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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

A Finite Volume Procedure for Thermo-Fluid System Analysis in a Flow Network

This paper describes a finite volume procedure for network flow analysis in a thermofluid system. A flow network is defined as a group of inter-connected control volumes called “nodes” that are connected by “branches”. The mass and energy conservation equations are solved at the nodes and momentum conservation equations are solved at the branches. The flow network also includes solid nodes to account for fluid to solid heat transfer. The heat conduction equation is solved at the solid nodes in conjunction with the flow equations. The properties of a real fluid are calculated using a thermodynamic property program and used in the conservation equations. The system of equations describing the fluid-solid network is solved by a hybrid numerical method that is a combination of the Newton-Raphson and successive substitution method. This procedure has been incorporated into a general-purpose computer program, the Generalized Fluid System Simulation Program, GFSSP. This paper also presents the application and verification of the method by comparison with test data for several applications that include (a) internal flow in a rocket engine turbo-pump, (b) pressurization and loading of a cryogenic propellant tank, (c) fluid transient during sudden opening of valve for priming of an evacuated feed line, and (d) chill down of a cryogenic transfer line with phase change and two phase flows.

Majumdar, Alok↗
DOE OSTI2019

Convex Relaxations of the Network Flow Problem Under Cycle Constraints

In this paper, we consider the problem of optimizing the flows in a lossless flow network with additional nonconvex cycle constraints on nodal variables; such constraints appear in several applications, including electric power, water distribution, and natural gas networks. This problem is a nonconvex version of the minimum-cost network flow problem (NFP), and to solve it, we propose three different approaches. One approach is based on solving a convex approximation of the problem, obtained by augmenting the cost function with an entropy-like term to relax the nonconvex constraints. We show that the approximation error, for which we give an upper bound, can be made small enough for practical use. An alternative approach is to solve the classical NFP, that is, without the cycle constraints, and solve a separate optimization problem afterwards in order to recover the actual flows satisfying the cycle constraints; the solution of this separate problem maximizes the individual entropies of the cycles. The third approach is based on replacing the nonconvex constraint set with a convex inner approximation, which yields a suboptimal solution for the cyclic networks with each edge belonging to at most two cycles. We validate the practical usefulness of the theoretical results through numerical examples, in which we study the standard test systems for water and electric power distribution networks.

42 ENGINEERING↗
DOE OSTI2018

Uniform redundancy allocation maximizes the robustness of flow networks against cascading failures

We study the robustness of flow networks against cascading failures under a partial load redistribution model. In particular, we consider a flow network of N lines with initial loads L 1 ,...,L N and free spaces (i.e., redundant space) S 1 ,...,S N that are independent and identically distributed with joint distribution P LS (x,y) = P[L ≤ x, S ≤ y]. The capacity C i is the maximum load allowed on line i and is given by C i = L i + S i . Furthermore, when a line fails due to overloading, it is removed from the system and (1 – ε) fraction of the load it was carrying is redistributed equally among all remaining lines in the system. The rest (i.e., ε fraction) of the load is assumed to be lost or absorbed, e.g., due to advanced circuitry disconnecting overloaded power lines or an interconnected network or material absorbing a fraction of the flow from overloaded lines. We analyze the robustness of this flow network against random attacks that remove a p fraction of the lines. Our contributions include (i) deriving the final fraction of alive lines n ∞ (p,ε) for all p,εϵ(0,1) and confirming the results via extensive simulations; (ii) showing that partial redistribution might lead to (depending on the parameter 0 < ε ≤ 1) the order of transition at the critical attack size p* changing from first to second-order; and (iii) proving analytically that flow networks achieve maximum robustness [quantified by the area ∫$^{1}_{0}$ n ∞ (p,ε)dp] when all lines have the same free space regardless of their initial load. The optimality of equal free-space allocation is also confirmed on real-world data from the UK National Power Grid.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Hierarchical Network Partitioning for Solution of Potential-Driven, Steady-State Nonlinear Network Flow Equations

The solution of potential-driven steady-state flow in large networks is a task which manifests in various engineering applications, such as transport of natural gas or water through pipeline networks. The resultant system of nonlinear equations depends on the network topology, and in general, there is no numerical algorithm that offers guaranteed convergence to the solution (assuming a solution exists). Some methods offer guarantees in cases where the network topology satisfies certain assumptions, but these methods fail for larger networks. On the other hand, the Newton-Raphson algorithm offers a convergence guarantee if the starting point lies close to the (unknown) solution. It would be advantageous to compute the solution of the large nonlinear system through the solution of smaller nonlinear sub-systems wherein the solution algorithms (Newton-Raphson or otherwise) are more likely to succeed. Here, this letter proposes and describes such a procedure, a hierarchical network partitioning algorithm that enables the solution of large nonlinear systems corresponding to potential-driven steady-state network flow equations.

42 ENGINEERING↗
DOE OSTI2017

Post-Fracturing Experiment Simulation of Hydraulic Fracture Propagation in a Deep Mine Using a Fully Coupled 3D Network-Flow and Quasi-static Discrete Element Model

Aimed at supporting the hydraulic fracturing experiments in a vertical borehole in the Poorman phyllite at approximately 1500 m depth at the Sanford Underground Research Facility (SURF), we perform post-hydraulic fracturing experiment simulations and compare the simulated borehole pressure changes and flow rates with actual measurements using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beam between them. A conjugate 3D flow network based on DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the DEM model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams.

15 GEOTHERMAL ENERGY↗
NASA NTRS2001

Incorporation of Condensation Heat Transfer in a Flow Network Code

In this paper we have investigated the condensation of water vapor in a short tube. A numerical model of condensation heat transfer was incorporated in a flow network code. The flow network code that we have used in this paper is Generalized Fluid System Simulation Program (GFSSP). GFSSP is a finite volume based flow network code. Four different condensation models were presented in the paper. Soliman's correlation has been found to be the most stable in low flow rates which is of particular interest in this application. Another highlight of this investigation is conjugate or coupled heat transfer between solid or fluid. This work was done in support of NASA's International Space Station program.

Anthony, Miranda↗
DOE OSTI2017

Modeling of Hydraulic Fracture Propagation at the kISMET Site Using a Fully Coupled 3D Network-Flow and Quasi- Static Discrete Element Model

Aimed at supporting the design of hydraulic fracturing experiments at the kISMET site, ~1500 m below ground in a deep mine, we performed pre-experimental hydraulic fracturing simulations in order to estimate the breakdown pressure, propagation pressure, fracture geometry, and the magnitude of induced seismicity using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beams between them. A conjugate 3D flow network based on the DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams. In this paper, the 3D hydraulic fracturing model was verified against the analytic solution for a penny-shaped crack model. We applied the model to simulate fracture propagation from a vertical open borehole based on initial estimates of rock mechanical properties and in-situ stress conditions. The breakdown pressure and propagation pressure are directly obtained from the simulation. In addition, the released elastic strain energies of individual fracturing events were calculated and used as a conservative estimate for the magnitudes of the potential induced seismic activities associated with fracturing. The comparisons between model predictions and experimental results are still ongoing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Numerical Solution of the Steady-State Network Flow Equations for a Non-Ideal Gas

Herein we formulate a steady-state network flow problem for non-ideal gas that relates injection rates and nodal pressures in the network to flows in pipes. For this problem, we present and prove a theorem on uniqueness of generalized solution for a broad class of non-ideal pressure-density relations that satisfy a monotonicity property. Further, we develop a Newton-Raphson algorithm for numerical solution of the steady-state problem, which is made possible by a systematic non-dimensionalization of the equations. The developed algorithm has been extensively tested on benchmark instances and shown to converge robustly to a generalized solution. Previous results [1]-[4], indicate that the steady-state network flow equations for an ideal gas are difficult to solve by the Newton-Raphson method because of its extreme sensitivity to the initial guess. In contrast, we find that non-dimensionalization of the steady-state problem is key to robust convergence of the Newton-Raphson method. We identify criteria based on the uniqueness of solutions under which the existence of a non-physical generalized solution found by a non-linear solver implies non-existence of a physical solution, i.e., infeasibility of the problem. Finally, we compare pressure and flow solutions based on ideal and non-ideal equations of state to demonstrate the need to apply the latter in practice. The solver developed in this article is open-source and is made available for both the academic and research communities as well as the industry.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

Schallhorn, Paul↗
DOE OSTI2019

Randomized methods to characterize large-scale vortical flow networks

We demonstrate the effective use of randomized methods for linear algebra to perform network-based analysis of complex vortical flows. Network theoretic approaches can reveal the connectivity structures among a set of vortical elements and analyze their collective dynamics. These approaches have recently been generalized to analyze high-dimensional turbulent flows, for which network computations can become prohibitively expensive. In this work, we propose efficient methods to approximate network quantities, such as the leading eigendecomposition of the adjacency matrix, using randomized methods. Specifically, we use the Nyström method to approximate the leading eigenvalues and eigenvectors, achieving significant computational savings and reduced memory requirements. The effectiveness of the proposed technique is demonstrated on two high-dimensional flow fields: two-dimensional flow past an airfoil and two-dimensional turbulence. We find that quasi-uniform column sampling outperforms uniform column sampling, while both feature the same computational complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Systems and methods for detecting large network flows

In a system for efficiently detecting large/elephant flows in a network, the rate at which the received packets are sampled is adjusted according to the measured heavy tailedness of the arriving traffic, such that the measured heavy tailedness reaches a specified target level. The heavy tailedness is measured using the estimated sizes of different flows associated with the arriving packets. When the measured heavy tailedness reaches and remains at the specified target level, the flows having the largest estimated sizes are likely to be the largest/elephant flows in the network.

Ros-Giralt, Jordi↗
DOE OSTI2019

Energy flow networks: deep sets for particle jets

A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event is intrinsically a variable-length unordered set of particles, we build upon recent machine learning efforts to learn directly from sets of features or “point clouds”. Adapting and specializing the “Deep Sets” framework to particle physics, we introduce Energy Flow Networks, which respect infrared and collinear safety by construction. We also develop Particle Flow Networks, which allow for general energy dependence and the inclusion of additional particle-level information such as charge and flavor. These networks feature a per-particle internal (latent) representation, and summing over all particles yields an overall event-level latent representation. We show how this latent space decomposition unifies existing event representations based on detector images and radiation moments. To demonstrate the power and simplicity of this set-based approach, we apply these networks to the collider task of discriminating quark jets from gluon jets, finding similar or improved performance compared to existing methods. We also show how the learned event representation can be directly visualized, providing insight into the inner workings of the model. These architectures lend themselves to efficiently processing and analyzing events for a wide variety of tasks at the Large Hadron Collider. Implementations and examples of our architectures are available online in our EnergyFlow package.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1973

Computer program for compressible flow network analysis

Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

Wilton, M. E.↗
NASA NTRS1972

A feedback control model for network flow with multiple pure time delays

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

Press, J.↗
NASA NTRS1999

Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

Schallhorn, Paul↗
NASA NTRS2009

Serial Network Flow Monitor

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

Robinson, Julie A.↗