Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “adaptive algorithm”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Autonomous Sensor System for Wind Turbine Blade Collision Detection

This paper presents an automated blade collision detection system for use on wind turbines, toward the goal of supporting monitoring and quantitative assessment of wind energy impacts on wildlife. A wireless, multisensor module mounted at the blade root measures surface vibrations, and a blade-mounted camera provides image capture of colliding objects. Using sensor data recorded during field testing of the system on an operational wind turbine, we present the development, training, and testing of automated detection algorithms for collision detection using machine-learning approaches. In particular, we compare the use of a new two-step, anomaly-based classification algorithm with conventional adaptive boosting and amplitude-based detection techniques, where the two-step approach improves average precision for the experimental data set. This integrated sensor and classification systems demonstrates a new approach for automated, on-blade collision detection for wind turbines, with broad utility across structural health monitoring applications.

17 WIND ENERGY↗
DOE OSTI2021

Power Grid Reliability Estimation via Adaptive Importance Sampling

Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.

power system faults↗
DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗
DOE OSTI2021

The Polar System Analysis Package (Ver. 1 Specifications)

The Polar System Analysis Package (POLeSTAr) is a modern data fusion tool being designed to benchmark,evaluate and compare the polar physics and biogeochemistry of Earth System Models (ESMs). It is being written in Python to make use of libraries including Xarray, Matplotlib, SciPy, NumPy and PyTorch within algorithms developed specifically for polar system modeling. Initial POLeSTAr algorithms will be adapted from the MATLAB Ridgepack package that was designed to analyze the Model for Prediction Across Scales (MPAS) sea ice component of the Energy Exascale Earth System Model (E3SM) and sea ice model CICE within the Community Earth System Model (CESM).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization

In this paper, we propose a hybrid method that uses stochastic and deterministic search to compute the maximum likelihood estimator of a low-rank count tensor with Poisson loss via state-of-theart local methods. Our approach is inspired by Simulated Annealing for global optimization and allows for fine-grain parameter tuning as well as adaptive updates to algorithm parameters. We present numerical results that indicate our hybrid approach can compute better approximations to the maximum likelihood estimator with less computation than the state-of-the-art methods by themselves.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Processing Particle Data Flows with SmartNICs

Many distributed applications implement complex data flows and need a flexible mechanism for routing data between producers and consumers. Recent advances in programmable network interface cards, or SmartNICs, represent an opportunity to offload data-flow tasks into the network fabric, thereby freeing the hosts to perform other work. System architects in this space face multiple questions about the best way to leverage SmartNICs as processing elements in data flows. In this paper, we advocate the use of Apache Arrow as a foundation for implementing data-flow tasks on SmartNICs. We report on our experiences adapting a partitioning algorithm for particle data to Apache Arrow and measure the on-card processing performance for the BlueField-2 SmartNIC. Our experiments confirm that the BlueField-2’s (de)compression hardware can have a significant impact on in-transit workflows where data must be unpacked, processed, and repacked.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

Adaptive control and identification via Liapunov's direct method.

The adaptive control and identification problems for single input, single output, time invariant systems with unknown parameters are considered here. A model reference is used and Liapunov's direct method provides the mechanisms for deriving the adaptive and identification algorithms. The Kalman Lemma (derived in connection with the Lure' problem) is shown to be extremely helpful in the design of these systems.

Monopoli, R. V.↗
NASA NTRS1973

Some approximation concepts for structural synthesis.

An efficient automated minimum weight design procedure is presented which is applicable to sizing structural systems that can be idealized by truss, shear panel, and constant strain triangles. Static stress and displacement constraints under alternative loading conditions are considered. The optimization algorithm is an adaptation of the method of inscribed hyperspheres and high efficiency is achieved by using several approximation concepts including temporary deletion of noncritical constraints, design variable linking, and Taylor series expansions for response variables in terms of design variables. Optimum designs for several planar and space truss example problems are presented. The results reported support the contention that the innovative use of approximation concepts in structural synthesis can produce significant improvements in efficiency.

Schmit, L. A., Jr.↗
NASA NTRS1973

Digital adaptive flight controller development

The development of a digital adaptive flight control algorithm is described that combines a weighted least squares estimator with optimal linear regulator control logic designed to minimize a quadratic model following performance index. Very promising results for a typical fighter aircraft's trajectory over six distinct flight conditions are reported.

Kaufman, H.↗
NASA NTRS1974

Some approximation concepts for structural synthesis

An efficient automated minimum weight design procedure is presented which is applicable to sizing structural systems that can be idealized by truss, shear panel, and constant strain triangles. Static stress and displacement constraints under alternative loading conditions are considered. The optimization algorithm is an adaptation of the method of inscribed hyperspheres and high efficiency is achieved by using several approximation concepts including temporary deletion of noncritical constraints, design variable linking, and Taylor series expansions for response variables in terms of design variables. Optimum designs for several planar and space truss examples problems are presented. The results reported support the contention that the innovative use of approximation concepts in structural synthesis can produce significant improvements in efficiency.

Schmit, L. A., Jr.↗
NASA NTRS1981

A modified adaptive delta modulator

This paper presents the results of a study in data compression of adaptive delta modulated video signals. The Song mode ADM is first investigated at a sampling rate of 16 Mbits/s and shown not to produce enough redundancy to warrant entropy encoding. A modified adaptive delta modulator algorithm is presented that operates at a sampling rate of 16 Mbits/s and does produce sufficient redundancy to yield a 40-50 percent data compression by using a simple code on 4 bit data blocks. Other techniques such as field interpolation and direct substitution are shown to increase the possible data compression further without noticeable degradation in the two input images used in this investigation. The effects of channel errors in the transmission of packet video over a computer network are considered. A leaky integrator is used to reduce the effects of channel errors in the data bits. It is shown that the effects of channel errors can be reduced by field interpolating those packets that can be shown to contain errors.

Barba, J.↗
NASA NTRS1982

Interaction of a cumulus cloud ensemble with the large-scale environment. IV - The discrete model

The Arakawa-Schubert (1974) parameterization is applied to a prognostic model of large-scale atmospheric circulations and used to analyze data in a general circulation model (GCM). The vertical structure of the large-scale model and the solution for the cloud subensemble thermodynamical properties are examined to choose cloud levels and representative regions. A mass flux distribution equation is adapted to formulate algorithms for calculating the large-scale forcing and the mass flux kernel, using either direct solution or linear programming. Finally, the feedback of the cumulus ensemble on the large-scale environment for a given subensemble mass flux is calculated. All cloud subensemble properties were determined from the conservation of mass, moist static energy, and total water.

Lord, S. J.↗
NASA NTRS1987

Incipient fault detection and power system protection for spaceborne systems

A program was initiated to study the feasibility of using advanced terrestrial power system protection techniques for spacecraft power systems. It was designed to enhance and automate spacecraft power distribution systems in the areas of safety, reliability and maintenance. The proposed power management/distribution system is described as well as security assessment and control, incipient and low current fault detection, and the proposed spaceborne protection system. It is noted that the intelligent remote power controller permits the implementation of digital relaying algorithms with both adaptive and programmable characteristics.

Russell, B. Don↗
NASA NTRS1987

Adaptive finite element methods for high-speed compressible flows

An adaptive finite element algorithm for solving the unsteady Euler equations is described. The finite element algorithm is based on a Taylor/Galerkin formulation and uses a very fast and efficient data structure to refine and unrefine the grid in order to optimize the approximation. A general version of the method which can be applied to moving grids with sliding interfaces is given, and results for a transient supersonic calculation of rotor-stator interaction are presented.

Oden, J. T.↗
NASA NTRS1988

Time domain simulation of the response of geometrically nonlinear panels subjected to random loading

The response of composite panels subjected to random pressure loads large enough to cause geometrically nonlinear responses is studied. A time domain simulation is employed to solve the equations of motion. An adaptive time stepping algorithm is employed to minimize intermittent transients. A modified algorithm for the prediction of response spectral density is presented which predicts smooth spectral peaks for discrete time histories. Results are presented for a number of input pressure levels and damping coefficients. Response distributions are calculated and compared with the analytical solution of the Fokker-Planck equations. RMS response is reported as a function of input pressure level and damping coefficient. Spectral densities are calculated for a number of examples.

Moyer, E. Thomas, Jr.↗
NASA NTRS1988

Adaptive suppression of biodynamic interference in helmet mounted and head down displays

This paper addresses errors caused by vibrations or turbulence in airborne helmet teleoperation, helmet mounted, and head down displays. A preliminary study is presented which indicates that these errors can be significantly suppressed by adaptive filtering. A modified version of the LMS adaptive noise suppression algorithm facilitates the separation of the voluntary large head movements from the vibration-induced small nonvoluntary head movements. Computer simulations demonstrate the potential of the approach in suppressing both aiming errors and apparent display blurring.

Merhav, Shmuel J.↗
NASA NTRS1988

Image processing software for imaging spectrometry

The paper presents a software system, Spectral Analysis Manager (SPAM), which has been specifically designed and implemented to provide the exploratory analysis tools necessary for imaging spectrometer data, using only modest computational resources. The basic design objectives are described as well as the major algorithms designed or adapted for high-dimensional images. Included in a discussion of system implementation are interactive data display, statistical analysis, image segmentation and spectral matching, and mixture analysis.

Mazer, Alan S.↗