Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computation time”

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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Aeroelastic analysis of advanced propellers using an efficient Euler solver

A 3D Euler solver is coupled with a 3D structural dynamics model to investigate flutter of propfans. A hybrid scheme is used to reduce computational time for the Euler equations and a normal mode analysis is used for flutter calculations. Experimental and calculated flutter results are compared for an advanced propeller propfan which experienced flutter at transonic tip relative velocities. The predicted flutter calculations are in close agreement with the experimental data. A structural damping value of 0.5 percent was required to predict the behavior observed in the experiment. Computations show that the flutter behavior is dominated by the second mode, but coupling with the first mode is required. The addition of other modes to the calculations did not affect the flutter behavior.

Srivastava, R.↗
NASA NTRS2010

Public Risk Assessment Program

The Public Entry Risk Assessment (PERA) program addresses risk to the public from shuttle or other spacecraft re-entry trajectories. Managing public risk to acceptable levels is a major component of safe spacecraft operation. PERA is given scenario inputs of vehicle trajectory, probability of failure along that trajectory, the resulting debris characteristics, and field size and distribution, and returns risk metrics that quantify the individual and collective risk posed by that scenario. Due to the large volume of data required to perform such a risk analysis, PERA was designed to streamline the analysis process by using innovative mathematical analysis of the risk assessment equations. Real-time analysis in the event of a shuttle contingency operation, such as damage to the Orbiter, is possible because PERA allows for a change to the probability of failure models, therefore providing a much quicker estimation of public risk. PERA also provides the ability to generate movie files showing how the entry risk changes as the entry develops. PERA was designed to streamline the computation of the enormous amounts of data needed for this type of risk assessment by using an average distribution of debris on the ground, rather than pinpointing the impact point of every piece of debris. This has reduced the amount of computational time significantly without reducing the accuracy of the results. PERA was written in MATLAB; a compiled version can run from a DOS or UNIX prompt.

Mendeck, Gavin↗
DOE OSTI2022

Controller-Based Energy-Aware Wireless Sensor Network Routing Using Quantum Algorithms

Energy-efficient routing in wireless sensor networks has attracted attention from researchers in both academia and industry, most recently motivated by the opportunity to use software-defined network-inspired approaches. These problems are NP-hard, with algorithms needing computation time that scales faster than polynomials in the problem size. Consequently, heuristic algorithms are used in practice, which are unable to guarantee optimally. In this article, we show proof-of-principle for the use of a quantum annealing processor instead of a classical processor, to find optimal or nearly optimal solutions very quickly. Our preliminary results for small networks show that this approach using quantum computing has great promise and may open the door for other significant improvements in the efficacy of network algorithms.

42 ENGINEERING↗
DOE OSTI2022

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗
DOE OSTI2022

A fast and accurate modeling approach for water and steam thermodynamics with practical applications in district heating system simulation

In U.S. district heating (DH) systems, steam is the most common heat transport medium. Industry demand for new advanced modeling capabilities of complete steam DH systems is increasing; however, the existing models for water/steam thermodynamics are too slow for large system simulations because of computationally expensive algebraic loops that require the solution to nonlinear systems of equations. For practical applications, this work presents a novel split-medium approach that implements numerically efficient liquid water models alongside various water/steam models, breaking costly algebraic loops by decoupling mass and energy balance equations. New component models for steam DH systems are also presented. We implemented the models in the equation based Modelica language and evaluated accuracy and computing speed across multiple scales: from fundamental thermodynamic properties to complete districts featuring 10 to 200 buildings. Compared to district models with the IF97 water/steam model and equipment models from the Modelica Standard Library, the new implementation improves the scaling rate for large districts from cubic to quadratic with negligible compromise to accuracy. Additionally, for an annual simulation with 180 buildings, this translates to a computing time reduction from 33 to 1-1.5 h. These results are critically important for industry practitioners to simulate steam DH systems at large scales.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Grid Event Signature Library Analytics Report: Signature Matching Tool Development Efforts

This report describes the purpose and features of the Signature Matching Tool (SMT), employed in the Department of Energy (DOE) Grid Event Signature Library (GESL). The SMT supports a user of GESL to identify snippets of electric signatures, usually from sensor devices measuring electric characteristics such as phase voltages and currents, frequency, etc., suspected to represent certain events in the power grid but are not known to the user. The SMT uses a classification method to identify an event of the unknown signature, using the repository of known and labeled signatures in the GESL. The classifier applies a local binary classifier per node (LCN) approach to the unique event tag taxonomy used in the GESL, where training phases are separated based on the Primary labels in the taxonomy, sensor type, and voltage level. Results show that this method helps with computing time during training, in comparison to a flat, multinomial classifier, and produces acceptable average accuracy of 83% across all Primary labels. The report concludes with planned future work including integration to the web interface and API.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sequence2Self: Self-supervised image sequence denoising of pixel-level spray breakup morphology

Optical imaging of fast and transient phenomena such as the turbulent breakup of liquid sprays exhibit low signal-to-noise ratios due to the limited illumination intensity relative to the short exposure time. Image denoising is required to facilitate physical studies over these data but is challenging due to the absence of clean ground-truths and the stringency of the denoising task (e.g., strong and complex noise, limited resolution, preserving physical fidelity), preventing supervised and existing un-/self-supervised deep learning methods. To this end, Sequence2Self (Seq2S) is proposed, an extension of Self2Self (S2S) to image sequences that leverages both the signal’s spatial and temporal correlation. Seq2S is demonstrated on time-resolved x-ray phase contrast imaging of liquid jet fuel sprays in a gas turbine combustor, which possesses all of challenges detailed above. Experiments are conducted across four fuels with different breakup morphology using various state-of-the-art methods. Overall, many of the methods failed and Seq2S was most successful: (1) Accurate spray structures were reconstructed with consistent evolution across frames void of artifacts. (2) The performance was robust, invariant to the hyperparameter choice. (3) Computational time is short and can be made eligible for real-time denoising. In particular, the images denoised by Seq2S showed spray droplet diameter distributions with near-zero Kullback–Leibler divergence (0.01 ± 0.01) to a cleaner reference, whereas the second best method yielded 0.06 ± 0.03. In conclusion, this suggests that Seq2S can be reliably used prior to subsequent quantitative spray analyses as it retains (if not, improves) the statistical physical properties of the data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

An Efficient End-To-End Model for the Kepler Photometer

The Kepler Mission is designed to characterize the frequency of Earth-sized planets in the habitable zones of solar-like stars in the solar galactic neighborhood by observing >100,000 main-sequence stars in a >100 square degree field of view (FOV) and seeking evidence of transiting planets. As part of the system engineering effort, we have developed an End-To-End Model (ETEM) of the photometer to better characterize the expected performance of the instrument and to guide us in making design trades. This model incorporates engineering information such as the point spread function, time histories of pointing offsets, operating temperature, quantization noise, the effects of shutterless readout, and read noise. Astrophysical parameters, such as a realistic distribution of stars vs. magnitude for the chosen FOV, zodiacal light, and cosmic ray events are also included. For a given set of design and operating parameters, ETEM generates pixel time series for all pixels of interest for a single CCD channel of the photometer. These time series are then processed to form light curves for the target stars and the impact of various noise sources on the combined differential photometric precision can be determined. This model is of particular value when investigating the effects of noise sources that cannot be easily subjected to direct analysis, such as residual pointing offsets, thermal drift or cosmic ray effects. This version of ETEM features extremely efficient computation times relative to the previous version while maintaining a high degree of fidelity with respect to the realism of the relevant phenomena.

performance modeling↗
DOE OSTI2023

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Efficient Topology Design Algorithms for Power Grid Stability

The dynamic response of power grids to small disturbances influences their overall stability. This letter examines the effect of network topology on the linearized time-invariant dynamics of electric power systems. The proposed framework utilizes H 2 -norm based stability metrics to study the optimal placement of lines on existing networks as well as the topology design of new networks. The design task is first posed as an NP-hard mixed-integer nonlinear program (MINLP) that is exactly reformulated as a mixed-integer linear program (MILP) using McCormick linearization. To improve computation time, graph-theoretic properties are exploited to derive valid inequalities (cuts) and tighten bounds on the continuous optimization variables. Moreover, a cutting plane generation procedure is put forth that is able to interject the MILP solver and augment additional constraints to the problem on-the-fly. Finally, the efficacy of our approach in designing optimal grid topologies is demonstrated through numerical tests on the IEEE 39-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1988

Gaussian approximation versus nearly exact performance analysis of optical communication systems with PPM signaling and APD receivers

A 25-Mb/s direct-detection optical communication system that used Q = 4 PPM (pulse-position modulation) signaling was constructed and its performance measured under laboratory conditions. The system used a single-mode AlGaAs laser diode (lambda = 834 nm) and low-noise silicon avalanche photodiode (APD). A procedure for numerically computing system performance is given that uses the nearly exact Webb approximation of the true Conradi distribution for the APD output and does not require excessive amounts of computer time. Comparison revealed that modeling the APD ouptut as a Gaussian process under conditions of negligible background radiation and low (less than 10 to the -12 A) APD bulk leakage currents leads to substantial underestimates of optimal APD gain and overestimates of system bit error probability. Examples illustrate the breakdown of the Gaussian approximation in assessing system performance. The measured performance was in excellent agreement with that predicted by the computational procedure. The system achieved a bit error probability of 10 to the -6 at a received signal energy, corresponding to an average of 60 absorbed photons/bit and optimal APD gain of 700.

Davidson, Frederic M.↗
NASA NTRSDate not supplied

AstroLoc: An Efficient and Robust Localizer for a Free-flying Robot

We present AstroLoc, an efficient and robust monocular visual-inertial graph-based localization system used by the Astrobee free-flying robots onboard the International Space Station (ISS). We provide a novel localization system that limits the traditionally higher computation times for graph-based localization systems and enables the resource constrained Astrobee robots to benefit from their increased accuracy. We also introduce methods for handling cheirality issues for visual odometry and localization factors that further increase localization robustness. We evaluate the performance of AstroLoc on a dataset of ISS activities and show that it greatly improves pose, velocity, and IMU bias estimation accuracy while efficiently running in a limited computation environment. The source code for AstroLoc is released to the public.

Localization↗
DOE OSTI2024

Universal parameters of bulk-solvent masks

The bulk solvent is a major component of biomacromolecular crystals that contributes significantly to the observed diffraction intensities. Accurate modelling of the bulk solvent has been recognized as important for many crystallographic calculations. Owing to its simplicity and modelling power, the flat (mask-based) bulk-solvent model is used by most modern crystallographic software packages to account for disordered solvent. In this model, the bulk-solvent contribution is defined by a binary mask and a scale (scattering) function. The mask is calculated on a regular grid using the atomic model coordinates and their chemical types. The grid step and two radii, solvent and shrinkage, are the three parameters that govern the mask calculation. They are highly correlated and their choice is a compromise between the computer time needed to calculate the mask and the accuracy of the mask. It is demonstrated here that this choice can be optimized using a unique value of 0.6 Å for the grid step irrespective of the data resolution, and the radii values adjusted correspondingly. The improved values were tested on a large sample of Protein Data Bank entries derived from X-ray diffraction data and are now used in the computational crystallography toolbox ( CCTBX ) and in Phenix as the default choice.

36 MATERIALS SCIENCE↗
NASA NTRS2023

Compact Lightweight Aerial Sensor System (CLASSy)

In the wake of increasingly intense wildfires, innovative solutions are imperative to enhance wildfire mitigation strategies. Current technological integrations have hit a communicative limit. Between limited flight time, computational expenses as well as financial expenses, there is a hole in the market for an effective, low-tech, and disposable solution. The Compact Lightweight Aerial Sensor System (CLASSy) is designed to revolutionize active disaster operations through comprehensive decision support. CLASSy consists of a lightweight launch mechanism and a flight body equipped with a sensor package and parachute. The assembly integrates sensor networks with data analytics to provide real-time, high-resolution information to incident commanders, directly facilitating decision-making and resource allocation. Infrared imagery and temperature differentials are processed and analyzed throughout flight, offering valuable insights into fire behavior, hotspot detection, and fire spread trajectories. CLASSy is intended to meet a variety of natural disaster mitigation needs through its variable launch height and disposability. CLASSy’s goal is to assist wildfire fighting without taking up any human or material resources. As a result, CLASSy is as lightweight as possible, easily expendable, inexpensive to manufacture, and only requires one operator for effective use. CLASSy’s integrated sensor suite, real-time analytics, and closed loop active communications empower firefighting teams to proactively address wildfire challenges. As the frequency of wildfires continues to rise, technological innovations like CLASSy are crucial to effective wildfire management systems.

Kyleigh Anderson↗
DOE OSTI2026

Latent heat thermal energy storage performance maps enabling fast & accurate building energy simulations

Thermal energy storage (TES) using phase change materials (PCMs) has gained attention as an effective approach to manage energy demand fluctuations and shift peak building loads. PCM embedded heat exchangers (PCM-HXs) offer high energy storage density and low temperature variation during phase change, being suitable for load-shifting applications. However, this component is typically evaluated using computationally expensive methods, which present significant challenges when the ultimate goal is to assess the performance of PCM-HX integrated thermal energy storage systems in the full building context. In this paper, we present a methodology to generate highly accurate and computationally efficient PCM-HX performance maps which can be easily integrated into building energy simulation tools to analyze the feasibility of space conditioning systems with latent heat PCM-based TES. The performance maps are generated using a computationally efficient PCM-HX simulation tool based on a Generalized Resistance-Capacitance Model (GRCM) which can simulate arbitrary PCM-HXs with high accuracy and significantly less computational effort compared to full CFD simulations. The methodology was verified for a case study considering a 5-ton (~17.5 kW) air-to-water heat pump-thermal energy storage system (HP-TES), which was co-simulated in Modelica for a DOE prototype small-office building in Vienna, Austria, using Spawn of EnergyPlus™. The TES performance maps provided accurate predictions of PCM-HX behavior when used as Modelica component, with deviations within 2-4% while also achieving at least 103 computational time reduction. Leveraging this faster prediction capability, four PCMs with different melting temperatures for cooling (12°C, 16°C) and heating (31°C, 36°C) were assessed to investigate their impact on system performance. This work highlights the importance of robust PCM-HX models for efficient and high-fidelity building-level simulations, presenting new opportunities for advanced control strategy development and parametric analysis of TES configurations in a computationally efficient manner

Modelica Building Simulations↗
DOE OSTI2020

Optimal 1D Ly α forest power spectrum estimation – I. DESI-lite spectra

ABSTRACT The 1D Ly α forest flux power spectrum P1D is sensitive to scales smaller than a typical galaxy survey, and hence ties to the intergalactic medium’s thermal state, suppression from neutrino masses, and new dark matter models. It has emerged as a competitive framework to study new physics, but also has come with various challenges and systematic errors in analysis. In this work, we revisit the optimal quadratic estimator for P1D, which is robust against the relevant problems such as pixel masking, time evolution within spectrum, and quasar continuum errors. We further improve the estimator by introducing a fiducial power spectrum, which enables us to extract more information by alleviating the discreteness of band powers. We meticulously apply our method to synthetic Dark Energy Spectroscopic Instrument (DESI) spectra and demonstrate how the estimator overcomes each challenge. We further apply an optimization scheme that approximates the Fisher matrix to three elements per row and reduces computation time by 60 per cent. We show that we can achieve per cent precision in P1D with 5-yr DESI data in the absence of systematics and provide forecasts for different spectral qualities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Fast and flexible analysis of direct dark matter search data with machine learning

We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor of 30 when compared with the previous approach, without loss of performance on real data. We establish its flexibility to capture non-linear correlations between variables (such as smearing in light and charge signals due to position variation) by achieving equal performance using pulse areas with and without position-corrections applied. Its efficiency and scalability furthermore enables searching for dark matter using additional variables without significant computational burden. We demonstrate this by including a light signal pulse shape variable alongside more traditional inputs such as light and charge signal strengths. Furthermore, this technique can be exploited by future dark matter experiments to make use of additional information, reduce computational resources needed for signal searches and simulations, and make inclusion of physical nuisance parameters in fits tractable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1993

Development and comparison of advanced reduced-basis methods for the transient structural analysis of unconstrained structures

The development of two advanced reduced-basis methods, the force derivative method and the Lanczos method, and two widely used modal methods, the mode displacement method and the mode acceleration method, for transient structural analysis of unconstrained structures is presented. Two example structural problems are studied: an undamped, unconstrained beam subject to a uniformly distributed load which varies as a sinusoidal function of time and an undamped high-speed civil transport aircraft subject to a normal wing tip load which varies as a sinusoidal function of time. These example problems are used to verify the methods and to compare the relative effectiveness of each of the four reduced-basis methods for performing transient structural analyses on unconstrained structures. The methods are verified with a solution obtained by integrating directly the full system of equations of motion, and they are compared using the number of basis vectors required to obtain a desired level of accuracy and the associated computational times as comparison criteria.

Mcgowan, David M.↗