Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

Remote sensing data with the conditional latin hypercube sampling and geostatistical approach to delineate landscape changes induced by large chronological physical disturbances.

PubMed

Lin, Yu-Pin; Chu, Hone-Jay; Wang, Cheng-Long; Yu, Hsiao-Hsuan; Wang, Yung-Chieh

2009-01-01

This study applies variogram analyses of normalized difference vegetation index (NDVI) images derived from SPOT HRV images obtained before and after the ChiChi earthquake in the Chenyulan watershed, Taiwan, as well as images after four large typhoons, to delineate the spatial patterns, spatial structures and spatial variability of landscapes caused by these large disturbances. The conditional Latin hypercube sampling approach was applied to select samples from multiple NDVI images. Kriging and sequential Gaussian simulation with sufficient samples were then used to generate maps of NDVI images. The variography of NDVI image results demonstrate that spatial patterns of disturbed landscapes were successfully delineated by variogram analysis in study areas. The high-magnitude Chi-Chi earthquake created spatial landscape variations in the study area. After the earthquake, the cumulative impacts of typhoons on landscape patterns depended on the magnitudes and paths of typhoons, but were not always evident in the spatiotemporal variability of landscapes in the study area. The statistics and spatial structures of multiple NDVI images were captured by 3,000 samples from 62,500 grids in the NDVI images. Kriging and sequential Gaussian simulation with the 3,000 samples effectively reproduced spatial patterns of NDVI images. However, the proposed approach, which integrates the conditional Latin hypercube sampling approach, variogram, kriging and sequential Gaussian simulation in remotely sensed images, efficiently monitors, samples and maps the effects of large chronological disturbances on spatial characteristics of landscape changes including spatial variability and heterogeneity.

Extension of latin hypercube samples with correlated variables.

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

Hora, Stephen Curtis; Helton, Jon Craig; Sallaberry, Cedric J. PhD.

2006-11-01

A procedure for extending the size of a Latin hypercube sample (LHS) with rank correlated variables is described and illustrated. The extension procedure starts with an LHS of size m and associated rank correlation matrix C and constructs a new LHS of size 2m that contains the elements of the original LHS and has a rank correlation matrix that is close to the original rank correlation matrix C. The procedure is intended for use in conjunction with uncertainty and sensitivity analysis of computationally demanding models in which it is important to make efficient use of a necessarily limited number ofmore » model evaluations.« less

Hypercube matrix computation task

NASA Technical Reports Server (NTRS)

Calalo, R.; Imbriale, W.; Liewer, P.; Lyons, J.; Manshadi, F.; Patterson, J.

1987-01-01

The Hypercube Matrix Computation (Year 1986-1987) task investigated the applicability of a parallel computing architecture to the solution of large scale electromagnetic scattering problems. Two existing electromagnetic scattering codes were selected for conversion to the Mark III Hypercube concurrent computing environment. They were selected so that the underlying numerical algorithms utilized would be different thereby providing a more thorough evaluation of the appropriateness of the parallel environment for these types of problems. The first code was a frequency domain method of moments solution, NEC-2, developed at Lawrence Livermore National Laboratory. The second code was a time domain finite difference solution of Maxwell's equations to solve for the scattered fields. Once the codes were implemented on the hypercube and verified to obtain correct solutions by comparing the results with those from sequential runs, several measures were used to evaluate the performance of the two codes. First, a comparison was provided of the problem size possible on the hypercube with 128 megabytes of memory for a 32-node configuration with that available in a typical sequential user environment of 4 to 8 megabytes. Then, the performance of the codes was anlyzed for the computational speedup attained by the parallel architecture.

Efficiency enhancement of optimized Latin hypercube sampling strategies: Application to Monte Carlo uncertainty analysis and meta-modeling

NASA Astrophysics Data System (ADS)

Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad; Janssen, Hans

2015-02-01

The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of midpoints in the hypercube intervals (midpoint LHS). Both approaches have been extensively used, but no attempt has been previously made to compare the efficiency and robustness of their resulting sample designs. In this study we compare the two approaches and show that the space-filling characteristics of OLHS designs are sensitive to the initial design that is fed into the optimization algorithm. It is also illustrated that the space-filling characteristics of OLHS designs based on midpoint LHS are significantly better those based on random LHS. The two approaches are compared by incorporating their resulting sample designs in Monte Carlo simulation (MCS) for uncertainty propagation analysis, and then, by employing the sample designs in the selection of the training set for constructing non-intrusive polynomial chaos expansion (NIPCE) meta-models which subsequently replace the original full model in MCSs. The analysis is based on two case studies involving numerical simulation of density dependent flow and solute transport in porous media within the context of seawater intrusion in coastal aquifers. We show that the use of midpoint LHS as the initial design increases the efficiency and robustness of the resulting MCSs and NIPCE meta-models. The study also illustrates that this relative improvement decreases with increasing number of sample points and input parameter dimensions. Since the computational time and efforts for generating the sample designs in the two approaches are identical, the use of midpoint LHS as the initial design in OLHS is thus recommended.

Optimal cube-connected cube multiprocessors

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Wu, Jie

1993-01-01

Many CFD (computational fluid dynamics) and other scientific applications can be partitioned into subproblems. However, in general the partitioned subproblems are very large. They demand high performance computing power themselves, and the solutions of the subproblems have to be combined at each time step. The cube-connect cube (CCCube) architecture is studied. The CCCube architecture is an extended hypercube structure with each node represented as a cube. It requires fewer physical links between nodes than the hypercube, and provides the same communication support as the hypercube does on many applications. The reduced physical links can be used to enhance the bandwidth of the remaining links and, therefore, enhance the overall performance. The concept and the method to obtain optimal CCCubes, which are the CCCubes with a minimum number of links under a given total number of nodes, are proposed. The superiority of optimal CCCubes over standard hypercubes was also shown in terms of the link usage in the embedding of a binomial tree. A useful computation structure based on a semi-binomial tree for divide-and-conquer type of parallel algorithms was identified. It was shown that this structure can be implemented in optimal CCCubes without performance degradation compared with regular hypercubes. The result presented should provide a useful approach to design of scientific parallel computers.

Concurrent Image Processing Executive (CIPE). Volume 1: Design overview

NASA Technical Reports Server (NTRS)

Lee, Meemong; Groom, Steven L.; Mazer, Alan S.; Williams, Winifred I.

1990-01-01

The design and implementation of a Concurrent Image Processing Executive (CIPE), which is intended to become the support system software for a prototype high performance science analysis workstation are described. The target machine for this software is a JPL/Caltech Mark 3fp Hypercube hosted by either a MASSCOMP 5600 or a Sun-3, Sun-4 workstation; however, the design will accommodate other concurrent machines of similar architecture, i.e., local memory, multiple-instruction-multiple-data (MIMD) machines. The CIPE system provides both a multimode user interface and an applications programmer interface, and has been designed around four loosely coupled modules: user interface, host-resident executive, hypercube-resident executive, and application functions. The loose coupling between modules allows modification of a particular module without significantly affecting the other modules in the system. In order to enhance hypercube memory utilization and to allow expansion of image processing capabilities, a specialized program management method, incremental loading, was devised. To minimize data transfer between host and hypercube, a data management method which distributes, redistributes, and tracks data set information was implemented. The data management also allows data sharing among application programs. The CIPE software architecture provides a flexible environment for scientific analysis of complex remote sensing image data, such as planetary data and imaging spectrometry, utilizing state-of-the-art concurrent computation capabilities.

Simulation of Fault Tolerance in a Hypercube Arrangement of Discrete Processors.

DTIC Science & Technology

1987-12-01

Geometric Properties .................... 22 Binary Properties ....................... 26 Intel Hypercube Hardware Arrangement ... 28 IV. Cube-Connected... Properties of the CCC..............35 CCC Redundancy............................... 38 iii 6L V. Re-Configurable Cube-Connected Cycles ....... 40 Global...o........ 74 iv List of Figures Page Figure 1: Hypercubes of Different Dimensions ......... 21 Figure 2: Hypercube Properties

Constraining Unsaturated Hydraulic Parameters Using the Latin Hypercube Sampling Method and Coupled Hydrogeophysical Approach

NASA Astrophysics Data System (ADS)

Farzamian, Mohammad; Monteiro Santos, Fernando A.; Khalil, Mohamed A.

2017-12-01

The coupled hydrogeophysical approach has proved to be a valuable tool for improving the use of geoelectrical data for hydrological model parameterization. In the coupled approach, hydrological parameters are directly inferred from geoelectrical measurements in a forward manner to eliminate the uncertainty connected to the independent inversion of electrical resistivity data. Several numerical studies have been conducted to demonstrate the advantages of a coupled approach; however, only a few attempts have been made to apply the coupled approach to actual field data. In this study, we developed a 1D coupled hydrogeophysical code to estimate the van Genuchten-Mualem model parameters, K s, n, θ r and α, from time-lapse vertical electrical sounding data collected during a constant inflow infiltration experiment. van Genuchten-Mualem parameters were sampled using the Latin hypercube sampling method to provide a full coverage of the range of each parameter from their distributions. By applying the coupled approach, vertical electrical sounding data were coupled to hydrological models inferred from van Genuchten-Mualem parameter samples to investigate the feasibility of constraining the hydrological model. The key approaches taken in the study are to (1) integrate electrical resistivity and hydrological data and avoiding data inversion, (2) estimate the total water mass recovery of electrical resistivity data and consider it in van Genuchten-Mualem parameters evaluation and (3) correct the influence of subsurface temperature fluctuations during the infiltration experiment on electrical resistivity data. The results of the study revealed that the coupled hydrogeophysical approach can improve the value of geophysical measurements in hydrological model parameterization. However, the approach cannot overcome the technical limitations of the geoelectrical method associated with resolution and of water mass recovery.

Least squares polynomial chaos expansion: A review of sampling strategies

NASA Astrophysics Data System (ADS)

Hadigol, Mohammad; Doostan, Alireza

2018-04-01

As non-institutive polynomial chaos expansion (PCE) techniques have gained growing popularity among researchers, we here provide a comprehensive review of major sampling strategies for the least squares based PCE. Traditional sampling methods, such as Monte Carlo, Latin hypercube, quasi-Monte Carlo, optimal design of experiments (ODE), Gaussian quadratures, as well as more recent techniques, such as coherence-optimal and randomized quadratures are discussed. We also propose a hybrid sampling method, dubbed alphabetic-coherence-optimal, that employs the so-called alphabetic optimality criteria used in the context of ODE in conjunction with coherence-optimal samples. A comparison between the empirical performance of the selected sampling methods applied to three numerical examples, including high-order PCE's, high-dimensional problems, and low oversampling ratios, is presented to provide a road map for practitioners seeking the most suitable sampling technique for a problem at hand. We observed that the alphabetic-coherence-optimal technique outperforms other sampling methods, specially when high-order ODE are employed and/or the oversampling ratio is low.

Experimental demonstration of the optical multi-mesh hypercube: scaleable interconnection network for multiprocessors and multicomputers.

PubMed

Louri, A; Furlonge, S; Neocleous, C

1996-12-10

A prototype of a novel topology for scaleable optical interconnection networks called the optical multi-mesh hypercube (OMMH) is experimentally demonstrated to as high as a 150-Mbit/s data rate (2(7) - 1 nonreturn-to-zero pseudo-random data pattern) at a bit error rate of 10(-13)/link by the use of commercially available devices. OMMH is a scaleable network [Appl. Opt. 33, 7558 (1994); J. Lightwave Technol. 12, 704 (1994)] architecture that combines the positive features of the hypercube (small diameter, connectivity, symmetry, simple routing, and fault tolerance) and the mesh (constant node degree and size scaleability). The optical implementation method is divided into two levels: high-density local connections for the hypercube modules, and high-bit-rate, low-density, long connections for the mesh links connecting the hypercube modules. Free-space imaging systems utilizing vertical-cavity surface-emitting laser (VCSEL) arrays, lenslet arrays, space-invariant holographic techniques, and photodiode arrays are demonstrated for the local connections. Optobus fiber interconnects from Motorola are used for the long-distance connections. The OMMH was optimized to operate at the data rate of Motorola's Optobus (10-bit-wide, VCSEL-based bidirectional data interconnects at 150 Mbits/s). Difficulties encountered included the varying fan-out efficiencies of the different orders of the hologram, misalignment sensitivity of the free-space links, low power (1 mW) of the individual VCSEL's, and noise.

Improvement of Simulation Method in Validation of Software of the Coordinate Measuring Systems

NASA Astrophysics Data System (ADS)

Nieciąg, Halina

2015-10-01

Software is used in order to accomplish various tasks at each stage of the functioning of modern measuring systems. Before metrological confirmation of measuring equipment, the system has to be validated. This paper discusses the method for conducting validation studies of a fragment of software to calculate the values of measurands. Due to the number and nature of the variables affecting the coordinate measurement results and the complex character and multi-dimensionality of measurands, the study used the Monte Carlo method of numerical simulation. The article presents an attempt of possible improvement of results obtained by classic Monte Carlo tools. The algorithm LHS (Latin Hypercube Sampling) was implemented as alternative to the simple sampling schema of classic algorithm.

Mapping implicit spectral methods to distributed memory architectures

NASA Technical Reports Server (NTRS)

Overman, Andrea L.; Vanrosendale, John

1991-01-01

Spectral methods were proven invaluable in numerical simulation of PDEs (Partial Differential Equations), but the frequent global communication required raises a fundamental barrier to their use on highly parallel architectures. To explore this issue, a 3-D implicit spectral method was implemented on an Intel hypercube. Utilization of about 50 percent was achieved on a 32 node iPSC/860 hypercube, for a 64 x 64 x 64 Fourier-spectral grid; finer grids yield higher utilizations. Chebyshev-spectral grids are more problematic, since plane-relaxation based multigrid is required. However, by using a semicoarsening multigrid algorithm, and by relaxing all multigrid levels concurrently, relatively high utilizations were also achieved in this harder case.

Implementation and Performance Analysis of Parallel Assignment Algorithms on a Hypercube Computer.

DTIC Science & Technology

1987-12-01

coupled pro- cessors because of the degree of interaction between processors imposed by the global memory [HwB84]. Another sub-class of MIMD... interaction between the individual processors [MuA87]. Many of the commercial MIMD computers available today are loosely coupled [HwB84]. 2.1.3 The Hypercube...Alpha-beta is a method usually employed in the solution of two-person zero-sum games like chess and checkers [Qui87]. The ha sic approach of the alpha

Concurrent Image Processing Executive (CIPE). Volume 2: Programmer's guide

NASA Technical Reports Server (NTRS)

Williams, Winifred I.

1990-01-01

This manual is intended as a guide for application programmers using the Concurrent Image Processing Executive (CIPE). CIPE is intended to become the support system software for a prototype high performance science analysis workstation. In its current configuration CIPE utilizes a JPL/Caltech Mark 3fp Hypercube with a Sun-4 host. CIPE's design is capable of incorporating other concurrent architectures as well. CIPE provides a programming environment to applications' programmers to shield them from various user interfaces, file transactions, and architectural complexities. A programmer may choose to write applications to use only the Sun-4 or to use the Sun-4 with the hypercube. A hypercube program will use the hypercube's data processors and optionally the Weitek floating point accelerators. The CIPE programming environment provides a simple set of subroutines to activate user interface functions, specify data distributions, activate hypercube resident applications, and to communicate parameters to and from the hypercube.

Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling.

PubMed

Chaudhary, Neha; Tøndel, Kristin; Bhatnagar, Rakesh; dos Santos, Vítor A P Martins; Puchałka, Jacek

2016-03-01

Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them.

A discrete random walk on the hypercube

NASA Astrophysics Data System (ADS)

Zhang, Jingyuan; Xiang, Yonghong; Sun, Weigang

2018-03-01

In this paper, we study the scaling for mean first-passage time (MFPT) of random walks on the hypercube and obtain a closed-form formula for the MFPT over all node pairs. We also determine the exponent of scaling efficiency characterizing the random walks and compare it with those of the existing networks. Finally we study the random walks on the hypercube with a located trap and provide a solution of the Kirchhoff index of the hypercube.

Optimization of an Advanced Multi-Junction Solar-Cell Design for Space Environments (AM0) Using Nearly Orthogonal Latin Hypercubes

DTIC Science & Technology

2017-06-01

AN ADVANCED MULTI-JUNCTION SOLAR -CELL DESIGN FOR SPACE ENVIRONMENTS (AM0) USING NEARLY ORTHOGONAL LATIN HYPERCUBES by Silvio Pueschel June...ADVANCED MULTI-JUNCTION SOLAR -CELL DESIGN FOR SPACE ENVIRONMENTS (AM0) USING NEARLY ORTHOGONAL LATIN HYPERCUBES 5. FUNDING NUMBERS 6. AUTHOR(S) Silvio...multi-junction solar cells with Silvaco Atlas simulation software. It introduces the nearly orthogonal Latin hypercube (NOLH) design of experiments (DoE

Assessing performance and validating finite element simulations using probabilistic knowledge

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

Dolin, Ronald M.; Rodriguez, E. A.

Two probabilistic approaches for assessing performance are presented. The first approach assesses probability of failure by simultaneously modeling all likely events. The probability each event causes failure along with the event's likelihood of occurrence contribute to the overall probability of failure. The second assessment method is based on stochastic sampling using an influence diagram. Latin-hypercube sampling is used to stochastically assess events. The overall probability of failure is taken as the maximum probability of failure of all the events. The Likelihood of Occurrence simulation suggests failure does not occur while the Stochastic Sampling approach predicts failure. The Likelihood of Occurrencemore » results are used to validate finite element predictions.« less

Influence of scanning parameters on the estimation accuracy of control points of B-spline surfaces

NASA Astrophysics Data System (ADS)

Aichinger, Julia; Schwieger, Volker

2018-04-01

This contribution deals with the influence of scanning parameters like scanning distance, incidence angle, surface quality and sampling width on the average estimated standard deviations of the position of control points from B-spline surfaces which are used to model surfaces from terrestrial laser scanning data. The influence of the scanning parameters is analyzed by the Monte Carlo based variance analysis. The samples were generated for non-correlated and correlated data, leading to the samples generated by Latin hypercube and replicated Latin hypercube sampling algorithms. Finally, the investigations show that the most influential scanning parameter is the distance from the laser scanner to the object. The angle of incidence shows a significant effect for distances of 50 m and longer, while the surface quality contributes only negligible effects. The sampling width has no influence. Optimal scanning parameters can be found in the smallest possible object distance at an angle of incidence close to 0° in the highest surface quality. The consideration of correlations improves the estimation accuracy and underlines the importance of complete stochastic models for TLS measurements.

Stochastic Investigation of Natural Frequency for Functionally Graded Plates

NASA Astrophysics Data System (ADS)

Karsh, P. K.; Mukhopadhyay, T.; Dey, S.

2018-03-01

This paper presents the stochastic natural frequency analysis of functionally graded plates by applying artificial neural network (ANN) approach. Latin hypercube sampling is utilised to train the ANN model. The proposed algorithm for stochastic natural frequency analysis of FGM plates is validated and verified with original finite element method and Monte Carlo simulation (MCS). The combined stochastic variation of input parameters such as, elastic modulus, shear modulus, Poisson ratio, and mass density are considered. Power law is applied to distribute the material properties across the thickness. The present ANN model reduces the sample size and computationally found efficient as compared to conventional Monte Carlo simulation.

Parallel and fault-tolerant algorithms for hypercube multiprocessors

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

Aykanat, C.

1988-01-01

Several techniques for increasing the performance of parallel algorithms on distributed-memory message-passing multi-processor systems are investigated. These techniques are effectively implemented for the parallelization of the Scaled Conjugate Gradient (SCG) algorithm on a hypercube connected message-passing multi-processor. Significant performance improvement is achieved by using these techniques. The SCG algorithm is used for the solution phase of an FE modeling system. Almost linear speed-up is achieved, and it is shown that hypercube topology is scalable for an FE class of problem. The SCG algorithm is also shown to be suitable for vectorization, and near supercomputer performance is achieved on a vectormore » hypercube multiprocessor by exploiting both parallelization and vectorization. Fault-tolerance issues for the parallel SCG algorithm and for the hypercube topology are also addressed.« less

High-throughput Raman chemical imaging for evaluating food safety and quality

NASA Astrophysics Data System (ADS)

Qin, Jianwei; Chao, Kuanglin; Kim, Moon S.

2014-05-01

A line-scan hyperspectral system was developed to enable Raman chemical imaging for large sample areas. A custom-designed 785 nm line-laser based on a scanning mirror serves as an excitation source. A 45° dichroic beamsplitter reflects the laser light to form a 24 cm x 1 mm excitation line normally incident on the sample surface. Raman signals along the laser line are collected by a detection module consisting of a dispersive imaging spectrograph and a CCD camera. A hypercube is accumulated line by line as a motorized table moves the samples transversely through the laser line. The system covers a Raman shift range of -648.7-2889.0 cm-1 and a 23 cm wide area. An example application, for authenticating milk powder, was presented to demonstrate the system performance. In four minutes, the system acquired a 512x110x1024 hypercube (56,320 spectra) from four 47-mm-diameter Petri dishes containing four powder samples. Chemical images were created for detecting two adulterants (melamine and dicyandiamide) that had been mixed into the milk powder.

A flexible importance sampling method for integrating subgrid processes

DOE PAGES

Raut, E. K.; Larson, V. E.

2016-01-29

Numerical models of weather and climate need to compute grid-box-averaged rates of physical processes such as microphysics. These averages are computed by integrating subgrid variability over a grid box. For this reason, an important aspect of atmospheric modeling is spatial integration over subgrid scales. The needed integrals can be estimated by Monte Carlo integration. Monte Carlo integration is simple and general but requires many evaluations of the physical process rate. To reduce the number of function evaluations, this paper describes a new, flexible method of importance sampling. It divides the domain of integration into eight categories, such as the portion that containsmore » both precipitation and cloud, or the portion that contains precipitation but no cloud. It then allows the modeler to prescribe the density of sample points within each of the eight categories. The new method is incorporated into the Subgrid Importance Latin Hypercube Sampler (SILHS). Here, the resulting method is tested on drizzling cumulus and stratocumulus cases. In the cumulus case, the sampling error can be considerably reduced by drawing more sample points from the region of rain evaporation.« less

SIAM Conference on Parallel Processing for Scientific Computing, 4th, Chicago, IL, Dec. 11-13, 1989, Proceedings

NASA Technical Reports Server (NTRS)

Dongarra, Jack (Editor); Messina, Paul (Editor); Sorensen, Danny C. (Editor); Voigt, Robert G. (Editor)

1990-01-01

Attention is given to such topics as an evaluation of block algorithm variants in LAPACK and presents a large-grain parallel sparse system solver, a multiprocessor method for the solution of the generalized Eigenvalue problem on an interval, and a parallel QR algorithm for iterative subspace methods on the CM2. A discussion of numerical methods includes the topics of asynchronous numerical solutions of PDEs on parallel computers, parallel homotopy curve tracking on a hypercube, and solving Navier-Stokes equations on the Cedar Multi-Cluster system. A section on differential equations includes a discussion of a six-color procedure for the parallel solution of elliptic systems using the finite quadtree structure, data parallel algorithms for the finite element method, and domain decomposition methods in aerodynamics. Topics dealing with massively parallel computing include hypercube vs. 2-dimensional meshes and massively parallel computation of conservation laws. Performance and tools are also discussed.

A parallel simulated annealing algorithm for standard cell placement on a hypercube computer

NASA Technical Reports Server (NTRS)

Jones, Mark Howard

1987-01-01

A parallel version of a simulated annealing algorithm is presented which is targeted to run on a hypercube computer. A strategy for mapping the cells in a two dimensional area of a chip onto processors in an n-dimensional hypercube is proposed such that both small and large distance moves can be applied. Two types of moves are allowed: cell exchanges and cell displacements. The computation of the cost function in parallel among all the processors in the hypercube is described along with a distributed data structure that needs to be stored in the hypercube to support parallel cost evaluation. A novel tree broadcasting strategy is used extensively in the algorithm for updating cell locations in the parallel environment. Studies on the performance of the algorithm on example industrial circuits show that it is faster and gives better final placement results than the uniprocessor simulated annealing algorithms. An improved uniprocessor algorithm is proposed which is based on the improved results obtained from parallelization of the simulated annealing algorithm.

Benchmarking hypercube hardware and software

NASA Technical Reports Server (NTRS)

Grunwald, Dirk C.; Reed, Daniel A.

1986-01-01

It was long a truism in computer systems design that balanced systems achieve the best performance. Message passing parallel processors are no different. To quantify the balance of a hypercube design, an experimental methodology was developed and the associated suite of benchmarks was applied to several existing hypercubes. The benchmark suite includes tests of both processor speed in the absence of internode communication and message transmission speed as a function of communication patterns.

Domain decomposition methods in computational fluid dynamics

NASA Technical Reports Server (NTRS)

Gropp, William D.; Keyes, David E.

1991-01-01

The divide-and-conquer paradigm of iterative domain decomposition, or substructuring, has become a practical tool in computational fluid dynamic applications because of its flexibility in accommodating adaptive refinement through locally uniform (or quasi-uniform) grids, its ability to exploit multiple discretizations of the operator equations, and the modular pathway it provides towards parallelism. These features are illustrated on the classic model problem of flow over a backstep using Newton's method as the nonlinear iteration. Multiple discretizations (second-order in the operator and first-order in the preconditioner) and locally uniform mesh refinement pay dividends separately, and they can be combined synergistically. Sample performance results are included from an Intel iPSC/860 hypercube implementation.

Analysis of hepatitis C viral dynamics using Latin hypercube sampling

NASA Astrophysics Data System (ADS)

Pachpute, Gaurav; Chakrabarty, Siddhartha P.

2012-12-01

We consider a mathematical model comprising four coupled ordinary differential equations (ODEs) to study hepatitis C viral dynamics. The model includes the efficacies of a combination therapy of interferon and ribavirin. There are two main objectives of this paper. The first one is to approximate the percentage of cases in which there is a viral clearance in absence of treatment as well as percentage of response to treatment for various efficacy levels. The other is to better understand and identify the parameters that play a key role in the decline of viral load and can be estimated in a clinical setting. A condition for the stability of the uninfected and the infected steady states is presented. A large number of sample points for the model parameters (which are physiologically feasible) are generated using Latin hypercube sampling. An analysis of the simulated values identifies that, approximately 29.85% cases result in clearance of the virus during the early phase of the infection. Results from the χ2 and the Spearman's tests done on the samples, indicate a distinctly different distribution for certain parameters for the cases exhibiting viral clearance under the combination therapy.

Uncertainty quantification of resonant ultrasound spectroscopy for material property and single crystal orientation estimation on a complex part

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Mayes, Alexander; Jauriqui, Leanne; Biedermann, Eric; Heffernan, Julieanne; Livings, Richard; Goodlet, Brent; Mazdiyasni, Siamack

2018-04-01

A case study is presented evaluating uncertainty in Resonance Ultrasound Spectroscopy (RUS) inversion for a single crystal (SX) Ni-based superalloy Mar-M247 cylindrical dog-bone specimens. A number of surrogate models were developed with FEM model solutions, using different sampling schemes (regular grid, Monte Carlo sampling, Latin Hyper-cube sampling) and model approaches, N-dimensional cubic spline interpolation and Kriging. Repeated studies were used to quantify the well-posedness of the inversion problem, and the uncertainty was assessed in material property and crystallographic orientation estimates given typical geometric dimension variability in aerospace components. Surrogate model quality was found to be an important factor in inversion results when the model more closely represents the test data. One important discovery was when the model matches well with test data, a Kriging surrogate model using un-sorted Latin Hypercube sampled data performed as well as the best results from an N-dimensional interpolation model using sorted data. However, both surrogate model quality and mode sorting were found to be less critical when inverting properties from either experimental data or simulated test cases with uncontrolled geometric variation.

FORMAL UNCERTAINTY ANALYSIS OF A LAGRANGIAN PHOTOCHEMICAL AIR POLLUTION MODEL. (R824792)

EPA Science Inventory

This study applied Monte Carlo analysis with Latin
hypercube sampling to evaluate the effects of uncertainty
in air parcel trajectory paths, emissions, rate constants,
deposition affinities, mixing heights, and atmospheric stability
on predictions from a vertically...

The Mark III Hypercube-Ensemble Computers

NASA Technical Reports Server (NTRS)

Peterson, John C.; Tuazon, Jesus O.; Lieberman, Don; Pniel, Moshe

1988-01-01

Mark III Hypercube concept applied in development of series of increasingly powerful computers. Processor of each node of Mark III Hypercube ensemble is specialized computer containing three subprocessors and shared main memory. Solves problem quickly by simultaneously processing part of problem at each such node and passing combined results to host computer. Disciplines benefitting from speed and memory capacity include astrophysics, geophysics, chemistry, weather, high-energy physics, applied mechanics, image processing, oil exploration, aircraft design, and microcircuit design.

A parallel row-based algorithm with error control for standard-cell replacement on a hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Sargent, Jeff Scott

1988-01-01

A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.

Hyperswitch Network For Hypercube Computer

NASA Technical Reports Server (NTRS)

Chow, Edward; Madan, Herbert; Peterson, John

1989-01-01

Data-driven dynamic switching enables high speed data transfer. Proposed hyperswitch network based on mixed static and dynamic topologies. Routing header modified in response to congestion or faults encountered as path established. Static topology meets requirement if nodes have switching elements that perform necessary routing header revisions dynamically. Hypercube topology now being implemented with switching element in each computer node aimed at designing very-richly-interconnected multicomputer system. Interconnection network connects great number of small computer nodes, using fixed hypercube topology, characterized by point-to-point links between nodes.

Ordered fast Fourier transforms on a massively parallel hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Tong, Charles; Swarztrauber, Paul N.

1991-01-01

The present evaluation of alternative, massively parallel hypercube processor-applicable designs for ordered radix-2 decimation-in-frequency FFT algorithms gives attention to the reduction of computation time-dominating communication. A combination of the order and computational phases of the FFT is accordingly employed, in conjunction with sequence-to-processor maps which reduce communication. Two orderings, 'standard' and 'cyclic', in which the order of the transform is the same as that of the input sequence, can be implemented with ease on the Connection Machine (where orderings are determined by geometries and priorities. A parallel method for trigonometric coefficient computation is presented which does not employ trigonometric functions or interprocessor communication.

High-Accuracy Finite Element Method: Benchmark Calculations

NASA Astrophysics Data System (ADS)

Gusev, Alexander; Vinitsky, Sergue; Chuluunbaatar, Ochbadrakh; Chuluunbaatar, Galmandakh; Gerdt, Vladimir; Derbov, Vladimir; Góźdź, Andrzej; Krassovitskiy, Pavel

2018-02-01

We describe a new high-accuracy finite element scheme with simplex elements for solving the elliptic boundary-value problems and show its efficiency on benchmark solutions of the Helmholtz equation for the triangle membrane and hypercube.

Model Based Predictive Control of Multivariable Hammerstein Processes with Fuzzy Logic Hypercube Interpolated Models

PubMed Central

Coelho, Antonio Augusto Rodrigues

2016-01-01

This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723

Comparison of Drainmod Based Watershed Scale Models

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2004-01-01

Watershed scale hydrology and water quality models (DRAINMOD-DUFLOW, DRAINMOD-W, DRAINMOD-GIS and WATGIS) that describe the nitrogen loadings at the outlet of poorly drained watersheds were examined with respect to their accuracy and uncertainty in model predictions. Latin Hypercube Sampling (LHS) was applied to determine the impact of uncertainty in estimating field...

Performance analysis of parallel branch and bound search with the hypercube architecture

NASA Technical Reports Server (NTRS)

Mraz, Richard T.

1987-01-01

With the availability of commercial parallel computers, researchers are examining new classes of problems which might benefit from parallel computing. This paper presents results of an investigation of the class of search intensive problems. The specific problem discussed is the Least-Cost Branch and Bound search method of deadline job scheduling. The object-oriented design methodology was used to map the problem into a parallel solution. While the initial design was good for a prototype, the best performance resulted from fine-tuning the algorithm for a specific computer. The experiments analyze the computation time, the speed up over a VAX 11/785, and the load balance of the problem when using loosely coupled multiprocessor system based on the hypercube architecture.

Erosion Modeling in Central China - Soil Data Acquisition by Conditioned Latin Hypercube Sampling and Incorporation of Legacy Data

NASA Astrophysics Data System (ADS)

Stumpf, Felix; Schönbrodt-Stitt, Sarah; Schmidt, Karsten; Behrens, Thorsten; Scholten, Thomas

2013-04-01

The Three Gorges Dam at the Yangtze River in Central China outlines a prominent example of human-induced environmental impacts. Throughout one year the water table at the main river fluctuates about 30m due to impoundment and drainage activities. The dynamic water table implicates a range of georisks such as soil erosion, mass movements, sediment transport and diffuse matter inputs into the reservoir. Within the framework of the joint Sino-German project YANGTZE GEO, the subproject "Soil Erosion" deals with soil erosion risks and sediment transport pathways into the reservoir. The study site is a small catchment (4.8 km²) in Badong, approximately 100 km upstream the dam. It is characterized by scattered plots of agricultural landuse and resettlements in a largely wooded, steep sloping and mountainous area. Our research is focused on data acquisition and processing to develop a process-oriented erosion model. Hereby, area-covering knowledge of specific soil properties in the catchment is an intrinsic input parameter. This will be acquired by means of digital soil mapping (DSM). Thereby, soil properties are estimated by covariates. The functions are calibrated by soil property samples. The DSM approach is based on an appropriate sample design, which reflects the heterogeneity of the catchment, regarding the covariates with influence on the relevant soil properties. In this approach the covariates, processed by a digital terrain analysis, are outlined by the slope, altitude, profile curvature, plane curvature, and the aspect. For the development of the sample design, we chose the Conditioned Latin Hypercube Sampling (cLHS) procedure (Minasny and McBratney, 2006). It provides an efficient method of sampling variables from their multivariate distribution. Thereby, a sample size n from multiple variables is drawn such that for each variable the sample is marginally maximally stratified. The method ensures the maximal stratification by two features: First, number of strata equals the sample size n and secondly, the probability of falling in each of the strata is n-¹ (McKay et al., 1979). We extended the classical cLHS with extremes (Schmidt et al., 2012) approach by incorporating legacy data of previous field campaigns. Instead of identifying precise sample locations by CLHS, we demarcate the multivariate attribute space of the samples based on the histogram borders of each stratum. This widens the spatial scope of the actual CLHS sample locations and allows the incorporation of legacy data lying within that scope. Furthermore, this approach provides an extended potential regarding the accessibility of sample sites in the field.

Geostatistical Sampling Methods for Efficient Uncertainty Analysis in Flow and Transport Problems

NASA Astrophysics Data System (ADS)

Liodakis, Stylianos; Kyriakidis, Phaedon; Gaganis, Petros

2015-04-01

In hydrogeological applications involving flow and transport of in heterogeneous porous media the spatial distribution of hydraulic conductivity is often parameterized in terms of a lognormal random field based on a histogram and variogram model inferred from data and/or synthesized from relevant knowledge. Realizations of simulated conductivity fields are then generated using geostatistical simulation involving simple random (SR) sampling and are subsequently used as inputs to physically-based simulators of flow and transport in a Monte Carlo framework for evaluating the uncertainty in the spatial distribution of solute concentration due to the uncertainty in the spatial distribution of hydraulic con- ductivity [1]. Realistic uncertainty analysis, however, calls for a large number of simulated concentration fields; hence, can become expensive in terms of both time and computer re- sources. A more efficient alternative to SR sampling is Latin hypercube (LH) sampling, a special case of stratified random sampling, which yields a more representative distribution of simulated attribute values with fewer realizations [2]. Here, term representative implies realizations spanning efficiently the range of possible conductivity values corresponding to the lognormal random field. In this work we investigate the efficiency of alternative methods to classical LH sampling within the context of simulation of flow and transport in a heterogeneous porous medium. More precisely, we consider the stratified likelihood (SL) sampling method of [3], in which attribute realizations are generated using the polar simulation method by exploring the geometrical properties of the multivariate Gaussian distribution function. In addition, we propose a more efficient version of the above method, here termed minimum energy (ME) sampling, whereby a set of N representative conductivity realizations at M locations is constructed by: (i) generating a representative set of N points distributed on the surface of a M-dimensional, unit radius hyper-sphere, (ii) relocating the N points on a representative set of N hyper-spheres of different radii, and (iii) transforming the coordinates of those points to lie on N different hyper-ellipsoids spanning the multivariate Gaussian distribution. The above method is applied in a dimensionality reduction context by defining flow-controlling points over which representative sampling of hydraulic conductivity is performed, thus also accounting for the sensitivity of the flow and transport model to the input hydraulic conductivity field. The performance of the various stratified sampling methods, LH, SL, and ME, is compared to that of SR sampling in terms of reproduction of ensemble statistics of hydraulic conductivity and solute concentration for different sample sizes N (numbers of realizations). The results indicate that ME sampling constitutes an equally if not more efficient simulation method than LH and SL sampling, as it can reproduce to a similar extent statistics of the conductivity and concentration fields, yet with smaller sampling variability than SR sampling. References [1] Gutjahr A.L. and Bras R.L. Spatial variability in subsurface flow and transport: A review. Reliability Engineering & System Safety, 42, 293-316, (1993). [2] Helton J.C. and Davis F.J. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81, 23-69, (2003). [3] Switzer P. Multiple simulation of spatial fields. In: Heuvelink G, Lemmens M (eds) Proceedings of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Coronet Books Inc., pp 629?635 (2000).

Experiences and results multitasking a hydrodynamics code on global and local memory machines

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

Mandell, D.

1987-01-01

A one-dimensional, time-dependent Lagrangian hydrodynamics code using a Godunov solution method has been multitasked for the Cray X-MP/48, the Intel iPSC hypercube, the Alliant FX series and the IBM RP3 computers. Actual multitasking results have been obtained for the Cray, Intel and Alliant computers and simulated results were obtained for the Cray and RP3 machines. The differences in the methods required to multitask on each of the machines is discussed. Results are presented for a sample problem involving a shock wave moving down a channel. Comparisons are made between theoretical speedups, predicted by Amdahl's law, and the actual speedups obtained.more » The problems of debugging on the different machines are also described.« less

Distributed Memory Compiler Methods for Irregular Problems - Data Copy Reuse and Runtime Partitioning

DTIC Science & Technology

1991-09-01

addition, support for Saltz was provided by NSF from NSF Grant ASC-8819374. i 1, introduction Over the past fewyers, ,we have devoped -methods needed to... network . In Third Conf. on Hypercube Concurrent Computers and Applications, pages 241-27278, 1988. [17] G. Fox, S. Hiranandani, K. Kennedy, C. Koelbel

High-speed mid-infrared hyperspectral imaging using quantum cascade lasers

NASA Astrophysics Data System (ADS)

Kelley, David B.; Goyal, Anish K.; Zhu, Ninghui; Wood, Derek A.; Myers, Travis R.; Kotidis, Petros; Murphy, Cara; Georgan, Chelsea; Raz, Gil; Maulini, Richard; Müller, Antoine

2017-05-01

We report on a standoff chemical detection system using widely tunable external-cavity quantum cascade lasers (ECQCLs) to illuminate target surfaces in the mid infrared (λ = 7.4 - 10.5 μm). Hyperspectral images (hypercubes) are acquired by synchronously operating the EC-QCLs with a LN2-cooled HgCdTe camera. The use of rapidly tunable lasers and a high-frame-rate camera enables the capture of hypercubes with 128 x 128 pixels and >100 wavelengths in <0.1 s. Furthermore, raster scanning of the laser illumination allowed imaging of a 100-cm2 area at 5-m standoff. Raw hypercubes are post-processed to generate a hypercube that represents the surface reflectance relative to that of a diffuse reflectance standard. Results will be shown for liquids (e.g., silicone oil) and solid particles (e.g., caffeine, acetaminophen) on a variety of surfaces (e.g., aluminum, plastic, glass). Signature spectra are obtained for particulate loadings of RDX on glass of <1 μg/cm2.

Performance of a parallel code for the Euler equations on hypercube computers

NASA Technical Reports Server (NTRS)

Barszcz, Eric; Chan, Tony F.; Jesperson, Dennis C.; Tuminaro, Raymond S.

1990-01-01

The performance of hypercubes were evaluated on a computational fluid dynamics problem and the parallel environment issues were considered that must be addressed, such as algorithm changes, implementation choices, programming effort, and programming environment. The evaluation focuses on a widely used fluid dynamics code, FLO52, which solves the two dimensional steady Euler equations describing flow around the airfoil. The code development experience is described, including interacting with the operating system, utilizing the message-passing communication system, and code modifications necessary to increase parallel efficiency. Results from two hypercube parallel computers (a 16-node iPSC/2, and a 512-node NCUBE/ten) are discussed and compared. In addition, a mathematical model of the execution time was developed as a function of several machine and algorithm parameters. This model accurately predicts the actual run times obtained and is used to explore the performance of the code in interesting but yet physically realizable regions of the parameter space. Based on this model, predictions about future hypercubes are made.

Ordered fast fourier transforms on a massively parallel hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Tong, Charles; Swarztrauber, Paul N.

1989-01-01

Design alternatives for ordered Fast Fourier Transformation (FFT) algorithms were examined on massively parallel hypercube multiprocessors such as the Connection Machine. Particular emphasis is placed on reducing communication which is known to dominate the overall computing time. To this end, the order and computational phases of the FFT were combined, and the sequence to processor maps that reduce communication were used. The class of ordered transforms is expanded to include any FFT in which the order of the transform is the same as that of the input sequence. Two such orderings are examined, namely, standard-order and A-order which can be implemented with equal ease on the Connection Machine where orderings are determined by geometries and priorities. If the sequence has N = 2 exp r elements and the hypercube has P = 2 exp d processors, then a standard-order FFT can be implemented with d + r/2 + 1 parallel transmissions. An A-order sequence can be transformed with 2d - r/2 parallel transmissions which is r - d + 1 fewer than the standard order. A parallel method for computing the trigonometric coefficients is presented that does not use trigonometric functions or interprocessor communication. A performance of 0.9 GFLOPS was obtained for an A-order transform on the Connection Machine.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

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

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

Requirements analysis for a hardware, discrete-event, simulation engine accelerator

NASA Astrophysics Data System (ADS)

Taylor, Paul J., Jr.

1991-12-01

An analysis of a general Discrete Event Simulation (DES), executing on the distributed architecture of an eight mode Intel PSC/2 hypercube, was performed. The most time consuming portions of the general DES algorithm were determined to be the functions associated with message passing of required simulation data between processing nodes of the hypercube architecture. A behavioral description, using the IEEE standard VHSIC Hardware Description and Design Language (VHDL), for a general DES hardware accelerator is presented. The behavioral description specifies the operational requirements for a DES coprocessor to augment the hypercube's execution of DES simulations. The DES coprocessor design implements the functions necessary to perform distributed discrete event simulations using a conservative time synchronization protocol.

Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.

PubMed

Fu, Zhaohao; Hao, Lingxin

2018-01-15

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Agent-based modeling of China's rural-urban migration and social network structure

NASA Astrophysics Data System (ADS)

Fu, Zhaohao; Hao, Lingxin

2018-01-01

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Multiphase complete exchange on Paragon, SP2 and CS-2

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

The overhead of interprocessor communication is a major factor in limiting the performance of parallel computer systems. The complete exchange is the severest communication pattern in that it requires each processor to send a distinct message to every other processor. This pattern is at the heart of many important parallel applications. On hypercubes, multiphase complete exchange has been developed and shown to provide optimal performance over varying message sizes. Most commercial multicomputer systems do not have a hypercube interconnect. However, they use special purpose hardware and dedicated communication processors to achieve very high performance communication and can be made to emulate the hypercube quite well. Multiphase complete exchange has been implemented on three contemporary parallel architectures: the Intel Paragon, IBM SP2 and Meiko CS-2. The essential features of these machines are described and their basic interprocessor communication overheads are discussed. The performance of multiphase complete exchange is evaluated on each machine. It is shown that the theoretical ideas developed for hypercubes are also applicable in practice to these machines and that multiphase complete exchange can lead to major savings in execution time over traditional solutions.

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Zubair, Mohammad

1993-01-01

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

Statistics of lattice animals

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Nadler, Walder; Grassberger, Peter

2005-07-01

The scaling behavior of randomly branched polymers in a good solvent is studied in two to nine dimensions, modeled by lattice animals on simple hypercubic lattices. For the simulations, we use a biased sequential sampling algorithm with re-sampling, similar to the pruned-enriched Rosenbluth method (PERM) used extensively for linear polymers. We obtain high statistics of animals with up to several thousand sites in all dimension 2⩽d⩽9. The partition sum (number of different animals) and gyration radii are estimated. In all dimensions we verify the Parisi-Sourlas prediction, and we verify all exactly known critical exponents in dimensions 2, 3, 4, and ⩾8. In addition, we present the hitherto most precise estimates for growth constants in d⩾3. For clusters with one site attached to an attractive surface, we verify the superuniversality of the cross-over exponent at the adsorption transition predicted by Janssen and Lyssy.

Application of positive-real functions in hyperstable discrete model-reference adaptive system design.

NASA Technical Reports Server (NTRS)

Karmarkar, J. S.

1972-01-01

Proposal of an algorithmic procedure, based on mathematical programming methods, to design compensators for hyperstable discrete model-reference adaptive systems (MRAS). The objective of the compensator is to render the MRAS insensitive to initial parameter estimates within a maximized hypercube in the model parameter space.

Parallel Algorithm Solves Coupled Differential Equations

NASA Technical Reports Server (NTRS)

Hayashi, A.

1987-01-01

Numerical methods adapted to concurrent processing. Algorithm solves set of coupled partial differential equations by numerical integration. Adapted to run on hypercube computer, algorithm separates problem into smaller problems solved concurrently. Increase in computing speed with concurrent processing over that achievable with conventional sequential processing appreciable, especially for large problems.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed

Nadkarni, P M; Miller, P L

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

A 2D electrostatic PIC code for the Mark III Hypercube

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

Ferraro, R.D.; Liewer, P.C.; Decyk, V.K.

We have implemented a 2D electrostastic plasma particle in cell (PIC) simulation code on the Caltech/JPL Mark IIIfp Hypercube. The code simulates plasma effects by evolving in time the trajectories of thousands to millions of charged particles subject to their self-consistent fields. Each particle`s position and velocity is advanced in time using a leap frog method for integrating Newton`s equations of motion in electric and magnetic fields. The electric field due to these moving charged particles is calculated on a spatial grid at each time by solving Poisson`s equation in Fourier space. These two tasks represent the largest part ofmore » the computation. To obtain efficient operation on a distributed memory parallel computer, we are using the General Concurrent PIC (GCPIC) algorithm previously developed for a 1D parallel PIC code.« less

Uncertain dynamic analysis for rigid-flexible mechanisms with random geometry and material properties

NASA Astrophysics Data System (ADS)

Wu, Jinglai; Luo, Zhen; Zhang, Nong; Zhang, Yunqing; Walker, Paul D.

2017-02-01

This paper proposes an uncertain modelling and computational method to analyze dynamic responses of rigid-flexible multibody systems (or mechanisms) with random geometry and material properties. Firstly, the deterministic model for the rigid-flexible multibody system is built with the absolute node coordinate formula (ANCF), in which the flexible parts are modeled by using ANCF elements, while the rigid parts are described by ANCF reference nodes (ANCF-RNs). Secondly, uncertainty for the geometry of rigid parts is expressed as uniform random variables, while the uncertainty for the material properties of flexible parts is modeled as a continuous random field, which is further discretized to Gaussian random variables using a series expansion method. Finally, a non-intrusive numerical method is developed to solve the dynamic equations of systems involving both types of random variables, which systematically integrates the deterministic generalized-α solver with Latin Hypercube sampling (LHS) and Polynomial Chaos (PC) expansion. The benchmark slider-crank mechanism is used as a numerical example to demonstrate the characteristics of the proposed method.

Non-intrusive reduced order modeling of nonlinear problems using neural networks

NASA Astrophysics Data System (ADS)

Hesthaven, J. S.; Ubbiali, S.

2018-06-01

We develop a non-intrusive reduced basis (RB) method for parametrized steady-state partial differential equations (PDEs). The method extracts a reduced basis from a collection of high-fidelity solutions via a proper orthogonal decomposition (POD) and employs artificial neural networks (ANNs), particularly multi-layer perceptrons (MLPs), to accurately approximate the coefficients of the reduced model. The search for the optimal number of neurons and the minimum amount of training samples to avoid overfitting is carried out in the offline phase through an automatic routine, relying upon a joint use of the Latin hypercube sampling (LHS) and the Levenberg-Marquardt (LM) training algorithm. This guarantees a complete offline-online decoupling, leading to an efficient RB method - referred to as POD-NN - suitable also for general nonlinear problems with a non-affine parametric dependence. Numerical studies are presented for the nonlinear Poisson equation and for driven cavity viscous flows, modeled through the steady incompressible Navier-Stokes equations. Both physical and geometrical parametrizations are considered. Several results confirm the accuracy of the POD-NN method and show the substantial speed-up enabled at the online stage as compared to a traditional RB strategy.

Hypercube technology

NASA Technical Reports Server (NTRS)

Parker, Jay W.; Cwik, Tom; Ferraro, Robert D.; Liewer, Paulett C.; Patterson, Jean E.

1991-01-01

The JPL designed MARKIII hypercube supercomputer has been in application service since June 1988 and has had successful application to a broad problem set including electromagnetic scattering, discrete event simulation, plasma transport, matrix algorithms, neural network simulation, image processing, and graphics. Currently, problems that are not homogeneous are being attempted, and, through this involvement with real world applications, the software is evolving to handle the heterogeneous class problems efficiently.

Generalized Likelihood Uncertainty Estimation (GLUE) methodology for optimization of extraction in natural products.

PubMed

Maulidiani; Rudiyanto; Abas, Faridah; Ismail, Intan Safinar; Lajis, Nordin H

2018-06-01

Optimization process is an important aspect in the natural product extractions. Herein, an alternative approach is proposed for the optimization in extraction, namely, the Generalized Likelihood Uncertainty Estimation (GLUE). The approach combines the Latin hypercube sampling, the feasible range of independent variables, the Monte Carlo simulation, and the threshold criteria of response variables. The GLUE method is tested in three different techniques including the ultrasound, the microwave, and the supercritical CO 2 assisted extractions utilizing the data from previously published reports. The study found that this method can: provide more information on the combined effects of the independent variables on the response variables in the dotty plots; deal with unlimited number of independent and response variables; consider combined multiple threshold criteria, which is subjective depending on the target of the investigation for response variables; and provide a range of values with their distribution for the optimization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Accurate evaluation of sensitivity for calibration between a LiDAR and a panoramic camera used for remote sensing

NASA Astrophysics Data System (ADS)

García-Moreno, Angel-Iván; González-Barbosa, José-Joel; Ramírez-Pedraza, Alfonso; Hurtado-Ramos, Juan B.; Ornelas-Rodriguez, Francisco-Javier

2016-04-01

Computer-based reconstruction models can be used to approximate urban environments. These models are usually based on several mathematical approximations and the usage of different sensors, which implies dependency on many variables. The sensitivity analysis presented in this paper is used to weigh the relative importance of each uncertainty contributor into the calibration of a panoramic camera-LiDAR system. Both sensors are used for three-dimensional urban reconstruction. Simulated and experimental tests were conducted. For the simulated tests we analyze and compare the calibration parameters using the Monte Carlo and Latin hypercube sampling techniques. Sensitivity analysis for each variable involved into the calibration was computed by the Sobol method, which is based on the analysis of the variance breakdown, and the Fourier amplitude sensitivity test method, which is based on Fourier's analysis. Sensitivity analysis is an essential tool in simulation modeling and for performing error propagation assessments.

Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

PubMed Central

Nadkarni, P. M.; Miller, P. L.

1991-01-01

A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations. PMID:1807632

A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model

DOE PAGES

Gan, Yanjun; Duan, Qingyun; Gong, Wei; ...

2014-01-01

Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin nearmore » Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LPτ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.« less

Communication overhead on the Intel iPSC-860 hypercube

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1990-01-01

Experiments were conducted on the Intel iPSC-860 hypercube in order to evaluate the overhead of interprocessor communication. It is demonstrated that: (1) contrary to popular belief, the distance between two communicating processors has a significant impact on communication time, (2) edge contention can increase communication time by a factor of more than 7, and (3) node contention has no measurable impact.

RISC-type microprocessors may revolutionize aerospace simulation

NASA Astrophysics Data System (ADS)

Jackson, Albert S.

The author explores the application of RISC (reduced instruction set computer) processors in massively parallel computer (MPC) designs for aerospace simulation. The MPC approach is shown to be well adapted to the needs of aerospace simulation. It is shown that any of the three common types of interconnection schemes used with MPCs are effective for general-purpose simulation, although the bus-or switch-oriented machines are somewhat easier to use. For partial differential equation models, the hypercube approach at first glance appears more efficient because the nearest-neighbor connections required for three-dimensional models are hardwired in a hypercube machine. However, the data broadcast ability of a bus system, combined with the fact that data can be transmitted over a bus as soon as it has been updated, makes the bus approach very competitive with the hypercube approach even for these types of models.

Generalized hypercube structures and hyperswitch communication network

NASA Technical Reports Server (NTRS)

Young, Steven D.

1992-01-01

This paper discusses an ongoing study that uses a recent development in communication control technology to implement hybrid hypercube structures. These architectures are similar to binary hypercubes, but they also provide added connectivity between the processors. This added connectivity increases communication reliability while decreasing the latency of interprocessor message passing. Because these factors directly determine the speed that can be obtained by multiprocessor systems, these architectures are attractive for applications such as remote exploration and experimentation, where high performance and ultrareliability are required. This paper describes and enumerates these architectures and discusses how they can be implemented with a modified version of the hyperswitch communication network (HCN). The HCN is analyzed because it has three attractive features that enable these architectures to be effective: speed, fault tolerance, and the ability to pass multiple messages simultaneously through the same hyperswitch controller.

Design optimization of hydraulic turbine draft tube based on CFD and DOE method

NASA Astrophysics Data System (ADS)

Nam, Mun chol; Dechun, Ba; Xiangji, Yue; Mingri, Jin

2018-03-01

In order to improve performance of the hydraulic turbine draft tube in its design process, the optimization for draft tube is performed based on multi-disciplinary collaborative design optimization platform by combining the computation fluid dynamic (CFD) and the design of experiment (DOE) in this paper. The geometrical design variables are considered as the median section in the draft tube and the cross section in its exit diffuser and objective function is to maximize the pressure recovery factor (Cp). Sample matrixes required for the shape optimization of the draft tube are generated by optimal Latin hypercube (OLH) method of the DOE technique and their performances are evaluated through computational fluid dynamic (CFD) numerical simulation. Subsequently the main effect analysis and the sensitivity analysis of the geometrical parameters of the draft tube are accomplished. Then, the design optimization of the geometrical design variables is determined using the response surface method. The optimization result of the draft tube shows a marked performance improvement over the original.

A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

Matched-filter algorithm for subpixel spectral detection in hyperspectral image data

NASA Astrophysics Data System (ADS)

Borough, Howard C.

1991-11-01

Hyperspectral imagery, spatial imagery with associated wavelength data for every pixel, offers a significant potential for improved detection and identification of certain classes of targets. The ability to make spectral identifications of objects which only partially fill a single pixel (due to range or small size) is of considerable interest. Multiband imagery such as Landsat's 5 and 7 band imagery has demonstrated significant utility in the past. Hyperspectral imaging systems with hundreds of spectral bands offer improved performance. To explore the application of differentpixel spectral detection algorithms a synthesized set of hyperspectral image data (hypercubes) was generated utilizing NASA earth resources and other spectral data. The data was modified using LOWTRAN 7 to model the illumination, atmospheric contributions, attenuations and viewing geometry to represent a nadir view from 10,000 ft. altitude. The base hypercube (HC) represented 16 by 21 spatial pixels with 101 wavelength samples from 0.5 to 2.5 micrometers for each pixel. Insertions were made into the base data to provide random location, random pixel percentage, and random material. Fifteen different hypercubes were generated for blind testing of candidate algorithms. An algorithm utilizing a matched filter in the spectral dimension proved surprisingly good yielding 100% detections for pixels filled greater than 40% with a standard camouflage paint, and a 50% probability of detection for pixels filled 20% with the paint, with no false alarms. The false alarm rate as a function of the number of spectral bands in the range from 101 to 12 bands was measured and found to increase from zero to 50% illustrating the value of a large number of spectral bands. This test was on imagery without system noise; the next step is to incorporate typical system noise sources.

Validation of heat transfer, thermal decomposition, and container pressurization of polyurethane foam using mean value and Latin hypercube sampling approaches

DOE PAGES

Scott, Sarah N.; Dodd, Amanda B.; Larsen, Marvin E.; ...

2014-12-09

In this study, polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container in order to protect them from hostile environments or from accidents such as fire. In fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of polymeric methylene diisocyanate (PMDI)-polyether-polyol based polyurethane foam is presented and compared to experimental results to assess the validity of a 3-D finite element model of themore » heat transfer and degradation processes. In this series of experiments, 320 kg/m 3 PMDI foam in a 0.2 L sealed steel container is heated to 1,073 K at a rate of 150 K/min. The experiment ends when the can breaches due to the buildup of pressure. The temperature at key location is monitored as well as the internal pressure of the can. Both experimental uncertainty and computational uncertainty are examined and compared. The mean value method (MV) and Latin hypercube sampling (LHS) approach are used to propagate the uncertainty through the model. The results of the both the MV method and the LHS approach show that while the model generally can predict the temperature at given locations in the system, it is less successful at predicting the pressure response. Also, these two approaches for propagating uncertainty agree with each other, the importance of each input parameter on the simulation results is also investigated, showing that for the temperature response the conductivity of the steel container and the effective conductivity of the foam, are the most important parameters. For the pressure response, the activation energy, effective conductivity, and specific heat are most important. The comparison to experiments and the identification of the drivers of uncertainty allow for targeted development of the computational model and for definition of the experiments necessary to improve accuracy.« less

Validation of heat transfer, thermal decomposition, and container pressurization of polyurethane foam using mean value and Latin hypercube sampling approaches

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

Scott, Sarah N.; Dodd, Amanda B.; Larsen, Marvin E.

In this study, polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container in order to protect them from hostile environments or from accidents such as fire. In fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of polymeric methylene diisocyanate (PMDI)-polyether-polyol based polyurethane foam is presented and compared to experimental results to assess the validity of a 3-D finite element model of themore » heat transfer and degradation processes. In this series of experiments, 320 kg/m 3 PMDI foam in a 0.2 L sealed steel container is heated to 1,073 K at a rate of 150 K/min. The experiment ends when the can breaches due to the buildup of pressure. The temperature at key location is monitored as well as the internal pressure of the can. Both experimental uncertainty and computational uncertainty are examined and compared. The mean value method (MV) and Latin hypercube sampling (LHS) approach are used to propagate the uncertainty through the model. The results of the both the MV method and the LHS approach show that while the model generally can predict the temperature at given locations in the system, it is less successful at predicting the pressure response. Also, these two approaches for propagating uncertainty agree with each other, the importance of each input parameter on the simulation results is also investigated, showing that for the temperature response the conductivity of the steel container and the effective conductivity of the foam, are the most important parameters. For the pressure response, the activation energy, effective conductivity, and specific heat are most important. The comparison to experiments and the identification of the drivers of uncertainty allow for targeted development of the computational model and for definition of the experiments necessary to improve accuracy.« less

Concurrent electromagnetic scattering analysis

NASA Technical Reports Server (NTRS)

Patterson, Jean E.; Cwik, Tom; Ferraro, Robert D.; Jacobi, Nathan; Liewer, Paulett C.; Lockhart, Thomas G.; Lyzenga, Gregory A.; Parker, Jay

1989-01-01

The computational power of the hypercube parallel computing architecture is applied to the solution of large-scale electromagnetic scattering and radiation problems. Three analysis codes have been implemented. A Hypercube Electromagnetic Interactive Analysis Workstation was developed to aid in the design and analysis of metallic structures such as antennas and to facilitate the use of these analysis codes. The workstation provides a general user environment for specification of the structure to be analyzed and graphical representations of the results.

Asynchronous Communication Scheme For Hypercube Computer

NASA Technical Reports Server (NTRS)

Madan, Herb S.

1988-01-01

Scheme devised for asynchronous-message communication system for Mark III hypercube concurrent-processor network. Network consists of up to 1,024 processing elements connected electrically as though were at corners of 10-dimensional cube. Each node contains two Motorola 68020 processors along with Motorola 68881 floating-point processor utilizing up to 4 megabytes of shared dynamic random-access memory. Scheme intended to support applications requiring passage of both polled or solicited and unsolicited messages.

Image-Processing Software For A Hypercube Computer

NASA Technical Reports Server (NTRS)

Lee, Meemong; Mazer, Alan S.; Groom, Steven L.; Williams, Winifred I.

1992-01-01

Concurrent Image Processing Executive (CIPE) is software system intended to develop and use image-processing application programs on concurrent computing environment. Designed to shield programmer from complexities of concurrent-system architecture, it provides interactive image-processing environment for end user. CIPE utilizes architectural characteristics of particular concurrent system to maximize efficiency while preserving architectural independence from user and programmer. CIPE runs on Mark-IIIfp 8-node hypercube computer and associated SUN-4 host computer.

Virtual time and time warp on the JPL hypercube. [operating system implementation for distributed simulation

NASA Technical Reports Server (NTRS)

Jefferson, David; Beckman, Brian

1986-01-01

This paper describes the concept of virtual time and its implementation in the Time Warp Operating System at the Jet Propulsion Laboratory. Virtual time is a distributed synchronization paradigm that is appropriate for distributed simulation, database concurrency control, real time systems, and coordination of replicated processes. The Time Warp Operating System is targeted toward the distributed simulation application and runs on a 32-node JPL Mark II Hypercube.

Electrooptical adaptive switching network for the hypercube computer

NASA Technical Reports Server (NTRS)

Chow, E.; Peterson, J.

1988-01-01

An all-optical network design for the hyperswitch network using regular free-space interconnects between electronic processor nodes is presented. The adaptive routing model used is described, and an adaptive routing control example is presented. The design demonstrates that existing electrooptical techniques are sufficient for implementing efficient parallel architectures without the need for more complex means of implementing arbitrary interconnection schemes. The electrooptical hyperswitch network significantly improves the communication performance of the hypercube computer.

Novel snapshot hyperspectral imager for fluorescence imaging

NASA Astrophysics Data System (ADS)

Chandler, Lynn; Chandler, Andrea; Periasamy, Ammasi

2018-02-01

Hyperspectral imaging has emerged as a new technique for the identification and classification of biological tissue1. Benefitting recent developments in sensor technology, the new class of hyperspectral imagers can capture entire hypercubes with single shot operation and it shows great potential for real-time imaging in biomedical sciences. This paper explores the use of a SnapShot imager in fluorescence imaging via microscope for the very first time. Utilizing the latest imaging sensor, the Snapshot imager is both compact and attachable via C-mount to any commercially available light microscope. Using this setup, fluorescence hypercubes of several cells were generated, containing both spatial and spectral information. The fluorescence images were acquired with one shot operation for all the emission range from visible to near infrared (VIS-IR). The paper will present the hypercubes obtained images from example tissues (475-630nm). This study demonstrates the potential of application in cell biology or biomedical applications for real time monitoring.

Inferring patterns in mitochondrial DNA sequences through hypercube independent spanning trees.

PubMed

Silva, Eduardo Sant Ana da; Pedrini, Helio

2016-03-01

Given a graph G, a set of spanning trees rooted at a vertex r of G is said vertex/edge independent if, for each vertex v of G, v≠r, the paths of r to v in any pair of trees are vertex/edge disjoint. Independent spanning trees (ISTs) provide a number of advantages in data broadcasting due to their fault tolerant properties. For this reason, some studies have addressed the issue by providing mechanisms for constructing independent spanning trees efficiently. In this work, we investigate how to construct independent spanning trees on hypercubes, which are generated based upon spanning binomial trees, and how to use them to predict mitochondrial DNA sequence parts through paths on the hypercube. The prediction works both for inferring mitochondrial DNA sequences comprised of six bases as well as infer anomalies that probably should not belong to the mitochondrial DNA standard. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiphase complete exchange on a circuit switched hypercube

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1991-01-01

On a distributed memory parallel computer, the complete exchange (all-to-all personalized) communication pattern requires each of n processors to send a different block of data to each of the remaining n - 1 processors. This pattern is at the heart of many important algorithms, most notably the matrix transpose. For a circuit switched hypercube of dimension d(n = 2(sup d)), two algorithms for achieving complete exchange are known. These are (1) the Standard Exchange approach that employs d transmissions of size 2(sup d-1) blocks each and is useful for small block sizes, and (2) the Optimal Circuit Switched algorithm that employs 2(sup d) - 1 transmissions of 1 block each and is best for large block sizes. A unified multiphase algorithm is described that includes these two algorithms as special cases. The complete exchange on a hypercube of dimension d and block size m is achieved by carrying out k partial exchange on subcubes of dimension d(sub i) Sigma(sup k)(sub i=1) d(sub i) = d and effective block size m(sub i) = m2(sup d-di). When k = d and all d(sub i) = 1, this corresponds to algorithm (1) above. For the case of k = 1 and d(sub i) = d, this becomes the circuit switched algorithm (2). Changing the subcube dimensions d, varies the effective block size and permits a compromise between the data permutation and block transmission overhead of (1) and the startup overhead of (2). For a hypercube of dimension d, the number of possible combinations of subcubes is p(d), the number of partitions of the integer d. This is an exponential but very slowly growing function and it is feasible over these partitions to discover the best combination for a given message size. The approach was analyzed for, and implemented on, the Intel iPSC-860 circuit switched hypercube. Measurements show good agreement with predictions and demonstrate that the multiphase approach can substantially improve performance for block sizes in the 0 to 160 byte range. This range, which corresponds to 0 to 40 floating point numbers per processor, is commonly encountered in practical numeric applications. The multiphase technique is applicable to all circuit-switched hypercubes that use the common e-cube routing strategy.

Parallel algorithms for quantum chemistry. I. Integral transformations on a hypercube multiprocessor

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

Whiteside, R.A.; Binkley, J.S.; Colvin, M.E.

1987-02-15

For many years it has been recognized that fundamental physical constraints such as the speed of light will limit the ultimate speed of single processor computers to less than about three billion floating point operations per second (3 GFLOPS). This limitation is becoming increasingly restrictive as commercially available machines are now within an order of magnitude of this asymptotic limit. A natural way to avoid this limit is to harness together many processors to work on a single computational problem. In principle, these parallel processing computers have speeds limited only by the number of processors one chooses to acquire. Themore » usefulness of potentially unlimited processing speed to a computationally intensive field such as quantum chemistry is obvious. If these methods are to be applied to significantly larger chemical systems, parallel schemes will have to be employed. For this reason we have developed distributed-memory algorithms for a number of standard quantum chemical methods. We are currently implementing these on a 32 processor Intel hypercube. In this paper we present our algorithm and benchmark results for one of the bottleneck steps in quantum chemical calculations: the four index integral transformation.« less

Revolution or evolution? An analysis of E-health innovation and impact using a hypercube model.

PubMed

Wu, Jen-Her; Huang, An-Sheng; Hisa, Tzyh-Lih; Tsai, Hsien-Tang

2006-01-01

This study utilises a hypercube innovation model to analyse the changes in both healthcare informatics and medical related delivery models based on the innovations from Tele-healthcare, electronic healthcare (E-healthcare), to mobile healthcare (M-healthcare). Further, the critical impacts of these E-health innovations on the stakeholders: healthcare customers, hospitals, healthcare complementary providers and healthcare regulators are identified. Thereafter, the critical capabilities for adopting each innovation are discussed.

Validation of Heat Transfer Thermal Decomposition and Container Pressurization of Polyurethane Foam.

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

Scott, Sarah Nicole; Dodd, Amanda B.; Larsen, Marvin E.

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. In fire environments, gas pressure from thermal decomposition of polymers can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of PMDI-based polyurethane foam is presented to assess the validity of the computational model. Both experimental measurement uncertainty and model prediction uncertainty are examined and compared. Both the mean value method and Latin hypercube sampling approach are used to propagate the uncertainty through the model. In addition to comparing computational and experimental results, the importance of each input parameter on the simulation resultmore » is also investigated. These results show that further development in the physics model of the foam and appropriate associated material testing are necessary to improve model accuracy.« less

Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

NASA Astrophysics Data System (ADS)

Chlebda, Damian K.; Majda, Alicja; Łojewski, Tomasz; Łojewska, Joanna

2016-11-01

Differentiation of the written text can be performed with a non-invasive and non-contact tool that connects conventional imaging methods with spectroscopy. Hyperspectral imaging (HSI) is a relatively new and rapid analytical technique that can be applied in forensic science disciplines. It allows an image of the sample to be acquired, with full spectral information within every pixel. For this paper, HSI and three statistical methods (hierarchical cluster analysis, principal component analysis, and spectral angle mapper) were used to distinguish between traces of modern black gel pen inks. Non-invasiveness and high efficiency are among the unquestionable advantages of ink differentiation using HSI. It is also less time-consuming than traditional methods such as chromatography. In this study, a set of 45 modern gel pen ink marks deposited on a paper sheet were registered. The spectral characteristics embodied in every pixel were extracted from an image and analysed using statistical methods, externally and directly on the hypercube. As a result, different black gel inks deposited on paper can be distinguished and classified into several groups, in a non-invasive manner.

Sensitivity analysis of infectious disease models: methods, advances and their application

PubMed Central

Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

2013-01-01

Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

Monte Carlo methods for multidimensional integration for European option pricing

NASA Astrophysics Data System (ADS)

Todorov, V.; Dimov, I. T.

2016-10-01

In this paper, we illustrate examples of highly accurate Monte Carlo and quasi-Monte Carlo methods for multiple integrals related to the evaluation of European style options. The idea is that the value of the option is formulated in terms of the expectation of some random variable; then the average of independent samples of this random variable is used to estimate the value of the option. First we obtain an integral representation for the value of the option using the risk neutral valuation formula. Then with an appropriations change of the constants we obtain a multidimensional integral over the unit hypercube of the corresponding dimensionality. Then we compare a specific type of lattice rules over one of the best low discrepancy sequence of Sobol for numerical integration. Quasi-Monte Carlo methods are compared with Adaptive and Crude Monte Carlo techniques for solving the problem. The four approaches are completely different thus it is a question of interest to know which one of them outperforms the other for evaluation multidimensional integrals in finance. Some of the advantages and disadvantages of the developed algorithms are discussed.

An uncertainty analysis of the flood-stage upstream from a bridge.

PubMed

Sowiński, M

2006-01-01

The paper begins with the formulation of the problem in the form of a general performance function. Next the Latin hypercube sampling (LHS) technique--a modified version of the Monte Carlo method is briefly described. The essential uncertainty analysis of the flood-stage upstream from a bridge starts with a description of the hydraulic model. This model concept is based on the HEC-RAS model developed for subcritical flow under a bridge without piers in which the energy equation is applied. The next section contains the characteristic of the basic variables including a specification of their statistics (means and variances). Next the problem of correlated variables is discussed and assumptions concerning correlation among basic variables are formulated. The analysis of results is based on LHS ranking lists obtained from the computer package UNCSAM. Results fot two examples are given: one for independent and the other for correlated variables.

Dynamics of hepatitis C under optimal therapy and sampling based analysis

NASA Astrophysics Data System (ADS)

Pachpute, Gaurav; Chakrabarty, Siddhartha P.

2013-08-01

We examine two models for hepatitis C viral (HCV) dynamics, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. Optimal therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The optimal therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the optimal therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.

Performance Model and Sensitivity Analysis for a Solar Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Rehman, Naveed Ur; Siddiqui, Mubashir Ali

2017-03-01

In this paper, a regression model for evaluating the performance of solar concentrated thermoelectric generators (SCTEGs) is established and the significance of contributing parameters is discussed in detail. The model is based on several natural, design and operational parameters of the system, including the thermoelectric generator (TEG) module and its intrinsic material properties, the connected electrical load, concentrator attributes, heat transfer coefficients, solar flux, and ambient temperature. The model is developed by fitting a response curve, using the least-squares method, to the results. The sample points for the model were obtained by simulating a thermodynamic model, also developed in this paper, over a range of values of input variables. These samples were generated employing the Latin hypercube sampling (LHS) technique using a realistic distribution of parameters. The coefficient of determination was found to be 99.2%. The proposed model is validated by comparing the predicted results with those in the published literature. In addition, based on the elasticity for parameters in the model, sensitivity analysis was performed and the effects of parameters on the performance of SCTEGs are discussed in detail. This research will contribute to the design and performance evaluation of any SCTEG system for a variety of applications.

The Influence of PV Module Materials and Design on Solder Joint Thermal Fatigue Durability

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

Bosco, Nick; Silverman, Timothy J.; Kurtz, Sarah

Finite element model (FEM) simulations have been performed to elucidate the effect of flat plate photovoltaic (PV) module materials and design on PbSn eutectic solder joint thermal fatigue durability. The statistical method of Latin Hypercube sampling was employed to investigate the sensitivity of simulated damage to each input variable. Variables of laminate material properties and their thicknesses were investigated. Using analysis of variance, we determined that the rate of solder fatigue was most sensitive to solder layer thickness, with copper ribbon and silicon thickness being the next two most sensitive variables. By simulating both accelerated thermal cycles (ATCs) and PVmore » cell temperature histories through two characteristic days of service, we determined that the acceleration factor between the ATC and outdoor service was independent of the variables sampled in this study. This result implies that an ATC test will represent a similar time of outdoor exposure for a wide range of module designs. This is an encouraging result for the standard ATC that must be universally applied across all modules.« less

Energies and radial distributions of Bs mesons - the effect of hypercubic blocking

NASA Astrophysics Data System (ADS)

Koponen, Jonna

2006-12-01

This is a follow-up to our earlier work for the energies and the charge (vector) and matter (scalar) distributions for S-wave states in a heavy-light meson, where the heavy quark is static and the light quark has a mass about that of the strange quark. We study the radial distributions of higher angular momentum states, namely P- and D-wave states, using a "fuzzy" static quark. A new improvement is the use of hypercubic blocking in the time direction, which effectively constrains the heavy quark to move within a 2a hypercube (a is the lattice spacing). The calculation is carried out with dynamical fermions on a 163 × 32 lattice with a ≈ 0.10 fm generated using the non-perturbatively improved clover action. The configurations were gener- ated by the UKQCD Collaboration using lattice action parameters β = 5.2, c SW = 2.0171 and κ = 0.1350. In nature the closest equivalent of this heavy-light system is the Bs meson. Attempts are now being made to understand these results in terms of the Dirac equation.

Finite elements and the method of conjugate gradients on a concurrent processor

NASA Technical Reports Server (NTRS)

Lyzenga, G. A.; Raefsky, A.; Hager, G. H.

1985-01-01

An algorithm for the iterative solution of finite element problems on a concurrent processor is presented. The method of conjugate gradients is used to solve the system of matrix equations, which is distributed among the processors of a MIMD computer according to an element-based spatial decomposition. This algorithm is implemented in a two-dimensional elastostatics program on the Caltech Hypercube concurrent processor. The results of tests on up to 32 processors show nearly linear concurrent speedup, with efficiencies over 90 percent for sufficiently large problems.

Finite elements and the method of conjugate gradients on a concurrent processor

NASA Technical Reports Server (NTRS)

Lyzenga, G. A.; Raefsky, A.; Hager, B. H.

1984-01-01

An algorithm for the iterative solution of finite element problems on a concurrent processor is presented. The method of conjugate gradients is used to solve the system of matrix equations, which is distributed among the processors of a MIMD computer according to an element-based spatial decomposition. This algorithm is implemented in a two-dimensional elastostatics program on the Caltech Hypercube concurrent processor. The results of tests on up to 32 processors show nearly linear concurrent speedup, with efficiencies over 90% for sufficiently large problems.

Robust stabilization of the Space Station in the presence of inertia matrix uncertainty

NASA Technical Reports Server (NTRS)

Wie, Bong; Liu, Qiang; Sunkel, John

1993-01-01

This paper presents a robust H-infinity full-state feedback control synthesis method for uncertain systems with D11 not equal to 0. The method is applied to the robust stabilization problem of the Space Station in the face of inertia matrix uncertainty. The control design objective is to find a robust controller that yields the largest stable hypercube in uncertain parameter space, while satisfying the nominal performance requirements. The significance of employing an uncertain plant model with D11 not equal 0 is demonstrated.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot.

PubMed

Barhen, J; Toomarian, N; Protopopescu, V

1987-12-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of singleneuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as prec xdence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Optimization of the computational load of a hypercube supercomputer onboard a mobile robot

NASA Technical Reports Server (NTRS)

Barhen, Jacob; Toomarian, N.; Protopopescu, V.

1987-01-01

A combinatorial optimization methodology is developed, which enables the efficient use of hypercube multiprocessors onboard mobile intelligent robots dedicated to time-critical missions. The methodology is implemented in terms of large-scale concurrent algorithms based either on fast simulated annealing, or on nonlinear asynchronous neural networks. In particular, analytic expressions are given for the effect of single-neuron perturbations on the systems' configuration energy. Compact neuromorphic data structures are used to model effects such as precedence constraints, processor idling times, and task-schedule overlaps. Results for a typical robot-dynamics benchmark are presented.

Maximum Torque and Momentum Envelopes for Reaction Wheel Arrays

NASA Technical Reports Server (NTRS)

Reynolds, R. G.; Markley, F. Landis

2001-01-01

Spacecraft reaction wheel maneuvers are limited by the maximum torque and/or angular momentum which the wheels can provide. For an n-wheel configuration, the torque or momentum envelope can be obtained by projecting the n-dimensional hypercube, representing the domain boundary of individual wheel torques or momenta, into three dimensional space via the 3xn matrix of wheel axes. In this paper, the properties of the projected hypercube are discussed, and algorithms are proposed for determining this maximal torque or momentum envelope for general wheel configurations. Practical implementation strategies for specific wheel configurations are also considered.

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

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

Mandelli, Diego; Alfonsi, Andrea; Maljovec, Daniel P.

2016-09-01

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually calledmore » Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.« less

Using an ensemble smoother to evaluate parameter uncertainty of an integrated hydrological model of Yanqi basin

NASA Astrophysics Data System (ADS)

Li, Ning; McLaughlin, Dennis; Kinzelbach, Wolfgang; Li, WenPeng; Dong, XinGuang

2015-10-01

Model uncertainty needs to be quantified to provide objective assessments of the reliability of model predictions and of the risk associated with management decisions that rely on these predictions. This is particularly true in water resource studies that depend on model-based assessments of alternative management strategies. In recent decades, Bayesian data assimilation methods have been widely used in hydrology to assess uncertain model parameters and predictions. In this case study, a particular data assimilation algorithm, the Ensemble Smoother with Multiple Data Assimilation (ESMDA) (Emerick and Reynolds, 2012), is used to derive posterior samples of uncertain model parameters and forecasts for a distributed hydrological model of Yanqi basin, China. This model is constructed using MIKESHE/MIKE11software, which provides for coupling between surface and subsurface processes (DHI, 2011a-d). The random samples in the posterior parameter ensemble are obtained by using measurements to update 50 prior parameter samples generated with a Latin Hypercube Sampling (LHS) procedure. The posterior forecast samples are obtained from model runs that use the corresponding posterior parameter samples. Two iterative sample update methods are considered: one based on an a perturbed observation Kalman filter update and one based on a square root Kalman filter update. These alternatives give nearly the same results and converge in only two iterations. The uncertain parameters considered include hydraulic conductivities, drainage and river leakage factors, van Genuchten soil property parameters, and dispersion coefficients. The results show that the uncertainty in many of the parameters is reduced during the smoother updating process, reflecting information obtained from the observations. Some of the parameters are insensitive and do not benefit from measurement information. The correlation coefficients among certain parameters increase in each iteration, although they generally stay below 0.50.

Performance of a plasma fluid code on the Intel parallel computers

NASA Technical Reports Server (NTRS)

Lynch, V. E.; Carreras, B. A.; Drake, J. B.; Leboeuf, J. N.; Liewer, P.

1992-01-01

One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel (sigma) machine gives an improvement factor close to 64 over the single-processor CRAY-2.

A parallel algorithm for switch-level timing simulation on a hypercube multiprocessor

NASA Technical Reports Server (NTRS)

Rao, Hariprasad Nannapaneni

1989-01-01

The parallel approach to speeding up simulation is studied, specifically the simulation of digital LSI MOS circuitry on the Intel iPSC/2 hypercube. The simulation algorithm is based on RSIM, an event driven switch-level simulator that incorporates a linear transistor model for simulating digital MOS circuits. Parallel processing techniques based on the concepts of Virtual Time and rollback are utilized so that portions of the circuit may be simulated on separate processors, in parallel for as large an increase in speed as possible. A partitioning algorithm is also developed in order to subdivide the circuit for parallel processing.

Geometry control of long-span continuous girder concrete bridge during construction through finite element model updating

NASA Astrophysics Data System (ADS)

Wu, Jie; Yan, Quan-sheng; Li, Jian; Hu, Min-yi

2016-04-01

In bridge construction, geometry control is critical to ensure that the final constructed bridge has the consistent shape as design. A common method is by predicting the deflections of the bridge during each construction phase through the associated finite element models. Therefore, the cambers of the bridge during different construction phases can be determined beforehand. These finite element models are mostly based on the design drawings and nominal material properties. However, the accuracy of these bridge models can be large due to significant uncertainties of the actual properties of the materials used in construction. Therefore, the predicted cambers may not be accurate to ensure agreement of bridge geometry with design, especially for long-span bridges. In this paper, an improved geometry control method is described, which incorporates finite element (FE) model updating during the construction process based on measured bridge deflections. A method based on the Kriging model and Latin hypercube sampling is proposed to perform the FE model updating due to its simplicity and efficiency. The proposed method has been applied to a long-span continuous girder concrete bridge during its construction. Results show that the method is effective in reducing construction error and ensuring the accuracy of the geometry of the final constructed bridge.

Scalability of Parallel Spatial Direct Numerical Simulations on Intel Hypercube and IBM SP1 and SP2

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Hanebutte, Ulf R.; Zubair, Mohammad

1995-01-01

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube and IBM SP1 and SP2 parallel computers is documented. Spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows are computed with the PSDNS code. The feasibility of using the PSDNS to perform transition studies on these computers is examined. The results indicate that PSDNS approach can effectively be parallelized on a distributed-memory parallel machine by remapping the distributed data structure during the course of the calculation. Scalability information is provided to estimate computational costs to match the actual costs relative to changes in the number of grid points. By increasing the number of processors, slower than linear speedups are achieved with optimized (machine-dependent library) routines. This slower than linear speedup results because the computational cost is dominated by FFT routine, which yields less than ideal speedups. By using appropriate compile options and optimized library routines on the SP1, the serial code achieves 52-56 M ops on a single node of the SP1 (45 percent of theoretical peak performance). The actual performance of the PSDNS code on the SP1 is evaluated with a "real world" simulation that consists of 1.7 million grid points. One time step of this simulation is calculated on eight nodes of the SP1 in the same time as required by a Cray Y/MP supercomputer. For the same simulation, 32-nodes of the SP1 and SP2 are required to reach the performance of a Cray C-90. A 32 node SP1 (SP2) configuration is 2.9 (4.6) times faster than a Cray Y/MP for this simulation, while the hypercube is roughly 2 times slower than the Y/MP for this application. KEY WORDS: Spatial direct numerical simulations; incompressible viscous flows; spectral methods; finite differences; parallel computing.

Parallel, adaptive finite element methods for conservation laws

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Devine, Karen D.; Flaherty, Joseph E.

1994-01-01

We construct parallel finite element methods for the solution of hyperbolic conservation laws in one and two dimensions. Spatial discretization is performed by a discontinuous Galerkin finite element method using a basis of piecewise Legendre polynomials. Temporal discretization utilizes a Runge-Kutta method. Dissipative fluxes and projection limiting prevent oscillations near solution discontinuities. A posteriori estimates of spatial errors are obtained by a p-refinement technique using superconvergence at Radau points. The resulting method is of high order and may be parallelized efficiently on MIMD computers. We compare results using different limiting schemes and demonstrate parallel efficiency through computations on an NCUBE/2 hypercube. We also present results using adaptive h- and p-refinement to reduce the computational cost of the method.

Proceedings of the Image Understanding Workshop (18th) Held in Cambridge, Massachusetts on 6-8 April 1988. Volume 1

DTIC Science & Technology

1988-04-01

hypercube; methods, which work best in structured scenes, and parent/ child operations run in a smaller fixed time independent spatiotemporal energy...rectangle defines a new coordinate sVstem for it, image is constructed under orthographic projection. The child links that is relative to its own...that the child rectangle can shift in the X -- V plane, rectangle in the image. At first, a noiseless image is created relative to the nominal

Uncertainty and Sensitivity Analyses of a Pebble Bed HTGR Loss of Cooling Event

DOE PAGES

Strydom, Gerhard

2013-01-01

The Very High Temperature Reactor Methods Development group at the Idaho National Laboratory identified the need for a defensible and systematic uncertainty and sensitivity approach in 2009. This paper summarizes the results of an uncertainty and sensitivity quantification investigation performed with the SUSA code, utilizing the International Atomic Energy Agency CRP 5 Pebble Bed Modular Reactor benchmark and the INL code suite PEBBED-THERMIX. Eight model input parameters were selected for inclusion in this study, and after the input parameters variations and probability density functions were specified, a total of 800 steady state and depressurized loss of forced cooling (DLOFC) transientmore » PEBBED-THERMIX calculations were performed. The six data sets were statistically analyzed to determine the 5% and 95% DLOFC peak fuel temperature tolerance intervals with 95% confidence levels. It was found that the uncertainties in the decay heat and graphite thermal conductivities were the most significant contributors to the propagated DLOFC peak fuel temperature uncertainty. No significant differences were observed between the results of Simple Random Sampling (SRS) or Latin Hypercube Sampling (LHS) data sets, and use of uniform or normal input parameter distributions also did not lead to any significant differences between these data sets.« less

Overcoming sampling depth variations in the analysis of broadband hyperspectral images of breast tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kho, Esther; de Boer, Lisanne L.; Van de Vijver, Koen K.; Sterenborg, Henricus J. C. M.; Ruers, Theo J. M.

2017-02-01

Worldwide, up to 40% of the breast conserving surgeries require additional operations due to positive resection margins. We propose to reduce this percentage by using hyperspectral imaging for resection margin assessment during surgery. Spectral hypercubes were collected from 26 freshly excised breast specimens with a pushbroom camera (900-1700nm). Computer simulations of the penetration depth in breast tissue suggest a strong variation in sampling depth ( 0.5-10 mm) over this wavelength range. This was confirmed with a breast tissue mimicking phantom study. Smaller penetration depths are observed in wavelength regions with high water and/or fat absorption. Consequently, tissue classification based on spectral analysis over the whole wavelength range becomes complicated. This is especially a problem in highly inhomogeneous human tissue. We developed a method, called derivative imaging, which allows accurate tissue analysis, without the impediment of dissimilar sampling volumes. A few assumptions were made based on previous research. First, the spectra acquired with our camera from breast tissue are mainly shaped by fat and water absorption. Second, tumor tissue contains less fat and more water than healthy tissue. Third, scattering slopes of different tissue types are assumed to be alike. In derivative imaging, the derivatives are calculated of wavelengths a few nanometers apart; ensuring similar penetration depths. The wavelength choice determines the accuracy of the method and the resolution. Preliminary results on 3 breast specimens indicate a classification accuracy of 93% when using wavelength regions characterized by water and fat absorption. The sampling depths at these regions are 1mm and 5mm.

A hypercube compact neural network

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

Rostykus, P.L.; Somani, A.K.

1988-09-01

A major problem facing implementation of neural networks is the connection problem. One popular tradeoff is to remove connections. Random disconnection severely degrades the capabilities. The hypercube based Compact Neural Network (CNN) has structured architecture combined with a rearrangement of the memory vectors gives a larger input space and better degradation than a cost equivalent network with more connections. The CNNs are based on a Hopfield network. The changes from the Hopfield net include states of -1 and +1 and when a node was evaluated to 0, it was not biased either positive or negative, instead it resumed its previousmore » state. L = PEs, N = memories and t/sub ij/s is the weights between i and j.« less

Maximum Torque and Momentum Envelopes for Reaction Wheel Arrays

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Reynolds, Reid G.; Liu, Frank X.; Lebsock, Kenneth L.

2009-01-01

Spacecraft reaction wheel maneuvers are limited by the maximum torque and/or angular momentum that the wheels can provide. For an n-wheel configuration, the torque or momentum envelope can be obtained by projecting the n-dimensional hypercube, representing the domain boundary of individual wheel torques or momenta, into three dimensional space via the 3xn matrix of wheel axes. In this paper, the properties of the projected hypercube are discussed, and algorithms are proposed for determining this maximal torque or momentum envelope for general wheel configurations. Practical strategies for distributing a prescribed torque or momentum among the n wheels are presented, with special emphasis on configurations of four, five, and six wheels.

System health monitoring using multiple-model adaptive estimation techniques

NASA Astrophysics Data System (ADS)

Sifford, Stanley Ryan

Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary. Customizable rules define the specific resample behavior when the GRAPE parameter estimates converge. Convergence itself is determined from the derivatives of the parameter estimates using a simple moving average window to filter out noise. The system can be tuned to match the desired performance goals by making adjustments to parameters such as the sample size, convergence criteria, resample criteria, initial sampling method, resampling method, confidence in prior sample covariances, sample delay, and others.

PC-CUBE: A Personal Computer Based Hypercube

NASA Technical Reports Server (NTRS)

Ho, Alex; Fox, Geoffrey; Walker, David; Snyder, Scott; Chang, Douglas; Chen, Stanley; Breaden, Matt; Cole, Terry

1988-01-01

PC-CUBE is an ensemble of IBM PCs or close compatibles connected in the hypercube topology with ordinary computer cables. Communication occurs at the rate of 115.2 K-band via the RS-232 serial links. Available for PC-CUBE is the Crystalline Operating System III (CrOS III), Mercury Operating System, CUBIX and PLOTIX which are parallel I/O and graphics libraries. A CrOS performance monitor was developed to facilitate the measurement of communication and computation time of a program and their effects on performance. Also available are CXLISP, a parallel version of the XLISP interpreter; GRAFIX, some graphics routines for the EGA and CGA; and a general execution profiler for determining execution time spent by program subroutines. PC-CUBE provides a programming environment similar to all hypercube systems running CrOS III, Mercury and CUBIX. In addition, every node (personal computer) has its own graphics display monitor and storage devices. These allow data to be displayed or stored at every processor, which has much instructional value and enables easier debugging of applications. Some application programs which are taken from the book Solving Problems on Concurrent Processors (Fox 88) were implemented with graphics enhancement on PC-CUBE. The applications range from solving the Mandelbrot set, Laplace equation, wave equation, long range force interaction, to WaTor, an ecological simulation.

Growing a hypercubical output space in a self-organizing feature map.

PubMed

Bauer, H U; Villmann, T

1997-01-01

Neural maps project data from an input space onto a neuron position in a (often lower dimensional) output space grid in a neighborhood preserving way, with neighboring neurons in the output space responding to neighboring data points in the input space. A map-learning algorithm can achieve an optimal neighborhood preservation only, if the output space topology roughly matches the effective structure of the data in the input space. We here present a growth algorithm, called the GSOM or growing self-organizing map, which enhances a widespread map self-organization process, Kohonen's self-organizing feature map (SOFM), by an adaptation of the output space grid during learning. The GSOM restricts the output space structure to the shape of a general hypercubical shape, with the overall dimensionality of the grid and its extensions along the different directions being subject of the adaptation. This constraint meets the demands of many larger information processing systems, of which the neural map can be a part. We apply our GSOM-algorithm to three examples, two of which involve real world data. Using recently developed methods for measuring the degree of neighborhood preservation in neural maps, we find the GSOM-algorithm to produce maps which preserve neighborhoods in a nearly optimal fashion.

Stochastic species abundance models involving special copulas

NASA Astrophysics Data System (ADS)

Huillet, Thierry E.

2018-01-01

Copulas offer a very general tool to describe the dependence structure of random variables supported by the hypercube. Inspired by problems of species abundances in Biology, we study three distinct toy models where copulas play a key role. In a first one, a Marshall-Olkin copula arises in a species extinction model with catastrophe. In a second one, a quasi-copula problem arises in a flagged species abundance model. In a third model, we study completely random species abundance models in the hypercube as those, not of product type, with uniform margins and singular. These can be understood from a singular copula supported by an inflated simplex. An exchangeable singular Dirichlet copula is also introduced, together with its induced completely random species abundance vector.

A site oriented supercomputer for theoretical physics: The Fermilab Advanced Computer Program Multi Array Processor System (ACMAPS)

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

Nash, T.; Atac, R.; Cook, A.

1989-03-06

The ACPMAPS multipocessor is a highly cost effective, local memory parallel computer with a hypercube or compound hypercube architecture. Communication requires the attention of only the two communicating nodes. The design is aimed at floating point intensive, grid like problems, particularly those with extreme computing requirements. The processing nodes of the system are single board array processors, each with a peak power of 20 Mflops, supported by 8 Mbytes of data and 2 Mbytes of instruction memory. The system currently being assembled has a peak power of 5 Gflops. The nodes are based on the Weitek XL Chip set. Themore » system delivers performance at approximately $300/Mflop. 8 refs., 4 figs.« less

Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

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

Bonney, Matthew S.; Brake, Matthew R.W.

2015-08-01

The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better representmore » the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.« less

A Heuristic Method of Optimal Generalized Hypercube Encoding for Pictorial Databases.

DTIC Science & Technology

1980-01-15

Sqhm*w1*d~WZ ’Nfr ~ K >~ V January15, lfl *1 ~’>L-N; %j4~S ~ C- (*4Th ~4,.,* - <C ~fl2~ ~tS-ri*’.v **’~~ >, 𔃾 4. 4-. ? 7 V A > - ~ W>4~,,.. * ~S td ...IF I SUM .6?. I I PSUm a PSUM + SUM *SUM ,2. P~to = PSLIM L53 . RETURN £54. so CALL PF4APII.MI.TEMPRI 155. G070 20 156o.N £57. CCCCCCCCCC 158. C 159. C

Assessment of the transportation route of oversize and excessive loads in relation to the load-bearing capacity of existing bridges

NASA Astrophysics Data System (ADS)

Doležel, Jiří; Novák, Drahomír; Petrů, Jan

2017-09-01

Transportation routes of oversize and excessive loads are currently planned in relation to ensure the transit of a vehicle through critical points on the road. Critical points are level-intersection of roads, bridges etc. This article presents a comprehensive procedure to determine a reliability and a load-bearing capacity level of the existing bridges on highways and roads using the advanced methods of reliability analysis based on simulation techniques of Monte Carlo type in combination with nonlinear finite element method analysis. The safety index is considered as a main criterion of the reliability level of the existing construction structures and the index is described in current structural design standards, e.g. ISO and Eurocode. An example of a single-span slab bridge made of precast prestressed concrete girders of the 60 year current time and its load bearing capacity is set for the ultimate limit state and serviceability limit state. The structure’s design load capacity was estimated by the full probability nonlinear MKP analysis using a simulation technique Latin Hypercube Sampling (LHS). Load-bearing capacity values based on a fully probabilistic analysis are compared with the load-bearing capacity levels which were estimated by deterministic methods of a critical section of the most loaded girders.

Polyhedra and Higher Dimensions.

ERIC Educational Resources Information Center

Scott, Paul

1988-01-01

Describes the definition and characteristics of a regular polyhedron, tessellation, and pseudopolyhedra with diagrams. Discusses the nature of simplex, hypercube, and cross-polytope in the fourth dimension and beyond. (YP)

Estimation of the discharges of the multiple water level stations by multi-objective optimization

NASA Astrophysics Data System (ADS)

Matsumoto, Kazuhiro; Miyamoto, Mamoru; Yamakage, Yuzuru; Tsuda, Morimasa; Yanami, Hitoshi; Anai, Hirokazu; Iwami, Yoichi

2016-04-01

This presentation shows two aspects of the parameter identification to estimate the discharges of the multiple water level stations by multi-objective optimization. One is how to adjust the parameters to estimate the discharges accurately. The other is which optimization algorithms are suitable for the parameter identification. Regarding the previous studies, there is a study that minimizes the weighted error of the discharges of the multiple water level stations by single-objective optimization. On the other hand, there are some studies that minimize the multiple error assessment functions of the discharge of a single water level station by multi-objective optimization. This presentation features to simultaneously minimize the errors of the discharges of the multiple water level stations by multi-objective optimization. Abe River basin in Japan is targeted. The basin area is 567.0km2. There are thirteen rainfall stations and three water level stations. Nine flood events are investigated. They occurred from 2005 to 2012 and the maximum discharges exceed 1,000m3/s. The discharges are calculated with PWRI distributed hydrological model. The basin is partitioned into the meshes of 500m x 500m. Two-layer tanks are placed on each mesh. Fourteen parameters are adjusted to estimate the discharges accurately. Twelve of them are the hydrological parameters and two of them are the parameters of the initial water levels of the tanks. Three objective functions are the mean squared errors between the observed and calculated discharges at the water level stations. Latin Hypercube sampling is one of the uniformly sampling algorithms. The discharges are calculated with respect to the parameter values sampled by a simplified version of Latin Hypercube sampling. The observed discharge is surrounded by the calculated discharges. It suggests that it might be possible to estimate the discharge accurately by adjusting the parameters. In a sense, it is true that the discharge of a water level station can be accurately estimated by setting the parameter values optimized to the responding water level station. However, there are some cases that the calculated discharge by setting the parameter values optimized to one water level station does not meet the observed discharge at another water level station. It is important to estimate the discharges of all the water level stations in some degree of accuracy. It turns out to be possible to select the parameter values from the pareto optimal solutions by the condition that all the normalized errors by the minimum error of the responding water level station are under 3. The optimization performance of five implementations of the algorithms and a simplified version of Latin Hypercube sampling are compared. Five implementations are NSGA2 and PAES of an optimization software inspyred and MCO_NSGA2R, MOPSOCD and NSGA2R_NSGA2R of a statistical software R. NSGA2, PAES and MOPSOCD are the optimization algorithms of a genetic algorithm, an evolution strategy and a particle swarm optimization respectively. The number of the evaluations of the objective functions is 10,000. Two implementations of NSGA2 of R outperform the others. They are promising to be suitable for the parameter identification of PWRI distributed hydrological model.

A smart Monte Carlo procedure for production costing and uncertainty analysis

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

Parker, C.; Stremel, J.

1996-11-01

Electric utilities using chronological production costing models to decide whether to buy or sell power over the next week or next few weeks need to determine potential profits or losses under a number of uncertainties. A large amount of money can be at stake--often $100,000 a day or more--and one party of the sale must always take on the risk. In the case of fixed price ($/MWh) contracts, the seller accepts the risk. In the case of cost plus contracts, the buyer must accept the risk. So, modeling uncertainty and understanding the risk accurately can improve the competitive edge ofmore » the user. This paper investigates an efficient procedure for representing risks and costs from capacity outages. Typically, production costing models use an algorithm based on some form of random number generator to select resources as available or on outage. These algorithms allow experiments to be repeated and gains and losses to be observed in a short time. The authors perform several experiments to examine the capability of three unit outage selection methods and measures their results. Specifically, a brute force Monte Carlo procedure, a Monte Carlo procedure with Latin Hypercube sampling, and a Smart Monte Carlo procedure with cost stratification and directed sampling are examined.« less

Uncertainty quantification analysis of the dynamics of an electrostatically actuated microelectromechanical switch model

NASA Astrophysics Data System (ADS)

Snow, Michael G.; Bajaj, Anil K.

2015-08-01

This work presents an uncertainty quantification (UQ) analysis of a comprehensive model for an electrostatically actuated microelectromechanical system (MEMS) switch. The goal is to elucidate the effects of parameter variations on certain key performance characteristics of the switch. A sufficiently detailed model of the electrostatically actuated switch in the basic configuration of a clamped-clamped beam is developed. This multi-physics model accounts for various physical effects, including the electrostatic fringing field, finite length of electrodes, squeeze film damping, and contact between the beam and the dielectric layer. The performance characteristics of immediate interest are the static and dynamic pull-in voltages for the switch. Numerical approaches for evaluating these characteristics are developed and described. Using Latin Hypercube Sampling and other sampling methods, the model is evaluated to find these performance characteristics when variability in the model's geometric and physical parameters is specified. Response surfaces of these results are constructed via a Multivariate Adaptive Regression Splines (MARS) technique. Using a Direct Simulation Monte Carlo (DSMC) technique on these response surfaces gives smooth probability density functions (PDFs) of the outputs characteristics when input probability characteristics are specified. The relative variation in the two pull-in voltages due to each of the input parameters is used to determine the critical parameters.

Monte Carlo Study of Four-Dimensional Self-avoiding Walks of up to One Billion Steps

NASA Astrophysics Data System (ADS)

Clisby, Nathan

2018-04-01

We study self-avoiding walks on the four-dimensional hypercubic lattice via Monte Carlo simulations of walks with up to one billion steps. We study the expected logarithmic corrections to scaling, and find convincing evidence in support the scaling form predicted by the renormalization group, with an estimate for the power of the logarithmic factor of 0.2516(14), which is consistent with the predicted value of 1/4. We also characterize the behaviour of the pivot algorithm for sampling four dimensional self-avoiding walks, and conjecture that the probability of a pivot move being successful for an N-step walk is O([ log N ]^{-1/4}).

Mixing-model Sensitivity to Initial Conditions in Hydrodynamic Predictions

NASA Astrophysics Data System (ADS)

Bigelow, Josiah; Silva, Humberto; Truman, C. Randall; Vorobieff, Peter

2017-11-01

Amagat and Dalton mixing-models were studied to compare their thermodynamic prediction of shock states. Numerical simulations with the Sandia National Laboratories shock hydrodynamic code CTH modeled University of New Mexico (UNM) shock tube laboratory experiments shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6) . Five input parameters were varied for sensitivity analysis: driver section pressure, driver section density, test section pressure, test section density, and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds. Supported by NNSA Grant DE-0002913.

Parameter identification and optimization of slide guide joint of CNC machine tools

NASA Astrophysics Data System (ADS)

Zhou, S.; Sun, B. B.

2017-11-01

The joint surface has an important influence on the performance of CNC machine tools. In order to identify the dynamic parameters of slide guide joint, the parametric finite element model of the joint is established and optimum design method is used based on the finite element simulation and modal test. Then the mode that has the most influence on the dynamics of slip joint is found through harmonic response analysis. Take the frequency of this mode as objective, the sensitivity analysis of the stiffness of each joint surface is carried out using Latin Hypercube Sampling and Monte Carlo Simulation. The result shows that the vertical stiffness of slip joint surface constituted by the bed and the slide plate has the most obvious influence on the structure. Therefore, this stiffness is taken as the optimization variable and the optimal value is obtained through studying the relationship between structural dynamic performance and stiffness. Take the stiffness values before and after optimization into the FEM of machine tool, and it is found that the dynamic performance of the machine tool is improved.

Genetic code, hamming distance and stochastic matrices.

PubMed

He, Matthew X; Petoukhov, Sergei V; Ricci, Paolo E

2004-09-01

In this paper we use the Gray code representation of the genetic code C=00, U=10, G=11 and A=01 (C pairs with G, A pairs with U) to generate a sequence of genetic code-based matrices. In connection with these code-based matrices, we use the Hamming distance to generate a sequence of numerical matrices. We then further investigate the properties of the numerical matrices and show that they are doubly stochastic and symmetric. We determine the frequency distributions of the Hamming distances, building blocks of the matrices, decomposition and iterations of matrices. We present an explicit decomposition formula for the genetic code-based matrix in terms of permutation matrices, which provides a hypercube representation of the genetic code. It is also observed that there is a Hamiltonian cycle in a genetic code-based hypercube.

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

Cook, J.; Derrida, B.

The problem of directed polymers on disordered hierarchical and hypercubic lattices is considered. For the hierarchical lattices the problem can be reduced to the study of the stable laws for combining random variables in a nonlinear way. The authors present the results of numerical simulations of two hierarchical lattices, finding evidence of a phase transition in one case. For a limiting case they extend the perturbation theory developed by Derrida and Griffiths to nonzero temperature and to higher order and use this approach to calculate thermal and geometrical properties (overlaps) of the model. In this limit they obtain an interpolationmore » formula, allowing one to obtain the noninteger moments of the partition function from the integer moments. They obtain bounds for the transition temperature for hierarchical and hypercubic lattices, and some similarities between the problem on the two different types of lattice are discussed.« less

Construction of nested maximin designs based on successive local enumeration and modified novel global harmony search algorithm

NASA Astrophysics Data System (ADS)

Yi, Jin; Li, Xinyu; Xiao, Mi; Xu, Junnan; Zhang, Lin

2017-01-01

Engineering design often involves different types of simulation, which results in expensive computational costs. Variable fidelity approximation-based design optimization approaches can realize effective simulation and efficiency optimization of the design space using approximation models with different levels of fidelity and have been widely used in different fields. As the foundations of variable fidelity approximation models, the selection of sample points of variable-fidelity approximation, called nested designs, is essential. In this article a novel nested maximin Latin hypercube design is constructed based on successive local enumeration and a modified novel global harmony search algorithm. In the proposed nested designs, successive local enumeration is employed to select sample points for a low-fidelity model, whereas the modified novel global harmony search algorithm is employed to select sample points for a high-fidelity model. A comparative study with multiple criteria and an engineering application are employed to verify the efficiency of the proposed nested designs approach.

Pu239 Cross-Section Variations Based on Experimental Uncertainties and Covariances

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

Sigeti, David Edward; Williams, Brian J.; Parsons, D. Kent

2016-10-18

Algorithms and software have been developed for producing variations in plutonium-239 neutron cross sections based on experimental uncertainties and covariances. The varied cross-section sets may be produced as random samples from the multi-variate normal distribution defined by an experimental mean vector and covariance matrix, or they may be produced as Latin-Hypercube/Orthogonal-Array samples (based on the same means and covariances) for use in parametrized studies. The variations obey two classes of constraints that are obligatory for cross-section sets and which put related constraints on the mean vector and covariance matrix that detemine the sampling. Because the experimental means and covariances domore » not obey some of these constraints to sufficient precision, imposing the constraints requires modifying the experimental mean vector and covariance matrix. Modification is done with an algorithm based on linear algebra that minimizes changes to the means and covariances while insuring that the operations that impose the different constraints do not conflict with each other.« less

In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model

PubMed Central

Kolokotroni, Eleni; Dionysiou, Dimitra; Veith, Christian; Kim, Yoo-Jin; Franz, Astrid; Grgic, Aleksandar; Bohle, Rainer M.; Stamatakos, Georgios

2016-01-01

The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs’ cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with the molecular profile of patients could serve as a basis for reliable personalized predictions. PMID:27657742

Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data.

PubMed

Wang, Zhaodi; Hu, Menghan; Zhai, Guangtao

2018-04-07

Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for online fruit sorting. The results of this study demonstrate the potential of deep CNN application on analyzing the internal mechanical damage of fruit.

Application of Deep Learning Architectures for Accurate and Rapid Detection of Internal Mechanical Damage of Blueberry Using Hyperspectral Transmittance Data

PubMed Central

Hu, Menghan; Zhai, Guangtao

2018-01-01

Deep learning has become a widely used powerful tool in many research fields, although not much so yet in agriculture technologies. In this work, two deep convolutional neural networks (CNN), viz. Residual Network (ResNet) and its improved version named ResNeXt, are used to detect internal mechanical damage of blueberries using hyperspectral transmittance data. The original structure and size of hypercubes are adapted for the deep CNN training. To ensure that the models are applicable to hypercube, we adjust the number of filters in the convolutional layers. Moreover, a total of 5 traditional machine learning algorithms, viz. Sequential Minimal Optimization (SMO), Linear Regression (LR), Random Forest (RF), Bagging and Multilayer Perceptron (MLP), are performed as the comparison experiments. In terms of model assessment, k-fold cross validation is used to indicate that the model performance does not vary with the different combination of dataset. In real-world application, selling damaged berries will lead to greater interest loss than discarding the sound ones. Thus, precision, recall, and F1-score are also used as the evaluation indicators alongside accuracy to quantify the false positive rate. The first three indicators are seldom used by investigators in the agricultural engineering domain. Furthermore, ROC curves and Precision-Recall curves are plotted to visualize the performance of classifiers. The fine-tuned ResNet/ResNeXt achieve average accuracy and F1-score of 0.8844/0.8784 and 0.8952/0.8905, respectively. Classifiers SMO/ LR/RF/Bagging/MLP obtain average accuracy and F1-score of 0.8082/0.7606/0.7314/0.7113/0.7827 and 0.8268/0.7796/0.7529/0.7339/0.7971, respectively. Two deep learning models achieve better classification performance than the traditional machine learning methods. Classification for each testing sample only takes 5.2 ms and 6.5 ms respectively for ResNet and ResNeXt, indicating that the deep learning framework has great potential for online fruit sorting. The results of this study demonstrate the potential of deep CNN application on analyzing the internal mechanical damage of fruit. PMID:29642454

When to Make Mountains out of Molehills: The Pros and Cons of Simple and Complex Model Calibration Procedures

NASA Astrophysics Data System (ADS)

Smith, K. A.; Barker, L. J.; Harrigan, S.; Prudhomme, C.; Hannaford, J.; Tanguy, M.; Parry, S.

2017-12-01

Earth and environmental models are relied upon to investigate system responses that cannot otherwise be examined. In simulating physical processes, models have adjustable parameters which may, or may not, have a physical meaning. Determining the values to assign to these model parameters is an enduring challenge for earth and environmental modellers. Selecting different error metrics by which the models results are compared to observations will lead to different sets of calibrated model parameters, and thus different model results. Furthermore, models may exhibit `equifinal' behaviour, where multiple combinations of model parameters lead to equally acceptable model performance against observations. These decisions in model calibration introduce uncertainty that must be considered when model results are used to inform environmental decision-making. This presentation focusses on the uncertainties that derive from the calibration of a four parameter lumped catchment hydrological model (GR4J). The GR models contain an inbuilt automatic calibration algorithm that can satisfactorily calibrate against four error metrics in only a few seconds. However, a single, deterministic model result does not provide information on parameter uncertainty. Furthermore, a modeller interested in extreme events, such as droughts, may wish to calibrate against more low flows specific error metrics. In a comprehensive assessment, the GR4J model has been run with 500,000 Latin Hypercube Sampled parameter sets across 303 catchments in the United Kingdom. These parameter sets have been assessed against six error metrics, including two drought specific metrics. This presentation compares the two approaches, and demonstrates that the inbuilt automatic calibration can outperform the Latin Hypercube experiment approach in single metric assessed performance. However, it is also shown that there are many merits of the more comprehensive assessment, which allows for probabilistic model results, multi-objective optimisation, and better tailoring to calibrate the model for specific applications such as drought event characterisation. Modellers and decision-makers may be constrained in their choice of calibration method, so it is important that they recognise the strengths and limitations of their chosen approach.

Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November–December 2017

PubMed Central

Matsuyama, Ryota; Lee, Hyojung; Yamaguchi, Takayuki; Tsuzuki, Shinya

2018-01-01

Background A Rohingya refugee camp in Cox’s Bazar, Bangladesh experienced a large-scale diphtheria epidemic in 2017. The background information of previously immune fraction among refugees cannot be explicitly estimated, and thus we conducted an uncertainty analysis of the basic reproduction number, R0. Methods A renewal process model was devised to estimate the R0 and ascertainment rate of cases, and loss of susceptible individuals was modeled as one minus the sum of initially immune fraction and the fraction naturally infected during the epidemic. To account for the uncertainty of initially immune fraction, we employed a Latin Hypercube sampling (LHS) method. Results R0 ranged from 4.7 to 14.8 with the median estimate at 7.2. R0 was positively correlated with ascertainment rates. Sensitivity analysis indicated that R0 would become smaller with greater variance of the generation time. Discussion Estimated R0 was broadly consistent with published estimate from endemic data, indicating that the vaccination coverage of 86% has to be satisfied to prevent the epidemic by means of mass vaccination. LHS was particularly useful in the setting of a refugee camp in which the background health status is poorly quantified. PMID:29629244

Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

PubMed

Huang, X N; Ren, H P

2016-05-13

Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation.

Advanced Stochastic Collocation Methods for Polynomial Chaos in RAVEN

NASA Astrophysics Data System (ADS)

Talbot, Paul W.

As experiment complexity in fields such as nuclear engineering continually increases, so does the demand for robust computational methods to simulate them. In many simulations, input design parameters and intrinsic experiment properties are sources of uncertainty. Often small perturbations in uncertain parameters have significant impact on the experiment outcome. For instance, in nuclear fuel performance, small changes in fuel thermal conductivity can greatly affect maximum stress on the surrounding cladding. The difficulty quantifying input uncertainty impact in such systems has grown with the complexity of numerical models. Traditionally, uncertainty quantification has been approached using random sampling methods like Monte Carlo. For some models, the input parametric space and corresponding response output space is sufficiently explored with few low-cost calculations. For other models, it is computationally costly to obtain good understanding of the output space. To combat the expense of random sampling, this research explores the possibilities of using advanced methods in Stochastic Collocation for generalized Polynomial Chaos (SCgPC) as an alternative to traditional uncertainty quantification techniques such as Monte Carlo (MC) and Latin Hypercube Sampling (LHS) methods for applications in nuclear engineering. We consider traditional SCgPC construction strategies as well as truncated polynomial spaces using Total Degree and Hyperbolic Cross constructions. We also consider applying anisotropy (unequal treatment of different dimensions) to the polynomial space, and offer methods whereby optimal levels of anisotropy can be approximated. We contribute development to existing adaptive polynomial construction strategies. Finally, we consider High-Dimensional Model Reduction (HDMR) expansions, using SCgPC representations for the subspace terms, and contribute new adaptive methods to construct them. We apply these methods on a series of models of increasing complexity. We use analytic models of various levels of complexity, then demonstrate performance on two engineering-scale problems: a single-physics nuclear reactor neutronics problem, and a multiphysics fuel cell problem coupling fuels performance and neutronics. Lastly, we demonstrate sensitivity analysis for a time-dependent fuels performance problem. We demonstrate the application of all the algorithms in RAVEN, a production-level uncertainty quantification framework.

Simulations of lattice animals and trees

NASA Astrophysics Data System (ADS)

Hsu, Hsiao-Ping; Nadler, Walter; Grassberger, Peter

2005-01-01

The scaling behaviour of randomly branched polymers in a good solvent is studied in two to nine dimensions, using as microscopic models lattice animals and lattice trees on simple hypercubic lattices. As a stochastic sampling method we use a biased sequential sampling algorithm with re-sampling, similar to the pruned-enriched Rosenbluth method (PERM) used extensively for linear polymers. Essentially we start simulating percolation clusters (either site or bond), re-weigh them according to the animal (tree) ensemble, and prune or branch the further growth according to a heuristic fitness function. In contrast to previous applications of PERM, this fitness function is not the weight with which the actual configuration would contribute to the partition sum, but is closely related to it. We obtain high statistics of animals with up to several thousand sites in all dimension 2 <= d <= 9. In addition to the partition sum (number of different animals) we estimate gyration radii and numbers of perimeter sites. In all dimensions we verify the Parisi-Sourlas prediction, and we verify all exactly known critical exponents in dimensions 2, 3, 4 and >=8. In addition, we present the hitherto most precise estimates for growth constants in d >= 3. For clusters with one site attached to an attractive surface, we verify for d >= 3 the superuniversality of the cross-over exponent phgr at the adsorption transition predicted by Janssen and Lyssy, but not for d = 2. There, we find phgr = 0.480(4) instead of the conjectured phgr = 1/2. Finally, we discuss the collapse of animals and trees, arguing that our present version of the algorithm is also efficient for some of the models studied in this context, but showing that it is not very efficient for the 'classical' model for collapsing animals.

Performance Evaluation of Parallel Branch and Bound Search with the Intel iPSC (Intel Personal SuperComputer) Hypercube Computer.

DTIC Science & Technology

1986-12-01

17 III. Analysis of Parallel Design ................................................ 18 Parallel Abstract Data ...Types ........................................... 18 Abstract Data Type .................................................. 19 Parallel ADT...22 Data -Structure Design ........................................... 23 Object-Oriented Design

Discrete sensitivity derivatives of the Navier-Stokes equations with a parallel Krylov solver

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Taylor, Arthur C., III

1994-01-01

This paper solves an 'incremental' form of the sensitivity equations derived by differentiating the discretized thin-layer Navier Stokes equations with respect to certain design variables of interest. The equations are solved with a parallel, preconditioned Generalized Minimal RESidual (GMRES) solver on a distributed-memory architecture. The 'serial' sensitivity analysis code is parallelized by using the Single Program Multiple Data (SPMD) programming model, domain decomposition techniques, and message-passing tools. Sensitivity derivatives are computed for low and high Reynolds number flows over a NACA 1406 airfoil on a 32-processor Intel Hypercube, and found to be identical to those computed on a single-processor Cray Y-MP. It is estimated that the parallel sensitivity analysis code has to be run on 40-50 processors of the Intel Hypercube in order to match the single-processor processing time of a Cray Y-MP.

A framework for building hypercubes using MapReduce

NASA Astrophysics Data System (ADS)

Tapiador, D.; O'Mullane, W.; Brown, A. G. A.; Luri, X.; Huedo, E.; Osuna, P.

2014-05-01

The European Space Agency's Gaia mission will create the largest and most precise three dimensional chart of our galaxy (the Milky Way), by providing unprecedented position, parallax, proper motion, and radial velocity measurements for about one billion stars. The resulting catalog will be made available to the scientific community and will be analyzed in many different ways, including the production of a variety of statistics. The latter will often entail the generation of multidimensional histograms and hypercubes as part of the precomputed statistics for each data release, or for scientific analysis involving either the final data products or the raw data coming from the satellite instruments. In this paper we present and analyze a generic framework that allows the hypercube generation to be easily done within a MapReduce infrastructure, providing all the advantages of the new Big Data analysis paradigm but without dealing with any specific interface to the lower level distributed system implementation (Hadoop). Furthermore, we show how executing the framework for different data storage model configurations (i.e. row or column oriented) and compression techniques can considerably improve the response time of this type of workload for the currently available simulated data of the mission. In addition, we put forward the advantages and shortcomings of the deployment of the framework on a public cloud provider, benchmark against other popular solutions available (that are not always the best for such ad-hoc applications), and describe some user experiences with the framework, which was employed for a number of dedicated astronomical data analysis techniques workshops.

Surrogate Model Application to the Identification of Optimal Groundwater Exploitation Scheme Based on Regression Kriging Method—A Case Study of Western Jilin Province

PubMed Central

An, Yongkai; Lu, Wenxi; Cheng, Weiguo

2015-01-01

This paper introduces a surrogate model to identify an optimal exploitation scheme, while the western Jilin province was selected as the study area. A numerical simulation model of groundwater flow was established first, and four exploitation wells were set in the Tongyu county and Qian Gorlos county respectively so as to supply water to Daan county. Second, the Latin Hypercube Sampling (LHS) method was used to collect data in the feasible region for input variables. A surrogate model of the numerical simulation model of groundwater flow was developed using the regression kriging method. An optimization model was established to search an optimal groundwater exploitation scheme using the minimum average drawdown of groundwater table and the minimum cost of groundwater exploitation as multi-objective functions. Finally, the surrogate model was invoked by the optimization model in the process of solving the optimization problem. Results show that the relative error and root mean square error of the groundwater table drawdown between the simulation model and the surrogate model for 10 validation samples are both lower than 5%, which is a high approximation accuracy. The contrast between the surrogate-based simulation optimization model and the conventional simulation optimization model for solving the same optimization problem, shows the former only needs 5.5 hours, and the latter needs 25 days. The above results indicate that the surrogate model developed in this study could not only considerably reduce the computational burden of the simulation optimization process, but also maintain high computational accuracy. This can thus provide an effective method for identifying an optimal groundwater exploitation scheme quickly and accurately. PMID:26264008

RTNN: The New Parallel Machine in Zaragoza

NASA Astrophysics Data System (ADS)

Sijs, A. J. V. D.

I report on the development of RTNN, a parallel computer designed as a 4^4 hypercube of 256 T9000 transputer nodes, each with 8 MB memory. The peak performance of the machine is expected to be 2.5 Gflops.

Fault tolerant hypercube computer system architecture

NASA Technical Reports Server (NTRS)

Madan, Herb S. (Inventor); Chow, Edward (Inventor)

1989-01-01

A fault-tolerant multiprocessor computer system of the hypercube type comprising a hierarchy of computers of like kind which can be functionally substituted for one another as necessary is disclosed. Communication between the working nodes is via one communications network while communications between the working nodes and watch dog nodes and load balancing nodes higher in the structure is via another communications network separate from the first. A typical branch of the hierarchy reporting to a master node or host computer comprises, a plurality of first computing nodes; a first network of message conducting paths for interconnecting the first computing nodes as a hypercube. The first network provides a path for message transfer between the first computing nodes; a first watch dog node; and a second network of message connecting paths for connecting the first computing nodes to the first watch dog node independent from the first network, the second network provides an independent path for test message and reconfiguration affecting transfers between the first computing nodes and the first switch watch dog node. There is additionally, a plurality of second computing nodes; a third network of message conducting paths for interconnecting the second computing nodes as a hypercube. The third network provides a path for message transfer between the second computing nodes; a fourth network of message conducting paths for connecting the second computing nodes to the first watch dog node independent from the third network. The fourth network provides an independent path for test message and reconfiguration affecting transfers between the second computing nodes and the first watch dog node; and a first multiplexer disposed between the first watch dog node and the second and fourth networks for allowing the first watch dog node to selectively communicate with individual ones of the computing nodes through the second and fourth networks; as well as, a second watch dog node operably connected to the first multiplexer whereby the second watch dog node can selectively communicate with individual ones of the computing nodes through the second and fourth networks. The branch is completed by a first load balancing node; and a second multiplexer connected between the first load balancing node and the first and second watch dog nodes, allowing the first load balancing node to selectively communicate with the first and second watch dog nodes.

The software and algorithms for hyperspectral data processing

NASA Astrophysics Data System (ADS)

Shyrayeva, Anhelina; Martinov, Anton; Ivanov, Victor; Katkovsky, Leonid

2017-04-01

Hyperspectral remote sensing technique is widely used for collecting and processing -information about the Earth's surface objects. Hyperspectral data are combined to form a three-dimensional (x, y, λ) data cube. Department of Aerospace Research of the Institute of Applied Physical Problems of the Belarusian State University presents a general model of the software for hyperspectral image data analysis and processing. The software runs in Windows XP/7/8/8.1/10 environment on any personal computer. This complex has been has been written in C++ language using QT framework and OpenGL for graphical data visualization. The software has flexible structure that consists of a set of independent plugins. Each plugin was compiled as Qt Plugin and represents Windows Dynamic library (dll). Plugins can be categorized in terms of data reading types, data visualization (3D, 2D, 1D) and data processing The software has various in-built functions for statistical and mathematical analysis, signal processing functions like direct smoothing function for moving average, Savitzky-Golay smoothing technique, RGB correction, histogram transformation, and atmospheric correction. The software provides two author's engineering techniques for the solution of atmospheric correction problem: iteration method of refinement of spectral albedo's parameters using Libradtran and analytical least square method. The main advantages of these methods are high rate of processing (several minutes for 1 GB data) and low relative error in albedo retrieval (less than 15%). Also, the software supports work with spectral libraries, region of interest (ROI) selection, spectral analysis such as cluster-type image classification and automatic hypercube spectrum comparison by similarity criterion with similar ones from spectral libraries, and vice versa. The software deals with different kinds of spectral information in order to identify and distinguish spectrally unique materials. Also, the following advantages should be noted: fast and low memory hypercube manipulation features, user-friendly interface, modularity, and expandability.

Three Dimensional Speckle Imaging Employing a Frequency-Locked Tunable Diode Laser

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

Cannon, Bret D.; Bernacki, Bruce E.; Schiffern, John T.

2015-09-01

We describe a high accuracy frequency stepping method for a tunable diode laser to improve a three dimensional (3D) imaging approach based upon interferometric speckle imaging. The approach, modeled after Takeda, exploits tuning an illumination laser in frequency as speckle interferograms of the object (specklegrams) are acquired at each frequency in a Michelson interferometer. The resulting 3D hypercube of specklegrams encode spatial information in the x-y plane of each image with laser tuning arrayed along its z-axis. We present laboratory data of before and after results showing enhanced 3D imaging resulting from precise laser frequency control.

A partitioning strategy for nonuniform problems on multiprocessors

NASA Technical Reports Server (NTRS)

Berger, M. J.; Bokhari, S.

1985-01-01

The partitioning of a problem on a domain with unequal work estimates in different subddomains is considered in a way that balances the work load across multiple processors. Such a problem arises for example in solving partial differential equations using an adaptive method that places extra grid points in certain subregions of the domain. A binary decomposition of the domain is used to partition it into rectangles requiring equal computational effort. The communication costs of mapping this partitioning onto different microprocessors: a mesh-connected array, a tree machine and a hypercube is then studied. The communication cost expressions can be used to determine the optimal depth of the above partitioning.

Asynchronous multilevel adaptive methods for solving partial differential equations on multiprocessors - Performance results

NASA Technical Reports Server (NTRS)

Mccormick, S.; Quinlan, D.

1989-01-01

The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids (global and local) to provide adaptive resolution and fast solution of PDEs. Like all such methods, it offers parallelism by using possibly many disconnected patches per level, but is hindered by the need to handle these levels sequentially. The finest levels must therefore wait for processing to be essentially completed on all the coarser ones. A recently developed asynchronous version of FAC, called AFAC, completely eliminates this bottleneck to parallelism. This paper describes timing results for AFAC, coupled with a simple load balancing scheme, applied to the solution of elliptic PDEs on an Intel iPSC hypercube. These tests include performance of certain processes necessary in adaptive methods, including moving grids and changing refinement. A companion paper reports on numerical and analytical results for estimating convergence factors of AFAC applied to very large scale examples.

Feasibility of Stochastic Voltage/VAr Optimization Considering Renewable Energy Resources for Smart Grid

NASA Astrophysics Data System (ADS)

Momoh, James A.; Salkuti, Surender Reddy

2016-06-01

This paper proposes a stochastic optimization technique for solving the Voltage/VAr control problem including the load demand and Renewable Energy Resources (RERs) variation. The RERs often take along some inputs like stochastic behavior. One of the important challenges i. e., Voltage/VAr control is a prime source for handling power system complexity and reliability, hence it is the fundamental requirement for all the utility companies. There is a need for the robust and efficient Voltage/VAr optimization technique to meet the peak demand and reduction of system losses. The voltages beyond the limit may damage costly sub-station devices and equipments at consumer end as well. Especially, the RERs introduces more disturbances and some of the RERs are not even capable enough to meet the VAr demand. Therefore, there is a strong need for the Voltage/VAr control in RERs environment. This paper aims at the development of optimal scheme for Voltage/VAr control involving RERs. In this paper, Latin Hypercube Sampling (LHS) method is used to cover full range of variables by maximally satisfying the marginal distribution. Here, backward scenario reduction technique is used to reduce the number of scenarios effectively and maximally retain the fitting accuracy of samples. The developed optimization scheme is tested on IEEE 24 bus Reliability Test System (RTS) considering the load demand and RERs variation.

Convoy Protection under Multi-Threat Scenario

DTIC Science & Technology

2017-06-01

14. SUBJECT TERMS antisubmarine warfare, convoy protection, screening, design of experiments, agent-based simulation 15. NUMBER OF...46 5. Scenarios 33–36 (Red Submarine Tactic-2) ...............................46 IV. DESIGN OF EXPERIMENT...47 C. NEARLY ORTHOGONAL LATIN HYPERCUBE DESIGN ............51 V. DATA ANALYSIS

Economic consequences of aviation system disruptions: A reduced-form computable general equilibrium analysis

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

Chen, Zhenhua; Rose, Adam Z.; Prager, Fynnwin

The state of the art approach to economic consequence analysis (ECA) is computable general equilibrium (CGE) modeling. However, such models contain thousands of equations and cannot readily be incorporated into computerized systems used by policy analysts to yield estimates of economic impacts of various types of transportation system failures due to natural hazards, human related attacks or technological accidents. This paper presents a reduced-form approach to simplify the analytical content of CGE models to make them more transparent and enhance their utilization potential. The reduced-form CGE analysis is conducted by first running simulations one hundred times, varying key parameters, suchmore » as magnitude of the initial shock, duration, location, remediation, and resilience, according to a Latin Hypercube sampling procedure. Statistical analysis is then applied to the “synthetic data” results in the form of both ordinary least squares and quantile regression. The analysis yields linear equations that are incorporated into a computerized system and utilized along with Monte Carlo simulation methods for propagating uncertainties in economic consequences. Although our demonstration and discussion focuses on aviation system disruptions caused by terrorist attacks, the approach can be applied to a broad range of threat scenarios.« less

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

Scalable and fault tolerant orthogonalization based on randomized distributed data aggregation

PubMed Central

Gansterer, Wilfried N.; Niederbrucker, Gerhard; Straková, Hana; Schulze Grotthoff, Stefan

2013-01-01

The construction of distributed algorithms for matrix computations built on top of distributed data aggregation algorithms with randomized communication schedules is investigated. For this purpose, a new aggregation algorithm for summing or averaging distributed values, the push-flow algorithm, is developed, which achieves superior resilience properties with respect to failures compared to existing aggregation methods. It is illustrated that on a hypercube topology it asymptotically requires the same number of iterations as the optimal all-to-all reduction operation and that it scales well with the number of nodes. Orthogonalization is studied as a prototypical matrix computation task. A new fault tolerant distributed orthogonalization method rdmGS, which can produce accurate results even in the presence of node failures, is built on top of distributed data aggregation algorithms. PMID:24748902

Hypercube Expert System Shell - Applying Production Parallelism.

DTIC Science & Technology

1989-12-01

possible processor organizations, or int( rconntction n thod,, for par- allel architetures . The following are examples of commonlv used interconnection...this timing analysis because match speed-up avaiiah& from production parallelism is proportional to the average number of affected produclions1 ( 11:5

Design Optimization of a Centrifugal Fan with Splitter Blades

NASA Astrophysics Data System (ADS)

Heo, Man-Woong; Kim, Jin-Hyuk; Kim, Kwang-Yong

2015-05-01

Multi-objective optimization of a centrifugal fan with additionally installed splitter blades was performed to simultaneously maximize the efficiency and pressure rise using three-dimensional Reynolds-averaged Navier-Stokes equations and hybrid multi-objective evolutionary algorithm. Two design variables defining the location of splitter, and the height ratio between inlet and outlet of impeller were selected for the optimization. In addition, the aerodynamic characteristics of the centrifugal fan were investigated with the variation of design variables in the design space. Latin hypercube sampling was used to select the training points, and response surface approximation models were constructed as surrogate models of the objective functions. With the optimization, both the efficiency and pressure rise of the centrifugal fan with splitter blades were improved considerably compared to the reference model.

The simulation of a two-dimensional (2D) transport problem in a rectangular region with Lattice Boltzmann method with two-relaxation-time

NASA Astrophysics Data System (ADS)

Sugiyanto, S.; Hardyanto, W.; Marwoto, P.

2018-03-01

Transport phenomena are found in many problems in many engineering and industrial sectors. We analyzed a Lattice Boltzmann method with Two-Relaxation Time (LTRT) collision operators for simulation of pollutant moving through the medium as a two-dimensional (2D) transport problem in a rectangular region model. This model consists of a 2D rectangular region with 54 length (x), 27 width (y), and it has isotropic homogeneous medium. Initially, the concentration is zero and is distributed evenly throughout the region of interest. A concentration of 1 is maintained at 9 < y < 18, whereas the concentration of zero is maintained at 0 < y < 9 and 18 < y < 27. A specific discharge (Darcy velocity) of 1.006 is assumed. A diffusion coefficient of 0.8333 is distributed uniformly with a uniform porosity of 0.35. A computer program is written in MATLAB to compute the concentration of pollutant at any specified place and time. The program shows that LTRT solution with quadratic equilibrium distribution functions (EDFs) and relaxation time τa=1.0 are in good agreement result with other numerical solutions methods such as 3DLEWASTE (Hybrid Three-dimensional Lagrangian-Eulerian Finite Element Model of Waste Transport Through Saturated-Unsaturated Media) obtained by Yeh and 3DFEMWATER-LHS (Three-dimensional Finite Element Model of Water Flow Through Saturated-Unsaturated Media with Latin Hypercube Sampling) obtained by Hardyanto.

A Cascade Approach to Uncertainty Estimation for the Hydrological Simulation of Droughts

NASA Astrophysics Data System (ADS)

Smith, Katie; Tanguy, Maliko; Parry, Simon; Prudhomme, Christel

2016-04-01

Uncertainty poses a significant challenge in environmental research and the characterisation and quantification of uncertainty has become a research priority over the past decade. Studies of extreme events are particularly affected by issues of uncertainty. This study focusses on the sources of uncertainty in the modelling of streamflow droughts in the United Kingdom. Droughts are a poorly understood natural hazard with no universally accepted definition. Meteorological, hydrological and agricultural droughts have different meanings and vary both spatially and temporally, yet each is inextricably linked. The work presented here is part of two extensive interdisciplinary projects investigating drought reconstruction and drought forecasting capabilities in the UK. Lumped catchment models are applied to simulate streamflow drought, and uncertainties from 5 different sources are investigated: climate input data, potential evapotranspiration (PET) method, hydrological model, within model structure, and model parameterisation. Latin Hypercube sampling is applied to develop large parameter ensembles for each model structure which are run using parallel computing on a high performance computer cluster. Parameterisations are assessed using a multi-objective evaluation criteria which includes both general and drought performance metrics. The effect of different climate input data and PET methods on model output is then considered using the accepted model parameterisations. The uncertainty from each of the sources creates a cascade, and when presented as such the relative importance of each aspect of uncertainty can be determined.

Probability-based methodology for buckling investigation of sandwich composite shells with and without cut-outs

NASA Astrophysics Data System (ADS)

Alfano, M.; Bisagni, C.

2017-01-01

The objective of the running EU project DESICOS (New Robust DESign Guideline for Imperfection Sensitive COmposite Launcher Structures) is to formulate an improved shell design methodology in order to meet the demand of aerospace industry for lighter structures. Within the project, this article discusses the development of a probability-based methodology developed at Politecnico di Milano. It is based on the combination of the Stress-Strength Interference Method and the Latin Hypercube Method with the aim to predict the bucking response of three sandwich composite cylindrical shells, assuming a loading condition of pure compression. The three shells are made of the same material, but have different stacking sequence and geometric dimensions. One of them presents three circular cut-outs. Different types of input imperfections, treated as random variables, are taken into account independently and in combination: variability in longitudinal Young's modulus, ply misalignment, geometric imperfections, and boundary imperfections. The methodology enables a first assessment of the structural reliability of the shells through the calculation of a probabilistic buckling factor for a specified level of probability. The factor depends highly on the reliability level, on the number of adopted samples, and on the assumptions made in modeling the input imperfections. The main advantage of the developed procedure is the versatility, as it can be applied to the buckling analysis of laminated composite shells and sandwich composite shells including different types of imperfections.

PCLIPS: Parallel CLIPS

NASA Technical Reports Server (NTRS)

Hall, Lawrence O.; Bennett, Bonnie H.; Tello, Ivan

1994-01-01

A parallel version of CLIPS 5.1 has been developed to run on Intel Hypercubes. The user interface is the same as that for CLIPS with some added commands to allow for parallel calls. A complete version of CLIPS runs on each node of the hypercube. The system has been instrumented to display the time spent in the match, recognize, and act cycles on each node. Only rule-level parallelism is supported. Parallel commands enable the assertion and retraction of facts to/from remote nodes working memory. Parallel CLIPS was used to implement a knowledge-based command, control, communications, and intelligence (C(sup 3)I) system to demonstrate the fusion of high-level, disparate sources. We discuss the nature of the information fusion problem, our approach, and implementation. Parallel CLIPS has also be used to run several benchmark parallel knowledge bases such as one to set up a cafeteria. Results show from running Parallel CLIPS with parallel knowledge base partitions indicate that significant speed increases, including superlinear in some cases, are possible.

Optimisation and evaluation of hyperspectral imaging system using machine learning algorithm

NASA Astrophysics Data System (ADS)

Suthar, Gajendra; Huang, Jung Y.; Chidangil, Santhosh

2017-10-01

Hyperspectral imaging (HSI), also called imaging spectrometer, originated from remote sensing. Hyperspectral imaging is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the objects physiology, morphology, and composition. The present work involves testing and evaluating the performance of the hyperspectral imaging system. The methodology involved manually taking reflectance of the object in many images or scan of the object. The object used for the evaluation of the system was cabbage and tomato. The data is further converted to the required format and the analysis is done using machine learning algorithm. The machine learning algorithms applied were able to distinguish between the object present in the hypercube obtain by the scan. It was concluded from the results that system was working as expected. This was observed by the different spectra obtained by using the machine-learning algorithm.

Implementation and evaluation of a hypercube-based method for spatiotemporal exploration and analysis

NASA Astrophysics Data System (ADS)

Marchand, Pierre; Brisebois, Alexandre; Bédard, Yvan; Edwards, Geoffrey

This paper presents the results obtained with a new type of spatiotemporal topological dimension implemented within a hypercube, i.e., within a multidimensional database (MDDB) structure formed by the conjunction of several thematic, spatial and temporal dimensions. Our goal is to support efficient SpatioTemporal Exploration and Analysis (STEA) in the context of Automatic Position Reporting System (APRS), the worldwide amateur radio system for position report transmission. Mobile APRS stations are equipped with GPS navigation systems to provide real-time positioning reports. Previous research about the multidimensional approach has proved good potential for spatiotemporal exploration and analysis despite a lack of explicit topological operators (spatial, temporal and spatiotemporal). Our project implemented such operators through a hierarchy of operators that are applied to pairs of instances of objects. At the top of the hierarchy, users can use simple operators such as "same place", "same time" or "same time, same place". As they drill down into the hierarchy, more detailed topological operators are made available such as "adjacent immediately after", "touch during" or more detailed operators. This hierarchy is structured according to four levels of granularity based on cognitive models, generalized relationships and formal models of topological relationships. In this paper, we also describe the generic approach which allows efficient STEA within the multidimensional approach. Finally, we demonstrate that such an implementation offers query run times which permit to maintain a "train-of-thought" during exploration and analysis operations as they are compatible with Newell's cognitive band (query runtime<10 s) (Newell, A., 1990. Unified theories of cognition. Harvard University Press, Cambridge MA, 549 p.).

Effective implementation of wavelet Galerkin method

NASA Astrophysics Data System (ADS)

Finěk, Václav; Šimunková, Martina

2012-11-01

It was proved by W. Dahmen et al. that an adaptive wavelet scheme is asymptotically optimal for a wide class of elliptic equations. This scheme approximates the solution u by a linear combination of N wavelets and a benchmark for its performance is the best N-term approximation, which is obtained by retaining the N largest wavelet coefficients of the unknown solution. Moreover, the number of arithmetic operations needed to compute the approximate solution is proportional to N. The most time consuming part of this scheme is the approximate matrix-vector multiplication. In this contribution, we will introduce our implementation of wavelet Galerkin method for Poisson equation -Δu = f on hypercube with homogeneous Dirichlet boundary conditions. In our implementation, we identified nonzero elements of stiffness matrix corresponding to the above problem and we perform matrix-vector multiplication only with these nonzero elements.

Estimating the Non-Monetary Burden of Neurocysticercosis in Mexico

PubMed Central

Bhattarai, Rachana; Budke, Christine M.; Carabin, Hélène; Proaño, Jefferson V.; Flores-Rivera, Jose; Corona, Teresa; Ivanek, Renata; Snowden, Karen F.; Flisser, Ana

2012-01-01

Background Neurocysticercosis (NCC) is a major public health problem in many developing countries where health education, sanitation, and meat inspection infrastructure are insufficient. The condition occurs when humans ingest eggs of the pork tapeworm Taenia solium, which then develop into larvae in the central nervous system. Although NCC is endemic in many areas of the world and is associated with considerable socio-economic losses, the burden of NCC remains largely unknown. This study provides the first estimate of disability adjusted life years (DALYs) associated with NCC in Mexico. Methods DALYs lost for symptomatic cases of NCC in Mexico were estimated by incorporating morbidity and mortality due to NCC-associated epilepsy, and morbidity due to NCC-associated severe chronic headaches. Latin hypercube sampling methods were employed to sample the distributions of uncertain parameters and to estimate 95% credible regions (95% CRs). Findings In Mexico, 144,433 and 98,520 individuals are estimated to suffer from NCC-associated epilepsy and NCC-associated severe chronic headaches, respectively. A total of 25,341 (95% CR: 12,569–46,640) DALYs were estimated to be lost due to these clinical manifestations, with 0.25 (95% CR: 0.12–0.46) DALY lost per 1,000 person-years of which 90% was due to NCC-associated epilepsy. Conclusion This is the first estimate of DALYs associated with NCC in Mexico. However, this value is likely to be underestimated since only the clinical manifestations of epilepsy and severe chronic headaches were included. In addition, due to limited country specific data, some parameters used in the analysis were based on systematic reviews of the literature or primary research from other geographic locations. Even with these limitations, our estimates suggest that healthy years of life are being lost due to NCC in Mexico. PMID:22363827

NASA Tech Briefs, November/December 1986, Special Edition

NASA Technical Reports Server (NTRS)

1986-01-01

Topics: Computing: The View from NASA Headquarters; Earth Resources Laboratory Applications Software: Versatile Tool for Data Analysis; The Hypercube: Cost-Effective Supercomputing; Artificial Intelligence: Rendezvous with NASA; NASA's Ada Connection; COSMIC: NASA's Software Treasurehouse; Golden Oldies: Tried and True NASA Software; Computer Technical Briefs; NASA TU Services; Digital Fly-by-Wire.

Stochastic Multi-Commodity Facility Location Based on a New Scenario Generation Technique

NASA Astrophysics Data System (ADS)

Mahootchi, M.; Fattahi, M.; Khakbazan, E.

2011-11-01

This paper extends two models for stochastic multi-commodity facility location problem. The problem is formulated as two-stage stochastic programming. As a main point of this study, a new algorithm is applied to efficiently generate scenarios for uncertain correlated customers' demands. This algorithm uses Latin Hypercube Sampling (LHS) and a scenario reduction approach. The relation between customer satisfaction level and cost are considered in model I. The risk measure using Conditional Value-at-Risk (CVaR) is embedded into the optimization model II. Here, the structure of the network contains three facility layers including plants, distribution centers, and retailers. The first stage decisions are the number, locations, and the capacity of distribution centers. In the second stage, the decisions are the amount of productions, the volume of transportation between plants and customers.

Optimization on the impeller of a low-specific-speed centrifugal pump for hydraulic performance improvement

NASA Astrophysics Data System (ADS)

Pei, Ji; Wang, Wenjie; Yuan, Shouqi; Zhang, Jinfeng

2016-09-01

In order to widen the high-efficiency operating range of a low-specific-speed centrifugal pump, an optimization process for considering efficiencies under 1.0 Q d and 1.4 Q d is proposed. Three parameters, namely, the blade outlet width b 2, blade outlet angle β 2, and blade wrap angle φ, are selected as design variables. Impellers are generated using the optimal Latin hypercube sampling method. The pump efficiencies are calculated using the software CFX 14.5 at two operating points selected as objectives. Surrogate models are also constructed to analyze the relationship between the objectives and the design variables. Finally, the particle swarm optimization algorithm is applied to calculate the surrogate model to determine the best combination of the impeller parameters. The results show that the performance curve predicted by numerical simulation has a good agreement with the experimental results. Compared with the efficiencies of the original impeller, the hydraulic efficiencies of the optimized impeller are increased by 4.18% and 0.62% under 1.0 Q d and 1.4Qd, respectively. The comparison of inner flow between the original pump and optimized one illustrates the improvement of performance. The optimization process can provide a useful reference on performance improvement of other pumps, even on reduction of pressure fluctuations.

Uncertainty and sensitivity analysis of the basic reproduction number of diphtheria: a case study of a Rohingya refugee camp in Bangladesh, November-December 2017.

PubMed

Matsuyama, Ryota; Akhmetzhanov, Andrei R; Endo, Akira; Lee, Hyojung; Yamaguchi, Takayuki; Tsuzuki, Shinya; Nishiura, Hiroshi

2018-01-01

A Rohingya refugee camp in Cox's Bazar, Bangladesh experienced a large-scale diphtheria epidemic in 2017. The background information of previously immune fraction among refugees cannot be explicitly estimated, and thus we conducted an uncertainty analysis of the basic reproduction number, R 0 . A renewal process model was devised to estimate the R 0 and ascertainment rate of cases, and loss of susceptible individuals was modeled as one minus the sum of initially immune fraction and the fraction naturally infected during the epidemic. To account for the uncertainty of initially immune fraction, we employed a Latin Hypercube sampling (LHS) method. R 0 ranged from 4.7 to 14.8 with the median estimate at 7.2. R 0 was positively correlated with ascertainment rates. Sensitivity analysis indicated that R 0 would become smaller with greater variance of the generation time. Estimated R 0 was broadly consistent with published estimate from endemic data, indicating that the vaccination coverage of 86% has to be satisfied to prevent the epidemic by means of mass vaccination. LHS was particularly useful in the setting of a refugee camp in which the background health status is poorly quantified.

Redundancy management for efficient fault recovery in NASA's distributed computing system

NASA Technical Reports Server (NTRS)

Malek, Miroslaw; Pandya, Mihir; Yau, Kitty

1991-01-01

The management of redundancy in computer systems was studied and guidelines were provided for the development of NASA's fault-tolerant distributed systems. Fault recovery and reconfiguration mechanisms were examined. A theoretical foundation was laid for redundancy management by efficient reconfiguration methods and algorithmic diversity. Algorithms were developed to optimize the resources for embedding of computational graphs of tasks in the system architecture and reconfiguration of these tasks after a failure has occurred. The computational structure represented by a path and the complete binary tree was considered and the mesh and hypercube architectures were targeted for their embeddings. The innovative concept of Hybrid Algorithm Technique was introduced. This new technique provides a mechanism for obtaining fault tolerance while exhibiting improved performance.

Super and parallel computers and their impact on civil engineering

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

Kamat, M.P.

1986-01-01

This book presents the papers given at a conference on the use of supercomputers in civil engineering. Topics considered at the conference included solving nonlinear equations on a hypercube, a custom architectured parallel processing system, distributed data processing, algorithms, computer architecture, parallel processing, vector processing, computerized simulation, and cost benefit analysis.

Assignment Of Finite Elements To Parallel Processors

NASA Technical Reports Server (NTRS)

Salama, Moktar A.; Flower, Jon W.; Otto, Steve W.

1990-01-01

Elements assigned approximately optimally to subdomains. Mapping algorithm based on simulated-annealing concept used to minimize approximate time required to perform finite-element computation on hypercube computer or other network of parallel data processors. Mapping algorithm needed when shape of domain complicated or otherwise not obvious what allocation of elements to subdomains minimizes cost of computation.

3D Navier-Stokes Flow Analysis for a Large-Array Multiprocessor

DTIC Science & Technology

1989-04-17

computer, Alliant’s FX /8, Intel’s Hypercube, and Encore’s Multimax. Unfortunately, the current algorithms have been developed pri- marily for SISD machines...Reversing and Thrust-Vectoring Nozzle Flows," Ph.D. Dissertation in the Dept. of Aero. and Astro ., Univ. of Wash., Washington, 1986. [11] Anderson

Extending Orthogonal and Nearly Orthogonal Latin Hypercube Designs for Computer Simulation and Experimentation

DTIC Science & Technology

2006-12-01

The code was initially developed to be run within the netBeans IDE 5.04 running J2SE 5.0. During the course of the development, Eclipse SDK 3.2...covers the results from the research. Chapter V concludes and recommends future research. 4 netBeans

Taste symmetry breaking with hypercubic-smeared staggered fermions

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

Bae, Taegil; Adams, David H.; Kim, Hyung-Jin

2008-05-01

We study the impact of hypercubic (HYP) smearing on the size of taste-breaking for staggered fermions, comparing to unimproved and to asqtad-improved staggered fermions. As in previous studies, we find a substantial reduction in taste-breaking compared to unimproved staggered fermions (by a factor of 4-7 on lattices with spacing a{approx_equal}0.1 fm). In addition, we observe that discretization effects of next-to-leading order in the chiral expansion (O(a{sup 2}p{sup 2})) are markedly reduced by HYP smearing. Compared to asqtad valence fermions, we find that taste-breaking in the pion spectrum is reduced by a factor of 2.5-3, down to a level comparable tomore » the expected size of generic O(a{sup 2}) effects. Our results suggest that, once one reaches a lattice spacing of a{approx_equal}0.09 fm, taste-breaking will be small enough after HYP smearing that one can use a modified power counting in which O(a{sup 2})<

A parallel expert system for the control of a robotic air vehicle

NASA Technical Reports Server (NTRS)

Shakley, Donald; Lamont, Gary B.

1988-01-01

Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation.

Comparison of empirical strategies to maximize GENEHUNTER lod scores.

PubMed

Chen, C H; Finch, S J; Mendell, N R; Gordon, D

1999-01-01

We compare four strategies for finding the settings of genetic parameters that maximize the lod scores reported in GENEHUNTER 1.2. The four strategies are iterated complete factorial designs, iterated orthogonal Latin hypercubes, evolutionary operation, and numerical optimization. The genetic parameters that are set are the phenocopy rate, penetrance, and disease allele frequency; both recessive and dominant models are considered. We selected the optimization of a recessive model on the Collaborative Study on the Genetics of Alcoholism (COGA) data of chromosome 1 for complete analysis. Convergence to a setting producing a local maximum required the evaluation of over 100 settings (for a time budget of 800 minutes on a Pentium II 300 MHz PC). Two notable local maxima were detected, suggesting the need for a more extensive search before claiming that a global maximum had been found. The orthogonal Latin hypercube design was the best strategy for finding areas that produced high lod scores with small numbers of evaluations. Numerical optimization starting from a region producing high lod scores was the strategy that found the highest maximum observed.

Hypercat - Hypercube of AGN tori

NASA Astrophysics Data System (ADS)

Nikutta, Robert; Lopez-Rodriguez, Enrique; Ichikawa, Kohei; Levenson, Nancy A.; Packham, Christopher C.

2018-06-01

AGN unification and observations hold that a dusty torus obscures the central accretion engine along some lines of sight. SEDs of dust tori have been modeled for a long time, but resolved emission morphologies have not been studied in much detail, because resolved observations are only possible recently (VLTI,ALMA) and in the near future (TMT,ELT,GMT). Some observations challenge a simple torus model, because in several objects most of MIR emission appears to emanate from polar regions high above the equatorial plane, i.e. not where the dust supposedly resides.We introduce our software framework and hypercube of AGN tori (Hypercat) made with CLUMPY (www.clumpy.org), a large set of images (6 model parameters + wavelength) to facilitate studies of emission and dust morphologies. We make use of Hypercat to study the morphological properties of the emission and dust distributions as function of model parameters. We find that a simple clumpy torus can indeed produce 10-micron emission patterns extended in polar directions, with extension ratios compatible with those found in observations. We are able to constrain the range of parameters that produce such morphologies.

Machine learning from computer simulations with applications in rail vehicle dynamics

NASA Astrophysics Data System (ADS)

Taheri, Mehdi; Ahmadian, Mehdi

2016-05-01

The application of stochastic modelling for learning the behaviour of a multibody dynamics (MBD) models is investigated. Post-processing data from a simulation run are used to train the stochastic model that estimates the relationship between model inputs (suspension relative displacement and velocity) and the output (sum of suspension forces). The stochastic model can be used to reduce the computational burden of the MBD model by replacing a computationally expensive subsystem in the model (suspension subsystem). With minor changes, the stochastic modelling technique is able to learn the behaviour of a physical system and integrate its behaviour within MBD models. The technique is highly advantageous for MBD models where real-time simulations are necessary, or with models that have a large number of repeated substructures, e.g. modelling a train with a large number of railcars. The fact that the training data are acquired prior to the development of the stochastic model discards the conventional sampling plan strategies like Latin Hypercube sampling plans where simulations are performed using the inputs dictated by the sampling plan. Since the sampling plan greatly influences the overall accuracy and efficiency of the stochastic predictions, a sampling plan suitable for the process is developed where the most space-filling subset of the acquired data with ? number of sample points that best describes the dynamic behaviour of the system under study is selected as the training data.

Optimization design of energy deposition on single expansion ramp nozzle

NASA Astrophysics Data System (ADS)

Ju, Shengjun; Yan, Chao; Wang, Xiaoyong; Qin, Yupei; Ye, Zhifei

2017-11-01

Optimization design has been widely used in the aerodynamic design process of scramjets. The single expansion ramp nozzle is an important component for scramjets to produces most of thrust force. A new concept of increasing the aerodynamics of the scramjet nozzle with energy deposition is presented. The essence of the method is to create a heated region in the inner flow field of the scramjet nozzle. In the current study, the two-dimensional coupled implicit compressible Reynolds Averaged Navier-Stokes and Menter's shear stress transport turbulence model have been applied to numerically simulate the flow fields of the single expansion ramp nozzle with and without energy deposition. The numerical results show that the proposal of energy deposition can be an effective method to increase force characteristics of the scramjet nozzle, the thrust coefficient CT increase by 6.94% and lift coefficient CN decrease by 26.89%. Further, the non-dominated sorting genetic algorithm coupled with the Radial Basis Function neural network surrogate model has been employed to determine optimum location and density of the energy deposition. The thrust coefficient CT and lift coefficient CN are selected as objective functions, and the sampling points are obtained numerically by using a Latin hypercube design method. The optimized thrust coefficient CT further increase by 1.94%, meanwhile, the optimized lift coefficient CN further decrease by 15.02% respectively. At the same time, the optimized performances are in good and reasonable agreement with the numerical predictions. The findings suggest that scramjet nozzle design and performance can benefit from the application of energy deposition.

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

NASA Astrophysics Data System (ADS)

He, F.

2015-12-01

This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.

The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D

NASA Technical Reports Server (NTRS)

Canuto, Claudio; Tabacco, Anita; Urban, Karsten

1998-01-01

The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.

[Uncertainty characterization approaches for ecological risk assessment of polycyclic aromatic hydrocarbon in Taihu Lake].

PubMed

Guo, Guang-Hui; Wu, Feng-Chang; He, Hong-Ping; Feng, Cheng-Lian; Zhang, Rui-Qing; Li, Hui-Xian

2012-04-01

Probabilistic approaches, such as Monte Carlo Sampling (MCS) and Latin Hypercube Sampling (LHS), and non-probabilistic approaches, such as interval analysis, fuzzy set theory and variance propagation, were used to characterize uncertainties associated with risk assessment of sigma PAH8 in surface water of Taihu Lake. The results from MCS and LHS were represented by probability distributions of hazard quotients of sigma PAH8 in surface waters of Taihu Lake. The probabilistic distribution of hazard quotient were obtained from the results of MCS and LHS based on probabilistic theory, which indicated that the confidence intervals of hazard quotient at 90% confidence level were in the range of 0.000 18-0.89 and 0.000 17-0.92, with the mean of 0.37 and 0.35, respectively. In addition, the probabilities that the hazard quotients from MCS and LHS exceed the threshold of 1 were 9.71% and 9.68%, respectively. The sensitivity analysis suggested the toxicity data contributed the most to the resulting distribution of quotients. The hazard quotient of sigma PAH8 to aquatic organisms ranged from 0.000 17 to 0.99 using interval analysis. The confidence interval was (0.001 5, 0.016 3) at the 90% confidence level calculated using fuzzy set theory, and the confidence interval was (0.000 16, 0.88) at the 90% confidence level based on the variance propagation. These results indicated that the ecological risk of sigma PAH8 to aquatic organisms were low. Each method has its own set of advantages and limitations, which was based on different theory; therefore, the appropriate method should be selected on a case-by-case to quantify the effects of uncertainties on the ecological risk assessment. Approach based on the probabilistic theory was selected as the most appropriate method to assess the risk of sigma PAH8 in surface water of Taihu Lake, which provided an important scientific foundation of risk management and control for organic pollutants in water.

Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations

NASA Astrophysics Data System (ADS)

Ware, Tim; Dobson, Geoff; Hanlon, David; Hiles, Richard; Mason, Robert; Perry, Ray

2017-09-01

The ANSWERS Software Service is developing a number of techniques to better understand and quantify uncertainty on calculations of the neutron multiplication factor, k-effective, in nuclear fuel and other systems containing fissile material. The uncertainty on the calculated k-effective arises from a number of sources, including nuclear data uncertainties, manufacturing tolerances, modelling approximations and, for Monte Carlo simulation, stochastic uncertainty. For determining the uncertainties due to nuclear data, a set of application libraries have been generated for use with the MONK10 Monte Carlo and the WIMS10 deterministic criticality and reactor physics codes. This paper overviews the generation of these nuclear data libraries by Latin hypercube sampling of JEFF-3.1.2 evaluated data based upon a library of covariance data taken from JEFF, ENDF/B, JENDL and TENDL evaluations. Criticality calculations have been performed with MONK10 and WIMS10 using these sampled libraries for a number of benchmark models of fissile systems. Results are presented which show the uncertainty on k-effective for these systems arising from the uncertainty on the input nuclear data.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

DOE PAGES

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra; ...

2017-11-20

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Development of building energy asset rating using stock modelling in the USA

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

Wang, Na; Goel, Supriya; Makhmalbaf, Atefe

2016-01-29

The US Building Energy Asset Score helps building stakeholders quickly gain insight into the efficiency of building systems (envelope, electrical and mechanical systems). A robust, easy-to-understand 10-point scoring system was developed to facilitate an unbiased comparison of similar building types across the country. The Asset Score does not rely on a database or specific building baselines to establish a rating. Rather, distributions of energy use intensity (EUI) for various building use types were constructed using Latin hypercube sampling and converted to a series of stepped linear scales to score buildings. A score is calculated based on the modelled source EUImore » after adjusting for climate. A web-based scoring tool, which incorporates an analytical engine and a simulation engine, was developed to standardize energy modelling and reduce implementation cost. This paper discusses the methodology used to perform several hundred thousand building simulation runs and develop the scoring scales.« less

Uncertainty and sensitivity analysis for two-phase flow in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant: Undisturbed conditions

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

HELTON,JON CRAIG; BEAN,J.E.; ECONOMY,K.

2000-05-19

Uncertainty and sensitivity analysis results obtained in the 1996 performance assessment for the Waste Isolation Pilot Plant are presented for two-phase flow the vicinity of the repository under undisturbed conditions. Techniques based on Latin hypercube sampling, examination of scatterplots, stepwise regression analysis, partial correlation analysis and rank transformation are used to investigate brine inflow, gas generation repository pressure, brine saturation and brine and gas outflow. Of the variables under study, repository pressure is potentially the most important due to its influence on spallings and direct brine releases, with the uncertainty in its value being dominated by the extent to whichmore » the microbial degradation of cellulose takes place, the rate at which the corrosion of steel takes place, and the amount of brine that drains from the surrounding disturbed rock zone into the repository.« less

Optimisation of lateral car dynamics taking into account parameter uncertainties

NASA Astrophysics Data System (ADS)

Busch, Jochen; Bestle, Dieter

2014-02-01

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.

Efficient hybrid evolutionary algorithm for optimization of a strip coiling process

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Park, Won-Woong; Kim, Dong-Kyu; Im, Yong-Taek; Bureerat, Sujin; Kwon, Hyuck-Cheol; Chun, Myung-Sik

2015-04-01

This article proposes an efficient metaheuristic based on hybridization of teaching-learning-based optimization and differential evolution for optimization to improve the flatness of a strip during a strip coiling process. Differential evolution operators were integrated into the teaching-learning-based optimization with a Latin hypercube sampling technique for generation of an initial population. The objective function was introduced to reduce axial inhomogeneity of the stress distribution and the maximum compressive stress calculated by Love's elastic solution within the thin strip, which may cause an irregular surface profile of the strip during the strip coiling process. The hybrid optimizer and several well-established evolutionary algorithms (EAs) were used to solve the optimization problem. The comparative studies show that the proposed hybrid algorithm outperformed other EAs in terms of convergence rate and consistency. It was found that the proposed hybrid approach was powerful for process optimization, especially with a large-scale design problem.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

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

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Research into the Architecture of CAD Based Robot Vision Systems

DTIC Science & Technology

1988-02-09

Vision 󈨚 and "Automatic Generation of Recognition Features for Com- puter Vision," Mudge, Turney and Volz, published in Robotica (1987). All of the...Occluded Parts," (T.N. Mudge, J.L. Turney, and R.A. Volz), Robotica , vol. 5, 1987, pp. 117-127. 5. "Vision Algorithms for Hypercube Machines," (T.N. Mudge

What Friends Are For: Collaborative Intelligence Analysis and Search

DTIC Science & Technology

2014-06-01

14. SUBJECT TERMS Intelligence Community, information retrieval, recommender systems , search engines, social networks, user profiling, Lucene...improvements over existing search systems . The improvements are shown to be robust to high levels of human error and low similarity between users ...precision NOLH nearly orthogonal Latin hypercubes P@ precision at documents RS recommender systems TREC Text REtrieval Conference USM user

A graph with fractional revival

NASA Astrophysics Data System (ADS)

Bernard, Pierre-Antoine; Chan, Ada; Loranger, Érika; Tamon, Christino; Vinet, Luc

2018-02-01

An example of a graph that admits balanced fractional revival between antipodes is presented. It is obtained by establishing the correspondence between the quantum walk on a hypercube where the opposite vertices across the diagonals of each face are connected and, the coherent transport of single excitations in the extension of the Krawtchouk spin chain with next-to-nearest neighbour interactions.

Optimal mapping of irregular finite element domains to parallel processors

NASA Technical Reports Server (NTRS)

Flower, J.; Otto, S.; Salama, M.

1987-01-01

Mapping the solution domain of n-finite elements into N-subdomains that may be processed in parallel by N-processors is an optimal one if the subdomain decomposition results in a well-balanced workload distribution among the processors. The problem is discussed in the context of irregular finite element domains as an important aspect of the efficient utilization of the capabilities of emerging multiprocessor computers. Finding the optimal mapping is an intractable combinatorial optimization problem, for which a satisfactory approximate solution is obtained here by analogy to a method used in statistical mechanics for simulating the annealing process in solids. The simulated annealing analogy and algorithm are described, and numerical results are given for mapping an irregular two-dimensional finite element domain containing a singularity onto the Hypercube computer.

On multigrid methods for the Navier-Stokes Computer

NASA Technical Reports Server (NTRS)

Nosenchuck, D. M.; Krist, S. E.; Zang, T. A.

1988-01-01

The overall architecture of the multipurpose parallel-processing Navier-Stokes Computer (NSC) being developed by Princeton and NASA Langley (Nosenchuck et al., 1986) is described and illustrated with extensive diagrams, and the NSC implementation of an elementary multigrid algorithm for simulating isotropic turbulence (based on solution of the incompressible time-dependent Navier-Stokes equations with constant viscosity) is characterized in detail. The present NSC design concept calls for 64 nodes, each with the performance of a class VI supercomputer, linked together by a fiber-optic hypercube network and joined to a front-end computer by a global bus. In this configuration, the NSC would have a storage capacity of over 32 Gword and a peak speed of over 40 Gflops. The multigrid Navier-Stokes code discussed would give sustained operation rates of about 25 Gflops.

Parallel grid generation algorithm for distributed memory computers

NASA Technical Reports Server (NTRS)

Moitra, Stuti; Moitra, Anutosh

1994-01-01

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Comparative Analysis of Reconstructed Image Quality in a Simulated Chromotomographic Imager

DTIC Science & Technology

2014-03-01

quality . This example uses five basic images a backlit bar chart with random intensity, 100 nm separation. A total of 54 initial target...compared for a variety of scenes. Reconstructed image quality is highly dependent on the initial target hypercube so a total of 54 initial target...COMPARATIVE ANALYSIS OF RECONSTRUCTED IMAGE QUALITY IN A SIMULATED CHROMOTOMOGRAPHIC IMAGER THESIS

Flexible Space-Filling Designs for Complex System Simulations

DTIC Science & Technology

2013-06-01

interior of the experimental region and cannot fit higher-order models. We present a genetic algorithm that constructs space-filling designs with...Computer Experiments, Design of Experiments, Genetic Algorithm , Latin Hypercube, Response Surface Methodology, Nearly Orthogonal 15. NUMBER OF PAGES 147...experimental region and cannot fit higher-order models. We present a genetic algorithm that constructs space-filling designs with minimal correlations

Different Formulations of the Orthogonal Array Problem and Their Symmetries

DTIC Science & Technology

2014-06-19

t). Note that OAP(k, s, t, λ) is a polytope not an unbounded polyhedron because it can be embedded inside the hypercube [0, λ]m. Theorem 5. The OAP(k...3.1) is a facet since otherwise OAP(k, s, t, λ) would be an unbounded polyhedron . Then there exists Ny ∈ Rm satisfying all but the 28 facet defining

Hypercube Solutions for Conjugate Directions

DTIC Science & Technology

1991-12-01

1800s, Charles Babbage had designed his Difference Engine and proceeded to the more advanced Analytical Engine. These machines were 1 never completed...Consider his motivation. The following example was frequently cited by Charles Babbage (1792-1871) to justify the construction of his first computing...360 LIST OF REFERENCES [1] P. Morrison and E. Morrison, editors. Charles Babbage and His Calculating Engines. Dover Publications, Inc., New

HERMIES-I: a mobile robot for navigation and manipulation experiments

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

Weisbin, C.R.; Barhen, J.; de Saussure, G.

1985-01-01

The purpose of this paper is to report the current status of investigations ongoing at the Center for Engineering Systems Advanced Research (CESAR) in the areas of navigation and manipulation in unstructured environments. The HERMIES-I mobile robot, a prototype of a series which contains many of the major features needed for remote work in hazardous environments is discussed. Initial experimental work at CESAR has begun in the area of navigation. It briefly reviews some of the ongoing research in autonomous navigation and describes initial research with HERMIES-I and associated graphic simulation. Since the HERMIES robots will generally be composed ofmore » a variety of asynchronously controlled hardware components (such as manipulator arms, digital image sensors, sonars, etc.) it seems appropriate to consider future development of the HERMIES brain as a hypercube ensemble machine with concurrent computation and associated message passing. The basic properties of such a hypercube architecture are presented. Decision-making under uncertainty eventually permeates all of our work. Following a survey of existing analytical approaches, it was decided that a stronger theoretical basis is required. As such, this paper presents the framework for a recently developed hybrid uncertainty theory. 21 refs., 2 figs.« less

Critical and Griffiths-McCoy singularities in quantum Ising spin glasses on d-dimensional hypercubic lattices: A series expansion study.

PubMed

Singh, R R P; Young, A P

2017-08-01

We study the ±J transverse-field Ising spin-glass model at zero temperature on d-dimensional hypercubic lattices and in the Sherrington-Kirkpatrick (SK) model, by series expansions around the strong-field limit. In the SK model and in high dimensions our calculated critical properties are in excellent agreement with the exact mean-field results, surprisingly even down to dimension d=6, which is below the upper critical dimension of d=8. In contrast, at lower dimensions we find a rich singular behavior consisting of critical and Griffiths-McCoy singularities. The divergence of the equal-time structure factor allows us to locate the critical coupling where the correlation length diverges, implying the onset of a thermodynamic phase transition. We find that the spin-glass susceptibility as well as various power moments of the local susceptibility become singular in the paramagnetic phase before the critical point. Griffiths-McCoy singularities are very strong in two dimensions but decrease rapidly as the dimension increases. We present evidence that high enough powers of the local susceptibility may become singular at the pure-system critical point.

A parallel strategy for implementing real-time expert systems using CLIPS

NASA Technical Reports Server (NTRS)

Ilyes, Laszlo A.; Villaseca, F. Eugenio; Delaat, John

1994-01-01

As evidenced by current literature, there appears to be a continued interest in the study of real-time expert systems. It is generally recognized that speed of execution is only one consideration when designing an effective real-time expert system. Some other features one must consider are the expert system's ability to perform temporal reasoning, handle interrupts, prioritize data, contend with data uncertainty, and perform context focusing as dictated by the incoming data to the expert system. This paper presents a strategy for implementing a real time expert system on the iPSC/860 hypercube parallel computer using CLIPS. The strategy takes into consideration not only the execution time of the software, but also those features which define a true real-time expert system. The methodology is then demonstrated using a practical implementation of an expert system which performs diagnostics on the Space Shuttle Main Engine (SSME). This particular implementation uses an eight node hypercube to process ten sensor measurements in order to simultaneously diagnose five different failure modes within the SSME. The main program is written in ANSI C and embeds CLIPS to better facilitate and debug the rule based expert system.

Critical and Griffiths-McCoy singularities in quantum Ising spin glasses on d -dimensional hypercubic lattices: A series expansion study

NASA Astrophysics Data System (ADS)

Singh, R. R. P.; Young, A. P.

2017-08-01

We study the ±J transverse-field Ising spin-glass model at zero temperature on d -dimensional hypercubic lattices and in the Sherrington-Kirkpatrick (SK) model, by series expansions around the strong-field limit. In the SK model and in high dimensions our calculated critical properties are in excellent agreement with the exact mean-field results, surprisingly even down to dimension d =6 , which is below the upper critical dimension of d =8 . In contrast, at lower dimensions we find a rich singular behavior consisting of critical and Griffiths-McCoy singularities. The divergence of the equal-time structure factor allows us to locate the critical coupling where the correlation length diverges, implying the onset of a thermodynamic phase transition. We find that the spin-glass susceptibility as well as various power moments of the local susceptibility become singular in the paramagnetic phase before the critical point. Griffiths-McCoy singularities are very strong in two dimensions but decrease rapidly as the dimension increases. We present evidence that high enough powers of the local susceptibility may become singular at the pure-system critical point.

Spacecraft On-Board Information Extraction Computer (SOBIEC)

NASA Technical Reports Server (NTRS)

Eisenman, David; Decaro, Robert E.; Jurasek, David W.

1994-01-01

The Jet Propulsion Laboratory is the Technical Monitor on an SBIR Program issued for Irvine Sensors Corporation to develop a highly compact, dual use massively parallel processing node known as SOBIEC. SOBIEC couples 3D memory stacking technology provided by nCUBE. The node contains sufficient network Input/Output to implement up to an order-13 binary hypercube. The benefit of this network, is that it scales linearly as more processors are added, and it is a superset of other commonly used interconnect topologies such as: meshes, rings, toroids, and trees. In this manner, a distributed processing network can be easily devised and supported. The SOBIEC node has sufficient memory for most multi-computer applications, and also supports external memory expansion and DMA interfaces. The SOBIEC node is supported by a mature set of software development tools from nCUBE. The nCUBE operating system (OS) provides configuration and operational support for up to 8000 SOBIEC processors in an order-13 binary hypercube or any subset or partition(s) thereof. The OS is UNIX (USL SVR4) compatible, with C, C++, and FORTRAN compilers readily available. A stand-alone development system is also available to support SOBIEC test and integration.

A two-step framework for the registration of HE stained and FTIR images

NASA Astrophysics Data System (ADS)

Peñaranda, Francisco; Naranjo, Valery; Verdú, Rafaél.; Lloyd, Gavin R.; Nallala, Jayakrupakar; Stone, Nick

2016-03-01

FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical phenomena that require special processing. Little work has been done in the field with the aim of registering hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant structures that the pathologist may identify in the gold standard HE images. A two-step registration framework is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This representative image, which must have a spatial contrast as similar as possible to a gray image obtained from the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the registration algorithm a similarity transformation is estimated from interest points, which are automatically detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in the frequency domain compensates for local anatomical variations between both images. After a proper tuning of some parameters the proposed registration framework works in an automated way. The method was tested on 7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).

Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

NASA Astrophysics Data System (ADS)

Papaioannou, George; Vasiliades, Lampros; Loukas, Athanasios; Aronica, Giuseppe T.

2017-04-01

Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.

Acute effect of Vagus nerve stimulation parameters on cardiac chronotropic, inotropic, and dromotropic responses

NASA Astrophysics Data System (ADS)

Ojeda, David; Le Rolle, Virginie; Romero-Ugalde, Hector M.; Gallet, Clément; Bonnet, Jean-Luc; Henry, Christine; Bel, Alain; Mabo, Philippe; Carrault, Guy; Hernández, Alfredo I.

2017-11-01

Vagus nerve stimulation (VNS) is an established therapy for drug-resistant epilepsy and depression, and is considered as a potential therapy for other pathologies, including Heart Failure (HF) or inflammatory diseases. In the case of HF, several experimental studies on animals have shown an improvement in the cardiac function and a reverse remodeling of the cardiac cavity when VNS is applied. However, recent clinical trials have not been able to reproduce the same response in humans. One of the hypothesis to explain this lack of response is related to the way in which stimulation parameters are defined. The combined effect of VNS parameters is still poorly-known, especially in the case of VNS synchronously delivered with cardiac activity. In this paper, we propose a methodology to analyze the acute cardiovascular effects of VNS parameters individually, as well as their interactive effects. A Latin hypercube sampling method was applied to design a uniform experimental plan. Data gathered from this experimental plan was used to produce a Gaussian process regression (GPR) model in order to estimate unobserved VNS sequences. Finally, a Morris screening sensitivity analysis method was applied to each obtained GPR model. Results highlight dominant effects of pulse current, pulse width and number of pulses over frequency and delay and, more importantly, the degree of interactions between these parameters on the most important acute cardiovascular responses. In particular, high interacting effects between current and pulse width were found. Similar sensitivity profiles were observed for chronotropic, dromotropic and inotropic effects. These findings are of primary importance for the future development of closed-loop, personalized neuromodulator technologies.

An optimization based sampling approach for multiple metrics uncertainty analysis using generalized likelihood uncertainty estimation

NASA Astrophysics Data System (ADS)

Zhou, Rurui; Li, Yu; Lu, Di; Liu, Haixing; Zhou, Huicheng

2016-09-01

This paper investigates the use of an epsilon-dominance non-dominated sorted genetic algorithm II (ɛ-NSGAII) as a sampling approach with an aim to improving sampling efficiency for multiple metrics uncertainty analysis using Generalized Likelihood Uncertainty Estimation (GLUE). The effectiveness of ɛ-NSGAII based sampling is demonstrated compared with Latin hypercube sampling (LHS) through analyzing sampling efficiency, multiple metrics performance, parameter uncertainty and flood forecasting uncertainty with a case study of flood forecasting uncertainty evaluation based on Xinanjiang model (XAJ) for Qing River reservoir, China. Results obtained demonstrate the following advantages of the ɛ-NSGAII based sampling approach in comparison to LHS: (1) The former performs more effective and efficient than LHS, for example the simulation time required to generate 1000 behavioral parameter sets is shorter by 9 times; (2) The Pareto tradeoffs between metrics are demonstrated clearly with the solutions from ɛ-NSGAII based sampling, also their Pareto optimal values are better than those of LHS, which means better forecasting accuracy of ɛ-NSGAII parameter sets; (3) The parameter posterior distributions from ɛ-NSGAII based sampling are concentrated in the appropriate ranges rather than uniform, which accords with their physical significance, also parameter uncertainties are reduced significantly; (4) The forecasted floods are close to the observations as evaluated by three measures: the normalized total flow outside the uncertainty intervals (FOUI), average relative band-width (RB) and average deviation amplitude (D). The flood forecasting uncertainty is also reduced a lot with ɛ-NSGAII based sampling. This study provides a new sampling approach to improve multiple metrics uncertainty analysis under the framework of GLUE, and could be used to reveal the underlying mechanisms of parameter sets under multiple conflicting metrics in the uncertainty analysis process.

Vision-Based Navigation and Parallel Computing

DTIC Science & Technology

1990-08-01

33 5.8. Behizad Kamgar-Parsi and Behrooz Karngar-Parsi,"On Problem 5- lving with Hopfield Neural Networks", CAR-TR-462, CS-TR...Second. the hypercube connections support logarithmic implementations of fundamental parallel algorithms. such as grid permutations and scan...the pose space. It also uses a set of virtual processors to represent an orthogonal projection grid , and projections of the six dimensional pose space

Hypercat - Hypercube of Clumpy AGN Tori

NASA Astrophysics Data System (ADS)

Nikutta, Robert; Lopez-Rodriguez, Enrique; Ichikawa, Kohei; Levenson, Nancy; Packham, Christopher C.

2017-06-01

Dusty tori surrounding the central engines of Active Galactic Nuclei (AGN) are required by the Unification Paradigm, and are supported by many observations, e.g. variable nuclear absorber (sometimes Compton-thick) in X-rays, reverberation mapping in optical/UV, hot dust emission and SED shapes in NIR/MIR, molecular and cool-dust tori observed with ALMA in sub-mm.While models of AGN torus SEDs have been developed and utilized for a long time, the study of the resolved emission morphology (brightness maps) has so far been under-appreciated, presumably because resolved observations of the central parsec in AGN are only possible very recently. Currently, only NIR+MIR interferometry is capable of resolving the nuclear dust emission (but not of producing images, until MATISSE comes online). Furthermore, MIR interferometry has delivered also puzzling results, e.g. that in some resolved sources the light emanates preferentially from polar directions above the "torus" system, and not from the equatorial plane, where most of the dust is located.We are preparing the release of a panchromatic, fully interpolable hypercube of brightness maps and projected dust images for a large number of CLUMPY torus models (Nenkova+2008), that will help facilitate studies of resolved AGN emission and dust morphologies. Together with the cube we will release a comprehensive set of open-source tools (Python) that will enable researches to work efficiently with this large hypercube:* easy sub-cube selection + memory-mapping (mitigating the too-big-for-RAM problem)* multi-dim image interpolation (get an image at any wavelength & model parameter combination)* simulation of observations with telescopes (compute/provide + apply a PSF) and interferometers (get visibilities)* analyze images with respect to the power contained at all scales and orientations (via 2D steerable wavelets), addressing the seemingly puzzling results mentioned aboveA series of papers is in preparation, aiming at solving the puzzles, and at making predictions about the resolvability of all nearby AGN tori with any combination of current and future instruments (e.g. VLTI+MATISSE, TMT+MICHI, GMT, ELT, JWST, ALMA).

Designing an optimal software intensive system acquisition: A game theoretic approach

NASA Astrophysics Data System (ADS)

Buettner, Douglas John

The development of schedule-constrained software-intensive space systems is challenging. Case study data from national security space programs developed at the U.S. Air Force Space and Missile Systems Center (USAF SMC) provide evidence of the strong desire by contractors to skip or severely reduce software development design and early defect detection methods in these schedule-constrained environments. The research findings suggest recommendations to fully address these issues at numerous levels. However, the observations lead us to investigate modeling and theoretical methods to fundamentally understand what motivated this behavior in the first place. As a result, Madachy's inspection-based system dynamics model is modified to include unit testing and an integration test feedback loop. This Modified Madachy Model (MMM) is used as a tool to investigate the consequences of this behavior on the observed defect dynamics for two remarkably different case study software projects. Latin Hypercube sampling of the MMM with sample distributions for quality, schedule and cost-driven strategies demonstrate that the higher cost and effort quality-driven strategies provide consistently better schedule performance than the schedule-driven up-front effort-reduction strategies. Game theory reasoning for schedule-driven engineers cutting corners on inspections and unit testing is based on the case study evidence and Austin's agency model to describe the observed phenomena. Game theory concepts are then used to argue that the source of the problem and hence the solution to developers cutting corners on quality for schedule-driven system acquisitions ultimately lies with the government. The game theory arguments also lead to the suggestion that the use of a multi-player dynamic Nash bargaining game provides a solution for our observed lack of quality game between the government (the acquirer) and "large-corporation" software developers. A note is provided that argues this multi-player dynamic Nash bargaining game also provides the solution to Freeman Dyson's problem, for a way to place a label of good or bad on systems.

Parallelization of Finite Element Analysis Codes Using Heterogeneous Distributed Computing

NASA Technical Reports Server (NTRS)

Ozguner, Fusun

1996-01-01

Performance gains in computer design are quickly consumed as users seek to analyze larger problems to a higher degree of accuracy. Innovative computational methods, such as parallel and distributed computing, seek to multiply the power of existing hardware technology to satisfy the computational demands of large applications. In the early stages of this project, experiments were performed using two large, coarse-grained applications, CSTEM and METCAN. These applications were parallelized on an Intel iPSC/860 hypercube. It was found that the overall speedup was very low, due to large, inherently sequential code segments present in the applications. The overall execution time T(sub par), of the application is dependent on these sequential segments. If these segments make up a significant fraction of the overall code, the application will have a poor speedup measure.

Dynamical analysis of continuous higher-order hopfield networks for combinatorial optimization.

PubMed

Atencia, Miguel; Joya, Gonzalo; Sandoval, Francisco

2005-08-01

In this letter, the ability of higher-order Hopfield networks to solve combinatorial optimization problems is assessed by means of a rigorous analysis of their properties. The stability of the continuous network is almost completely clarified: (1) hyperbolic interior equilibria, which are unfeasible, are unstable; (2) the state cannot escape from the unitary hypercube; and (3) a Lyapunov function exists. Numerical methods used to implement the continuous equation on a computer should be designed with the aim of preserving these favorable properties. The case of nonhyperbolic fixed points, which occur when the Hessian of the target function is the null matrix, requires further study. We prove that these nonhyperbolic interior fixed points are unstable in networks with three neurons and order two. The conjecture that interior equilibria are unstable in the general case is left open.

Running coupling constant from lattice studies of gluon and ghost propagators

NASA Astrophysics Data System (ADS)

Cucchieri, A.; Mendes, T.

2004-12-01

We present a numerical study of the running coupling constant in four-dimensional pure-SU(2) lattice gauge theory. The running coupling is evaluated by fitting data for the gluon and ghost propagators in minimal Landau gauge. Following Refs. [1, 2], the fitting formulae are obtained by a simultaneous integration of the β function and of a function coinciding with the anomalous dimension of the propagator in the momentum subtraction scheme. We consider these formulae at three and four loops. The fitting method works well, especially for the ghost case, for which statistical error and hyper-cubic effects are very small. Our present result for ΛMS is 200-40+60 MeV, where the error is purely systematic. We are currently extending this analysis to five loops in order to reduce this systematic error.

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

Lee, S. M.; Kim, K. Y.

Printed circuit heat exchanger (PCHE) is recently considered as a recuperator for the high temperature gas cooled reactor. In this work, the zigzag-channels of a PCHE have been optimized by using three-dimensional Reynolds-Averaged Navier-Stokes (RANS) analysis and response surface approximation (RSA) modeling technique to enhance thermal-hydraulic performance. Shear stress transport turbulence model is used as a turbulence closure. The objective function is defined as a linear combination of the functions related to heat transfer and friction loss of the PCHE, respectively. Three geometric design variables viz., the ratio of the radius of the fillet to hydraulic diameter of the channels,more » the ratio of wavelength to hydraulic diameter of the channels, and the ratio of wave height to hydraulic diameter of the channels, are used for the optimization. Design points are selected through Latin-hypercube sampling. The optimal design is determined through the RSA model which uses RANS derived calculations at the design points. The results show that the optimum shape enhances considerably the thermal-hydraulic performance than a reference shape. (authors)« less

Developing an in silico model of the modulation of base excision repair using methoxyamine for more targeted cancer therapeutics.

PubMed

Gurkan-Cavusoglu, Evren; Avadhani, Sriya; Liu, Lili; Kinsella, Timothy J; Loparo, Kenneth A

2013-04-01

Base excision repair (BER) is a major DNA repair pathway involved in the processing of exogenous non-bulky base damages from certain classes of cancer chemotherapy drugs as well as ionising radiation (IR). Methoxyamine (MX) is a small molecule chemical inhibitor of BER that is shown to enhance chemotherapy and/or IR cytotoxicity in human cancers. In this study, the authors have analysed the inhibitory effect of MX on the BER pathway kinetics using a computational model of the repair pathway. The inhibitory effect of MX depends on the BER efficiency. The authors have generated variable efficiency groups using different sets of protein concentrations generated by Latin hypercube sampling, and they have clustered simulation results into high, medium and low efficiency repair groups. From analysis of the inhibitory effect of MX on each of the three groups, it is found that the inhibition is most effective for high efficiency BER, and least effective for low efficiency repair.

Boundary conditions, dimensionality, topology and size dependence of the superconducting transition temperature

NASA Astrophysics Data System (ADS)

Fink, Herman J.; Haley, Stephen B.; Giuraniuc, Claudiu V.; Kozhevnikov, Vladimir F.; Indekeu, Joseph O.

2005-11-01

For various sample geometries (slabs, cylinders, spheres, hypercubes), de Gennes' boundary condition parameter b is used to study its effect upon the transition temperature Tc of a superconductor. For b > 0 the order parameter at the surface is decreased, and as a consequence Tc is reduced, while for b < 0 the order parameter at the surface is increased, thereby enhancing Tc of a specimen in zero magnetic field. Exact solutions, derived by Fink and Haley (Int. J. mod. Phys. B, 17, 2171 (2003)), of the order parameter of a slab of finite thickness as a function of temperature are presented, both for reduced and enhanced transition (nucleation) temperatures. At the nucleation temperature the order parameter approaches zero. This concise review closes with a link established between de Gennes' microscopic boundary condition and the Ginzburg-Landau phenomenological approach, and a discussion of some relevant experiments. For example, applying the boundary condition with b < 0 to tin whiskers elucidates the increase of Tc with strain.

Computer program to minimize prediction error in models from experiments with 16 hypercube points and 0 to 6 center points

NASA Technical Reports Server (NTRS)

Holms, A. G.

1982-01-01

A previous report described a backward deletion procedure of model selection that was optimized for minimum prediction error and which used a multiparameter combination of the F - distribution and an order statistics distribution of Cochran's. A computer program is described that applies the previously optimized procedure to real data. The use of the program is illustrated by examples.

Software Techniques for Non-Von Neumann Architectures

DTIC Science & Technology

1990-01-01

Commtopo programmable Benes net.; hypercubic lattice for QCD Control CENTRALIZED Assign STATIC Memory :SHARED Synch UNIVERSAL Max-cpu 566 Proessor...boards (each = 4 floating point units, 2 multipliers) Cpu-size 32-bit floating point chips Perform 11.4 Gflops Market quantum chromodynamics ( QCD ...functions there should exist a capability to define hierarchies and lattices of complex objects. A complex object can be made up of a set of simple objects

On the Local Equivalence Between the Canonical and the Microcanonical Ensembles for Quantum Spin Systems

NASA Astrophysics Data System (ADS)

Tasaki, Hal

2018-06-01

We study a quantum spin system on the d-dimensional hypercubic lattice Λ with N=L^d sites with periodic boundary conditions. We take an arbitrary translation invariant short-ranged Hamiltonian. For this system, we consider both the canonical ensemble with inverse temperature β _0 and the microcanonical ensemble with the corresponding energy U_N(β _0) . For an arbitrary self-adjoint operator \\hat{A} whose support is contained in a hypercubic block B inside Λ , we prove that the expectation values of \\hat{A} with respect to these two ensembles are close to each other for large N provided that β _0 is sufficiently small and the number of sites in B is o(N^{1/2}) . This establishes the equivalence of ensembles on the level of local states in a large but finite system. The result is essentially that of Brandao and Cramer (here restricted to the case of the canonical and the microcanonical ensembles), but we prove improved estimates in an elementary manner. We also review and prove standard results on the thermodynamic limits of thermodynamic functions and the equivalence of ensembles in terms of thermodynamic functions. The present paper assumes only elementary knowledge on quantum statistical mechanics and quantum spin systems.

A methodology for system-of-systems design in support of the engineering team

NASA Astrophysics Data System (ADS)

Ridolfi, G.; Mooij, E.; Cardile, D.; Corpino, S.; Ferrari, G.

2012-04-01

Space missions have experienced a trend of increasing complexity in the last decades, resulting in the design of very complex systems formed by many elements and sub-elements working together to meet the requirements. In a classical approach, especially in a company environment, the two steps of design-space exploration and optimization are usually performed by experts inferring on major phenomena, making assumptions and doing some trial-and-error runs on the available mathematical models. This is done especially in the very early design phases where most of the costs are locked-in. With the objective of supporting the engineering team and the decision-makers during the design of complex systems, the authors developed a modelling framework for a particular category of complex, coupled space systems called System-of-Systems. Once modelled, the System-of-Systems is solved using a computationally cheap parametric methodology, named the mixed-hypercube approach, based on the utilization of a particular type of fractional factorial design-of-experiments, and analysis of the results via global sensitivity analysis and response surfaces. As an applicative example, a system-of-systems of a hypothetical human space exploration scenario for the support of a manned lunar base is presented. The results demonstrate that using the mixed-hypercube to sample the design space, an optimal solution is reached with a limited computational effort, providing support to the engineering team and decision makers thanks to sensitivity and robustness information. The analysis of the system-of-systems model that was implemented shows that the logistic support of a human outpost on the Moon for 15 years is still feasible with currently available launcher classes. The results presented in this paper have been obtained in cooperation with Thales Alenia Space—Italy, in the framework of a regional programme called STEPS. STEPS—Sistemi e Tecnologie per l'EsPlorazione Spaziale is a research project co-financed by Piedmont Region and firms and universities of the Piedmont Aerospace District in the ambit of the P.O.R-F.E.S.R. 2007-2013 program.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Efficient uncertainty quantification in fully-integrated surface and subsurface hydrologic simulations

NASA Astrophysics Data System (ADS)

Miller, K. L.; Berg, S. J.; Davison, J. H.; Sudicky, E. A.; Forsyth, P. A.

2018-01-01

Although high performance computers and advanced numerical methods have made the application of fully-integrated surface and subsurface flow and transport models such as HydroGeoSphere common place, run times for large complex basin models can still be on the order of days to weeks, thus, limiting the usefulness of traditional workhorse algorithms for uncertainty quantification (UQ) such as Latin Hypercube simulation (LHS) or Monte Carlo simulation (MCS), which generally require thousands of simulations to achieve an acceptable level of accuracy. In this paper we investigate non-intrusive polynomial chaos for uncertainty quantification, which in contrast to random sampling methods (e.g., LHS and MCS), represents a model response of interest as a weighted sum of polynomials over the random inputs. Once a chaos expansion has been constructed, approximating the mean, covariance, probability density function, cumulative distribution function, and other common statistics as well as local and global sensitivity measures is straightforward and computationally inexpensive, thus making PCE an attractive UQ method for hydrologic models with long run times. Our polynomial chaos implementation was validated through comparison with analytical solutions as well as solutions obtained via LHS for simple numerical problems. It was then used to quantify parametric uncertainty in a series of numerical problems with increasing complexity, including a two-dimensional fully-saturated, steady flow and transient transport problem with six uncertain parameters and one quantity of interest; a one-dimensional variably-saturated column test involving transient flow and transport, four uncertain parameters, and two quantities of interest at 101 spatial locations and five different times each (1010 total); and a three-dimensional fully-integrated surface and subsurface flow and transport problem for a small test catchment involving seven uncertain parameters and three quantities of interest at 241 different times each. Numerical experiments show that polynomial chaos is an effective and robust method for quantifying uncertainty in fully-integrated hydrologic simulations, which provides a rich set of features and is computationally efficient. Our approach has the potential for significant speedup over existing sampling based methods when the number of uncertain model parameters is modest ( ≤ 20). To our knowledge, this is the first implementation of the algorithm in a comprehensive, fully-integrated, physically-based three-dimensional hydrosystem model.

Distributed Adaptive Binary Quantization for Fast Nearest Neighbor Search.

PubMed

Xianglong Liu; Zhujin Li; Cheng Deng; Dacheng Tao

2017-11-01

Hashing has been proved an attractive technique for fast nearest neighbor search over big data. Compared with the projection based hashing methods, prototype-based ones own stronger power to generate discriminative binary codes for the data with complex intrinsic structure. However, existing prototype-based methods, such as spherical hashing and K-means hashing, still suffer from the ineffective coding that utilizes the complete binary codes in a hypercube. To address this problem, we propose an adaptive binary quantization (ABQ) method that learns a discriminative hash function with prototypes associated with small unique binary codes. Our alternating optimization adaptively discovers the prototype set and the code set of a varying size in an efficient way, which together robustly approximate the data relations. Our method can be naturally generalized to the product space for long hash codes, and enjoys the fast training linear to the number of the training data. We further devise a distributed framework for the large-scale learning, which can significantly speed up the training of ABQ in the distributed environment that has been widely deployed in many areas nowadays. The extensive experiments on four large-scale (up to 80 million) data sets demonstrate that our method significantly outperforms state-of-the-art hashing methods, with up to 58.84% performance gains relatively.

Parallel solution of the symmetric tridiagonal eigenproblem. Research report

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

Jessup, E.R.

1989-10-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed-memory Multiple Instruction, Multiple Data multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speed up, and accuracy. Experiments on an IPSC hypercube multiprocessor reveal that Cuppen's method ismore » the most accurate approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effect of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptions of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Parallel solution of the symmetric tridiagonal eigenproblem

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

Jessup, E.R.

1989-01-01

This thesis discusses methods for computing all eigenvalues and eigenvectors of a symmetric tridiagonal matrix on a distributed memory MIMD multiprocessor. Only those techniques having the potential for both high numerical accuracy and significant large-grained parallelism are investigated. These include the QL method or Cuppen's divide and conquer method based on rank-one updating to compute both eigenvalues and eigenvectors, bisection to determine eigenvalues, and inverse iteration to compute eigenvectors. To begin, the methods are compared with respect to computation time, communication time, parallel speedup, and accuracy. Experiments on an iPSC hyper-cube multiprocessor reveal that Cuppen's method is the most accuratemore » approach, but bisection with inverse iteration is the fastest and most parallel. Because the accuracy of the latter combination is determined by the quality of the computed eigenvectors, the factors influencing the accuracy of inverse iteration are examined. This includes, in part, statistical analysis of the effects of a starting vector with random components. These results are used to develop an implementation of inverse iteration producing eigenvectors with lower residual error and better orthogonality than those generated by the EISPACK routine TINVIT. This thesis concludes with adaptations of methods for the symmetric tridiagonal eigenproblem to the related problem of computing the singular value decomposition (SVD) of a bidiagonal matrix.« less

Multi-objective aerodynamic shape optimization of small livestock trailers

NASA Astrophysics Data System (ADS)

Gilkeson, C. A.; Toropov, V. V.; Thompson, H. M.; Wilson, M. C. T.; Foxley, N. A.; Gaskell, P. H.

2013-11-01

This article presents a formal optimization study of the design of small livestock trailers, within which the majority of animals are transported to market in the UK. The benefits of employing a headboard fairing to reduce aerodynamic drag without compromising the ventilation of the animals' microclimate are investigated using a multi-stage process involving computational fluid dynamics (CFD), optimal Latin hypercube (OLH) design of experiments (DoE) and moving least squares (MLS) metamodels. Fairings are parameterized in terms of three design variables and CFD solutions are obtained at 50 permutations of design variables. Both global and local search methods are employed to locate the global minimum from metamodels of the objective functions and a Pareto front is generated. The importance of carefully selecting an objective function is demonstrated and optimal fairing designs, offering drag reductions in excess of 5% without compromising animal ventilation, are presented.

Parallel computing works

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

Not Available

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of manymore » computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.« less

Probabilistic Modeling of Intracranial Pressure Effects on Optic Nerve Biomechanics

NASA Technical Reports Server (NTRS)

Ethier, C. R.; Feola, Andrew J.; Raykin, Julia; Myers, Jerry G.; Nelson, Emily S.; Samuels, Brian C.

2016-01-01

Altered intracranial pressure (ICP) is involved/implicated in several ocular conditions: papilledema, glaucoma and Visual Impairment and Intracranial Pressure (VIIP) syndrome. The biomechanical effects of altered ICP on optic nerve head (ONH) tissues in these conditions are uncertain but likely important. We have quantified ICP-induced deformations of ONH tissues, using finite element (FE) and probabilistic modeling (Latin Hypercube Simulations (LHS)) to consider a range of tissue properties and relevant pressures.

Parallel Processing and Scientific Applications

DTIC Science & Technology

1992-11-30

Lattice QCD Calculations on the Connection Machine), SIAM News 24, 1 (May 1991) 5. C. F. Baillie and D. A. Johnston, Crumpling Dynamically Triangulated...hypercubic lattice ; in the second, the surface is randomly triangulated once at the beginning of the simulation; and in the third the random...Sharpe, QCD with Dynamical Wilson Fermions 1I, Phys. Rev. D44, 3272 (1991), 8. R. Gupta and C. F. Baillie, Critical Behavior of the 2D XY Model, Phys

Mapping Flows onto Networks to Optimize Organizational Processes

DTIC Science & Technology

2005-01-01

And G . Porter, “Assessments of Simulated Performance of Alternative Architectures for Command and Control: The Role of Coordination”, Proceedings of...the 1999 Command & Control Research & Technology Symposium, NWC, Newport, RI, June 1999, pp. 123-143. [Iverson95] M. Iverson, F. Ozguner, G . Follen...Technology Symposium, NPS, Monterrey, CA, June, 2002. [Wu88] Min-You Wu, D. Gajski . “A Programming Aid for Hypercube Architectures.” The Journal of Supercomputing, 2(1988), pp. 349-372.

Computer-Access-Code Matrices

NASA Technical Reports Server (NTRS)

Collins, Earl R., Jr.

1990-01-01

Authorized users respond to changing challenges with changing passwords. Scheme for controlling access to computers defeats eavesdroppers and "hackers". Based on password system of challenge and password or sign, challenge, and countersign correlated with random alphanumeric codes in matrices of two or more dimensions. Codes stored on floppy disk or plug-in card and changed frequently. For even higher security, matrices of four or more dimensions used, just as cubes compounded into hypercubes in concurrent processing.

VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox

NASA Astrophysics Data System (ADS)

Razavi, S.; Sheikholeslami, R.; Haghnegahdar, A.; Esfahbod, B.

2016-12-01

VARS-TOOL is an advanced sensitivity and uncertainty analysis toolbox, applicable to the full range of computer simulation models, including Earth and Environmental Systems Models (EESMs). The toolbox was developed originally around VARS (Variogram Analysis of Response Surfaces), which is a general framework for Global Sensitivity Analysis (GSA) that utilizes the variogram/covariogram concept to characterize the full spectrum of sensitivity-related information, thereby providing a comprehensive set of "global" sensitivity metrics with minimal computational cost. VARS-TOOL is unique in that, with a single sample set (set of simulation model runs), it generates simultaneously three philosophically different families of global sensitivity metrics, including (1) variogram-based metrics called IVARS (Integrated Variogram Across a Range of Scales - VARS approach), (2) variance-based total-order effects (Sobol approach), and (3) derivative-based elementary effects (Morris approach). VARS-TOOL is also enabled with two novel features; the first one being a sequential sampling algorithm, called Progressive Latin Hypercube Sampling (PLHS), which allows progressively increasing the sample size for GSA while maintaining the required sample distributional properties. The second feature is a "grouping strategy" that adaptively groups the model parameters based on their sensitivity or functioning to maximize the reliability of GSA results. These features in conjunction with bootstrapping enable the user to monitor the stability, robustness, and convergence of GSA with the increase in sample size for any given case study. VARS-TOOL has been shown to achieve robust and stable results within 1-2 orders of magnitude smaller sample sizes (fewer model runs) than alternative tools. VARS-TOOL, available in MATLAB and Python, is under continuous development and new capabilities and features are forthcoming.

Global sensitivity analysis of water age and temperature for informing salmonid disease management

NASA Astrophysics Data System (ADS)

Javaheri, Amir; Babbar-Sebens, Meghna; Alexander, Julie; Bartholomew, Jerri; Hallett, Sascha

2018-06-01

Many rivers in the Pacific Northwest region of North America are anthropogenically manipulated via dam operations, leading to system-wide impacts on hydrodynamic conditions and aquatic communities. Understanding how dam operations alter abiotic and biotic variables is important for designing management actions. For example, in the Klamath River, dam outflows could be manipulated to alter water age and temperature to reduce risk of parasite infections in salmon by diluting or altering viability of parasite spores. However, sensitivity of water age and temperature to the riverine conditions such as bathymetry can affect outcomes from dam operations. To examine this issue in detail, we conducted a global sensitivity analysis of water age and temperature to a comprehensive set of hydraulics and meteorological parameters in the Klamath River, California, where management of salmonid disease is a high priority. We applied an analysis technique, which combined Latin-hypercube and one-at-a-time sampling methods, and included simulation runs with the hydrodynamic numerical model of the Lower Klamath. We found that flow rate and bottom roughness were the two most important parameters that influence water age. Water temperature was more sensitive to inflow temperature, air temperature, solar radiation, wind speed, flow rate, and wet bulb temperature respectively. Our results are relevant for managers because they provide a framework for predicting how water within 'high infection risk' sections of the river will respond to dam water (low infection risk) input. Moreover, these data will be useful for prioritizing the use of water age (dilution) versus temperature (spore viability) under certain contexts when considering flow manipulation as a method to reduce risk of infection and disease in Klamath River salmon.

Uncertainty analysis for absorbed dose from a brain receptor imaging agent

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

Aydogan, B.; Miller, L.F.; Sparks, R.B.

Absorbed dose estimates are known to contain uncertainties. A recent literature search indicates that prior to this study no rigorous investigation of uncertainty associated with absorbed dose has been undertaken. A method of uncertainty analysis for absorbed dose calculations has been developed and implemented for the brain receptor imaging agent {sup 123}I-IPT. The two major sources of uncertainty considered were the uncertainty associated with the determination of residence time and that associated with the determination of the S values. There are many sources of uncertainty in the determination of the S values, but only the inter-patient organ mass variation wasmore » considered in this work. The absorbed dose uncertainties were determined for lung, liver, heart and brain. Ninety-five percent confidence intervals of the organ absorbed dose distributions for each patient and for a seven-patient population group were determined by the ``Latin Hypercube Sampling`` method. For an individual patient, the upper bound of the 95% confidence interval of the absorbed dose was found to be about 2.5 times larger than the estimated mean absorbed dose. For the seven-patient population the upper bound of the 95% confidence interval of the absorbed dose distribution was around 45% more than the estimated population mean. For example, the 95% confidence interval of the population liver dose distribution was found to be between 1.49E+0.7 Gy/MBq and 4.65E+07 Gy/MBq with a mean of 2.52E+07 Gy/MBq. This study concluded that patients in a population receiving {sup 123}I-IPT could receive absorbed doses as much as twice as large as the standard estimated absorbed dose due to these uncertainties.« less

An uncertainty analysis of the hydrogen source term for a station blackout accident in Sequoyah using MELCOR 1.8.5

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

Gauntt, Randall O.; Bixler, Nathan E.; Wagner, Kenneth Charles

2014-03-01

A methodology for using the MELCOR code with the Latin Hypercube Sampling method was developed to estimate uncertainty in various predicted quantities such as hydrogen generation or release of fission products under severe accident conditions. In this case, the emphasis was on estimating the range of hydrogen sources in station blackout conditions in the Sequoyah Ice Condenser plant, taking into account uncertainties in the modeled physics known to affect hydrogen generation. The method uses user-specified likelihood distributions for uncertain model parameters, which may include uncertainties of a stochastic nature, to produce a collection of code calculations, or realizations, characterizing themore » range of possible outcomes. Forty MELCOR code realizations of Sequoyah were conducted that included 10 uncertain parameters, producing a range of in-vessel hydrogen quantities. The range of total hydrogen produced was approximately 583kg 131kg. Sensitivity analyses revealed expected trends with respected to the parameters of greatest importance, however, considerable scatter in results when plotted against any of the uncertain parameters was observed, with no parameter manifesting dominant effects on hydrogen generation. It is concluded that, with respect to the physics parameters investigated, in order to further reduce predicted hydrogen uncertainty, it would be necessary to reduce all physics parameter uncertainties similarly, bearing in mind that some parameters are inherently uncertain within a range. It is suspected that some residual uncertainty associated with modeling complex, coupled and synergistic phenomena, is an inherent aspect of complex systems and cannot be reduced to point value estimates. The probabilistic analyses such as the one demonstrated in this work are important to properly characterize response of complex systems such as severe accident progression in nuclear power plants.« less

Estimated Under-Five Deaths Associated with Poor-Quality Antimalarials in Sub-Saharan Africa

PubMed Central

Renschler, John P.; Walters, Kelsey M.; Newton, Paul N.; Laxminarayan, Ramanan

2015-01-01

Many antimalarials sold in sub-Saharan Africa are poor-quality (falsified, substandard, or degraded), and the burden of disease caused by this problem is inadequately quantified. In this article, we estimate the number of under-five deaths caused by ineffective treatment of malaria associated with consumption of poor-quality antimalarials in 39 sub-Saharan countries. Using Latin hypercube sampling our estimates were calculated as the product of the number of private sector antimalarials consumed by malaria-positive children in 2013; the proportion of private sector antimalarials consumed that were of poor-quality; and the case fatality rate (CFR) of under-five malaria-positive children who did not receive appropriate treatment. An estimated 122,350 (interquartile range [IQR]: 91,577–154,736) under-five malaria deaths were associated with consumption of poor-quality antimalarials, representing 3.75% (IQR: 2.81–4.75%) of all under-five deaths in our sample of 39 countries. There is considerable uncertainty surrounding our results because of gaps in data on case fatality rates and prevalence of poor-quality antimalarials. Our analysis highlights the need for further investigation into the distribution of poor-quality antimalarials and the need for stronger surveillance and regulatory efforts to prevent the sale of poor-quality antimalarials. PMID:25897068

Integration of tools for the Design and Assessment of High-Performance, Highly Reliable Computing Systems (DAHPHRS), phase 1

NASA Technical Reports Server (NTRS)

Scheper, C.; Baker, R.; Frank, G.; Yalamanchili, S.; Gray, G.

1992-01-01

Systems for Space Defense Initiative (SDI) space applications typically require both high performance and very high reliability. These requirements present the systems engineer evaluating such systems with the extremely difficult problem of conducting performance and reliability trade-offs over large design spaces. A controlled development process supported by appropriate automated tools must be used to assure that the system will meet design objectives. This report describes an investigation of methods, tools, and techniques necessary to support performance and reliability modeling for SDI systems development. Models of the JPL Hypercubes, the Encore Multimax, and the C.S. Draper Lab Fault-Tolerant Parallel Processor (FTPP) parallel-computing architectures using candidate SDI weapons-to-target assignment algorithms as workloads were built and analyzed as a means of identifying the necessary system models, how the models interact, and what experiments and analyses should be performed. As a result of this effort, weaknesses in the existing methods and tools were revealed and capabilities that will be required for both individual tools and an integrated toolset were identified.

SPOTting model parameters using a ready-made Python package

NASA Astrophysics Data System (ADS)

Houska, Tobias; Kraft, Philipp; Breuer, Lutz

2015-04-01

The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for optimization methods. Here we see simple algorithms like the MCMC struggling to find the global optimum of the function, while algorithms like SCE-UA and DE-MCZ show their strengths. Thirdly, we apply an uncertainty analysis of a one-dimensional physically based hydrological model build with the Catchment Modelling Framework (CMF). The model is driven by meteorological and groundwater data from a Free Air Carbon Enrichment (FACE) experiment in Linden (Hesse, Germany). Simulation results are evaluated with measured soil moisture data. We search for optimal parameter sets of the van Genuchten-Mualem function and find different equally optimal solutions with some of the algorithms. The case studies reveal that the implemented SPOT methods work sufficiently well. They further show the benefit of having one tool at hand that includes a number of parameter search methods, likelihood functions and a priori parameter distributions within one platform independent package.

A unified model of the standard genetic code.

PubMed

José, Marco V; Zamudio, Gabriel S; Morgado, Eberto R

2017-03-01

The Rodin-Ohno (RO) and the Delarue models divide the table of the genetic code into two classes of aminoacyl-tRNA synthetases (aaRSs I and II) with recognition from the minor or major groove sides of the tRNA acceptor stem, respectively. These models are asymmetric but they are biologically meaningful. On the other hand, the standard genetic code (SGC) can be derived from the primeval RNY code (R stands for purines, Y for pyrimidines and N any of them). In this work, the RO-model is derived by means of group actions, namely, symmetries represented by automorphisms, assuming that the SGC originated from a primeval RNY code. It turns out that the RO-model is symmetric in a six-dimensional (6D) hypercube. Conversely, using the same automorphisms, we show that the RO-model can lead to the SGC. In addition, the asymmetric Delarue model becomes symmetric by means of quotient group operations. We formulate isometric functions that convert the class aaRS I into the class aaRS II and vice versa. We show that the four polar requirement categories display a symmetrical arrangement in our 6D hypercube. Altogether these results cannot be attained, neither in two nor in three dimensions. We discuss the present unified 6D algebraic model, which is compatible with both the SGC (based upon the primeval RNY code) and the RO-model.

Optimizing Radiometric Processing and Feature Extraction of Drone Based Hyperspectral Frame Format Imagery for Estimation of Yield Quantity and Quality of a Grass Sward

NASA Astrophysics Data System (ADS)

Näsi, R.; Viljanen, N.; Oliveira, R.; Kaivosoja, J.; Niemeläinen, O.; Hakala, T.; Markelin, L.; Nezami, S.; Suomalainen, J.; Honkavaara, E.

2018-04-01

Light-weight 2D format hyperspectral imagers operable from unmanned aerial vehicles (UAV) have become common in various remote sensing tasks in recent years. Using these technologies, the area of interest is covered by multiple overlapping hypercubes, in other words multiview hyperspectral photogrammetric imagery, and each object point appears in many, even tens of individual hypercubes. The common practice is to calculate hyperspectral orthomosaics utilizing only the most nadir areas of the images. However, the redundancy of the data gives potential for much more versatile and thorough feature extraction. We investigated various options of extracting spectral features in the grass sward quantity evaluation task. In addition to the various sets of spectral features, we used photogrammetry-based ultra-high density point clouds to extract features describing the canopy 3D structure. Machine learning technique based on the Random Forest algorithm was used to estimate the fresh biomass. Results showed high accuracies for all investigated features sets. The estimation results using multiview data provided approximately 10 % better results than the most nadir orthophotos. The utilization of the photogrammetric 3D features improved estimation accuracy by approximately 40 % compared to approaches where only spectral features were applied. The best estimation RMSE of 239 kg/ha (6.0 %) was obtained with multiview anisotropy corrected data set and the 3D features.

A multi-satellite orbit determination problem in a parallel processing environment

NASA Technical Reports Server (NTRS)

Deakyne, M. S.; Anderle, R. J.

1988-01-01

The Engineering Orbit Analysis Unit at GE Valley Forge used an Intel Hypercube Parallel Processor to investigate the performance and gain experience of parallel processors with a multi-satellite orbit determination problem. A general study was selected in which major blocks of computation for the multi-satellite orbit computations were used as units to be assigned to the various processors on the Hypercube. Problems encountered or successes achieved in addressing the orbit determination problem would be more likely to be transferable to other parallel processors. The prime objective was to study the algorithm to allow processing of observations later in time than those employed in the state update. Expertise in ephemeris determination was exploited in addressing these problems and the facility used to bring a realism to the study which would highlight the problems which may not otherwise be anticipated. Secondary objectives were to gain experience of a non-trivial problem in a parallel processor environment, to explore the necessary interplay of serial and parallel sections of the algorithm in terms of timing studies, to explore the granularity (coarse vs. fine grain) to discover the granularity limit above which there would be a risk of starvation where the majority of nodes would be idle or under the limit where the overhead associated with splitting the problem may require more work and communication time than is useful.

Assessing Degree of Susceptibility to Landslide Hazard

NASA Astrophysics Data System (ADS)

Sheridan, M. F.; Cordoba, G. A.; Delgado, H.; Stefanescu, R.

2013-05-01

The modeling of hazardous mass flows, both dry and water saturated, is currently an area of active research and several stable models have now emerged that have differing degrees of physical and mathematical fidelity. Models based on the early work of Savage and Hutter (1989) assume that very large dense granular flows could be modeled as incompressible continua governed by a Coulomb failure criterion. Based on this concept, Patra et al. (2005) developed a code for dry avalanches, which proposes a thin layer mathematical model similar to shallow-water equations. This concept was implemented in the widely-used TITAN2D program, which integrates the shock-capturing Godunov solution methodology for the equation system. We propose a method to assess the susceptibility of specific locations susceptible to landslides following heavy tephra fall using the TIATN2D code. Successful application requires that the range of several uncertainties must be framed in the selection of model input data: 1) initial conditions, like volume and location of origin of the landslide, 2) bed and internal friction parameters and 3) digital elevation model (DEM) uncertainties. Among the possible ways of coping with these uncertainties, we chose to use Latin Hypercube Sampling (LHS). This statistical technique reduces a computationally intractable problem to such an extent that is it possible to apply it, even with current personal computers. LHS requires that there is only one sample in each row and each column of the sampling matrix, where each row (multi-dimensional) corresponds to each uncertainty. LHS requires less than 10% of the sample runs needed by Monte Carlo approaches to achieve a stable solution. In our application LHS output provides model sampling for 4 input parameters: initial random volumes, UTM location (x and y), and bed friction. We developed a simple Octave script to link the output of LHS with TITAN2D. In this way, TITAN2D can run several times with successively different initial conditions provided by the LHC routine. Finally the set of results from TITAN2D are computed to obtain the distribution of maximum exceedance probability given that a landslide occurs at a place of interest. We apply this method to find sectors least prone to be affected by landslides, in a region along the Panamerican Highway in the southern part of Colombia. The goal of such a study is to provide decision makers to improve their assessments regarding permissions for development along the highway.

Probabilistic Analysis and Density Parameter Estimation Within Nessus

NASA Astrophysics Data System (ADS)

Godines, Cody R.; Manteufel, Randall D.

2002-12-01

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Probabilistic Analysis and Density Parameter Estimation Within Nessus

NASA Technical Reports Server (NTRS)

Godines, Cody R.; Manteufel, Randall D.; Chamis, Christos C. (Technical Monitor)

2002-01-01

This NASA educational grant has the goal of promoting probabilistic analysis methods to undergraduate and graduate UTSA engineering students. Two undergraduate-level and one graduate-level course were offered at UTSA providing a large number of students exposure to and experience in probabilistic techniques. The grant provided two research engineers from Southwest Research Institute the opportunity to teach these courses at UTSA, thereby exposing a large number of students to practical applications of probabilistic methods and state-of-the-art computational methods. In classroom activities, students were introduced to the NESSUS computer program, which embodies many algorithms in probabilistic simulation and reliability analysis. Because the NESSUS program is used at UTSA in both student research projects and selected courses, a student version of a NESSUS manual has been revised and improved, with additional example problems being added to expand the scope of the example application problems. This report documents two research accomplishments in the integration of a new sampling algorithm into NESSUS and in the testing of the new algorithm. The new Latin Hypercube Sampling (LHS) subroutines use the latest NESSUS input file format and specific files for writing output. The LHS subroutines are called out early in the program so that no unnecessary calculations are performed. Proper correlation between sets of multidimensional coordinates can be obtained by using NESSUS' LHS capabilities. Finally, two types of correlation are written to the appropriate output file. The program enhancement was tested by repeatedly estimating the mean, standard deviation, and 99th percentile of four different responses using Monte Carlo (MC) and LHS. These test cases, put forth by the Society of Automotive Engineers, are used to compare probabilistic methods. For all test cases, it is shown that LHS has a lower estimation error than MC when used to estimate the mean, standard deviation, and 99th percentile of the four responses at the 50 percent confidence level and using the same number of response evaluations for each method. In addition, LHS requires fewer calculations than MC in order to be 99.7 percent confident that a single mean, standard deviation, or 99th percentile estimate will be within at most 3 percent of the true value of the each parameter. Again, this is shown for all of the test cases studied. For that reason it can be said that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ; furthermore, the newest LHS module is a valuable new enhancement of the program.

Global sensitivity analysis in wind energy assessment

NASA Astrophysics Data System (ADS)

Tsvetkova, O.; Ouarda, T. B.

2012-12-01

Wind energy is one of the most promising renewable energy sources. Nevertheless, it is not yet a common source of energy, although there is enough wind potential to supply world's energy demand. One of the most prominent obstacles on the way of employing wind energy is the uncertainty associated with wind energy assessment. Global sensitivity analysis (SA) studies how the variation of input parameters in an abstract model effects the variation of the variable of interest or the output variable. It also provides ways to calculate explicit measures of importance of input variables (first order and total effect sensitivity indices) in regard to influence on the variation of the output variable. Two methods of determining the above mentioned indices were applied and compared: the brute force method and the best practice estimation procedure In this study a methodology for conducting global SA of wind energy assessment at a planning stage is proposed. Three sampling strategies which are a part of SA procedure were compared: sampling based on Sobol' sequences (SBSS), Latin hypercube sampling (LHS) and pseudo-random sampling (PRS). A case study of Masdar City, a showcase of sustainable living in the UAE, is used to exemplify application of the proposed methodology. Sources of uncertainty in wind energy assessment are very diverse. In the case study the following were identified as uncertain input parameters: the Weibull shape parameter, the Weibull scale parameter, availability of a wind turbine, lifetime of a turbine, air density, electrical losses, blade losses, ineffective time losses. Ineffective time losses are defined as losses during the time when the actual wind speed is lower than the cut-in speed or higher than the cut-out speed. The output variable in the case study is the lifetime energy production. Most influential factors for lifetime energy production are identified with the ranking of the total effect sensitivity indices. The results of the present research show that the brute force method is best for wind assessment purpose, SBSS outperforms other sampling strategies in the majority of cases. The results indicate that the Weibull scale parameter, turbine lifetime and Weibull shape parameter are the three most influential variables in the case study setting. The following conclusions can be drawn from these results: 1) SBSS should be recommended for use in Monte Carlo experiments, 2) The brute force method should be recommended for conducting sensitivity analysis in wind resource assessment, and 3) Little variation in the Weibull scale causes significant variation in energy production. The presence of the two distribution parameters in the top three influential variables (the Weibull shape and scale) emphasizes the importance of accuracy of (a) choosing the distribution to model wind regime at a site and (b) estimating probability distribution parameters. This can be labeled as the most important conclusion of this research because it opens a field for further research, which the authors see could change the wind energy field tremendously.

Implementation of an Object-Oriented Flight Simulator D.C. Electrical System on a Hypercube Architecture

DTIC Science & Technology

1991-12-01

abstract data type is, what an object-oriented design is and how to apply "software engineering" principles to the design of both of them. I owe a great... Program (ASVP), a research and development effort by two aerospace contractors to redesign and implement subsets of two existing flight simulators in...effort addresses how to implement a simulator designed using the SEI OOD Paradigm on a distributed, parallel, multiple instruction, multiple data (MIMD

A Portable Parallel Implementation of the U.S. Navy Layered Ocean Model

DTIC Science & Technology

1995-01-01

Wallcraft, PhD (I.C. 1981) Planning Systems Inc. & P. R. Moore, PhD (Camb. 1971) IC Dept. Math. DR Moore 1° Encontro de Metodos Numericos...Kendall Square, Hypercube, D R Moore 1 ° Encontro de Metodos Numericos para Equacöes de Derivadas Parciais A. J. Wallcraft IC Mathematics...chips: Chips Machine DEC Alpha CrayT3D/E SUN Sparc Fujitsu AP1000 Intel 860 Paragon D R Moore 1° Encontro de Metodos Numericos para Equacöes

On k-ary n-cubes: Theory and applications

NASA Technical Reports Server (NTRS)

Mao, Weizhen; Nicol, David M.

1994-01-01

Many parallel processing networks can be viewed as graphs called k-ary n-cubes, whose special cases include rings, hypercubes and toruses. In this paper, combinatorial properties of k-ary n-cubes are explored. In particular, the problem of characterizing the subgraph of a given number of nodes with the maximum edge count is studied. These theoretical results are then used to compute a lower bounding function in branch-and-bound partitioning algorithms and to establish the optimality of some irregular partitions.

Synchronizability of random rectangular graphs

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

Estrada, Ernesto, E-mail: ernesto.estrada@strath.ac.uk; Chen, Guanrong

2015-08-15

Random rectangular graphs (RRGs) represent a generalization of the random geometric graphs in which the nodes are embedded into hyperrectangles instead of on hypercubes. The synchronizability of RRG model is studied. Both upper and lower bounds of the eigenratio of the network Laplacian matrix are determined analytically. It is proven that as the rectangular network is more elongated, the network becomes harder to synchronize. The synchronization processing behavior of a RRG network of chaotic Lorenz system nodes is numerically investigated, showing complete consistence with the theoretical results.

Statistical uncertainty analysis applied to the DRAGONv4 code lattice calculations and based on JENDL-4 covariance data

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

Hernandez-Solis, A.; Demaziere, C.; Ekberg, C.

2012-07-01

In this paper, multi-group microscopic cross-section uncertainty is propagated through the DRAGON (Version 4) lattice code, in order to perform uncertainty analysis on k{infinity} and 2-group homogenized macroscopic cross-sections predictions. A statistical methodology is employed for such purposes, where cross-sections of certain isotopes of various elements belonging to the 172 groups DRAGLIB library format, are considered as normal random variables. This library is based on JENDL-4 data, because JENDL-4 contains the largest amount of isotopic covariance matrixes among the different major nuclear data libraries. The aim is to propagate multi-group nuclide uncertainty by running the DRAGONv4 code 500 times, andmore » to assess the output uncertainty of a test case corresponding to a 17 x 17 PWR fuel assembly segment without poison. The chosen sampling strategy for the current study is Latin Hypercube Sampling (LHS). The quasi-random LHS allows a much better coverage of the input uncertainties than simple random sampling (SRS) because it densely stratifies across the range of each input probability distribution. Output uncertainty assessment is based on the tolerance limits concept, where the sample formed by the code calculations infers to cover 95% of the output population with at least a 95% of confidence. This analysis is the first attempt to propagate parameter uncertainties of modern multi-group libraries, which are used to feed advanced lattice codes that perform state of the art resonant self-shielding calculations such as DRAGONv4. (authors)« less

Three-particle annihilation in a 2D heterostructure revealed through data-hypercubic photoresponse microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gabor, Nathaniel M.

2017-05-01

Van de Waals (vdW) heterostructures - which consist of precisely assembled atomically thin electronic materials - exhibit unusual quantum behavior. These quantum materials-by-design are of fundamental interest in basic scientific research and hold tremendous potential in advanced technological applications. Problematically, the fundamental optoelectronic response in these heterostructures is difficult to access using the standard techniques within the traditions of materials science and condensed matter physics. In the standard approach, characterization is based on the measurement of a small amount of one-dimensional data, which is used to gain a precise picture of the material properties of the sample. However, these techniques are fundamentally lacking in describing the complex interdependency of experimental degrees of freedom in vdW heterostructures. In this talk, I will present our recent experiments that utilize a highly data-intensive approach to gain deep understanding of the infrared photoresponse in vdW heterostructure photodetectors. These measurements, which combine state-of-the-art data analytics and measurement design with fundamentally new device structures and experimental parameters, give a clear picture of electron-hole pair interactions at ultrafast time scales.

Optimized Reduction of Unsteady Radial Forces in a Singlechannel Pump for Wastewater Treatment

NASA Astrophysics Data System (ADS)

Kim, Jin-Hyuk; Cho, Bo-Min; Choi, Young-Seok; Lee, Kyoung-Yong; Peck, Jong-Hyeon; Kim, Seon-Chang

2016-11-01

A single-channel pump for wastewater treatment was optimized to reduce unsteady radial force sources caused by impeller-volute interactions. The steady and unsteady Reynolds- averaged Navier-Stokes equations using the shear-stress transport turbulence model were discretized by finite volume approximations and solved on tetrahedral grids to analyze the flow in the single-channel pump. The sweep area of radial force during one revolution and the distance of the sweep-area center of mass from the origin were selected as the objective functions; the two design variables were related to the internal flow cross-sectional area of the volute. These objective functions were integrated into one objective function by applying the weighting factor for optimization. Latin hypercube sampling was employed to generate twelve design points within the design space. A response-surface approximation model was constructed as a surrogate model for the objectives, based on the objective function values at the generated design points. The optimized results showed considerable reduction in the unsteady radial force sources in the optimum design, relative to those of the reference design.

Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging.

PubMed

Caporaso, Nicola; Whitworth, Martin B; Grebby, Stephen; Fisk, Ian D

2018-06-01

Hyperspectral imaging (1000-2500 nm) was used for rapid prediction of moisture and total lipid content in intact green coffee beans on a single bean basis. Arabica and Robusta samples from several growing locations were scanned using a "push-broom" system. Hypercubes were segmented to select single beans, and average spectra were measured for each bean. Partial Least Squares regression was used to build quantitative prediction models on single beans (n = 320-350). The models exhibited good performance and acceptable prediction errors of ∼0.28% for moisture and ∼0.89% for lipids. This study represents the first time that HSI-based quantitative prediction models have been developed for coffee, and specifically green coffee beans. In addition, this is the first attempt to build such models using single intact coffee beans. The composition variability between beans was studied, and fat and moisture distribution were visualized within individual coffee beans. This rapid, non-destructive approach could have important applications for research laboratories, breeding programmes, and for rapid screening for industry.

Uncertainty and sensitivity analysis for two-phase flow in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant: Disturbed conditions

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

HELTON,JON CRAIG; BEAN,J.E.; ECONOMY,K.

2000-05-22

Uncertainty and sensitivity analysis results obtained in the 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) are presented for two-phase flow in the vicinity of the repository under disturbed conditions resulting from drilling intrusions. Techniques based on Latin hypercube sampling, examination of scatterplots, stepwise regression analysis, partial correlation analysis and rank transformations are used to investigate brine inflow, gas generation repository pressure, brine saturation and brine and gas outflow. Of the variables under study, repository pressure and brine flow from the repository to the Culebra Dolomite are potentially the most important in PA for the WIPP. Subsequentmore » to a drilling intrusion repository pressure was dominated by borehole permeability and generally below the level (i.e., 8 MPa) that could potentially produce spallings and direct brine releases. Brine flow from the repository to the Culebra Dolomite tended to be small or nonexistent with its occurrence and size also dominated by borehole permeability.« less

A Novel Approach for Determining Source–Receptor Relationships in Model Simulations: A Case Study of Black Carbon Transport in Northern Hemisphere Winter

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

Ma, Po-Lun; Gattiker, J. R.; Liu, Xiaohong

2013-06-27

A Gaussian process (GP) emulator is applied to quantify the contribution of local and remote emissions of black carbon (BC) on the BC concentrations in different regions using a Latin Hypercube sampling strategy for emission perturbations in the offline version of the Community Atmosphere Model Version 5.1 (CAM5) simulations. The source-receptor relationships are computed based on simulations constrained by a standard free-running CAM5 simulation and the ERA-Interim reanalysis product. The analysis demonstrates that the emulator is capable of retrieving the source-receptor relationships based on a small number of CAM5 simulations. Most regions are found susceptible to their local emissions. Themore » emulator also finds that the source-receptor relationships retrieved from the model-driven and the reanalysis-driven simulations are very similar, suggesting that the simulated circulation in CAM5 resembles the assimilated meteorology in ERA-Interim. The robustness of the results provides confidence for applying the emulator to detect dose-response signals in the climate system.« less

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Accounting for uncertainty in model-based prevalence estimation: paratuberculosis control in dairy herds.

PubMed

Davidson, Ross S; McKendrick, Iain J; Wood, Joanna C; Marion, Glenn; Greig, Alistair; Stevenson, Karen; Sharp, Michael; Hutchings, Michael R

2012-09-10

A common approach to the application of epidemiological models is to determine a single (point estimate) parameterisation using the information available in the literature. However, in many cases there is considerable uncertainty about parameter values, reflecting both the incomplete nature of current knowledge and natural variation, for example between farms. Furthermore model outcomes may be highly sensitive to different parameter values. Paratuberculosis is an infection for which many of the key parameter values are poorly understood and highly variable, and for such infections there is a need to develop and apply statistical techniques which make maximal use of available data. A technique based on Latin hypercube sampling combined with a novel reweighting method was developed which enables parameter uncertainty and variability to be incorporated into a model-based framework for estimation of prevalence. The method was evaluated by applying it to a simulation of paratuberculosis in dairy herds which combines a continuous time stochastic algorithm with model features such as within herd variability in disease development and shedding, which have not been previously explored in paratuberculosis models. Generated sample parameter combinations were assigned a weight, determined by quantifying the model's resultant ability to reproduce prevalence data. Once these weights are generated the model can be used to evaluate other scenarios such as control options. To illustrate the utility of this approach these reweighted model outputs were used to compare standard test and cull control strategies both individually and in combination with simple husbandry practices that aim to reduce infection rates. The technique developed has been shown to be applicable to a complex model incorporating realistic control options. For models where parameters are not well known or subject to significant variability, the reweighting scheme allowed estimated distributions of parameter values to be combined with additional sources of information, such as that available from prevalence distributions, resulting in outputs which implicitly handle variation and uncertainty. This methodology allows for more robust predictions from modelling approaches by allowing for parameter uncertainty and combining different sources of information, and is thus expected to be useful in application to a large number of disease systems.

Influence of Population Variation of Physiological Parameters in Computational Models of Space Physiology

NASA Technical Reports Server (NTRS)

Myers, J. G.; Feola, A.; Werner, C.; Nelson, E. S.; Raykin, J.; Samuels, B.; Ethier, C. R.

2016-01-01

The earliest manifestations of Visual Impairment and Intracranial Pressure (VIIP) syndrome become evident after months of spaceflight and include a variety of ophthalmic changes, including posterior globe flattening and distension of the optic nerve sheath. Prevailing evidence links the occurrence of VIIP to the cephalic fluid shift induced by microgravity and the subsequent pressure changes around the optic nerve and eye. Deducing the etiology of VIIP is challenging due to the wide range of physiological parameters that may be influenced by spaceflight and are required to address a realistic spectrum of physiological responses. Here, we report on the application of an efficient approach to interrogating physiological parameter space through computational modeling. Specifically, we assess the influence of uncertainty in input parameters for two models of VIIP syndrome: a lumped-parameter model (LPM) of the cardiovascular and central nervous systems, and a finite-element model (FEM) of the posterior eye, optic nerve head (ONH) and optic nerve sheath. Methods: To investigate the parameter space in each model, we employed Latin hypercube sampling partial rank correlation coefficient (LHSPRCC) strategies. LHS techniques outperform Monte Carlo approaches by enforcing efficient sampling across the entire range of all parameters. The PRCC method estimates the sensitivity of model outputs to these parameters while adjusting for the linear effects of all other inputs. The LPM analysis addressed uncertainties in 42 physiological parameters, such as initial compartmental volume and nominal compartment percentage of total cardiac output in the supine state, while the FEM evaluated the effects on biomechanical strain from uncertainties in 23 material and pressure parameters for the ocular anatomy. Results and Conclusion: The LPM analysis identified several key factors including high sensitivity to the initial fluid distribution. The FEM study found that intraocular pressure and intracranial pressure had dominant impact on the peak strains in the ONH and retro-laminar optic nerve, respectively; optic nerve and lamina cribrosa stiffness were also important. This investigation illustrates the ability of LHSPRCC to identify the most influential physiological parameters, which must therefore be well-characterized to produce the most accurate numerical results.

Towards systematic evaluation of crop model outputs for global land-use models

NASA Astrophysics Data System (ADS)

Leclere, David; Azevedo, Ligia B.; Skalský, Rastislav; Balkovič, Juraj; Havlík, Petr

2016-04-01

Land provides vital socioeconomic resources to the society, however at the cost of large environmental degradations. Global integrated models combining high resolution global gridded crop models (GGCMs) and global economic models (GEMs) are increasingly being used to inform sustainable solution for agricultural land-use. However, little effort has yet been done to evaluate and compare the accuracy of GGCM outputs. In addition, GGCM datasets require a large amount of parameters whose values and their variability across space are weakly constrained: increasing the accuracy of such dataset has a very high computing cost. Innovative evaluation methods are required both to ground credibility to the global integrated models, and to allow efficient parameter specification of GGCMs. We propose an evaluation strategy for GGCM datasets in the perspective of use in GEMs, illustrated with preliminary results from a novel dataset (the Hypercube) generated by the EPIC GGCM and used in the GLOBIOM land use GEM to inform on present-day crop yield, water and nutrient input needs for 16 crops x 15 management intensities, at a spatial resolution of 5 arc-minutes. We adopt the following principle: evaluation should provide a transparent diagnosis of model adequacy for its intended use. We briefly describe how the Hypercube data is generated and how it articulates with GLOBIOM in order to transparently identify the performances to be evaluated, as well as the main assumptions and data processing involved. Expected performances include adequately representing the sub-national heterogeneity in crop yield and input needs: i) in space, ii) across crop species, and iii) across management intensities. We will present and discuss measures of these expected performances and weight the relative contribution of crop model, input data and data processing steps in performances. We will also compare obtained yield gaps and main yield-limiting factors against the M3 dataset. Next steps include iterative improvement of parameter assumptions and evaluation of implications of GGCM performances for intended use in the IIASA EPIC-GLOBIOM model cluster. Our approach helps targeting future efforts at improving GGCM accuracy and would achieve highest efficiency if combined with traditional field-scale evaluation and sensitivity analysis.

Developing a Screening Algorithm for Type II Diabetes Mellitus in the Resource-Limited Setting of Rural Tanzania.

PubMed

West, Caroline; Ploth, David; Fonner, Virginia; Mbwambo, Jessie; Fredrick, Francis; Sweat, Michael

2016-04-01

Noncommunicable diseases are on pace to outnumber infectious disease as the leading cause of death in sub-Saharan Africa, yet many questions remain unanswered with concern toward effective methods of screening for type II diabetes mellitus (DM) in this resource-limited setting. We aim to design a screening algorithm for type II DM that optimizes sensitivity and specificity of identifying individuals with undiagnosed DM, as well as affordability to health systems and individuals. Baseline demographic and clinical data, including hemoglobin A1c (HbA1c), were collected from 713 participants using probability sampling of the general population. We used these data, along with model parameters obtained from the literature, to mathematically model 8 purposed DM screening algorithms, while optimizing the sensitivity and specificity using Monte Carlo and Latin Hypercube simulation. An algorithm that combines risk assessment and measurement of fasting blood glucose was found to be superior for the most resource-limited settings (sensitivity 68%, sensitivity 99% and cost per patient having DM identified as $2.94). Incorporating HbA1c testing improves the sensitivity to 75.62%, but raises the cost per DM case identified to $6.04. The preferred algorithms are heavily biased to diagnose those with more severe cases of DM. Using basic risk assessment tools and fasting blood sugar testing in lieu of HbA1c testing in resource-limited settings could allow for significantly more feasible DM screening programs with reasonable sensitivity and specificity. Copyright © 2016 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Sensitivity Analysis of the Sheet Metal Stamping Processes Based on Inverse Finite Element Modeling and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Yu, Maolin; Du, R.

2005-08-01

Sheet metal stamping is one of the most commonly used manufacturing processes, and hence, much research has been carried for economic gain. Searching through the literatures, however, it is found that there are still a lots of problems unsolved. For example, it is well known that for a same press, same workpiece material, and same set of die, the product quality may vary owing to a number of factors, such as the inhomogeneous of the workpice material, the loading error, the lubrication, and etc. Presently, few seem able to predict the quality variation, not to mention what contribute to the quality variation. As a result, trial-and-error is still needed in the shop floor, causing additional cost and time delay. This paper introduces a new approach to predict the product quality variation and identify the sensitive design / process parameters. The new approach is based on a combination of inverse Finite Element Modeling (FEM) and Monte Carlo Simulation (more specifically, the Latin Hypercube Sampling (LHS) approach). With an acceptable accuracy, the inverse FEM (also called one-step FEM) requires much less computation load than that of the usual incremental FEM and hence, can be used to predict the quality variations under various conditions. LHS is a statistical method, through which the sensitivity analysis can be carried out. The result of the sensitivity analysis has clear physical meaning and can be used to optimize the die design and / or the process design. Two simulation examples are presented including drawing a rectangular box and drawing a two-step rectangular box.

Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

2009-01-01

The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

Evaluation of incremental reactivity and its uncertainty in Southern California.

PubMed

Martien, Philip T; Harley, Robert A; Milford, Jana B; Russell, Armistead G

2003-04-15

The incremental reactivity (IR) and relative incremental reactivity (RIR) of carbon monoxide and 30 individual volatile organic compounds (VOC) were estimated for the South Coast Air Basin using two photochemical air quality models: a 3-D, grid-based model and a vertically resolved trajectory model. Both models include an extended version of the SAPRC99 chemical mechanism. For the 3-D modeling, the decoupled direct method (DDM-3D) was used to assess reactivities. The trajectory model was applied to estimate uncertainties in reactivities due to uncertainties in chemical rate parameters, deposition parameters, and emission rates using Monte Carlo analysis with Latin hypercube sampling. For most VOC, RIRs were found to be consistent in rankings with those produced by Carter using a box model. However, 3-D simulations show that coastal regions, upwind of most of the emissions, have comparatively low IR but higher RIR than predicted by box models for C4-C5 alkenes and carbonyls that initiate the production of HOx radicals. Biogenic VOC emissions were found to have a lower RIR than predicted by box model estimates, because emissions of these VOC were mostly downwind of the areas of primary ozone production. Uncertainties in RIR of individual VOC were found to be dominated by uncertainties in the rate parameters of their primary oxidation reactions. The coefficient of variation (COV) of most RIR values ranged from 20% to 30%, whereas the COV of absolute incremental reactivity ranged from about 30% to 40%. In general, uncertainty and variability both decreased when relative rather than absolute reactivity metrics were used.

Tensor form factor for the D → π(K) transitions with Twisted Mass fermions.

NASA Astrophysics Data System (ADS)

Lubicz, Vittorio; Riggio, Lorenzo; Salerno, Giorgio; Simula, Silvano; Tarantino, Cecilia

2018-03-01

We present a preliminary lattice calculation of the D → π and D → K tensor form factors fT (q2) as a function of the squared 4-momentum transfer q2. ETMC recently computed the vector and scalar form factors f+(q2) and f0(q2) describing D → π(K)lv semileptonic decays analyzing the vector current and the scalar density. The study of the weak tensor current, which is directly related to the tensor form factor, completes the set of hadronic matrix element regulating the transition between these two pseudoscalar mesons within and beyond the Standard Model where a non-zero tensor coupling is possible. Our analysis is based on the gauge configurations produced by the European Twisted Mass Collaboration with Nf = 2 + 1 + 1 flavors of dynamical quarks. We simulated at three different values of the lattice spacing and with pion masses as small as 210 MeV and with the valence heavy quark in the mass range from ≃ 0.7 mc to ≃ 1.2mc. The matrix element of the tensor current are determined for a plethora of kinematical conditions in which parent and child mesons are either moving or at rest. As for the vector and scalar form factors, Lorentz symmetry breaking due to hypercubic effects is clearly observed in the data. We will present preliminary results on the removal of such hypercubic lattice effects.

ProperCAD: A portable object-oriented parallel environment for VLSI CAD

NASA Technical Reports Server (NTRS)

Ramkumar, Balkrishna; Banerjee, Prithviraj

1993-01-01

Most parallel algorithms for VLSI CAD proposed to date have one important drawback: they work efficiently only on machines that they were designed for. As a result, algorithms designed to date are dependent on the architecture for which they are developed and do not port easily to other parallel architectures. A new project under way to address this problem is described. A Portable object-oriented parallel environment for CAD algorithms (ProperCAD) is being developed. The objectives of this research are (1) to develop new parallel algorithms that run in a portable object-oriented environment (CAD algorithms using a general purpose platform for portable parallel programming called CARM is being developed and a C++ environment that is truly object-oriented and specialized for CAD applications is also being developed); and (2) to design the parallel algorithms around a good sequential algorithm with a well-defined parallel-sequential interface (permitting the parallel algorithm to benefit from future developments in sequential algorithms). One CAD application that has been implemented as part of the ProperCAD project, flat VLSI circuit extraction, is described. The algorithm, its implementation, and its performance on a range of parallel machines are discussed in detail. It currently runs on an Encore Multimax, a Sequent Symmetry, Intel iPSC/2 and i860 hypercubes, a NCUBE 2 hypercube, and a network of Sun Sparc workstations. Performance data for other applications that were developed are provided: namely test pattern generation for sequential circuits, parallel logic synthesis, and standard cell placement.

Genome-scale fluxes predicted under the guidance of enzyme abundance using a novel hyper-cube shrink algorithm.

PubMed

Xie, Zhengwei; Zhang, Tianyu; Ouyang, Qi

2018-02-01

One of the long-expected goals of genome-scale metabolic modelling is to evaluate the influence of the perturbed enzymes on flux distribution. Both ordinary differential equation (ODE) models and constraint-based models, like Flux balance analysis (FBA), lack the capacity to perform metabolic control analysis (MCA) for large-scale networks. In this study, we developed a hyper-cube shrink algorithm (HCSA) to incorporate the enzymatic properties into the FBA model by introducing a pseudo reaction V constrained by enzymatic parameters. Our algorithm uses the enzymatic information quantitatively rather than qualitatively. We first demonstrate the concept by applying HCSA to a simple three-node network, whereby we obtained a good correlation between flux and enzyme abundance. We then validate its prediction by comparison with ODE and with a synthetic network producing voilacein and analogues in Saccharomyces cerevisiae. We show that HCSA can mimic the state-state results of ODE. Finally, we show its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast. We show the ability of HCSA to operate without biomass flux and perform MCA to determine rate-limiting reactions. Algorithm was implemented by Matlab and C ++. The code is available at https://github.com/kekegg/HCSA. xiezhengwei@hsc.pku.edu.cn or qi@pku.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Modeling Semantic Emotion Space Using a 3D Hypercube-Projection: An Innovative Analytical Approach for the Psychology of Emotions

PubMed Central

Trnka, Radek; Lačev, Alek; Balcar, Karel; Kuška, Martin; Tavel, Peter

2016-01-01

The widely accepted two-dimensional circumplex model of emotions posits that most instances of human emotional experience can be understood within the two general dimensions of valence and activation. Currently, this model is facing some criticism, because complex emotions in particular are hard to define within only these two general dimensions. The present theory-driven study introduces an innovative analytical approach working in a way other than the conventional, two-dimensional paradigm. The main goal was to map and project semantic emotion space in terms of mutual positions of various emotion prototypical categories. Participants (N = 187; 54.5% females) judged 16 discrete emotions in terms of valence, intensity, controllability and utility. The results revealed that these four dimensional input measures were uncorrelated. This implies that valence, intensity, controllability and utility represented clearly different qualities of discrete emotions in the judgments of the participants. Based on this data, we constructed a 3D hypercube-projection and compared it with various two-dimensional projections. This contrasting enabled us to detect several sources of bias when working with the traditional, two-dimensional analytical approach. Contrasting two-dimensional and three-dimensional projections revealed that the 2D models provided biased insights about how emotions are conceptually related to one another along multiple dimensions. The results of the present study point out the reductionist nature of the two-dimensional paradigm in the psychological theory of emotions and challenge the widely accepted circumplex model. PMID:27148130

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

Multiobjective robust design of the double wishbone suspension system based on particle swarm optimization.

PubMed

Cheng, Xianfu; Lin, Yuqun

2014-01-01

The performance of the suspension system is one of the most important factors in the vehicle design. For the double wishbone suspension system, the conventional deterministic optimization does not consider any deviations of design parameters, so design sensitivity analysis and robust optimization design are proposed. In this study, the design parameters of the robust optimization are the positions of the key points, and the random factors are the uncertainties in manufacturing. A simplified model of the double wishbone suspension is established by software ADAMS. The sensitivity analysis is utilized to determine main design variables. Then, the simulation experiment is arranged and the Latin hypercube design is adopted to find the initial points. The Kriging model is employed for fitting the mean and variance of the quality characteristics according to the simulation results. Further, a particle swarm optimization method based on simple PSO is applied and the tradeoff between the mean and deviation of performance is made to solve the robust optimization problem of the double wishbone suspension system.

A concurrent distributed system for aircraft tactical decision generation

NASA Technical Reports Server (NTRS)

Mcmanus, John W.

1990-01-01

A research program investigating the use of AI techniques to aid in the development of a tactical decision generator (TDG) for within visual range (WVR) air combat engagements is discussed. The application of AI programming and problem-solving methods in the development and implementation of a concurrent version of the computerized logic for air-to-air warfare simulations (CLAWS) program, a second-generation TDG, is presented. Concurrent computing environments and programming approaches are discussed, and the design and performance of prototype concurrent TDG system (Cube CLAWS) are presented. It is concluded that the Cube CLAWS has provided a useful testbed to evaluate the development of a distributed blackboard system. The project has shown that the complexity of developing specialized software on a distributed, message-passing architecture such as the Hypercube is not overwhelming, and that reasonable speedups and processor efficiency can be achieved by a distributed blackboard system. The project has also highlighted some of the costs of using a distributed approach to designing a blackboard system.

Time warp operating system version 2.7 internals manual

NASA Technical Reports Server (NTRS)

1992-01-01

The Time Warp Operating System (TWOS) is an implementation of the Time Warp synchronization method proposed by David Jefferson. In addition, it serves as an actual platform for running discrete event simulations. The code comprising TWOS can be divided into several different sections. TWOS typically relies on an existing operating system to furnish some very basic services. This existing operating system is referred to as the Base OS. The existing operating system varies depending on the hardware TWOS is running on. It is Unix on the Sun workstations, Chrysalis or Mach on the Butterfly, and Mercury on the Mark 3 Hypercube. The base OS could be an entirely new operating system, written to meet the special needs of TWOS, but, to this point, existing systems have been used instead. The base OS's used for TWOS on various platforms are not discussed in detail in this manual, as they are well covered in their own manuals. Appendix G discusses the interface between one such OS, Mach, and TWOS.

Renormalization of minimally doubled fermions

NASA Astrophysics Data System (ADS)

Capitani, Stefano; Creutz, Michael; Weber, Johannes; Wittig, Hartmut

2010-09-01

We investigate the renormalization properties of minimally doubled fermions, at one loop in perturbation theory. Our study is based on the two particular realizations of Boriçi-Creutz and Karsten-Wilczek. A common feature of both formulations is the breaking of hyper-cubic symmetry, which requires that the lattice actions are supplemented by suitable counterterms. We show that three counterterms are required in each case and determine their coefficients to one loop in perturbation theory. For both actions we compute the vacuum polarization of the gluon. It is shown that no power divergences appear and that all contributions which arise from the breaking of Lorentz symmetry are cancelled by the counterterms. We also derive the conserved vector and axial-vector currents for Karsten-Wilczek fermions. Like in the case of the previously studied Boriçi-Creutz action, one obtains simple expressions, involving only nearest-neighbour sites. We suggest methods how to fix the coefficients of the counterterms non-perturbatively and discuss the implications of our findings for practical simulations.

Preconditioned implicit solvers for the Navier-Stokes equations on distributed-memory machines

NASA Technical Reports Server (NTRS)

Ajmani, Kumud; Liou, Meng-Sing; Dyson, Rodger W.

1994-01-01

The GMRES method is parallelized, and combined with local preconditioning to construct an implicit parallel solver to obtain steady-state solutions for the Navier-Stokes equations of fluid flow on distributed-memory machines. The new implicit parallel solver is designed to preserve the convergence rate of the equivalent 'serial' solver. A static domain-decomposition is used to partition the computational domain amongst the available processing nodes of the parallel machine. The SPMD (Single-Program Multiple-Data) programming model is combined with message-passing tools to develop the parallel code on a 32-node Intel Hypercube and a 512-node Intel Delta machine. The implicit parallel solver is validated for internal and external flow problems, and is found to compare identically with flow solutions obtained on a Cray Y-MP/8. A peak computational speed of 2300 MFlops/sec has been achieved on 512 nodes of the Intel Delta machine,k for a problem size of 1024 K equations (256 K grid points).

Detailed design of a lattice composite fuselage structure by a mixed optimization method

NASA Astrophysics Data System (ADS)

Liu, D.; Lohse-Busch, H.; Toropov, V.; Hühne, C.; Armani, U.

2016-10-01

In this article, a procedure for designing a lattice fuselage barrel is developed. It comprises three stages: first, topology optimization of an aircraft fuselage barrel is performed with respect to weight and structural performance to obtain the conceptual design. The interpretation of the optimal result is given to demonstrate the development of this new lattice airframe concept for the fuselage barrel. Subsequently, parametric optimization of the lattice aircraft fuselage barrel is carried out using genetic algorithms on metamodels generated with genetic programming from a 101-point optimal Latin hypercube design of experiments. The optimal design is achieved in terms of weight savings subject to stability, global stiffness and strain requirements, and then verified by the fine mesh finite element simulation of the lattice fuselage barrel. Finally, a practical design of the composite skin complying with the aircraft industry lay-up rules is presented. It is concluded that the mixed optimization method, combining topology optimization with the global metamodel-based approach, allows the problem to be solved with sufficient accuracy and provides the designers with a wealth of information on the structural behaviour of the novel anisogrid composite fuselage design.

Speeding up parallel processing

NASA Technical Reports Server (NTRS)

Denning, Peter J.

1988-01-01

In 1967 Amdahl expressed doubts about the ultimate utility of multiprocessors. The formulation, now called Amdahl's law, became part of the computing folklore and has inspired much skepticism about the ability of the current generation of massively parallel processors to efficiently deliver all their computing power to programs. The widely publicized recent results of a group at Sandia National Laboratory, which showed speedup on a 1024 node hypercube of over 500 for three fixed size problems and over 1000 for three scalable problems, have convincingly challenged this bit of folklore and have given new impetus to parallel scientific computing.

Hardware-assisted software clock synchronization for homogeneous distributed systems

NASA Technical Reports Server (NTRS)

Ramanathan, P.; Kandlur, Dilip D.; Shin, Kang G.

1990-01-01

A clock synchronization scheme that strikes a balance between hardware and software solutions is proposed. The proposed is a software algorithm that uses minimal additional hardware to achieve reasonably tight synchronization. Unlike other software solutions, the guaranteed worst-case skews can be made insensitive to the maximum variation of message transit delay in the system. The scheme is particularly suitable for large partially connected distributed systems with topologies that support simple point-to-point broadcast algorithms. Examples of such topologies include the hypercube and the mesh interconnection structures.

Differentially coherent quadrature-quadrature phase shift keying (Q2PSK)

NASA Astrophysics Data System (ADS)

Saha, Debabrata; El-Ghandour, Osama

The quadrature-quadrature phase-shift-keying (Q2PSK) signaling scheme uses the vertices of a hypercube of dimension four. A generalized Q2PSK signaling format for differentially coherent detection at the receiver is considered. Performance in the presence of additive white Gaussian noise (AWGN) is analyzed. The symbol error rate is found to be approximately twice the symbol error rate in a quaternary DPSK system operating at the same Eb/Nb. However, the bandwidth efficiency of differential Q2PSK is substantially higher than that of quaternary DPSK.

Monte Carlo simulation of a dynamical fermion problem: The light q sup 2 q sup 2 system

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

Grondin, G.

1991-01-01

We present results from a Guided Random Walk Monte Carlo simulation of the light q{sup 2}{bar q}{sup 2} system in a Coulomb-plus-linear quark potential model using an Intel iPSC/860 hypercube. A solvable model problem is first considered, after which we study the full q{sup 2}{bar q}{sup 2} system in (J,I) = (2,2) and (2,0) sectors. We find evidence for no bound states below the vector-vector threshold in these systems. 17 refs., 6 figs.

Uncertainty and sensitivity assessments of an agricultural-hydrological model (RZWQM2) using the GLUE method

NASA Astrophysics Data System (ADS)

Sun, Mei; Zhang, Xiaolin; Huo, Zailin; Feng, Shaoyuan; Huang, Guanhua; Mao, Xiaomin

2016-03-01

Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural-hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water-nitrogen migration and transformation in wheat-maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This new and successful application of the GLUE method for determining the uncertainty and sensitivity of the RZWQM2 could provide a reference for the optimization of model parameters with different emphases according to research interests.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Landscape patterns and soil organic carbon stocks in agricultural bocage landscapes

NASA Astrophysics Data System (ADS)

Viaud, Valérie; Lacoste, Marine; Michot, Didier; Walter, Christian

2014-05-01

Soil organic carbon (SOC) has a crucial impact on global carbon storage at world scale. SOC spatial variability is controlled by the landscape patterns resulting from the continuous interactions between the physical environment and the society. Natural and anthropogenic processes occurring and interplaying at the landscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage and water erosion processes or spatial differentiation of land-use and land-management practices, strongly affect SOC dynamics. Inventories of SOC stocks, reflecting their spatial distribution, are thus key elements to develop relevant management strategies to improving carbon sequestration and mitigating climate change and soil degradation. This study aims to quantify SOC stocks and their spatial distribution in a 1,000-ha agricultural bocage landscape with dairy production as dominant farming system (Zone Atelier Armorique, LTER Europe, NW France). The site is characterized by high heterogeneity on short distance due to a high diversity of soils with varying waterlogging, soil parent material, topography, land-use and hedgerow density. SOC content and stocks were measured up to 105-cm depth in 200 sampling locations selected using conditioned Latin hypercube sampling. Additive sampling was designed to specifically explore SOC distribution near to hedges: 112 points were sampled at fixed distance on 14 transects perpendicular from hedges. We illustrate the heterogeneity of spatial and vertical distribution of SOC stocks at landscape scale, and quantify SOC stocks in the various landscape components. Using multivariate statistics, we discuss the variability and co-variability of existing spatial organization of cropping systems, environmental factors, and SOM stocks, over landscape. Ultimately, our results may contribute to improving regional or national digital soil mapping approaches, by considering the distribution of SOC stocks within each modeling unit and by accounting for the impact of sensitive ecosystems.

Optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Harp, D.

2010-12-01

The process of decision making to protect groundwater resources requires a detailed estimation of uncertainties in model predictions. Various uncertainties associated with modeling a natural system, such as: (1) measurement and computational errors; (2) uncertainties in the conceptual model and model-parameter estimates; (3) simplifications in model setup and numerical representation of governing processes, contribute to the uncertainties in the model predictions. Due to this combination of factors, the sources of predictive uncertainties are generally difficult to quantify individually. Decision support related to optimal design of monitoring networks requires (1) detailed analyses of existing uncertainties related to model predictions of groundwater flow and contaminant transport, (2) optimization of the proposed monitoring network locations in terms of their efficiency to detect contaminants and provide early warning. We apply existing and newly-proposed methods to quantify predictive uncertainties and to optimize well locations. An important aspect of the analysis is the application of newly-developed optimization technique based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods which proved to be robust and computationally efficient. These techniques and algorithms are bundled in a software package called MADS. MADS (Model Analyses for Decision Support) is an object-oriented code that is capable of performing various types of model analyses and supporting model-based decision making. The code can be executed under different computational modes, which include (1) sensitivity analyses (global and local), (2) Monte Carlo analysis, (3) model calibration, (4) parameter estimation, (5) uncertainty quantification, and (6) model selection. The code can be externally coupled with any existing model simulator through integrated modules that read/write input and output files using a set of template and instruction files (consistent with the PEST I/O protocol). MADS can also be internally coupled with a series of built-in analytical simulators. MADS provides functionality to work directly with existing control files developed for the code PEST (Doherty 2009). To perform the computational modes mentioned above, the code utilizes (1) advanced Latin-Hypercube sampling techniques (including Improved Distributed Sampling), (2) various gradient-based Levenberg-Marquardt optimization methods, (3) advanced global optimization methods (including Particle Swarm Optimization), and (4) a selection of alternative objective functions. The code has been successfully applied to perform various model analyses related to environmental management of real contamination sites. Examples include source identification problems, quantification of uncertainty, model calibration, and optimization of monitoring networks. The methodology and software codes are demonstrated using synthetic and real case studies where monitoring networks are optimized taking into account the uncertainty in model predictions of contaminant transport.

An information model for managing multi-dimensional gridded data in a GIS

NASA Astrophysics Data System (ADS)

Xu, H.; Abdul-Kadar, F.; Gao, P.

2016-04-01

Earth observation agencies like NASA and NOAA produce huge volumes of historical, near real-time, and forecasting data representing terrestrial, atmospheric, and oceanic phenomena. The data drives climatological and meteorological studies, and underpins operations ranging from weather pattern prediction and forest fire monitoring to global vegetation analysis. These gridded data sets are distributed mostly as files in HDF, GRIB, or netCDF format and quantify variables like precipitation, soil moisture, or sea surface temperature, along one or more dimensions like time and depth. Although the data cube is a well-studied model for storing and analyzing multi-dimensional data, the GIS community remains in need of a solution that simplifies interactions with the data, and elegantly fits with existing database schemas and dissemination protocols. This paper presents an information model that enables Geographic Information Systems (GIS) to efficiently catalog very large heterogeneous collections of geospatially-referenced multi-dimensional rasters—towards providing unified access to the resulting multivariate hypercubes. We show how the implementation of the model encapsulates format-specific variations and provides unified access to data along any dimension. We discuss how this framework lends itself to familiar GIS concepts like image mosaics, vector field visualization, layer animation, distributed data access via web services, and scientific computing. Global data sources like MODIS from USGS and HYCOM from NOAA illustrate how one would employ this framework for cataloging, querying, and intuitively visualizing such hypercubes. ArcGIS—an established platform for processing, analyzing, and visualizing geospatial data—serves to demonstrate how this integration brings the full power of GIS to the scientific community.

Optimal design of a piezoelectric transducer for exciting guided wave ultrasound in rails

NASA Astrophysics Data System (ADS)

Ramatlo, Dineo A.; Wilke, Daniel N.; Loveday, Philip W.

2017-02-01

An existing Ultrasonic Broken Rail Detection System installed in South Africa on a heavy duty railway line is currently being upgraded to include defect detection and location. To accomplish this, an ultrasonic piezoelectric transducer to strongly excite a guided wave mode with energy concentrated in the web (web mode) of a rail is required. A previous study demonstrated that the recently developed SAFE-3D (Semi-Analytical Finite Element - 3 Dimensional) method can effectively predict the guided waves excited by a resonant piezoelectric transducer. In this study, the SAFE-3D model is used in the design optimization of a rail web transducer. A bound-constrained optimization problem was formulated to maximize the energy transmitted by the transducer in the web mode when driven by a pre-defined excitation signal. Dimensions of the transducer components were selected as the three design variables. A Latin hypercube sampled design of experiments that required a total of 500 SAFE-3D analyses in the design space was employed in a response surface-based optimization approach. The Nelder-Mead optimization algorithm was then used to find an optimal transducer design on the constructed response surface. The radial basis function response surface was first verified by comparing a number of predicted responses against the computed SAFE-3D responses. The performance of the optimal transducer predicted by the optimization algorithm on the response surface was also verified to be sufficiently accurate using SAFE-3D. The computational advantages of SAFE-3D in optimal transducer design are noteworthy as more than 500 analyses were performed. The optimal design was then manufactured and experimental measurements were used to validate the predicted performance. The adopted design method has demonstrated the capability to automate the design of transducers for a particular rail cross-section and frequency range.

Seismic Fragility Analysis of a Condensate Storage Tank with Age-Related Degradations

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

Nie, J.; Braverman, J.; Hofmayer, C

2011-04-01

The Korea Atomic Energy Research Institute (KAERI) is conducting a five-year research project to develop a realistic seismic risk evaluation system which includes the consideration of aging of structures and components in nuclear power plants (NPPs). The KAERI research project includes three specific areas that are essential to seismic probabilistic risk assessment (PRA): (1) probabilistic seismic hazard analysis, (2) seismic fragility analysis including the effects of aging, and (3) a plant seismic risk analysis. Since 2007, Brookhaven National Laboratory (BNL) has entered into a collaboration agreement with KAERI to support its development of seismic capability evaluation technology for degraded structuresmore » and components. The collaborative research effort is intended to continue over a five year period. The goal of this collaboration endeavor is to assist KAERI to develop seismic fragility analysis methods that consider the potential effects of age-related degradation of structures, systems, and components (SSCs). The research results of this multi-year collaboration will be utilized as input to seismic PRAs. This report describes the research effort performed by BNL for the Year 4 scope of work. This report was developed as an update to the Year 3 report by incorporating a major supplement to the Year 3 fragility analysis. In the Year 4 research scope, an additional study was carried out to consider an additional degradation scenario, in which the three basic degradation scenarios, i.e., degraded tank shell, degraded anchor bolts, and cracked anchorage concrete, are combined in a non-perfect correlation manner. A representative operational water level is used for this effort. Building on the same CDFM procedure implemented for the Year 3 Tasks, a simulation method was applied using optimum Latin Hypercube samples to characterize the deterioration behavior of the fragility capacity as a function of age-related degradations. The results are summarized in Section 5 and Appendices G through I.« less

Photovoltaic frequency–watt curve design for frequency regulation and fast contingency reserves

DOE PAGES

Johnson, Jay; Neely, Jason C.; Delhotal, Jarod J.; ...

2016-09-02

When renewable energy resources are installed in electricity grids, they typically increase generation variability and displace thermal generator control action and inertia. Grid operators combat these emerging challenges with advanced distributed energy resource (DER) functions to support frequency and provide voltage regulation and protection mechanisms. This paper focuses on providing frequency reserves using autonomous IEC TR 61850-90-7 pointwise frequency-watt (FW) functions that adjust DER active power as a function of measured grid frequency. The importance of incorporating FW functions into a fleet of photovoltaic (PV) systems is demonstrated in simulation. Effects of FW curve design, including curtailment, deadband, and droop,more » were analyzed against performance metrics using Latin hypercube sampling for 20%, 70%, and 120% PV penetration scenarios on the Hawaiian island of Lanai. Finally, to understand the financial implications of FW functions to utilities, a performance function was defined based on monetary costs attributable to curtailed PV production, load shedding, and generator wear. An optimization wrapper was then created to find the best FW function curve for each penetration level. Lastly, it was found that in all cases, the utility would save money by implementing appropriate FW functions.« less

Coach simplified structure modeling and optimization study based on the PBM method

NASA Astrophysics Data System (ADS)

Zhang, Miaoli; Ren, Jindong; Yin, Ying; Du, Jian

2016-09-01

For the coach industry, rapid modeling and efficient optimization methods are desirable for structure modeling and optimization based on simplified structures, especially for use early in the concept phase and with capabilities of accurately expressing the mechanical properties of structure and with flexible section forms. However, the present dimension-based methods cannot easily meet these requirements. To achieve these goals, the property-based modeling (PBM) beam modeling method is studied based on the PBM theory and in conjunction with the characteristics of coach structure of taking beam as the main component. For a beam component of concrete length, its mechanical characteristics are primarily affected by the section properties. Four section parameters are adopted to describe the mechanical properties of a beam, including the section area, the principal moments of inertia about the two principal axles, and the torsion constant of the section. Based on the equivalent stiffness strategy, expressions for the above section parameters are derived, and the PBM beam element is implemented in HyperMesh software. A case is realized using this method, in which the structure of a passenger coach is simplified. The model precision is validated by comparing the basic performance of the total structure with that of the original structure, including the bending and torsion stiffness and the first-order bending and torsional modal frequencies. Sensitivity analysis is conducted to choose design variables. The optimal Latin hypercube experiment design is adopted to sample the test points, and polynomial response surfaces are used to fit these points. To improve the bending and torsion stiffness and the first-order torsional frequency and taking the allowable maximum stresses of the braking and left turning conditions as constraints, the multi-objective optimization of the structure is conducted using the NSGA-II genetic algorithm on the ISIGHT platform. The result of the Pareto solution set is acquired, and the selection strategy of the final solution is discussed. The case study demonstrates that the mechanical performances of the structure can be well-modeled and simulated by PBM beam. Because of the merits of fewer parameters and convenience of use, this method is suitable to be applied in the concept stage. Another merit is that the optimization results are the requirements for the mechanical performance of the beam section instead of those of the shape and dimensions, bringing flexibility to the succeeding design.

Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment

NASA Astrophysics Data System (ADS)

Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.

2016-12-01

Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.

Modeling bronchial circulation with application to soluble gas exchange: description and sensitivity analysis.

PubMed

Bui, T D; Dabdub, D; George, S C

1998-06-01

The steady-state exchange of inert gases across an in situ canine trachea has recently been shown to be limited equally by diffusion and perfusion over a wide range (0.01-350) of blood solubilities (betablood; ml . ml-1 . atm-1). Hence, we hypothesize that the exchange of ethanol (betablood = 1,756 at 37 degrees C) in the airways depends on the blood flow rate from the bronchial circulation. To test this hypothesis, the dynamics of the bronchial circulation were incorporated into an existing model that describes the simultaneous exchange of heat, water, and a soluble gas in the airways. A detailed sensitivity analysis of key model parameters was performed by using the method of Latin hypercube sampling. The model accurately predicted a previously reported experimental exhalation profile of ethanol (R2 = 0.991) as well as the end-exhalation airstream temperature (34.6 degrees C). The model predicts that 27, 29, and 44% of exhaled ethanol in a single exhalation are derived from the tissues of the mucosa and submucosa, the bronchial circulation, and the tissue exterior to the submucosa (which would include the pulmonary circulation), respectively. Although the concentration of ethanol in the bronchial capillary decreased during inspiration, the three key model outputs (end-exhaled ethanol concentration, the slope of phase III, and end-exhaled temperature) were all statistically insensitive (P > 0.05) to the parameters describing the bronchial circulation. In contrast, the model outputs were all sensitive (P < 0.05) to the thickness of tissue separating the core body conditions from the bronchial smooth muscle. We conclude that both the bronchial circulation and the pulmonary circulation impact soluble gas exchange when the entire conducting airway tree is considered.

Threshold conditions for integrated pest management models with pesticides that have residual effects.

PubMed

Tang, Sanyi; Liang, Juhua; Tan, Yuanshun; Cheke, Robert A

2013-01-01

Impulsive differential equations (hybrid dynamical systems) can provide a natural description of pulse-like actions such as when a pesticide kills a pest instantly. However, pesticides may have long-term residual effects, with some remaining active against pests for several weeks, months or years. Therefore, a more realistic method for modelling chemical control in such cases is to use continuous or piecewise-continuous periodic functions which affect growth rates. How to evaluate the effects of the duration of the pesticide residual effectiveness on successful pest control is key to the implementation of integrated pest management (IPM) in practice. To address these questions in detail, we have modelled IPM including residual effects of pesticides in terms of fixed pulse-type actions. The stability threshold conditions for pest eradication are given. Moreover, effects of the killing efficiency rate and the decay rate of the pesticide on the pest and on its natural enemies, the duration of residual effectiveness, the number of pesticide applications and the number of natural enemy releases on the threshold conditions are investigated with regard to the extent of depression or resurgence resulting from pulses of pesticide applications and predator releases. Latin Hypercube Sampling/Partial Rank Correlation uncertainty and sensitivity analysis techniques are employed to investigate the key control parameters which are most significantly related to threshold values. The findings combined with Volterra's principle confirm that when the pesticide has a strong effect on the natural enemies, repeated use of the same pesticide can result in target pest resurgence. The results also indicate that there exists an optimal number of pesticide applications which can suppress the pest most effectively, and this may help in the design of an optimal control strategy.

Environmental drivers of spatial patterns of topsoil nitrogen and phosphorus under monsoon conditions in a complex terrain of South Korea

PubMed Central

Choi, Kwanghun; Spohn, Marie; Park, Soo Jin; Huwe, Bernd; Ließ, Mareike

2017-01-01

Nitrogen (N) and phosphorus (P) in topsoils are critical for plant nutrition. Relatively little is known about the spatial patterns of N and P in the organic layer of mountainous landscapes. Therefore, the spatial distributions of N and P in both the organic layer and the A horizon were analyzed using a light detection and ranging (LiDAR) digital elevation model and vegetation metrics. The objective of the study was to analyze the effect of vegetation and topography on the spatial patterns of N and P in a small watershed covered by forest in South Korea. Soil samples were collected using the conditioned latin hypercube method. LiDAR vegetation metrics, the normalized difference vegetation index (NDVI), and terrain parameters were derived as predictors. Spatial explicit predictions of N/P ratios were obtained using a random forest with uncertainty analysis. We tested different strategies of model validation (repeated 2-fold to 20-fold and leave-one-out cross validation). Repeated 10-fold cross validation was selected for model validation due to the comparatively high accuracy and low variance of prediction. Surface curvature was the best predictor of P contents in the organic layer and in the A horizon, while LiDAR vegetation metrics and NDVI were important predictors of N in the organic layer. N/P ratios increased with surface curvature and were higher on the convex upper slope than on the concave lower slope. This was due to P enrichment of the soil on the lower slope and a more even spatial distribution of N. Our digital soil maps showed that the topsoils on the upper slopes contained relatively little P. These findings are critical for understanding N and P dynamics in mountainous ecosystems. PMID:28837590

Towards a consensus-based biokinetic model for green microalgae - The ASM-A.

PubMed

Wágner, Dorottya S; Valverde-Pérez, Borja; Sæbø, Mariann; Bregua de la Sotilla, Marta; Van Wagenen, Jonathan; Smets, Barth F; Plósz, Benedek Gy

2016-10-15

Cultivation of microalgae in open ponds and closed photobioreactors (PBRs) using wastewater resources offers an opportunity for biochemical nutrient recovery. Effective reactor system design and process control of PBRs requires process models. Several models with different complexities have been developed to predict microalgal growth. However, none of these models can effectively describe all the relevant processes when microalgal growth is coupled with nutrient removal and recovery from wastewaters. Here, we present a mathematical model developed to simulate green microalgal growth (ASM-A) using the systematic approach of the activated sludge modelling (ASM) framework. The process model - identified based on a literature review and using new experimental data - accounts for factors influencing photoautotrophic and heterotrophic microalgal growth, nutrient uptake and storage (i.e. Droop model) and decay of microalgae. Model parameters were estimated using laboratory-scale batch and sequenced batch experiments using the novel Latin Hypercube Sampling based Simplex (LHSS) method. The model was evaluated using independent data obtained in a 24-L PBR operated in sequenced batch mode. Identifiability of the model was assessed. The model can effectively describe microalgal biomass growth, ammonia and phosphate concentrations as well as the phosphorus storage using a set of average parameter values estimated with the experimental data. A statistical analysis of simulation and measured data suggests that culture history and substrate availability can introduce significant variability on parameter values for predicting the reaction rates for bulk nitrate and the intracellularly stored nitrogen state-variables, thereby requiring scenario specific model calibration. ASM-A was identified using standard cultivation medium and it can provide a platform for extensions accounting for factors influencing algal growth and nutrient storage using wastewater resources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations

NASA Astrophysics Data System (ADS)

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Simplifying the complexity of a coupled carbon turnover and pesticide degradation model

NASA Astrophysics Data System (ADS)

Marschmann, Gianna; Erhardt, André H.; Pagel, Holger; Kügler, Philipp; Streck, Thilo

2016-04-01

The mechanistic one-dimensional model PECCAD (PEsticide degradation Coupled to CArbon turnover in the Detritusphere; Pagel et al. 2014, Biogeochemistry 117, 185-204) has been developed as a tool to elucidate regulation mechanisms of pesticide degradation in soil. A feature of this model is that it integrates functional traits of microorganisms, identifiable by molecular tools, and physicochemical processes such as transport and sorption that control substrate availability. Predicting the behavior of microbially active interfaces demands a fundamental understanding of factors controlling their dynamics. Concepts from dynamical systems theory allow us to study general properties of the model such as its qualitative behavior, intrinsic timescales and dynamic stability: Using a Latin hypercube method we sampled the parameter space for physically realistic steady states of the PECCAD ODE system and set up a numerical continuation and bifurcation problem with the open-source toolbox MatCont in order to obtain a complete classification of the dynamical system's behaviour. Bifurcation analysis reveals an equilibrium state of the system entirely controlled by fungal kinetic parameters. The equilibrium is generally unstable in response to small perturbations except for a small band in parameter space where the pesticide pool is stable. Time scale separation is a phenomenon that occurs in almost every complex open physical system. Motivated by the notion of "initial-stage" and "late-stage" decomposers and the concept of r-, K- or L-selected microbial life strategies, we test the applicability of geometric singular perturbation theory to identify fast and slow time scales of PECCAD. Revealing a generic fast-slow structure would greatly simplify the analysis of complex models of organic matter turnover by reducing the number of unknowns and parameters and providing a systematic mathematical framework for studying their properties.

Proposal for continued research in intelligent machines at the Center for Engineering Systems Advanced Research (CESAR) for FY 1988 to FY 1991

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

Weisbin, C.R.

1987-03-01

This document reviews research accomplishments achieved by the staff of the Center for Engineering Systems Advanced Research (CESAR) during the fiscal years 1984 through 1987. The manuscript also describes future CESAR objectives for the 1988-1991 planning horizon, and beyond. As much as possible, the basic research goals are derived from perceived Department of Energy (DOE) needs for increased safety, productivity, and competitiveness in the United States energy producing and consuming facilities. Research areas covered include the HERMIES-II Robot, autonomous robot navigation, hypercube computers, machine vision, and manipulators.

Three Dimensional Imaging with Multiple Wavelength Speckle Interferometry

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

Bernacki, Bruce E.; Cannon, Bret D.; Schiffern, John T.

2014-05-28

We present the design, modeling, construction, and results of a three-dimensional imager based upon multiple-wavelength speckle interferometry. A surface under test is illuminated with tunable laser light in a Michelson interferometer configuration while a speckled image is acquired at each laser frequency step. The resulting hypercube is Fourier transformed in the frequency dimension and the beat frequencies that result map the relative offsets of surface features. Synthetic wavelengths resulting from the laser tuning can probe features ranging from 18 microns to hundreds of millimeters. Three dimensional images will be presented along with modeling results.

An Examination of Hypercube Implementations of Genetic Algorithms

DTIC Science & Technology

1992-03-01

t of th s C!ie(tol.3 ) i ., r .’ Itor l’C ". Ing sUq , -Cs iS or reducing ,is ourlen : .V,isr,qon Heac uar’ers Ser .ces. Directorate for -nformation...is of length n and the building.block-size is r , all combinations of the n loc* taken r at a time must be generated. The cardinality of the size i n...U Approved for public release; distribution unlimited RO Form Approved REPORT DOCUMENTATION PAGE OMB No. 0704-0188 Pi C rponr! - ; Lurcen " r :T"s

Minimally doubled fermions at one loop

NASA Astrophysics Data System (ADS)

Capitani, Stefano; Weber, Johannes; Wittig, Hartmut

2009-10-01

Minimally doubled fermions have been proposed as a cost-effective realization of chiral symmetry at non-zero lattice spacing. Using lattice perturbation theory at one loop, we study their renormalization properties. Specifically, we investigate the consequences of the breaking of hyper-cubic symmetry, which is a typical feature of this class of fermionic discretizations. Our results for the quark self-energy indicate that the four-momentum undergoes a renormalization which is linearly divergent. We also compute renormalization factors for quark bilinears, construct the conserved vector and axial-vector currents and verify that at one loop the renormalization factors of the latter are equal to one.

Hypercluster - Parallel processing for computational mechanics

NASA Technical Reports Server (NTRS)

Blech, Richard A.

1988-01-01

An account is given of the development status, performance capabilities and implications for further development of NASA-Lewis' testbed 'hypercluster' parallel computer network, in which multiple processors communicate through a shared memory. Processors have local as well as shared memory; the hypercluster is expanded in the same manner as the hypercube, with processor clusters replacing the normal single processor node. The NASA-Lewis machine has three nodes with a vector personality and one node with a scalar personality. Each of the vector nodes uses four board-level vector processors, while the scalar node uses four general-purpose microcomputer boards.

Algorithm implementation on the Navier-Stokes computer

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

Krist, S.E.; Zang, T.A.

1987-03-01

The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.

Algorithm implementation on the Navier-Stokes computer

NASA Technical Reports Server (NTRS)

Krist, Steven E.; Zang, Thomas A.

1987-01-01

The Navier-Stokes Computer is a multi-purpose parallel-processing supercomputer which is currently under development at Princeton University. It consists of multiple local memory parallel processors, called Nodes, which are interconnected in a hypercube network. Details of the procedures involved in implementing an algorithm on the Navier-Stokes computer are presented. The particular finite difference algorithm considered in this analysis was developed for simulation of laminar-turbulent transition in wall bounded shear flows. Projected timing results for implementing this algorithm indicate that operation rates in excess of 42 GFLOPS are feasible on a 128 Node machine.

Advanced flight computers for planetary exploration

NASA Technical Reports Server (NTRS)

Stephenson, R. Rhoads

1988-01-01

Research concerning flight computers for use on interplanetary probes is reviewed. The history of these computers from the Viking mission to the present is outlined. The differences between ground commercial computers and computers for planetary exploration are listed. The development of a computer for the Mariner Mark II comet rendezvous asteroid flyby mission is described. Various aspects of recently developed computer systems are examined, including the Max real time, embedded computer, a hypercube distributed supercomputer, a SAR data processor, a processor for the High Resolution IR Imaging Spectrometer, and a robotic vision multiresolution pyramid machine for processsing images obtained by a Mars Rover.

Critical Concentration Ratio for Solar Thermoelectric Generators

NASA Astrophysics Data System (ADS)

ur Rehman, Naveed; Siddiqui, Mubashir Ali

2016-10-01

A correlation for determining the critical concentration ratio (CCR) of solar concentrated thermoelectric generators (SCTEGs) has been established, and the significance of the contributing parameters is discussed in detail. For any SCTEG, higher concentration ratio leads to higher temperatures at the hot side of modules. However, the maximum value of this temperature for safe operation is limited by the material properties of the modules and should be considered as an important design constraint. Taking into account this limitation, the CCR can be defined as the maximum concentration ratio usable for a particular SCTEG. The established correlation is based on factors associated with the material and geometric properties of modules, thermal characteristics of the receiver, installation site attributes, and thermal and electrical operating conditions. To reduce the number of terms in the correlation, these factors are combined to form dimensionless groups by applying the Buckingham Pi theorem. A correlation model containing these groups is proposed and fit to a dataset obtained by simulating a thermodynamic (physical) model over sampled values acquired by applying the Latin hypercube sampling (LHS) technique over a realistic distribution of factors. The coefficient of determination and relative error are found to be 97% and ±20%, respectively. The correlation is validated by comparing the predicted results with literature values. In addition, the significance and effects of the Pi groups on the CCR are evaluated and thoroughly discussed. This study will lead to a wide range of opportunities regarding design and optimization of SCTEGs.

Tumor margin assessment of surgical tissue specimen of cancer patients using label-free hyperspectral imaging

NASA Astrophysics Data System (ADS)

Fei, Baowei; Lu, Guolan; Wang, Xu; Zhang, Hongzheng; Little, James V.; Magliocca, Kelly R.; Chen, Amy Y.

2017-02-01

We are developing label-free hyperspectral imaging (HSI) for tumor margin assessment. HSI data, hypercube (x,y,λ), consists of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on the HSI image has an optical spectrum. We developed preprocessing and classification methods for HSI data. We used spectral features from HSI data for the classification of cancer and benign tissue. We collected surgical tissue specimens from 16 human patients who underwent head and neck (H&N) cancer surgery. We acquired both HSI, autofluorescence images, and fluorescence images with 2-NBDG and proflavine from the specimens. Digitized histologic slides were examined by an H&N pathologist. The hyperspectral imaging and classification method was able to distinguish between cancer and normal tissue from oral cavity with an average accuracy of 90+/-8%, sensitivity of 89+/-9%, and specificity of 91+/-6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94+/-6%, sensitivity of 94+/-6%, and specificity of 95+/-6%. Hyperspectral imaging outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study suggests that label-free hyperspectral imaging has great potential for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the hyperspectral imaging technology is warranted for its application in image-guided surgery.

Uncertainty Analysis of Decomposing Polyurethane Foam

NASA Technical Reports Server (NTRS)

Hobbs, Michael L.; Romero, Vicente J.

2000-01-01

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Analysis of a parallelized nonlinear elliptic boundary value problem solver with application to reacting flows

NASA Technical Reports Server (NTRS)

Keyes, David E.; Smooke, Mitchell D.

1987-01-01

A parallelized finite difference code based on the Newton method for systems of nonlinear elliptic boundary value problems in two dimensions is analyzed in terms of computational complexity and parallel efficiency. An approximate cost function depending on 15 dimensionless parameters is derived for algorithms based on stripwise and boxwise decompositions of the domain and a one-to-one assignment of the strip or box subdomains to processors. The sensitivity of the cost functions to the parameters is explored in regions of parameter space corresponding to model small-order systems with inexpensive function evaluations and also a coupled system of nineteen equations with very expensive function evaluations. The algorithm was implemented on the Intel Hypercube, and some experimental results for the model problems with stripwise decompositions are presented and compared with the theory. In the context of computational combustion problems, multiprocessors of either message-passing or shared-memory type may be employed with stripwise decompositions to realize speedup of O(n), where n is mesh resolution in one direction, for reasonable n.

Soil organic carbon content assessment in a heterogeneous landscape: comparison of digital soil mapping and visible and near Infrared spectroscopy approaches

NASA Astrophysics Data System (ADS)

Michot, Didier; Fouad, Youssef; Pascal, Pichelin; Viaud, Valérie; Soltani, Inès; Walter, Christian

2017-04-01

This study aims are: i) to assess SOC content distribution according to the global soil map (GSM) project recommendations in a heterogeneous landscape ; ii) to compare the prediction performance of digital soil mapping (DSM) and visible-near infrared (Vis-NIR) spectroscopy approaches. The study area of 140 ha, located at Plancoët, surrounds the unique mineral spring water of Brittany (Western France). It's a hillock characterized by a heterogeneous landscape mosaic with different types of forest, permanent pastures and wetlands along a small coastal river. We acquired two independent datasets: j) 50 points selected using a conditioned Latin hypercube sampling (cLHS); jj) 254 points corresponding to the GSM grid. Soil samples were collected in three layers (0-5, 20-25 and 40-50cm) for both sampling strategies. SOC content was only measured in cLHS soil samples, while Vis-NIR spectra were measured on all the collected samples. For the DSM approach, a machine-learning algorithm (Cubist) was applied on the cLHS calibration data to build rule-based models linking soil carbon content in the different layers with environmental covariates, derived from digital elevation model, geological variables, land use data and existing large scale soil maps. For the spectroscopy approach, we used two calibration datasets: k) the local cLHS ; kk) a subset selected from the regional spectral database of Brittany after a PCA with a hierarchical clustering analysis and spiked by local cLHS spectra. The PLS regression algorithm with "leave-one-out" cross validation was performed for both calibration datasets. SOC contents for the 3 layers of the GSM grid were predicted using the different approaches and were compared with each other. Their prediction performance was evaluated by the following parameters: R2, RMSE and RPD. Both approaches led to satisfactory predictions for SOC content with an advantage for the spectral approach, particularly as regards the pertinence of the variation range.

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

NASA Technical Reports Server (NTRS)

Chamis, Chrisos C. (Technical Monitor); Godines, Cody Ric

2003-01-01

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

SOARCA Peach Bottom Atomic Power Station Long-Term Station Blackout Uncertainty Analysis: Convergence of the Uncertainty Results

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

Bixler, Nathan E.; Osborn, Douglas M.; Sallaberry, Cedric Jean-Marie

2014-02-01

This paper describes the convergence of MELCOR Accident Consequence Code System, Version 2 (MACCS2) probabilistic results of offsite consequences for the uncertainty analysis of the State-of-the-Art Reactor Consequence Analyses (SOARCA) unmitigated long-term station blackout scenario at the Peach Bottom Atomic Power Station. The consequence metrics evaluated are individual latent-cancer fatality (LCF) risk and individual early fatality risk. Consequence results are presented as conditional risk (i.e., assuming the accident occurs, risk per event) to individuals of the public as a result of the accident. In order to verify convergence for this uncertainty analysis, as recommended by the Nuclear Regulatory Commission’s Advisorymore » Committee on Reactor Safeguards, a ‘high’ source term from the original population of Monte Carlo runs has been selected to be used for: (1) a study of the distribution of consequence results stemming solely from epistemic uncertainty in the MACCS2 parameters (i.e., separating the effect from the source term uncertainty), and (2) a comparison between Simple Random Sampling (SRS) and Latin Hypercube Sampling (LHS) in order to validate the original results obtained with LHS. Three replicates (each using a different random seed) of size 1,000 each using LHS and another set of three replicates of size 1,000 using SRS are analyzed. The results show that the LCF risk results are well converged with either LHS or SRS sampling. The early fatality risk results are less well converged at radial distances beyond 2 miles, and this is expected due to the sparse data (predominance of “zero” results).« less

A parallel-pipelined architecture for a multi carrier demodulator

NASA Astrophysics Data System (ADS)

Kwatra, S. C.; Jamali, M. M.; Eugene, Linus P.

1991-03-01

Analog devices have been used for processing the information on board the satellites. Presently, digital devices are being used because they are economical and flexible as compared to their analog counterparts. Several schemes of digital transmission can be used depending on the data rate requirement of the user. An economical scheme of transmission for small earth stations uses single channel per carrier/frequency division multiple access (SCPC/FDMA) on the uplink and time division multiplexing (TDM) on the downlink. This is a typical communication service offered to low data rate users in commercial mass market. These channels usually pertain to either voice or data transmission. An efficient digital demodulator architecture is provided for a large number of law data rate users. A demodulator primarily consists of carrier, clock, and data recovery modules. This design uses principles of parallel processing, pipelining, and time sharing schemes to process large numbers of voice or data channels. It maintains the optimum throughput which is derived from the designed architecture and from the use of high speed components. The design is optimized for reduced power and area requirements. This is essential for satellite applications. The design is also flexible in processing a group of a varying number of channels. The algorithms that are used are verified by the use of a computer aided software engineering (CASE) tool called the Block Oriented System Simulator. The data flow, control circuitry, and interface of the hardware design is simulated in C language. Also, a multiprocessor approach is provided to map, model, and simulate the demodulation algorithms mainly from a speed view point. A hypercude based architecture implementation is provided for such a scheme of operation. The hypercube structure and the demodulation models on hypercubes are simulated in Ada.

A parallel-pipelined architecture for a multi carrier demodulator. M.S. Thesis Final Technical Report, Jan. 1989 - Aug. 1990

NASA Technical Reports Server (NTRS)

Kwatra, S. C.; Jamali, M. M.; Eugene, Linus P.

1991-01-01

Analog devices have been used for processing the information on board the satellites. Presently, digital devices are being used because they are economical and flexible as compared to their analog counterparts. Several schemes of digital transmission can be used depending on the data rate requirement of the user. An economical scheme of transmission for small earth stations uses single channel per carrier/frequency division multiple access (SCPC/FDMA) on the uplink and time division multiplexing (TDM) on the downlink. This is a typical communication service offered to low data rate users in commercial mass market. These channels usually pertain to either voice or data transmission. An efficient digital demodulator architecture is provided for a large number of law data rate users. A demodulator primarily consists of carrier, clock, and data recovery modules. This design uses principles of parallel processing, pipelining, and time sharing schemes to process large numbers of voice or data channels. It maintains the optimum throughput which is derived from the designed architecture and from the use of high speed components. The design is optimized for reduced power and area requirements. This is essential for satellite applications. The design is also flexible in processing a group of a varying number of channels. The algorithms that are used are verified by the use of a computer aided software engineering (CASE) tool called the Block Oriented System Simulator. The data flow, control circuitry, and interface of the hardware design is simulated in C language. Also, a multiprocessor approach is provided to map, model, and simulate the demodulation algorithms mainly from a speed view point. A hypercude based architecture implementation is provided for such a scheme of operation. The hypercube structure and the demodulation models on hypercubes are simulated in Ada.

On the relationship between parallel computation and graph embedding

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

Gupta, A.K.

1989-01-01

The problem of efficiently simulating an algorithm designed for an n-processor parallel machine G on an m-processor parallel machine H with n > m arises when parallel algorithms designed for an ideal size machine are simulated on existing machines which are of a fixed size. The author studies this problem when every processor of H takes over the function of a number of processors in G, and he phrases the simulation problem as a graph embedding problem. New embeddings presented address relevant issues arising from the parallel computation environment. The main focus centers around embedding complete binary trees into smaller-sizedmore » binary trees, butterflies, and hypercubes. He also considers simultaneous embeddings of r source machines into a single hypercube. Constant factors play a crucial role in his embeddings since they are not only important in practice but also lead to interesting theoretical problems. All of his embeddings minimize dilation and load, which are the conventional cost measures in graph embeddings and determine the maximum amount of time required to simulate one step of G on H. His embeddings also optimize a new cost measure called ({alpha},{beta})-utilization which characterizes how evenly the processors of H are used by the processors of G. Ideally, the utilization should be balanced (i.e., every processor of H simulates at most (n/m) processors of G) and the ({alpha},{beta})-utilization measures how far off from a balanced utilization the embedding is. He presents embeddings for the situation when some processors of G have different capabilities (e.g. memory or I/O) than others and the processors with different capabilities are to be distributed uniformly among the processors of H. Placing such conditions on an embedding results in an increase in some of the cost measures.« less

Software integration for automated stability analysis and design optimization of a bearingless rotor blade

NASA Astrophysics Data System (ADS)

Gunduz, Mustafa Emre

Many government agencies and corporations around the world have found the unique capabilities of rotorcraft indispensable. Incorporating such capabilities into rotorcraft design poses extra challenges because it is a complicated multidisciplinary process. The concept of applying several disciplines to the design and optimization processes may not be new, but it does not currently seem to be widely accepted in industry. The reason for this might be the lack of well-known tools for realizing a complete multidisciplinary design and analysis of a product. This study aims to propose a method that enables engineers in some design disciplines to perform a fairly detailed analysis and optimization of a design using commercially available software as well as codes developed at Georgia Tech. The ultimate goal is when the system is set up properly, the CAD model of the design, including all subsystems, will be automatically updated as soon as a new part or assembly is added to the design; or it will be updated when an analysis and/or an optimization is performed and the geometry needs to be modified. Designers and engineers will be involved in only checking the latest design for errors or adding/removing features. Such a design process will take dramatically less time to complete; therefore, it should reduce development time and costs. The optimization method is demonstrated on an existing helicopter rotor originally designed in the 1960's. The rotor is already an effective design with novel features. However, application of the optimization principles together with high-speed computing resulted in an even better design. The objective function to be minimized is related to the vibrations of the rotor system under gusty wind conditions. The design parameters are all continuous variables. Optimization is performed in a number of steps. First, the most crucial design variables of the objective function are identified. With these variables, Latin Hypercube Sampling method is used to probe the design space of several local minima and maxima. After analysis of numerous samples, an optimum configuration of the design that is more stable than that of the initial design is reached. The above process requires several software tools: CATIA as the CAD tool, ANSYS as the FEA tool, VABS for obtaining the cross-sectional structural properties, and DYMORE for the frequency and dynamic analysis of the rotor. MATLAB codes are also employed to generate input files and read output files of DYMORE. All these tools are connected using ModelCenter.

Hyperswitch Communication Network Computer

NASA Technical Reports Server (NTRS)

Peterson, John C.; Chow, Edward T.; Priel, Moshe; Upchurch, Edwin T.

1993-01-01

Hyperswitch Communications Network (HCN) computer is prototype multiple-processor computer being developed. Incorporates improved version of hyperswitch communication network described in "Hyperswitch Network For Hypercube Computer" (NPO-16905). Designed to support high-level software and expansion of itself. HCN computer is message-passing, multiple-instruction/multiple-data computer offering significant advantages over older single-processor and bus-based multiple-processor computers, with respect to price/performance ratio, reliability, availability, and manufacturing. Design of HCN operating-system software provides flexible computing environment accommodating both parallel and distributed processing. Also achieves balance among following competing factors; performance in processing and communications, ease of use, and tolerance of (and recovery from) faults.

Implementation and performance of parallel Prolog interpreter

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

Wei, S.; Kale, L.V.; Balkrishna, R.

1988-01-01

In this paper, the authors discuss the implementation of a parallel Prolog interpreter on different parallel machines. The implementation is based on the REDUCE--OR process model which exploits both AND and OR parallelism in logic programs. It is machine independent as it runs on top of the chare-kernel--a machine-independent parallel programming system. The authors also give the performance of the interpreter running a diverse set of benchmark pargrams on parallel machines including shared memory systems: an Alliant FX/8, Sequent and a MultiMax, and a non-shared memory systems: Intel iPSC/32 hypercube, in addition to its performance on a multiprocessor simulation system.

Non-Perturbative Renormalization of the Lattice Heavy Quark Classical Velocity

NASA Astrophysics Data System (ADS)

Mandula, Jeffrey E.; Ogilvie, Michael C.

1997-02-01

We discuss the renormalization of the lattice formulation of the Heavy Quark Effective Theory (LHQET). In addition to wave function and composite operator renormalizations, on the lattice the classical velocity is also renormalized. The origin of this renormalization is the reduction of Lorentz (or O(4)) invariance to (hyper)cubic invariance. We present results of a new, direct lattice simulation of this finite renormalization, and compare the results to the perturbative (one loop) result. The simulation results are obtained with the use of a variationally optimized heavy-light meson operator, using an ensemble of lattices provided by the Fermilab ACP-MAPS collaboration.

Renormalization of the Lattice Heavy Quark Classical Velocity

NASA Astrophysics Data System (ADS)

Mandula, Jeffrey E.; Ogilvie, Michael C.

1996-03-01

In the lattice formulation of the Heavy Quark Effective Theory (LHQET), the "classical velocity" v becomes renormalized. The origin of this renormalization is the reduction of Lorentz (or O(4)) invariance to (hyper)cubic invariance. The renormalization is finite and depends on the form of the decretization of the reduced heavy quark Dirac equation. For the Forward Time — Centered Space discretization, the renormalization is computed both perturbatively, to one loop, and non-perturbatively using two ensembles of lattices, one at β = 5.7 and the other at β = 6.1 The estimates agree, and indicate that for small classical velocities, ν→ is reduced by about 25-30%.

Experiences with hypercube operating system instrumentation

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Rudolph, David C.

1989-01-01

The difficulties in conceptualizing the interactions among a large number of processors make it difficult both to identify the sources of inefficiencies and to determine how a parallel program could be made more efficient. This paper describes an instrumentation system that can trace the execution of distributed memory parallel programs by recording the occurrence of parallel program events. The resulting event traces can be used to compile summary statistics that provide a global view of program performance. In addition, visualization tools permit the graphic display of event traces. Visual presentation of performance data is particularly useful, indeed, necessary for large-scale parallel computers; the enormous volume of performance data mandates visual display.

Medical hyperspectral imaging: a review

PubMed Central

Lu, Guolan; Fei, Baowei

2014-01-01

Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

Self-Reflecting Skew Polygons and Polytopes in the 4-Dimensional Hypercube.

DTIC Science & Technology

1983-01-01

in a general position. Definition 1. We say that Lk is in general position provided that (1.7) the n x k matrix i11 has no vanishing minor of order k...monochromes (4.8) are parallel, a condition expressed by requiring that (4.9) the 4 x 2 matrix IA I has no vanishing minor of order 2 !i • I !.li -11- 6...8217 . every (ulu 2 ) we have (ul,u 2) e .M(, for some L and by Lemna 1 and (5.1) we conclude that for some 1 we have 1 3 either 0 < x , or else < x 1 • This

Hypercubane: DFT-based prediction of an Oh-symmetric double-shell hydrocarbon

NASA Astrophysics Data System (ADS)

Pichierri, Fabio

2014-09-01

Using density functional theory we design a molecular analog of the four-dimensional hypercube or tesseract which we called hypercubane. The title hydrocarbon (C40H24) is Oh-symmetric like cubane and is characterized by a double-shell architecture. The perfluorinated analog of hypercubane also is stable with a positive value of the electron affinity. Removal of the C8 core from hypercubane yields a hollowed Oh-symmetric hydrocarbon with enough room to host a single atom/ion guest. The resonances of the NMR-active 13C and 1H nuclei have been computed so as to assist the spectroscopic identification of the predicted molecules.

Efficient stochastic approaches for sensitivity studies of an Eulerian large-scale air pollution model

NASA Astrophysics Data System (ADS)

Dimov, I.; Georgieva, R.; Todorov, V.; Ostromsky, Tz.

2017-10-01

Reliability of large-scale mathematical models is an important issue when such models are used to support decision makers. Sensitivity analysis of model outputs to variation or natural uncertainties of model inputs is crucial for improving the reliability of mathematical models. A comprehensive experimental study of Monte Carlo algorithms based on Sobol sequences for multidimensional numerical integration has been done. A comparison with Latin hypercube sampling and a particular quasi-Monte Carlo lattice rule based on generalized Fibonacci numbers has been presented. The algorithms have been successfully applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters (six chemical reactions rates and four different groups of pollutants) on the concentrations of important air pollutants. The concentration values have been generated by the Unified Danish Eulerian Model. The sensitivity study has been done for the areas of several European cities with different geographical locations. The numerical tests show that the stochastic algorithms under consideration are efficient for multidimensional integration and especially for computing small by value sensitivity indices. It is a crucial element since even small indices may be important to be estimated in order to achieve a more accurate distribution of inputs influence and a more reliable interpretation of the mathematical model results.

Re-evaluation of the sorption behaviour of Bromide and Sulfamethazine under field conditions using leaching data and modelling methods

NASA Astrophysics Data System (ADS)

Gassmann, Matthias; Olsson, Oliver; Höper, Heinrich; Hamscher, Gerd; Kümmerer, Klaus

2016-04-01

The simulation of reactive transport in the aquatic environment is hampered by the ambiguity of environmental fate process conceptualizations for a specific substance in the literature. Concepts are usually identified by experimental studies and inverse modelling under controlled lab conditions in order to reduce environmental uncertainties such as uncertain boundary conditions and input data. However, since environmental conditions affect substance behaviour, a re-evaluation might be necessary under environmental conditions which might, in turn, be affected by uncertainties. Using a combination of experimental data and simulations of the leaching behaviour of the veterinary antibiotic Sulfamethazine (SMZ; synonym: sulfadimidine) and the hydrological tracer Bromide (Br) in a field lysimeter, we re-evaluated the sorption concepts of both substances under uncertain field conditions. Sampling data of a field lysimeter experiment in which both substances were applied twice a year with manure and sampled at the bottom of two lysimeters during three subsequent years was used for model set-up and evaluation. The total amount of leached SMZ and Br were 22 μg and 129 mg, respectively. A reactive transport model was parameterized to the conditions of the two lysimeters filled with monoliths (depth 2 m, area 1 m²) of a sandy soil showing a low pH value under which Bromide is sorptive. We used different sorption concepts such as constant and organic-carbon dependent sorption coefficients and instantaneous and kinetic sorption equilibrium. Combining the sorption concepts resulted in four scenarios per substance with different equations for sorption equilibrium and sorption kinetics. The GLUE (Generalized Likelihood Uncertainty Estimation) method was applied to each scenario using parameter ranges found in experimental and modelling studies. The parameter spaces for each scenario were sampled using a Latin Hypercube method which was refined around local model efficiency maxima. Results of the cumulative SMZ leaching simulations suggest a best conceptualization combination of instantaneous sorption to organic carbon which is consistent with the literature. The best Nash-Sutcliffe efficiency (Neff) was 0.96 and the 5th and 95th percentile of the uncertainty estimation were 18 and 27 μg. In contrast, both scenarios of kinetic Br sorption had similar results (Neff =0.99, uncertainty bounds 110-176 mg and 112-176 mg) but were clearly better than instantaneous sorption scenarios. Therefore, only the concept of sorption kinetics could be identified for Br modelling whereas both tested sorption equilibrium coefficient concepts performed equally well. The reasons for this specific case of equifinality may be uncertainties of model input data under field conditions or an insensitivity of the sorption equilibrium method due to relatively low adsorption of Br. Our results show that it may be possible to identify or at least falsify specific sorption concepts under uncertain field conditions using a long-term leaching experiment and modelling methods. Cases of environmental fate concept equifinality arouse the possibility of future model structure uncertainty analysis using an ensemble of models with different environmental fate concepts.

Modeling Soil Organic Carbon Variation Along Climatic and Topographic Trajectories in the Central Andes

NASA Astrophysics Data System (ADS)

Gavilan, C.; Grunwald, S.; Quiroz, R.; Zhu, L.

2015-12-01

The Andes represent the largest and highest mountain range in the tropics. Geological and climatic differentiation favored landscape and soil diversity, resulting in ecosystems adapted to very different climatic patterns. Although several studies support the fact that the Andes are a vast sink of soil organic carbon (SOC) only few have quantified this variable in situ. Estimating the spatial distribution of SOC stocks in data-poor and/or poorly accessible areas, like the Andean region, is challenging due to the lack of recent soil data at high spatial resolution and the wide range of coexistent ecosystems. Thus, the sampling strategy is vital in order to ensure the whole range of environmental covariates (EC) controlling SOC dynamics is represented. This approach allows grasping the variability of the area, which leads to more efficient statistical estimates and improves the modeling process. The objectives of this study were to i) characterize and model the spatial distribution of SOC stocks in the Central Andean region using soil-landscape modeling techniques, and to ii) validate and evaluate the model for predicting SOC content in the area. For that purpose, three representative study areas were identified and a suite of variables including elevation, mean annual temperature, annual precipitation and Normalized Difference Vegetation Index (NDVI), among others, was selected as EC. A stratified random sampling (namely conditioned Latin Hypercube) was implemented and a total of 400 sampling locations were identified. At all sites, four composite topsoil samples (0-30 cm) were collected within a 2 m radius. SOC content was measured using dry combustion and SOC stocks were estimated using bulk density measurements. Regression Kriging was used to map the spatial variation of SOC stocks. The accuracy, fit and bias of SOC models was assessed using a rigorous validation assessment. This study produced the first comprehensive, geospatial SOC stock assessment in this undersampled region that serves as a baseline reference to assess potential impacts of climate and land use change.

Regional prediction of soil organic carbon content over temperate croplands using visible near-infrared airborne hyperspectral imagery and synchronous field spectra

NASA Astrophysics Data System (ADS)

Vaudour, E.; Gilliot, J. M.; Bel, L.; Lefevre, J.; Chehdi, K.

2016-07-01

This study aimed at identifying the potential of Vis-NIR airborne hyperspectral AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with both contrasted soils and SOC contents, located in the western region of Paris, France. Soil types comprised haplic luvisols, calcaric cambisols and colluvic cambisols. Airborne AISA-Eagle data (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks. Tracks were atmospherically corrected then mosaicked at a 2 m-resolution using a set of 24 synchronous field spectra of bare soils, black and white targets and impervious surfaces. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then calculation and thresholding of NDVI from an atmospherically corrected SPOT image acquired the same day enabled to map agricultural fields with bare soil. A total of 101 sites sampled either in 2013 or in the 3 previous years and in 2015 were identified as bare by means of this map. Predictions were made from the mosaic AISA spectra which were related to topsoil SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples, considering 74 sites outside cloud shadows only, and different sampling strategies for selecting calibration samples. Validation root-mean-square errors (RMSE) were comprised between 3.73 and 4.49 g Kg-1 and were ∼4 g Kg-1 in median. The most performing models in terms of coefficient of determination (R2) and Residual Prediction Deviation (RPD) values were the calibration models derived either from Kennard-Stone or conditioned Latin Hypercube sampling on smoothed spectra. The most generalizable model leading to lowest RMSE value of 3.73 g Kg-1 at the regional scale and 1.44 g Kg-1 at the within-field scale and low bias was the cross-validated leave-one-out PLSR model constructed with the 28 near-synchronous samples and raw spectra.

Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

DOE PAGES

Qian, Yun; Yan, Huiping; Hou, Zhangshuan; ...

2015-04-10

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less

Simulating maize yield and bomass with spatial variability of soil field capacity

USGS Publications Warehouse

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Minimal spanning trees at the percolation threshold: a numerical calculation

NASA Astrophysics Data System (ADS)

Sweeney, Sean; Middleton, A. Alan

2013-03-01

Through computer simulations on a hypercubic lattice, we grow minimal spanning trees (MSTs) in up to five dimensions and examine their fractal dimensions. Understanding MSTs is imporant for studying systems with quenched disorder such as spin glasses. We implement a combination of Prim's and Kruskal's algorithms for finding MSTs in order to reduce memory usage and allow for simulation of larger systems than would otherwise be possible. These fractal objects are analyzed in an attempt to numerically verify predictions of the perturbation expansion developed by T. S. Jackson and N. Read for the pathlength fractal dimension ds of MSTs on percolation clusters at criticality [T. S. Jackson and N. Read, Phys. Rev. E 81, 021131 (2010)]. Examining these trees also sparked the development of an analysis technique for dealing with correlated data that could be easily generalized to other systems and should be a robust method for analyzing a wide array of randomly generated fractal structures. This work was made possible in part by NSF Grant No. DMR-1006731 and by the Syracuse University Gravitation and Relativity computing cluster, which is supported in part by NSF Grant No. PHY-0600953.

A probabilistic assessment of calcium carbonate export and dissolution in the modern ocean

NASA Astrophysics Data System (ADS)

Battaglia, G.; Steinacher, M.; Joos, F.

2015-12-01

The marine cycle of calcium carbonate (CaCO3) is an important element of the carbon cycle and co-governs the distribution of carbon and alkalinity within the ocean. However, CaCO3 fluxes and mechanisms governing CaCO3 dissolution are highly uncertain. We present an observationally-constrained, probabilistic assessment of the global and regional CaCO3 budgets. Parameters governing pelagic CaCO3 export fluxes and dissolution rates are sampled using a Latin-Hypercube scheme to construct a 1000 member ensemble with the Bern3D ocean model. Ensemble results are constrained by comparing simulated and observation-based fields of excess dissolved calcium carbonate (TA*). The minerals calcite and aragonite are modelled explicitly and ocean-sediment fluxes are considered. For local dissolution rates either a strong, a weak or no dependency on CaCO3 saturation is assumed. Median (68 % confidence interval) global CaCO3 export is 0.82 (0.67-0.98) Gt PIC yr-1, within the lower half of previously published estimates (0.4-1.8 Gt PIC yr-1). The spatial pattern of CaCO3 export is broadly consistent with earlier assessments. Export is large in the Southern Ocean, the tropical Indo-Pacific, the northern Pacific and relatively small in the Atlantic. Dissolution within the 200 to 1500 m depth range (0.33; 0.26-0.40 Gt PIC yr-1) is substantially lower than inferred from the TA*-CFC age method (1 ± 0.5 Gt PIC yr-1). The latter estimate is likely biased high as the TA*-CFC method neglects transport. The constrained results are robust across a range of diapycnal mixing coefficients and, thus, ocean circulation strengths. Modelled ocean circulation and transport time scales for the different setups were further evaluated with CFC11 and radiocarbon observations. Parameters and mechanisms governing dissolution are hardly constrained by either the TA* data or the current compilation of CaCO3 flux measurements such that model realisations with and without saturation-dependent dissolution achieve skill. We suggest to apply saturation-independent dissolution rates in Earth System Models to minimise computational costs.

Supporting shared data structures on distributed memory architectures

NASA Technical Reports Server (NTRS)

Koelbel, Charles; Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. A new programming environment is presented for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. The analysis and program transformations required to implement this environment are described, and the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes are described.

Group velocity of discrete-time quantum walks

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

Kempf, A.; Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1; Portugal, R.

2009-05-15

We show that certain types of quantum walks can be modeled as waves that propagate in a medium with phase and group velocities that are explicitly calculable. Since the group and phase velocities indicate how fast wave packets can propagate causally, we propose the use of these wave velocities in our definition for the hitting time of quantum walks. Our definition of hitting time has the advantage that it requires neither the specification of a walker's initial condition nor of an arrival probability threshold. We give full details for the case of quantum walks on the Cayley graphs of Abelianmore » groups. This includes the special cases of quantum walks on the line and on hypercubes.« less

Maximum projection designs for computer experiments

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

Joseph, V. Roshan; Gul, Evren; Ba, Shan

Space-filling properties are important in designing computer experiments. The traditional maximin and minimax distance designs only consider space-filling in the full dimensional space. This can result in poor projections onto lower dimensional spaces, which is undesirable when only a few factors are active. Restricting maximin distance design to the class of Latin hypercubes can improve one-dimensional projections, but cannot guarantee good space-filling properties in larger subspaces. We propose designs that maximize space-filling properties on projections to all subsets of factors. We call our designs maximum projection designs. As a result, our design criterion can be computed at a cost nomore » more than a design criterion that ignores projection properties.« less

Dimension improvement in Dhar's refutation of the Eden conjecture

NASA Astrophysics Data System (ADS)

Bertrand, Quentin; Pertinand, Jules

2018-03-01

We consider the Eden model on the d-dimensional hypercubical unoriented lattice, for large d. Initially, every lattice point is healthy, except the origin which is infected. Then, each infected lattice point contaminates any of its neighbours with rate 1. The Eden model is equivalent to first passage percolation, with exponential passage times on edges. The Eden conjecture states that the limit shape of the Eden model is a Euclidean ball. By pushing the computations of Dhar [5] a little further with modern computers and efficient implementation we obtain improved bounds for the speed of infection. This shows that the Eden conjecture does not hold in dimension superior to 22 (the lowest known dimension was 35).

A multiarchitecture parallel-processing development environment

NASA Technical Reports Server (NTRS)

Townsend, Scott; Blech, Richard; Cole, Gary

1993-01-01

A description is given of the hardware and software of a multiprocessor test bed - the second generation Hypercluster system. The Hypercluster architecture consists of a standard hypercube distributed-memory topology, with multiprocessor shared-memory nodes. By using standard, off-the-shelf hardware, the system can be upgraded to use rapidly improving computer technology. The Hypercluster's multiarchitecture nature makes it suitable for researching parallel algorithms in computational field simulation applications (e.g., computational fluid dynamics). The dedicated test-bed environment of the Hypercluster and its custom-built software allows experiments with various parallel-processing concepts such as message passing algorithms, debugging tools, and computational 'steering'. Such research would be difficult, if not impossible, to achieve on shared, commercial systems.

Maximum projection designs for computer experiments

DOE PAGES

Joseph, V. Roshan; Gul, Evren; Ba, Shan

2015-03-18

Space-filling properties are important in designing computer experiments. The traditional maximin and minimax distance designs only consider space-filling in the full dimensional space. This can result in poor projections onto lower dimensional spaces, which is undesirable when only a few factors are active. Restricting maximin distance design to the class of Latin hypercubes can improve one-dimensional projections, but cannot guarantee good space-filling properties in larger subspaces. We propose designs that maximize space-filling properties on projections to all subsets of factors. We call our designs maximum projection designs. As a result, our design criterion can be computed at a cost nomore » more than a design criterion that ignores projection properties.« less

Algorithms for synthesizing management solutions based on OLAP-technologies

NASA Astrophysics Data System (ADS)

Pishchukhin, A. M.; Akhmedyanova, G. F.

2018-05-01

OLAP technologies are a convenient means of analyzing large amounts of information. An attempt was made in their work to improve the synthesis of optimal management decisions. The developed algorithms allow forecasting the needs and accepted management decisions on the main types of the enterprise resources. Their advantage is the efficiency, based on the simplicity of quadratic functions and differential equations of only the first order. At the same time, the optimal redistribution of resources between different types of products from the assortment of the enterprise is carried out, and the optimal allocation of allocated resources in time. The proposed solutions can be placed on additional specially entered coordinates of the hypercube representing the data warehouse.

Parallel solution of high-order numerical schemes for solving incompressible flows

NASA Technical Reports Server (NTRS)

Milner, Edward J.; Lin, Avi; Liou, May-Fun; Blech, Richard A.

1993-01-01

A new parallel numerical scheme for solving incompressible steady-state flows is presented. The algorithm uses a finite-difference approach to solving the Navier-Stokes equations. The algorithms are scalable and expandable. They may be used with only two processors or with as many processors as are available. The code is general and expandable. Any size grid may be used. Four processors of the NASA LeRC Hypercluster were used to solve for steady-state flow in a driven square cavity. The Hypercluster was configured in a distributed-memory, hypercube-like architecture. By using a 50-by-50 finite-difference solution grid, an efficiency of 74 percent (a speedup of 2.96) was obtained.

Numerical studies of electron dynamics in oblique quasi-perpendicular collisionless shock waves

NASA Technical Reports Server (NTRS)

Liewer, P. C.; Decyk, V. K.; Dawson, J. M.; Lembege, B.

1991-01-01

Linear and nonlinear electron damping of the whistler precursor wave train to low Mach number quasi-perpendicular oblique shocks is studied using a one-dimensional electromagnetic plasma simulation code with particle electrons and ions. In some parameter regimes, electrons are observed to trap along the magnetic field lines in the potential of the whistler precursor wave train. This trapping can lead to significant electron heating in front of the shock for low beta(e). Use of a 64-processor hypercube concurrent computer has enabled long runs using realistic mass ratios in the full particle in-cell code and thus simulate shock parameter regimes and phenomena not previously studied numerically.

iCFD: Interpreted Computational Fluid Dynamics - Degeneration of CFD to one-dimensional advection-dispersion models using statistical experimental design - The secondary clarifier.

PubMed

Guyonvarch, Estelle; Ramin, Elham; Kulahci, Murat; Plósz, Benedek Gy

2015-10-15

The present study aims at using statistically designed computational fluid dynamics (CFD) simulations as numerical experiments for the identification of one-dimensional (1-D) advection-dispersion models - computationally light tools, used e.g., as sub-models in systems analysis. The objective is to develop a new 1-D framework, referred to as interpreted CFD (iCFD) models, in which statistical meta-models are used to calculate the pseudo-dispersion coefficient (D) as a function of design and flow boundary conditions. The method - presented in a straightforward and transparent way - is illustrated using the example of a circular secondary settling tank (SST). First, the significant design and flow factors are screened out by applying the statistical method of two-level fractional factorial design of experiments. Second, based on the number of significant factors identified through the factor screening study and system understanding, 50 different sets of design and flow conditions are selected using Latin Hypercube Sampling (LHS). The boundary condition sets are imposed on a 2-D axi-symmetrical CFD simulation model of the SST. In the framework, to degenerate the 2-D model structure, CFD model outputs are approximated by the 1-D model through the calibration of three different model structures for D. Correlation equations for the D parameter then are identified as a function of the selected design and flow boundary conditions (meta-models), and their accuracy is evaluated against D values estimated in each numerical experiment. The evaluation and validation of the iCFD model structure is carried out using scenario simulation results obtained with parameters sampled from the corners of the LHS experimental region. For the studied SST, additional iCFD model development was carried out in terms of (i) assessing different density current sub-models; (ii) implementation of a combined flocculation, hindered, transient and compression settling velocity function; and (iii) assessment of modelling the onset of transient and compression settling. Furthermore, the optimal level of model discretization both in 2-D and 1-D was undertaken. Results suggest that the iCFD model developed for the SST through the proposed methodology is able to predict solid distribution with high accuracy - taking a reasonable computational effort - when compared to multi-dimensional numerical experiments, under a wide range of flow and design conditions. iCFD tools could play a crucial role in reliably predicting systems' performance under normal and shock events. Copyright © 2015 Elsevier Ltd. All rights reserved.

Aerodynamic simulation on massively parallel systems

NASA Technical Reports Server (NTRS)

Haeuser, Jochem; Simon, Horst D.

1992-01-01

This paper briefly addresses the computational requirements for the analysis of complete configurations of aircraft and spacecraft currently under design to be used for advanced transportation in commercial applications as well as in space flight. The discussion clearly shows that massively parallel systems are the only alternative which is both cost effective and on the other hand can provide the necessary TeraFlops, needed to satisfy the narrow design margins of modern vehicles. It is assumed that the solution of the governing physical equations, i.e., the Navier-Stokes equations which may be complemented by chemistry and turbulence models, is done on multiblock grids. This technique is situated between the fully structured approach of classical boundary fitted grids and the fully unstructured tetrahedra grids. A fully structured grid best represents the flow physics, while the unstructured grid gives best geometrical flexibility. The multiblock grid employed is structured within a block, but completely unstructured on the block level. While a completely unstructured grid is not straightforward to parallelize, the above mentioned multiblock grid is inherently parallel, in particular for multiple instruction multiple datastream (MIMD) machines. In this paper guidelines are provided for setting up or modifying an existing sequential code so that a direct parallelization on a massively parallel system is possible. Results are presented for three parallel systems, namely the Intel hypercube, the Ncube hypercube, and the FPS 500 system. Some preliminary results for an 8K CM2 machine will also be mentioned. The code run is the two dimensional grid generation module of Grid, which is a general two dimensional and three dimensional grid generation code for complex geometries. A system of nonlinear Poisson equations is solved. This code is also a good testcase for complex fluid dynamics codes, since the same datastructures are used. All systems provided good speedups, but message passing MIMD systems seem to be best suited for large miltiblock applications.

Probabilistic risk assessment for a loss of coolant accident in McMaster Nuclear Reactor and application of reliability physics model for modeling human reliability

NASA Astrophysics Data System (ADS)

Ha, Taesung

A probabilistic risk assessment (PRA) was conducted for a loss of coolant accident, (LOCA) in the McMaster Nuclear Reactor (MNR). A level 1 PRA was completed including event sequence modeling, system modeling, and quantification. To support the quantification of the accident sequence identified, data analysis using the Bayesian method and human reliability analysis (HRA) using the accident sequence evaluation procedure (ASEP) approach were performed. Since human performance in research reactors is significantly different from that in power reactors, a time-oriented HRA model (reliability physics model) was applied for the human error probability (HEP) estimation of the core relocation. This model is based on two competing random variables: phenomenological time and performance time. The response surface and direct Monte Carlo simulation with Latin Hypercube sampling were applied for estimating the phenomenological time, whereas the performance time was obtained from interviews with operators. An appropriate probability distribution for the phenomenological time was assigned by statistical goodness-of-fit tests. The human error probability (HEP) for the core relocation was estimated from these two competing quantities: phenomenological time and operators' performance time. The sensitivity of each probability distribution in human reliability estimation was investigated. In order to quantify the uncertainty in the predicted HEPs, a Bayesian approach was selected due to its capability of incorporating uncertainties in model itself and the parameters in that model. The HEP from the current time-oriented model was compared with that from the ASEP approach. Both results were used to evaluate the sensitivity of alternative huinan reliability modeling for the manual core relocation in the LOCA risk model. This exercise demonstrated the applicability of a reliability physics model supplemented with a. Bayesian approach for modeling human reliability and its potential usefulness of quantifying model uncertainty as sensitivity analysis in the PRA model.

Probabilistic seismic history matching using binary images

NASA Astrophysics Data System (ADS)

Davolio, Alessandra; Schiozer, Denis Jose

2018-02-01

Currently, the goal of history-matching procedures is not only to provide a model matching any observed data but also to generate multiple matched models to properly handle uncertainties. One such approach is a probabilistic history-matching methodology based on the discrete Latin Hypercube sampling algorithm, proposed in previous works, which was particularly efficient for matching well data (production rates and pressure). 4D seismic (4DS) data have been increasingly included into history-matching procedures. A key issue in seismic history matching (SHM) is to transfer data into a common domain: impedance, amplitude or pressure, and saturation. In any case, seismic inversions and/or modeling are required, which can be time consuming. An alternative to avoid these procedures is using binary images in SHM as they allow the shape, rather than the physical values, of observed anomalies to be matched. This work presents the incorporation of binary images in SHM within the aforementioned probabilistic history matching. The application was performed with real data from a segment of the Norne benchmark case that presents strong 4D anomalies, including softening signals due to pressure build up. The binary images are used to match the pressurized zones observed in time-lapse data. Three history matchings were conducted using: only well data, well and 4DS data, and only 4DS. The methodology is very flexible and successfully utilized the addition of binary images for seismic objective functions. Results proved the good convergence of the method in few iterations for all three cases. The matched models of the first two cases provided the best results, with similar well matching quality. The second case provided models presenting pore pressure changes according to the expected dynamic behavior (pressurized zones) observed on 4DS data. The use of binary images in SHM is relatively new with few examples in the literature. This work enriches this discussion by presenting a new application to match pressure in a reservoir segment with complex pressure behavior.

Performance Improvement of a Return Channel in a Multistage Centrifugal Compressor Using Multiobjective Optimization.

PubMed

Nishida, Yoshifumi; Kobayashi, Hiromi; Nishida, Hideo; Sugimura, Kazuyuki

2013-05-01

The effect of the design parameters of a return channel on the performance of a multistage centrifugal compressor was numerically investigated, and the shape of the return channel was optimized using a multiobjective optimization method based on a genetic algorithm to improve the performance of the centrifugal compressor. The results of sensitivity analysis using Latin hypercube sampling suggested that the inlet-to-outlet area ratio of the return vane affected the total pressure loss in the return channel, and that the inlet-to-outlet radius ratio of the return vane affected the outlet flow angle from the return vane. Moreover, this analysis suggested that the number of return vanes affected both the loss and the flow angle at the outlet. As a result of optimization, the number of return vane was increased from 14 to 22 and the area ratio was decreased from 0.71 to 0.66. The radius ratio was also decreased from 2.1 to 2.0. Performance tests on a centrifugal compressor with two return channels (the original design and optimized design) were carried out using two-stage test apparatus. The measured flow distribution exhibited a swirl flow in the center region and a reversed swirl flow near the hub and shroud sides. The exit flow of the optimized design was more uniform than that of the original design. For the optimized design, the overall two-stage efficiency and pressure coefficient were increased by 0.7% and 1.5%, respectively. Moreover, the second-stage efficiency and pressure coefficient were respectively increased by 1.0% and 3.2%. It is considered that the increase in the second-stage efficiency was caused by the increased uniformity of the flow, and the rise in the pressure coefficient was caused by a decrease in the residual swirl flow. It was thus concluded from the numerical and experimental results that the optimized return channel improved the performance of the multistage centrifugal compressor.

Motor-response learning at a process control panel by an autonomous robot

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

Spelt, P.F.; de Saussure, G.; Lyness, E.

1988-01-01

The Center for Engineering Systems Advanced Research (CESAR) was founded at Oak Ridge National Laboratory (ORNL) by the Department of Energy's Office of Energy Research/Division of Engineering and Geoscience (DOE-OER/DEG) to conduct basic research in the area of intelligent machines. Therefore, researchers at the CESAR Laboratory are engaged in a variety of research activities in the field of machine learning. In this paper, we describe our approach to a class of machine learning which involves motor response acquisition using feedback from trial-and-error learning. Our formulation is being experimentally validated using an autonomous robot, learning tasks of control panel monitoring andmore » manipulation for effect process control. The CLIPS Expert System and the associated knowledge base used by the robot in the learning process, which reside in a hypercube computer aboard the robot, are described in detail. Benchmark testing of the learning process on a robot/control panel simulation system consisting of two intercommunicating computers is presented, along with results of sample problems used to train and test the expert system. These data illustrate machine learning and the resulting performance improvement in the robot for problems similar to, but not identical with, those on which the robot was trained. Conclusions are drawn concerning the learning problems, and implications for future work on machine learning for autonomous robots are discussed. 16 refs., 4 figs., 1 tab.« less

A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

NASA Astrophysics Data System (ADS)

Lienert, Sebastian; Joos, Fortunat

2018-05-01

A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211) PgC (median and 90 % confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

Thermal inclusions: how one spin can destroy a many-body localized phase

NASA Astrophysics Data System (ADS)

Ponte, Pedro; Laumann, C. R.; Huse, David A.; Chandran, A.

2017-10-01

Many-body localized (MBL) systems lie outside the framework of statistical mechanics, as they fail to equilibrate under their own quantum dynamics. Even basic features of MBL systems, such as their stability to thermal inclusions and the nature of the dynamical transition to thermalizing behaviour, remain poorly understood. We study a simple central spin model to address these questions: a two-level system interacting with strength J with N≫1 localized bits subject to random fields. On increasing J, the system transitions from an MBL to a delocalized phase on the vanishing scale Jc(N)˜1/N, up to logarithmic corrections. In the transition region, the single-site eigenstate entanglement entropies exhibit bimodal distributions, so that localized bits are either `on' (strongly entangled) or `off' (weakly entangled) in eigenstates. The clusters of `on' bits vary significantly between eigenstates of the same sample, which provides evidence for a heterogeneous discontinuous transition out of the localized phase in single-site observables. We obtain these results by perturbative mapping to bond percolation on the hypercube at small J and by numerical exact diagonalization of the full many-body system. Our results support the arguments that the MBL phase is unstable in systems with short-range interactions and quenched randomness in dimensions d that are high but finite. This article is part of the themed issue 'Breakdown of ergodicity in quantum systems: from solids to synthetic matter'.

A Monte Carlo risk assessment model for acrylamide formation in French fries.

PubMed

Cummins, Enda; Butler, Francis; Gormley, Ronan; Brunton, Nigel

2009-10-01

The objective of this study is to estimate the likely human exposure to the group 2a carcinogen, acrylamide, from French fries by Irish consumers by developing a quantitative risk assessment model using Monte Carlo simulation techniques. Various stages in the French-fry-making process were modeled from initial potato harvest, storage, and processing procedures. The model was developed in Microsoft Excel with the @Risk add-on package. The model was run for 10,000 iterations using Latin hypercube sampling. The simulated mean acrylamide level in French fries was calculated to be 317 microg/kg. It was found that females are exposed to smaller levels of acrylamide than males (mean exposure of 0.20 microg/kg bw/day and 0.27 microg/kg bw/day, respectively). Although the carcinogenic potency of acrylamide is not well known, the simulated probability of exceeding the average chronic human dietary intake of 1 microg/kg bw/day (as suggested by WHO) was 0.054 and 0.029 for males and females, respectively. A sensitivity analysis highlighted the importance of the selection of appropriate cultivars with known low reducing sugar levels for French fry production. Strict control of cooking conditions (correlation coefficient of 0.42 and 0.35 for frying time and temperature, respectively) and blanching procedures (correlation coefficient -0.25) were also found to be important in ensuring minimal acrylamide formation.

Development of a decision support tool for seasonal water supply management incorporating system uncertainties and operational constraints

NASA Astrophysics Data System (ADS)

Wang, H.; Asefa, T.

2017-12-01

A real-time decision support tool (DST) for water supply system would consider system uncertainties, e.g., uncertain streamflow and demand, as well as operational constraints and infrastructure outage (e.g., pump station shutdown, an offline reservoir due to maintenance). Such DST is often used by water managers for resource allocation and delivery for customers. Although most seasonal DST used by water managers recognize those system uncertainties and operational constraints, most use only historical information or assume deterministic outlook of water supply systems. This study presents a seasonal DST that incorporates rainfall/streamflow uncertainties, seasonal demand outlook and system operational constraints. Large scale climate-information is captured through a rainfall simulator driven by a Bayesian non-homogeneous Markov Chain Monte Carlo model that allows non-stationary transition probabilities contingent on Nino 3.4 index. An ad-hoc seasonal demand forecasting model considers weather conditions explicitly and socio-economic factors implicitly. Latin Hypercube sampling is employed to effectively sample probability density functions of flow and demand. Seasonal system operation is modelled as a mixed-integer optimization problem that aims at minimizing operational costs. It embeds the flexibility of modifying operational rules at different components, e.g., surface water treatment plants, desalination facilities, and groundwater pumping stations. The proposed framework is illustrated at a wholesale water supplier in Southeastern United States, Tampa Bay Water. The use of the tool is demonstrated in proving operational guidance in a typical drawdown and refill cycle of a regional reservoir. The DST provided: 1) probabilistic outlook of reservoir storage and chance of a successful refill by the end of rainy season; 2) operational expectations for large infrastructures (e.g., high service pumps and booster stations) throughout the season. Other potential use of such DST is also discussed.

Estimation of ice activation parameters within a particle tracking Lagrangian cloud model using the ensemble Kalman filter to match ISCDAC golden case observations

NASA Astrophysics Data System (ADS)

Reisner, J. M.; Dubey, M. K.

2010-12-01

To both quantify and reduce uncertainty in ice activation parameterizations for stratus clouds occurring in the temperature range between -5 to -10 C ensemble simulations of an ISDAC golden case have been conducted. To formulate the ensemble, three parameters found within an ice activation model have been sampled using a Latin hypercube technique over a parameter range that induces large variability in both number and mass of ice. The ice activation model is contained within a Lagrangian cloud model that simulates particle number as a function of radius for cloud ice, snow, graupel, cloud, and rain particles. A unique aspect of this model is that it produces very low levels of numerical diffusion that enable the model to accurately resolve the sharp cloud edges associated with the ISDAC stratus deck. Another important aspect of the model is that near the cloud edges the number of particles can be significantly increased to reduce sampling errors and accurately resolve physical processes such as collision-coalescence that occur in this region. Thus, given these relatively low numerical errors, as compared to traditional bin models, the sensitivity of a stratus deck to changes in parameters found within the activation model can be examined without fear of numerical contamination. Likewise, once the ensemble has been completed, ISDAC observations can be incorporated into a Kalman filter to optimally estimate the ice activation parameters and reduce overall model uncertainty. Hence, this work will highlight the ability of an ensemble Kalman filter system coupled to a highly accurate numerical model to estimate important parameters found within microphysical parameterizations containing high uncertainty.

Parallel Decomposition of the Fictitious Lagrangian Algorithm and its Accuracy for Molecular Dynamics Simulations of Semiconductors.

NASA Astrophysics Data System (ADS)

Yeh, Mei-Ling

We have performed a parallel decomposition of the fictitious Lagrangian method for molecular dynamics with tight-binding total energy expression into the hypercube computer. This is the first time in literature that the dynamical simulation of semiconducting systems containing more than 512 silicon atoms has become possible with the electrons treated as quantum particles. With the utilization of the Intel Paragon system, our timing analysis predicts that our code is expected to perform realistic simulations on very large systems consisting of thousands of atoms with time requirements of the order of tens of hours. Timing results and performance analysis of our parallel code are presented in terms of calculation time, communication time, and setup time. The accuracy of the fictitious Lagrangian method in molecular dynamics simulation is also investigated, especially the energy conservation of the total energy of ions. We find that the accuracy of the fictitious Lagrangian scheme in small silicon cluster and very large silicon system simulations is good for as long as the simulations proceed, even though we quench the electronic coordinates to the Born-Oppenheimer surface only in the beginning of the run. The kinetic energy of electrons does not increase as time goes on, and the energy conservation of the ionic subsystem remains very good. This means that, as far as the ionic subsystem is concerned, the electrons are on the average in the true quantum ground states. We also tie up some odds and ends regarding a few remaining questions about the fictitious Lagrangian method, such as the difference between the results obtained from the Gram-Schmidt and SHAKE method of orthonormalization, and differences between simulations where the electrons are quenched to the Born -Oppenheimer surface only once compared with periodic quenching.

Soil hydraulic material properties and layered architecture from time-lapse GPR

NASA Astrophysics Data System (ADS)

Jaumann, Stefan; Roth, Kurt

2018-04-01

Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global-local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg-Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).

Modeling uncertainty and correlation in soil properties using Restricted Pairing and implications for ensemble-based hillslope-scale soil moisture and temperature estimation

NASA Astrophysics Data System (ADS)

Flores, A. N.; Entekhabi, D.; Bras, R. L.

2007-12-01

Soil hydraulic and thermal properties (SHTPs) affect both the rate of moisture redistribution in the soil column and the volumetric soil water capacity. Adequately constraining these properties through field and lab analysis to parameterize spatially-distributed hydrology models is often prohibitively expensive. Because SHTPs vary significantly at small spatial scales individual soil samples are also only reliably indicative of local conditions, and these properties remain a significant source of uncertainty in soil moisture and temperature estimation. In ensemble-based soil moisture data assimilation, uncertainty in the model-produced prior estimate due to associated uncertainty in SHTPs must be taken into account to avoid under-dispersive ensembles. To treat SHTP uncertainty for purposes of supplying inputs to a distributed watershed model we use the restricted pairing (RP) algorithm, an extension of Latin Hypercube (LH) sampling. The RP algorithm generates an arbitrary number of SHTP combinations by sampling the appropriate marginal distributions of the individual soil properties using the LH approach, while imposing a target rank correlation among the properties. A previously-published meta- database of 1309 soils representing 12 textural classes is used to fit appropriate marginal distributions to the properties and compute the target rank correlation structure, conditioned on soil texture. Given categorical soil textures, our implementation of the RP algorithm generates an arbitrarily-sized ensemble of realizations of the SHTPs required as input to the TIN-based Realtime Integrated Basin Simulator with vegetation dynamics (tRIBS+VEGGIE) distributed parameter ecohydrology model. Soil moisture ensembles simulated with RP- generated SHTPs exhibit less variance than ensembles simulated with SHTPs generated by a scheme that neglects correlation among properties. Neglecting correlation among SHTPs can lead to physically unrealistic combinations of parameters that exhibit implausible hydrologic behavior when input to the tRIBS+VEGGIE model.

Applications and development of communication models for the touchstone GAMMA and DELTA prototypes

NASA Technical Reports Server (NTRS)

Seidel, Steven R.

1993-01-01

The goal of this project was to develop models of the interconnection networks of the Intel iPSC/860 and DELTA multicomputers to guide the design of efficient algorithms for interprocessor communication in problems that commonly occur in CFD codes and other applications. Interprocessor communication costs of codes for message-passing architectures such as the iPSC/860 and DELTA significantly affect the level of performance that can be obtained from those machines. This project addressed several specific problems in the achievement of efficient communication on the Intel iPSC/860 hypercube and DELTA mesh. In particular, an efficient global processor synchronization algorithm was developed for the iPSC/860 and numerous broadcast algorithms were designed for the DELTA.

samiDB: A Prototype Data Archive for Big Science Exploration

NASA Astrophysics Data System (ADS)

Konstantopoulos, I. S.; Green, A. W.; Cortese, L.; Foster, C.; Scott, N.

2015-04-01

samiDB is an archive, database, and query engine to serve the spectra, spectral hypercubes, and high-level science products that make up the SAMI Galaxy Survey. Based on the versatile Hierarchical Data Format (HDF5), samiDB does not depend on relational database structures and hence lightens the setup and maintenance load imposed on science teams by metadata tables. The code, written in Python, covers the ingestion, querying, and exporting of data as well as the automatic setup of an HTML schema browser. samiDB serves as a maintenance-light data archive for Big Science and can be adopted and adapted by science teams that lack the means to hire professional archivists to set up the data back end for their projects.

Traffic routing for multicomputer networks with virtual cut-through capability

NASA Technical Reports Server (NTRS)

Kandlur, Dilip D.; Shin, Kang G.

1992-01-01

Consideration is given to the problem of selecting routes for interprocess communication in a network with virtual cut-through capability, while balancing the network load and minimizing the number of times that a message gets buffered. An approach is proposed that formulates the route selection problem as a minimization problem with a link cost function that depends upon the traffic through the link. The form of this cost function is derived using the probability of establishing a virtual cut-through route. The route selection problem is shown to be NP-hard, and an algorithm is developed to incrementally reduce the cost by rerouting the traffic. The performance of this algorithm is exemplified by two network topologies: the hypercube and the C-wrapped hexagonal mesh.

Using Response Surface Methods to Correlate the Modal Test of an Inflatable Test Article

NASA Technical Reports Server (NTRS)

Gupta, Anju

2013-01-01

This paper presents a practical application of response surface methods (RSM) to correlate a finite element model of a structural modal test. The test article is a quasi-cylindrical inflatable structure which primarily consists of a fabric weave, with an internal bladder and metallic bulkheads on either end. To mitigate model size, the fabric weave was simplified by representing it with shell elements. The task at hand is to represent the material behavior of the weave. The success of the model correlation is measured by comparing the four major modal frequencies of the analysis model to the four major modal frequencies of the test article. Given that only individual strap material properties were provided and material properties of the overall weave were not available, defining the material properties of the finite element model became very complex. First it was necessary to determine which material properties (modulus of elasticity in the hoop and longitudinal directions, shear modulus, Poisson's ratio, etc.) affected the modal frequencies. Then a Latin Hypercube of the parameter space was created to form an efficiently distributed finite case set. Each case was then analyzed with the results input into RSM. In the resulting response surface it was possible to see how each material parameter affected the modal frequencies of the analysis model. If the modal frequencies of the analysis model and its corresponding parameters match the test with acceptable accuracy, it can be said that the model correlation is successful.

Robust human body model injury prediction in simulated side impact crashes.

PubMed

Golman, Adam J; Danelson, Kerry A; Stitzel, Joel D

2016-01-01

This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode.

PubMed

Beddows, Andrew V; Kitwiroon, Nutthida; Williams, Martin L; Beevers, Sean D

2017-06-06

Gaussian process emulation techniques have been used with the Community Multiscale Air Quality model, simulating the effects of input uncertainties on ozone and NO 2 output, to allow robust global sensitivity analysis (SA). A screening process ranked the effect of perturbations in 223 inputs, isolating the 30 most influential from emissions, boundary conditions (BCs), and reaction rates. Community Multiscale Air Quality (CMAQ) simulations of a July 2006 ozone pollution episode in the UK were made with input values for these variables plus ozone dry deposition velocity chosen according to a 576 point Latin hypercube design. Emulators trained on the output of these runs were used in variance-based SA of the model output to input uncertainties. Performing these analyses for every hour of a 21 day period spanning the episode and several days on either side allowed the results to be presented as a time series of sensitivity coefficients, showing how the influence of different input uncertainties changed during the episode. This is one of the most complex models to which these methods have been applied, and here, they reveal detailed spatiotemporal patterns of model sensitivities, with NO and isoprene emissions, NO 2 photolysis, ozone BCs, and deposition velocity being among the most influential input uncertainties.

Persistence in a Random Bond Ising Model of Socio-Econo Dynamics

NASA Astrophysics Data System (ADS)

Jain, S.; Yamano, T.

We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a finite temperature on hypercubic lattices in dimensions up to five. The model includes a "social" local field which contains the magnetization at time t. The nearest neighbour quenched interactions are drawn from a binary distribution which is a function of the bond concentration, p. The decay of the persistence probability in the model depends on both the spatial dimension and p. We find no evidence of "blocking" in this model. We also discuss the implications of our results for possible applications in the social and economic fields. It is suggested that the absence, or otherwise, of blocking could be used as a criterion to decide on the validity of a given model in different scenarios.

Speed and accuracy improvements in FLAASH atmospheric correction of hyperspectral imagery

NASA Astrophysics Data System (ADS)

Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael W.; Berk, Alexander; Bernstein, Lawrence S.; Lee, Jamine; Fox, Marsha

2012-11-01

Remotely sensed spectral imagery of the earth's surface can be used to fullest advantage when the influence of the atmosphere has been removed and the measurements are reduced to units of reflectance. Here, we provide a comprehensive summary of the latest version of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes atmospheric correction algorithm. We also report some new code improvements for speed and accuracy. These include the re-working of the original algorithm in C-language code parallelized with message passing interface and containing a new radiative transfer look-up table option, which replaces executions of the MODTRAN model. With computation times now as low as ~10 s per image per computer processor, automated, real-time, on-board atmospheric correction of hyper- and multi-spectral imagery is within reach.

A proposal for self-correcting stabilizer quantum memories in 3 dimensions (or slightly less)

NASA Astrophysics Data System (ADS)

Brell, Courtney G.

2016-01-01

We propose a family of local CSS stabilizer codes as possible candidates for self-correcting quantum memories in 3D. The construction is inspired by the classical Ising model on a Sierpinski carpet fractal, which acts as a classical self-correcting memory. Our models are naturally defined on fractal subsets of a 4D hypercubic lattice with Hausdorff dimension less than 3. Though this does not imply that these models can be realized with local interactions in {{{R}}}3, we also discuss this possibility. The X and Z sectors of the code are dual to one another, and we show that there exists a finite temperature phase transition associated with each of these sectors, providing evidence that the system may robustly store quantum information at finite temperature.

A message passing kernel for the hypercluster parallel processing test bed

NASA Technical Reports Server (NTRS)

Blech, Richard A.; Quealy, Angela; Cole, Gary L.

1989-01-01

A Message-Passing Kernel (MPK) for the Hypercluster parallel-processing test bed is described. The Hypercluster is being developed at the NASA Lewis Research Center to support investigations of parallel algorithms and architectures for computational fluid and structural mechanics applications. The Hypercluster resembles the hypercube architecture except that each node consists of multiple processors communicating through shared memory. The MPK efficiently routes information through the Hypercluster, using a message-passing protocol when necessary and faster shared-memory communication whenever possible. The MPK also interfaces all of the processors with the Hypercluster operating system (HYCLOPS), which runs on a Front-End Processor (FEP). This approach distributes many of the I/O tasks to the Hypercluster processors and eliminates the need for a separate I/O support program on the FEP.

Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor.

PubMed

Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

2015-07-31

The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.

Label-free reflectance hyperspectral imaging for tumor margin assessment: a pilot study on surgical specimens of cancer patients

NASA Astrophysics Data System (ADS)

Fei, Baowei; Lu, Guolan; Wang, Xu; Zhang, Hongzheng; Little, James V.; Patel, Mihir R.; Griffith, Christopher C.; El-Diery, Mark W.; Chen, Amy Y.

2017-08-01

A label-free, hyperspectral imaging (HSI) approach has been proposed for tumor margin assessment. HSI data, i.e., hypercube (x,y,λ), consist of a series of high-resolution images of the same field of view that are acquired at different wavelengths. Every pixel on an HSI image has an optical spectrum. In this pilot clinical study, a pipeline of a machine-learning-based quantification method for HSI data was implemented and evaluated in patient specimens. Spectral features from HSI data were used for the classification of cancer and normal tissue. Surgical tissue specimens were collected from 16 human patients who underwent head and neck (H&N) cancer surgery. HSI, autofluorescence images, and fluorescence images with 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl)amino]-D-glucose (2-NBDG) and proflavine were acquired from each specimen. Digitized histologic slides were examined by an H&N pathologist. The HSI and classification method were able to distinguish between cancer and normal tissue from the oral cavity with an average accuracy of 90%±8%, sensitivity of 89%±9%, and specificity of 91%±6%. For tissue specimens from the thyroid, the method achieved an average accuracy of 94%±6%, sensitivity of 94%±6%, and specificity of 95%±6%. HSI outperformed autofluorescence imaging or fluorescence imaging with vital dye (2-NBDG or proflavine). This study demonstrated the feasibility of label-free, HSI for tumor margin assessment in surgical tissue specimens of H&N cancer patients. Further development of the HSI technology is warranted for its application in image-guided surgery.

Retrospective and current risks of mercury to panthers in the Florida Everglades.

PubMed

Barron, Mace G; Duvall, Stephanie E; Barron, Kyle J

2004-04-01

Florida panthers are an endangered species inhabiting south Florida. Hg has been suggested as a causative factor for low populations and some reported panther deaths, but a quantitative assessment of risks has never been performed. This study quantitatively evaluated retrospective (pre-1992) and current (2002) risks of chronic dietary Hg exposures to panthers in the Florida Everglades. A probabilistic assessment of Hg risks was performed using a dietary exposure model and Latin Hypercube sampling that incorporated the variability and uncertainty in ingestion rate, diet, body weight, and mercury exposure of panthers. Hazard quotients (HQs) for retrospective risks ranged from less than 0.1-20, with a 46% probability of exceeding chronic dietary thresholds for methylmercury. Retrospective risks of developing clinical symptoms, including ataxia and convulsions, had an HQ range of <0.1-5.4 with a 17% probability of exceeding an HQ of 1. Current risks were substantially lower (4% probability of exceedences; HQ range <0.1-3.5) because of an estimated 70-90% decline in Hg exposure to panthers over the last decade. Under worst case conditions of panthers consuming only raccoons from the most contaminated area of the Everglades, current risks of developing clinical symptoms that may lead to death was 4.6%. Current risks of mercury poisoning of panthers with a diversified diet was 0.1% (HQ range of <0.1-1.4). The results of this assessment indicate that past Hg exposures likely adversely affected panthers in the Everglades, but current risks of Hg are low.

A parallel offline CFD and closed-form approximation strategy for computationally efficient analysis of complex fluid flows

NASA Astrophysics Data System (ADS)

Allphin, Devin

Computational fluid dynamics (CFD) solution approximations for complex fluid flow problems have become a common and powerful engineering analysis technique. These tools, though qualitatively useful, remain limited in practice by their underlying inverse relationship between simulation accuracy and overall computational expense. While a great volume of research has focused on remedying these issues inherent to CFD, one traditionally overlooked area of resource reduction for engineering analysis concerns the basic definition and determination of functional relationships for the studied fluid flow variables. This artificial relationship-building technique, called meta-modeling or surrogate/offline approximation, uses design of experiments (DOE) theory to efficiently approximate non-physical coupling between the variables of interest in a fluid flow analysis problem. By mathematically approximating these variables, DOE methods can effectively reduce the required quantity of CFD simulations, freeing computational resources for other analytical focuses. An idealized interpretation of a fluid flow problem can also be employed to create suitably accurate approximations of fluid flow variables for the purposes of engineering analysis. When used in parallel with a meta-modeling approximation, a closed-form approximation can provide useful feedback concerning proper construction, suitability, or even necessity of an offline approximation tool. It also provides a short-circuit pathway for further reducing the overall computational demands of a fluid flow analysis, again freeing resources for otherwise unsuitable resource expenditures. To validate these inferences, a design optimization problem was presented requiring the inexpensive estimation of aerodynamic forces applied to a valve operating on a simulated piston-cylinder heat engine. The determination of these forces was to be found using parallel surrogate and exact approximation methods, thus evidencing the comparative benefits of this technique. For the offline approximation, latin hypercube sampling (LHS) was used for design space filling across four (4) independent design variable degrees of freedom (DOF). Flow solutions at the mapped test sites were converged using STAR-CCM+ with aerodynamic forces from the CFD models then functionally approximated using Kriging interpolation. For the closed-form approximation, the problem was interpreted as an ideal 2-D converging-diverging (C-D) nozzle, where aerodynamic forces were directly mapped by application of the Euler equation solutions for isentropic compression/expansion. A cost-weighting procedure was finally established for creating model-selective discretionary logic, with a synthesized parallel simulation resource summary provided.

ArcGIS Framework for Scientific Data Analysis and Serving

NASA Astrophysics Data System (ADS)

Xu, H.; Ju, W.; Zhang, J.

2015-12-01

ArcGIS is a platform for managing, visualizing, analyzing, and serving geospatial data. Scientific data as part of the geospatial data features multiple dimensions (X, Y, time, and depth) and large volume. Multidimensional mosaic dataset (MDMD), a newly enhanced data model in ArcGIS, models the multidimensional gridded data (e.g. raster or image) as a hypercube and enables ArcGIS's capabilities to handle the large volume and near-real time scientific data. Built on top of geodatabase, the MDMD stores the dimension values and the variables (2D arrays) in a geodatabase table which allows accessing a slice or slices of the hypercube through a simple query and supports animating changes along time or vertical dimension using ArcGIS desktop or web clients. Through raster types, MDMD can manage not only netCDF, GRIB, and HDF formats but also many other formats or satellite data. It is scalable and can handle large data volume. The parallel geo-processing engine makes the data ingestion fast and easily. Raster function, definition of a raster processing algorithm, is a very important component in ArcGIS platform for on-demand raster processing and analysis. The scientific data analytics is achieved through the MDMD and raster function templates which perform on-demand scientific computation with variables ingested in the MDMD. For example, aggregating monthly average from daily data; computing total rainfall of a year; calculating heat index for forecasting data, and identifying fishing habitat zones etc. Addtionally, MDMD with the associated raster function templates can be served through ArcGIS server as image services which provide a framework for on-demand server side computation and analysis, and the published services can be accessed by multiple clients such as ArcMap, ArcGIS Online, JavaScript, REST, WCS, and WMS. This presentation will focus on the MDMD model and raster processing templates. In addtion, MODIS land cover, NDFD weather service, and HYCOM ocean model will be used to illustrate how ArcGIS platform and MDMD model can facilitate scientific data visualization and analytics and how the analysis results can be shared to more audience through ArcGIS Online and Portal.

A soil-specific agro-ecological strategy for sustainable production in Argentina farm fields

NASA Astrophysics Data System (ADS)

Zamora, Martin; Barbera, Agustin; Castro-Franco, Mauricio; Hansson, Alejandro; Domenech, Marisa

2017-04-01

The continuous increment of frequencies and doses of pesticides, glyphosate and fertilizers, the deterioration of the structure, biotic balance and fertility of soils and the ground water pollution are characteristics of the current Argentinian agricultural model. In this context, agro-ecological innovations are needed to develop a real sustainable agriculture, enhancing the food supply. Precision agriculture technologies can strengthen the expansion of agro-ecological farming in experimental farm fields. The aim of this study was to propose a soil-specific agro-ecological strategy for sustainable production at field scale focused on the use of soil sensors and digital soil mapping techniques. This strategy has been developed in 15 hectares transition agro-ecological farm field, located at Barrow Experimental Station (Lat:-38.322844, Lon:-60.25572) Argentina. The strategy included five steps: (i) to measure apparent electrical conductivity (ECa) and elevation within agro-ecological farm field; (ii) to apply a clustering method using MULTISPATI-PCA algorithm to delimitate three soil-specific zones (Z1, Z2 and Z3); (iii) to determine three soil sampling points by zone, using conditioned Latin hypercube method, in addition to elevation and ECa as auxiliary information; (iv) to collect soil samples at 2-10 cm depth in each point and to determine in laboratory: total organic carbon content (TOC), cation-exchange capacity (CEC), pH and phosphorus availability (P-Bray). In addition, soil bulk density (SBD) was measured at 0-20 cm depth. Finally, (v) according to each soil-specific zone, a management strategy was recommended. Important differences in soil properties among zones could suggest that the strategy developed was able to apply an agro ecological soil-specific practice management. pH and P-Bray were significantly (p<0.05) higher in Z1 than in Z2 and Z3. TOC did not show significant difference among zones, but it was higher in Z2. CEC was significantly (p<0.05) lower in Z3 than in the other ones. SBD did not show significant difference among zones; however it had a higher content in Z1. From these results, we propose an agro ecology strategy which involves a continuous nutrient cycling. During the first two years, P-Bray levels will be adjusted among zones, by using different external phosphorous sources. Only in Z3, this strategy will be achieved adding P fertilizer and also rotating plots with high stocking rate. The aim is to increase soil organic matter content and CEC. Furthermore, P content will be supplied through manure because the animal nutrition will include wheat husk, in order to achieve similar P levels among zones. The proposed strategy demonstrated that the agro-ecology soil-specific management allows a sustainable scheme in Argentinian agro-productive systems.

Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

NASA Astrophysics Data System (ADS)

Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

2005-10-01

Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

Optimization of Heat Exchangers with Dimpled Surfaces to Improve the Performance in Thermoelectric Generators Using a Kriging Model

NASA Astrophysics Data System (ADS)

Li, Shuai; Wang, Yiping; Wang, Tao; Yang, Xue; Deng, Yadong; Su, Chuqi

2017-05-01

Thermoelectric generators (TEGs) have become a topic of interest for vehicle exhaust energy recovery. Electrical power generation is deeply influenced by temperature differences, temperature uniformity and topological structures of TEGs. When the dimpled surfaces are adopted in heat exchangers, the heat transfer rates can be augmented with a minimal pressure drop. However, the temperature distribution shows a large gradient along the flow direction which has adverse effects on the power generation. In the current study, the heat exchanger performance was studied in a computational fluid dynamics (CFD) model. The dimple depth, dimple print diameter, and channel height were chosen as design variables. The objective function was defined as a combination of average temperature, temperature uniformity and pressure loss. The optimal Latin hypercube method was used to determine the experiment points as a method of design of the experiment in order to analyze the sensitivity of the design variables. A Kriging surrogate model was built and verified according to the database resulting from the CFD simulation. A multi-island genetic algorithm was used to optimize the structure in the heat exchanger based on the surrogate model. The results showed that the average temperature of the heat exchanger was most sensitive to the dimple depth. The pressure loss and temperature uniformity were most sensitive to the parameter of channel rear height, h 2. With an optimal design of channel structure, the temperature uniformity can be greatly improved compared with the initial exchanger, and the additional pressure loss also increased.

Concurrent Image Processing Executive (CIPE). Volume 3: User's guide

NASA Technical Reports Server (NTRS)

Lee, Meemong; Cooper, Gregory T.; Groom, Steven L.; Mazer, Alan S.; Williams, Winifred I.; Kong, Mih-Seh

1990-01-01

CIPE (the Concurrent Image Processing Executive) is both an executive which organizes the parameter inputs for hypercube applications and an environment which provides temporary data workspace and simple real-time function definition facilities for image analysis. CIPE provides two types of user interface. The Command Line Interface (CLI) provides a simple command-driven environment allowing interactive function definition and evaluation of algebraic expressions. The menu interface employs a hierarchical screen-oriented menu system where the user is led through a menu tree to any specific application and then given a formatted panel screen for parameter entry. How to initialize the system through the setup function, how to read data into CIPE symbols, how to manipulate and display data through the use of executive functions, and how to run an application in either user interface mode, are described.

Connectivity is a Poor Indicator of Fast Quantum Search

NASA Astrophysics Data System (ADS)

Meyer, David A.; Wong, Thomas G.

2015-03-01

A randomly walking quantum particle evolving by Schrödinger's equation searches on d -dimensional cubic lattices in O (√{N }) time when d ≥5 , and with progressively slower runtime as d decreases. This suggests that graph connectivity (including vertex, edge, algebraic, and normalized algebraic connectivities) is an indicator of fast quantum search, a belief supported by fast quantum search on complete graphs, strongly regular graphs, and hypercubes, all of which are highly connected. In this Letter, we show this intuition to be false by giving two examples of graphs for which the opposite holds true: one with low connectivity but fast search, and one with high connectivity but slow search. The second example is a novel two-stage quantum walk algorithm in which the walking rate must be adjusted to yield high search probability.

The fuzzy polynucleotide space: basic properties.

PubMed

Torres, Angela; Nieto, Juan J

2003-03-22

Any triplet codon may be regarded as a 12-dimensional fuzzy code. Sufficient information about a particular sequence may not be available in certain situations. The investigator will be confronted with imprecise sequences, yet want to make comparisons of sequences. Fuzzy polynucleotides can be compared by using geometrical interpretation of fuzzy sets as points in a hypercube. We introduce the space of fuzzy polynucleotides and a means of measuring dissimilitudes between them. We establish mathematical principles to measure dissimilarities between fuzzy polynucleotides and present several examples in this metric space. We calculate the frequencies of the nucleotides at the three base sites of a codon in the coding sequences of Escherichia coli K-12 and Mycobacterium tuberculosis H37Rv, and consider them as points in that fuzzy space. We compute the distance between the genomes of E.coli and M.tuberculosis.

Restoration of rotational symmetry in the continuum limit of lattice field theories

NASA Astrophysics Data System (ADS)

Davoudi, Zohreh; Savage, Martin J.

2012-09-01

We explore how rotational invariance is systematically recovered from calculations on hyper-cubic lattices through the use of smeared lattice operators that smoothly evolve into continuum operators with definite angular momentum as the lattice-spacing is reduced. Perturbative calculations of the angular momentum violation associated with such operators at tree level and at one loop are presented in λϕ4 theory and QCD. Contributions from these operators that violate rotational invariance occur at tree-level, with coefficients that are suppressed by O(a2) in the continuum limit. Quantum loops do not modify this behavior in λϕ4, nor in QCD if the gauge-fields are smeared over a comparable spatial region. Consequently, the use of this type of operator should, in principle, allow for Lattice QCD calculations of the higher moments of the hadron structure functions.

Numerical Evidence for a Phase Transition in 4D Spin-Foam Quantum Gravity

NASA Astrophysics Data System (ADS)

Bahr, Benjamin; Steinhaus, Sebastian

2016-09-01

Building on recent advances in defining Wilsonian renormalization group (RG) flows, and the notion of scales in particular, for background-independent theories, we present a first investigation of the renormalization of the 4D spin-foam path integral for quantum gravity, both analytically and numerically. Focusing on a specific truncation of the model using a hypercubic lattice, we compute the RG flow and find strong indications for a phase transition, as well as an interesting interplay between the different observed phases and the (broken) diffeomorphism symmetry of the model. Most notably, it appears that the critical point between the phases, which is a fixed point of the RG flow, is precisely where broken diffeomorphism symmetry is restored, which suggests that it might allow us to define a continuum limit of the quantum gravity theory.

Numerical Evidence for a Phase Transition in 4D Spin-Foam Quantum Gravity.

PubMed

Bahr, Benjamin; Steinhaus, Sebastian

2016-09-30

Building on recent advances in defining Wilsonian renormalization group (RG) flows, and the notion of scales in particular, for background-independent theories, we present a first investigation of the renormalization of the 4D spin-foam path integral for quantum gravity, both analytically and numerically. Focusing on a specific truncation of the model using a hypercubic lattice, we compute the RG flow and find strong indications for a phase transition, as well as an interesting interplay between the different observed phases and the (broken) diffeomorphism symmetry of the model. Most notably, it appears that the critical point between the phases, which is a fixed point of the RG flow, is precisely where broken diffeomorphism symmetry is restored, which suggests that it might allow us to define a continuum limit of the quantum gravity theory.

An efficient parallel algorithm for matrix-vector multiplication

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

Hendrickson, B.; Leland, R.; Plimpton, S.

The multiplication of a vector by a matrix is the kernel computation of many algorithms in scientific computation. A fast parallel algorithm for this calculation is therefore necessary if one is to make full use of the new generation of parallel supercomputers. This paper presents a high performance, parallel matrix-vector multiplication algorithm that is particularly well suited to hypercube multiprocessors. For an n x n matrix on p processors, the communication cost of this algorithm is O(n/[radical]p + log(p)), independent of the matrix sparsity pattern. The performance of the algorithm is demonstrated by employing it as the kernel in themore » well-known NAS conjugate gradient benchmark, where a run time of 6.09 seconds was observed. This is the best published performance on this benchmark achieved to date using a massively parallel supercomputer.« less

Reducing space overhead for independendent checkpointing

NASA Technical Reports Server (NTRS)

Wang, Yi-Min; Chung, Pi-Yu; Lin, In-Jen; Fuchs, W. Kent

1992-01-01

The main disadvantages of independent checkpointing are the possible domino effect and the associated storage space overhead for maintaining multiple checkpoints. In most previous work, it has been assumed that only the checkpoints older than the current global recovery line can be discarded. Here, we generalize a notion of recovery line to potential recovery line. Only the checkpoints belonging to at least one of the potential recovery lines cannot be discarded. By using the model of maximum-sized antichains on a partially ordered set, an efficient algorithm is developed for finding all non-discardable checkpoints, and we show that the number of non-discardable checkpoints cannot exceed N(N+1)/2, where N is the number of processors. Communication trace driven simulation for several hypercube programs is performed to show the benefit of the proposed algorithm for real applications.

iTOUGH2 v7.1

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

FINSTERLE, STEFAN; JUNG, YOOJIN; KOWALSKY, MICHAEL

2016-09-15

iTOUGH2 (inverse TOUGH2) provides inverse modeling capabilities for TOUGH2, a simulator for multi-dimensional, multi-phase, multi-component, non-isothermal flow and transport in fractured porous media. iTOUGH2 performs sensitivity analyses, data-worth analyses, parameter estimation, and uncertainty propagation analyses in geosciences and reservoir engineering and other application areas. iTOUGH2 supports a number of different combinations of fluids and components (equation-of-state (EOS) modules). In addition, the optimization routines implemented in iTOUGH2 can also be used for sensitivity analysis, automatic model calibration, and uncertainty quantification of any external code that uses text-based input and output files using the PEST protocol. iTOUGH2 solves the inverse problem bymore » minimizing a non-linear objective function of the weighted differences between model output and the corresponding observations. Multiple minimization algorithms (derivative-free, gradient-based, and second-order; local and global) are available. iTOUGH2 also performs Latin Hypercube Monte Carlo simulations for uncertainty propagation analyses. A detailed residual and error analysis is provided. This upgrade includes (a) global sensitivity analysis methods, (b) dynamic memory allocation (c) additional input features and output analyses, (d) increased forward simulation capabilities, (e) parallel execution on multicore PCs and Linux clusters, and (f) bug fixes. More details can be found at http://esd.lbl.gov/iTOUGH2.« less

Model of random center vortex lines in continuous 2 +1 -dimensional spacetime

NASA Astrophysics Data System (ADS)

Altarawneh, Derar; Engelhardt, Michael; Höllwieser, Roman

2016-12-01

A picture of confinement in QCD based on a condensate of thick vortices with fluxes in the center of the gauge group (center vortices) is studied. Previous concrete model realizations of this picture utilized a hypercubic space-time scaffolding, which, together with many advantages, also has some disadvantages, e.g., in the treatment of vortex topological charge. In the present work, we explore a center vortex model which does not rely on such a scaffolding. Vortices are represented by closed random lines in continuous 2 +1 -dimensional space-time. These random lines are modeled as being piecewise linear, and an ensemble is generated by Monte Carlo methods. The physical space in which the vortex lines are defined is a torus with periodic boundary conditions. Besides moving, growing, and shrinking of the vortex configurations, also reconnections are allowed. Our ensemble therefore contains not a fixed but a variable number of closed vortex lines. This is expected to be important for realizing the deconfining phase transition. We study both vortex percolation and the potential V (R ) between the quark and antiquark as a function of distance R at different vortex densities, vortex segment lengths, reconnection conditions, and at different temperatures. We find three deconfinement phase transitions, as a function of density, as a function of vortex segment length, and as a function of temperature.

Deriving global parameter estimates for the Noah land surface model using FLUXNET and machine learning

NASA Astrophysics Data System (ADS)

Chaney, Nathaniel W.; Herman, Jonathan D.; Ek, Michael B.; Wood, Eric F.

2016-11-01

With their origins in numerical weather prediction and climate modeling, land surface models aim to accurately partition the surface energy balance. An overlooked challenge in these schemes is the role of model parameter uncertainty, particularly at unmonitored sites. This study provides global parameter estimates for the Noah land surface model using 85 eddy covariance sites in the global FLUXNET network. The at-site parameters are first calibrated using a Latin Hypercube-based ensemble of the most sensitive parameters, determined by the Sobol method, to be the minimum stomatal resistance (rs,min), the Zilitinkevich empirical constant (Czil), and the bare soil evaporation exponent (fxexp). Calibration leads to an increase in the mean Kling-Gupta Efficiency performance metric from 0.54 to 0.71. These calibrated parameter sets are then related to local environmental characteristics using the Extra-Trees machine learning algorithm. The fitted Extra-Trees model is used to map the optimal parameter sets over the globe at a 5 km spatial resolution. The leave-one-out cross validation of the mapped parameters using the Noah land surface model suggests that there is the potential to skillfully relate calibrated model parameter sets to local environmental characteristics. The results demonstrate the potential to use FLUXNET to tune the parameterizations of surface fluxes in land surface models and to provide improved parameter estimates over the globe.

Within-field and regional-scale accuracies of topsoil organic carbon content prediction from an airborne visible near-infrared hyperspectral image combined with synchronous field spectra for temperate croplands

NASA Astrophysics Data System (ADS)

Vaudour, Emmanuelle; Gilliot, Jean-Marc; Bel, Liliane; Lefevre, Josias; Chehdi, Kacem

2016-04-01

This study was carried out in the framework of the TOSCA-PLEIADES-CO of the French Space Agency and benefited data from the earlier PROSTOCK-Gessol3 project supported by the French Environment and Energy Management Agency (ADEME). It aimed at identifying the potential of airborne hyperspectral visible near-infrared AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with intensive annual crop cultivation and both contrasted soils and SOC contents, located in the western region of Paris, France. Soils comprise hortic or glossic luvisols, calcaric, rendzic cambisols and colluvic cambisols. Airborne AISA-Eagle images (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks. Tracks were atmospherically corrected then mosaicked at a 2 m-resolution using a set of 24 synchronous field spectra of bare soils, black and white targets and impervious surfaces. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then calculation and thresholding of NDVI from an atmospherically corrected SPOT4 image acquired the same day enabled to map agricultural fields with bare soil. A total of 101 sites, which were sampled either at the regional scale or within one field, were identified as bare by means of this map. Predictions were made from the mosaic AISA spectra which were related to SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples, considering those 75 sites outside cloud shadows only, and different sampling strategies for selecting calibration samples. Validation root-mean-square errors (RMSE) were comprised between 3.73 and 4.49 g. Kg-1 and were ~4 g. Kg-1 in median. The most performing models in terms of coefficient of determination (R²) and Residual Prediction Deviation (RPD) values were the calibration models derived either from Kennard-Stone or conditioned Latin Hypercube sampling on smoothed spectra. However, the most generalizable model leading to lowest RMSE value of 3.73 g. Kg-1 at the regional scale and 1.44 g. Kg-1 at the within-field scale and low validation bias was the cross-validated leave-one-out PLSR model constructed with the 28 near-synchronous samples and raw spectra.

Understanding controls of hydrologic processes across two headwater monolithological catchments using model-data synthesis

NASA Astrophysics Data System (ADS)

Xiao, D.; Shi, Y.; Hoagland, B.; Del Vecchio, J.; Russo, T. A.; DiBiase, R. A.; Li, L.

2017-12-01

How do watershed hydrologic processes differ in catchments derived from different lithology? This study compares two first order, deciduous forest watersheds in Pennsylvania, a sandstone watershed, Garner Run (GR, 1.34 km2), and a shale-derived watershed, Shale Hills (SH, 0.08 km2). Both watersheds are simulated using a combination of national datasets and field measurements, and a physics-based land surface hydrologic model, Flux-PIHM. We aim to evaluate the effects of lithology on watershed hydrology and assess if we can simulate a new watershed without intensive measurements, i.e., directly use calibration information from one watershed (SH) to reproduce hydrologic dynamics of another watershed (GR). Without any calibration, the model at GR based on national datasets and calibration inforamtion from SH cannot capture some discharge peaks or the baseflow during dry periods. The model prediction agrees well with the GR field discharge and soil moisture after calibrating the soil hydraulic parameters using the uncertainty based Hornberger-Spear-Young algorithm and the Latin Hypercube Sampling method. Agreeing with the field observation and national datasets, the difference in parameter values shows that the sandstone watershed has a larger averaged soil pore diameter, greater water storage created by porosity, lower water retention ability, and greater preferential flow. The water budget calculation shows that the riparian zone and the colluvial valley serves as buffer zones that stores water at GR. Using the same procedure, we compared Flux-PIHM simulations with and without a field measured surface boulder map at GR. When the boulder map is used, the prediction of areal averaged soil moisture is improved, without performing extra calibration. When calibrated separately, the cases with or without boulder map yield different calibration values, but their hydrologic predictions are similar, showing equifinality. The calibrated soil hydraulic parameter values in the with boulder map case is more physically plausible than the without boulder map case. We switched the topography and soil properties between GR and SH, and results indicate that the hydrologic processes are more sensitive to changes in domain topography than to changes in the soil properties.

Uncertainty Analysis of Simulated Hydraulic Fracturing

NASA Astrophysics Data System (ADS)

Chen, M.; Sun, Y.; Fu, P.; Carrigan, C. R.; Lu, Z.

2012-12-01

Artificial hydraulic fracturing is being used widely to stimulate production of oil, natural gas, and geothermal reservoirs with low natural permeability. Optimization of field design and operation is limited by the incomplete characterization of the reservoir, as well as the complexity of hydrological and geomechanical processes that control the fracturing. Thus, there are a variety of uncertainties associated with the pre-existing fracture distribution, rock mechanics, and hydraulic-fracture engineering that require evaluation of their impact on the optimized design. In this study, a multiple-stage scheme was employed to evaluate the uncertainty. We first define the ranges and distributions of 11 input parameters that characterize the natural fracture topology, in situ stress, geomechanical behavior of the rock matrix and joint interfaces, and pumping operation, to cover a wide spectrum of potential conditions expected for a natural reservoir. These parameters were then sampled 1,000 times in an 11-dimensional parameter space constrained by the specified ranges using the Latin-hypercube method. These 1,000 parameter sets were fed into the fracture simulators, and the outputs were used to construct three designed objective functions, i.e. fracture density, opened fracture length and area density. Using PSUADE, three response surfaces (11-dimensional) of the objective functions were developed and global sensitivity was analyzed to identify the most sensitive parameters for the objective functions representing fracture connectivity, which are critical for sweep efficiency of the recovery process. The second-stage high resolution response surfaces were constructed with dimension reduced to the number of the most sensitive parameters. An additional response surface with respect to the objective function of the fractal dimension for fracture distributions was constructed in this stage. Based on these response surfaces, comprehensive uncertainty analyses were conducted among input parameters and objective functions. In addition, reduced-order emulation models resulting from this analysis can be used for optimal control of hydraulic fracturing. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Male Circumcision and the Epidemic Emergence of HIV-2 in West Africa

PubMed Central

Hewlett, Barry Stephen; Camacho, Ricardo Jorge

2016-01-01

Background Epidemic HIV-2 (groups A and B) emerged in humans circa 1930–40. Its closest ancestors are SIVsmm infecting sooty mangabeys from southwestern Côte d'Ivoire. The earliest large-scale serological surveys of HIV-2 in West Africa (1985–91) show a patchy spread. Côte d'Ivoire and Guinea-Bissau had the highest prevalence rates by then, and phylogeographical analysis suggests they were the earliest epicenters. Wars and parenteral transmission have been hypothesized to have promoted HIV-2 spread. Male circumcision (MC) is known to correlate negatively with HIV-1 prevalence in Africa, but studies examining this issue for HIV-2 are lacking. Methods We reviewed published HIV-2 serosurveys for 30 cities of all West African countries and obtained credible estimates of real prevalence through Bayesian estimation. We estimated past MC rates of 218 West African ethnic groups, based on ethnographic literature and fieldwork. We collected demographic tables specifying the ethnic partition in cities. Uncertainty was incorporated by defining plausible ranges of parameters (e.g. timing of introduction, proportion circumcised). We generated 1,000 sets of past MC rates per city using Latin Hypercube Sampling with different parameter combinations, and explored the correlation between HIV-2 prevalence and estimated MC rate (both logit-transformed) in the 1,000 replicates. Results and Conclusions Our survey reveals that, in the early 20th century, MC was far less common and geographically more variable than nowadays. HIV-2 prevalence in 1985–91 and MC rates in 1950 were negatively correlated (Spearman rho = -0.546, IQR: -0.553–-0.546, p≤0.0021). Guinea-Bissau and Côte d'Ivoire cities had markedly lower MC rates. In addition, MC was uncommon in rural southwestern Côte d'Ivoire in 1930.The differential HIV-2 spread in West Africa correlates with different historical MC rates. We suggest HIV-2 only formed early substantial foci in cities with substantial uncircumcised populations. Lack of MC in rural areas exposed to bushmeat may have had a role in successful HIV-2 emergence. PMID:27926927

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

An Elitist Multiobjective Tabu Search for Optimal Design of Groundwater Remediation Systems.

PubMed

Yang, Yun; Wu, Jianfeng; Wang, Jinguo; Zhou, Zhifang

2017-11-01

This study presents a new multiobjective evolutionary algorithm (MOEA), the elitist multiobjective tabu search (EMOTS), and incorporates it with MODFLOW/MT3DMS to develop a groundwater simulation-optimization (SO) framework based on modular design for optimal design of groundwater remediation systems using pump-and-treat (PAT) technique. The most notable improvement of EMOTS over the original multiple objective tabu search (MOTS) lies in the elitist strategy, selection strategy, and neighborhood move rule. The elitist strategy is to maintain all nondominated solutions within later search process for better converging to the true Pareto front. The elitism-based selection operator is modified to choose two most remote solutions from current candidate list as seed solutions to increase the diversity of searching space. Moreover, neighborhood solutions are uniformly generated using the Latin hypercube sampling (LHS) in the bounded neighborhood space around each seed solution. To demonstrate the performance of the EMOTS, we consider a synthetic groundwater remediation example. Problem formulations consist of two objective functions with continuous decision variables of pumping rates while meeting water quality requirements. Especially, sensitivity analysis is evaluated through the synthetic case for determination of optimal combination of the heuristic parameters. Furthermore, the EMOTS is successfully applied to evaluate remediation options at the field site of the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. With both the hypothetical and the large-scale field remediation sites, the EMOTS-based SO framework is demonstrated to outperform the original MOTS in achieving the performance metrics of optimality and diversity of nondominated frontiers with desirable stability and robustness. © 2017, National Ground Water Association.

Analysis of the influence of handset phone position on RF exposure of brain tissue.

PubMed

Ghanmi, Amal; Varsier, Nadège; Hadjem, Abdelhamid; Conil, Emmanuelle; Picon, Odile; Wiart, Joe

2014-12-01

Exposure to mobile phone radio frequency (RF) electromagnetic fields depends on many different parameters. For epidemiological studies investigating the risk of brain cancer linked to RF exposure from mobile phones, it is of great interest to characterize brain tissue exposure and to know which parameters this exposure is sensitive to. One such parameter is the position of the phone during communication. In this article, we analyze the influence of the phone position on the brain exposure by comparing the specific absorption rate (SAR) induced in the head by two different mobile phone models operating in Global System for Mobile Communications (GSM) frequency bands. To achieve this objective, 80 different phone positions were chosen using an experiment based on the Latin hypercube sampling (LHS) to select a representative set of positions. The averaged SAR over 10 g (SAR10 g) in the head, the averaged SAR over 1 g (SAR1 g ) in the brain, and the averaged SAR in different anatomical brain structures were estimated at 900 and 1800 MHz for the 80 positions. The results illustrate that SAR distributions inside the brain area are sensitive to the position of the mobile phone relative to the head. The results also show that for 5-10% of the studied positions the SAR10 g in the head and the SAR1 g in the brain can be 20% higher than the SAR estimated for the standard cheek position and that the Specific Anthropomorphic Mannequin (SAM) model is conservative for 95% of all the studied positions. © 2014 Wiley Periodicals, Inc.

The formation of continuous opinion dynamics based on a gambling mechanism and its sensitivity analysis

NASA Astrophysics Data System (ADS)

Zhu, Yueying; Alexandre Wang, Qiuping; Li, Wei; Cai, Xu

2017-09-01

The formation of continuous opinion dynamics is investigated based on a virtual gambling mechanism where agents fight for a limited resource. We propose a model with agents holding opinions between -1 and 1. Agents are segregated into two cliques according to the sign of their opinions. Local communication happens only when the opinion distance between corresponding agents is no larger than a pre-defined confidence threshold. Theoretical analysis regarding special cases provides a deep understanding of the roles of both the resource allocation parameter and confidence threshold in the formation of opinion dynamics. For a sparse network, the evolution of opinion dynamics is negligible in the region of low confidence threshold when the mindless agents are absent. Numerical results also imply that, in the presence of economic agents, high confidence threshold is required for apparent clustering of agents in opinion. Moreover, a consensus state is generated only when the following three conditions are satisfied simultaneously: mindless agents are absent, the resource is concentrated in one clique, and confidence threshold tends to a critical value(=1.25+2/ka ; k_a>8/3 , the average number of friends of individual agents). For fixed a confidence threshold and resource allocation parameter, the most chaotic steady state of the dynamics happens when the fraction of mindless agents is about 0.7. It is also demonstrated that economic agents are more likely to win at gambling, compared to mindless ones. Finally, the importance of three involved parameters in establishing the uncertainty of model response is quantified in terms of Latin hypercube sampling-based sensitivity analysis.

3-D ballistic transport of ellipsoidal volcanic projectiles considering horizontal wind field and variable shape-dependent drag coefficients

NASA Astrophysics Data System (ADS)

Bertin, Daniel

2017-02-01

An innovative 3-D numerical model for the dynamics of volcanic ballistic projectiles is presented here. The model focuses on ellipsoidal particles and improves previous approaches by considering horizontal wind field, virtual mass forces, and drag forces subjected to variable shape-dependent drag coefficients. Modeling suggests that the projectile's launch velocity and ejection angle are first-order parameters influencing ballistic trajectories. The projectile's density and minor radius are second-order factors, whereas both intermediate and major radii of the projectile are of third order. Comparing output parameters, assuming different input data, highlights the importance of considering a horizontal wind field and variable shape-dependent drag coefficients in ballistic modeling, which suggests that they should be included in every ballistic model. On the other hand, virtual mass forces should be discarded since they almost do not contribute to ballistic trajectories. Simulation results were used to constrain some crucial input parameters (launch velocity, ejection angle, wind speed, and wind azimuth) of the block that formed the biggest and most distal ballistic impact crater during the 1984-1993 eruptive cycle of Lascar volcano, Northern Chile. Subsequently, up to 106 simulations were performed, whereas nine ejection parameters were defined by a Latin-hypercube sampling approach. Simulation results were summarized as a quantitative probabilistic hazard map for ballistic projectiles. Transects were also done in order to depict aerial hazard zones based on the same probabilistic procedure. Both maps combined can be used as a hazard prevention tool for ground and aerial transits nearby unresting volcanoes.

Significant uncertainty in global scale hydrological modeling from precipitation data errors

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek C.; Vrugt, Jasper A.; van Beek, Rens (L.) P. H.; Weerts, Albrecht H.; Bierkens, Marc F. P.

2015-10-01

In the past decades significant progress has been made in the fitting of hydrologic models to data. Most of this work has focused on simple, CPU-efficient, lumped hydrologic models using discharge, water table depth, soil moisture, or tracer data from relatively small river basins. In this paper, we focus on large-scale hydrologic modeling and analyze the effect of parameter and rainfall data uncertainty on simulated discharge dynamics with the global hydrologic model PCR-GLOBWB. We use three rainfall data products; the CFSR reanalysis, the ERA-Interim reanalysis, and a combined ERA-40 reanalysis and CRU dataset. Parameter uncertainty is derived from Latin Hypercube Sampling (LHS) using monthly discharge data from five of the largest river systems in the world. Our results demonstrate that the default parameterization of PCR-GLOBWB, derived from global datasets, can be improved by calibrating the model against monthly discharge observations. Yet, it is difficult to find a single parameterization of PCR-GLOBWB that works well for all of the five river basins considered herein and shows consistent performance during both the calibration and evaluation period. Still there may be possibilities for regionalization based on catchment similarities. Our simulations illustrate that parameter uncertainty constitutes only a minor part of predictive uncertainty. Thus, the apparent dichotomy between simulations of global-scale hydrologic behavior and actual data cannot be resolved by simply increasing the model complexity of PCR-GLOBWB and resolving sub-grid processes. Instead, it would be more productive to improve the characterization of global rainfall amounts at spatial resolutions of 0.5° and smaller.

The Caltech Concurrent Computation Program - Project description

NASA Technical Reports Server (NTRS)

Fox, G.; Otto, S.; Lyzenga, G.; Rogstad, D.

1985-01-01

The Caltech Concurrent Computation Program wwhich studies basic issues in computational science is described. The research builds on initial work where novel concurrent hardware, the necessary systems software to use it and twenty significant scientific implementations running on the initial 32, 64, and 128 node hypercube machines have been constructed. A major goal of the program will be to extend this work into new disciplines and more complex algorithms including general packages that decompose arbitrary problems in major application areas. New high-performance concurrent processors with up to 1024-nodes, over a gigabyte of memory and multigigaflop performance are being constructed. The implementations cover a wide range of problems in areas such as high energy and astrophysics, condensed matter, chemical reactions, plasma physics, applied mathematics, geophysics, simulation, CAD for VLSI, graphics and image processing. The products of the research program include the concurrent algorithms, hardware, systems software, and complete program implementations.

High order parallel numerical schemes for solving incompressible flows

NASA Technical Reports Server (NTRS)

Lin, Avi; Milner, Edward J.; Liou, May-Fun; Belch, Richard A.

1992-01-01

The use of parallel computers for numerically solving flow fields has gained much importance in recent years. This paper introduces a new high order numerical scheme for computational fluid dynamics (CFD) specifically designed for parallel computational environments. A distributed MIMD system gives the flexibility of treating different elements of the governing equations with totally different numerical schemes in different regions of the flow field. The parallel decomposition of the governing operator to be solved is the primary parallel split. The primary parallel split was studied using a hypercube like architecture having clusters of shared memory processors at each node. The approach is demonstrated using examples of simple steady state incompressible flows. Future studies should investigate the secondary split because, depending on the numerical scheme that each of the processors applies and the nature of the flow in the specific subdomain, it may be possible for a processor to seek better, or higher order, schemes for its particular subcase.

Communication overhead on the Intel Paragon, IBM SP2 and Meiko CS-2

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1995-01-01

Interprocessor communication overhead is a crucial measure of the power of parallel computing systems-its impact can severely limit the performance of parallel programs. This report presents measurements of communication overhead on three contemporary commercial multicomputer systems: the Intel Paragon, the IBM SP2 and the Meiko CS-2. In each case the time to communicate between processors is presented as a function of message length. The time for global synchronization and memory access is discussed. The performance of these machines in emulating hypercubes and executing random pairwise exchanges is also investigated. It is shown that the interprocessor communication time depends heavily on the specific communication pattern required. These observations contradict the commonly held belief that communication overhead on contemporary machines is independent of the placement of tasks on processors. The information presented in this report permits the evaluation of the efficiency of parallel algorithm implementations against standard baselines.

Graphical Representations and Cluster Algorithms for Ice Rule Vertex Models.

NASA Astrophysics Data System (ADS)

Shtengel, Kirill; Chayes, L.

2002-03-01

We introduce a new class of polymer models which is closely related to loop models, recently a topic of intensive studies. These particular models arise as graphical representations for ice-rule vertex models. The associated cluster algorithms provide a unification and generalisation of most of the existing algorithms. For many lattices, percolation in the polymer models evidently indicates first order phase transitions in the vertex models. Critical phases can be understood as being susceptible to colour symmetry breaking in the polymer models. The analysis includes, but is certainly not limited to the square lattice six-vertex model. In particular, analytic criteria can be found for low temperature phases in other even coordinated 2D lattices such as the triangular lattice, or higher dimensional lattices such as the hyper-cubic lattices of arbitrary dimensionality. Finally, our approach can be generalised to the vertex models that do not obey the ice rule, such as the eight-vertex model.

Scaling of Loop-Erased Walks in 2 to 4 Dimensions

NASA Astrophysics Data System (ADS)

Grassberger, Peter

2009-07-01

We simulate loop-erased random walks on simple (hyper-)cubic lattices of dimensions 2, 3 and 4. These simulations were mainly motivated to test recent two loop renormalization group predictions for logarithmic corrections in d=4, simulations in lower dimensions were done for completeness and in order to test the algorithm. In d=2, we verify with high precision the prediction D=5/4, where the number of steps n after erasure scales with the number N of steps before erasure as n˜ N D/2. In d=3 we again find a power law, but with an exponent different from the one found in the most precise previous simulations: D=1.6236±0.0004. Finally, we see clear deviations from the naive scaling n˜ N in d=4. While they agree only qualitatively with the leading logarithmic corrections predicted by several authors, their agreement with the two-loop prediction is nearly perfect.

Multinode reconfigurable pipeline computer

NASA Technical Reports Server (NTRS)

Nosenchuck, Daniel M. (Inventor); Littman, Michael G. (Inventor)

1989-01-01

A multinode parallel-processing computer is made up of a plurality of innerconnected, large capacity nodes each including a reconfigurable pipeline of functional units such as Integer Arithmetic Logic Processors, Floating Point Arithmetic Processors, Special Purpose Processors, etc. The reconfigurable pipeline of each node is connected to a multiplane memory by a Memory-ALU switch NETwork (MASNET). The reconfigurable pipeline includes three (3) basic substructures formed from functional units which have been found to be sufficient to perform the bulk of all calculations. The MASNET controls the flow of signals from the memory planes to the reconfigurable pipeline and vice versa. the nodes are connectable together by an internode data router (hyperspace router) so as to form a hypercube configuration. The capability of the nodes to conditionally configure the pipeline at each tick of the clock, without requiring a pipeline flush, permits many powerful algorithms to be implemented directly.

Ferromagnetism in the Hubbard Model with a Gapless Nearly-Flat Band

NASA Astrophysics Data System (ADS)

Tanaka, Akinori

2018-01-01

We present a version of the Hubbard model with a gapless nearly-flat lowest band which exhibits ferromagnetism in two or more dimensions. The model is defined on a lattice obtained by placing a site on each edge of the hypercubic lattice, and electron hopping is assumed to be only between nearest and next nearest neighbor sites. The lattice, where all the sites are identical, is simple, and the corresponding single-electron band structure, where two cosine-type bands touch without an energy gap, is also simple. We prove that the ground state of the model is unique and ferromagnetic at half-filling of the lower band, if the lower band is nearly flat and the strength of on-site repulsion is larger than a certain value which is independent of the lattice size. This is the first example of ferromagnetism in three dimensional non-singular models with a gapless band structure.

Disorder-assisted quantum transport in suboptimal decoherence regimes

PubMed Central

Novo, Leonardo; Mohseni, Masoud; Omar, Yasser

2016-01-01

We investigate quantum transport in binary tree structures and in hypercubes for the disordered Frenkel-exciton Hamiltonian under pure dephasing noise. We compute the energy transport efficiency as a function of disorder and dephasing rates. We demonstrate that dephasing improves transport efficiency not only in the disordered case, but also in the ordered one. The maximal transport efficiency is obtained when the dephasing timescale matches the hopping timescale, which represent new examples of the Goldilocks principle at the quantum scale. Remarkably, we find that in weak dephasing regimes, away from optimal levels of environmental fluctuations, the average effect of increasing disorder is to improve the transport efficiency until an optimal value for disorder is reached. Our results suggest that rational design of the site energies statistical distributions could lead to better performances in transport systems at nanoscale when their natural environments are far from the optimal dephasing regime. PMID:26726133

HERMIES-3: A step toward autonomous mobility, manipulation, and perception

NASA Technical Reports Server (NTRS)

Weisbin, C. R.; Burks, B. L.; Einstein, J. R.; Feezell, R. R.; Manges, W. W.; Thompson, D. H.

1989-01-01

HERMIES-III is an autonomous robot comprised of a seven degree-of-freedom (DOF) manipulator designed for human scale tasks, a laser range finder, a sonar array, an omni-directional wheel-driven chassis, multiple cameras, and a dual computer system containing a 16-node hypercube expandable to 128 nodes. The current experimental program involves performance of human-scale tasks (e.g., valve manipulation, use of tools), integration of a dexterous manipulator and platform motion in geometrically complex environments, and effective use of multiple cooperating robots (HERMIES-IIB and HERMIES-III). The environment in which the robots operate has been designed to include multiple valves, pipes, meters, obstacles on the floor, valves occluded from view, and multiple paths of differing navigation complexity. The ongoing research program supports the development of autonomous capability for HERMIES-IIB and III to perform complex navigation and manipulation under time constraints, while dealing with imprecise sensory information.

Mixed Spin-1/2 and Spin-5/2 Model by Renormalization Group Theory: Recursion Equations and Thermodynamic Study

NASA Astrophysics Data System (ADS)

Antari, A. El; Zahir, H.; Hasnaoui, A.; Hachem, N.; Alrajhi, A.; Madani, M.; Bouziani, M. El

2018-04-01

Using the renormalization group approximation, specifically the Migdal-Kadanoff technique, we investigate the Blume-Capel model with mixed spins S = 1/2 and S = 5/2 on d-dimensional hypercubic lattice. The flow in the parameter space of the Hamiltonian and the thermodynamic functions are determined. The phase diagram of this model is plotted in the (anisotropy, temperature) plane for both cases d = 2 and d = 3 in which the system exhibits the first and second order phase transitions and critical end-points. The associated fixed points are drawn up in a table, and by linearizing the transformation at the vicinity of these points, we determine the critical exponents for d = 2 and d = 3. We have also presented a variation of the free energy derivative at the vicinity of the first and second order transitions. Finally, this work is completed by a discussion and comparison with other approximation.

Networking and AI systems: Requirements and benefits

NASA Technical Reports Server (NTRS)

1988-01-01

The price performance benefits of network systems is well documented. The ability to share expensive resources sold timesharing for mainframes, department clusters of minicomputers, and now local area networks of workstations and servers. In the process, other fundamental system requirements emerged. These have now been generalized with open system requirements for hardware, software, applications and tools. The ability to interconnect a variety of vendor products has led to a specification of interfaces that allow new techniques to extend existing systems for new and exciting applications. As an example of the message passing system, local area networks provide a testbed for many of the issues addressed by future concurrent architectures: synchronization, load balancing, fault tolerance and scalability. Gold Hill has been working with a number of vendors on distributed architectures that range from a network of workstations to a hypercube of microprocessors with distributed memory. Results from early applications are promising both for performance and scalability.

A GIS-assisted regional screening tool to evaluate the leaching potential of volatile and non-volatile pesticides

NASA Astrophysics Data System (ADS)

Ki, Seo Jin; Ray, Chittaranjan

2015-03-01

A regional screening tool-which is useful in cases where few site-specific parameters are available for complex vadose zone models-assesses the leaching potential of pollutants to groundwater over large areas. In this study, the previous pesticide leaching tool used in Hawaii was revised to account for the release of new volatile organic compounds (VOCs) from the soil surface. The tool was modified to introduce expanded terms in the traditional pesticide ranking indices (i.e., retardation and attenuation factors), allowing the estimation of the leaching fraction of volatile chemicals based on recharge, soil, and chemical properties to be updated. Results showed that the previous tool significantly overestimated the mass fraction of VOCs leached through soils as the recharge rates increased above 0.001801 m/d. In contrast, the revised tool successfully delineated vulnerable areas to the selected VOCs based on two reference chemicals, a known leacher and non-leacher, which were determined in local conditions. The sensitivity analysis with the Latin-Hypercube-One-factor-At-a-Time method revealed that the new leaching tool was most sensitive to changes in the soil organic carbon sorption coefficient, fractional organic carbon content, and Henry's law constant; and least sensitive to parameters such as the bulk density, water content at field capacity, and particle density in soils. When the revised tool was compared to the analytical (STANMOD) and numerical (HYDRUS-1D) models as a susceptibility measure, it ranked particular VOCs well (e.g., benzene, carbofuran, and toluene) that were consistent with other two models under the given conditions. Therefore, the new leaching tool can be widely used to address intrinsic groundwater vulnerability to contamination of pesticides and VOCs, along with the DRASTIC method or similar Tier 1 models such as SCI-GROW and WIN-PST.

Machine learning for predicting soil classes in three semi-arid landscapes

USGS Publications Warehouse

Brungard, Colby W.; Boettinger, Janis L.; Duniway, Michael C.; Wills, Skye A.; Edwards, Thomas C.

2015-01-01

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

Transformation of two and three-dimensional regions by elliptic systems

NASA Technical Reports Server (NTRS)

Mastin, C. Wayne

1994-01-01

Several reports are attached to this document which contain the results of our research at the end of this contract period. Three of the reports deal with our work on generating surface grids. One is a preprint of a paper which will appear in the journal Applied Mathematics and Computation. Another is the abstract from a dissertation which has been prepared by Ahmed Khamayseh, a graduate student who has been supported by this grant for the last two years. The last report on surface grids is the extended abstract of a paper to be presented at the 14th IMACS World Congress in July. This report contains results on conformal mappings of surfaces, which are closely related to elliptic methods for surface grid generation. A preliminary report is included on new methods for dealing with block interfaces in multiblock grid systems. The development work is complete and the methods will eventually be incorporated into the National Grid Project (NGP) grid generation code. Thus, the attached report contains only a simple grid system which was used to test the algorithms to prove that the concepts are sound. These developments will greatly aid grid control when using elliptic systems and prevent unwanted grid movement. The last report is a brief summary of some timings that were obtained when the multiblock grid generation code was run on the Intel IPSC/860 hypercube. Since most of the data in a grid code is local to a particular block, only a small fraction of the total data must be passed between processors. The data is also distributed among the processors so that the total size of the grid can be increase along with the number of processors. This work is only in a preliminary stage. However, one of the ERC graduate students has taken an interest in the project and is presently extending these results as a part of his master's thesis.

Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor

PubMed Central

Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

2015-01-01

The reflectance of the Earth’s surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE’s, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development. PMID:26263996

Artifacts and power corrections: Reexamining Z{sub {psi}}(p{sup 2}) and Z{sub V} in the momentum-subtraction scheme

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

Boucaud, Ph.; Leroy, J. P.; Le Yaouanc, A.

2006-08-01

The next-to-leading-order (NLO) term in the operator product expansion (OPE) of the quark propagator vector part Z{sub {psi}} and the vertex function g{sub 1} of the vector current in the Landau gauge should be dominated by the same condensate as in the gluon propagator. On the other hand, the perturbative part has been calculated to a very high precision thanks to Chetyrkin and collaborators. We test this on the lattice, with both clover and overlap fermion actions at {beta}=6.0, 6.4, 6.6, 6.8. Elucidation of discretization artifacts appears to be absolutely crucial. First hypercubic artifacts are eliminated by amore » powerful method, which gives results notably different from the standard democratic method. Then, the presence of unexpected, very large, nonperturbative, O(4) symmetric discretization artifacts, increasing towards small momenta, is demonstrated by considering Z{sub V}{sup MOM}, which should be constant in the absence of such artifacts. They impede in general the analysis of OPE. However, in two special cases with overlap action--(1) for Z{sub {psi}}; (2) for g{sub 1}, but only at large p{sup 2}--we are able to identify the condensate; it agrees with the one resulting from gluonic Green functions. We conclude that the OPE analysis of quark and gluon Green function has reached a quite consistent status, and that the power corrections have been correctly identified. A practical consequence of the whole analysis is that the renormalization constant Z{sub {psi}} (=Z{sub 2}{sup -1} of the momentum-subtraction (MOM) scheme) may differ sizably from the one given by democratic selection methods. More generally, the values of the renormalization constants may be seriously affected by the differences in the treatment of the various types of artifacts, and by the subtraction of power corrections.« less

Hyperspectral imaging of colonic polyps in vivo (Conference Presentation)

NASA Astrophysics Data System (ADS)

Clancy, Neil T.; Elson, Daniel S.; Teare, Julian

2017-02-01

Standard endoscopic tools restrict clinicians to making subjective visual assessments of lesions detected in the bowel, with classification results depending strongly on experience level and training. Histological examination of resected tissue remains the diagnostic gold standard, meaning that all detected lesions are routinely removed. This subjects the patient to risk of polypectomy-related injury, and places significant workload and economic burdens on the hospital. An objective endoscopic classification method would allow hyperplastic polyps, with no malignant potential, to be left in situ, or low grade adenomas to be resected and discarded without histology. A miniature multimodal flexible endoscope is proposed to obtain hyperspectral reflectance and dual excitation autofluorescence information from polyps in vivo. This is placed inside the working channel of a conventional colonoscope, with the external scanning and detection optics on a bedside trolley. A blue and violet laser diode pair excite endogenous fluorophores in the respiration chain, while the colonoscope's xenon light source provides broadband white light for diffuse reflectance measurements. A push-broom HSI scanner collects the hypercube. System characterisation experiments are presented, defining resolution limits as well as acquisition settings for optimal spectral, spatial and temporal performance. The first in vivo results in human subjects are presented, demonstrating the clinical utility of the device. The optical properties (reflectance and autofluorescence) of imaged polyps are quantified and compared to the histologically-confirmed tissue type as well as the clinician's visual assessment. Further clinical studies will allow construction of a full robust training dataset for development of classification schemes.

Parallel computing of physical maps--a comparative study in SIMD and MIMD parallelism.

PubMed

Bhandarkar, S M; Chirravuri, S; Arnold, J

1996-01-01

Ordering clones from a genomic library into physical maps of whole chromosomes presents a central computational problem in genetics. Chromosome reconstruction via clone ordering is usually isomorphic to the NP-complete Optimal Linear Arrangement problem. Parallel SIMD and MIMD algorithms for simulated annealing based on Markov chain distribution are proposed and applied to the problem of chromosome reconstruction via clone ordering. Perturbation methods and problem-specific annealing heuristics are proposed and described. The SIMD algorithms are implemented on a 2048 processor MasPar MP-2 system which is an SIMD 2-D toroidal mesh architecture whereas the MIMD algorithms are implemented on an 8 processor Intel iPSC/860 which is an MIMD hypercube architecture. A comparative analysis of the various SIMD and MIMD algorithms is presented in which the convergence, speedup, and scalability characteristics of the various algorithms are analyzed and discussed. On a fine-grained, massively parallel SIMD architecture with a low synchronization overhead such as the MasPar MP-2, a parallel simulated annealing algorithm based on multiple periodically interacting searches performs the best. For a coarse-grained MIMD architecture with high synchronization overhead such as the Intel iPSC/860, a parallel simulated annealing algorithm based on multiple independent searches yields the best results. In either case, distribution of clonal data across multiple processors is shown to exacerbate the tendency of the parallel simulated annealing algorithm to get trapped in a local optimum.

Parametric binary dissection

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.; Crockett, Thomas W.; Nicol, David M.

1993-01-01

Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.

Cystic echinococcosis in marketed offal of sheep in Basrah, Iraq: Abattoir-based survey and a probabilistic model estimation of the direct economic losses due to hydatid cyst.

PubMed

Abdulhameed, Mohanad F; Habib, Ihab; Al-Azizz, Suzan A; Robertson, Ian

2018-02-01

Cystic echinococcosis (CE) is a highly endemic parasitic zoonosis in Iraq with substantial impacts on livestock productivity and human health. The objectives of this study were to study the abattoir-based occurrence of CE in marketed offal of sheep in Basrah province, Iraq, and to estimate, using a probabilistic modelling approach, the direct economic losses due to hydatid cysts. Based on detailed visual meat inspection, results from an active abattoir survey in this study revealed detection of hydatid cysts in 7.3% (95% CI: 5.4; 9.6) of 631 examined sheep carcasses. Post-mortem lesions of hydatid cyst were concurrently present in livers and lungs of more than half (54.3% (25/46)) of the positive sheep. Direct economic losses due to hydatid cysts in marketed offal were estimated using data from government reports, the one abattoir survey completed in this study, and expert opinions of local veterinarians and butchers. A Monte-Carlo simulation model was developed in a spreadsheet utilizing Latin Hypercube sampling to account for uncertainty in the input parameters. The model estimated that the average annual economic losses associated with hydatid cysts in the liver and lungs of sheep marketed for human consumption in Basrah to be US$72,470 (90% Confidence Interval (CI); ±11,302). The mean proportion of annual losses in meat products value (carcasses and offal) due to hydatid cysts in the liver and lungs of sheep marketed in Basrah province was estimated as 0.42% (90% CI; ±0.21). These estimates suggest that CE is responsible for considerable livestock-associated monetary losses in the south of Iraq. These findings can be used to inform different regional CE control program options in Iraq.

Effects of surface area and inflow on the performance of stormwater best management practices with uncertainty analysis.

PubMed

Park, Daeryong; Roesner, Larry A

2013-09-01

The performance of stormwater best management practices (BMPs) is affected by BMP geometric and hydrologic factors. The objective of this study was to investigate the effect of BMP surface area and inflow on BMP performance using the k-C* model with uncertainty analysis. Observed total suspended solids (TSS) from detention basins and retention ponds data sets in the International Stormwater BMP Database were used to build and evaluate the model. Detention basins are regarded as dry ponds because they do not always have water, whereas retention ponds have a permanent pool and are considered wet ponds. In this study, Latin hypercube sampling (LHS) was applied to consider uncertainty in both influent event mean concentration (EMC), C(in), and the areal removal constant, k. The latter was estimated from the hydraulic loading rate, q, through use of a power function relationship. Results show that effluent EMC, C(out), decreased as inflow decreased and as BMP surface area increased in both detention basins and retention ponds. However, the change in C(out), depending on inflow and BMP surface area for detention basins, differed from the change in C(out) for retention ponds. Specifically, C(in) was more dominantly associated with the performance of the k-C* model of detention basins than were BMP surface area and inflow. For retention ponds, however, results suggest that BMP surface area and inflow both influenced changes in C(out) as well as C(in). These results suggest that sensitive factors in the performance of the k-C* model are limited to C(in) for detention basins, whereas BMP surface area, inflow, and C(in) are important for retention ponds.

Using palaeoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Phipps, Steven; King, Matt; Roberts, Jason; White, Duanne

2017-04-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modelling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how palaeoclimate data can improve our ability to predict the future evolution of the AIS. A 50-member perturbed-physics ensemble is generated, spanning uncertainty in the parameterisations of three key physical processes within the model: (i) the stress balance within the ice sheet, (ii) basal sliding and (iii) calving of ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Palaeoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.

Using paleoclimate data to improve models of the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

King, M. A.; Phipps, S. J.; Roberts, J. L.; White, D.

2016-12-01

Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modeling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how paleoclimate data can improve our ability to predict the future evolution of the AIS. A large, perturbed-physics ensemble is generated, spanning uncertainty in the parameterizations of four key physical processes within ice sheet models: ice rheology, ice shelf calving, and the stress balances within ice sheets and ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Paleoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.

Constructing Rigorous and Broad Biosurveillance Networks for Detecting Emerging Zoonotic Outbreaks

PubMed Central

Brown, Mac; Moore, Leslie; McMahon, Benjamin; Powell, Dennis; LaBute, Montiago; Hyman, James M.; Rivas, Ariel; Jankowski, Mark; Berendzen, Joel; Loeppky, Jason; Manore, Carrie; Fair, Jeanne

2015-01-01

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities of potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic. PMID:25946164

Pilot study for supervised target detection applied to spatially registered multiparametric MRI in order to non-invasively score prostate cancer.

PubMed

Mayer, Rulon; Simone, Charles B; Skinner, William; Turkbey, Baris; Choykey, Peter

2018-03-01

Gleason Score (GS) is a validated predictor of prostate cancer (PCa) disease progression and outcomes. GS from invasive needle biopsies suffers from significant inter-observer variability and possible sampling error, leading to underestimating disease severity ("underscoring") and can result in possible complications. A robust non-invasive image-based approach is, therefore, needed. Use spatially registered multi-parametric MRI (MP-MRI), signatures, and supervised target detection algorithms (STDA) to non-invasively GS PCa at the voxel level. This study retrospectively analyzed 26 MP-MRI from The Cancer Imaging Archive. The MP-MRI (T2, Diffusion Weighted, Dynamic Contrast Enhanced) were spatially registered to each other, combined into stacks, and stitched together to form hypercubes. Multi-parametric (or multi-spectral) signatures derived from a training set of registered MP-MRI were transformed using statistics-based Whitening-Dewhitening (WD). Transformed signatures were inserted into STDA (having conical decision surfaces) applied to registered MP-MRI determined the tumor GS. The MRI-derived GS was quantitatively compared to the pathologist's assessment of the histology of sectioned whole mount prostates from patients who underwent radical prostatectomy. In addition, a meta-analysis of 17 studies of needle biopsy determined GS with confusion matrices and was compared to the MRI-determined GS. STDA and histology determined GS are highly correlated (R = 0.86, p < 0.02). STDA more accurately determined GS and reduced GS underscoring of PCa relative to needle biopsy as summarized by meta-analysis (p < 0.05). This pilot study found registered MP-MRI, STDA, and WD transforms of signatures shows promise in non-invasively GS PCa and reducing underscoring with high spatial resolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reduced-Order Model for the Geochemical Impacts of Carbon Dioxide, Brine and Trace Metal Leakage into an Unconfined, Oxidizing Carbonate Aquifer, Version 2.1

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

Bacon, Diana H.

2013-03-31

The National Risk Assessment Partnership (NRAP) consists of 5 U.S DOE national laboratories collaborating to develop a framework for predicting the risks associated with carbon sequestration. The approach taken by NRAP is to divide the system into components, including injection target reservoirs, wellbores, natural pathways including faults and fractures, groundwater and the atmosphere. Next, develop a detailed, physics and chemistry-based model of each component. Using the results of the detailed models, develop efficient, simplified models, termed reduced order models (ROM) for each component. Finally, integrate the component ROMs into a system model that calculates risk profiles for the site. Thismore » report details the development of the Groundwater Geochemistry ROM for the Edwards Aquifer at PNNL. The Groundwater Geochemistry ROM for the Edwards Aquifer uses a Wellbore Leakage ROM developed at LANL as input. The detailed model, using the STOMP simulator, covers a 5x8 km area of the Edwards Aquifer near San Antonio, Texas. The model includes heterogeneous hydraulic properties, and equilibrium, kinetic and sorption reactions between groundwater, leaked CO2 gas, brine, and the aquifer carbonate and clay minerals. Latin Hypercube sampling was used to generate 1024 samples of input parameters. For each of these input samples, the STOMP simulator was used to predict the flux of CO2 to the atmosphere, and the volume, length and width of the aquifer where pH was less than the MCL standard, and TDS, arsenic, cadmium and lead exceeded MCL standards. In order to decouple the Wellbore Leakage ROM from the Groundwater Geochemistry ROM, the response surface was transformed to replace Wellbore Leakage ROM input parameters with instantaneous and cumulative CO2 and brine leakage rates. The most sensitive parameters proved to be the CO2 and brine leakage rates from the well, with equilibrium coefficients for calcite and dolomite, as well as the number of illite and kaolinite sorption sites proving to be of secondary importance. The Groundwater Geochemistry ROM was developed using nonlinear regression to fit the response surface with a quadratic polynomial. The goodness of fit was excellent for the CO2 flux to the atmosphere, and very good for predicting the volumes of groundwater exceeding the pH, TDS, As, Cd and Pb threshold values.« less

Fossil vs. non-fossil sources of fine carbonaceous aerosols in four Chinese cities during the extreme winter haze episode of 2013

NASA Astrophysics Data System (ADS)

Zhang, Y.-L.; Huang, R.-J.; El Haddad, I.; Ho, K.-F.; Cao, J.-J.; Han, Y.; Zotter, P.; Bozzetti, C.; Daellenbach, K. R.; Canonaco, F.; Slowik, J. G.; Salazar, G.; Schwikowski, M.; Schnelle-Kreis, J.; Abbaszade, G.; Zimmermann, R.; Baltensperger, U.; Prévôt, A. S. H.; Szidat, S.

2015-02-01

During winter 2013, extremely high concentrations (i.e., 4-20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter < 2.5 μm) mass concentrations (24 h samples) were found in four major cities in China including Xi'an, Beijing, Shanghai and Guangzhou. Statistical analysis of a combined data set from elemental carbon (EC), organic carbon (OC), 14C and biomass-burning marker measurements using Latin hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. Based on 14C measurements of EC fractions (six samples each city), we found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% across all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xi'an (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10 and 48 ± 9% of OC and total carbon (TC), respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8, 48 ± 18, 53 ± 4 and 65 ± 26% of non-fossil OC for Xi'an, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately to heavily polluted days according to particulate matter mass. Despite a significant increase of the absolute mass concentrations of primary emissions from both fossil and non-fossil sources during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.

"A space-time ensemble Kalman filter for state and parameter estimation of groundwater transport models"

NASA Astrophysics Data System (ADS)

Briseño, Jessica; Herrera, Graciela S.

2010-05-01

Herrera (1998) proposed a method for the optimal design of groundwater quality monitoring networks that involves space and time in a combined form. The method was applied later by Herrera et al (2001) and by Herrera and Pinder (2005). To get the estimates of the contaminant concentration being analyzed, this method uses a space-time ensemble Kalman filter, based on a stochastic flow and transport model. When the method is applied, it is important that the characteristics of the stochastic model be congruent with field data, but, in general, it is laborious to manually achieve a good match between them. For this reason, the main objective of this work is to extend the space-time ensemble Kalman filter proposed by Herrera, to estimate the hydraulic conductivity, together with hydraulic head and contaminant concentration, and its application in a synthetic example. The method has three steps: 1) Given the mean and the semivariogram of the natural logarithm of hydraulic conductivity (ln K), random realizations of this parameter are obtained through two alternatives: Gaussian simulation (SGSim) and Latin Hypercube Sampling method (LHC). 2) The stochastic model is used to produce hydraulic head (h) and contaminant (C) realizations, for each one of the conductivity realizations. With these realization the mean of ln K, h and C are obtained, for h and C, the mean is calculated in space and time, and also the cross covariance matrix h-ln K-C in space and time. The covariance matrix is obtained averaging products of the ln K, h and C realizations on the estimation points and times, and the positions and times with data of the analyzed variables. The estimation points are the positions at which estimates of ln K, h or C are gathered. In an analogous way, the estimation times are those at which estimates of any of the three variables are gathered. 3) Finally the ln K, h and C estimate are obtained using the space-time ensemble Kalman filter. The realization mean for each one of the variables is used as the prior space-time estimate for the Kalman filter, and the space-time cross-covariance matrix of h-ln K-C as the prior estimate-error covariance-matrix. The synthetic example has a modeling area of 700 x 700 square meters; a triangular mesh model with 702 nodes and 1306 elements is used. A pumping well located in the central part of the study area is considered. For the contaminant transport model, a contaminant source area is present in the western part of the study area. The estimation points for hydraulic conductivity, hydraulic head and contaminant concentrations are located on a submesh of the model mesh (same location for h, ln K and c), composed by 48 nodes spread throughout the study area, with an approximately separation of 90 meters between nodes. The results analysis was done through the mean error, root mean square error, initial and final estimation maps of h, ln K and C at each time, and the initial and final variance maps of h, ln K and C. To obtain model convergence, 3000 realizations of ln K were required using SGSim, and only 1000 with LHC. The results show that for both alternatives, the Kalman filter estimates for h, ln K and C using h and C data, have errors which magnitudes decrease as data is added. HERRERA, G. S.(1998), Cost Effective Groundwater Quality Sampling Network Design. Ph. D. thesis, University of Vermont, Burlington, Vermont, 172 pp. HERRERA G., GUARNACCIA J., PINDER G. Y SIMUTA R.(2001),"Diseño de redes de monitoreo de la calidad del agua subterránea eficientes", Proceedings of the 2001 International Symposium on Environmental Hydraulics, Arizona, U.S.A. HERRERA G. S. and PINDER G.F. (2005), Space-time optimization of groundwater quality sampling networks Water Resour. Res., Vol. 41, No. 12, W12407, 10.1029/2004WR003626.

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

On extreme points of the diffusion polytope

DOE PAGES

Hay, M. J.; Schiff, J.; Fisch, N. J.

2017-01-04

Here, we consider a class of diffusion problems defined on simple graphs in which the populations at any two vertices may be averaged if they are connected by an edge. The diffusion polytope is the convex hull of the set of population vectors attainable using finite sequences of these operations. A number of physical problems have linear programming solutions taking the diffusion polytope as the feasible region, e.g. the free energy that can be removed from plasma using waves, so there is a need to describe and enumerate its extreme points. We also review known results for the case ofmore » the complete graph Kn, and study a variety of problems for the path graph Pn and the cyclic graph Cn. Finall, we describe the different kinds of extreme points that arise, and identify the diffusion polytope in a number of simple cases. In the case of increasing initial populations on Pn the diffusion polytope is topologically an n-dimensional hypercube.« less

Development of the HERMIES III mobile robot research testbed at Oak Ridge National Laboratory

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

Manges, W.W.; Hamel, W.R.; Weisbin, C.R.

1988-01-01

The latest robot in the Hostile Environment Robotic Machine Intelligence Experiment Series (HERMIES) is now under development at the Center for Engineering Systems Advanced Research (CESAR) in the Oak Ridge National Laboratory. The HERMIES III robot incorporates a larger than human size 7-degree-of-freedom manipulator mounted on a 2-degree-of-freedom mobile platform including a variety of sensors and computers. The deployment of this robot represents a significant increase in research capabilities for the CESAR laboratory. The initial on-board computer capacity of the robot exceeds that of 20 Vax 11/780s. The navigation and vision algorithms under development make extensive use of the on-boardmore » NCUBE hypercube computer while the sensors are interfaced through five VME computers running the OS-9 real-time, multitasking operating system. This paper describes the motivation, key issues, and detailed design trade-offs of implementing the first phase (basic functionality) of the HERMIES III robot. 10 refs., 7 figs.« less

The noncommutative index theorem and the periodic table for disordered topological insulators and superconductors

NASA Astrophysics Data System (ADS)

Katsura, Hosho; Koma, Tohru

2018-03-01

We study a wide class of topological free-fermion systems on a hypercubic lattice in spatial dimensions d ≥ 1. When the Fermi level lies in a spectral gap or a mobility gap, the topological properties, e.g., the integral quantization of the topological invariant, are protected by certain symmetries of the Hamiltonian against disorder. This generic feature is characterized by a generalized index theorem which is a noncommutative analog of the Atiyah-Singer index theorem. The noncommutative index defined in terms of a pair of projections gives a precise formula for the topological invariant in each symmetry class in any dimension (d ≥ 1). Under the assumption on the nonvanishing spectral or mobility gap, we prove that the index formula reproduces Bott periodicity and all of the possible values of topological invariants in the classification table of topological insulators and superconductors. We also prove that the indices are robust against perturbations that do not break the symmetry of the unperturbed Hamiltonian.

N = 2* Yang-Mills on the Lattice

NASA Astrophysics Data System (ADS)

Joseph, Anosh

2018-03-01

The N = 2* Yang-Mills theory in four dimensions is a non-conformal theory that appears as a mass deformation of maximally supersymmetric N = 4 Yang-Mills theory. This theory also takes part in the AdS/CFT correspondence and its gravity dual is type IIB supergravity on the Pilch-Warner background. The finite temperature properties of this theory have been studied recently in the literature. It has been argued that at large N and strong coupling this theory exhibits no thermal phase transition at any nonzero temperature. The low temperature N = 2* plasma can be compared to the QCD plasma. We provide a lattice construction of N = 2* Yang-Mills on a hypercubic lattice starting from the N = 4 gauge theory. The lattice construction is local, gauge-invariant, free from fermion doubling problem and preserves a part of the supersymmetry. This nonperturbative formulation of the theory can be used to provide a highly nontrivial check of the AdS/CFT correspondence in a non-conformal theory.

Efficient iteration in data-parallel programs with irregular and dynamically distributed data structures

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

Littlefield, R.J.

1990-02-01

To implement an efficient data-parallel program on a non-shared memory MIMD multicomputer, data and computations must be properly partitioned to achieve good load balance and locality of reference. Programs with irregular data reference patterns often require irregular partitions. Although good partitions may be easy to determine, they can be difficult or impossible to implement in programming languages that provide only regular data distributions, such as blocked or cyclic arrays. We are developing Onyx, a programming system that provides a shared memory model of distributed data structures and extends the concept of data distribution to include irregular and dynamic distributions. Thismore » provides a powerful means to specify irregular partitions. Perhaps surprisingly, programs using it can also execute efficiently. In this paper, we describe and evaluate the Onyx implementation of a model problem that repeatedly executes an irregular but fixed data reference pattern. On an NCUBE hypercube, the speed of the Onyx implementation is comparable to that of carefully handwritten message-passing code.« less

A study of entropy/clarity of genetic sequences using metric spaces and fuzzy sets.

PubMed

Georgiou, D N; Karakasidis, T E; Nieto, Juan J; Torres, A

2010-11-07

The study of genetic sequences is of great importance in biology and medicine. Sequence analysis and taxonomy are two major fields of application of bioinformatics. In the present paper we extend the notion of entropy and clarity to the use of different metrics and apply them in the case of the Fuzzy Polynuclotide Space (FPS). Applications of these notions on selected polynucleotides and complete genomes both in the I(12×k) space, but also using their representation in FPS are presented. Our results show that the values of fuzzy entropy/clarity are indicative of the degree of complexity necessary for the description of the polynucleotides in the FPS, although in the latter case the interpretation is slightly different than in the case of the I(12×k) hypercube. Fuzzy entropy/clarity along with the use of appropriate metrics can contribute to sequence analysis and taxonomy. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Fermilab lattice supercomputer project

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

Fischler, M.; Atac, R.; Cook, A.

1989-02-01

The ACPMAPS system is a highly cost effective, local memory MIMD computer targeted at algorithm development and production running for gauge theory on the lattice. The machine consists of a compound hypercube of crates, each of which is a full crossbar switch containing several processors. The processing nodes are single board array processors based on the Weitek XL chip set, each with a peak power of 20 MFLOPS and supported by 8 MBytes of data memory. The system currently being assembled has a peak power of 5 GFLOPS, delivering performance at approximately $250/MFLOP. The system is programmable in C andmore » Fortran. An underpinning of software routines (CANOPY) provides an easy and natural way of coding lattice problems, such that the details of parallelism, and communication and system architecture are transparent to the user. CANOPY can easily be ported to any single CPU or MIMD system which supports C, and allows the coding of typical applications with very little effort. 3 refs., 1 fig.« less

The design and implementation of a parallel unstructured Euler solver using software primitives

NASA Technical Reports Server (NTRS)

Das, R.; Mavriplis, D. J.; Saltz, J.; Gupta, S.; Ponnusamy, R.

1992-01-01

This paper is concerned with the implementation of a three-dimensional unstructured grid Euler-solver on massively parallel distributed-memory computer architectures. The goal is to minimize solution time by achieving high computational rates with a numerically efficient algorithm. An unstructured multigrid algorithm with an edge-based data structure has been adopted, and a number of optimizations have been devised and implemented in order to accelerate the parallel communication rates. The implementation is carried out by creating a set of software tools, which provide an interface between the parallelization issues and the sequential code, while providing a basis for future automatic run-time compilation support. Large practical unstructured grid problems are solved on the Intel iPSC/860 hypercube and Intel Touchstone Delta machine. The quantitative effect of the various optimizations are demonstrated, and we show that the combined effect of these optimizations leads to roughly a factor of three performance improvement. The overall solution efficiency is compared with that obtained on the CRAY-YMP vector supercomputer.

Experiences with serial and parallel algorithms for channel routing using simulated annealing

NASA Technical Reports Server (NTRS)

Brouwer, Randall Jay

1988-01-01

Two algorithms for channel routing using simulated annealing are presented. Simulated annealing is an optimization methodology which allows the solution process to back up out of local minima that may be encountered by inappropriate selections. By properly controlling the annealing process, it is very likely that the optimal solution to an NP-complete problem such as channel routing may be found. The algorithm presented proposes very relaxed restrictions on the types of allowable transformations, including overlapping nets. By freeing that restriction and controlling overlap situations with an appropriate cost function, the algorithm becomes very flexible and can be applied to many extensions of channel routing. The selection of the transformation utilizes a number of heuristics, still retaining the pseudorandom nature of simulated annealing. The algorithm was implemented as a serial program for a workstation, and a parallel program designed for a hypercube computer. The details of the serial implementation are presented, including many of the heuristics used and some of the resulting solutions.

Exploring the spatial variability of soil properties in an Alfisol Catena

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

Rosemary, F.; Vitharana, U. W. A.; Indraratne, S. P.

Detailed digital soil maps showing the spatial heterogeneity of soil properties consistent with the landscape are required for site-specific management of plant nutrients, land use planning and process-based environmental modeling. We characterized the short-scale spatial heterogeneity of soil properties in an Alfisol catena in a tropical landscape of Sri Lanka. The impact of different land-uses (paddy, vegetable and un-cultivated) was examined to assess the impact of anthropogenic activities on the variability of soil properties at the catenary level. Conditioned Latin hypercube sampling was used to collect 58 geo-referenced topsoil samples (0–30 cm) from the study area. Soil samples were analyzedmore » for pH, electrical conductivity (EC), organic carbon (OC), cation exchange capacity (CEC) and texture. The spatial correlation between soil properties was analyzed by computing crossvariograms and subsequent fitting of theoretical model. Spatial distribution maps were developed using ordinary kriging. The range of soil properties, pH: 4.3–7.9; EC: 0.01–0.18 dS m –1 ; OC: 0.1–1.37%; CEC: 0.44– 11.51 cmol (+) kg –1 ; clay: 1.5–25% and sand: 59.1–84.4% and their coefficient of variations indicated a large variability in the study area. Electrical conductivity and pH showed a strong spatial correlation which was reflected by the cross-variogram close to the hull of the perfect correlation. Moreover, cross-variograms calculated for EC and Clay, CEC and OC, CEC and clay and CEC and pH indicated weak positive spatial correlation between these properties. Relative nugget effect (RNE) calculated from variograms showed strongly structured spatial variability for pH, EC and sand content (RNE < 25%) while CEC, organic carbon and clay content showed moderately structured spatial variability (25% < RNE < 75%). Spatial dependencies for examined soil properties ranged from 48 to 984 m. The mixed effects model fitting followed by Tukey's post-hoc test showed significant effect of land use on the spatial variability of EC. Our study revealed a structured variability of topsoil properties in the selected tropical Alfisol catena. Except for EC, observed variability was not modified by the land uses. Investigated soil properties showed distinct spatial structures at different scales and magnitudes of strength. Our results will be useful for digital soil mapping, site specific management of soil properties, developing appropriate land use plans and quantifying anthropogenic impacts on the soil system.« less

A hardware/software environment to support R D in intelligent machines and mobile robotic systems

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

Mann, R.C.

1990-01-01

The Center for Engineering Systems Advanced Research (CESAR) serves as a focal point at the Oak Ridge National Laboratory (ORNL) for basic and applied research in intelligent machines. R D at CESAR addresses issues related to autonomous systems, unstructured (i.e. incompletely known) operational environments, and multiple performing agents. Two mobile robot prototypes (HERMIES-IIB and HERMIES-III) are being used to test new developments in several robot component technologies. This paper briefly introduces the computing environment at CESAR which includes three hypercube concurrent computers (two on-board the mobile robots), a graphics workstation, VAX, and multiple VME-based systems (several on-board the mobile robots).more » The current software environment at CESAR is intended to satisfy several goals, e.g.: code portability, re-usability in different experimental scenarios, modularity, concurrent computer hardware transparent to applications programmer, future support for multiple mobile robots, support human-machine interface modules, and support for integration of software from other, geographically disparate laboratories with different hardware set-ups. 6 refs., 1 fig.« less

A network flow model for load balancing in circuit-switched multicomputers

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1990-01-01

In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.

Impact of atmospheric correction and image filtering on hyperspectral classification of tree species using support vector machine

NASA Astrophysics Data System (ADS)

Shahriari Nia, Morteza; Wang, Daisy Zhe; Bohlman, Stephanie Ann; Gader, Paul; Graves, Sarah J.; Petrovic, Milenko

2015-01-01

Hyperspectral images can be used to identify savannah tree species at the landscape scale, which is a key step in measuring biomass and carbon, and tracking changes in species distributions, including invasive species, in these ecosystems. Before automated species mapping can be performed, image processing and atmospheric correction is often performed, which can potentially affect the performance of classification algorithms. We determine how three processing and correction techniques (atmospheric correction, Gaussian filters, and shade/green vegetation filters) affect the prediction accuracy of classification of tree species at pixel level from airborne visible/infrared imaging spectrometer imagery of longleaf pine savanna in Central Florida, United States. Species classification using fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) atmospheric correction outperformed ATCOR in the majority of cases. Green vegetation (normalized difference vegetation index) and shade (near-infrared) filters did not increase classification accuracy when applied to large and continuous patches of specific species. Finally, applying a Gaussian filter reduces interband noise and increases species classification accuracy. Using the optimal preprocessing steps, our classification accuracy of six species classes is about 75%.

The science of computing - Parallel computation

NASA Technical Reports Server (NTRS)

Denning, P. J.

1985-01-01

Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.

Examples of equilibrium and non-equilibrium behavior in evolutionary systems

NASA Astrophysics Data System (ADS)

Soulier, Arne

With this thesis, we want to shed some light into the darkness of our understanding of simply defined statistical mechanics systems and the surprisingly complex dynamical behavior they exhibit. We will do so by presenting in turn one equilibrium and then one non-equilibrium system with evolutionary dynamics. In part 1, we will present the seceder-model, a newly developed system that cannot equilibrate. We will then study several properties of the system and obtain an idea of the richness of the dynamics of the seceder model, which is particular impressive given the minimal amount of modeling necessary in its setup. In part 2, we will present extensions to the directed polymer in random media problem on a hypercube and its connection to the Eigen model of evolution. Our main interest will be the influence of time-dependent and time-independent changes in the fitness landscape viewed by an evolving population. This part contains the equilibrium dynamics. The stochastic models and the topic of evolution and non-equilibrium in general will allow us to point out similarities to the various lines of thought in game theory.

High dimensional feature reduction via projection pursuit

NASA Technical Reports Server (NTRS)

Jimenez, Luis; Landgrebe, David

1994-01-01

The recent development of more sophisticated remote sensing systems enables the measurement of radiation in many more spectral intervals than previously possible. An example of that technology is the AVIRIS system, which collects image data in 220 bands. As a result of this, new algorithms must be developed in order to analyze the more complex data effectively. Data in a high dimensional space presents a substantial challenge, since intuitive concepts valid in a 2-3 dimensional space to not necessarily apply in higher dimensional spaces. For example, high dimensional space is mostly empty. This results from the concentration of data in the corners of hypercubes. Other examples may be cited. Such observations suggest the need to project data to a subspace of a much lower dimension on a problem specific basis in such a manner that information is not lost. Projection Pursuit is a technique that will accomplish such a goal. Since it processes data in lower dimensions, it should avoid many of the difficulties of high dimensional spaces. In this paper, we begin the investigation of some of the properties of Projection Pursuit for this purpose.

Dynamics of clade diversification on the morphological hypercube

PubMed Central

Gavrilets, S.

1999-01-01

Understanding the relationship between taxonomic and morphological changes is important in identifying the reasons for accelerated morphological diversification early in the history of animal phyla. Here, a simple general model describing the joint dynamics of taxonomic diversity and morphological disparity is presented and applied to the data on the diversification of blastozoans. I show that the observed patterns of deceleration in clade diversification can be explicable in terms of the geometric structure of the morphospace and the effects of extinction and speciation on morphological disparity without invoking major declines in the size of morphological transitions or taxonomic turnover rates. The model allows testing of hypotheses about patterns of diversification and estimation of rates of morphological evolution. In the case of blastozoans, I find no evidence that major changes in evolutionary rates and mechanisms are responsible for the deceleration of morphological diversification seen during the period of this clade's expansion. At the same time, there is evidence for a moderate decline in overall rates of morphological diversification concordant with a major change (from positive to negative values) in the clade's growth rate.

On the Coupling Time of the Heat-Bath Process for the Fortuin-Kasteleyn Random-Cluster Model

NASA Astrophysics Data System (ADS)

Collevecchio, Andrea; Elçi, Eren Metin; Garoni, Timothy M.; Weigel, Martin

2018-01-01

We consider the coupling from the past implementation of the random-cluster heat-bath process, and study its random running time, or coupling time. We focus on hypercubic lattices embedded on tori, in dimensions one to three, with cluster fugacity at least one. We make a number of conjectures regarding the asymptotic behaviour of the coupling time, motivated by rigorous results in one dimension and Monte Carlo simulations in dimensions two and three. Amongst our findings, we observe that, for generic parameter values, the distribution of the appropriately standardized coupling time converges to a Gumbel distribution, and that the standard deviation of the coupling time is asymptotic to an explicit universal constant multiple of the relaxation time. Perhaps surprisingly, we observe these results to hold both off criticality, where the coupling time closely mimics the coupon collector's problem, and also at the critical point, provided the cluster fugacity is below the value at which the transition becomes discontinuous. Finally, we consider analogous questions for the single-spin Ising heat-bath process.

Optimal expression evaluation for data parallel architectures

NASA Technical Reports Server (NTRS)

Gilbert, John R.; Schreiber, Robert

1990-01-01

A data parallel machine represents an array or other composite data structure by allocating one processor (at least conceptually) per data item. A pointwise operation can be performed between two such arrays in unit time, provided their corresponding elements are allocated in the same processors. If the arrays are not aligned in this fashion, the cost of moving one or both of them is part of the cost of the operation. The choice of where to perform the operation then affects this cost. If an expression with several operands is to be evaluated, there may be many choices of where to perform the intermediate operations. An efficient algorithm is given to find the minimum-cost way to evaluate an expression, for several different data parallel architectures. This algorithm applies to any architecture in which the metric describing the cost of moving an array is robust. This encompasses most of the common data parallel communication architectures, including meshes of arbitrary dimension and hypercubes. Remarks are made on several variations of the problem, some of which are solved and some of which remain open.

Proteus: a reconfigurable computational network for computer vision

NASA Astrophysics Data System (ADS)

Haralick, Robert M.; Somani, Arun K.; Wittenbrink, Craig M.; Johnson, Robert; Cooper, Kenneth; Shapiro, Linda G.; Phillips, Ihsin T.; Hwang, Jenq N.; Cheung, William; Yao, Yung H.; Chen, Chung-Ho; Yang, Larry; Daugherty, Brian; Lorbeski, Bob; Loving, Kent; Miller, Tom; Parkins, Larye; Soos, Steven L.

1992-04-01

The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.

User's guide to the Reliability Estimation System Testbed (REST)

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Rifkin, Adam

1992-01-01

The Reliability Estimation System Testbed is an X-window based reliability modeling tool that was created to explore the use of the Reliability Modeling Language (RML). RML was defined to support several reliability analysis techniques including modularization, graphical representation, Failure Mode Effects Simulation (FMES), and parallel processing. These techniques are most useful in modeling large systems. Using modularization, an analyst can create reliability models for individual system components. The modules can be tested separately and then combined to compute the total system reliability. Because a one-to-one relationship can be established between system components and the reliability modules, a graphical user interface may be used to describe the system model. RML was designed to permit message passing between modules. This feature enables reliability modeling based on a run time simulation of the system wide effects of a component's failure modes. The use of failure modes effects simulation enhances the analyst's ability to correctly express system behavior when using the modularization approach to reliability modeling. To alleviate the computation bottleneck often found in large reliability models, REST was designed to take advantage of parallel processing on hypercube processors.

Two-dimensional nonsteady viscous flow simulation on the Navier-Stokes computer miniNode

NASA Technical Reports Server (NTRS)

Nosenchuck, Daniel M.; Littman, Michael G.; Flannery, William

1986-01-01

The needs of large-scale scientific computation are outpacing the growth in performance of mainframe supercomputers. In particular, problems in fluid mechanics involving complex flow simulations require far more speed and capacity than that provided by current and proposed Class VI supercomputers. To address this concern, the Navier-Stokes Computer (NSC) was developed. The NSC is a parallel-processing machine, comprised of individual Nodes, each comparable in performance to current supercomputers. The global architecture is that of a hypercube, and a 128-Node NSC has been designed. New architectural features, such as a reconfigurable many-function ALU pipeline and a multifunction memory-ALU switch, have provided the capability to efficiently implement a wide range of algorithms. Efficient algorithms typically involve numerically intensive tasks, which often include conditional operations. These operations may be efficiently implemented on the NSC without, in general, sacrificing vector-processing speed. To illustrate the architecture, programming, and several of the capabilities of the NSC, the simulation of two-dimensional, nonsteady viscous flows on a prototype Node, called the miniNode, is presented.

SPEEDES - A multiple-synchronization environment for parallel discrete-event simulation

NASA Technical Reports Server (NTRS)

Steinman, Jeff S.

1992-01-01

Synchronous Parallel Environment for Emulation and Discrete-Event Simulation (SPEEDES) is a unified parallel simulation environment. It supports multiple-synchronization protocols without requiring users to recompile their code. When a SPEEDES simulation runs on one node, all the extra parallel overhead is removed automatically at run time. When the same executable runs in parallel, the user preselects the synchronization algorithm from a list of options. SPEEDES currently runs on UNIX networks and on the California Institute of Technology/Jet Propulsion Laboratory Mark III Hypercube. SPEEDES also supports interactive simulations. Featured in the SPEEDES environment is a new parallel synchronization approach called Breathing Time Buckets. This algorithm uses some of the conservative techniques found in Time Bucket synchronization, along with the optimism that characterizes the Time Warp approach. A mathematical model derived from first principles predicts the performance of Breathing Time Buckets. Along with the Breathing Time Buckets algorithm, this paper discusses the rules for processing events in SPEEDES, describes the implementation of various other synchronization protocols supported by SPEEDES, describes some new ones for the future, discusses interactive simulations, and then gives some performance results.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

Optimization of a simplified automobile finite element model using time varying injury metrics.

PubMed

Gaewsky, James P; Danelson, Kerry A; Weaver, Caitlin M; Stitzel, Joel D

2014-01-01

In 2011, frontal crashes resulted in 55% of passenger car injuries with 10,277 fatalities and 866,000 injuries in the United States. To better understand frontal crash injury mechanisms, human body finite element models (FEMs) can be used to reconstruct Crash Injury Research and Engineering Network (CIREN) cases. A limitation of this method is the paucity of vehicle FEMs; therefore, we developed a functionally equivalent simplified vehicle model. The New Car Assessment Program (NCAP) data for our selected vehicle was from a frontal collision with Hybrid III (H3) Anthropomorphic Test Device (ATD) occupant. From NCAP test reports, the vehicle geometry was created and the H3 ATD was positioned. The material and component properties optimized using a variation study process were: steering column shear bolt fracture force and stroke resistance, seatbelt pretensioner force, frontal and knee bolster airbag stiffness, and belt friction through the D-ring. These parameters were varied using three successive Latin Hypercube Designs of Experiments with 130-200 simulations each. The H3 injury response was compared to the reported NCAP frontal test results for the head, chest and pelvis accelerations, and seat belt and femur forces. The phase, magnitude, and comprehensive error factors, from a Sprague and Geers analysis were calculated for each injury metric and then combined to determine the simulations with the best match to the crash test. The Sprague and Geers analyses typically yield error factors ranging from 0 to 1 with lower scores being more optimized. The total body injury response error factor for the most optimized simulation from each round of the variation study decreased from 0.466 to 0.395 to 0.360. This procedure to optimize vehicle FEMs is a valuable tool to conduct future CIREN case reconstructions in a variety of vehicles.

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

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

Walker, Andrew; Lawrence, Earl

The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, "Automated RSM", automates the generation of a drag coefficient RSM for a particular object to a single command. "Automated RSM" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the "Automated RSM" code,more » a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, "RSM Area", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, "RSM Cd", uses the RSM generated by the "Automated RSM" code and the projected area look-up table generated by the "RSM Area" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.« less

Constructing rigorous and broad biosurveillance networks for detecting emerging zoonotic outbreaks

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

Brown, Mac; Moore, Leslie; McMahon, Benjamin

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities ofmore » potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.« less

Drivers And Uncertainties Of Increasing Global Water Scarcity

NASA Astrophysics Data System (ADS)

Scherer, L.; Pfister, S.

2015-12-01

Water scarcity threatens ecosystems and human health and hampers economic development. It generally depends on the ratio of water consumption to availability. We calculated global, spatially explicit water stress indices (WSIs) which describe the vulnerability to additional water consumption on a scale from 0 (low) to 1 (high) and compare them for the decades 1981-1990 and 2001-2010. Input data are obtained from a multi-model ensemble at a resolution of 0.5 degrees. The variability among the models was used to run 1000 Monte Carlo simulations (latin hypercube sampling) and to subsequently estimate uncertainties of the WSIs. Globally, a trend of increasing water scarcity can be observed, however, uncertainties are large. The probability that this trend is actually occurring is as low as 53%. The increase in WSIs is rather driven by higher water use than lower water availability. Water availability is only 40% likely to decrease whereas water consumption is 67% likely to increase. Independent from the trend, we are already living under water scarce conditions, which is reflected in a consumption-weighted average of monthly WSIs of 0.51 in the recent decade. Its coefficient of variation points with 0.8 to the high uncertainties entailed, which might still hide poor model performance where all models consistently over- or underestimate water availability or use. Especially in arid areas, models generally overestimate availability. Although we do not traverse the planetary boundary of freshwater use as global water availability is sufficient, local water scarcity might be high. Therefore the regionalized assessment of WSIs under uncertainty helps to focus on specific regions to optimise water consumption. These global results can also help to raise awareness of water scarcity, and to suggest relevant measures such as more water efficient technologies to international companies, which have to deal with complex and distributed supply chains (e.g. in food production).

Assessing the impact of intervention strategies against Taenia solium cysticercosis using the EPICYST transmission model.

PubMed

Winskill, Peter; Harrison, Wendy E; French, Michael D; Dixon, Matthew A; Abela-Ridder, Bernadette; Basáñez, María-Gloria

2017-02-09

The pork tapeworm, Taenia solium, and associated human infections, taeniasis, cysticercosis and neurocysticercosis, are serious public health problems, especially in developing countries. The World Health Organization (WHO) has set goals for having a validated strategy for control and elimination of T. solium taeniasis/cysticercosis by 2015 and interventions scaled-up in selected countries by 2020. Timely achievement of these internationally-endorsed targets requires that the relative benefits and effectiveness of potential interventions be explored rigorously within a quantitative framework. A deterministic, compartmental transmission model (EPICYST) was developed to capture the dynamics of the taeniasis/cysticercosis disease system in the human and pig hosts. Cysticercosis prevalence in humans, an outcome of high epidemiological and clinical importance, was explicitly modelled. A next generation matrix approach was used to derive an expression for the basic reproduction number, R 0 . A full sensitivity analysis was performed using a methodology based on Latin-hypercube sampling partial rank correlation coefficient index. EPICYST outputs indicate that chemotherapeutic intervention targeted at humans or pigs would be highly effective at reducing taeniasis and cysticercosis prevalence when applied singly, with annual chemotherapy of humans and pigs resulting, respectively, in 94 and 74% of human cysticercosis cases averted. Improved sanitation, meat inspection and animal husbandry are less effective but are still able to reduce prevalence singly or in combination. The value of R 0 for taeniasis was estimated at 1.4 (95% Credible Interval: 0.5-3.6). Human- and pig-targeted drug-focussed interventions appear to be the most efficacious approach from the options currently available. The model presented is a forward step towards developing an informed control and elimination strategy for cysticercosis. Together with its validation against field data, EPICYST will be a valuable tool to help reach the WHO goals and to conduct economic evaluations of interventions in varying epidemiological settings.

Capturing spatial heterogeneity of soil organic carbon under changing climate

NASA Astrophysics Data System (ADS)

Mishra, U.; Fan, Z.; Jastrow, J. D.; Matamala, R.; Vitharana, U.

2015-12-01

The spatial heterogeneity of the land surface affects water, energy, and greenhouse gas exchanges with the atmosphere. Designing observation networks that capture land surface spatial heterogeneity is a critical scientific challenge. Here, we present a geospatial approach to capture the existing spatial heterogeneity of soil organic carbon (SOC) stocks across Alaska, USA. We used the standard deviation of 556 georeferenced SOC profiles previously compiled in Mishra and Riley (2015, Biogeosciences, 12:3993-4004) to calculate the number of observations that would be needed to reliably estimate Alaskan SOC stocks. This analysis indicated that 906 randomly distributed observation sites would be needed to quantify the mean value of SOC stocks across Alaska at a confidence interval of ± 5 kg m-2. We then used soil-forming factors (climate, topography, land cover types, surficial geology) to identify the locations of appropriately distributed observation sites by using the conditioned Latin hypercube sampling approach. Spatial correlation and variogram analyses demonstrated that the spatial structures of soil-forming factors were adequately represented by these 906 sites. Using the spatial correlation length of existing SOC observations, we identified 484 new observation sites would be needed to provide the best estimate of the present status of SOC stocks in Alaska. We then used average decadal projections (2020-2099) of precipitation, temperature, and length of growing season for three representative concentration pathway (RCP 4.5, 6.0, and 8.5) scenarios of the Intergovernmental Panel on Climate Change to investigate whether the location of identified observation sites will shift/change under future climate. Our results showed 12-41 additional observation sites (depending on emission scenarios) will be required to capture the impact of projected climatic conditions by 2100 on the spatial heterogeneity of Alaskan SOC stocks. Our results represent an ideal distribution of observation sites across Alaska that captures the land surface spatial heterogeneity and can be used in efforts to quantify SOC stocks, monitor greenhouse gas emissions, and benchmark Earth System Model results.

A clinically parameterized mathematical model of Shigella immunity to inform vaccine design

PubMed Central

Wahid, Rezwanul; Toapanta, Franklin R.; Simon, Jakub K.; Sztein, Marcelo B.

2018-01-01

We refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella′s lipopolysaccharide (LPS) and O-membrane proteins (OMP) were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella′s LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1) the rate that Shigella migrates into the lamina propria or epithelium, 2) the rate that memory B cells (BM) differentiate into antibody-secreting cells (ASC), 3) the rate at which antibodies are produced by activated ASC, and 4) the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine. PMID:29304144

A clinically parameterized mathematical model of Shigella immunity to inform vaccine design.

PubMed

Davis, Courtney L; Wahid, Rezwanul; Toapanta, Franklin R; Simon, Jakub K; Sztein, Marcelo B

2018-01-01

We refine and clinically parameterize a mathematical model of the humoral immune response against Shigella, a diarrheal bacteria that infects 80-165 million people and kills an estimated 600,000 people worldwide each year. Using Latin hypercube sampling and Monte Carlo simulations for parameter estimation, we fit our model to human immune data from two Shigella EcSf2a-2 vaccine trials and a rechallenge study in which antibody and B-cell responses against Shigella's lipopolysaccharide (LPS) and O-membrane proteins (OMP) were recorded. The clinically grounded model is used to mathematically investigate which key immune mechanisms and bacterial targets confer immunity against Shigella and to predict which humoral immune components should be elicited to create a protective vaccine against Shigella. The model offers insight into why the EcSf2a-2 vaccine had low efficacy and demonstrates that at a group level a humoral immune response induced by EcSf2a-2 vaccine or wild-type challenge against Shigella's LPS or OMP does not appear sufficient for protection. That is, the model predicts an uncontrolled infection of gut epithelial cells that is present across all best-fit model parameterizations when fit to EcSf2a-2 vaccine or wild-type challenge data. Using sensitivity analysis, we explore which model parameter values must be altered to prevent the destructive epithelial invasion by Shigella bacteria and identify four key parameter groups as potential vaccine targets or immune correlates: 1) the rate that Shigella migrates into the lamina propria or epithelium, 2) the rate that memory B cells (BM) differentiate into antibody-secreting cells (ASC), 3) the rate at which antibodies are produced by activated ASC, and 4) the Shigella-specific BM carrying capacity. This paper underscores the need for a multifaceted approach in ongoing efforts to design an effective Shigella vaccine.

Assessing the Impact of Model Parameter Uncertainty in Simulating Grass Biomass Using a Hybrid Carbon Allocation Strategy

NASA Astrophysics Data System (ADS)

Reyes, J. J.; Adam, J. C.; Tague, C.

2016-12-01

Grasslands play an important role in agricultural production as forage for livestock; they also provide a diverse set of ecosystem services including soil carbon (C) storage. The partitioning of C between above and belowground plant compartments (i.e. allocation) is influenced by both plant characteristics and environmental conditions. The objectives of this study are to 1) develop and evaluate a hybrid C allocation strategy suitable for grasslands, and 2) apply this strategy to examine the importance of various parameters related to biogeochemical cycling, photosynthesis, allocation, and soil water drainage on above and belowground biomass. We include allocation as an important process in quantifying the model parameter uncertainty, which identifies the most influential parameters and what processes may require further refinement. For this, we use the Regional Hydro-ecologic Simulation System, a mechanistic model that simulates coupled water and biogeochemical processes. A Latin hypercube sampling scheme was used to develop parameter sets for calibration and evaluation of allocation strategies, as well as parameter uncertainty analysis. We developed the hybrid allocation strategy to integrate both growth-based and resource-limited allocation mechanisms. When evaluating the new strategy simultaneously for above and belowground biomass, it produced a larger number of less biased parameter sets: 16% more compared to resource-limited and 9% more compared to growth-based. This also demonstrates its flexible application across diverse plant types and environmental conditions. We found that higher parameter importance corresponded to sub- or supra-optimal resource availability (i.e. water, nutrients) and temperature ranges (i.e. too hot or cold). For example, photosynthesis-related parameters were more important at sites warmer than the theoretical optimal growth temperature. Therefore, larger values of parameter importance indicate greater relative sensitivity in adequately representing the relevant process to capture limiting resources or manage atypical environmental conditions. These results may inform future experimental work by focusing efforts on quantifying specific parameters under various environmental conditions or across diverse plant functional types.

Constructing rigorous and broad biosurveillance networks for detecting emerging zoonotic outbreaks

DOE PAGES

Brown, Mac; Moore, Leslie; McMahon, Benjamin; ...

2015-05-06

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities ofmore » potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.« less

Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study

NASA Astrophysics Data System (ADS)

Aleksankina, Ksenia; Heal, Mathew R.; Dore, Anthony J.; Van Oijen, Marcel; Reis, Stefan

2018-04-01

Atmospheric chemistry transport models (ACTMs) are widely used to underpin policy decisions associated with the impact of potential changes in emissions on future pollutant concentrations and deposition. It is therefore essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input pollutant emissions. ACTMs incorporate complex and non-linear descriptions of chemical and physical processes which means that interactions and non-linearities in input-output relationships may not be revealed through the local one-at-a-time sensitivity analysis typically used. The aim of this work is to demonstrate a global sensitivity and uncertainty analysis approach for an ACTM, using as an example the FRAME model, which is extensively employed in the UK to generate source-receptor matrices for the UK Integrated Assessment Model and to estimate critical load exceedances. An optimised Latin hypercube sampling design was used to construct model runs within ±40 % variation range for the UK emissions of SO2, NOx, and NH3, from which regression coefficients for each input-output combination and each model grid ( > 10 000 across the UK) were calculated. Surface concentrations of SO2, NOx, and NH3 (and of deposition of S and N) were found to be predominantly sensitive to the emissions of the respective pollutant, while sensitivities of secondary species such as HNO3 and particulate SO42-, NO3-, and NH4+ to pollutant emissions were more complex and geographically variable. The uncertainties in model output variables were propagated from the uncertainty ranges reported by the UK National Atmospheric Emissions Inventory for the emissions of SO2, NOx, and NH3 (±4, ±10, and ±20 % respectively). The uncertainties in the surface concentrations of NH3 and NOx and the depositions of NHx and NOy were dominated by the uncertainties in emissions of NH3, and NOx respectively, whilst concentrations of SO2 and deposition of SOy were affected by the uncertainties in both SO2 and NH3 emissions. Likewise, the relative uncertainties in the modelled surface concentrations of each of the secondary pollutant variables (NH4+, NO3-, SO42-, and HNO3) were due to uncertainties in at least two input variables. In all cases the spatial distribution of relative uncertainty was found to be geographically heterogeneous. The global methods used here can be applied to conduct sensitivity and uncertainty analyses of other ACTMs.

Security, protection, and control of power systems with large-scale wind power penetration

NASA Astrophysics Data System (ADS)

Acharya, Naresh

As the number of wind generation facilities in the utility system is fast increasing, many issues associated with their integration into the power system are beginning to emerge. Of the various issues, this dissertation deals with the development of new concepts and computational methods to handle the transmission issues and voltage issues caused by large-scale integration of wind turbines. This dissertation also formulates a probabilistic framework for the steady-state security assessment of wind power incorporating the forecast uncertainty and correlation. Transmission issues are mainly related to the overloading of transmission lines, when all the wind power generated cannot be delivered in full due to prior outage conditions. To deal with this problem, a method to curtail the wind turbine outputs through Energy Management System facilities in the on-line operational environment is proposed. The proposed method, which is based on linear optimization, sends the calculated control signals via the Supervisory Control and Data Acquisition system to wind farm controllers. The necessary ramping of the wind farm outputs is implemented either by the appropriate blade pitch angle control at the turbine level or by switching a certain number of turbines. The curtailment strategy is tested with an equivalent system model of MidAmerican Energy Company. The results show that the line overload in high wind areas can be alleviated by controlling the outputs of the wind farms step-by-step over an allowable period of time. A low voltage event during a system fault can cause a large number of wind turbines to trip, depending on voltages at the wind turbine terminals during the fault and the under-voltage protection setting of wind turbines. As a result, an N-1 contingency may evolve into an N-(K+1) contingency, where K is the number of wind farms tripped due to low voltage conditions. Losing a large amount of wind power following a line contingency might lead to system instabilities. It is important for the system operator to be aware of such limiting events during system operation and be prepared to take proper control actions. This can be achieved by incorporating the wind farm tripping status for each contingency as part of the static security assessment. A methodology to calculate voltages at the wind farm buses during a worst case line fault is proposed, which, along with the protection settings of wind turbines, can be used to determine the tripping of wind farms. The proposed algorithm is implemented in MATLAB and tested with MidAmerican Energy reduced network. The result shows that a large amount of wind capacity can be tripped due to a fault in the lines. Therefore, the technique will find its application in the static security assessment where each line fault can be associated with the tripping of wind farms as determined from the proposed method. A probabilistic framework to handle the uncertainty in day-ahead forecast error in order to correctly assess the steady-state security of the power system is presented. Stochastic simulations are conducted by means of Latin hypercube sampling along with the consideration of correlations. The correlation is calculated from the historical distribution of wind power forecast errors. The results from the deterministic simulation based on point forecast and the stochastic simulation show that security assessment based solely on deterministic simulations can lead to incorrect assessment of system security. With stochastic simulations, each outcome can be assigned a probability and the decision regarding control actions can be made based on the associated probability.

Wavefunctions, quantum diffusion, and scaling exponents in golden-mean quasiperiodic tilings.

PubMed

Thiem, Stefanie; Schreiber, Michael

2013-02-20

We study the properties of wavefunctions and the wavepacket dynamics in quasiperiodic tight-binding models in one, two, and three dimensions. The atoms in the one-dimensional quasiperiodic chains are coupled by weak and strong bonds aligned according to the Fibonacci sequence. The associated d-dimensional quasiperiodic tilings are constructed from the direct product of d such chains, which yields either the hypercubic tiling or the labyrinth tiling. This approach allows us to consider fairly large systems numerically. We show that the wavefunctions of the system are multifractal and that their properties can be related to the structure of the system in the regime of strong quasiperiodic modulation by a renormalization group (RG) approach. We also study the dynamics of wavepackets to get information about the electronic transport properties. In particular, we investigate the scaling behaviour of the return probability of the wavepacket with time. Applying again the RG approach we show that in the regime of strong quasiperiodic modulation the return probability is governed by the underlying quasiperiodic structure. Further, we also discuss lower bounds for the scaling exponent of the width of the wavepacket and propose a modified lower bound for the absolute continuous regime.

de Almeida-Thouless instability in short-range Ising spin glasses

NASA Astrophysics Data System (ADS)

Singh, R. R. P.; Young, A. P.

2017-07-01

We use high-temperature series expansions to study the ±J Ising spin glass in a magnetic field in d -dimensional hypercubic lattices for d =5 -8 and in the infinite-range Sherrington-Kirkpatrick (SK) model. The expansions are obtained in the variable w =tanh2J /T for arbitrary values of u =tanh2h /T complete to order w10. We find that the scaling dimension Δ associated with the ordering-field h2 equals 2 in the SK model and for d ≥6 . However, in agreement with the work of Fisher and Sompolinsky [Phys. Rev. Lett. 54, 1063 (1985), 10.1103/PhysRevLett.54.1063], there is a violation of scaling in a finite field, leading to an anomalous h -T dependence of the de Almeida-Thouless (AT) [J. Phys. A 11, 983 (1978), 10.1088/0305-4470/11/5/028] line in high dimensions, whereas scaling is restored as d →6 . Within the convergence of our series analysis, we present evidence supporting an AT line in d ≥6 . In d =5 , the exponents γ and Δ are substantially larger than mean-field values, but we do not see clear evidence for the AT line in d =5 .

Maximally random discrete-spin systems with symmetric and asymmetric interactions and maximally degenerate ordering

NASA Astrophysics Data System (ADS)

Atalay, Bora; Berker, A. Nihat

2018-05-01

Discrete-spin systems with maximally random nearest-neighbor interactions that can be symmetric or asymmetric, ferromagnetic or antiferromagnetic, including off-diagonal disorder, are studied, for the number of states q =3 ,4 in d dimensions. We use renormalization-group theory that is exact for hierarchical lattices and approximate (Migdal-Kadanoff) for hypercubic lattices. For all d >1 and all noninfinite temperatures, the system eventually renormalizes to a random single state, thus signaling q ×q degenerate ordering. Note that this is the maximally degenerate ordering. For high-temperature initial conditions, the system crosses over to this highly degenerate ordering only after spending many renormalization-group iterations near the disordered (infinite-temperature) fixed point. Thus, a temperature range of short-range disorder in the presence of long-range order is identified, as previously seen in underfrustrated Ising spin-glass systems. The entropy is calculated for all temperatures, behaves similarly for ferromagnetic and antiferromagnetic interactions, and shows a derivative maximum at the short-range disordering temperature. With a sharp immediate contrast of infinitesimally higher dimension 1 +ɛ , the system is as expected disordered at all temperatures for d =1 .

Critical percolation clusters in seven dimensions and on a complete graph

NASA Astrophysics Data System (ADS)

Huang, Wei; Hou, Pengcheng; Wang, Junfeng; Ziff, Robert M.; Deng, Youjin

2018-02-01

We study critical bond percolation on a seven-dimensional hypercubic lattice with periodic boundary conditions (7D) and on the complete graph (CG) of finite volume (number of vertices) V . We numerically confirm that for both cases, the critical number density n (s ,V ) of clusters of size s obeys a scaling form n (s ,V ) ˜s-τn ˜(s /Vdf*) with identical volume fractal dimension df*=2 /3 and exponent τ =1 +1 /df*=5 /2 . We then classify occupied bonds into bridge bonds, which includes branch and junction bonds, and nonbridge bonds; a bridge bond is a branch bond if and only if its deletion produces at least one tree. Deleting branch bonds from percolation configurations produces leaf-free configurations, whereas deleting all bridge bonds leads to bridge-free configurations composed of blobs. It is shown that the fraction of nonbridge (biconnected) bonds vanishes, ρn ,CG→0 , for large CGs, but converges to a finite value, ρn ,7 D=0.006 193 1 (7 ) , for the 7D hypercube. Further, we observe that while the bridge-free dimension dbf*=1 /3 holds for both the CG and 7D cases, the volume fractal dimensions of the leaf-free clusters are different: dlf,7 D *=0.669 (9 ) ≈2 /3 and dlf,CG *=0.3337 (17 ) ≈1 /3 . On the CG and in 7D, the whole, leaf-free, and bridge-free clusters all have the shortest-path volume fractal dimension dmin*≈1 /3 , characterizing their graph diameters. We also study the behavior of the number and the size distribution of leaf-free and bridge-free clusters. For the number of clusters, we numerically find the number of leaf-free and bridge-free clusters on the CG scale as ˜lnV , while for 7D they scale as ˜V . For the size distribution, we find the behavior on the CG is governed by a modified Fisher exponent τ'=1 , while for leaf-free clusters in 7D, it is governed by Fisher exponent τ =5 /2 . The size distribution of bridge-free clusters in 7D displays two-scaling behavior with exponents τ =4 and τ'=1 . The probability distribution P (C1,V ) d C1 of the largest cluster of size C1 for whole percolation configurations is observed to follow a single-variable function P ¯(x ) d x , with x ≡C1/Vdf* for both CG and 7D. Up to a rescaling factor for the variable x , the probability functions for CG and 7D collapse on top of each other within the entire range of x . The analytical expressions in the x →0 and x →∞ limits are further confirmed. Our work demonstrates that the geometric structure of high-dimensional percolation clusters cannot be fully accounted for by their complete-graph counterparts.

Simplified predictive models for CO 2 sequestration performance assessment

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

Mishra, Srikanta; Ganesh, Priya; Schuetter, Jared

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessmentmore » modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.« less

Coastal aquifer management under parameter uncertainty: Ensemble surrogate modeling based simulation-optimization

NASA Astrophysics Data System (ADS)

Janardhanan, S.; Datta, B.

2011-12-01

Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of saltwater intrusion are considered. The salinity levels resulting at strategic locations due to these pumping are predicted using the ensemble surrogates and are constrained to be within pre-specified levels. Different realizations of the concentration values are obtained from the ensemble predictions corresponding to each candidate solution of pumping. Reliability concept is incorporated as the percent of the total number of surrogate models which satisfy the imposed constraints. The methodology was applied to a realistic coastal aquifer system in Burdekin delta area in Australia. It was found that all optimal solutions corresponding to a reliability level of 0.99 satisfy all the constraints and as reducing reliability level decreases the constraint violation increases. Thus ensemble surrogate model based simulation-optimization was found to be useful in deriving multi-objective optimal pumping strategies for coastal aquifers under parameter uncertainty.

Fossil vs. non-fossil sources of fine carbonaceous aerosols in four Chinese cities during the extreme winter haze episode in 2013

NASA Astrophysics Data System (ADS)

Zhang, Y.-L.; Huang, R.-J.; El Haddad, I.; Ho, K.-F.; Cao, J.-J.; Han, Y.; Zotter, P.; Bozzetti, C.; Daellenbach, K. R.; Canonaco, F.; Slowik, J. G.; Salazar, G.; Schwikowski, M.; Schnelle-Kreis, J.; Abbaszade, G.; Zimmermann, R.; Baltensperger, U.; Prévôt, A. S. H.; Szidat, S.

2014-10-01

During winter 2013, extremely high concentrations (i.e. 4-20 times higher than the World Health Organization guideline) of PM2.5 (particulate matter with an aerodynamic diameter <2.5 μm) were reported in several large cities in China. In this work, source apportionment of fine carbonaceous aerosols during this haze episode was conducted at four major cities in China including Xian, Beijing, Shanghai and Guangzhou. An effective statistical analysis of a combined dataset from elemental carbon (EC) and organic carbon (OC), radiocarbon (14C) and biomass-burning marker measurements using Latin-hypercube sampling allowed a quantitative source apportionment of carbonaceous aerosols. We found that fossil emissions from coal combustion and vehicle exhaust dominated EC with a mean contribution of 75 ± 8% at all sites. The remaining 25 ± 8% was exclusively attributed to biomass combustion, consistent with the measurements of biomass-burning markers such as anhydrosugars (levoglucosan and mannosan) and water-soluble potassium (K+). With a combination of the levoglucosan-to-mannosan and levoglucosan-to-K+ ratios, the major source of biomass burning in winter in China is suggested to be combustion of crop residues. The contribution of fossil sources to OC was highest in Beijing (58 ± 5%) and decreased from Shanghai (49 ± 2%) to Xian (38 ± 3%) and Guangzhou (35 ± 7%). Generally, a larger fraction of fossil OC was rather from secondary origins than primary sources for all sites. Non-fossil sources accounted on average for 55 ± 10% and 48 ± 9% of OC and TC, respectively, which suggests that non-fossil emissions were very important contributors of urban carbonaceous aerosols in China. The primary biomass-burning emissions accounted for 40 ± 8%, 48 ± 18%, 53 ± 4% and 65 ± 26% of non-fossil OC for Xian, Beijing, Shanghai and Guangzhou, respectively. Other non-fossil sources excluding primary biomass-burning were mainly attributed to formation of secondary organic carbon (SOC) from non-fossil precursors such as biomass-burning emissions. For each site, we also compared samples from moderately with heavily polluted days according to particulate matter mass. Despite a significant increase of absolute mass concentrations of primary emissions from both, fossil and non-fossil sources, during the heavily polluted events, their relative contribution to TC was even decreased, whereas the portion of SOC was consistently increased at all sites. This observation indicates that SOC was an important fraction in the increment of carbonaceous aerosols during the haze episode in China.

Simplified Predictive Models for CO2 Sequestration Performance Assessment

NASA Astrophysics Data System (ADS)

Mishra, Srikanta; RaviGanesh, Priya; Schuetter, Jared; Mooney, Douglas; He, Jincong; Durlofsky, Louis

2014-05-01

We present results from an ongoing research project that seeks to develop and validate a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formation. The overall research goal is to provide tools for predicting: (a) injection well and formation pressure buildup, and (b) lateral and vertical CO2 plume migration. Simplified modeling approaches that are being developed in this research fall under three categories: (1) Simplified physics-based modeling (SPM), where only the most relevant physical processes are modeled, (2) Statistical-learning based modeling (SLM), where the simulator is replaced with a "response surface", and (3) Reduced-order method based modeling (RMM), where mathematical approximations reduce the computational burden. The system of interest is a single vertical well injecting supercritical CO2 into a 2-D layered reservoir-caprock system with variable layer permeabilities. In the first category (SPM), we use a set of well-designed full-physics compositional simulations to understand key processes and parameters affecting pressure propagation and buoyant plume migration. Based on these simulations, we have developed correlations for dimensionless injectivity as a function of the slope of fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. In the second category (SLM), we develop statistical "proxy models" using the simulation domain described previously with two different approaches: (a) classical Box-Behnken experimental design with a quadratic response surface fit, and (b) maximin Latin Hypercube sampling (LHS) based design with a Kriging metamodel fit using a quadratic trend and Gaussian correlation structure. For roughly the same number of simulations, the LHS-based meta-model yields a more robust predictive model, as verified by a k-fold cross-validation approach. In the third category (RMM), we use a reduced-order modeling procedure that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) for extrapolating system response at new control points from a limited number of trial runs ("snapshots"). We observe significant savings in computational time with very good accuracy from the POD-TPWL reduced order model - which could be important in the context of history matching, uncertainty quantification and optimization problems. The paper will present results from our ongoing investigations, and also discuss future research directions and likely outcomes. This work was supported by U.S. Department of Energy National Energy Technology Laboratory award DE-FE0009051 and Ohio Department of Development grant D-13-02.

Microgravity-Driven Optic Nerve/Sheath Biomechanics Simulations

NASA Technical Reports Server (NTRS)

Ethier, C. R.; Feola, A.; Myers, J. G.; Nelson, E.; Raykin, J.; Samuels, B.

2016-01-01

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Current thinking suggests that the ocular changes observed in VIIP syndrome are related to cephalad fluid shifts resulting in altered fluid pressures [1]. In particular, we hypothesize that increased intracranial pressure (ICP) drives connective tissue remodeling of the posterior eye and optic nerve sheath (ONS). We describe here finite element (FE) modeling designed to understand how altered pressures, particularly altered ICP, affect the tissues of the posterior eye and optic nerve sheath (ONS) in VIIP. METHODS: Additional description of the modeling methodology is provided in the companion IWS abstract by Feola et al. In brief, a geometric model of the posterior eye and optic nerve, including the ONS, was created and the effects of fluid pressures on tissue deformations were simulated. We considered three ICP scenarios: an elevated ICP assumed to occur in chronic microgravity, and ICP in the upright and supine positions on earth. Within each scenario we used Latin hypercube sampling (LHS) to consider a range of ICPs, ONH tissue mechanical properties, intraocular pressures (IOPs) and mean arterial pressures (MAPs). The outcome measures were biomechanical strains in the lamina cribrosa, optic nerve and retina; here we focus on peak values of these strains, since elevated strain alters cell phenotype and induce tissue remodeling. In 3D, the strain field can be decomposed into three orthogonal components, denoted as first, second and third principal strains. RESULTS AND CONCLUSIONS: For baseline material properties, increasing ICP from 0 to 20 mmHg significantly changed strains within the posterior eye and ONS (Fig. 1), indicating that elevated ICP affects ocular tissue biomechanics. Notably, strains in the lamina cribrosa and retina became less extreme as ICP increased; however, within the optic nerve, the occurrence of such extreme strains greatly increased as ICP was elevated (Fig. 2). In particular, c. 48 of simulations in the elevated ICP condition showed peak strains in the optic nerve that exceeded the strains expected on earth. Such extreme strains are likely important, since they represent a larger signal for mechano-responsive resident cells [2]. The models predicted little to no anterior motion of the prelaminar neural tissue (optic nerve swelling, or papilledema, secondary to axoplasmic stasis), typically seen with elevated ICP. Specialized FE models to capture axoplasmic stasis would be required to study papilledema. These results suggest that the most notable effect of elevated ICP may occur via direct optic nerve loading, rather than through connective tissue deformation. These FE models can inform the design of future studies designed to bridge the gap between biomechanics and pathophysiological function in VIIP.

Cystic Echinococcosis in the Province of Álava, North Spain: The Monetary Burden of a Disease No Longer under Surveillance

PubMed Central

Carabin, Hélène; Balsera-Rodríguez, Francisco J.; Rebollar-Sáenz, José; Benner, Christine T.; Benito, Aitziber; Fernández-Crespo, Juan C.; Carmena, David

2014-01-01

Cystic echinococcosis (CE) is endemic in Spain but has been considered non-endemic in the province of Álava, Northern Spain, since 1997. However, Álava is surrounded by autonomous regions with some of the highest CE prevalence proportions in the nation, casting doubts about the current classification. The purpose of this study is to estimate the frequency of CE in humans and animals and to use this data to determine the societal cost incurred due to CE in the Álava population in 2005. We have identified epidemiological and clinical data from surveillance and hospital records, prevalence data in intermediate (sheep and cattle) host species from abattoir records, and economical data from national and regional official institutions. Direct costs (diagnosis, treatment, medical care in humans and condemnation of offal in livestock species) and indirect costs (productivity losses in humans and reduction in growth, fecundity and milk production in livestock) were modelled using the Latin hypercube method under five different scenarios reflecting different assumptions regarding the prevalence of asymptomatic cases and associated productivity losses in humans. A total of 13 human CE cases were reported in 2005. The median total cost (95% credible interval) of CE in humans and animals in Álava in 2005 was estimated to range between €61,864 (95%CI%: €47,304–€76,590) and €360,466 (95%CI: €76,424–€752,469), with human-associated losses ranging from 57% to 93% of the total losses, depending on the scenario used. Our data provide evidence that CE is still very well present in Álava and incurs important cost to the province every year. We expect this information to prove valuable for public health agencies and policy-makers, as it seems advisable to reinstate appropriate surveillance and monitoring systems and to implement effective control measures that avoid the spread and recrudescence of the disease. PMID:25102173

Assessing the Impact of Climate Change on Extreme Streamflow and Reservoir Operation for Nuuanu Watershed, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.

2016-12-01

Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in reservoir operation as well as in identifying appropriate climate change adaptation strategies.

Male Circumcision and the Epidemic Emergence of HIV-2 in West Africa.

PubMed

Sousa, João Dinis; Temudo, Marina Padrão; Hewlett, Barry Stephen; Camacho, Ricardo Jorge; Müller, Viktor; Vandamme, Anne-Mieke

2016-01-01

Epidemic HIV-2 (groups A and B) emerged in humans circa 1930-40. Its closest ancestors are SIVsmm infecting sooty mangabeys from southwestern Côte d'Ivoire. The earliest large-scale serological surveys of HIV-2 in West Africa (1985-91) show a patchy spread. Côte d'Ivoire and Guinea-Bissau had the highest prevalence rates by then, and phylogeographical analysis suggests they were the earliest epicenters. Wars and parenteral transmission have been hypothesized to have promoted HIV-2 spread. Male circumcision (MC) is known to correlate negatively with HIV-1 prevalence in Africa, but studies examining this issue for HIV-2 are lacking. We reviewed published HIV-2 serosurveys for 30 cities of all West African countries and obtained credible estimates of real prevalence through Bayesian estimation. We estimated past MC rates of 218 West African ethnic groups, based on ethnographic literature and fieldwork. We collected demographic tables specifying the ethnic partition in cities. Uncertainty was incorporated by defining plausible ranges of parameters (e.g. timing of introduction, proportion circumcised). We generated 1,000 sets of past MC rates per city using Latin Hypercube Sampling with different parameter combinations, and explored the correlation between HIV-2 prevalence and estimated MC rate (both logit-transformed) in the 1,000 replicates. Our survey reveals that, in the early 20th century, MC was far less common and geographically more variable than nowadays. HIV-2 prevalence in 1985-91 and MC rates in 1950 were negatively correlated (Spearman rho = -0.546, IQR: -0.553--0.546, p≤0.0021). Guinea-Bissau and Côte d'Ivoire cities had markedly lower MC rates. In addition, MC was uncommon in rural southwestern Côte d'Ivoire in 1930.The differential HIV-2 spread in West Africa correlates with different historical MC rates. We suggest HIV-2 only formed early substantial foci in cities with substantial uncircumcised populations. Lack of MC in rural areas exposed to bushmeat may have had a role in successful HIV-2 emergence.

Uncertainty quantification of surface-water/groundwater exchange estimates in large wetland systems using Python

NASA Astrophysics Data System (ADS)

Hughes, J. D.; Metz, P. A.

2014-12-01

Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss the uncertainty of SWGW exchange estimates using an ET model that partitions the watershed into open water and wetland land-cover types. We will also discuss the uncertainty of SWGW exchange estimates calculated using ET models partitioned into additional land-cover types.

Colorado River basin sensitivity to disturbance impacts

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Urrego-Blanco, J. R.; Jonko, A. K.; Vano, J. A.; Newman, A. J.; Bohn, T. J.; Middleton, R. S.

2017-12-01

The Colorado River basin is an important river for the food-energy-water nexus in the United States and is projected to change under future scenarios of increased CO2emissions and warming. Streamflow estimates to consider climate impacts occurring as a result of this warming are often provided using modeling tools which rely on uncertain inputs—to fully understand impacts on streamflow sensitivity analysis can help determine how models respond under changing disturbances such as climate and vegetation. In this study, we conduct a global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the Variable Infiltration Capacity (VIC) hydrologic model to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in VIC. Additionally, we examine sensitivities of basin-wide model simulations using an approach that incorporates changes in temperature, precipitation and vegetation to consider impact responses for snow-dominated headwater catchments, low elevation arid basins, and for the upper and lower river basins. We find that for the Colorado River basin, snow-dominated regions are more sensitive to uncertainties. New parameter sensitivities identified include runoff/evapotranspiration sensitivity to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI). Basin-wide streamflow sensitivities to precipitation, temperature and vegetation are variable seasonally and also between sub-basins; with the largest sensitivities for smaller, snow-driven headwater systems where forests are dense. For a major headwater basin, a 1ºC of warming equaled a 30% loss of forest cover, while a 10% precipitation loss equaled a 90% forest cover decline. Scenarios utilizing multiple disturbances led to unexpected results where changes could either magnify or diminish extremes, such as low and peak flows and streamflow timing, dependent on the strength and direction of the forcing. These results indicate the importance of understanding model sensitivities under disturbance impacts to manage these shifts; plan for future water resource changes and determine how the impacts will affect the sustainability and adaptability of food-energy-water systems.

The MIT Integrated Global System Model: A facility for Assessing and Communicating Climate Change Uncertainty (Invited)

NASA Astrophysics Data System (ADS)

Prinn, R. G.

2013-12-01

The world is facing major challenges that create tensions between human development and environmental sustenance. In facing these challenges, computer models are invaluable tools for addressing the need for probabilistic approaches to forecasting. To illustrate this, I use the MIT Integrated Global System Model framework (IGSM; http://globalchange.mit.edu ). The IGSM consists of a set of coupled sub-models of global economic and technological development and resultant emissions, and physical, dynamical and chemical processes in the atmosphere, land, ocean and ecosystems (natural and managed). Some of the sub-models have both complex and simplified versions available, with the choice of which version to use being guided by the questions being addressed. Some sub-models (e.g.urban air pollution) are reduced forms of complex ones created by probabilistic collocation with polynomial chaos bases. Given the significant uncertainties in the model components, it is highly desirable that forecasts be probabilistic. We achieve this by running 400-member ensembles (Latin hypercube sampling) with different choices for key uncertain variables and processes within the human and natural system model components (pdfs of inputs estimated by model-observation comparisons, literature surveys, or expert elicitation). The IGSM has recently been used for probabilistic forecasts of climate, each using 400-member ensembles: one ensemble assumes no explicit climate mitigation policy and others assume increasingly stringent policies involving stabilization of greenhouse gases at various levels. These forecasts indicate clearly that the greatest effect of these policies is to lower the probability of extreme changes. The value of such probability analyses for policy decision-making lies in their ability to compare relative (not just absolute) risks of various policies, which are less affected by the earth system model uncertainties. Given the uncertainties in forecasts, it is also clear that we need to evaluate policies based on their ability to lower risk, and to re-evaluate decisions over time as new knowledge is gained. Reference: R. G. Prinn, Development and Application of Earth System Models, Proceedings, National Academy of Science, June 15, 2012, http://www.pnas.org/cgi/doi/10.1073/pnas.1107470109.

Development and Implementation of a Formal Framework for Bottom-up Uncertainty Analysis of Input Emissions: Case Study of Residential Wood Combustion

NASA Astrophysics Data System (ADS)

Zhao, S.; Mashayekhi, R.; Saeednooran, S.; Hakami, A.; Ménard, R.; Moran, M. D.; Zhang, J.

2016-12-01

We have developed a formal framework for documentation, quantification, and propagation of uncertainties in upstream emissions inventory data at various stages leading to the generation of model-ready gridded emissions through emissions processing software such as the EPA's SMOKE (Sparse Matrix Operator Kernel Emissions) system. To illustrate this framework we present a proof-of-concept case study of a bottom-up quantitative assessment of uncertainties in emissions from residential wood combustion (RWC) in the U.S. and Canada. Uncertainties associated with key inventory parameters are characterized based on existing information sources, including the American Housing Survey (AHS) from the U.S. Census Bureau, Timber Products Output (TPO) surveys from the U.S. Forest Service, TNS Canadian Facts surveys, and the AP-42 emission factor document from the U.S. EPA. The propagation of uncertainties is based on Monte Carlo simulation code external to SMOKE. Latin Hypercube Sampling (LHS) is implemented to generate a set of random realizations of each RWC inventory parameter, for which the uncertainties are assumed to be normally distributed. Random realizations are also obtained for each RWC temporal and chemical speciation profile and spatial surrogate field external to SMOKE using the LHS approach. SMOKE outputs for primary emissions (e.g., CO, VOC) using both RWC emission inventory realizations and perturbed temporal and chemical profiles and spatial surrogates show relative uncertainties of about 30-50% across the U.S. and about 70-100% across Canada. Positive skewness values (up to 2.7) and variable kurtosis values (up to 4.8) were also found. Spatial allocation contributes significantly to the overall uncertainty, particularly in Canada. By applying this framework we are able to produce random realizations of model-ready gridded emissions that along with available meteorological ensembles can be used to propagate uncertainties through chemical transport models. The approach described here provides an effective means for formal quantification of uncertainties in estimated emissions from various source sectors and for continuous documentation, assessment, and reduction of emission uncertainties.

A Monte Carlo Uncertainty Analysis of Ozone Trend Predictions in a Two Dimensional Model. Revision

NASA Technical Reports Server (NTRS)

Considine, D. B.; Stolarski, R. S.; Hollandsworth, S. M.; Jackman, C. H.; Fleming, E. L.

1998-01-01

We use Monte Carlo analysis to estimate the uncertainty in predictions of total O3 trends between 1979 and 1995 made by the Goddard Space Flight Center (GSFC) two-dimensional (2D) model of stratospheric photochemistry and dynamics. The uncertainty is caused by gas-phase chemical reaction rates, photolysis coefficients, and heterogeneous reaction parameters which are model inputs. The uncertainty represents a lower bound to the total model uncertainty assuming the input parameter uncertainties are characterized correctly. Each of the Monte Carlo runs was initialized in 1970 and integrated for 26 model years through the end of 1995. This was repeated 419 times using input parameter sets generated by Latin Hypercube Sampling. The standard deviation (a) of the Monte Carlo ensemble of total 03 trend predictions is used to quantify the model uncertainty. The 34% difference between the model trend in globally and annually averaged total O3 using nominal inputs and atmospheric trends calculated from Nimbus 7 and Meteor 3 total ozone mapping spectrometer (TOMS) version 7 data is less than the 46% calculated 1 (sigma), model uncertainty, so there is no significant difference between the modeled and observed trends. In the northern hemisphere midlatitude spring the modeled and observed total 03 trends differ by more than 1(sigma) but less than 2(sigma), which we refer to as marginal significance. We perform a multiple linear regression analysis of the runs which suggests that only a few of the model reactions contribute significantly to the variance in the model predictions. The lack of significance in these comparisons suggests that they are of questionable use as guides for continuing model development. Large model/measurement differences which are many multiples of the input parameter uncertainty are seen in the meridional gradients of the trend and the peak-to-peak variations in the trends over an annual cycle. These discrepancies unambiguously indicate model formulation problems and provide a measure of model performance which can be used in attempts to improve such models.

On the Cubic Lattice Green Functions

NASA Astrophysics Data System (ADS)

Joyce, G. S.

1994-05-01

Wheatstone Physics Laboratory, King's College, University of London, Strand, London WC2R 2LS, U.K. It is proved that K (k+) = [(4-eta )1/2 - (1 - eta )1/2]K(k-), where eta is a complex variable which lies in a certain region R2 of the eta plane, and K (k±) are complete elliptic integrals of the first kind with moduli k± which are given by k±2equiv k±2(eta ) = 1/2 ± 1/4eta (4 - eta )1/2 - 1/4(2-eta )(1-eta )1/2. This basic result is then used to express the face-centred cubic and simple cubic lattice Green functions at the origin in terms of the square of a complete elliptic integral of the first kind. Several new identities involving the Heun function F(a, b; α , β , γ , δ ; eta ) are also derived. Next it is shown that the three cubic lattice Green functions all have parametric representations which involve the Green function for the two-dimensional honeycomb lattice. Finally, the results are applied to a variety of problems in lattice statistics. In particular, a new simplified formula for the generating function of staircase polygons on a four-dimensional hypercubic lattice is derived.

Complete exchange on the iPSC-860

NASA Technical Reports Server (NTRS)

Bokhari, Shahid H.

1991-01-01

The implementation of complete exchange on the circuit switched Intel iPSC-860 hypercube is described. This pattern, also known as all-to-all personalized communication, is the densest requirement that can be imposed on a network. On the iPSC-860, care needs to be taken to avoid edge contention, which can have a disastrous impact on communication time. There are basically two classes of algorithms that achieve contention-free complete exchange. The first contains the classical standard exchange algorithm that is generally useful for small message sizes. The second includes a number of optimal or near-optimal algorithms that are best for large messages. Measurement of communication overhead on the iPSC-860 are given and a notation for analyzing communication link usage is developed. It is shown that for the two classes of algorithms, there is substantial variation in performance with synchronization technique and choice of message protocol. Timings of six implementations are given; each of these is useful over a particular range of message size and cube dimension. Since the complete exchange is a superset of communication patterns, these timings represent upper bounds on the time required by an arbitrary communication requirement. These results indicate that the programmer needs to evaluate several possibilities before finalizing an implementation - a careful choice can lead to very significant savings in time.

Concurrent hypercube system with improved message passing

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Tuazon, Jesus O. (Inventor); Lieberman, Don (Inventor); Pniel, Moshe (Inventor)

1989-01-01

A network of microprocessors, or nodes, are interconnected in an n-dimensional cube having bidirectional communication links along the edges of the n-dimensional cube. Each node's processor network includes an I/O subprocessor dedicated to controlling communication of message packets along a bidirectional communication link with each end thereof terminating at an I/O controlled transceiver. Transmit data lines are directly connected from a local FIFO through each node's communication link transceiver. Status and control signals from the neighboring nodes are delivered over supervisory lines to inform the local node that the neighbor node's FIFO is empty and the bidirectional link between the two nodes is idle for data communication. A clocking line between neighbors, clocks a message into an empty FIFO at a neighbor's node and vica versa. Either neighbor may acquire control over the bidirectional communication link at any time, and thus each node has circuitry for checking whether or not the communication link is busy or idle, and whether or not the receive FIFO is empty. Likewise, each node can empty its own FIFO and in turn deliver a status signal to a neighboring node indicating that the local FIFO is empty. The system includes features of automatic message rerouting, block message transfer and automatic parity checking and generation.

Chrestenson transform FPGA embedded factorizations.

PubMed

Corinthios, Michael J

2016-01-01

Chrestenson generalized Walsh transform factorizations for parallel processing imbedded implementations on field programmable gate arrays are presented. This general base transform, sometimes referred to as the Discrete Chrestenson transform, has received special attention in recent years. In fact, the Discrete Fourier transform and Walsh-Hadamard transform are but special cases of the Chrestenson generalized Walsh transform. Rotations of a base-p hypercube, where p is an arbitrary integer, are shown to produce dynamic contention-free memory allocation, in processor architecture. The approach is illustrated by factorizations involving the processing of matrices of the transform which are function of four variables. Parallel operations are implemented matrix multiplications. Each matrix, of dimension N × N, where N = p (n) , n integer, has a structure that depends on a variable parameter k that denotes the iteration number in the factorization process. The level of parallelism, in the form of M = p (m) processors can be chosen arbitrarily by varying m between zero to its maximum value of n - 1. The result is an equation describing the generalised parallelism factorization as a function of the four variables n, p, k and m. Applications of the approach are shown in relation to configuring field programmable gate arrays for digital signal processing applications.

D → π and D → K semileptonic form factors with Nf = 2 + 1 + 1 twisted mass fermions

NASA Astrophysics Data System (ADS)

Lubicz, Vittorio; Riggio, Lorenzo; Salerno, Giorgio; Simula, Silvano; Tarantino, Cecilia

2018-03-01

We present a lattice determination of the vector and scalar form factors of the D → π(K)lv semileptonic decays, which are relevant for the extraction of the CKM matrix elements |Vcd| and |Vcs| from experimental data. Our analysis is based on the gauge configurations produced by the European Twisted Mass Collaboration with Nf = 2 + 1 +1 flavors of dynamical quarks. We simulated at three different values of the lattice spacing and with pion masses as small as 210 MeV. The matrix elements of both vector and scalar currents are determined for a plenty of kinematical conditions in which parent and child mesons are either moving or at rest. Lorentz symmetry breaking due to hypercubic effects is clearly observed in the data and included in the decomposition of the current matrix elements in terms of additional form factors. After the extrapolations to the physical pion mass and to the continuum limit the vector and scalar form factors are determined in the whole kinematical region from q2 = 0 up to qmax2 = (MD - Mπ(K))2 accessible in the experiments, obtaining a good overall agreement with experiments, except in the region at high values of q2 where some deviations are visible.

Compact Hyperspectral Imaging System (cosi) for Small Remotely Piloted Aircraft Systems (rpas) - System Overview and First Performance Evaluation Results

NASA Astrophysics Data System (ADS)

Sima, A. A.; Baeck, P.; Nuyts, D.; Delalieux, S.; Livens, S.; Blommaert, J.; Delauré, B.; Boonen, M.

2016-06-01

This paper gives an overview of the new COmpact hyperSpectral Imaging (COSI) system recently developed at the Flemish Institute for Technological Research (VITO, Belgium) and suitable for remotely piloted aircraft systems. A hyperspectral dataset captured from a multirotor platform over a strawberry field is presented and explored in order to assess spectral bands co-registration quality. Thanks to application of line based interference filters deposited directly on the detector wafer the COSI camera is compact and lightweight (total mass of 500g), and captures 72 narrow (FWHM: 5nm to 10 nm) bands in the spectral range of 600-900 nm. Covering the region of red edge (680 nm to 730 nm) allows for deriving plant chlorophyll content, biomass and hydric status indicators, making the camera suitable for agriculture purposes. Additionally to the orthorectified hypercube digital terrain model can be derived enabling various analyses requiring object height, e.g. plant height in vegetation growth monitoring. Geometric data quality assessment proves that the COSI camera and the dedicated data processing chain are capable to deliver very high resolution data (centimetre level) where spectral information can be correctly derived. Obtained results are comparable or better than results reported in similar studies for an alternative system based on the Fabry-Pérot interferometer.