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At least 379 records · Page 21

Machine learning in motion control

The existing methodologies for robot programming originate primarily from robotic applications to manufacturing, where uncertainties of the robots and their task environment may be minimized by repeated off-line modeling and identification. In space application of robots, however, a higher degree of automation is required for robot programming because of the desire of minimizing the human intervention. We discuss a new paradigm of robotic programming which is based on the concept of machine learning. The goal is to let robots practice tasks by themselves and the operational data are used to automatically improve their motion performance. The underlying mathematical problem is to solve the problem of dynamical inverse by iterative methods. One of the key questions is how to ensure the convergence of the iterative process. There have been a few small steps taken into this important approach to robot programming. We give a representative result on the convergence problem.

Su, Renjeng↗

Carbon Monoxide Accumulation in the Extravehicular Mobility Unit

Introduction: Life support technology in large closed systems like submarines and space stations catalyzes carbon monoxide (CO) to carbon dioxide, which is easily removed. However, in a small system like the Extravehicular Mobility Unit (EMU), spacesuit, CO from exogenous (contaminated oxygen (O (sub 2) supply) and endogenous (human metabolism) sources will accumulate in the free suit volume. The free volume becomes a sink for CO that is rebreathed by the astronaut. The accumulation through time depends on many variables: the amount absorbed by the astronaut, the amount produced by the astronaut (between 0.28 and 0.34 moles per hour per kilogram)[1], the amount that enters the suit from contaminated O (sub 2), the amount removed through suit leak, the free volume of the suit, and the O (sub 2) partial pressure[2], just to list a few. Contamination of the EMU O (sub 2) supply with no greater than 1 part per million CO was the motivation for empirical measurements from CO pulse oximetry (SpCO) as well as mathematical modeling of the EMU as a rebreather for CO. Methods: We developed a first-order differential mixing equation as well as an iterative method to compute CO accumulation in the EMU. Pre-post measurements of SpCO (Rad-57, Masimo Corporation) from EMU ground training and on-orbit extravehicular activities (EVAs) were collected. Results: Initial modeling without consideration of the astronaut as a sink but only the source of CO showed that after 8 hours breathing 100 percent O (sub 2) with a 10 milliliter per minute (760 millimeters Hg at 21 degrees Centigrade standard) suit leak, an endogenous production rate of 0.23 moles per hour per kilogram for a 70 kilogram person with 42 liters (1.5 cubic feet) free suit volume resulted in a peak CO partial pressure (pCO) of 0.047 millimeters Hg at 4.3 pounds per square inch absolute (222 millimeters Hg). Preliminary results based on a 2008 model[3] with consideration of the astronaut as a sink and source of CO suggests that most of the rebreathed CO stays bound to hemoglobin and myoglobin and; therefore, pCO only increased to 0.002 millimeters Hg in the EMU. Hemoglobin saturation after 8 hours was an insignificant 0.4 percent compared to about 4 percent for cigarette smokers in the general population. This preliminary modeling result supplements 11 pre-post index finger SpCO measurements from EMU ground training (mean 0.5 percent versus 1 percent, probability equal to 0.41 from paired t-test) and 10 on-orbit pre-post EVAs (mean 1.5 percent versus 1.1 percent, probability equal to 0.17 from paired t-test) that showed no consistent increase, at least no increase outside the accuracy of the oximeter (1 percent display resolution with plus or minus 3 percent Standard Deviation). Discussion: Simulations continue, but a preliminary conclusion is that rebreathing endogenous CO accumulating in the EMU is not a serious medical issue during EVA. The absence of CO poisoning signs or symptoms following hundreds of EVAs is also good empirical evidence that corroborates the limited SpCO measurements and preliminary modeling results.

Conkin, J.↗

Improved Regression Analysis of Temperature-Dependent Strain-Gage Balance Calibration Data

An improved approach is discussed that may be used to directly include first and second order temperature effects in the load prediction algorithm of a wind tunnel strain-gage balance. The improved approach was designed for the Iterative Method that fits strain-gage outputs as a function of calibration loads and uses a load iteration scheme during the wind tunnel test to predict loads from measured gage outputs. The improved approach assumes that the strain-gage balance is at a constant uniform temperature when it is calibrated and used. First, the method introduces a new independent variable for the regression analysis of the balance calibration data. The new variable is designed as the difference between the uniform temperature of the balance and a global reference temperature. This reference temperature should be the primary calibration temperature of the balance so that, if needed, a tare load iteration can be performed. Then, two temperature{dependent terms are included in the regression models of the gage outputs. They are the temperature difference itself and the square of the temperature difference. Simulated temperature{dependent data obtained from Triumph Aerospace's 2013 calibration of NASA's ARC-30K five component semi{span balance is used to illustrate the application of the improved approach.

wind tunnel testing↗

The MHOST finite element program: 3-D inelastic analysis methods for hot section components. Volume 1: Theoretical manual

Formulations and algorithms implemented in the MHOST finite element program are discussed. The code uses a novel concept of the mixed iterative solution technique for the efficient 3-D computations of turbine engine hot section components. The general framework of variational formulation and solution algorithms are discussed which were derived from the mixed three field Hu-Washizu principle. This formulation enables the use of nodal interpolation for coordinates, displacements, strains, and stresses. Algorithmic description of the mixed iterative method includes variations for the quasi static, transient dynamic and buckling analyses. The global-local analysis procedure referred to as the subelement refinement is developed in the framework of the mixed iterative solution, of which the detail is presented. The numerically integrated isoparametric elements implemented in the framework is discussed. Methods to filter certain parts of strain and project the element discontinuous quantities to the nodes are developed for a family of linear elements. Integration algorithms are described for linear and nonlinear equations included in MHOST program.

Nakazawa, Shohei↗

A boundary element alternating method for two-dimensional mixed-mode fracture problems

A boundary element alternating method, denoted herein as BEAM, is presented for two dimensional fracture problems. This is an iterative method which alternates between two solutions. An analytical solution for arbitrary polynomial normal and tangential pressure distributions applied to the crack faces of an embedded crack in an infinite plate is used as the fundamental solution in the alternating method. A boundary element method for an uncracked finite plate is the second solution. For problems of edge cracks a technique of utilizing finite elements with BEAM is presented to overcome the inherent singularity in boundary element stress calculation near the boundaries. Several computational aspects that make the algorithm efficient are presented. Finally, the BEAM is applied to a variety of two dimensional crack problems with different configurations and loadings to assess the validity of the method. The method gives accurate stress intensity factors with minimal computing effort.

Raju, I. S.↗

SU-D-12A-05: Iterative Reconstruction Techniques to Enable Intrinsic Respiratory Gated CT in Mice

Purpose: Longitudinal studies of lung function in mice need the ability to image different phases of ventilation in free-breathing mice using retrospective gating. However, retrospective gating often produces under-sampled and uneven angular samples, resulting in severe reconstruction artifacts when using traditional FDK based reconstruction algorithms. We wanted to demonstrate the utility of iterative reconstruction method to enable intrinsic respiratory gating in small-animal CT. Methods: Free-breathing mice were imaged using a Siemens Inveon PET/micro-CT system. Evenly distributed projection images were acquired at 360 angles. Retrospective respiratory gating was performed using an intrinsic marker based on the average intensity in a region covering the diaphragm. Projections were classified into 4 and 6 phases (finer temporal resolution) resulting in 138 and 67 projections respectively. Reconstruction was carried out using 3 Methods: conventional FDK, iterative penalized least-square (PWLS) with total variation (TV), and PWLS with edge-preserving penalty. The performance of the methods was compared using contrast-to-noise (CNR) in a region of interest (ROI). Line profile through a specific region was plotted to evaluate the preserving of edges. Results: In both the cases with 4 and 6 phases, inadequate and non-uniform angular sampling results in artifacts using conventional FDK. However, such artifacts are minimized using both the iterative methods. Using both 4 and 6 phases, the iterative techniques outperformed FDK in terms of CNR and maintaining sharp edges. This is further evidenced especially with increased artifacts using FDK for 6 phases. Conclusion: This work indicates fewer artifacts and better image details can be achieved with iterative reconstruction methods in non-uniform under-sampled reconstruction. Using iterative methods can enable free-breathing intrinsic respiratory gating in small-animal CT. Further studies are needed to compare the computational complexity for large datasets.

60 APPLIED LIFE SCIENCES↗

Experience in grid optimization

Two optimization methods for solving a variational problem in grid generation are described and evaluated. The smoothness, cell volumes, and orthogonality of the variational integrals are examined. The Jacobi-Newton iterative method is compared to the Fletcher-Reeves conjugate gradient method. It is observed that a combination of the Jacobi-Newton iteration and the direct solution of the variational problem produces an algorithm which is easy to program and requires less storage and computer time/iteration than the conjugate gradient method.

Mastin, C. W.↗

Aerodynamic shape optimization via sensitivity analysis on decomposed computational domains

Direct and iterative method considered to be most applicable to large systems of linear equations arising in discrete sensitivity analysis are assessed. Based on a single-domain grid, computations are performed using a banded matrix solver and an iterative solver, the generalized minimum residual (GMRES) method. The banded matrix solver is found to be generally the most economical method for those applications where the number of right-hand sides is large (i.e., a large number of design variables or a large number of adjoint vectors). For systems of equations that are too large to be solved by direct methods, an approach is proposed whereby the computational domain is divided into small subdomains, and each subdomain is solved separately.

Eleshaky, Mohamed E.↗

Equilibrium core modeling of a pebble bed reactor similar to the Xe-100 with SCALE

As the nuclear industry moves towards licensing and constructing advanced reactors, new attention has been focused on the advanced reactor designs that have past operational experience, such as pebble-bed high-temperature gas-cooled reactors (PB-HTGRs). Pebble-bed reactor designs have many advantages, such as their higher operating temperatures and online refueling capabilities. However, high-fidelity computational modeling of pebble-bed reactor designs, from reactor startup to operation at equilibrium, is more challenging compared to conventionally fueled reactors due to the continuous movement of the fuel pebbles through the reactor during operation. In previous work at Oak Ridge National Laboratory (ORNL), the SCALE Leap-In method for Cores at Equilibrium (SLICE) was developed around tools within the SCALE code system. This iterative method can effectively generate pebble-bed reactor zone-wise fuel inventories at equilibrium core operation within a reasonable computational time. The objective of this work was to further verify the ORNL SLICE method and to investigate the impact of considering temperature profiles during the application of the method. The SLICE method was applied to a modular high-temperature gas-cooled reactor design based upon publicly available design specifications of the Xe-100 pebble-bed reactor. Upon comparing the results from the SLICE method to published literature, the differences in the eigenvalue k effective were on the order of several hundred pcm (percent millirho). To investigate one possible cause of these differences, a study looking at the sensitivity of the full-core equilibrium k effective and discharge nuclide inventory to temperature was performed by developing equilibrium cores of two additional temperature profiles. From this temperature study, differences on the order of hundreds of pcm for the full-core equilibrium k effective , and up to 15% difference for the discharge inventories were found. In conclusion, these results indicated the strong dependence on temperature that needs to be considered for future work in equilibrium modeling of PB-HTGRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Implementation of natural frequency analysis and optimality criterion design

A description is presented of an effective optimality criterion computer design approach for member size selection to improve frequency characteristics for moderately large structure models. It is shown that the implementation of the simultaneous iteration method within a natural frequency structural design optimization provides a method which is more efficient in isolating the lowest natural frequency modes than the frequently applied Stodola method. Additional computational advantages are derived by using previously converged eigenvectors at the start of the iterations during the second and the following design cycles. Vectors with random components can be used at the first design cycle, which, in relation to the entire computer time for the design program, results in only a moderate computational penalty.

Levy, R.↗

USM3D-ME Revised SA-neg Implementation and Assessment for Seventh Drag Prediction Workshop Solutions

Simulations performed by an unstructured-grid, cell-centered, finite-volume, mixed-element flow solver USM3D-MEwere presented at the Seventh Drag Prediction Workshop (DPW-7). Reynolds-averaged Navier-Stokes (RANS) solutions for the NASA high-speed common research model wing-body configuration were computed using a new implementation of the negative variant of the Spalart-Allmaras turbulence model (SA-neg) with hierarchical adaptive nonlinear iteration method (HANIM).ThisUSM3D-ME enhancement improved efficiency and robustness of RANS solutions resulting in fast iterative convergence to machine zero residuals on mixed-element unstructured grids provided by the DPW-7 organizing committee. This paper presents theoretical foundations for the new implementation of the SA-neg model and analyzesUSM3D-ME solutions for flow conditions corresponding to the required DPW-7 cases.

Boris Diskin↗

Preconditioners for the spectral multigrid method

The systems of algebraic equations which arise from spectral discretizations of elliptic equations are full and direct solutions of them are rarely feasible. Iterative methods are an attractive alternative because Fourier transform techniques enable the discrete matrix-vector products to be computed with nearly the same efficiency as is possible for corresponding but sparse finite difference discretizations. For realistic Dirichlet problems preconditioning is essential for acceptable convergence rates. A brief description of Chebyshev spectral approximations and spectral multigrid methods for elliptic problems is given. A survey of preconditioners for Dirichlet problems based on second-order finite difference methods is made. New preconditioning techniques based on higher order finite differences and on the spectral matrix itself are presented. The preconditioners are analyzed in terms of their spectra and numerical examples are presented.

Phillips, T. N.↗

Preconditioners for the spectral multigrid method

The systems of algebraic equations which arise from spectral discretizations of elliptic equations are full and direct solutions of them are rarely feasible. Iterative methods are an attractive alternative because Fourier transform techniques enable the discrete matrix-vector products to be computed with nearly the same efficiency as is possible for corresponding but sparse finite difference discretizations. For realistic Dirichlet problem preconditioning is essential for acceptable convergence rates. A brief description of Chebyshev spectral approximations and spectral multigrid methods for elliptic problems is given. A survey of preconditioners for Dirichlet problems based on second-order finite difference methods is made. New preconditioning techniques based on higher order finite differences and on the spectral matrix itself are presented. The preconditioners are analyzed in terms of their spectra and numerical examples are presented.

Phillips, T. N.↗

Fission Matrix Capability for MCNP Monte Carlo

In a Monte Carlo criticality calculation, before the tallying of quantities can begin, a converged fission source (the fundamental eigenvector of the fission kernel) is required. Tallies of interest may include powers, absorption rates, leakage rates, or the multiplication factor (the fundamental eigenvalue of the fission kernel, k eff ). Just as in the power iteration method of linear algebra, if the dominance ratio (the ratio of the first and zeroth eigenvalues) is high, many iterations of neutron history simulations are required to isolate the fundamental mode of the problem. Optically large systems have large dominance ratios, and systems containing poor neutron communication between regions are also slow to converge. The fission matrix method, implemented into MCNP, addresses these problems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Time-fractional Gardner equation for ion-acoustic waves in negative-ion-beam plasma with negative ions and nonthermal nonextensive electrons

Nonlinear propagation of ion-acoustic waves is investigated in a one-dimensional, unmagnetized plasma consisting of positive ions, negative ions, and nonthermal electrons featuring Tsallis distribution that is penetrated by a negative-ion-beam. The classical Gardner equation is derived to describe nonlinear behavior of ion-acoustic waves in the considered plasma system via reductive perturbation technique. We convert the classical Gardner equation into the time-fractional Gardner equation by Agrawal's method, where the time-fractional term is under the sense of Riesz fractional derivative. Employing variational iteration method, we construct solitary wave solutions of the time-fractional Gardner equation with initial condition which depends on the nonlinear and dispersion coefficients. The effect of the plasma parameters on the compressive and rarefactive ion-acoustic solitary waves is also discussed in detail.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗

CORSS: Cylinder Optimization of Rings, Skin, and Stringers

Launch vehicle designs typically make extensive use of cylindrical skin stringer construction. Structural analysis methods are well developed for preliminary design of this type of construction. This report describes an automated, iterative method to obtain a minimum weight preliminary design. Structural optimization has been researched extensively, and various programs have been written for this purpose. Their complexity and ease of use depends on their generality, the failure modes considered, the methodology used, and the rigor of the analysis performed. This computer program employs closed-form solutions from a variety of well-known structural analysis references and joins them with a commercially available numerical optimizer called the 'Design Optimization Tool' (DOT). Any ring and stringer stiffened shell structure of isotropic materials that has beam type loading can be analyzed. Plasticity effects are not included. It performs a more limited analysis than programs such as PANDA, but it provides an easy and useful preliminary design tool for a large class of structures. This report briefly describes the optimization theory, outlines the development and use of the program, and describes the analysis techniques that are used. Examples of program input and output, as well as the listing of the analysis routines, are included.

Finckenor, J.↗