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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

What is (quantitative) system dynamics modeling? Defining characteristics and the opportunities they create

A clear definition of system dynamics modeling can provide shared understanding and clarify the impact of the field. We introduce a set of characteristics that define quantitative system dynamics, selected to capture core philosophy, describe theoretical and practical principles, and apply to historical work but be flexible enough to remain relevant as the field progresses. The defining characteristics are: (1) models are based on causal feedback structure, (2) accumulations and delays are foundational, (3) models are equation-based, (4) concept of time is continuous, and (5) analysis focuses on feedback dynamics. We discuss the implications of these principles and use them to identify research opportunities in which the system dynamics field can advance. These research opportunities include causality, disaggregation, data science and AI, and contributing to scientific advancement. Progress in these areas has the potential to improve both the science and practice of system dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗
DOE OSTI2020

Demonstration and performance testing of extreme-resolution simulations with static meshes on Summit (CPU & GPU) for a parked-turbine configuration and an actuator-line (mid-fidelity model) wind farm configuration (ECP-Q4 FY2020 Milestone Report)

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind simulation environment are Nalu-Wind, an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, AMR-Wind, a block-structured-grid solver with adaptive mesh refinement capabilities, and OpenFAST, a wind-turbine structural dynamics solver. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and Helmholtz-type equations for transport of momentum and other scalars. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. The choice of overset-mesh methodology to model the moving and non-moving parts of the computational domain introduces constraint equations in the elliptic pressure-Poisson solver. The presence of constraints greatly affects the performance of algebraic multigrid preconditioners.

17 WIND ENERGY↗
DOE OSTI2025

Understanding plasma turbulence through exact coherent structures

Plasma turbulence is a key challenge in understanding transport phenomena in magnetically confined plasmas. This work presents a generalized framework to analyze plasma turbulence that utilizes periodic orbit theory. In periodic orbit theory, doubly periodic solutions (coherent structures) of the governing equation(s) serve as building blocks of the considered turbulent dynamics. To illustrate the concept and method, the particularly simple Kuramoto–Sivashinsky (referred to here as LMRT for the original authors: LaQuey, Mahajan, Rutherford, and Tang) trapped-ion mode toy model is used. By applying numerical optimization techniques to the LMRT equation, we extract coherent spacetime patterns that represent the library of allowable fundamental structures of the equation. These structures provide a framework to systematically describe turbulence as a composition of recurrent solutions, revealing an underlying order within chaotic plasma motion. Although illustrated here using the simplified LMRT model for clarity, this framework provides a general strategy that can be extended to more complex and realistic models of plasma turbulence, including gyrokinetic systems. This offers a new method for predicting and potentially controlling transport processes in fusion plasmas by providing a bridge between nonlinear dynamical systems theory and plasma physics in the form of a generalized framework with which to analyze and understand spatially extended nonlinear partial differential equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

On finite-dimensional smoothed-particle Hamiltonian reductions of the Vlasov equation

The inclusion of spatial smoothing in finite-dimensional particle-based Hamiltonian reductions of the Vlasov equation and related models is considered. Here, this work investigates the underlying Hamiltonian structure of such smoothed particle-based methods for Hamiltonian systems and the small-scale regularization such methods implicitly make in approximating the continuum theory. In the context of the Vlasov–Poisson equation and other mean-field Lie–Poisson systems, of which Vlasov–Poisson is a special case, smoothing amounts to a convolutive regularization of the Hamiltonian. This regularization may be interpreted as a change of the inner product structure used to identify the dual space in the Lie–Poisson Hamiltonian formulation. In particular, the shape function used for spatial smoothing may be identified as the kernel function of a reproducing kernel Hilbert space whose inner product is used to define the Lie–Poisson Hamiltonian structure. It is likewise possible to introduce smoothing in the Vlasov–Maxwell system, but in this case the Poisson bracket must be modified rather than the Hamiltonian. The smoothing applied to the Vlasov–Maxwell system is incorporated by inserting smoothing in the map from canonical to kinematic coordinates. In the filtered system, the Lorentz force law and the current, the two terms coupling the Vlasov equation with Maxwell’s equations, are spatially smoothed.

Hamiltonian mechanics↗
DOE OSTI2020

Analytic fits to atom-in-jellium shear modulus predictions

Fits to AJ shear modulus calculations from ρ0 to the limit of the corresponding AJ EOS table (usually 1000 ρ0), adjusted to reproduce STP shear modulus where possible. Fitting minimized the fractional difference, so low-pressure points would be reproduced accurately despite the wide-ranging tabulation. AJ calculations were at T=0. Isochoric variation G(T) has been small for all cases spot-tested so far, and may have either sign. The fitted equation usually matches the AJ data to within a few percent. Between numerical noise in the AJ calculation and probably-physical structure not captured by the equation, the deviation could be up to 20% in some places in most models, and 30% in a few. AJ does not capture structural phase transitions or phases stabilized by directional bonds, where the shear modulus may vary by a greater amount. Where possible, STP ρ,G were used as parameters, and low pressure AJ points were de-weighted or removed if necessary. Otherwise, such as where AJ fails to capture solid phases with a significantly different shear modulus, the AJ data were fitted as far down in pressure as possible, G0 was also fitted if necessary, and ρ0 was also adjusted if needed to keep G0>0. The resulting models are not intended for use at low pressure, though some are probably adequate for practical purposes

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advanced Turbulence Models for Large-Scale Atmospheric Boundary Layer Flows

We present high-fidelity large-eddy-simulation (LES) modeling approaches for the turbulent atmospheric boundary layer (ABL) flows. Wind energy is a prime example of an application driven by ABL. Generation of electrical energy from farms of wind turbines at night in the stable ABL is a particularly interesting situation. In this report, we consider the well-known GEWEX (Global Energy and Water Cycle Experiment) Atmospheric Boundary Layer Study (GABLS) stably stratified benchmark LES case. We use a high-order spectral element code Nek5000/RS, which is supported under the DOE's Exascale Computing Project (ECP) Center for Efficient Exascale Discretizations (CEED) project, targeting application simulations on various acceleration-device based exascale computing platforms. In our earlier ANL report, we demonstrated our newly developed subgrid-scale (SGS) models based on high-pass filter (HPF), mean-field eddy viscosity (MFEV), and Smagorinsky (SMG) with no-slip and traction boundary conditions, provided with low-order statistics, convergence and turbulent structure analysis. In this report, we extend the range of our SGS modeling approaches in the context of the mean-field eddy viscosity (MFEV), to include the solution of an SGS turbulent kinetic energy equation (TKE). We demonstrate the model fidelity of Nek5000/RS in comparison to that of AMR-Wind, a block-structured second-order finite-volume code with adaptive-mesh-refinement capabilities, with which we studied scaling performance for both codes in comparison on DOE's leadership computing platforms.

17 WIND ENERGY↗
DOE OSTI2023

Wide-range continuous tuning of the thermal conductivity of La0.5Sr0.5CoO3-δ films via room-temperature ion-gel gating

Abstract Solid-state control of the thermal conductivity of materials is of exceptional interest for novel devices such as thermal diodes and switches. Here, we demonstrate the ability to continuously tune the thermal conductivity of nanoscale films of La 0.5 Sr 0.5 CoO 3- δ (LSCO) by a factor of over 5, via a room-temperature electrolyte-gate-induced non-volatile topotactic phase transformation from perovskite (with δ ≈ 0.1) to an oxygen-vacancy-ordered brownmillerite phase (with δ = 0.5), accompanied by a metal-insulator transition. Combining time-domain thermoreflectance and electronic transport measurements, model analyses based on molecular dynamics and Boltzmann transport equation, and structural characterization by X-ray diffraction, we uncover and deconvolve the effects of these transitions on heat carriers, including electrons and lattice vibrations. The wide-range continuous tunability of LSCO thermal conductivity enabled by low-voltage (below 4 V) room-temperature electrolyte gating opens the door to non-volatile dynamic control of thermal transport in perovskite-based functional materials, for thermal regulation and management in device applications.

42 ENGINEERING↗
DOE OSTI2024

Quantum mechanical model of crossing and anti-crossing points in 3D full-band Monte Carlo simulations

This work presents a 3D quantum mechanics based model to address the physics at band structure crossing/anti-crossing points in full band Monte Carlo (FBMC) simulations. The model solves the Krieger and Iafrate (KI) equations in real time using pre-computed coefficients at k-points spatially sampled within the first Brillouin zone. Solving the KI equations in real time makes this model applicable for all electric fields, which enables its use in FBMC device simulations. In this work, a two-level refinement scheme is used to aggressively sample regions in proximity to band crossings for accurate solutions to the KI equations and coarsely sample everywhere else to limit the number of k-points used. The presented sampling method is demonstrated on the band structure of silicon but is effective for the band structure of any semiconductor material. Next, the adaptation of the fully quantum KI model into the semi-classical FBMC method is discussed. Finally, FBMC simulations of hole transport in 4H silicon carbide with and without the KI model are performed. Results along different crystallographic directions for a wide range of electric fields are compared to previously published simulation and experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Direct observation of diamond formation in a shock-compressed high explosive

Understanding the formation timescale and structure of carbonaceous reaction products is critical for modeling the high-pressure equation-of-state of organic materials. We use the National Ignition Facility to shock-compress polycrystalline TATB (C 6 H 6 N 6 O 6 ) samples to ~70–130 GPa and ~4000–5500 K, employing in situ nanosecond X-ray diffraction to probe reaction products and velocimetry to measure transmitted compression wave profiles. Our diffraction data is consistent with the formation of diamond over timescales less than ~60 ns. This represents carbon condensation from a molecular explosive on timescales three times faster than previously reported and the earliest observation of diamond produced from reacting TATB. Reactive flow simulations with explicit chemistry reproduce the observed temporal structure within wave profiles to inform the distribution of P-T states. These findings provide direct evidence of ultrafast diamond formation in a reactive system at extreme conditions and provide new constraints for models of shock and detonation chemistry.

Clarke, Samantha M. [Lawrence Livermore National L↗
DOE OSTI2023

Dark Energy Survey Year 3 results: Constraints on extensions to Λ CDM with weak lensing and galaxy clustering

We constrain six possible extensions to the Λ cold dark matter (CDM) model using measurements from the Dark Energy Survey’s first three years of observations, alone and in combination with external cosmological probes. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data vectors and blind analyses of real data to validate the robustness of our results to astrophysical and modeling systematic errors. In many cases, constraining power is limited by the absence of theoretical predictions beyond the linear regime that are reliable at our required precision. The Λ CDM extensions are dark energy with a time-dependent equation of state, nonzero spatial curvature, additional relativistic degrees of freedom, sterile neutrinos with eV-scale mass, modifications of gravitational physics, and a binned σ 8 ( z ) model which serves as a phenomenological probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find ( w p , w a ) = ( - 0.9 9 - 0.17 + 0.28 , - 0.9 ± 1.2 ) at 68% confidence with z p = 0.24 from the DES measurements alone, and ( w p , w a ) = ( - 1.0 3 - 0.03 + 0.04 , - 0. 4 - 0.3 + 0.4 ) with z p = 0.21 for the combination of all data considered. Curvature constraints of Ω k = 0.0009 ± 0.0017 and effective relativistic species N eff = 3.1 0 - 0.16 + 0.15 are dominated by external data, though adding DES information to external low-redshift probes tightens the Ω k constraints that can be made without cosmic microwave background observables by 20%. For massive sterile neutrinos, DES combined with external data improves the upper bound on the mass m eff by a factor of 3 compared to previous analyses, giving 95% limits of ( Δ N eff , m eff ) ≤ ( 0.28 , 0.20 eV ) when using priors matching a comparable Planck analysis. For modified gravity, we constrain changes to the lensing and Poisson equations controlled by functions Σ ( k , z ) = Σ 0 Ω Λ ( z ) / Ω Λ , 0 and μ ( k , z ) = μ 0 Ω Λ ( z ) / Ω Λ , 0 , respectively, to Σ 0 = 0. 6 - 0.5 + 0.4 from DES alone and ( Σ 0 , μ 0 ) = ( 0.04 ± 0.05 , 0.0 8 - 0.19 + 0.21 ) for the combination of all data, both at 68% confidence. Overall, we find no significant evidence for physics beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Extreme compression of planetary gases: High-accuracy pressure-density measurements of hydrogen-helium mixtures above fourfold compression

Hydrogen (H 2 ) and helium (He), the most abundant elements in the universe, pose a unique challenge in measuring the equation of state of the mixture, owing to their differing physical properties. There remains a need for data with high enough precision to discriminate between existing equation of state (EOS) mix models in order to understand the internal structure of gas-giant planets. Here, we have measured the EOS of precompressed H 2 - He mixtures at conditions directly relevant to the planetary interiors using hypervelocity gas guns and Sandia’s Z machine with less than 10% uncertainty in density, enabling validation of mixture models. We precompressed 50:50 molar mixtures of H 2 -He to 0.1–0.2 GPa and directly measured particle velocity (in gas-gun experiments) and shock velocities (in Z-machine experiments). To complement the experimental efforts, we also computed the Hugoniots of precompressed H 2 -He mixtures using density-functional-theory-based molecular dynamics. Furthermore, we observe approximately 3- to 4.3-fold density compression at pressures up to 44 GPa.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Modeling of Sagging for 3D Printed Layers During the Curing Process

Here, a printed layer of silica-enforced poly(dimethylsiloxane)-co-(diphenylsiloxane) is modeled as a two-phase system consisting of air and polymer with an interface set up during the printing process. The structural geometry changes mostly due to the action of surface tension, while all material properties are strongly temperature dependent. Polymer flow is described using equations of the extended Herschel–Bulkley model, with parameters strongly dependent on temperature and degree of curing. Parameters of the model are determined using flow sweep measurements and separate experiments with vertical structure sagging at different temperatures. The curing process is modeled using dependencies between the curing rate, degree of curing, and temperature obtained in studies by differential scanning calorimetry. The developed model is used for simulations of printed structure deformations with different initial and boundary conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interactions Between Microturbulence and Magnetohydrodynamic Instabilities in Magnetized Plasmas (Final Technical Report)

This document details the work accomplished during the period 04/15/2012-01/31/2020 for the collaborative project “Interactions Between Microturbulence and Magnetohydrodynamic Instabilities in Magnetized Plasmas,” and serves as the final report on the University of California, San Diego part of this collaborative project for Department of Energy Office of Science - Fusion Energy Sciences Grant No. DE- SC0007783. This project focused on the development of analytic and computational tools, seeking to better understand the mutual interactions between small-scale temperature-gradient driven microturbulence and macroscopic magnetohydrodynamic (MHD) instabilities, particularly tearing modes, in magnetically confined plasmas relevant for the generation of fusion energy. This project advanced understanding through numerical simulations of different sets of model equations, corresponding to different microturbulence instabilities. Questions addressed included how the magnitudes, spatial structures, and scaling's of turbulent forcing's and drags impact magnetic island dynamics, as well as quantifying the “region of influence” of an island on the microturbulence dynamics. A key finding of the project is that the microturbulence fluctuations and associated cross-field particle and energy fluxes exhibit spatial asymmetries for sufficiently large islands. The results have improved our fundamental understanding of plasma dynamics, motivated new experimental investigations, and will help inform future fusion predictive modeling efforts.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Aeroelastic oscillations of a pitching flexible wing with structural geometric nonlinearities: Theory and numerical simulation

In this paper, we focus on the derivation of an analytical model of the aeroelastic dynamics of an elastically mounted flexible wing. This equations of motion obtained serve to help understand the behaviour of the aeroelastic wind tunnel setup in question, which consists of a rectangular wing with a uniform NACA 0012 airfoil profile, whose base is free to rotate rigidly about a longitudinal axis. Of particular interest are the structural geometric nonlinearities primarily introduced by the coupling between the rigid body pitch degree-of-freedom and the continuous system. A coupled system of partial differential equations (PDEs) coupled with an ordinary differential equation (ODE) describing axial-bending-bending-torsion-pitch motion is derived using Hamilton's principle. A finite dimensional approximation of the system of coupled differential equations is obtained using the Galerkin method, leading to a system of coupled nonlinear ODEs. Subsequently, these nonlinear ODEs are solved numerically using Houbolt's method. The results that are obtained are verified by comparison with the results obtained by direct integration of the equations of motion using a finite difference scheme. Adopting a linear unsteady aerodynamic model, it is observed that the system undergoes coalescence flutter due to coupling between the rigid body pitch rotation dominated mode and the first flapwise bending dominated mode. Finally, the behaviour of the limit cycle oscillations is primarily influenced by the structural geometric nonlinear terms in the coupled system of PDEs and ODE.

42 ENGINEERING↗
DOE OSTI2022

A Higher Order, Stable Partitioned Scheme for Fluid-Structure Interaction Problems

Although still a very active area of research with many open questions, there exist highly-accurate and efficient algorithms for numerically estimating solutions to the equations of fluid motion. Similarly, great strides have been made in numerically modeling the motion of solids. However, there exist many practical applications where one must solve both fluid and structure in tandem. There is a gap in the literature for high order unconditionally stable partitioned algorithms for problems of this type. We investigate a new partitioned scheme which shows promise in filling this gap. We use a finite-element-based model with an added mass approach on problems coupling the Euler beam equation with the incompressible Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Validation of prediction capability of operating space for plasma initiation in MAST-U

DYON is a plasma initiation modelling code that solves the differential equation system of the full circuit equations (plasma current, active coil currents and eddy currents in full passive structures) and 0D global energy and particle balance equations (Kim 2022 Nucl. Fusion 62 126012). In order to test the capability of the full electromagnetic plasma initiation model to predict individual discharges in experiments and thus the operating space in the device, a dedicated experimental database was built in MAST-U by scanning the prefilled gas pressure p 0 and the induced loop voltage V loop . In the experimental operating space of p 0 and V loop the lower and the upper limits of p 0 are determined by the plasma breakdown failure and the plasma burn-through failure, respectively. The lower limit of V loop is determined by the plasma burn-through failure. By directly reading the control room data used in each discharge (i.e. currents in the solenoid, poloidal field coils, and toroidal field coils, p 0 , and gas puffing rate), the full electromagnetic DYON consistently predicted the failed breakdown, failed burn-through, and successful plasma initiation discharges in the experimental database, demonstrating its capability to predict the operating space for inductive plasma initiation. The Paschen curve calculated with the effective connection length in MAST-U indicates a much higher p 0 required for plasma breakdown than the experimental data, indicating that individual field line evaluation is necessary to calculate the quantitative requirements for Townsend breakdown. The demonstration in this paper shows that the full electromagnetic DYON could be a useful simulation tool to assess the feasibility of inductive plasma initiation and to optimise operating scenarios in future devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Formation of turing patterns in strongly magnetized electric discharges

Abstract Pattern formation and self-organization in many biological and non-biological systems can be explained through Turing’s activator-inhibitor model. Here we show how this model can be employed to describe the formation of filamentary structures in a low-pressure electric discharge exposed to a strong magnetic field. Theoretical investigation reveals that the fluid equations describing a magnetized plasma can be rearranged to take the mathematical form of Turing’s activator-inhibitor model. Numerical simulations based on the equations derived from this approach could reproduce the various patterns observed in the experiments. Also, it is shown that a density imbalance between electrons and ions exists in the bulk of the magnetized plasma that generates an electric field structure transverse to the applied magnetic field. This electric field is responsible for the stability of the filamentary patterns in the magnetized plasma over time scales much longer than the characteristic time scales of the electric discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗