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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Accelerated Sparse Recovery via Gradient Descent with Nonlinear Conjugate Gradient Momentum

This paper applies an idea of adaptive momentum for the nonlinear conjugate gradient to accelerate optimization problems in sparse recovery. Specifically, we consider two types of minimization problems: a (single) differentiable function and the sum of a non-smooth function and a differentiable function. In the first case, we adopt a fixed step size to avoid the traditional line search and establish the convergence analysis of the proposed algorithm for a quadratic problem. This acceleration is further incorporated with an operator splitting technique to deal with the non-smooth function in the second case. As a result, we use the convex ι 1 and the nonconvex ι 1 – ι 2 functionals as two case studies to demonstrate the efficiency of the proposed approaches over traditional methods.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

SIRTF controller simulation - Instability masked by numerical integration

In the course of a simulation study of a candidate design for the Space Infrared Telescope Facility (SIRTF), an unusual phenomenon was observed. The uncompensated control system was unstable, but a numerical simulation with the fixed-step-size classical fourth-order Runge-Kutta method gave a stable response. This phenomenon is described in the setting in which it occurred. The Runge-Kutta simulation model is analyzed as a discrete linear system and shown to be stable, thus corroborating the numerical results.

Rajan, N.↗
NASA NTRS1971

Dynamic programming training period for an MSE adaptive equalizer.

A steepest descent variable step-size algorithm has been designed using dynamic programming for a mean-square-error adaptive equalizer. Additive noise and a constraint have been included. It is found that the new algorithm converges faster than the common fixed step-size algorithm.

Richman, S. H.↗
DOE OSTI2025

An iterative dynamic chemical stiffness removal method for reacting flow simulations

Abstract An iterative dynamic chemical stiffness removal method (IDCSR) based on quasi-steady-state approximation (QSSA) is proposed. The IDCSR method is built on a previously developed non-iterative method which has proved to work well for small timestep sizes. A novel iterative procedure is designed in IDCSR to enable explicit time integration of stiff chemistry at relatively large timestep sizes relevant to practical reacting flow simulations. The effectiveness of the iterative procedure is first demonstrated with a toy problem and homogeneous auto-ignition with fixed integration step sizes, showing that larger timestep sizes can be allowed for explicit time integration using IDCSR compared with the previous non-iterative method. IDCSR is then compared with existing explicit chemistry solvers for simulations of homogeneous auto-ignition and shows similar or lower computational cost but significantly higher accuracy across a wide range of timestep sizes. IDCSR is further combined with an automatic adaptive time-stepping scheme for simulations of 0-D homogeneous auto-ignition and a 2-D laminar lifted n -dodecane jet flame. For the 0-D auto-ignition simulations, IDCSR is shown to reduce both the error (by 43%–90%) and computational cost (by 6–15 times) compared with existing explicit solvers, while achieving speed-up factors of up to 400 compared with VODE for a wide range of timestep sizes and reaction mechanisms. For the 2-D jet flame simulations, speed-up factors of 15 and 31 for chemistry integration, and 5 and 9 for overall simulation, are achieved by IDCSR compared with CVODE with and without analytic Jacobian, respectively.

Xu, Chao (ORCID:0000000153074159)↗
DOE OSTI2026

TANTE: Time-adaptive operator learning via neural Taylor expansion

Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynamics. However, most existing methods rely on fixed time step sizes during rollout, which limits their ability to adapt to varying temporal complexity and often leads to error accumulation. In this work, we propose the Time-Adaptive Transformer with Neural Taylor Expansion (TANTE), a novel operator-learning framework that produces continuous-time predictions with adaptive step sizes. TANTE predicts future states by performing a Taylor expansion at the current state, where neural networks learn both the higher-order temporal derivatives and the local radius of convergence. This allows the model to dynamically adjust its rollout based on the local behavior of the solution, thereby reducing cumulative error and improving computational efficiency. We demonstrate the effectiveness of TANTE across a wide range of PDE benchmarks, achieving superior accuracy and adaptability compared to fixed-step baselines, delivering accuracy gains of 60-80 % and speed-ups of 30-40 % at inference time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Necessary and sufficient conditions for quadratic stabilizability of switched systems on non-uniform time domains

In this paper, we consider the quadratic stabilizability via state feedback for a particular class of switched systems that evolve on a non-uniform time domain by introducing time scales theory. The system considered switches between a continuous-time subsystem with variable lengths and a discrete-time subsystem with variable discrete step sizes. Necessary and sufficient conditions are derived to guarantee the quadratic stability of this class of switched systems via a switching state feedback law based on the existence of a common positive definite matrix satisfying the quadratic stabilizability condition by considering that the two subsystems are unstable. By state feedback, we mean that the switching among subsystems depends on the system states. Current results for this kind of state switching feedback control are derived only for switched systems evolving on a continuous time domain or a discrete time domain with fixed step’s size. These results are not applicable for the particular class of switched systems where there is a mixing between the continuous and discrete dynamics. This motivates the derivation of a new and more general state feedback control law for switched systems in this work. Here, a numerical example illustrating the results is presented.

42 ENGINEERING↗
DOE OSTI2024

AIRES-NODE

This software package performs time series forecasting for engineering systems using neural controlled differential equations. Neural controlled differential equations are continuous time analogues to recurrent neural networks. AIRES-NODE is particularly well suited for dynamic systems which are subject to external forcing terms and time-dependent boundary conditions. AIRES-NODE provides an encoder-decoder architecture which allows for variable-length forecasts to be made and is not limited to a fixed time step size when forecasting. Additionally, by utilizing a novel combination of a variational autoencoder and neural controlled differential equations, the AIRES-NODE package is capable of producing probabilistic future forecasts.

Gurecky, William [Oak Ridge National Laboratory (O↗
DOE OSTI2025

Stability analysis of the Eulerian–Lagrangian finite volume methods for nonlinear hyperbolic equations in one space dimension

In this paper, we construct a novel Eulerian–Lagrangian finite volume (ELFV) method for nonlinear scalar hyperbolic equations in one space dimension. It is well known that the exact solutions to such problems may contain shocks though the initial conditions are smooth, and direct numerical methods may suffer from restricted time step sizes. To relieve the restriction, we propose an ELFV method, where the space-time domain was separated by the partition lines originated from the cell interfaces whose slopes are obtained following the Rakine–Hugoniot junmp condition. Unfortunately, to avoid the intersection of the partition lines, the time step sizes are still limited. To fix this gap, we detect effective troubled cells (ETCs) and carefully design the influence region of each ETC, within which the partitioned space-time regions are merged together to form a new one. Then with the new partition of the space-time domain, we theoretically prove that the proposed first-order scheme with Euler forward time discretization is total-variation-diminishing and maximum-principle-preserving with at least twice larger time step constraints than the classical first order Eulerian method for Burgers’ equation. Numerical experiments verify the optimality of the designed time step sizes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

A comparative study of the parabolized Navier-Stokes code using various grid-generation techniques

The parabolized Navier-Stokes (PNS) equations are used to calculate the flow-field characteristics about the hypersonic research aircraft X-24C. A comparison of the results obtained using elliptic, hyperbolic, and algebraic grid generators is presented. The outer bow shock is treated as a sharp discontinuity, and the discontinuities within the shock layer are captured. Surface pressures and heat-transfer results at angles of attack of 6 deg and 20 deg, obtained using the three grid generators, are compared. The PNS equations are marched downstream over the body in both Cartesian and cylindrical base coordinate systems, and the results are compared. A robust marching procedure is demonstrated by successfully using large marching step sizes with the implicit shock fitting procedure. A correlation is found between the marching step size, Reynolds number, and the angle of attack at fixed values of smoothing and stability coefficients for the marching scheme.

Kaul, U. K.↗
NASA NTRS1985

A comparative study of the parabolized Navier-Stokes code using various grid-generation techniques

The parabolized Navier-Stokes (PNS) equations are used to calculate the flow-field characteristics about the hypersonic research aircraft X-24C. A comparison of the results obtained using elliptic, hyperbolic and algebraic grid generators is presented. The outer bow shock is treated as a sharp discontinuity, and the discontinuities within the shock layer are captured. Surface pressures and heat-transfer results at angles of attack of 6 deg and 20 deg, obtained using the three grid generators, are compared. The PNS equations are marched downstream over the body in both Cartesian and cylindrical base coordinate systems, and the results are compared. A robust marching procedure is demonstrated by successfully using large marching-step sizes with the implicit shock fitting procedure. A correlation is found between the marching-step size, Reynolds number and the angle of attack at fixed values of smoothing and stability coefficients for the marching scheme.

Kaul, U. K.↗
DOE OSTI2021

Deep Symbolic Optimization for Electric Component Sizing in Fixed Topology Power Converters

Power converters (PC) are a major component in any current electronic hardware device. The development and design is usually guided by expert knowledge and heavily relies on human intuition and experience. The process is a very time consuming and costly activity and it is generally hard to improve upon current designs. As a first step towards autonomous PC design, we are here proposing a new framework for the sizing of components for fixed topology PCs based on given design requirements. To this end, we developed surrogate models for rapid evaluation of new topologies and adapt the deep symbolic optimization (DSO) framework to generate new topologies guided by a reinforcement learning training signal. In an empirical evaluation, we show that our DSO based approach is able to find the optimal configuration for all investigated topologies, while reducing the learning time by at least a factor of 100 compared to popular RL algorithms.

Xue, Lincoln↗
NASA NTRS1980

Solar-ion penetration in the early solar nebula

A model for the early solar nebula is presented, along with the use of available ion range-energy relationships to determine when the irradiation of meteoritic grains occurred. Ions are assumed to travel on rectilinear paths with an energy change due solely to passage through absorbing materials, and consideration is given to the chances of energetic ions penetrating the nebular cloud to a distance of 3 AU. Cases of no absorbing gas, no absorbing dust, and the presence of both gas and dust are discussed, and model calculations are presented for protons and Fe nuclei ions. Penetration is found to decrease with the increase of the total amount of dust, a step function results when the size of the particles decreases, a fixed dust mass yields a penetration probability tending toward zero as the radius of the particles decreases, the fraction of the total dust mass required for penetration at 3 AU is small, and penetration to 3 AU readily occurs under present conditions.

Housen, K. R.↗
NASA NTRS1985

Mean Winds and Tides over Urbana, Illinois During November 16-22, 1981

The Urbana Meteor Radar uses a high power pulse transmitter to achieve high echo rates, and an interferometer to spatially locate the individual echoes. The irregularly spaced observations of range, radial velocity, and direction cosines are reduced to a rectangular grid, evenly spaced in time and height, of estimates of the zonal and meridional wind. This is accomplished using the method of GROVES whereby a constant horizontal wind is fitted, using least squares, to all echoes occurring within a fixed time/height interval. This interpolation region is then stepped in time and height. the size of the interpolation region is 2 hours by 5 km, the time step is approximately 11 minutes, and the height step is 2 km. The filtering of high temporal and spatial frequencies is somewhat reduced by weighting the echoes according to their distance from the center of the interpolation box.

Tetenbaum, D.↗
DOE OSTI2025

Feature engineering descriptors, transforms, and machine learning for grain boundaries and variable-sized atom clusters

Abstract Obtaining microscopic structure-property relationships for grain boundaries is challenging due to their complex atomic structures. Recent efforts use machine learning to derive these relationships, but the way the atomic grain boundary structure is represented can have a significant impact on the predictions. Key steps for property prediction common to grain boundaries and other variable-sized atom clustered structures include: (1) describing the atomic structure as a feature matrix, (2) transforming the variable-sized feature matrix to a fixed length common to all structures, and (3) applying a machine learning algorithm to predict properties from the transformed matrices. We examine how these steps and different combinations of engineered features impact the accuracy of grain boundary energy predictions using a database of over 7000 grain boundaries. Additionally, we assess how different engineered features support interpretability, offering insights into the physics of the structure-property relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Global error analysis of the Chebyshev rational approximation method

The Chebyshev rational approximation method (CRAM) has become a widely adopted method for solving nuclear depletion problems. Therefore, understanding CRAM’s accuracy is important for the safe operation of nuclear power plants. This article performs a global error analysis of CRAM and finds that, as the length of the time step approaches zero, the relative error measured between the exact and CRAM solutions at a fixed end time approaches one and infinity for even and odd orders, respectively; for intermediate time step sizes, a minimum in relative error is observed. Finally, we show that the reason for CRAM’s behavior is that the method is inconsistent. Two best practices for using CRAM, derived from these results, are: (1) use CRAM order 16 or higher, (2) if necessary, increase the CRAM order when multiphysics coupling requires smaller time steps.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2007

Visual Acuity Using Head-fixed Displays During Passive Self and Surround Motion

The ability to read head-fixed displays on various motion platforms requires the suppression of vestibulo-ocular reflexes. This study examined dynamic visual acuity while viewing a head-fixed display during different self and surround rotation conditions. Twelve healthy subjects were asked to report the orientation of Landolt C optotypes presented on a micro-display fixed to a rotating chair at 50 cm distance. Acuity thresholds were determined by the lowest size at which the subjects correctly identified 3 of 5 optotype orientations at peak velocity. Visual acuity was compared across four different conditions, each tested at 0.05 and 0.4 Hz (peak amplitude of 57 deg/s). The four conditions included: subject rotated in semi-darkness (i.e., limited to background illumination of the display), subject stationary while visual scene rotated, subject rotated around a stationary visual background, and both subject and visual scene rotated together. Visual acuity performance was greatest when the subject rotated around a stationary visual background; i.e., when both vestibular and visual inputs provided concordant information about the motion. Visual acuity performance was most reduced when the subject and visual scene rotated together; i.e., when the visual scene provided discordant information about the motion. Ranges of 4-5 logMAR step sizes across the conditions indicated the acuity task was sufficient to discriminate visual performance levels. The background visual scene can influence the ability to read head-fixed displays during passive motion disturbances. Dynamic visual acuity using head-fixed displays can provide an operationally relevant screening tool for visual performance during exposure to novel acceleration environments.

Wood, Scott J.↗
NASA NTRSDate not supplied

Multirotor Configuration Trades Informed by Handling Qualities for Urban Air Mobility Application

Many contemporary Advanced Air Mobility (AAM), and more specifically, urban air mobility (UAM) vehicle designers are attracted to variable rotor speed-controlled designs with multiple rotors because of the great potential for mass savings compared to more traditional, variable blade pitch-controlled vehicles. These designs are based on the assumption that the stability and control of recreation or basic utility-sized drones can be scaled to larger passenger-sized vehicles. Previous work had shown the challenges in stabilizing passenger-sized quadcopters. In this study, power constraints were made less restrictive and varied, allowing more control power. Motor parameters such as efficiency, nominal voltage and current operating point, and rise time of the rotor speed controller step response were studied. By fixing the efficiency of the motor to 95% and assuming a motor voltage to current ratio of 2.0 (previously, assumed to be 1.0), the authors were able to stabilize the quadcopter in the roll axis because this allowed the vehicle to achieve adequate rise times between 0.4 and 0.8 s. This motor optimization was extended to a hexacopter and octocopter designed to the same payload size and mission as the quadcopter. The three vehicle configurations and their motor speed controllers were compared. It was found that while hexacopter and octocopter required more mass and overall power; all three configurations had similar margins required for control. However, the hexacopter and octocopter were able to use this power margin to achieve lower rise times (i.e. the vehicle responded more quickly to pilot inputs) than the quadcopter, with the octocopter having the lowest rotor response rise time of the three vehicle configurations studied.

Multirotor↗
DOE OSTI2024

Adaptive time stepping for the two-time integro-differential Kadanoff-Baym equations

The nonequilibrium Green's function gives access to one-body observables for quantum systems. Of particular interest are quantities such as density, currents, and absorption spectra which are important for interpreting experimental results in quantum transport and spectroscopy. We present an integration scheme for the Green's function's equations of motion, the Kadanoff-Baym equations (KBE), which is both adaptive in the time integrator step size and method order as well as the history integration order. We analyze the importance of solving the KBE self-consistently and show that adapting the order of history integral evaluation is important for obtaining accurate results. To examine the efficiency of our method, we compare runtimes to a state-of-the-art fixed time step integrator for several test systems and show an order of magnitude speedup at similar levels of accuracy. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗