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At least 865 records · Page 48

The CHIMERAS project: design framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.

astrophysical plasmas↗

Electric Potentials of Metastable Salt Clusters

Small metastable NaCl clusters and cubic nanocrystals in vacuum and condensed aqueous electrolytes are used to characterize the electric potentials and fields experienced by the ions. The range of electrostatic potentials and fields experienced by NaCl nanocrystals and metastable clusters are analyzed using point charges, and quantified as a function of particle size and charge state. We show how the potentials and fields of these nanocrystals can be classified into various subgroups corresponding to corners, edges, faces, and interior sites. The difference between the interior and face potentials are correlated with the interfacial surface energy. This, in turn, influences cluster free energies and their corresponding populations. As a result, these potentials are correlated to the nucleation rate through the formalism of classical nucleation theory. Through this process, we consider the representation of the charge density, comparing point charge and continuous densities obtained from quantum mechanical electronic structure. A key result of this work is the identification of the electrical potential as an order parameter to understand nucleation pathways of salts. To do this, connection to the bulk Madelung potential reference must be established.

Chemical physics, nucleation, Madelung potential↗

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: B. A reduced model based on reversed-direction two point modeling

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter–erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding (Pitts et al 2019). Part A of the present study reports new results for largely the same ITER cases, confirming the strong correlation reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not as yet been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne (Ne s –1 ), and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In this part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction two point modeling, Rev2PM. The input to the reduced model is a value of the variable pair (T e,t @q ⊥,pk , Inj Ne )for a chosen case and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , the electron density at the X-point, n e,Xpt , etc. The reduced model was quantitatively characterized using one half of the code cases; it was then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Control-Oriented Modeling of Cycle-to-Cycle Combustion Variability at the Misfire Limit in SI Engines

A control-oriented model is presented that can capture the prior-cycle correlation of combustion cycles during conditions with high levels of exhaust gas recirculation (EGR). Combustion events are modeled in discrete time and the dynamic evolution is captured by the residual air, fuel, and inert gas trapped in the combustion chamber. The mathematical formulation of the model is presented together with the calibration procedure to emulate a particular engine operating condition. A cycle-to-cycle system identification methodology is described which allows regressing model parameters from experimental data. Simulations are presented and compared to real engine measurements to show the modeling potential for analysis and control of combustion events.

Maldonado Puente, Bryan↗

Metagenomic Analysis of Three Samples from the MCU Process

Three Modular Caustic-Side Solvent Extraction (CSSX) Unit (MCU) Strip Effluent Feed samples were sent from Savannah River National Laboratory (SRNL) to Microbial Insights (MI), Knoxville, TN, for molecular analysis. The objective of the analysis was to profile and identify dominant members of the microbial community in these samples. More effective control of microbial growth in the MCU depends on the fundamental understanding of the microorganisms responsible for system colonization that leads to biofilm formation and coalescer impairment. This analysis entailed Next-generation sequencing (NGS) of DNA, a collective term for advanced technologies that allow the determination of microbial species present. NGS, also commonly called metagenomics, provides for the identification of microorganisms down to the genus level. Although function, e.g. biofilm formation or corrosion, cannot always be predicted from identification, knowledge of the microorganisms present can offer insight into the potential microbial processes that may influence system function occurring in the MCU. Information on microbial identification can also influence control measures, e.g. operational/maintenance parameters or the choice of biocides to employ. This knowledge can help control undesired microbial activity as conventional cleaning and disinfection regimens may also contribute to inefficient biofilm control and dissemination of microbial resistance to remediation efforts.

59 BASIC BIOLOGICAL SCIENCES↗

Structural analysis model validation using modal test data

The design of a structure which can survive a prescribed dynamic environment is generally based on the use of an analytical model of the structure. The modal test is employed to verify the analytical model. This paper is concerned with the involved validation process, taking into account modal test results from realistic complex spacecraft structural systems as examples to demonstrate the proposed validation procedure. Attention is given to a load analysis model definition, a pretest analysis and test/analysis model, and the correlation parameters. Coordinate transformation is considered along with mode identification, frequency orthogonality, effective mass, mode shape, local kinetic energy, modal force, strain energy, and modal forces by acceleration measurements. Two examples are used to illustrate the procedure.

Chen, J.-C.↗

An enhanced mode shape identification algorithm

A mode shape identification algorithm is developed which is characterized by a low sensitivity to measurement noise and a high accuracy of mode identification. The algorithm proposed here is also capable of identifying the mode shapes of structures with significant damping. The combined results indicate that mode shape identification is much more dependent on measurement noise than identification of natural frequencies. Accurate detection of modal parameters and mode shapes is demonstrated for modes with damping ratios exceeding 15 percent.

Roemer, Michael J.↗

A consistent-mode indicator for the eigensystem realization algorithm

A new method is described for assessing the consistency of model parameters identified with the Eigensystem Realization Algorithm (ERA). Identification results show varying consistency in practice due to many sources, including high modal density, nonlinearity, and inadequate excitation. Consistency is considered to be a reliable indicator of accuracy. The new method is the culmination of many years of experience in developing a practical implementation of the Eigensystem Realization Algorithm. The effectiveness of the method is illustrated using data from NASA Langley's Controls-Structures-Interaction Evolutionary Model.

Pappa, Richard S.↗

Automation of Command and Data Entry in a Glovebox Work Volume: An Evaluation of Data Entry Devices

The present study was designed to examine the human-computer interface for data entry while performing experimental procedures within a glovebox work volume in order to make a recommendation to the Space Station Biological Research Project for a data entry system to be used within the Life Sciences Glovebox. Test subjects entered data using either a manual keypad, similar to a standard computer numerical keypad located within the glovebox work volume, or a voice input system using a speech recognition program with a microphone headset. Numerical input and commands were programmed in an identical manner between the two systems. With both electronic systems, a small trackball was available within the work volume for cursor control. Data, such as sample vial identification numbers, sample tissue weights, and health check parameters of the specimen, were entered directly into procedures that were electronically displayed on a video monitor within the glovebox. A pen and paper system with a 'flip-chart' format for procedure display, similar to that currently in use on the Space Shuttle, was used as a baseline data entry condition. Procedures were performed by a single operator; eight test subjects were used in the study. The electronic systems were tested under both a 'nominal' or 'anomalous' condition. The anomalous condition was introduced into the experimental procedure to increase the probability of finding limitations or problems with human interactions with the electronic systems. Each subject performed five test runs during a test day: two procedures each with voice and keypad, one with and one without anomalies, and one pen and paper procedure. The data collected were both quantitative (times, errors) and qualitative (subjective ratings of the subjects).

Steele, Marianne K.↗

A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION

Identification of parametric nonlinear models involves estimating unknown parameters and detecting its underlying structure. Structure computation is concerned with selecting a subset of parameters to give a parsimonious description of the system which may afford greater insight into the functionality of the system or a simpler controller design. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear systems. The LASSO minimises the residual sum of squares by the addition of a 1 penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. The performance of this LASSO structure detection method was evaluated by using it to estimate the structure of a nonlinear polynomial model. Applicability of the method to more complex systems such as those encountered in aerospace applications was shown by identifying a parsimonious system description of the F/A-18 Active Aeroelastic Wing using flight test data.

Kukreja, Sunil L.↗

A13K-0336: Airborne Multi-Wavelength High Spectral Resolution Lidar for Process Studies and Assessment of Future Satellite Remote Sensing Concepts

NASA Langley recently developed the world's first airborne multi-wavelength high spectral resolution lidar (HSRL). This lidar employs the HSRL technique at 355 and 532 nm to make independent, unambiguous retrievals of aerosol extinction and backscatter. It also employs the standard backscatter technique at 1064 nm and is polarization-sensitive at all three wavelengths. This instrument, dubbed HSRL-2 (the secondgeneration HSRL developed by NASA Langley), is a prototype for the lidar on NASA's planned Aerosols- Clouds-Ecosystems (ACE) mission. HSRL-2 completed its first science mission in July 2012, the Two-Column Aerosol Project (TCAP) conducted by the Department of Energy (DOE) in Hyannis, MA. TCAP presents an excellent opportunity to assess some of the remote sensing concepts planned for ACE: HSRL-2 was deployed on the Langley King Air aircraft with another ACE-relevant instrument, the NASA GISS Research Scanning Polarimeter (RSP), and flights were closely coordinated with the DOE's Gulfstream-1 aircraft, which deployed a variety of in situ aerosol and trace gas instruments and the new Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR). The DOE also deployed their Atmospheric Radiation Measurement Mobile Facility and their Mobile Aerosol Observing System at a ground site located on the northeastern coast of Cape Cod for this mission. In this presentation we focus on the capabilities, data products, and applications of the new HSRL-2 instrument. Data products include aerosol extinction, backscatter, depolarization, and optical depth; aerosol type identification; mixed layer depth; and rangeresolved aerosol microphysical parameters (e.g., effective radius, index of refraction, single scatter albedo, and concentration). Applications include radiative closure studies, studies of aerosol direct and indirect effects, investigations of aerosol-cloud interactions, assessment of chemical transport models, air quality studies, present (e.g., CALIPSO) and future (e.g., EarthCARE) satellite calibration/validation, and development/assessment of advanced retrieval techniques for future satellite applications (e.g., lidar+polarimeter retrievals of aerosol and cloud properties). We will also discuss the relevance of HSRL-2 measurement capabilities to the ACE remote sensing concept.

Hostetler, Chris A.↗

Computational methods for the identification of spatially varying stiffness and damping in beams

A numerical approximation scheme for the estimation of functional parameters in Euler-Bernoulli models for the transverse vibration of flexible beams with tip bodies is developed. The method permits the identification of spatially varying flexural stiffness and Voigt-Kelvin viscoelastic damping coefficients which appear in the hybrid system of ordinary and partial differential equations and boundary conditions describing the dynamics of such structures. An inverse problem is formulated as a least squares fit to data subject to constraints in the form of a vector system of abstract first order evolution equations. Spline-based finite element approximations are used to finite dimensionalize the problem. Theoretical convergence results are given and numerical studies carried out on both conventional (serial) and vector computers are discussed.

Banks, H. T.↗

Space station configuration and flight dynamics identification

The Space Station will be assembled in low earth orbit by a combination of deployable and space erectable modules that are progressively integrated during successive flights of the Shuttle. The crew assisted space construction will result in a configuration which is a large scale composite of structural elements having connectivity with a wide range of possible end conditions and imprecisely known dynamic characteristics. The generic applications of Flight Dynamics Identification to the candidate Space Station configurations currently under consideration are described. Identification functions are categorized, and the various methods for extracting parameter estimates are correlated with the sensing of parameter estimates are correlated with the sensing of specific characteristics of interest to both engineering subsystems and users of the Station's commercial and scientific facilities. Onboard implementation architecture and constraints are discussed from the viewpoint of maximizing integration of the Identification process with the flight subsystem's data and signal flow.

Metter, E.↗

Interactive automated Bragg peak identification with 3D neutron scattering data

Neutron scattering experiments have undergone significant technological development through large area detectors with concurrent enhancements in neutron transport and electronic functionality. Data collected for neutron events include detector pixel location in 3D, time and associated metadata, such as, sample orientation, neutron wavelength, and environmental conditions. RadiaSoft and Oak Ridge National Laboratory personnel are considering single-crystal diffraction data from the TOPAZ instrument. We are leveraging a new method for rapid, interactive analysis of neutron data using NVIDIA’s IndeX 3D volumetric visualization framework. We have implemented machine learning techniques to automatically identify Bragg peaks and separate them from diffuse backgrounds and analyze the crystalline lattice parameters for further analysis. The implementation of automatic peak identification into IndeX allows scientists to visualize and analyze data in real-time. Our methods include a robust comparison with current analysis techniques which show improvement in a variety of aspects. These improvements will be incorporated into IndeX for visualization to allow scientists an interactive tool for crystal analysis.

Kilpatrick, Matthew↗

The Mass Change Designated Observable Study: Overview and Results

The 2017–2027 United States National Academy of Sciences Decadal Survey (DS) for Earth Science and Applications from Space identified Mass Change (MC) as one of five Designated Observables (DOs) having the highest priority in terms of Earth observations required to advance Earth system science over the next decade. In response to this designation, NASA initiated several multi-center studies, with the goal of recommending observing system architectures for each DO for implementation within this decade. This paper provides an overview of the Mass Change Designated Observable (MCDO) Study along with key findings. The study process included: (a) generation of a Science and Applications Traceability Matrix (SATM) that maps required measurement parameters to the DS Science and Applications Objectives; (b) identification of three architecture classes relevant for measuring mass change: Precise Orbit Determination (POD), Satellite-Satellite-Tracking (SST) and Gravity Gradiometry (GG), along with variants within each architecture class; and (c) creation of a Value Framework process that considers science value, cost, risk, schedule, and partnership opportunities, to identify and recommend high value observing systems for further in-depth study. The study team recommended the implementation of an SST architecture, and identified variants that simultaneously (a) satisfy the baseline measurement parameters of the SATM; (b) maximize the probability of providing overlap with the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission currently in operation, accelerating science return from both missions; and (c) provide a pathway towards substantial improvements in resolution and accuracy of mass change data products relative to the program of record.

D N Wiese↗

Optimal inputs for system identification

Identification criteria are presented for linear dynamic systems with and without process noise. With process noise, the state equations are replaced by the Kalman filter equations. If the identification performance index is expanded in a Taylor's series with respect to the parameters to be identified, then maximizing the weighting factor of the quadratic term with respect to the inputs will insure that an identification algorithm will converge more rapidly and to a more accurate result than with nonoptimal inputs. The expectation of this weighting factor is the Fisher information matrix, and its inverse is a lower bound for the covariance of the parameters. Direct and indirect methods of calculating the information matrix are presented for systems with and without process noise.

Reid, D. B.↗

Mallat Scattering Transformation based surrogate for Magnetohydrodynamics

Abstract A Machine and Deep Learning (MLDL) methodology is developed and applied to give a high fidelity, fast surrogate for 2D resistive MagnetoHydroDynamic (MHD) simulations of Magnetic Liner Inertial Fusion (MagLIF) implosions. The resistive MHD code is used to generate an ensemble of implosions with different liner aspect ratios, initial gas preheat temperatures (that is, different adiabats), and different liner perturbations. The liner density and magnetic field as functions of x , y , and z were generated. The Mallat Scattering Transformation (MST) is taken of the logarithm of both fields and a Principal Components Analysis (PCA) is done on the logarithm of the MST of both fields. The fields are projected onto the PCA vectors and a small number of these PCA vector components are kept. Singular Value Decompositions of the cross correlation of the input parameters to the output logarithm of the MST of the fields, and of the cross correlation of the SVD vector components to the PCA vector components are done. This allows the identification of the PCA vectors vis-a-vis the input parameters. Finally, a Multi Layer Perceptron (MLP) neural network with ReLU activation and a simple three layer encoder/decoder architecture is trained on this dataset to predict the PCA vector components of the fields as a function of time. Details of the implosion, stagnation, and the disassembly are well captured. Examination of the PCA vectors and a permutation importance analysis of the MLP show definitive evidence of an inverse turbulent cascade into a dipole emergent behavior. The orientation of the dipole is set by the initial liner perturbation. The analysis is repeated with a version of the MST which includes phase, called Wavelet Phase Harmonics (WPH). While WPH do not give the physical insight of the MST, they can and are inverted to give field configurations as a function of time, including field-to-field correlations.

97 MATHEMATICS AND COMPUTING↗

System Identification of Flexible Aircraft: Lessons Learned from the X-56A Phase 1 Flight Tests

The X-56A Multi-Utility Technology Testbed (MUTT) is a subscale airplane that was de-signed as an experimental flight research platform for improving aeroelastic modeling and control technologies. The Phase 1 flight tests, conducted from 2017 to 2019 at the NASA Arm-strong Flight Research Center (AFRC), included 39 flights and approximately 1000 research maneuvers, some of which demonstrated stable closed-loop flight beyond the open-loop flutter speed. This paper summarizes the system identification effort to extract nondimensional stability and control derivatives from the flight test data for constructing aeroelastic models of the flight dynamics. Topics discussed include instrumentation, experiment design, model postulation and reduction, parameter estimation, and others. Throughout the paper, unique challenges for the identification of flexible aircraft, practical aspects of the analysis, and lessons learned are presented.

Jared A Grauer↗