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At least 613 records · Page 34

Low order dynamical models for mixing layers

The goal of this project was to investigate the feasibility of developing useful low order dynamical systems to allow one to determine cheaply the effect of various initial conditions on the evolution of mixing layers. A mathematically rigorous approach for a time evolving base flow as found in a mixing layer seems to be the singular value decomposition of the linear operator transforming some initial perturbations into the solution at a given later time. Unfortunately, this is very costly, if at all feasible, and only deals with the linear evolution of a disturbance. A different approach based on weakly nonlinear analysis was attempted, but numerous difficulties were encountered. Several formulations were proposed which may be ill-posed. The reasons for this possible failure of the attempted approach is related to the fundamental limitations of weakly nonlinear analysis. The clarification of these issues is attempted in this report.

Riahi, D. N.↗

Dynamic modelling and analysis of a magnetically suspended flexible rotor

A 12-state lumped-element model is presented for a flexible rotor supported by two attractive force electromagnetic journal bearings. The rotor is modeled as a rigid disk with radial mass unbalance mounted on a flexible, massless shaft with internal damping (Jeffcott rotor). The disk is offset axially from the midspan of the shaft. Bearing dynamics in each radial direction are modeled as a parallel combination of a negative (unstable) spring and a linear current-to-force actuator. The model includes translation and rotation of the rigid mass and the first and second bending models of the flexible shaft, and it simultaneously includes internal shaft damping, gyroscopic effects, and the unstable nature of the attractive force magnetic bearings. The model is used to analyze the dependence of the system transmission zeros and open-loop poles on system parameters. The dominant open-loop poles occur in stable/unstable pairs with bandwidth dependent on the ratios of bearing (unstable) stiffnesses to rotor mass and damping dependent on the shaft spin rate. The zeros occur in complex conjugate pairs with bandwidth dependent on the ratios of shaft stiffness to rotor mass and damping dependent on the shaft spin rate. Some of the transmission zeros are non-minimum phase when the spin rate exceeds the shaft critical speed. The transmission zeros and open-loop poles impact the design of magnetic bearing control systems. The minimum loop cross-over frequency of the closed-loop system is the speed of the unstable open-loop poles. For the supercritical shaft spin rates, the presence of non-minimum phase zeros limits the distribution rejection achievable at frequencies near or above the shaft critical speed. Since non-minimum phase transmission zeros can only be changed by changing the system inputs and/or outputs, closed-loop performance is limited for supercritical spin rates unless additional force or torque actuators are added.

Mccallum, Duncan C.↗

Constrained optimization framework for interface-aware sub-scale dynamics models for voids closure in Lagrangian hydrodynamics

In hydrocodes, voids are used to represent vacuum and model free boundaries between vacuum and real materials. We give a systematic description of a new treatment of void closure in the framework of the multimaterial arbitrary Lagrangian–Eulerian (ALE) methods. This includes a new formulation of the interface-aware sub-scale-dynamics (IA-SSD) closure model for multimaterial cells with voids, which is used in the Lagrangian stage of our indirect ALE scheme. The results of the comprehensive testing of the new model are presented for one- and two-dimensional multimaterial calculations in the presence of voids. Finally, we also present a sneak peek of a realistic shaped charge calculation in the presence of voids and solids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancing EnergyPlus capabilities to model dynamic building envelopes using python plugin

Nearly half of the energy consumption in the United States is related to buildings, resulting in an urgent need to develop innovative technologies to improve building energy efficiency. Dynamic building envelopes, comprising switchable insulation and thermal energy storage materials, have been proposed recently as a promising solution to reduce buildings' heating and cooling loads by thermally coupling the indoor environment with the ambient environment when beneficial while decoupling them when outdoor conditions are not favorable. Although various related technologies are still underway, the whole-building energy modeling tools, like EnergyPlus, do not have the capability to simulate the transient and dynamic nature of dynamic envelope materials and components to accurately predict their impact on building energy use. The objective of this study is to formulate a method in EnergyPlus simulation engine to model multilayer envelopes, comprising dynamic building materials with variable thermophysical properties, and discuss the changes made to the program using a Python plugin. Furthermore, the thermal performance of the dynamic envelopes using the proposed method is compared and verified with the results from a well-established commercial code, COMSOL Multiphysics. A parametric assessment is also conducted to evaluate the energy efficiency benefits of dynamic envelopes in a single-family residential building, demonstrating total annual energy savings up to 11.6 %, when a dynamic envelope operates alone, and up to 18.2 % when it is combined with a thin layer of phase change material as a thermal storage medium. Finally, a United States wide energy efficiency assessment is presented to showcase the geographical spread of the energy savings. The method designed and implemented in this study provides the researchers with the ability to implement their dynamic insulation methods in EnergyPlus and evaluate the whole building energy impact.

25 ENERGY STORAGE↗

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States; NREL (National Renewable Energy Laboratory)

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States: Preprint

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

User's instructions for the Guyton circulatory dynamics model using the Univac 1110 batch and demand processing (with graphic capabilities)

The model presents a systems analysis of a human circulatory regulation based almost entirely on experimental data and cumulative present knowledge of the many facets of the circulatory system. The model itself consists of eighteen different major systems that enter into circulatory control. These systems are grouped into sixteen distinct subprograms that are melded together to form the total model. The model develops circulatory and fluid regulation in a simultaneous manner. Thus, the effects of hormonal and autonomic control, electrolyte regulation, and excretory dynamics are all important and are all included in the model.

Archer, G. T.↗

Atomistic and cluster dynamics modeling of fission gas (Xe) diffusivity in TRISO fuel kernels

TRISO fuel particles are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The UCO fuel kernel consists of a uranium dioxide (UO) and uranium carbide mixture. The addition of UC helps suppress the formation of carbon monoxide gas, which led to failures during initial TRISO development. The addition of uranium carbide alters the chemistry of the UO kernel, which is known to influence performance parameters such as fission gas diffusivity, although the impact has not been quantified and no models exist that take the change in chemistry into account. Therefore, better understanding and more accurate models of the impact of chemistry on fuel performance are of high priority. In this paper, a first-principles density functional theory (DFT) and empirical potential based multi-scale study has been carried out to model the diffusivity of fission gas xenon (Xe) in UCO TRISO fuel kernels. The focus is on the UO component in the UCO fuel kernels, as that represents the largest volume fraction of the fuel kernels. The study relies on DFT and empirical potential calculations to determine Xe and point defect properties, which are then used in thermodynamic and kinetic models to predict diffusion for intrinsic conditions. In addition, the information is utilized in cluster dynamics simulations using the Centipede code to estimate the impact of irradiation on defect transport. Additionally, the presence of UC or UC in the UCO fuel kernels is shown to have a substantial impact on the UO non-stoichiometry by inducing oxygen vacancies and driving UO sub-stoichiometric, which causes much slower Xe diffusion in UCO compared to light water reactor UO fuel. The application of this model in fuel performance simulations using the Bison code is also demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Flight Dynamics Model for a Multi-Actuated Flexible Rocket Vehicle

A comprehensive set of motion equations for a multi-actuated flight vehicle is presented. The dynamics are derived from a vector approach that generalizes the classical linear perturbation equations for flexible launch vehicles into a coupled three-dimensional model. The effects of nozzle and aerosurface inertial coupling, sloshing propellant, and elasticity are incorporated without restrictions on the position, orientation, or number of model elements. The present formulation is well suited to matrix implementation for large-scale linear stability and sensitivity analysis and is also shown to be extensible to nonlinear time-domain simulation through the application of a special form of Lagrange s equations in quasi-coordinates. The model is validated through frequency-domain response comparison with a high-fidelity planar implementation.

Orr, Jeb S.↗

Dynamic Modeling and Grid Interaction of a Tidal and River Generator

This presentation provides a high-level overview of the deployment of a river generator installed in a small system. The turbine dynamics of a river generator, electrical generator, and power converter are modeled in detail. Various simulations can be exercised, and the impact of different control algorithms, failures of power switches, and corresponding impacts can be examined.

13 HYDRO ENERGY↗

PLASMA INSTABILITIES IN THE CONTEXT OF CURRENT HELIUM SEDIMENTATION MODELS: DYNAMICAL IMPLICATIONS FOR THE ICM IN GALAXY CLUSTERS

Understanding whether Helium can sediment to the core of galaxy clusters is important for a number of problems in cosmology and astrophysics. All current models addressing this question are one-dimensional and do not account for the fact that magnetic fields can effectively channel ions and electrons, leading to anisotropic transport of momentum, heat, and particle diffusion in the weakly collisional intracluster medium (ICM). This anisotropy can lead to a wide variety of instabilities, which could be relevant for understanding the dynamics of heterogeneous media. In this paper, we consider the radial temperature and composition profiles as obtained from a state-of-the-art Helium sedimentation model and analyze its stability properties. We find that the associated radial profiles are unstable to different kinds of instabilities depending on the magnetic field orientation at all radii. The fastest growing modes are usually related to generalizations of the magnetothermal instability (MTI) and the heat-flux-driven buoyancy instability which operate in heterogeneous media. We find that the effect of sedimentation is to increase (decrease) the predicted growth rates in the inner (outer) cluster region. The unstable modes grow quickly compared to the sedimentation timescale. This suggests that the composition gradients as inferred from sedimentation models, which do not fully account for the anisotropic character of the weakly collisional environment, might not be very robust. Our results emphasize the subtleties involved in understanding the gas dynamics of the ICM and argue for the need of a comprehensive approach to address the issue of Helium sedimentation beyond current models.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamic Modeling and Characterization of Nuclear-grade Graphite

Idaho National Labs serves as the spearhead for many innovative energy solutions to the world's energy crisis. One such solution is the INL's Microreactor which is designed to deploy to extreme/remote environments where other sources of power are either unavailable or unreliable. In order to best design these energy solutions for their operational environments, it is crucial to understand how the design, components, and materials will respond to the environmental conditions. One key material in these innovative designs is a nuclear-grade graphite known as PCEA. This study examines the behavior of PCEA graphite under dynamic loading, similar to that which may occur in extreme environments. The objective is to characterize the dynamic behavior and produce an accurate, reliable constitutive model suitable for use in simulation tools such as INL's MOOSE. Graphite specimens were tested using a Split Hopkinson Pressure Bar (SHPB) to administer the dynamic compressive load. The SHPB was charged at various pressures to produce a range of strain rates on the material in compression. Data was acquired via strain gauges on the SHPB setup, from which stress, strain, and time data were collected. Analysis revealed the stress-strain behavior of the material as well as insights into the material behavior's relationship to strain rate. Further work must continue to characterize the various other dynamic behaviors of the material which will combine to create a substantially trustworthy constitutive model for this grade of nuclear-grade graphite. Ultimately, this will allow for realistic simulation of the material in reactor designs, allowing for prediction of design weaknesses and leading to improved designs for increased resilience, security, and reliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational Fluid Dynamics Models of the NASA White Sands Test Facility Particle Impact Test Nozzles

The particle impact ignition mechanism is considered to be the most effective means for igniting metals in gaseous oxygen environments and is a concern for every oxygen system. For this reason, the National Aeronautics and Space Administration (NASA) commits a large amount of resources attempting to understand and defend against this phenomenon. The most practical means of accomplishing this is through extensive of testing. To this end, over the years NASA has developed and built a facility and various apparatuses to test material or component vulnerability to a particle impact ignition. In testing materials, NASA uses sub-sonic and supersonic nozzles to replicate the conditions that a material is expected to experience in service. However, challenges include obtaining an understanding of the gas dynamics and of the particle behavior through and up to the point of impact at the material under test. One means of addressing these challenges is the use of computational fluid dynamics (CFD). If a CFD model can be built and validated, the model can then be used to confidently interrogate changes to inlet conditions and particle geometries, as well as changes to nozzle geometries to better simulate a material’s in-situ conditions and greatly reduce or eliminate trial-and-error approaches in testing. This paper will show NASA’s approach to and results of using CFD to better understand their particle impact nozzles.

Computational Fluid Dynamics↗