Reducing the Time and Cost of Testing Engines

NASA Technical Reports Server (NTRS)

2004-01-01

Producing a new aircraft engine currently costs approximately $1 billion, with 3 years of development time for a commercial engine and 10 years for a military engine. The high development time and cost make it extremely difficult to transition advanced technologies for cleaner, quieter, and more efficient new engines. To reduce this time and cost, NASA created a vision for the future where designers would use high-fidelity computer simulations early in the design process in order to resolve critical design issues before building the expensive engine hardware. To accomplish this vision, NASA's Glenn Research Center initiated a collaborative effort with the aerospace industry and academia to develop its Numerical Propulsion System Simulation (NPSS), an advanced engineering environment for the analysis and design of aerospace propulsion systems and components. Partners estimate that using NPSS has the potential to dramatically reduce the time, effort, and expense necessary to design and test jet engines by generating sophisticated computer simulations of an aerospace object or system. These simulations will permit an engineer to test various design options without having to conduct costly and time-consuming real-life tests. By accelerating and streamlining the engine system design analysis and test phases, NPSS facilitates bringing the final product to market faster. NASA's NPSS Version (V)1.X effort was a task within the Agency s Computational Aerospace Sciences project of the High Performance Computing and Communication program, which had a mission to accelerate the availability of high-performance computing hardware and software to the U.S. aerospace community for its use in design processes. The technology brings value back to NASA by improving methods of analyzing and testing space transportation components.

Correlation energy extrapolation by many-body expansion

DOE PAGES

Boschen, Jeffery S.; Theis, Daniel; Ruedenberg, Klaus; ...

2017-01-09

Accounting for electron correlation is required for high accuracy calculations of molecular energies. The full configuration interaction (CI) approach can fully capture the electron correlation within a given basis, but it does so at a computational expense that is impractical for all but the smallest chemical systems. In this work, a new methodology is presented to approximate configuration interaction calculations at a reduced computational expense and memory requirement, namely, the correlation energy extrapolation by many-body expansion (CEEMBE). This method combines a MBE approximation of the CI energy with an extrapolated correction obtained from CI calculations using subsets of the virtualmore » orbitals. The extrapolation approach is inspired by, and analogous to, the method of correlation energy extrapolation by intrinsic scaling. Benchmark calculations of the new method are performed on diatomic fluorine and ozone. Finally, the method consistently achieves agreement with CI calculations to within a few mhartree and often achieves agreement to within ~1 millihartree or less, while requiring significantly less computational resources.« less

Correlation energy extrapolation by many-body expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boschen, Jeffery S.; Theis, Daniel; Ruedenberg, Klaus

Accounting for electron correlation is required for high accuracy calculations of molecular energies. The full configuration interaction (CI) approach can fully capture the electron correlation within a given basis, but it does so at a computational expense that is impractical for all but the smallest chemical systems. In this work, a new methodology is presented to approximate configuration interaction calculations at a reduced computational expense and memory requirement, namely, the correlation energy extrapolation by many-body expansion (CEEMBE). This method combines a MBE approximation of the CI energy with an extrapolated correction obtained from CI calculations using subsets of the virtualmore » orbitals. The extrapolation approach is inspired by, and analogous to, the method of correlation energy extrapolation by intrinsic scaling. Benchmark calculations of the new method are performed on diatomic fluorine and ozone. Finally, the method consistently achieves agreement with CI calculations to within a few mhartree and often achieves agreement to within ~1 millihartree or less, while requiring significantly less computational resources.« less

A preprocessing strategy for helioseismic inversions

NASA Astrophysics Data System (ADS)

Christensen-Dalsgaard, J.; Thompson, M. J.

1993-05-01

Helioseismic inversion in general involves considerable computational expense, due to the large number of modes that is typically considered. This is true in particular of the widely used optimally localized averages (OLA) inversion methods, which require the inversion of one or more matrices whose order is the number of modes in the set. However, the number of practically independent pieces of information that a large helioseismic mode set contains is very much less than the number of modes, suggesting that the set might first be reduced before the expensive inversion is performed. We demonstrate with a model problem that by first performing a singular value decomposition the original problem may be transformed into a much smaller one, reducing considerably the cost of the OLA inversion and with no significant loss of information.

Optimize Resources and Help Reduce Cost of Ownership with Dell[TM] Systems Management

ERIC Educational Resources Information Center

Technology & Learning, 2008

2008-01-01

Maintaining secure, convenient administration of the PC system environment can be a significant drain on resources. Deskside visits can greatly increase the cost of supporting a large number of computers. Even simple tasks, such as tracking inventory or updating software, quickly become expensive when they require physically visiting every…

An Authoring System for Creating Computer-Based Role-Performance Trainers.

ERIC Educational Resources Information Center

Guralnick, David; Kass, Alex

This paper describes a multimedia authoring system called MOPed-II. Like other authoring systems, MOPed-II reduces the time and expense of producing end-user applications by eliminating much of the programming effort they require. However, MOPed-II reflects an approach to authoring tools for educational multimedia which is different from most…

24 CFR 990.165 - Computation of project expense level (PEL).

Code of Federal Regulations, 2011 CFR

2011-04-01

...) Ownership type (profit, non-profit, or limited dividend); and (10) Geographic. (c) Cost adjustments. HUD... ceiling; (3) Application of a four percent reduction for any PEL calculated over $325 PUM, with the reduction limited so that a PEL will not be reduced to less than $325; and (4) The reduction of audit costs...

Accelerating MP2C dispersion corrections for dimers and molecular crystals

NASA Astrophysics Data System (ADS)

Huang, Yuanhang; Shao, Yihan; Beran, Gregory J. O.

2013-06-01

The MP2C dispersion correction of Pitonak and Hesselmann [J. Chem. Theory Comput. 6, 168 (2010)], 10.1021/ct9005882 substantially improves the performance of second-order Møller-Plesset perturbation theory for non-covalent interactions, albeit with non-trivial computational cost. Here, the MP2C correction is computed in a monomer-centered basis instead of a dimer-centered one. When applied to a single dimer MP2 calculation, this change accelerates the MP2C dispersion correction several-fold while introducing only trivial new errors. More significantly, in the context of fragment-based molecular crystal studies, combination of the new monomer basis algorithm and the periodic symmetry of the crystal reduces the cost of computing the dispersion correction by two orders of magnitude. This speed-up reduces the MP2C dispersion correction calculation from a significant computational expense to a negligible one in crystals like aspirin or oxalyl dihydrazide, without compromising accuracy.

Advanced Computational Methods for Thermal Radiative Heat Transfer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tencer, John; Carlberg, Kevin Thomas; Larsen, Marvin E.

2016-10-01

Participating media radiation (PMR) in weapon safety calculations for abnormal thermal environments are too costly to do routinely. This cost may be s ubstantially reduced by applying reduced order modeling (ROM) techniques. The application of ROM to PMR is a new and unique approach for this class of problems. This approach was investigated by the authors and shown to provide significant reductions in the computational expense associated with typical PMR simulations. Once this technology is migrated into production heat transfer analysis codes this capability will enable the routine use of PMR heat transfer in higher - fidelity simulations of weaponmore » resp onse in fire environments.« less

Self-energy matrices for electron transport calculations within the real-space finite-difference formalism

NASA Astrophysics Data System (ADS)

Tsukamoto, Shigeru; Ono, Tomoya; Hirose, Kikuji; Blügel, Stefan

2017-03-01

The self-energy term used in transport calculations, which describes the coupling between electrode and transition regions, is able to be evaluated only from a limited number of the propagating and evanescent waves of a bulk electrode. This obviously contributes toward the reduction of the computational expenses in transport calculations. In this paper, we present a mathematical formula for reducing the computational expenses further without using any approximation and without losing accuracy. So far, the self-energy term has been handled as a matrix with the same dimension as the Hamiltonian submatrix representing the interaction between an electrode and a transition region. In this work, through the singular-value decomposition of the submatrix, the self-energy matrix is handled as a smaller matrix, whose dimension is the rank number of the Hamiltonian submatrix. This procedure is practical in the case of using the pseudopotentials in a separable form, and the computational expenses for determining the self-energy matrix are reduced by 90% when employing a code based on the real-space finite-difference formalism and projector-augmented wave method. In addition, this technique is applicable to the transport calculations using atomic or localized basis sets. Adopting the self-energy matrices obtained from this procedure, we present the calculation of the electron transport properties of C20 molecular junctions. The application demonstrates that the electron transmissions are sensitive to the orientation of the molecule with respect to the electrode surface. In addition, channel decomposition of the scattering wave functions reveals that some unoccupied C20 molecular orbitals mainly contribute to the electron conduction through the molecular junction.

24 CFR 990.170 - Computation of utilities expense level (UEL): Overview.

Code of Federal Regulations, 2010 CFR

2010-04-01

... level (UEL): Overview. 990.170 Section 990.170 Housing and Urban Development Regulations Relating to... Expenses § 990.170 Computation of utilities expense level (UEL): Overview. (a) General. The UEL for each... by the payable consumption level multiplied by the inflation factor. The UEL is expressed in terms of...

GPU Accelerated Prognostics

NASA Technical Reports Server (NTRS)

Gorospe, George E., Jr.; Daigle, Matthew J.; Sankararaman, Shankar; Kulkarni, Chetan S.; Ng, Eley

2017-01-01

Prognostic methods enable operators and maintainers to predict the future performance for critical systems. However, these methods can be computationally expensive and may need to be performed each time new information about the system becomes available. In light of these computational requirements, we have investigated the application of graphics processing units (GPUs) as a computational platform for real-time prognostics. Recent advances in GPU technology have reduced cost and increased the computational capability of these highly parallel processing units, making them more attractive for the deployment of prognostic software. We present a survey of model-based prognostic algorithms with considerations for leveraging the parallel architecture of the GPU and a case study of GPU-accelerated battery prognostics with computational performance results.

Parameterized reduced-order models using hyper-dual numbers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fike, Jeffrey A.; Brake, Matthew Robert

2013-10-01

The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize themore » effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.« less

Efficient Strategies for Estimating the Spatial Coherence of Backscatter

PubMed Central

Hyun, Dongwoon; Crowley, Anna Lisa C.; Dahl, Jeremy J.

2017-01-01

The spatial coherence of ultrasound backscatter has been proposed to reduce clutter in medical imaging, to measure the anisotropy of the scattering source, and to improve the detection of blood flow. These techniques rely on correlation estimates that are obtained using computationally expensive strategies. In this study, we assess existing spatial coherence estimation methods and propose three computationally efficient modifications: a reduced kernel, a downsampled receive aperture, and the use of an ensemble correlation coefficient. The proposed methods are implemented in simulation and in vivo studies. Reducing the kernel to a single sample improved computational throughput and improved axial resolution. Downsampling the receive aperture was found to have negligible effect on estimator variance, and improved computational throughput by an order of magnitude for a downsample factor of 4. The ensemble correlation estimator demonstrated lower variance than the currently used average correlation. Combining the three methods, the throughput was improved 105-fold in simulation with a downsample factor of 4 and 20-fold in vivo with a downsample factor of 2. PMID:27913342

Inner Space Perturbation Theory in Matrix Product States: Replacing Expensive Iterative Diagonalization.

PubMed

Ren, Jiajun; Yi, Yuanping; Shuai, Zhigang

2016-10-11

We propose an inner space perturbation theory (isPT) to replace the expensive iterative diagonalization in the standard density matrix renormalization group theory (DMRG). The retained reduced density matrix eigenstates are partitioned into the active and secondary space. The first-order wave function and the second- and third-order energies are easily computed by using one step Davidson iteration. Our formulation has several advantages including (i) keeping a balance between the efficiency and accuracy, (ii) capturing more entanglement with the same amount of computational time, (iii) recovery of the standard DMRG when all the basis states belong to the active space. Numerical examples for the polyacenes and periacene show that the efficiency gain is considerable and the accuracy loss due to the perturbation treatment is very small, when half of the total basis states belong to the active space. Moreover, the perturbation calculations converge in all our numerical examples.

Real-time algorithm for acoustic imaging with a microphone array.

PubMed

Huang, Xun

2009-05-01

Acoustic phased array has become an important testing tool in aeroacoustic research, where the conventional beamforming algorithm has been adopted as a classical processing technique. The computation however has to be performed off-line due to the expensive cost. An innovative algorithm with real-time capability is proposed in this work. The algorithm is similar to a classical observer in the time domain while extended for the array processing to the frequency domain. The observer-based algorithm is beneficial mainly for its capability of operating over sampling blocks recursively. The expensive experimental time can therefore be reduced extensively since any defect in a testing can be corrected instantaneously.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krityakierne, Tipaluck; Akhtar, Taimoor; Shoemaker, Christine A.

This paper presents a parallel surrogate-based global optimization method for computationally expensive objective functions that is more effective for larger numbers of processors. To reach this goal, we integrated concepts from multi-objective optimization and tabu search into, single objective, surrogate optimization. Our proposed derivative-free algorithm, called SOP, uses non-dominated sorting of points for which the expensive function has been previously evaluated. The two objectives are the expensive function value of the point and the minimum distance of the point to previously evaluated points. Based on the results of non-dominated sorting, P points from the sorted fronts are selected as centersmore » from which many candidate points are generated by random perturbations. Based on surrogate approximation, the best candidate point is subsequently selected for expensive evaluation for each of the P centers, with simultaneous computation on P processors. Centers that previously did not generate good solutions are tabu with a given tenure. We show almost sure convergence of this algorithm under some conditions. The performance of SOP is compared with two RBF based methods. The test results show that SOP is an efficient method that can reduce time required to find a good near optimal solution. In a number of cases the efficiency of SOP is so good that SOP with 8 processors found an accurate answer in less wall-clock time than the other algorithms did with 32 processors.« less

47 CFR 32.6124 - General purpose computers expense.

Code of Federal Regulations, 2013 CFR

2013-10-01

... is the physical operation of general purpose computers and the maintenance of operating systems. This... UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6124... application systems and databases for general purpose computers. (See also § 32.6720, General and...

47 CFR 32.6124 - General purpose computers expense.

Code of Federal Regulations, 2014 CFR

2014-10-01

... is the physical operation of general purpose computers and the maintenance of operating systems. This... UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6124... application systems and databases for general purpose computers. (See also § 32.6720, General and...

47 CFR 32.6124 - General purpose computers expense.

Code of Federal Regulations, 2011 CFR

2011-10-01

... is the physical operation of general purpose computers and the maintenance of operating systems. This... UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6124... application systems and databases for general purpose computers. (See also § 32.6720, General and...

47 CFR 32.6124 - General purpose computers expense.

Code of Federal Regulations, 2012 CFR

2012-10-01

... is the physical operation of general purpose computers and the maintenance of operating systems. This... UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6124... application systems and databases for general purpose computers. (See also § 32.6720, General and...

47 CFR 32.6124 - General purpose computers expense.

Code of Federal Regulations, 2010 CFR

2010-10-01

... is the physical operation of general purpose computers and the maintenance of operating systems. This... UNIFORM SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6124... application systems and databases for general purpose computers. (See also § 32.6720, General and...

A Practical, Robust Methodology for Acquiring New Observation Data Using Computationally Expensive Groundwater Models

NASA Astrophysics Data System (ADS)

Siade, Adam J.; Hall, Joel; Karelse, Robert N.

2017-11-01

Regional groundwater flow models play an important role in decision making regarding water resources; however, the uncertainty embedded in model parameters and model assumptions can significantly hinder the reliability of model predictions. One way to reduce this uncertainty is to collect new observation data from the field. However, determining where and when to obtain such data is not straightforward. There exist a number of data-worth and experimental design strategies developed for this purpose. However, these studies often ignore issues related to real-world groundwater models such as computational expense, existing observation data, high-parameter dimension, etc. In this study, we propose a methodology, based on existing methods and software, to efficiently conduct such analyses for large-scale, complex regional groundwater flow systems for which there is a wealth of available observation data. The method utilizes the well-established d-optimality criterion, and the minimax criterion for robust sampling strategies. The so-called Null-Space Monte Carlo method is used to reduce the computational burden associated with uncertainty quantification. And, a heuristic methodology, based on the concept of the greedy algorithm, is proposed for developing robust designs with subsets of the posterior parameter samples. The proposed methodology is tested on a synthetic regional groundwater model, and subsequently applied to an existing, complex, regional groundwater system in the Perth region of Western Australia. The results indicate that robust designs can be obtained efficiently, within reasonable computational resources, for making regional decisions regarding groundwater level sampling.

REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Khushbu; Sharma, Poorva; Ma, Jinliang

2013-04-30

Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to bemore » extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.« less

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of the failure constraints in the deterministic and reliability based optimization of the ITPS panel. It was shown that using adaptive sampling, the number of designs required to find the optimum were reduced drastically, while improving the accuracy. System reliability of ITPS was estimated using Monte Carlo Simulation (MCS) based method. Separable Monte Carlo method was employed that allowed separable sampling of the random variables to predict the probability of failure accurately. The reliability analysis considered uncertainties in the geometry, material properties, loading conditions of the panel and error in finite element modeling. These uncertainties further increased the computational cost of MCS techniques which was also reduced by employing surrogate models. In order to estimate the error in the probability of failure estimate, bootstrapping method was applied. This research work thus demonstrates optimization of the ITPS composite panel with multiple failure modes and large number of uncertainties using adaptive sampling techniques.

49 CFR 1242.46 - Computers and data processing equipment (account XX-27-46).

Code of Federal Regulations, 2012 CFR

2012-10-01

... REPORTS SEPARATION OF COMMON OPERATING EXPENSES BETWEEN FREIGHT SERVICE AND PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Equipment § 1242.46 Computers and data processing equipment (account XX-27-46... 49 Transportation 9 2012-10-01 2012-10-01 false Computers and data processing equipment (account...

49 CFR 1242.46 - Computers and data processing equipment (account XX-27-46).

Code of Federal Regulations, 2013 CFR

2013-10-01

... REPORTS SEPARATION OF COMMON OPERATING EXPENSES BETWEEN FREIGHT SERVICE AND PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Equipment § 1242.46 Computers and data processing equipment (account XX-27-46... 49 Transportation 9 2013-10-01 2013-10-01 false Computers and data processing equipment (account...

49 CFR 1242.46 - Computers and data processing equipment (account XX-27-46).

Code of Federal Regulations, 2011 CFR

2011-10-01

... REPORTS SEPARATION OF COMMON OPERATING EXPENSES BETWEEN FREIGHT SERVICE AND PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Equipment § 1242.46 Computers and data processing equipment (account XX-27-46... 49 Transportation 9 2011-10-01 2011-10-01 false Computers and data processing equipment (account...

49 CFR 1242.46 - Computers and data processing equipment (account XX-27-46).

Code of Federal Regulations, 2014 CFR

2014-10-01

... REPORTS SEPARATION OF COMMON OPERATING EXPENSES BETWEEN FREIGHT SERVICE AND PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Equipment § 1242.46 Computers and data processing equipment (account XX-27-46... 49 Transportation 9 2014-10-01 2014-10-01 false Computers and data processing equipment (account...

49 CFR 1242.46 - Computers and data processing equipment (account XX-27-46).

Code of Federal Regulations, 2010 CFR

2010-10-01

... REPORTS SEPARATION OF COMMON OPERATING EXPENSES BETWEEN FREIGHT SERVICE AND PASSENGER SERVICE FOR RAILROADS 1 Operating Expenses-Equipment § 1242.46 Computers and data processing equipment (account XX-27-46... 49 Transportation 9 2010-10-01 2010-10-01 false Computers and data processing equipment (account...

A Zonal Approach for Prediction of Jet Noise

NASA Technical Reports Server (NTRS)

Shih, S. H.; Hixon, D. R.; Mankbadi, Reda R.

1995-01-01

A zonal approach for direct computation of sound generation and propagation from a supersonic jet is investigated. The present work splits the computational domain into a nonlinear, acoustic-source regime and a linear acoustic wave propagation regime. In the nonlinear regime, the unsteady flow is governed by the large-scale equations, which are the filtered compressible Navier-Stokes equations. In the linear acoustic regime, the sound wave propagation is described by the linearized Euler equations. Computational results are presented for a supersonic jet at M = 2. 1. It is demonstrated that no spurious modes are generated in the matching region and the computational expense is reduced substantially as opposed to fully large-scale simulation.

A fast CT reconstruction scheme for a general multi-core PC.

PubMed

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.

A Fast CT Reconstruction Scheme for a General Multi-Core PC

PubMed Central

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors. PMID:18256731

Improving finite element results in modeling heart valve mechanics.

PubMed

Earl, Emily; Mohammadi, Hadi

2018-06-01

Finite element analysis is a well-established computational tool which can be used for the analysis of soft tissue mechanics. Due to the structural complexity of the leaflet tissue of the heart valve, the currently available finite element models do not adequately represent the leaflet tissue. A method of addressing this issue is to implement computationally expensive finite element models, characterized by precise constitutive models including high-order and high-density mesh techniques. In this study, we introduce a novel numerical technique that enhances the results obtained from coarse mesh finite element models to provide accuracy comparable to that of fine mesh finite element models while maintaining a relatively low computational cost. Introduced in this study is a method by which the computational expense required to solve linear and nonlinear constitutive models, commonly used in heart valve mechanics simulations, is reduced while continuing to account for large and infinitesimal deformations. This continuum model is developed based on the least square algorithm procedure coupled with the finite difference method adhering to the assumption that the components of the strain tensor are available at all nodes of the finite element mesh model. The suggested numerical technique is easy to implement, practically efficient, and requires less computational time compared to currently available commercial finite element packages such as ANSYS and/or ABAQUS.

Exponential approximations in optimal design

NASA Technical Reports Server (NTRS)

Belegundu, A. D.; Rajan, S. D.; Rajgopal, J.

1990-01-01

One-point and two-point exponential functions have been developed and proved to be very effective approximations of structural response. The exponential has been compared to the linear, reciprocal and quadratic fit methods. Four test problems in structural analysis have been selected. The use of such approximations is attractive in structural optimization to reduce the numbers of exact analyses which involve computationally expensive finite element analysis.

Modifications in the AA5083 Johnson-Cook Material Model for Use in Friction Stir Welding Computational Analyses

DTIC Science & Technology

2011-12-30

which reduces the need for expensive post-weld machining; and (g) low environmental impact . However, some disadvantages of the FSW process have also...next set to that of AISI- H13 , a hot-worked tool steel, frequently used as the FSW-tool material (Ref 16). The work-piece material is assumed to be

Cloud Computing with iPlant Atmosphere.

PubMed

McKay, Sheldon J; Skidmore, Edwin J; LaRose, Christopher J; Mercer, Andre W; Noutsos, Christos

2013-10-15

Cloud Computing refers to distributed computing platforms that use virtualization software to provide easy access to physical computing infrastructure and data storage, typically administered through a Web interface. Cloud-based computing provides access to powerful servers, with specific software and virtual hardware configurations, while eliminating the initial capital cost of expensive computers and reducing the ongoing operating costs of system administration, maintenance contracts, power consumption, and cooling. This eliminates a significant barrier to entry into bioinformatics and high-performance computing for many researchers. This is especially true of free or modestly priced cloud computing services. The iPlant Collaborative offers a free cloud computing service, Atmosphere, which allows users to easily create and use instances on virtual servers preconfigured for their analytical needs. Atmosphere is a self-service, on-demand platform for scientific computing. This unit demonstrates how to set up, access and use cloud computing in Atmosphere. Copyright © 2013 John Wiley & Sons, Inc.

Reducing Earth Topography Resolution for SMAP Mission Ground Tracks Using K-Means Clustering

NASA Technical Reports Server (NTRS)

Rizvi, Farheen

2013-01-01

The K-means clustering algorithm is used to reduce Earth topography resolution for the SMAP mission ground tracks. As SMAP propagates in orbit, knowledge of the radar antenna footprints on Earth is required for the antenna misalignment calibration. Each antenna footprint contains a latitude and longitude location pair on the Earth surface. There are 400 pairs in one data set for the calibration model. It is computationally expensive to calculate corresponding Earth elevation for these data pairs. Thus, the antenna footprint resolution is reduced. Similar topographical data pairs are grouped together with the K-means clustering algorithm. The resolution is reduced to the mean of each topographical cluster called the cluster centroid. The corresponding Earth elevation for each cluster centroid is assigned to the entire group. Results show that 400 data points are reduced to 60 while still maintaining algorithm performance and computational efficiency. In this work, sensitivity analysis is also performed to show a trade-off between algorithm performance versus computational efficiency as the number of cluster centroids and algorithm iterations are increased.

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

NASA Technical Reports Server (NTRS)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

2003-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Computational reduction strategies for the detection of steady bifurcations in incompressible fluid-dynamics: Applications to Coanda effect in cardiology

NASA Astrophysics Data System (ADS)

Pitton, Giuseppe; Quaini, Annalisa; Rozza, Gianluigi

2017-09-01

We focus on reducing the computational costs associated with the hydrodynamic stability of solutions of the incompressible Navier-Stokes equations for a Newtonian and viscous fluid in contraction-expansion channels. In particular, we are interested in studying steady bifurcations, occurring when non-unique stable solutions appear as physical and/or geometric control parameters are varied. The formulation of the stability problem requires solving an eigenvalue problem for a partial differential operator. An alternative to this approach is the direct simulation of the flow to characterize the asymptotic behavior of the solution. Both approaches can be extremely expensive in terms of computational time. We propose to apply Reduced Order Modeling (ROM) techniques to reduce the demanding computational costs associated with the detection of a type of steady bifurcations in fluid dynamics. The application that motivated the present study is the onset of asymmetries (i.e., symmetry breaking bifurcation) in blood flow through a regurgitant mitral valve, depending on the Reynolds number and the regurgitant mitral valve orifice shape.

Simplifying silicon burning: Application of quasi-equilibrium to (alpha) network nucleosynthesis

NASA Technical Reports Server (NTRS)

Hix, W. R.; Thielemann, F.-K.; Khokhlov, A. M.; Wheeler, J. C.

1997-01-01

While the need for accurate calculation of nucleosynthesis and the resulting rate of thermonuclear energy release within hydrodynamic models of stars and supernovae is clear, the computational expense of these nucleosynthesis calculations often force a compromise in accuracy to reduce the computational cost. To redress this trade-off of accuracy for speed, the authors present an improved nuclear network which takes advantage of quasi- equilibrium in order to reduce the number of independent nuclei, and hence the computational cost of nucleosynthesis, without significant reduction in accuracy. In this paper they will discuss the first application of this method, the further reduction in size of the minimal alpha network. The resultant QSE- reduced alpha network is twice as fast as the conventional alpha network it replaces and requires the tracking of half as many abundance variables, while accurately estimating the rate of energy generation. Such reduction in cost is particularly necessary for future generation of multi-dimensional models for supernovae.

47 CFR 69.156 - Marketing expenses.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 3 2014-10-01 2014-10-01 false Marketing expenses. 69.156 Section 69.156... Computation of Charges for Price Cap Local Exchange Carriers § 69.156 Marketing expenses. Effective July 1, 2000, the marketing expenses formerly allocated to the common line and traffic sensitive baskets, and...

47 CFR 69.156 - Marketing expenses.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 3 2012-10-01 2012-10-01 false Marketing expenses. 69.156 Section 69.156... Computation of Charges for Price Cap Local Exchange Carriers § 69.156 Marketing expenses. Effective July 1, 2000, the marketing expenses formerly allocated to the common line and traffic sensitive baskets, and...

47 CFR 69.156 - Marketing expenses.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Marketing expenses. 69.156 Section 69.156... Computation of Charges for Price Cap Local Exchange Carriers § 69.156 Marketing expenses. Effective July 1, 2000, the marketing expenses formerly allocated to the common line and traffic sensitive baskets, and...

47 CFR 69.156 - Marketing expenses.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Marketing expenses. 69.156 Section 69.156... Computation of Charges for Price Cap Local Exchange Carriers § 69.156 Marketing expenses. Effective July 1, 2000, the marketing expenses formerly allocated to the common line and traffic sensitive baskets, and...

47 CFR 69.156 - Marketing expenses.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 3 2013-10-01 2013-10-01 false Marketing expenses. 69.156 Section 69.156... Computation of Charges for Price Cap Local Exchange Carriers § 69.156 Marketing expenses. Effective July 1, 2000, the marketing expenses formerly allocated to the common line and traffic sensitive baskets, and...

Adaptive Crack Modeling with Interface Solid Elements for Plain and Fiber Reinforced Concrete Structures.

PubMed

Zhan, Yijian; Meschke, Günther

2017-07-08

The effective analysis of the nonlinear behavior of cement-based engineering structures not only demands physically-reliable models, but also computationally-efficient algorithms. Based on a continuum interface element formulation that is suitable to capture complex cracking phenomena in concrete materials and structures, an adaptive mesh processing technique is proposed for computational simulations of plain and fiber-reinforced concrete structures to progressively disintegrate the initial finite element mesh and to add degenerated solid elements into the interfacial gaps. In comparison with the implementation where the entire mesh is processed prior to the computation, the proposed adaptive cracking model allows simulating the failure behavior of plain and fiber-reinforced concrete structures with remarkably reduced computational expense.

Adaptive Crack Modeling with Interface Solid Elements for Plain and Fiber Reinforced Concrete Structures

PubMed Central

Zhan, Yijian

2017-01-01

The effective analysis of the nonlinear behavior of cement-based engineering structures not only demands physically-reliable models, but also computationally-efficient algorithms. Based on a continuum interface element formulation that is suitable to capture complex cracking phenomena in concrete materials and structures, an adaptive mesh processing technique is proposed for computational simulations of plain and fiber-reinforced concrete structures to progressively disintegrate the initial finite element mesh and to add degenerated solid elements into the interfacial gaps. In comparison with the implementation where the entire mesh is processed prior to the computation, the proposed adaptive cracking model allows simulating the failure behavior of plain and fiber-reinforced concrete structures with remarkably reduced computational expense. PMID:28773130

Methods for simulation-based analysis of fluid-structure interaction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barone, Matthew Franklin; Payne, Jeffrey L.

2005-10-01

Methods for analysis of fluid-structure interaction using high fidelity simulations are critically reviewed. First, a literature review of modern numerical techniques for simulation of aeroelastic phenomena is presented. The review focuses on methods contained within the arbitrary Lagrangian-Eulerian (ALE) framework for coupling computational fluid dynamics codes to computational structural mechanics codes. The review treats mesh movement algorithms, the role of the geometric conservation law, time advancement schemes, wetted surface interface strategies, and some representative applications. The complexity and computational expense of coupled Navier-Stokes/structural dynamics simulations points to the need for reduced order modeling to facilitate parametric analysis. The proper orthogonalmore » decomposition (POD)/Galerkin projection approach for building a reduced order model (ROM) is presented, along with ideas for extension of the methodology to allow construction of ROMs based on data generated from ALE simulations.« less

The successful merger of theoretical thermochemistry with fragment-based methods in quantum chemistry.

PubMed

Ramabhadran, Raghunath O; Raghavachari, Krishnan

2014-12-16

CONSPECTUS: Quantum chemistry and electronic structure theory have proven to be essential tools to the experimental chemist, in terms of both a priori predictions that pave the way for designing new experiments and rationalizing experimental observations a posteriori. Translating the well-established success of electronic structure theory in obtaining the structures and energies of small chemical systems to increasingly larger molecules is an exciting and ongoing central theme of research in quantum chemistry. However, the prohibitive computational scaling of highly accurate ab initio electronic structure methods poses a fundamental challenge to this research endeavor. This scenario necessitates an indirect fragment-based approach wherein a large molecule is divided into small fragments and is subsequently reassembled to compute its energy accurately. In our quest to further reduce the computational expense associated with the fragment-based methods and overall enhance the applicability of electronic structure methods to large molecules, we realized that the broad ideas involved in a different area, theoretical thermochemistry, are transferable to the area of fragment-based methods. This Account focuses on the effective merger of these two disparate frontiers in quantum chemistry and how new concepts inspired by theoretical thermochemistry significantly reduce the total number of electronic structure calculations needed to be performed as part of a fragment-based method without any appreciable loss of accuracy. Throughout, the generalized connectivity based hierarchy (CBH), which we developed to solve a long-standing problem in theoretical thermochemistry, serves as the linchpin in this merger. The accuracy of our method is based on two strong foundations: (a) the apt utilization of systematic and sophisticated error-canceling schemes via CBH that result in an optimal cutting scheme at any given level of fragmentation and (b) the use of a less expensive second layer of electronic structure method to recover all the missing long-range interactions in the parent large molecule. Overall, the work featured here dramatically decreases the computational expense and empowers the execution of very accurate ab initio calculations (gold-standard CCSD(T)) on large molecules and thereby facilitates sophisticated electronic structure applications to a wide range of important chemical problems.

A Markov Chain-based quantitative study of angular distribution of photons through turbid slabs via isotropic light scattering

NASA Astrophysics Data System (ADS)

Li, Xuesong; Northrop, William F.

2016-04-01

This paper describes a quantitative approach to approximate multiple scattering through an isotropic turbid slab based on Markov Chain theorem. There is an increasing need to utilize multiple scattering for optical diagnostic purposes; however, existing methods are either inaccurate or computationally expensive. Here, we develop a novel Markov Chain approximation approach to solve multiple scattering angular distribution (AD) that can accurately calculate AD while significantly reducing computational cost compared to Monte Carlo simulation. We expect this work to stimulate ongoing multiple scattering research and deterministic reconstruction algorithm development with AD measurements.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

NASA Astrophysics Data System (ADS)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.

Using Reconstructed POD Modes as Turbulent Inflow for LES Wind Turbine Simulations

NASA Astrophysics Data System (ADS)

Nielson, Jordan; Bhaganagar, Kiran; Juttijudata, Vejapong; Sirisup, Sirod

2016-11-01

Currently, in order to get realistic atmospheric effects of turbulence, wind turbine LES simulations require computationally expensive precursor simulations. At times, the precursor simulation is more computationally expensive than the wind turbine simulation. The precursor simulations are important because they capture turbulence in the atmosphere and as stated above, turbulence impacts the power production estimation. On the other hand, POD analysis has been shown to be capable of capturing turbulent structures. The current study was performed to determine the plausibility of using lower dimension models from POD analysis of LES simulations as turbulent inflow to wind turbine LES simulations. The study will aid the wind energy community by lowering the computational cost of full scale wind turbine LES simulations, while maintaining a high level of turbulent information and being able to quickly apply the turbulent inflow to multi turbine wind farms. This will be done by comparing a pure LES precursor wind turbine simulation with simulations that use reduced POD mod inflow conditions. The study shows the feasibility of using lower dimension models as turbulent inflow of LES wind turbine simulations. Overall the power production estimation and velocity field of the wind turbine wake are well captured with small errors.

CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms

PubMed Central

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.

2011-01-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404

CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.

PubMed

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W

2012-06-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

48 CFR 227.7103-6 - Contract clauses.

Code of Federal Regulations, 2013 CFR

2013-10-01

... private expense). Do not use the clause when the only deliverable items are computer software or computer software documentation (see 227.72), commercial items developed exclusively at private expense (see 227... the clause in architect-engineer and construction contracts. (b)(1) Use the clause at 252.227-7013...

48 CFR 227.7103-6 - Contract clauses.

Code of Federal Regulations, 2014 CFR

2014-10-01

... private expense). Do not use the clause when the only deliverable items are computer software or computer software documentation (see 227.72), commercial items developed exclusively at private expense (see 227... the clause in architect-engineer and construction contracts. (b)(1) Use the clause at 252.227-7013...

The QSE-Reduced Nuclear Reaction Network for Silicon Burning

NASA Astrophysics Data System (ADS)

Hix, W. Raphael; Parete-Koon, Suzanne T.; Freiburghaus, Christian; Thielemann, Friedrich-Karl

2007-09-01

Iron and neighboring nuclei are formed in massive stars shortly before core collapse and during their supernova outbursts, as well as during thermonuclear supernovae. Complete and incomplete silicon burning are responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. However, examination of the physics of silicon burning has revealed that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present a new hybrid equilibrium-network scheme which takes advantage of this quasi-equilibrium in order to reduce the number of independent variables calculated. This allows accurate prediction of the nuclear abundance evolution, deleptonization, and energy generation at a greatly reduced computational cost when compared to a conventional nuclear reaction network. During silicon burning, the resultant QSE-reduced network is approximately an order of magnitude faster than the full network it replaces and requires the tracking of less than a third as many abundance variables, without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multidimensional applications.

24 CFR 990.165 - Computation of project expense level (PEL).

Code of Federal Regulations, 2010 CFR

2010-04-01

... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Computation of project expense level (PEL). 990.165 Section 990.165 Housing and Urban Development Regulations Relating to Housing and Urban Development (Continued) OFFICE OF ASSISTANT SECRETARY FOR PUBLIC AND INDIAN HOUSING, DEPARTMENT OF...

Fast Legendre moment computation for template matching

NASA Astrophysics Data System (ADS)

Li, Bing C.

2017-05-01

Normalized cross correlation (NCC) based template matching is insensitive to intensity changes and it has many applications in image processing, object detection, video tracking and pattern recognition. However, normalized cross correlation implementation is computationally expensive since it involves both correlation computation and normalization implementation. In this paper, we propose Legendre moment approach for fast normalized cross correlation implementation and show that the computational cost of this proposed approach is independent of template mask sizes which is significantly faster than traditional mask size dependent approaches, especially for large mask templates. Legendre polynomials have been widely used in solving Laplace equation in electrodynamics in spherical coordinate systems, and solving Schrodinger equation in quantum mechanics. In this paper, we extend Legendre polynomials from physics to computer vision and pattern recognition fields, and demonstrate that Legendre polynomials can help to reduce the computational cost of NCC based template matching significantly.

Impact of energy taxation on economy, environmental and public health quality.

PubMed

Wang, Baoqing; Liu, Bowei; Niu, Honghong; Liu, Jianfeng; Yao, Shu

2018-01-15

This paper argues computable general equilibrium model and assess impact of energy taxation on economy, environmental and public health quality in Tianjin. In order to investigate different energy taxation based on medical cost and labor loss, the computable general equilibrium model integrating with input-output table and social accounting matrix (SAM) was constructed. The medical expense caused by air pollution of Tianjin in 2007 is 396 million yuan and death for 18104 people, which accounted for the total GDP and population 0.754‰ and 1.6‰, respectively. The results show that the enery taxes levy can improve the GDP, but it is only slightly. The energy taxes have adverse impact on energy sector because that the energy cost is increased. The scale of production is reduced, and the capital and labor resources are transferred to low energy consumption low emissions sector. The energy tax levy can reduce air pollutants concentration and improve air environmental quality. The PM 10 , SO 2 and NO 2 concentration in the energy taxes 5%-30% was reduced by 0.24%-0.24%, 0.09-0.52% and 0.29%-0.52% respectively. The medical expense has little impact on GDP, but labor loss has a certain effect on GDP. For higher energy taxes rate, the health effects on GDP can reach 0.06%-0.16%. This simultaneous economic and environmental improvement and health effect would thus have positive implications regarding energy taxes of the country. Copyright © 2017 Elsevier Ltd. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mueller, Juliane

MISO is an optimization framework for solving computationally expensive mixed-integer, black-box, global optimization problems. MISO uses surrogate models to approximate the computationally expensive objective function. Hence, derivative information, which is generally unavailable for black-box simulation objective functions, is not needed. MISO allows the user to choose the initial experimental design strategy, the type of surrogate model, and the sampling strategy.

48 CFR 9905.506-60 - Illustrations.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., installs a computer service center to begin operations on May 1. The operating expense related to the new... operating expenses of the computer service center for the 8-month part of the cost accounting period may be... 48 Federal Acquisition Regulations System 7 2013-10-01 2012-10-01 true Illustrations. 9905.506-60...

26 CFR 1.50B-1 - Definitions of WIN expenses and WIN employees.

Code of Federal Regulations, 2010 CFR

2010-04-01

... employee. (c) Trade or business expenses. The term “WIN expenses” includes only salaries and wages which... 26 Internal Revenue 1 2010-04-01 2010-04-01 true Definitions of WIN expenses and WIN employees. 1... INCOME TAXES Rules for Computing Credit for Expenses of Work Incentive Programs § 1.50B-1 Definitions of...

Faster simulation plots

NASA Technical Reports Server (NTRS)

Fowell, Richard A.

1989-01-01

Most simulation plots are heavily oversampled. Ignoring unnecessary data points dramatically reduces plot time with imperceptible effect on quality. The technique is suited to most plot devices. The departments laser printer's speed was tripled for large simulation plots by data thinning. This reduced printer delays without the expense of a faster laser printer. Surpisingly, it saved computer time as well. All plot data are now thinned, including PostScript and terminal plots. The problem, solution, and conclusions are described. The thinning algorithm is described and performance studies are presented. To obtain FORTRAN 77 or C source listings, mail a SASE to the author.

47 CFR 32.6112 - Motor vehicle expense.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Motor vehicle expense. 32.6112 Section 32.6112 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES UNIFORM SYSTEM OF ACCOUNTS.../or to other Plant Specific Operations Expense accounts. These amounts shall be computed on the basis...

AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, D.; Alfonsi, A.; Talbot, P.

2016-10-01

The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, themore » overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).« less

Parallel hyperspectral image reconstruction using random projections

NASA Astrophysics Data System (ADS)

Sevilla, Jorge; Martín, Gabriel; Nascimento, José M. P.

2016-10-01

Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE PAGES

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

Economical Unsteady High-Fidelity Aerodynamics for Structural Optimization with a Flutter Constraint

NASA Technical Reports Server (NTRS)

Bartels, Robert E.; Stanford, Bret K.

2017-01-01

Structural optimization with a flutter constraint for a vehicle designed to fly in the transonic regime is a particularly difficult task. In this speed range, the flutter boundary is very sensitive to aerodynamic nonlinearities, typically requiring high-fidelity Navier-Stokes simulations. However, the repeated application of unsteady computational fluid dynamics to guide an aeroelastic optimization process is very computationally expensive. This expense has motivated the development of methods that incorporate aspects of the aerodynamic nonlinearity, classical tools of flutter analysis, and more recent methods of optimization. While it is possible to use doublet lattice method aerodynamics, this paper focuses on the use of an unsteady high-fidelity aerodynamic reduced order model combined with successive transformations that allows for an economical way of utilizing high-fidelity aerodynamics in the optimization process. This approach is applied to the common research model wing structural design. As might be expected, the high-fidelity aerodynamics produces a heavier wing than that optimized with doublet lattice aerodynamics. It is found that the optimized lower skin of the wing using high-fidelity aerodynamics differs significantly from that using doublet lattice aerodynamics.

Signal decomposition for surrogate modeling of a constrained ultrasonic design space

NASA Astrophysics Data System (ADS)

Homa, Laura; Sparkman, Daniel; Wertz, John; Welter, John; Aldrin, John C.

2018-04-01

The U.S. Air Force seeks to improve the methods and measures by which the lifecycle of composite structures are managed. Nondestructive evaluation of damage - particularly internal damage resulting from impact - represents a significant input to that improvement. Conventional ultrasound can detect this damage; however, full 3D characterization has not been demonstrated. A proposed approach for robust characterization uses model-based inversion through fitting of simulated results to experimental data. One challenge with this approach is the high computational expense of the forward model to simulate the ultrasonic B-scans for each damage scenario. A potential solution is to construct a surrogate model using a subset of simulated ultrasonic scans built using a highly accurate, computationally expensive forward model. However, the dimensionality of these simulated B-scans makes interpolating between them a difficult and potentially infeasible problem. Thus, we propose using the chirplet decomposition to reduce the dimensionality of the data, and allow for interpolation in the chirplet parameter space. By applying the chirplet decomposition, we are able to extract the salient features in the data and construct a surrogate forward model.

47 CFR 32.6121 - Land and building expense.

Code of Federal Regulations, 2013 CFR

2013-10-01

... operate the telecommunications network shall be charged to Account 6531, Power Expense, and the cost of separately metered electricity used for operating specific types of equipment, such as computers, shall be... SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6121 Land and...

47 CFR 32.6121 - Land and building expense.

Code of Federal Regulations, 2012 CFR

2012-10-01

... operate the telecommunications network shall be charged to Account 6531, Power Expense, and the cost of separately metered electricity used for operating specific types of equipment, such as computers, shall be... SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6121 Land and...

47 CFR 32.6121 - Land and building expense.

Code of Federal Regulations, 2011 CFR

2011-10-01

... operate the telecommunications network shall be charged to Account 6531, Power Expense, and the cost of separately metered electricity used for operating specific types of equipment, such as computers, shall be... SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6121 Land and...

47 CFR 32.6121 - Land and building expense.

Code of Federal Regulations, 2014 CFR

2014-10-01

... operate the telecommunications network shall be charged to Account 6531, Power Expense, and the cost of separately metered electricity used for operating specific types of equipment, such as computers, shall be... SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6121 Land and...

47 CFR 32.6121 - Land and building expense.

Code of Federal Regulations, 2010 CFR

2010-10-01

... operate the telecommunications network shall be charged to Account 6531, Power Expense, and the cost of separately metered electricity used for operating specific types of equipment, such as computers, shall be... SYSTEM OF ACCOUNTS FOR TELECOMMUNICATIONS COMPANIES Instructions for Expense Accounts § 32.6121 Land and...

The Case for Modular Redundancy in Large-Scale High Performance Computing Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engelmann, Christian; Ong, Hong Hoe; Scott, Stephen L

2009-01-01

Recent investigations into resilience of large-scale high-performance computing (HPC) systems showed a continuous trend of decreasing reliability and availability. Newly installed systems have a lower mean-time to failure (MTTF) and a higher mean-time to recover (MTTR) than their predecessors. Modular redundancy is being used in many mission critical systems today to provide for resilience, such as for aerospace and command \\& control systems. The primary argument against modular redundancy for resilience in HPC has always been that the capability of a HPC system, and respective return on investment, would be significantly reduced. We argue that modular redundancy can significantly increasemore » compute node availability as it removes the impact of scale from single compute node MTTR. We further argue that single compute nodes can be much less reliable, and therefore less expensive, and still be highly available, if their MTTR/MTTF ratio is maintained.« less

7 CFR 1484.53 - What are the requirements for documenting and reporting contributions?

Code of Federal Regulations, 2010 CFR

2010-01-01

... contribution must be documented by the Cooperator, showing the method of computing non-cash contributions, salaries, and travel expenses. (b) Each Cooperator must keep records of the methods used to compute the value of non-cash contributions, and (1) Copies of invoices or receipts for expenses paid by the U.S...

An energy-efficient failure detector for vehicular cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Dong, Jian; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.

An energy-efficient failure detector for vehicular cloud computing

PubMed Central

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption. PMID:29352282

Metasurface optics for full-color computational imaging.

PubMed

Colburn, Shane; Zhan, Alan; Majumdar, Arka

2018-02-01

Conventional imaging systems comprise large and expensive optical components that successively mitigate aberrations. Metasurface optics offers a route to miniaturize imaging systems by replacing bulky components with flat and compact implementations. The diffractive nature of these devices, however, induces severe chromatic aberrations, and current multiwavelength and narrowband achromatic metasurfaces cannot support full visible spectrum imaging (400 to 700 nm). We combine principles of both computational imaging and metasurface optics to build a system with a single metalens of numerical aperture ~0.45, which generates in-focus images under white light illumination. Our metalens exhibits a spectrally invariant point spread function that enables computational reconstruction of captured images with a single digital filter. This work connects computational imaging and metasurface optics and demonstrates the capabilities of combining these disciplines by simultaneously reducing aberrations and downsizing imaging systems using simpler optics.

SubspaceEM: A Fast Maximum-a-posteriori Algorithm for Cryo-EM Single Particle Reconstruction

PubMed Central

Dvornek, Nicha C.; Sigworth, Fred J.; Tagare, Hemant D.

2015-01-01

Single particle reconstruction methods based on the maximum-likelihood principle and the expectation-maximization (E–M) algorithm are popular because of their ability to produce high resolution structures. However, these algorithms are computationally very expensive, requiring a network of computational servers. To overcome this computational bottleneck, we propose a new mathematical framework for accelerating maximum-likelihood reconstructions. The speedup is by orders of magnitude and the proposed algorithm produces similar quality reconstructions compared to the standard maximum-likelihood formulation. Our approach uses subspace approximations of the cryo-electron microscopy (cryo-EM) data and projection images, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300. PMID:25839831

Efficient convolutional sparse coding

DOEpatents

Wohlberg, Brendt

2017-06-20

Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

26 CFR 1.213-1 - Medical, dental, etc., expenses.

Code of Federal Regulations, 2010 CFR

2010-04-01

... medical care includes the diagnosis, cure, mitigation, treatment, or prevention of disease. Expenses paid... taxable year for insurance that constitute expenses paid for medical care shall, for purposes of computing... care of the taxpayer, his spouse, or a dependent of the taxpayer and not be compensated for by...

26 CFR 1.556-2 - Adjustments to taxable income.

Code of Federal Regulations, 2010 CFR

2010-04-01

... of deductions for trade or business expenses and depreciation which are allocable to the operation... computed without the deduction of the amount disallowed under section 556(b)(5), relating to expenses and... disallowed under section 556(b)(5), relating to expenses and depreciation applicable to property of the...

Time-Shifted Boundary Conditions Used for Navier-Stokes Aeroelastic Solver

NASA Technical Reports Server (NTRS)

Srivastava, Rakesh

1999-01-01

Under the Advanced Subsonic Technology (AST) Program, an aeroelastic analysis code (TURBO-AE) based on Navier-Stokes equations is currently under development at NASA Lewis Research Center s Machine Dynamics Branch. For a blade row, aeroelastic instability can occur in any of the possible interblade phase angles (IBPA s). Analyzing small IBPA s is very computationally expensive because a large number of blade passages must be simulated. To reduce the computational cost of these analyses, we used time shifted, or phase-lagged, boundary conditions in the TURBO-AE code. These conditions can be used to reduce the computational domain to a single blade passage by requiring the boundary conditions across the passage to be lagged depending on the IBPA being analyzed. The time-shifted boundary conditions currently implemented are based on the direct-store method. This method requires large amounts of data to be stored over a period of the oscillation cycle. On CRAY computers this is not a major problem because solid-state devices can be used for fast input and output to read and write the data onto a disk instead of storing it in core memory.

Development of a Navier-Stokes algorithm for parallel-processing supercomputers. Ph.D. Thesis - Colorado State Univ., Dec. 1988

NASA Technical Reports Server (NTRS)

Swisshelm, Julie M.

1989-01-01

An explicit flow solver, applicable to the hierarchy of model equations ranging from Euler to full Navier-Stokes, is combined with several techniques designed to reduce computational expense. The computational domain consists of local grid refinements embedded in a global coarse mesh, where the locations of these refinements are defined by the physics of the flow. Flow characteristics are also used to determine which set of model equations is appropriate for solution in each region, thereby reducing not only the number of grid points at which the solution must be obtained, but also the computational effort required to get that solution. Acceleration to steady-state is achieved by applying multigrid on each of the subgrids, regardless of the particular model equations being solved. Since each of these components is explicit, advantage can readily be taken of the vector- and parallel-processing capabilities of machines such as the Cray X-MP and Cray-2.

Reduced description of reactive flows with tabulation of chemistry

NASA Astrophysics Data System (ADS)

Ren, Zhuyin; Goldin, Graham M.; Hiremath, Varun; Pope, Stephen B.

2011-12-01

The direct use of large chemical mechanisms in multi-dimensional Computational Fluid Dynamics (CFD) is computationally expensive due to the large number of chemical species and the wide range of chemical time scales involved. To meet this challenge, a reduced description of reactive flows in combination with chemistry tabulation is proposed to effectively reduce the computational cost. In the reduced description, the species are partitioned into represented species and unrepresented species; the reactive system is described in terms of a smaller number of represented species instead of the full set of chemical species in the mechanism; and the evolution equations are solved only for the represented species. When required, the unrepresented species are reconstructed assuming that they are in constrained chemical equilibrium. In situ adaptive tabulation (ISAT) is employed to speed the chemistry calculation through tabulating information of the reduced system. The proposed dimension-reduction / tabulation methodology determines and tabulates in situ the necessary information of the nr-dimensional reduced system based on the ns-species detailed mechanism. Compared to the full description with ISAT, the reduced descriptions achieve additional computational speed-up by solving fewer transport equations and faster ISAT retrieving. The approach is validated in both a methane/air premixed flame and a methane/air non-premixed flame. With the GRI 1.2 mechanism consisting of 31 species, the reduced descriptions (with 12 to 16 represented species) achieve a speed-up factor of up to three compared to the full description with ISAT, with a relatively moderate decrease in accuracy compared to the full description.

Parallel implementation of geometrical shock dynamics for two dimensional converging shock waves

NASA Astrophysics Data System (ADS)

Qiu, Shi; Liu, Kuang; Eliasson, Veronica

2016-10-01

Geometrical shock dynamics (GSD) theory is an appealing method to predict the shock motion in the sense that it is more computationally efficient than solving the traditional Euler equations, especially for converging shock waves. However, to solve and optimize large scale configurations, the main bottleneck is the computational cost. Among the existing numerical GSD schemes, there is only one that has been implemented on parallel computers, with the purpose to analyze detonation waves. To extend the computational advantage of the GSD theory to more general applications such as converging shock waves, a numerical implementation using a spatial decomposition method has been coupled with a front tracking approach on parallel computers. In addition, an efficient tridiagonal system solver for massively parallel computers has been applied to resolve the most expensive function in this implementation, resulting in an efficiency of 0.93 while using 32 HPCC cores. Moreover, symmetric boundary conditions have been developed to further reduce the computational cost, achieving a speedup of 19.26 for a 12-sided polygonal converging shock.

Multidisciplinary optimization of an HSCT wing using a response surface methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giunta, A.A.; Grossman, B.; Mason, W.H.

1994-12-31

Aerospace vehicle design is traditionally divided into three phases: conceptual, preliminary, and detailed. Each of these design phases entails a particular level of accuracy and computational expense. While there are several computer programs which perform inexpensive conceptual-level aircraft multidisciplinary design optimization (MDO), aircraft MDO remains prohibitively expensive using preliminary- and detailed-level analysis tools. This occurs due to the expense of computational analyses and because gradient-based optimization requires the analysis of hundreds or thousands of aircraft configurations to estimate design sensitivity information. A further hindrance to aircraft MDO is the problem of numerical noise which occurs frequently in engineering computations. Computermore » models produce numerical noise as a result of the incomplete convergence of iterative processes, round-off errors, and modeling errors. Such numerical noise is typically manifested as a high frequency, low amplitude variation in the results obtained from the computer models. Optimization attempted using noisy computer models may result in the erroneous calculation of design sensitivities and may slow or prevent convergence to an optimal design.« less

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a powerful tool for large-scale applications.

Simultaneous Aerodynamic and Structural Design Optimization (SASDO) for a 3-D Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.; Newman, Perry A.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic and Structural Design Optimization (SASDO) is shown as an extension of the Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) method. It is extended by the inclusion of structure element sizing parameters as design variables and Finite Element Method (FEM) analysis responses as constraints. The method aims to reduce the computational expense. incurred in performing shape and sizing optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, FEM structural analysis and sensitivity analysis tools. SASDO is applied to a simple. isolated, 3-D wing in inviscid flow. Results show that the method finds the saine local optimum as a conventional optimization method with some reduction in the computational cost and without significant modifications; to the analysis tools.

Reduced Design Load Basis for Ultimate Blade Loads Estimation in Multidisciplinary Design Optimization Frameworks

NASA Astrophysics Data System (ADS)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.; Kim, Taeseong; Thomsen, Kenneth

2016-09-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar to the one computed using the full DLB. This observation is used to propose a scheme that is computationally cheap, and that can be integrated inside an MDO framework, providing a sufficiently reliable estimation of the blade ultimate loading. The latter aspect is of key importance when design variables implementing passive control methodologies are included in the formulation of the optimization problem. An MDO of a 10 MW wind turbine blade is presented as an applied case study to show the efficacy of the reduced DLB concept.

Energy Efficiency Challenges of 5G Small Cell Networks.

PubMed

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-05-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks.

Energy Efficiency Challenges of 5G Small Cell Networks

PubMed Central

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

2017-01-01

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this paper is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 watt when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks. PMID:28757670

Using Neural Networks in the Mapping of Mixed Discrete/Continuous Design Spaces With Application to Structural Design

DTIC Science & Technology

1994-02-01

desired that the problem to which the design space mapping techniques were applied be easily analyzed, yet provide a design space with realistic complexity...consistent fully stressed solution. 3 DESIGN SPACE MAPPING In order to reduce the computational expense required to optimize design spaces, neural networks...employed in this study. Some of the issues involved in using neural networks to do design space mapping are how to configure the neural network, how much

CASL VMA Milestone Report FY16 (L3:VMA.VUQ.P13.08): Westinghouse Mixing with STAR-CCM+

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilkey, Lindsay Noelle

2016-09-30

STAR-CCM+ (STAR) is a high-resolution computational fluid dynamics (CFD) code developed by CD-adapco. STAR includes validated physics models and a full suite of turbulence models including ones from the k-ε and k-ω families. STAR is currently being developed to be able to do two phase flows, but the current focus of the software is single phase flow. STAR can use imported meshes or use the built in meshing software to create computation domains for CFD. Since the solvers generally require a fine mesh for good computational results, the meshes used with STAR tend to number in the millions of cells,more » with that number growing with simulation and geometry complexity. The time required to model the flow of a full 5x5 Mixing Vane Grid Assembly (5x5MVG) in the current STAR configuration is on the order of hours, and can be very computationally expensive. COBRA-TF (CTF) is a low-resolution subchannel code that can be trained using high fidelity data from STAR. CTF does not have turbulence models and instead uses a turbulent mixing coefficient β. With a properly calibrated β, CTF can be used a low-computational cost alternative to expensive full CFD calculations performed with STAR. During the Hi2Lo work with CTF and STAR, STAR-CCM+ will be used to calibrate β and to provide high-resolution results that can be used in the place of and in addition to experimental results to reduce the uncertainty in the CTF results.« less

A New Low Complexity Angle of Arrival Algorithm for 1D and 2D Direction Estimation in MIMO Smart Antenna Systems

PubMed Central

Al-Sadoon, Mohammed A. G.; Zuid, Abdulkareim; Jones, Stephen M. R.; Noras, James M.

2017-01-01

This paper proposes a new low complexity angle of arrival (AOA) method for signal direction estimation in multi-element smart wireless communication systems. The new method estimates the AOAs of the received signals directly from the received signals with significantly reduced complexity since it does not need to construct the correlation matrix, invert the matrix or apply eigen-decomposition, which are computationally expensive. A mathematical model of the proposed method is illustrated and then verified using extensive computer simulations. Both linear and circular sensors arrays are studied using various numerical examples. The method is systematically compared with other common and recently introduced AOA methods over a wide range of scenarios. The simulated results show that the new method has several advantages in terms of reduced complexity and improved accuracy under the assumptions of correlated signals and limited numbers of snapshots. PMID:29140313

A New Low Complexity Angle of Arrival Algorithm for 1D and 2D Direction Estimation in MIMO Smart Antenna Systems.

PubMed

Al-Sadoon, Mohammed A G; Ali, Nazar T; Dama, Yousf; Zuid, Abdulkareim; Jones, Stephen M R; Abd-Alhameed, Raed A; Noras, James M

2017-11-15

This paper proposes a new low complexity angle of arrival (AOA) method for signal direction estimation in multi-element smart wireless communication systems. The new method estimates the AOAs of the received signals directly from the received signals with significantly reduced complexity since it does not need to construct the correlation matrix, invert the matrix or apply eigen-decomposition, which are computationally expensive. A mathematical model of the proposed method is illustrated and then verified using extensive computer simulations. Both linear and circular sensors arrays are studied using various numerical examples. The method is systematically compared with other common and recently introduced AOA methods over a wide range of scenarios. The simulated results show that the new method has several advantages in terms of reduced complexity and improved accuracy under the assumptions of correlated signals and limited numbers of snapshots.

An Adaptive QSE-reduced Nuclear Reaction Network for Silicon Burning

NASA Astrophysics Data System (ADS)

Parete-Koon, Suzanne; Hix, William Raphael; Thielemann, Friedrich-Karl

2010-02-01

The nuclei of the ``iron peak'' are formed late in the evolution of massive stars and during supernovae. Silicon burning during these events is responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. The large number of nuclei involved make accurate modeling of silicon burning computationally expensive. Examination of the physics of silicon burning reveals that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present an improvement on our hybrid equilibrium-network scheme that takes advantage of this quasi-equilibrium (QSE) to reduce the number of independent variables calculated. Because the membership and number of these groups vary as the temperature, density and electron faction change, achieving maximal efficiency requires dynamic adjustment of group number and membership. The resultant QSE-reduced network is up to 20 times faster than the full network it replaces without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multi-dimensional applications. )

A case study of tuning MapReduce for efficient Bioinformatics in the cloud

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Lizhen; Wang, Zhong; Yu, Weikuan

The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics datamore » analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.« less

Rank restriction for the variational calculation of two-electron reduced density matrices of many-electron atoms and molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naftchi-Ardebili, Kasra; Hau, Nathania W.; Mazziotti, David A.

2011-11-15

Variational minimization of the ground-state energy as a function of the two-electron reduced density matrix (2-RDM), constrained by necessary N-representability conditions, provides a polynomial-scaling approach to studying strongly correlated molecules without computing the many-electron wave function. Here we introduce a route to enhancing necessary conditions for N representability through rank restriction of the 2-RDM. Rather than adding computationally more expensive N-representability conditions, we directly enhance the accuracy of two-particle (2-positivity) conditions through rank restriction, which removes degrees of freedom in the 2-RDM that are not sufficiently constrained. We select the rank of the particle-hole 2-RDM by deriving the ranks associatedmore » with model wave functions, including both mean-field and antisymmetrized geminal power (AGP) wave functions. Because the 2-positivity conditions are exact for quantum systems with AGP ground states, the rank of the particle-hole 2-RDM from the AGP ansatz provides a minimum for its value in variational 2-RDM calculations of general quantum systems. To implement the rank-restricted conditions, we extend a first-order algorithm for large-scale semidefinite programming. The rank-restricted conditions significantly improve the accuracy of the energies; for example, the percentages of correlation energies recovered for HF, CO, and N{sub 2} improve from 115.2%, 121.7%, and 121.5% without rank restriction to 97.8%, 101.1%, and 100.0% with rank restriction. Similar results are found at both equilibrium and nonequilibrium geometries. While more accurate, the rank-restricted N-representability conditions are less expensive computationally than the full-rank conditions.« less

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

NASA Technical Reports Server (NTRS)

Simpson, Timothy W.; Peplinski, Jesse; Koch, Patrick N.; Allen, Janet K.

1997-01-01

The use of statistical techniques to build approximations of expensive computer analysis codes pervades much of todays engineering design. These statistical approximations, or metamodels, are used to replace the actual expensive computer analyses, facilitating multidisciplinary, multiobjective optimization and concept exploration. In this paper we review several of these techniques including design of experiments, response surface methodology, Taguchi methods, neural networks, inductive learning, and kriging. We survey their existing application in engineering design and then address the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes. We conclude with recommendations for the appropriate use of statistical approximation techniques in given situations and how common pitfalls can be avoided.

41 CFR 301-71.105 - Must we issue a written or electronic travel authorization in advance of travel?

Code of Federal Regulations, 2010 CFR

2010-07-01

...; (c) Use of reduced fares for group or charter arrangements; (d) Use of cash to pay for common carrier... Government aircraft; (i) Payment of a reduced rate per diem; (j) Payment of actual expenses; (k) Travel expenses related to emergency travel; (l) Transportation expenses related to threatened law enforcement...

Can price controls reduce pharmaceutical expenses? A case study of antibacterial expenditures in 12 Chinese hospitals from 1996 to 2005.

PubMed

Han, Sheng; Liang, Huigang; Su, Weiping; Xue, Yajiong; Shi, Luwen

2013-01-01

The objective of this article is to investigate whether the Chinese government's pricing policies have reduced pharmaceutical expenses. The purchasing records for systemic antibacterial drugs of 12 hospitals in Beijing from 1996 to 2005 were analyzed by separating the expenditure growth into three components: the price change, the volume change, and the structure change. Our results reveal that the structure change is the dominant determinant of drug expenditure growth. Despite lowered prices, the antibacterial drug expenditure was raised because more expensive drugs in the same therapeutic category were prescribed. It is insufficient to rely only on pricing policies to reduce drug expenses, given that physicians could circumvent the policy by prescribing more expensive drugs. In addition, physician behaviors need to be regulated to eliminate unnecessary overprescribing.

GPGPU-based explicit finite element computations for applications in biomechanics: the performance of material models, element technologies, and hardware generations.

PubMed

Strbac, V; Pierce, D M; Vander Sloten, J; Famaey, N

2017-12-01

Finite element (FE) simulations are increasingly valuable in assessing and improving the performance of biomedical devices and procedures. Due to high computational demands such simulations may become difficult or even infeasible, especially when considering nearly incompressible and anisotropic material models prevalent in analyses of soft tissues. Implementations of GPGPU-based explicit FEs predominantly cover isotropic materials, e.g. the neo-Hookean model. To elucidate the computational expense of anisotropic materials, we implement the Gasser-Ogden-Holzapfel dispersed, fiber-reinforced model and compare solution times against the neo-Hookean model. Implementations of GPGPU-based explicit FEs conventionally rely on single-point (under) integration. To elucidate the expense of full and selective-reduced integration (more reliable) we implement both and compare corresponding solution times against those generated using underintegration. To better understand the advancement of hardware, we compare results generated using representative Nvidia GPGPUs from three recent generations: Fermi (C2075), Kepler (K20c), and Maxwell (GTX980). We explore scaling by solving the same boundary value problem (an extension-inflation test on a segment of human aorta) with progressively larger FE meshes. Our results demonstrate substantial improvements in simulation speeds relative to two benchmark FE codes (up to 300[Formula: see text] while maintaining accuracy), and thus open many avenues to novel applications in biomechanics and medicine.

Preliminary Structural Sensitivity Study of Hypersonic Inflatable Aerodynamic Decelerator Using Probabilistic Methods

NASA Technical Reports Server (NTRS)

Lyle, Karen H.

2014-01-01

Acceptance of new spacecraft structural architectures and concepts requires validated design methods to minimize the expense involved with technology validation via flighttesting. This paper explores the implementation of probabilistic methods in the sensitivity analysis of the structural response of a Hypersonic Inflatable Aerodynamic Decelerator (HIAD). HIAD architectures are attractive for spacecraft deceleration because they are lightweight, store compactly, and utilize the atmosphere to decelerate a spacecraft during re-entry. However, designers are hesitant to include these inflatable approaches for large payloads or spacecraft because of the lack of flight validation. In the example presented here, the structural parameters of an existing HIAD model have been varied to illustrate the design approach utilizing uncertainty-based methods. Surrogate models have been used to reduce computational expense several orders of magnitude. The suitability of the design is based on assessing variation in the resulting cone angle. The acceptable cone angle variation would rely on the aerodynamic requirements.

Tchebichef moment transform on image dithering for mobile applications

NASA Astrophysics Data System (ADS)

Ernawan, Ferda; Abu, Nur Azman; Rahmalan, Hidayah

2012-04-01

Currently, mobile image applications spend a lot of computing process to display images. A true color raw image contains billions of colors and it consumes high computational power in most mobile image applications. At the same time, mobile devices are only expected to be equipped with lower computing process and minimum storage space. Image dithering is a popular technique to reduce the numbers of bit per pixel at the expense of lower quality image displays. This paper proposes a novel approach on image dithering using 2x2 Tchebichef moment transform (TMT). TMT integrates a simple mathematical framework technique using matrices. TMT coefficients consist of real rational numbers. An image dithering based on TMT has the potential to provide better efficiency and simplicity. The preliminary experiment shows a promising result in term of error reconstructions and image visual textures.

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

Closed-form solution of decomposable stochastic models

NASA Technical Reports Server (NTRS)

Sjogren, Jon A.

1990-01-01

Markov and semi-Markov processes are increasingly being used in the modeling of complex reconfigurable systems (fault tolerant computers). The estimation of the reliability (or some measure of performance) of the system reduces to solving the process for its state probabilities. Such a model may exhibit numerous states and complicated transition distributions, contributing to an expensive and numerically delicate solution procedure. Thus, when a system exhibits a decomposition property, either structurally (autonomous subsystems), or behaviorally (component failure versus reconfiguration), it is desirable to exploit this decomposition in the reliability calculation. In interesting cases there can be failure states which arise from non-failure states of the subsystems. Equations are presented which allow the computation of failure probabilities of the total (combined) model without requiring a complete solution of the combined model. This material is presented within the context of closed-form functional representation of probabilities as utilized in the Symbolic Hierarchical Automated Reliability and Performance Evaluator (SHARPE) tool. The techniques adopted enable one to compute such probability functions for a much wider class of systems at a reduced computational cost. Several examples show how the method is used, especially in enhancing the versatility of the SHARPE tool.

[The effectiveness of a system using re-useable linens to reduce the expense of surgical operations].

PubMed

Nagano, Kazuko; Morita, Saori; Shinoda, Maiko; Kawana, Yuki; Satou, Yuu; Yokozuka, Makito

2013-10-01

We introduced a system that uses re-useable linens for surgical operations in 2008. After 3 years from introduction we were able to reduce the expense of about yen 4,340,000 per year and CO2 production of 9,548 kg CO2 x m(-2) per year. We were convinced of the effect on reducing the expense of surgical operations and of decreasing the level of CO2 production that leads to global warming.

Using quantum chemistry muscle to flex massive systems: How to respond to something perturbing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bertoni, Colleen

Computational chemistry uses the theoretical advances of quantum mechanics and the algorithmic and hardware advances of computer science to give insight into chemical problems. It is currently possible to do highly accurate quantum chemistry calculations, but the most accurate methods are very computationally expensive. Thus it is only feasible to do highly accurate calculations on small molecules, since typically more computationally efficient methods are also less accurate. The overall goal of my dissertation work has been to try to decrease the computational expense of calculations without decreasing the accuracy. In particular, my dissertation work focuses on fragmentation methods, intermolecular interactionsmore » methods, analytic gradients, and taking advantage of new hardware.« less

47 CFR 36.311 - Network Support/General Support Expenses-Accounts 6110 and 6120 (Class B Telephone Companies...

Code of Federal Regulations, 2014 CFR

2014-10-01

... (Class A Telephone Companies). 36.311 Section 36.311 Telecommunication FEDERAL COMMUNICATIONS COMMISSION..., office equipment, and general purpose computers. (b) The expenses in these account are apportioned among...

47 CFR 36.311 - Network Support/General Support Expenses-Accounts 6110 and 6120 (Class B Telephone Companies...

Code of Federal Regulations, 2013 CFR

2013-10-01

... (Class A Telephone Companies). 36.311 Section 36.311 Telecommunication FEDERAL COMMUNICATIONS COMMISSION..., office equipment, and general purpose computers. (b) The expenses in these account are apportioned among...

47 CFR 36.311 - Network Support/General Support Expenses-Accounts 6110 and 6120 (Class B Telephone Companies...

Code of Federal Regulations, 2012 CFR

2012-10-01

... (Class A Telephone Companies). 36.311 Section 36.311 Telecommunication FEDERAL COMMUNICATIONS COMMISSION..., office equipment, and general purpose computers. (b) The expenses in these account are apportioned among...

Reduced-cost linear-response CC2 method based on natural orbitals and natural auxiliary functions

PubMed Central

Mester, Dávid

2017-01-01

A reduced-cost density fitting (DF) linear-response second-order coupled-cluster (CC2) method has been developed for the evaluation of excitation energies. The method is based on the simultaneous truncation of the molecular orbital (MO) basis and the auxiliary basis set used for the DF approximation. For the reduction of the size of the MO basis, state-specific natural orbitals (NOs) are constructed for each excited state using the average of the second-order Møller–Plesset (MP2) and the corresponding configuration interaction singles with perturbative doubles [CIS(D)] density matrices. After removing the NOs of low occupation number, natural auxiliary functions (NAFs) are constructed [M. Kállay, J. Chem. Phys. 141, 244113 (2014)], and the NAF basis is also truncated. Our results show that, for a triple-zeta basis set, about 60% of the virtual MOs can be dropped, while the size of the fitting basis can be reduced by a factor of five. This results in a dramatic reduction of the computational costs of the solution of the CC2 equations, which are in our approach about as expensive as the evaluation of the MP2 and CIS(D) density matrices. All in all, an average speedup of more than an order of magnitude can be achieved at the expense of a mean absolute error of 0.02 eV in the calculated excitation energies compared to the canonical CC2 results. Our benchmark calculations demonstrate that the new approach enables the efficient computation of CC2 excitation energies for excited states of all types of medium-sized molecules composed of up to 100 atoms with triple-zeta quality basis sets. PMID:28527453

Using Neural Networks to Improve the Performance of Radiative Transfer Modeling Used for Geometry Dependent LER Calculations

NASA Astrophysics Data System (ADS)

Fasnacht, Z.; Qin, W.; Haffner, D. P.; Loyola, D. G.; Joiner, J.; Krotkov, N. A.; Vasilkov, A. P.; Spurr, R. J. D.

2017-12-01

In order to estimate surface reflectance used in trace gas retrieval algorithms, radiative transfer models (RTM) such as the Vector Linearized Discrete Ordinate Radiative Transfer Model (VLIDORT) can be used to simulate the top of the atmosphere (TOA) radiances with advanced models of surface properties. With large volumes of satellite data, these model simulations can become computationally expensive. Look up table interpolation can improve the computational cost of the calculations, but the non-linear nature of the radiances requires a dense node structure if interpolation errors are to be minimized. In order to reduce our computational effort and improve the performance of look-up tables, neural networks can be trained to predict these radiances. We investigate the impact of using look-up table interpolation versus a neural network trained using the smart sampling technique, and show that neural networks can speed up calculations and reduce errors while using significantly less memory and RTM calls. In future work we will implement a neural network in operational processing to meet growing demands for reflectance modeling in support of high spatial resolution satellite missions.

Ferruleless coupled-cavity traveling-wave tube cold-test characteristics simulated with micro-SOS

NASA Technical Reports Server (NTRS)

Schroeder, Dana L.; Wilson, Jeffrey D.

1993-01-01

The three-dimensional, electromagnetic circuit analysis code, Micro-SOS, can be used to reduce expensive and time consuming experimental 'cold-testing' of traveling-wave tube (TWT) circuits. The frequency-phase dispersion and beam interaction impedance characteristics of a ferruleless coupled-cavity traveling-wave tube slow-wave circuit were simulated using the code. Computer results agree closely with experimental data. Variations in the cavity geometry dimensions of period length and gap-to-period ratio were modeled. These variations can be used in velocity taper designs to reduce the radiofrequency (RF) phase velocity in synchronism with the decelerating electron beam. Such circuit designs can result in enhanced TWT power and efficiency.

Release of information: are hospitals taking a hit?

PubMed

Bellenghi, G Michael; Coffey, Bonnie; Fournier, Joseph E; McDavid, Jan P

2008-11-01

Outsourcing release-of-information requests helps hospitals alleviate administrative and compliance burdens and expense. Recently, state lawmakers have begun to draft legislation reducing the maximum fee that may be charged for copies of electronically stored records. The reduced fees may not cover expenses. If such legislation makes it difficult for outsourcing companies to make a profit from this service, hospitals ultimately could bear the expense and risk.

Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea

2015-09-01

The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, themore » overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.« less

A microeconomic scheduler for parallel computers

NASA Technical Reports Server (NTRS)

Stoica, Ion; Abdel-Wahab, Hussein; Pothen, Alex

1995-01-01

We describe a scheduler based on the microeconomic paradigm for scheduling on-line a set of parallel jobs in a multiprocessor system. In addition to the classical objectives of increasing the system throughput and reducing the response time, we consider fairness in allocating system resources among the users, and providing the user with control over the relative performances of his jobs. We associate with every user a savings account in which he receives money at a constant rate. When a user wants to run a job, he creates an expense account for that job to which he transfers money from his savings account. The job uses the funds in its expense account to obtain the system resources it needs for execution. The share of the system resources allocated to the user is directly related to the rate at which the user receives money; the rate at which the user transfers money into a job expense account controls the job's performance. We prove that starvation is not possible in our model. Simulation results show that our scheduler improves both system and user performances in comparison with two different variable partitioning policies. It is also shown to be effective in guaranteeing fairness and providing control over the performance of jobs.

Benefit from NASA

NASA Image and Video Library

1998-01-01

Don Sirois, an Auburn University research associate, and Bruce Strom, a mechanical engineering Co-Op Student, are evaluating the dimensional characteristics of an aluminum automobile engine casting. More accurate metal casting processes may reduce the weight of some cast metal products used in automobiles, such as engines. Research in low gravity has taken an important first step toward making metal products used in homes, automobiles, and aircraft less expensive, safer, and more durable. Auburn University and industry are partnering with NASA to develop one of the first accurate computer model predictions of molten metals and molding materials used in a manufacturing process called casting. Ford Motor Company's casting plant in Cleveland, Ohio is using NASA-sponsored computer modeling information to improve the casting process of automobile and light-truck engine blocks.

Improving Metal Casting Process

NASA Technical Reports Server (NTRS)

1998-01-01

Don Sirois, an Auburn University research associate, and Bruce Strom, a mechanical engineering Co-Op Student, are evaluating the dimensional characteristics of an aluminum automobile engine casting. More accurate metal casting processes may reduce the weight of some cast metal products used in automobiles, such as engines. Research in low gravity has taken an important first step toward making metal products used in homes, automobiles, and aircraft less expensive, safer, and more durable. Auburn University and industry are partnering with NASA to develop one of the first accurate computer model predictions of molten metals and molding materials used in a manufacturing process called casting. Ford Motor Company's casting plant in Cleveland, Ohio is using NASA-sponsored computer modeling information to improve the casting process of automobile and light-truck engine blocks.

Efficient approach to obtain free energy gradient using QM/MM MD simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asada, Toshio; Koseki, Shiro; The Research Institute for Molecular Electronic Devices

2015-12-31

The efficient computational approach denoted as charge and atom dipole response kernel (CDRK) model to consider polarization effects of the quantum mechanical (QM) region is described using the charge response and the atom dipole response kernels for free energy gradient (FEG) calculations in the quantum mechanical/molecular mechanical (QM/MM) method. CDRK model can reasonably reproduce energies and also energy gradients of QM and MM atoms obtained by expensive QM/MM calculations in a drastically reduced computational time. This model is applied on the acylation reaction in hydrated trypsin-BPTI complex to optimize the reaction path on the free energy surface by means ofmore » FEG and the nudged elastic band (NEB) method.« less

Enhanced Performance of Streamline-Traced External-Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Slater, John W.

2015-01-01

A computational design study was conducted to enhance the aerodynamic performance of streamline-traced, external-compression inlets for Mach 1.6. Compared to traditional external-compression, two-dimensional and axisymmetric inlets, streamline-traced inlets promise reduced cowl wave drag and sonic boom, but at the expense of reduced total pressure recovery and increased total pressure distortion. The current study explored a new parent flowfield for the streamline tracing and several variations of inlet design factors, including the axial displacement and angle of the subsonic cowl lip, the vertical placement of the engine axis, and the use of porous bleed in the subsonic diffuser. The performance was enhanced over that of an earlier streamline-traced inlet such as to increase the total pressure recovery and reduce total pressure distortion.

HEVC optimizations for medical environments

NASA Astrophysics Data System (ADS)

Fernández, D. G.; Del Barrio, A. A.; Botella, Guillermo; García, Carlos; Meyer-Baese, Uwe; Meyer-Baese, Anke

2016-05-01

HEVC/H.265 is the most interesting and cutting-edge topic in the world of digital video compression, allowing to reduce by half the required bandwidth in comparison with the previous H.264 standard. Telemedicine services and in general any medical video application can benefit from the video encoding advances. However, the HEVC is computationally expensive to implement. In this paper a method for reducing the HEVC complexity in the medical environment is proposed. The sequences that are typically processed in this context contain several homogeneous regions. Leveraging these regions, it is possible to simplify the HEVC flow while maintaining a high-level quality. In comparison with the HM16.2 standard, the encoding time is reduced up to 75%, with a negligible quality loss. Moreover, the algorithm is straightforward to implement in any hardware platform.

Software Models Impact Stresses

NASA Technical Reports Server (NTRS)

Hanshaw, Timothy C.; Roy, Dipankar; Toyooka, Mark

1991-01-01

Generalized Impact Stress Software designed to assist engineers in predicting stresses caused by variety of impacts. Program straightforward, simple to implement on personal computers, "user friendly", and handles variety of boundary conditions applied to struck body being analyzed. Applications include mathematical modeling of motions and transient stresses of spacecraft, analysis of slamming of piston, of fast valve shutoffs, and play of rotating bearing assembly. Provides fast and inexpensive analytical tool for analysis of stresses and reduces dependency on expensive impact tests. Written in FORTRAN 77. Requires use of commercial software package PLOT88.

A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics

PubMed Central

Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.

2013-01-01

We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055

Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens

NASA Astrophysics Data System (ADS)

Litjens, G.; Ehteshami Bejnordi, B.; Timofeeva, N.; Swadi, G.; Kovacs, I.; Hulsbergen-van de Kaa, C.; van der Laak, J.

2015-03-01

Automated detection of prostate cancer in digitized H and E whole-slide images is an important first step for computer-driven grading. Most automated grading algorithms work on preselected image patches as they are too computationally expensive to calculate on the multi-gigapixel whole-slide images. An automated multi-resolution cancer detection system could reduce the computational workload for subsequent grading and quantification in two ways: by excluding areas of definitely normal tissue within a single specimen or by excluding entire specimens which do not contain any cancer. In this work we present a multi-resolution cancer detection algorithm geared towards the latter. The algorithm methodology is as follows: at a coarse resolution the system uses superpixels, color histograms and local binary patterns in combination with a random forest classifier to assess the likelihood of cancer. The five most suspicious superpixels are identified and at a higher resolution more computationally expensive graph and gland features are added to refine classification for these superpixels. Our methods were evaluated in a data set of 204 digitized whole-slide H and E stained images of MR-guided biopsy specimens from 163 patients. A pathologist exhaustively annotated the specimens for areas containing cancer. The performance of our system was evaluated using ten-fold cross-validation, stratified according to patient. Image-based receiver operating characteristic (ROC) analysis was subsequently performed where a specimen containing cancer was considered positive and specimens without cancer negative. We obtained an area under the ROC curve of 0.96 and a 0.4 specificity at a 1.0 sensitivity.

Effective orthorhombic anisotropic models for wavefield extrapolation

NASA Astrophysics Data System (ADS)

Ibanez-Jacome, Wilson; Alkhalifah, Tariq; Waheed, Umair bin

2014-09-01

Wavefield extrapolation in orthorhombic anisotropic media incorporates complicated but realistic models to reproduce wave propagation phenomena in the Earth's subsurface. Compared with the representations used for simpler symmetries, such as transversely isotropic or isotropic, orthorhombic models require an extended and more elaborated formulation that also involves more expensive computational processes. The acoustic assumption yields more efficient description of the orthorhombic wave equation that also provides a simplified representation for the orthorhombic dispersion relation. However, such representation is hampered by the sixth-order nature of the acoustic wave equation, as it also encompasses the contribution of shear waves. To reduce the computational cost of wavefield extrapolation in such media, we generate effective isotropic inhomogeneous models that are capable of reproducing the first-arrival kinematic aspects of the orthorhombic wavefield. First, in order to compute traveltimes in vertical orthorhombic media, we develop a stable, efficient and accurate algorithm based on the fast marching method. The derived orthorhombic acoustic dispersion relation, unlike the isotropic or transversely isotropic ones, is represented by a sixth order polynomial equation with the fastest solution corresponding to outgoing P waves in acoustic media. The effective velocity models are then computed by evaluating the traveltime gradients of the orthorhombic traveltime solution, and using them to explicitly evaluate the corresponding inhomogeneous isotropic velocity field. The inverted effective velocity fields are source dependent and produce equivalent first-arrival kinematic descriptions of wave propagation in orthorhombic media. We extrapolate wavefields in these isotropic effective velocity models using the more efficient isotropic operator, and the results compare well, especially kinematically, with those obtained from the more expensive anisotropic extrapolator.

Many Masses on One Stroke:. Economic Computation of Quark Propagators

NASA Astrophysics Data System (ADS)

Frommer, Andreas; Nöckel, Bertold; Güsken, Stephan; Lippert, Thomas; Schilling, Klaus

The computational effort in the calculation of Wilson fermion quark propagators in Lattice Quantum Chromodynamics can be considerably reduced by exploiting the Wilson fermion matrix structure in inversion algorithms based on the non-symmetric Lanczos process. We consider two such methods: QMR (quasi minimal residual) and BCG (biconjugate gradients). Based on the decomposition M/κ = 1/κ-D of the Wilson mass matrix, using QMR, one can carry out inversions on a whole trajectory of masses simultaneously, merely at the computational expense of a single propagator computation. In other words, one has to compute the propagator corresponding to the lightest mass only, while all the heavier masses are given for free, at the price of extra storage. Moreover, the symmetry γ5M = M†γ5 can be used to cut the computational effort in QMR and BCG by a factor of two. We show that both methods then become — in the critical regime of small quark masses — competitive to BiCGStab and significantly better than the standard MR method, with optimal relaxation factor, and CG as applied to the normal equations.

Distributed computing for membrane-based modeling of action potential propagation.

PubMed

Porras, D; Rogers, J M; Smith, W M; Pollard, A E

2000-08-01

Action potential propagation simulations with physiologic membrane currents and macroscopic tissue dimensions are computationally expensive. We, therefore, analyzed distributed computing schemes to reduce execution time in workstation clusters by parallelizing solutions with message passing. Four schemes were considered in two-dimensional monodomain simulations with the Beeler-Reuter membrane equations. Parallel speedups measured with each scheme were compared to theoretical speedups, recognizing the relationship between speedup and code portions that executed serially. A data decomposition scheme based on total ionic current provided the best performance. Analysis of communication latencies in that scheme led to a load-balancing algorithm in which measured speedups at 89 +/- 2% and 75 +/- 8% of theoretical speedups were achieved in homogeneous and heterogeneous clusters of workstations. Speedups in this scheme with the Luo-Rudy dynamic membrane equations exceeded 3.0 with eight distributed workstations. Cluster speedups were comparable to those measured during parallel execution on a shared memory machine.

Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) for a 3-D Flexible Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) are extended from single discipline analysis (aerodynamics only) to multidisciplinary analysis - in this case, static aero-structural analysis - and applied to a simple 3-D wing problem. The method aims to reduce the computational expense incurred in performing shape optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, Finite Element Method (FEM) structural analysis and sensitivity analysis tools. Results for this small problem show that the method reaches the same local optimum as conventional optimization. However, unlike its application to the win,, (single discipline analysis), the method. as I implemented here, may not show significant reduction in the computational cost. Similar reductions were seen in the two-design-variable (DV) problem results but not in the 8-DV results given here.

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

VLSI processors for signal detection in SETI

NASA Technical Reports Server (NTRS)

Duluk, J. F.; Linscott, I. R.; Peterson, A. M.; Burr, J.; Ekroot, B.; Twicken, J.

1989-01-01

The objective of the Search for Extraterrestrial Intelligence (SETI) is to locate an artificially created signal coming from a distant star. This is done in two steps: (1) spectral analysis of an incoming radio frequency band, and (2) pattern detection for narrow-band signals. Both steps are computationally expensive and require the development of specially designed computer architectures. To reduce the size and cost of the SETI signal detection machine, two custom VLSI chips are under development. The first chip, the SETI DSP Engine, is used in the spectrum analyzer and is specially designed to compute Discrete Fourier Transforms (DFTs). It is a high-speed arithmetic processor that has two adders, one multiplier-accumulator, and three four-port memories. The second chip is a new type of Content-Addressable Memory. It is the heart of an associative processor that is used for pattern detection. Both chips incorporate many innovative circuits and architectural features.

VLSI processors for signal detection in SETI.

PubMed

Duluk, J F; Linscott, I R; Peterson, A M; Burr, J; Ekroot, B; Twicken, J

1989-01-01

The objective of the Search for Extraterrestrial Intelligence (SETI) is to locate an artificially created signal coming from a distant star. This is done in two steps: (1) spectral analysis of an incoming radio frequency band, and (2) pattern detection for narrow-band signals. Both steps are computationally expensive and require the development of specially designed computer architectures. To reduce the size and cost of the SETI signal detection machine, two custom VLSI chips are under development. The first chip, the SETI DSP Engine, is used in the spectrum analyzer and is specially designed to compute Discrete Fourier Transforms (DFTs). It is a high-speed arithmetic processor that has two adders, one multiplier-accumulator, and three four-port memories. The second chip is a new type of Content-Addressable Memory. It is the heart of an associative processor that is used for pattern detection. Both chips incorporate many innovative circuits and architectural features.

Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, Sajeev; Martin, Randall V.; Keller, Christoph A.

2016-05-01

Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typically used by global chemistry-transport models, and identify the operator durations that optimize both computational expense and simulation accuracy. We find that longer continuous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but increases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, secondary inorganic aerosols, ozone and carbon monoxide with a finer temporal or spatial resolution taken as "truth". Relative simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) operator duration. Chemical operator duration twice that of the transport operator duration offers more simulation accuracy per unit computation. However, the relative simulation error from coarser spatial resolution generally exceeds that from longer operator duration; e.g., degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different operator durations in offline chemistry-transport models. We encourage chemistry-transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

NASA Astrophysics Data System (ADS)

Philip, S.; Martin, R. V.; Keller, C. A.

2015-11-01

Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

Effects of combined dimension reduction and tabulation on the simulations of a turbulent premixed flame using a large-eddy simulation/probability density function method

NASA Astrophysics Data System (ADS)

Kim, Jeonglae; Pope, Stephen B.

2014-05-01

A turbulent lean-premixed propane-air flame stabilised by a triangular cylinder as a flame-holder is simulated to assess the accuracy and computational efficiency of combined dimension reduction and tabulation of chemistry. The computational condition matches the Volvo rig experiments. For the reactive simulation, the Lagrangian Large-Eddy Simulation/Probability Density Function (LES/PDF) formulation is used. A novel two-way coupling approach between LES and PDF is applied to obtain resolved density to reduce its statistical fluctuations. Composition mixing is evaluated by the modified Interaction-by-Exchange with the Mean (IEM) model. A baseline case uses In Situ Adaptive Tabulation (ISAT) to calculate chemical reactions efficiently. Its results demonstrate good agreement with the experimental measurements in turbulence statistics, temperature, and minor species mass fractions. For dimension reduction, 11 and 16 represented species are chosen and a variant of Rate Controlled Constrained Equilibrium (RCCE) is applied in conjunction with ISAT to each case. All the quantities in the comparison are indistinguishable from the baseline results using ISAT only. The combined use of RCCE/ISAT reduces the computational time for chemical reaction by more than 50%. However, for the current turbulent premixed flame, chemical reaction takes only a minor portion of the overall computational cost, in contrast to non-premixed flame simulations using LES/PDF, presumably due to the restricted manifold of purely premixed flame in the composition space. Instead, composition mixing is the major contributor to cost reduction since the mean-drift term, which is computationally expensive, is computed for the reduced representation. Overall, a reduction of more than 15% in the computational cost is obtained.

Symplectic multi-particle tracking on GPUs

NASA Astrophysics Data System (ADS)

Liu, Zhicong; Qiang, Ji

2018-05-01

A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation.

Approximation of Failure Probability Using Conditional Sampling

NASA Technical Reports Server (NTRS)

Giesy. Daniel P.; Crespo, Luis G.; Kenney, Sean P.

2008-01-01

In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

A Case against Computer Symbolic Manipulation in School Mathematics Today.

ERIC Educational Resources Information Center

Waits, Bert K.; Demana, Franklin

1992-01-01

Presented are two reasons discouraging computer symbol manipulation systems use in school mathematics at present: cost for computer laboratories or expensive pocket computers; and impracticality of exact solution representations. Although development with this technology in mathematics education advances, graphing calculators are recommended to…

A simple parameterization of aerosol emissions in RAMS

NASA Astrophysics Data System (ADS)

Letcher, Theodore

Throughout the past decade, a high degree of attention has been focused on determining the microphysical impact of anthropogenically enhanced concentrations of Cloud Condensation Nuclei (CCN) on orographic snowfall in the mountains of the western United States. This area has garnered a lot of attention due to the implications this effect may have on local water resource distribution within the Region. Recent advances in computing power and the development of highly advanced microphysical schemes within numerical models have provided an estimation of the sensitivity that orographic snowfall has to changes in atmospheric CCN concentrations. However, what is still lacking is a coupling between these advanced microphysical schemes and a real-world representation of CCN sources. Previously, an attempt to representation the heterogeneous evolution of aerosol was made by coupling three-dimensional aerosol output from the WRF Chemistry model to the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS) (Ward et al. 2011). The biggest problem associated with this scheme was the computational expense. In fact, the computational expense associated with this scheme was so high, that it was prohibitive for simulations with fine enough resolution to accurately represent microphysical processes. To improve upon this method, a new parameterization for aerosol emission was developed in such a way that it was fully contained within RAMS. Several assumptions went into generating a computationally efficient aerosol emissions parameterization in RAMS. The most notable assumption was the decision to neglect the chemical processes in formed in the formation of Secondary Aerosol (SA), and instead treat SA as primary aerosol via short-term WRF-CHEM simulations. While, SA makes up a substantial portion of the total aerosol burden (much of which is made up of organic material), the representation of this process is highly complex and highly expensive within a numerical model. Furthermore, SA formation is greatly reduced during the winter months due to the lack of naturally produced organic VOC's. Because of these reasons, it was felt that neglecting SOA within the model was the best course of action. The actual parameterization uses a prescribed source map to add aerosol to the model at two vertical levels that surround an arbitrary height decided by the user. To best represent the real-world, the WRF Chemistry model was run using the National Emissions Inventory (NEI2005) to represent anthropogenic emissions and the Model Emissions of Gases and Aerosols from Nature (MEGAN) to represent natural contributions to aerosol. WRF Chemistry was run for one hour, after which the aerosol output along with the hygroscopicity parameter (κ) were saved into a data file that had the capacity to be interpolated to an arbitrary grid used in RAMS. The comparison of this parameterization to observations collected at Mesa Verde National Park (MVNP) during the Inhibition of Snowfall from Pollution Aerosol (ISPA-III) field campaign yielded promising results. The model was able to simulate the variability in near surface aerosol concentration with reasonable accuracy, though with a general low bias. Furthermore, this model compared much better to the observations than did the WRF Chemistry model using a fraction of the computational expense. This emissions scheme was able to show reasonable solutions regarding the aerosol concentrations and can therefore be used to provide an estimate of the seasonal impact of increased CCN on water resources in Western Colorado with relatively low computational expense.

Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture.

PubMed

Ferrández-Pastor, Francisco Javier; García-Chamizo, Juan Manuel; Nieto-Hidalgo, Mario; Mora-Pascual, Jerónimo; Mora-Martínez, José

2016-07-22

The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched.

A Simplified Model for Multiphase Leakage through Faults with Applications for CO2 Storage

NASA Astrophysics Data System (ADS)

Watson, F. E.; Doster, F.

2017-12-01

In the context of geological CO2 storage, faults in the subsurface could affect storage security by acting as high permeability pathways which allow CO2 to flow upwards and away from the storage formation. To assess the likelihood of leakage through faults and the impacts faults might have on storage security numerical models are required. However, faults are complex geological features, usually consisting of a fault core surrounded by a highly fractured damage zone. A direct representation of these in a numerical model would require very fine grid resolution and would be computationally expensive. Here, we present the development of a reduced complexity model for fault flow using the vertically integrated formulation. This model captures the main features of the flow but does not require us to resolve the vertical dimension, nor the fault in the horizontal dimension, explicitly. It is thus less computationally expensive than full resolution models. Consequently, we can quickly model many realisations for parameter uncertainty studies of CO2 injection into faulted reservoirs. We develop the model based on explicitly simulating local 3D representations of faults for characteristic scenarios using the Matlab Reservoir Simulation Toolbox (MRST). We have assessed the impact of variables such as fault geometry, porosity and permeability on multiphase leakage rates.

Deployment Analysis of a Simple Tape-Spring Hinge Using Probabilistic Methods

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Horta, Lucas G.

2012-01-01

Acceptance of new deployable structures architectures and concepts requires validated design methods to minimize the expense involved with technology validation flight testing. Deployable concepts for large lightweight spacecraft include booms, antennae, and masts. This paper explores the implementation of probabilistic methods in the design process for the deployment of a strain-energy mechanism, specifically a simple tape-spring hinge. Strain-energy mechanisms are attractive for deployment in very lightweight systems because they do not require the added mass and complexity associated with motors and controllers. However, designers are hesitant to include free deployment, strain-energy mechanisms because of the potential for uncontrolled behavior. In the example presented here, the tapespring cross-sectional dimensions have been varied and a target displacement during deployment has been selected as the design metric. Specifically, the tape-spring should reach the final position in the shortest time with the minimal amount of overshoot and oscillations. Surrogate models have been used to reduce computational expense. Parameter values to achieve the target response have been computed and used to demonstrate the approach. Based on these results, the application of probabilistic methods for design of a tape-spring hinge has shown promise as a means of designing strain-energy components for more complex space concepts.

Developing Ubiquitous Sensor Network Platform Using Internet of Things: Application in Precision Agriculture

PubMed Central

Ferrández-Pastor, Francisco Javier; García-Chamizo, Juan Manuel; Nieto-Hidalgo, Mario; Mora-Pascual, Jerónimo; Mora-Martínez, José

2016-01-01

The application of Information Technologies into Precision Agriculture methods has clear benefits. Precision Agriculture optimises production efficiency, increases quality, minimises environmental impact and reduces the use of resources (energy, water); however, there are different barriers that have delayed its wide development. Some of these main barriers are expensive equipment, the difficulty to operate and maintain and the standard for sensor networks are still under development. Nowadays, new technological development in embedded devices (hardware and communication protocols), the evolution of Internet technologies (Internet of Things) and ubiquitous computing (Ubiquitous Sensor Networks) allow developing less expensive systems, easier to control, install and maintain, using standard protocols with low-power consumption. This work develops and test a low-cost sensor/actuator network platform, based in Internet of Things, integrating machine-to-machine and human-machine-interface protocols. Edge computing uses this multi-protocol approach to develop control processes on Precision Agriculture scenarios. A greenhouse with hydroponic crop production was developed and tested using Ubiquitous Sensor Network monitoring and edge control on Internet of Things paradigm. The experimental results showed that the Internet technologies and Smart Object Communication Patterns can be combined to encourage development of Precision Agriculture. They demonstrated added benefits (cost, energy, smart developing, acceptance by agricultural specialists) when a project is launched. PMID:27455265

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

NASA Astrophysics Data System (ADS)

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-05-01

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kai; Fu, Shubin; Chung, Eric T.

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructsmore » high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.« less

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

DOE PAGES

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-02-04

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructsmore » high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.« less

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; Zhang, Guannan; Ye, Ming; Wu, Jianfeng; Wu, Jichun

2017-12-01

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we develop a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.

Crashworthiness: Planes, trains, and automobiles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Logan, R.W.; Tokarz, F.J.; Whirley, R.G.

A powerful DYNA3D computer code simulates the dynamic effects of stress traveling through structures. It is the most advanced modeling tool available to study crashworthiness problems and to analyze impacts. Now used by some 1000 companies, government research laboratories, and universities in the U.S. and abroad, DYNA3D is also a preeminent example of successful technology transfer. The initial interest in such a code was to simulate the structural response of weapons systems. The need was to model not the explosive or nuclear events themselves but rather the impacts of weapons systems with the ground, tracking the stress waves as theymore » move through the object. This type of computer simulation augmented or, in certain cases, reduced the need for expensive and time-consuming crash testing.« less

Multifidelity Analysis and Optimization for Supersonic Design

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Willcox, Karen; March, Andrew; Haas, Alex; Rajnarayan, Dev; Kays, Cory

2010-01-01

Supersonic aircraft design is a computationally expensive optimization problem and multifidelity approaches over a significant opportunity to reduce design time and computational cost. This report presents tools developed to improve supersonic aircraft design capabilities including: aerodynamic tools for supersonic aircraft configurations; a systematic way to manage model uncertainty; and multifidelity model management concepts that incorporate uncertainty. The aerodynamic analysis tools developed are appropriate for use in a multifidelity optimization framework, and include four analysis routines to estimate the lift and drag of a supersonic airfoil, a multifidelity supersonic drag code that estimates the drag of aircraft configurations with three different methods: an area rule method, a panel method, and an Euler solver. In addition, five multifidelity optimization methods are developed, which include local and global methods as well as gradient-based and gradient-free techniques.

Reduced order models for assessing CO 2 impacts in shallow unconfined aquifers

DOE PAGES

Keating, Elizabeth H.; Harp, Dylan H.; Dai, Zhenxue; ...

2016-01-28

Risk assessment studies of potential CO 2 sequestration projects consider many factors, including the possibility of brine and/or CO 2 leakage from the storage reservoir. Detailed multiphase reactive transport simulations have been developed to predict the impact of such leaks on shallow groundwater quality; however, these simulations are computationally expensive and thus difficult to directly embed in a probabilistic risk assessment analysis. Here we present a process for developing computationally fast reduced-order models which emulate key features of the more detailed reactive transport simulations. A large ensemble of simulations that take into account uncertainty in aquifer characteristics and CO 2/brinemore » leakage scenarios were performed. Twelve simulation outputs of interest were used to develop response surfaces (RSs) using a MARS (multivariate adaptive regression splines) algorithm (Milborrow, 2015). A key part of this study is to compare different measures of ROM accuracy. We then show that for some computed outputs, MARS performs very well in matching the simulation data. The capability of the RS to predict simulation outputs for parameter combinations not used in RS development was tested using cross-validation. Again, for some outputs, these results were quite good. For other outputs, however, the method performs relatively poorly. Performance was best for predicting the volume of depressed-pH-plumes, and was relatively poor for predicting organic and trace metal plume volumes. We believe several factors, including the non-linearity of the problem, complexity of the geochemistry, and granularity in the simulation results, contribute to this varied performance. The reduced order models were developed principally to be used in probabilistic performance analysis where a large range of scenarios are considered and ensemble performance is calculated. We demonstrate that they effectively predict the ensemble behavior. But, the performance of the RSs is much less accurate when used to predict time-varying outputs from a single simulation. If an analysis requires only a small number of scenarios to be investigated, computationally expensive physics-based simulations would likely provide more reliable results. Finally, if the aggregate behavior of a large number of realizations is the focus, as will be the case in probabilistic quantitative risk assessment, the methodology presented here is relatively robust.« less

Development of Comprehensive Reduced Kinetic Models for Supersonic Reacting Shear Layer Simulations

NASA Technical Reports Server (NTRS)

Zambon, A. C.; Chelliah, H. K.; Drummond, J. P.

2006-01-01

Large-scale simulations of multi-dimensional unsteady turbulent reacting flows with detailed chemistry and transport can be computationally extremely intensive even on distributed computing architectures. With the development of suitable reduced chemical kinetic models, the number of scalar variables to be integrated can be decreased, leading to a significant reduction in the computational time required for the simulation with limited loss of accuracy in the results. A general MATLAB-based automated mechanism reduction procedure is presented to reduce any complex starting mechanism (detailed or skeletal) with minimal human intervention. Based on the application of the quasi steady-state (QSS) approximation for certain chemical species and on the elimination of the fast reaction rates in the mechanism, several comprehensive reduced models, capable of handling different fuels such as C2H4, CH4 and H2, have been developed and thoroughly tested for several combustion problems (ignition, propagation and extinction) and physical conditions (reactant compositions, temperatures, and pressures). A key feature of the present reduction procedure is the explicit solution of the concentrations of the QSS species, needed for the evaluation of the elementary reaction rates. In contrast, previous approaches relied on an implicit solution due to the strong coupling between QSS species, requiring computationally expensive inner iterations. A novel algorithm, based on the definition of a QSS species coupling matrix, is presented to (i) introduce appropriate truncations to the QSS algebraic relations and (ii) identify the optimal sequence for the explicit solution of the concentration of the QSS species. With the automatic generation of the relevant source code, the resulting reduced models can be readily implemented into numerical codes.

Computationally Efficient Multiconfigurational Reactive Molecular Dynamics

PubMed Central

Yamashita, Takefumi; Peng, Yuxing; Knight, Chris; Voth, Gregory A.

2012-01-01

It is a computationally demanding task to explicitly simulate the electronic degrees of freedom in a system to observe the chemical transformations of interest, while at the same time sampling the time and length scales required to converge statistical properties and thus reduce artifacts due to initial conditions, finite-size effects, and limited sampling. One solution that significantly reduces the computational expense consists of molecular models in which effective interactions between particles govern the dynamics of the system. If the interaction potentials in these models are developed to reproduce calculated properties from electronic structure calculations and/or ab initio molecular dynamics simulations, then one can calculate accurate properties at a fraction of the computational cost. Multiconfigurational algorithms model the system as a linear combination of several chemical bonding topologies to simulate chemical reactions, also sometimes referred to as “multistate”. These algorithms typically utilize energy and force calculations already found in popular molecular dynamics software packages, thus facilitating their implementation without significant changes to the structure of the code. However, the evaluation of energies and forces for several bonding topologies per simulation step can lead to poor computational efficiency if redundancy is not efficiently removed, particularly with respect to the calculation of long-ranged Coulombic interactions. This paper presents accurate approximations (effective long-range interaction and resulting hybrid methods) and multiple-program parallelization strategies for the efficient calculation of electrostatic interactions in reactive molecular simulations. PMID:25100924

CRADA Final Report: Weld Predictor App

DOE Office of Scientific and Technical Information (OSTI.GOV)

Billings, Jay Jay

Welding is an important manufacturing process used in a broad range of industries and market sectors, including automotive, aerospace, heavy manufacturing, medical, and defense. During welded fabrication, high localized heat input and subsequent rapid cooling result in the creation of residual stresses and distortion. These residual stresses can significantly affect the fatigue resistance, cracking behavior, and load-carrying capacity of welded structures during service. Further, additional fitting and tacking time is often required to fit distorted subassemblies together, resulting in non-value added cost. Using trial-and-error methods to determine which welding parameters, welding sequences, and fixture designs will most effectively reduce distortionmore » is a time-consuming and expensive process. For complex structures with many welds, this approach can take several months. For this reason, efficient and accurate methods of mitigating distortion are in-demand across all industries where welding is used. Analytical and computational methods and commercial software tools have been developed to predict welding-induced residual stresses and distortion. Welding process parameters, fixtures, and tooling can be optimized to reduce the HAZ softening and minimize weld residual stress and distortion, improving performance and reducing design, fabrication and testing costs. However, weld modeling technology tools are currently accessible only to engineers and designers with a background in finite element analysis (FEA) who work with large manufacturers, research institutes, and universities with access to high-performance computing (HPC) resources. Small and medium enterprises (SMEs) in the US do not typically have the human and computational resources needed to adopt and utilize weld modeling technology. To allow an engineer with no background in FEA and SMEs to gain access to this important design tool, EWI and the Ohio Supercomputer Center (OSC) developed the online weld application software tool “WeldPredictor” ( https://eweldpredictor.ewi.org ). About 1400 users have tested this application. This project marked the beginning of development on the next version of WeldPredictor that addresses many outstanding features of the original, including 3D models, allow more material hardening laws, model material phase transformation, and uses open source finite element solvers to quickly solve problems (as opposed to expensive commercial tools).« less

Accelerating epistasis analysis in human genetics with consumer graphics hardware.

PubMed

Sinnott-Armstrong, Nicholas A; Greene, Casey S; Cancare, Fabio; Moore, Jason H

2009-07-24

Human geneticists are now capable of measuring more than one million DNA sequence variations from across the human genome. The new challenge is to develop computationally feasible methods capable of analyzing these data for associations with common human disease, particularly in the context of epistasis. Epistasis describes the situation where multiple genes interact in a complex non-linear manner to determine an individual's disease risk and is thought to be ubiquitous for common diseases. Multifactor Dimensionality Reduction (MDR) is an algorithm capable of detecting epistasis. An exhaustive analysis with MDR is often computationally expensive, particularly for high order interactions. This challenge has previously been met with parallel computation and expensive hardware. The option we examine here exploits commodity hardware designed for computer graphics. In modern computers Graphics Processing Units (GPUs) have more memory bandwidth and computational capability than Central Processing Units (CPUs) and are well suited to this problem. Advances in the video game industry have led to an economy of scale creating a situation where these powerful components are readily available at very low cost. Here we implement and evaluate the performance of the MDR algorithm on GPUs. Of primary interest are the time required for an epistasis analysis and the price to performance ratio of available solutions. We found that using MDR on GPUs consistently increased performance per machine over both a feature rich Java software package and a C++ cluster implementation. The performance of a GPU workstation running a GPU implementation reduces computation time by a factor of 160 compared to an 8-core workstation running the Java implementation on CPUs. This GPU workstation performs similarly to 150 cores running an optimized C++ implementation on a Beowulf cluster. Furthermore this GPU system provides extremely cost effective performance while leaving the CPU available for other tasks. The GPU workstation containing three GPUs costs $2000 while obtaining similar performance on a Beowulf cluster requires 150 CPU cores which, including the added infrastructure and support cost of the cluster system, cost approximately $82,500. Graphics hardware based computing provides a cost effective means to perform genetic analysis of epistasis using MDR on large datasets without the infrastructure of a computing cluster.

Two schemes for rapid generation of digital video holograms using PC cluster

NASA Astrophysics Data System (ADS)

Park, Hanhoon; Song, Joongseok; Kim, Changseob; Park, Jong-Il

2017-12-01

Computer-generated holography (CGH), which is a process of generating digital holograms, is computationally expensive. Recently, several methods/systems of parallelizing the process using graphic processing units (GPUs) have been proposed. Indeed, use of multiple GPUs or a personal computer (PC) cluster (each PC with GPUs) enabled great improvements in the process speed. However, extant literature has less often explored systems involving rapid generation of multiple digital holograms and specialized systems for rapid generation of a digital video hologram. This study proposes a system that uses a PC cluster and is able to more efficiently generate a video hologram. The proposed system is designed to simultaneously generate multiple frames and accelerate the generation by parallelizing the CGH computations across a number of frames, as opposed to separately generating each individual frame while parallelizing the CGH computations within each frame. The proposed system also enables the subprocesses for generating each frame to execute in parallel through multithreading. With these two schemes, the proposed system significantly reduced the data communication time for generating a digital hologram when compared with that of the state-of-the-art system.

Computational methods in drug discovery

PubMed Central

Leelananda, Sumudu P

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341

Computational methods in drug discovery.

PubMed

Leelananda, Sumudu P; Lindert, Steffen

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

Efficient and accurate Greedy Search Methods for mining functional modules in protein interaction networks.

PubMed

He, Jieyue; Li, Chaojun; Ye, Baoliu; Zhong, Wei

2012-06-25

Most computational algorithms mainly focus on detecting highly connected subgraphs in PPI networks as protein complexes but ignore their inherent organization. Furthermore, many of these algorithms are computationally expensive. However, recent analysis indicates that experimentally detected protein complexes generally contain Core/attachment structures. In this paper, a Greedy Search Method based on Core-Attachment structure (GSM-CA) is proposed. The GSM-CA method detects densely connected regions in large protein-protein interaction networks based on the edge weight and two criteria for determining core nodes and attachment nodes. The GSM-CA method improves the prediction accuracy compared to other similar module detection approaches, however it is computationally expensive. Many module detection approaches are based on the traditional hierarchical methods, which is also computationally inefficient because the hierarchical tree structure produced by these approaches cannot provide adequate information to identify whether a network belongs to a module structure or not. In order to speed up the computational process, the Greedy Search Method based on Fast Clustering (GSM-FC) is proposed in this work. The edge weight based GSM-FC method uses a greedy procedure to traverse all edges just once to separate the network into the suitable set of modules. The proposed methods are applied to the protein interaction network of S. cerevisiae. Experimental results indicate that many significant functional modules are detected, most of which match the known complexes. Results also demonstrate that the GSM-FC algorithm is faster and more accurate as compared to other competing algorithms. Based on the new edge weight definition, the proposed algorithm takes advantages of the greedy search procedure to separate the network into the suitable set of modules. Experimental analysis shows that the identified modules are statistically significant. The algorithm can reduce the computational time significantly while keeping high prediction accuracy.

The Effect of Computer Automation on Institutional Review Board (IRB) Office Efficiency

ERIC Educational Resources Information Center

Oder, Karl; Pittman, Stephanie

2015-01-01

Companies purchase computer systems to make their processes more efficient through automation. Some academic medical centers (AMC) have purchased computer systems for their institutional review boards (IRB) to increase efficiency and compliance with regulations. IRB computer systems are expensive to purchase, deploy, and maintain. An AMC should…

A Test of the Validity of Inviscid Wall-Modeled LES

NASA Astrophysics Data System (ADS)

Redman, Andrew; Craft, Kyle; Aikens, Kurt

2015-11-01

Computational expense is one of the main deterrents to more widespread use of large eddy simulations (LES). As such, it is important to reduce computational costs whenever possible. In this vein, it may be reasonable to assume that high Reynolds number flows with turbulent boundary layers are inviscid when using a wall model. This assumption relies on the grid being too coarse to resolve either the viscous length scales in the outer flow or those near walls. We are not aware of other studies that have suggested or examined the validity of this approach. The inviscid wall-modeled LES assumption is tested here for supersonic flow over a flat plate on three different grids. Inviscid and viscous results are compared to those of another wall-modeled LES as well as experimental data - the results appear promising. Furthermore, the inviscid assumption reduces simulation costs by about 25% and 39% for supersonic and subsonic flows, respectively, with the current LES application. Recommendations are presented as are future areas of research. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575. Computational resources on TACC Stampede were provided under XSEDE allocation ENG150001.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

RMP: Reduced-set matching pursuit approach for efficient compressed sensing signal reconstruction.

PubMed

Abdel-Sayed, Michael M; Khattab, Ahmed; Abu-Elyazeed, Mohamed F

2016-11-01

Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted [Formula: see text] minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal [Formula: see text] minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing. Unlike existing approaches which either select too many or too few values per iteration, RMP aims at selecting the most sufficient number of correlation values per iteration, which improves both the reconstruction time and error. Furthermore, RMP prunes the estimated signal, and hence, excludes the incorrectly selected values. The RMP algorithm achieves a higher reconstruction accuracy at a significantly low computational complexity compared to existing greedy recovery algorithms. It is even superior to [Formula: see text] minimization in terms of the normalized time-error product, a new metric introduced to measure the trade-off between the reconstruction time and error. RMP superior performance is illustrated with both noiseless and noisy samples.

Application of reduced order modeling techniques to problems in heat conduction, isoelectric focusing and differential algebraic equations

NASA Astrophysics Data System (ADS)

Mathai, Pramod P.

This thesis focuses on applying and augmenting 'Reduced Order Modeling' (ROM) techniques to large scale problems. ROM refers to the set of mathematical techniques that are used to reduce the computational expense of conventional modeling techniques, like finite element and finite difference methods, while minimizing the loss of accuracy that typically accompanies such a reduction. The first problem that we address pertains to the prediction of the level of heat dissipation in electronic and MEMS devices. With the ever decreasing feature sizes in electronic devices, and the accompanied rise in Joule heating, the electronics industry has, since the 1990s, identified a clear need for computationally cheap heat transfer modeling techniques that can be incorporated along with the electronic design process. We demonstrate how one can create reduced order models for simulating heat conduction in individual components that constitute an idealized electronic device. The reduced order models are created using Krylov Subspace Techniques (KST). We introduce a novel 'plug and play' approach, based on the small gain theorem in control theory, to interconnect these component reduced order models (according to the device architecture) to reliably and cheaply replicate whole device behavior. The final aim is to have this technique available commercially as a computationally cheap and reliable option that enables a designer to optimize for heat dissipation among competing VLSI architectures. Another place where model reduction is crucial to better design is Isoelectric Focusing (IEF) - the second problem in this thesis - which is a popular technique that is used to separate minute amounts of proteins from the other constituents that are present in a typical biological tissue sample. Fundamental questions about how to design IEF experiments still remain because of the high dimensional and highly nonlinear nature of the differential equations that describe the IEF process as well as the uncertainty in the parameters of the differential equations. There is a clear need to design better experiments for IEF without the current overhead of expensive chemicals and labor. We show how with a simpler modeling of the underlying chemistry, we can still achieve the accuracy that has been achieved in existing literature for modeling small ranges of pH (hydrogen ion concentration) in IEF, but with far less computational time. We investigate a further reduction of time by modeling the IEF problem using the Proper Orthogonal Decomposition (POD) technique and show why POD may not be sufficient due to the underlying constraints. The final problem that we address in this thesis addresses a certain class of dynamics with high stiffness - in particular, differential algebraic equations. With the help of simple examples, we show how the traditional POD procedure will fail to model certain high stiffness problems due to a particular behavior of the vector field which we will denote as twist. We further show how a novel augmentation to the traditional POD algorithm can model-reduce problems with twist in a computationally cheap manner without any additional data requirements.

Thermochemical Modeling of Nonequilibrium Oxygen Flows

NASA Astrophysics Data System (ADS)

Neitzel, Kevin Joseph

The development of hypersonic vehicles leans heavily on computational simulation due to the high enthalpy flow conditions that are expensive and technically challenging to replicate experimentally. The accuracy of the nonequilibrium modeling in the computer simulations dictates the design margin that is required for the thermal protection system and flight dynamics. Previous hypersonic vehicles, such as Apollo and the Space Shuttle, were primarily concerned with re-entry TPS design. The strong flow conditions of re-entry, involving Mach numbers of 25, quickly dissociate the oxygen molecules in air. Sustained flight, hypersonic vehicles will be designed to operate in Mach number ranges of 5 to 10. The oxygen molecules will not quickly dissociate and will play an important role in the flow field behavior. The development of nonequilibrium models of oxygen is crucial for limiting modeling uncertainty. Thermochemical nonequilibrium modeling is investigated for oxygen flows. Specifically, the vibrational relaxation and dissociation behavior that dominate the nonequilibrium physics in this flight regime are studied in detail. The widely used two-temperature (2T) approach is compared to the higher fidelity and more computationally expensive state-to-state (STS) approach. This dissertation utilizes a wide range of rate sources, including newly available STS rates, to conduct a comprehensive study of modeling approaches for hypersonic nonequilibrium thermochemical modeling. Additionally, the physical accuracy of the computational methods are assessed by comparing the numerical results with available experimental data. The numerical results and experimental measurements present strong nonequilibrium, and even non-Boltzmann behavior in the vibrational energy mode for the sustained hypersonic flight regime. The STS approach is able to better capture the behavior observed in the experimental data, especially for stronger nonequilibrium conditions. Additionally, a reduced order model (ROM) modification to the 2T model is developed to improve the capability of the 2T approach framework.

A comparison of native GPU computing versus OpenACC for implementing flow-routing algorithms in hydrological applications

NASA Astrophysics Data System (ADS)

Rueda, Antonio J.; Noguera, José M.; Luque, Adrián

2016-02-01

In recent years GPU computing has gained wide acceptance as a simple low-cost solution for speeding up computationally expensive processing in many scientific and engineering applications. However, in most cases accelerating a traditional CPU implementation for a GPU is a non-trivial task that requires a thorough refactorization of the code and specific optimizations that depend on the architecture of the device. OpenACC is a promising technology that aims at reducing the effort required to accelerate C/C++/Fortran code on an attached multicore device. Virtually with this technology the CPU code only has to be augmented with a few compiler directives to identify the areas to be accelerated and the way in which data has to be moved between the CPU and GPU. Its potential benefits are multiple: better code readability, less development time, lower risk of errors and less dependency on the underlying architecture and future evolution of the GPU technology. Our aim with this work is to evaluate the pros and cons of using OpenACC against native GPU implementations in computationally expensive hydrological applications, using the classic D8 algorithm of O'Callaghan and Mark for river network extraction as case-study. We implemented the flow accumulation step of this algorithm in CPU, using OpenACC and two different CUDA versions, comparing the length and complexity of the code and its performance with different datasets. We advance that although OpenACC can not match the performance of a CUDA optimized implementation (×3.5 slower in average), it provides a significant performance improvement against a CPU implementation (×2-6) with by far a simpler code and less implementation effort.

Expecting the Unexpected: Radiation Hardened Software

NASA Technical Reports Server (NTRS)

Penix, John; Mehlitz, Peter C.

2005-01-01

Radiation induced Single Event Effects (SEEs) are a serious problem for spacecraft flight software, potentially leading to a complete loss of mission. Conventional risk mitigation has been focused on hardware, leading to slow, expensive and outdated on-board computing devices, increased power consumption and launch mass. Our approach is to look at SEEs from a software perspective, and to explicitly design flight software so that it can detect and correct the majority of SEES. Radiation hardened flight software will reduce the significant residual residual risk for critical missions and flight phases, and enable more use of inexpensive and fast COTS hardware.

Symplectic modeling of beam loading in electromagnetic cavities

DOE PAGES

Abell, Dan T.; Cook, Nathan M.; Webb, Stephen D.

2017-05-22

Simulating beam loading in radio frequency accelerating structures is critical for understanding higher-order mode effects on beam dynamics, such as beam break-up instability in energy recovery linacs. Full wave simulations of beam loading in radio frequency structures are computationally expensive, and while reduced models can ignore essential physics, it can be difficult to generalize. Here, we present a self-consistent algorithm derived from the least-action principle which can model an arbitrary number of cavity eigenmodes and with a generic beam distribution. It has been implemented in our new Open Library for Investigating Vacuum Electronics (OLIVE).

Efficient 3D movement-based kernel density estimator and application to wildlife ecology

USGS Publications Warehouse

Tracey-PR, Jeff; Sheppard, James K.; Lockwood, Glenn K.; Chourasia, Amit; Tatineni, Mahidhar; Fisher, Robert N.; Sinkovits, Robert S.

2014-01-01

We describe an efficient implementation of a 3D movement-based kernel density estimator for determining animal space use from discrete GPS measurements. This new method provides more accurate results, particularly for species that make large excursions in the vertical dimension. The downside of this approach is that it is much more computationally expensive than simpler, lower-dimensional models. Through a combination of code restructuring, parallelization and performance optimization, we were able to reduce the time to solution by up to a factor of 1000x, thereby greatly improving the applicability of the method.

An analysis of computerization in primary care practices.

PubMed

Condon, James V; Smith, Sherry P

2002-12-01

To remain profitable, primary care practices, the front-line health care providers, must provide excellent patient care and reduce expenses while providing payers with accurate data. Many primary care practices have turned to computer technology to achieve these goals. This study examined the degree of computerization of primary care providers in the Augusta, Georgia, metropolitan area as well as the level of awareness of the Health Insurance Portability and Accountability Act (HIPAA) by primary care providers and its potential effect on their future computerization plans. The study's findings are presented and discussed as well as a number of recommendations for practice managers.

Simulation of TunneLadder traveling-wave tube cold-test characteristics: Implementation of the three-dimensional, electromagnetic circuit analysis code micro-SOS

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Wilson, Jeffrey D.

1993-01-01

The three-dimensional, electromagnetic circuit analysis code, Micro-SOS, can be used to reduce expensive time-consuming experimental 'cold-testing' of traveling-wave tube (TWT) circuits. The frequency-phase dispersion characteristics and beam interaction impedance of a TunneLadder traveling-wave tube slow-wave structure were simulated using the code. When reasonable dimensional adjustments are made, computer results agree closely with experimental data. Modifications to the circuit geometry that would make the TunneLadder TWT easier to fabricate for higher frequency operation are explored.

78 FR 50374 - Proposed Information Collection; Comment Request; Information and Communication Technology Survey

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-19

... expenses (purchases; and operating leases and rental payments) for four types of information and communication technology equipment and software (computers and peripheral equipment; ICT equipment, excluding computers and peripherals; electromedical and electrotherapeutic apparatus; and computer software, including...

Can Early Rehabilitation after Total Hip Arthroplasty Reduce Its Major Complications and Medical Expenses? Report from a Nationally Representative Cohort.

PubMed

Chiung-Jui Su, Daniel; Yuan, Kuo-Shu; Weng, Shih-Feng; Hong, Rong-Bin; Wu, Ming-Ping; Wu, Hing-Man; Chou, Willy

2015-01-01

To investigate whether early rehabilitation reduces the occurrence of posttotal hip arthroplasty (THA) complications, adverse events, and medical expenses within one postoperative year. We retrospectively retrieve data from Taiwan's National Health Insurance Research Database. Patients who had undergone THA during the period from 1998 to 2010 were recruited, matched for propensity scores, and divided into 2 groups: early rehabilitation (Early Rehab) and delayed rehabilitation (Delayed Rehab). Eight hundred twenty of 999 THA patients given early rehabilitation treatments were matched to 205 of 233 THA patients given delayed rehabilitation treatments. The Delayed Rehab group had significantly (all p < 0.001) higher medical and rehabilitation expenses and more outpatient department (OPD) visits than the Early Rehab group. In addition, the Delayed Rehab group was associated with more prosthetic infection (odds ratio (OR): 3.152; 95% confidence interval (CI): 1.211-8.203; p < 0.05) than the Early Rehab group. Early rehabilitation can significantly reduce the incidence of prosthetic infection, total rehabilitation expense, total medical expenses, and number of OPD visits within the first year after THA.

26 CFR 1.280C-3 - Disallowance of certain deductions for qualified clinical testing expenses when section 28 credit...

Code of Federal Regulations, 2010 CFR

2010-04-01

... clinical testing expenses when section 28 credit is allowable. 1.280C-3 Section 1.280C-3 Internal Revenue... Not Deductible § 1.280C-3 Disallowance of certain deductions for qualified clinical testing expenses... section 28 for qualified clinical testing expenses (as defined in section 28(b)), it must reduce the...

Discretization of the induced-charge boundary integral equation.

PubMed

Bardhan, Jaydeep P; Eisenberg, Robert S; Gillespie, Dirk

2009-07-01

Boundary-element methods (BEMs) for solving integral equations numerically have been used in many fields to compute the induced charges at dielectric boundaries. In this paper, we consider a more accurate implementation of BEM in the context of ions in aqueous solution near proteins, but our results are applicable more generally. The ions that modulate protein function are often within a few angstroms of the protein, which leads to the significant accumulation of polarization charge at the protein-solvent interface. Computing the induced charge accurately and quickly poses a numerical challenge in solving a popular integral equation using BEM. In particular, the accuracy of simulations can depend strongly on seemingly minor details of how the entries of the BEM matrix are calculated. We demonstrate that when the dielectric interface is discretized into flat tiles, the qualocation method of Tausch [IEEE Trans Comput.-Comput.-Aided Des. 20, 1398 (2001)] to compute the BEM matrix elements is always more accurate than the traditional centroid-collocation method. Qualocation is not more expensive to implement than collocation and can save significant computational time by reducing the number of boundary elements needed to discretize the dielectric interfaces.

Discretization of the induced-charge boundary integral equation

NASA Astrophysics Data System (ADS)

Bardhan, Jaydeep P.; Eisenberg, Robert S.; Gillespie, Dirk

2009-07-01

Boundary-element methods (BEMs) for solving integral equations numerically have been used in many fields to compute the induced charges at dielectric boundaries. In this paper, we consider a more accurate implementation of BEM in the context of ions in aqueous solution near proteins, but our results are applicable more generally. The ions that modulate protein function are often within a few angstroms of the protein, which leads to the significant accumulation of polarization charge at the protein-solvent interface. Computing the induced charge accurately and quickly poses a numerical challenge in solving a popular integral equation using BEM. In particular, the accuracy of simulations can depend strongly on seemingly minor details of how the entries of the BEM matrix are calculated. We demonstrate that when the dielectric interface is discretized into flat tiles, the qualocation method of Tausch [IEEE Trans Comput.-Comput.-Aided Des. 20, 1398 (2001)] to compute the BEM matrix elements is always more accurate than the traditional centroid-collocation method. Qualocation is not more expensive to implement than collocation and can save significant computational time by reducing the number of boundary elements needed to discretize the dielectric interfaces.

Stream-based Hebbian eigenfilter for real-time neuronal spike discrimination

PubMed Central

2012-01-01

Background Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems. Method In this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computing Results and discussion Results demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants. PMID:22490725

Low-Cost Terminal Alternative for Learning Center Managers. Final Report.

ERIC Educational Resources Information Center

Nix, C. Jerome; And Others

This study established the feasibility of replacing high performance and relatively expensive computer terminals with less expensive ones adequate for supporting specific tasks of Advanced Instructional System (AIS) at Lowry AFB, Colorado. Surveys of user requirements and available devices were conducted and the results used in a system analysis.…

Multiple Scattering Principal Component-based Radiative Transfer Model (PCRTM) from Far IR to UV-Vis

NASA Astrophysics Data System (ADS)

Liu, X.; Wu, W.; Yang, Q.

2017-12-01

Modern satellite hyperspectral satellite remote sensors such as AIRS, CrIS, IASI, CLARREO all require accurate and fast radiative transfer models that can deal with multiple scattering of clouds and aerosols to explore the information contents. However, performing full radiative transfer calculations using multiple stream methods such as discrete ordinate (DISORT), doubling and adding (AD), successive order of scattering order of scattering (SOS) are very time consuming. We have developed a principal component-based radiative transfer model (PCRTM) to reduce the computational burden by orders of magnitudes while maintain high accuracy. By exploring spectral correlations, the PCRTM reduce the number of radiative transfer calculations in frequency domain. It further uses a hybrid stream method to decrease the number of calls to the computational expensive multiple scattering calculations with high stream numbers. Other fast parameterizations have been used in the infrared spectral region reduce the computational time to milliseconds for an AIRS forward simulation (2378 spectral channels). The PCRTM has been development to cover spectral range from far IR to UV-Vis. The PCRTM model have been be used for satellite data inversions, proxy data generation, inter-satellite calibrations, spectral fingerprinting, and climate OSSE. We will show examples of applying the PCRTM to single field of view cloudy retrievals of atmospheric temperature, moisture, traces gases, clouds, and surface parameters. We will also show how the PCRTM are used for the NASA CLARREO project.

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oxberry, Geoffrey M.; Kostova-Vassilevska, Tanya; Arrighi, Bill

2015-04-02

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory boundingmore » the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.« less

MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT

PubMed Central

Zhang, Guo-Qiang; Zhu, Wei; Sun, Mengmeng; Tao, Shiqiang; Bodenreider, Olivier; Cui, Licong

2015-01-01

Non-lattice fragments are often indicative of structural anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. However, extracting the non-lattice fragments in large ontological systems is computationally expensive if not prohibitive, using a traditional sequential approach. In this paper we present a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), for extracting non-lattice fragments in large partially ordered sets and demonstrate its applicability in ontology quality assurance. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014 (each containing over 300k concepts), with an average total computing time of less than 3 hours per version. With dramatically reduced time, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies, but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). This demonstrates that fragments around non-lattice pairs exhibit significantly higher rates of change in the process of ontological evolution. PMID:25705725

MaPLE: A MapReduce Pipeline for Lattice-based Evaluation and Its Application to SNOMED CT.

PubMed

Zhang, Guo-Qiang; Zhu, Wei; Sun, Mengmeng; Tao, Shiqiang; Bodenreider, Olivier; Cui, Licong

2014-10-01

Non-lattice fragments are often indicative of structural anomalies in ontological systems and, as such, represent possible areas of focus for subsequent quality assurance work. However, extracting the non-lattice fragments in large ontological systems is computationally expensive if not prohibitive, using a traditional sequential approach. In this paper we present a general MapReduce pipeline, called MaPLE (MapReduce Pipeline for Lattice-based Evaluation), for extracting non-lattice fragments in large partially ordered sets and demonstrate its applicability in ontology quality assurance. Using MaPLE in a 30-node Hadoop local cloud, we systematically extracted non-lattice fragments in 8 SNOMED CT versions from 2009 to 2014 (each containing over 300k concepts), with an average total computing time of less than 3 hours per version. With dramatically reduced time, MaPLE makes it feasible not only to perform exhaustive structural analysis of large ontological hierarchies, but also to systematically track structural changes between versions. Our change analysis showed that the average change rates on the non-lattice pairs are up to 38.6 times higher than the change rates of the background structure (concept nodes). This demonstrates that fragments around non-lattice pairs exhibit significantly higher rates of change in the process of ontological evolution.

Multispectral x-ray CT: multivariate statistical analysis for efficient reconstruction

NASA Astrophysics Data System (ADS)

Kheirabadi, Mina; Mustafa, Wail; Lyksborg, Mark; Lund Olsen, Ulrik; Bjorholm Dahl, Anders

2017-10-01

Recent developments in multispectral X-ray detectors allow for an efficient identification of materials based on their chemical composition. This has a range of applications including security inspection, which is our motivation. In this paper, we analyze data from a tomographic setup employing the MultiX detector, that records projection data in 128 energy bins covering the range from 20 to 160 keV. Obtaining all information from this data requires reconstructing 128 tomograms, which is computationally expensive. Instead, we propose to reduce the dimensionality of projection data prior to reconstruction and reconstruct from the reduced data. We analyze three linear methods for dimensionality reduction using a dataset with 37 equally-spaced projection angles. Four bottles with different materials are recorded for which we are able to obtain similar discrimination of their content using a very reduced subset of tomograms compared to the 128 tomograms that would otherwise be needed without dimensionality reduction.

The Influence of Inlet Asymmetry on Steam Turbine Exhaust Hood Flows.

PubMed

Burton, Zoe; Hogg, Simon; Ingram, Grant L

2014-04-01

It has been widely recognized for some decades that it is essential to accurately represent the strong coupling between the last stage blades (LSB) and the diffuser inlet, in order to correctly capture the flow through the exhaust hoods of steam turbine low pressure cylinders. This applies to any form of simulation of the flow, i.e., numerical or experimental. The exhaust hood flow structure is highly three-dimensional and appropriate coupling will enable the important influence of this asymmetry to be transferred to the rotor. This, however, presents challenges as the calculation size grows rapidly when the full annulus is calculated. The size of the simulation means researchers are constantly searching for methods to reduce the computational effort without compromising solution accuracy. However, this can result in excessive computational demands in numerical simulations. Unsteady full-annulus CFD calculation will remain infeasible for routine design calculations for the foreseeable future. More computationally efficient methods for coupling the unsteady rotor flow to the hood flow are required that bring computational expense within realizable limits while still maintaining sufficient accuracy for meaningful design calculations. Research activity in this area is focused on developing new methods and techniques to improve accuracy and reduce computational expense. A novel approach for coupling the turbine last stage to the exhaust hood employing the nonlinear harmonic (NLH) method is presented in this paper. The generic, IP free, exhaust hood and last stage blade geometries from Burton et al. (2012. "A Generic Low Pressure Exhaust Diffuser for Steam Turbine Research,"Proceedings of the ASME Turbo Expo, Copenhagen, Denmark, Paper No. GT2012-68485) that are representative of modern designs, are used to demonstrate the effectiveness of the method. This is achieved by comparing results obtained with the NLH to those obtained with a more conventional mixing-plane approach. The results show that the circumferential asymmetry can be successfully transferred in both directions between the exhaust hood flow and that through the LSB, by using the NLH. This paper also suggests that for exhaust hoods of generous axial length, little change in C p is observed when the circumferential asymmetry is captured. However, the predicted flow structure is significantly different, which will influence the design and placement of the exhaust hood internal "furniture."

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Web-Based Job Submission Interface for the GAMESS Computational Chemistry Program

ERIC Educational Resources Information Center

Perri, M. J.; Weber, S. H.

2014-01-01

A Web site is described that facilitates use of the free computational chemistry software: General Atomic and Molecular Electronic Structure System (GAMESS). Its goal is to provide an opportunity for undergraduate students to perform computational chemistry experiments without the need to purchase expensive software.

A Simplified Biosphere Model for Global Climate Studies.

NASA Astrophysics Data System (ADS)

Xue, Y.; Sellers, P. J.; Kinter, J. L.; Shukla, J.

1991-03-01

The Simple Biosphere Model (SiB) as described in Sellers et al. is a bio-physically based model of land surface-atmosphere interaction. For some general circulation model (GCM) climate studies, further simplifications are desirable to have greater computation efficiency, and more important, to consolidate the parametric representation. Three major reductions in the complexity of SiB have been achieved in the present study.The diurnal variation of surface albedo is computed in SiB by means of a comprehensive yet complex calculation. Since the diurnal cycle is quite regular for each vegetation type, this calculation can be simplified considerably. The effect of root zone soil moisture on stomatal resistance is substantial, but the computation in SiB is complicated and expensive. We have developed approximations, which simulate the effects of reduced soil moisture more simply, keeping the essence of the biophysical concepts used in SiB.The surface stress and the fluxes of heat and moisture between the top of the vegetation canopy and an atmospheric reference level have been parameterized in an off-line version of SiB based upon the studies by Businger et al. and Paulson. We have developed a linear relationship between Richardson number and aero-dynamic resistance. Finally, the second vegetation layer of the original model does not appear explicitly after simplification. Compared to the model of Sellers et al., we have reduced the number of input parameters from 44 to 21. A comparison of results using the reduced parameter biosphere with those from the original formulation in a GCM and a zero-dimensional model shows the simplified version to reproduce the original results quite closely. After simplification, the computational requirement of SiB was reduced by about 55%.

Computing Systems | High-Performance Computing | NREL

Science.gov Websites

investigate, build, and test models of complex phenomena or entire integrated systems-that cannot be directly observed or manipulated in the lab, or would be too expensive or time consuming. Models and visualizations

Application of multi-grid method on the simulation of incremental forging processes

NASA Astrophysics Data System (ADS)

Ramadan, Mohamad; Khaled, Mahmoud; Fourment, Lionel

2016-10-01

Numerical simulation becomes essential in manufacturing large part by incremental forging processes. It is a splendid tool allowing to show physical phenomena however behind the scenes, an expensive bill should be paid, that is the computational time. That is why many techniques are developed to decrease the computational time of numerical simulation. Multi-Grid method is a numerical procedure that permits to reduce computational time of numerical calculation by performing the resolution of the system of equations on several mesh of decreasing size which allows to smooth faster the low frequency of the solution as well as its high frequency. In this paper a Multi-Grid method is applied to cogging process in the software Forge 3. The study is carried out using increasing number of degrees of freedom. The results shows that calculation time is divide by two for a mesh of 39,000 nodes. The method is promising especially if coupled with Multi-Mesh method.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

Increasing the sampling efficiency of protein conformational transition using velocity-scaling optimized hybrid explicit/implicit solvent REMD simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Yuqi; Wang, Jinan; Shao, Qiang, E-mail: qshao@mail.shcnc.ac.cn, E-mail: Jiye.Shi@ucb.com, E-mail: wlzhu@mail.shcnc.ac.cn

2015-03-28

The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much lessmore » computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.« less

Dish layouts analysis method for concentrative solar power plant.

PubMed

Xu, Jinshan; Gan, Shaocong; Li, Song; Ruan, Zhongyuan; Chen, Shengyong; Wang, Yong; Gui, Changgui; Wan, Bin

2016-01-01

Designs leading to maximize the use of sun radiation of a given reflective area without increasing the expense on investment are important to solar power plants construction. We here provide a method that allows one to compute shade area at any given time as well as the total shading effect of a day. By establishing a local coordinate system with the origin at the apex of a parabolic dish and z -axis pointing to the sun, neighboring dishes only with [Formula: see text] would shade onto the dish when in tracking mode. This procedure reduces the required computational resources, simplifies the calculation and allows a quick search for the optimum layout by considering all aspects leading to optimized arrangement: aspect ratio, shifting and rotation. Computer simulations done with information on dish Stirling system as well as DNI data released from NREL, show that regular-spacing is not an optimal layout, shifting and rotating column by certain amount can bring more benefits.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

Development of soft-sphere contact models for thermal heat conduction in granular flows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, A. B.; Pannala, S.; Ma, Z.

2016-06-08

Conductive heat transfer to flowing particles occurs when two particles (or a particle and wall) come into contact. The direct conduction between the two bodies depends on the collision dynamics, namely the size of the contact area and the duration of contact. For soft-sphere discrete-particle simulations, it is computationally expensive to resolve the true collision time because doing so would require a restrictively small numerical time step. To improve the computational speed, it is common to increase the 'softness' of the material to artificially increase the collision time, but doing so affects the heat transfer. In this work, two physically-basedmore » correction terms are derived to compensate for the increased contact area and time stemming from artificial particle softening. By including both correction terms, the impact that artificial softening has on the conductive heat transfer is removed, thus enabling simulations at greatly reduced computational times without sacrificing physical accuracy.« less

OpenCluster: A Flexible Distributed Computing Framework for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Wei, Shoulin; Wang, Feng; Deng, Hui; Liu, Cuiyin; Dai, Wei; Liang, Bo; Mei, Ying; Shi, Congming; Liu, Yingbo; Wu, Jingping

2017-02-01

The volume of data generated by modern astronomical telescopes is extremely large and rapidly growing. However, current high-performance data processing architectures/frameworks are not well suited for astronomers because of their limitations and programming difficulties. In this paper, we therefore present OpenCluster, an open-source distributed computing framework to support rapidly developing high-performance processing pipelines of astronomical big data. We first detail the OpenCluster design principles and implementations and present the APIs facilitated by the framework. We then demonstrate a case in which OpenCluster is used to resolve complex data processing problems for developing a pipeline for the Mingantu Ultrawide Spectral Radioheliograph. Finally, we present our OpenCluster performance evaluation. Overall, OpenCluster provides not only high fault tolerance and simple programming interfaces, but also a flexible means of scaling up the number of interacting entities. OpenCluster thereby provides an easily integrated distributed computing framework for quickly developing a high-performance data processing system of astronomical telescopes and for significantly reducing software development expenses.

The changing nature of spacecraft operations: From the Vikings of the 1970's to the great observatories of the 1990's and beyond

NASA Technical Reports Server (NTRS)

Ledbetter, Kenneth W.

1992-01-01

Four trends in spacecraft flight operations are discussed which will reduce overall program costs. These trends are the use of high-speed, highly reliable data communications systems for distributing operations functions to more convenient and cost-effective sites; the improved capability for remote operation of sensors; a continued rapid increase in memory and processing speed of flight qualified computer chips; and increasingly capable ground-based hardware and software systems, notably those augmented by artificial intelligence functions. Changes reflected by these trends are reviewed starting from the NASA Viking missions of the early 70s, when mission control was conducted at one location using expensive and cumbersome mainframe computers and communications equipment. In the 1980s, powerful desktop computers and modems enabled the Magellan project team to operate the spacecraft remotely. In the 1990s, the Hubble Space Telescope project uses multiple color screens and automated sequencing software on small computers. Given a projection of current capabilities, future control centers will be even more cost-effective.

Practical Use of Computationally Frugal Model Analysis Methods

DOE PAGES

Hill, Mary C.; Kavetski, Dmitri; Clark, Martyn; ...

2015-03-21

Computationally frugal methods of model analysis can provide substantial benefits when developing models of groundwater and other environmental systems. Model analysis includes ways to evaluate model adequacy and to perform sensitivity and uncertainty analysis. Frugal methods typically require 10s of parallelizable model runs; their convenience allows for other uses of the computational effort. We suggest that model analysis be posed as a set of questions used to organize methods that range from frugal to expensive (requiring 10,000 model runs or more). This encourages focus on method utility, even when methods have starkly different theoretical backgrounds. We note that many frugalmore » methods are more useful when unrealistic process-model nonlinearities are reduced. Inexpensive diagnostics are identified for determining when frugal methods are advantageous. Examples from the literature are used to demonstrate local methods and the diagnostics. We suggest that the greater use of computationally frugal model analysis methods would allow questions such as those posed in this work to be addressed more routinely, allowing the environmental sciences community to obtain greater scientific insight from the many ongoing and future modeling efforts« less

41 CFR 301-10.301 - How do I compute my mileage reimbursement?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 41 Public Contracts and Property Management 4 2010-07-01 2010-07-01 false How do I compute my...-TRANSPORTATION EXPENSES Privately Owned Vehicle (POV) § 301-10.301 How do I compute my mileage reimbursement? You compute mileage reimbursement by multiplying the distance traveled, determined under § 301-10.302 of this...

An Adaptive QSE-reduced Nuclear Reaction Network for Silicon Burning

NASA Astrophysics Data System (ADS)

Parete-Koon, Suzanne; Hix, W.; Thielemann, F.

2008-03-01

The nuclei of the "iron peak" are formed in massive stars shortly before core collapse and during their supernova outbursts as well as during thermonuclear supernovae. Complete and incomplete silicon burning during these events are responsible for the production of a wide range of nuclei with atomic mass numbers from 28 to 64. Because of the large number of nuclei involved, accurate modeling of silicon burning is computationally expensive. However, examination of the physics of silicon burning has revealed that the nuclear evolution is dominated by large groups of nuclei in mutual equilibrium. We present an improvement on our hybrid equilibrium-network scheme which takes advantage of this quasi-equilibrium in order to reduce the number of independent variables calculated. Because the size and membership of these groups vary as the temperature, density and electron faction change, achieving maximal efficiency requires dynamic adjustment of group number and membership. Toward this end, we are implementing a scheme beginning with a single QSE (NSE) group at appropriately high temperature, then progressing through 2, 3 and 4 group stages (with successively more independent variables) as temperature declines. This combination allows accurate prediction of the nuclear abundance evolution, deleptonization and energy generation at a further reduced computational cost when compared to a conventional nuclear reaction network or our previous 3 fixed group QSE-reduced network. During silicon burning, the resultant QSE-reduced network is up to 20 times faster than the full network it replaces without significant loss of accuracy. These reductions in computational cost and the number of species evolved make QSE-reduced networks well suited for inclusion within hydrodynamic simulations, particularly in multi-dimensional applications. This work has been supported by the National Science Foundation, by the Department of Energy's Scientic Discovery through Advanced Computing Programs, and by the Joint Institute for Heavy Ion Research at ORNL.

Is Your School Y2K-OK?

ERIC Educational Resources Information Center

Bates, Martine G.

1999-01-01

The most vulnerable Y2K areas for schools are networked computers, free-standing personal computers, software, and embedded chips in utilities such as telephones and fire alarms. Expensive, time-consuming procedures and software have been developed for testing and bringing most computers into compliance. Districts need a triage prioritization…

Understanding the Internet.

ERIC Educational Resources Information Center

Oblinger, Diana

The Internet is an international network linking hundreds of smaller computer networks in North America, Europe, and Asia. Using the Internet, computer users can connect to a variety of computers with little effort or expense. The potential for use by college faculty is enormous. The largest problem faced by most users is understanding what such…

"Mini", "Midi" and the Student.

ERIC Educational Resources Information Center

Edwards, Perry; Broadwell, Bruce

Mini- and midi-computers have been introduced into the computer science program at Sierra College to afford students more direct contact with computers. The college's administration combined with the Science and Business departments to share the expense and utilization of the program. The National Cash Register Century 100 and the Data General…

48 CFR 970.5227-1 - Rights in data-facilities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... software. (2) Computer software, as used in this clause, means (i) computer programs which are data... software. The term “data” does not include data incidental to the administration of this contract, such as... this clause, means data, other than computer software, developed at private expense that embody trade...

SAChES: Scalable Adaptive Chain-Ensemble Sampling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swiler, Laura Painton; Ray, Jaideep; Ebeida, Mohamed Salah

We present the development of a parallel Markov Chain Monte Carlo (MCMC) method called SAChES, Scalable Adaptive Chain-Ensemble Sampling. This capability is targed to Bayesian calibration of com- putationally expensive simulation models. SAChES involves a hybrid of two methods: Differential Evo- lution Monte Carlo followed by Adaptive Metropolis. Both methods involve parallel chains. Differential evolution allows one to explore high-dimensional parameter spaces using loosely coupled (i.e., largely asynchronous) chains. Loose coupling allows the use of large chain ensembles, with far more chains than the number of parameters to explore. This reduces per-chain sampling burden, enables high-dimensional inversions and the usemore » of computationally expensive forward models. The large number of chains can also ameliorate the impact of silent-errors, which may affect only a few chains. The chain ensemble can also be sampled to provide an initial condition when an aberrant chain is re-spawned. Adaptive Metropolis takes the best points from the differential evolution and efficiently hones in on the poste- rior density. The multitude of chains in SAChES is leveraged to (1) enable efficient exploration of the parameter space; and (2) ensure robustness to silent errors which may be unavoidable in extreme-scale computational platforms of the future. This report outlines SAChES, describes four papers that are the result of the project, and discusses some additional results.« less

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE PAGES

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing; ...

2017-12-27

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

A Taylor Expansion-Based Adaptive Design Strategy for Global Surrogate Modeling With Applications in Groundwater Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mo, Shaoxing; Lu, Dan; Shi, Xiaoqing

Global sensitivity analysis (GSA) and uncertainty quantification (UQ) for groundwater modeling are challenging because of the model complexity and significant computational requirements. To reduce the massive computational cost, a cheap-to-evaluate surrogate model is usually constructed to approximate and replace the expensive groundwater models in the GSA and UQ. Constructing an accurate surrogate requires actual model simulations on a number of parameter samples. Thus, a robust experimental design strategy is desired to locate informative samples so as to reduce the computational cost in surrogate construction and consequently to improve the efficiency in the GSA and UQ. In this study, we developmore » a Taylor expansion-based adaptive design (TEAD) that aims to build an accurate global surrogate model with a small training sample size. TEAD defines a novel hybrid score function to search informative samples, and a robust stopping criterion to terminate the sample search that guarantees the resulted approximation errors satisfy the desired accuracy. The good performance of TEAD in building global surrogate models is demonstrated in seven analytical functions with different dimensionality and complexity in comparison to two widely used experimental design methods. The application of the TEAD-based surrogate method in two groundwater models shows that the TEAD design can effectively improve the computational efficiency of GSA and UQ for groundwater modeling.« less

Challenges and opportunities of cloud computing for atmospheric sciences

NASA Astrophysics Data System (ADS)

Pérez Montes, Diego A.; Añel, Juan A.; Pena, Tomás F.; Wallom, David C. H.

2016-04-01

Cloud computing is an emerging technological solution widely used in many fields. Initially developed as a flexible way of managing peak demand it has began to make its way in scientific research. One of the greatest advantages of cloud computing for scientific research is independence of having access to a large cyberinfrastructure to fund or perform a research project. Cloud computing can avoid maintenance expenses for large supercomputers and has the potential to 'democratize' the access to high-performance computing, giving flexibility to funding bodies for allocating budgets for the computational costs associated with a project. Two of the most challenging problems in atmospheric sciences are computational cost and uncertainty in meteorological forecasting and climate projections. Both problems are closely related. Usually uncertainty can be reduced with the availability of computational resources to better reproduce a phenomenon or to perform a larger number of experiments. Here we expose results of the application of cloud computing resources for climate modeling using cloud computing infrastructures of three major vendors and two climate models. We show how the cloud infrastructure compares in performance to traditional supercomputers and how it provides the capability to complete experiments in shorter periods of time. The monetary cost associated is also analyzed. Finally we discuss the future potential of this technology for meteorological and climatological applications, both from the point of view of operational use and research.

Cloud computing for comparative genomics

PubMed Central

2010-01-01

Background Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. Results We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. Conclusions The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems. PMID:20482786

Cloud computing for comparative genomics.

PubMed

Wall, Dennis P; Kudtarkar, Parul; Fusaro, Vincent A; Pivovarov, Rimma; Patil, Prasad; Tonellato, Peter J

2010-05-18

Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastructures are likely to become prohibitive with the increase, especially as the breadth of questions continues to rise. Alternative computing architectures, in particular cloud computing environments, may help alleviate this increasing pressure and enable fast, large-scale, and cost-effective comparative genomics strategies going forward. To test this, we redesigned a typical comparative genomics algorithm, the reciprocal smallest distance algorithm (RSD), to run within Amazon's Elastic Computing Cloud (EC2). We then employed the RSD-cloud for ortholog calculations across a wide selection of fully sequenced genomes. We ran more than 300,000 RSD-cloud processes within the EC2. These jobs were farmed simultaneously to 100 high capacity compute nodes using the Amazon Web Service Elastic Map Reduce and included a wide mix of large and small genomes. The total computation time took just under 70 hours and cost a total of $6,302 USD. The effort to transform existing comparative genomics algorithms from local compute infrastructures is not trivial. However, the speed and flexibility of cloud computing environments provides a substantial boost with manageable cost. The procedure designed to transform the RSD algorithm into a cloud-ready application is readily adaptable to similar comparative genomics problems.

Variable fidelity robust optimization of pulsed laser orbital debris removal under epistemic uncertainty

NASA Astrophysics Data System (ADS)

Hou, Liqiang; Cai, Yuanli; Liu, Jin; Hou, Chongyuan

2016-04-01

A variable fidelity robust optimization method for pulsed laser orbital debris removal (LODR) under uncertainty is proposed. Dempster-shafer theory of evidence (DST), which merges interval-based and probabilistic uncertainty modeling, is used in the robust optimization. The robust optimization method optimizes the performance while at the same time maximizing its belief value. A population based multi-objective optimization (MOO) algorithm based on a steepest descent like strategy with proper orthogonal decomposition (POD) is used to search robust Pareto solutions. Analytical and numerical lifetime predictors are used to evaluate the debris lifetime after the laser pulses. Trust region based fidelity management is designed to reduce the computational cost caused by the expensive model. When the solutions fall into the trust region, the analytical model is used to reduce the computational cost. The proposed robust optimization method is first tested on a set of standard problems and then applied to the removal of Iridium 33 with pulsed lasers. It will be shown that the proposed approach can identify the most robust solutions with minimum lifetime under uncertainty.

P-CSI v1.0, an accelerated barotropic solver for the high-resolution ocean model component in the Community Earth System Model v2.0

NASA Astrophysics Data System (ADS)

Huang, Xiaomeng; Tang, Qiang; Tseng, Yuheng; Hu, Yong; Baker, Allison H.; Bryan, Frank O.; Dennis, John; Fu, Haohuan; Yang, Guangwen

2016-11-01

In the Community Earth System Model (CESM), the ocean model is computationally expensive for high-resolution grids and is often the least scalable component for high-resolution production experiments. The major bottleneck is that the barotropic solver scales poorly at high core counts. We design a new barotropic solver to accelerate the high-resolution ocean simulation. The novel solver adopts a Chebyshev-type iterative method to reduce the global communication cost in conjunction with an effective block preconditioner to further reduce the iterations. The algorithm and its computational complexity are theoretically analyzed and compared with other existing methods. We confirm the significant reduction of the global communication time with a competitive convergence rate using a series of idealized tests. Numerical experiments using the CESM 0.1° global ocean model show that the proposed approach results in a factor of 1.7 speed-up over the original method with no loss of accuracy, achieving 10.5 simulated years per wall-clock day on 16 875 cores.

RenderMan design principles

NASA Technical Reports Server (NTRS)

Apodaca, Tony; Porter, Tom

1989-01-01

The two worlds of interactive graphics and realistic graphics have remained separate. Fast graphics hardware runs simple algorithms and generates simple looking images. Photorealistic image synthesis software runs slowly on large expensive computers. The time has come for these two branches of computer graphics to merge. The speed and expense of graphics hardware is no longer the barrier to the wide acceptance of photorealism. There is every reason to believe that high quality image synthesis will become a standard capability of every graphics machine, from superworkstation to personal computer. The significant barrier has been the lack of a common language, an agreed-upon set of terms and conditions, for 3-D modeling systems to talk to 3-D rendering systems for computing an accurate rendition of that scene. Pixar has introduced RenderMan to serve as that common language. RenderMan, specifically the extensibility it offers in shading calculations, is discussed.

Extending Strong Scaling of Quantum Monte Carlo to the Exascale

NASA Astrophysics Data System (ADS)

Shulenburger, Luke; Baczewski, Andrew; Luo, Ye; Romero, Nichols; Kent, Paul

Quantum Monte Carlo is one of the most accurate and most computationally expensive methods for solving the electronic structure problem. In spite of its significant computational expense, its massively parallel nature is ideally suited to petascale computers which have enabled a wide range of applications to relatively large molecular and extended systems. Exascale capabilities have the potential to enable the application of QMC to significantly larger systems, capturing much of the complexity of real materials such as defects and impurities. However, both memory and computational demands will require significant changes to current algorithms to realize this possibility. This talk will detail both the causes of the problem and potential solutions. Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corp, a wholly owned subsidiary of Lockheed Martin Corp, for the US Department of Energys National Nuclear Security Administration under contract DE-AC04-94AL85000.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Fast inverse scattering solutions using the distorted Born iterative method and the multilevel fast multipole algorithm

PubMed Central

Hesford, Andrew J.; Chew, Weng C.

2010-01-01

The distorted Born iterative method (DBIM) computes iterative solutions to nonlinear inverse scattering problems through successive linear approximations. By decomposing the scattered field into a superposition of scattering by an inhomogeneous background and by a material perturbation, large or high-contrast variations in medium properties can be imaged through iterations that are each subject to the distorted Born approximation. However, the need to repeatedly compute forward solutions still imposes a very heavy computational burden. To ameliorate this problem, the multilevel fast multipole algorithm (MLFMA) has been applied as a forward solver within the DBIM. The MLFMA computes forward solutions in linear time for volumetric scatterers. The typically regular distribution and shape of scattering elements in the inverse scattering problem allow the method to take advantage of data redundancy and reduce the computational demands of the normally expensive MLFMA setup. Additional benefits are gained by employing Kaczmarz-like iterations, where partial measurements are used to accelerate convergence. Numerical results demonstrate both the efficiency of the forward solver and the successful application of the inverse method to imaging problems with dimensions in the neighborhood of ten wavelengths. PMID:20707438

Adaptable Iterative and Recursive Kalman Filter Schemes

NASA Technical Reports Server (NTRS)

Zanetti, Renato

2014-01-01

Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. The Iterated Kalman filter (IKF) and the Recursive Update Filter (RUF) are two algorithms that reduce the consequences of the linearization assumption of the EKF by performing N updates for each new measurement, where N is the number of recursions, a tuning parameter. This paper introduces an adaptable RUF algorithm to calculate N on the go, a similar technique can be used for the IKF as well.

Fast sparse recovery and coherence factor weighting in optoacoustic tomography

NASA Astrophysics Data System (ADS)

He, Hailong; Prakash, Jaya; Buehler, Andreas; Ntziachristos, Vasilis

2017-03-01

Sparse recovery algorithms have shown great potential to reconstruct images with limited view datasets in optoacoustic tomography, with a disadvantage of being computational expensive. In this paper, we improve the fast convergent Split Augmented Lagrangian Shrinkage Algorithm (SALSA) method based on least square QR (LSQR) formulation for performing accelerated reconstructions. Further, coherence factor is calculated to weight the final reconstruction result, which can further reduce artifacts arising in limited-view scenarios and acoustically heterogeneous mediums. Several phantom and biological experiments indicate that the accelerated SALSA method with coherence factor (ASALSA-CF) can provide improved reconstructions and much faster convergence compared to existing sparse recovery methods.

hPIN/hTAN: Low-Cost e-Banking Secure against Untrusted Computers

NASA Astrophysics Data System (ADS)

Li, Shujun; Sadeghi, Ahmad-Reza; Schmitz, Roland

We propose hPIN/hTAN, a low-cost token-based e-banking protection scheme when the adversary has full control over the user's computer. Compared with existing hardware-based solutions, hPIN/hTAN depends on neither second trusted channel, nor secure keypad, nor computationally expensive encryption module.

The AAHA Computer Program. American Animal Hospital Association.

PubMed

Albers, J W

1986-07-01

The American Animal Hospital Association Computer Program should benefit all small animal practitioners. Through the availability of well-researched and well-developed certified software, veterinarians will have increased confidence in their purchase decisions. With the expansion of computer applications to improve practice management efficiency, veterinary computer systems will further justify their initial expense. The development of the Association's veterinary computer network will provide a variety of important services to the profession.

Numerical experience with a class of algorithms for nonlinear optimization using inexact function and gradient information

NASA Technical Reports Server (NTRS)

Carter, Richard G.

1989-01-01

For optimization problems associated with engineering design, parameter estimation, image reconstruction, and other optimization/simulation applications, low accuracy function and gradient values are frequently much less expensive to obtain than high accuracy values. Here, researchers investigate the computational performance of trust region methods for nonlinear optimization when high accuracy evaluations are unavailable or prohibitively expensive, and confirm earlier theoretical predictions when the algorithm is convergent even with relative gradient errors of 0.5 or more. The proper choice of the amount of accuracy to use in function and gradient evaluations can result in orders-of-magnitude savings in computational cost.

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Xiao; Blazek, Jonathan A.; McEwen, Joseph E.

Cosmological perturbation theory is a powerful tool to predict the statistics of large-scale structure in the weakly non-linear regime, but even at 1-loop order it results in computationally expensive mode-coupling integrals. Here we present a fast algorithm for computing 1-loop power spectra of quantities that depend on the observer's orientation, thereby generalizing the FAST-PT framework (McEwen et al., 2016) that was originally developed for scalars such as the matter density. This algorithm works for an arbitrary input power spectrum and substantially reduces the time required for numerical evaluation. We apply the algorithm to four examples: intrinsic alignments of galaxies inmore » the tidal torque model; the Ostriker-Vishniac effect; the secondary CMB polarization due to baryon flows; and the 1-loop matter power spectrum in redshift space. Code implementing this algorithm and these applications is publicly available at https://github.com/JoeMcEwen/FAST-PT.« less

Directional view interpolation for compensation of sparse angular sampling in cone-beam CT.

PubMed

Bertram, Matthias; Wiegert, Jens; Schafer, Dirk; Aach, Til; Rose, Georg

2009-07-01

In flat detector cone-beam computed tomography and related applications, sparse angular sampling frequently leads to characteristic streak artifacts. To overcome this problem, it has been suggested to generate additional views by means of interpolation. The practicality of this approach is investigated in combination with a dedicated method for angular interpolation of 3-D sinogram data. For this purpose, a novel dedicated shape-driven directional interpolation algorithm based on a structure tensor approach is developed. Quantitative evaluation shows that this method clearly outperforms conventional scene-based interpolation schemes. Furthermore, the image quality trade-offs associated with the use of interpolated intermediate views are systematically evaluated for simulated and clinical cone-beam computed tomography data sets of the human head. It is found that utilization of directionally interpolated views significantly reduces streak artifacts and noise, at the expense of small introduced image blur.

Particle swarm optimization and gravitational wave data analysis: Performance on a binary inspiral testbed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang Yan; Mohanty, Soumya D.; Center for Gravitational Wave Astronomy, Department of Physics and Astronomy, University of Texas at Brownsville, 80 Fort Brown, Brownsville, Texas 78520

2010-03-15

The detection and estimation of gravitational wave signals belonging to a parameterized family of waveforms requires, in general, the numerical maximization of a data-dependent function of the signal parameters. Because of noise in the data, the function to be maximized is often highly multimodal with numerous local maxima. Searching for the global maximum then becomes computationally expensive, which in turn can limit the scientific scope of the search. Stochastic optimization is one possible approach to reducing computational costs in such applications. We report results from a first investigation of the particle swarm optimization method in this context. The method ismore » applied to a test bed motivated by the problem of detection and estimation of a binary inspiral signal. Our results show that particle swarm optimization works well in the presence of high multimodality, making it a viable candidate method for further applications in gravitational wave data analysis.« less

Low rank factorization of the Coulomb integrals for periodic coupled cluster theory.

PubMed

Hummel, Felix; Tsatsoulis, Theodoros; Grüneis, Andreas

2017-03-28

We study a tensor hypercontraction decomposition of the Coulomb integrals of periodic systems where the integrals are factorized into a contraction of six matrices of which only two are distinct. We find that the Coulomb integrals can be well approximated in this form already with small matrices compared to the number of real space grid points. The cost of computing the matrices scales as O(N 4 ) using a regularized form of the alternating least squares algorithm. The studied factorization of the Coulomb integrals can be exploited to reduce the scaling of the computational cost of expensive tensor contractions appearing in the amplitude equations of coupled cluster methods with respect to system size. We apply the developed methodologies to calculate the adsorption energy of a single water molecule on a hexagonal boron nitride monolayer in a plane wave basis set and periodic boundary conditions.

Utilizing the Structure and Content Information for XML Document Clustering

NASA Astrophysics Data System (ADS)

Tran, Tien; Kutty, Sangeetha; Nayak, Richi

This paper reports on the experiments and results of a clustering approach used in the INEX 2008 document mining challenge. The clustering approach utilizes both the structure and content information of the Wikipedia XML document collection. A latent semantic kernel (LSK) is used to measure the semantic similarity between XML documents based on their content features. The construction of a latent semantic kernel involves the computing of singular vector decomposition (SVD). On a large feature space matrix, the computation of SVD is very expensive in terms of time and memory requirements. Thus in this clustering approach, the dimension of the document space of a term-document matrix is reduced before performing SVD. The document space reduction is based on the common structural information of the Wikipedia XML document collection. The proposed clustering approach has shown to be effective on the Wikipedia collection in the INEX 2008 document mining challenge.

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

PubMed

Li, Yeqing; Liu, Wei; Huang, Junzhou

2018-06-01

Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning. As case studies, we apply the sub-selection algorithm to several popular quantization techniques including cases using linear and nonlinear mappings. Crucially, we can justify the resulting sub-selective quantization by proving its theoretic properties. Extensive experiments are carried out on three image benchmarks with up to one million samples, corroborating the efficacy of the sub-selective quantization method in terms of image retrieval.

Distributive, Non-destructive Real-time System and Method for Snowpack Monitoring

NASA Technical Reports Server (NTRS)

Frolik, Jeff (Inventor); Skalka, Christian (Inventor)

2013-01-01

A ground-based system that provides quasi real-time measurement and collection of snow-water equivalent (SWE) data in remote settings is provided. The disclosed invention is significantly less expensive and easier to deploy than current methods and less susceptible to terrain and snow bridging effects. Embodiments of the invention include remote data recovery solutions. Compared to current infrastructure using existing SWE technology, the disclosed invention allows more SWE sites to be installed for similar cost and effort, in a greater variety of terrain; thus, enabling data collection at improved spatial resolutions. The invention integrates a novel computational architecture with new sensor technologies. The invention's computational architecture is based on wireless sensor networks, comprised of programmable, low-cost, low-powered nodes capable of sophisticated sensor control and remote data communication. The invention also includes measuring attenuation of electromagnetic radiation, an approach that is immune to snow bridging and significantly reduces sensor footprints.

Model-based spectral estimation of Doppler signals using parallel genetic algorithms.

PubMed

Solano González, J; Rodríguez Vázquez, K; García Nocetti, D F

2000-05-01

Conventional spectral analysis methods use a fast Fourier transform (FFT) on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the non-stationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements in real-time a parametric spectral estimator method using genetic algorithms (GAs) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GAs and exploiting its parallel characteristics. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.

Three-dimensional simulation of helix traveling-wave tube cold-test characteristics using MAFIA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kory, C.L.

1996-12-31

A critically important step in the traveling-wave tube (TWT) design process is the cold-testing of the slow-wave circuit for dispersion, beam interaction impedance and RF losses. Experimental cold-tests can be very time-consuming and expensive, thus limiting the freedom to examine numerous variations to the test circuit. This makes the need for computational methods crucial as they can lower cost, reduce tube development time and allow the freedom to introduce novel and improved designs. The cold-test parameters have been calculated for a C-Band Northrop-Grumman helix TWT slow-wave circuit using MAFIA, the three-dimensional electromagnetic finite-integration computer code. Measured and simulated cold-test datamore » for the Northrop-Grumman helix TWT including dispersion, impedance and attenuation will be presented. Close agreement between simulated and measured values of the dispersion, impedance and attenuation has been obtained.« less

Abort Options for Human Missions to Earth-Moon Halo Orbits

NASA Technical Reports Server (NTRS)

Jesick, Mark C.

2013-01-01

Abort trajectories are optimized for human halo orbit missions about the translunar libration point (L2), with an emphasis on the use of free return trajectories. Optimal transfers from outbound free returns to L2 halo orbits are numerically optimized in the four-body ephemeris model. Circumlunar free returns are used for direct transfers, and cislunar free returns are used in combination with lunar gravity assists to reduce propulsive requirements. Trends in orbit insertion cost and flight time are documented across the southern L2 halo family as a function of halo orbit position and free return flight time. It is determined that the maximum amplitude southern halo incurs the lowest orbit insertion cost for direct transfers but the maximum cost for lunar gravity assist transfers. The minimum amplitude halo is the most expensive destination for direct transfers but the least expensive for lunar gravity assist transfers. The on-orbit abort costs for three halos are computed as a function of abort time and return time. Finally, an architecture analysis is performed to determine launch and on-orbit vehicle requirements for halo orbit missions.

Modelling and analysis of the wetting characteristics of ink for display applications with the surface evolution technique

NASA Astrophysics Data System (ADS)

Shin, Dong-Youn; Brakke, Kenneth A.

2009-06-01

Piezo drop-on-demand inkjet printing technology has attracted the attention of display industries for the production of colour filters for thin film transistor liquid crystal displays (TFT LCD) because of the opportunity of reducing manufacturing cost. Colourant ink droplets ejected from inkjet nozzles selectively fill subpixels surrounded with black matrix (BM). Surface energy differences between the glass substrate and the BM generally guide this ink filling process. This colourant ink filling process, however, results from the complex hydrodynamic interaction of ink with the substrate and the BM. Neither computationally expensive numerical methods nor time and cost expensive experiments are suitable for the derivation of optimum surface conditions at the early development stage. In this study, a more concise surface evolution technique is proposed and ways to find the optimum surface conditions for the fabrication of TFT LCD colour filters and polymer light emitting devices are discussed, which might be useful for chemists and developers of ink and BM material, as well as for process engineers in display industries.

Model Reduction of Computational Aerothermodynamics for Multi-Discipline Analysis in High Speed Flows

NASA Astrophysics Data System (ADS)

Crowell, Andrew Rippetoe

This dissertation describes model reduction techniques for the computation of aerodynamic heat flux and pressure loads for multi-disciplinary analysis of hypersonic vehicles. NASA and the Department of Defense have expressed renewed interest in the development of responsive, reusable hypersonic cruise vehicles capable of sustained high-speed flight and access to space. However, an extensive set of technical challenges have obstructed the development of such vehicles. These technical challenges are partially due to both the inability to accurately test scaled vehicles in wind tunnels and to the time intensive nature of high-fidelity computational modeling, particularly for the fluid using Computational Fluid Dynamics (CFD). The aim of this dissertation is to develop efficient and accurate models for the aerodynamic heat flux and pressure loads to replace the need for computationally expensive, high-fidelity CFD during coupled analysis. Furthermore, aerodynamic heating and pressure loads are systematically evaluated for a number of different operating conditions, including: simple two-dimensional flow over flat surfaces up to three-dimensional flows over deformed surfaces with shock-shock interaction and shock-boundary layer interaction. An additional focus of this dissertation is on the implementation and computation of results using the developed aerodynamic heating and pressure models in complex fluid-thermal-structural simulations. Model reduction is achieved using a two-pronged approach. One prong focuses on developing analytical corrections to isothermal, steady-state CFD flow solutions in order to capture flow effects associated with transient spatially-varying surface temperatures and surface pressures (e.g., surface deformation, surface vibration, shock impingements, etc.). The second prong is focused on minimizing the computational expense of computing the steady-state CFD solutions by developing an efficient surrogate CFD model. The developed two-pronged approach is found to exhibit balanced performance in terms of accuracy and computational expense, relative to several existing approaches. This approach enables CFD-based loads to be implemented into long duration fluid-thermal-structural simulations.

Tunable inter-qubit coupling as a resource for gate based quantum computing with superconducting circuits

NASA Astrophysics Data System (ADS)

Chiaro, B.; Neill, C.; Chen, Z.; Dunsworth, A.; Foxen, B.; Quintana, C.; Wenner, J.; Martinis, J. M.; Google Quantum Hardware Team

Fast, high fidelity two qubit gates are an essential requirement of a quantum processor. In this talk, we discuss how the tunable coupling of the gmon architecture provides a pathway for an improved two qubit controlled-Z gate. The maximum inter-qubit coupling strength gmax = 60 MHz is sufficient for fast adiabatic two qubit gates to be performed as quickly as single qubit gates, reducing dephasing errors. Additionally, the ability to turn the coupling off allows all qubits to idle at low magnetic flux sensitivity, further reducing susceptibility to noise. However, the flexibility that this platform offers comes at the expense of increased control complexity. We describe our strategy for addressing the control challenges of the gmon architecture and show experimental progress toward fast, high fidelity controlled-Z gates with gmon qubits.

Exploiting GPUs in Virtual Machine for BioCloud

PubMed Central

Jo, Heeseung; Jeong, Jinkyu; Lee, Myoungho; Choi, Dong Hoon

2013-01-01

Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their computation performance and utilize infinite cloud computing resource while reducing expenses for computations. In this paper, we propose a BioCloud system architecture that enables VMs to use GPUs in cloud environment. Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing. The proposed system exploits the pass-through mode of PCI express (PCI-E) channel. By making each VM be able to access underlying GPUs directly, applications can show almost the same performance as when those are in native environment. In addition, our scheme multiplexes GPUs by using hot plug-in/out device features of PCI-E channel. By adding or removing GPUs in each VM in on-demand manner, VMs in the same physical host can time-share their GPUs. We implemented the proposed system using the Xen VMM and NVIDIA GPUs and showed that our prototype is highly effective for biological GPU applications in cloud environment. PMID:23710465

Exploiting GPUs in virtual machine for BioCloud.

PubMed

Jo, Heeseung; Jeong, Jinkyu; Lee, Myoungho; Choi, Dong Hoon

2013-01-01

Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their computation performance and utilize infinite cloud computing resource while reducing expenses for computations. In this paper, we propose a BioCloud system architecture that enables VMs to use GPUs in cloud environment. Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing. The proposed system exploits the pass-through mode of PCI express (PCI-E) channel. By making each VM be able to access underlying GPUs directly, applications can show almost the same performance as when those are in native environment. In addition, our scheme multiplexes GPUs by using hot plug-in/out device features of PCI-E channel. By adding or removing GPUs in each VM in on-demand manner, VMs in the same physical host can time-share their GPUs. We implemented the proposed system using the Xen VMM and NVIDIA GPUs and showed that our prototype is highly effective for biological GPU applications in cloud environment.

Efficient hyperspectral image segmentation using geometric active contour formulation

NASA Astrophysics Data System (ADS)

Albalooshi, Fatema A.; Sidike, Paheding; Asari, Vijayan K.

2014-10-01

In this paper, we present a new formulation of geometric active contours that embeds the local hyperspectral image information for an accurate object region and boundary extraction. We exploit self-organizing map (SOM) unsupervised neural network to train our model. The segmentation process is achieved by the construction of a level set cost functional, in which, the dynamic variable is the best matching unit (BMU) coming from SOM map. In addition, we use Gaussian filtering to discipline the deviation of the level set functional from a signed distance function and this actually helps to get rid of the re-initialization step that is computationally expensive. By using the properties of the collective computational ability and energy convergence capability of the active control models (ACM) energy functional, our method optimizes the geometric ACM energy functional with lower computational time and smoother level set function. The proposed algorithm starts with feature extraction from raw hyperspectral images. In this step, the principal component analysis (PCA) transformation is employed, and this actually helps in reducing dimensionality and selecting best sets of the significant spectral bands. Then the modified geometric level set functional based ACM is applied on the optimal number of spectral bands determined by the PCA. By introducing local significant spectral band information, our proposed method is capable to force the level set functional to be close to a signed distance function, and therefore considerably remove the need of the expensive re-initialization procedure. To verify the effectiveness of the proposed technique, we use real-life hyperspectral images and test our algorithm in varying textural regions. This framework can be easily adapted to different applications for object segmentation in aerial hyperspectral imagery.

26 CFR 1.50B-3 - Estates and trusts.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 1 2010-04-01 2010-04-01 true Estates and trusts. 1.50B-3 Section 1.50B-3... Computing Credit for Expenses of Work Incentive Programs § 1.50B-3 Estates and trusts. (a) General rule—(1) In general. In the case of an estate or trust, WIN expenses (as defined in paragraph (a) of § 1.50B-1...

Paradigm Paralysis and the Plight of the PC in Education.

ERIC Educational Resources Information Center

O'Neil, Mick

1998-01-01

Examines the varied factors involved in providing Internet access in K-12 education, including expense, computer installation and maintenance, and security, and explores how the network computer could be useful in this context. Operating systems and servers are discussed. (MSE)

Computational Modeling in Concert with Laboratory Studies: Application to B Cell Differentiation

EPA Science Inventory

Remediation is expensive, so accurate prediction of dose-response is important to help control costs. Dose response is a function of biological mechanisms. Computational models of these mechanisms improve the efficiency of research and provide the capability for prediction.

A Talking Computers System for Persons with Vision and Speech Handicaps. Final Report.

ERIC Educational Resources Information Center

Visek & Maggs, Urbana, IL.

This final report contains a detailed description of six software systems designed to assist individuals with blindness and/or speech disorders in using inexpensive, off-the-shelf computers rather than expensive custom-made devices. The developed software is not written in the native machine language of any particular brand of computer, but in the…

The Financial Impact of the ‘Zero-Markup Policy for Essential Drugs’ on Patients in County Hospitals in Western Rural China

PubMed Central

Zhou, Zhongliang; Su, Yanfang; Campbell, Benjamin; Zhou, Zhiying; Gao, Jianmin; Yu, Qiang; Chen, Jiuhao; Pan, Yishan

2015-01-01

Objective With a quasi-experimental design, this study aims to assess whether the Zero-markup Policy for Essential Drugs (ZPED) reduces the medical expense for patients at county hospitals, the major healthcare provider in rural China. Methods Data from Ningshan county hospital and Zhenping county hospital, China, include 2014 outpatient records and 9239 inpatient records. Quantitative methods are employed to evaluate ZPED. Both hospital-data difference-in-differences and individual-data regressions are applied to analyze the data from inpatient and outpatient departments. Results In absolute terms, the total expense per visit reduced by 19.02 CNY (3.12 USD) for outpatient services and 399.6 CNY (65.60 USD) for inpatient services. In relative terms, the expense per visit was reduced by 11% for both outpatient and inpatient services. Due to the reduction of inpatient expense, the estimated reduction of outpatient visits is 2% among the general population and 3.39% among users of outpatient services. The drug expense per visit dropped by 27.20 CNY (4.47 USD) for outpatient services and 278.7 CNY (45.75 USD) for inpatient services. The proportion of drug expense out of total expense per visit dropped by 11.73 percentage points in outpatient visits and by 3.92 percentage points in inpatient visits. Conclusion Implementation of ZPED is a benefit for patients in both absolute and relative terms. The absolute monetary reduction of the per-visit inpatient expense is 20 times of that in outpatient care. According to cross-price elasticity, the substitution between inpatient and outpatient due to the change in inpatient price is small. Furthermore, given that the relative reductions are the same for outpatient and inpatient visits, according to relative thinking theory, the incentive to utilize outpatient or inpatient care attributed to ZPED is equivalent, regardless of the 20-times price difference in absolute terms. PMID:25790443

The financial impact of the 'zero-markup policy for essential drugs' on patients in county hospitals in western rural China.

PubMed

Zhou, Zhongliang; Su, Yanfang; Campbell, Benjamin; Zhou, Zhiying; Gao, Jianmin; Yu, Qiang; Chen, Jiuhao; Pan, Yishan

2015-01-01

With a quasi-experimental design, this study aims to assess whether the Zero-markup Policy for Essential Drugs (ZPED) reduces the medical expense for patients at county hospitals, the major healthcare provider in rural China. Data from Ningshan county hospital and Zhenping county hospital, China, include 2014 outpatient records and 9239 inpatient records. Quantitative methods are employed to evaluate ZPED. Both hospital-data difference-in-differences and individual-data regressions are applied to analyze the data from inpatient and outpatient departments. In absolute terms, the total expense per visit reduced by 19.02 CNY (3.12 USD) for outpatient services and 399.6 CNY (65.60 USD) for inpatient services. In relative terms, the expense per visit was reduced by 11% for both outpatient and inpatient services. Due to the reduction of inpatient expense, the estimated reduction of outpatient visits is 2% among the general population and 3.39% among users of outpatient services. The drug expense per visit dropped by 27.20 CNY (4.47 USD) for outpatient services and 278.7 CNY (45.75 USD) for inpatient services. The proportion of drug expense out of total expense per visit dropped by 11.73 percentage points in outpatient visits and by 3.92 percentage points in inpatient visits. Implementation of ZPED is a benefit for patients in both absolute and relative terms. The absolute monetary reduction of the per-visit inpatient expense is 20 times of that in outpatient care. According to cross-price elasticity, the substitution between inpatient and outpatient due to the change in inpatient price is small. Furthermore, given that the relative reductions are the same for outpatient and inpatient visits, according to relative thinking theory, the incentive to utilize outpatient or inpatient care attributed to ZPED is equivalent, regardless of the 20-times price difference in absolute terms.

Using Clinical Decision Support Software in Health Insurance Company

NASA Astrophysics Data System (ADS)

Konovalov, R.; Kumlander, Deniss

This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

[Cost analysis for navigation in knee endoprosthetics].

PubMed

Cerha, O; Kirschner, S; Günther, K-P; Lützner, J

2009-12-01

Total knee arthroplasty (TKA) is one of the most frequent procedures in orthopaedic surgery. The outcome depends on a range of factors including alignment of the leg and the positioning of the implant in addition to patient-associated factors. Computer-assisted navigation systems can improve the restoration of a neutral leg alignment. This procedure has been established especially in Europe and North America. The additional expenses are not reimbursed in the German DRG system (Diagnosis Related Groups). In the present study a cost analysis of computer-assisted TKA compared to the conventional technique was performed. The acquisition expenses of various navigation systems (5 and 10 year depreciation), annual costs for maintenance and software updates as well as the accompanying costs per operation (consumables, additional operating time) were considered. The additional operating time was determined on the basis of a meta-analysis according to the current literature. Situations with 25, 50, 100, 200 and 500 computer-assisted TKAs per year were simulated. The amount of the incremental costs of the computer-assisted TKA depends mainly on the annual volume and the additional operating time. A relevant decrease of the incremental costs was detected between 50 and 100 procedures per year. In a model with 100 computer-assisted TKAs per year an additional operating time of 14 mins and a 10 year depreciation of the investment costs, the incremental expenses amount to 300-395 depending on the navigation system. Computer-assisted TKA is associated with additional costs. From an economical point of view an amount of more than 50 procedures per year appears to be favourable. The cost-effectiveness could be estimated if long-term results will show a reduction of revisions or a better clinical outcome.

Algorithm and code development for unsteady three-dimensional Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Obayashi, Shigeru

1993-01-01

In the last two decades, there have been extensive developments in computational aerodynamics, which constitutes a major part of the general area of computational fluid dynamics. Such developments are essential to advance the understanding of the physics of complex flows, to complement expensive wind-tunnel tests, and to reduce the overall design cost of an aircraft, particularly in the area of aeroelasticity. Aeroelasticity plays an important role in the design and development of aircraft, particularly modern aircraft, which tend to be more flexible. Several phenomena that can be dangerous and limit the performance of an aircraft occur because of the interaction of the flow with flexible components. For example, an aircraft with highly swept wings may experience vortex-induced aeroelastic oscillations. Also, undesirable aeroelastic phenomena due to the presence and movement of shock waves occur in the transonic range. Aeroelastically critical phenomena, such as a low transonic flutter speed, have been known to occur through limited wind-tunnel tests and flight tests. Aeroelastic tests require extensive cost and risk. An aeroelastic wind-tunnel experiment is an order of magnitude more expensive than a parallel experiment involving only aerodynamics. By complementing the wind-tunnel experiments with numerical simulations the overall cost of the development of aircraft can be considerably reduced. In order to accurately compute aeroelastic phenomenon it is necessary to solve the unsteady Euler/Navier-Stokes equations simultaneously with the structural equations of motion. These equations accurately describe the flow phenomena for aeroelastic applications. At Ames a code, ENSAERO, is being developed for computing the unsteady aerodynamics and aeroelasticity of aircraft and it solves the Euler/Navier-Stokes equations. The purpose of this contract is to continue the algorithm enhancements of ENSAERO and to apply the code to complicated geometries. During the last year, the geometric capability of the code was extended to simulate transonic flows, a wing with oscillating control surface. Single-grid and zonal approaches were tested. For the zonal approach, a new interpolation technique was introduced. The key development of the algorithm was an interface treatment between moving zones for a control surface using the virtual-zone concept. The work performed during the period, 1 Apr. 1992 through 31 Mar. 1993 is summarized. Additional details on the various aspects of the study are given in the Appendices.

Use of less expensive cigarettes in six cities in China: findings from the International Tobacco Control (ITC) China Survey.

PubMed

Li, Qiang; Hyland, Andrew; Fong, Geoffrey T; Jiang, Yuan; Elton-Marshall, Tara

2010-10-01

The existence of less expensive cigarettes in China may undermine public health. The aim of the current study is to examine the use of less expensive cigarettes in six cities in China. Data was from the baseline wave of the International Tobacco Control (ITC) China Survey of 4815 adult urban smokers in 6 cities, conducted between April and August 2006. The percentage of smokers who reported buying less expensive cigarettes (the lowest pricing tertile within each city) at last purchase was computed. Complex sample multivariate logistic regression models were used to identify factors associated with use of less expensive cigarettes. The association between the use of less expensive cigarettes and intention to quit smoking was also examined. Smokers who reported buying less expensive cigarettes at last purchase tended to be older, heavier smokers, to have lower education and income, and to think more about the money spent on smoking in the last month. Smokers who bought less expensive cigarettes at the last purchase and who were less knowledgeable about the health harm of smoking were less likely to intend to quit smoking. Measures need to be taken to minimise the price differential among cigarette brands and to increase smokers' health knowledge, which may in turn increase their intentions to quit.

Cyclone Simulation via Action Minimization

NASA Astrophysics Data System (ADS)

Plotkin, D. A.; Weare, J.; Abbot, D. S.

2016-12-01

A postulated impact of climate change is an increase in intensity of tropical cyclones (TCs). This hypothesized effect results from the fact that TCs are powered subsaturated boundary layer air picking up water vapor from the surface ocean as it flows inwards towards the eye. This water vapor serves as the energy input for TCs, which can be idealized as heat engines. The inflowing air has a nearly identical temperature as the surface ocean; therefore, warming of the surface leads to a warmer atmospheric boundary layer. By the Clausius-Clapeyron relationship, warmer boundary layer air can hold more water vapor and thus results in more energetic storms. Changes in TC intensity are difficult to predict due to the presence of fine structures (e.g. convective structures and rainbands) with length scales of less than 1 km, while general circulation models (GCMs) generally have horizontal resolutions of tens of kilometers. The models are therefore unable to capture these features, which are critical to accurately simulating cyclone structure and intensity. Further, strong TCs are rare events, meaning that long multi-decadal simulations are necessary to generate meaningful statistics about intense TC activity. This adds to the computational expense, making it yet more difficult to generate accurate statistics about long-term changes in TC intensity due to global warming via direct simulation. We take an alternative approach, applying action minimization techniques developed in molecular dynamics to the WRF weather/climate model. We construct artificial model trajectories that lead from quiescent (TC-free) states to TC states, then minimize the deviation of these trajectories from true model dynamics. We can thus create Monte Carlo model ensembles that are biased towards cyclogenesis, which reduces computational expense by limiting time spent in non-TC states. This allows for: 1) selective interrogation of model states with TCs; 2) finding the likeliest paths for transitions between TC-free and TC states; and 3) an increase in horizontal resolution due to computational savings achieved by reducing time spent simulating TC-free states. This increase in resolution, coupled with a decrease in simulation time, allows for prediction of the change in TC frequency and intensity distributions resulting from climate change.

Strategy and methodology for rank-ordering Virginia state agencies regarding solar attractiveness and identification of specific project possibilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hewett, R.

1997-12-31

This paper describes the strategy and computer processing system that NREL, the Virginia Department of Mines, Minerals and Energy (DMME) and the state energy office, are developing for computing solar attractiveness scores for state agencies and the individual facilities or buildings within each agency. In the case of an agency, solar attractiveness is a measure of that agency`s having a significant number of facilities for which solar has the potential to be promising. In the case of a facility, solar attractiveness is a measure of its potential for being good, economically viable candidate for a solar waste heating system. Virginiamore » State agencies are charged with reducing fossil energy and electricity use and expense. DMME is responsible for working with them to achieve the goals and for managing the state`s energy consumption and cost monitoring program. This is done using the Fast Accounting System for Energy Reporting (FASER) computerized energy accounting and tracking system and database. Agencies report energy use and expenses (by individual facility and energy type) to DMME quarterly. DMME is also responsible for providing technical and other assistance services to agencies and facilities interested in investigating use of solar. Since Virginia has approximately 80 agencies operating over 8,000 energy-consuming facilities and since DMME`s resources are limited, it is interested in being able to determine: (1) on which agencies to focus; (2) specific facilities on which to focus within each high-priority agency; and (3) irrespective of agency, which facilities are the most promising potential candidates for solar. The computer processing system described in this paper computes numerical solar attractiveness scores for the state`s agencies and the individual facilities using the energy use and cost data in the FASER system database and the state`s and NREL`s experience in implementing, testing and evaluating solar water heating systems in commercial and government facilities.« less

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

DOE PAGES

Butler, Troy; Wildey, Timothy

2018-01-01

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, Troy; Wildey, Timothy

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

PubMed

Yazar, Seyhan; Gooden, George E C; Mackey, David A; Hewitt, Alex W

2014-01-01

A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5-78.2) for E.coli and 53.5% (95% CI: 34.4-72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5-303.1) and 173.9% (95% CI: 134.6-213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE.

Benchmarking Undedicated Cloud Computing Providers for Analysis of Genomic Datasets

PubMed Central

Yazar, Seyhan; Gooden, George E. C.; Mackey, David A.; Hewitt, Alex W.

2014-01-01

A major bottleneck in biological discovery is now emerging at the computational level. Cloud computing offers a dynamic means whereby small and medium-sized laboratories can rapidly adjust their computational capacity. We benchmarked two established cloud computing services, Amazon Web Services Elastic MapReduce (EMR) on Amazon EC2 instances and Google Compute Engine (GCE), using publicly available genomic datasets (E.coli CC102 strain and a Han Chinese male genome) and a standard bioinformatic pipeline on a Hadoop-based platform. Wall-clock time for complete assembly differed by 52.9% (95% CI: 27.5–78.2) for E.coli and 53.5% (95% CI: 34.4–72.6) for human genome, with GCE being more efficient than EMR. The cost of running this experiment on EMR and GCE differed significantly, with the costs on EMR being 257.3% (95% CI: 211.5–303.1) and 173.9% (95% CI: 134.6–213.1) more expensive for E.coli and human assemblies respectively. Thus, GCE was found to outperform EMR both in terms of cost and wall-clock time. Our findings confirm that cloud computing is an efficient and potentially cost-effective alternative for analysis of large genomic datasets. In addition to releasing our cost-effectiveness comparison, we present available ready-to-use scripts for establishing Hadoop instances with Ganglia monitoring on EC2 or GCE. PMID:25247298

A Parametric Study of Unsteady Rotor-Stator Interaction in a Simplified Francis Turbine

NASA Astrophysics Data System (ADS)

Wouden, Alex; Cimbala, John; Lewis, Bryan

2011-11-01

CFD analysis is becoming a critical stage in the design of hydroturbines. However, its capability to represent unsteady flow interactions between the rotor and stator (which requires a 360-degree, mesh-refined model of the turbine passage) is hindered. For CFD to become a more effective tool in predicting the performance of a hydroturbine, the key interactions between the rotor and stator need to be understood using current numerical methods. As a first step towards evaluating this unsteady behavior without the burden of a computationally expensive domain, the stator and Francis-type rotor blades are reduced to flat plates. Local and global variables are compared using periodic, semi-periodic, and 360-degree geometric models and various turbulence models (k-omega, k-epsilon, and Spalart-Allmaras). The computations take place within the OpenFOAM® environment and utilize a general grid interface (GGI) between the rotor and stator computational domains. The rotor computational domain is capable of dynamic rotation. The results demonstrate some of the strengths and limitations of utilizing CFD for hydroturbine analysis. These case studies will also serve as tutorials to help others learn how to use CFD for turbomachinery. This research is funded by a grant from the DOE.

A Solution in Search of Problems

NASA Technical Reports Server (NTRS)

1981-01-01

Ferrofluids offered vast-problem solving potential. Under license for the NASA technology, Dr. Ronald Moskowitz and Dr. Ronald Rosensweig formed Ferrofluids Corporation. First problem they found a solution for was related to the manufacture of semiconductor "chips" for use in electronic systems. They developed a magnetic seal composed of ferrofluid and a magnetic circuit. Magnetic field confines the ferrofluid in the regions between the stationary elements and the rotary shaft of the seal. Result is a series of liquid barriers that totally bar passage of contaminants. Seal is virtually wear-proof and has a lifetime measured in billions of shaft revolutions. It has reduced maintenance, minimizes "downtime" of production equipment, and reduces the cost of expensive materials that had previously been lost through seal failures. Products based on ferrofluid are exclusion seals for computer disc drives and inertia dampers for stepper motors. Uses are performance-improving, failure-reducing coolants for hi-fi loudspeakers. Other applications include analytical instrumentation, medical equipment, industrial processes, silicon crystal growing furnaces, plasma processes, fusion research, visual displays, and automated machine tools.

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

PubMed

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

Deep learning beyond Lefschetz thimbles

NASA Astrophysics Data System (ADS)

Alexandru, Andrei; Bedaque, Paulo F.; Lamm, Henry; Lawrence, Scott

2017-11-01

The generalized thimble method to treat field theories with sign problems requires repeatedly solving the computationally expensive holomorphic flow equations. We present a machine learning technique to bypass this problem. The central idea is to obtain a few field configurations via the flow equations to train a feed-forward neural network. The trained network defines a new manifold of integration which reduces the sign problem and can be rapidly sampled. We present results for the 1 +1 dimensional Thirring model with Wilson fermions on sizable lattices. In addition to the gain in speed, the parametrization of the integration manifold we use avoids the "trapping" of Monte Carlo chains which plagues large-flow calculations, a considerable shortcoming of the previous attempts.

Performance optimization of internet firewalls

NASA Astrophysics Data System (ADS)

Chiueh, Tzi-cker; Ballman, Allen

1997-01-01

Internet firewalls control the data traffic in and out of an enterprise network by checking network packets against a set of rules that embodies an organization's security policy. Because rule checking is computationally more expensive than routing-table look-up, it could become a potential bottleneck for scaling up the performance of IP routers, which typically implement firewall functions in software. in this paper, we analyzed the performance problems associated with firewalls, particularly packet filters, propose a good connection cache to amortize the costly security check over the packets in a connection, and report the preliminary performance results of a trace-driven simulation that show the average packet check time can be reduced by a factor of 2.5 at the least.

Solvated molecular dynamics of LiCN isomerization: All-atom argon solvent versus a generalized Langevin bath.

PubMed

Junginger, Andrej; Garcia-Muller, Pablo L; Borondo, F; Benito, R M; Hernandez, Rigoberto

2016-01-14

The reaction rate rises and falls with increasing density or friction when a molecule is activated by collisions with the solvent particles. This so-called Kramers turnover has recently been observed in the isomerization reaction of LiCN in an argon bath. In this paper, we demonstrate by direct comparison with those results that a reduced-dimensional (generalized) Langevin description gives rise to similar reaction dynamics as the corresponding (computationally expensive) full molecular dynamics calculations. We show that the density distributions within the Langevin description are in direct agreement with the full molecular dynamics results and that the turnover in the reaction rates is reproduced qualitatively and quantitatively at different temperatures.

Dynamic modeling of Tampa Bay urban development using parallel computing

USGS Publications Warehouse

Xian, G.; Crane, M.; Steinwand, D.

2005-01-01

Urban land use and land cover has changed significantly in the environs of Tampa Bay, Florida, over the past 50 years. Extensive urbanization has created substantial change to the region's landscape and ecosystems. This paper uses a dynamic urban-growth model, SLEUTH, which applies six geospatial data themes (slope, land use, exclusion, urban extent, transportation, hillside), to study the process of urbanization and associated land use and land cover change in the Tampa Bay area. To reduce processing time and complete the modeling process within an acceptable period, the model is recoded and ported to a Beowulf cluster. The parallel-processing computer system accomplishes the massive amount of computation the modeling simulation requires. SLEUTH calibration process for the Tampa Bay urban growth simulation spends only 10 h CPU time. The model predicts future land use/cover change trends for Tampa Bay from 1992 to 2025. Urban extent is predicted to double in the Tampa Bay watershed between 1992 and 2025. Results show an upward trend of urbanization at the expense of a decline of 58% and 80% in agriculture and forested lands, respectively.

LittleQuickWarp: an ultrafast image warping tool.

PubMed

Qu, Lei; Peng, Hanchuan

2015-02-01

Warping images into a standard coordinate space is critical for many image computing related tasks. However, for multi-dimensional and high-resolution images, an accurate warping operation itself is often very expensive in terms of computer memory and computational time. For high-throughput image analysis studies such as brain mapping projects, it is desirable to have high performance image warping tools that are compatible with common image analysis pipelines. In this article, we present LittleQuickWarp, a swift and memory efficient tool that boosts 3D image warping performance dramatically and at the same time has high warping quality similar to the widely used thin plate spline (TPS) warping. Compared to the TPS, LittleQuickWarp can improve the warping speed 2-5 times and reduce the memory consumption 6-20 times. We have implemented LittleQuickWarp as an Open Source plug-in program on top of the Vaa3D system (http://vaa3d.org). The source code and a brief tutorial can be found in the Vaa3D plugin source code repository. Copyright © 2014 Elsevier Inc. All rights reserved.

A New Minimum Trees-Based Approach for Shape Matching with Improved Time Computing: Application to Graphical Symbols Recognition

NASA Astrophysics Data System (ADS)

Franco, Patrick; Ogier, Jean-Marc; Loonis, Pierre; Mullot, Rémy

Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longer operates in the image space but in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discussed and justified. The experimental results led on the GREC2003 database show that the proposed method is characterized by a good discrimination power, a real robustness to noise with an acceptable time computing.

Stereo Correspondence Using Moment Invariants

NASA Astrophysics Data System (ADS)

Premaratne, Prashan; Safaei, Farzad

Autonomous navigation is seen as a vital tool in harnessing the enormous potential of Unmanned Aerial Vehicles (UAV) and small robotic vehicles for both military and civilian use. Even though, laser based scanning solutions for Simultaneous Location And Mapping (SLAM) is considered as the most reliable for depth estimation, they are not feasible for use in UAV and land-based small vehicles due to their physical size and weight. Stereovision is considered as the best approach for any autonomous navigation solution as stereo rigs are considered to be lightweight and inexpensive. However, stereoscopy which estimates the depth information through pairs of stereo images can still be computationally expensive and unreliable. This is mainly due to some of the algorithms used in successful stereovision solutions require high computational requirements that cannot be met by small robotic vehicles. In our research, we implement a feature-based stereovision solution using moment invariants as a metric to find corresponding regions in image pairs that will reduce the computational complexity and improve the accuracy of the disparity measures that will be significant for the use in UAVs and in small robotic vehicles.

Evaluation of the effectiveness of two support surfaces following myocutaneous flap surgery.

PubMed

Economides, N G; Skoutakis, V A; Carter, C A; Smith, V H

1995-01-01

Recurrence of pressure ulcers is a serious problem following myocutaneous flap surgery and can lead to prolonged and expensive hospitalization. One of the most important aspects of patient care after surgery is the monitoring of reduced pressure in the area of the flap. Usually reducing pressure requires an expensive high-tech support surface. The purpose of this study was to evaluate the effectiveness of a less expensive support surface. There were 12 patients involved in a clinical trial that lasted 14 days and compared the effectiveness of the ROHO dry-floatation mattress to that of the Clinitron bed. Findings indicated that post-operative patients were effectively treated on either support surface.

Health savings accounts--a revolutionary method of funding medical care expenses.

PubMed

Knox, George Con

2004-10-01

Health Savings Accounts coupled with a High-Deductible Health Care plan offer many eligible individuals the opportunity to reduce their insurance premiums and create a tax-deductible account to pay medical, dental, and vision care expenses.

49 CFR Appendix A to Part 1511 - Aviation Security Infrastructure Fee

Code of Federal Regulations, 2012 CFR

2012-10-01

.... Please also submit the same information in Microsoft Word either on a computer disk or by e-mail to TSA..., including Checkpoint Screening Supervisors. 7. All associated expensed non-labor costs including computers, communications equipment, time management systems, supplies, parking, identification badging, furniture, fixtures...

49 CFR Appendix A to Part 1511 - Aviation Security Infrastructure Fee

Code of Federal Regulations, 2014 CFR

2014-10-01

.... Please also submit the same information in Microsoft Word either on a computer disk or by e-mail to TSA..., including Checkpoint Screening Supervisors. 7. All associated expensed non-labor costs including computers, communications equipment, time management systems, supplies, parking, identification badging, furniture, fixtures...

49 CFR Appendix A to Part 1511 - Aviation Security Infrastructure Fee

Code of Federal Regulations, 2013 CFR

2013-10-01

.... Please also submit the same information in Microsoft Word either on a computer disk or by e-mail to TSA..., including Checkpoint Screening Supervisors. 7. All associated expensed non-labor costs including computers, communications equipment, time management systems, supplies, parking, identification badging, furniture, fixtures...

A coupled ALE-AMR method for shock hydrodynamics

DOE PAGES

Waltz, J.; Bakosi, J.

2018-03-05

We present a numerical method combining adaptive mesh refinement (AMR) with arbitrary Lagrangian-Eulerian (ALE) mesh motion for the simulation of shock hydrodynamics on unstructured grids. The primary goal of the coupled method is to use AMR to reduce numerical error in ALE simulations at reduced computational expense relative to uniform fine mesh calculations, in the same manner that AMR has been used in Eulerian simulations. We also identify deficiencies with ALE methods that AMR is able to mitigate, and discuss the unique coupling challenges. The coupled method is demonstrated using three-dimensional unstructured meshes of up to O(10 7) tetrahedral cells.more » Convergence of ALE-AMR solutions towards both uniform fine mesh ALE results and analytic solutions is demonstrated. Speed-ups of 5-10× for a given level of error are observed relative to uniform fine mesh calculations.« less

A coupled ALE-AMR method for shock hydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waltz, J.; Bakosi, J.

We present a numerical method combining adaptive mesh refinement (AMR) with arbitrary Lagrangian-Eulerian (ALE) mesh motion for the simulation of shock hydrodynamics on unstructured grids. The primary goal of the coupled method is to use AMR to reduce numerical error in ALE simulations at reduced computational expense relative to uniform fine mesh calculations, in the same manner that AMR has been used in Eulerian simulations. We also identify deficiencies with ALE methods that AMR is able to mitigate, and discuss the unique coupling challenges. The coupled method is demonstrated using three-dimensional unstructured meshes of up to O(10 7) tetrahedral cells.more » Convergence of ALE-AMR solutions towards both uniform fine mesh ALE results and analytic solutions is demonstrated. Speed-ups of 5-10× for a given level of error are observed relative to uniform fine mesh calculations.« less

Modeling Production Plant Forming Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rhee, M; Becker, R; Couch, R

2004-09-22

Engineering has simulation tools and experience in modeling forming processes. Y-12 personnel have expressed interest in validating our tools and experience against their manufacturing process activities such as rolling, casting, and forging etc. We have demonstrated numerical capabilities in a collaborative DOE/OIT project with ALCOA that is nearing successful completion. The goal was to use ALE3D to model Alcoa's slab rolling process in order to demonstrate a computational tool that would allow Alcoa to define a rolling schedule that would minimize the probability of ingot fracture, thus reducing waste and energy consumption. It is intended to lead to long-term collaborationmore » with Y-12 and perhaps involvement with other components of the weapons production complex. Using simulations to aid in design of forming processes can: decrease time to production; reduce forming trials and associated expenses; and guide development of products with greater uniformity and less scrap.« less

A method for reducing the largest relative errors in Monte Carlo iterated-fission-source calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunter, J. L.; Sutton, T. M.

2013-07-01

In Monte Carlo iterated-fission-source calculations relative uncertainties on local tallies tend to be larger in lower-power regions and smaller in higher-power regions. Reducing the largest uncertainties to an acceptable level simply by running a larger number of neutron histories is often prohibitively expensive. The uniform fission site method has been developed to yield a more spatially-uniform distribution of relative uncertainties. This is accomplished by biasing the density of fission neutron source sites while not biasing the solution. The method is integrated into the source iteration process, and does not require any auxiliary forward or adjoint calculations. For a given amountmore » of computational effort, the use of the method results in a reduction of the largest uncertainties relative to the standard algorithm. Two variants of the method have been implemented and tested. Both have been shown to be effective. (authors)« less

Ground Vehicle Convoying

NASA Astrophysics Data System (ADS)

Gage, Douglas W.; Pletta, J. Bryan

1987-01-01

Initial investigations into two different approaches for applying autonomous ground vehicle technology to the vehicle convoying application are described. A minimal capability system that would maintain desired speed and vehicle spacing while a human driver provided steering control could improve convoy performance and provide positive control at night and in inclement weather, but would not reduce driver manpower requirements. Such a system could be implemented in a modular and relatively low cost manner. A more capable system would eliminate the human driver in following vehicles and reduce manpower requirements for the transportation of supplies. This technology could also be used to aid in the deployment of teleoperated vehicles in a battlefield environment. The needs, requirements, and several proposed solutions for such an Attachable Robotic Convoy Capability (ARCC) system will be discussed. Included are discussions of sensors, communications, computers, control systems and safety issues. This advanced robotic convoy system will provide a much greater capability, but will be more difficult and expensive to implement.

Miniature Bioreactor System for Long-Term Cell Culture

NASA Technical Reports Server (NTRS)

Gonda, Steve R.; Kleis, Stanley J.; Geffert, Sandara K.

2010-01-01

A prototype miniature bioreactor system is designed to serve as a laboratory benchtop cell-culturing system that minimizes the need for relatively expensive equipment and reagents and can be operated under computer control, thereby reducing the time and effort required of human investigators and reducing uncertainty in results. The system includes a bioreactor, a fluid-handling subsystem, a chamber wherein the bioreactor is maintained in a controlled atmosphere at a controlled temperature, and associated control subsystems. The system can be used to culture both anchorage-dependent and suspension cells, which can be either prokaryotic or eukaryotic. Cells can be cultured for extended periods of time in this system, and samples of cells can be extracted and analyzed at specified intervals. By integrating this system with one or more microanalytical instrument(s), one can construct a complete automated analytical system that can be tailored to perform one or more of a large variety of assays.

Off-Design Performance of a Streamline-Traced, External-Compression Supersonic Inlet

NASA Technical Reports Server (NTRS)

Slater, John W.

2017-01-01

A computational study was performed to explore the aerodynamic performance of a streamline-traced, external-compression inlet designed for Mach 1.664 at off-design conditions of freestream Mach number, angle-of-attack, and angle-of-sideslip. Serious degradation of the inlet performance occurred for negative angles-of-attack and angles-of-sideslip greater than 3 degrees. At low subsonic speeds, the swept leading edges of the inlet created a pair of vortices that propagated to the engine face. Increasing the bluntness of the cowl lip showed no real improvement in the inlet performance at the low speeds, but did improve the inlet performance at the design conditions. Reducing the inlet flow rate improved the inlet performance, but at the likely expense of reduced thrust of the propulsion system. Deforming the cowl lip for low-speed operation of the inlet increased the inlet capture area and improved the inlet performance.

Reducing the computational footprint for real-time BCPNN learning

PubMed Central

Vogginger, Bernhard; Schüffny, René; Lansner, Anders; Cederström, Love; Partzsch, Johannes; Höppner, Sebastian

2015-01-01

The implementation of synaptic plasticity in neural simulation or neuromorphic hardware is usually very resource-intensive, often requiring a compromise between efficiency and flexibility. A versatile, but computationally-expensive plasticity mechanism is provided by the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm. Building upon Bayesian statistics, and having clear links to biological plasticity processes, the BCPNN learning rule has been applied in many fields, ranging from data classification, associative memory, reward-based learning, probabilistic inference to cortical attractor memory networks. In the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-pass-filtering stages, requiring a total of eight state variables, whose dynamics are typically simulated with the fixed step size Euler method. We derive analytic solutions allowing an efficient event-driven implementation of this learning rule. Further speedup is achieved by first rewriting the model which reduces the number of basic arithmetic operations per update to one half, and second by using look-up tables for the frequently calculated exponential decay. Ultimately, in a typical use case, the simulation using our approach is more than one order of magnitude faster than with the fixed step size Euler method. Aiming for a small memory footprint per BCPNN synapse, we also evaluate the use of fixed-point numbers for the state variables, and assess the number of bits required to achieve same or better accuracy than with the conventional explicit Euler method. All of this will allow a real-time simulation of a reduced cortex model based on BCPNN in high performance computing. More important, with the analytic solution at hand and due to the reduced memory bandwidth, the learning rule can be efficiently implemented in dedicated or existing digital neuromorphic hardware. PMID:25657618

Reducing the computational footprint for real-time BCPNN learning.

PubMed

Vogginger, Bernhard; Schüffny, René; Lansner, Anders; Cederström, Love; Partzsch, Johannes; Höppner, Sebastian

2015-01-01

The implementation of synaptic plasticity in neural simulation or neuromorphic hardware is usually very resource-intensive, often requiring a compromise between efficiency and flexibility. A versatile, but computationally-expensive plasticity mechanism is provided by the Bayesian Confidence Propagation Neural Network (BCPNN) paradigm. Building upon Bayesian statistics, and having clear links to biological plasticity processes, the BCPNN learning rule has been applied in many fields, ranging from data classification, associative memory, reward-based learning, probabilistic inference to cortical attractor memory networks. In the spike-based version of this learning rule the pre-, postsynaptic and coincident activity is traced in three low-pass-filtering stages, requiring a total of eight state variables, whose dynamics are typically simulated with the fixed step size Euler method. We derive analytic solutions allowing an efficient event-driven implementation of this learning rule. Further speedup is achieved by first rewriting the model which reduces the number of basic arithmetic operations per update to one half, and second by using look-up tables for the frequently calculated exponential decay. Ultimately, in a typical use case, the simulation using our approach is more than one order of magnitude faster than with the fixed step size Euler method. Aiming for a small memory footprint per BCPNN synapse, we also evaluate the use of fixed-point numbers for the state variables, and assess the number of bits required to achieve same or better accuracy than with the conventional explicit Euler method. All of this will allow a real-time simulation of a reduced cortex model based on BCPNN in high performance computing. More important, with the analytic solution at hand and due to the reduced memory bandwidth, the learning rule can be efficiently implemented in dedicated or existing digital neuromorphic hardware.

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

CO2, H2O, and chlorophyll fluorescence retrieved from OCO-2 measurements using a fast radiative transfer model approximating multiple scattering effects

NASA Astrophysics Data System (ADS)

Reuter, Maximilian; Bovensmann, Heinrich; Buchwitz, Michael; Burrows, John P.; Heymann, Jens; Noël, Stefan; Rozanov, Vladimir; Schneising, Oliver

2017-04-01

Carbon dioxide is the most important anthropogenic greenhouse gas. Its global increasing concentration in the Earth's atmosphere is the main driver for global climate change. In spite of its importance, there are still large uncertainties on its global sources and sinks. Satellite measurements have the potential to reduce these surface flux uncertainties. However, the demanding accuracy requirements usually involve the need for precise radiative transfer calculations in a scattering atmosphere. These can be computationally so expensive that hundreds or thousands of CPU cores are need to keep up with the data stream of an instrument like OCO-2. Future instruments will further increase the amount of soundings at least by an order of magnitude. A radiative transfer model has been developed approximating scattering effects by multiple scattering at an optically thin scattering layer reducing the computational costs by several orders of magnitude. The model can be used to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and chlorophyll fluorescence. First retrieval results for OCO-2 data will be presented.

A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method

NASA Astrophysics Data System (ADS)

Fu, Shubin; Gao, Kai

2017-11-01

Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.

Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2018-03-01

Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

48 CFR 227.7103-6 - Contract clauses.

Code of Federal Regulations, 2011 CFR

2011-10-01

... expense). Do not use the clause when the only deliverable items are computer software or computer software... architect-engineer and construction contracts. (b)(1) Use the clause at 252.227-7013 with its Alternate I in... Software Previously Delivered to the Government, in solicitations when the resulting contract will require...

48 CFR 227.7103-6 - Contract clauses.

Code of Federal Regulations, 2012 CFR

2012-10-01

... expense). Do not use the clause when the only deliverable items are computer software or computer software... architect-engineer and construction contracts. (b)(1) Use the clause at 252.227-7013 with its Alternate I in... Software Previously Delivered to the Government, in solicitations when the resulting contract will require...

A COMPUTATIONALLY EFFICIENT HYBRID APPROACH FOR DYNAMIC GAS/AEROSOL TRANSFER IN AIR QUALITY MODELS. (R826371C005)

EPA Science Inventory

Dynamic mass transfer methods have been developed to better describe the interaction of the aerosol population with semi-volatile species such as nitrate, ammonia, and chloride. Unfortunately, these dynamic methods are computationally expensive. Assumptions are often made to r...

Looking At Display Technologies

ERIC Educational Resources Information Center

Bull, Glen; Bull, Gina

2005-01-01

A projection system in a classroom with an Internet connection provides a window on the world. Until recently, projectors were expensive and difficult to maintain. Technological advances have resulted in solid-state projectors that require little maintenance and cost no more than a computer. Adding a second or third computer to a classroom…

Large-scale expensive black-box function optimization

NASA Astrophysics Data System (ADS)

Rashid, Kashif; Bailey, William; Couët, Benoît

2012-09-01

This paper presents the application of an adaptive radial basis function method to a computationally expensive black-box reservoir simulation model of many variables. An iterative proxy-based scheme is used to tune the control variables, distributed for finer control over a varying number of intervals covering the total simulation period, to maximize asset NPV. The method shows that large-scale simulation-based function optimization of several hundred variables is practical and effective.

Use of less expensive cigarettes in six cities in China: findings from the International Tobacco Control (ITC) China Survey

PubMed Central

Hyland, Andrew; Fong, Geoffrey T; Jiang, Yuan; Elton-Marshall, Tara

2010-01-01

Objective The existence of less expensive cigarettes in China may undermine public health. The aim of the current study is to examine the use of less expensive cigarettes in six cities in China. Methods Data was from the baseline wave of the International Tobacco Control (ITC) China Survey of 4815 adult urban smokers in 6 cities, conducted between April and August 2006. The percentage of smokers who reported buying less expensive cigarettes (the lowest pricing tertile within each city) at last purchase was computed. Complex sample multivariate logistic regression models were used to identify factors associated with use of less expensive cigarettes. The association between the use of less expensive cigarettes and intention to quit smoking was also examined. Results Smokers who reported buying less expensive cigarettes at last purchase tended to be older, heavier smokers, to have lower education and income, and to think more about the money spent on smoking in the last month. Smokers who bought less expensive cigarettes at the last purchase and who were less knowledgeable about the health harm of smoking were less likely to intend to quit smoking. Conclusions Measures need to be taken to minimise the price differential among cigarette brands and to increase smokers' health knowledge, which may in turn increase their intentions to quit. PMID:20935199

The Advantages of Using Technology in Second Language Education: Technology Integration in Foreign Language Teaching Demonstrates the Shift from a Behavioral to a Constructivist Learning Approach

ERIC Educational Resources Information Center

Wang, Li

2005-01-01

With the advent of networked computers and Internet technology, computer-based instruction has been widely used in language classrooms throughout the United States. Computer technologies have dramatically changed the way people gather information, conduct research and communicate with others worldwide. Considering the tremendous startup expenses,…

Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

PubMed Central

Saa, Pedro A.; Nielsen, Lars K.

2016-01-01

Motivation: Computation of steady-state flux solutions in large metabolic models is routinely performed using flux balance analysis based on a simple LP (Linear Programming) formulation. A minimal requirement for thermodynamic feasibility of the flux solution is the absence of internal loops, which are enforced using ‘loopless constraints’. The resulting loopless flux problem is a substantially harder MILP (Mixed Integer Linear Programming) problem, which is computationally expensive for large metabolic models. Results: We developed a pre-processing algorithm that significantly reduces the size of the original loopless problem into an easier and equivalent MILP problem. The pre-processing step employs a fast matrix sparsification algorithm—Fast- sparse null-space pursuit (SNP)—inspired by recent results on SNP. By finding a reduced feasible ‘loop-law’ matrix subject to known directionalities, Fast-SNP considerably improves the computational efficiency in several metabolic models running different loopless optimization problems. Furthermore, analysis of the topology encoded in the reduced loop matrix enabled identification of key directional constraints for the potential permanent elimination of infeasible loops in the underlying model. Overall, Fast-SNP is an effective and simple algorithm for efficient formulation of loop-law constraints, making loopless flux optimization feasible and numerically tractable at large scale. Availability and Implementation: Source code for MATLAB including examples is freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization uses Gurobi, CPLEX or GLPK (the latter is included with the algorithm). Contact: lars.nielsen@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27559155

Recent advances in QM/MM free energy calculations using reference potentials.

PubMed

Duarte, Fernanda; Amrein, Beat A; Blaha-Nelson, David; Kamerlin, Shina C L

2015-05-01

Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014. Published by Elsevier B.V.

Two-phase strategy of controlling motor coordination determined by task performance optimality.

PubMed

Shimansky, Yury P; Rand, Miya K

2013-02-01

A quantitative model of optimal coordination between hand transport and grip aperture has been derived in our previous studies of reach-to-grasp movements without utilizing explicit knowledge of the optimality criterion or motor plant dynamics. The model's utility for experimental data analysis has been demonstrated. Here we show how to generalize this model for a broad class of reaching-type, goal-directed movements. The model allows for measuring the variability of motor coordination and studying its dependence on movement phase. The experimentally found characteristics of that dependence imply that execution noise is low and does not affect motor coordination significantly. From those characteristics it is inferred that the cost of neural computations required for information acquisition and processing is included in the criterion of task performance optimality as a function of precision demand for state estimation and decision making. The precision demand is an additional optimized control variable that regulates the amount of neurocomputational resources activated dynamically. It is shown that an optimal control strategy in this case comprises two different phases. During the initial phase, the cost of neural computations is significantly reduced at the expense of reducing the demand for their precision, which results in speed-accuracy tradeoff violation and significant inter-trial variability of motor coordination. During the final phase, neural computations and thus motor coordination are considerably more precise to reduce the cost of errors in making a contact with the target object. The generality of the optimal coordination model and the two-phase control strategy is illustrated on several diverse examples.

Robust simulation of buckled structures using reduced order modeling

NASA Astrophysics Data System (ADS)

Wiebe, R.; Perez, R. A.; Spottswood, S. M.

2016-09-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

Enhancement of DFT-calculations at petascale: Nuclear Magnetic Resonance, Hybrid Density Functional Theory and Car-Parrinello calculations

NASA Astrophysics Data System (ADS)

Varini, Nicola; Ceresoli, Davide; Martin-Samos, Layla; Girotto, Ivan; Cavazzoni, Carlo

2013-08-01

One of the most promising techniques used for studying the electronic properties of materials is based on Density Functional Theory (DFT) approach and its extensions. DFT has been widely applied in traditional solid state physics problems where periodicity and symmetry play a crucial role in reducing the computational workload. With growing compute power capability and the development of improved DFT methods, the range of potential applications is now including other scientific areas such as Chemistry and Biology. However, cross disciplinary combinations of traditional Solid-State Physics, Chemistry and Biology drastically improve the system complexity while reducing the degree of periodicity and symmetry. Large simulation cells containing of hundreds or even thousands of atoms are needed to model these kind of physical systems. The treatment of those systems still remains a computational challenge even with modern supercomputers. In this paper we describe our work to improve the scalability of Quantum ESPRESSO (Giannozzi et al., 2009 [3]) for treating very large cells and huge numbers of electrons. To this end we have introduced an extra level of parallelism, over electronic bands, in three kernels for solving computationally expensive problems: the Sternheimer equation solver (Nuclear Magnetic Resonance, package QE-GIPAW), the Fock operator builder (electronic ground-state, package PWscf) and most of the Car-Parrinello routines (Car-Parrinello dynamics, package CP). Final benchmarks show our success in computing the Nuclear Magnetic Response (NMR) chemical shift of a large biological assembly, the electronic structure of defected amorphous silica with hybrid exchange-correlation functionals and the equilibrium atomic structure of height Porphyrins anchored to a Carbon Nanotube, on many thousands of CPU cores.

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

Joint Model and Parameter Dimension Reduction for Bayesian Inversion Applied to an Ice Sheet Flow Problem

NASA Astrophysics Data System (ADS)

Ghattas, O.; Petra, N.; Cui, T.; Marzouk, Y.; Benjamin, P.; Willcox, K.

2016-12-01

Model-based projections of the dynamics of the polar ice sheets play a central role in anticipating future sea level rise. However, a number of mathematical and computational challenges place significant barriers on improving predictability of these models. One such challenge is caused by the unknown model parameters (e.g., in the basal boundary conditions) that must be inferred from heterogeneous observational data, leading to an ill-posed inverse problem and the need to quantify uncertainties in its solution. In this talk we discuss the problem of estimating the uncertainty in the solution of (large-scale) ice sheet inverse problems within the framework of Bayesian inference. Computing the general solution of the inverse problem--i.e., the posterior probability density--is intractable with current methods on today's computers, due to the expense of solving the forward model (3D full Stokes flow with nonlinear rheology) and the high dimensionality of the uncertain parameters (which are discretizations of the basal sliding coefficient field). To overcome these twin computational challenges, it is essential to exploit problem structure (e.g., sensitivity of the data to parameters, the smoothing property of the forward model, and correlations in the prior). To this end, we present a data-informed approach that identifies low-dimensional structure in both parameter space and the forward model state space. This approach exploits the fact that the observations inform only a low-dimensional parameter space and allows us to construct a parameter-reduced posterior. Sampling this parameter-reduced posterior still requires multiple evaluations of the forward problem, therefore we also aim to identify a low dimensional state space to reduce the computational cost. To this end, we apply a proper orthogonal decomposition (POD) approach to approximate the state using a low-dimensional manifold constructed using ``snapshots'' from the parameter reduced posterior, and the discrete empirical interpolation method (DEIM) to approximate the nonlinearity in the forward problem. We show that using only a limited number of forward solves, the resulting subspaces lead to an efficient method to explore the high-dimensional posterior.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Chang, Siyuan; Luo, Haoxiang; Luo's lab Team

2016-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which is often needed in procedures such as optimization and parameter estimation. In this work, we study the performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin. Supported by the NSF.

Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices

NASA Astrophysics Data System (ADS)

Morin, B.; Legay, A.; Deü, J.-F.

2016-09-01

In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.

The Chemical Engineer's Toolbox: A Glass Box Approach to Numerical Problem Solving

ERIC Educational Resources Information Center

Coronell, Daniel G.; Hariri, M. Hossein

2009-01-01

Computer programming in undergraduate engineering education all too often begins and ends with the freshman programming course. Improvements in computer technology and curriculum revision have improved this situation, but often at the expense of the students' learning due to the use of commercial "black box" software. This paper describes the…

Superintendents' Perceptions of 1:1 Initiative Implementation and Sustainability

ERIC Educational Resources Information Center

Cole, Bobby Virgil, Jr.; Sauers, Nicholas J.

2018-01-01

One of the fastest growing, most discussed, and most expensive technology initiatives over the last decade has been one-to-one (1:1) computing initiatives. The purpose of this study was to examine key factors that influenced implementing and sustaining 1:1 computing initiatives from the perspective of school superintendents. Nine superintendents…

Data Bases at a State Institution--Costs, Uses and Needs. AIR Forum Paper 1978.

ERIC Educational Resources Information Center

McLaughlin, Gerald W.

The cost-benefit of administrative data at a state college is placed in perspective relative to the institutional involvement in computer use. The costs of computer operations, personnel, and peripheral equipment expenses related to instruction are analyzed. Data bases and systems support institutional activities, such as registration, and aid…

Film Library Information Management System.

ERIC Educational Resources Information Center

Minnella, C. Vincent; And Others

The computer program described not only allows the user to determine rental sources for a particular film title quickly, but also to select the least expensive of the sources. This program developed at SUNY Cortland's Sperry Learning Resources Center and Computer Center is designed to maintain accurate data on rental and purchase films in both…

Estimating Angle-of-Arrival and Time-of-Flight for Multipath Components Using WiFi Channel State Information.

PubMed

Ahmed, Afaz Uddin; Arablouei, Reza; Hoog, Frank de; Kusy, Branislav; Jurdak, Raja; Bergmann, Neil

2018-05-29

Channel state information (CSI) collected during WiFi packet transmissions can be used for localization of commodity WiFi devices in indoor environments with multipath propagation. To this end, the angle of arrival (AoA) and time of flight (ToF) for all dominant multipath components need to be estimated. A two-dimensional (2D) version of the multiple signal classification (MUSIC) algorithm has been shown to solve this problem using 2D grid search, which is computationally expensive and is therefore not suited for real-time localisation. In this paper, we propose using a modified matrix pencil (MMP) algorithm instead. Specifically, we show that the AoA and ToF estimates can be found independently of each other using the one-dimensional (1D) MMP algorithm and the results can be accurately paired to obtain the AoA⁻ToF pairs for all multipath components. Thus, the 2D estimation problem reduces to running 1D estimation multiple times, substantially reducing the computational complexity. We identify and resolve the problem of degenerate performance when two or more multipath components have the same AoA. In addition, we propose a packet aggregation model that uses the CSI data from multiple packets to improve the performance under noisy conditions. Simulation results show that our algorithm achieves two orders of magnitude reduction in the computational time over the 2D MUSIC algorithm while achieving similar accuracy. High accuracy and low computation complexity of our approach make it suitable for applications that require location estimation to run on resource-constrained embedded devices in real time.

Efficient Data-Worth Analysis Using a Multilevel Monte Carlo Method Applied in Oil Reservoir Simulations

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Evans, K. J.

2017-12-01

Data-worth analysis plays an essential role in improving the understanding of the subsurface system, in developing and refining subsurface models, and in supporting rational water resources management. However, data-worth analysis is computationally expensive as it requires quantifying parameter uncertainty, prediction uncertainty, and both current and potential data uncertainties. Assessment of these uncertainties in large-scale stochastic subsurface simulations using standard Monte Carlo (MC) sampling or advanced surrogate modeling is extremely computationally intensive, sometimes even infeasible. In this work, we propose efficient Bayesian analysis of data-worth using a multilevel Monte Carlo (MLMC) method. Compared to the standard MC that requires a significantly large number of high-fidelity model executions to achieve a prescribed accuracy in estimating expectations, the MLMC can substantially reduce the computational cost with the use of multifidelity approximations. As the data-worth analysis involves a great deal of expectation estimations, the cost savings from MLMC in the assessment can be very outstanding. While the proposed MLMC-based data-worth analysis is broadly applicable, we use it to a highly heterogeneous oil reservoir simulation to select an optimal candidate data set that gives the largest uncertainty reduction in predicting mass flow rates at four production wells. The choices made by the MLMC estimation are validated by the actual measurements of the potential data, and consistent with the estimation obtained from the standard MC. But compared to the standard MC, the MLMC greatly reduces the computational costs in the uncertainty reduction estimation, with up to 600 days cost savings when one processor is used.

Formation of algae growth constitutive relations for improved algae modeling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gharagozloo, Patricia E.; Drewry, Jessica Louise.

This SAND report summarizes research conducted as a part of a two year Laboratory Directed Research and Development (LDRD) project to improve our abilities to model algal cultivation. Algae-based biofuels have generated much excitement due to their potentially large oil yield from relatively small land use and without interfering with the food or water supply. Algae mitigate atmospheric CO2 through metabolism. Efficient production of algal biofuels could reduce dependence on foreign oil by providing a domestic renewable energy source. Important factors controlling algal productivity include temperature, nutrient concentrations, salinity, pH, and the light-to-biomass conversion rate. Computational models allow for inexpensivemore » predictions of algae growth kinetics in these non-ideal conditions for various bioreactor sizes and geometries without the need for multiple expensive measurement setups. However, these models need to be calibrated for each algal strain. In this work, we conduct a parametric study of key marine algae strains and apply the findings to a computational model.« less

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Linear chirp phase perturbing approach for finding binary phased codes

NASA Astrophysics Data System (ADS)

Li, Bing C.

2017-05-01

Binary phased codes have many applications in communication and radar systems. These applications require binary phased codes to have low sidelobes in order to reduce interferences and false detection. Barker codes are the ones that satisfy these requirements and they have lowest maximum sidelobes. However, Barker codes have very limited code lengths (equal or less than 13) while many applications including low probability of intercept radar, and spread spectrum communication, require much higher code lengths. The conventional techniques of finding binary phased codes in literatures include exhaust search, neural network, and evolutionary methods, and they all require very expensive computation for large code lengths. Therefore these techniques are limited to find binary phased codes with small code lengths (less than 100). In this paper, by analyzing Barker code, linear chirp, and P3 phases, we propose a new approach to find binary codes. Experiments show that the proposed method is able to find long low sidelobe binary phased codes (code length >500) with reasonable computational cost.

Extreme-Scale Stochastic Particle Tracing for Uncertain Unsteady Flow Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Hanqi; He, Wenbin; Seo, Sangmin

2016-11-13

We present an efficient and scalable solution to estimate uncertain transport behaviors using stochastic flow maps (SFM,) for visualizing and analyzing uncertain unsteady flows. SFM computation is extremely expensive because it requires many Monte Carlo runs to trace densely seeded particles in the flow. We alleviate the computational cost by decoupling the time dependencies in SFMs so that we can process adjacent time steps independently and then compose them together for longer time periods. Adaptive refinement is also used to reduce the number of runs for each location. We then parallelize over tasks—packets of particles in our design—to achieve highmore » efficiency in MPI/thread hybrid programming. Such a task model also enables CPU/GPU coprocessing. We show the scalability on two supercomputers, Mira (up to 1M Blue Gene/Q cores) and Titan (up to 128K Opteron cores and 8K GPUs), that can trace billions of particles in seconds.« less

Distributed Observer Network

NASA Technical Reports Server (NTRS)

2008-01-01

NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

Placement of clock gates in time-of-flight optoelectronic circuits

NASA Astrophysics Data System (ADS)

Feehrer, John R.; Jordan, Harry F.

1995-12-01

Time-of-flight synchronized optoelectronic circuits capitalize on the highly controllable delays of optical waveguides. Circuits have no latches; synchronization is achieved by adjustment of the lengths of waveguides that connect circuit elements. Clock gating and pulse stretching are used to restore timing and power. A functional circuit requires that every feedback loop contain at least one clock gate to prevent cumulative timing drift and power loss. A designer specifies an ideal circuit, which contains no or very few clock gates. To make the circuit functional, we must identify locations in which to place clock gates. Because clock gates are expensive, add area, and increase delay, a minimal set of locations is desired. We cast this problem in graph-theoretical form as the minimum feedback edge set problem and solve it by using an adaptation of an algorithm proposed in 1966 [IEEE Trans. Circuit Theory CT-13, 399 (1966)]. We discuss a computer-aided-design implementation of the algorithm that reduces computational complexity and demonstrate it on a set of circuits.

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

PubMed

Gonzalez-Dominguez, Jorge; Martin, Maria J

2017-10-10

In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

Elders' nonadherence, its assessment, and computer assisted instruction for medication recall training.

PubMed

Leirer, V O; Morrow, D G; Pariante, G M; Sheikh, J I

1988-10-01

This study investigates three questions related to the problem of medication nonadherence among elders. First, does recall failure play a significant role in nonadherence? Recent research suggests that it may not. Second, can the new portable bar code scanner technology be used to study nonadherence? Other forms of monitoring are obtrusive or inaccurate. Finally, can inexpensive computer assisted instructions (CAI) be used to teach mnemonic techniques specifically designed to improve medication schedule recall? Current research on memory training teaches nonspecific mnemonics and uses the expensive classroom approach. Results of the present study suggest that physically active and cognitively alert elders do have significant nonadherence (control group = 32.0%) problems related to forgetting and that CAI courseware can significantly reduce (medication recall training group = 10.0%) this form of nonadherence. Portable bar code technology proved easy to use by elderly patients and provided detailed information about the type of forgetting underlying nonadherence. Most significant recall failure was in the complete forgetting to take medication rather than delays in medicating or overmedicating.

Nonlinear Dynamic Model-Based Multiobjective Sensor Network Design Algorithm for a Plant with an Estimator-Based Control System

DOE PAGES

Paul, Prokash; Bhattacharyya, Debangsu; Turton, Richard; ...

2017-06-06

Here, a novel sensor network design (SND) algorithm is developed for maximizing process efficiency while minimizing sensor network cost for a nonlinear dynamic process with an estimator-based control system. The multiobjective optimization problem is solved following a lexicographic approach where the process efficiency is maximized first followed by minimization of the sensor network cost. The partial net present value, which combines the capital cost due to the sensor network and the operating cost due to deviation from the optimal efficiency, is proposed as an alternative objective. The unscented Kalman filter is considered as the nonlinear estimator. The large-scale combinatorial optimizationmore » problem is solved using a genetic algorithm. The developed SND algorithm is applied to an acid gas removal (AGR) unit as part of an integrated gasification combined cycle (IGCC) power plant with CO 2 capture. Due to the computational expense, a reduced order nonlinear model of the AGR process is identified and parallel computation is performed during implementation.« less

Model reduction by trimming for a class of semi-Markov reliability models and the corresponding error bound

NASA Technical Reports Server (NTRS)

White, Allan L.; Palumbo, Daniel L.

1991-01-01

Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.

Response Matrix Monte Carlo for electron transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ballinger, C.T.; Nielsen, D.E. Jr.; Rathkopf, J.A.

1990-11-01

A Response Matrix Monte Carol (RMMC) method has been developed for solving electron transport problems. This method was born of the need to have a reliable, computationally efficient transport method for low energy electrons (below a few hundred keV) in all materials. Today, condensed history methods are used which reduce the computation time by modeling the combined effect of many collisions but fail at low energy because of the assumptions required to characterize the electron scattering. Analog Monte Carlo simulations are prohibitively expensive since electrons undergo coulombic scattering with little state change after a collision. The RMMC method attempts tomore » combine the accuracy of an analog Monte Carlo simulation with the speed of the condensed history methods. The combined effect of many collisions is modeled, like condensed history, except it is precalculated via an analog Monte Carol simulation. This avoids the scattering kernel assumptions associated with condensed history methods. Results show good agreement between the RMMC method and analog Monte Carlo. 11 refs., 7 figs., 1 tabs.« less

Random-subset fitting of digital holograms for fast three-dimensional particle tracking [invited].

PubMed

Dimiduk, Thomas G; Perry, Rebecca W; Fung, Jerome; Manoharan, Vinothan N

2014-09-20

Fitting scattering solutions to time series of digital holograms is a precise way to measure three-dimensional dynamics of microscale objects such as colloidal particles. However, this inverse-problem approach is computationally expensive. We show that the computational time can be reduced by an order of magnitude or more by fitting to a random subset of the pixels in a hologram. We demonstrate our algorithm on experimentally measured holograms of micrometer-scale colloidal particles, and we show that 20-fold increases in speed, relative to fitting full frames, can be attained while introducing errors in the particle positions of 10 nm or less. The method is straightforward to implement and works for any scattering model. It also enables a parallelization strategy wherein random-subset fitting is used to quickly determine initial guesses that are subsequently used to fit full frames in parallel. This approach may prove particularly useful for studying rare events, such as nucleation, that can only be captured with high frame rates over long times.

Visual Navigation - SARE Mission

NASA Technical Reports Server (NTRS)

Alonso, Roberto; Kuba, Jose; Caruso, Daniel

2007-01-01

The SARE Earth Observing and Technological Mission is part of the Argentinean Space Agency (CONAE - Comision Nacional de Actividades Espaciales) Small and Technological Payloads Program. The Argentinean National Space Program requires from the SARE program mission to test in a real environment of several units, assemblies and components to reduce the risk of using these equipments in more expensive Space Missions. The objective is to make use those components with an acceptable maturity in design or development, but without any heritage at space. From the application point of view, this mission offers new products in the Earth Observation data market which are listed in the present paper. One of the technological payload on board of the SARE satellite is the sensor Ground Tracker. It computes the satellite attitude and orbit in real time (goal) and/or by ground processing. For the first operating mode a dedicated computer and mass memory are necessary to be part of the mentioned sensor. For the second operational mode the hardware and software are much simpler.

Real-time autocorrelator for fluorescence correlation spectroscopy based on graphical-processor-unit architecture: method, implementation, and comparative studies

NASA Astrophysics Data System (ADS)

Laracuente, Nicholas; Grossman, Carl

2013-03-01

We developed an algorithm and software to calculate autocorrelation functions from real-time photon-counting data using the fast, parallel capabilities of graphical processor units (GPUs). Recent developments in hardware and software have allowed for general purpose computing with inexpensive GPU hardware. These devices are more suited for emulating hardware autocorrelators than traditional CPU-based software applications by emphasizing parallel throughput over sequential speed. Incoming data are binned in a standard multi-tau scheme with configurable points-per-bin size and are mapped into a GPU memory pattern to reduce time-expensive memory access. Applications include dynamic light scattering (DLS) and fluorescence correlation spectroscopy (FCS) experiments. We ran the software on a 64-core graphics pci card in a 3.2 GHz Intel i5 CPU based computer running Linux. FCS measurements were made on Alexa-546 and Texas Red dyes in a standard buffer (PBS). Software correlations were compared to hardware correlator measurements on the same signals. Supported by HHMI and Swarthmore College

An adaptive tau-leaping method for stochastic simulations of reaction-diffusion systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padgett, Jill M. A.; Ilie, Silvana, E-mail: silvana@ryerson.ca

2016-03-15

Stochastic modelling is critical for studying many biochemical processes in a cell, in particular when some reacting species have low population numbers. For many such cellular processes the spatial distribution of the molecular species plays a key role. The evolution of spatially heterogeneous biochemical systems with some species in low amounts is accurately described by the mesoscopic model of the Reaction-Diffusion Master Equation. The Inhomogeneous Stochastic Simulation Algorithm provides an exact strategy to numerically solve this model, but it is computationally very expensive on realistic applications. We propose a novel adaptive time-stepping scheme for the tau-leaping method for approximating themore » solution of the Reaction-Diffusion Master Equation. This technique combines effective strategies for variable time-stepping with path preservation to reduce the computational cost, while maintaining the desired accuracy. The numerical tests on various examples arising in applications show the improved efficiency achieved by the new adaptive method.« less

Efficient Multiple Kernel Learning Algorithms Using Low-Rank Representation.

PubMed

Niu, Wenjia; Xia, Kewen; Zu, Baokai; Bai, Jianchuan

2017-01-01

Unlike Support Vector Machine (SVM), Multiple Kernel Learning (MKL) allows datasets to be free to choose the useful kernels based on their distribution characteristics rather than a precise one. It has been shown in the literature that MKL holds superior recognition accuracy compared with SVM, however, at the expense of time consuming computations. This creates analytical and computational difficulties in solving MKL algorithms. To overcome this issue, we first develop a novel kernel approximation approach for MKL and then propose an efficient Low-Rank MKL (LR-MKL) algorithm by using the Low-Rank Representation (LRR). It is well-acknowledged that LRR can reduce dimension while retaining the data features under a global low-rank constraint. Furthermore, we redesign the binary-class MKL as the multiclass MKL based on pairwise strategy. Finally, the recognition effect and efficiency of LR-MKL are verified on the datasets Yale, ORL, LSVT, and Digit. Experimental results show that the proposed LR-MKL algorithm is an efficient kernel weights allocation method in MKL and boosts the performance of MKL largely.

An Innovative Infrastructure with a Universal Geo-Spatiotemporal Data Representation Supporting Cost-Effective Integration of Diverse Earth Science Data

NASA Technical Reports Server (NTRS)

Rilee, Michael Lee; Kuo, Kwo-Sen

2017-01-01

The SpatioTemporal Adaptive Resolution Encoding (STARE) is a unifying scheme encoding geospatial and temporal information for organizing data on scalable computing/storage resources, minimizing expensive data transfers. STARE provides a compact representation that turns set-logic functions into integer operations, e.g. conditional sub-setting, taking into account representative spatiotemporal resolutions of the data in the datasets. STARE geo-spatiotemporally aligns data placements of diverse data on massive parallel resources to maximize performance. Automating important scientific functions (e.g. regridding) and computational functions (e.g. data placement) allows scientists to focus on domain-specific questions instead of expending their efforts and expertise on data processing. With STARE-enabled automation, SciDB (Scientific Database) plus STARE provides a database interface, reducing costly data preparation, increasing the volume and variety of interoperable data, and easing result sharing. Using SciDB plus STARE as part of an integrated analysis infrastructure dramatically eases combining diametrically different datasets.

A modeling study of the time-averaged electric currents in the vicinity of isolated thunderstorms

NASA Technical Reports Server (NTRS)

Driscoll, Kevin T.; Blakeslee, Richard J.; Baginski, Michael E.

1992-01-01

A thorough examination of the results of a time-dependent computer model of a dipole thunderstorm revealed that there are numerous similarities between the time-averaged electrical properties and the steady-state properties of an active thunderstorm. Thus, the electrical behavior of the atmosphere in the vicinity of a thunderstorm can be determined with a formulation similar to what was first described by Holzer and Saxon (1952). From the Maxwell continuity equation of electric current, a simple analytical equation was derived that expresses a thunderstorm's average current contribution to the global electric circuit in terms of the generator current within the thundercloud, the intracloud lightning current, the cloud-to-ground lightning current, the altitudes of the charge centers, and the conductivity profile of the atmosphere. This equation was found to be nearly as accurate as the more computationally expensive numerical model, even when it is applied to a thunderstorm with a reduced conductivity thundercloud, a time-varying generator current, a varying flash rate, and a changing lightning mix.

Data Structures for Extreme Scale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kahan, Simon

As computing problems of national importance grow, the government meets the increased demand by funding the development of ever larger systems. The overarching goal of the work supported in part by this grant is to increase efficiency of programming and performing computations on these large computing systems. In past work, we have demonstrated that some of these computations once thought to require expensive hardware designs and/or complex, special-purpose programming may be executed efficiently on low-cost commodity cluster computing systems using a general-purpose “latency-tolerant” programming framework. One important developed application of the ideas underlying this framework is graph database technology supportingmore » social network pattern matching used by US intelligence agencies to more quickly identify potential terrorist threats. This database application has been spun out by the Pacific Northwest National Laboratory, a Department of Energy Laboratory, into a commercial start-up, Trovares Inc. We explore an alternative application of the same underlying ideas to a well-studied challenge arising in engineering: solving unstructured sparse linear equations. Solving these equations is key to predicting the behavior of large electronic circuits before they are fabricated. Predicting that behavior ahead of fabrication means that designs can optimized and errors corrected ahead of the expense of manufacture.« less

Household catastrophic medical expenses in eastern China: determinants and policy implications

PubMed Central

2013-01-01

Background Much of research on household catastrophic medical expenses in China has focused on less developed areas and little is known about this problem in more developed areas. This study aimed to analyse the incidence and determinants of catastrophic medical expenses in eastern China. Methods Data were obtained from a health care utilization and expense survey of 11,577 households conducted in eastern China in 2008. The incidence of household catastrophic medical expenses was calculated using the method introduced by the World Health Organization. A multi-level logistic regression model was used to identify the determinants. Results The incidence of household catastrophic medical expenses in eastern China ranged from 9.24% to 24.79%. Incidence of household catastrophic medical expenses was lower if the head of household had a higher level of education, labor insurance coverage, while the incidence was higher if they lived in rural areas, had a family member with chronic diseases, had a child younger than 5 years old, had a person at home who was at least 65 years old, and had a household member who was hospitalized. Moreover, the impact of the economic level on catastrophic medical expenses was non-linear. The poorest group had a lower incidence than that of the second lowest income group and the group with the highest income had a higher incidence than that of the second highest income group. In addition, region was a significant determinant. Conclusions Reducing the incidence of household catastrophic medical expenses should be one of the priorities of health policy. It can be achieved by improving residents’ health status to reduce avoidable health services such as hospitalization. It is also important to design more targeted health insurance in order to increase financial support for such vulnerable groups as the poor, chronically ill, children, and senior populations. PMID:24308317

Variable-Complexity Multidisciplinary Optimization on Parallel Computers

NASA Technical Reports Server (NTRS)

Grossman, Bernard; Mason, William H.; Watson, Layne T.; Haftka, Raphael T.

1998-01-01

This report covers work conducted under grant NAG1-1562 for the NASA High Performance Computing and Communications Program (HPCCP) from December 7, 1993, to December 31, 1997. The objective of the research was to develop new multidisciplinary design optimization (MDO) techniques which exploit parallel computing to reduce the computational burden of aircraft MDO. The design of the High-Speed Civil Transport (HSCT) air-craft was selected as a test case to demonstrate the utility of our MDO methods. The three major tasks of this research grant included: development of parallel multipoint approximation methods for the aerodynamic design of the HSCT, use of parallel multipoint approximation methods for structural optimization of the HSCT, mathematical and algorithmic development including support in the integration of parallel computation for items (1) and (2). These tasks have been accomplished with the development of a response surface methodology that incorporates multi-fidelity models. For the aerodynamic design we were able to optimize with up to 20 design variables using hundreds of expensive Euler analyses together with thousands of inexpensive linear theory simulations. We have thereby demonstrated the application of CFD to a large aerodynamic design problem. For the predicting structural weight we were able to combine hundreds of structural optimizations of refined finite element models with thousands of optimizations based on coarse models. Computations have been carried out on the Intel Paragon with up to 128 nodes. The parallel computation allowed us to perform combined aerodynamic-structural optimization using state of the art models of a complex aircraft configurations.

Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

PubMed Central

Chalmers, Eric; Luczak, Artur; Gruber, Aaron J.

2016-01-01

The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL) to guide “goal-directed” behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals' ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, “forward sweeps” through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort) required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks. PMID:28018203

Camera processing with chromatic aberration.

PubMed

Korneliussen, Jan Tore; Hirakawa, Keigo

2014-10-01

Since the refractive index of materials commonly used for lens depends on the wavelengths of light, practical camera optics fail to converge light to a single point on an image plane. Known as chromatic aberration, this phenomenon distorts image details by introducing magnification error, defocus blur, and color fringes. Though achromatic and apochromatic lens designs reduce chromatic aberration to a degree, they are complex and expensive and they do not offer a perfect correction. In this paper, we propose a new postcapture processing scheme designed to overcome these problems computationally. Specifically, the proposed solution is comprised of chromatic aberration-tolerant demosaicking algorithm and post-demosaicking chromatic aberration correction. Experiments with simulated and real sensor data verify that the chromatic aberration is effectively corrected.

Applying Virtual Reality to commercial Edutainment

NASA Technical Reports Server (NTRS)

Grissom, F.; Goza, Sharon P.; Goza, S. Michael

1994-01-01

Virtual reality (VR) when defined as a computer generated, immersive, three dimensional graphics environment which provides varying degrees of interactivity, remains an expensive, highly specialized application, yet to find its way into the school, home, or business. As a novel approach to a theme park-type attraction, though, its use can be justified. This paper describes how a virtual reality 'tour of the human digestive system' was created for the Omniplex Science Museum of Oklahoma City, Oklahoma. The customers main objectives were: (1) to educate; (2) to entertain; (3) to draw visitors; and (4) to generate revenue. The 'Edutainment' system ultimately delivered met these goals. As more such systems come into existence the resulting library of licensable programs will greatly reduce development costs to individual institutions.

Gas dynamic improvement of the axial compressor design for reduction of the flow non-uniformity level

NASA Astrophysics Data System (ADS)

Matveev, V. N.; Baturin, O. V.; Kolmakova, D. A.; Popov, G. M.

2017-01-01

Circumferential nonuniformity of gas flow is one of the main problems in the gas turbine engine. Usually, the flow circumferential nonuniformity appears near the annular frame located in the flow passage of the engine. The presence of circumferential nonuniformity leads to the increased dynamic stresses in the blade rows and the blade damage. The goal of this research was to find the ways of the flow non-uniformity reduction, which would not require a fundamental changing of the engine design. A new method for reducing the circumferential nonuniformity of the gas flow was proposed that allows the prediction of the pressure peak values of the rotor blades without computationally expensive CFD calculations.

Evaluation of Rutter Sigma S6 Ice Navigation Radar on USCGC Healy during Arctic Shield 2014

DTIC Science & Technology

2015-03-01

useful in making decisions about the pressure ridges ahead of time instead of making an immediate decision. Figure 33. CG radar display of... use the radar to help chart an efficient path through an ice field to reduce transit time and fuel expenses. This includes a clear picture of the ice...a ship would be able to use the radar to help chart an efficient path through an ice field to reduce transit time and fuel expenses. This includes

An Analytical Solution for Yaw Maneuver Optimization on the International Space Station and Other Orbiting Space Vehicles

NASA Technical Reports Server (NTRS)

Dobrinskaya, Tatiana

2015-01-01

This paper suggests a new method for optimizing yaw maneuvers on the International Space Station (ISS). Yaw rotations are the most common large maneuvers on the ISS often used for docking and undocking operations, as well as for other activities. When maneuver optimization is used, large maneuvers, which were performed on thrusters, could be performed either using control moment gyroscopes (CMG), or with significantly reduced thruster firings. Maneuver optimization helps to save expensive propellant and reduce structural loads - an important factor for the ISS service life. In addition, optimized maneuvers reduce contamination of the critical elements of the vehicle structure, such as solar arrays. This paper presents an analytical solution for optimizing yaw attitude maneuvers. Equations describing pitch and roll motion needed to counteract the major torques during a yaw maneuver are obtained. A yaw rate profile is proposed. Also the paper describes the physical basis of the suggested optimization approach. In the obtained optimized case, the torques are significantly reduced. This torque reduction was compared to the existing optimization method which utilizes the computational solution. It was shown that the attitude profiles and the torque reduction have a good match for these two methods of optimization. The simulations using the ISS flight software showed similar propellant consumption for both methods. The analytical solution proposed in this paper has major benefits with respect to computational approach. In contrast to the current computational solution, which only can be calculated on the ground, the analytical solution does not require extensive computational resources, and can be implemented in the onboard software, thus, making the maneuver execution automatic. The automatic maneuver significantly simplifies the operations and, if necessary, allows to perform a maneuver without communication with the ground. It also reduces the probability of command errors. The suggested analytical solution provides a new method of maneuver optimization which is less complicated, automatic and more universal. A maneuver optimization approach, presented in this paper, can be used not only for the ISS, but for other orbiting space vehicles.

Expert Systems In Medical Studies - A New Twist

NASA Astrophysics Data System (ADS)

Slagle, James R.; Long, John M.; Wick, Michael R.; Matts, John P.; Leon, Arthur S.

1986-03-01

The use of experts to evaluate large amounts of trial data results in increasingly expensive and time consuming research. We are investigating the role expert systems can play in reducing the time and expense of research projects. Current methods in large clinical studies for evaluating data are often crude and superficial. We have developed, for a large clinical trial, an expert system for analysis of treadmill exercise ECG test results. In the cases we are studying, a patient is given a treadmill exercise ECG test once a year for five years. Pairs of these exercise tests are then evaluated by cardiologists to determine the condition of the patient's heart. The results of our system show great promise for the use of expert systems in reducing the time and expense of large clinical trials.

Systematic comparison of the behaviors produced by computational models of epileptic neocortex.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warlaumont, A. S.; Lee, H. C.; Benayoun, M.

2010-12-01

Two existing models of brain dynamics in epilepsy, one detailed (i.e., realistic) and one abstract (i.e., simplified) are compared in terms of behavioral range and match to in vitro mouse recordings. A new method is introduced for comparing across computational models that may have very different forms. First, high-level metrics were extracted from model and in vitro output time series. A principal components analysis was then performed over these metrics to obtain a reduced set of derived features. These features define a low-dimensional behavior space in which quantitative measures of behavioral range and degree of match to real data canmore » be obtained. The detailed and abstract models and the mouse recordings overlapped considerably in behavior space. Both the range of behaviors and similarity to mouse data were similar between the detailed and abstract models. When no high-level metrics were used and principal components analysis was computed over raw time series, the models overlapped minimally with the mouse recordings. The method introduced here is suitable for comparing across different kinds of model data and across real brain recordings. It appears that, despite differences in form and computational expense, detailed and abstract models do not necessarily differ in their behaviors.« less

An active learning representative subset selection method using net analyte signal.

PubMed

He, Zhonghai; Ma, Zhenhe; Luan, Jingmin; Cai, Xi

2018-05-05

To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced. Copyright © 2018 Elsevier B.V. All rights reserved.

Cloud CPFP: a shotgun proteomics data analysis pipeline using cloud and high performance computing.

PubMed

Trudgian, David C; Mirzaei, Hamid

2012-12-07

We have extended the functionality of the Central Proteomics Facilities Pipeline (CPFP) to allow use of remote cloud and high performance computing (HPC) resources for shotgun proteomics data processing. CPFP has been modified to include modular local and remote scheduling for data processing jobs. The pipeline can now be run on a single PC or server, a local cluster, a remote HPC cluster, and/or the Amazon Web Services (AWS) cloud. We provide public images that allow easy deployment of CPFP in its entirety in the AWS cloud. This significantly reduces the effort necessary to use the software, and allows proteomics laboratories to pay for compute time ad hoc, rather than obtaining and maintaining expensive local server clusters. Alternatively the Amazon cloud can be used to increase the throughput of a local installation of CPFP as necessary. We demonstrate that cloud CPFP allows users to process data at higher speed than local installations but with similar cost and lower staff requirements. In addition to the computational improvements, the web interface to CPFP is simplified, and other functionalities are enhanced. The software is under active development at two leading institutions and continues to be released under an open-source license at http://cpfp.sourceforge.net.

An active learning representative subset selection method using net analyte signal

NASA Astrophysics Data System (ADS)

He, Zhonghai; Ma, Zhenhe; Luan, Jingmin; Cai, Xi

2018-05-01

To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced.

Computer Simulation of Microwave Devices

NASA Technical Reports Server (NTRS)

Kory, Carol L.

1997-01-01

The accurate simulation of cold-test results including dispersion, on-axis beam interaction impedance, and attenuation of a helix traveling-wave tube (TWT) slow-wave circuit using the three-dimensional code MAFIA (Maxwell's Equations Solved by the Finite Integration Algorithm) was demonstrated for the first time. Obtaining these results is a critical step in the design of TWT's. A well-established procedure to acquire these parameters is to actually build and test a model or a scale model of the circuit. However, this procedure is time-consuming and expensive, and it limits freedom to examine new variations to the basic circuit. These limitations make the need for computational methods crucial since they can lower costs, reduce tube development time, and lessen limitations on novel designs. Computer simulation has been used to accurately obtain cold-test parameters for several slow-wave circuits. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. A new computer modeling technique developed at the NASA Lewis Research Center overcomes these difficulties. The MAFIA three-dimensional mesh for a C-band helix slow-wave circuit is shown.

An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

NASA Astrophysics Data System (ADS)

Zhan, Ge; Pestana, Reynam C.; Stoffa, Paul L.

2013-04-01

The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward-backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations.

A simple grid implementation with Berkeley Open Infrastructure for Network Computing using BLAST as a model

PubMed Central

Pinthong, Watthanai; Muangruen, Panya

2016-01-01

Development of high-throughput technologies, such as Next-generation sequencing, allows thousands of experiments to be performed simultaneously while reducing resource requirement. Consequently, a massive amount of experiment data is now rapidly generated. Nevertheless, the data are not readily usable or meaningful until they are further analysed and interpreted. Due to the size of the data, a high performance computer (HPC) is required for the analysis and interpretation. However, the HPC is expensive and difficult to access. Other means were developed to allow researchers to acquire the power of HPC without a need to purchase and maintain one such as cloud computing services and grid computing system. In this study, we implemented grid computing in a computer training center environment using Berkeley Open Infrastructure for Network Computing (BOINC) as a job distributor and data manager combining all desktop computers to virtualize the HPC. Fifty desktop computers were used for setting up a grid system during the off-hours. In order to test the performance of the grid system, we adapted the Basic Local Alignment Search Tools (BLAST) to the BOINC system. Sequencing results from Illumina platform were aligned to the human genome database by BLAST on the grid system. The result and processing time were compared to those from a single desktop computer and HPC. The estimated durations of BLAST analysis for 4 million sequence reads on a desktop PC, HPC and the grid system were 568, 24 and 5 days, respectively. Thus, the grid implementation of BLAST by BOINC is an efficient alternative to the HPC for sequence alignment. The grid implementation by BOINC also helped tap unused computing resources during the off-hours and could be easily modified for other available bioinformatics software. PMID:27547555

45 CFR 2507.5 - How does the Corporation process requests for records?

Code of Federal Regulations, 2013 CFR

2013-10-01

... compelled to create new records or do statistical computations. For example, the Corporation is not required... feasible way to respond to a request. The Corporation is not required to perform any research for the... duplicating all of them. For example, if it requires less time and expense to provide a computer record as a...

26 CFR 1.179-5 - Time and manner of making election.

Code of Federal Regulations, 2010 CFR

2010-04-01

... desktop computer costing $1,500. On Taxpayer's 2003 Federal tax return filed on April 15, 2004, Taxpayer elected to expense under section 179 the full cost of the laptop computer and the full cost of the desktop... provided by the Internal Revenue Code, the regulations under the Code, or other guidance published in the...

Innovative Leaders Take the Phone and Run: Profiles of Four Trailblazing Programs

ERIC Educational Resources Information Center

Norris, Cathleen; Soloway, Elliot; Menchhofer, Kyle; Bauman, Billie Diane; Dickerson, Mindy; Schad, Lenny; Tomko, Sue

2010-01-01

While the Internet changed everything, mobile will change everything squared. The Internet is just a roadway, and computers--the equivalent of cars for the Internet--have been expensive. The keepers of the information roadway--the telecommunication companies--will give one a "computer," such as cell phone, mobile learning device, or MLD,…

75 FR 25161 - Defense Federal Acquisition Regulation Supplement; Presumption of Development at Private Expense

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-07

... asserted restrictions on technical data and computer software. DATES: Comments on the proposed rule should... restrictions on technical data and computer software. More specifically, the proposed rule affects these...) items (as defined at 41 U.S.C. 431(c)). Since COTS items are a subtype of commercial items, this change...

17 CFR 240.17a-3 - Records to be made by certain exchange members, brokers and dealers.

Code of Federal Regulations, 2011 CFR

2011-04-01

... records) reflecting all assets and liabilities, income and expense and capital accounts. (3) Ledger..., and a record of the computation of aggregate indebtedness and net capital, as of the trial balance...) thereof shall make a record of the computation of aggregate indebtedness and net capital as of the trial...

Containing the Cost of Heart Failure Management: A Focus on Reducing Readmissions.

PubMed

Soundarraj, Dwarakraj; Singh, Vini; Satija, Vaibhav; Thakur, Ranjan K

2017-01-01

Heart failure (HF) consumes a large proportion of the total national health care budget. Incidence and prevalence of HF are increasing and may give rise to an unsustainable increase in health care spending. Hospitalizations account for the vast majority of HF-related expenses, and 20% to 25% of patients discharged with a diagnosis of HF are readmitted within 60 days. Thus, efforts to reduce HF readmissions are a reasonable target for reducing overall expenses. It is to be seen if targeting readmission rates will lead to significant cost savings, and more importantly, to improved patient outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Hospital economics of primary total knee arthroplasty at a teaching hospital.

PubMed

Healy, William L; Rana, Adam J; Iorio, Richard

2011-01-01

The hospital cost of total knee arthroplasty (TKA) in the United States is a major growing expense for the Centers for Medicare & Medicaid Services (CMS). Many hospitals are unable to deliver TKA with profitable or breakeven economics under the current Diagnosis-Related Group (DRG) hospital reimbursement system. The purposes of the current study were to (1) determine revenue, expenses, and profitability (loss) for TKA for all patients and for different payors; (2) define changes in utilization and unit costs associated with this operation; and (3) describe TKA cost control strategies to provide insight for hospitals to improve their economic results for TKA. From 1991 to 2009, Lahey Clinic converted a $2172 loss per case on primary TKA in 1991 to a $2986 profit per case in 2008. The improved economics was associated with decreasing revenue in inflation-adjusted dollars and implementation of hospital cost control programs that reduced hospital expenses for TKA. Reduction of hospital length of stay and reduction of knee implant costs were the major drivers of hospital expense reduction. During the last 25 years, our economic experience with TKA is concerning. Hospital revenues have lagged behind inflation, hospital expenses have been reduced, and our institution is earning a profit. However, the margin for TKA is decreasing and Managed Medicare patients do not generate a profit. The erosion of hospital revenue for TKA will become a critical issue if it leads to economic losses for hospitals or reduced access to TKA. Level III, Economic and Decision Analyses. See Guidelines for Authors for a complete description of levels of evidence.

A reduced successive quadratic programming strategy for errors-in-variables estimation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tjoa, I.-B.; Biegler, L. T.; Carnegie-Mellon Univ.

Parameter estimation problems in process engineering represent a special class of nonlinear optimization problems, because the maximum likelihood structure of the objective function can be exploited. Within this class, the errors in variables method (EVM) is particularly interesting. Here we seek a weighted least-squares fit to the measurements with an underdetermined process model. Thus, both the number of variables and degrees of freedom available for optimization increase linearly with the number of data sets. Large optimization problems of this type can be particularly challenging and expensive to solve because, for general-purpose nonlinear programming (NLP) algorithms, the computational effort increases atmore » least quadratically with problem size. In this study we develop a tailored NLP strategy for EVM problems. The method is based on a reduced Hessian approach to successive quadratic programming (SQP), but with the decomposition performed separately for each data set. This leads to the elimination of all variables but the model parameters, which are determined by a QP coordination step. In this way the computational effort remains linear in the number of data sets. Moreover, unlike previous approaches to the EVM problem, global and superlinear properties of the SQP algorithm apply naturally. Also, the method directly incorporates inequality constraints on the model parameters (although not on the fitted variables). This approach is demonstrated on five example problems with up to 102 degrees of freedom. Compared to general-purpose NLP algorithms, large improvements in computational performance are observed.« less

Iterative methods for 3D implicit finite-difference migration using the complex Padé approximation

NASA Astrophysics Data System (ADS)

Costa, Carlos A. N.; Campos, Itamara S.; Costa, Jessé C.; Neto, Francisco A.; Schleicher, Jörg; Novais, Amélia

2013-08-01

Conventional implementations of 3D finite-difference (FD) migration use splitting techniques to accelerate performance and save computational cost. However, such techniques are plagued with numerical anisotropy that jeopardises the correct positioning of dipping reflectors in the directions not used for the operator splitting. We implement 3D downward continuation FD migration without splitting using a complex Padé approximation. In this way, the numerical anisotropy is eliminated at the expense of a computationally more intensive solution of a large-band linear system. We compare the performance of the iterative stabilized biconjugate gradient (BICGSTAB) and that of the multifrontal massively parallel direct solver (MUMPS). It turns out that the use of the complex Padé approximation not only stabilizes the solution, but also acts as an effective preconditioner for the BICGSTAB algorithm, reducing the number of iterations as compared to the implementation using the real Padé expansion. As a consequence, the iterative BICGSTAB method is more efficient than the direct MUMPS method when solving a single term in the Padé expansion. The results of both algorithms, here evaluated by computing the migration impulse response in the SEG/EAGE salt model, are of comparable quality.

A hybrid finite element-transfer matrix model for vibroacoustic systems with flat and homogeneous acoustic treatments.

PubMed

Alimonti, Luca; Atalla, Noureddine; Berry, Alain; Sgard, Franck

2015-02-01

Practical vibroacoustic systems involve passive acoustic treatments consisting of highly dissipative media such as poroelastic materials. The numerical modeling of such systems at low to mid frequencies typically relies on substructuring methodologies based on finite element models. Namely, the master subsystems (i.e., structural and acoustic domains) are described by a finite set of uncoupled modes, whereas condensation procedures are typically preferred for the acoustic treatments. However, although accurate, such methodology is computationally expensive when real life applications are considered. A potential reduction of the computational burden could be obtained by approximating the effect of the acoustic treatment on the master subsystems without introducing physical degrees of freedom. To do that, the treatment has to be assumed homogeneous, flat, and of infinite lateral extent. Under these hypotheses, simple analytical tools like the transfer matrix method can be employed. In this paper, a hybrid finite element-transfer matrix methodology is proposed. The impact of the limiting assumptions inherent within the analytical framework are assessed for the case of plate-cavity systems involving flat and homogeneous acoustic treatments. The results prove that the hybrid model can capture the qualitative behavior of the vibroacoustic system while reducing the computational effort.

Analyzing brain networks with PCA and conditional Granger causality.

PubMed

Zhou, Zhenyu; Chen, Yonghong; Ding, Mingzhou; Wright, Paul; Lu, Zuhong; Liu, Yijun

2009-07-01

Identifying directional influences in anatomical and functional circuits presents one of the greatest challenges for understanding neural computations in the brain. Granger causality mapping (GCM) derived from vector autoregressive models of data has been employed for this purpose, revealing complex temporal and spatial dynamics underlying cognitive processes. However, the traditional GCM methods are computationally expensive, as signals from thousands of voxels within selected regions of interest (ROIs) are individually processed, and being based on pairwise Granger causality, they lack the ability to distinguish direct from indirect connectivity among brain regions. In this work a new algorithm called PCA based conditional GCM is proposed to overcome these problems. The algorithm implements the following two procedures: (i) dimensionality reduction in ROIs of interest with principle component analysis (PCA), and (ii) estimation of the direct causal influences in local brain networks, using conditional Granger causality. Our results show that the proposed method achieves greater accuracy in detecting network connectivity than the commonly used pairwise Granger causality method. Furthermore, the use of PCA components in conjunction with conditional GCM greatly reduces the computational cost relative to the use of individual voxel time series. Copyright 2009 Wiley-Liss, Inc

Novel Method for Incorporating Model Uncertainties into Gravitational Wave Parameter Estimates

NASA Astrophysics Data System (ADS)

Moore, Christopher J.; Gair, Jonathan R.

2014-12-01

Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications, these models are incomplete, which both reduces the prospects of detection and leads to a systematic error in the parameter estimates. In the analysis of data from gravitational wave detectors, for example, accurate waveform templates can be computed using numerical methods, but the prohibitive cost of these simulations means this can only be done for a small handful of parameters. In this Letter, a novel method to fold model uncertainties into data analysis is proposed; the waveform uncertainty is analytically marginalized over using with a prior distribution constructed by using Gaussian process regression to interpolate the waveform difference from a small training set of accurate templates. The method is well motivated, easy to implement, and no more computationally expensive than standard techniques. The new method is shown to perform extremely well when applied to a toy problem. While we use the application to gravitational wave data analysis to motivate and illustrate the technique, it can be applied in any context where model uncertainties exist.

Simulation of 2D Kinetic Effects in Plasmas using the Grid Based Continuum Code LOKI

NASA Astrophysics Data System (ADS)

Banks, Jeffrey; Berger, Richard; Chapman, Tom; Brunner, Stephan

2016-10-01

Kinetic simulation of multi-dimensional plasma waves through direct discretization of the Vlasov equation is a useful tool to study many physical interactions and is particularly attractive for situations where minimal fluctuation levels are desired, for instance, when measuring growth rates of plasma wave instabilities. However, direct discretization of phase space can be computationally expensive, and as a result there are few examples of published results using Vlasov codes in more than a single configuration space dimension. In an effort to fill this gap we have developed the Eulerian-based kinetic code LOKI that evolves the Vlasov-Poisson system in 2+2-dimensional phase space. The code is designed to reduce the cost of phase-space computation by using fully 4th order accurate conservative finite differencing, while retaining excellent parallel scalability that efficiently uses large scale computing resources. In this poster I will discuss the algorithms used in the code as well as some aspects of their parallel implementation using MPI. I will also overview simulation results of basic plasma wave instabilities relevant to laser plasma interaction, which have been obtained using the code.

7 CFR 3560.102 - Housing project management.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., unless the machine becomes the property of the project after purchase. (iii) Determining if Expenses are... computer learning center activities benefiting tenants are not covered in this prohibition. (viii) It is...

7 CFR 3560.102 - Housing project management.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., unless the machine becomes the property of the project after purchase. (iii) Determining if Expenses are... computer learning center activities benefiting tenants are not covered in this prohibition. (viii) It is...

7 CFR 3560.102 - Housing project management.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., unless the machine becomes the property of the project after purchase. (iii) Determining if Expenses are... computer learning center activities benefiting tenants are not covered in this prohibition. (viii) It is...

7 CFR 3560.102 - Housing project management.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., unless the machine becomes the property of the project after purchase. (iii) Determining if Expenses are... computer learning center activities benefiting tenants are not covered in this prohibition. (viii) It is...

Total knee arthroplasty with a computer-navigated saw: a pilot study.

PubMed

Garvin, Kevin L; Barrera, Andres; Mahoney, Craig R; Hartman, Curtis W; Haider, Hani

2013-01-01

Computer-aided surgery aims to improve implant alignment in TKA but has only been adopted by a minority for routine use. A novel approach, navigated freehand bone cutting (NFC), is intended to achieve wider acceptance by eliminating the need for cumbersome, implant-specific mechanical jigs and avoiding the expense of navigation. We determined cutting time, surface quality, implant fit, and implant alignment after NFC of synthetic femoral specimens and the feasibility and alignment of a complete TKA performed with NFC technology in cadaveric specimens. Seven surgeons prepared six synthetic femoral specimens each, using our custom NFC system. Cutting times, quality of bone cuts, and implant fit and alignment were assessed quantitatively by CT surface scanning and computational measurements. Additionally, a single surgeon performed a complete TKA on two cadaveric specimens using the NFC system, with cutting time and implant alignment analyzed through plain radiographs and CT. For the synthetic specimens, femoral coronal alignment was within ± 2° of neutral in 94% of the specimens. Sagittal alignment was within 0° to 5° of flexion in all specimens. Rotation was within ± 1° of the epicondylar axis in 97% of the specimens. The mean time to make cuts improved from 13 minutes for the first specimen to 9 minutes for the fourth specimen. TKA was performed in two cadaveric specimens without complications and implants were well aligned. TKA is feasible with NFC, which eliminates the need for implant-specific instruments. We observed a fast learning curve. NFC has the potential to improve TKA alignment, reduce operative time, and reduce the number of instruments in surgery. Fewer instruments and less sterilization could reduce costs associated with TKA.

Recent advances in QM/MM free energy calculations using reference potentials☆

PubMed Central

Duarte, Fernanda; Amrein, Beat A.; Blaha-Nelson, David; Kamerlin, Shina C.L.

2015-01-01

Background Recent years have seen enormous progress in the development of methods for modeling (bio)molecular systems. This has allowed for the simulation of ever larger and more complex systems. However, as such complexity increases, the requirements needed for these models to be accurate and physically meaningful become more and more difficult to fulfill. The use of simplified models to describe complex biological systems has long been shown to be an effective way to overcome some of the limitations associated with this computational cost in a rational way. Scope of review Hybrid QM/MM approaches have rapidly become one of the most popular computational tools for studying chemical reactivity in biomolecular systems. However, the high cost involved in performing high-level QM calculations has limited the applicability of these approaches when calculating free energies of chemical processes. In this review, we present some of the advances in using reference potentials and mean field approximations to accelerate high-level QM/MM calculations. We present illustrative applications of these approaches and discuss challenges and future perspectives for the field. Major conclusions The use of physically-based simplifications has shown to effectively reduce the cost of high-level QM/MM calculations. In particular, lower-level reference potentials enable one to reduce the cost of expensive free energy calculations, thus expanding the scope of problems that can be addressed. General significance As was already demonstrated 40 years ago, the usage of simplified models still allows one to obtain cutting edge results with substantially reduced computational cost. This article is part of a Special Issue entitled Recent developments of molecular dynamics. PMID:25038480

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bishop, Joseph E.; Brown, Judith Alice

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Adaptive reduction of constitutive model-form error using a posteriori error estimation techniques

DOE PAGES

Bishop, Joseph E.; Brown, Judith Alice

2018-06-15

In engineering practice, models are typically kept as simple as possible for ease of setup and use, computational efficiency, maintenance, and overall reduced complexity to achieve robustness. In solid mechanics, a simple and efficient constitutive model may be favored over one that is more predictive, but is difficult to parameterize, is computationally expensive, or is simply not available within a simulation tool. In order to quantify the modeling error due to the choice of a relatively simple and less predictive constitutive model, we adopt the use of a posteriori model-form error-estimation techniques. Based on local error indicators in the energymore » norm, an algorithm is developed for reducing the modeling error by spatially adapting the material parameters in the simpler constitutive model. The resulting material parameters are not material properties per se, but depend on the given boundary-value problem. As a first step to the more general nonlinear case, we focus here on linear elasticity in which the “complex” constitutive model is general anisotropic elasticity and the chosen simpler model is isotropic elasticity. As a result, the algorithm for adaptive error reduction is demonstrated using two examples: (1) A transversely-isotropic plate with hole subjected to tension, and (2) a transversely-isotropic tube with two side holes subjected to torsion.« less

Scaling to diversity: The DERECHOS distributed infrastructure for analyzing and sharing data

NASA Astrophysics Data System (ADS)

Rilee, M. L.; Kuo, K. S.; Clune, T.; Oloso, A.; Brown, P. G.

2016-12-01

Integrating Earth Science data from diverse sources such as satellite imagery and simulation output can be expensive and time-consuming, limiting scientific inquiry and the quality of our analyses. Reducing these costs will improve innovation and quality in science. The current Earth Science data infrastructure focuses on downloading data based on requests formed from the search and analysis of associated metadata. And while the data products provided by archives may use the best available data sharing technologies, scientist end-users generally do not have such resources (including staff) available to them. Furthermore, only once an end-user has received the data from multiple diverse sources and has integrated them can the actual analysis and synthesis begin. The cost of getting from idea to where synthesis can start dramatically slows progress. In this presentation we discuss a distributed computational and data storage framework that eliminates much of the aforementioned cost. The SciDB distributed array database is central as it is optimized for scientific computing involving very large arrays, performing better than less specialized frameworks like Spark. Adding spatiotemporal functions to the SciDB creates a powerful platform for analyzing and integrating massive, distributed datasets. SciDB allows Big Earth Data analysis to be performed "in place" without the need for expensive downloads and end-user resources. Spatiotemporal indexing technologies such as the hierarchical triangular mesh enable the compute and storage affinity needed to efficiently perform co-located and conditional analyses minimizing data transfers. These technologies automate the integration of diverse data sources using the framework, a critical step beyond current metadata search and analysis. Instead of downloading data into their idiosyncratic local environments, end-users can generate and share data products integrated from diverse multiple sources using a common shared environment, turning distributed active archive centers (DAACs) from warehouses into distributed active analysis centers.

Towards an accurate representation of electrostatics in classical force fields: Efficient implementation of multipolar interactions in biomolecular simulations

NASA Astrophysics Data System (ADS)

Sagui, Celeste; Pedersen, Lee G.; Darden, Thomas A.

2004-01-01

The accurate simulation of biologically active macromolecules faces serious limitations that originate in the treatment of electrostatics in the empirical force fields. The current use of "partial charges" is a significant source of errors, since these vary widely with different conformations. By contrast, the molecular electrostatic potential (MEP) obtained through the use of a distributed multipole moment description, has been shown to converge to the quantum MEP outside the van der Waals surface, when higher order multipoles are used. However, in spite of the considerable improvement to the representation of the electronic cloud, higher order multipoles are not part of current classical biomolecular force fields due to the excessive computational cost. In this paper we present an efficient formalism for the treatment of higher order multipoles in Cartesian tensor formalism. The Ewald "direct sum" is evaluated through a McMurchie-Davidson formalism [L. McMurchie and E. Davidson, J. Comput. Phys. 26, 218 (1978)]. The "reciprocal sum" has been implemented in three different ways: using an Ewald scheme, a particle mesh Ewald (PME) method, and a multigrid-based approach. We find that even though the use of the McMurchie-Davidson formalism considerably reduces the cost of the calculation with respect to the standard matrix implementation of multipole interactions, the calculation in direct space remains expensive. When most of the calculation is moved to reciprocal space via the PME method, the cost of a calculation where all multipolar interactions (up to hexadecapole-hexadecapole) are included is only about 8.5 times more expensive than a regular AMBER 7 [D. A. Pearlman et al., Comput. Phys. Commun. 91, 1 (1995)] implementation with only charge-charge interactions. The multigrid implementation is slower but shows very promising results for parallelization. It provides a natural way to interface with continuous, Gaussian-based electrostatics in the future. It is hoped that this new formalism will facilitate the systematic implementation of higher order multipoles in classical biomolecular force fields.

3-D and quasi-2-D discrete element modeling of grain commingling in a bucket elevator boot system

USDA-ARS?s Scientific Manuscript database

Unwanted grain commingling impedes new quality-based grain handling systems and has proven to be an expensive and time consuming issue to study experimentally. Experimentally validated models may reduce the time and expense of studying grain commingling while providing additional insight into detail...

A computational fluid dynamics simulation of the hypersonic flight of the Pegasus(TM) vehicle using an artificial viscosity model and a nonlinear filtering method. M.S. Thesis

NASA Technical Reports Server (NTRS)

Mendoza, John Cadiz

1995-01-01

The computational fluid dynamics code, PARC3D, is tested to see if its use of non-physical artificial dissipation affects the accuracy of its results. This is accomplished by simulating a shock-laminar boundary layer interaction and several hypersonic flight conditions of the Pegasus(TM) launch vehicle using full artificial dissipation, low artificial dissipation, and the Engquist filter. Before the filter is applied to the PARC3D code, it is validated in one-dimensional and two-dimensional form in a MacCormack scheme against the Riemann and convergent duct problem. For this explicit scheme, the filter shows great improvements in accuracy and computational time as opposed to the nonfiltered solutions. However, for the implicit PARC3D code it is found that the best estimate of the Pegasus experimental heat fluxes and surface pressures is the simulation utilizing low artificial dissipation and no filter. The filter does improve accuracy over the artificially dissipative case but at a computational expense greater than that achieved by the low artificial dissipation case which has no computational time penalty and shows better results. For the shock-boundary layer simulation, the filter does well in terms of accuracy for a strong impingement shock but not as well for weaker shock strengths. Furthermore, for the latter problem the filter reduces the required computational time to convergence by 18.7 percent.

Application of high-performance computing to numerical simulation of human movement

NASA Technical Reports Server (NTRS)

Anderson, F. C.; Ziegler, J. M.; Pandy, M. G.; Whalen, R. T.

1995-01-01

We have examined the feasibility of using massively-parallel and vector-processing supercomputers to solve large-scale optimization problems for human movement. Specifically, we compared the computational expense of determining the optimal controls for the single support phase of gait using a conventional serial machine (SGI Iris 4D25), a MIMD parallel machine (Intel iPSC/860), and a parallel-vector-processing machine (Cray Y-MP 8/864). With the human body modeled as a 14 degree-of-freedom linkage actuated by 46 musculotendinous units, computation of the optimal controls for gait could take up to 3 months of CPU time on the Iris. Both the Cray and the Intel are able to reduce this time to practical levels. The optimal solution for gait can be found with about 77 hours of CPU on the Cray and with about 88 hours of CPU on the Intel. Although the overall speeds of the Cray and the Intel were found to be similar, the unique capabilities of each machine are better suited to different portions of the computational algorithm used. The Intel was best suited to computing the derivatives of the performance criterion and the constraints whereas the Cray was best suited to parameter optimization of the controls. These results suggest that the ideal computer architecture for solving very large-scale optimal control problems is a hybrid system in which a vector-processing machine is integrated into the communication network of a MIMD parallel machine.

Reducing the cost of headache medication.

PubMed

Solomon, Glen D

2009-06-01

Although medication costs make up one of the smallest portions of the overall expense of headache care, it is the segment of expense that often impacts the patient most directly. The advent of triptans marked a major advance in migraine therapy, but their high cost has limited their widespread use. Four options can be considered as potential means to reduce the cost of triptans. These include compulsory licensing, exclusive contracting, over-the-counter -availability, and the introduction of generic triptans. Each method impacts the consumer, third-party payer, or pharmaceutical company in a different manner.

An iterative method for hydrodynamic interactions in Brownian dynamics simulations of polymer dynamics

NASA Astrophysics Data System (ADS)

Miao, Linling; Young, Charles D.; Sing, Charles E.

2017-07-01

Brownian Dynamics (BD) simulations are a standard tool for understanding the dynamics of polymers in and out of equilibrium. Quantitative comparison can be made to rheological measurements of dilute polymer solutions, as well as direct visual observations of fluorescently labeled DNA. The primary computational challenge with BD is the expensive calculation of hydrodynamic interactions (HI), which are necessary to capture physically realistic dynamics. The full HI calculation, performed via a Cholesky decomposition every time step, scales with the length of the polymer as O(N3). This limits the calculation to a few hundred simulated particles. A number of approximations in the literature can lower this scaling to O(N2 - N2.25), and explicit solvent methods scale as O(N); however both incur a significant constant per-time step computational cost. Despite this progress, there remains a need for new or alternative methods of calculating hydrodynamic interactions; large polymer chains or semidilute polymer solutions remain computationally expensive. In this paper, we introduce an alternative method for calculating approximate hydrodynamic interactions. Our method relies on an iterative scheme to establish self-consistency between a hydrodynamic matrix that is averaged over simulation and the hydrodynamic matrix used to run the simulation. Comparison to standard BD simulation and polymer theory results demonstrates that this method quantitatively captures both equilibrium and steady-state dynamics after only a few iterations. The use of an averaged hydrodynamic matrix allows the computationally expensive Brownian noise calculation to be performed infrequently, so that it is no longer the bottleneck of the simulation calculations. We also investigate limitations of this conformational averaging approach in ring polymers.

Automatic Data Filter Customization Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Mandrake, Lukas

2013-01-01

This work predicts whether a retrieval algorithm will usefully determine CO2 concentration from an input spectrum of GOSAT (Greenhouse Gases Observing Satellite). This was done to eliminate needless runtime on atmospheric soundings that would never yield useful results. A space of 50 dimensions was examined for predictive power on the final CO2 results. Retrieval algorithms are frequently expensive to run, and wasted effort defeats requirements and expends needless resources. This algorithm could be used to help predict and filter unneeded runs in any computationally expensive regime. Traditional methods such as the Fischer discriminant analysis and decision trees can attempt to predict whether a sounding will be properly processed. However, this work sought to detect a subsection of the dimensional space that can be simply filtered out to eliminate unwanted runs. LDAs (linear discriminant analyses) and other systems examine the entire data and judge a "best fit," giving equal weight to complex and problematic regions as well as simple, clear-cut regions. In this implementation, a genetic space of "left" and "right" thresholds outside of which all data are rejected was defined. These left/right pairs are created for each of the 50 input dimensions. A genetic algorithm then runs through countless potential filter settings using a JPL computer cluster, optimizing the tossed-out data s yield (proper vs. improper run removal) and number of points tossed. This solution is robust to an arbitrary decision boundary within the data and avoids the global optimization problem of whole-dataset fitting using LDA or decision trees. It filters out runs that would not have produced useful CO2 values to save needless computation. This would be an algorithmic preprocessing improvement to any computationally expensive system.

Energy measurement using flow computers and chromatography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beeson, J.

1995-12-01

Arkla Pipeline Group (APG), along with most transmission companies, went to electronic flow measurement (EFM) to: (1) Increase resolution and accuracy; (2) Real time correction of flow variables; (3) Increase speed in data retrieval; (4) Reduce capital expenditures; and (5) Reduce operation and maintenance expenditures Prior to EFM, mechanical seven day charts were used which yielded 800 pressure and differential pressure readings. EFM yields 1.2-million readings, a 1500 time improvement in resolution and additional flow representation. The total system accuracy of the EFM system is 0.25 % compared with 2 % for the chart system which gives APG improved accuracy.more » A typical APG electronic measurement system includes a microprocessor-based flow computer, a telemetry communications package, and a gas chromatograph. Live relative density (specific gravity), BTU, CO{sub 2}, and N{sub 2} are updated from the chromatograph to the flow computer every six minutes which provides accurate MMBTU computations. Because the gas contract length has changed from years to monthly and from a majority of direct sales to transports both Arkla and its customers wanted access to actual volumes on a much more timely basis than is allowed with charts. The new electronic system allows volumes and other system data to be retrieved continuously, if EFM is on Supervisory Control and Data Acquisition (SCADA) or daily if on dial up telephone. Previously because of chart integration, information was not available for four to six weeks. EFM costs much less than the combined costs of telemetry transmitters, pressure and differential pressure chart recorders, and temperature chart recorder which it replaces. APG will install this equipment on smaller volume stations at a customers expense. APG requires backup measurement on metering facilities this size. It could be another APG flow computer or chart recorder, or the other companies flow computer or chart recorder.« less

Computing LORAN time differences with an HP-25 hand calculator

NASA Technical Reports Server (NTRS)

Jones, E. D.

1978-01-01

A program for an HP-25 or HP-25C hand calculator that will calculate accurate LORAN-C time differences is described and presented. The program is most useful when checking the accuracy of a LORAN-C receiver at a known latitude and longitude without the aid of an expensive computer. It can thus be used to compute time differences for known landmarks or waypoints to predict in advance the approximate readings during a navigation mission.

Design Trade-off Between Performance and Fault-Tolerance of Space Onboard Computers

NASA Astrophysics Data System (ADS)

Gorbunov, M. S.; Antonov, A. A.

2017-01-01

It is well known that there is a trade-off between performance and power consumption in onboard computers. The fault-tolerance is another important factor affecting performance, chip area and power consumption. Involving special SRAM cells and error-correcting codes is often too expensive with relation to the performance needed. We discuss the possibility of finding the optimal solutions for modern onboard computer for scientific apparatus focusing on multi-level cache memory design.

Sustaining Moore's law with 3D chips

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeBenedictis, Erik P.; Badaroglu, Mustafa; Chen, An

Here, rather than continue the expensive and time-consuming quest for transistor replacement, the authors argue that 3D chips coupled with new computer architectures can keep Moore's law on its traditional scaling path.

Sustaining Moore's law with 3D chips

DOE PAGES

DeBenedictis, Erik P.; Badaroglu, Mustafa; Chen, An; ...

2017-08-01

Here, rather than continue the expensive and time-consuming quest for transistor replacement, the authors argue that 3D chips coupled with new computer architectures can keep Moore's law on its traditional scaling path.

46 CFR 404.5 - Guidelines for the recognition of expenses.

Code of Federal Regulations, 2010 CFR

2010-10-01

... to the extent that they conform to depreciation plus an allowance for return on investment (computed... ratemaking purposes. The Director reviews non-pilotage activities to determine if any adversely impact the...

A feasibility study to determine if there is a market for automatic meter-reading devices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hilberg, G.R.

1996-08-01

For many utilities the cost of manually reading meters is increasing due to personnel expenses and equipment costs. The current system of manual meters provides little ability for the utility to reduce costs. To reduce meter reading costs the utility must automate the manual system and reduce personnel expenses. A water utility in San Diego county was studied to calculate the cost of reading individual water meters. This would allow for the selective replacement of {open_quotes}high-cost{close_quotes} meters to quickly reduce meter-reading costs while limiting the necessary capital investments. As the {open_quotes}high-cost{close_quotes} meters are selectively replaced, a utility with a significantmore » difference in individual meter reading costs could save three to five dollars per meter per year. This study showed that the {open_quotes}high-cost{close_quotes} meters were six times more expensive to read than the average meter. Additionally, AMR systems increase the information available to consumers and to the utility on usage patterns and problems. The challenge was to cost effectively identify the {open_quotes}high-cost{close_quotes} meters. The costs to collect these data were less than $500.« less

Towards Wearable Cognitive Assistance

DTIC Science & Technology

2013-12-01

ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Keywords: mobile computing, cloud...It presents a muli-tiered mobile system architecture that offers tight end-to-end latency bounds on compute-intensive cognitive assistance...to an entire neighborhood or an entire city is extremely expensive and time-consuming. Physical infrastructure in public spaces tends to evolve very

Behavior-Based Fault Monitoring

DTIC Science & Technology

1990-12-03

processor targeted for avionics and space applications . It appears that the signature monitoring technique can be extended to detect computer viruses as...most common approach is structural duplication. Although effective, duplication is too expensive for all but a few applications . Redundancy can also be...Signature Monitoring and Encryption," Int. Conf. on Dependable Computing for Critical Applications , August 1989. 7. K.D. Wilken and J.P. Shen

Artificial Intelligence Methods: Challenge in Computer Based Polymer Design

NASA Astrophysics Data System (ADS)

Rusu, Teodora; Pinteala, Mariana; Cartwright, Hugh

2009-08-01

This paper deals with the use of Artificial Intelligence Methods (AI) in the design of new molecules possessing desired physical, chemical and biological properties. This is an important and difficult problem in the chemical, material and pharmaceutical industries. Traditional methods involve a laborious and expensive trial-and-error procedure, but computer-assisted approaches offer many advantages in the automation of molecular design.

Gaussian process regression of chirplet decomposed ultrasonic B-scans of a simulated design case

NASA Astrophysics Data System (ADS)

Wertz, John; Homa, Laura; Welter, John; Sparkman, Daniel; Aldrin, John

2018-04-01

The US Air Force seeks to implement damage tolerant lifecycle management of composite structures. Nondestructive characterization of damage is a key input to this framework. One approach to characterization is model-based inversion of the ultrasonic response from damage features; however, the computational expense of modeling the ultrasonic waves within composites is a major hurdle to implementation. A surrogate forward model with sufficient accuracy and greater computational efficiency is therefore critical to enabling model-based inversion and damage characterization. In this work, a surrogate model is developed on the simulated ultrasonic response from delamination-like structures placed at different locations within a representative composite layup. The resulting B-scans are decomposed via the chirplet transform, and a Gaussian process model is trained on the chirplet parameters. The quality of the surrogate is tested by comparing the B-scan for a delamination configuration not represented within the training data set. The estimated B-scan has a maximum error of ˜15% for an estimated reduction in computational runtime of ˜95% for 200 function calls. This considerable reduction in computational expense makes full 3D characterization of impact damage tractable.

Using Approximations to Accelerate Engineering Design Optimization

NASA Technical Reports Server (NTRS)

Torczon, Virginia; Trosset, Michael W.

1998-01-01

Optimization problems that arise in engineering design are often characterized by several features that hinder the use of standard nonlinear optimization techniques. Foremost among these features is that the functions used to define the engineering optimization problem often are computationally intensive. Within a standard nonlinear optimization algorithm, the computational expense of evaluating the functions that define the problem would necessarily be incurred for each iteration of the optimization algorithm. Faced with such prohibitive computational costs, an attractive alternative is to make use of surrogates within an optimization context since surrogates can be chosen or constructed so that they are typically much less expensive to compute. For the purposes of this paper, we will focus on the use of algebraic approximations as surrogates for the objective. In this paper we introduce the use of so-called merit functions that explicitly recognize the desirability of improving the current approximation to the objective during the course of the optimization. We define and experiment with the use of merit functions chosen to simultaneously improve both the solution to the optimization problem (the objective) and the quality of the approximation. Our goal is to further improve the effectiveness of our general approach without sacrificing any of its rigor.

APHiD: Hierarchical Task Placement to Enable a Tapered Fat Tree Topology for Lower Power and Cost in HPC Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michelogiannakis, George; Ibrahim, Khaled Z.; Shalf, John

The power and procurement cost of bandwidth in system-wide networks has forced a steady drop in the byte/flop ratio. This trend of computation becoming faster relative to the network is expected to hold. In this paper, we explore how cost-oriented task placement enables reducing the cost of system-wide networks by enabling high performance even on tapered topologies where more bandwidth is provisioned at lower levels. We describe APHiD, an efficient hierarchical placement algorithm that uses new techniques to improve the quality of heuristic solutions and reduces the demand on high-level, expensive bandwidth in hierarchical topologies. We apply APHiD to amore » tapered fat-tree, demonstrating that APHiD maintains application scalability even for severely tapered network configurations. Using simulation, we show that for tapered networks APHiD improves performance by more than 50% over random placement and even 15% in some cases over costlier, state-of-the-art placement algorithms.« less

An improved coupled-states approximation including the nearest neighbor Coriolis couplings for diatom-diatom inelastic collision

NASA Astrophysics Data System (ADS)

Yang, Dongzheng; Hu, Xixi; Zhang, Dong H.; Xie, Daiqian

2018-02-01

Solving the time-independent close coupling equations of a diatom-diatom inelastic collision system by using the rigorous close-coupling approach is numerically difficult because of its expensive matrix manipulation. The coupled-states approximation decouples the centrifugal matrix by neglecting the important Coriolis couplings completely. In this work, a new approximation method based on the coupled-states approximation is presented and applied to time-independent quantum dynamic calculations. This approach only considers the most important Coriolis coupling with the nearest neighbors and ignores weaker Coriolis couplings with farther K channels. As a result, it reduces the computational costs without a significant loss of accuracy. Numerical tests for para-H2+ortho-H2 and para-H2+HD inelastic collision were carried out and the results showed that the improved method dramatically reduces the errors due to the neglect of the Coriolis couplings in the coupled-states approximation. This strategy should be useful in quantum dynamics of other systems.

FaceTime for Physicians: Using Real Time Mobile Phone–Based Videoconferencing to Augment Diagnosis and Care in Telemedicine

PubMed Central

Armstrong, David G.; Giovinco, Nicholas; Mills, Joseph L.; Rogers, Lee C.

2011-01-01

Objective/Background: Telemedicine has, even in its infancy, had an impact on the provision of healthcare, particularly in rural communities. However, this often relies on an expensive and ponderous infrastructure that reduces the rapid use and spontaneity for consultations. Methods: Using postoperative and intraoperative examples, we describe the use of one rapid and widely available technology (iPhone FaceTime, Cupertino, California). Results: The device, in allowing “one button connection” similar to making a phone call, reduced the need for preplanning that is generally required for real-time telemedicine consultation. Conclusions: The ability to communicate quickly with something that is an afterthought has the potential to alter how we work with our colleagues and patients. Just as with the iPod in music and the laptop in computing, it is not the change in technology, but the change in form factor and ubiquity that alters this landscape. PMID:21559249

Integrating Cloud-Computing-Specific Model into Aircraft Design

NASA Astrophysics Data System (ADS)

Zhimin, Tian; Qi, Lin; Guangwen, Yang

Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

Reducing overlay sampling for APC-based correction per exposure by replacing measured data with computational prediction

NASA Astrophysics Data System (ADS)

Noyes, Ben F.; Mokaberi, Babak; Oh, Jong Hun; Kim, Hyun Sik; Sung, Jun Ha; Kea, Marc

2016-03-01

One of the keys to successful mass production of sub-20nm nodes in the semiconductor industry is the development of an overlay correction strategy that can meet specifications, reduce the number of layers that require dedicated chuck overlay, and minimize measurement time. Three important aspects of this strategy are: correction per exposure (CPE), integrated metrology (IM), and the prioritization of automated correction over manual subrecipes. The first and third aspects are accomplished through an APC system that uses measurements from production lots to generate CPE corrections that are dynamically applied to future lots. The drawback of this method is that production overlay sampling must be extremely high in order to provide the system with enough data to generate CPE. That drawback makes IM particularly difficult because of the throughput impact that can be created on expensive bottleneck photolithography process tools. The goal is to realize the cycle time and feedback benefits of IM coupled with the enhanced overlay correction capability of automated CPE without impacting process tool throughput. This paper will discuss the development of a system that sends measured data with reduced sampling via an optimized layout to the exposure tool's computational modelling platform to predict and create "upsampled" overlay data in a customizable output layout that is compatible with the fab user CPE APC system. The result is dynamic CPE without the burden of extensive measurement time, which leads to increased utilization of IM.

Computer Generated Hologram System for Wavefront Measurement System Calibration

NASA Technical Reports Server (NTRS)

Olczak, Gene

2011-01-01

Computer Generated Holograms (CGHs) have been used for some time to calibrate interferometers that require nulling optics. A typical scenario is the testing of aspheric surfaces with an interferometer placed near the paraxial center of curvature. Existing CGH technology suffers from a reduced capacity to calibrate middle and high spatial frequencies. The root cause of this shortcoming is as follows: the CGH is not placed at an image conjugate of the asphere due to limitations imposed by the geometry of the test and the allowable size of the CGH. This innovation provides a calibration system where the imaging properties in calibration can be made comparable to the test configuration. Thus, if the test is designed to have good imaging properties, then middle and high spatial frequency errors in the test system can be well calibrated. The improved imaging properties are provided by a rudimentary auxiliary optic as part of the calibration system. The auxiliary optic is simple to characterize and align to the CGH. Use of the auxiliary optic also reduces the size of the CGH required for calibration and the density of the lines required for the CGH. The resulting CGH is less expensive than the existing technology and has reduced write error and alignment error sensitivities. This CGH system is suitable for any kind of calibration using an interferometer when high spatial resolution is required. It is especially well suited for tests that include segmented optical components or large apertures.

Chapter 15: Disease Gene Prioritization

PubMed Central

Bromberg, Yana

2013-01-01

Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases. PMID:23633938

Tight-binding approximations to time-dependent density functional theory — A fast approach for the calculation of electronically excited states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rüger, Robert, E-mail: rueger@scm.com; Department of Theoretical Chemistry, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam; Wilhelm-Ostwald-Institut für Physikalische und Theoretische Chemie, Linnéstr. 2, 04103 Leipzig

2016-05-14

We propose a new method of calculating electronically excited states that combines a density functional theory based ground state calculation with a linear response treatment that employs approximations used in the time-dependent density functional based tight binding (TD-DFTB) approach. The new method termed time-dependent density functional theory TD-DFT+TB does not rely on the DFTB parametrization and is therefore applicable to systems involving all combinations of elements. We show that the new method yields UV/Vis absorption spectra that are in excellent agreement with computationally much more expensive TD-DFT calculations. Errors in vertical excitation energies are reduced by a factor of twomore » compared to TD-DFTB.« less

A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation

NASA Astrophysics Data System (ADS)

Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang

2010-11-01

This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.

Ocean Models and Proper Orthogonal Decomposition

NASA Astrophysics Data System (ADS)

Salas-de-Leon, D. A.

2007-05-01

The increasing computational developments and the better understanding of mathematical and physical systems resulted in an increasing number of ocean models. Long time ago, modelers were like a secret organization and recognize each other by using secret codes and languages that only a select group of people was able to recognize and understand. The access to computational systems was reduced, on one hand equipment and the using time of computers were expensive and restricted, and on the other hand, they required an advance computational languages that not everybody wanted to learn. Now a days most college freshman own a personal computer (PC or laptop), and/or have access to more sophisticated computational systems than those available for research in the early 80's. The resource availability resulted in a mayor access to all kind models. Today computer speed and time and the algorithms does not seem to be a problem, even though some models take days to run in small computational systems. Almost every oceanographic institution has their own model, what is more, in the same institution from one office to the next there are different models for the same phenomena, developed by different research member, the results does not differ substantially since the equations are the same, and the solving algorithms are similar. The algorithms and the grids, constructed with algorithms, can be found in text books and/or over the internet. Every year more sophisticated models are constructed. The Proper Orthogonal Decomposition is a technique that allows the reduction of the number of variables to solve keeping the model properties, for which it can be a very useful tool in diminishing the processes that have to be solved using "small" computational systems, making sophisticated models available for a greater community.

75 FR 65599 - Migratory Bird Subsistence Harvest in Alaska; Harvest Regulations for Migratory Birds in Alaska...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-26

... goals in mind, the Service, working with partners, developed measures in 2009 to further reduce the.... Participation on regional management bodies and the Co-management Council will require travel expenses for some... will also incur expenses for travel to Co-management Council and regional management body meetings. In...

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

PubMed Central

Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

2009-01-01

Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

Temperature scaling method for Markov chains.

PubMed

Crosby, Lonnie D; Windus, Theresa L

2009-01-22

The use of ab initio potentials in Monte Carlo simulations aimed at investigating the nucleation kinetics of water clusters is complicated by the computational expense of the potential energy determinations. Furthermore, the common desire to investigate the temperature dependence of kinetic properties leads to an urgent need to reduce the expense of performing simulations at many different temperatures. A method is detailed that allows a Markov chain (obtained via Monte Carlo) at one temperature to be scaled to other temperatures of interest without the need to perform additional large simulations. This Markov chain temperature-scaling (TeS) can be generally applied to simulations geared for numerous applications. This paper shows the quality of results which can be obtained by TeS and the possible quantities which may be extracted from scaled Markov chains. Results are obtained for a 1-D analytical potential for which the exact solutions are known. Also, this method is applied to water clusters consisting of between 2 and 5 monomers, using Dynamical Nucleation Theory to determine the evaporation rate constant for monomer loss. Although ab initio potentials are not utilized in this paper, the benefit of this method is made apparent by using the Dang-Chang polarizable classical potential for water to obtain statistical properties at various temperatures.

Computing technology in the 1980's. [computers

NASA Technical Reports Server (NTRS)

Stone, H. S.

1978-01-01

Advances in computing technology have been led by consistently improving semiconductor technology. The semiconductor industry has turned out ever faster, smaller, and less expensive devices since transistorized computers were first introduced 20 years ago. For the next decade, there appear to be new advances possible, with the rate of introduction of improved devices at least equal to the historic trends. The implication of these projections is that computers will enter new markets and will truly be pervasive in business, home, and factory as their cost diminishes and their computational power expands to new levels. The computer industry as we know it today will be greatly altered in the next decade, primarily because the raw computer system will give way to computer-based turn-key information and control systems.

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

NASA Astrophysics Data System (ADS)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Numerical investigation of a modified family of centered schemes applied to multiphase equations with nonconservative sources

NASA Astrophysics Data System (ADS)

Crochet, M. W.; Gonthier, K. A.

2013-12-01

Systems of hyperbolic partial differential equations are frequently used to model the flow of multiphase mixtures. These equations often contain sources, referred to as nozzling terms, that cannot be posed in divergence form, and have proven to be particularly challenging in the development of finite-volume methods. Upwind schemes have recently shown promise in properly resolving the steady wave solution of the associated multiphase Riemann problem. However, these methods require a full characteristic decomposition of the system eigenstructure, which may be either unavailable or computationally expensive. Central schemes, such as the Kurganov-Tadmor (KT) family of methods, require minimal characteristic information, which makes them easily applicable to systems with an arbitrary number of phases. However, the proper implementation of nozzling terms in these schemes has been mathematically ambiguous. The primary objectives of this work are twofold: first, an extension of the KT family of schemes is proposed that formally accounts for the nonconservative nozzling sources. This modification results in a semidiscrete form that retains the simplicity of its predecessor and introduces little additional computational expense. Second, this modified method is applied to multiple, but equivalent, forms of the multiphase equations to perform a numerical study by solving several one-dimensional test problems. Both ideal and Mie-Grüneisen equations of state are used, with the results compared to an analytical solution. This study demonstrates that the magnitudes of the resulting numerical errors are sensitive to the form of the equations considered, and suggests an optimal form to minimize these errors. Finally, a separate modification of the wave propagation speeds used in the KT family is also suggested that can reduce the extent of numerical diffusion in multiphase flows.

Economical and Energy Efficiency of Iron and Steel Industry Reindustrialisation in Russia Based on Implementation of Breakthrough Energy-Saving Technologies

NASA Astrophysics Data System (ADS)

Shevelev, L. N.

2017-12-01

Estimates were given of economical and energy efficiency of breakthrough energy-saving technologies, which increase competitive advantages and provide energy efficiency of production while reducing negative impact on the environment through reduction of emissions of harmful substances and greenhouse gases in the atmosphere. Among these technologies, preference is given to the following: pulverized coal fuel, blast-furnace gas recycling, gasification of non-coking coal in bubble-type gas-generators, iron-ore concentrate briquetting with steam coal with further use of ore-coal briquettes in electric furnace steel making. Implementation of these technologies at iron and steel works will significantly reduce the energy intensity of production through reduction of expensive coking coal consumption by means of their substitution by less expensive non-coking (steam) coal, and natural gas substitution by own secondary energy resource, which is the reducing gas. As the result, plants will get an opportunity to become self-sufficient in energy-resources and free themselves entirely from expensive purchased energy resources (natural gas, electric power, and partially coking coals), and cross over to low-carbon development.

Switching from computer to microcomputer architecture education

NASA Astrophysics Data System (ADS)

Bolanakis, Dimosthenis E.; Kotsis, Konstantinos T.; Laopoulos, Theodore

2010-03-01

In the last decades, the technological and scientific evolution of the computing discipline has been widely affecting research in software engineering education, which nowadays advocates more enlightened and liberal ideas. This article reviews cross-disciplinary research on a computer architecture class in consideration of its switching to microcomputer architecture. The authors present their strategies towards a successful crossing of boundaries between engineering disciplines. This communication aims at providing a different aspect on professional courses that are, nowadays, addressed at the expense of traditional courses.

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

DOE PAGES

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; ...

2015-11-09

Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.

Digital video technology, today and tomorrow

NASA Astrophysics Data System (ADS)

Liberman, J.

1994-10-01

Digital video is probably computing's fastest moving technology today. Just three years ago, the zenith of digital video technology on the PC was the successful marriage of digital text and graphics with analog audio and video by means of expensive analog laser disc players and video overlay boards. The state of the art involves two different approaches to fully digital video on computers: hardware-assisted and software-only solutions.

Detroit's avoidable mortality project: breast cancer control for inner-city women.

PubMed Central

Burack, R C; Gimotty, P A; Stengle, W; Eckert, D; Warbasse, L; Moncrease, A

1989-01-01

Mammography remains substantially under-used in low-income minority populations despite its well-established efficacy as a means of breast cancer control. The Metropolitan Detroit Avoidable Mortality Project is a 2-year controlled clinical trial of coordinated interventions which seek to improve the use of early breast cancer detection services at five clinical sites providing primary health care services to inner-city women. Baseline assessment for two of the five participating clinic populations demonstrated that only one-quarter of women who visited these clinics were referred for mammography in 1988, and only half of those who were referred were able to complete the procedure. Patient characteristics including age, marital status, ethnicity, and insurance status were not associated with use of mammography during the baseline period. Each of the project's intervention components is a cue to action: a physician prompt for mammography referral within the medical record of procedure-due women, a reminder postcard for scheduled appointments, and a telephone call to encourage rescheduling of missed appointments. The interventions are initiated by a computerized information management system in the existing network of health care services. The patient's out-of-pocket mammography expense has been eliminated in three of the five sites. Although their efficacy as individual interventions has been well established, a controlled trial of computer prompts to physicians, reduced expense for patients, and patient appointment reminders as an integrated system in inner-city medical care settings has not been previously described. We have implemented the prompting, facilitated rescheduling procedures, and eliminated patient expense for mammography at three of five eventual clinical sites. This report provides an overview of the study's design, data management system, and methodology for evaluation. PMID:2511584

Modifying prescribing behaviour of angiotensin receptor blockers by selectively rescinding managerial prior authorization requirements for losartan.

PubMed

Kahan, Natan R; Chinitz, David P; Blackman, Shimon; Waitman, Dan-Andrei; Vardy, Daniel A

2011-12-01

To evaluate whether rescinding the prior authorization (PA) requirement (managerial pre-approval) for losartan in an health maintenance organization (HMO) could reduce prescribing of the more expensive angiotensin receptor blockers (ARBs). HMO physicians were notified that losartan would no longer require PA, and appropriate changes were made to the electronic prescribing computer program. The monthly distribution by drug of the number of prescriptions for ARBs dispensed for new patients was calculated before and after the policy change from data captured from electronic records. The proportion of patients (percentage and 95% confidence interval) treated with losartan who met the criteria for treatment with ARBs (hypertension or cardiac insufficiency in patients who have developed adverse effects in response to angiotensin-converting enzyme inhibitors or macroproteinuria) during the first month after the PA requirement was rescinded was calculated. The total number of PA requests for ARBs declined by 48.6% from 961 in December 2008, the month before the policy change, to 494 the following January, rising again to 651 during January 2010. Prescription incidence changed from 121 to 255 patients treated per month (114% increase) for losartan, from 15 to 16 (6.7% increase) for candesartan, and from 89 to 71 (20.2% decrease) for valsartan. The duration of effect for decrease in ARB requests for the more expensive drugs was approximately 1 year. Only 23.3% (95% confidence interval 18.1-28.4) of patients receiving losartan met the criteria for receiving ARBs. Rescinding the PA requirement for this drug alone was an effective limited-duration strategy for reduction of prescription of relatively expensive drugs. © 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.

25 CFR 700.163 - Expenses in searching for replacement location-nonresidential moves.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., including— (a) Transportation computed at prevailing federal per diem and mileage allowance schedules; meals and lodging away from home; (b) Time spent searching, based on reasonable earnings; (c) Fees paid to a...

25 CFR 700.163 - Expenses in searching for replacement location-nonresidential moves.

Code of Federal Regulations, 2011 CFR

2011-04-01

..., including— (a) Transportation computed at prevailing federal per diem and mileage allowance schedules; meals and lodging away from home; (b) Time spent searching, based on reasonable earnings; (c) Fees paid to a...

SIMULATING ATMOSPHERIC EXPOSURE USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME

EPA Science Inventory

Multimedia Risk assessments require the temporal integration of atmospheric concentration and deposition estimates with other media modules. However, providing an extended time series of estimates is computationally expensive. An alternative approach is to substitute long-ter...

47 CFR 54.639 - Ineligible expenses.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., including the following: i. Computers, including servers, and related hardware (e.g., printers, scanners, laptops), unless used exclusively for network management, maintenance, or other network operations; ii... installation/construction; marketing studies, marketing activities, or outreach to potential network members...

47 CFR 54.639 - Ineligible expenses.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., including the following: i. Computers, including servers, and related hardware (e.g., printers, scanners, laptops), unless used exclusively for network management, maintenance, or other network operations; ii... installation/construction; marketing studies, marketing activities, or outreach to potential network members...

Application of the MacCormack scheme to overland flow routing for high-spatial resolution distributed hydrological model

NASA Astrophysics Data System (ADS)

Zhang, Ling; Nan, Zhuotong; Liang, Xu; Xu, Yi; Hernández, Felipe; Li, Lianxia

2018-03-01

Although process-based distributed hydrological models (PDHMs) are evolving rapidly over the last few decades, their extensive applications are still challenged by the computational expenses. This study attempted, for the first time, to apply the numerically efficient MacCormack algorithm to overland flow routing in a representative high-spatial resolution PDHM, i.e., the distributed hydrology-soil-vegetation model (DHSVM), in order to improve its computational efficiency. The analytical verification indicates that both the semi and full versions of the MacCormack schemes exhibit robust numerical stability and are more computationally efficient than the conventional explicit linear scheme. The full-version outperforms the semi-version in terms of simulation accuracy when a same time step is adopted. The semi-MacCormack scheme was implemented into DHSVM (version 3.1.2) to solve the kinematic wave equations for overland flow routing. The performance and practicality of the enhanced DHSVM-MacCormack model was assessed by performing two groups of modeling experiments in the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The experiments show that DHSVM-MacCormack can considerably improve the computational efficiency without compromising the simulation accuracy of the original DHSVM model. More specifically, with the same computational environment and model settings, the computational time required by DHSVM-MacCormack can be reduced to several dozen minutes for a simulation period of three months (in contrast with one day and a half by the original DHSVM model) without noticeable sacrifice of the accuracy. The MacCormack scheme proves to be applicable to overland flow routing in DHSVM, which implies that it can be coupled into other PHDMs for watershed routing to either significantly improve their computational efficiency or to make the kinematic wave routing for high resolution modeling computational feasible.

Computing sextic centrifugal distortion constants by DFT: A benchmark analysis on halogenated compounds

NASA Astrophysics Data System (ADS)

Pietropolli Charmet, Andrea; Stoppa, Paolo; Tasinato, Nicola; Giorgianni, Santi

2017-05-01

This work presents a benchmark study on the calculation of the sextic centrifugal distortion constants employing cubic force fields computed by means of density functional theory (DFT). For a set of semi-rigid halogenated organic compounds several functionals (B2PLYP, B3LYP, B3PW91, M06, M06-2X, O3LYP, X3LYP, ωB97XD, CAM-B3LYP, LC-ωPBE, PBE0, B97-1 and B97-D) were used for computing the sextic centrifugal distortion constants. The effects related to the size of basis sets and the performances of hybrid approaches, where the harmonic data obtained at higher level of electronic correlation are coupled with cubic force constants yielded by DFT functionals, are presented and discussed. The predicted values were compared to both the available data published in the literature and those obtained by calculations carried out at increasing level of electronic correlation: Hartree-Fock Self Consistent Field (HF-SCF), second order Møller-Plesset perturbation theory (MP2), and coupled-cluster single and double (CCSD) level of theory. Different hybrid approaches, having the cubic force field computed at DFT level of theory coupled to harmonic data computed at increasing level of electronic correlation (up to CCSD level of theory augmented by a perturbational estimate of the effects of connected triple excitations, CCSD(T)) were considered. The obtained results demonstrate that they can represent reliable and computationally affordable methods to predict sextic centrifugal terms with an accuracy almost comparable to that yielded by the more expensive anharmonic force fields fully computed at MP2 and CCSD levels of theory. In view of their reduced computational cost, these hybrid approaches pave the route to the study of more complex systems.

Magnetic Shield for Adiabatic Demagnetization Refrigerators (ADR)

NASA Technical Reports Server (NTRS)

Chui, Talso C.; Haddad, Nicolas E.

2013-01-01

A new method was developed for creating a less expensive shield for ADRs using 1018 carbon steel. This shield has been designed to have similar performance to the expensive vanadium permendur shields, but the cost is 30 to 50% less. Also, these shields can be stocked in a variety of sizes, eliminating the need for special forgings, which also greatly reduces cost.

Not Just a Cover

DTIC Science & Technology

2009-02-01

provided the US Military cost avoidance by reducing corrosion and the resulting degradation The Problem Dehumidification Systems very expensive cumbersome...effective establishes greenhouse effect Vapor Corrosion Inhibitors moderate expense hermetic environments required effective if used properly • A 2003 GAO...cases they accelerated corrosion ( Greenhouse Effect) • Initiated a search for a better form of protection that would • Act to remove moisture/water

Delamination detection using methods of computational intelligence

NASA Astrophysics Data System (ADS)

Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata

2012-11-01

Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.

Multi-chain Markov chain Monte Carlo methods for computationally expensive models

NASA Astrophysics Data System (ADS)

Huang, M.; Ray, J.; Ren, H.; Hou, Z.; Bao, J.

2017-12-01

Markov chain Monte Carlo (MCMC) methods are used to infer model parameters from observational data. The parameters are inferred as probability densities, thus capturing estimation error due to sparsity of the data, and the shortcomings of the model. Multiple communicating chains executing the MCMC method have the potential to explore the parameter space better, and conceivably accelerate the convergence to the final distribution. We present results from tests conducted with the multi-chain method to show how the acceleration occurs i.e., for loose convergence tolerances, the multiple chains do not make much of a difference. The ensemble of chains also seems to have the ability to accelerate the convergence of a few chains that might start from suboptimal starting points. Finally, we show the performance of the chains in the estimation of O(10) parameters using computationally expensive forward models such as the Community Land Model, where the sampling burden is distributed over multiple chains.

On Using Surrogates with Genetic Programming.

PubMed

Hildebrandt, Torsten; Branke, Jürgen

2015-01-01

One way to accelerate evolutionary algorithms with expensive fitness evaluations is to combine them with surrogate models. Surrogate models are efficiently computable approximations of the fitness function, derived by means of statistical or machine learning techniques from samples of fully evaluated solutions. But these models usually require a numerical representation, and therefore cannot be used with the tree representation of genetic programming (GP). In this paper, we present a new way to use surrogate models with GP. Rather than using the genotype directly as input to the surrogate model, we propose using a phenotypic characterization. This phenotypic characterization can be computed efficiently and allows us to define approximate measures of equivalence and similarity. Using a stochastic, dynamic job shop scenario as an example of simulation-based GP with an expensive fitness evaluation, we show how these ideas can be used to construct surrogate models and improve the convergence speed and solution quality of GP.

An optimized and low-cost FPGA-based DNA sequence alignment--a step towards personal genomics.

PubMed

Shah, Hurmat Ali; Hasan, Laiq; Ahmad, Nasir

2013-01-01

DNA sequence alignment is a cardinal process in computational biology but also is much expensive computationally when performing through traditional computational platforms like CPU. Of many off the shelf platforms explored for speeding up the computation process, FPGA stands as the best candidate due to its performance per dollar spent and performance per watt. These two advantages make FPGA as the most appropriate choice for realizing the aim of personal genomics. The previous implementation of DNA sequence alignment did not take into consideration the price of the device on which optimization was performed. This paper presents optimization over previous FPGA implementation that increases the overall speed-up achieved as well as the price incurred by the platform that was optimized. The optimizations are (1) The array of processing elements is made to run on change in input value and not on clock, so eliminating the need for tight clock synchronization, (2) the implementation is unrestrained by the size of the sequences to be aligned, (3) the waiting time required for the sequences to load to FPGA is reduced to the minimum possible and (4) an efficient method is devised to store the output matrix that make possible to save the diagonal elements to be used in next pass, in parallel with the computation of output matrix. Implemented on Spartan3 FPGA, this implementation achieved 20 times performance improvement in terms of CUPS over GPP implementation.

QMachine: commodity supercomputing in web browsers.

PubMed

Wilkinson, Sean R; Almeida, Jonas S

2014-06-09

Ongoing advancements in cloud computing provide novel opportunities in scientific computing, especially for distributed workflows. Modern web browsers can now be used as high-performance workstations for querying, processing, and visualizing genomics' "Big Data" from sources like The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) without local software installation or configuration. The design of QMachine (QM) was driven by the opportunity to use this pervasive computing model in the context of the Web of Linked Data in Biomedicine. QM is an open-sourced, publicly available web service that acts as a messaging system for posting tasks and retrieving results over HTTP. The illustrative application described here distributes the analyses of 20 Streptococcus pneumoniae genomes for shared suffixes. Because all analytical and data retrieval tasks are executed by volunteer machines, few server resources are required. Any modern web browser can submit those tasks and/or volunteer to execute them without installing any extra plugins or programs. A client library provides high-level distribution templates including MapReduce. This stark departure from the current reliance on expensive server hardware running "download and install" software has already gathered substantial community interest, as QM received more than 2.2 million API calls from 87 countries in 12 months. QM was found adequate to deliver the sort of scalable bioinformatics solutions that computation- and data-intensive workflows require. Paradoxically, the sandboxed execution of code by web browsers was also found to enable them, as compute nodes, to address critical privacy concerns that characterize biomedical environments.

Trajectory-based visual localization in underwater surveying missions.

PubMed

Burguera, Antoni; Bonin-Font, Francisco; Oliver, Gabriel

2015-01-14

We present a new vision-based localization system applied to an autonomous underwater vehicle (AUV) with limited sensing and computation capabilities. The traditional EKF-SLAM approaches are usually expensive in terms of execution time; the approach presented in this paper strengthens this method by adopting a trajectory-based schema that reduces the computational requirements. The pose of the vehicle is estimated using an extended Kalman filter (EKF), which predicts the vehicle motion by means of a visual odometer and corrects these predictions using the data associations (loop closures) between the current frame and the previous ones. One of the most important steps in this procedure is the image registration method, as it reinforces the data association and, thus, makes it possible to close loops reliably. Since the use of standard EKFs entail linearization errors that can distort the vehicle pose estimations, the approach has also been tested using an iterated Kalman filter (IEKF). Experiments have been conducted using a real underwater vehicle in controlled scenarios and in shallow sea waters, showing an excellent performance with very small errors, both in the vehicle pose and in the overall trajectory estimates.

DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors.

PubMed

Schmollinger, Martin; Nieselt, Kay; Kaufmann, Michael; Morgenstern, Burkhard

2004-09-09

Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a) pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b) For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

The Atmospheric Data Acquisition And Interpolation Process For Center-TRACON Automation System

NASA Technical Reports Server (NTRS)

Jardin, M. R.; Erzberger, H.; Denery, Dallas G. (Technical Monitor)

1995-01-01

The Center-TRACON Automation System (CTAS), an advanced new air traffic automation program, requires knowledge of spatial and temporal atmospheric conditions such as the wind speed and direction, the temperature and the pressure in order to accurately predict aircraft trajectories. Real-time atmospheric data is available in a grid format so that CTAS must interpolate between the grid points to estimate the atmospheric parameter values. The atmospheric data grid is generally not in the same coordinate system as that used by CTAS so that coordinate conversions are required. Both the interpolation and coordinate conversion processes can introduce errors into the atmospheric data and reduce interpolation accuracy. More accurate algorithms may be computationally expensive or may require a prohibitively large amount of data storage capacity so that trade-offs must be made between accuracy and the available computational and data storage resources. The atmospheric data acquisition and processing employed by CTAS will be outlined in this report. The effects of atmospheric data processing on CTAS trajectory prediction will also be analyzed, and several examples of the trajectory prediction process will be given.

Development of a surgical navigation system based on 3D Slicer for intraoperative implant placement surgery

PubMed Central

Chen, Xiaojun; Xu, Lu; Wang, Huixiang; Wang, Fang; Wang, Qiugen; Kikinis, Ron

2017-01-01

Implant placement has been widely used in various kinds of surgery. However, accurate intraoperative drilling performance is essential to avoid injury to adjacent structures. Although some commercially-available surgical navigation systems have been approved for clinical applications, these systems are expensive and the source code is not available to researchers. 3D Slicer is a free, open source software platform for the research community of computer-aided surgery. In this study, a loadable module based on Slicer has been developed and validated to support surgical navigation. This research module allows reliable calibration of the surgical drill, point-based registration and surface matching registration, so that the position and orientation of the surgical drill can be tracked and displayed on the computer screen in real time, aiming at reducing risks. In accuracy verification experiments, the mean target registration error (TRE) for point-based and surface-based registration were 0.31±0.06mm and 1.01±0.06mm respectively, which should meet clinical requirements. Both phantom and cadaver experiments demonstrated the feasibility of our surgical navigation software module. PMID:28109564

Distributed Parallel Processing and Dynamic Load Balancing Techniques for Multidisciplinary High Speed Aircraft Design

NASA Technical Reports Server (NTRS)

Krasteva, Denitza T.

1998-01-01

Multidisciplinary design optimization (MDO) for large-scale engineering problems poses many challenges (e.g., the design of an efficient concurrent paradigm for global optimization based on disciplinary analyses, expensive computations over vast data sets, etc.) This work focuses on the application of distributed schemes for massively parallel architectures to MDO problems, as a tool for reducing computation time and solving larger problems. The specific problem considered here is configuration optimization of a high speed civil transport (HSCT), and the efficient parallelization of the embedded paradigm for reasonable design space identification. Two distributed dynamic load balancing techniques (random polling and global round robin with message combining) and two necessary termination detection schemes (global task count and token passing) were implemented and evaluated in terms of effectiveness and scalability to large problem sizes and a thousand processors. The effect of certain parameters on execution time was also inspected. Empirical results demonstrated stable performance and effectiveness for all schemes, and the parametric study showed that the selected algorithmic parameters have a negligible effect on performance.

A fast algorithm for multiscale electromagnetic problems using interpolative decomposition and multilevel fast multipole algorithm

NASA Astrophysics Data System (ADS)

Pan, Xiao-Min; Wei, Jian-Gong; Peng, Zhen; Sheng, Xin-Qing

2012-02-01

The interpolative decomposition (ID) is combined with the multilevel fast multipole algorithm (MLFMA), denoted by ID-MLFMA, to handle multiscale problems. The ID-MLFMA first generates ID levels by recursively dividing the boxes at the finest MLFMA level into smaller boxes. It is specifically shown that near-field interactions with respect to the MLFMA, in the form of the matrix vector multiplication (MVM), are efficiently approximated at the ID levels. Meanwhile, computations on far-field interactions at the MLFMA levels remain unchanged. Only a small portion of matrix entries are required to approximate coupling among well-separated boxes at the ID levels, and these submatrices can be filled without computing the complete original coupling matrix. It follows that the matrix filling in the ID-MLFMA becomes much less expensive. The memory consumed is thus greatly reduced and the MVM is accelerated as well. Several factors that may influence the accuracy, efficiency and reliability of the proposed ID-MLFMA are investigated by numerical experiments. Complex targets are calculated to demonstrate the capability of the ID-MLFMA algorithm.

Down to the roughness scale assessment of piston-ring/liner contacts

NASA Astrophysics Data System (ADS)

Checo, H. M.; Jaramillo, A.; Ausas, R. F.; Jai, M.; Buscaglia, G. C.

2017-02-01

The effects of surface roughness in hydrodynamic bearings been accounted for through several approaches, the most widely used being averaging or stochastic techniques. With these the surface is not treated “as it is”, but by means of an assumed probability distribution for the roughness. The so called direct, deterministic or measured-surface simulation) solve the lubrication problem with realistic surfaces down to the roughness scale. This leads to expensive computational problems. Most researchers have tackled this problem considering non-moving surfaces and neglecting the ring dynamics to reduce the computational burden. What is proposed here is to solve the fully-deterministic simulation both in space and in time, so that the actual movement of the surfaces and the rings dynamics are taken into account. This simulation is much more complex than previous ones, as it is intrinsically transient. The feasibility of these fully-deterministic simulations is illustrated two cases: fully deterministic simulation of liner surfaces with diverse finishings (honed and coated bores) with constant piston velocity and load on the ring and also in real engine conditions.

CMOS Image Sensor with a Built-in Lane Detector.

PubMed

Hsiao, Pei-Yung; Cheng, Hsien-Chein; Huang, Shih-Shinh; Fu, Li-Chen

2009-01-01

This work develops a new current-mode mixed signal Complementary Metal-Oxide-Semiconductor (CMOS) imager, which can capture images and simultaneously produce vehicle lane maps. The adopted lane detection algorithm, which was modified to be compatible with hardware requirements, can achieve a high recognition rate of up to approximately 96% under various weather conditions. Instead of a Personal Computer (PC) based system or embedded platform system equipped with expensive high performance chip of Reduced Instruction Set Computer (RISC) or Digital Signal Processor (DSP), the proposed imager, without extra Analog to Digital Converter (ADC) circuits to transform signals, is a compact, lower cost key-component chip. It is also an innovative component device that can be integrated into intelligent automotive lane departure systems. The chip size is 2,191.4 × 2,389.8 μm, and the package uses 40 pin Dual-In-Package (DIP). The pixel cell size is 18.45 × 21.8 μm and the core size of photodiode is 12.45 × 9.6 μm; the resulting fill factor is 29.7%.

Unfolding of Proteins: Thermal and Mechanical Unfolding

NASA Technical Reports Server (NTRS)

Hur, Joe S.; Darve, Eric

2004-01-01

We have employed a Hamiltonian model based on a self-consistent Gaussian appoximation to examine the unfolding process of proteins in external - both mechanical and thermal - force elds. The motivation was to investigate the unfolding pathways of proteins by including only the essence of the important interactions of the native-state topology. Furthermore, if such a model can indeed correctly predict the physics of protein unfolding, it can complement more computationally expensive simulations and theoretical work. The self-consistent Gaussian approximation by Micheletti et al. has been incorporated in our model to make the model mathematically tractable by signi cantly reducing the computational cost. All thermodynamic properties and pair contact probabilities are calculated by simply evaluating the values of a series of Incomplete Gamma functions in an iterative manner. We have compared our results to previous molecular dynamics simulation and experimental data for the mechanical unfolding of the giant muscle protein Titin (1TIT). Our model, especially in light of its simplicity and excellent agreement with experiment and simulation, demonstrates the basic physical elements necessary to capture the mechanism of protein unfolding in an external force field.

Resolvent analysis of shear flows using One-Way Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Rigas, Georgios; Schmidt, Oliver; Towne, Aaron; Colonius, Tim

2017-11-01

For three-dimensional flows, questions of stability, receptivity, secondary flows, and coherent structures require the solution of large partial-derivative eigenvalue problems. Reduced-order approximations are thus required for engineering prediction since these problems are often computationally intractable or prohibitively expensive. For spatially slowly evolving flows, such as jets and boundary layers, the One-Way Navier-Stokes (OWNS) equations permit a fast spatial marching procedure that results in a huge reduction in computational cost. Here, an adjoint-based optimization framework is proposed and demonstrated for calculating optimal boundary conditions and optimal volumetric forcing. The corresponding optimal response modes are validated against modes obtained in terms of global resolvent analysis. For laminar base flows, the optimal modes reveal modal and non-modal transition mechanisms. For turbulent base flows, they predict the evolution of coherent structures in a statistical sense. Results from the application of the method to three-dimensional laminar wall-bounded flows and turbulent jets will be presented. This research was supported by the Office of Naval Research (N00014-16-1-2445) and Boeing Company (CT-BA-GTA-1).

Model-based POD study of manual ultrasound inspection and sensitivity analysis using metamodel

NASA Astrophysics Data System (ADS)

Ribay, Guillemette; Artusi, Xavier; Jenson, Frédéric; Reece, Christopher; Lhuillier, Pierre-Emile

2016-02-01

The reliability of NDE can be quantified by using the Probability of Detection (POD) approach. Former studies have shown the potential of the model-assisted POD (MAPOD) approach to replace expensive experimental determination of POD curves. In this paper, we make use of CIVA software to determine POD curves for a manual ultrasonic inspection of a heavy component, for which a whole experimental POD campaign was not available. The influential parameters were determined by expert analysis. The semi-analytical models used in CIVA for wave propagation and beam-defect interaction have been validated in the range of variation of the influential parameters by comparison with finite element modelling (Athena). The POD curves are computed for « hit/miss » and « â versus a » analysis. The verification of Berens hypothesis is evaluated by statistical tools. A sensitivity study is performed to measure the relative influence of parameters on the defect response amplitude variance, using the Sobol sensitivity index. A meta-model is also built to reduce computing cost and enhance the precision of estimated index.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy.

PubMed

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-10-01

Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4-6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3-8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts.

Four-dimensional volume-of-interest reconstruction for cone-beam computed tomography-guided radiation therapy

PubMed Central

Ahmad, Moiz; Balter, Peter; Pan, Tinsu

2011-01-01

Purpose: Data sufficiency are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) on linear accelerator-integrated scanners for image-guided radiotherapy. Scan times must be in the range of 4–6 min to avoid undersampling artifacts. Various image reconstruction algorithms have been proposed to accommodate undersampled data acquisitions, but these algorithms are computationally expensive, may require long reconstruction times, and may require algorithm parameters to be optimized. The authors present a novel reconstruction method, 4D volume-of-interest (4D-VOI) reconstruction which suppresses undersampling artifacts and resolves lung tumor motion for undersampled 1-min scans. The 4D-VOI reconstruction is much less computationally expensive than other 4D-CBCT algorithms. Methods: The 4D-VOI method uses respiration-correlated projection data to reconstruct a four-dimensional (4D) image inside a VOI containing the moving tumor, and uncorrelated projection data to reconstruct a three-dimensional (3D) image outside the VOI. Anatomical motion is resolved inside the VOI and blurred outside the VOI. The authors acquired a 1-min. scan of an anthropomorphic chest phantom containing a moving water-filled sphere. The authors also used previously acquired 1-min scans for two lung cancer patients who had received CBCT-guided radiation therapy. The same raw data were used to test and compare the 4D-VOI reconstruction with the standard 4D reconstruction and the McKinnon-Bates (MB) reconstruction algorithms. Results: Both the 4D-VOI and the MB reconstructions suppress nearly all the streak artifacts compared with the standard 4D reconstruction, but the 4D-VOI has 3–8 times greater contrast-to-noise ratio than the MB reconstruction. In the dynamic chest phantom study, the 4D-VOI and the standard 4D reconstructions both resolved a moving sphere with an 18 mm displacement. The 4D-VOI reconstruction shows a motion blur of only 3 mm, whereas the MB reconstruction shows a motion blur of 13 mm. With graphics processing unit hardware used to accelerate computations, the 4D-VOI reconstruction required a 40-s reconstruction time. Conclusions: 4D-VOI reconstruction effectively reduces undersampling artifacts and resolves lung tumor motion in 4D-CBCT. The 4D-VOI reconstruction is computationally inexpensive compared with more sophisticated iterative algorithms. Compared with these algorithms, our 4D-VOI reconstruction is an attractive alternative in 4D-CBCT for reconstructing target motion without generating numerous streak artifacts. PMID:21992381

Space-filling designs for computer experiments: A review

DOE PAGES

Joseph, V. Roshan

2016-01-29

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

Space-filling designs for computer experiments: A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joseph, V. Roshan

Improving the quality of a product/process using a computer simulator is a much less expensive option than the real physical testing. However, simulation using computationally intensive computer models can be time consuming and therefore, directly doing the optimization on the computer simulator can be infeasible. Experimental design and statistical modeling techniques can be used for overcoming this problem. This article reviews experimental designs known as space-filling designs that are suitable for computer simulations. In the review, a special emphasis is given for a recently developed space-filling design called maximum projection design. Furthermore, its advantages are illustrated using a simulation conductedmore » for optimizing a milling process.« less

GPU-computing in econophysics and statistical physics

NASA Astrophysics Data System (ADS)

Preis, T.

2011-03-01

A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today's GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In particular computationally expensive analyses employed in financial market context are coded on a graphics card architecture which leads to a significant reduction of computing time. In order to demonstrate the wide range of possible applications, a standard model in statistical physics - the Ising model - is ported to a graphics card architecture as well, resulting in large speedup values.

A computer-based physics laboratory apparatus: Signal generator software

NASA Astrophysics Data System (ADS)

Thanakittiviroon, Tharest; Liangrocapart, Sompong

2005-09-01

This paper describes a computer-based physics laboratory apparatus to replace expensive instruments such as high-precision signal generators. This apparatus uses a sound card in a common personal computer to give sinusoidal signals with an accurate frequency that can be programmed to give different frequency signals repeatedly. An experiment on standing waves on an oscillating string uses this apparatus. In conjunction with interactive lab manuals, which have been developed using personal computers in our university, we achieve a complete set of low-cost, accurate, and easy-to-use equipment for teaching a physics laboratory.

A Toolkit for ARB to Integrate Custom Databases and Externally Built Phylogenies

DOE PAGES

Essinger, Steven D.; Reichenberger, Erin; Morrison, Calvin; ...

2015-01-21

Researchers are perpetually amassing biological sequence data. The computational approaches employed by ecologists for organizing this data (e.g. alignment, phylogeny, etc.) typically scale nonlinearly in execution time with the size of the dataset. This often serves as a bottleneck for processing experimental data since many molecular studies are characterized by massive datasets. To keep up with experimental data demands, ecologists are forced to choose between continually upgrading expensive in-house computer hardware or outsourcing the most demanding computations to the cloud. Outsourcing is attractive since it is the least expensive option, but does not necessarily allow direct user interaction with themore » data for exploratory analysis. Desktop analytical tools such as ARB are indispensable for this purpose, but they do not necessarily offer a convenient solution for the coordination and integration of datasets between local and outsourced destinations. Therefore, researchers are currently left with an undesirable tradeoff between computational throughput and analytical capability. To mitigate this tradeoff we introduce a software package to leverage the utility of the interactive exploratory tools offered by ARB with the computational throughput of cloud-based resources. Our pipeline serves as middleware between the desktop and the cloud allowing researchers to form local custom databases containing sequences and metadata from multiple resources and a method for linking data outsourced for computation back to the local database. Furthermore, a tutorial implementation of the toolkit is provided in the supporting information, S1 Tutorial.« less

A Toolkit for ARB to Integrate Custom Databases and Externally Built Phylogenies

PubMed Central

Essinger, Steven D.; Reichenberger, Erin; Morrison, Calvin; Blackwood, Christopher B.; Rosen, Gail L.

2015-01-01

Researchers are perpetually amassing biological sequence data. The computational approaches employed by ecologists for organizing this data (e.g. alignment, phylogeny, etc.) typically scale nonlinearly in execution time with the size of the dataset. This often serves as a bottleneck for processing experimental data since many molecular studies are characterized by massive datasets. To keep up with experimental data demands, ecologists are forced to choose between continually upgrading expensive in-house computer hardware or outsourcing the most demanding computations to the cloud. Outsourcing is attractive since it is the least expensive option, but does not necessarily allow direct user interaction with the data for exploratory analysis. Desktop analytical tools such as ARB are indispensable for this purpose, but they do not necessarily offer a convenient solution for the coordination and integration of datasets between local and outsourced destinations. Therefore, researchers are currently left with an undesirable tradeoff between computational throughput and analytical capability. To mitigate this tradeoff we introduce a software package to leverage the utility of the interactive exploratory tools offered by ARB with the computational throughput of cloud-based resources. Our pipeline serves as middleware between the desktop and the cloud allowing researchers to form local custom databases containing sequences and metadata from multiple resources and a method for linking data outsourced for computation back to the local database. A tutorial implementation of the toolkit is provided in the supporting information, S1 Tutorial. Availability: http://www.ece.drexel.edu/gailr/EESI/tutorial.php. PMID:25607539

Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

PubMed

Gilles, Luc; Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Ellerbroek, Brent

2013-05-01

This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

Strategies for reducing large fMRI data sets for independent component analysis.

PubMed

Wang, Ze; Wang, Jiongjiong; Calhoun, Vince; Rao, Hengyi; Detre, John A; Childress, Anna R

2006-06-01

In independent component analysis (ICA), principal component analysis (PCA) is generally used to reduce the raw data to a few principal components (PCs) through eigenvector decomposition (EVD) on the data covariance matrix. Although this works for spatial ICA (sICA) on moderately sized fMRI data, it is intractable for temporal ICA (tICA), since typical fMRI data have a high spatial dimension, resulting in an unmanageable data covariance matrix. To solve this problem, two practical data reduction methods are presented in this paper. The first solution is to calculate the PCs of tICA from the PCs of sICA. This approach works well for moderately sized fMRI data; however, it is highly computationally intensive, even intractable, when the number of scans increases. The second solution proposed is to perform PCA decomposition via a cascade recursive least squared (CRLS) network, which provides a uniform data reduction solution for both sICA and tICA. Without the need to calculate the covariance matrix, CRLS extracts PCs directly from the raw data, and the PC extraction can be terminated after computing an arbitrary number of PCs without the need to estimate the whole set of PCs. Moreover, when the whole data set becomes too large to be loaded into the machine memory, CRLS-PCA can save data retrieval time by reading the data once, while the conventional PCA requires numerous data retrieval steps for both covariance matrix calculation and PC extractions. Real fMRI data were used to evaluate the PC extraction precision, computational expense, and memory usage of the presented methods.

Fixed-point image orthorectification algorithms for reduced computational cost

NASA Astrophysics Data System (ADS)

French, Joseph Clinton

Imaging systems have been applied to many new applications in recent years. With the advent of low-cost, low-power focal planes and more powerful, lower cost computers, remote sensing applications have become more wide spread. Many of these applications require some form of geolocation, especially when relative distances are desired. However, when greater global positional accuracy is needed, orthorectification becomes necessary. Orthorectification is the process of projecting an image onto a Digital Elevation Map (DEM), which removes terrain distortions and corrects the perspective distortion by changing the viewing angle to be perpendicular to the projection plane. Orthorectification is used in disaster tracking, landscape management, wildlife monitoring and many other applications. However, orthorectification is a computationally expensive process due to floating point operations and divisions in the algorithm. To reduce the computational cost of on-board processing, two novel algorithm modifications are proposed. One modification is projection utilizing fixed-point arithmetic. Fixed point arithmetic removes the floating point operations and reduces the processing time by operating only on integers. The second modification is replacement of the division inherent in projection with a multiplication of the inverse. The inverse must operate iteratively. Therefore, the inverse is replaced with a linear approximation. As a result of these modifications, the processing time of projection is reduced by a factor of 1.3x with an average pixel position error of 0.2% of a pixel size for 128-bit integer processing and over 4x with an average pixel position error of less than 13% of a pixel size for a 64-bit integer processing. A secondary inverse function approximation is also developed that replaces the linear approximation with a quadratic. The quadratic approximation produces a more accurate approximation of the inverse, allowing for an integer multiplication calculation to be used in place of the traditional floating point division. This method increases the throughput of the orthorectification operation by 38% when compared to floating point processing. Additionally, this method improves the accuracy of the existing integer-based orthorectification algorithms in terms of average pixel distance, increasing the accuracy of the algorithm by more than 5x. The quadratic function reduces the pixel position error to 2% and is still 2.8x faster than the 128-bit floating point algorithm.

Investigation of comparative effectiveness research in Asia, Europe, and North America.

PubMed

Patel, Isha; Rarus, Rachel; Tan, Xi; Lee, E K; Guy, Jason; Ahmad, Akram; Chang, Jongwha

2015-01-01

Comparative effectiveness research (CER) is an important branch of pharmacoeconomics that systematically studies and evaluates the cost-effectiveness of medical interventions. CER plays instrumental roles in guiding government public health policy programs and insurance. Countries throughout the world use different methods of CER to help make medical decisions based on providing optimal therapy at a reduced cost. Expenses to the healthcare system continue to rise, and CER is one-way in which expenses could be curbed in the future by applying cost-effectiveness evidence to clinical decisions. China, India, South Korea, and the United Kingdom are of essential focus because these country's economies and health care expenses continue to expand. The structures and use of CER are diverse throughout these countries, and each is of prime importance. By conducting this thorough comparison of CER in different nations, strategies and organizational setups from different countries can be applied to help guide public health and medical decision-making in order to continue to expand the establishment and role of CER programs. The patient-centered medical home has been created to help reduce costs in the primary care sector and to help improve the effectiveness of therapy. Barriers to CER are also important as many stakeholders need to be able to work together to provide the best CER evidence. The advancement of CER in multiple countries throughout the world provides a possible way of reducing costs to the healthcare system in an age of expanding expenses.

Contact Graph Routing

NASA Technical Reports Server (NTRS)

Burleigh, Scott C.

2011-01-01

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.

Attitude to the Use of the Computer for Learning Biological Concepts and Achievement of Students in an Environment Dominated by Indigenous Technology.

ERIC Educational Resources Information Center

Jegede, Olugbemiro J.; And Others

The use of computers to facilitate learning is yet to make an appreciable in-road into the teaching-learning process in most developing Third World countries. The purchase cost and maintenance expenses of the equipment are the major inhibiting factors related to adoption of this high technology in these countries. This study investigated: (1) the…

Analysis of Disaster Preparedness Planning Measures in DoD Computer Facilities

DTIC Science & Technology

1993-09-01

city, stae, aod ZP code) 10 Source of Funding Numbers SProgram Element No lProject No ITask No lWork Unit Accesion I 11 Title include security...Computer Disaster Recovery .... 13 a. PC and LAN Lessons Learned . . ..... 13 2. Distributed Architectures . . . .. . 14 3. Backups...amount of expense, but no client problems." (Leeke, 1993, p. 8) 2. Distributed Architectures The majority of operations that were disrupted by the

Network Support for Group Coordination

DTIC Science & Technology

2000-01-01

telecommuting and ubiquitous computing [40], the advent of networked multimedia, and less expensive technology have shifted telecollaboration into...of Computer Engineering,Santa Cruz,CA,95064 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/ MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10...participants A and B, the payoff structure for choosing two actions i and j is P = Aij + Bij . If P = 0, then the interaction is called a zero -sum game, and

High-Fidelity Simulations of Electromagnetic Propagation and RF Communication Systems

DTIC Science & Technology

2017-05-01

addition to high -fidelity RF propagation modeling, lower-fidelity mod- els, which are less computationally burdensome, are available via a C++ API...expensive to perform, requiring roughly one hour of computer time with 36 available cores and ray tracing per- formed by a single high -end GPU...ER D C TR -1 7- 2 Military Engineering Applied Research High -Fidelity Simulations of Electromagnetic Propagation and RF Communication

Development of Multidisciplinary, Multifidelity Analysis, Integration, and Optimization of Aerospace Vehicles

DTIC Science & Technology

2010-02-27

investigated in more detail. The intermediate level of fidelity, though more expensive, is then used to refine the analysis , add geometric detail, and...design stage is used to further refine the analysis , narrowing the design to a handful of options. Figure 1. Integrated Hierarchical Framework. In...computational structural and computational fluid modeling. For the structural analysis tool we used McIntosh Structural Dynamics’ finite element code CNEVAL

COST FUNCTION STUDIES FOR POWER REACTORS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heestand, J.; Wos, L.T.

1961-11-01

A function to evaluate the cost of electricity produced by a nuclear power reactor was developed. The basic equation, revenue = capital charges + profit + operating expenses, was expanded in terms of various cost parameters to enable analysis of multiregion nuclear reactors with uranium and/or plutonium for fuel. A corresponding IBM 704 computer program, which will compute either the price of electricity or the value of plutonium, is presented in detail. (auth)

Clean then Assemble Versus Assemble then Clean: Several Comparisons

NASA Technical Reports Server (NTRS)

Welker, Roger W.

2004-01-01

Cleanliness of manufactured parts and assemblies is a significant issue in many industries including disk drives, semiconductors, aerospace, and medical devices. Clean manufacturing requires cleanroom floor space and cleaning technology that are both expensive to own and expensive to operate. Strategies to reduce these costs are an important consideration. One strategy shown to be effective at reducing costs is to assemble parts into subassemblies and then clean the subassembly, rather than clean the individual parts first and then assemble them. One advantage is that assembly outside of the cleanroom reduces the amount of cleanroom floor space and its associated operating cost premium. A second advantage is that this strategy reduces the number of individual parts that must be cleaned prior to assembly, reducing the number of cleaning baskets, handling and, possibly, reducing the number of cleaners. The assemble then clean strategy also results in a part that is significantly cleaner because contamination generated during the assembly steps are more effectively removed that normally can be achieved by hand wiping after assembly in the cleanroom.

Sensitivity analysis and approximation methods for general eigenvalue problems

NASA Technical Reports Server (NTRS)

Murthy, D. V.; Haftka, R. T.

1986-01-01

Optimization of dynamic systems involving complex non-hermitian matrices is often computationally expensive. Major contributors to the computational expense are the sensitivity analysis and reanalysis of a modified design. The present work seeks to alleviate this computational burden by identifying efficient sensitivity analysis and approximate reanalysis methods. For the algebraic eigenvalue problem involving non-hermitian matrices, algorithms for sensitivity analysis and approximate reanalysis are classified, compared and evaluated for efficiency and accuracy. Proper eigenvector normalization is discussed. An improved method for calculating derivatives of eigenvectors is proposed based on a more rational normalization condition and taking advantage of matrix sparsity. Important numerical aspects of this method are also discussed. To alleviate the problem of reanalysis, various approximation methods for eigenvalues are proposed and evaluated. Linear and quadratic approximations are based directly on the Taylor series. Several approximation methods are developed based on the generalized Rayleigh quotient for the eigenvalue problem. Approximation methods based on trace theorem give high accuracy without needing any derivatives. Operation counts for the computation of the approximations are given. General recommendations are made for the selection of appropriate approximation technique as a function of the matrix size, number of design variables, number of eigenvalues of interest and the number of design points at which approximation is sought.

Computational search for rare-earth free hard-magnetic materials

NASA Astrophysics Data System (ADS)

Flores Livas, José A.; Sharma, Sangeeta; Dewhurst, John Kay; Gross, Eberhard; MagMat Team

2015-03-01

It is difficult to over state the importance of hard magnets for human life in modern times; they enter every walk of our life from medical equipments (NMR) to transport (trains, planes, cars, etc) to electronic appliances (for house hold use to computers). All the known hard magnets in use today contain rare-earth elements, extraction of which is expensive and environmentally harmful. Rare-earths are also instrumental in tipping the balance of world economy as most of them are mined in limited specific parts of the world. Hence it would be ideal to have similar characteristics as a hard magnet but without or at least with reduced amount of rare-earths. This is the main goal of our work: search for rare-earth-free magnets. To do so we employ a combination of density functional theory and crystal prediction methods. The quantities which define a hard magnet are magnetic anisotropy energy (MAE) and saturation magnetization (Ms), which are the quantities we maximize in search for an ideal magnet. In my talk I will present details of the computation search algorithm together with some potential newly discovered rare-earth free hard magnet. J.A.F.L. acknowledge financial support from EU's 7th Framework Marie-Curie scholarship program within the ``ExMaMa'' Project (329386).

Effect of Turbulence Modeling on an Excited Jet

NASA Technical Reports Server (NTRS)

Brown, Clifford A.; Hixon, Ray

2010-01-01

The flow dynamics in a high-speed jet are dominated by unsteady turbulent flow structures in the plume. Jet excitation seeks to control these flow structures through the natural instabilities present in the initial shear layer of the jet. Understanding and optimizing the excitation input, for jet noise reduction or plume mixing enhancement, requires many trials that may be done experimentally or computationally at a significant cost savings. Numerical simulations, which model various parts of the unsteady dynamics to reduce the computational expense of the simulation, must adequately capture the unsteady flow dynamics in the excited jet for the results are to be used. Four CFD methods are considered for use in an excited jet problem, including two turbulence models with an Unsteady Reynolds Averaged Navier-Stokes (URANS) solver, one Large Eddy Simulation (LES) solver, and one URANS/LES hybrid method. Each method is used to simulate a simplified excited jet and the results are evaluated based on the flow data, computation time, and numerical stability. The knowledge gained about the effect of turbulence modeling and CFD methods from these basic simulations will guide and assist future three-dimensional (3-D) simulations that will be used to understand and optimize a realistic excited jet for a particular application.

Physically weighted approximations of unsteady aerodynamic forces using the minimum-state method

NASA Technical Reports Server (NTRS)

Karpel, Mordechay; Hoadley, Sherwood Tiffany

1991-01-01

The Minimum-State Method for rational approximation of unsteady aerodynamic force coefficient matrices, modified to allow physical weighting of the tabulated aerodynamic data, is presented. The approximation formula and the associated time-domain, state-space, open-loop equations of motion are given, and the numerical procedure for calculating the approximation matrices, with weighted data and with various equality constraints are described. Two data weighting options are presented. The first weighting is for normalizing the aerodynamic data to maximum unit value of each aerodynamic coefficient. The second weighting is one in which each tabulated coefficient, at each reduced frequency value, is weighted according to the effect of an incremental error of this coefficient on aeroelastic characteristics of the system. This weighting yields a better fit of the more important terms, at the expense of less important ones. The resulting approximate yields a relatively low number of aerodynamic lag states in the subsequent state-space model. The formulation forms the basis of the MIST computer program which is written in FORTRAN for use on the MicroVAX computer and interfaces with NASA's Interaction of Structures, Aerodynamics and Controls (ISAC) computer program. The program structure, capabilities and interfaces are outlined in the appendices, and a numerical example which utilizes Rockwell's Active Flexible Wing (AFW) model is given and discussed.

Quantization and training of object detection networks with low-precision weights and activations

NASA Astrophysics Data System (ADS)

Yang, Bo; Liu, Jian; Zhou, Li; Wang, Yun; Chen, Jie

2018-01-01

As convolutional neural networks have demonstrated state-of-the-art performance in object recognition and detection, there is a growing need for deploying these systems on resource-constrained mobile platforms. However, the computational burden and energy consumption of inference for these networks are significantly higher than what most low-power devices can afford. To address these limitations, this paper proposes a method to train object detection networks with low-precision weights and activations. The probability density functions of weights and activations of each layer are first directly estimated using piecewise Gaussian models. Then, the optimal quantization intervals and step sizes for each convolution layer are adaptively determined according to the distribution of weights and activations. As the most computationally expensive convolutions can be replaced by effective fixed point operations, the proposed method can drastically reduce computation complexity and memory footprint. Performing on the tiny you only look once (YOLO) and YOLO architectures, the proposed method achieves comparable accuracy to their 32-bit counterparts. As an illustration, the proposed 4-bit and 8-bit quantized versions of the YOLO model achieve a mean average precision of 62.6% and 63.9%, respectively, on the Pascal visual object classes 2012 test dataset. The mAP of the 32-bit full-precision baseline model is 64.0%.

Enhanced algorithms for stochastic programming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishna, Alamuru S.

1993-09-01

In this dissertation, we present some of the recent advances made in solving two-stage stochastic linear programming problems of large size and complexity. Decomposition and sampling are two fundamental components of techniques to solve stochastic optimization problems. We describe improvements to the current techniques in both these areas. We studied different ways of using importance sampling techniques in the context of Stochastic programming, by varying the choice of approximation functions used in this method. We have concluded that approximating the recourse function by a computationally inexpensive piecewise-linear function is highly efficient. This reduced the problem from finding the mean ofmore » a computationally expensive functions to finding that of a computationally inexpensive function. Then we implemented various variance reduction techniques to estimate the mean of a piecewise-linear function. This method achieved similar variance reductions in orders of magnitude less time than, when we directly applied variance-reduction techniques directly on the given problem. In solving a stochastic linear program, the expected value problem is usually solved before a stochastic solution and also to speed-up the algorithm by making use of the information obtained from the solution of the expected value problem. We have devised a new decomposition scheme to improve the convergence of this algorithm.« less

History of computer-assisted orthopedic surgery (CAOS) in sports medicine.

PubMed

Jackson, Douglas W; Simon, Timothy M

2008-06-01

Computer-assisted orthopedic surgery and navigation applications have a history rooted in the desire to link imaging technology with real-time anatomic landmarks. Although applications are still evolving in the clinical and research setting, computer-assisted orthopedic surgery has already demonstrated in certain procedures its potential for improving the surgeon's accuracy, reproducibility (once past the learning curve), and in reducing outlier outcomes. It is also being used as an educational tool to assist less experienced surgeons in interpreting measurements and precision placements related to well defined anatomic landmarks. It also can assist experienced surgeons, in real-time, plan their bony cuts, tunnel placement, and with ligament balancing. Presently, the additional time, the expense to acquire the needed software and hardware, and restricted reimbursement have slowed the widespread use of navigation. Its current applications have been primarily in joint replacement surgery, spine surgery, and trauma. It has not been widely used in the clinical setting for sports medicine procedures. Sports medicine applications such as individualizing tunnel placement in ligament surgery, opening wedge osteotomy with and without accompanying ligament reconstruction, and balancing and tensioning of the ligaments during the procedure (allowing real-time corrections if necessary) are currently being evaluated and being used on a limited clinical basis.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

PubMed

Guo, Hao; Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%.

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network

PubMed Central

Qin, Mengna; Chen, Junjie; Xu, Yong; Xiang, Jie

2017-01-01

High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional methods for processing high-order functional connectivity networks generally include the clustering method, which reduces data dimensionality. As a result, such networks cannot be effectively interpreted in the context of neurology. Additionally, due to the large scale of high-order functional connectivity networks, it can be computationally very expensive to use complex network or graph theory to calculate certain topological properties. Here, we propose a novel method of generating a high-order minimum spanning tree functional connectivity network. This method increases the neurological significance of the high-order functional connectivity network, reduces network computing consumption, and produces a network scale that is conducive to subsequent network analysis. To ensure the quality of the topological information in the network structure, we used frequent subgraph mining technology to capture the discriminative subnetworks as features and combined this with quantifiable local network features. Then we applied a multikernel learning technique to the corresponding selected features to obtain the final classification results. We evaluated our proposed method using a data set containing 38 patients with major depressive disorder and 28 healthy controls. The experimental results showed a classification accuracy of up to 97.54%. PMID:29387141

Modeling Electrochemical Performance of the Hierarchical Morphology of Precious Group Metal-free Cathode for Polymer Electrolyte Fuel Cell

DOE PAGES

Komini Babu, Siddharth; Chung, Hoon Taek; Zelenay, Piotr; ...

2017-08-04

Here, this paper presents a two-dimensional (2D) computational model of a polymer electrolyte fuel cell (PEFC) with a platinum group metal-free (PGM-free) catalyst cathode that can significantly reduce PEFC costs by eliminating the need for expensive platinum catalysts. Due to their comparatively low volumetric activity, PGM-free cathodes are an order of magnitude thicker than their Pt-based counterpart. The resulting need for greater electrode thickness to achieve sufficient power density requires careful attention to the transport losses across the thicker cathodes. The presented model is used to correlate the composition and morphology of the cathode to PEFC performance. The model ismore » a complete cell, continuum model that includes an advanced agglomerate model for a microstructurally consistent representation of the cathode. A unique feature of the approach is the integration of morphology and transport parameter statistics extracted from nano-scale resolution X-ray computed tomography (nano-CT) imaging of PGM-free cathodes. The model was validated with experimental results of PGM-free cathodes with varying Nafion loading. Lastly, our key findings are a need for increased cathode hydrophobicity and increased ionomer conductivity through either reduced tortuosity or increased bulk conductivity. We further use the model to evaluate targets for the volumetric activity and active site density for future catalysts.« less

Modeling Electrochemical Performance of the Hierarchical Morphology of Precious Group Metal-free Cathode for Polymer Electrolyte Fuel Cell

DOE Office of Scientific and Technical Information (OSTI.GOV)

Komini Babu, Siddharth; Chung, Hoon Taek; Zelenay, Piotr

Here, this paper presents a two-dimensional (2D) computational model of a polymer electrolyte fuel cell (PEFC) with a platinum group metal-free (PGM-free) catalyst cathode that can significantly reduce PEFC costs by eliminating the need for expensive platinum catalysts. Due to their comparatively low volumetric activity, PGM-free cathodes are an order of magnitude thicker than their Pt-based counterpart. The resulting need for greater electrode thickness to achieve sufficient power density requires careful attention to the transport losses across the thicker cathodes. The presented model is used to correlate the composition and morphology of the cathode to PEFC performance. The model ismore » a complete cell, continuum model that includes an advanced agglomerate model for a microstructurally consistent representation of the cathode. A unique feature of the approach is the integration of morphology and transport parameter statistics extracted from nano-scale resolution X-ray computed tomography (nano-CT) imaging of PGM-free cathodes. The model was validated with experimental results of PGM-free cathodes with varying Nafion loading. Lastly, our key findings are a need for increased cathode hydrophobicity and increased ionomer conductivity through either reduced tortuosity or increased bulk conductivity. We further use the model to evaluate targets for the volumetric activity and active site density for future catalysts.« less

Sequential Design of Experiments to Maximize Learning from Carbon Capture Pilot Plant Testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soepyan, Frits B.; Morgan, Joshua C.; Omell, Benjamin P.

Pilot plant test campaigns can be expensive and time-consuming. Therefore, it is of interest to maximize the amount of learning and the efficiency of the test campaign given the limited number of experiments that can be conducted. This work investigates the use of sequential design of experiments (SDOE) to overcome these challenges by demonstrating its usefulness for a recent solvent-based CO2 capture plant test campaign. Unlike traditional design of experiments methods, SDOE regularly uses information from ongoing experiments to determine the optimum locations in the design space for subsequent runs within the same experiment. However, there are challenges that needmore » to be addressed, including reducing the high computational burden to efficiently update the model, and the need to incorporate the methodology into a computational tool. We address these challenges by applying SDOE in combination with a software tool, the Framework for Optimization, Quantification of Uncertainty and Surrogates (FOQUS) (Miller et al., 2014a, 2016, 2017). The results of applying SDOE on a pilot plant test campaign for CO2 capture suggests that relative to traditional design of experiments methods, SDOE can more effectively reduce the uncertainty of the model, thus decreasing technical risk. Future work includes integrating SDOE into FOQUS and using SDOE to support additional large-scale pilot plant test campaigns.« less

Computation of Thermodynamic Equilibria Pertinent to Nuclear Materials in Multi-Physics Codes

NASA Astrophysics Data System (ADS)

Piro, Markus Hans Alexander

Nuclear energy plays a vital role in supporting electrical needs and fulfilling commitments to reduce greenhouse gas emissions. Research is a continuing necessity to improve the predictive capabilities of fuel behaviour in order to reduce costs and to meet increasingly stringent safety requirements by the regulator. Moreover, a renewed interest in nuclear energy has given rise to a "nuclear renaissance" and the necessity to design the next generation of reactors. In support of this goal, significant research efforts have been dedicated to the advancement of numerical modelling and computational tools in simulating various physical and chemical phenomena associated with nuclear fuel behaviour. This undertaking in effect is collecting the experience and observations of a past generation of nuclear engineers and scientists in a meaningful way for future design purposes. There is an increasing desire to integrate thermodynamic computations directly into multi-physics nuclear fuel performance and safety codes. A new equilibrium thermodynamic solver is being developed with this matter as a primary objective. This solver is intended to provide thermodynamic material properties and boundary conditions for continuum transport calculations. There are several concerns with the use of existing commercial thermodynamic codes: computational performance; limited capabilities in handling large multi-component systems of interest to the nuclear industry; convenient incorporation into other codes with quality assurance considerations; and, licensing entanglements associated with code distribution. The development of this software in this research is aimed at addressing all of these concerns. The approach taken in this work exploits fundamental principles of equilibrium thermodynamics to simplify the numerical optimization equations. In brief, the chemical potentials of all species and phases in the system are constrained by estimates of the chemical potentials of the system components at each iterative step, and the objective is to minimize the residuals of the mass balance equations. Several numerical advantages are achieved through this simplification. In particular, computational expense is reduced and the rate of convergence is enhanced. Furthermore, the software has demonstrated the ability to solve systems involving as many as 118 component elements. An early version of the code has already been integrated into the Advanced Multi-Physics (AMP) code under development by the Oak Ridge National Laboratory, Los Alamos National Laboratory, Idaho National Laboratory and Argonne National Laboratory. Keywords: Engineering, Nuclear -- 0552, Engineering, Material Science -- 0794, Chemistry, Mathematics -- 0405, Computer Science -- 0984

Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

NASA Astrophysics Data System (ADS)

Mohan, K. Aditya

2017-10-01

4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

Analyzing locomotion synthesis with feature-based motion graphs.

PubMed

Mahmudi, Mentar; Kallmann, Marcelo

2013-05-01

We propose feature-based motion graphs for realistic locomotion synthesis among obstacles. Among several advantages, feature-based motion graphs achieve improved results in search queries, eliminate the need of postprocessing for foot skating removal, and reduce the computational requirements in comparison to traditional motion graphs. Our contributions are threefold. First, we show that choosing transitions based on relevant features significantly reduces graph construction time and leads to improved search performances. Second, we employ a fast channel search method that confines the motion graph search to a free channel with guaranteed clearance among obstacles, achieving faster and improved results that avoid expensive collision checking. Lastly, we present a motion deformation model based on Inverse Kinematics applied over the transitions of a solution branch. Each transition is assigned a continuous deformation range that does not exceed the original transition cost threshold specified by the user for the graph construction. The obtained deformation improves the reachability of the feature-based motion graph and in turn also reduces the time spent during search. The results obtained by the proposed methods are evaluated and quantified, and they demonstrate significant improvements in comparison to traditional motion graph techniques.

The techniques of quality operations computational and experimental researches of the launch vehicles in the drawing-board stage

NASA Astrophysics Data System (ADS)

Rozhaeva, K.

2018-01-01

The aim of the researchis the quality operations of the design process at the stage of research works on the development of active on-Board system of the launch vehicles spent stages descent with liquid propellant rocket engines by simulating the gasification process of undeveloped residues of fuel in the tanks. The design techniques of the gasification process of liquid rocket propellant components residues in the tank to the expense of finding and fixing errors in the algorithm calculation to increase the accuracy of calculation results is proposed. Experimental modelling of the model liquid evaporation in a limited reservoir of the experimental stand, allowing due to the false measurements rejection based on given criteria and detected faults to enhance the results reliability of the experimental studies; to reduce the experiments cost.

High Order Schemes in BATS-R-US: Is it OK to Simplify Them?

NASA Astrophysics Data System (ADS)

Tóth, G.; Chen, Y.; van der Holst, B.; Daldorff, L. K. S.

2014-09-01

We describe a number of high order schemes and their simplified variants that have been implemented into the University of Michigan global magnetohydrodynamics code BATS-R-US. We compare the various schemes with each other and the legacy 2nd order TVD scheme for various test problems and two space physics applications. We find that the simplified schemes are often quite competitive with the more complex and expensive full versions, despite the fact that the simplified versions are only high order accurate for linear systems of equations. We find that all the high order schemes require some fixes to ensure positivity in the space physics applications. On the other hand, they produce superior results as compared with the second order scheme and/or produce the same quality of solution at a much reduced computational cost.

Shadow Probability of Detection and False Alarm for Median-Filtered SAR Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raynal, Ann Marie; Doerry, Armin Walter; Miller, John A.

2014-06-01

Median filtering reduces speckle in synthetic aperture radar (SAR) imagery while preserving edges, at the expense of coarsening the resolution, by replacing the center pixel of a sliding window by the median value. For shadow detection, this approach helps distinguish shadows from clutter more easily, while preserving shadow shape delineations. However, the nonlinear operation alters the shadow and clutter distributions and statistics, which must be taken into consideration when computing probability of detection and false alarm metrics. Depending on system parameters, median filtering can improve probability of detection and false alarm by orders of magnitude. Herein, we examine shadow probabilitymore » of detection and false alarm in a homogeneous, ideal clutter background after median filter post-processing. Some comments on multi-look processing effects with and without median filtering are also made.« less

Influence of minor geometric features on Stirling pulse tube cryocooler performance

NASA Astrophysics Data System (ADS)

Fang, T.; Spoor, P. S.; Ghiaasiaan, S. M.; Perrella, M.

2017-12-01

Minor geometric features and imperfections are commonly introduced into the basic design of multi-component systems to simplify or reduce the manufacturing expense. In this work, the cooling performance of a Stirling type cryocooler was tested in different driving powers, cold-end temperatures and inclination angles. A series of Computational Fluid Dynamics (CFD) simulations based on a prototypical cold tip was carried out. Detailed CFD model predictions were compared with the experiment and were used to investigate the impact of such apparently minor geometric imperfections on the performance of Stirling type pulse tube cryocoolers. Predictions of cooling performance and gravity orientation sensitivity were compared with experimental results obtained with the cryocooler prototypes. The results indicate that minor geometry features in the cold tip assembly can have considerable negative effects on the gravity orientation sensitivity of a pulse tube cryocooler.

Lost in Cloud

NASA Technical Reports Server (NTRS)

Maluf, David A.; Shetye, Sandeep D.; Chilukuri, Sri; Sturken, Ian

2012-01-01

Cloud computing can reduce cost significantly because businesses can share computing resources. In recent years Small and Medium Businesses (SMB) have used Cloud effectively for cost saving and for sharing IT expenses. With the success of SMBs, many perceive that the larger enterprises ought to move into Cloud environment as well. Government agency s stove-piped environments are being considered as candidates for potential use of Cloud either as an enterprise entity or pockets of small communities. Cloud Computing is the delivery of computing as a service rather than as a product, whereby shared resources, software, and information are provided to computers and other devices as a utility over a network. Underneath the offered services, there exists a modern infrastructure cost of which is often spread across its services or its investors. As NASA is considered as an Enterprise class organization, like other enterprises, a shift has been occurring in perceiving its IT services as candidates for Cloud services. This paper discusses market trends in cloud computing from an enterprise angle and then addresses the topic of Cloud Computing for NASA in two possible forms. First, in the form of a public Cloud to support it as an enterprise, as well as to share it with the commercial and public at large. Second, as a private Cloud wherein the infrastructure is operated solely for NASA, whether managed internally or by a third-party and hosted internally or externally. The paper addresses the strengths and weaknesses of both paradigms of public and private Clouds, in both internally and externally operated settings. The content of the paper is from a NASA perspective but is applicable to any large enterprise with thousands of employees and contractors.

Bigdata Driven Cloud Security: A Survey

NASA Astrophysics Data System (ADS)

Raja, K.; Hanifa, Sabibullah Mohamed

2017-08-01

Cloud Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through cloud computing. CC consists of a front-end, includes the users’ computers and software required to access the cloud network, and back-end consists of various computers, servers and database systems that create the cloud. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a cloud), where leading / traditional cloud ecosystem delivers the cloud services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for cloud computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, cloud service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing cloud-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a cloud environment, and a model for Cloud providers.

Application of the System Identification Technique to Goal-Directed Saccades.

DTIC Science & Technology

1984-07-30

1983 to May 31, 1984 by the AFOSR under Grant No. AFOSR-83-0187. 1. Salaries & Wages $7,257 2. Employee Benefits $ 4186 3. Indirect Costs $1,177 *’ 1...Equipment $2,127 DEC VT100 Terminal Computer Terminal Table & Chair Computer Interface 5. Travel $ 672 6. Miscellaneous Expenses 281 Computer Costs ...Telephone Xeroxing Report Costs Total $12,000 A 1cc;3t Ion r . ;. ., ’o n. e, Ef V r CI3 k.i *r 7’r’ ’ - s-I - . CLef • -- * 0 - -- -, r ~ 𔄁 . r w

[Transfusion supply optimization in multiple-discipline surgical hospital].

PubMed

Solov'eva, I N; Trekova, N A; Krapivkin, I A

2016-01-01

To define optimal variant of transfusion supply of hospital by blood components and to decrease donor blood expense via application of blood preserving technologies. Donor blood components expense, volume of hemotransfusions and their proportion for the period 2012-2014 were analyzed. Number of recipients of packed red cells, fresh-frozen plasma and packed platelets reduced 18.5%, 25% and 80% respectively. Need for donor plasma decreased 35%. Expense of autologous plasma in cardiac surgery was 76% of overall volume. Preoperative plasma sampling is introduced in patients with aortic aneurysm. Number of cardiac interventions performed without donor blood is increased 7-31% depending on its complexity.

GPSS/360 computer models to simulate aircraft passenger emergency evacuations.

DOT National Transportation Integrated Search

1972-09-01

Live tests of emergency evacuation of transport aircraft are becoming increasingly expensive as the planes grow to a size seating hundreds of passengers. Repeated tests, to cope with random variations, increase these costs, as well as risks of injuri...

Another View of "PC vs. Mac."

ERIC Educational Resources Information Center

DeMillion, John A.

1998-01-01

An article by Nan Wodarz in the November 1997 issue listed reasons why the Microsoft computer operating system was superior to the Apple Macintosh platform. This rebuttal contends the Macintosh is less expensive, lasts longer, and requires less technical staff for support. (MLF)