Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Relative accuracy”

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 991 records · Page 55

Reformulation of the relativistic conversion between coordinate time and atomic time

The relativistic conversion between coordinate time and atomic time is reformulated to allow simpler time calculations relating analysis in solar system barycentric coordinates (using coordinate time) with earth-fixed observations (measuring 'earth-bound' proper time or atomic time). After an interpretation in terms of relatively well-known concepts, this simplified formulation, which has a rate accuracy of about 10 to the minus 15th, is used to explain the conventions required in the synchronization of a worldwide clock network and to analyze two synchronization techniques - portable clocks and radio interferometry. Finally, pertinent experimental tests of relativity are briefly discussed in terms of the reformulated time conversion.

Thomas, J. B.↗

Numerical prediction of axial turbine stage aerodynamics

A preliminary assessment is made of two NASA-developed unsteady turbine stage computer codes. The methodology and previous partial validation of the codes are briefly outlined. Application of these codes to a Space Shuttle main engine turbine for two sets of operating conditions is then described. Steady and unsteady, two and three-dimensional results are presented, compared, and discussed. These results include time-mean and instantaneous airfoil pressure distributions and pressure fluctuations, streamlines on the airfoil surfaces and endwalls, and relative total pressure contours at different axial locations in the rotor passage. Although not available at the time of this writing, experimental data for one of the operating conditions simulated is forthcoming and will be used to assess the accuracy of the unsteady, as well as, the steady predictions presented. Issues related to code usage and resource requirements of the two codes are also discussed.

Mcconnaughey, H. V.↗

Science Benefits of Onboard Spacecraft Navigation

Primitive bodies (asteroids and comets), which have remained relatively unaltered since their formation, are important targets for scientific missions that seek to understand the evolution of the solar system. Often the first step is to fly by these bodies with robotic spacecraft. The key to maximizing data returns from these flybys is to determine the spacecraft trajectory relative to the target body-in short, navigate the spacecraft- with sufficient accuracy so that the target is guaranteed to be in the instruments' field of view. The most powerful navigation data in these scenarios are images taken by the spacecraft of the target against a known star field (onboard astrometry). Traditionally, the relative trajectory of the spacecraft must be estimated hours to days in advance using images collected by the spacecraft. This is because of (1)!the long round-trip light times between the spacecraft and the Earth and (2)!the time needed to downlink and process navigation data on the ground, make decisions based on the result, and build and uplink instrument pointing sequences from the results. The light time and processing time compromise navigation accuracy considerably, because there is not enough time to use more accurate data collected closer to the target-such data are more accurate because the angular capability of the onboard astrometry is essentially constant as the distance to the target decreases, resulting in better "plane-of- sky" knowledge of the target. Excellent examples of these timing limitations are high-speed comet encounters. Comets are difficult to observe up close; their orbits often limit scientists to brief, rapid flybys, and their coma further restricts viewers from seeing the nucleus in any detail, unless they can view the nucleus at close range. Comet nuclei details are typically discernable for much shorter durations than the roundtrip light time to Earth, so robotic spacecraft must be able to perform onboard navigation. This onboard navigation can be accomplished through a self- contained system that by eliminating light time restrictions dramatically improves the relative trajectory knowledge and control and subsequently increases the amount of quality data collected. Flybys are one-time events, so the system's underlying algorithms and software must be extremely robust. The autonomous software must also be able to cope with the unknown size, shape, and orientation of the previously unseen comet nucleus. Furthermore, algorithms must be reliable in the presence of imperfections and/or damage to onboard cameras accrued after many years of deep-space operations. The AutoNav operational flight software packages, developed by scientists at the Jet Propulsion Laboratory (JPL) under contract with NASA, meet all these requirements. They have been directly responsible for the successful encounters on all of NASA's close-up comet-imaging missions (see Figure !1). AutoNav is the only system to date that has autonomously tracked comet nuclei during encounters and performed autonomous interplanetary navigation. AutoNav has enabled five cometary flyby missions (Table!1) residing on four NASA spacecraft provided by three different spacecraft builders. Using this software, missions were able to process a combined total of nearly 1000 images previously unseen by humans. By eliminating the need to navigate spacecraft from Earth, the accuracy gained by AutoNav during flybys compared to ground-based navigation is about 1!order of magnitude in targeting and 2!orders of magnitude in time of flight. These benefits ensure that pointing errors do not compromise data gathered during flybys. In addition, these benefits can be applied to flybys of other solar system objects, flybys at much slower relative velocities, mosaic imaging campaigns, and other proximity activities (e.g., orbiting, hovering, and descent/ascent).

Autonomy↗

Radiometric Quality of the MODIS Bands at 667 and 678nm

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top- of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Meister, Gerhard↗

Radiometric Quality of the MODIS Bands at 667 and 678nm

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top-of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Meister, Gerhard↗

Multimodel Ensembles of Wheat Growth: More Models are Better than One

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

wheat↗

Multimodel Ensembles of Wheat Growth: Many Models are Better than One

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop model scan give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 2438 for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

model intercomparison↗

A Multi-scaled Analysis of Forest Structure using Individual-Based Modeling in a Costa Rican Rainforest

Consideration of scale is essential when examining structural relationships in forests. In this study, we present a parameterization of the FORMIND individual-based forest model for old growth Atlantic lowland rainforest in La Selva, Costa Rica. Results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest within 2.3% of aboveground biomass values, based on comparisons with CARBONO inventory plot data. The Costa Rica FORMIND simulation was then used to investigate the relationship between canopy height and aboveground biomass (AGB), leaf area index (LAI) and gross primary productivity (GPP) at different spatial scales (20 × 20 m, 60 × 60 m, 100mx100m). The relationship between aboveground biomass and height is of particular importance toward the calibration of various remote sensing products including lidar and radar, whereas the LAI and GPP relationships are understudied in this context. We found that the relationship between all three variables and height varies considerably: the relationship is stronger at finer scales and weaker at coarser resolution. However, in all three comparisons, RMSE also decreased as scales coarsened, with the largest difference shown between 100 m and 10 m resolutions in relating AGB to Lorey's height (R^2 decreased by 0.3; RMSE decreased by 114.5 Mg/ha). This suggests that a trade-off between accuracy and precision exists, and further highlights the importance of spatial scale in determining the relatability of forest structure variables.

A.H.Armstrong↗

Accelerated computation of lattice thermal conductivity using neural network interatomic potentials

We report with the development of the density functional theory (DFT) and ever-increasing computational capacity, an accurate prediction of lattice thermal conductivity based on the Boltzmann transport theory becomes computationally feasible, contributing to a fundamental understanding of thermal conductivity as well as a choice of the optimal materials for specific applications. However, steep costs in evaluating third-order force constants limit the theoretical investigation to crystals with high symmetry and few atoms in the unit cell. Currently, machine learning potentials are garnering attention as a computationally efficient high-fidelity model of DFT, and several studies have demonstrated that the lattice thermal conductivity could be computed accurately via the machine learning potentials. However, test materials were mostly crystals with high symmetries, and the applicability of machine learning potentials to a wide range of materials has yet to be demonstrated. Furthermore, establishing a standard training set that provides consistent accuracy and computational efficiencies across a wide range of materials would be useful. To address these issues, herein we compute lattice thermal conductivities at 300 K using neural network interatomic potentials. As test materials, we select 25 materials with diverse symmetries and a wide range of lattice thermal conductivities between 10 -1 and 10 3 Wm -1 K -1 . Among various choices of training sets, we find that molecular dynamics trajectories at 50–700 K consistently provide results at par with DFT for the test materials. In contrast to pure DFT approaches, the computational cost in the present approach is uniform over the test materials, yielding a speed gain of 2–10 folds. When a smaller reduced training set is used, the relative efficiency increases by up to ~50 folds without sacrificing accuracy significantly. The current work will broaden the application scope of machine learning potentials by establishing a robust framework for accurately computing lattice thermal conductivity with machine learning potentials.

36 MATERIALS SCIENCE↗

L-band Dielectric Constant Measurements of Seawater (Oral presentation and SMOS Poster)

This paper describes a resonant cavity technique for the measurement of the dielectric constant of seawater as a function of its salinity. Accurate relationships between salinity and dielectric constant (which determines emissivity) are needed for sensor systems such as SMOS and Aquarius that will monitor salinity from space in the near future. The purpose of the new measurements is to establish the dependence of the dielectric constant of seawater on salinity in contemporary units (e.g. psu) and to take advantage of modern instrumentation to increase the accuracy of these measurements. The measurement device is a brass cylindrical cavity 16cm in diameter and 7cm in height. The seawater is introduced into the cavity through a slender glass tube having an inner diameter of 0.1 mm. By assuming that this small amount of seawater slightly perturbs the internal fields in the cavity, perturbation theory can be employed. A simple formula results relating the real part of the dielectric constant to the change in resonant frequency of the cavity. In a similar manner, the imaginary part of the dielectric constant is related to the change in the cavity s Q. The expected accuracy of the cavity technique is better than 1% for the real part and 1 to 2% for the imaginary part. Presently, measurements of methanol have been made and agree with precision measurements in the literature to within 1% in both real and imaginary parts. Measurements have been made of the dielectric constant of seawater samples from Ocean Scientific in the United Kingdom with salinities of 10, 30, 35 and 38 psu. All measurements were made at room temperature. Plans to make measurements at a range of temperatures and salinities will be discussed.

Lang, Roger H.↗

Learning macroscopic internal variables and history dependence from microscopic models

This paper concerns the study of history dependent phenomena in heterogeneous materials in a two-scale setting where the material is specified at a fine microscopic scale of heterogeneities that is much smaller than the coarse macroscopic scale of application. Here, we specifically study a polycrystalline medium where each grain is governed by crystal plasticity while the solid is subjected to macroscopic dynamic loads. The theory of homogenization allows us to solve the macroscale problem directly with a constitutive relation that is defined implicitly by the solution of the microscale problem. However, the homogenization leads to a highly complex history dependence at the macroscale, one that can be quite different from that at the microscale. In this paper, we examine the use of machine-learning, and especially deep neural networks, to harness data generated by repeatedly solving the finer scale model to: (i) gain insights into the history dependence and the macroscopic internal variables that govern the overall response; and (ii) to create a computationally efficient surrogate of its solution operator, that can directly be used at the coarser scale with no further modeling. We do so by introducing a recurrent neural operator (RNO), and show that: (i) the architecture and the learned internal variables can provide insight into the physics of the macroscopic problem; and (ii) that the RNO can provide multiscale, specifically FE 2 , accuracy at a cost comparable to a conventional empirical constitutive relation.

36 MATERIALS SCIENCE↗

The Davis–Chandrasekhar–Fermi method revisited

ABSTRACT Despite the rich observational results on interstellar magnetic fields in star-forming regions, it is still unclear how dynamically significant the magnetic fields are at varying physical scales, because direct measurement of the field strength is observationally difficult. The Davis–Chandrasekhar–Fermi (DCF) method has been the most commonly used method to estimate the magnetic field strength from polarization data. It is based on the assumption that gas turbulent motion is the driving source of field distortion via linear Alfvén waves. In this work, using MHD simulations of star-forming clouds, we test the validity of the assumption underlying the DCF method by examining its accuracy in the real 3D space. Our results suggest that the DCF relation between turbulent kinetic energy and magnetic energy fluctuation should be treated as a statistical result instead of a local property. We then develop and investigate several modifications to the original DCF method using synthetic observations, and propose new recipes to improve the accuracy of DCF-derived magnetic field strength. We further note that the biggest uncertainty in the DCF analysis may come from the linewidth measurement instead of the polarization observation, especially since the line-of-sight gas velocity can be used to estimate the gas volume density, another critical parameter in the DCF method.

79 ASTRONOMY AND ASTROPHYSICS↗

Short-arc orbit determination using coherent X-band ranging data

The use of X-band frequencies in ground-spacecraft and spacecraft-ground telecommunication links for current and future robotic interplanetary missions makes it possible to perform ranging measurements of greater accuracy than previously obtained. It is shown that ranging data of sufficient accuracy, when acquired from multiple stations, can sense the geocentric angular position of a distant spacecraft. The application of high-accuracy S/X-band and X-band ranging to orbit determination with relatively short data arcs is investigated in planetary approach and encounter scenarios. Actual trajectory solutions for the Ulysses spacecraft constructed from S/X-band ranging and Doppler data are presented; error covariance calculations are used to predict the performance of X-band ranging and Doppler data. The Ulysses trajectory solutions indicate that the aim point for the spacecraft's February 1992 Jupiter encounter was predicted to a geocentric accuracy of 0.20 to 0.23/microrad. Explicit modeling of range bias parameters for each station pass is shown to largely remove systematic ground system calibration errors and transmission media effects from the Ulysses range measurements, which would otherwise corrupt the angle finding capabilities of the data. The Ulysses solutions were found to be reasonably consistent with the theoretical results, which suggest that angular accuracies of 0.08 to 0.1/microrad are achievable with X-band ranging.

Thurman, S. W.↗

Measurement Decision Risk - The Importance of Definitions

One of the more misunderstood areas of metrology is the Test Uncertainty Ratio (TUR) and the Test Accuracy Ratio (TAR). There have been many definitions over the years, but why are these definitions important to a discussion on measurement decision risk? The importance lies in the clarity of communication. Problems can immediately arise in the application (or misapplication) of the definition of these terms. In other words, while it is important to understand the definitions, it is more important to understand concepts behind the definitions and to be precise in how they are applied. The objective of any measurement is a decision. Measurement Decision Risk is a way to look at the quality of a measurement, and although it is not a new concept, it has generated a lot of attention since its addition as a requirement in the new U.S. National Standard, ANSIINCSL Z540.3-2006. In addition to Measurement Decision Risk as the prime method of managing measurement risk, Z540.3 has added, as a fall-back, an explicit definition for TUR. The impact these new requirements may have on calibration service providers has become the topic of much discussion and in some cases concern. This paper will look at the concepts behind the definitions and how they relate to Measurement Decision Risk. Using common examples, this paper will also provide a comparison of various elements of risk related to measurement science using the concepts of TAR, TUR, accuracy ratios, and Consumer Risk (False Accept Risk). The goal of this paper is to provide a better understanding of their relevance to the measurement decision process.

Mimbs, Scott M.↗

Measurement Decision Risk - The Importance of Definitions

One of the more misunderstood areas of metrology is the Test Uncertainty Ratio (TUR) and its cousin, the Test Accuracy Ratio (TAR). There have been many definitions over the years, but why are these definitions important to a discussion on measurement decision risk? The importance lies in the clarity of communication. Problems can immediately arise in the application (or misapplication) of the definition of these terms. In other words, while it is important to understand the definitions, it is more important to understand concepts behind the definitions and to be precise in how they are applied. The objective of any measurement is a decision. Measurement Decision Risk is a way to look at the quality of a measurement and although it is not a new concept, it has generated a lot of attention since its addition as a requirement in the new U.S. National Standard, ANSI/NCSL Z540.3-2006. In addition to Measurement Decision Risk as the prime method of managing measurement risk, Z540.3 has also added, as a fall-back, an explicit definition for TUR. The impact these changes might have on calibration service providers if these requirements are levied on them has become the topic of much discussion and in some cases concern. This paper looks at the concepts behind the definitions and how they relate to Measurement Decision Risk. Using common examples, this paper will also provide a comparison of various elements of risk related to measurement science using the concepts of TAR, TUR, accuracy ratios, and Consumer Risk (False Accept Risk). The goal is to provide a better understanding of their relevance to the measurement decision process.

Mimbs, Scott M.↗

The system of EAS time analysis

The extensive air showers' (EAS) front shape, angle of incidence, disk thickness, particle distribution along the shower, on the delayed and EAS front advancing particles were determined. The suggested system of the EAS time analysis allows determination of the whole EAS longitudinal structure at the observation points. The information from the detectors is continuously recorded in the memory with the memory cell switching in 5 ns, this enables fixation of the moment of pulse input from the detector with an accuracy to + or - 2.5 ns. Along with the fast memory, a slow memory with the cell switching in 1 micron s is introduced in the system, this permits observation of relatively large time intervals with respect to the trigger pulse with an appropriately lower accuracy.

Khalafyan, A. Z.↗

Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration

A variable-order, variable-step Taylor series integration algorithm was implemented in NASA Glenn's SNAP (Spacecraft N-body Analysis Program) code. SNAP is a high-fidelity trajectory propagation program that can propagate the trajectory of a spacecraft about virtually any body in the solar system. The Taylor series algorithm's very high order accuracy and excellent stability properties lead to large reductions in computer time relative to the code's existing 8th order Runge-Kutta scheme. Head-to-head comparison on near-Earth, lunar, Mars, and Europa missions showed that Taylor series integration is 15.8 times faster than Runge- Kutta on average, and is more accurate. These speedups were obtained for calculations involving central body, other body, thrust, and drag forces. Similar speedups have been obtained for calculations that include J2 spherical harmonic for central body gravitation. The algorithm includes a step size selection method that directly calculates the step size and never requires a repeat step. High-order Taylor series integration algorithms have been shown to provide major reductions in computer time over conventional integration methods in numerous scientific applications. The objective here was to directly implement Taylor series integration in an existing trajectory analysis code and demonstrate that large reductions in computer time (order of magnitude) could be achieved while simultaneously maintaining high accuracy. This software greatly accelerates the calculation of spacecraft trajectories. At each time level, the spacecraft position, velocity, and mass are expanded in a high-order Taylor series whose coefficients are obtained through efficient differentiation arithmetic. This makes it possible to take very large time steps at minimal cost, resulting in large savings in computer time. The Taylor series algorithm is implemented primarily through three subroutines: (1) a driver routine that automatically introduces auxiliary variables and sets up initial conditions and integrates; (2) a routine that calculates system reduced derivatives using recurrence relations for quotients and products; and (3) a routine that determines the step size and sums the series. The order of accuracy used in a trajectory calculation is arbitrary and can be set by the user. The algorithm directly calculates the motion of other planetary bodies and does not require ephemeris files (except to start the calculation). The code also runs with Taylor series and Runge-Kutta used interchangeably for different phases of a mission.

Scott, James R.↗

Large scale surface heat fluxes

The heat flux through the ocean surface, Q, is the sum of the net radiation at the surface, the latent heat flux into the atmosphere, and the sensible heat flux into the atmosphere (all fluxes positive upwards). A review is presented of the geographical distribution of Q and its constituents, and the current accuracy of measuring Q by ground based measurements (both directly and by 'bulk formulae') is assessed. The relation of Q to changes of oceanic heat content, heat flux, and SST is examined and for each of these processes, the accuracy needed for Q is discussed. The needed accuracy for Q varies from process to process, varies geographically, and varies with the time and space scale considered.

Sarachik, E. S.↗