Dynamic Modeling of Nuclear Thermal Propulsion Systems Under Drum Fault Conditions
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Anderson, David↗
SEARCH · Engineering Papers
Results for “dynamic models”
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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Dynamic Modelling of HiveWind Floating Wind Substructure in OpenFAST
Current aero-elastic modes tend to consider the wind turbine floating substructures as rigid. However, the new generation of offshore wind platforms are leaner, less rigid. The OpenFAST code has been updated to consider the flexibility of the floating substructure. This presentation shows how a numerical model of the HiveWind design was created within OpenFAST as well as some verifications performed. When comparing the flexible model to a simplified rigid model (previous state-of-the-art), there are some significant differences in key performance indicators. The new flexibility capability within OpenFAST allows to calculate ultimate and fatigue loads within the floating substructure, allowing for the development of more economical designs.
ENGINEERING,WIND ENERGY↗
Dynamic Modeling of Power Conversion Stages for an Exascale Supercomputer
In this paper a power conversion and energy consumption model for an exascale supercomputer is investigated. Power consumption, energy loss and efficiency are derived for the 27.2 MW liquid-cooled, centralized, High Performance Computing (HPC) power system, which is supplied directly from the 480 V three-phase mains. Two energy conversion stages are analyzed, measured and modeled. The model is developed in order to be adapted and implemented in a digital twin platform utilizing a Resource Allocator and Power Simulator (RAPS) module. RAPS enables estimation of potential energy savings in the direct AC power supply architecture via both conventional rectifier load sharing (commonly used in HPC systems), as well as smart rectifier load sharing. Moreover, besides the direct AC supply architecture analysis, the full direct DC supply architecture with with 1 kV DC bus were also studied. Comparison of 10 hour time frame operation of the system, with direct 480 V AC voltage supply with conventional and smart load sharing and medium dc voltage supply were done. For the direct AC supply architecture, with conventional and smart load sharing the predicted power loss was approximately 840 kW and 820 kW, respectively and the predicted total system efficiency was 92.87% and 93.05%, respectively. For the direct DC supply architecture with the 1000 V DC supply bus power loss was approximately 340 kW and the predicted total system efficiency was 97.02%.
Wojda, Rafal↗
Multi-Tethered Space-Based Interferometers: Particle System Model
Dynamics models are presented for a class of space-based interferometers comprised of multiple component bodies, interconnected in various arrangements, by low-mass flexible tethers of variable length. The tethered constellations are to perform coordinated rotational scanning accompanied by baseline dimensional changes, as well as spin axis realignments and spin-up/spin-down maneuvers. The mechanical idealization is a system of N point masses interconnected by massless tethers of variable length. Both extensible and inextensible tethers are considered. Expressions for system angular and linear momenta are developed. The unrestricted nonlinear motion equations are derived via Lagranges equations. Rheonomic constraints are introduced to allow prescribed motion of any degrees of freedom, and the associated physical forces are determined. The linearized equations of motion are obtained for the steady rotation of a system with extensible tethers of constant unstrained length.
Gates, Stephen S.↗
D-RM Builder: A software tool for generating fast and accurate nonlinear dynamic reduced models from high-fidelity models
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Carbon capture↗
Long and Short Term Geomagnetic Prediction (Chapter 19)
Prediction of geomagnetic variability depends on the accuracy of geomagnetic field modeling, dynamical modeling of source regions that contribute to geomagnetic signals, and advanced assimilation algorithms that combine effectively the results of geomagnetic field and dynamic models to make accurate estimates of the dynamic states of the sources and, therefore, accurate forecast of geomagnetic variations. In this chapter we provide an overview of recent research efforts in these three research areas, focusing primarily on geomagnetic variations from the dynamic outer core and from solar and lunar tidal effects, but also including a review of relevant research results and developments. Prediction of weak but periodic tidal phenomena, and of strong but chaotic secular variation (SV) showcases two very important new developments which will lead to new opportunities in geomagnetic research and application.
Weijia Kuang↗
Dynamic stall modeling and correlation with experimental data on airfoils and rotors
Two methods for modeling dynamic stall have been developed. The alpha, A, B method generates lift and pitching moments as functions of angle of attack and its first two time derivatives. The coefficients are derived from experimental data for oscillating airfoils. The Time Delay Method generates the coefficients from steady state airfoil characteristics and an associated time delay in stall beyond the steady state stall angle. Correlation with three types of test data shows that the alpha, A, B method is somewhat better for use in predicting helicopter rotor response in forward flight. Correlation with lift and moment hysteresis loops generated for oscillating airfoils was good for both models.
Carlson, R. G.↗
Long-wavelength variations in earth's geoid - Physical models and dynamical implications
Seismic tomography and fluid dynamical models are extended to include a detailed and realistic parameterization of the viscosity structure of the mantle. The model also includes the effects of heterogeneity inferred from surface-wave studies of upper-mantle structure. It is found that about 90 percent of the observed geoid may be explained by density anomalies inferred from tomography, a model of subducted slabs, and an earth model with a low-viscosity asthenosphere over a moderate-viscosity lower mantle.
Hager, B. H.↗
A method for modeling contact dynamics for automated capture mechanisms
Logicon Control Dynamics develops contact dynamics models for space-based docking and berthing vehicles. The models compute contact forces for the physical contact between mating capture mechanism surfaces. Realistic simulation requires proportionality constants, for calculating contact forces, to approximate surface stiffness of contacting bodies. Proportionality for rigid metallic bodies becomes quite large. Small penetrations of surface boundaries can produce large contact forces.
Williams, Philip J.↗
Discrete Empirical Interpolation Method Based Dynamic Load Model Reduction
Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.
bulk power system↗
Modeling Load Dynamics to Support Resiliency-based Operations in Low-Inertia Microgrids
Microgrids have repeatedly demonstrated the ability to provide uninterrupted service to critical end-use loads during normal outages, severe weather events, and natural disasters. While their ability to provide critical services is well documented, microgrids present a more dynamic operational environment than grid-connected distribution systems. The dynamics of a microgrid are commonly driven by the high inertia of rotating generators, which are common in many microgrids. In such high-inertia systems, the impact of end-use load dynamics are often not examined. However, with the increased penetration of inverter-based generation with little or no inertia, it is necessary to consider the impact that the dynamics of the end-use loads have on the operations of microgrids, particularly for a resiliency-based operation. These operations include, but are not limited to, switching operations, loss of generating units, and the starting of induction motors. This paper examines the importance of including dynamic models of the end-use load when evaluating the operations of low inertia microgrids, and shows that by properly representing their behavior, it is possible to cost effectively size equipment while supporting resilient operations of critical end-use loads.
Tuffner, Francis K.↗
Identification of multivariable high-performance turbofan engine dynamics from closed loop data
A typical engine control design cycle consists of developing a dynamic engine simulation from steady-state component performance data, designing a control based upon this simulation, and then testing and modifying the control in an engine test cell to meet performance requirements. This design cycle was successful for state-of-the-art engines. However, for more advanced multivariable engines that exhibit strong variable interactions, this procedure will result in substantial trial and error modification of the control during the testing phase. One method to automate the design process and reduce control modification testing and development cost would be to identify accurate dynamic models directly from the closed-loop test data. These identified models would then be used in conjunction with a synthesis procedure to systematically refine the control. Recent advances in closed-loop identifiability present a methodology for this direct identification of engine model dynamics from closed-loop test data. The application of an identification method to simulated and actual closed-loop F100 engine data is described. This study was undertaken to determine if useful dynamic engine models could be identified directly from closed-loop engine test data.
Merrill, W. C.↗
Hidden-strangeness tetraquarks in the dynamical diquark model
The dynamical diquark model describes multiquark exotic hadrons in terms of diquark components nucleated by heavy quarks and successfully explains multiple features of hidden-charm and hidden-bottom exotics. Here, we apply the model to the marginally heavy case of hidden-strange states to probe whether mesons near 2 GeV with peculiar properties, such as 𝜙(2170), 𝑓 2 (2340), and 𝑋(2370), are possible tetraquark candidates. We calculate spin-multiplet average masses using potentials obtained through lattice simulations and quark models, and we also describe the detailed spectra of the expected multiplets as a diagnostic to discern the nature of future hadrons likely to be discovered in this mass region by experiments at facilities such as BESIII, JLab, and the EIC.
Bound states↗
An extended supersonic combustion model for the dynamic analysis of hypersonic vehicles
The development of an advanced dynamic model for aeroelastic hypersonic vehicles powered by air breathing engines requires an adequate engine model. This report provides a discussion of some of the more important features of supersonic combustion and their relevance to the analysis and design of supersonic ramjet engines. Of particular interest are those aspects of combustion that impact the control of the process. Furthermore, the report summarizes efforts to enhance the aeropropulsive/aeroelastic dynamic model developed at the Aerospace Research Center of Arizona State University by focusing on combustion and improved modeling of this flow. The expanded supersonic combustor model described here has the capability to model the effects of friction, area change, and mass addition, in addition to the heat addition process. A comparison is made of the results from four cases: (1) heat addition only; (2) heat addition plus friction; (3) heat addition, friction, and area reduction, and (4) heat addition, friction, area reduction, and mass addition. The relative impact of these effects on the Mach number, static temperature, and static pressure distributions within the combustor are then shown. Finally, the effects of frozen versus equilibrium flow conditions within the exhaust plume is discussed.
Bossard, J. A.↗
The AFDD International Dynamic Stall Workshop on Correlation of Dynamic Stall Models with 3-D Dynamic Stall Data
A variety of empirical and computational fluid dynamics two-dimensional (2-D) dynamic stall models were compared to recently obtained three-dimensional (3-D) dynamic stall data in a workshop on modeling of 3-D dynamic stall of an unswept, rectangular wing, of aspect ratio 10. Dynamic stall test data both below and above the static stall angle-of-attack were supplied to the participants, along with a 'blind' case where only the test conditions were supplied in advance, with results being compared to experimental data at the workshop itself. Detailed graphical comparisons are presented in the report, which also includes discussion of the methods and the results. The primary conclusion of the workshop was that the 3-D effects of dynamic stall on the oscillating wing studied in the workshop can be reasonably reproduced by existing semi-empirical models once 2-D dynamic stall data have been obtained. The participants also emphasized the need for improved quantification of 2-D dynamic stall.
Tan, C. M.↗
A computer program for model verification of dynamic systems
Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, and then qualified for future use in predicting system response in a different dynamic environment. There are various ways to conduct model verification. The approach adopted in MOVER II employs Bayesian statistical parameter estimation. Unlike curve fitting whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that function (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data, (2) will assist in the interpretation of test data, (3) can be used to help verify a design, (4) will reliably predict performance, and (5) in the case of space structures, facilitate dynamic control.
Chrostowski, J. D.↗
Dynamic tests of v/stol transport models
Dynamic tests of free flight models of various configurations for V/STOL transport aircraft
DYNAMIC MODEL↗
Modeling error PDF optimization based wavelet neural network modeling of dynamic system and its application in blast furnace ironmaking
In general, the modeling errors of dynamic system model are a set of random variables. The traditional performance index of modeling such as means square error (MSE) and root means square error (RMSE) can not fully express the connotation of modeling errors with stochastic characteristics both in the dimension of time domain and space domain. Therefore, the probability density function (PDF) is introduced to completely describe the modeling errors in both time scales and space scales. Based on it, a novel wavelet neural network (WNN) modeling method is proposed by minimizing the two-dimensional (2D) PDF shaping of modeling errors. First, the modeling error PDF by the tradional WNN is estimated using data-driven kernel density estimation (KDE) technique. Then, the quadratic sum of 2D deviation between the modeling error PDF and the target PDF is utilized as performance index to optimize the WNN model parameters by gradient descent method. Since the WNN has strong nonlinear approximation and adaptive capability, and all the parameters are well optimized by the proposed method, the developed WNN model can make the modeling error PDF track the target PDF, eventually. Simulation example and application in a blast furnace ironmaking process show that the proposed method has a higher modeling precision and better generalization ability compared with the conventional WNN modeling based on MSE criteria. Furthermore, the proposed method has more desirable estimation for modeling error PDF that approximates to a Gaussian distribution whose shape is high and narrow.
Modelling↗