Digital communication and tracking - Ranging subsystem acquisition probabilities
Error acquisition probability in Mark 1 ranging subsystem as function of signal-to-noise ratio and integration time used in correlation
CORRELATION FUNCTION↗
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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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Minimum mean square error approximation of unknown probability distribution functions.
Double stochastic approximation algorithm for minimizing mean square error in finite expansion of unknown probability distribution functions
Deuser, L. M.↗
The resonance line of B II in IUE spectra of chemically peculiar stars
A description is presented of high-dispersion spectroscopic observations of eight chemically peculiar stars including Kappa Cnc and Mu Lep, and of one normal comparison star, Nu Cap, in the vicinity of 1362 A. The reported data were obtained with the International Ultraviolet Explorer during the first 15 months of its operation. The initial reduction of the data, which were originally described in a qualitative summary by Leckrone (1980), was affected by a serious error in the calibration of the instrument's intensity transfer function. This error has been corrected in the currently presented data. The results of spectrum syntheses of the 1362 A feature are also described for several of the stars.
Leckrone, D. S.↗
Unmasking Static Correlation Error in Hybrid Kohn–Sham Density Functional Theory
To uncover the way Hartree–Fock exchange brings static correlation error into hybrid Kohn–Sham density functional theory, we compare the potential energy curves of four diatomic molecules, namely, H 2 , F 2 , HF, and NaF, using both restricted and unrestricted Kohn–Sham theory. Here, we find that increasing the percentage of Hartree–Fock exchange significantly increases the static correlation error because Hartree–Fock exchange replaces the ability of local exchange in density functionals to account for the localization effects associated with static correlation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Density functional theory of water with the machine-learned DM21 functional
The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn–Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. Furthermore, we find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A fast semi-implicit algorithm for problems of mixed type
Certain physical processes are modeled by partial differential equations which are parabolic over part of the domain and elliptic over the remainder. A family of semi-implicit algorithms which are well suited to initial-boundary value problems of this mixed type is discussed. One important feature of these algorithms is the use of an approximate inverse for the solution of the implicit linear system. A strong error analysis results in an estimate of the total error as a function of approximate inverse error e and time step h.
Frederickson, P. O.↗
An Examination of Heavy Ion-Induced Persistent Visual Error Signatures in an Electronic Display Driver Integrated Circuit
Given the ubiquity of electronic displays integration in human-based systems, the impending mission critical, space-based applications of electronic displays will necessitate SEE assessment of components unique to electronic displays. A commercially available DDIC designed to drive a small form factor organic light emitting diode (OLED) was visually monitored during heavy ion irradiation to catalogue radiation induced persistent visual error signatures that require manual intervention (i.e., power cycling) to return to nominal function. These error signatures were able to be reproduced via modification of configuration register values utilizing the instruction set intended for interfacing a microcontroller with the DDIC. This approach to emulation of heavy-ion induced errors on a table-top assists with human perception-based criticality analysis as well as development of mitigation techniques.
Electronic Displays↗
Assessing the source of error in the Thomas–Fermi–von Weizsäcker density functional
We investigate the source of error in the Thomas–Fermi–von Weizsäcker (TFW) density functional relative to Kohn–Sham density functional theory (DFT). In particular, through numerical studies on a range of materials, for a variety of crystal structures subject to strain and atomic displacements, we find that while the ground state electron density in TFW orbital-free DFT is close to the Kohn–Sham density, the corresponding energy deviates significantly from the Kohn–Sham value. Here, we show that these differences are a consequence of the poor representation of the linear response within the TFW approximation for the electronic kinetic energy, confirming conjectures in the literature. In so doing, we find that the energy computed from a non-self-consistent Kohn–Sham calculation using the TFW electronic ground state density is in very good agreement with that obtained from the fully self-consistent Kohn–Sham solution.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm
The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.
D estefani, André↗
Burst-error characteristics of the equatorial transionospheric channel
Analyses of AGC analog data from the Small Astronomy Satellite (SAS) at VHF (136 MHz) have shown amplitude fluctuations in the signals received at several equatorial tracking sites operated by NASA. Errors in data are shown to increase markedly for nighttime satellite passes around the periods of the two equinoxes as compared to the errors observed during other periods. Qualitative and quantitative correlations are established between the ionospheric scintillation phenomenon and the occurrence of errors. Strong time and geographic cause-and-effect relationships are established by determining the statistical correlation between scintillation indices and bit error rates. Detailed analyses of the AGC fading statistics and the fine grain error statistics, such as the block-error distribution and the bit-error autocorrelation function, establish the strong correlation between deep fades and their effects on the burst error structure associated with the transionospheric channel and the communication receiver being employed.
Blank, H. A.↗
Accurate description of torsion potentials in conjugated polymers using density functionals with reduced self-interaction error
We investigate the torsion potentials in two prototypical π-conjugated polymers, polyacetylene and polydiacetylene, as a function of chain length using different flavors of density functional theory. Our study provides a quantitative analysis of the delocalization error in standard semilocal and hybrid density functionals and demonstrates how it can influence structural and thermodynamic properties. The delocalization error is quantified by evaluating the many-electron self-interaction error (MESIE) for fractional electron numbers, which allows us to establish a direct connection between the MESIE and the error in the torsion barriers. The use of non-empirically tuned long-range corrected hybrid functionals results in a very significant reduction of the MESIE and leads to an improved description of torsion barrier heights. In addition, we demonstrate how our analysis allows the determination of the effective conjugation length in polyacetylene and polydiacetylene chains.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Comparing the performance of density functionals in describing the adsorption of atoms and small molecules on Ni(111)
Reaction networks calculated using density functional theory (DFT) play a crucial role in understanding and predicting heterogeneous catalyst performance. However, results obtained using different density functionals can vary significantly. Accordingly, it is important to assess the accuracy of available functionals in capturing adsorption energetics derived from single-crystal adsorption microcalorimetry experiments. Here, we evaluate how different density functionals describe the molecular and dissociative adsorption of CH 3 I, the adsorption of CH 3 , I, and H, and the dissociative adsorption of CH 4 on Ni(111). First, we identify energetically-preferred adsorbed states for each adsorbate at three surface coverages and calculate the corresponding enthalpies of adsorption at 160 K. Then, we compare the results to experimental measurements published in the literature. For each adsorption process we find at least one functional that is quantitatively accurate within experimental error, but no functional is accurate (within experimental error) for all adsorption processes studied. Even when assuming an additional DFT error of ±20 kJ/mol on top of the experimental error, only the PBE-D3 and RPBE-D3 functionals are accurate for all considered adsorption systems. Overall, these results indicate that quantitative agreement between density functional theory calculations and experimental measurements is both system- and functional-dependent. Importantly, single-crystal adsorption microcalorimetry experiments will continue to play an important role for benchmarking density functionals.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mariner IV midcourse propulsion system impulse and accuracy prediction.
Mariner IV midcourse 50-lb thrust pressure- controlled monopropellant hydrazine propellant system, predicting impulse and velocity error as function of burn time
SPECIFIC IMPULSE↗
Modeling and measurement of error propagation in a multimodule computing system
An error propagation model has been developed for multimodule computing systems in which the main parameters are the distribution functions of error propagation times. A digraph model is used to represent a multimodule computing system, and error propagation in the system is modeled by general distributions of error propagation times between all pairs of modules. Two algorithms are developed to compute systematically and efficiently the distributions of error propagation times. Experiments are also conducted to measure the distributions of error propagation times with the fault-tolerant microprocessor (FTMP). Statistical analysis of experimental data shows that the error propagation times in FTMP do not follow a well-known distribution, thus justifying the use of general distributions in the present model.
Shin, Kang G.↗
A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers
This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.
Woodard, Stanley E.↗
Ocean data assimilation using optimal interpolation with a quasi-geostrophic model
A quasi-geostrophic (QG) stream function is analyzed by optimal interpolation (OI) over a 59-day period in a 150-km-square domain off northern California. Hydrographic observations acquired over five surveys were assimilated into a QG open boundary ocean model. Assimilation experiments were conducted separately for individual surveys to investigate the sensitivity of the OI analyses to parameters defining the decorrelation scale of an assumed error covariance function. The analyses were intercompared through dynamical hindcasts between surveys. The best hindcast was obtained using the smooth analyses produced with assumed error decorrelation scales identical to those of the observed stream function. The rms difference between the hindcast stream function and the final analysis was only 23 percent of the observation standard deviation. The two sets of OI analyses were temporally smoother than the fields from statistical objective analysis and in good agreement with the only independent data available for comparison.
Rienecker, Michele M.↗
Computing maximum tracking error due to payload dynamics
The determination of maximum endpoint tracking error due to uncompensated inertial payload dynamics is investigated. The problem is formulated on the basis of well-known kinetic and kinematic relationships with constraints on maximum joint positions and velocities as well as the generalized force/speed constraint relationship for each actuator. An endpoint tracking error objective function is formed, and numerical optimization is used to determine the maximum. An example computation is presented to show the tracking error under progressively increasing payload using a PUMA 560 manipulator with its first three joints in motion.
Kelkar, Atul G.↗
Uniform codes.
Existence of q-ary uniform convolutional codes where q is any prime-power, noting error- correcting ability comparable to familiar maximal- length block codes
ENCODING↗