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All sources NASA NTRS DOE OSTI

DOE OSTI2022

An improved framework for the dynamic likelihood filtering approach to data assimilation

Here, we propose improvements to the Dynamic Likelihood Filter (DLF), a Bayesian data assimilation filtering approach, specifically tailored to wave problems. The DLF approach was developed to address the common challenge in the application of data assimilation to hyperbolic problems in the geosciences and in engineering, where observation systems are sparse in space and time. When these observations have low uncertainties, as compared to model uncertainties, the DLF exploits the inherent nature of information and uncertainties to propagate along characteristics to produce estimates that are phase aware as well as amplitude aware, as would be the case in the traditional data assimilation approach. Along characteristics, the stochastic partial differential equations underlying the linear or nonlinear stochastic dynamics are differential equations. This study focuses on developing the explicit challenges of relating dynamics and uncertainties in the Eulerian and Lagrangian frames via dynamic Gaussian processes. It also implements the approach using the ensemble Kalman filter (EnKF) and compares the DLF approach to the conventional one with respect to wave amplitude and phase estimates in linear and nonlinear wave problems. Numerical comparisons show that the DLF/EnKF outperforms the EnKF estimates, when applied to linear and nonlinear wave problems. This advantage is particularly noticeable when sparse, low uncertainty observations are used.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A tri-level distribution locational marginal price-based demand response framework

Here, in this paper, we propose a tri-level, nested, two-stage price-based demand response (PBDR) framework that considers distribution locational marginal price (DLMP) as DR enabler between load-serving entities (LSE), demand response providers (DRPs), and customers in the day-ahead distribution market. It enables LSE and customer interactions by using multiple DRPs, positioned in-between, and independently optimizes their objectives. The problem is formulated using linear power flow with approximated power losses and its application in DLMP as DR pricing. The tri-level problem is solved using a nested reformulation & decomposition (R&D) method and tested on the real Indian-108 bus distribution system under various dynamic pricings. Further, the temporal–spatial variations in DLMPs are assessed using fairness criteria. Numerical analyses demonstrate that DLMP applications can effectively improve economic efficiency, and transparency in DR programs valuation with a favorable fairness margin. The results show that DLMP as DR pricing signal induces (0-2) % variation in DLMP for DR participation up to 10 %. Further, it gives over 90 % fairness over temporal–spatial variation for all the customers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

A manifold learning perspective on surrogate modeling of nitrate concentration in the Kansas River

Abstract A non-linear surrogate model of nitrate concentration in the Kansas River (USA) is described. The model is an (almost) Piece-wise Linear response surface that provides a mean field approximation to the dynamics of the measured data for nitrate plus nitrite (target product) correlations to turbidity and chlorophyll-a concentrations (input variables). The method extends the United States Geological Survey’s linear procedures for surrogate data modeling allowing for better approximations for river systems exhibiting algal blooms due to nutrient-rich source waters. The model and visualization procedures illustrated in the Kansas River example should be generally applicable to many medium-size rivers in agricultural regions.

Tufillaro, Nicholas (ORCID:0009000628968832)↗

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↗

NASA NTRS1974

Limiting performance of ground transportation vehicles subject to transient loading

A computational approach to determining the limiting performance of vehicles subject to transient disturbances based on response variable criteria is set forth. For the purposes of a limiting performance study, the transportation system dynamics are described using second- or first-order equations in which the sought for quantity is a vector of time-varying functions called control or isolator forces that have replaced portions of the physical system. Computations are performed as a linear programming problem. As an example of the limiting performance of vehicles in protecting passengers or cargo under crash conditions, the problem of lading damage of a rail vehicle that is struck by another vehicle is considered.

Pilkey, W. D.↗

NASA NTRS1976

Alternative methods for the design of jet engine control systems

Various alternatives to linear quadratic design methods for jet engine control systems are discussed. The main alternatives are classified into two broad categories: nonlinear global mathematical programming methods and linear local multivariable frequency domain methods. Specific studies within these categories include model reduction, the eigenvalue locus method, the inverse Nyquist method, polynomial design, dynamic programming, and conjugate gradient approaches.

Sain, M. K.↗

NASA NTRS1980

Review - Axial compressor stall phenomena

Stall in compressors can be associated with the initiation of several types of fluid dynamic instabilities. These instabilities and the different phenomena, surge and rotating stall, which result from them, are discussed in this paper. Assessment is made of the various methods of predicting the onset of compressor and/or compression system instability, such as empirical correlations, linearized stability analyses, and numerical unsteady flow calculation procedures. Factors which affect the compressor stall point, in particular inlet flow distortion, are reviewed, and the techniques which are used to predict the loss in stall margin due to these factors are described. The influence of rotor casing treatment (grooves) on increasing compressor flow range is examined. Compressor and compression system behavior subsequent to the onset of stall is surveyed, with particular reference to the problem of engine recovery from a stalled condition. The distinction between surge and rotating stall is emphasized because of the very different consequences on recoverability. The structure of the compressor flow field during rotating stall is examined, and the prediction of compressor performance in rotating stall, including stall/unstall hysteresis, is described.

Greitzer, E. M.↗

NASA NTRS1989

A variational approach to dynamics of flexible multibody systems

This paper presents a variational formulation of constrained dynamics of flexible multibody systems, using a vector-variational calculus approach. Body reference frames are used to define global position and orientation of individual bodies in the system, located and oriented by position of its origin and Euler parameters, respectively. Small strain linear elastic deformation of individual components, relative to their body references frames, is defined by linear combinations of deformation modes that are induced by constraint reaction forces and normal modes of vibration. A library of kinematic couplings between flexible and/or rigid bodies is defined and analyzed. Variational equations of motion for multibody systems are obtained and reduced to mixed differential-algebraic equations of motion. A space structure that must deform during deployment is analyzed, to illustrate use of the methods developed.

Wu, Shih-Chin↗

NASA NTRS2000

Sliding Mode Control of the X-33 with an Engine Failure

Ascent flight control of the X-3 is performed using two XRS-2200 linear aerospike engines. in addition to aerosurfaces. The baseline control algorithms are PID with gain scheduling. Flight control using an innovative method. Sliding Mode Control. is presented for nominal and engine failed modes of flight. An easy to implement, robust controller. requiring no reconfiguration or gain scheduling is demonstrated through high fidelity flight simulations. The proposed sliding mode controller utilizes a two-loop structure and provides robust. de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of engine failure, bounded external disturbances (wind gusts) and uncertain matrix of inertia. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues. Conditions that restrict engine failures to robustness domain of the sliding mode controller are derived. Overall stability of a two-loop flight control system is assessed. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in the presence of external disturbances and vehicle inertia uncertainties, as well as the single engine failed case. The designed robust controller will significantly reduce the time and cost associated with flying new trajectory profiles or orbits, with new payloads, and with modified vehicles

Shtessel, Yuri B.↗

NASA NTRS1994

Dynamics of Numerics and CFD

This lecture attempts to illustrate the basic ideas of how the recent advances in nonlinear dynamical systems theory (dynamics) can provide new insights into the understanding of numerical algorithms used in solving nonlinear differential equations (DEs). Examples will be given of the use of dynamics to explain unusual phenomena that occur in numerics. The inadequacy of the use of linearized analysis for the understanding of long time behavior of nonlinear problems will be illustrated, and the role of dynamics in studying the nonlinear stability, accuracy, convergence property and efficiency of using time- dependent approaches to obtaining steady-state numerical solutions in computational fluid dynamics (CFD) will briefly be explained.

Yee, H. C.↗

NASA NTRS2006

Adjoint Method and Predictive Control for 1-D Flow in NASA Ames 11-Foot Transonic Wind Tunnel

This paper describes a modeling method and a new optimal control approach to investigate a Mach number control problem for the NASA Ames 11-Foot Transonic Wind Tunnel. The flow in the wind tunnel is modeled by the 1-D unsteady Euler equations whose boundary conditions prescribe a controlling action by a compressor. The boundary control inputs to the compressor are in turn controlled by a drive motor system and an inlet guide vane system whose dynamics are modeled by ordinary differential equations. The resulting Euler equations are thus coupled to the ordinary differential equations via the boundary conditions. Optimality conditions are established by an adjoint method and are used to develop a model predictive linear-quadratic optimal control for regulating the Mach number due to a test model disturbance during a continuous pitch

Nguyen, Nhan↗

DOE OSTI2021

An Ab Initio Multiple Cloning Method for Non-Adiabatic Excited-State Molecular Dynamics in NWChem

The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Temperature Evolution of the Activation Barriers Leads to Meyer−Neldel Rules for Structural Relaxation and Transport in Polymers

Understanding activation barriers controlling structural relaxation in glass-forming liquids, molecular transport, and ionic conductivity in amorphous polymers is a grand challenge of fundamental scientific and materials engineering interest across disciplines. Over decades, intriguing but puzzling empirical correlations between the elementary time scale of activated barrier crossing and the apparent Arrhenius activation energy, the so-called Meyer−Neldel (MN) rules, have been discovered in diverse liquids and glasses. Here, in this study, we formulate and successfully apply a new experimental analysis and an explicitly dynamical theoretical framework which provides an understanding of the origin, validity, and failure of such correlations, that bridge and unify the three fields of structural relaxation, molecular transport, and ionic conductivity in liquids and quenched glasses. Distinct quasi-universal laws are predicted in equilibrated liquids and nonequilibrium glasses, consistent with experiments. Our analysis reveals that even if the relaxation appears Arrhenius over a limited temperature range, the physical activation barrier is generally temperature-dependent in polymeric systems even below glass transition temperature. In addition, we show that the approximate validity of classical MN rules hinges on a linear temperature dependence of this barrier and the temperature range probed in experiments. Our findings are relevant for controlling the activation barrier in functional soft polymeric materials relevant to molecular separations, barrier coatings, and charge transport, and also provide new constraints on the theoretical understanding of the mechanism underlying slow activated dynamics in glass-forming condensed matter.

Meyer-Neldel rules↗

DOE OSTI2022

Effect of coaxial nozzle wear on catchment efficiency in direct energy deposition built components

Laser based Direct Energy Deposition (DED) systems using metallic powder feedstock are recognized as a promising manufacturing method for their ability to shorten production cycles and create complex part geometries. Components are built by generating a melt pool with a high-power laser beam while material is coaxially injected and left to solidify. An impediment to large scale use of DED lies in poor powder catchment efficiency, the condition in which a portion of injected powder escapes the melt pool resulting in a ratio of decreased printed material mass to mass of supplied feedstock. The wear state of a coaxial nozzle on a DED system within a hybrid manufacturing machine tool has been observed to decrease catchment efficiency over time. Herein this study investigates this effect by adapting flow visualization techniques to an in-situ process monitoring format, the implementation of a Computational Fluid Dynamics (CFD) simulation, and deposition testing. Nozzle geometric defects due to wear are identified and categorized, and the impact of nozzle tip wear, resulting in axial tip reduction, on powder catchment efficiency is proven by multiple calculation methods. A linear correlation between catchment efficiency and powder stream diameter is identified, causing a 15–20% loss in efficiency sustained over incremental nozzle tip reduction up to − 1 mm. These results provide a foundation for further study of wear effects and Zero defect manufacturing solutions for powder fed DED systems.

42 ENGINEERING↗

DOE OSTI2022

LaRIS: Targeting Portability and Productivity for LAPACK Codes on Extreme Heterogeneous Systems by Using IRIS

In keeping with the trend of heterogeneity in high-performance computing, hardware manufacturers and vendors are developing new architectures and associated software stacks (e.g., libraries) to harness the best possible performance from commonly used kernels (e.g., linear algebra kernels). However, kernels tuned for one architecture are not portable to others. Moreover, the coexistence of different architectures in a single node makes orchestration difficult. To address these challenges, we introduce LaRIS, a portable framework for LAPACK functionalities. LaRIS ensures a separation between linear algebra algorithms and vendor-library kernels by using the IRIS run time and IRIS-BLAS library. Such abstraction at the algorithm level makes the implementation completely agnostic to the vendor library and architecture. LaRIS uses the IRIS run time to dynamically select the vendor-library kernel and suitable processor architecture at run time. Through LU factorization, we demonstrate that LaRIS can fully utilize different heterogeneous systems by launching and orchestrating different vendor-library kernels without any change in the source code.

Monil, M. A. H.↗

NASA NTRS1990

Randomly Sampled-Data Control Systems

The purpose is to solve the Linear Quadratic Regulator (LQR) problem with random time sampling. Such a sampling scheme may arise from imperfect instrumentation as in the case of sampling jitter. It can also model the stochastic information exchange among decentralized controllers to name just a few. A practical suboptimal controller is proposed with the nice property of mean square stability. The proposed controller is suboptimal in the sense that the control structure is limited to be linear. Because of i. i. d. assumption, this does not seem unreasonable. Once the control structure is fixed, the stochastic discrete optimal control problem is transformed into an equivalent deterministic optimal control problem with dynamics described by the matrix difference equation. The N-horizon control problem is solved using the Lagrange's multiplier method. The infinite horizon control problem is formulated as a classical minimization problem. Assuming existence of solution to the minimization problem, the total system is shown to be mean square stable under certain observability conditions. Computer simulations are performed to illustrate these conditions.

Han, Kuoruey↗

DOE OSTI2023

Integrated Quantum-Classical Protocol for the Realistic Description of Solvated Multinuclear Mixed-Valence Transition-Metal Complexes and Their Solvatochromic Properties

Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Deep Koopman operators for causal discovery

Causal discovery aims to identify cause-effect mechanisms for better scientific understanding, explainable decision-making, and more accurate modeling. Standard statistical frameworks, such as Granger causality, lack the ability to quantify causal relationships in nonlinear dynamics due to the presence of complex feedback mechanisms, timescale mixing, and nonstationarity. Thus, applying these methods to study causal dynamics in real-world systems, such as the Earth, is a major challenge. Addressing this shortcoming, we leverage deep learning and a Koopman operator-theoretic formalism to present a class of causal discovery algorithms. Kausal uses deep Koopman operator methods to approximate nonlinear dynamics in a linearized vector space in which traditional causal inference methods such as Granger causality can be more easily applied. Our idealized experiments demonstrate Kausal’s superior ability in discovering and characterizing causal signals compared to existing deep learning and non-deep learning state-of-the-art approaches. Finally, the successful identification of major El Niño and La Niña events in observations showcases Kausal’s skill to handle real-world applications.

54 ENVIRONMENTAL SCIENCES↗