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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

Experimental measurements and mathematical modeling of cold plate for aviation thermal management

Herein, this study, which has been motivated by the recent applications of the cold plate device in aviation thermal management, reports on physics-based mathematical models derived from the conservation laws of mass, momentum, and energy, and empiricism-based models. One of the objectives of the present work is to report on an elaborate and successful experimental work carried out on an additively manufactured device for the purpose of rigorously validating the numerical predictions. The excellent agreement between the numerical predictions and measured performance provides much needed confidence in the implementation, in the software package, of the offset-strip fin passage correlations, as well as in the software implementation of user-defined wavy fin correlations for aerospace heat exchangers and cold plates operating with ram air at Reynolds numbers below 8000. The contributions of this work can also be found in the development of a new and accurate thermal-hydraulic analysis procedure, referred to in this paper as plate-fin analogy. Results from this procedure are compared with those from thermal resistance network. The comparative study in this paper of the bulk and discrete enthalpy flux method is also new, as is the relative assessment of four off-set strip fin thermal-hydraulic models.

42 ENGINEERING↗

Review—Development of Highly Active and Durable Hybrid Compressive Platinum Lattice Catalysts for Polymer Electrolyte Membrane Fuel Cells: Mathematical Modeling and Experimental Work

This review provides a comprehensive overview on the development of highly active and durable platinum catalysts with ultra-low Pt loadings for polymer electrolyte membrane fuel cells (PEMFCs) through a combined mathematical modeling and experimental work. First, simulation techniques were applied to evaluate the validity of the Tafel approximation for the calculation of the mass activity (MA) and specific activity (SA). A one-dimensional agglomeration model was developed and solved to understand the effects of exchange current density, porosity, agglomerate size, Nafion ® film thickness, and Pt loading on the MA and SA. High porosity (> 60%) and agglomerations at high Pt loadings cause the loss of the Tafel approximation and consequently the decrease in MA and SA. A new structure parameter was introduced to estimate the real porous structure using the fractal theory. The volumetric catalyst density was corrected by the fractal dimension (measured by Hg porosimetry), which gave a good agreement with the experimental values. The loading-dependent Tafel equation was then derived, which contains both the utilization and the non-linear scaling factor. Second, activated carbon composite support (ACCS) with optimized surface area, porosity, pore size, and pore size distribution was developed. The hydrophilic/hydrophobic ratio, structural properties (amorphous/crystalline ratio), and the number of active sites were optimized through metal-catalyzed pyrolysis. Stability of ACCS and Pt/ACCS were evaluated using an accelerated stress test (AST). The results indicated that Pt/ACCS showed no significant loss of MA and power density after 5,000 cycles at 1.0–1.5 V, while the commercial Pt/C catalysts showed drastic losses of MA and power density. Finally, monolayers of compressed Pt (core–shell-type Pt 3 Co 1 ) catalysts were structured by diffusing Co atoms (previously embedded in ACCS) into Pt. Compressive Pt lattice (Pt * ) catalysts were synthesized through an annealing procedure developed at the University of South Carolina (USC). The Pt * /ACCS catalyst showed high initial power density (rated) of 0.174 g Pt kW −1 and high stability (24 mV loss) at 0.8 A cm −2 after 30,000 cycles (0.6–1.0 V). The outstanding performance of Pt * /ACCS is due to the synergistic effect of ACCS and compressive Pt * lattice.

25 ENERGY STORAGE↗

Comment on “Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production” by Baroukh et al. [Curr Opin Biotechnol. 2015, 33:198–205]

This letter concerns an article recently published in Current Opinion in Biotechnology by Baroukh et al. entitled "Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production" (2015 Mar 26; 33:198-205). The issue we wish to bring to light is the authors’ claim that dynamic metabolic models including Hybrid Cybernetic Model (HCM) (Kim et al., 2008; Song et al., 2009) and Lumped HCM (L-HCM) (Song and Ramkrishna, 2010; 2011) are based on the balanced growth hypothesis so that they are unable to simulate the accumulation of intracellular metabolites. This is a misrepresentation of these models due to the following reasons.

balanced growth↗

RELAP-7 Progress Report: A Mathematical Model for 1-D Compressible, Single-Phase Flow Through a Branching Junction

In the literature, the abundance of pipe network junction models, as well as inclusion of dissipative losses between connected pipes with loss coefficients, has been treated using the incompressible flow assumption of constant density. This approach is fundamentally, physically wrong for compressible flow with density change. This report introduces a mathematical modeling approach for general junctions in piping network systems for which the transient flows are compressible and single-phase. The junction could be as simple as a 1-pipe input and 1-pipe output with differing pipe cross-sectional areas for which a dissipative loss is necessary, or it could include an active component, between an inlet pipe and an outlet pipe, such as a pump or turbine. In this report, discussion will be limited to the former. A more general branching junction connecting an arbitrary number of pipes with transient, 1-D compressible single-phase flows is also presented. These models will be developed in a manner consistent with the use of a general equation of state like, for example, the recent Spline-Based Table Look-up method [1] for incorporating the IAPWS-95 formulation [2] to give accurate and efficient calculations for properties for water and steam with RELAP-7 [3].

42 ENGINEERING↗

Coupled CFD and chemical-kinetics simulations of cellulosic-biomass enzymatic hydrolysis: Mathematical-model development and validation

Computational simulations of cellulosic-biomass enzymatic hydrolysis using a computational-fluid-dynamics (CFD) model coupled to a chemical-kinetics model are presented in this work. A time-step sub-cycling strategy was used to circumvent large disparities in time scales with respect to transport physics and chemical kinetics. The unknown reaction and transport parameters in the mathematical model were first fit to two canonical experiments: a well-mixed case that was limited by reaction kinetics and a settled-solids case that was limited by transport. Here, the model was then validated against a benchtop experiment for an intermediate-mixing scenario, for which simulation results were in reasonable agreement with experimentally measured cellulose conversions. Settling of cellulose particles and diffusion of enzymes determine overall conversion rates for lower mixing rates, while reaction rates dominate conversion at higher mixing rates for which greater homogenization of substrates is achieved.

09 BIOMASS FUELS↗

Mathematical modeling of within-host Zika virus dynamics

Recent Zika virus outbreaks have been associated with severe outcomes, especially during pregnancy. A great deal of effort has been put toward understanding this virus, particularly the immune mechanisms responsible for rapid viral control in the majority of infections. Identifying and understanding the key mechanisms of immune control will provide the foundation for the development of effective vaccines and antiviral therapy. In this paper, we outline a mathematical modeling approach for analyzing the within-host dynamics of Zika virus, and we describe how these models can be used to understand key aspects of the viral life cycle and to predict antiviral efficacy.

60 APPLIED LIFE SCIENCES↗

Mathematical Modeling of Electrochemical Flow Capacitors

Electrochemical flow capacitors (EFCs) for grid-scale energy storage are a new technology that is beginning to receive interest. Prediction of the expected performance of such systems is important as modeling can be a useful avenue in the search for design improvements. Models based off of circuit analogues exist to predict EFC performance, but these suffer from deficiencies (e.g. a multitude of fitting constants that are required and the ability to analyze only one spatial direction at a time). In this paper mathematical models based off of three-dimensional macroscopic balances (similar to models for porous electrodes) are reported. Unlike existing three-dimensional porous electrode-based approaches for modeling slurry electrodes, advection (i.e., transport associated with bulk fluid motion) of the overpotential is included in order to account for the surface charge at the interface between flowing particles and the electrolyte. Doing so leads to the presence of overpotential boundary layers that control the performance of EFCs. These models were used to predict the charging behavior of an EFC under both flowing and non-flowing conditions. Agreement with experimental data was good, including proper prediction of the steady-state current that is achieved during charging of a flowing EFC. (C) The Author(s) 2015. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa@electrochem.org. All rights reserved.

Hoyt, NC↗

Mathematical Modeling of Liquid-Phase Alkylation of Benzene with Ethylene Considering the Process Unsteadiness

Ethylbenzene is a key intermediate in the manufacture of styrene that is an important industrial monomer. Ethylbenzene is produced by benzene alkylation using either gas-phase or liquid-phase methods. The liquid-phase alkylation that uses liquid acidic catalysts needs to be improved. We develop a mathematical model for the liquid-phase benzene alkylation. The reaction scheme, designed with a due analysis of desired and side reactions, and with the analysis of the formation of deactivating agents, reflects, in particular, the influence of the concentration of heavy hydrocarbons on the catalyst activity. The account of the catalyst deactivation by heavy alkylaromatics allows predictions of the temporal changes in the outputs of the alkylation process. In particular, the decrease of the ethylbenzene concentration by 2–3 wt % and increase of the polyalkylate outlet concentration by 1.5–2 wt % are the results of the catalyst deactivation. These effects, however, can be compensated by 1.3-time increase of polyalkylate supply and by the temperature increase up to 398 K. Finally, the calculations also show that it is possible to decrease the supply of fresh catalyst from 0.498 to 0.472 t/hour without loss in the yield of ethylbenzene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mathematical modelling the pathway of genomic instability in lung cancer

Genomic instability plays a significant role in lung cancer. Although substantial research has been conducted using both clinical and theoretical studies, it is still a hotly debated issue to whether genomic instability is necessary or whether genomic instability precedes oncogenes activation and tumor suppressor genes inactivation for lung cancer. In response to this issue, we come up with a mathematical model incorporating effects of genomic instability to investigate the genomic instability pathway of human lung cancer. The presented model are applied to match the incidence rate data of lung cancer from the Life Span Study cohort of the atomic bomb survivors in Nagasaki and Hiroshima and the Surveillance Epidemiology and End Results registry in the United States. Model results suggest that genomic instability is necessary in the tumorigenesis of lung cancer, and genomic instability has no significant impact on the net proliferation rate of cells by statistical criteria. By comparing the results of the LSS data to those of the SEER data, we conclude that the genomic instability pathway exhibits a sensitivity to radiation exposure, more intensive in male patients.

60 APPLIED LIFE SCIENCES↗

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4 + and CD8 + T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

60 APPLIED LIFE SCIENCES↗

Mathematical Model for Li-S Cell with Shuttling-Induced Capacity Loss Approximation

Lithium sulfur (Li-S) batteries have the potential to outperform the current lithium ion batteries and transform the technology of the future. However, dissolution, diffusion, and shuttling of the dissolved polysulfides result in parasitic reactions and substantial capacity loss. To provide a better understanding of the shuttling process, a 1D porous electrode mathematical model has been developed in this paper. An approximation method is used to account for the shuttling-induced capacity loss by adding an extra source/sink term in the material balance equations for the species involved in the parasitic reactions. Shuttling constants used in the source terms can be determined by fitting the model predictions to the experimental measurements. Here, the results showed that by including the approximation method, the model was able to predict the active material loss and the continuous decrease of volume fractions of Li 2 S on the cathode surface. The model sheds light on the capacity loss mechanism occurring inside the cell as a result of the shuttling of polysulfides.

25 ENERGY STORAGE↗

Mathematical model of broadly reactive plasma cell production

Strain-specific plasma cells are capable of producing neutralizing antibodies that are essential for clearance of challenging pathogens. These neutralizing antibodies also function as a main defense against disease establishment in a host. However, when a rapidly mutating pathogen infects a host, successful control of the invasion requires shifting the production of plasma cells from strain-specific to broadly reactive. In this study, we develop a mathematical model of germinal center dynamics and use it to predict the events that lead to improved breadth of the plasma cell response. We examine scenarios that lead to germinal centers that are composed of B-cells that come from a single strain-specific clone, a single broadly reactive clone or both clones. We find that the initial B-cell clonal composition, T-follicular helper cell signaling, increased rounds of productive somatic hypermutation, and B-cell selection strength are among the mechanisms differentiating between strain-specific and broadly reactive plasma cell production during infections. Understanding the contribution of these factors to emergence of breadth may assist in boosting broadly reactive plasma cells production.

59 BASIC BIOLOGICAL SCIENCES↗

TU-CD-304-05: 4Ï€ Non-Coplanar Radiotherapy: From Mathematical Modeling to Clinical Implementation

Purpose: To develop and clinically implement 4π radiotherapy, an inverse optimization platform that maximally utilizes non-coplanar intensity modulated radiotherapy (IMRT) beams to significantly improve critical organ sparing. Methods: A 3D scanner was used to digitize the human and phantom subject surfaces, which were positioned in the computer assisted design (CAD) model of a TrueBeam machine to create a virtual geometrical model, based on which, the feasible beam space was calculated for different tumor locations. Beamlets were computed for all feasible beams using convolution/superposition. A column generation algorithm was employed to optimize patient specific beam orientations and fluence maps. Optimal routing through all selected beams were calculated by a level set method. The resultant plans were converted to XML files and delivered to phantoms in the TrueBeam developer mode. Finally, 4π plans were recomputed in Eclipse and manually delivered to recurrent GBM patients. Results: Compared to IMRT utilizing manually selected beams and volumetric modulated arc therapy plans, markedly improved dosimetry was observed using 4π for the brain, head and neck, liver, lung, and prostate patients. The improvements were due to significantly improved conformality and reduced high dose spillage to organs mediolateral to the PTV. The virtual geometrical model was experimentally validated. Safety margins with 99.9% confidence in collision avoidance were included to the model based model accuracy estimates determined via 300 physical machine to phantom distance measurements. Automated delivery in the developer mode was completed in 10 minutes and collision free. Manual 4 π treatment on the GBM cases resulted in significant brainstem sparing and took 35–45 minutes including multiple images, which showed submillimeter cranial intrafractional motion. Conclusion: The mathematical modeling utilized in 4π is accurate to create and guide highly complex non-coplanar IMRT treatments that consistently and significantly outperform human-operator-created plans. Deliverability of such plans is clinically demonstrated. This work is funded by Varian Medical Systems and the NSF Graduate Research Fellowship DGE-1144087.

60 APPLIED LIFE SCIENCES↗

Mathematical modeling of a proton-conducting solid oxide fuel cell with current leakage

Here, a framework of charge transports in proton-conducting solid oxide fuel cells (H-SOFCs) with considering current leakage is developed by assuming four electrode reactions. Current leakage happens when electron holes pass through the electrolyte and combine with electrons at the anode side. An analytical solution of leakage currents is proposed depending on the Nernst-Planck equation. On the basis of the analysis expression, a mathematical model of H-SOFCs is proposed, which can provide the information about current-voltage characteristics, leakage current density, Faraday and energy efficiencies. Moreover, H-SOFCs with the BaZr 0.8 Y 0.2 O 3 electrolyte are fabricated and tested, and the proposed model well reproduces the experimental data. The simulation results indicate that current leakage primarily affects the H-SOFC performance when the output voltage is close to the OCV. Both Faraday efficiencies and energy efficiencies decrease with increasing operating temperatures due to the existence of current leakage.

25 ENERGY STORAGE↗

Effect of Antigen Shedding on Targeted Delivery of Immunotoxins in Solid Tumors from a Mathematical Model

Most cancer-specific antigens used as targets of antibody-drug conjugates and immunotoxins are shed from the cell surface (Zhang & Pastan (2008) Clin. Cancer Res. 14: 7981-7986), although at widely varying rates and by different mechanisms (Dello Sbarba & Rovida (2002) Biol. Chem. 383: 69–83). Why many cancer-specific antigens are shed and how the shedding affects delivery efficiency of antibody-based protein drugs are poorly understood questions at present. Before a detailed numerical study, it was assumed that antigen shedding would reduce the efficacy of antibody-drug conjugates and immunotoxins. However, our previous study using a comprehensive mathematical model showed that antigen shedding can significantly improve the efficacy of the mesothelin-binding immunotoxin, SS1P (anti-mesothelin-Fv-PE38), and suggested that receptor shedding can be a general mechanism for enhancing the effect of inter-cellular signaling molecules. Here, we improved this model and applied it to both SS1P and another recombinant immunotoxin, LMB-2, which targets CD25. We show that the effect of antigen shedding is influenced by a number of factors including the number of antigen molecules on the cell surface and the endocytosis rate. The high shedding rate of mesothelin is beneficial for SS1P, for which the antigen is large in number and endocytosed rapidly. On the other hand, the slow shedding of CD25 is beneficial for LMB-2, for which the antigen is small in number and endocytosed slowly.

60 APPLIED LIFE SCIENCES↗

A mathematical model to systematically align superconducting radio frequency cavities employing the serial robot kinematic theory

In Superconducting Radio Frequency (SRF) cryomodules, precise alignment of cavities is necessary to ensure high beam quality and to increase the overall energetic efficiency. In the SSR1 (Single Spoke Resonator 1) cryomodule, the cavities are aligned using a system of seven screws which allows to control five Degree of Freedoms (DOFs). The relation between the rotation of each screw and the movement of the cavity is non-linear, thus the aligning process, currently based on a trial-and-error procedure, can be time consuming and affected by human error. In this paper the design of an alignment mathematical model, based on the serial robot kinematic, is described and tested on a SSR1 cavity. Furthermore, the goal of the proposed model is to give a step by step operational procedure that bring the SSR1 cavity to a desired location reducing the uncertainties related to the current operator-driven alignment process.

43 PARTICLE ACCELERATORS↗

(Invited) Continuum Mathematical Modeling of Water Electrolysis: A Tutorial

Widespread use of hydrogen energy is contingent on the development of reliable and economical sources of hydrogen. Electrolysis from renewably-derived low-carbon electricity is a potentially viable method of hydrogen generation. Prime among the electrolysis technologies are those utilizing ion-conducting polymers (ionomers) including proton-exchange-membrane water electrolyzer (PEMWE). However, these technologies need to exhibit increased efficiency, performance, and durability to become commercially viable. Like most electrochemical devices, PEMWEs involve multiple components (e.g., catalyst, ionomer, transport layers, membrane, plates) and multiple phases, with phenomena occurring across different time and length scales. Furthermore, it is difficult to experimentally probe many of the species and phenomena during operation. Thus, mathematical modeling at the continuum level has been an invaluable aid in exploring, understanding, and optimizing PEMWE cell and components. Furthermore, this is especially true in the highly coupled and complex physics and chemistries that occur with the membrane-electrode assembly (MEA). The physics in a typical volume-averaged non-isothermal model include multiphase transport in porous media, concentrated-solution theory, Ohm's Law, and Butler-Volmer kinetics, and ion, gas, and water transport in the ionomer.

Dizon, Arthur↗