On Bayesian Search for the Feasible Space Under Computationally Expensive Constraints

While self mixing interferometry(SMI) has proven to be suitable for displacement measurement and other sensing applications,its characteristic self mixing signal shape is strongly governed by the non-linear phase equation which forms relation between perturbed and unperturbed phase of self mixing laser.Therefore, while it is desirable for robust estimation of displacement of moving target, the algorithms to achieve this must have an objective strategy which can be achieved by understanding the characteristic of extracting knowledge of perturbed phase from unperturbed phase. Therefore, it has been proved and shown that such strategy must not involve sole methods where perturbed phase is continuous function of unperturbed phase (e.g:Taylor series or fixed point methods) or through successive displacements (e.g: variations of Gauss Seidal method). Subset of this strategy is to perform spectral filtering of perturbed phase followed by perturbative or homotopic deformation. A less computationally expensive approach of this strategy is adopted to achieve displacement with mean error of 62.2nm covering all feedback regimes, when coupling factor 'C' is unknown.<br>

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Eco-Driving for Different Electric Powertrain Topologies Considering Motor Efficiency

World Electric Vehicle Journal ◽

10.3390/wevj12010006 ◽

2021 ◽

Vol 12 (1) ◽

pp. 6

Author(s):

Alexander Koch ◽

Tim Bürchner ◽

Thomas Herrmann ◽

Markus Lienkamp

Keyword(s):

Dynamic Programming ◽

Electric Vehicles ◽

Quadratic Functions ◽

Simultaneous Optimization ◽

Speed Profile ◽

Power Demand ◽

Electric Motors ◽

Car Following ◽

Motor Efficiency ◽

Computationally Expensive

Electrification and automatization may change the environmental impact of vehicles. Current eco-driving approaches for electric vehicles fit the electric power of the motor by quadratic functions and are limited to powertrains with one motor and single-speed transmission or use computationally expensive algorithms. This paper proposes an online nonlinear algorithm, which handles the non-convex power demand of electric motors. Therefore, this algorithm allows the simultaneous optimization of speed profile and powertrain operation for electric vehicles with multiple motors and multiple gears. We compare different powertrain topologies in a free-flow scenario and a car-following scenario. Dynamic Programming validates the proposed algorithm. Optimal speed profiles alter for different powertrain topologies. Powertrains with multiple gears and motors require less energy during eco-driving. Furthermore, the powertrain-dependent correlations between jerk restriction and energy consumption are shown.

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Efficient downscaling of satellite oceanographic data with convolutional neural networks

SIGSPATIAL Special ◽

10.1145/3447994.3448011 ◽

2021 ◽

Vol 12 (3) ◽

pp. 46-47

Author(s):

Nikita Saxena

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Convolutional Neural Networks ◽

Super Resolution ◽

Sea Surface ◽

Clear Sky ◽

Oceanographic Data ◽

Computationally Expensive ◽

Sky Conditions ◽

Data Inference

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.

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Impedance eduction for uniform and multizone acoustic liners

International Journal of Aeroacoustics ◽

10.1177/1475472x211023855 ◽

2021 ◽

pp. 1475472X2110238

Author(s):

Michael G Jones ◽

Douglas M Nark ◽

Brian M Howerton

Keyword(s):

Impedance Spectra ◽

International Forum ◽

Acoustic Liners ◽

Prony Method ◽

Research Challenges ◽

Test Conditions ◽

Acoustic Liner ◽

Flow Impedance ◽

Grazing Flow ◽

Computationally Expensive

This paper presents results for five uniform and two multizone liners based on data acquired in the NASA Langley Grazing Flow Impedance Tube. Two methods, Prony and CHE, are used to educe the impedance spectra for each of these liners for many test conditions. The Prony method is efficient and generally provides accurate results for uniform liners, but is not well suited for multizone liners. The CHE method supports assessment of both uniform and multizone liners, but is much more computationally expensive. The results from these liners demonstrate the efficacy of both eduction methods, but also clearly demonstrate that sufficient attenuation is required to support accurate impedance eduction. For the liners considered in this study, the data indicate approximately 3 dB attenuation is needed for each zone of a multizone liner in order to ensure quality impedance eduction results. This study was conducted in response to two acoustic liner research challenges in support of a collaboration of multiple national laboratories under the International Forum for Aviation Research.

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Monomial codes seen as invariant subspaces

Open Mathematics ◽

10.1515/math-2017-0093 ◽

2017 ◽

Vol 15 (1) ◽

pp. 1099-1107 ◽

Cited By ~ 1

Author(s):

María Isabel García-Planas ◽

Maria Dolors Magret ◽

Laurence Emilie Um

Keyword(s):

Finite Field ◽

Linear Algebra ◽

Linear Transformation ◽

Cyclic Codes ◽

Invariant Subspaces ◽

Hyperinvariant Subspaces ◽

Computationally Expensive ◽

The Relationship

Abstract It is well known that cyclic codes are very useful because of their applications, since they are not computationally expensive and encoding can be easily implemented. The relationship between cyclic codes and invariant subspaces is also well known. In this paper a generalization of this relationship is presented between monomial codes over a finite field 𝔽 and hyperinvariant subspaces of 𝔽n under an appropriate linear transformation. Using techniques of Linear Algebra it is possible to deduce certain properties for this particular type of codes, generalizing known results on cyclic codes.

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Learning Adaptive Coarse Spaces of BDDC Algorithms for Stochastic Elliptic Problems with Oscillatory and High Contrast Coefficients

Mathematical and Computational Applications ◽

10.3390/mca26020044 ◽

2021 ◽

Vol 26 (2) ◽

pp. 44

Author(s):

Eric Chung ◽

Hyea-Hyun Kim ◽

Ming-Fai Lam ◽

Lina Zhao

Keyword(s):

Deep Neural Network ◽

Elliptic Problems ◽

Learning Approach ◽

High Contrast ◽

Spectral Problems ◽

Significant Challenge ◽

Machine Learning Approach ◽

Balancing Domain Decomposition ◽

Computationally Expensive ◽

Coarse Space

In this paper, we consider the balancing domain decomposition by constraints (BDDC) algorithm with adaptive coarse spaces for a class of stochastic elliptic problems. The key ingredient in the construction of the coarse space is the solutions of local spectral problems, which depend on the coefficient of the PDE. This poses a significant challenge for stochastic coefficients as it is computationally expensive to solve the local spectral problems for every realization of the coefficient. To tackle this computational burden, we propose a machine learning approach. Our method is based on the use of a deep neural network (DNN) to approximate the relation between the stochastic coefficients and the coarse spaces. For the input of the DNN, we apply the Karhunen–Loève expansion and use the first few dominant terms in the expansion. The output of the DNN is the resulting coarse space, which is then applied with the standard adaptive BDDC algorithm. We will present some numerical results with oscillatory and high contrast coefficients to show the efficiency and robustness of the proposed scheme.

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Performance Distribution Analysis and Robust Design

Journal of Mechanical Design ◽

10.1115/1.1333095 ◽

2000 ◽

Vol 123 (1) ◽

pp. 11-17 ◽

Cited By ~ 53

Author(s):

Jianmin Zhu ◽

Kwun-Lon Ting

Keyword(s):

Robust Design ◽

Robust Parameter Design ◽

Distribution Analysis ◽

Performance Space ◽

Sensitivity Distribution ◽

Performance Sensitivity ◽

Design Variables ◽

Robust Parameter ◽

Performance Distribution ◽

Feasible Space

The paper presents the theory of performance sensitivity distribution and a novel robust parameter design technique. In the theory, a Jacobian matrix describes the effect of the component tolerance to the system performance, and the performance distribution is characterized in the variation space by a set of eigenvalues and eigenvectors. Thus, the feasible performance space is depicted as an ellipsoid. The size, shape, and orientation of the ellipsoid describe the quantity as well as quality of the feasible space and, therefore, the performance sensitivity distribution against the tolerance variation. The robustness of a design is evaluated by comparing the fitness between the ellipsoid feasible space and the tolerance space, which is a block, through a set of quantitative and qualitative indexes. The robust design can then be determined. The design approach is demonstrated in a mechanism design problem. Because of the generality of the analysis theory, the method can be used in any design situation as long as the relationship between the performance and design variables can be expressed analytically.

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Modeling the center-to-limb variation of the Ca i 4227 Å line using FCHHT models

Proceedings of the International Astronomical Union ◽

10.1017/s1743921315005098 ◽

2014 ◽

Vol 10 (S305) ◽

pp. 381-386

Author(s):

H. D. Supriya ◽

H. N. Smitha ◽

K. N. Nagendra ◽

J. O. Stenflo ◽

M. Bianda ◽

...

Keyword(s):

Solar Spectrum ◽

Visible Spectrum ◽

Observational Constraints ◽

Solar Model ◽

The Sun ◽

Dimensional Modeling ◽

Height Dependence ◽

Computationally Expensive ◽

Chromospheric Line ◽

The Magnetic Field

AbstractThe Ca i 4227 Å is a chromospheric line exhibiting the largest degree of linear polarization near the limb, in the visible spectrum of the Sun. Modeling the observations of the center-to-limb variations (CLV) of different lines in the Second Solar Spectrum helps to sample the height dependence of the magnetic field, as the observations made at different lines of sight sample different heights in the solar atmosphere. Supriya et al. (2014) attempted to simultaneously model the CLV of the (I, Q/I) spectra of the Ca i 4227 Å line using the standard 1-D FAL model atmospheres. They found that the standard FAL model atmospheres and also any appropriate combination of them, fail to simultaneously fit the observed Stokes (I, Q/I) profiles at all the limb distances (μ) satisfying at the same time all the observational constraints. This failure of 1-D modeling approach can probably be overcome by using multi-dimensional modeling which is computationally expensive. To eliminate an even wider choice of 1-D models, we attempt here to simultaneously model the CLV of the (I, Q/I) spectra using the FCHHT solar model atmospheres which are updated and recent versions of the FAL models. The details of our modeling efforts and the results are presented.

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Depth migration from irregular surfaces with depth extrapolation methods

Geophysics ◽

10.1190/1.1442947 ◽

1991 ◽

Vol 56 (1) ◽

pp. 119-122 ◽

Cited By ~ 59

Author(s):

Moshe Reshef

Keyword(s):

Wave Equation ◽

Surface Topography ◽

Time Shift ◽

Extrapolation Methods ◽

Irregular Surfaces ◽

Depth Migration ◽

Numerical Problem ◽

Flat Interface ◽

Interface Wave ◽

Computationally Expensive

Nonflat surface topography introduces a numerical problem for migration algorithms that are based on depth extrapolation. Since the numerically efficient migration schemes start at a flat interface, wave‐equation datuming is required (Berryhill, 1979) prior to the migration. The computationally expensive datuming procedure is often replaced by a simple time shift for the elevation to datum correction. For nonvertically traveling energy this correction is inaccurate. Subsequent migration wrongly positions the reflectors in depth.

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