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At least 253 records · Page 14

Estimating Relative Positions of Outer-Space Structures

A computer program estimates the relative position and orientation of two structures from measurements, made by use of electronic cameras and laser range finders on one structure, of distances and angular positions of fiducial objects on the other structure. The program was written specifically for use in determining errors in the alignment of large structures deployed in outer space from a space shuttle. The program is based partly on equations for transformations among the various coordinate systems involved in the measurements and on equations that account for errors in the transformation operators. It computes a least-squares estimate of the relative position and orientation. Sequential least-squares estimates, acquired at a measurement rate of 4 Hz, are averaged by passing them through a fourth-order Butterworth filter. The program is executed in a computer aboard the space shuttle, and its position and orientation estimates are displayed to astronauts on a graphical user interface.

Balian, Harry↗

Eulerian-Lagrangian Simulations of Transonic Flutter Instabilities

This paper presents an overview of recent applications of Eulerian-Lagrangian computational schemes in simulating transonic flutter instabilities. This approach, the fluid-structure system is treated as a single continuum dynamics problem, by switching from an Eulerian to a Lagrangian formulation at the fluid-structure boundary. This computational approach effectively eliminates the phase integration errors associated with previous methods, where the fluid and structure are integrated sequentially using different schemes. The formulation is based on Hamilton's Principle in mixed coordinates, and both finite volume and finite element discretization schemes are considered. Results from numerical simulations of transonic flutter instabilities are presented for isolated wings, thin panels, and turbomachinery blades. The results suggest that the method is capable of reproducing the energy exchange between the fluid and the structure with significantly less error than existing methods. Localized flutter modes and panel flutter modes involving traveling waves can also be simulated effectively with no a priori knowledge of the type of instability involved.

Bendiksen, Oddvar O.↗

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗

Load distributions on slender delta wings having vortex flow

Results obtained through application of potential-flow theory based on a suction flow analogy for incompressible flow are compared to attached-flow theory and to experimental data acquired for sharp-edged delta wings. The error incurred in predicting structural loads on the basis of attached-flow theory is investigated. Force and moment coefficients and load distributions are used in the comparisons. The root bending moment can be estimated by assuming vortex lift concentrated at the wing leading edge. While this may entail some error at large angles of attack (owing to inboard movement of the center of vortex lift), it may furnish an upper bound in evaluating results based on other theories.

Kuhlman, J.↗

Reduction of truncation errors in modal analysis

A condensation method and computer program are described for large discrete parameter vibration analysis of complex structures that greatly reduces truncation errors and provides accurate definition of modes in a selected frequency range. A dynamic transformation is obtained from the partitioned equations of motion that relates modes not explicitly in the condensed solution to the retained modes at a selected system frequency. The generalized mass and stiffness matrices, obtained with existing modal synthesis methods, are reduced using this transformation and solved. Revised solutions are then obtained using new transformations at the calculated eigenvalues and are also used to assess the accuracy of the results. Computations are made tractable by simplified forms of the transformation that result with various modal synthesis methods. Three examples using the dynamic transformation in conjunction with a General Electric stiffness coupling method and the method of Craig and Bampton indicate large reductions in truncation errors and demonstrate the method for sequential groups of modes.

Kuhar, E. J.↗

An expert system for integrated structural analysis and design optimization for aerospace structures

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

Source record↗

Reflector sidelobe degradation due to random surface errors

It is well known that the sidelobe structure of a reflector antenna is highly susceptible to random surface errors, and that in most applications it is not adequate to investigate only the average behavior of the antenna. In this study, an attempt is made to determine the probability distribution of the sidelobe level of a reflector antenna subject to some random surface errors. Specifically, the random pattern function is considered and its sidelobe level studied using the level-upcrossing theory. Both the degradation of the maximum sidelobe and the degradation of the sidelobe region with respect to an International Radio Consultative Committee (CCIR) sidelobe envelope are obtained. The theoretical results are found in excellent agreement with those obtained by Monte Carlo simulations. Finally, some useful tolerance charts are presented.

Ling, H.↗

Sensor filter designs for large flexible spacecraft

Traditional control methods may excite flexible modes causing degraded performance or instability of large flexible space structures (LFSS). Control techniques developed for control of LFSS requires a numerical model of the structure and some knowledge of model error. This will be increasingly difficult with the complex space structures planned for the future. If filters could be used to condition the sensor output, control design would be less demanding. This paper is presented in viewgraph format.

Nimmo, Nancy A.↗

Inhomogeneous structural evolution of silver-containing Alpha-MnO2 nanorods in sodium-ion batteries investigated by comparative transmission electron microscopy approach

Alpha-MnO 2 is an attractive cathode candidate for sodium-ion batteries attributed to its unique one-dimensional 2×2 tunnels for facile sodium-ion diffusion, in addition to its incomparable cost advantage. In particular, α-MnO2 shows superior rate capability with silver stabilizing ions at the center of tunnels that improve electrical conductivity. In this work, we directly compare structural transformation of silver-containing α-MnO 2 nanorods (Ag 1.22 Mn 8 O 16-x or L-Ag-HOL and Ag 1.66 Mn 8 O 16-y or H–Ag-HOL), containing higher and lower concentrations of oxygen vacancies respectively, by transmission electron microscopy (TEM). The elaborate comparative and statistical TEM studies eliminate concerns regarding generalization errors and facilitate rational structural development of nanorods with improved functionality. It is found that sodium ions favorably diffuse through the area where oxygen vacancies are concentrated, and the samples with more silver ions and fewer oxygen vacancies (H–Ag-HOL) show more significant structural deformation with more inhomogeneous sodiation. The difference in functional electrochemistry coupled with the observed difference in inter- and intra-nanorod inhomogeneous structural evolution emphasizes the significance of the uniform electrical conductivity of the electrode. This work helps to improve the α-MnO 2 electrode material for sodium-ion batteries as well as suggesting the importance of delicate statistical approaches for TEM investigations.

25 ENERGY STORAGE↗

Precision in Assembled Discrete Lattice Space Structures for Next-Generation ISAM Applications

Robust autonomous robotic assembly of large-scale space structures has been a long-term and challenging goal to enable higher quality in-space communication and science instrumentation. For optical observatory support structures and antenna structures, the challenge is the strict dimensional precision requirements (generally RMS surface error) driven by the operational radiation wavelength. Early theoretical work in the area linked RMS surface error of a reflector support truss plate to the natural passive dynamic mode frequencies of the structure, as well as to the error distribution in dimensions of constituent structural elements. Prior robotic truss assembly demonstrations focused on designing ultra-high precision structural elements, joints, and robotic actuators. Recently, an alternative space structure assembly strategy based on a programmable matter approach (NASA ARMADAS) was demonstrated. This approach uses lattice building blocks (voxels) that are reversibly, mechanically joined into a bulk lattice structure by robots that locomote in and on the structure itself. Such a system can achieve high-level autonomy with low computation, robustly assemble utilizing inexpensive and imprecise robots, and efficiently build structures several orders of magnitude larger than the assembly robots. However, for instrumentation support structure applications, the resulting precision of these building block-based lattice structures is not well studied. Since they are demonstrated with many more assembly units than prior art trusses, it is unclear whether the same precision design approaches apply. In this work, we study in simulation the effects of voxel geometry, error in distribution, assembly resolution (module size), and assembly geometry on the error of both beam and plate lattice structures. While average RMS error of a plate increases with plate size, increasing plate thickness quickly collapses RMS error towards a limit that is on the order of the error of the constituent parts. We validate our models against previously published precision measurements of built systems. Results from this study will guide manufacturing precision requirements, as well as designs, for future robotically assembled structural applications and establish feasibility for different applications.

Christine E Gregg↗

Ytterbium ion trap quantum computing: The current state-of-the-art

In this work, we present an overview of contemporary quantum computing with ytterbium ion traps, placing the emphasis on industry implementations. We provide brief, concrete descriptions of various key features, such as trap loading, electronic structure, qubit function, gates, error analysis, and benchmarking. We focus on the underlying science and current technologies to provide readers with a holistic picture of available techniques for using ytterbium in contemporary ion trap designs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Understanding the origin of bandgap problem in transition and post-transition metal oxides

Improving electronic structure calculations for practical and technologically-important materials has been a never-ending pursue. This is especially true for transition and post-transition metal oxides for which the current first-principles approaches still suffer various drawbacks. Here we present a hierarchical-hybrid functional approach built on the use of pseudopotentials. The key is to introduce a discontinuity in the exchange functional between core and valence electrons. It allows for treating the localization errors of sp and d electrons differently, which have been known to be an important source of error for the band structure. Using ZnO as a prototype, we show the approach is successful in simultaneously reproducing the band gap and d-band position. Remarkably, the same approach, without having to change the hybrid mixing parameters from those of Zn, works reasonably well for other binary 3d transition and post-transition metal oxides across board. Finally, our findings point to a new direction of systematically improving the exchange functional in first-principles calculations.

36 MATERIALS SCIENCE↗

Additive manufacturing enabled hot-wire apparatus with suppressed edge effect error

This invention describes a method of structuring a metal or metal coated wire in a manner such that it provides enhanced accuracy when used in a hot-wire apparatus for transient thermal conductivity measurements for low-density materials. This is accomplished by using a diameter varying structure with two ends of the wire of sufficiently small diameter that the edge-effect induced error can be reduced by generating a more uniform temperature profile along the wire, whereas in conventional apparatus the temperatures always drop at the ends of a finite wire due to its ends that are being cooled by the wire-supports.

36 MATERIALS SCIENCE↗

Thermal-distortion analysis of a spacecraft box truss in geostationary orbit

The Mission to Planet Earth enlists the use of a geostationary platform to support Earth science monitoring instruments. The strongback for a proposed geostationary platform is a deployable box truss that supports two large diameter passive microwave radiometer (PMR) and several other science instruments. A study was performed to estimate the north-south and east-west pointing errors at the mounting locations of the two PMRs due to on-orbit thermal distortions of the main truss. The baseline configuration indicated that the east-west pointing error greatly exceeded the required limits. Primary origins of the pointing errors were identified, and methods for their reduction were discussed. Thermal performance enhancements to the truss structure were modeled and analyzed, including state-of-the-art surface coatings and insulation techniques. Comparisons of the thermal enhancements to the baseline were performed. Results demonstrated that using a thermal enclosure insulating technique reduced external heat fluxes, and distributed those heat fluxes more evenly throughout the structure, sufficiently reducing the pointing error to satisfy pointing accuracy requirements for the PMR's.

Cosgrove, Patrick A.↗

Q-BEEP: Quantum Bayesian Error Mitigation Employing Poisson Modeling over the Hamming Spectrum

Quantum computing technology has grown rapidly in recent years, with new technologies being explored, error rates being reduced, and quantum processor’s qubit capacity growing. However, near-term quantum algorithms are still unable to be induced without compounding consequential levels of noise, leading to non-trivial erroneous results. Quantum Error Correction (in-situ error mitigation) and Quantum Error Mitigation (post-induction error mitigation) are promising fields of research within the quantum algorithm scene, aiming to alleviate quantum errors, increasing the overall fidelity and hence the overall quality of circuit induction. Earlier this year, a pioneering work, namely HAMMER, published in ASPLOS-22 demonstrated the existence of a latent structure regarding post-circuit induction errors when mapping to the Hamming spectrum. However, they intuitively assumed that errors occur in local clusters, and that at higher average Hamming distances this structure falls away. In this work, we show that such a correlation structure is not only local but extends certain non-local clustering patterns which can be precisely described by a Poisson distribution model taking the input circuit, the device run time status (i.e., calibration statistics) and qubit topology into consideration. Using this quantum error characterizing model, we developed an iterative algorithm over the generated Bayesian network state-graph for post-induction error mitigation. Thanks to more precise modeling of the error distribution latent structure and the new iterative method, our Q-Beep approach provides state of the art performance and can boost circuit execution fidelity by up to 234.6% on Bernstein-Vazirani circuits and on average 71.0% on QAOA solution quality, using 16 practical IBMQ quantum processors. For other benchmarks such as those in QASMBench, the fidelity improvement is up to 17.8%. Q-Beep is a light-weight post-processing technique that can be performed offline and remotely, making it a useful tool for quantum vendors to integrate and provide more reliable circuit induction results.

Stein, Samuel A.↗

Stellar-reddening-based Extinction Maps for Cosmological Applications

Cosmological surveys must correct their observations for the reddening of extragalactic objects by Galactic dust. Existing dust maps, however, have been found to have spatial correlations with the large-scale structure of the Universe. Errors in extinction maps can propagate systematic biases into samples of dereddened extragalactic objects and into cosmological measurements such as correlation functions between foreground lenses and background objects and the primordial non-Gaussianity parameter f NL . Emission-based maps are contaminated by the cosmic infrared background, while maps inferred from stellar reddenings suffer from imperfect removal of quasars and galaxies from stellar catalogs. Thus, stellar-reddening-based maps using catalogs without extragalactic objects offer a promising path to making dust maps with minimal correlations with large-scale structure. We present two high-latitude integrated extinction maps based on stellar reddenings, with a point-spread functions of FWHMs 6'. 1 and 15'. We employ a strict selection of catalog objects to filter out galaxies and quasars and measure the spatial correlation of our extinction maps with extragalactic structure. Our galactic extinction maps have reduced spatial correlation with large-scale structure relative to most existing stellar-reddening-based and emission-based extinction maps.

79 ASTRONOMY AND ASTROPHYSICS↗

Stochastic process approximation for recursive estimation with guaranteed bound on the error covariance

An approach, is proposed for the design of approximate, fixed order, discrete time realizations of stochastic processes from the output covariance over a finite time interval, was proposed. No restrictive assumptions are imposed on the process; it can be nonstationary and lead to a high dimension realization. Classes of fixed order models are defined, having the joint covariance matrix of the combined vector of the outputs in the interval of definition greater or equal than the process covariance; (the difference matrix is nonnegative definite). The design is achieved by minimizing, in one of those classes, a measure of the approximation between the model and the process evaluated by the trace of the difference of the respective covariance matrices. Models belonging to these classes have the notable property that, under the same measurement system and estimator structure, the output estimation error covariance matrix computed on the model is an upper bound of the corresponding covariance on the real process. An application of the approach is illustrated by the modeling of random meteorological wind profiles from the statistical analysis of historical data.

Menga, G.↗

Modeling the behavior of concentrated aqueous HNO 3 using machine learning interatomic potentials

We develop two multi-defect machine learning interatomic potentials (MLIPs) trained at the BLYP-D2 and PBE-D3 density functional theories using the DeepMD-kit, allowing for the investigation of structural and thermodynamic properties of nitric acid over a wide range of concentrations via molecular dynamics (MD) simulations. We directly compute the degree of dissociation, α, and pK a from MD simulations, revealing that HNO 3 behaves as a weaker acid at higher concentrations, noting that our standard-state pK a value is in excellent agreement with the experimental one. In general, good agreement is observed with experimental results such as α and density outside the training dataset, with only modest deviations at low-to-medium concentrations. We benchmark our custom multi-defect DeepMD MLIPs against foundational models MACE-MP0 and MACE-OFF23. The foundation models capture some aspects of HNO 3 /NO 3 − solvation in concentrated nitric acid but show noticeable density errors and miss subtle structural features relevant to spectroscopy, whereas the bespoke DeepMD MLIPs yield more compact solvation shells, reproduce density-concentration trends, and run ∼12–15× faster than MACE-MP0. Although classical FFs are still more efficient and match experimental densities better, they lack chemical reactivity and thus cannot predict α or pK a , underscoring the need for system-specific reactive MLIPs beyond universal MLIPs.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗