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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Experimental unsteady aerodynamics of conventional and supercritical airfoils

Experimental data on the unsteady aerodynamics of oscillating airfoils in transonic flow are presented. Two 0.5 m-chord airfoil models - an NACA 64A010 and an NLR 7301 - were tested in the NASA-Ames 11 by 11 foot Transonic Wind Tunnel at Mach numbers to 0.85, at chord Reynolds numbers to 12 million and at mean angles of attack to 4 deg. The airfoils were subjected to both pitching and plunging motions at reduced frequencies to 0.3 (physical frequencies to 53 Hz). The new hardware and the extensive use of computer-experiment integration developed for this test are described. The geometrical configuration of the model and the test arrangement are described in detail. Mean and first harmonic data are presented in both tabular and graphical form to aid in comparisons with other data and with numerical computations.

Davis, S. S.↗
DOE OSTI2018

Weak and strong orders of linear recurring sequences

The concept of the strong order of linear recurring sequence (LRS) is introduced in this paper. Necessary and sufficient conditions for the existence of the strong LRS order are derived. The strong LRS order is exploited for the formalization of the problem of the extension of a sequence from the available fragment (fragments) of that sequence. The definition of the strong LRS order opens new possibilities for formal sequence analysis whenever the weak LRS order of that sequence exists. Computational experiments with discrete iterative maps are used to illustrate the applicability of the strong LRS order in nonlinear system analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics

Here, in this paper, we consider the problem of learning a regression function without assuming its functional form. This problem is referred to as symbolic regression. An expression tree is typically used to represent a solution function, which is determined by assigning operators and operands to the nodes. Cozad and Sahinidis propose a nonconvex mixed-integer nonlinear program (MINLP), in which binary variables are used to assign operators and nonlinear expressions are used to propagate data values through nonlinear operators, such as square, square root, and exponential. We extend this formulation by adding new cuts that improve the solution of this challenging MINLP. We also propose a heuristic that iteratively builds an expression tree by solving a restricted MINLP. We perform computational experiments and compare our approach with a mixed-integer program–based method and a neural network–based method from the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Predicting Complex Relaxation Processes in Metallic Glass

Relaxation processes significantly influence the properties of glass materials. However, understanding their specific origins is difficult; even more challenging is to forecast them theoretically. In this study, using microseconds molecular dynamics simulations together with an accurate many-body interaction potential, we predict that an Al 90 Sm 10 metallic glass would have complex relaxation behaviors: In addition to the main (α) relaxation, the glass (i) shows a pronounced secondary (β) relaxation at cryogenic temperatures and (ii) exhibits an anomalous relaxation process (α 2 ) accompanying α relaxation. Both of the predictions are verified by experiments. Computational simulations reveal the microscopic origins of relaxation processes: while the pronounced β relaxation is attributed to the abundance of stringlike cooperative atomic rearrangements, the anomalous α 2 process is found to correlate with the decoupling of the faster motions of Al with slower Sm atoms. The combination of simulations and experiments represents a first glimpse of what may become a predictive routine and integral step for glass physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Real-Time Radiological Source Term Estimation for Multiple Sources in Cluttered Environments

A particle filter algorithm is presented to estimate the position, strength, and cardinality of an unknown number of radioactive point sources in an obstacle-rich environment using count measurements. The algorithm addresses gaps in the prior literature by incorporating two novel elements. The first is a precomputation step in which local terrain and obstacle data is processed to compute attenuation kernels throughout the search area. This enables rapid estimation performance in obstacle-rich environments as measurements are gathered. The second novel feature is a dynamic particle allocation technique in which the number of particles is adjusted in real time to meet convergence goals. This feature allows the algorithm to scale more efficiently to scenarios with a larger number of sources. Furthermore, a series of computational experiments using simulated data demonstrates the algorithm’s performance in a cluttered environment with up to eight sources.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

EUCLID: Experiments Underpinned by Computational Learning for Improvements in Nuclear Data [Slides]

EUCLID will design validation experiments optimized to resolve compensating errors and adjust nuclear data to experiments. A big part of the success of the EUCLID proposal was due to previous work supported by NCSP (MCNP, nuclear data, and NCERC capabilities). The work performed under EUCLID will similarly benefit the NCSP mission. It will lead to new MCNP capabilities, improved nuclear data and nuclear data capabilities, and new methodology and tools that will have large impact on future NCERC experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Discovering Active Subspaces for High-Dimensional Computer Models

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. While sensible in some settings, this approach has obvious drawbacks. Recent research has demonstrated that active subspace calculations can be obtained in closed form, conditional on a Gaussian process (GP) surrogate, which can be limiting in high-dimensional settings for computational reasons. In this paper, we produce the relevant calculations for a more general case when the model of interest is a linear combination of tensor products. These general equations can be applied to the GP, recovering previous results as a special case, or applied to the models constructed by other regression techniques including multivariate adaptive regression splines (MARS). Furthermore, using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. In one real-world example, we obtain the active subspace of a radiation-transport code with 240 inputs and 9,372 model runs in under half an hour.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Gemma V&V/UQ/Credibility Activities: FY2020 Progress

This report describes the credibility activities undertaken in support of Gemma code development in FY20, which include Verification & Validation (V&V), Uncertainty Quantification (UQ), and Credibility process application. The main goal of these activities is to establish capabilities and process frameworks that can be more broadly applied to new and more advanced problems as the Gemma code development effort matures. This will provide Gemma developers and analysts with the tools needed to generate credibility evidence in support of Gemma predictions for future use cases. The FY20 Gemma V&V/UQ/Credibility activities described in this report include experimental uncertainty analysis, the development and use of methods for optimal design of computer experiments, and the development of a framework for validation. These initial activities supported the development of broader credibility planning for Gemma that continued into FY21.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2003

Software for Acoustic Rendering

SLAB is a software system that can be run on a personal computer to simulate an acoustic environment in real time. SLAB was developed to enable computational experimentation in which one can exert low-level control over a variety of signal-processing parameters, related to spatialization, for conducting psychoacoustic studies. Among the parameters that can be manipulated are the number and position of reflections, the fidelity (that is, the number of taps in finite-impulse-response filters), the system latency, and the update rate of the filters. Another goal in the development of SLAB was to provide an inexpensive means of dynamic synthesis of virtual audio over headphones, without need for special-purpose signal-processing hardware. SLAB has a modular, object-oriented design that affords the flexibility and extensibility needed to accommodate a variety of computational experiments and signal-flow structures. SLAB s spatial renderer has a fixed signal-flow architecture corresponding to a set of parallel signal paths from each source to a listener. This fixed architecture can be regarded as a compromise that optimizes efficiency at the expense of complete flexibility. Such a compromise is necessary, given the design goal of enabling computational psychoacoustic experimentation on inexpensive personal computers.

Miller, Joel D.↗
DOE OSTI2023

Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping

Abstract Understanding three‐dimensional (3D) root traits is essential to improve water uptake, increase nitrogen capture, and raise carbon sequestration from the atmosphere. However, quantifying 3D root traits by reconstructing 3D root models for deeper field‐grown roots remains a challenge due to the unknown tradeoff between 3D root‐model quality and 3D root‐trait accuracy. Therefore, we performed two computational experiments. We first compared the 3D model quality generated by five state‐of‐the‐art open‐source 3D model reconstruction pipelines on 12 contrasting genotypes of field‐grown maize roots. These pipelines included COLMAP, COLMAP+PMVS (Patch‐based Multi‐View Stereo), VisualSFM, Meshroom, and OpenMVG+MVE (Multi‐View Environment). The COLMAP pipeline achieved the best performance regarding 3D model quality versus computational time and image number needed. In the second test, we compared the accuracy of 3D root‐trait measurement generated by the Digital Imaging of Root Traits 3D pipeline (DIRT/3D) using COLMAP‐based 3D reconstruction with our current DIRT/3D pipeline that uses a VisualSFM‐based 3D reconstruction on the same dataset of 12 genotypes, with 5–10 replicates per genotype. The results revealed that (1) the average number of images needed to build a denser 3D model was reduced from 3000 to 3600 (DIRT/3D [VisualSFM‐based 3D reconstruction]) to around 360 for computational test 1, and around 600 for computational test 2 (DIRT/3D [COLMAP‐based 3D reconstruction]); (2) denser 3D models helped improve the accuracy of the 3D root‐trait measurement; (3) reducing the number of images can help resolve data storage problems. The updated DIRT/3D (COLMAP‐based 3D reconstruction) pipeline enables quicker image collection without compromising the accuracy of 3D root‐trait measurements.

09 BIOMASS FUELS↗
NASA NTRS2002

Tactical Defenses Against Systematic Variation in Wind Tunnel Testing

This paper examines the role of unexplained systematic variation on the reproducibility of wind tunnel test results. Sample means and variances estimated in the presence of systematic variations are shown to be susceptible to bias errors that are generally non-reproducible functions of those variations. Unless certain precautions are taken to defend against the effects of systematic variation, it is shown that experimental results can be difficult to duplicate and of dubious value for predicting system response with the highest precision or accuracy that could otherwise be achieved. Results are reported from an experiment designed to estimate how frequently systematic variations are in play in a representative wind tunnel experiment. These results suggest that significant systematic variation occurs frequently enough to cast doubts on the common assumption that sample observations can be reliably assumed to be independent. The consequences of ignoring correlation among observations induced by systematic variation are considered in some detail. Experimental tactics are described that defend against systematic variation. The effectiveness of these tactics is illustrated through computational experiments and real wind tunnel experimental results. Some tutorial information describes how to analyze experimental results that have been obtained using such quality assurance tactics.

DeLoach, Richard↗
DOE OSTI2022

Multi-stage heat release of multi-component fuels: Insights and implications for advanced engine operation

Multi-stage heat release (MSHR) is a unique phenomenon typically seen in lean/diluted and low- to intermediate-temperature combustion. Despite its relevance to advanced engine operation, the MSHR of multi-component fuels has barely been quantified. This study aims to characterize the MSHR of multi-component fuels in a rapid compression machine (RCM) at conditions representative of advanced combustion engines. New experimental data are first reported in the RCM at an equivalence ratio of 0.4, pressure of 60 bar and temperatures from 702 to 795 K for a research grade, multi-component gasoline surrogate, termed PACE-20. Here, experiments confirm the existence of MSHR for PACE-20 at all temperatures, and reveal the strong inhibiting effect of temperature on MSHR, where increasing temperature inhibits MSHR by suppressing first stage heat release and promoting second and third stage heat release. A detailed chemical kinetic model is also adopted to model the experiments, with good agreement observed. The response of MSHR characteristics to changes in different engine operating parameters (i.e., temperature, pressure, equivalence ratio and CO 2 dilution level) and fuel compositions (i.e., mole fraction of n-pentane, n-heptane, isooctane, cyclopentane, 1-hexene, ethanol and aromatics in PACE-20) is further evaluated via statistical analysis coupling quasi-random sampling, extensive computer experiments and high-dimensional model representation. The change in MSHR is characterized through 8 quantities of interest (QOIs), i.e., duration and extent of each heat release stage, and their standard deviations. The analysis highlights the dependence of the QOIs on the individual parameters as well as their interplays, with temperature exhibiting the strongest impact among all parameters. Furthermore, it is demonstrated that if MSHR is to be facilitated and combustion phasing is to be extended to enable engine operation at higher compression ratios, it is recommended to operate the engine at low intake temperatures, boosted intake pressures and high CO 2 dilutions (i.e., high EGR levels) with gasoline fuels containing more n-pentane and less aromatics.

42 ENGINEERING↗
NASA NTRS1993

The effect of grid aspect ratio on convergence

Vector stability theory and computational experiments are used to examine the effects of high aspect ratio grids on algorithm convergence. Emphasis is placed on identifying the degree of convergence deterioration that ADI schemes experience as grid aspect ratio increases and on deriving methods for circumventing this problem. Approximately factored implicit schemes are found to experience convergence deterioration because of nonoptimum local time stepping procedures and the increased need for viscous preconditioning. An enhanced algorithm is devised on the basis of improved selection of the local time step, appropriate definition of viscous preconditioning matrix, and proper implementation of boundary conditions. The novel algorithm provides uniformly efficient convergence at all aspect ratios for both Euler and Navier-Stokes computations for a variety of test problems.

Buelow, P. E. O.↗
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 NTRS1983

A versatile ground data display system for Spacelab experiments

A microprocessor-based data capture and display system suited to the needs of many Spacelab experimenters is described. Although developed specifically for the needs of the FAUST UV astronomy telescope, several features of the system may make it attractive to other groups who need to interact with their Spacelab data in real or near-real time. The display system captures data from the serial data stream originating in the Spacelab experiment computer input/output (ECIO) data channel, and can reformat and display several hundred variables per second in real time. The system offers a combination of CRT display and analog paper strip-chart output. A facility is also provided for simultaneously creating floppy-disk records of short segments of data according to prearranged criteria, to allow detailed examination of critical events in the operation of the experiment. The simplicity, economy, reliability, and flexibility of the display system suggest its use for monitoring a variety of low- and medium-data-rate Spacelab experiments.

Werthimer, D.↗
NASA NTRS1994

Effect of grid aspect ratio on convergence

The effects of high-aspect-ratio grids on algorithm convergence are considered by means of vector stability theory and computational experiments. The results indicate that approximately factored implicit schemes experience convergence deterioration because of nonoptimum local time-stepping procedures and increased need for viscous preconditioning. Based on this insight, an enhanced algorithm is devised using improved selection of the local time step, appropriate definition of the viscous preconditioning matrix, and proper implementation of the boundary conditions. The new algorithm provides uniformly efficient convergence at all aspect ratios for both Euler and Navier-Stokes computations for a variety of test problems.

Buelow, P. E. O.↗
DOE OSTI2025

Motion Dynamics of Motile Microbes in Pore-Networks and its Implications for Reactive Transport Processes

This report outlines new methods to improve simulations of microbial transport and microbially mediated reactions in porous media. A range of experimental, modeling, and machine learning tools are introduced to make these simulations faster, more reliable, and useful for real-world applications. At the microscopic level, the study investigates how different types of bacteria move through confined spaces. A new artificial intelligence tool called DeepTrackStat, is introduced to track motions dynamics as observed in videos of particles migrating through pore networks. This tool is especially helpful for studying fast-moving microbes and requires less computing power than traditional tracking methods. At larger scales, the research looks at how microbes and chemicals interact in zones where surface water and groundwater meet. To connect the small- and large-scale findings, the study presents a neural network model called STAMNet. This tool helps scale up detailed small-scale microbial motion behaviors to predict large-scale environmental changes more efficiently. By combining lab experiments, computer models, and artificial intelligence, the research presented supports smarter environmental decision-making, especially in bioremediation of contaminated groundwater and protection of water quality.

54 ENVIRONMENTAL SCIENCES↗