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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-510: Mathematical Analysis of Approximate Biological Effective Dose (BED) Calculation for Multi-Phase Radiotherapy Treatment Plans

Purpose: There is growing interest about biological effective dose (BED) and its application in treatment plan evaluation due to its stronger correlation with treatment outcome. An approximate biological effective dose (BEDA) equation was introduced to simplify BED calculations by treatment planning systems in multi-phase treatments. The purpose of this work is to reveal its mathematical properties relative to the true, multi-phase BED (BEDT) equation. Methods: The BEDT equation was derived and used to reveal the mathematical properties of BEDA. MATLAB (MathWorks, Natick, MA) was used to simulate and analyze common and extreme clinical multi-phase cases. In those cases, percent error (Perror) and Bland-Altman analysis were used to study the significance of the inaccuracies of BEDA for different combinations of total doses, numbers of fractions, doses per fractions and α over β values. All the calculations were performed on a voxel-basis in order to study how dose distributions would affect the accuracy of BEDA. Results: When the voxel dose-per-fractions (DPF) delivered by both phases are equal, BEDA and BEDT are equal. In heterogeneous dose distributions, which significantly vary between the phases, there are fewer occurrences of equal DPFs and hence the imprecision of BEDA is greater. It was shown that as the α over β ratio increased the accuracy of BEDA would improve. Examining twenty-four cases, it was shown that the range of DPF ratios for a 3 Perror varied from 0.32 to 7.50Gy, whereas for Perror of 1 the range varied from 0.50 to 2.96Gy. Conclusion: The DPF between the different phases should be equal in order to render BEDA accurate. OARs typically receive heterogeneous dose distributions hence the probability of equal DPFs is low. Consequently, the BEDA equation should only be used for targets or OARs that receive uniform or very similar dose distributions by the different treatment phases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Applied Mathematics Challenge: Simulation of Power Electronics in Future Power Grid

There has been a buzz around increased grid modernization for more than a decade. Grid modernization includes, but is not limited to, upgrades to the grid to enhance reliability, resilience, security, and access to clean energy sources. One significant change that has been happening in this context is the increased penetration of computing power and controlled devices like power electronics in the power grid. As this change happens, the operation and characteristics of the power grid are set to undergo a significant change. The power grid moves from an older electric machine dominated grid that used analog electronics for controls to a power electronics dominated grid that uses digital computing for controls. As this transition happens, there are significant problems of applied mathematics that will need to be resolved in power electronics and power grid. The problems include the ability to simulate in different timescales, while also leveraging the significantly improved computing capabilities available today. In this paper, the challenges related to simulation of power electronics are discussed and the challenge problems laid down that applied mathematics may help resolve in future.

Debnath, Suman↗
DOE OSTI2023

Mathematical Framework Underlying the In Situ Electrochemical Diagnosis of Adsorbed Intermediates Formed during Redox Reactions at Electrode Surfaces

Previously, we have presented an electrochemical technique wherein an electroactive tracer species is employed to probe the rate-limiting factors governing redox reactions at an electrode surface. In this technique, the electrode is first held potentiostatically to facilitate a redox process (step 1), and then the potential is released to open circuit conditions (step 2) so as to monitor the time-dependent re-equilibration of the electrode potential in the presence of the tracer. The time-dependent potential response in step 2 has been shown to contain information about diffusion—limited or desorption—limited steps, enabling in situ probing of the electrochemistry at the electrode surface during step 1. In the present contribution, a theoretical model governing the transient response in step 2 is developed for two limiting cases: diffusion—limited and desorption—limited recovery of the electrode potential. Mathematical modeling shows that, during re-equilibration, the step 2 potential transient corresponding to a case where step 1 involves surface adsorbed species which undergo desorption in step 2 exhibits a much longer time constant than that when re-equilibration occurs under diffusion limitations. The mathematical framework presented herein provides a sound fundamental basis for applying the aforementioned technique to studying adsorption-desorption processes during electrochemistry. Also, technique limitations are presented in light of the modeling findings.

25 ENERGY STORAGE↗
DOE OSTI2026

Mathematical Modeling of the Potential and Time Dependence of Ir Dissolution from Hydrous Ir Oxide Oxygen Evolution Catalysts

One of the main degradation mechanisms of hydrous iridium oxide acidic oxygen evolution reaction (OER) catalysts is dissolution and loss into the acidic membrane. While degradation models have been proposed, there is a gap in understanding the potential and time dependence of the iridium dissolution reaction and its mechanistic underpinnings. In this work, Ir dissolution rates measured as a function of time and potential via time-resolved inductively-coupled plasma mass spectrometry (ICP-MS) in aqueous acidic electrolyte are used to establish a mathematical model for Ir dissolution. The mathematical model is generated using proposed formation and dissolution reactions for Ir species. Through comparison with the ICP-MS data and existing information on the potential-dependent Ir phase, we find that the potential and time-dependence of dissolution can be modeled as dissolution of an oxide phase, here represented as IrO 2 , with potential dependent kinetics and formation of a passivating species, a process with a rate-limiting step that is not potential dependent. This understanding of the potential dependence of dissolution and passivation kinetics using aqueous electrolyte half-cell measurements can be used to predict the degradation of Ir oxide in operating energy conversion devices relying on the OER, such as proton-exchange membrane water electrolyzers.

Kariuki, Nancy N. [Argonne National Laboratory (AN↗
DOE OSTI2024

Machine learning mathematical models for incidence estimation during pandemics

Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread; this leads to significant and systematic under-reporting of the real incidence. Here, we propose a machine learning approach to estimate the incidence of a pandemic in real-time, using reported cases and the overall test rate. In particular, we use Bayesian symbolic regression to automatically learn the closed-form mathematical models that most parsimoniously describe incidence. We develop and validate our models using COVID-19 incidence values for nine different countries, confirming their ability to accurately predict daily incidence. Remarkably, despite the differences in epidemic trajectories and dynamics across countries, we find that a single model for all countries offers a more parsimonious description and is more predictive of actual incidence compared to separate models for each country. Our results show the potential to accurately model incidence in real-time using closed-form mathematical models, providing a valuable tool for public health decision-makers.

Fajardo-Fontiveros, Oscar (ORCID:0000000207058972)↗
DOE OSTI2021

AmeriFlux US-MWU Battle Creek Area Mathematics and Science Center

This is the AmeriFlux version of the carbon flux data for the site US-MWU Battle Creek Area Mathematics and Science Center. Site Description - Urban site located above the roof of the Battle Creek Area Mathematics and Science Center, a regional STEM magnet school. Site was chosen to represent urban areas within the Kalamazoo River watershed.

Chen, Jiquan↗
DOE OSTI2025

Mathematical Morphological Filtering with a Self-Adaptive Reconstruction Technique and Application to Local Seismic Data

Recorded seismic data are generally contaminated by noise from different sources, which masks the signals of interest. In the seismology community, frequency filtering (FF) is the standard method for noise suppression. However, when the signal of interest and noise share the same frequency band, the latter cannot be filtered out without infringing on the former. We implemented a noise suppression approach based on the mathematical morphology theorem. The method involves compound operations of dilation and erosion using structuring elements of varying lengths and decomposes an input noisy waveform into several time functions with differing characteristics. Further, the filtered waveform is constructed from the time functions using a self-adaptive reconstruction technique. Application to a data set of >4700 local waveforms suggests that the implemented mathematical morphological filtering (MMF) approach is efficient for data with low signal-to-noise ratio (SNR) and significantly outperforms FF in that SNR range. For most of the dataset, FF, machine learning (ML) denoising, and continuous wavelet transform (CWT) thresholding result in higher SNR values compared with the MMF method. However, for ~42% of the waveforms, MMF outperforms FF, and the SNR gain achieved with MMF is as large as ~23 dB. Compared to ML denoising and CWT thresholding, this proportion drops to only ~10%–14%. Our results suggests that in an operational setting, MMF cannot replace the other noise suppression methods; however, signal detection can be improved if MMF is used to supplement them in some scenarios. MMF could help detect signals in problematic low-SNR data, which are currently being missed particularly when using FF alone.

58 GEOSCIENCES↗
DOE OSTI2016

Development of Kinetics and Mathematical Models for High Pressure Gasification of Lignite-Switchgrass Blends

The overall objective of the current project was to investigate the high pressure gasification characteristics of a feed containing both coal and biomass. The two feed types differ in their ash contents and ash composition, particularly the alkali content. Gasification of a combined feed of coal and biomass has the potential for considerable synergies that might lead to a dramatic improvement in process economics and flexibility. The proposed study aimed to develop a detailed understanding of the chemistry, kinetics, and transport effects during high pressure gasification of coal-biomass blend feed. Specifically, we studied to develop: (a) an understanding of the catalytic effect of alkali and other inorganic species present in the biomass and coal, (b) an understanding of processing conditions under which synergistic effects of the blending of coal and biomass might be observed. This included the role of particle size, residence time, and proximity of the two feed types, (c) kinetics of high pressure gasification of individual feeds as well as the blends, and (d) development of mathematical models that incorporate kinetics and transport models to enable prediction of gasification rate at a given set of operating conditions, and (e) protocols to extend the results to other feed resources. The goal was to provide a fundamental understanding of the gasification process and guide in optimizing the configurations and design of the next generation of gasifiers. The approach undertaken was centered on two basic premises: (1) the gasification for small particles without internal mass transfer limitations can be treated as the sum of two processes in series (pyrolysis and char gasification) , and (2) the reactivity of the char generated during pyrolysis not only depends on the pressure and temperature but is also affected by the heating rates. Thus low heating rates (10-50 °C/min) typical of PTGA fail to produce char that would typically be formed at high heating rates (~10 4 °C/sec), encountered in entrained flow gasifiers. The char morphology, also a function of the heating rate, would influence the transport rates during the char gasification phase. Thus, heating rate plays a critical role through which both, pyrolysis and char gasification, are interconnected. We utilized two complementary gasification experiments: PEFR (pressurized entrained flow gasifier) and PTGA (pressurized thermo-gravimetric analyzer). The PEFR allowed us to study gasification at pressures, temperatures, and heating rates relevant for coal-biomass gasifiers. The PTGA work was useful in understanding the basic chemistry of the evolution of various gaseous species during pyrolysis. These results helped improved our understanding of the chemistry and chemical changes during pyrolysis. The role alkali metals and other inorganics in char gasification using steam and/or CO 2 was investigated. Finally, the mathematical models for char gasification without the transport effects were developed at commercial operating conditions.

09 BIOMASS FUELS↗
DOE OSTI2017

Mathematical Basis and Test Cases for Colloid-Facilitated Radionuclide Transport Modeling in GDSA-PFLOTRAN

This report provides documentation of the mathematical basis for a colloid-facilitated radionuclide transport modeling capability that can be incorporated into GDSA-PFLOTRAN. It also provides numerous test cases against which the modeling capability can be benchmarked once the model is implemented numerically in GDSA-PFLOTRAN. The test cases were run using a 1-D numerical model developed by the author, and the inputs and outputs from the 1-D model are provided in an electronic spreadsheet supplement to this report so that all cases can be reproduced in GDSA-PFLOTRAN, and the outputs can be directly compared with the 1-D model. The cases include examples of all potential scenarios in which colloid-facilitated transport could result in the accelerated transport of a radionuclide relative to its transport in the absence of colloids. Although it cannot be claimed that all the model features that are described in the mathematical basis were rigorously exercised in the test cases, the goal was to test the features that matter the most for colloid-facilitated transport; i.e., slow desorption of radionuclides from colloids, slow filtration of colloids, and equilibrium radionuclide partitioning to colloids that is strongly favored over partitioning to immobile surfaces, resulting in a substantial fraction of radionuclide mass being associated with mobile colloids.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Asymptotic preserving methods for fluid electron-fluid models in the large magnetic field limit with mathematically guaranteed properties (Final Report)

The current manuscript is a final report on the activities carried out under the Project LDRD-CIS #226834. In scientific terms, the work reported in this manuscript is a continuation of the efforts started with Project LDRD-express #223796 with final report of activities SAND2021-11481, see [83]. In this section we briefly explain what pre-existing developments motivated the current body of work and provide an overview of the activities developed with the funds provided. The overarching goal of the current project LDRD-CIS #226834 and the previous project LDRD-express #223796 is the development of numerical methods with mathematically guaranteed properties in order to solve the Euler-Maxwell system of plasma physics and generalizations thereof. Even though Project #223796 laid out general foundations of space and time discretization of Euler-Maxwell system, overall, it was focused on the development of numerical schemes for purely electrostatic fluid-plasma models. In particular, the project developed a family of schemes with mathematically guaranteed robustness in order to solve the Euler-Poisson model. This model is an asymptotic limit where only electrostatic response of the plasma is considered. Its primary feature is the presence of a non-local force, the electrostatic force, which introduces effects with infinite speed propagation into the problem. Even though instantaneous propagation of perturbations may be considered nonphysical, there are plenty of physical regimes of technical interest where such an approximation is perfectly valid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Mathematical Underpinnings of the Multiwavelength Structure of the Tip of the Red Giant Branch

We consider the application of the tip of the red giant branch (TRGB) in the optical and in the near-infrared for the determination of distances to nearby galaxies. We analyze ACS VI (F555W and F814W) data and self-consistently cross-calibrate WFC3-IR JH (F110W and F120W) data using an absolute magnitude calibration of M {sub I} = −4.05 mag as determined in the Large Magellanic Cloud using detached eclipsing binary star geometric parallaxes. We demonstrate how the optical and near-infrared calibrations of the TRGB method are mathematically self-consistent, and illustrate the mathematical basis and relations among these multiwavelength calibrations. We go on to present a method for determining the reddening, extinction, and the true modulus to the host galaxy using multiwavelength data. The power of the method is that with high-precision data, the reddening can be determined using the TRGB stars themselves, and decreases the systematic (albeit generally small) uncertainty in distance due to reddening for these halo stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Mathematical Calibration of Modular Plastic Scintillators for Various Assay Applications - 17322

Plastic scintillators provide an inexpensive option to assay and characterize radioactive material. Due to the low cost it is generally possible to an array of large numbers of plastic scintillators to achieve high measurement efficiencies. The beta only thin plastic scintillators used in the Argos contamination monitors provide a convenient and reliable scintillator package that can be grouped together to form an assay system. Mathematical calibrations, using MCNP, have been produced for this detector that allow for rapid construction of various custom measurement geometries. The calibrations were constructed by comparing a series of measurements made with a number of beta and beta/gamma emitting nuclides. Characterization of the beta scintillators utilized beta emitting nuclides that included spectra from low average energy, e.g. C-14, to relatively high average energy, e.g. Sr/Y-90. In order to perform the calibration, custom versions of the standard Argos scintillators were produced that provide an MCA output for spectroscopic investigation. The spectra were then compared to detailed MCNP models in an iterative process to energy calibrate and efficiency calibrate each detector type. The validated models and energy calibrations were then tested against a number of volumetric geometries to confirm that the model would translate well to any other geometry. These validated models can then be used to rapidly construct custom measurement geometries for material measurement and screening. Two examples of measurement applications include a beta screening system for dirt on a conveyor belt and a flow through beta liquid assay system. The mathematical calibration process, validation results, and a number of application examples are discussed. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Validation of general purpose mathematical efficiency modeling with ISOCS - 15579

Gamma spectroscopy is a commonly used method for radioactive waste characterization and activity determination in in-situ objects. The gamma rays emitted by radionuclides in the waste container matrix are highly penetrating and can be measured using one or more gamma ray detectors, thus allowing for a passive nondestructive assay. One problem is that a source based calibration of full energy peak efficiency can be difficult or impractical because of the large size and/or an unusual shape of the sample geometry. One attractive solution is to use mathematical efficiency modeling to calculate the full energy peak efficiency. The In-Situ Object Calibration Software (ISOCS) has successfully been used for more than a decade for mathematical efficiency modeling of template based geometries. Templates include the most common objects in waste characterization and D and D, including but not limited to: boxes, drums, and pipes with hotspots, beams, tanks and walls. Scenarios exist where these templates cannot model the desired measurement geometry. Canberra has developed a general purpose version of ISOCS where primitive objects can be combined into practically any geometry. The primitive objects are right circular cylinder, right elliptical cylinder, right circular cone, right elliptical cone, sphere, spheroid, ellipsoid, box (rectangular parallelepiped), torus, and beaker (any cylindrical symmetric object). Multiple primitive objects can be combined using the priority scheme and cut by planes into almost any desired shape. In addition, multiple objects can be defined in the same scene, for example cylinders next to each other or a pipe and a box. Collimators can be constructed as easily as in template based ISOCS. The ray tracing algorithm in ISOCS has been extended to support the new primitive objects for attenuation calculation between the radioactive source and the detector end cap. The new version uses the same vacuum efficiency response, or characterization, in the energy range 10 - 7000 keV of individual detectors to be able to calculate the efficiency as accurately as possible. MCNP has been shown to be able to calculate detection efficiencies for any geometry and the new version of ISOCS have been validated to MCNP. The vacuum efficiency is based on an MCNP model and this model was the base for constructing an identical model in MCNP as in ISOCS. The calculated efficiencies from the two codes have been compared and the agreement is within 3% except for the lowest energies for one geometry. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Mathematical Model for the Emission Infrared Tomography of the Temperature Field in an Isotropic Layer

We consider a mathematical model for the determination of the temperature field in a layer that emits, absorbs, and scatters infrared radiation both in the volume and on the surface. Within the framework of the model, we formulate nonlinear direct and inverse problems of emission infrared tomography of the temperature field in the layer according to known space-and-angular distributions of the flows of infrared radiation emitted into the ambient medium. The iterative-variational methods are proposed for the solution of the indicated direct and inverse problems. As a specific example, we perform the numerical analysis of the developed algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Systems of Functions Orthogonal Over the Domain and Their Application in Boundary-Value Problems of Mathematical Physics

We formulate a boundary-value problem for eigenvalues and eigenfunctions of the Helmholtz equation in a complex domain with the use of mutually conjugated complex variables. The obtained systems of functions are orthogonal in this domain and constructed by using the Bessel functions and powers of the conformal mappings of the analyzed domains onto a circle. The solutions of boundary-value problems for the principal equations of mathematical physics (hyperbolic, parabolic and elliptic types) are obtained in the form of the sums of series in the systems of functions orthogonal over the domain.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

New approach based on group technology for the consolidation problem in cloud computing-mathematical model and genetic algorithm

Resource management is a hotspot issue in distributed systems like cloud computing (CC). It means how to prepare the computational resources, i.e., servers and virtual machines (VMS), to execute the tasks. This paper offers a new approach based on Group Technology (GT)—known as a powerful philosophy for the resource management in cellular manufacturing systems—to deal with the resource management problem in CC. We develop a mathematical model to optimally consolidate the VMs, servers and tasks simultaneously to control several important factors such as task migrations and server load variation, as well as the number of VMs. To test the validity of our proposed model, several small problems are generated randomly and solved by LINGO 9 software. Furthermore, to cope with larger problems, which cannot be solved optimally, a genetic algorithm is proposed. We, finally, compare our methods with the most well-known algorithms in this context, round robin (RR) and first-come, first-served (FCFS) algorithms.

97 MATHEMATICS AND COMPUTING↗