A Method for Correcting Frequency Estimates for Synthetic Inertia Control
Not Available
Wilches-Bernal, Felipe (ORCID:0000000211351071)↗
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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↗
Multivariate Drought Monitoring, Propagation, and Projection Using Bias-Corrected General Circulation Models
Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological-hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought-related consequences.
54 ENVIRONMENTAL SCIENCES↗
Adapting quantile mapping to bias correct solar radiation data
Not Available
Bailey, Maggie D. (ORCID:0000000347017849)↗
A Systematic Investigation of the Effects of Standard-Sample Concentration Mismatch during Fe Isotope Measurement by MC-ICP-MS
Advances in multi-collector inductively coupled plasma-mass spectrometry (MC-ICP-MS) have led to the widespread use of iron (Fe) isotopes to elucidate the (bio)geochemical history of a range of environments. To generate Fe isotope ratio measurements, standard-sample bracketing (SSB) is commonly used to correct for instrumental mass bias inherent to MC-ICP-MS. However, SSB is only accurate when sample and isotope standard Fe concentrations match, in addition to the bulk solution matrix. When the Fe concentrations differ, Fe isotope ratio measurement results may be inaccurate, a phenomenon known as the "self-induced matrix effect." Here, this study systematically characterised the self-induced matrix effect for dry plasma Fe isotope ratio measurements on three MC-ICP-MS instruments and three introduction systems. Our extensive dataset indicates that: (1) the degree of mass bias is consistent regardless of MC-ICP-MS front-end design, (2) the degree of mass bias becomes less reproducible as the concentration difference between the sample and bracketing standard increases, and (3) this applies to both pure Fe solutions and solutions from geological materials. This study reinforces the requirement to match bracketing standard and sample concentrations within 10% and provides a correction method for that fall beyond the recommended concentration range to subsequently allow for proper concentration matching during SSB.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Improvement and Verification of Online Cross Section Generation Capability of Griffin for TRISO-fueled Reactors
Griffin, a MOOSE-based reactor multiphysics code jointly developed by Idaho National Laboratory and Argonne National Laboratory under the DOE Office of Nuclear Energy’s NEAMS program, has pursued the development of an online multigroup cross section generation capability for a few years to enable high-fidelity, problem-dependent neutronics analyses of advanced thermal reactors. Recent advancements in Griffin’s online multigroup cross section generation capability have significantly improved the accuracy, robustness, and efficiency of self-shielding calculations for both prismatic and pebble-bed TRISO-fueled reactor applications. Key developments include a unified fuel self-shielding method applicable to both TRISO and annular compact/spherical shell fuel zone geometries; an advanced Dancoff Category-based Equivalence Theory using a bell function for non-fuel resonance treatment, achieving more than an order-of-magnitude speedup compared to the Tone method; an on-the-fly multigroup equivalence approach to mitigate group condensation errors; and a streaming correction method for pebble-bed homogenization. A proof-of-concept demonstration of on-the-fly group condensation with consistent P0 transport correction was also achieved. The method reproduced direct fine-group solutions with excellent accuracy (eigenvalue errors within 10 pcm and pin-power differences within 0.5%), but due to performance limitations of the current fixed-source solver, improvements to solver efficiency will be addressed in future work. Verification tests were performed on graphite-moderated TRISO-fueled two-dimensional core benchmark problems representing gas-cooled microreactors, heat pipe-cooled microreactors, gas-cooled pebble-bed reactors, and fluoride salt-cooled high-temperature reactors. Across all cases, Griffin showed excellent agreement with Serpent2 continuous energy Monte Carlo solutions: eigenvalue errors within 200 pcm, pin-power root-mean-square errors within 2%, and control rod and drum worth errors less than 2%. It should be noted that, for the benchmark problem, cross section generation contributed less than 3% of the total simulation times. These results demonstrate that Griffin’s online cross section generation capability delivers accurate and efficient reactor physics solutions across a wide spectrum of TRISO-fueled advanced reactor designs. With further improvements to the fine-group fixed-source solver and planned extensions to depletion, transients, and coupled neutron–gamma transport, Griffin will be well-positioned to become a powerful and comprehensive tool for advanced reactor analysis.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Spectral shape corrections for SDSS BOSS quasars
Modifications were made to the Sloan Digital Sky Survey’s Baryonic Oscillations Spectroscopic Survey (SDSS/BOSS) optical fibres assigned to quasar targets in order to improve the signal-to-noise ratio in the Ly-α forest. However, the consequence of these modifications is that quasars observed in this way require additional flux correction procedures in order to recover the correct spectral shapes. Here, in this paper, we describe such a procedure, based on the geometry of the problem, and other observational parameters. Applying several correction methods to four SDSS quasars with multiple observations permits a detailed verification of the relative performances of the different flux correction procedures. We contrast our method (which takes into account a wavelength-dependent seeing profile) with the BOSS pipeline approach (which does not). Our results provide independent confirmation that the geometric approach employed in the SDSS pipeline works well, although with room for improvement. By separating the contributions from four effects, we are able to quantify their relative importance. Most importantly, we demonstrate that wavelength dependence has a significant impact on the derived spectral shapes and thus should not be ignored.
79 ASTRONOMY AND ASTROPHYSICS↗
PUF Entropy
This note discusses aspects of fuzzy extraction: in particular, how the interplay between PUF entropy and the revelation of helper data affects the entropy of the underlying secret. We examine the theory behind a scheme by Dodis et alii to develop exact formulas for the entropy of the given seed, given that an adversary knows the helper data. We also give a simple lower bound on the security of the Dodis scheme that is achieved exactly in many instances. By way of several examples, we quantify the amount of entropy that can be lost due to interactions between imperfect PUF implementations and given error correction methods. We repeatedly show that understanding the details of the error correction scheme and the interaction with the PUF response is crucial to being able to estimate the entropy of the system.
97 MATHEMATICS AND COMPUTING↗
AutoBEM for BlocPower
As part of a cooperative research and development agreement (CRADA), the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) and BlocPower partnered to rectify disparities between simulated and actual energy consumption in buildings using various correction methods. This team extended ORNL’s building energy modeling capabilities and used bias-correction techniques to reduce the difference between simulated energy consumption estimations and ground-truth consumption data of buildings provided by utilities. ORNL is one of three core DOE laboratories developing the energy modeling tools EnergyPlus and OpenStudio.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
A Particle-in-Cell Method for Plasmas with a Generalized Momentum Formulation, Part II: Enforcing the Lorenz Gauge Condition
In a previous paper Christlieb et al. (A particle-in-cell method for plasmas with a generalized momentum formulation, part I: Model formulation, 2024), we developed a new particle-in-cell (PIC) method for the relativistic Vlasov–Maxwell system in which the electromagnetic fields and the equations of motion for the particles were cast in terms of scalar and vector potentials through a Hamiltonian formulation. This new method evolved the potentials under the Lorenz gauge using integral equation methods. New methods to construct spatial derivatives of the potentials that converge at the same rates as the fields were also presented. The new particle method was compared against standard explicit discretizations, including the well-known FDTD-PIC method, for a range of applications involving sheaths and particle beams. Here, this paper extends this new class of methods by focusing on the enforcement the Lorenz gauge condition in both exact and approximate forms using co-located meshes. A time-consistency property of the proposed field solver for the vector potential form of Maxwell’s equations is established, which is shown to preserve the equivalence between the semi-discrete Lorenz gauge condition and the analogous semi-discrete continuity equation. Using this property, we present three methods to enforce a semi-discrete gauge condition. The first method introduces an update for the continuity equation that is consistent with the discretization of the Lorenz gauge condition. Both the finite difference and spectral implementations satisfy this discrete gauge condition to machine precision. The second approach we propose enforces a semi-discrete continuity equation using the boundary integral solution to the field equations. The potential benefit of this approach is that it eliminates spatial derivatives that appear on the particle data, namely the current density, which is often calculated by linear combinations of low-order spline basis functions. This method is ideally suited to boundary integral equation methods that invert multi-dimensional operators without dimensional splitting techniques and will be the subject of future work. The third approach introduces a gauge correcting method that makes direct use of the gauge condition to modify the scalar potential and uses local maps for both the charge and current densities. This results in a gauge error, as the maps do not enforce the continuity equation. The vector potential coming from the current density is taken to be exact, and using the Lorenz gauge, we compute a correction to the scalar potential that makes the two potentials satisfy the gauge condition. This method also enforces the gauge condition to machine precision. We demonstrate two of the proposed methods in the context of periodic domains. Problems defined on bounded domains, including those with complex geometric features remain an ongoing effort. However, this work shows that it is possible to design computationally efficient methods that can effectively enforce the Lorenz gauge condition in a non-staggered PIC formulation.
97 MATHEMATICS AND COMPUTING↗
A new approach to study adsorption on shales and other microporous solids via the thermogravimetric analysis (TGA) technique
Measuring the adsorption of gases in microporous solids like the shales requires accurate knowledge of the solid’s skeletal volume. Helium (He) is commonly used to determine the sample’s skeletal volume based on the assumption that it does not adsorb in these porous media. The validity of such an assumption for microporous solids has been questioned in recent years, and in this study, we show that it is not applicable for the shale sample studied. We present a new method to measure the adsorption of shale-gas components in shales, which does not require the use of He to measure the solid’s skeletal volume. Since the proposed analysis method relies on the use of dynamic adsorption data, we also propose here a new zero-point correction method for the magnetic suspension balance, which is better suited for the analysis of such data. Here, we employ the new technique to the study of Argon adsorption in Marcellus Shales.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Analytical noise bias correction for precise weak lensing shear inference
Noise bias is a significant source of systematic error in weak gravitational lensing measurements that must be corrected to satisfy the stringent standards of modern imaging surveys in the era of precision cosmology. This paper reviews the analytical noise bias correction method and provides analytical derivations demonstrating that we can recover shear to its second order using the ‘renoising’ noise bias correction approach introduced by METACALIBRATION. We implement this analytical noise bias correction within the AnaCal shear estimation framework and propose several enhancements to the noise bias correction algorithm. We evaluate the improved AnaCal using simulations designed to replicate Rubin Legacy Survey of Space and Time (LSST) imaging data. These simulations feature semi-realistic galaxies and stars, complete with representative distributions of magnitudes and Galactic spatial density. We conduct tests under various observational challenges, including cosmic rays, defective CCD columns, bright star saturation, bleed trails, and spatially variable point spread functions. Our results indicate a multiplicative bias in weak lensing shear recovery of less than a few tenths of a per cent, meeting LSST Dark Energy Science Collaboration requirements without requiring calibration from external image simulations. Additionally, our algorithm achieves rapid processing, handling one galaxy in less than a millisecond.
79 ASTRONOMY AND ASTROPHYSICS↗
Addressing delayed case reporting in infectious disease forecast modeling
Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting, however, forecasting models may often underestimate the current and future disease burden. In this paper, we propose a general framework for addressing reporting delay in disease forecasting efforts with the goal of improving forecasts. We propose strategies for leveraging either historical data on case reporting or external internet-based data to estimate the amount of reporting error. We then describe several approaches for adapting general forecasting pipelines to account for under- or over-reporting of cases. We apply these methods to address reporting delay in data on dengue fever cases in Puerto Rico from 1990 to 2009 and to reports of influenza-like illness (ILI) in the United States between 2010 and 2019. Through a simulation study, we compare method performance and evaluate robustness to assumption violations. Our results show that forecasting accuracy and prediction coverage almost always increase when correction methods are implemented to address reporting delay. Some of these methods required knowledge about the reporting error or high quality external data, which may not always be available. Provided alternatives include excluding recently-reported data and performing sensitivity analysis. This work provides intuition and guidance for handling delay in disease case reporting and may serve as a useful resource to inform practical infectious disease forecasting efforts.
59 BASIC BIOLOGICAL SCIENCES↗
Application of automated iterative target detection for standoff hyperspectral imaging
The utility of hyperspectral imaging (HSI) has been well established for a wide array of applications but has generated a need for automated screening of high volumes of large HSI cubes. We report two important automated algorithms for more efficient standoff processing: atmospheric correction and target detection. The atmospheric correction method is based on a fast asymmetric least squares approach that is applied on a pixel-by-pixel basis. Here, the correction can be applied to entire images without manually identifying regions of interest and utilizes only in-scene information, no ancillary modeling of the atmosphere is required. An iterative target detection approach is also introduced which demonstrates faster speeds relative to moving window approaches. The target detection algorithm classifies each pixel as true target detections, near target detections, clutter, and no-calls. The algorithms were tested on forty images of twenty-two solid mineral targets placed at a 14-meter standoff distance allowing general observations on expected detection performance for a variety of minerals. In addition to identifying anomalous pixels, the inclusion of “no-calls” reduced the number of false detections significantly.
47 OTHER INSTRUMENTATION↗
To bin or not to bin: Does binning in multiplicity reliably suppress unwanted volume fluctuations?
Here, in this study, we examine the effect of the so-called Centrality Bin Width Correction (CBWC) on the measurement of (net-)proton number cumulants in nucleus-nucleus collisions. We present an analytically tractable model, which includes correlations between multiplicity and proton number similar to those generated by the decay of baryon resonances. Within this model, we analyze the circumstances under which the CBWC method correctly removes the undesired effects of volume or impact parameter fluctuations. Additionally, we explore situations where the method fails and produces misleading results.
Critical point↗
Assessing North Atlantic Tropical Cyclone Rainfall Hazard Using Engineered-Synthetic Storms and a Physics-Based Tropical Cyclone Rainfall Model
In this study, we design a statistical method to couple observations with a physics-based tropical cyclone (TC) rainfall model (TCR) and engineered-synthetic storms for assessing TC rainfall hazard. We first propose a bias-correction method to minimize the errors induced by TCR via matching the probability distribution of TCR-simulated historical TC rainfall with gauge observations. Then we assign occurrence probabilities to engineered-synthetic storms to reflect local climatology, through a resampling method that matches the probability distribution of a newly proposed storm parameter named rainfall potential (POT) in the synthetic dataset with that in the observation. POT is constructed to include several important storm parameters for TC rainfall such as TC intensity, duration, and distance and environmental humidity near landfall, and it is shown to be correlated with TCR-simulated rainfall. The proposed method has a satisfactory performance in reproducing the rainfall hazard curve in various locations in the continental United States; it is an improvement over the traditional joint probability method (JPM) for TC rainfall hazard assessment.
54 ENVIRONMENTAL SCIENCES↗
Day-ahead photovoltaic power production forecasting methodology based on machine learning and statistical post-processing
A main challenge towards ensuring large-scale and seamless integration of photovoltaic systems is to improve the accuracy of energy yield forecasts, especially in grid areas of high photovoltaic shares. The scope of this paper is to address this issue by presenting a unified methodology for hourly-averaged day-ahead photovoltaic power forecasts with improved accuracy, based on data-driven machine learning techniques and statistical post-processing. More specifically, the proposed forecasting methodology framework comprised of a data quality stage, data-driven power output machine learning model development (artificial neural networks), weather clustering assessment (K-means clustering), post-processing output optimisation (linear regressive correction method) and the final performance accuracy evaluation. The results showed that the application of linear regression coefficients to the forecasted outputs of the developed day-ahead photovoltaic power production neural network improved the performance accuracy by further correcting solar irradiance forecasting biases. The resulting optimised model provided a mean absolute percentage error of 4.7% when applied to historical system datasets. Finally, the model was validated both, at a hot as well as a cold semi-arid climatic location, and the obtained results demonstrated close agreement by yielding forecasting accuracies of mean absolute percentage error of 4.7% and 6.3%, respectively. Finally, the validation analysis provides evidence that the proposed model exhibits high performance in both forecasting accuracy and stability.
42 ENGINEERING↗
A New Post‐Hoc Method to Reduce the Energy Imbalance in Eddy Covariance Measurements
Abstract Latent and sensible heat flux observations are essential for understanding land–atmosphere interactions. Measurements from the eddy covariance technique are widely used but suffer from systematic energy imbalance problems, partly due to missing large eddies from sub‐mesoscale transport. Because available energy drives the development of large eddies, we propose an available energy based correction method for turbulent flux measurements. We apply our method to 172 flux tower sites and show that we can reduce the energy imbalance from −14.99 to −0.65 W m −2 on average, together with improved consistency between turbulent fluxes and available energy and associated increases inr 2 at individual sites and across networks. Our results suggest that our method is conceptually and empirically preferable over the method implemented in the ONEFlux processing. This can contribute to the efforts in understanding and addressing the energy imbalance issue, which is crucial for the evaluation and calibration of land surface models.
Geology↗