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At least 937 records · Page 52

Understanding Shock Dynamics in the Inner Heliosphere with Modeling and Type II Radio Data: the 2010-04-03 Event

The 2010 April 03 solar event was studied using observations from STEREO SECCHI, SOHO LASCO, and Wind kilometric Type II data (kmTII) combined with WSA-Cone-ENLIL model simulations performed at the Community Coordinated Modeling Center (CCMC). In particular, we identified the origin of the coronal mass ejection (CME) using STEREO EUVI and SOHO EIT images. A flux-rope model was fit to the SECCHI A and B, and LASCO images to determine the CMEs direction, size, and actual speed. J-maps from STEREO COR2HI-1HI-2 and simulations fromCCMC were used to study the formation and evolution of the shock in the inner heliosphere. In addition, we also studied the time-distance profile of the shock propagation from kmTII radio burst observations. The J-maps together with in-situ datafrom the Wind spacecraft provided an opportunity to validate the simulation results andthe kmTII prediction. Here we report on a comparison of two methods of predictinginterplanetary shock arrival time: the ENLIL model and the kmTII method; andinvestigate whether or not using the ENLIL model density improves the kmTIIprediction. We found that the ENLIL model predicted the kinematics of shock evolutionwell. The shock arrival times (SAT) and linear-fit shock velocities in the ENLILmodel agreed well with those measurements in the J-maps along both the CME leading edge and the Sun-Earth line. The ENLIL model also reproduced most of the largescale structures of the shock propagation and gave the SAT prediction at Earth with an error of 17 hours. The kmTII method predicted the SAT at Earth with an error of 15 hours when using n0 4.16 cm3, the ENLIL model plasma density near Earth; but itimproved to 2 hours when using n0 6.64 cm3, the model density near the CMEleading edge at 1 AU.

Space weather forecast↗

Lessons Learned in Fabrication of a High-Specific-Torque Concentric Magnetic Gear

Magnetic gearing is being investigated at NASA as a replacement to conventional mechanical gearing in aerospace applications. Some key benefits of magnetic gears over mechanical gearing are torque transmission without mechanical contact, decreased transmission noise, less frequent maintenance, and lack of lubrication. In order to take advantage of these benefits in aerospace applications, magnetic gearing must be shown to provide high enough specific torque (torque per unit mass). Prototype 2 (PT-2), developed to maximize specific torque, and fabricated at NASA Glenn Research Center, has shown promising specific torque comparable to low torque mechanical gears. This work will briefly review the electromagnetic and structural design of PT-2, provide detailed information on fabrication and assembly, examine build errors, walk through rebuild efforts to improve operation, and conclude with remarks on build difficulties and opportunities for improvement in future prototypes.

Electrified Vertical Take Off and Landing↗

Lessons Learned in Fabrication of a High-Specific-Torque Concentric Magnetic Gear

Magnetic gearing is being investigated at NASA as a replacement to conventional mechanical gearing in aerospace applications. Some potential benefits of magnetic gears over mechanical gearing are torque transmission without mechanical contact, decreased transmission noise, and no required lubrication. However, in order to be a viable alternative for aerospace applications, magnetic gearing must be shown to provide high enough specific torque (torque per unit mass). NASA's second magnetic gearing prototype (PT-2) was able to achieve promising specific torque on par with low torque mechanical gearboxes. This work will briefly review the electromagnetic and structural design of PT-2, provide detailed information on fabrication and assembly, examine build errors, walk through rebuild efforts to improve operation, and conclude with remarks on build difficulties and opportunities for improvement in future prototypes.

Magnetic Gearing↗

A Systematic Approach to Isolating the Causes and Impacts of Climate Model Bias Employing Analysis Increments

One of the most promising approaches to isolating the causes and understanding the impacts of climate model formulation errors is through the utilization of information contained in short-term forecast errors. The underlying assumption being that by capturing the errors at the very early stages of growth (before nonlinearities develop), we should be able to associate those errors with specific deficiencies in the model's formulation of the relevant physical processes. Here, we provide an example of utilizing the long-term mean of the 6-hourly analysis increments (first guess forecast minus analysis) produced by MERRA-2 to correct the NASA/GEOS AGCM over well-defined regions, thereby allowing us to quantify how the reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections to reduce the model's climatological biases. We extend previous work (focused on boreal summer) to address the full annual cycle of model bias. A key result is the large seasonality of the errors over the Tibet region and their impacts on the Northern Hemisphere jet biases, and related precipitation and temperature biases over North American. Attempts to correct the phase and amplitude errors of the climatological boreal winter ridge over western North America (a likely key requirement for improving winter climate forecasts over North America) reveal a surprising complexity in the sources of the errors in what is otherwise manifest as a rather simple PNA-like bias structure.

Schubert, S.↗

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Two-Stage Passive Vibration Isolator

The design and testing of a structural system were implemented to hold the optics of the planned Space Interferometry Mission (SIM) at positions and orientations characterized by vibrational translation and rotation errors of no more than a few nanometers or a few milliarcseconds, respectively. Much of the effort was devoted to a test bed for verifying the predicted behavior of a vibration- isolation structural subsystem working together with an active control system for positioning and orienting the SIM optics. There was considerable emphasis on the vibration-isolation subsystem, which was passive and comprised two stages. The main sources of vibration were six reaction wheels in an assembly denoted the "backpack." The first vibration-isolation stage consisted of hexapod isolator mounts - one for each reaction wheel - characterized by a natural vibration frequency of 10 Hz. The second stage was a set of three beams, disposed between the backpack and the structure that held the SIM optics, that were flexured such that they transmitted only bending loads, with a natural vibrational frequency and damping of about 5 Hz and 4 percent, respectively. Preliminary test results were presented and characterized as demonstrating the effectiveness of the two-stage vibration-isolation design.

Goullioud, Renaud↗

Actuated Hybrid Mirror Telescope

The figure depicts the planned Actuated Hybrid Mirror Telescope (AHMT), which is intended to demonstrate a new approach to the design and construction of wide-aperture spaceborne telescopes for astronomy and Earth science. This technology is also appropriate for Earth-based telescopes. The new approach can be broadly summarized as using advanced lightweight mirrors that can be manufactured rapidly at relatively low cost. More specifically, it is planned to use precise replicated metallic nanolaminate mirrors to obtain the required high-quality optical finishes. Lightweight, dimensionally stable silicon carbide (SiC) structures will support the nanolaminate mirrors in the required surface figures. To enable diffraction- limited telescope performance, errors in surface figures will be corrected by use of mirror-shape-control actuators that will be energized, as needed, by a wave-front-sensing and control system. The concepts of nanolaminate materials and mirrors made from nanolaminate materials were discussed in several previous NASA Tech Briefs articles. Nanolaminates constitute a relatively new class of materials that can approach theoretical limits of stiffness and strength. Nanolaminate mirrors are synthesized by magnetron sputter deposition of metallic alloys and/or compounds on optically precise master surfaces to obtain optical-quality reflector surfaces backed by thin shell structures. As an integral part of the deposition process, a layer of gold that will constitute the reflective surface layer is deposited first, eliminating the need for a subsequent and separate reflective-coating process. The crystallographic textures of the nanolaminate will be controlled to optimize the performance of the mirror. The entire deposition process for making a nanolaminate mirror takes less than 100 hours, regardless of the mirror diameter. Each nanolaminate mirror will be bonded to its lightweight SiC supporting structure. The lightweight nanolaminate mirrors and SiC supporting structures will be fabricated from reusable master molds. The mirror-shape-control actuators will be low-power, high-capacitance lead magnesium niobate electrostrictive actuators that will be embedded in the SiC structures. The mode of operation of these actuators will be such that once power was applied, they will change in length and once power was removed, they will maintain dimensional stability to nanometer precision. This mode of operation will enable the use of low-power, minimally complex electronic control circuitry. The wave-front-sensing and control system will be designed and built according to a two-stage architecture. The first stage will be implemented by a Shack- Hartmann (SH) sensor subsystem, which will provide a large capture range. The second, higher-performance stage will be implemented by an image-based wave-front-sensing subsystem that will include a phase-retrieval camera (PRC), and will utilize phase retrieval and other techniques to measure wavefront error directly. Phase retrieval is a process in which multiple images of an unresolved object are iterated to estimate the phase of the optical system that acquired the images. The combination of SH and phase-retrieval sensors will afford the virtues of both a dynamic range of 105 and an accuracy of <10 nm.

Hickey, Gregory↗

Poisson-response Tensor-on-Tensor Regression and Applications

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed of counts are common data in fields such as inter national relations, social networks, epidemiology, and medical imaging, where events occur across multiple dimensions like time, location, and dyads. PToTR accommodates such tensor responses alongside tensor covariates, providing a versatile tool for multi dimensional data analysis. We propose algorithms for maximum likelihood estimation under a canonical polyadic (CP) structure on the regression coefficient tensor that satisfy the positivity of Poisson parameters and then provide an initial theoretical error analysis for PToTR estimators. We also demonstrate the utility of PToTR through three concrete applications: longitudinal data analysis of the Integrated Crisis Early Warning System database, positron emission tomography (PET) image reconstruction, and change-point detection of communication patterns in longitudinal dyadic data. These applications highlight the versatility of PToTR in addressing complex, structured count data across various domains.

97 MATHEMATICS AND COMPUTING↗

Can Large Language Models Understand Intermediate Representations?

Intermediate Representations (IRs) are essential in compiler design and program analysis, yet their comprehension by Large Language Models (LLMs) remains underexplored. This paper presents a pioneering empirical study to investigate the capabilities of LLMs, including GPT-4, GPT-3, Gemma 2, LLaMA 3.1, and Code Llama, in understanding IRs. We analyze their performance across four tasks: Control Flow Graph (CFG) reconstruction, decompilation, code summarization, and execution reasoning. Our results indicate that while LLMs demonstrate competence in parsing IR syntax and recognizing high-level structures, they struggle with control flow reasoning, execution semantics, and loop handling. Specifically, they often misinterpret branching instructions, omit critical IR operations, and rely on heuristic-based reasoning, leading to errors in CFG reconstruction, IR decompilation, and execution reasoning. The study underscores the necessity for IR-specific enhancements in LLMs, recommending fine-tuning on structured IR datasets and integration of explicit control flow models to augment their comprehension and handling of IR-related tasks.

Jiang, Hailong↗

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗

An analysis of the AVE-SESAME I period using statistical structure and correlation functions

Structure and correlation functions are used to describe atmospheric variability during the 10-11 April day of AVE-SESAME 1979 that coincided with the Red River Valley tornado outbreak. The special mesoscale rawinsonde data are employed in calculations involving temperature, geopotential height, horizontal wind speed and mixing ratio. Functional analyses are performed in both the lower and upper troposphere for the composite 24 h experiment period and at individual 3 h observation times. Results show that mesoscale features are prominent during the composite period. Fields of mixing ratio and horizontal wind speed exhibit the greatest amounts of small-scale variance, whereas temperature and geopotential height contain the least. Results for the nine individual times show that small-scale variance is greatest during the convective outbreak. The functions also are used to estimate random errors in the rawinsonde data. Finally, sensitivity analyses are presented to quantify confidence limits of the structure functions.

Fuelberg, H. E.↗

Evaluation of Two Computational Techniques of Calculating Multipath Using Global Positioning System Carrier Phase Measurements

Two computational techniques are used to calculate differential phase errors on Global Positioning System (GPS) carrier war phase measurements due to certain multipath-producing objects. The two computational techniques are a rigorous computati electromagnetics technique called Geometric Theory of Diffraction (GTD) and the other is a simple ray tracing method. The GTD technique has been used successfully to predict microwave propagation characteristics by taking into account the dominant multipath components due to reflections and diffractions from scattering structures. The ray tracing technique only solves for reflected signals. The results from the two techniques are compared to GPS differential carrier phase ns taken on the ground using a GPS receiver in the presence of typical International Space Station (ISS) interference structures. The calculations produced using the GTD code compared to the measured results better than the ray tracing technique. The agreement was good, demonstrating that the phase errors due to multipath can be modeled and characterized using the GTD technique and characterized to a lesser fidelity using the DECAT technique. However, some discrepancies were observed. Most of the discrepancies occurred at lower devations and were either due to phase center deviations of the antenna, the background multipath environment, or the receiver itself. Selected measured and predicted differential carrier phase error results are presented and compared. Results indicate that reflections and diffractions caused by the multipath producers, located near the GPS antennas, can produce phase shifts of greater than 10 mm, and as high as 95 mm. It should be noted tl the field test configuration was meant to simulate typical ISS structures, but the two environments are not identical. The GZ and DECAT techniques have been used to calculate phase errors due to multipath o the ISS configuration to quantify the expected attitude determination errors.

Gomez, Susan F.↗

Similarity Metrics for Closed Loop Dynamic Systems

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Whorton, Mark S.↗

Electron petrography of Apollo sample 14310.

Thin sections prepared from Apollo sample 14310 have been examined with 100-kV transmission electron microscopy. The sample is composed principally of anorthite and pyroxene. The anorthites fall into two categories. The transitional anorthites that show the characteristic 'c' type diffraction maxima are characterized by very fine antiphase domain structures and some fine twinning. The body-centered anorthites that show no 'c' reflections are characterized by an absence of fine twinning and a less well-defined antiphase domain structure. Although both orthopyroxene and clinopyroxenes are reported in sample 14310, only clinopyroxenes were observed in this study and all show exsolution structures. The augite exsolved in pigeonite commonly is along lamellae parallel to (100), although (001) lamellae are also present. This unusual orientation was verified by diffraction patterns. The pigeonite commonly shows antiphase domains, attributed to stacking errors when the sample inverted from its high-temperature disordered form. In augite as the host phase, the pigeonite lamellae contain very complex structures including antiphase domains.

Smith, D. K.↗

Quantification and prediction of error in MIMO tests

Dynamic testing of systems is most realistic of real-world conditions when multiple input and multiple output (MIMO) techniques are used. To replicate measured environmental conditions, a series of desired outputs (responses) on the system must be realized by inverting the frequency response functions (FRF) matrix for input estimation. System identification is dependent on the number of inputs and outputs, which affect the type of solutions. In input estimation, the auto spectra of the determined inputs are affected by both the auto spectra and cross spectra of the desired outputs. This research evaluates errors and investigates two sources in an experimental setting. The first significant error source is test-to-test variability in FRFs from system identification tests, quantified by magnitude variability from long-duration tests. The second significant error source is the realization of time histories from frequency domain inputs. The spectral content of the realized random process deviates from the desired content and is also quantified. The structure is a linear three-story frame fixed at the base; two inputs are provided uniaxially with the use of suspended electrodynamic shakers. The proposed model for error sources was found to be effective in predicting errors in a SISO (single-input single-output) and a square (2-input 2-output) MIMO test.

Yousef, Odey↗

Stiffness-matrix condition number and shape sensitivity errors

This paper derives an error magnification index for assessing the sensitivity of the displacement field to errors in the load vector. It is shown that the error magnification index is less conservative than the stiffness-matrix condition number and that, for some cases, no error magnification occurs even when the condition number is very high. The proposed index was used to calculate the derivatives of beam response to changes in the beam structural parameters, using a semianalytical method. It is shown that the proposed index discriminates well between the calculation of the derivative with respect to length, which is very sensitive to errors, and the calculation of the derivative with respect to cross-sectional height, which is not sensitive.

Haftka, Raphael T.↗

Optimization of the structural and control system for LSS with reduced-order model

The objective is the simultaneous design of the structural and control system for space structures. The minimum weight of the structure is the objective function, and the constraints are placed on the closed loop distribution of the frequencies and the damping parameters. The controls approach used is linear quadratic regulator with constant feedback. A reduced-order control system is used. The effect of uncontrolled modes is taken into consideration by the model error sensitivity suppression (MESS) technique which modified the weighting parameters for the control forces. For illustration, an ACOSS-FOUR structure is designed for a different number of controlled modes with specified values for the closed loop damping parameters and frequencies. The dynamic response of the optimum designs for an initial disturbance is compared.

Khot, N. S.↗

Rationalizing accurate structure prediction in the meta-GGA SCAN functional

The ability of first-principles computational methods to reproduce ground-state crystal structure selection is key to their application in the discovery of new materials, and yet presents a formidable challenge due to the low-energy scale of the problem and lack of systematic error cancellation. The recently developed Strongly Constrained and Appropriately Normed (SCAN) functional is notable for accurately calculating physical properties such as formation energies and in particular, correctly predicting ground-state structures. Here in this paper, we attempt to rationalize the improved structure prediction accuracy in SCAN by investigating the relationship between preferred coordination environments, the description of attractive van der Waals (vdW) interactions, and the overall ground-state prediction in bulk main-group solids. We observe a systematic undercoordination error in the traditional Perdew, Burke, and Ernzerhof (PBE) functional which is not present in SCAN results and find that semiempirical dispersion corrections in the form of PBE + D 3 fail to correct this error in a consistent or physical manner. We conclude that the medium-range vdW interaction is correctly parametrized in SCAN and yields meaningful relative energies between coordination environments.

36 MATERIALS SCIENCE↗