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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1961

A Threshold Theory for Phase-Locked Loops

A model of a phase-locked loop has been developed which is valid for all signal-to-noise ratios. The model is in the form of a nonlinear feedback system with randomly time-varying parameters. The analysis considers two operating regions. In low signal-to-noise ratio regions, the important consideration is stability. We want to study the asymptotic stability in the mean of a nonlinear system. It follows directly that a necessary condition for asymptotic stability of any nonlinear system is that a linearized model about some equilibrium point be asymptotically stable. By considering all possible equilibrium points, we can find an upper bound on the value of noise density which makes the system unstable. This upper bound represents a threshold value for system operation. In high signal-to-noise ratio regions, our results provide an exact statistical. description of system behavior. Therefore, knowledge of the spectrum of the signal and noise may be used to optimize the system configuration.

Van Trees, H. L.↗
DOE OSTI2024

Analysis of a Computational Framework for Bayesian Inverse Problems: Ensemble Kalman Updates and MAP Estimators under Mesh Refinement

This paper analyzes a popular computational framework to solve infinite-dimensional Bayesian inverse problems, discretizing the prior and the forward model in a finite-dimensional weighted inner product space. We demonstrate the benefit of working on a weighted space by establishing operator-norm bounds for finite element and graph-based discretizations of Matérn-type priors and deconvolution forward models. For linear-Gaussian inverse problems, we develop a general theory to characterize the error in the approximation to the posterior. We also embed the computational framework into ensemble Kalman methods and MAP estimators for nonlinear inverse problems. Furthermore, our operator-norm bounds for prior discretizations guarantee the scalability and accuracy of these algorithms under mesh refinement.

Bayesian inverse problem↗
NASA NTRS2004

Linear and Nonlinear Analyses of a Wind-Tunnel Balance

The NASA Langley Research Center (LaRC) has been designing strain-gauge balances for utilization in wind tunnels since its inception. The utilization of balances span a wide variety of aerodynamic tests. A force balance is an inherently critically stressed component due to the requirements of measurement sensitivity. Force balance stress analysis and acceptance criteria are under review due to LaRC wind tunnel operational safety requirements. This paper presents some of the analyses done at NASA LaRC. Research and analyses were performed in order to investigate the structural integrity of the balances and better understand their performance. The analyses presented in this paper are helpful in understanding the overall behavior of an existing balance and can also be used in design of new balances to enhance their performance. As a first step, maximum load combination is used for linear structural analysis. When nonlinear effects are encountered, the analysis is extended to include the nonlinearities. Balance 1621 is typical for LaRC designed balances and was chosen for this study due to its traditional high load capacity, Figure 1. Maximum loading occurs when all 6 components are applied simultaneously with their maximum value allowed (limit load). This circumstance normally will not occur in the wind tunnel. However, if it occurs, is the balance capable of handling the loads with an acceptable factor of safety? Preliminary analysis using Pro/Mechanica indicated that this balance might experience nonlinearity. It was decided to analyze this balance by using NASTRAN so that a nonlinear analysis could be conducted. Balance 1621 was modeled and meshed in PATRAN for analysis in NASTRAN. The model from PATRAN/NASTRAN is compared to the one from Pro/Mechanica. For a complete analysis, it is necessary to consider all the load cases as well as use a dense mesh near all the edges. Because of computer limitations, it is not feasible to analyze model with the dense mesh near all edges. In the present study, the dense mesh is limited to the surface on the end of the axial sections.

Karkehabadi, R.↗
DOE OSTI2020

Optimal Network Topology for Node-Breaker Representations With AC Power Flow Constraints

It has been demonstrated that network topology optimization (NTO) may change the topology of power system networks, and consequently, provide additional flexibility to reduce network congestion and violations. Most NTO problems are formulated based on the bus-branch model in which it is challenging to represent a realistic picture of all substation configurations. In this paper, we explore advantages of substation reconfiguration modeling based on node-breaker representations for NTO problem with full nonlinear alternating current power flow. It also proposes a tailored solution algorithm to solve this nonconvex mixed-integer nonlinear programming through the outer approximation method. The proposed solution approach iterates between a mixed-integer linear programming and a nonlinear subproblem. Additional enhancements to further accelerate the iteration process are illustrated. Numerical case studies demonstrate the relative economic and operational impact of optimal network topology with node-breaker representations.

42 ENGINEERING↗
NASA NTRS1986

Eigenvalue assignment strategies in rotor systems

The work done to establish the control and direction of effective eigenvalue excursions of lightly damped, speed dependent rotor systems using passive control is discussed. Both second order and sixth order bi-axis, quasi-linear, speed dependent generic models were investigated. In every case a single, bi-directional control bearing was used in a passive feedback stabilization loop to resist modal destabilization above the rotor critical speed. Assuming incomplete state measurement, sub-optimal control strategies were used to define the preferred location of the control bearing, the most effective measurement locations, and the best set of control gains to extend the speed range of stable operation. Speed dependent control gains were found by Powell's method to maximize the minimum modal damping ratio for the speed dependent linear model. An increase of 300 percent in stable speed operation was obtained for the sixth order linear system using passive control. Simulations were run to examine the effectiveness of the linear control law on nonlinear rotor models with bearing deadband. The maximum level of control effort (force) required by the control bearing to stabilize the rotor at speeds above the critical was determined for the models with bearing deadband.

Youngblood, J. N.↗
NASA NTRS1993

Canonical forms of multidimensional steady inviscid flows

Canonical forms and canonical variables for inviscid flow problems are derived. In these forms the components of the system governed by different types of operators (elliptic and hyperbolic) are separated. Both the incompressible and compressible cases are analyzed, and their similarities and differences are discussed. The canonical forms obtained are block upper triangular operator form in which the elliptic and non-elliptic parts reside in different blocks. The full nonlinear equations are treated without using any linearization process. This form enables a better analysis of the equations as well as better numerical treatment. These forms are the analog of the decomposition of the one dimensional Euler equations into characteristic directions and Riemann invariants.

Taasan, Shlomo↗
NASA NTRS1959

Ground Simulator Studies of a Nonlinear Linkage in a Power Control System

An investigation was made to determine the characteristics of a nonlinear linkage installed in a power control system incorporated in a ground simulator. The nonlinear linkage provided for increased control-stick motion for relatively small simulator response at control motions near neutral. The quality of the control system was rated on the ease and precision with which various tracking tasks were performed by the pilots who operated the simulator. The results obtained with the nonlinear linkage installed in the control system were compared with those obtained by using the normal linear control system. Several combinations of nonlinearity of the linkage were tested for various dynamic characteristics of the simulator. It was found that the pilots were able to track almost as well with the nonlinear linkage installed as with the normal system. All of the pilots were of the opinion, however, that the nonlinearity was an undesirable feature in the control system because of the apparent lack of simulator response through the neutral range of the linkage where relatively large stick deflections could be made with very little simulator motion. The results showed that increased lag between the target and chair position, higher stick-force levels, and uneven stick forces due to the dynamics of the linkage were general characteristics of all the nonlinear linkage conditions tested. It was also found that for cases of low simulator damping, rapid control motions caused considerably higher overshoots when the nonlinear linkage was installed than were obtained for the normal linear control system. These characteristics were considered to be sufficiently undesirable to out-weigh the advantages to be gained from the use of a nonlinear linkage in the control system of an airplane.

Assadourian, Arthur↗
NASA NTRS2002

Analysis of High Order Difference Methods for Multiscale Complex Compressible Flows

Accurate numerical simulations of complex multiscale compressible viscous flows, especially high speed turbulence combustion and acoustics, demand high order schemes with adaptive numerical dissipation controls. Standard high resolution shock-capturing methods are too dissipative to capture the small scales and/or long-time wave propagations without extreme grid refinements and small time steps. An integrated approach for the control of numerical dissipation in high order schemes with incremental studies was initiated. Here we further refine the analysis on, and improve the understanding of the adaptive numerical dissipation control strategy. Basically, the development of these schemes focuses on high order nondissipative schemes and takes advantage of the progress that has been made for the last 30 years in numerical methods for conservation laws, such as techniques for imposing boundary conditions, techniques for stability at shock waves, and techniques for stable and accurate long-time integration. We concentrate on high order centered spatial discretizations and a fourth-order Runge-Kutta temporal discretizations as the base scheme. Near the bound-aries, the base scheme has stable boundary difference operators. To further enhance stability, the split form of the inviscid flux derivatives is frequently used for smooth flow problems. To enhance nonlinear stability, linear high order numerical dissipations are employed away from discontinuities, and nonlinear filters are employed after each time step in order to suppress spurious oscillations near discontinuities to minimize the smearing of turbulent fluctuations. Although these schemes are built from many components, each of which is well-known, it is not entirely obvious how the different components be best connected. For example, the nonlinear filter could instead have been built into the spatial discretization, so that it would have been activated at each stage in the Runge-Kutta time stepping. We could think of a mechanism that activates the split form of the equations only at some parts of the domain. Another issue is how to define good sensors for determining in which parts of the computational domain a certain feature should be filtered by the appropriate numerical dissipation. For the present study we employ a wavelet technique introduced in as sensors. Here, the method is briefly described with selected numerical experiments.

Sjoegreen, Bjoern↗
DOE OSTI2020

Multigrid Algorithms with Projection and Prolongation over Elements of the Phase Space for K-Eigenvalue Transport Problems

This paper describes new multilevel acceleration methods for solving the multigroup neu- tron transport eigenvalue problems. These multilevel algorithms use different projection and prolongation operators in the phase space. The Nonlinear Diffusion Acceleration (NDA) method with multiple grids in energy is formulated with the prolongation oper- ator based on multiplication iterative correction and linear-in-energy mapping. Another multilevel NDA method uses the projection operator with coarsening in energy between the high-order transport and low-order NDA equations. The third algorithm is formu- lated with the partial-current based CMFD low-order equations and applies projection operators in space and energy. The numerical results are presented.

Cornejo, Luke↗
DOE OSTI2022

Evaluating the demand response potential of ammonia plants

Demand-side management/demand response (DSM/DR) are key strategies for mitigating the inherent variability in electricity generation rates by renewable sources. This article represents—to our knowledge—the first foray into assessing the DR potential of ammonia plants. Ammonia plants are interesting candidates for DR initiatives because of their significant electricity use (for operating compressors driving the synthesis loop) and the ability to store the ammonia product relatively easily and safely. Our approach is based on formulating and solving an optimal DR scheduling problem for an ammonia plant while accounting for the process dynamics. To this end, we introduce a new Hammerstein–Wiener-inspired modeling framework based on injecting linear dynamics in a first-principles static nonlinear model of the process. The results are encouraging; for the cases considered, peak-time power consumption decreases between 3.57% and 7.40%, coupled with 1.39% to 3.70% reductions in operating cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Effect of the neutral beam injector operational regime on the Alfven eigenmode saturation phase in DIII-D plasma

The aim of this study is to analyze the effect of the neutral beam injector (NBI) operation regime on the saturation phase of the Alfven Eigenmodes (AEs) in DIII-D plasma. Here, the analysis is done using the linear and nonlinear versions of the gyro-fluid code FAR3d. A set of parametric analyses are performed modifying the nonlinear simulation EP $β$ (NBI injection power), EP energy (NBI voltage) and the radial location of the EP density profile gradient (NBI radial deposition). The analysis indicates a transition from the soft (local plasma relaxation) to the hard MHD (global plasma relaxation) limit if the simulation EP $β$ $\unicode{x2A7E}$ $0.02$, leading to bursting MHD activity caused by radial AEs overlapping. MHD bursts cause an enhancement of the EP transport showing ballistic-like features as avalanche-like events. Simulations in the soft MHD limit show an increment of the EP density gradient as the EP $β$ increases. On the other hand, there is a gradient upper limit in the hard MHD limit, consistent with the critical-gradient behavior. AEs induce shear flows and zonal current leading to the deformation of the flux surfaces and the safety factor profile, respectively, particularly strong for the simulation in the hard MHD limit. Simulations in the hard MHD regime show a decrease of the AE frequency in the saturation phase; this is caused by the destabilization of a transitional mode between a $9/3-10/3$ TAE and a $9/3$ RSAE that may explain the AE frequency down-sweeping observed in some DIII-D discharges. Reducing the EP energy in the nonlinear simulations leads to a weakening of the plasma perturbation. On the other hand, increasing the EP energy causes the opposite effect. Nonlinear simulations of off-axis NBI profiles indicate a lower plasma perturbation as the EP density gradient is located further away from the magnetic axis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Inrush Current Mitigation for Grid-Forming Inverters in Islanded Microgrids

Virtual-inertia and droop control methods are commonly used for grid-forming inverters. While the virtual inertia is used to emulate the equation of motion/frequency, if the inverter output voltage is emulated as in synchronous generators, then the method is known as the virtual synchronous generator. An inductive pulse-load, e.g., a relatively large induction motor, connection to a microgrid fed only by grid-forming inverters may lead to blackout due to high inrush currents. This article presents virtual reactance techniques to mitigate the inrush current effects and enhance the inverter’s robustness for the safe connection of inductive and dynamic loads. This article also compares the virtual inertia and droop control methods under switching inductive-dynamic loads while the proposed techniques are implemented. Experimental tests are performed considering the linear and nonlinear virtual reactance techniques, and the findings are discussed. The mitigation significantly suppresses the inrush currents while the inverters can perform a normal operation. Furthermore, the frequency and power response of the virtual inertia control with different inertia settings to a sudden change in the load is analyzed. The virtual reactance technique is tested in a laboratory-scale hardware setup of a 208V microgrid fed by 5kVA and 10kVA inverters, and the results are presented in this article.

Gursoy, Mehmetcan↗
DOE OSTI2026

Data-Driven Modeling and Correction of Vehicle Dynamics

We develop a data-driven framework for learning and correcting nonautonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exhibit inherent model-form uncertainty, motivating the need for data-driven correction. Moreover, nonautonomous dynamics are governed by time-dependent control inputs, which pose challenges in learning predictive models directly from temporal snapshot data. To address these, we reformulate the vehicle dynamics via a local parameterization of the time-dependent inputs, yielding a modified system composed ofa sequence of local parametric dynamical systems. Here, we approximate these parametric systems using two complementary approaches. First, we employ the dimension reduction and interpolation in parameter space (DRIPS) methodology to construct efficient linear surrogate models, equipped with lifted observable spaces and manifold-based operator interpolation. This enables data-efficient learning of vehicle models whose dynamics admit accurate linear representations in the lifted spaces. Second, for more strongly nonlinear systems, we employ flow map learning (FML), a deep neural network (DNN) approach that approximates the parametric evolution map without requiring special treatment of nonlinearities. We further extend FML with a transfer-learning-based model correction procedure, enabling the correction of misspecified prior models using only a sparse set of high-fidelity or experimental measurements, without assuming a prescribed form for the correction term. Through a suite of numerical experiments on unicycle, simplified bicycle, and slip-based bicycle models, we demonstrate that DRIPS offers robust and highly data-efficient learning of nonautonomous vehicle dynamics, while FML provides expressive nonlinear modeling and effective correction of model-form errors under severe data scarcity.

data-driven modeling↗
NASA NTRS1996

A New Approach to Parallel Interference Cancellation for CDMA

This paper introduces an improved nonlinear parallel interference cancellation scheme that significantly reduces the degrading effect of user interference with implementation complexity linear in the number of users. The scheme operates on the fact that parallel processing simultaneously removes from each user a part of the interference produced by the remaining users accessing the channel the amount being proportional to their reliability. The parallel processing can be done in multiple stages. Simulation results are given for a multitude of different situations, in particular those cases for which the analysis is too complex.

interference cancellation multiuser communication ↗
DOE OSTI2022

Data-driven Resilience Characterization of Control Dynamical Systems

In this paper, we define and quantify resiliency of a power network and propose data-driven algorithms for computing the same for the power grid. To do this, we use the Koopman operator framework to lift the controlled dynamical system to an abstract (possibly higher) dimensional space, where the evolution is linear. The linear system representation allows us to relate small time local controllability and observability of a general nonlinear control system to the controllability and observability of the lifted linear system. Finally, we define the resiliency of the underlying power grid in terms of the controllability and observability gramians of the lifted linear system. We illustrate the proposed approach to compute the resiliency metrics on time-series data obtained from a microgrid.

koopman operator, resilience, control↗
DOE OSTI2023

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. Here, the performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This article describes a novel fully data-driven probabilistic framework to derive a linear representation of postcontingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

Rayleigh Scattering Density Measurements from Ultrafast Lasers in High-Pressure, Cryogenic Wind Tunnels

The Rayleigh scattering signal from femtosecond laser pulses is examined for its utility at making instantaneous density measurements in the NASA Langley 0.3-m Transonic Cryogenic Tunnel. An electron-multiplying CCD camera is used to visualize Rayleigh scattering signal taken concurrently with velocity measurements utilizing the femtosecond laser tagging velocimetry technique (FLEET). The results indicate a strong potential for making instantaneous measurements. Viable single-shot images are obtained over the full operational envelope of the facility, and shot-to-shot variations are found to be on average 6 percent (at 95 percent confidence level) and tend to decrease as the facility density is increased. The Rayleigh scattering signals observed before the optical focus exhibit a characteristically linear dependence on the mass-density of the gas, while signals after the focus exhibit a nonlinear (sublinear) density dependence, indicative of stronger absorption at higher densities. The measured Rayleigh scattering signals compare favorably to theoretical assessments made at the tunnel operating conditions.

Burns, Ross A.↗
DOE OSTI2023

A Mixed integer linear programming‐based distributed energy management for networked microgrids considering network operational objectives and constraints

Abstract Mixed integer linear programming (MILP)–based distributed energy management for networked microgrids embedded modern distribution systems is proposed. Considering the diverse ownership of microgrids, distributed energy resources (DERs) that interface directly with utilities and responsive loads, an alternating direction method of multipliers–based distributed framework was formulated for the scheduling of networked microgrids embedded modern distribution systems by adjusting nodal price signals iteratively. In addition, to make the formulated optimization problems resolvable through more accessible and popular MILP solvers, different linearisation techniques were employed to transform the nonlinear terms into linear or mixed integer linear formats. The proposed MILP‐based distributed method preserves all participants' autonomy (e.g., microgrids, DERs that interface directly with utilities and responsive loads), while incentivising them to actively participate in the distribution system operation with price signals. The proposed method is validated with results of numerical simulation using a modern distribution system consisting of multiple networked microgrids, DERs that interface directly with utilities, as well as responsive loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗