Extrapolating Dynamic Transfer Functions from Multiple-Input Multiple-Output Vibration Testing and Simulation (EDTF) [Slides]
Abstract not provided.
42 ENGINEERING↗
Including massive neutrinos in thermal Sunyaev Zeldovich power spectrum and cluster counts analyses
We consistently include the effect of massive neutrinos in the thermal Sunyaev Zeldovich (SZ) power spectrum and cluster counts analyses, highlighting subtle dependencies on the total neutrino mass and data combination. In particular, we find that using the transfer functions for cold dark matter (CDM) + baryons in the computation of the halo mass function, instead of the transfer functions including neutrino perturbations, as prescribed in recent work, yields an ≈0.25 percent downward shift of the σ 8 constraint from tSZ power spectrum data, with a fiducial neutrino mass Σm ν = 0.06 eV. In ΛCDM, with an X-ray mass bias corresponding to the expected hydrostatic mass bias, i.e. (1 - b) ≃ 0.8, our constraints from Planck SZ data are consistent with the latest results from SPT, DES-Y1, and KiDS+VIKING-450. In νΛCDM, our joint analyses of Planck SZ with Planck 2015 primary CMB yield a small improvement on the total neutrino mass bound compared to the Planck 2015 primary CMB constraint, as well as (1 - b) = 0.64 ± 0.04 (68 percent CL). For forecasts, we find that competitive neutrino mass measurements using cosmic variance limited SZ power spectrum require masking the heaviest clusters and probing the small-scale SZ power spectrum up to ℓ max ≈ 10 4 . Although this is challenging, we find that SZ power spectrum can realistically be used to tightly constrain intracluster medium properties: we forecast a 2 percent determination of the X-ray mass bias by combining CMB-S4 and our mock SZ power spectrum with ℓ max = 10 3 .
Astronomy & Astrophysics↗
Beam Signal Recovery Using Wiener Deconvolution
This project explores the use of Wiener deconvolution to recover an original signal that has been distorted by a known transfer function and by noise. A simulated Gaussian pulse was used as the test signal, and a transfer function was applied in the frequency domain to model system distortion. Controlled noise was then introduced to approximate real-world signal degradation. A Wiener filter was implemented to reverse the effects of the transfer function while minimizing the influence of noise. The recovered signal was compared to the original pulse to evaluate the effectiveness of the filter. Results demonstrate that Wiener deconvolution offers a stable and effective approach to signal recovery, balancing complete transfer function inversion and noise suppression.
Campbell, Savanna [El Camino Coll.]↗
Wiener Filter Deconvolution for Analog Signals
This project explores the use of Wiener deconvolution to recover an original signal that has been distorted by a known transfer function and by noise. A simulated Gaussian pulse was used as the test signal, and a transfer function was applied in the frequency domain to model the system distortion. Controlled noise was then introduced to approximate real-world signal degradation. A Wiener filter was implemented to reverse the effects of the transfer function while minimizing the influence of noise. The recovered signal was compared with the original pulse to evaluate the effectiveness of the filter. The results demonstrate that Wiener deconvolution offers a stable and effective approach to signal recovery, balancing complete transfer function inversion and noise suppression.
Campbell, Savanna [Fermilab]↗
Ensuring a Nuclear Power Plant Safe State Following an EMP Event - Task 7 Deliverable: EMP Testing of Secondary Coupling to Instrumentation Cables
Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle
Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.
algorithms↗
A VR-based volumetric medical image segmentation and visualization system with natural human interaction
Volume rendering produces informative two-dimensional (2D) images from a 3-dimensional (3D) volume. It highlights the region of interest and facilitates a good comprehension of the entire data set. However, volume rendering faces a few challenges. First, a high-dimensional transfer function is usually required to differentiate the target from its neighboring objects with subtle variance. Unfortunately, designing such a transfer function is a strenuously trial-and-error process. Second, manipulating/visualizing a 3D volume with a traditional 2D input/output device suffers dimensional limitations. To address all the challenges, we design NUI-VR 2 , a natural user interface-enabled volume rendering system in the virtual reality space. NUI-VR 2 marries volume rendering and interactive image segmentation. It transforms the original volume into a probability map with image segmentation. A simple linear transfer function will highlight the target well in the probability map. More importantly, we set the entire image segmentation and volume rendering pipeline in an immersive virtual reality environment with a natural user interface. NUI-VR 2 eliminates the dimensional limitations in manipulating and perceiving 3D volumes and dramatically improves the user experience.
42 ENGINEERING↗
Reconciling Chord Length Distributions and Area Distributions for Fields of Fractal Cumulus Clouds
While the total cover of broken cloud fields can in principle be obtained from one-dimensional measurements, the cloud size distribution normally differs between two-dimensional (area) and one-dimensional retrieval (chord length) methods. In this study, we use output from high-resolution Large Eddy Simulations to generate a transfer function between the two. We retrieve chord lengths and areas for many clouds, and plot the one as a function of the other, and vice versa. We find that the cloud area distribution conditional on the chord length behaves like a gamma distribution with well-behaved parameters, with a mean μ=1.1L and a shape parameter β=L−0.645. Using this information, we are able to generate a transfer function that can adjust the chord length distribution so that it comes much closer to the cloud area distribution. Our transfer function improves the error in predicting the mean cloud size, and is performs without strong biases for smaller sample sizes. However, we find that the method is still has difficulties in accurately predicting the frequency of occurrence of the largest cloud sizes.
54 ENVIRONMENTAL SCIENCES↗
Computational optical physical unclonable function
A system or method for encryption of data includes a light source, a random optical element and a light detection element. The light source is arranged to transmit an input data signal to the random optical element. The light source is incident on the random optical element such that the input data signal is randomly scattered by the random optical element to generate an image at on the detector disposed at an output of the random optical element. The image received by the detector is applied to a compressive sensing algorithm to generate a transfer function. The transfer function defines a relationship between the input data signal and the image to enable estimation and reconstruction of the input data signal.
Birch, Gabriel Carlisle↗
Linear Time-Invariant Models of a Large Cumulus Ensemble
Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.
Meteorology & Atmospheric Sciences↗
Second-order wave excitation forces in WEC-Sim/MOST: Implementation, experimental validation, and code-to-code comparison
Accurate prediction of second-order hydrodynamic loads is essential for floating bodies, including floating offshore wind turbines, wave energy converters, and hybrid wind–wave platforms. These nonlinear effects, arising from both sum- and difference-frequency forcing, are critical for capturing key response characteristics but remain challenging to model efficiently. In this work, we extend the open-source Wave Energy Converter Simulator / MATLAB for Offshore Simulation Tool by implementing second-order wave excitation forces, supporting both the full Quadratic Transfer Function formulation and the Newman approximation. The full Quadratic Transfer Function method is used for all code-to-code comparisons and experimental validation, while the Newman approximation is provided as a computationally lighter alternative. To benchmark the new capability, we perform a code-to-code comparison with OpenFAST and OrcaFlex. We then validate the enhanced model using wave-tank measurements of a 1:96 scale DeepCwind semi-submersible, showing that second-order effects are required to reproduce platform motions. The implementation employs a computationally efficient pre-computation strategy for second-order wave excitation forces, reducing simulation cost while maintaining engineering accuracy. Overall, this work advances the tool as an open-source and versatile tool for modelling floating offshore renewable-energy systems requiring second-order hydrodynamic fidelity.
17 WIND ENERGY↗
Limiting the number of quantisation levels of a harmonic lens as a method for improving the quality of the generated image
The characteristics (modulation transfer functions) of harmonic lenses made by direct laser patterning of resist are experimentally studied. The influence of technological errors in the manufacture of lenses on the formation of the point spread function is modelled for harmonic lenses with 32 and 256 quantisation levels. Direct laser writing is used to produce lenses with these numbers of levels. It is experimentally shown that the modulation transfer function of the harmonic lens with 32 quantisation levels is significantly greater at high spatial frequencies (50 mm{sup −1}). (paper)
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
sf-23-021 SONICC (SCALE-DEPENDENT OMEGA FOR NEUTRINO INITIAL CONDITION CODES)
SONICC computes density and velocity transfer functions for use in the initial conditions of massive neutrino cosmological simulations. The transfer functions are backscaled using a scale-dependent growth function that produces self-consistent evolution for all three matter species (cold dark matter, baryons, massive neutrinos) in the Newtonian forward model of cosmological simulations.
EMBERSON, JEFFREYD↗
Simple strategy for the simulation of axially symmetric large-area metasurfaces
Metalenses are composed of nanostructures for focusing light and have been widely explored in many exciting applications. However, their expanding dimensions pose simulation challenges. We propose a method to simulate metalenses in a timely manner using vectorial wave and ray tracing models. We sample the metalens’s radial phase gradient and locally approximate the phase profile by a linear phase response. Each sampling point is modeled as a binary blazed grating, employing the chosen nanostructure, to build a transfer function set. The metalens transmission or reflection is then obtained by applying the corresponding transfer function to the incoming field on the regions surrounding each sampling point. Fourier optics is used to calculate the scattered fields under arbitrary illumination for the vectorial wave method, and a Monte Carlo algorithm is used in the ray tracing formalism. We validated our method against finite-difference time domain simulations at 632 nm, and we were able to simulate metalenses larger than 3000 wavelengths in diameter on a personal computer.
Martins, Augusto (ORCID:0000000295546481)↗
Multiobjective Optimal Controlled Variable Selection for a Gas Turbine–Solid Oxide Fuel Cell System Using a Multiagent Optimization Platform
Hybrid gas turbine–fuel cell systems have immense potential for high efficiency in electrical power generation with cleaner emissions compared with fossil-fueled power generation. We report a systematic controlled variable (CV) selection method is deployed for a hybrid gas turbine–fuel cell system in the HyPer (hybrid performance) facility at the U.S. Department of Energy’s National Energy Technology Laboratory (NETL) for maximizing its economic and control performance. A three-stage approach is used for the CV selection comprising a priori analysis, multiobjective optimization, and a posteriori analysis. The a priori analysis helps to screen off several candidate CVs, thus reducing the size of the combinatorial optimization problem for multiobjective CV selection. For optimal CV selection, a transfer function model of the HyPer facility is identified. By considering several candidate models, the final transfer function model is selected using Akaike’s Final Prediction Error criterion. Experimental data from the HyPer facility are used to estimate the noise in the measurement data. For solving the combinatorial multiobjective optimization problem for CV selection, a multiagent optimization platform comprising simulated annealing, genetic algorithm, and efficient ant colony optimization algorithms is used. Pareto-optimal CV sets exhibit a high trade-off between the economic and control objective. The a posteriori analysis is undertaken for several top Pareto-optimal CV sets. An optimal CV set is selected that shows the best compromise between process economics and controllability under both nominal and off-design conditions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Preliminary Monte Carlo and Thermal Hydraulic Analysis using a Hybrid ETF-Corrected-Diffusion Prediction Block
This paper builds upon previous work to accelerate the Picard iteration (PI) method typically applied for coupled Monte Carlo-Thermal hydraulic (MC-TH) solutions. Previously, the use of the generalized transfer functions (GTFs) to predict variation in macroscopic cross sections following a perturbation in TH properties was demonstrated for a subset of simple 3D problems. In addition, the reduced-order transport prediction block relied on the first order perturbation (FOP) method, which was shown to have computational overheads. Recent work replaced the FOP block with a 1-group nodal diffusion solver to eliminate these overheads. While the use of diffusion is desirable for large-scale problems, the new solver introduces significant homogenization error. This work aims to address this issue by using the Jacobian-Free Newton Krylov (JFNK) method to generate a set of super homogenization (SPH) factors to improve the accuracy of the diffusion solution. The SPH factors will be used in conjunction with an improved cross section prediction method – the expanded transfer function (ETF) method – to produce a highly accurate flux prediction for an axial 1D boiling water reactor (BWR) pincell following a large perturbation in moderator density. The ETF-corrected diffusion (ETF-CD) block is shown to be highly accurate for the 1D test case. Future work will investigate the accuracy of the method for a realistic 3D pressurized water reactor core.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
A new synthetic correlation electron cyclotron emission diagnostic for validating nonlinear gyrokinetic simulations of electron temperature turbulence
To validate nonlinear gyrokinetic simulations of electron temperature turbulence, the experimental correlation electron cyclotron emission (CECE) measurements are to be compared using a synthetic CECE diagnostic, which generates modeled CECE measurement quantities by implementing realistic measurement parameters (e.g., spatial and wavenumber resolutions, radial location, etc.) to nonlinear gyrokinetic simulations. In this work, we calculate the radial and vertical spatial and wavenumber transfer functions, which are defined by the electron cyclotron emission emissivity radial profile and vertical probing antenna pattern, respectively. These transfer functions are applied to nonlinear gyrokinetic simulations of electron temperature turbulence using the continuum gyrokinetic code. A simultaneous comparison of the experimental electron temperature turbulence power spectrum and root-mean-square (RMS) level, as well as the radial correlation length with the new synthetic CECE diagnostic at a core location ρ ∼ 0.75 in an L-mode DIII-D tokamak plasma, is presented. Here, the preliminary result shows that the synthetic CECE output underestimates the RMS level by ∼42% and overestimates the radial correlation length by ∼40%.
Cyclotron radiation↗