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At least 1,729 records · Page 96

Real parameter margin computation for uncertain structural dynamic systems

This paper is concerned with the problem of computing real parameter margins for stabilized, structural dynamic systems with the masses, spring constants, and damping constants as uncertain parameters. Numerical algorithms for uncertain systems with multilinear parameters are investigated. It is shown that for a certain class of structural dynamic systems with small passive damping (e.g., flexible structures in space), the computational complexity of the problem can be avoided by modeling the system as a conservative plant, without loss of any practical significance.

Wie, Bong↗

Expert system structures for fault detection in spaceborne power systems

This paper presents an architecture for an expert system structure suitable for use with power system fault detection algorithms. The system described is not for the purpose of reacting to faults which have occurred, but rather for the purpose of performing on-line diagnostics and parameter evaluation to determine potential or incipient fault conditions. The system is also designed to detect high impedance or arcing faults which cannot be detected by conventional protection devices. This system is part of an overall monitoring computer hierarchy which would provide a full evaluation of the status of the power system and react to both incipient and catastrophic faults. An approximate hardware structure is suggested and software requirements are discussed. Modifications to CLIPS software, to capitalize on features offered by expert systems, are presented. It is suggested that such a system would have significant advantages over existing protection philosophy.

Watson, Karan↗

Modal identification of structures from the responses and random decrement signatures

The theory and application of a method which utilizes the free response of a structure to determine its vibration parameters is described. The time-domain free response is digitized and used in a digital computer program to determine the number of modes excited, the natural frequencies, the damping factors, and the modal vectors. The technique is applied to a complex generalized payload model previously tested using sine sweep method and analyzed by NASTRAN. Ten modes of the payload model are identified. In case free decay response is not readily available, an algorithm is developed to obtain the free responses of a structure from its random responses, due to some unknown or known random input or inputs, using the random decrement technique without changing time correlation between signals. The algorithm is tested using random responses from a generalized payload model and from the space shuttle model.

Brahim, S. R.↗

Discrete-time demodulation of continuous-time signals.

Nonlinear stochastic estimation theory is applied to the problem of obtaining discrete-time demodulator structures for the common types of analog communication signals. A stochastic communication model is presented that can be treated with current results in estimation theory. Approximate algorithms are developed for the estimation problem that yield mathematically realizable receiver structures for the cases of AM, PC, and FM. The digital receivers yield performance characteristics that compare favorably with those of their analog counterparts.

Kelly, C. N.↗

Reverse time migration: A seismic processing application on the connection machine

The implementation of a reverse time migration algorithm on the Connection Machine, a massively parallel computer is described. Essential architectural features of this machine as well as programming concepts are presented. The data structures and parallel operations for the implementation of the reverse time migration algorithm are described. The algorithm matches the Connection Machine architecture closely and executes almost at the peak performance of this machine.

Fiebrich, Rolf-Dieter↗

Algorithmic Improvements for Portable Event-Based Monte Carlo Transport Using the Nvidia Thrust Library

High performance computing environments are progressively moving towards many-core computing architectures. The Los Alamos National Laboratory Trinity machine, available in late 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) coprocessors. The Lawrence Livermore National Laboratory Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing units (GPUs). Applications that must work in this supercomputing environment must continue to adapt in order to take advantage of the diverse hardware architectures that are coming. A significant consideration is not only the performance of the application on a given platform but also the portability of the application to other platforms. The algorithmic improvements presented in this paper build upon recently-reported work on event-based Monte Carlo transport in the ALPSMC code that models particle transport in one-dimensional binary stochastic media. That paper discussed the lack of available vectorization in the traditional history-based algorithm used for Monte Carlo transport and presented a data parallel event-based algorithm implemented using the Nvidia Thrust library for portability. The performance of the data parallel event-based algorithm implemented using Thrust was compared to a native CUDA implementation. The conclusions from that work were that the Thrust library abstraction technique caused too significant a loss in performance but that the event-based method was a viable option that should be further investigated. In this paper, we describe algorithmic improvements to the data parallel event-based algorithm previously presented. We made further algorithmic optimizations to the event-based CUDA implementation, most notably: data structure changes, a new conditional particle removal scheme in the event-based process, and the use of multiple GPUs. In addition to improvements to the algorithm, we re-implemented the Thrust version from the now further optimized CUDA version, giving a greater chance for success at a performant abstraction. Finally, we revisited our previous assumptions about the inability of the history-based method to achieve performance on vector style architectures such as the MICs and GPUs, with surprising and promising results. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Design of structures for optimum geometry

A general method is proposed for geometric optimization of finite element structures on the assumption that a reasonable initial geometry is specified. The number of finite elements, number of joints, and the element-joint relationships are specified and are not changed during the optimization process. The structure may be statically indeterminate and may support multiple loading conditions. Design variables include geometric and member sizing parameters. Design objectives may be minimum weight or cost, and constraints include strength and stiffness limitations. The optimization procedure is a general mathematical programming approach. An iterative design algorithm is outlined, and the method is specialized for truss structures. Design examples are given.

Vanderplaats, G. N.↗

FunMC^2: A Filter for Uncertainty Visualization of Marching Cubes on Multi-Core Devices

Visualization is an important tool for scientists to extract understanding from complex scientific data. Scientists need to understand the uncertainty inherent in all scientific data in order to interpret the data correctly. Uncertainty visualization has been an active and growing area of research to address this challenge. Algorithms for uncertainty visualization can be expensive, and research efforts have been focused mainly on structured grid types. Further, support for uncertainty visualization in production tools is limited. In this paper, we adapt an algorithm for computing key metrics for visualizing uncertainty in Marching Cubes (MC) to multi-core devices and present the design, implementation, and evaluation for a Filter for uncertainty visualization of Marching Cubes on Multi-Core devices (FunMC2). FunMC2 accelerates the uncertainty visualization of MC significantly, and it is portable across multi-core CPUs and GPUs. Evaluation results show that FunMC2 based on OpenMP runs around 11× to 41× faster on multi-core CPUs than the corresponding serial version using one CPU core. FunMC2 based on a single GPU is around 5× to 9× faster than FunMC2 running by OpenMP. Moreover, FunMC2 is flexible enough to process ensemble data with both structured and unstructured mesh types. Furthermore, we demonstrate that FunMC2 can be seamlessly integrated as a plugin into ParaView, a production visualization tool for post-processing.

Wang, Jay↗

Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India

Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India. Results also suggested saturation of the Sentinel-1A backscatter signal around hundred tonnes per hectare for VV polarization and one hundred and forty five tonnes per hectare for VH polarization. The presentation will highlight the above results in addition to potentials and limitations of Sentinel-1A data for retrieving forest structural parameters. Also, background information on different forest types of India, biomass variations and forest type mapping efforts in the region will be presented.

Data↗

A new procedure for dynamic adaption of three-dimensional unstructured grids

A new procedure is presented for the simultaneous coarsening and refinement of three-dimensional unstructured tetrahedral meshes. This algorithm allows for localized grid adaption that is used to capture aerodynamic flow features such as vortices and shock waves in helicopter flowfield simulations. The mesh-adaption algorithm is implemented in the C programming language and uses a data structure consisting of a series of dynamically-allocated linked lists. These lists allow the mesh connectivity to be rapidly reconstructed when individual mesh points are added and/or deleted. The algorithm allows the mesh to change in an anisotropic manner in order to efficiently resolve directional flow features. The procedure has been successfully implemented on a single processor of a Cray Y-MP computer. Two sample cases are presented involving three-dimensional transonic flow. Computed results show good agreement with conventional structured-grid solutions for the Euler equations.

Biswas, Rupak↗

Efficient generation of grids and traversal graphs in compositional spaces towards exploration and path planning

Abstract Diverse disciplines across science and engineering deal with problems related to compositions, which exist in non-Euclidean simplex spaces, rendering many standard tools inaccurate or inefficient. This work explores such spaces conceptually in the context of materials discovery, quantifies their computational feasibility, and implements several essential methods specific to simplex spaces through a new high-performance open-source library . Most significantly, we derive and implement an algorithm for constructing a novel n-dimensional simplex graph data structure, containing all discretized compositions and possible neighbor-to-neighbor transitions. Critically, no distance or neighborhood calculations are performed, instead leveraging pure combinatorics and order in procedurally generated simplex grids, keeping the algorithm $${\mathcal{O}}(N)$$ O ( N ) , with minimal memory, enabling rapid construction of graphs with billions of transitions in seconds. Additionally, we demonstrate how such graph representations can be combined to homogeneously express complex path-planning problems, while facilitating efficient deployment of existing high-performance gradient descent, graph traversal, and other optimization algorithms.

Krajewski, Adam M. (ORCID:0000000222660099)↗

SU-C-207B-02: Maximal Noise Reduction Filter with Anatomical Structures Preservation

Purpose: All medical images contain noise, which can result in an undesirable appearance and can reduce the visibility of anatomical details. There are varieties of techniques utilized to reduce noise such as increasing the image acquisition time and using post-processing noise reduction algorithms. However, these techniques are increasing the imaging time and cost or reducing tissue contrast and effective spatial resolution which are useful diagnosis information. The three main focuses in this study are: 1) to develop a novel approach that can adaptively and maximally reduce noise while preserving valuable details of anatomical structures, 2) to evaluate the effectiveness of available noise reduction algorithms in comparison to the proposed algorithm, and 3) to demonstrate that the proposed noise reduction approach can be used clinically. Methods: To achieve a maximal noise reduction without destroying the anatomical details, the proposed approach automatically estimated the local image noise strength levels and detected the anatomical structures, i.e. tissue boundaries. Such information was used to adaptively adjust strength of the noise reduction filter. The proposed algorithm was tested on 34 repeating swine head datasets and 54 patients MRI and CT images. The performance was quantitatively evaluated by image quality metrics and manually validated for clinical usages by two radiation oncologists and one radiologist. Results: Qualitative measurements on repeated swine head images demonstrated that the proposed algorithm efficiently removed noise while preserving the structures and tissues boundaries. In comparisons, the proposed algorithm obtained competitive noise reduction performance and outperformed other filters in preserving anatomical structures. Assessments from the manual validation indicate that the proposed noise reduction algorithm is quite adequate for some clinical usages. Conclusion: According to both clinical evaluation (human expert ranking) and qualitative assessment, the proposed approach has superior noise reduction and anatomical structures preservation capabilities over existing noise removal methods. Senior Author Dr. Deshan Yang received research funding form ViewRay and Varian.

60 APPLIED LIFE SCIENCES↗

PSelInv—A Distributed Memory Parallel Algorithm for Selected Inversion: The Symmetric Case

We describe an efficient parallel implementation of the selected inversion algorithm for distributed memory computer systems, which we call PSelInv. The PSelInv method computes selected elements of a general sparse matrix Athat can be decomposed as A= LU, where L is lower triangular and U is upper triangular. The implementation described in this article focuses on the case of sparse symmetric matrices. It contains an interface that is compatible with the distributed memory parallel sparse direct factorization SuperLU-DIST. Yet, the underlying data structure and design of PSelInv allows it to be easily combined with other factorization routines, such as PARDISO. We discuss general parallelization strategies such as data and task distribution schemes. Specifically, we describe how to exploit the concurrency exposed by the elimination tree associated with the LU factorization of A. We demonstrate the efficiency and accuracy of PSelInv by presenting several numerical experiments. In particular, we show that PSelInv can run efficiently on more than 4,000 cores for a modestly sized matrix. We also show how PSelInv can be used to accelerate large-scale electronic structure calculations.

97 MATHEMATICS AND COMPUTING↗

TU-F-18A-06: Dual Energy CT Using One Full Scan and a Second Scan with Very Few Projections

Purpose: The conventional dual energy CT (DECT) requires two full CT scans at different energy levels, resulting in dose increase as well as imaging errors from patient motion between the two scans. To shorten the scan time of DECT and thus overcome these drawbacks, we propose a new DECT algorithm using one full scan and a second scan with very few projections by preserving structural information. Methods: We first reconstruct a CT image on the full scan using a standard filtered-backprojection (FBP) algorithm. We then use a compressed sensing (CS) based iterative algorithm on the second scan for reconstruction from very few projections. The edges extracted from the first scan are used as weights in the Objectives: function of the CS-based reconstruction to substantially improve the image quality of CT reconstruction. The basis material images are then obtained by an iterative image-domain decomposition method and an electron density map is finally calculated. The proposed method is evaluated on phantoms. Results: On the Catphan 600 phantom, the CT reconstruction mean error using the proposed method on 20 and 5 projections are 4.76% and 5.02%, respectively. Compared with conventional iterative reconstruction, the proposed edge weighting preserves object structures and achieves a better spatial resolution. With basis materials of Iodine and Teflon, our method on 20 projections obtains similar quality of decomposed material images compared with FBP on a full scan and the mean error of electron density in the selected regions of interest is 0.29%. Conclusion: We propose an effective method for reducing projections and therefore scan time in DECT. We show that a full scan plus a 20-projection scan are sufficient to provide DECT images and electron density with similar quality compared with two full scans. Our future work includes more phantom studies to validate the performance of our method.

60 APPLIED LIFE SCIENCES↗

Posiform planting: generating QUBO instances for benchmarking

We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. Such problems are NP-hard in general, implying that the exact minima of randomly generated instances are hard to find and thus typically unknown. While brute forcing smaller instances is possible, such instances are typically not interesting due to being too easy for both quantum and classical algorithms. In this contribution, we propose a novel method, called posiform planting , for generating random QUBO instances of arbitrary size with known optimal solutions, and use those instances to benchmark the sampling quality of four D-Wave quantum annealers utilizing different interconnection structures (Chimera, Pegasus, and Zephyr hardware graphs) and the simulated annealing algorithm. Posiform planting differs from many existing methods in two key ways. It ensures the uniqueness of the planted optimal solution, thus avoiding groundstate degeneracy, and it enables the generation of QUBOs that are tailored to a given hardware connectivity structure, provided that the connectivity is not too sparse. Posiform planted QUBOs are a type of 2-SAT boolean satisfiability combinatorial optimization problems. Our experiments demonstrate the capability of the D-Wave quantum annealers to sample the optimal planted solution of combinatorial optimization problems with up to 5, 627 qubits.

97 MATHEMATICS AND COMPUTING↗

Ocean observations with EOS/MODIS: Algorithm development and post launch studies

During CY 1994 there are five objectives under this task: (1) investigate the effects of stratospheric aerosol on the proposed correction algorithm, and investigate the use of the 1380 nm MODIS band to remove the stratospheric aerosol perturbation; (2) investigate the effect of vertical structure in aerosol concentration and type on the behavior of the proposed correction algorithm; (3) investigate the effects of polarization on the accuracy of the algorithm; (4) improve the accuracy and speed of the existing algorithm; and (5) investigate removal of the O2 'A' absorption band at 762 nm from the 765 nm SeaWiFS band so the latter can be used in atmospheric correction of SeaWiFS. The importance of this to MODIS is that SeaWiFS data will be used extensively to test and improve the MODIS algorithm. Thus it is essential that the O2 absorption be adequately dealt with for SeaWiFS.

Gordon, Howard R.↗

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking

RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS) motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

59 BASIC BIOLOGICAL SCIENCES↗

An integrated optimum design approach for high speed prop rotors

The objective is to develop an optimization procedure for high-speed and civil tilt-rotors by coupling all of the necessary disciplines within a closed-loop optimization procedure. Both simplified and comprehensive analysis codes are used for the aerodynamic analyses. The structural properties are calculated using in-house developed algorithms for both isotropic and composite box beam sections. There are four major objectives of this study. (1) Aerodynamic optimization: The effects of blade aerodynamic characteristics on cruise and hover performance of prop-rotor aircraft are investigated using the classical blade element momentum approach with corrections for the high lift capability of rotors/propellers. (2) Coupled aerodynamic/structures optimization: A multilevel hybrid optimization technique is developed for the design of prop-rotor aircraft. The design problem is decomposed into a level for improved aerodynamics with continuous design variables and a level with discrete variables to investigate composite tailoring. The aerodynamic analysis is based on that developed in objective 1 and the structural analysis is performed using an in-house code which models a composite box beam. The results are compared to both a reference rotor and the optimum rotor found in the purely aerodynamic formulation. (3) Multipoint optimization: The multilevel optimization procedure of objective 2 is extended to a multipoint design problem. Hover, cruise, and take-off are the three flight conditions simultaneously maximized. (4) Coupled rotor/wing optimization: Using the comprehensive rotary wing code CAMRAD, an optimization procedure is developed for the coupled rotor/wing performance in high speed tilt-rotor aircraft. The developed procedure contains design variables which define the rotor and wing planforms.

Chattopadhyay, Aditi↗