Satellite situation report, volume 6, no. 1
Satellite situation report with identification data, orbital parameters, and transmission frequencies for objects in orbit, and dates for decayed objects
ORBIT DECAY↗
SEARCH · Engineering Papers
Results for “Parameter identification”
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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Technical and investigative support for high density digital satellite recording systems
Recent results of dropout measurements and defect analysis conducted on one reel of Ampex 721 which was submitted for evaluation by the manufacturer are described. The results or status of other tape evaluation activities are also reviewed. Several changes in test interpretations and applications are recommended. In some cases, deficiencies in test methods or equipment became apparent during continued work on this project and other IITRI tape evaluation projects. Techniques and equipment for future tasks such as tape qualification are also recommended and discussed. Project effort and expenditures were kept at a relatively low level. This rate provided added development time and experience with the IITRI Dropout Measurement System, which is approaching its potential as a computer based dropout analysis tool. Another benefit is the expanded data base on critical parameters that can be achieved from tests on different tape types and lots as they become available. More consideration and effort was directed toward identification of critical parameters, development of meaningful repeatable test procedures, and tape procurement strategy.
Schultz, R. A.↗
Resistance Curves in the Tensile and Compressive Longitudinal Failure of Composites
This paper presents a new methodology to measure the crack resistance curves associated with fiber-dominated failure modes in polymer-matrix composites. These crack resistance curves not only characterize the fracture toughness of the material, but are also the basis for the identification of the parameters of the softening laws used in the analytical and numerical simulation of fracture in composite materials. The method proposed is based on the identification of the crack tip location by the use of Digital Image Correlation and the calculation of the J-integral directly from the test data using a simple expression derived for cross-ply composite laminates. It is shown that the results obtained using the proposed methodology yield crack resistance curves similar to those obtained using FEM-based methods in compact tension carbon-epoxy specimens. However, it is also shown that the Digital Image Correlation based technique can be used to extract crack resistance curves in compact compression tests for which FEM-based techniques are inadequate.
Camanho, Pedro P.↗
Modal vector estimation for closely spaced frequency modes
Techniques for obtaining improved modal vector estimates for systems with closely spaced frequency modes are discussed. In describing the dynamical behavior of a complex structure modal parameters are often analyzed: undamped natural frequency, mode shape, modal mass, modal stiffness and modal damping. From both an analytical standpoint and an experimental standpoint, identification of modal parameters is more difficult if the system has repeated frequencies or even closely spaced frequencies. The more complex the structure, the more likely it is to have closely spaced frequencies. This makes it difficult to determine valid mode shapes using single shaker test methods. By employing band selectable analysis (zoom) techniques and by employing Kennedy-Pancu circle fitting or some multiple degree of freedom (MDOF) curve fit procedure, the usefulness of the single shaker approach can be extended.
Craig, R. R., Jr.↗
pyvisco [SWR-22-30]
pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. The necessary material model parameters are identified by fitting a Prony series to the experimental measurement data. pyvisco allows for the identification of Prony series parameters from experimental data measured in either the frequency-domain (via Dynamic Mechanical Thermal Analysis) or time-domain (via relaxation measurements). The experimental data can be provided as raw measurement sets at different temperatures or as pre-processed master curves. An optional minimization routine is included to reduce the number of Prony elements. This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time. See also, https://pypi.org/project/pyvisco/
Springer, Martin↗
The Making of a Metric: Co-Producing Decision-Relevant Climate Science
Developing decision-relevant science for adaptation requires the identification of climatic parameters that are both actionable for practitioners as well as tractable for modelers. In many sectors, these decision-relevant climatic metrics and the approaches that enable their identification remain largely unknown. “Co-production” of science with scientists and decision-makers is one potential way to identify these metrics, but there is little research describing specific and successful co-production approaches. This paper examines the negotiations and outcomes from Project Hyperion, wherein scientists and water managers jointly developed decision-relevant climatic metrics for adaptive water management. We identify successful co-production strategies by analyzing the project’s numerous back-and-forth engagements and tracing the evolution of the science during these engagements. We found that effective mediation between scientists and managers needed dedicated “boundary spanners” with significant modeling expertise. Translating practitioners’ information needs into tractable climatic metrics required direct and indirect methods of eliciting knowledge. We identified four indirect methods that were particularly salient for extracting tacitly held knowledge and enabling shared learning: developing a hierarchical framework linking management issues with metrics, starting discussions from the planning challenges, collaboratively exploring the planning relevance of new scientific capabilities, and using analogies of other “good” metrics. The decision-relevant metrics we developed provide insights into advancing adaptation-relevant climate science in the water sector. The co-production strategies we identified can be used to design and implement productive scientist–decision-maker interactions. Overall, the approaches and metrics we developed can help climate science to expand in new and more use-inspired directions.
Planning↗
Proposed input for determining longitudinal aerodynamic parameters for the space shuttle
A control input form to improve the identification of longitudinal aerodynamic parameters for the Space Shuttle, especially at low Mach numbers, has been proposed. This input combines features of several inputs currently used with the Shuttle to improve the response in angle-of-attack without exceeding pitch rate limits. The responses of the proposed input were generated using a simple three-degree-of-freedom simulation. An examination of the power spectral densities of these responses showed them to have more power near the vehicle natural frequency than doublet inputs previously used with the Shuttle. When the responses to the proposed input were corrupted with noise and processed using a maximum likelihood parameter extraction program, the identifiability of the parameters was improved over the identifiability of the same parameters using actual Shuttle responses from doublet input of a similar magnitude. This preliminary study indicates that the proposed input form should result in improved identifiability of longitudinal static and control parameters for the Shuttle vehicle.
Suit, W. T.↗
Frequency-Domain Modeling Of Dynamics Of Helicopters
Method for identification, in frequency domain, of parameters of mathematical models of dynamical behaviors of helicopters combines and extends several existing methods. Focuses on linear-state-space models. Comprehensive frequency-domain method for identification of parameters of mathematical model helicopter involves synthesis of several prior methods.
Tischler, Mark B.↗
The development of an augmented machine learning approach for the additive manufacturing of thermoelectric materials
Through the integration of machine learning (ML) techniques alongside additive manufacturing (AM) experimentation, we demonstrate an iterative process to rapidly predict laser-material interactions and melt pool geometries throughout the build parameter space for a bismuth telluride thermoelectric (TE) material. In doing so, we determined process parameters that created crack-free, highly dense (>99 %) n-type bismuth telluride (Bi 2 Te 2.7 Se 0.3 ) parts through laser powder bed fusion (LPBF). Furthermore, the ML-assisted understanding of the processing space allowed for the identification of build parameters that successfully yielded geometrically enhanced Bi 2 Te 2.7 Se 0.3 parts with reduced build times and no increase in experimental effort.
36 MATERIALS SCIENCE↗
Considerations for the Identification of Elasto-Plastic Material Model Parameters
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Fayad, Samuel Saiid↗
Identification of bearing and seal dynamic stiffness parameters
The results are presented of two simple tests, mainly steady state load test and squeeze film test, for establishing the coefficients of bearings and seals. It also discusses the methodology of the tests and some observed conclusions from the obtained data. Perturbation testing results are given as an example of verification and proof of validity of the two previous tests.
Bently, D. E.↗
Considerations for the Identification of Elasto-Plastic Material Model Parameters
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Fayad, Samuel Saiid↗
Some statistical performance characteristics of the 'ITD' modal identification algorithm
Performance characteristics of the Ibrahim time-domain algorithms are examined on a statistical basis. The method uses multiple free-response measurements from a test structure directly in the time domain, and displays varying accuracy, with the strongly excited modes identified most accurately and the weakly excited modes least accurately. Sets of computer-generated free-response functions for a simple 1-mode model are used to study the identification performance for several basic changes in the modal characteristics of the data, the user-selectable analysis constants, and the level of superimposed noise. Results indicate the existence of a direct and often linear effect of noise on the scatter of identified parameters, and good identification is maintained at the 1% noise level down to the point in frequency when only 1/4-cycle of data is analyzed.
Pappa, R. S.↗
Parameter estimation in space systems using recurrent neural networks
The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.
Parlos, Alexander G.↗
Propagation of statistical uncertainties of Skyrme mass models to simulations of r -process nucleosynthesis
Uncertainties in nuclear models have a major impact on simulations that aim at understanding the origin of heavy elements in the universe through the rapid neutron capture process ( r process) of nucleosynthesis. Within the framework of the nuclear density functional theory, we use results of Bayesian statistical analysis to propagate uncertainties in the parameters of energy density functionals to the predicted r -process abundance pattern, by way not only of the nuclear masses but also through the influence of the masses on β -decay and neutron capture rates. We point out the importance of the nonequilibrium end stage of the r process in determining the width of the resulting abundance pattern uncertainty bands. We additionally make the first identifications of specific parameters of Skyrme-like energy density functionals which show tentative correlations with particular aspects of the r -process abundance pattern. While previous studies have explored the reduction in the abundance pattern uncertainties due to anticipated new measurements of neutron-rich nuclei, here we point out that an even larger reduction will occur when these new measurements are used to reduce the uncertainty of model predictions of masses, which are then propagated through to the abundance pattern. We make a quantitative prediction for how large this reduction will be.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Lattice Parameter Evolution during the β-to-α and β-to-ω Transformations of Iron- and Aluminum-Modified Ti-11Cr(at.%)
β-titanium (β-Ti) alloys are useful in diverse industries because their mechanical properties can be tuned by transforming the metastable β phase into other metastable and stable phases. Relationships between lattice parameter and β-Ti alloy concentrations have been explored, but the lattice parameter evolution during β-phase transformations is not well understood. In this work, the β-Ti alloys, Ti-11Cr, Ti-11Cr-0.85Fe, Ti-11Cr-5.3Al, and Ti-11Cr-0.85Fe-5.3Al (all in at.%), underwent a 400 °C aging treatment for up to 12 h to induce the β-to-ω and β-to-α phase transformations. Phase identification and lattice parameters were measured in situ using high-temperature X-ray diffraction. Phase compositions were measured ex situ using atom probe tomography. During the phase transformations, Cr and Fe diffused from the ω and α phases into the β matrix, and the β-phase lattice parameter exhibited a corresponding decrease. The decrease in β-phase lattice parameter affected the α- and ω-phase lattice parameters. The α phase in the Fe-free alloys exhibited α-phase c/a ratios close to those of pure Ti. A larger β-phase composition change in Ti-11Cr resulted in larger ω-phase lattice parameter changes than that for Ti-11Cr-0.85Fe. This work illuminates the complex relationship between diffusion, composition, and structure for these diffusive/displacive transformations.
36 MATERIALS SCIENCE↗
An Indirect System Identification Technique for Stable Estimation of Continuous-Time Parameters of the Vestibulo-Ocular Reflex (VOR)
The vestibulo-ocular reflex (VOR) is a well-known dual mode bifurcating system that consists of slow and fast modes associated with nystagmus and saccade, respectively. Estimation of continuous-time parameters of nystagmus and saccade models are known to be sensitive to estimation methodology, noise and sampling rate. The stable and accurate estimation of these parameters are critical for accurate disease modelling, clinical diagnosis, robotic control strategies, mission planning for space exploration and pilot safety, etc. This paper presents a novel indirect system identification method for the estimation of continuous-time parameters of VOR employing standardised least-squares with dual sampling rates in a sparse structure. This approach permits the stable and simultaneous estimation of both nystagmus and saccade data. The efficacy of this approach is demonstrated via simulation of a continuous-time model of VOR with typical parameters found in clinical studies and in the presence of output additive noise.
Kukreja, Sunil L.↗
Some considerations in the evaluation of Seasat-A scatterometer /SASS/ measurements
A study is presented of the geophysical algorithms relating the Seasat-A scatterometer (SASS) backscatter measurements with a wind parameter. Although these measurements are closely related to surface features, an identification with surface layer parameters such as friction velocity or the roughness length is difficult. It is shown how surface truth in the form of wind speeds and coincident stability can be used to derive friction velocity or the equivalent neutral wind at an arbitrary height; it is also shown that the derived friction velocity values are sensitive to contested formulations relating friction velocity to the roughness length, while the derived values of the equivalent neutral wind are not. Examples of geophysical verification are demonstrated using values obtained from the Gulf of Alaska Seasat Experiment; these results show very little sensitivity to the type of wind parameter employed, suggesting that this insensitivity is mainly due to a large scatter in the SASS and surface truth data.
Halberstam, I.↗