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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 55 records · Page 3

Final report of activities for the LDRD-express project #223796 titled: “Fluid models of charged species transport: numerical methods with mathematically guaranteed properties”, PI: Ignacio Tomas, Co-PI: John Shadid

This report summarizes the findings and outcomes of the LDRD-express project with title “Fluid models of charged species transport: numerical methods with mathematically guaranteed properties”. The primary motivation of this project was the computational/mathematical exploration of the ideas advanced aiming to improve the state-of-the-art on numerical methods for the one-fluid Euler-Poisson models and gain some understanding on the Euler-Maxwell model. Euler-Poisson and Euler-Maxwell, by themselves are not the most technically relevant PDE plasma-models. However, both of them are elementary building blocks of PDE-models used in actual technical applications and include most (if not all) of their mathematical difficulties. Outside the classical ideal MHD models, rigorous mathematical and numerical understanding of one-fluid models is still a quite undeveloped research area, and the treatment/understanding of boundary conditions is minimal (borderline non-existent) at this point in time. This report focuses primarily on bulk-behaviour of Euler-Poisson’s model, touching boundary conditions only tangentially.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal control of mathematical models for the radiotherapy of gliomas: the scalar case

This paper deals with the optimal control of a mathematical model of glioma progression incorporating the basic facts of the evolution of primary brain tumors. We will consider a model of the simplest possible kind, based on the Fischer-Kolmogorov equations, using ideas from Pérez-García (Mathematical models for the radiotherapy of gliomas (preprint), 2016). The control is the 2n-tuple (t{sub 1},..., t{sub n}; d{sub 1},..., d{sub n}), where d{sub i} is the i-th applied radiotherapy dose an t{sub i} is the i-th administration for 1 ≤ i ≤ n. We search for controls that maximize the survival time, that is, the time at which the tumor mass reaches a critical value M{sub ∗}, over the class of admissible radiation times and doses. We present theoretical and numerical results that justify the relevance of the model and the existence of potential medical applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Mathematics in modern immunology

Mathematical and statistical methods enable multidisciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. Here, we collect a representative sample of studies in T-cell biology that illustrate the benefits of modelling–experimental collaborations and that have proven valuable or even groundbreaking. Furthermore, we conclude that it is possible to find excellent examples of synergy between mathematical modelling and experiment in immunology, which have brought significant insight that would not be available without these collaborations, but that much remains to be discovered.

60 APPLIED LIFE SCIENCES↗

Partial Support of Meetings of the Board on Mathematical Sciences and Their Applications

The National Academies of Sciences, Engineering, and Medicine received partial funding for quarterly meetings of and outreach activities by of the Board on Mathematical Sciences and Analytics (BMSA), formerly known as the Board on Mathematical Sciences and Their Applications. The total support from DOE was $240,000 over 36 months covering the period August 1, 2016 through July 31, 2019. Additional support for this activity comes from the National Science Foundation.

97 MATHEMATICS AND COMPUTING↗

A mathematical assessment of the isolation random forest method for anomaly detection in big data

We present the mathematical analysis of the Isolation Random Forest Method (IRF Method) for anomaly detection, proposed by Liu F.T., Ting K.M. and Zhou Z. H. in their seminal work as a heuristic method for anomaly detection in Big Data. We prove that the IRF space can be endowed with a probability induced by the Isolation Tree algorithm (iTree). In this setting, the convergence of the IRF method is proved, using the Law of Large Numbers. Here, a couple of counterexamples are presented to show that the method is inconclusive and no certificate of quality can be given, when using it as a means to detect anomalies. Hence, an alternative version of the method is proposed whose mathematical foundation is fully justified. Furthermore, a criterion for choosing the number of sampled trees needed to guarantee confidence intervals of the numerical results is presented. Finally, numerical experiments are presented to compare the performance of the classic method with the proposed one.

97 MATHEMATICS AND COMPUTING↗

Research Connections: Career and Research Journeys from the SMP Community. Association for Women in Mathematics Series

This book aims to provide perspectives on important questions that undergraduate and graduate students in mathematics ask themselves. Each chapter gives readers a taste of a different mathematician’s work, presented with enough background material that an advanced undergraduate or early graduate student can understand the key ideas of the research. Each mathematical contribution is prefaced by a short biography of the mathematician who wrote the chapter, to give the reader a connection to the author and provide examples of paths from undergraduate education, through graduate school and beyond.

mathematics, research, biographies↗

Mathematical modeling in cancer nanomedicine: a review

Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application of nanotechnology in medicine. This effort has provided drug delivery systems that can potentially revolutionize cancer treatment. Nanocarriers, due to their capacity for targeted drug delivery, can shift the balance of cytotoxicity from healthy to cancerous cells. The field of cancer nanomedicine has made significant progress, but challenges remain that impede its clinical translation. Several biophysical barriers to the transport of nanocarriers to the tumor exist, and a much deeper understanding of nano-bio interactions is necessary to change the status quo. Mathematical modeling has been instrumental in improving our understanding of the physicochemical and physiological underpinnings of nanomaterial behavior in biological systems. Here, we present a comprehensive review of literature on mathematical modeling works that have been and are being employed towards a better understanding of nano-bio interactions for improved tumor delivery efficacy.

60 APPLIED LIFE SCIENCES↗

Optimization of Cooling Water Flow Rate in Nuclear and Thermal Power Plants Based on a Mathematical Model of Cooling Systems{sup 1}

A mathematical model and algorithms are proposed for automatic calculation of the optimum flow rate of cooling water in nuclear and thermal power plants with cooling systems of arbitrary complexity. An unlimited number of configuration and design variants are assumed with the possibility of obtaining a result for any computational time interval, from monthly to hourly. The structural solutions corresponding to an optimum cooling water flow rate can be used for subsequent engineering-economic evaluation of the best cooling system variant. The computerized mathematical model and algorithms make it possible to determine the availability and degree of structural changes for the cooling system in all stages of the life cycle of a plant.

42 ENGINEERING↗

Mathematical Model for Collision–Coalescence Among Inclusions in the Bloom Continuous Caster with M-EMS

Mathematical simulation is an effective tool to analyze the fluid flow and the inclusion behavior in the bloom continuous caster with mold electromagnetic stirring (M-EMS). The mathematical model is applied to the modeling of magnetic field, flow field, and inclusion field. Due to the introduction of Archimedes force, the collision mechanism and inclusion’s slipping velocity should be modified in the inclusion mass and population conservation model. Numerically predicted magnetic field, flow field, and the inclusion spatial distribution conform to the experimental results in the existing literature. Lorentz force plays an important role in the fluid flow, and Archimedes force plays an important role in the inclusion distribution in the continuous caster. Due to Brownian collision, Stokes collision, Archimedes collision, and turbulent collision, the coalescence among inclusions occurs in the bloom continuous caster with M-EMS. Among the four types of collisions, turbulent collision occurs most frequently, followed by Archimedes collision and Stokes collision. The frequency of Brownian collision is several orders of magnitudes smaller and is therefore negligible. The inclusion volume concentration, number density, and characteristic radius exhibit a U-shape in the continuous caster without M-EMS. However, with M-EMS, they exhibit an inverted U-shape.

36 MATERIALS SCIENCE↗

The Oxidation Mechanism of Pure Magnesium Powder Particles: A Mathematical Approach

In this study, the mechanism of nonisothermal oxidation of magnesium powder was determined using a tension analysis, which was performed by mathematical modeling and the finite element method. The results revealed that phase transformation of magnesium hydroxide to magnesium oxide in the oxide layer plays an important role in this process so that formation of magnesium hydroxide in the early stages of oxidation (< 450 °C) leads to the formation of compressive stresses through the oxide layer, and as a result, the beginning of measurable oxidation is delayed. The results obtained by the mathematical model and finite element method were validated by the experimental results.

36 MATERIALS SCIENCE↗

Mathematical analysis of laboratory microbial experiments demonstrating deterministic chaotic dynamics

Presented is a system of four ordinary differential equations and a mathematical analysis of microbiological experiments in a four-component chemostat—nutrient n, rods r, cocci c, and predators p. The analysis is consistent with the conclusion that previous experiments produced features of deterministic chaotic and classical dynamics depending on dilution rate. The surrogate model incorporates as much experimental detail as possible, but necessarily contains unmeasured parameters. The objective is to understand better the differences between model simulations and experimental results in complex microbial populations. The key methodology for simulation of chaotic dynamics, consistent with the measured dilution rate and microbial volume averages, was to cause the preference of p for r vs. c to vary with the r and c concentrations, to make r more competitive for nutrient than c, and to recycle some dying p biomass, leading to a modified version of the Monod kinetics model. Our mathematical model demonstrated that the occurrence of chaotic dynamics requires a predator, p, preference for r versus c to increase significantly with increases in r and c populations. Also included is a discussion of several generalizations of the existing model and a possible involvement of the minimum energy dissipation principle. This principle appears fundamental to thermodynamic systems including living systems. Several new experiments are suggested.

59 BASIC BIOLOGICAL SCIENCES↗

Mathematical Programming Models for Shale Oil & Gas Development: A Review and Perspective

Here, in this paper, we provide a comprehensive review of mathematical programming models for shale oil & gas development, and we offer a perspective on outstanding research opportunities. We distinguish contributions in five major topic areas, namely: (1) development planning, (2) water management, (3) production optimization, (4) supplies, gathering & processing, and (5) life cycle analysis & sustainability. We highlight how various types of mathematical programming models (i.e., linear programs, nonlinear programs, mixed-integer linear programs, mixed-integer nonlinear programs) have been proposed primarily by the Process Systems Engineering community to address the respective decision-making problems, and we highlight instances of successful deployment in industry. Finally, based on a critical assessment of the existing body of work, we identify opportunities for future research across the major topic areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GenASiS Mathematics: Object-oriented manifolds, operations, and solvers for large-scale physics simulations (version 2)

We report GenASiS Mathematics provides modern Fortran classes furnishing extensible object-oriented functionality for the solution of fields governed by selected partial differential equations. The initial release included extensible object-oriented implementations of simple meshes and the evolution of generic conserved currents thereon. This revision - Version 2 of Mathematics - includes significant reorganization and streamlining of these classes, higher-order reconstruction by a different method, a Poisson solver, coarsening to avoid Courant time step limitations near coordinate singularities, and the offloading of computational kernels to GPUs.

97 MATHEMATICS AND COMPUTING↗

Mathematical model of marine diesel engine simulator for a new methodology of self propulsion tests

As a vessel operates in the open seas, a marine diesel engine simulator whose engine rotation is controlled to transmit through propeller shaft is a new methodology for the self propulsion tests to track the fuel saving in a real time. Considering the circumstance, this paper presents the real time of marine diesel engine simulator system to track the real performance of a ship through a computer-simulated model. A mathematical model of marine diesel engine and the propeller are used in the simulation to estimate fuel rate, engine rotating speed, thrust and torque of the propeller thus achieve the target vessel’s speed. The input and output are a real time control system of fuel saving rate and propeller rotating speed representing the marine diesel engine characteristics. The self-propulsion tests in calm waters were conducted using a vessel model to validate the marine diesel engine simulator. The simulator then was used to evaluate the fuel saving by employing a new mathematical model of turbochargers for the marine diesel engine simulator. The control system developed will be beneficial for users as to analyze different condition of vessel’s speed to obtain better characteristics and hence optimize the fuel saving rate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A mathematical model of the passage of an asteroid-comet body through the Earth’s atmosphere

In the paper, a mathematical model and a numerical algorithm are proposed for modeling the complex of phenomena which accompany the passage of a friable asteroid-comet body through the Earth’s atmosphere: the material ablation, the dissociation of molecules, and the radiation. The proposed model is constructed on the basis of the Navier-Stokes equations for viscous heat-conducting gas with an additional equation for the motion and propagation of a friable lumpy-dust material in air. The energy equation is modified for the relation between two its kinds: the usual energy of the translation of molecules (which defines the temperature and pressure) and the combined energy of their rotation, oscillation, electronic excitation, dissociation, and radiation. For the mathematical model of atmosphere, the distribution of density, pressure, and temperature in height is taken as for the standard atmosphere. An asteroid-comet body is taken initially as a round body consisting of a friable lumpy-dust material with corresponding density and significant viscosity which far exceed those for the atmosphere gas. A numerical algorithm is proposed for solving the initial-boundary problem for the extended system of Navier-Stokes equations. The algorithm is the combination of the semi-Lagrangian approximation for Lagrange transport derivatives and the conforming finite element method for other terms. The implementation of these approaches is illustrated by a numerical example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mathematical modeling of deformation of a porous medium, considering its strengthening due to pore collapse

Based on the generalized rheological method, the mathematical model describing small deformations of a single-phase porous medium without regard to the effects of a fluid or gas in pores is constructed. The change in resistance of a material to the external mechanical impacts at the moment of pore collapse is taken into account by means of the von Mises–Schleicher strength condition. In order to consider irreversible deformations, alongside with the classical yield conditions by von Mises and Tresca– Saint-Venant, the special condition modeling the plastic loss of stability of a porous skeleton is used. The random nature of the pore size distribution is taken into account. It is shown that the proposed mathematical model satisfies the principles of thermodynamics of irreversible processes. Phenomenological parameters of the model are determined on the basis of the approximate calculation of the problem on quasi-static loading of a cubic periodicity cell with spherical voids. In the framework of the obtained model, the process of propagation of plane longitudinal waves of the compression in a homogenous porous medium, accompanied by the plastic deformation of a skeleton and the collapse of pores, is analyzed.

42 ENGINEERING↗

Improving Mathematical Exposition of an Industrial-Scale Linear Program

Industrial-scale models require considerable setup time; hence, once built, they are used in myriad ways to consider closely related cases. In practice, the code for these models frequently evolves without appropriate notational choices, largely as a result of the lengthy development time of, and the number of individuals contributing to, their formulation. This leads to inefficiencies and obfuscates model structures that might be leveraged to expedite solutions. In this paper, we advocate for an emerging literature on model formulation “best practices” and present the reformulation of a widely used industrial-scale linear program. The efficient mathematical expression of this linear program, used to plan capacity expansion in the energy sector, allows for greater transparency of model structures and enhanced ability to identify computational performance improvements, as well as a lucid interpretation of its solutions. This type of formulation is employed in several mathematical programming courses at our university as an example of the advantages of best practices; the model more broadly is used widely to inform policy in the U.S. energy sector.

97 MATHEMATICS AND COMPUTING↗

Mathematical Formulation used by MATLAB Code to Convert FTIR Interferograms to Calibrated Spectra

This report discusses the mathematical procedures used to convert raw interferograms from Fourier transform infrared (FTIR) sensors to calibrated spectra. The work discussed in this report was completed as part of the Helios project at Los Alamos National Laboratory. MATLAB code was developed to convert the raw interferograms to calibrated spectra. The report summarizes the developed MATLAB scripts and functions, along with a description of the mathematical methods used by the code. The first step in working with raw interferograms is to convert them to uncalibrated spectra by applying an apodization function to the raw data and then by performing a Fourier transform. The developed MATLAB code also addresses phase error correction by applying the Mertz method. This report provides documentation for the MATLAB scripts.

97 MATHEMATICS AND COMPUTING↗