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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 181 records · Page 10

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NASA NTRS2019

Advanced Mathematics for Control System Design: Guidance, Navigation, and Control (GN&C) Studies

The study and control of inverted pendulum dynamics is of interest to NASA to better control the stability of a rocket. The different compartments of a rocket can move within a rocket during launch (i.e., rocket fuel slosh) and can affect its overall trajectory. Focusing on the inverted pendulum robot, PENNY, the dynamics are reduced to a simpler model which can prove to be more insightful for deriving more complex models and control laws. From the inverted pendulum bot, we can incorporate complexity into our physical model and approximate to the dynamics of a rocket (i.e., flexible inverted pendulum, multistage pendulum).

Autonomy↗

DOE OSTI2026

A Faster-Than-Real-Time Framework for Reliability-Oriented Simulation of PV Inverters

Physics-of-Failure (PoF) based reliability assessment for photovoltaic (PV) inverters requires long-duration electrical and electrothermal stress histories, yet generating such stress histories with high-fidelity switching models over year long mission profiles is computationally prohibitive. Conventional methods either sacrifice modeling fidelity for speed or require runtimes that are impractical for design iteration and uncertainty studies. To address this bottleneck, this paper presents a High-Performance Computing (HPC) based simulation frame work for faster-than-real-time reliability-oriented simulation. The proposed framework integrates the Average-to-Switching (A2S) method with parallel computing techniques to accelerate switching-level waveform reconstruction. We further introduce optimization strategies, including cluster merging and sensitivity based mission profile screening, to reduce the computational burden. Evaluated using real-world mission profile inputs and a MATLAB/Simulink switching-model reference, the framework reduces the simulation time for a one-year mission from an intractable multi-year duration to approximately 7.3 minutes while maintaining low waveform error. This acceleration provides a practical reliability-oriented simulation engine that can be coupled with component-specific aging models for subsequent PV inverter PoF assessment.

High-performance Computing↗

NASA NTRS1992

Ultrasonic and micromechanical study of damage and elastic properties of SiC/RBSN ceramic composites

Ultrasonic techniques are employed to develop methods for nondestructive evaluation of elastic properties and damage in SiC/RBSN composites. To incorporate imperfect boundary conditions between fibers and matrix into a micromechanical model, a model of fibers having effective anisotropic properties is introduced. By inverting Hashin's (1979) microstructural model for a composite material with microscopic constituents the effective fiber properties were found from ultrasonic measurements. Ultrasonic measurements indicate that damage due to thermal shock is located near the surface, so the surface wave is most appropriate for estimation of the ultimate strength reduction and critical temperature of thermal shock. It is concluded that bonding between laminates of SiC/RBSN composites is severely weakened by thermal oxidation. Generally, nondestructive evaluation of thermal oxidation effects and thermal shock shows good correlation with measurements previously performed by destructive methods.

Chu, Y. C.↗

NASA NTRS1947

Free-Spinning-Tunnel Tests of a 1/27-Scale Model of the Douglas XF3D-1 Airplane, TED No. NACA DE 312

Free-spinning-tunnel tests have been made on a 1/27-scale model of the Douglas XF3D-1 airplane to confirm a preliminary evaluation made of the airplane spin and recovery characteristics and previously reported. Recovery characteristics were satisfactory for erect and inverted spins when the model was in the clean condition. When the slow-down brakes were open, recoveries were slow. The pedal force necessary to reverse the airplane rudder during a spin will be within the physical capabilities of the pilot. A 10-foot-diameter parachute attached to the tail of the airplane (laid-out-flat diameter, drag coefficient 0.7) or a 4.5-foot-diameter parachute attached to the outboard wing tip will be satisfactory for emergency spin recovery from demonstration spins. If it becomes necessary for the crew to abandon the airplane during a spin, they should leave from the outboard side of the cockpit. The test results indicated spin and recovery characteristics generally similar to those indicated in the preliminary evaluation.

Scher, Stanley H.↗

NASA NTRS2004

The Robustness of Acoustic Analogies

Acoustic analogies for the prediction of flow noise are exact rearrangements of the flow equations N(right arrow q) = 0 into a nominal sound source S(right arrow q) and sound propagation operator L such that L(right arrow q) = S(right arrow q). In practice, the sound source is typically modeled and the propagation operator inverted to make predictions. Since the rearrangement is exact, any sufficiently accurate model of the source will yield the correct sound, so other factors must determine the merits of any particular formulation. Using data from a two-dimensional mixing layer direct numerical simulation (DNS), we evaluate the robustness of two analogy formulations to different errors intentionally introduced into the source. The motivation is that since S can not be perfectly modeled, analogies that are less sensitive to errors in S are preferable. Our assessment is made within the framework of Goldstein's generalized acoustic analogy, in which different choices of a base flow used in constructing L give different sources S and thus different analogies. A uniform base flow yields a Lighthill-like analogy, which we evaluate against a formulation in which the base flow is the actual mean flow of the DNS. The more complex mean flow formulation is found to be significantly more robust to errors in the energetic turbulent fluctuations, but its advantage is less pronounced when errors are made in the smaller scales.

Freund, J. B.↗

NASA NTRS1988

Random field estimation approach to multibody dynamics

The use of recursive techniques similar to random field models to factor and invert the inertia matrix of a multibody system is discussed. An equivalence is established between the composite multibody system inertia matrix and the covariance of the output of a described linear system model. Conditional mean estimation and sequential estimation problems are solved along with problems of filtering and smoothing. Formulas are developed to compute the covariance of several relevant quantities. The foregoing results are used to obtain the inverse of the composite multibody system inertia in closed form.

Rodriguez, G.↗

DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗

DOE OSTI2024

Towards a data-driven model of hadronization using normalizing flows

We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1996

Surface and Atmospheric Parameter Retrieval From AVIRIS Data: The Importance of Non-Linear Effects

AVIRIS data represent a new and important approach for the retrieval of atmospheric and surface parameters from optical remote sensing data. Not only as a test for future space systems, but also as an operational airborne remote sensing system, the development of algorithms to retrieve information from AVIRIS data is an important step to these new approaches and capabilities. Many things have been learned since AVIRIS became operational, and the successive technical improvements in the hardware and the more sophisticated calibration techniques employed have increased the quality of the data to the point of almost meeting optimum user requirements. However, the potential capabilities of imaging spectrometry over the standard multispectral techniques have still not been fully demonstrated. Reasons for this are the technical difficulties in handling the data, the critical aspect of calibration for advanced retrieval methods, and the lack of proper models with which to invert the measured AVIRIS radiances in all the spectral channels. To achieve the potential of imaging spectrometry, these issues must be addressed. In this paper, an algorithm to retrieve information about both atmospheric and surface parameters from AVIRIS data, by using model inversion techniques, is described. Emphasis is put on the derivation of the model itself as well as proper inversion techniques, robust to noise in the data and an inadequate ability of the model to describe natural variability in the data. The problem of non-linear effects is addressed, as it has been demonstrated to be a major source of error in the numerical values retrieved by more simple, linear-based approaches. Non-linear effects are especially critical for the retrieval of surface parameters where both scattering and absorption effects are coupled, as well as in the cases of significant multiple-scattering contributions. However, sophisticated modeling approaches can handle such non-linear effects, which are especially important over vegetated surfaces. All the data used in this study were acquired during the 1991 Multisensor Airborne Campaign (MAC-Europe), as part of the European Field Experiment on a Desertification-threatened Area (EFEDA), carried out in Spain in June-July 1991.

Green Robert O.↗

DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗

NASA NTRS1946

Free-Spinning Tunnel Tests of a 1/20-Scale Model of the Chance Vought XF6U-1 Airplane, TED No. NACA 2390

A spin investigation has been conducted in the Langley 20-foot free-spinning tunnel on a 1/20-scale model of the Chance Vought XF6U-1 airplane, The effects of control settings and movements upon the erect and inverted spin and recovery characteristics of the model were determined for the normal-fighter condition. The investigation also included tests for the take-off fighter condition (wing-tip tanks plus fuel added) spin-recovery parachutes, and simulated pilot escape. In general, for the normal-fighter condition, the model was extremely oscillatory in roll, pitch, and yaw. The angles of the fuselage varied from extremely flat to inverted attitudes, and the model rotated with the rudder in a series of short turns and glides. Recoveries by rudder reversal were rapid but the model would immediately go into a spin in the other direction. Recoveries by merely neutralizing the rudder were satisfactory when the elevator and ailerons were set to neutral, the ensuing flight path being a steep glide. Thus, it is recommended that all controls be neutralized for safe recovery from spins obtained on the airplane. With the external wing-tip tanks installed, the spins were somewhat less oscillatory in roll but recovery could not be obtained unless full-down elevator was used in conjunction with the rudder. If a spin is entered inadvertently with the full-scale airplane with external wing-tip tanks installed and if recovery is not imminent after a recovery attempt is made, it is recommended that the tanks be jettisoned and the controls neutralized.

Klinar, Walter J.↗

NASA NTRS1985

Geometric-optical modeling of a conifer forest canopy

A geometric-optical model of a conifer forest canopy was constructed to describe the variance of a remotely-sensed image of a forest stand. The model is driven by interpixel variance generated from three sources: (1) the number of crowns in the pixel; (2) the size of the individual crowns; and (3) the overlapping of crowns and shadows. The illumination of a tree and its shadow is described as a cone using parallel-ray geometry. The model can also be inverted to provide estimates of the size, shape and spacing of the trees using remotely-sensed imagery and a minimum of ground measurements. The results of field tests using 10-meter and 80-meter multispectral imagery of two test conifer stands in northeastern California are presented. It is shown that the model produces reasonable estimates for the geometric parameters of the stand and appears to be sufficiently robust for application to other geometric shapes corresponding to different types of vegetation.

Li, X.↗

NASA NTRS2005

Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms

In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.

Tedesco, Marco↗

DOE OSTI2025

On the Source of Conductivity in Alkaline Zn Anodes: Zn Percolation and ZnO Bridging

Alkaline Zn anodes are fundamental to commercial Zn-MnO 2 batteries as well as emerging rechargeable designs. In these electrodes, Zn particles are both the active material and source of electronic conduction. However, there are known cases in which electronic connectivity between Zn particles or the current collecting pin is lost even though the battery continues to function. Here we use X-ray computed tomography (CT) of AA batteries to demonstrate several examples of Zn particle-to-particle connectivity breakdown, which is observed even in cases at relatively high discharge rate. This indicates maintenance of the electronic network through the less-conductive ZnO discharge product. We introduce a new equation for electronic conductivity maintained through bridges of ZnO formed between percolating Zn particles. This necessitates discarding the Bruggeman correlation and instead redefining effective electronic conductivity using percolation theory. We demonstrate that such a model for conduction enables prediction of an inverted reaction zone, which is an experimentally observed case in which significant Zn dissolution and ZnO formation occurs heavily near the current collecting pin. Current computational Zn-MnO 2 models never predict an inverted reaction zone, and thus the updated conductivity enables models to accurately explain a wider range of experimental conditions.

Guida, Dominick P. [Northeastern Univ., Boston, MA↗

DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to sub-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗

DOE OSTI2024

Visibility-enhanced model-free deep reinforcement learning algorithm for voltage control in realistic distribution systems using smart inverters

Increasing integration of distributed solar photovoltaic (PV) into distribution networks could result in adverse effects on grid operation. Traditional model-based control algorithms require accurate model information that is difficult to acquire and thus are challenging to implement in practice. Here, this paper proposes a surrogate model-enabled grid visibility scheme to empower deep reinforcement learning (DRL) approach for distribution network voltage regulation using PV inverters with minimal system knowledge. In contrast to existing DRL methods, this paper presents and corroborates the adverse impact of missing load information on DRL performance and, based on this finding, proposes a surrogate model methodology to impute load information utilizing observable data. Additionally, a multi-fidelity neural network is utilized to construct the DRL training environment, chosen for its efficient data utilization and enhanced robustness to data uncertainty. The feasibility and effectiveness of the proposed algorithm are assessed by considering DRL testing across varying degrees of observable load information and diverse training environments on a realistic power system.

14 SOLAR ENERGY↗

NASA NTRS2000

Postural control model interpretation of stabilogram diffusion analysis

Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.

NASA Program Biomedical Research and Countermeasur↗

NASA NTRS1981

The ac propulsion system for an electric vehicle, phase 1

A functional prototype of an electric vehicle ac propulsion system was built consisting of a 18.65 kW rated ac induction traction motor, pulse width modulated (PWM) transistorized inverter, two speed mechanically shifted automatic transmission, and an overall drive/vehicle controller. Design developmental steps, and test results of individual components and the complex system on an instrumented test frame are described. Computer models were developed for the inverter, motor and a representative vehicle. A preliminary reliability model and failure modes effects analysis are given.

Geppert, S.↗