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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Mathematical Model of Oxygen Transport in Skeletal Muscle During Hindlimb Unloading

During hindlimb unloading (HU) dramatic fluid shifts occur within minutes of the suspension, leading to a less precise matching of blood flow to O2 demands of skeletal muscle. Vascular resistance directs blood away from certain muscles, such as the soleus (SOL). The muscle volume gradually reduces in these muscles so that eventually the relative blood flow returns to normal. It is generally believed that muscle volume change is not due to O2 depletion, but a consequence of disuse. However, the volume of the unloaded rat muscle declines over the course of weeks, whereas the redistribution of blood flow occurs immediately. Using a Krogh Cylinder Model, the distribution of O2 was predicted in two skeletal muscles: SOL and gastrocnemius (GAS). Effects of the muscle blood flow, volume, capillary density, and O2 uptake, are included to calculate the pO2 at rest and after 10 min and 15 days of unloading. The model predicts that 32 percent of the SOL muscle tissue has a pO2 1.25 mm Hg within 10 min, whereas the GAS maintains normal O2 levels, and that equilibrium is reached only as the SOL muscle cells degenerate. The results provide evidence that there is an inadequate O2 supply to the mitochondria in the SOL muscle after 10 min HU.

Mathematical models↗
NASA NTRS2026

Mathematical Model of a Regenerative Fuel Cell for System Optimization

This thesis developed a system-level optimization model of a regenerative fuel cell (RFC) system for long-duration, off-world energy storage applications. Prior RFC design studies have typically been limited to reduced parameter sets and simplified constraints due to computational limitations relative to the number of relevant degrees of freedom. As a result, important nonlinear interactions between subsystems have not been fully captured. This work began to address that gap by developing a higher-fidelity, nonlinear optimization framework that incorporates a broader set of design variables and coupled constraints, enabling a multidimensional model that captures the coupled behavior of RFC subsystems and demonstrates the feasibility of applying optimization to such systems. An expanded system-level optimization approach was established that captures interactions between electrochemical performance, structural requirements, and storage design. This enabled a more comprehensive evaluation of trade-offs than conventional formulations. The model integrates four coupled subsystems: a fuel cell, an electrolyzer, reactant gas, and high-pressure storage tanks, and was formulated to accommodate a wide range of mission parameters, including operational time and required output power. It incorporates constraints on available solar array power, reactant mass balance between production and consumption, and pressure-dependent storage requirements. To enable reliable convergence, the optimization problem was reformulated to reduce dimensionality and improve numerical stability, with subsystem models organized for efficient evaluation. Problem dimensionality was reduced by consolidating lower-level design variables into higher-level representative quantities, and subsystem behavior was evaluated within the optimization loop. A multi-start initialization strategy was employed to mitigate sensitivity to local minima and improve solution quality, while nonlinear relationships were solved using robust numerical methods. The results showed that convergence was achieved across a range of required output power values. Specific energy reached a maximum at a critical mission power level, where the electrolyzer power matched the available solar input and operated near its voltage and current density limits. Beyond this point, further increases in required power resulted in less mass-efficient operation, increasing total system mass and reducing overall performance. The developed model represents an advancement in RFC system-level optimization by enabling analysis of a broader and more tightly coupled design space than previous considerations. While convergence behavior and computational cost remain challenges, the methods introduced improve solvability and allow inclusion of additional design variables with minimal loss of physical fidelity. However, the numerical results should not be interpreted as definitive design recommendations, as the model includes simplifying assumptions and omits several higher-order effects. Future work should extend this framework by incorporating additional subsystems and loss mechanisms, such as thermal management, parasitic power consumption, and reactant losses, to improve fidelity and ensure more representative design conclusions.

Electrochemistry↗
DOE OSTI2013

MATHEMATICAL FRAMEWORK FOR THE ANALYSIS OF DYNAMC STOCHASTIC SYSTEMS WITH THE RAVEN CODE

RAVEN (Reactor Analysis and Virtual control Environment) is a software code under development at Idaho National Laboratory aimed at performing probabilistic risk assessment and uncertainty quantification using RELAP-7, for which it acts also as a simulation controller. In this paper we will present the equations characterizing a dynamic stochastic system and we will then discuss the behavior of each stochastic term and how it is accounted for in the RAVEN software design. Moreover we will present preliminary results of the implementation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Mathematical modeling of cold cap: Effect of bubbling on melting rate

The rate of melting is a primary concern in the vitrification of radioactive wastes because it directly influences the life cycle of nuclear waste cleanup efforts. To increase glass melting performance, experimental and industrial all-electric waste glass melters employ various melt-rate enhancement techniques, the most prominent being the application of bubblers submerged into molten glass. This study investigates various ways in which bubbling affects melting rate in a waste glass melter. Using the recently developed cold cap model, we suggest that forced convection of molten glass, which increases the cold cap bottom temperature, is the main factor. Other effects, such as stirring the feed into molten glass or reducing the insulating effect of foaming, also play a role.

bubbling↗
DOE OSTI2019

101 Careers in Mathematics: Emilie Purvine

This short chapter describes my career at PNNL including how I got there, day-to-day life, the PNNL scientific environment, and advice for students.

careers, STEM Outreach, mathematics↗
DOE OSTI2022

Mathematical Tools for the Analysis of Periodic and Aperiodic Grid Signals

Numerous sensing techniques and instrumentation are used in determining the state of the electric grid. Coupled with such measurements are the methods and analysis tools used. The parameters of interest result in both periodic and aperiodic signals. An examination of appropriate analysis tools is presented

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Interpretation of experimental data on safety parameters from standpoint of mathematical nuclear reactor theory

The paper deals with the problem of correct processing of experimental information for unambiguous determination of current reactivity value. The methodology for reactivity determination that is based on spectral decomposition of the solution obtained for non-stationary equation of neutron transport is presented. The proposed spectral projection algorithm takes into consideration the effects related with space-time re-distribution of neutron field and thus excludes the main systematic error and increases accuracy of current reactivity values. The paper presents the results of model calculations, demonstrating the effectiveness of the proposed method. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗