On Two-Dimensional ARMA Models for Image Analysis.
1980-03-24
2-D ARMA models for image analysis . Particular emphasis is placed on restoration of noisy images using 2-D ARMA models. Computer results are...is concluded that the models are very effective linear models for image analysis . (Author)
The application of time series models to cloud field morphology analysis
NASA Technical Reports Server (NTRS)
Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.
1987-01-01
A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.
Bildirici, Melike; Ersin, Özgür
2014-01-01
The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications.
Bildirici, Melike; Ersin, Özgür
2014-01-01
The study has two aims. The first aim is to propose a family of nonlinear GARCH models that incorporate fractional integration and asymmetric power properties to MS-GARCH processes. The second purpose of the study is to augment the MS-GARCH type models with artificial neural networks to benefit from the universal approximation properties to achieve improved forecasting accuracy. Therefore, the proposed Markov-switching MS-ARMA-FIGARCH, APGARCH, and FIAPGARCH processes are further augmented with MLP, Recurrent NN, and Hybrid NN type neural networks. The MS-ARMA-GARCH family and MS-ARMA-GARCH-NN family are utilized for modeling the daily stock returns in an emerging market, the Istanbul Stock Index (ISE100). Forecast accuracy is evaluated in terms of MAE, MSE, and RMSE error criteria and Diebold-Mariano equal forecast accuracy tests. The results suggest that the fractionally integrated and asymmetric power counterparts of Gray's MS-GARCH model provided promising results, while the best results are obtained for their neural network based counterparts. Further, among the models analyzed, the models based on the Hybrid-MLP and Recurrent-NN, the MS-ARMA-FIAPGARCH-HybridMLP, and MS-ARMA-FIAPGARCH-RNN provided the best forecast performances over the baseline single regime GARCH models and further, over the Gray's MS-GARCH model. Therefore, the models are promising for various economic applications. PMID:24977200
Huang, Lei
2015-01-01
To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409
Nonlinear ARMA models for the D(st) index and their physical interpretation
NASA Technical Reports Server (NTRS)
Vassiliadis, D.; Klimas, A. J.; Baker, D. N.
1996-01-01
Time series models successfully reproduce or predict geomagnetic activity indices from solar wind parameters. A method is presented that converts a type of nonlinear filter, the nonlinear Autoregressive Moving Average (ARMA) model to the nonlinear damped oscillator physical model. The oscillator parameters, the growth and decay, the oscillation frequencies and the coupling strength to the input are derived from the filter coefficients. Mathematical methods are derived to obtain unique and consistent filter coefficients while keeping the prediction error low. These methods are applied to an oscillator model for the Dst geomagnetic index driven by the solar wind input. A data set is examined in two ways: the model parameters are calculated as averages over short time intervals, and a nonlinear ARMA model is calculated and the model parameters are derived as a function of the phase space.
Two-stage damage diagnosis based on the distance between ARMA models and pre-whitening filters
NASA Astrophysics Data System (ADS)
Zheng, H.; Mita, A.
2007-10-01
This paper presents a two-stage damage diagnosis strategy for damage detection and localization. Auto-regressive moving-average (ARMA) models are fitted to time series of vibration signals recorded by sensors. In the first stage, a novel damage indicator, which is defined as the distance between ARMA models, is applied to damage detection. This stage can determine the existence of damage in the structure. Such an algorithm uses output only and does not require operator intervention. Therefore it can be embedded in the sensor board of a monitoring network. In the second stage, a pre-whitening filter is used to minimize the cross-correlation of multiple excitations. With this technique, the damage indicator can further identify the damage location and severity when the damage has been detected in the first stage. The proposed methodology is tested using simulation and experimental data. The analysis results clearly illustrate the feasibility of the proposed two-stage damage diagnosis methodology.
NASA Astrophysics Data System (ADS)
Guo, A.; Wang, Y.
2017-12-01
Investigating variability in dependence structures of hydrological processes is of critical importance for developing an understanding of mechanisms of hydrological cycles in changing environments. In focusing on this topic, present work involves the following: (1) identifying and eliminating serial correlation and conditional heteroscedasticity in monthly streamflow (Q), precipitation (P) and potential evapotranspiration (PE) series using the ARMA-GARCH model (ARMA: autoregressive moving average; GARCH: generalized autoregressive conditional heteroscedasticity); (2) describing dependence structures of hydrological processes using partial copula coupled with the ARMA-GARCH model and identifying their variability via copula-based likelihood-ratio test method; and (3) determining conditional probability of annual Q under different climate scenarios on account of above results. This framework enables us to depict hydrological variables in the presence of conditional heteroscedasticity and to examine dependence structures of hydrological processes while excluding the influence of covariates by using partial copula-based ARMA-GARCH model. Eight major catchments across the Loess Plateau (LP) are used as study regions. Results indicate that (1) The occurrence of change points in dependence structures of Q and P (PE) varies across the LP. Change points of P-PE dependence structures in all regions almost fully correspond to the initiation of global warming, i.e., the early 1980s. (3) Conditional probabilities of annual Q under various P and PE scenarios are estimated from the 3-dimensional joint distribution of (Q, P and PE) based on the above change points. These findings shed light on mechanisms of the hydrological cycle and can guide water supply planning and management, particularly in changing environments.
Rasch measurement: the Arm Activity measure (ArmA) passive function sub-scale.
Ashford, Stephen; Siegert, Richard J; Alexandrescu, Roxana
2016-01-01
To evaluate the conformity of the Arm Activity measure (ArmA) passive function sub-scale to the Rasch model. A consecutive cohort of patients (n = 92) undergoing rehabilitation, including upper limb rehabilitation and spasticity management, at two specialist rehabilitation units were included. Rasch analysis was used to examine scaling and conformity to the model. Responses were analysed using Rasch unidimensional measurement models (RUMM 2030). The following aspects were considered: overall model and individual item fit statistics and fit residuals, internal reliability, item response threshold ordering, item bias, local dependency and unidimensionality. ArmA contains both active and passive function sub-scales, but in this analysis only the passive function sub-scale was considered. Four of the seven items in the ArmA passive function sub-scale initially had disordered thresholds. These items were rescored to four response options, which resulted in ordered thresholds for all items. Once the items with disordered thresholds had been rescored, item bias was not identified for age, global disability level or diagnosis, but with a small difference in difficulty between males and females for one item of the scale. Local dependency was not observed and the unidimensionality of the sub-scale was supported and good fit to the Rasch model was identified. The person separation index (PSI) was 0.95 indicating that the scale is able to reliably differentiate at least two groups of patients. The ArmA passive function sub-scale was shown in this evaluation to conform to the Rasch model once disordered thresholds had been addressed. Using the logit scores produced by the Rasch model it was possible to convert this back to the original scale range. Implications for Rehabilitation The ArmA passive function sub-scale was shown, in this evaluation, to conform to the Rasch model once disordered thresholds had been addressed and therefore to be a clinically applicable and potentially useful hierarchical measure. Using Rasch logit scores it has be possible to convert back to the original ordinal scale range and provide an indication of real change to enable evaluation of clinical outcome of importance to patients and clinicians.
Fitting ARMA Time Series by Structural Equation Models.
ERIC Educational Resources Information Center
van Buuren, Stef
1997-01-01
This paper outlines how the stationary ARMA (p,q) model (G. Box and G. Jenkins, 1976) can be specified as a structural equation model. Maximum likelihood estimates for the parameters in the ARMA model can be obtained by software for fitting structural equation models. The method is applied to three problem types. (SLD)
NASA Astrophysics Data System (ADS)
Luo, Xiaoguang; Mayer, Michael; Heck, Bernhard
2010-05-01
One essential deficiency of the stochastic model used in many GNSS (Global Navigation Satellite Systems) software products consists in neglecting temporal correlation of GNSS observations. Analysing appropriately detrended time series of observation residuals resulting from GPS (Global Positioning System) data processing, the temporal correlation behaviour of GPS observations can be sufficiently described by means of so-called autoregressive moving average (ARMA) processes. Using the toolbox ARMASA which is available free of charge in MATLAB® Central (open exchange platform for the MATLAB® and SIMULINK® user community), a well-fitting time series model can be identified automatically in three steps. Firstly, AR, MA, and ARMA models are computed up to some user-specified maximum order. Subsequently, for each model type, the best-fitting model is selected using the combined (for AR processes) resp. generalised (for MA and ARMA processes) information criterion. The final model identification among the best-fitting AR, MA, and ARMA models is performed based on the minimum prediction error characterising the discrepancies between the given data and the fitted model. The ARMA coefficients are computed using Burg's maximum entropy algorithm (for AR processes), Durbin's first (for MA processes) and second (for ARMA processes) methods, respectively. This paper verifies the performance of the automated ARMA identification using the toolbox ARMASA. For this purpose, a representative data base is generated by means of ARMA simulation with respect to sample size, correlation level, and model complexity. The model error defined as a transform of the prediction error is used as measure for the deviation between the true and the estimated model. The results of the study show that the recognition rates of underlying true processes increase with increasing sample sizes and decrease with rising model complexity. Considering large sample sizes, the true underlying processes can be correctly recognised for nearly 80% of the analysed data sets. Additionally, the model errors of first-order AR resp. MA processes converge clearly more rapidly to the corresponding asymptotical values than those of high-order ARMA processes.
Linear and nonlinear ARMA model parameter estimation using an artificial neural network
NASA Technical Reports Server (NTRS)
Chon, K. H.; Cohen, R. J.
1997-01-01
This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.
Statistical models and time series forecasting of sulfur dioxide: a case study Tehran.
Hassanzadeh, S; Hosseinibalam, F; Alizadeh, R
2009-08-01
This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.
On the Nature of SEM Estimates of ARMA Parameters.
ERIC Educational Resources Information Center
Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.
2002-01-01
Reexamined the nature of structural equation modeling (SEM) estimates of autoregressive moving average (ARMA) models, replicated the simulation experiments of P. Molenaar, and examined the behavior of the log-likelihood ratio test. Simulation studies indicate that estimates of ARMA parameters observed with SEM software are identical to those…
NASA Astrophysics Data System (ADS)
Uilhoorn, F. E.
2016-10-01
In this article, the stochastic modelling approach proposed by Box and Jenkins is treated as a mixed-integer nonlinear programming (MINLP) problem solved with a mesh adaptive direct search and a real-coded genetic class of algorithms. The aim is to estimate the real-valued parameters and non-negative integer, correlated structure of stationary autoregressive moving average (ARMA) processes. The maximum likelihood function of the stationary ARMA process is embedded in Akaike's information criterion and the Bayesian information criterion, whereas the estimation procedure is based on Kalman filter recursions. The constraints imposed on the objective function enforce stability and invertibility. The best ARMA model is regarded as the global minimum of the non-convex MINLP problem. The robustness and computational performance of the MINLP solvers are compared with brute-force enumeration. Numerical experiments are done for existing time series and one new data set.
Comparison between volatility return intervals of the S&P 500 index and two common models
NASA Astrophysics Data System (ADS)
Vodenska-Chitkushev, I.; Wang, F. Z.; Weber, P.; Yamasaki, K.; Havlin, S.; Stanley, H. E.
2008-01-01
We analyze the S&P 500 index data for the 13-year period, from January 1, 1984 to December 31, 1996, with one data point every 10 min. For this database, we study the distribution and clustering of volatility return intervals, which are defined as the time intervals between successive volatilities above a certain threshold q. We find that the long memory in the volatility leads to a clustering of above-median as well as below-median return intervals. In addition, it turns out that the short return intervals form larger clusters compared to the long return intervals. When comparing the empirical results to the ARMA-FIGARCH and fBm models for volatility, we find that the fBm model predicts scaling better than the ARMA-FIGARCH model, which is consistent with the argument that both ARMA-FIGARCH and fBm capture the long-term dependence in return intervals to a certain extent, but only fBm accounts for the scaling. We perform the Student's t-test to compare the empirical data with the shuffled records, ARMA-FIGARCH and fBm. We analyze separately the clusters of above-median return intervals and the clusters of below-median return intervals for different thresholds q. We find that the empirical data are statistically different from the shuffled data for all thresholds q. Our results also suggest that the ARMA-FIGARCH model is statistically different from the S&P 500 for intermediate q for both above-median and below-median clusters, while fBm is statistically different from S&P 500 for small and large q for above-median clusters and for small q for below-median clusters. Neither model can fully explain the entire regime of q studied.
NASA Astrophysics Data System (ADS)
Zielinski, Jerzy S.
The dramatic increase in number and volume of digital images produced in medical diagnostics, and the escalating demand for rapid access to these relevant medical data, along with the need for interpretation and retrieval has become of paramount importance to a modern healthcare system. Therefore, there is an ever growing need for processed, interpreted and saved images of various types. Due to the high cost and unreliability of human-dependent image analysis, it is necessary to develop an automated method for feature extraction, using sophisticated mathematical algorithms and reasoning. This work is focused on digital image signal processing of biological and biomedical data in one- two- and three-dimensional space. Methods and algorithms presented in this work were used to acquire data from genomic sequences, breast cancer, and biofilm images. One-dimensional analysis was applied to DNA sequences which were presented as a non-stationary sequence and modeled by a time-dependent autoregressive moving average (TD-ARMA) model. Two-dimensional analyses used 2D-ARMA model and applied it to detect breast cancer from x-ray mammograms or ultrasound images. Three-dimensional detection and classification techniques were applied to biofilm images acquired using confocal laser scanning microscopy. Modern medical images are geometrically arranged arrays of data. The broadening scope of imaging as a way to organize our observations of the biophysical world has led to a dramatic increase in our ability to apply new processing techniques and to combine multiple channels of data into sophisticated and complex mathematical models of physiological function and dysfunction. With explosion of the amount of data produced in a field of biomedicine, it is crucial to be able to construct accurate mathematical models of the data at hand. Two main purposes of signal modeling are: data size conservation and parameter extraction. Specifically, in biomedical imaging we have four key problems that were addressed in this work: (i) registration, i.e. automated methods of data acquisition and the ability to align multiple data sets with each other; (ii) visualization and reconstruction, i.e. the environment in which registered data sets can be displayed on a plane or in multidimensional space; (iii) segmentation, i.e. automated and semi-automated methods to create models of relevant anatomy from images; (iv) simulation and prediction, i.e. techniques that can be used to simulate growth end evolution of researched phenomenon. Mathematical models can not only be used to verify experimental findings, but also to make qualitative and quantitative predictions, that might serve as guidelines for the future development of technology and/or treatment.
Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M
2015-10-01
To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Liang, Zhang; Yanqing, Hou; Jie, Wu
2016-12-01
The multi-antenna synchronized receiver (using a common clock) is widely applied in GNSS-based attitude determination (AD) or terrain deformations monitoring, and many other applications, since the high-accuracy single-differenced carrier phase can be used to improve the positioning or AD accuracy. Thus, the line bias (LB) parameter (fractional bias isolating) should be calibrated in the single-differenced phase equations. In the past decades, all researchers estimated the LB as a constant parameter in advance and compensated it in real time. However, the constant LB assumption is inappropriate in practical applications because of the physical length and permittivity changes of the cables, caused by the environmental temperature variation and the instability of receiver-self inner circuit transmitting delay. Considering the LB drift (or colored LB) in practical circumstances, this paper initiates a real-time estimator using auto regressive moving average-based (ARMA) prediction/whitening filter model or Moving average-based (MA) constant calibration model. In the ARMA-based filter model, four cases namely AR(1), ARMA(1, 1), AR(2) and ARMA(2, 1) are applied for the LB prediction. The real-time relative positioning model using the ARMA-based predicting LB is derived and it is theoretically proved that the positioning accuracy is better than the traditional double difference carrier phase (DDCP) model. The drifting LB is defined with a phase temperature changing rate integral function, which is a random walk process if the phase temperature changing rate is white noise, and is validated by the analysis of the AR model coefficient. The auto covariance function shows that the LB is indeed varying in time and estimating it as a constant is not safe, which is also demonstrated by the analysis on LB variation of each visible satellite during a zero and short baseline BDS/GPS experiment. Compared to the DDCP approach, in the zero-baseline experiment, the LB constant calibration (LBCC) and MA approaches improved the positioning accuracy of the vertical component, while slightly degrading the accuracy of the horizontal components. The ARMA(1, 0) model, however, improved the positioning accuracy of all three components, with 40 and 50 % improvement of the vertical component for BDS and GPS, respectively. In the short baseline experiment, compared to the DDCP approach, the LBCC approach yielded bad positioning solutions and degraded the AD accuracy; both MA and ARMA-based filter approaches improved the AD accuracy. Moreover, the ARMA(1, 0) and ARMA(1, 1) models have relatively better performance, improving to 55 % and 48 % the elevation angle in ARMA(1, 1) and MA model for GPS, respectively. Furthermore, the drifting LB variation is found to be continuous and slowly cumulative; the variation magnitudes in the unit of length are almost identical on different frequency carrier phases, so the LB variation does not show obvious correlation between different frequencies. Consequently, the wide-lane LB in the unit of cycle is very stable, while the narrow-lane LB varies largely in time. This reasoning probably also explains the phenomenon that the wide-lane LB originating in the satellites is stable, while the narrow-lane LB varies. The results of ARMA-based filters are better than the MA model, which probably implies that the modeling for drifting LB can further improve the precise point positioning accuracy.
An efficient approach to ARMA modeling of biological systems with multiple inputs and delays
NASA Technical Reports Server (NTRS)
Perrott, M. H.; Cohen, R. J.
1996-01-01
This paper presents a new approach to AutoRegressive Moving Average (ARMA or ARX) modeling which automatically seeks the best model order to represent investigated linear, time invariant systems using their input/output data. The algorithm seeks the ARMA parameterization which accounts for variability in the output of the system due to input activity and contains the fewest number of parameters required to do so. The unique characteristics of the proposed system identification algorithm are its simplicity and efficiency in handling systems with delays and multiple inputs. We present results of applying the algorithm to simulated data and experimental biological data In addition, a technique for assessing the error associated with the impulse responses calculated from estimated ARMA parameterizations is presented. The mapping from ARMA coefficients to impulse response estimates is nonlinear, which complicates any effort to construct confidence bounds for the obtained impulse responses. Here a method for obtaining a linearization of this mapping is derived, which leads to a simple procedure to approximate the confidence bounds.
Nonparametric Transfer Function Models
Liu, Jun M.; Chen, Rong; Yao, Qiwei
2009-01-01
In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between ‘input’ and ‘output’ time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modeling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example. PMID:20628584
Research on light rail electric load forecasting based on ARMA model
NASA Astrophysics Data System (ADS)
Huang, Yifan
2018-04-01
The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.
NASA Technical Reports Server (NTRS)
Bartels, Robert E.
2012-01-01
This paper presents the implementation of gust modeling capability in the CFD code FUN3D. The gust capability is verified by computing the response of an airfoil to a sharp edged gust. This result is compared with the theoretical result. The present simulations will be compared with other CFD gust simulations. This paper also serves as a users manual for FUN3D gust analyses using a variety of gust profiles. Finally, the development of an Auto-Regressive Moving-Average (ARMA) reduced order gust model using a gust with a Gaussian profile in the FUN3D code is presented. ARMA simulated results of a sequence of one-minus-cosine gusts is shown to compare well with the same gust profile computed with FUN3D. Proper Orthogonal Decomposition (POD) is combined with the ARMA modeling technique to predict the time varying pressure coefficient increment distribution due to a novel gust profile. The aeroelastic response of a pitch/plunge airfoil to a gust environment is computed with a reduced order model, and compared with a direct simulation of the system in the FUN3D code. The two results are found to agree very well.
Zhang, Hong; Zhang, Sheng; Wang, Ping; Qin, Yuzhe; Wang, Huifeng
2017-07-01
Particulate matter with aerodynamic diameter below 10 μm (PM 10 ) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM 10 concentrations. It was evaluated by experiments using a 10-year data set of daily PM 10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM 10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM 10 concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM 10 concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM 10 concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM 10 forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM 10 time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM 10 time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM 10 time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM 10 forecasting field.
GOBF-ARMA based model predictive control for an ideal reactive distillation column.
Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K
2015-11-01
This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. Copyright © 2015 Elsevier Inc. All rights reserved.
O'Leary, D D; Lin, D C; Hughson, R L
1999-09-01
The heart rate component of the arterial baroreflex gain (BRG) was determined with auto-regressive moving-average (ARMA) analysis during each of spontaneous (SB) and random breathing (RB) protocols. Ten healthy subjects completed each breathing pattern on two different days in each of two different body positions, supine (SUP) and head-up tilt (HUT). The R-R interval, systolic arterial pressure (SAP) and instantaneous lung volume were recorded continuously. BRG was estimated from the ARMA impulse response relationship of R-R interval to SAP and from the spontaneous sequence method. The results indicated that both the ARMA and spontaneous sequence methods were reproducible (r = 0.76 and r = 0.85, respectively). As expected, BRG was significantly less in the HUT compared to SUP position for both ARMA (mean +/- SEM; 3.5 +/- 0.3 versus 11.2 +/- 1.4 ms mmHg-1; P < 0.01) and spontaneous sequence analysis (10.3 +/- 0.8 versus 31.5 +/- 2.3 ms mmHg-1; P < 0.001). However, no significant difference was found between BRG during RB and SB protocols for either ARMA (7.9 +/- 1.4 versus 6.7 +/- 0.8 ms mmHg-1; P = 0.27) or spontaneous sequence methods (21.8 +/- 2.7 versus 20.0 +/- 2.1 ms mmHg-1; P = 0.24). BRG was correlated during RB and SB protocols (r = 0.80; P < 0.0001). ARMA and spontaneous BRG estimates were correlated (r = 0.79; P < 0.0001), with spontaneous sequence values being consistently larger (P < 0.0001). In conclusion, we have shown that ARMA-derived BRG values are reproducible and that they can be determined during SB conditions, making the ARMA method appropriate for use in a wider range of patients.
ERIC Educational Resources Information Center
Hamaker, Ellen L.; Dolan, Conor V.; Molenaar, Peter C. M.
2003-01-01
Demonstrated, through simulation, that stationary autoregressive moving average (ARMA) models may be fitted readily when T>N, using normal theory raw maximum likelihood structural equation modeling. Also provides some illustrations based on real data. (SLD)
NASA Astrophysics Data System (ADS)
Turki, Imen; Laignel, Benoit; Kakeh, Nabil; Chevalier, Laetitia; Costa, Stephane
2015-04-01
This research is carried out in the framework of the program Surface Water and Ocean Topography (SWOT) which is a partnership between NASA and CNES. Here, a new hybrid model is implemented for filling gaps and forecasting the hourly sea level variability by combining classical harmonic analyses to high statistical methods to reproduce the deterministic and stochastic processes, respectively. After simulating the mean trend sea level and astronomical tides, the nontidal residual surges are investigated using an autoregressive moving average (ARMA) methods by two ways: (1) applying a purely statistical approach and (2) introducing the SLP in ARMA as a main physical process driving the residual sea level. The new hybrid model is applied to the western Atlantic sea and the eastern English Channel. Using ARMA model and considering the SLP, results show that the hourly sea level observations of gauges with are well reproduced with a root mean square error (RMSE) ranging between 4.5 and 7 cm for 1 to 30 days of gaps and an explained variance more than 80 %. For larger gaps of months, the RMSE reaches 9 cm. The negative and the positive extreme values of sea levels are also well reproduced with a mean explained variance between 70 and 85 %. The statistical behavior of 1-year modeled residual components shows good agreements with observations. The frequency analysis using the discrete wavelet transform illustrate strong correlations between observed and modeled energy spectrum and the bands of variability. Accordingly, the proposed model presents a coherent, simple, and easy tool to estimate the total sea level at timescales from days to months. The ARMA model seems to be more promising for filling gaps and estimating the sea level at larger scales of years by introducing more physical processes driving its stochastic variability.
ARMA models for earthquake ground motions. Seismic safety margins research program
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chang, M. K.; Kwiatkowski, J. W.; Nau, R. F.
1981-02-01
Four major California earthquake records were analyzed by use of a class of discrete linear time-domain processes commonly referred to as ARMA (Autoregressive/Moving-Average) models. It was possible to analyze these different earthquakes, identify the order of the appropriate ARMA model(s), estimate parameters, and test the residuals generated by these models. It was also possible to show the connections, similarities, and differences between the traditional continuous models (with parameter estimates based on spectral analyses) and the discrete models with parameters estimated by various maximum-likelihood techniques applied to digitized acceleration data in the time domain. The methodology proposed is suitable for simulatingmore » earthquake ground motions in the time domain, and appears to be easily adapted to serve as inputs for nonlinear discrete time models of structural motions. 60 references, 19 figures, 9 tables.« less
Parameter estimation of an ARMA model for river flow forecasting using goal programming
NASA Astrophysics Data System (ADS)
Mohammadi, Kourosh; Eslami, H. R.; Kahawita, Rene
2006-11-01
SummaryRiver flow forecasting constitutes one of the most important applications in hydrology. Several methods have been developed for this purpose and one of the most famous techniques is the Auto regressive moving average (ARMA) model. In the research reported here, the goal was to minimize the error for a specific season of the year as well as for the complete series. Goal programming (GP) was used to estimate the ARMA model parameters. Shaloo Bridge station on the Karun River with 68 years of observed stream flow data was selected to evaluate the performance of the proposed method. The results when compared with the usual method of maximum likelihood estimation were favorable with respect to the new proposed algorithm.
Forecasting Instability Indicators in the Horn of Africa
2008-03-01
further than 2 (Makridakis, et al, 1983, 359). 2-32 Autoregressive Integrated Moving Average ( ARIMA ) Model . Similar to the ARMA model except for...stationary process. ARIMA models are described as ARIMA (p,d,q), where p is the order of the autoregressive process, d is the degree of the...differential process, and q is the order of the moving average process. The ARMA (1,1) model shown above is equivalent to an ARIMA (1,0,1) model . An ARIMA
Simultaneous Estimation of Electromechanical Modes and Forced Oscillations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Follum, Jim; Pierre, John W.; Martin, Russell
Over the past several years, great strides have been made in the effort to monitor the small-signal stability of power systems. These efforts focus on estimating electromechanical modes, which are a property of the system that dictate how generators in different parts of the system exchange energy. Though the algorithms designed for this task are powerful and important for reliable operation of the power system, they are susceptible to severe bias when forced oscillations are present in the system. Forced oscillations are fundamentally different from electromechanical oscillations in that they are the result of a rogue input to the system,more » rather than a property of the system itself. To address the presence of forced oscillations, the frequently used AutoRegressive Moving Average (ARMA) model is adapted to include sinusoidal inputs, resulting in the AutoRegressive Moving Average plus Sinusoid (ARMA+S) model. From this model, a new Two-Stage Least Squares algorithm is derived to incorporate the forced oscillations, thereby enabling the simultaneous estimation of the electromechanical modes and the amplitude and phase of the forced oscillations. The method is validated using simulated power system data as well as data obtained from the western North American power system (wNAPS) and Eastern Interconnection (EI).« less
Predicting long-term catchment nutrient export: the use of nonlinear time series models
NASA Astrophysics Data System (ADS)
Valent, Peter; Howden, Nicholas J. K.; Szolgay, Jan; Komornikova, Magda
2010-05-01
After the Second World War the nitrate concentrations in European water bodies changed significantly as the result of increased nitrogen fertilizer use and changes in land use. However, in the last decades, as a consequence of the implementation of nitrate-reducing measures in Europe, the nitrate concentrations in water bodies slowly decrease. This causes that the mean and variance of the observed time series also changes with time (nonstationarity and heteroscedascity). In order to detect changes and properly describe the behaviour of such time series by time series analysis, linear models (such as autoregressive (AR), moving average (MA) and autoregressive moving average models (ARMA)), are no more suitable. Time series with sudden changes in statistical characteristics can cause various problems in the calibration of traditional water quality models and thus give biased predictions. Proper statistical analysis of these non-stationary and heteroscedastic time series with the aim of detecting and subsequently explaining the variations in their statistical characteristics requires the use of nonlinear time series models. This information can be then used to improve the model building and calibration of conceptual water quality model or to select right calibration periods in order to produce reliable predictions. The objective of this contribution is to analyze two long time series of nitrate concentrations of the rivers Ouse and Stour with advanced nonlinear statistical modelling techniques and compare their performance with traditional linear models of the ARMA class in order to identify changes in the time series characteristics. The time series were analysed with nonlinear models with multiple regimes represented by self-exciting threshold autoregressive (SETAR) and Markov-switching models (MSW). The analysis showed that, based on the value of residual sum of squares (RSS) in both datasets, SETAR and MSW models described the time-series better than models of the ARMA class. In most cases the relative improvement of SETAR models against AR models of first order was low ranging between 1% and 4% with the exception of the three-regime model for the River Stour time-series where the improvement was 48.9%. In comparison, the relative improvement of MSW models was between 44.6% and 52.5 for two-regime and from 60.4% to 75% for three-regime models. However, the visual assessment of models plotted against original datasets showed that despite a high value of RSS, some ARMA models could describe the analyzed time-series better than AR, MA and SETAR models with lower values of RSS. In both datasets MSW models provided a very good visual fit describing most of the extreme values.
NASA Astrophysics Data System (ADS)
Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh
2016-08-01
We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.
Flood Nowcasting With Linear Catchment Models, Radar and Kalman Filters
NASA Astrophysics Data System (ADS)
Pegram, Geoff; Sinclair, Scott
A pilot study using real time rainfall data as input to a parsimonious linear distributed flood forecasting model is presented. The aim of the study is to deliver an operational system capable of producing flood forecasts, in real time, for the Mgeni and Mlazi catchments near the city of Durban in South Africa. The forecasts can be made at time steps which are of the order of a fraction of the catchment response time. To this end, the model is formulated in Finite Difference form in an equation similar to an Auto Regressive Moving Average (ARMA) model; it is this formulation which provides the required computational efficiency. The ARMA equation is a discretely coincident form of the State-Space equations that govern the response of an arrangement of linear reservoirs. This results in a functional relationship between the reservoir response con- stants and the ARMA coefficients, which guarantees stationarity of the ARMA model. Input to the model is a combined "Best Estimate" spatial rainfall field, derived from a combination of weather RADAR and Satellite rainfield estimates with point rain- fall given by a network of telemetering raingauges. Several strategies are employed to overcome the uncertainties associated with forecasting. Principle among these are the use of optimal (double Kalman) filtering techniques to update the model states and parameters in response to current streamflow observations and the application of short term forecasting techniques to provide future estimates of the rainfield as input to the model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Faranda, Davide, E-mail: davide.faranda@cea.fr; Dubrulle, Bérengère; Daviaud, François
We introduce a novel way to extract information from turbulent datasets by applying an Auto Regressive Moving Average (ARMA) statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations and links the behavior of the recorded time series to a discrete version of a stochastic differential equation which is able to describe the correlation structure in the dataset. We introduce a new index Υ that measures the difference between the resulting analysis and the Obukhov model of turbulence, the simplest stochastic model reproducing both Richardson law and the Kolmogorov spectrum. We test themore » method on datasets measured in a von Kármán swirling flow experiment. We found that the ARMA analysis is well correlated with spatial structures of the flow, and can discriminate between two different flows with comparable mean velocities, obtained by changing the forcing. Moreover, we show that the Υ is highest in regions where shear layer vortices are present, thereby establishing a link between deviations from the Kolmogorov model and coherent structures. These deviations are consistent with the ones observed by computing the Hurst exponents for the same time series. We show that some salient features of the analysis are preserved when considering global instead of local observables. Finally, we analyze flow configurations with multistability features where the ARMA technique is efficient in discriminating different stability branches of the system.« less
A statistical approach for generating synthetic tip stress data from limited CPT soundings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Basalams, M.K.
CPT tip stress data obtained from a Uranium mill tailings impoundment are treated as time series. A statistical class of models that was developed to model time series is explored to investigate its applicability in modeling the tip stress series. These models were developed by Box and Jenkins (1970) and are known as Autoregressive Moving Average (ARMA) models. This research demonstrates how to apply the ARMA models to tip stress series. Generation of synthetic tip stress series that preserve the main statistical characteristics of the measured series is also investigated. Multiple regression analysis is used to model the regional variationmore » of the ARMA model parameters as well as the regional variation of the mean and the standard deviation of the measured tip stress series. The reliability of the generated series is investigated from a geotechnical point of view as well as from a statistical point of view. Estimation of the total settlement using the measured and the generated series subjected to the same loading condition are performed. The variation of friction angle with depth of the impoundment materials is also investigated. This research shows that these series can be modeled by the Box and Jenkins ARMA models. A third degree Autoregressive model AR(3) is selected to represent these series. A theoretical double exponential density function is fitted to the AR(3) model residuals. Synthetic tip stress series are generated at nearby locations. The generated series are shown to be reliable in estimating the total settlement and the friction angle variation with depth for this particular site.« less
A vertical handoff decision algorithm based on ARMA prediction model
NASA Astrophysics Data System (ADS)
Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan
2012-01-01
With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.
Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation.
Monserud, R A; Marshall, J D
2001-09-01
Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.
NASA Astrophysics Data System (ADS)
Sivavaraprasad, G.; Venkata Ratnam, D.
2017-07-01
Ionospheric delay is one of the major atmospheric effects on the performance of satellite-based radio navigation systems. It limits the accuracy and availability of Global Positioning System (GPS) measurements, related to critical societal and safety applications. The temporal and spatial gradients of ionospheric total electron content (TEC) are driven by several unknown priori geophysical conditions and solar-terrestrial phenomena. Thereby, the prediction of ionospheric delay is challenging especially over Indian sub-continent. Therefore, an appropriate short/long-term ionospheric delay forecasting model is necessary. Hence, the intent of this paper is to forecast ionospheric delays by considering day to day, monthly and seasonal ionospheric TEC variations. GPS-TEC data (January 2013-December 2013) is extracted from a multi frequency GPS receiver established at K L University, Vaddeswaram, Guntur station (geographic: 16.37°N, 80.37°E; geomagnetic: 7.44°N, 153.75°E), India. An evaluation, in terms of forecasting capabilities, of three ionospheric time delay models - an Auto Regressive Moving Average (ARMA) model, Auto Regressive Integrated Moving Average (ARIMA) model, and a Holt-Winter's model is presented. The performances of these models are evaluated through error measurement analysis during both geomagnetic quiet and disturbed days. It is found that, ARMA model is effectively forecasting the ionospheric delay with an accuracy of 82-94%, which is 10% more superior to ARIMA and Holt-Winter's models. Moreover, the modeled VTEC derived from International Reference Ionosphere, IRI (IRI-2012) model and new global TEC model, Neustrelitz TEC Model (NTCM-GL) have compared with forecasted VTEC values of ARMA, ARIMA and Holt-Winter's models during geomagnetic quiet days. The forecast results are indicating that ARMA model would be useful to set up an early warning system for ionospheric disturbances at low latitude regions.
Beyond Rating Curves: Time Series Models for in-Stream Turbidity Prediction
NASA Astrophysics Data System (ADS)
Wang, L.; Mukundan, R.; Zion, M.; Pierson, D. C.
2012-12-01
The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies over 1 billion gallons of water per day to more than 9 million customers. DEP's "West of Hudson" reservoirs located in the Catskill Mountains are unfiltered per a renewable filtration avoidance determination granted by the EPA. While water quality is usually pristine, high volume storm events occasionally cause the reservoirs to become highly turbid. A logical strategy for turbidity control is to temporarily remove the turbid reservoirs from service. While effective in limiting delivery of turbid water and reducing the need for in-reservoir alum flocculation, this strategy runs the risk of negatively impacting water supply reliability. Thus, it is advantageous for DEP to understand how long a particular turbidity event will affect their system. In order to understand the duration, intensity and total load of a turbidity event, predictions of future in-stream turbidity values are important. Traditionally, turbidity predictions have been carried out by applying streamflow observations/forecasts to a flow-turbidity rating curve. However, predictions from rating curves are often inaccurate due to inter- and intra-event variability in flow-turbidity relationships. Predictions can be improved by applying an autoregressive moving average (ARMA) time series model in combination with a traditional rating curve. Since 2003, DEP and the Upstate Freshwater Institute have compiled a relatively consistent set of 15-minute turbidity observations at various locations on Esopus Creek above Ashokan Reservoir. Using daily averages of this data and streamflow observations at nearby USGS gauges, flow-turbidity rating curves were developed via linear regression. Time series analysis revealed that the linear regression residuals may be represented using an ARMA(1,2) process. Based on this information, flow-turbidity regressions with ARMA(1,2) errors were fit to the observations. Preliminary model validation exercises at a 30-day forecast horizon show that the ARMA error models generally improve the predictive skill of the linear regression rating curves. Skill seems to vary based on the ambient hydrologic conditions at the onset of the forecast. For example, ARMA error model forecasts issued before a high flow/turbidity event do not show significant improvements over the rating curve approach. However, ARMA error model forecasts issued during the "falling limb" of the hydrograph are significantly more accurate than rating curves for both single day and accumulated event predictions. In order to assist in reservoir operations decisions associated with turbidity events and general water supply reliability, DEP has initiated design of an Operations Support Tool (OST). OST integrates a reservoir operations model with 2D hydrodynamic water quality models and a database compiling near-real-time data sources and hydrologic forecasts. Currently, OST uses conventional flow-turbidity rating curves and hydrologic forecasts for predictive turbidity inputs. Given the improvements in predictive skill over traditional rating curves, the ARMA error models are currently being evaluated as an addition to DEP's Operations Support Tool.
AGN Variability: Probing Black Hole Accretion
NASA Astrophysics Data System (ADS)
Moreno, Jackeline; O'Brien, Jack; Vogeley, Michael S.; Richards, Gordon T.; Kasliwal, Vishal P.
2017-01-01
We combine the long temporal baseline of Sloan Digital Sky Survey (SDSS) for quasars in Stripe 82 with the high precision photometry of the Kepler/K2 Satellite to study the physics of optical variability in the accretion disk and supermassive black hole engine. We model the lightcurves directly as Continuous-time Auto Regressive Moving Average processes (C-ARMA) with the Kali analysis package (Kasliwal et al. 2016). These models are extremely robust to irregular sampling and can capture aperiodic variability structure on various timescales. We also estimate the power spectral density and structure function of both the model family and the data. A Green's function kernel may also be estimated for the resulting C-ARMA parameter fit, which may be interpreted as the response to driving impulses such as hotspots in the accretion disk. We also examine available spectra for our AGN sample to relate observed and modelled behavior to spectral properties. The objective of this work is twofold: to explore the proper physical interpretation of different families of C-ARMA models applied to AGN optical flux variability and to relate empirical characteristic timescales of our AGN sample to physical theory or to properties estimated from spectra or simulations like the disk viscosity and temperature. We find that AGN with strong variability features on timescales resolved by K2 are well modelled by a low order C-ARMA family while K2 lightcurves with weak amplitude variability are dominated by outliers and measurement errors which force higher order model fits. This work explores a novel approach to combining SDSS and K2 data sets and presents recovered characteristic timescales of AGN variability.
Kuhlmann, Levin; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J
2017-04-01
Tracking brain states with electrophysiological measurements often relies on short-term averages of extracted features and this may not adequately capture the variability of brain dynamics. The objective is to assess the hypotheses that this can be overcome by tracking distributions of linear models using anesthesia data, and that anesthetic brain state tracking performance of linear models is comparable to that of a high performing depth of anesthesia monitoring feature. Individuals' brain states are classified by comparing the distribution of linear (auto-regressive moving average-ARMA) model parameters estimated from electroencephalographic (EEG) data obtained with a sliding window to distributions of linear model parameters for each brain state. The method is applied to frontal EEG data from 15 subjects undergoing propofol anesthesia and classified by the observers assessment of alertness/sedation (OAA/S) scale. Classification of the OAA/S score was performed using distributions of either ARMA parameters or the benchmark feature, Higuchi fractal dimension. The highest average testing sensitivity of 59% (chance sensitivity: 17%) was found for ARMA (2,1) models and Higuchi fractal dimension achieved 52%, however, no statistical difference was observed. For the same ARMA case, there was no statistical difference if medians are used instead of distributions (sensitivity: 56%). The model-based distribution approach is not necessarily more effective than a median/short-term average approach, however, it performs well compared with a distribution approach based on a high performing anesthesia monitoring measure. These techniques hold potential for anesthesia monitoring and may be generally applicable for tracking brain states.
Numerical evidence of liquid crystalline mesophases of a lollipop shaped model in two dimensions
NASA Astrophysics Data System (ADS)
Pérez-Lemus, G. R.; Armas-Pérez, J. C.; Chapela, G. A.; Quintana-H., J.
2017-12-01
Small alterations in the molecular details may produce noticeable changes in the symmetry of the resulting phase behavior. It is possible to produce morphologies having different n-fold symmetries by manipulating molecular features such as chirality, polarity or anisotropy. In this paper, a two dimensional hard molecular model is introduced to study the formation of liquid crystalline phases in low dimensionality. The model is similar to that reported by Julio C. Armas-Pérez and Jacqueline Quintana-H., Phys. Rev. E 83, 051709 (2011). The main difference is the lack of chirality in the model proposed, although they share some characteristics like the geometrical polarity. Our model is called a lollipop model, because its shape is constructed by a rounded section attached to the end of a stick. Contrary to what happens in three dimensions where chiral nematogens produce interesting and complex phases such as blue phases, the lack of molecular chirality of our model generates a richer phase diagram compared to the chiral system. We show numerical and some geometrical evidences that the lack of laterality of the non chiral model seems to provide more routes of molecular self-assembly, producing triatic, a random cluster and possibly a tetratic phase behavior which were not presented in the previous work. We support our conclusions using results obtained from isobaric and isochoric Monte Carlo simulations. Properties as the n-fold order parameters such as the nematic, tetratic and triatic as well as their correlation functions were used to characterize the phases. We also provide the Fourier transform of equilibrium configurations to analyze the n-fold symmetry characteristic of each phase.
Neural net forecasting for geomagnetic activity
NASA Technical Reports Server (NTRS)
Hernandez, J. V.; Tajima, T.; Horton, W.
1993-01-01
We use neural nets to construct nonlinear models to forecast the AL index given solar wind and interplanetary magnetic field (IMF) data. We follow two approaches: (1) the state space reconstruction approach, which is a nonlinear generalization of autoregressive-moving average models (ARMA) and (2) the nonlinear filter approach, which reduces to a moving average model (MA) in the linear limit. The database used here is that of Bargatze et al. (1985).
Modeling Geodetic Processes with Levy α-Stable Distribution and FARIMA
NASA Astrophysics Data System (ADS)
Montillet, Jean-Philippe; Yu, Kegen
2015-04-01
Over the last years the scientific community has been using the auto regressive moving average (ARMA) model in the modeling of the noise in global positioning system (GPS) time series (daily solution). This work starts with the investigation of the limit of the ARMA model which is widely used in signal processing when the measurement noise is white. Since a typical GPS time series consists of geophysical signals (e.g., seasonal signal) and stochastic processes (e.g., coloured and white noise), the ARMA model may be inappropriate. Therefore, the application of the fractional auto-regressive integrated moving average (FARIMA) model is investigated. The simulation results using simulated time series as well as real GPS time series from a few selected stations around Australia show that the FARIMA model fits the time series better than other models when the coloured noise is larger than the white noise. The second fold of this work focuses on fitting the GPS time series with the family of Levy α-stable distributions. Using this distribution, a hypothesis test is developed to eliminate effectively coarse outliers from GPS time series, achieving better performance than using the rule of thumb of n standard deviations (with n chosen empirically).
Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng
This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA)more » models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.« less
Maximum likelihood estimation for periodic autoregressive moving average models
Vecchia, A.V.
1985-01-01
A useful class of models for seasonal time series that cannot be filtered or standardized to achieve second-order stationarity is that of periodic autoregressive moving average (PARMA) models, which are extensions of ARMA models that allow periodic (seasonal) parameters. An approximation to the exact likelihood for Gaussian PARMA processes is developed, and a straightforward algorithm for its maximization is presented. The algorithm is tested on several periodic ARMA(1, 1) models through simulation studies and is compared to moment estimation via the seasonal Yule-Walker equations. Applicability of the technique is demonstrated through an analysis of a seasonal stream-flow series from the Rio Caroni River in Venezuela.
A univariate model of river water nitrate time series
NASA Astrophysics Data System (ADS)
Worrall, F.; Burt, T. P.
1999-01-01
Four time series were taken from three catchments in the North and South of England. The sites chosen included two in predominantly agricultural catchments, one at the tidal limit and one downstream of a sewage treatment works. A time series model was constructed for each of these series as a means of decomposing the elements controlling river water nitrate concentrations and to assess whether this approach could provide a simple management tool for protecting water abstractions. Autoregressive (AR) modelling of the detrended and deseasoned time series showed a "memory effect". This memory effect expressed itself as an increase in the winter-summer difference in nitrate levels that was dependent upon the nitrate concentration 12 or 6 months previously. Autoregressive moving average (ARMA) modelling showed that one of the series contained seasonal, non-stationary elements that appeared as an increasing trend in the winter-summer difference. The ARMA model was used to predict nitrate levels and predictions were tested against data held back from the model construction process - predictions gave average percentage errors of less than 10%. Empirical modelling can therefore provide a simple, efficient method for constructing management models for downstream water abstraction.
NASA Astrophysics Data System (ADS)
Qian, Xiaoshan
2018-01-01
The traditional model of evaporation process parameters have continuity and cumulative characteristics of the prediction error larger issues, based on the basis of the process proposed an adaptive particle swarm neural network forecasting method parameters established on the autoregressive moving average (ARMA) error correction procedure compensated prediction model to predict the results of the neural network to improve prediction accuracy. Taking a alumina plant evaporation process to analyze production data validation, and compared with the traditional model, the new model prediction accuracy greatly improved, can be used to predict the dynamic process of evaporation of sodium aluminate solution components.
Multi-step-ahead crude oil price forecasting using a hybrid grey wave model
NASA Astrophysics Data System (ADS)
Chen, Yanhui; Zhang, Chuan; He, Kaijian; Zheng, Aibing
2018-07-01
Crude oil is crucial to the operation and economic well-being of the modern society. Huge changes of crude oil price always cause panics to the global economy. There are many factors influencing crude oil price. Crude oil price prediction is still a difficult research problem widely discussed among researchers. Based on the researches on Heterogeneous Market Hypothesis and the relationship between crude oil price and macroeconomic factors, exchange market, stock market, this paper proposes a hybrid grey wave forecasting model, which combines Random Walk (RW)/ARMA to forecast multi-step-ahead crude oil price. More specifically, we use grey wave forecasting model to model the periodical characteristics of crude oil price and ARMA/RW to simulate the daily random movements. The innovation also comes from using the information of the time series graph to forecast crude oil price, since grey wave forecasting is a graphical prediction method. The empirical results demonstrate that based on the daily data of crude oil price, the hybrid grey wave forecasting model performs well in 15- to 20-step-ahead prediction and it always dominates ARMA and Random Walk in correct direction prediction.
NASA Astrophysics Data System (ADS)
Ansari, Kutubuddin; Panda, Sampad Kumar; Althuwaynee, Omar F.; Corumluoglu, Ozsen
2017-09-01
The present study investigates the ionospheric Total Electron Content (TEC) variations in the lower mid-latitude Turkish region from the Turkish Permanent GNSS Network (TPGN) and International GNSS Services (IGS) observations during the year 2016. The corresponding vertical TEC (VTEC) predicted by Auto Regressive Moving Average (ARMA) and International Reference Ionosphere 2016 (IRI-2016) models are evaluated to realize their effectiveness over the region. The spatial, diurnal and seasonal behavior of VTEC and the relative VTEC variations are modeled with Ordinary Least Square Estimator (OLSE). The spatial behavior of modeled result during March equinox and June solstice indicates an inverse relationship of VTEC with the longitude across the region. On the other hand, the VTEC variation during September equinox and December solstice including March equinox and June solstice are decreasing with increase in latitude. The GNSS observed and modeled diurnal variation of the VTEC show that the VTEC slowly increases with dawn, attains a broader duration of peak around 09.00 to 12.00 UT, and thereafter decreases gradually reaching minimum around 21.00 UT. The seasonal variation of VTEC shows an annual mode, maxima in equinox and minima in solstice. The average value of VTEC during the June solstice is with slightly higher value than the March equinox though variations during the latter season is more. Moreover, the study shows minimum average value during December solstice compared to June solstice at all stations. The comparative analysis demonstrates the prediction errors by OLSE, ARMA and IRI remaining between 0.23 to 1.17%, 2.40 to 4.03% and 24.82 to 25.79% respectively. Also, the observed VTEC seasonal variation has good agreement with OLSE and ARMA models whereas IRI-VTEC often underestimated the observed value at each location. Hence, the deviations of IRI estimated VTEC compared to ARMA and OLSE models claim further improvements in IRI model over the Turkish region. Although IRI estimations are well accepted over the mid-latitudes but the performance over the lower mid-latitudes is not satisfactory and needs further improvement. The long-term TEC data from the TPGN network can be incorporated in the IRI under laying database with appropriate calibration for further improvement of estimation accuracy over the region.
Defense Applications of Signal Processing
1999-08-27
class of multiscale autoregressive moving average (MARMA) processes. These are generalisations of ARMA models in time series analysis , and they contain...including the two theoretical sinusoidal components. Analysis of the amplitude and frequency time series provided some novel insight into the real...communication channels, underwater acoustic signals, radar systems , economic time series and biomedical signals [7]. The alpha stable (aS) distribution has
46. View of Plaza de Armas taken through archway between ...
46. View of Plaza de Armas taken through archway between Plaza de Armas and Carmen Bastion, looking southwest - Castillo de San Felipe del Morro, Northwest end of San Juan, San Juan, San Juan Municipio, PR
Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches
NASA Astrophysics Data System (ADS)
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.
Spinal Ischemia in Thoracic Aortic Procedures: Impact of Radiculomedullary Artery Distribution.
Kari, Fabian A; Wittmann, Karin; Krause, Sonja; Saravi, Babak; Puttfarcken, Luisa; Förster, Katharina; Rylski, Bartosz; Maier, Sven; Göbel, Ulrich; Siepe, Matthias; Czerny, Martin; Beyersdorf, Friedhelm
2017-12-01
The aim of this study was to assess the influence of thoracic anterior radiculomedullary artery (tARMA) distribution on spinal cord perfusion in a thoracic aortic surgical model. Twenty-six pigs (34 ± 3 kg; study group, n = 20; sham group, n = 6) underwent ligation of the left subclavian artery and thoracic segmental arteries. End points were spinal cord perfusion pressure (SCPP), regional spinal cord blood flow (SCBF), and neurologic outcome with an observation time of 3 hours. tARMA distribution patterns tested for an effect on end points included (1) maximum distance between any 2 tARMAs within the treated aortic segment (0 or 1 segment = small-distance group; >1 segment = large-distance group) and (2) distance between the end of the treated aortic segment and the first distal tARMA (at the level of the distal simulated stent-graft end = group 0; gap of 1 or more segments = group ≥1). The number of tARMA ranged from 3 to 13 (mean, 8). In the large-distance group, SCBF dropped from 0.48 ± 0.16 mL/g/min to 0.3 ± 0.08 mL/g/min (p < 0.001). We observed no detectable SCBF drop in the small-distance group: 0.2 ± 0.05 mL/g/min at baseline to 0.23 ± 0.05 mL/g/min immediately after clamping (p = 0.147). SCBF increased from 0.201 ± 0.055 mL/g/min at baseline to 0.443 ± 0.051 mL/g/min at 3 hours postoperatively (p < 0.001) only in the small-distance group. We demonstrate experimental data showing that distribution patterns of tARMAs correlate with the degree of SCBF drop and insufficient reactive parenchymal hyperemia in aortic procedures. Individual ARMA distribution patterns along the treated aortic segment could help us predict the individual risk of spinal ischemia. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
Modeling methodology for MLS range navigation system errors using flight test data
NASA Technical Reports Server (NTRS)
Karmali, M. S.; Phatak, A. V.
1982-01-01
Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.
A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies
NASA Astrophysics Data System (ADS)
Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai
2010-05-01
Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.
Ghotaslou, Reza; Yeganeh Sefidan, Fatemeh; Akhi, Mohammad Taghi; Asgharzadeh, Mohammad; Mohammadzadeh Asl, Yalda
2017-10-01
Enzymatic inactivation is one of the most important mechanisms of resistance to aminoglycosides. The aim of this study was to investigate the prevalence of armA and diversity of the genes encoding aminoglycoside-modifying enzymes (AMEs) and their associations with resistance phenotypes in Enterobacteriaceae isolates. Three hundred and seven Enterobacteriaceae isolates were collected from five hospitals in northwest Iran. The disk diffusion method for amikacin, gentamicin, tobramycin, kanamycin, and streptomycin, as well as the minimum inhibitory concentration for amikacin, gentamicin, tobramycin, and kanamycin were done for susceptibility testing. Thirteen AME genes and armA methylase were screened using the PCR and sequencing assays. Two hundred and twenty (71.7%) of isolates were resistant to aminoglycosides and 155 (70.5%) of them were positive for aminoglycoside resistance genes. The most prevalent AME genes were ant(3″)-Ia and aph(3″)-Ib with the frequency 35.9% and 30.5%, respectively. Also, 21 (9.5%) of resistant isolates were positive for armA methylase gene. The prevalence of resistance to aminoglycoside is high and AME genes frequently are disseminated in Enterobacteriaceae isolates. There is an association between phenotypic resistance and the presence of some aminoglycoside genes.
NASA Astrophysics Data System (ADS)
Duangdai, Eakkapong; Likasiri, Chulin
2017-03-01
In this work, 4 models for predicting rainfall amounts are investigated and compared using Northern Thailand's seasonal rainfall data for 1973-2008. Two models, global temperature, forest area and seasonal rainfall (TFR) and modified TFR based on a system of differential equations, give the relationships between global temperature, Northern Thailand's forest cover and seasonal rainfalls in the region. The other two models studied are time series and Autoregressive Moving Average (ARMA) models. All models are validated using the k-fold cross validation method with the resulting errors being 0.971233, 0.740891, 2.376415 and 2.430891 for time series, ARMA, TFR and modified TFR models, respectively. Under Business as Usual (BaU) scenario, seasonal rainfalls in Northern Thailand are projected through the year 2020 using all 4 models. TFR and modified TFR models are also used to further analyze how global temperature rise and government reforestation policy affect seasonal rainfalls in the region. Rainfall projections obtained via the two models are also compared with those from the International Panel on Climate Change (IPCC) under IS92a scenario. Results obtained through a mathematical model for global temperature, forest area and seasonal rainfall show that the higher the forest cover, the less fluctuation there is between rainy-season and summer rainfalls. Moreover, growth in forest cover also correlates with an increase in summer rainfalls. An investigation into the relationship between main crop productions and rainfalls in dry and rainy seasons indicates that if the rainy-season rainfall is high, that year's main-crop rice production will decrease but the second-crop rice, maize, sugarcane and soybean productions will increase in the following year.
Techie Quaicoe, Michael; Twenefour, Frank B K; Baah, Emmanuel M; Nortey, Ezekiel N N
2015-01-01
This research article aimed at modeling the variations in the dollar/cedi exchange rate. It examines the applicability of a range of ARCH/GARCH specifications for modeling volatility of the series. The variants considered include the ARMA, GARCH, IGARCH, EGARCH and M-GARCH specifications. The results show that the series was non stationary which resulted from the presence of a unit root in it. The ARMA (1, 1) was found to be the most suitable model for the conditional mean. From the Box-Ljung test statistics x-squared of 1476.338 with p value 0.00217 for squared returns and 16.918 with 0.0153 p values for squared residuals, the null hypothesis of no ARCH effect was rejected at 5% significance level indicating the presence of an ARCH effect in the series. ARMA (1, 1) + GARCH (1, 1) which has all parameters significant was found to be the most suitable model for the conditional mean with conditional variance, thus showing adequacy in describing the conditional mean with variance of the return series at 5% significant level. A 24 months forecast for the mean actual exchange rates and mean returns from January, 2013 to December, 2014 made also showed that the fitted model is appropriate for the data and a depreciating trend of the cedi against the dollar for forecasted period respectively.
Yu, Fangyou; Wang, Liangxing; Pan, Jingye; Yao, Dan; Chen, Chan; Zhu, Tao; Lou, Qiang; Hu, Jian; Wu, Yang; Zhang, Xueqing; Chen, Zengqiang; Qu, Di
2009-05-01
16S rRNA methylase-mediated high-level resistance to aminoglycosides has been reported recently in clinical isolates of Gram-negative bacilli from several countries. Twenty-one (6.2%, 21/337) of 337 isolates of Klebsiella pneumoniae from a teaching hospital in Wenzhou, China, were positive for 16S rRNA methylase genes (3 for armA, 13 for rmtB, 5 for both armA and rmtB) and highly resistant to gentamicin, amikacin, and tobramycin (MICs, > or =256 microg/mL). Nineteen of 21 isolates harboring 16S rRNA methyalse genes were extended-spectrum beta-lactamase (ESBL) producers. The plasmids harboring 16S rRNA methylase genes from 14 of 21 donors were transferred into the recipients, Escherichia coli J53. The armA and the rmtB usually coexisted with ESBL genes in the same isolate in clinical isolates and cotransferred with ESBL genes on a self-transmissible conjugative plasmid to the recipients. Among 5 isolates harboring both armA and rmtB, the armA genes were located on the chromosomes, and the rmtB genes were located on the plasmids, as determined by Southern hybridization. The result of pulsed-field gel electrophoresis showed that horizontal gene transfer and clonal spread were responsible for the dissemination of the rmtB and the armA genes. 16S rRNA methylase-producing isolates of Klebsiella pneumoniae were commonly identified in the Chinese teaching hospital with coexistence of rmtB and armA genes in the same isolate.
ARMAS and NAIRAS Comparisons of Radiation at Aviation Altitudes
NASA Astrophysics Data System (ADS)
Bell, L. D.
2015-12-01
Space Environment Technologies and the Space Weather Center (SWC) at Utah State University are deploying and obtaining effective dose rate radiation data from dosimeters flown on research aircraft. This project is called Automated Radiation Measurements for Aerospace Safety (ARMAS). Through several dozen flights since 2013 the ARMAS project has successfully demonstrated the operation of a micro-dosimeter on commercial aviation altitude aircraft that captures the real-time radiation environment resulting from galactic cosmic rays (GCR's) and solar energetic particles (SEP's). Space weather effects upon the near Earth environment are to dynamic changes in the energy transfer process from the Sun's photons, particles, and fields. The coupling between the solar and galactic high-energy particles, and atmospheric regions can significantly affect human tissue and the aircrafts technology as a result of radiation exposure. We describe and compare the types of radiation we have been measuring with the NAIRAS global climatological model as it relates to human tissue susceptibility and as a source at different altitude regions.
NASA Astrophysics Data System (ADS)
Wang, Jin; Sun, Tao; Fu, Anmin; Xu, Hao; Wang, Xinjie
2018-05-01
Degradation in drylands is a critically important global issue that threatens ecosystem and environmental in many ways. Researchers have tried to use remote sensing data and meteorological data to perform residual trend analysis and identify human-induced vegetation changes. However, complex interactions between vegetation and climate, soil units and topography have not yet been considered. Data used in the study included annual accumulated Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m normalized difference vegetation index (NDVI) from 2002 to 2013, accumulated rainfall from September to August, digital elevation model (DEM) and soil units. This paper presents linear mixed-effect (LME) modeling methods for the NDVI-rainfall relationship. We developed linear mixed-effects models that considered the random effects of sample points nested in soil units for nested two-level modeling and single-level modeling of soil units and sample points, respectively. Additionally, three functions, including the exponential function (exp), the power function (power), and the constant plus power function (CPP), were tested to remove heterogeneity, and an additional three correlation structures, including the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)] and the compound symmetry structure (CS), were used to address the spatiotemporal correlations. It was concluded that the nested two-level model considering both heteroscedasticity with (CPP) and spatiotemporal correlation with [ARMA(1,1)] showed the best performance (AMR = 0.1881, RMSE = 0.2576, adj- R 2 = 0.9593). Variations between soil units and sample points that may have an effect on the NDVI-rainfall relationship should be included in model structures, and linear mixed-effects modeling achieves this in an effective and accurate way.
Anticommunism Versus Nonintervention in Latin America
1966-04-08
insistence of the Latin governments, another conference of American states was called at Chapultepec , near Mexico City, in 1945. There, the principles...overthrown in 195^ by an anti-Communist liberation army led by Colonel Carlos Castillo Armas. Castillo Armas became Provisional President in...contributed to the success of Castillo Armas’ liberation army in bringing about the downfall of tho Arbenz regime. The United States, as the leader
Unusual association of NDM-1 with KPC-2 and armA among Brazilian Enterobacteriaceae isolates
Quiles, M.G.; Rocchetti, T.T.; Fehlberg, L.C.; Kusano, E.J.U.; Chebabo, A.; Pereira, R.M.G.; Gales, A.C.; Pignatari, A.C.C.
2014-01-01
We report the microbiological characterization of four New Delhi metallo-β-lactamase-1 (bla NDM-1)-producing Enterobacteriaceae isolated in Rio de Janeiro, Brazil. bla NDM-1 was located on a conjugative plasmid and was associated with Klebsiella pneumoniae carbapenemase-2 (bla KPC-2) or aminoglycoside-resistance methylase (armA), a 16S rRNA methylase not previously reported in Brazil, in two distinct strains of Enterobacter cloacae. Our results suggested that the introduction of bla NDM-1 in Brazil has been accompanied by rapid spread, since our isolates showed no genetic relationship. PMID:25466163
Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia
NASA Astrophysics Data System (ADS)
Karimi, Sepideh; Kisi, Ozgur; Shiri, Jalal; Makarynskyy, Oleg
2013-03-01
Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In the present study, hourly sea levels for Darwin Harbor, Australia were predicted using two different, data driven techniques, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Multi linear regression (MLR) technique was used for selecting the optimal input combinations (lag times) of hourly sea level. The input combination comprises current sea level as well as five previous level values found to be optimal. For the ANFIS models, five different membership functions namely triangular, trapezoidal, generalized bell, Gaussian and two Gaussian membership function were tested and employed for predicting sea level for the next 1 h, 24 h, 48 h and 72 h. The used ANN models were trained using three different algorithms, namely, Levenberg-Marquardt, conjugate gradient and gradient descent. Predictions of optimal ANFIS and ANN models were compared with those of the optimal auto-regressive moving average (ARMA) models. The coefficient of determination, root mean square error and variance account statistics were used as comparison criteria. The obtained results indicated that triangular membership function was optimal for predictions with the ANFIS models while adaptive learning rate and Levenberg-Marquardt were most suitable for training the ANN models. Consequently, ANFIS and ANN models gave similar forecasts and performed better than the developed for the same purpose ARMA models for all the prediction intervals.
Forecasting daily lake levels using artificial intelligence approaches
NASA Astrophysics Data System (ADS)
Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher
2012-04-01
Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.
Li, Qiongge; Chan, Maria F
2017-01-01
Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.
Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.
2014-04-14
To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation.more » We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.« less
Poirier, E; Watier, L; Espie, E; Weill, F-X; De Valk, H; Desenclos, J-C
2008-09-01
In France, salmonellosis is the main cause of foodborne bacterial infection with serotypes Enteritis (SE) and Typhimurium (ST) accounting for 70% of all cases. French authorities implemented a national control programme targeting SE and ST in poultry and eggs from October 1998 onwards. A 33% decrease in salmonellosis has been observed since implementation. We designed an evaluation of the impact of this control programme on SE and ST human infections in France. Using monthly Salmonella human isolate reports to the National Reference Centre we defined two intervention series (SE and ST) and one control series comprising serotypes not know to be associated with poultry or eggs. The series, from 1992 to 2003, were analysed using autoregressive moving average models (ARMA). To test the hypothesis of a reduction of SE and ST human cases >0 after the programme started and to estimate its size, we introduced an intervention model to the ARMA modelling. In contrast to the control series, we found an annual reduction of 555 (95% CI 148-964) SE and of 492 (95% CI 0-1092) ST human infections, representing respectively a 21% and 18% decrease. For SE, the decrease occurred sharply after implementation while for ST, it followed a progressive decrease that started early in 1998. Our study, suggests a true relation between the Salmonella control programme and the subsequent decrease observed for the two targeted serotypes. For ST, however, the decrease prior to the intervention may also reflect control measures implemented earlier by the cattle and milk industry.
NASA Astrophysics Data System (ADS)
Sukono; Lesmana, E.; Susanti, D.; Napitupulu, H.; Hidayat, Y.
2017-11-01
Value-at-Risk has already become a standard measurement that must be carried out by the financial institution for both internal interest and regulatory. In this paper, the estimation of Value-at-Risk of some stocks with econometric models approach is analyzed. In this research, we assume that the stock return follows the time series model. To do the estimation of mean value we are using ARMA models, while to estimate the variance value we are using FIGARCH models. Furthermore, the mean value estimator and the variance are used to estimate the Value-at-Risk. The result of the analysis shows that from five stock PRUF, BBRI, MPPA, BMRI, and INDF, the Value-at-Risk obtained are 0.01791, 0.06037, 0.02550, 0.06030, and 0.02585 respectively. Since Value-at-Risk represents the maximum risk size of each stock at a 95% level of significance, then it can be taken into consideration in determining the investment policy on stocks.
Stock price forecasting based on time series analysis
NASA Astrophysics Data System (ADS)
Chi, Wan Le
2018-05-01
Using the historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-movingaverage model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in the paper was a certain accuracy.
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Secular Stellar Dynamics near a Massive Black Hole
NASA Astrophysics Data System (ADS)
Madigan, Ann-Marie; Hopman, Clovis; Levin, Yuri
2011-09-01
The angular momentum evolution of stars close to massive black holes (MBHs) is driven by secular torques. In contrast to two-body relaxation, where interactions between stars are incoherent, the resulting resonant relaxation (RR) process is characterized by coherence times of hundreds of orbital periods. In this paper, we show that all the statistical properties of RR can be reproduced in an autoregressive moving average (ARMA) model. We use the ARMA model, calibrated with extensive N-body simulations, to analyze the long-term evolution of stellar systems around MBHs with Monte Carlo simulations. We show that for a single-mass system in steady state, a depression is carved out near an MBH as a result of tidal disruptions. Using Galactic center parameters, the extent of the depression is about 0.1 pc, of similar order to but less than the size of the observed "hole" in the distribution of bright late-type stars. We also find that the velocity vectors of stars around an MBH are locally not isotropic. In a second application, we evolve the highly eccentric orbits that result from the tidal disruption of binary stars, which are considered to be plausible precursors of the "S-stars" in the Galactic center. We find that RR predicts more highly eccentric (e > 0.9) S-star orbits than have been observed to date.
Model Identification of Integrated ARMA Processes
ERIC Educational Resources Information Center
Stadnytska, Tetiana; Braun, Simone; Werner, Joachim
2008-01-01
This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Khalil, Mohammad; Salloum, Maher; Lee, Jina
2017-07-10
KARMA4 is a C++ library for autoregressive moving average (ARMA) modeling and forecasting of time-series data while incorporating both process and observation error. KARMA4 is designed for fitting and forecasting of time-series data for predictive purposes.
Kepler AutoRegressive Planet Search: Motivation & Methodology
NASA Astrophysics Data System (ADS)
Caceres, Gabriel; Feigelson, Eric; Jogesh Babu, G.; Bahamonde, Natalia; Bertin, Karine; Christen, Alejandra; Curé, Michel; Meza, Cristian
2015-08-01
The Kepler AutoRegressive Planet Search (KARPS) project uses statistical methodology associated with autoregressive (AR) processes to model Kepler lightcurves in order to improve exoplanet transit detection in systems with high stellar variability. We also introduce a planet-search algorithm to detect transits in time-series residuals after application of the AR models. One of the main obstacles in detecting faint planetary transits is the intrinsic stellar variability of the host star. The variability displayed by many stars may have autoregressive properties, wherein later flux values are correlated with previous ones in some manner. Auto-Regressive Moving-Average (ARMA) models, Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH), and related models are flexible, phenomenological methods used with great success to model stochastic temporal behaviors in many fields of study, particularly econometrics. Powerful statistical methods are implemented in the public statistical software environment R and its many packages. Modeling involves maximum likelihood fitting, model selection, and residual analysis. These techniques provide a useful framework to model stellar variability and are used in KARPS with the objective of reducing stellar noise to enhance opportunities to find as-yet-undiscovered planets. Our analysis procedure consisting of three steps: pre-processing of the data to remove discontinuities, gaps and outliers; ARMA-type model selection and fitting; and transit signal search of the residuals using a new Transit Comb Filter (TCF) that replaces traditional box-finding algorithms. We apply the procedures to simulated Kepler-like time series with known stellar and planetary signals to evaluate the effectiveness of the KARPS procedures. The ARMA-type modeling is effective at reducing stellar noise, but also reduces and transforms the transit signal into ingress/egress spikes. A periodogram based on the TCF is constructed to concentrate the signal of these periodic spikes. When a periodic transit is found, the model is displayed on a standard period-folded averaged light curve. We also illustrate the efficient coding in R.
POIRIER, E.; WATIER, L.; ESPIE, E.; WEILL, F.-X.; VALK, H. DE; DESENCLOS, J.-C.
2008-01-01
SUMMARY In France, salmonellosis is the main cause of foodborne bacterial infection with serotypes Enteritis (SE) and Typhimurium (ST) accounting for 70% of all cases. French authorities implemented a national control programme targeting SE and ST in poultry and eggs from October 1998 onwards. A 33% decrease in salmonellosis has been observed since implementation. We designed an evaluation of the impact of this control programme on SE and ST human infections in France. Using monthly Salmonella human isolate reports to the National Reference Centre we defined two intervention series (SE and ST) and one control series comprising serotypes not know to be associated with poultry or eggs. The series, from 1992 to 2003, were analysed using autoregressive moving average models (ARMA). To test the hypothesis of a reduction of SE and ST human cases >0 after the programme started and to estimate its size, we introduced an intervention model to the ARMA modelling. In contrast to the control series, we found an annual reduction of 555 (95% CI 148–964) SE and of 492 (95% CI 0–1092) ST human infections, representing respectively a 21% and 18% decrease. For SE, the decrease occurred sharply after implementation while for ST, it followed a progressive decrease that started early in 1998. Our study, suggests a true relation between the Salmonella control programme and the subsequent decrease observed for the two targeted serotypes. For ST, however, the decrease prior to the intervention may also reflect control measures implemented earlier by the cattle and milk industry. PMID:18047748
The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates
ERIC Educational Resources Information Center
Sivo, Stephen; Fan, Xitao; Witta, Lea
2005-01-01
The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…
Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model
NASA Astrophysics Data System (ADS)
Vazifedan, Turaj; Shitan, Mahendran
Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.
Stimulation at Desert Peak -modeling with the coupled THM code FEHM
kelkar, sharad
2013-04-30
Numerical modeling of the 2011 shear stimulation at the Desert Peak well 27-15. This submission contains the FEHM executable code for a 64-bit PC Windows-7 machine, and the input and output files for the results presented in the included paper from ARMA-213 meeting.
Robust Semi-Active Ride Control under Stochastic Excitation
2014-01-01
broad classes of time-series models which are of practical importance; the Auto-Regressive (AR) models, the Integrated (I) models, and the Moving...Average (MA) models [12]. Combinations of these models result in autoregressive moving average (ARMA) and autoregressive integrated moving average...Down Up 4) Down Down These four cases can be written in compact form as: (20) Where is the Heaviside
Taghvaei, Sajjad; Jahanandish, Mohammad Hasan; Kosuge, Kazuhiro
2017-01-01
Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a real-time fall prediction algorithm based on the acquired visual data of a user with walking assistive system from a depth sensor. In the lack of a coupled dynamic model of the human and the assistive walker a hybrid "system identification-machine learning" approach is used. An autoregressive-moving-average (ARMA) model is fitted on the time-series walking data to forecast the upcoming states, and a hidden Markov model (HMM) based classifier is built on the top of the ARMA model to predict falling in the upcoming time frames. The performance of the algorithm is evaluated through experiments with four subjects including an experienced physiotherapist while using a walker robot in five different falling scenarios; namely, fall forward, fall down, fall back, fall left, and fall right. The algorithm successfully predicts the fall with a rate of 84.72%.
NASA Astrophysics Data System (ADS)
Liley, David T.; Cadusch, Peter J.; Gray, Marcus; Nathan, Pradeep J.
2003-11-01
The benzodiazepine (BZ) class of minor tranquilizers are important modulators of the γ-amino butyric acid (GABAA)/BZ receptor complex that are well known to affect the spectral properties of spontaneous electroencephalographic activity. While it is experimentally well established that the BZs reduce total alpha band (8 13 Hz) power and increase total beta band (13 30 Hz) power, it is unclear what the physiological basis for this effect is. Based on a detailed theory of cortical electrorhythmogenesis it is conjectured that such an effect is explicable in terms of the modulation of GABAergic neurotransmission within locally connected populations of excitatory and inhibitory cortical neurons. Motivated by this theory, fixed order autoregressive moving average (ARMA) models were fitted to spontaneous eyes-closed electroencephalograms recorded from subjects before and approximately 2 h after the oral administration of a single 1 mg dose of the BZ alprazolam. Subsequent pole-zero analysis revealed that BZs significantly transform the dominant system pole such that its frequency and damping increase. Comparisons of ARMA derived power spectra with fast Fourier transform derived spectra indicate an enhanced ability to identify benzodiazepine induced electroencephalographic changes. This experimental result is in accord with the theoretical predictions implying that alprazolam enhances inhibition acting on inhibitory neurons more than inhibition acting on excitatory neurons. Further such a result is consistent with reported cortical neuronal distributions of the various GABAA receptor pharmacological subtypes. Therefore physiologically specified fixed order ARMA modeling is expected to become an important tool for the systematic investigation and modeling of a wide range of cortically acting compounds.
ERIC Educational Resources Information Center
McLean-Donaldson, Karen B.
1994-01-01
Identifies how students perceive racism and its effects on student learning and whether antiracist/multicultural arts (ARMA) curricula can empower students to address racism in schools. Results show racism, through students' eyes, damages learning, attitudes, and behavior. ARMA positively effected students' ability to confront racism within their…
ERIC Educational Resources Information Center
Sivo, Stephen; Fan, Xitao
2008-01-01
Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…
Atmospheric radiation flight dose rates
NASA Astrophysics Data System (ADS)
Tobiska, W. K.
2015-12-01
Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the domains that are affected by space weather, the coupling between the solar and galactic high-energy particles, the magnetosphere, and atmospheric regions can significantly affect humans and our technology as a result of radiation exposure. Space Environment Technologies (SET) has been conducting space weather observations of the atmospheric radiation environment at aviation altitudes that will eventually be transitioned into air traffic management operations. The Automated Radiation Measurements for Aerospace Safety (ARMAS) system and Upper-atmospheric Space and Earth Weather eXperiment (USEWX) both are providing dose rate measurements. Both activities are under the ARMAS goal of providing the "weather" of the radiation environment to improve aircraft crew and passenger safety. Over 5-dozen ARMAS and USEWX flights have successfully demonstrated the operation of a micro dosimeter on commercial aviation altitude aircraft that captures the real-time radiation environment resulting from Galactic Cosmic Rays and Solar Energetic Particles. The real-time radiation exposure is computed as an effective dose rate (body-averaged over the radiative-sensitive organs and tissues in units of microsieverts per hour); total ionizing dose is captured on the aircraft, downlinked in real-time, processed on the ground into effective dose rates, compared with NASA's Langley Research Center (LaRC) most recent Nowcast of Atmospheric Ionizing Radiation System (NAIRAS) global radiation climatology model runs, and then made available to end users via the web and smart phone apps. Flight altitudes now exceed 60,000 ft. and extend above commercial aviation altitudes into the stratosphere. In this presentation we describe recent ARMAS and USEWX results.
Stability of ARDS subphenotypes over time in two randomised controlled trials.
Delucchi, Kevin; Famous, Katie R; Ware, Lorraine B; Parsons, Polly E; Thompson, B Taylor; Calfee, Carolyn S
2018-05-01
Two distinct acute respiratory distress syndrome (ARDS) subphenotypes have been identified using data obtained at time of enrolment in clinical trials; it remains unknown if these subphenotypes are durable over time. To determine the stability of ARDS subphenotypes over time. Secondary analysis of data from two randomised controlled trials in ARDS, the ARMA trial of lung protective ventilation (n=473; patients randomised to low tidal volumes only) and the ALVEOLI trial of low versus high positive end-expiratory pressure (n=549). Latent class analysis (LCA) and latent transition analysis (LTA) were applied to data from day 0 and day 3, independent of clinical outcomes. In ALVEOLI, LCA indicated strong evidence of two ARDS latent classes at days 0 and 3; in ARMA, evidence of two classes was stronger at day 0 than at day 3. The clinical and biological features of these two classes were similar to those in our prior work and were largely stable over time, though class 2 demonstrated evidence of progressive organ failures by day 3, compared with class 1. In both LCA and LTA models, the majority of patients (>94%) stayed in the same class from day 0 to day 3. Clinical outcomes were statistically significantly worse in class 2 than class 1 and were more strongly associated with day 3 class assignment. ARDS subphenotypes are largely stable over the first 3 days of enrolment in two ARDS Network trials, suggesting that subphenotype identification may be feasible in the context of clinical trials. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Performance of Arma chinensis reared on an artificial diet formulated using transcriptomic methods
USDA-ARS?s Scientific Manuscript database
An artificial diet formulated for continuous rearing of the predator Arma chinensis was inferior to natural prey when evaluated using life history parameters. A transcriptome analysis identified differentially expressed genes in diet-fed and prey-fed A. chinensis that were suggestive of molecular me...
NASA Technical Reports Server (NTRS)
Johnson, C. R., Jr.; Balas, M. J.
1980-01-01
A novel interconnection of distributed parameter system (DPS) identification and adaptive filtering is presented, which culminates in a common statement of coupled autoregressive, moving-average expansion or parallel infinite impulse response configuration adaptive parameterization. The common restricted complexity filter objectives are seen as similar to the reduced-order requirements of the DPS expansion description. The interconnection presents the possibility of an exchange of problem formulations and solution approaches not yet easily addressed in the common finite dimensional lumped-parameter system context. It is concluded that the shared problems raised are nevertheless many and difficult.
NASA Astrophysics Data System (ADS)
Yang, Fan; Xue, Lianqing; Zhang, Luochen; Chen, Xinfang; Chi, Yixia
2017-12-01
This article aims to explore the adaptive utilization strategies of flow regime versus traditional practices in the context of climate change and human activities in the arid area. The study presents quantitative analysis of climatic and anthropogenic factors to streamflow alteration in the Tarim River Basin (TRB) using the Budyko method and adaptive utilization strategies to eco-hydrological regime by comparing the applicability between autoregressive moving average model (ARMA) model and combined regression model. Our results suggest that human activities played a dominant role in streamflow deduction in the mainstream with contribution of 120.7%~190.1%. While in the headstreams, climatic variables were the primary determinant of streamflow by 56.5~152.6% of the increase. The comparison revealed that combined regression model performed better than ARMA model with the qualified rate of 80.49~90.24%. Based on the forecasts of streamflow for different purposes, the adaptive utilization scheme of water flow is established from the perspective of time and space. Our study presents an effective water resources scheduling scheme for the ecological environment and provides references for ecological protection and water allocation in the arid area.
NASA Astrophysics Data System (ADS)
Celenk, Mehmet; Song, Yinglei; Ma, Limin; Zhou, Min
2003-05-01
A new algorithm that can be used to automatically recognize and classify malignant lymphomas and lukemia is proposed in this paper. The algorithm utilizes the morphological watershed to extract boundaries of cells from their grey-level images. It generates a sequence of Euclidean distances by selecting pixels in clockwise direction on the boundary of the cell and calculating the Euclidean distances of the selected pixels from the centroid of the cell. A feature vector associated with each cell is then obtained by applying the auto-regressive moving-average (ARMA) model to the generated sequence of Euclidean distances. The clustering measure J3=trace{inverse(Sw-1)Sm} involving the within (Sw) and mixed (Sm) class-scattering matrices is computed for both cell classes to provide an insight into the extent to which different cell classes in the training data are separated. Our test results suggest that the algorithm is highly accurate for the development of an interactive, computer-assisted diagnosis (CAD) tool.
Piekarska, Katarzyna; Zacharczuk, Katarzyna; Wołkowicz, Tomasz; Rzeczkowska, Magdalena; Bareja, Elżbieta; Olak, Monika; Gierczyński, Rafał
2016-01-01
Aminoglycosides are a group of antimicrobial agents still the most commonly used in the treatment of life-threatening bacterial infections in human and animals. The emergence and spread of 16S rRNA methylases, which confer high-level resistance to the majority of clinically relevant aminoglycosides, constitute a major public health concern. Our goal was to evaluate the distribution of 16S rRNA methylases among different species of Enterobacteriaceae during a five month-long survey in a tertiary hospital in Warszawa, Poland. In the survey, a total of 1770 non-duplicate clinical isolates were collected from all hospital wards in a tertiary hospital in Warszawa, Poland. The survey was conducted between 19 April and 19 September 2010. The ability to produce 16S rRNA methylase was examined by determining MICs for gentamicin, kanamycin, amikacin by means of the agar dilution method. The isolates resistant to high concentration of aminoglycosides were PCR tested for genes: armA, rmtA, rmtB and rmtC. PCR products were subjected to DNA sequencing by the Sanger method. The genetic similarity of the ArmA-producing isolates was analysed by pulsed-filed gel electrophoresis (PFGE). ArmA was the only 16S rRNA methylase detected in 20 of 1770 tested isolates. The overall prevalence rate of ArmA was 1.13%. In K. pneumoniae (n = 742), P. mirabilis (n = 130), and E. cloacae (n = 253) collected in the survey, the prevalence of ArmA was 0.4%, 0.8% and 5.9%, respectively. The PFGE revealed both horizontal and clonal spread of the armA gene in the hospital. The prevalence of 16S rRNA methylase ArmA reported in this study is significantly higher than observed in other countries in Europe.
Moving Average Models with Bivariate Exponential and Geometric Distributions.
1985-03-01
ordinary time series and of point processes. Developments in Statistics, Vol. 1, P.R. Krishnaiah , ed. Academic Press, New York. [9] Esary, J.D. and...valued and discrete - valued time series with ARMA correlation structure. Multivariate Analysis V, P.R. Krishnaiah , ed. North-Holland. 151-166. [28
An EM Algorithm for Maximum Likelihood Estimation of Process Factor Analysis Models
ERIC Educational Resources Information Center
Lee, Taehun
2010-01-01
In this dissertation, an Expectation-Maximization (EM) algorithm is developed and implemented to obtain maximum likelihood estimates of the parameters and the associated standard error estimates characterizing temporal flows for the latent variable time series following stationary vector ARMA processes, as well as the parameters defining the…
Sequential Monte Carlo for inference of latent ARMA time-series with innovations correlated in time
NASA Astrophysics Data System (ADS)
Urteaga, Iñigo; Bugallo, Mónica F.; Djurić, Petar M.
2017-12-01
We consider the problem of sequential inference of latent time-series with innovations correlated in time and observed via nonlinear functions. We accommodate time-varying phenomena with diverse properties by means of a flexible mathematical representation of the data. We characterize statistically such time-series by a Bayesian analysis of their densities. The density that describes the transition of the state from time t to the next time instant t+1 is used for implementation of novel sequential Monte Carlo (SMC) methods. We present a set of SMC methods for inference of latent ARMA time-series with innovations correlated in time for different assumptions in knowledge of parameters. The methods operate in a unified and consistent manner for data with diverse memory properties. We show the validity of the proposed approach by comprehensive simulations of the challenging stochastic volatility model.
Shekarchi, Sayedali; Hallam, John; Christensen-Dalsgaard, Jakob
2013-11-01
Head-related transfer functions (HRTFs) are generally large datasets, which can be an important constraint for embedded real-time applications. A method is proposed here to reduce redundancy and compress the datasets. In this method, HRTFs are first compressed by conversion into autoregressive-moving-average (ARMA) filters whose coefficients are calculated using Prony's method. Such filters are specified by a few coefficients which can generate the full head-related impulse responses (HRIRs). Next, Legendre polynomials (LPs) are used to compress the ARMA filter coefficients. LPs are derived on the sphere and form an orthonormal basis set for spherical functions. Higher-order LPs capture increasingly fine spatial details. The number of LPs needed to represent an HRTF, therefore, is indicative of its spatial complexity. The results indicate that compression ratios can exceed 98% while maintaining a spectral error of less than 4 dB in the recovered HRTFs.
Representation of high frequency Space Shuttle data by ARMA algorithms and random response spectra
NASA Technical Reports Server (NTRS)
Spanos, P. D.; Mushung, L. J.
1990-01-01
High frequency Space Shuttle lift-off data are treated by autoregressive (AR) and autoregressive-moving-average (ARMA) digital algorithms. These algorithms provide useful information on the spectral densities of the data. Further, they yield spectral models which lend themselves to incorporation to the concept of the random response spectrum. This concept yields a reasonably smooth power spectrum for the design of structural and mechanical systems when the available data bank is limited. Due to the non-stationarity of the lift-off event, the pertinent data are split into three slices. Each of the slices is associated with a rather distinguishable phase of the lift-off event, where stationarity can be expected. The presented results are rather preliminary in nature; it is aimed to call attention to the availability of the discussed digital algorithms and to the need to augment the Space Shuttle data bank as more flights are completed.
Damage localization of marine risers using time series of vibration signals
NASA Astrophysics Data System (ADS)
Liu, Hao; Yang, Hezhen; Liu, Fushun
2014-10-01
Based on dynamic response signals a damage detection algorithm is developed for marine risers. Damage detection methods based on numerous modal properties have encountered issues in the researches in offshore oil community. For example, significant increase in structure mass due to marine plant/animal growth and changes in modal properties by equipment noise are not the result of damage for riser structures. In an attempt to eliminate the need to determine modal parameters, a data-based method is developed. The implementation of the method requires that vibration data are first standardized to remove the influence of different loading conditions and the autoregressive moving average (ARMA) model is used to fit vibration response signals. In addition, a damage feature factor is introduced based on the autoregressive (AR) parameters. After that, the Euclidean distance between ARMA models is subtracted as a damage indicator for damage detection and localization and a top tensioned riser simulation model with different damage scenarios is analyzed using the proposed method with dynamic acceleration responses of a marine riser as sensor data. Finally, the influence of measured noise is analyzed. According to the damage localization results, the proposed method provides accurate damage locations of risers and is robust to overcome noise effect.
Castner, Jessica; Yin, Yong; Loomis, Dianne; Hewner, Sharon
2016-07-01
The purpose of this study is to describe and explain the temporal and seasonal trends in ED utilization for a low-income population. A retrospective analysis of 66,487 ED Medicaid-insured health care claims in 2009 was conducted for 2 Western New York Counties using time-series analysis with autoregressive moving average (ARMA) models. The final ARMA (2,0) model indicated an autoregressive structure with up to a 2-day lag. ED volume is lower on weekends than on weekdays, and the highest volumes are on Mondays. Summer and fall seasons demonstrated higher volumes, whereas lower volume outliers were associated with holidays. Day of the week was an influential predictor of ED utilization in low-income persons. Season and holidays are also predictors of ED utilization. These calendar-based patterns support the need for ongoing and future emergency leaders' collaborations in community-based care system redesign to meet the health care access needs of low-income persons. Copyright © 2016 Emergency Nurses Association. Published by Elsevier Inc. All rights reserved.
ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.
Lee, Keunbaik; Baek, Changryong; Daniels, Michael J
2017-11-01
In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.
Impaired cerebrovascular autoregulation and reduced CO₂ reactivity after long duration spaceflight.
Zuj, K A; Arbeille, Ph; Shoemaker, J K; Blaber, A P; Greaves, D K; Xu, D; Hughson, R L
2012-06-15
Long duration habitation on the International Space Station (ISS) is associated with chronic elevations in arterial blood pressure in the brain compared with normal upright posture on Earth and elevated inspired CO(2). Although results from short-duration spaceflights suggested possibly improved cerebrovascular autoregulation, animal models provided evidence of structural and functional changes in cerebral vessels that might negatively impact autoregulation with longer periods in microgravity. Seven astronauts (1 woman) spent 147 ± 49 days on ISS. Preflight testing (30-60 days before launch) was compared with postflight testing on landing day (n = 4) or the morning 1 (n = 2) or 2 days (n = 1) after return to Earth. Arterial blood pressure at the level of the middle cerebral artery (BP(MCA)) and expired CO(2) were monitored along with transcranial Doppler ultrasound assessment of middle cerebral artery (MCA) blood flow velocity (CBFV). Cerebrovascular resistance index was calculated as (CVRi = BP(MCA)/CBFV). Cerebrovascular autoregulation and CO(2) reactivity were assessed in a supine position from an autoregressive moving average (ARMA) model of data obtained during a test where two breaths of 10% CO(2) were given four times during a 5-min period. CBFV and Doppler pulsatility index were reduced during -20 mmHg lower body negative pressure, with no differences pre- to postflight. The postflight indicator of dynamic autoregulation from the ARMA model revealed reduced gain for the CVRi response to BP(MCA) (P = 0.017). The postflight responses to CO(2) were reduced for CBFV (P = 0.056) and CVRi (P = 0.047). These results indicate that long duration missions on the ISS impaired dynamic cerebrovascular autoregulation and reduced cerebrovascular CO(2) reactivity.
Spectral Estimation: An Overdetermined Rational Model Equation Approach.
1982-09-15
A-A123 122 SPECTRAL ESTIMATION: AN OVERDETERMINEO RATIONAL MODEL 1/2 EQUATION APPROACH..(U) ARIZONA STATE UNIV TEMPE DEPT OF ELECTRICAL AND COMPUTER...2 0 447,_______ 4. TITLE (mAd Sabile) S. TYPE or REPORT a PEP40D COVERED Spectral Estimation; An Overdeteruined Rational Final Report 9/3 D/8 to...andmmd&t, by uwek 7a5 4 Rational Spectral Estimation, ARMA mo~Ie1, AR model, NMA Mdle, Spectrum, Singular Value Decomposition. Adaptivb Implementatlan
Design and implementation of ticket price forecasting system
NASA Astrophysics Data System (ADS)
Li, Yuling; Li, Zhichao
2018-05-01
With the advent of the aviation travel industry, a large number of data mining technologies have been developed to increase profits for airlines in the past two decades. The implementation of the digital optimization strategy leads to price discrimination, for example, similar seats on the same flight are purchased at different prices, depending on the time of purchase, the supplier, and so on. Price fluctuations make the prediction of ticket prices have application value. In this paper, a combination of ARMA algorithm and random forest algorithm is proposed to predict the price of air ticket. The experimental results show that the model is more reliable by comparing the forecasting results with the actual results of each price model. The model is helpful for passengers to buy tickets and to save money. Based on the proposed model, using Python language and SQL Server database, we design and implement the ticket price forecasting system.
Giraldo, Gloria
2009-01-01
Dr Yamila de Armas has occupied an array of posts since finishing her residency in family medicine in her home province of Cienfuegos in 1992. She has served as a family doctor; polyclinic, municipal and provincial health director; medical school dean; and twice vice minister of public health. But few would doubt her toughest job is the one she has now: deputy director of the Havana City Provincial Health Department, in charge of medical services for the 2.2 million people living in Cuba's complex, sprawling capital. It was here in 2002-2003 that the program was launched to repair, refurbish and expand the country's nearly 500 community polyclinics. Key to the effort was equipping these facilities with a broader range of new and upgraded medical technology. Dr de Armas offers MEDICC Review her reflections on the results five years later.
NASA Astrophysics Data System (ADS)
Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.
1988-10-01
A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.
NASA Astrophysics Data System (ADS)
Tobiska, W.; Knipp, D. J.; Burke, W. J.; Bouwer, D.; Bailey, J. J.; Hagan, M. P.; Didkovsky, L. V.; Garrett, H. B.; Bowman, B. R.; Gannon, J. L.; Atwell, W.; Blake, J. B.; Crain, W.; Rice, D.; Schunk, R. W.; Fulgham, J.; Bell, D.; Gersey, B.; Wilkins, R.; Fuschino, R.; Flynn, C.; Cecil, K.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, S. I.; Wiley, S.; Holland, M.; Malone, K.
2013-12-01
Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET's Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the 'weather' of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.
Prototype Operational Advances for Atmospheric Radiation Dose Rate Specification
NASA Astrophysics Data System (ADS)
Tobiska, W. K.; Bouwer, D.; Bailey, J. J.; Didkovsky, L. V.; Judge, K.; Garrett, H. B.; Atwell, W.; Gersey, B.; Wilkins, R.; Rice, D.; Schunk, R. W.; Bell, D.; Mertens, C. J.; Xu, X.; Crowley, G.; Reynolds, A.; Azeem, I.; Wiltberger, M. J.; Wiley, S.; Bacon, S.; Teets, E.; Sim, A.; Dominik, L.
2014-12-01
Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. The coupling between the solar and galactic high-energy particles, the magnetosphere, and atmospheric regions can significantly affect humans and our technology as a result of radiation exposure. Space Environment Technologies (SET) has developed innovative, new space weather observations that will become part of the toolset that is transitioned into operational use. One prototype operational system for providing timely information about the effects of space weather is SET's Automated Radiation Measurements for Aerospace Safety (ARMAS) system. ARMAS will provide the "weather" of the radiation environment to improve aircraft crew and passenger safety. Through several dozen flights the ARMAS project has successfully demonstrated the operation of a micro dosimeter on commercial aviation altitude aircraft that captures the real-time radiation environment resulting from Galactic Cosmic Rays and Solar Energetic Particles. The real-time radiation exposure is computed as an effective dose rate (body-averaged over the radiative-sensitive organs and tissues in units of microsieverts per hour); total ionizing dose is captured on the aircraft, downlinked in real-time via Iridium satellites, processed on the ground into effective dose rates, compared with NASA's Langley Research Center (LaRC) most recent Nowcast of Atmospheric Ionizing Radiation System (NAIRAS) global radiation climatology model runs, and then made available to end users via the web and smart phone apps. We are extending the dose measurement domain above commercial aviation altitudes into the stratosphere with a collaborative project organized by NASA's Armstrong Flight Research Center (AFRC) called Upper-atmospheric Space and Earth Weather eXperiment (USEWX). In USEWX we will be flying on the ER-2 high altitude aircraft a micro dosimeter for effective dose rate measurements and a thermal neutron monitor to characterize Single Event Effects (SEEs) in avionics. In this presentation we describe recent ARMAS and USEWX advances that will ultimately provide operational users with real-time dose and dose rate data for human tissue and avionics exposure risk mitigation.
Simulating extreme low-discharge events for the Rhine using a stochastic model
NASA Astrophysics Data System (ADS)
Macian-Sorribes, Hector; Mens, Marjolein; Schasfoort, Femke; Diermanse, Ferdinand; Pulido-Velazquez, Manuel
2017-04-01
The specific features of hydrological droughts make them more difficult to be analysed than other water-related phenomena: longer time scales (months to several years) so less historical events are available, and the drought severity and associate damage depends on a combination of variables with no clear prevalence (e.g., total water deficit, maximum deficit and duration). As part of drought risk analysis, which aims to provide insight into the variability of hydrological conditions and associated socio-economic impacts, long synthetic time series should therefore be developed. In this contribution, we increase the length of the available inflow time series using stochastic autoregressive modelling. This enhancement could improve the characterization of the extreme range and can define extreme droughts with similar periods of return but different patterns that can lead to distinctly different damages. The methodology consists of: 1) fitting an autoregressive model (AR, ARMA…) to the available records; 2) generating extended time series (thousands of years); 3) performing a frequency analysis with different characteristic variables (total, deficit, maximum deficit and so on); and 4) selecting extreme drought events associated with different characteristic variables and return periods. The methodology was applied to the Rhine river discharge at location Lobith, where the Rhine enters The Netherlands. A monthly ARMA(1,1) autoregressive model with seasonally varying parameters was fitted and successfully validated to the historical records available since year 1901. The maximum monthly deficit with respect to a threshold value of 1800 m3/s and the average discharge for a given time span in m3/s were chosen as indicators to identify drought periods. A synthetic series of 10,000 years of discharges was generated using the validated ARMA model. Two time spans were considered in the analysis: the whole calendar year and the half-year period between April and September (the summer half year, where water demands are highest). Frequency analysis was performed for both indicators and time spans for the generated time series and the historical records. The comparison between observed and generated series showed that the ARMA model provides a good reproduction of the maximum deficits and total discharges, especially for the summer half-year period. The resulting synthetic series are therefore considered credible. These synthetic series, with its wealth of information, can then be used as inputs for the damage assessment models, together with information on precipitation deficits, in order to estimate the risk that lower inflows can have on the urban, the agricultural, the shipping sector and so on. This will help in associating economic losses and periods of return, as well as for estimating how droughts with similar periods of return but different patterns can lead to different damages. ACKNOWLEDGEMENT This study has been supported by the European Union's Horizon 2020 research and innovation programme under the IMPREX project (grant agreement no: 641.811), and by the Climate-KIC Pioneers into Practice Program supported by the European Union's EIT.
Eigenvalue Tests and Distributions for Small Sample Order Determination for Complex Wishart Matrices
1994-08-13
theoretic order determination criteria for ARMA(p, q) models can be expressed in the form of equation 4.2. The word ARIMA should not be a distractor...subjectivity is not necessarily bad. It enables us to build tractable models and efficiently achieve reasonable results. The charge of "subjectivity" lodged...signal processing studies because it simplifies the mathematics involved and it is not a bad model for a wide range of situations. Wooding [293] is
Müller-Tidow, C; Tschanter, P; Röllig, C; Thiede, C; Koschmieder, A; Stelljes, M; Koschmieder, S; Dugas, M; Gerss, J; Butterfaß-Bahloul, T; Wagner, R; Eveslage, M; Thiem, U; Krause, S W; Kaiser, U; Kunzmann, V; Steffen, B; Noppeney, R; Herr, W; Baldus, C D; Schmitz, N; Götze, K; Reichle, A; Kaufmann, M; Neubauer, A; Schäfer-Eckart, K; Hänel, M; Peceny, R; Frickhofen, N; Kiehl, M; Giagounidis, A; Görner, M; Repp, R; Link, H; Kiani, A; Naumann, R; Brümmendorf, T H; Serve, H; Ehninger, G; Berdel, W E; Krug, U
2016-03-01
DNA methylation changes are a constant feature of acute myeloid leukemia. Hypomethylating drugs such as azacitidine are active in acute myeloid leukemia (AML) as monotherapy. Azacitidine monotherapy is not curative. The AML-AZA trial tested the hypothesis that DNA methyltransferase inhibitors such as azacitidine can improve chemotherapy outcome in AML. This randomized, controlled trial compared the efficacy of azacitidine applied before each cycle of intensive chemotherapy with chemotherapy alone in older patients with untreated AML. Event-free survival (EFS) was the primary end point. In total, 214 patients with a median age of 70 years were randomized to azacitidine/chemotherapy (arm-A) or chemotherapy (arm-B). More arm-A patients (39/105; 37%) than arm-B (25/109; 23%) showed adverse cytogenetics (P=0.057). Adverse events were more frequent in arm-A (15.44) versus 13.52 in arm-B, (P=0.26), but early death rates did not differ significantly (30-day mortality: 6% versus 5%, P=0.76). Median EFS was 6 months in both arms (P=0.96). Median overall survival was 15 months for patients in arm-A compared with 21 months in arm-B (P=0.35). Azacitidine added to standard chemotherapy increases toxicity in older patients with AML, but provides no additional benefit for unselected patients.
A stochastic approach to noise modeling for barometric altimeters.
Sabatini, Angelo Maria; Genovese, Vincenzo
2013-11-18
The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes), we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM) random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA) system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component. M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.
Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model
Zhu, Qing; Zou, Yingchao; Lai, Kin Keung
2014-01-01
As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations. PMID:25061614
Value-at-risk estimation with wavelet-based extreme value theory: Evidence from emerging markets
NASA Astrophysics Data System (ADS)
Cifter, Atilla
2011-06-01
This paper introduces wavelet-based extreme value theory (EVT) for univariate value-at-risk estimation. Wavelets and EVT are combined for volatility forecasting to estimate a hybrid model. In the first stage, wavelets are used as a threshold in generalized Pareto distribution, and in the second stage, EVT is applied with a wavelet-based threshold. This new model is applied to two major emerging stock markets: the Istanbul Stock Exchange (ISE) and the Budapest Stock Exchange (BUX). The relative performance of wavelet-based EVT is benchmarked against the Riskmetrics-EWMA, ARMA-GARCH, generalized Pareto distribution, and conditional generalized Pareto distribution models. The empirical results show that the wavelet-based extreme value theory increases predictive performance of financial forecasting according to number of violations and tail-loss tests. The superior forecasting performance of the wavelet-based EVT model is also consistent with Basel II requirements, and this new model can be used by financial institutions as well.
Day-ahead crude oil price forecasting using a novel morphological component analysis based model.
Zhu, Qing; He, Kaijian; Zou, Yingchao; Lai, Kin Keung
2014-01-01
As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.
Computational problems in autoregressive moving average (ARMA) models
NASA Technical Reports Server (NTRS)
Agarwal, G. C.; Goodarzi, S. M.; Oneill, W. D.; Gottlieb, G. L.
1981-01-01
The choice of the sampling interval and the selection of the order of the model in time series analysis are considered. Band limited (up to 15 Hz) random torque perturbations are applied to the human ankle joint. The applied torque input, the angular rotation output, and the electromyographic activity using surface electrodes from the extensor and flexor muscles of the ankle joint are recorded. Autoregressive moving average models are developed. A parameter constraining technique is applied to develop more reliable models. The asymptotic behavior of the system must be taken into account during parameter optimization to develop predictive models.
A Regional Analysis of Non-Methane Hydrocarbons And Meteorology of The Rural Southeast United States
1996-01-01
Zt is an ARIMA time series. This is a typical regression model , except that it allows for autocorrelation in the error term Z. In this work, an ARMA...data=folder; var residual; run; II Statistical output of 1992 regression model on 1993 ozone data ARIMA Procedure Maximum Likelihood Estimation Approx...at each of the sites, and to show the effect of synoptic meteorology on high ozone by examining NOAA daily weather maps and climatic data
Ultra-Short-Term Wind Power Prediction Using a Hybrid Model
NASA Astrophysics Data System (ADS)
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.
NASA Astrophysics Data System (ADS)
Tobiska, W. Kent
Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the magnetosphere, thermosphere, and even troposphere are key regions that are affected. Space Environment Technologies (SET) has developed and is producing innovative space weather applications. Key operational systems for providing timely information about the effects of space weather on these domains are SET’s Magnetosphere Alert and Prediction System (MAPS), LEO Alert and Prediction System (LAPS), and Automated Radiation Measurements for Aviation Safety (ARMAS) system. MAPS provides a forecast Dst index out to 6 days through the data-driven, redundant data stream Anemomilos algorithm. Anemomilos uses observational proxies for the magnitude, location, and velocity of solar ejecta events. This forecast index is used by satellite operations to characterize upcoming geomagnetic storms, for example. In addition, an ENLIL/Rice Dst prediction out to several days has also been developed and will be described. LAPS is the SET fully redundant operational system providing recent history, current epoch, and forecast solar and geomagnetic indices for use in operational versions of the JB2008 thermospheric density model. The thermospheric densities produced by that system, driven by the LAPS data, are forecast to 72-hours to provide the global mass densities for satellite operators. ARMAS is a project that has successfully demonstrated the operation of a micro dosimeter on aircraft to capture the real-time radiation environment due to Galactic Cosmic Rays and Solar Energetic Particles. The dose and dose-rates are captured on aircraft, downlinked in real-time via the Iridium satellites, processed on the ground, incorporated into the most recent NAIRAS global radiation climatology data runs, and made available to end users via the web and smart phone apps. ARMAS provides the “weather” of the radiation environment to improve air-crew and passenger safety. Many of the data products from MAPS, LAPS, and ARMAS are available on the SpaceWx smartphone app for iPhone, iPad, iPod, and Android professional users and public space weather education. We describe recent forecasting advances for moving the space weather information from these automated systems into operational, derivative products for communications, aviation, and satellite operations uses.
Forecasting coconut production in the Philippines with ARIMA model
NASA Astrophysics Data System (ADS)
Lim, Cristina Teresa
2015-02-01
The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years.
Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Jun; Rabiti, Cristian
Hybrid energy systems consisting of multiple energy inputs and multiple energy outputs have been proposed to be an effective element to enable ever increasing penetration of clean energy. In order to better understand the dynamic and probabilistic behavior of hybrid energy systems, this paper proposes a model combining Fourier series and autoregressive moving average (ARMA) to characterize historical weather measurements and to generate synthetic weather (e.g., wind speed) data. In particular, Fourier series is used to characterize the seasonal trend in historical data, while ARMA is applied to capture the autocorrelation in residue time series (e.g., measurements minus seasonal trends).more » The generated synthetic wind speed data is then utilized to perform probabilistic analysis of a particular hybrid energy system con guration, which consists of nuclear power plant, wind farm, battery storage, natural gas boiler, and chemical plant. As a result, requirements on component ramping rate, economic and environmental impacts of hybrid energy systems, and the effects of deploying different sizes of batteries in smoothing renewable variability, are all investigated.« less
Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems
Chen, Jun; Rabiti, Cristian
2016-11-25
Hybrid energy systems consisting of multiple energy inputs and multiple energy outputs have been proposed to be an effective element to enable ever increasing penetration of clean energy. In order to better understand the dynamic and probabilistic behavior of hybrid energy systems, this paper proposes a model combining Fourier series and autoregressive moving average (ARMA) to characterize historical weather measurements and to generate synthetic weather (e.g., wind speed) data. In particular, Fourier series is used to characterize the seasonal trend in historical data, while ARMA is applied to capture the autocorrelation in residue time series (e.g., measurements minus seasonal trends).more » The generated synthetic wind speed data is then utilized to perform probabilistic analysis of a particular hybrid energy system con guration, which consists of nuclear power plant, wind farm, battery storage, natural gas boiler, and chemical plant. As a result, requirements on component ramping rate, economic and environmental impacts of hybrid energy systems, and the effects of deploying different sizes of batteries in smoothing renewable variability, are all investigated.« less
Parametric adaptive filtering and data validation in the bar GW detector AURIGA
NASA Astrophysics Data System (ADS)
Ortolan, A.; Baggio, L.; Cerdonio, M.; Prodi, G. A.; Vedovato, G.; Vitale, S.
2002-04-01
We report on our experience gained in the signal processing of the resonant GW detector AURIGA. Signal amplitude and arrival time are estimated by means of a matched-adaptive Wiener filter. The detector noise, entering in the filter set-up, is modelled as a parametric ARMA process; to account for slow non-stationarity of the noise, the ARMA parameters are estimated on an hourly basis. A requirement of the set-up of an unbiased Wiener filter is the separation of time spans with 'almost Gaussian' noise from non-Gaussian and/or strongly non-stationary time spans. The separation algorithm consists basically of a variance estimate with the Chauvenet convergence method and a threshold on the Curtosis index. The subsequent validation of data is strictly connected with the separation procedure: in fact, by injecting a large number of artificial GW signals into the 'almost Gaussian' part of the AURIGA data stream, we have demonstrated that the effective probability distributions of the signal-to-noise ratio χ2 and the time of arrival are those that are expected.
Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks
Wang, Xue; Wang, Sheng; Bi, Dao-Wei; Ma, Jun-Jie
2007-01-01
Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.
Incorporating measurement error in n = 1 psychological autoregressive modeling.
Schuurman, Noémi K; Houtveen, Jan H; Hamaker, Ellen L
2015-01-01
Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30-50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters.
Sandhu, R S; Treharne, G J; Justice, E A; Jordan, A C; Saravana, S; Obrenovic, K; Erb, N; Kitas, G D; Rowe, I F
2007-12-01
Secondary care rheumatology services for patients with inflammatory arthritis (IA) in the West Midlands were audited using Arthritis and Musculoskeletal Alliance (ARMA) standards of care. Questionnaires were analysed from 1,715 patients in 11 rheumatology departments. ARMA standards recommend full multidisciplinary team assessment; referral rates to nurse specialists (52.3%), physiotherapists (48.7%) and occupational therapists (36.5%) were, however, lower than expected. Attendance at existing hospital-led education groups was rare (8.9%), awareness of existing helplines was moderate (59.2%) but the proportion of patients reporting satisfaction with advice about their disease was high (80.5%). Significant variations were found between departments. For patients with IA < 2 years (n = 236), 84.5% were seen by a rheumatologist within the ARMA standard of 12 weeks of referral; diagnosis of a type of IA was made at the first rheumatology appointment in 66.4%; 82.8% of rheumatoid arthritis patients had commenced disease-modifying drugs, although time to commencement varied across departments. This study raises issues regarding provision of rheumatology services, prioritisation of patient referral and patient education.
Taylor, Brian A.; Hwang, Ken-Pin; Hazle, John D.; Stafford, R. Jason
2009-01-01
The authors investigated the performance of the iterative Steiglitz–McBride (SM) algorithm on an autoregressive moving average (ARMA) model of signals from a fast, sparsely sampled, multiecho, chemical shift imaging (CSI) acquisition using simulation, phantom, ex vivo, and in vivo experiments with a focus on its potential usage in magnetic resonance (MR)-guided interventions. The ARMA signal model facilitated a rapid calculation of the chemical shift, apparent spin-spin relaxation time (T2*), and complex amplitudes of a multipeak system from a limited number of echoes (≤16). Numerical simulations of one- and two-peak systems were used to assess the accuracy and uncertainty in the calculated spectral parameters as a function of acquisition and tissue parameters. The measured uncertainties from simulation were compared to the theoretical Cramer–Rao lower bound (CRLB) for the acquisition. Measurements made in phantoms were used to validate the T2* estimates and to validate uncertainty estimates made from the CRLB. We demonstrated application to real-time MR-guided interventions ex vivo by using the technique to monitor a percutaneous ethanol injection into a bovine liver and in vivo to monitor a laser-induced thermal therapy treatment in a canine brain. Simulation results showed that the chemical shift and amplitude uncertainties reached their respective CRLB at a signal-to-noise ratio (SNR)≥5 for echo train lengths (ETLs)≥4 using a fixed echo spacing of 3.3 ms. T2* estimates from the signal model possessed higher uncertainties but reached the CRLB at larger SNRs and∕or ETLs. Highly accurate estimates for the chemical shift (<0.01 ppm) and amplitude (<1.0%) were obtained with ≥4 echoes and for T2* (<1.0%) with ≥7 echoes. We conclude that, over a reasonable range of SNR, the SM algorithm is a robust estimator of spectral parameters from fast CSI acquisitions that acquire ≤16 echoes for one- and two-peak systems. Preliminary ex vivo and in vivo experiments corroborated the results from simulation experiments and further indicate the potential of this technique for MR-guided interventional procedures with high spatiotemporal resolution ∼1.6×1.6×4 mm3 in ≤5 s. PMID:19378736
An improved portmanteau test for autocorrelated errors in interrupted time-series regression models.
Huitema, Bradley E; McKean, Joseph W
2007-08-01
A new portmanteau test for autocorrelation among the errors of interrupted time-series regression models is proposed. Simulation results demonstrate that the inferential properties of the proposed Q(H-M) test statistic are considerably more satisfactory than those of the well known Ljung-Box test and moderately better than those of the Box-Pierce test. These conclusions generally hold for a wide variety of autoregressive (AR), moving averages (MA), and ARMA error processes that are associated with time-series regression models of the form described in Huitema and McKean (2000a, 2000b).
Alamaniotis, Miltiadis; Bargiotas, Dimitrios; Tsoukalas, Lefteri H
2016-01-01
Integration of energy systems with information technologies has facilitated the realization of smart energy systems that utilize information to optimize system operation. To that end, crucial in optimizing energy system operation is the accurate, ahead-of-time forecasting of load demand. In particular, load forecasting allows planning of system expansion, and decision making for enhancing system safety and reliability. In this paper, the application of two types of kernel machines for medium term load forecasting (MTLF) is presented and their performance is recorded based on a set of historical electricity load demand data. The two kernel machine models and more specifically Gaussian process regression (GPR) and relevance vector regression (RVR) are utilized for making predictions over future load demand. Both models, i.e., GPR and RVR, are equipped with a Gaussian kernel and are tested on daily predictions for a 30-day-ahead horizon taken from the New England Area. Furthermore, their performance is compared to the ARMA(2,2) model with respect to mean average percentage error and squared correlation coefficient. Results demonstrate the superiority of RVR over the other forecasting models in performing MTLF.
Dagdeviren, Omur E
2018-08-03
The effect of surface disorder, load, and velocity on friction between a single asperity contact and a model surface is explored with one-dimensional and two-dimensional Prandtl-Tomlinson (PT) models. We show that there are fundamental physical differences between the predictions of one-dimensional and two-dimensional models. The one-dimensional model estimates a monotonic increase in friction and energy dissipation with load, velocity, and surface disorder. However, a two-dimensional PT model, which is expected to approximate a tip-sample system more realistically, reveals a non-monotonic trend, i.e. friction is inert to surface disorder and roughness in wearless friction regime. The two-dimensional model discloses that the surface disorder starts to dominate the friction and energy dissipation when the tip and the sample interact predominantly deep into the repulsive regime. Our numerical calculations address that tracking the minimum energy path and the slip-stick motion are two competing effects that determine the load, velocity, and surface disorder dependence of friction. In the two-dimensional model, the single asperity can follow the minimum energy path in wearless regime; however, with increasing load and sliding velocity, the slip-stick movement dominates the dynamic motion and results in an increase in friction by impeding tracing the minimum energy path. Contrary to the two-dimensional model, when the one-dimensional PT model is employed, the single asperity cannot escape to the minimum energy minimum due to constraint motion and reveals only a trivial dependence of friction on load, velocity, and surface disorder. Our computational analyses clarify the physical differences between the predictions of the one-dimensional and two-dimensional models and open new avenues for disordered surfaces for low energy dissipation applications in wearless friction regime.
Random Process Simulation for stochastic fatigue analysis. Ph.D. Thesis - Rice Univ., Houston, Tex.
NASA Technical Reports Server (NTRS)
Larsen, Curtis E.
1988-01-01
A simulation technique is described which directly synthesizes the extrema of a random process and is more efficient than the Gaussian simulation method. Such a technique is particularly useful in stochastic fatigue analysis because the required stress range moment E(R sup m), is a function only of the extrema of the random stress process. The family of autoregressive moving average (ARMA) models is reviewed and an autoregressive model is presented for modeling the extrema of any random process which has a unimodal power spectral density (psd). The proposed autoregressive technique is found to produce rainflow stress range moments which compare favorably with those computed by the Gaussian technique and to average 11.7 times faster than the Gaussian technique. The autoregressive technique is also adapted for processes having bimodal psd's. The adaptation involves using two autoregressive processes to simulate the extrema due to each mode and the superposition of these two extrema sequences. The proposed autoregressive superposition technique is 9 to 13 times faster than the Gaussian technique and produces comparable values for E(R sup m) for bimodal psd's having the frequency of one mode at least 2.5 times that of the other mode.
NASA Astrophysics Data System (ADS)
Shiri, Jalal; Kisi, Ozgur; Yoon, Heesung; Lee, Kang-Kun; Hossein Nazemi, Amir
2013-07-01
The knowledge of groundwater table fluctuations is important in agricultural lands as well as in the studies related to groundwater utilization and management levels. This paper investigates the abilities of Gene Expression Programming (GEP), Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Networks (ANN) and Support Vector Machine (SVM) techniques for groundwater level forecasting in following day up to 7-day prediction intervals. Several input combinations comprising water table level, rainfall and evapotranspiration values from Hongcheon Well station (South Korea), covering a period of eight years (2001-2008) were used to develop and test the applied models. The data from the first six years were used for developing (training) the applied models and the last two years data were reserved for testing. A comparison was also made between the forecasts provided by these models and the Auto-Regressive Moving Average (ARMA) technique. Based on the comparisons, it was found that the GEP models could be employed successfully in forecasting water table level fluctuations up to 7 days beyond data records.
Incorporating measurement error in n = 1 psychological autoregressive modeling
Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.
2015-01-01
Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988
Space weather effects measured in atmospheric radiation on aircraft
NASA Astrophysics Data System (ADS)
Tobiska, W. K.; Bouwer, D.; Bailey, J. J.; Didkovsky, L. V.; Judge, K.; Wieman, S. R.; Atwell, W.; Gersey, B.; Wilkins, R.; Rice, D.; Schunk, R. W.; Bell, L. D.; Mertens, C. J.; Xu, X.; Wiltberger, M. J.; Wiley, S.; Teets, E.; Shea, M. A.; Smart, D. F.; Jones, J. B. L.; Crowley, G.; Azeem, S. I.; Halford, A. J.
2016-12-01
Space weather's effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun's photons, particles, and fields. Of the domains that are affected by space weather, the coupling between the solar and galactic high-energy particles, the magnetosphere, and atmospheric regions can significantly affect humans and our technology as a result of radiation exposure. Since 2013 Space Environment Technologies (SET) has been conducting observations of the atmospheric radiation environment at aviation altitudes using a small fleet of six instruments. The objective of this work is to improve radiation risk management in air traffic operations. Under the auspices of the Automated Radiation Measurements for Aerospace Safety (ARMAS) and Upper-atmospheric Space and Earth Weather eXperiment (USEWX) projects our team is making dose rate measurements on multiple aircraft flying global routes. Over 174 ARMAS and USEWX flights have successfully demonstrated the operation of a micro dosimeter on commercial aviation altitude aircraft that captures the radiation environment resulting from Galactic Cosmic Rays (GCRs), Solar Energetic Protons (SEPs), and outer radiation belt energetic electrons. The real-time radiation exposure is measured as an absorbed dose rate in silicon and then computed as an ambient dose equivalent rate for reporting dose relevant to radiative-sensitive organs and tissue in units of microsieverts per hour. ARMAS total ionizing absorbed dose is captured on the aircraft, downlinked in real-time, processed on the ground into ambient dose equivalent rates, compared with NASA's Langley Research Center (LaRC) most recent Nowcast of Atmospheric Ionizing Radiation System (NAIRAS) global radiation climatology model runs, and then made available to end users. Dose rates from flight altitudes up to 56,700 ft. are shown for flights across the planet under a variety of space weather conditions. We discuss several space weather effects on the atmospheric radiation environment, including the levels of GCR background radiation, small SEP events, and possible EMIC wave driven energetic electrons from the outer radiation belt creating "radiation" clouds in the troposphere.
NASA Astrophysics Data System (ADS)
Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin
2009-08-01
SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.
NASA Astrophysics Data System (ADS)
Seleznev, R. K.
2017-02-01
In the paper two-dimensional and quasi-one dimensional models for scramjet combustion chamber are described. Comparison of the results of calculations for the two-dimensional and quasi-one dimensional code by the example of VAG experiment are presented.
Schiek, Richard [Albuquerque, NM
2006-06-20
A method of generating two-dimensional masks from a three-dimensional model comprises providing a three-dimensional model representing a micro-electro-mechanical structure for manufacture and a description of process mask requirements, reducing the three-dimensional model to a topological description of unique cross sections, and selecting candidate masks from the unique cross sections and the cross section topology. The method further can comprise reconciling the candidate masks based on the process mask requirements description to produce two-dimensional process masks.
A comparative simulation study of AR(1) estimators in short time series.
Krone, Tanja; Albers, Casper J; Timmerman, Marieke E
2017-01-01
Various estimators of the autoregressive model exist. We compare their performance in estimating the autocorrelation in short time series. In Study 1, under correct model specification, we compare the frequentist r 1 estimator, C-statistic, ordinary least squares estimator (OLS) and maximum likelihood estimator (MLE), and a Bayesian method, considering flat (B f ) and symmetrized reference (B sr ) priors. In a completely crossed experimental design we vary lengths of time series (i.e., T = 10, 25, 40, 50 and 100) and autocorrelation (from -0.90 to 0.90 with steps of 0.10). The results show a lowest bias for the B sr , and a lowest variability for r 1 . The power in different conditions is highest for B sr and OLS. For T = 10, the absolute performance of all measurements is poor, as expected. In Study 2, we study robustness of the methods through misspecification by generating the data according to an ARMA(1,1) model, but still analysing the data with an AR(1) model. We use the two methods with the lowest bias for this study, i.e., B sr and MLE. The bias gets larger when the non-modelled moving average parameter becomes larger. Both the variability and power show dependency on the non-modelled parameter. The differences between the two estimation methods are negligible for all measurements.
NASA Astrophysics Data System (ADS)
Gukasyan, A. V.; Koshevoy, E. P.; Kosachev, V. S.
2018-05-01
A comparative analysis of alternative models for plastic flow in extrusive transportation of oil-bearing materials was conducted; the research was directed at determining the function describing the screw core throughput capacity of the press (extruder). Transition from a one-dimensional model to a two-dimensional model significantly improves the mathematical model and allows using two-dimensional rheological models determining the throughput of the screw core.
NASA Technical Reports Server (NTRS)
Triedman, J. K.; Perrott, M. H.; Cohen, R. J.; Saul, J. P.
1995-01-01
Fourier-based techniques are mathematically noncausal and are therefore limited in their application to feedback-containing systems, such as the cardiovascular system. In this study, a mathematically causal time domain technique, autoregressive moving average (ARMA) analysis, was used to parameterize the relations of respiration and arterial blood pressure to heart rate in eight humans before and during total cardiac autonomic blockade. Impulse-response curves thus generated showed the relation of respiration to heart rate to be characterized by an immediate increase in heart rate of 9.1 +/- 1.8 beats.min-1.l-1, followed by a transient mild decrease in heart rate to -1.2 +/- 0.5 beats.min-1.l-1 below baseline. The relation of blood pressure to heart rate was characterized by a slower decrease in heart rate of -0.5 +/- 0.1 beats.min-1.mmHg-1, followed by a gradual return to baseline. Both of these relations nearly disappeared after autonomic blockade, indicating autonomic mediation. Maximum values obtained from the respiration to heart rate impulse responses were also well correlated with frequency domain measures of high-frequency "vagal" heart rate control (r = 0.88). ARMA analysis may be useful as a time domain representation of autonomic heart rate control for cardiovascular modeling.
NASA Astrophysics Data System (ADS)
Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele
2014-04-01
A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.
A two-dimensional kinematic dynamo model of the ionospheric magnetic field at Venus
NASA Technical Reports Server (NTRS)
Cravens, T. E.; Wu, D.; Shinagawa, H.
1990-01-01
The results of a high-resolution, two-dimensional, time dependent, kinematic dynamo model of the ionospheric magnetic field of Venus are presented. Various one-dimensional models are considered and the two-dimensional model is then detailed. In this model, the two-dimensional magnetic induction equation, the magnetic diffusion-convection equation, is numerically solved using specified plasma velocities. Origins of the vertical velocity profile and of the horizontal velocities are discussed. It is argued that the basic features of the vertical magnetic field profile remain unaltered by horizontal flow effects and also that horizontal plasma flow can strongly affect the magnetic field for altitudes above 300 km.
Continuum modeling of three-dimensional truss-like space structures
NASA Technical Reports Server (NTRS)
Nayfeh, A. H.; Hefzy, M. S.
1978-01-01
A mathematical and computational analysis capability has been developed for calculating the effective mechanical properties of three-dimensional periodic truss-like structures. Two models are studied in detail. The first, called the octetruss model, is a three-dimensional extension of a two-dimensional model, and the second is a cubic model. Symmetry considerations are employed as a first step to show that the specific octetruss model has four independent constants and that the cubic model has two. The actual values of these constants are determined by averaging the contributions of each rod element to the overall structure stiffness. The individual rod member contribution to the overall stiffness is obtained by a three-dimensional coordinate transformation. The analysis shows that the effective three-dimensional elastic properties of both models are relatively close to each other.
Current status of one- and two-dimensional numerical models: Successes and limitations
NASA Technical Reports Server (NTRS)
Schwartz, R. J.; Gray, J. L.; Lundstrom, M. S.
1985-01-01
The capabilities of one and two-dimensional numerical solar cell modeling programs (SCAP1D and SCAP2D) are described. The occasions when a two-dimensional model is required are discussed. The application of the models to design, analysis, and prediction are presented along with a discussion of problem areas for solar cell modeling.
A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.
2013-12-18
This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and comparesmore » the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less
NASA Astrophysics Data System (ADS)
Haitjema, Henk M.
1985-10-01
A technique is presented to incorporate three-dimensional flow in a Dupuit-Forchheimer model. The method is based on superposition of approximate analytic solutions to both two- and three-dimensional flow features in a confined aquifer of infinite extent. Three-dimensional solutions are used in the domain of interest, while farfield conditions are represented by two-dimensional solutions. Approximate three- dimensional solutions have been derived for a partially penetrating well and a shallow creek. Each of these solutions satisfies the condition that no flow occurs across the confining layers of the aquifer. Because of this condition, the flow at some distance of a three-dimensional feature becomes nearly horizontal. Consequently, remotely from a three-dimensional feature, its three-dimensional solution is replaced by a corresponding two-dimensional one. The latter solution is trivial as compared to its three-dimensional counterpart, and its use greatly enhances the computational efficiency of the model. As an example, the flow is modeled between a partially penetrating well and a shallow creek that occur in a regional aquifer system.
Concentration data and dimensionality in groundwater models: evaluation using inverse modelling
Barlebo, H.C.; Hill, M.C.; Rosbjerg, D.; Jensen, K.H.
1998-01-01
A three-dimensional inverse groundwater flow and transport model that fits hydraulic-head and concentration data simultaneously using nonlinear regression is presented and applied to a layered sand and silt groundwater system beneath the Grindsted Landfill in Denmark. The aquifer is composed of rather homogeneous hydrogeologic layers. Two issues common to groundwater flow and transport modelling are investigated: 1) The accuracy of simulated concentrations in the case of calibration with head data alone; and 2) The advantages and disadvantages of using a two-dimensional cross-sectional model instead of a three-dimensional model to simulate contaminant transport when the source is at the land surface. Results show that using only hydraulic heads in the nonlinear regression produces a simulated plume that is profoundly different from what is obtained in a calibration using both hydraulic-head and concentration data. The present study provides a well-documented example of the differences that can occur. Representing the system as a two-dimensional cross-section obviously omits some of the system dynamics. It was, however, possible to obtain a simulated plume cross-section that matched the actual plume cross-section well. The two-dimensional model execution times were about a seventh of those for the three-dimensional model, but some difficulties were encountered in representing the spatially variable source concentrations and less precise simulated concentrations were calculated by the two-dimensional model compared to the three-dimensional model. Summed up, the present study indicates that three dimensional modelling using both hydraulic heads and concentrations in the calibration should be preferred in the considered type of transport studies.
Dimensional reduction for a SIR type model
NASA Astrophysics Data System (ADS)
Cahyono, Edi; Soeharyadi, Yudi; Mukhsar
2018-03-01
Epidemic phenomena are often modeled in the form of dynamical systems. Such model has also been used to model spread of rumor, spread of extreme ideology, and dissemination of knowledge. Among the simplest is SIR (susceptible, infected and recovered) model, a model that consists of three compartments, and hence three variables. The variables are functions of time which represent the number of subpopulations, namely suspect, infected and recovery. The sum of the three is assumed to be constant. Hence, the model is actually two dimensional which sits in three-dimensional ambient space. This paper deals with the reduction of a SIR type model into two variables in two-dimensional ambient space to understand the geometry and dynamics better. The dynamics is studied, and the phase portrait is presented. The two dimensional model preserves the equilibrium and the stability. The model has been applied for knowledge dissemination, which has been the interest of knowledge management.
NASA Astrophysics Data System (ADS)
Olekhno, N. A.; Beltukov, Y. M.
2018-05-01
Random impedance networks are widely used as a model to describe plasmon resonances in disordered metal-dielectric nanocomposites. Two-dimensional networks are applied when considering thin films despite the fact that such networks correspond to the two-dimensional electrodynamics [Clerc et al., J. Phys. A 29, 4781 (1996), 10.1088/0305-4470/29/16/006]. In the present work, we propose a model of two-dimensional systems with the three-dimensional Coulomb interaction and show that this model is equivalent to the planar network with long-range capacitive links between distant sites. In the case of a metallic film, we obtain the well-known dispersion of two-dimensional plasmons ω ∝√{k } . We study the evolution of resonances with a decrease in the metal filling factor within the framework of the proposed model. In the subcritical region with the metal filling p lower than the percolation threshold pc, we observe a gap with Lifshitz tails in the spectral density of states (DOS). In the supercritical region p >pc , the DOS demonstrates a crossover between plane-wave two-dimensional plasmons and resonances of finite clusters.
VALIDITY OF A TWO-DIMENSIONAL MODEL FOR VARIABLE-DENSITY HYDRODYNAMIC CIRCULATION
A three-dimensional model of temperatures and currents has been formulated to assist in the analysis and interpretation of the dynamics of stratified lakes. In this model, nonlinear eddy coefficients for viscosity and conductivities are included. A two-dimensional model (one vert...
NASA Astrophysics Data System (ADS)
Zhou, Wenzhen; Gong, Yanjun; Wang, Mingjun; Gong, Lei
2016-10-01
technology. Laser one-dimensional range profile can reflect the characteristics of the target shape and surface material. These techniques were motivated by applications of laser radar to target discrimination in ballistic missile defense. The radar equation of pulse laser about cone is given in this paper. This paper demonstrates the analytical model of laser one-dimensional range profile of cone based on the radar equation of the pulse laser. Simulations results of laser one-dimensional range profiles of some cones are given. Laser one-dimensional range profiles of cone, whose surface material with diffuse lambertian reflectance, is given in this paper. Laser one-dimensional range profiles of cone, whose surface mater with diffuse materials whose retroreflectance can be modeled closely with an exponential term that decays with increasing incidence angles, is given in this paper. Laser one-dimensional range profiles of different pulse width of cone is given in this paper. The influences of surface material, pulse width, attitude on the one-dimensional range are analyzed. The laser two-dimensional range profile is two-dimensional scattering imaging of pulse laser of target. The two-dimensional range profile of roughness target can provide range resolved information. An analytical model of two-dimensional laser range profile of cone is proposed. The simulations of two-dimensional laser range profiles of some cones are given. Laser two-dimensional range profiles of cone, whose surface mater with diffuse lambertian reflectance, is given in this paper. Laser two-dimensional range profiles of cone, whose surface mater with diffuse materials whose retroreflectance can be modeled closely with an exponential term that decays with increasing incidence angles, is given in this paper. The influence of pulse width, surface material on laser two-dimensional range profile is analyzed. Laser one-dimensional range profile and laser two-dimensional range profile are called as laser range profile (LRP).
NASA Astrophysics Data System (ADS)
Kohno, Masanori
2018-05-01
The single-particle spectral properties of the two-dimensional t-J model with next-nearest-neighbor hopping are investigated near the Mott transition by using cluster perturbation theory. The spectral features are interpreted by considering the effects of the next-nearest-neighbor hopping on the shift of the spectral-weight distribution of the two-dimensional t-J model. Various anomalous features observed in hole-doped and electron-doped high-temperature cuprate superconductors are collectively explained in the two-dimensional t-J model with next-nearest-neighbor hopping near the Mott transition.
DOE Office of Scientific and Technical Information (OSTI.GOV)
AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com
A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neuralmore » system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.« less
NASA Astrophysics Data System (ADS)
Farahani, Pooria; Lundberg, Marcus; Karlsson, Hans O.
2013-11-01
The SN2 substitution reactions at phosphorus play a key role in organic and biological processes. Quantum molecular dynamics simulations have been performed to study the prototype reaction Cl-+PH2Cl→ClPH2+Cl-, using one and two-dimensional models. A potential energy surface, showing an energy well for a transition complex, was generated using ab initio electronic structure calculations. The one-dimensional model is essentially reflection free, whereas the more realistic two-dimensional model displays involved resonance structures in the reaction probability. The reaction rate is almost two orders of magnitude smaller for the two-dimensional compared to the one-dimensional model. Energetic errors in the potential energy surface is estimated to affect the rate by only a factor of two. This shows that for these types of reactions it is more important to increase the dimensionality of the modeling than to increase the accuracy of the electronic structure calculation.
Wagner, Chad R.
2007-01-01
The use of one-dimensional hydraulic models currently is the standard method for estimating velocity fields through a bridge opening for scour computations and habitat assessment. Flood-flow contraction through bridge openings, however, is hydrodynamically two dimensional and often three dimensional. Although there is awareness of the utility of two-dimensional models to predict the complex hydraulic conditions at bridge structures, little guidance is available to indicate whether a one- or two-dimensional model will accurately estimate the hydraulic conditions at a bridge site. The U.S. Geological Survey, in cooperation with the North Carolina Department of Transportation, initiated a study in 2004 to compare one- and two-dimensional model results with field measurements at complex riverine and tidal bridges in North Carolina to evaluate the ability of each model to represent field conditions. The field data consisted of discharge and depth-averaged velocity profiles measured with an acoustic Doppler current profiler and surveyed water-surface profiles for two high-flow conditions. For the initial study site (U.S. Highway 13 over the Tar River at Greenville, North Carolina), the water-surface elevations and velocity distributions simulated by the one- and two-dimensional models showed appreciable disparity in the highly sinuous reach upstream from the U.S. Highway 13 bridge. Based on the available data from U.S. Geological Survey streamgaging stations and acoustic Doppler current profiler velocity data, the two-dimensional model more accurately simulated the water-surface elevations and the velocity distributions in the study reach, and contracted-flow magnitudes and direction through the bridge opening. To further compare the results of the one- and two-dimensional models, estimated hydraulic parameters (flow depths, velocities, attack angles, blocked flow width) for measured high-flow conditions were used to predict scour depths at the U.S. Highway 13 bridge by using established methods. Comparisons of pier-scour estimates from both models indicated that the scour estimates from the two-dimensional model were as much as twice the depth of the estimates from the one-dimensional model. These results can be attributed to higher approach velocities and the appreciable flow angles at the piers simulated by the two-dimensional model and verified in the field. Computed flood-frequency estimates of the 10-, 50-, 100-, and 500-year return-period floods on the Tar River at Greenville were also simulated with both the one- and two-dimensional models. The simulated water-surface profiles and velocity fields of the various return-period floods were used to compare the modeling approaches and provide information on what return-period discharges would result in road over-topping and(or) pressure flow. This information is essential in the design of new and replacement structures. The ability to accurately simulate water-surface elevations and velocity magnitudes and distributions at bridge crossings is essential in assuring that bridge plans balance public safety with the most cost-effective design. By compiling pertinent bridge-site characteristics and relating them to the results of several model-comparison studies, the framework for developing guidelines for selecting the most appropriate model for a given bridge site can be accomplished.
NASA Technical Reports Server (NTRS)
Newman, P. A.; Schoeberl, M. R.; Plumb, R. A.
1986-01-01
Calculations of the two-dimensional, species-independent mixing coefficients for two-dimensional chemical models for the troposphere and stratosphere are performed using quasi-geostrophic potential vorticity fluxes and gradients from 4 years of National Meteorological Center data for the four seasons in both hemispheres. Results show that the horizontal mixing coefficient values for the winter lower stratosphere are broadly consistent with those currently employed in two-dimensional models, but the horizontal mixing coefficient values in the northern winter upper stratosphere are much larger than those usually used.
Comparisons between thermodynamic and one-dimensional combustion models of spark-ignition engines
NASA Technical Reports Server (NTRS)
Ramos, J. I.
1986-01-01
Results from a one-dimensional combustion model employing a constant eddy diffusivity and a one-step chemical reaction are compared with those of one-zone and two-zone thermodynamic models to study the flame propagation in a spark-ignition engine. One-dimensional model predictions are found to be very sensitive to the eddy diffusivity and reaction rate data. The average mixing temperature found using the one-zone thermodynamic model is higher than those of the two-zone and one-dimensional models during the compression stroke, and that of the one-dimensional model is higher than those predicted by both thermodynamic models during the expansion stroke. The one-dimensional model is shown to predict an accelerating flame even when the front approaches the cold cylinder wall.
Simulation of chemical-vapor-deposited silicon carbide for a cold wall vertical reactor
NASA Astrophysics Data System (ADS)
Lee, Y. L.; Sanchez, J. M.
1997-07-01
The growth rate of silicon carbide obtained by low-pressure chemical vapor deposition from tetramethylsilane is numerically simulated for a cold wall vertical reactor. The transport equations for momentum, heat, and mass transfer are simultaneously solved by employing the finite volume method. A model for reaction rate is also proposed in order to predict the measured growth rates [A. Figueras, S. Garelik, J. Santiso, R. Rodroguez-Clemente, B. Armas, C. Combescure, R. Berjoan, J.M. Saurel and R. Caplain, Mater. Sci. Eng. B 11 (1992) 83]. Finally, the effects of thermal diffusion on the growth rate are investigated.
Optimum Multisensor, Multitarget Localization and Tracking.
1983-06-07
parameter vector t is given by (see Equation (3.5.1-7)’ the simul- taneous solution of A(e) N B G --1 ae &j’ -4n-in (fk’ ijn k3jn ~ k )kjn kjn - knn =1 k...the coefficient of mutual dependence given by M = 12 -(K-2) 121M12 :(3l 11J12 ) (K-2 and Jij is given by (see Equation (6.4.1-2)) - - (_ I R knN kn K...Transactions on Acoustic, Speech and Signal Processing, Vol ASSP-29, No. 3, June 1981. 17. B. Friedlander, "An ARMA Modeling Approach to Multitarget Tracking
An Illustration of Generalised Arma (garma) Time Series Modeling of Forest Area in Malaysia
NASA Astrophysics Data System (ADS)
Pillai, Thulasyammal Ramiah; Shitan, Mahendran
Forestry is the art and science of managing forests, tree plantations, and related natural resources. The main goal of forestry is to create and implement systems that allow forests to continue a sustainable provision of environmental supplies and services. Forest area is land under natural or planted stands of trees, whether productive or not. Forest area of Malaysia has been observed over the years and it can be modeled using time series models. A new class of GARMA models have been introduced in the time series literature to reveal some hidden features in time series data. For these models to be used widely in practice, we illustrate the fitting of GARMA (1, 1; 1, δ) model to the Annual Forest Area data of Malaysia which has been observed from 1987 to 2008. The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation.
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
A note on two-dimensional asymptotic magnetotail equilibria
NASA Technical Reports Server (NTRS)
Voigt, Gerd-Hannes; Moore, Brian D.
1994-01-01
In order to understand, on the fluid level, the structure, the time evolution, and the stability of current sheets, such as the magnetotail plasma sheet in Earth's magnetosphere, one has to consider magnetic field configurations that are in magnetohydrodynamic (MHD) force equilibrium. Any reasonable MHD current sheet model has to be two-dimensional, at least in an asymptotic sense (B(sub z)/B (sub x)) = epsilon much less than 1. The necessary two-dimensionality is described by a rather arbitrary function f(x). We utilize the free function f(x) to construct two-dimensional magnetotail equilibria are 'equivalent' to current sheets in empirical three-dimensional models. We obtain a class of asymptotic magnetotail equilibria ordered with respect to the magnetic disturbance index Kp. For low Kp values the two-dimensional MHD equilibria reflect some of the realistic, observation-based, aspects of three-dimensional models. For high Kp values the three-dimensional models do not fit the asymptotic MHD equlibria, which is indicative of their inconsistency with the assumed pressure function. This, in turn, implies that high magnetic activity levels of the real magnetosphere might be ruled by thermodynamic conditions different from local thermodynamic equilibrium.
NASA Astrophysics Data System (ADS)
Jiao, Huiqing; Zhao, Chengyi; Sheng, Yu; Chen, Yan; Shi, Jianchu; Li, Baoguo
2017-04-01
Water shortage and soil salinization increasingly become the main constraints for sustainable development of agriculture in Southern Xinjiang, China. Mulched drip irrigation, as a high-efficient water-saving irrigation method, has been widely applied in Southern Xinjiang for cotton production. In order to analyze the reasonability of describing the three-dimensional soil water and salt transport processes under mulched drip irrigation with a relatively simple two-dimensional model, a field experiment was conducted from 2007 to 2015 at Aksu of Southern Xinjiang, and soil water and salt transport processes were simulated through the three-dimensional and two-dimensional models based on COMSOL. Obvious differences were found between three-dimensional and two-dimensional simulations for soil water flow within the early 12 h of irrigation event and for soil salt transport in the area within 15 cm away from drip tubes during the whole irrigation event. The soil water and salt contents simulated by the two-dimensional model, however, agreed well with the mean values between two adjacent emitters simulated by the three-dimensional model, and also coincided with the measurements as corresponding RMSE less than 0.037 cm3 cm-3 and 1.80 g kg-1, indicating that the two-dimensional model was reliable for field irrigation management. Subsequently, the two-dimensional model was applied to simulate the dynamics of soil salinity for five numerical situations and for a widely adopted irrigation pattern in Southern Xinjiang (about 350 mm through mulched drip irrigation during growing season of cotton and total 400 mm through flooding irrigations before sowing and after harvesting). The simulation results indicated that the contribution of transpiration to salt accumulation in root layer was about 75% under mulched drip irrigation. Moreover, flooding irrigations before sowing and after harvesting were of great importance for salt leaching of arable layer, especially in bare strip where drip irrigation water hardly reached, and thus providing suitable root zone environment for cotton. Nevertheless, flooding irrigation should be further optimized to enhance water use efficiency.
Design of a compensation for an ARMA model of a discrete time system. M.S. Thesis
NASA Technical Reports Server (NTRS)
Mainemer, C. I.
1978-01-01
The design of an optimal dynamic compensator for a multivariable discrete time system is studied. Also the design of compensators to achieve minimum variance control strategies for single input single output systems is analyzed. In the first problem the initial conditions of the plant are random variables with known first and second order moments, and the cost is the expected value of the standard cost, quadratic in the states and controls. The compensator is based on the minimum order Luenberger observer and it is found optimally by minimizing a performance index. Necessary and sufficient conditions for optimality of the compensator are derived. The second problem is solved in three different ways; two of them working directly in the frequency domain and one working in the time domain. The first and second order moments of the initial conditions are irrelevant to the solution. Necessary and sufficient conditions are derived for the compensator to minimize the variance of the output.
Two-dimensional signal processing with application to image restoration
NASA Technical Reports Server (NTRS)
Assefi, T.
1974-01-01
A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.
[Rapid prototyping: a very promising method].
Haverman, T M; Karagozoglu, K H; Prins, H-J; Schulten, E A J M; Forouzanfar, T
2013-03-01
Rapid prototyping is a method which makes it possible to produce a three-dimensional model based on two-dimensional imaging. Various rapid prototyping methods are available for modelling, such as stereolithography, selective laser sintering, direct laser metal sintering, two-photon polymerization, laminated object manufacturing, three-dimensional printing, three-dimensional plotting, polyjet inkjet technology,fused deposition modelling, vacuum casting and milling. The various methods currently being used in the biomedical sector differ in production, materials and properties of the three-dimensional model which is produced. Rapid prototyping is mainly usedforpreoperative planning, simulation, education, and research into and development of bioengineering possibilities.
NASA Astrophysics Data System (ADS)
Tobiska, W. Kent; Bouwer, D.; Smart, D.; Shea, M.; Bailey, J.; Didkovsky, L.; Judge, K.; Garrett, H.; Atwell, W.; Gersey, B.; Wilkins, R.; Rice, D.; Schunk, R.; Bell, D.; Mertens, C.; Xu, X.; Wiltberger, M.; Wiley, S.; Teets, E.; Jones, B.; Hong, S.; Yoon, K.
2016-11-01
The Automated Radiation Measurements for Aerospace Safety (ARMAS) program has successfully deployed a fleet of six instruments measuring the ambient radiation environment at commercial aircraft altitudes. ARMAS transmits real-time data to the ground and provides quality, tissue-relevant ambient dose equivalent rates with 5 min latency for dose rates on 213 flights up to 17.3 km (56,700 ft). We show five cases from different aircraft; the source particles are dominated by galactic cosmic rays but include particle fluxes for minor radiation periods and geomagnetically disturbed conditions. The measurements from 2013 to 2016 do not cover a period of time to quantify galactic cosmic rays' dependence on solar cycle variation and their effect on aviation radiation. However, we report on small radiation "clouds" in specific magnetic latitude regions and note that active geomagnetic, variable space weather conditions may sufficiently modify the magnetospheric magnetic field that can enhance the radiation environment, particularly at high altitudes and middle to high latitudes. When there is no significant space weather, high-latitude flights produce a dose rate analogous to a chest X-ray every 12.5 h, every 25 h for midlatitudes, and every 100 h for equatorial latitudes at typical commercial flight altitudes of 37,000 ft ( 11 km). The dose rate doubles every 2 km altitude increase, suggesting a radiation event management strategy for pilots or air traffic control; i.e., where event-driven radiation regions can be identified, they can be treated like volcanic ash clouds to achieve radiation safety goals with slightly lower flight altitudes or more equatorial flight paths.
Two-dimensional lattice Boltzmann model for magnetohydrodynamics.
Schaffenberger, Werner; Hanslmeier, Arnold
2002-10-01
We present a lattice Boltzmann model for the simulation of two-dimensional magnetohydro dynamic (MHD) flows. The model is an extension of a hydrodynamic lattice Boltzman model with 9 velocities on a square lattice resulting in a model with 17 velocities. Earlier lattice Boltzmann models for two-dimensional MHD used a bidirectional streaming rule. However, the use of such a bidirectional streaming rule is not necessary. In our model, the standard streaming rule is used, allowing smaller viscosities. To control the viscosity and the resistivity independently, a matrix collision operator is used. The model is then applied to the Hartmann flow, giving reasonable results.
Identification of PARMA Models and Their Application to the Modeling of River flows
NASA Astrophysics Data System (ADS)
Tesfaye, Y. G.; Meerschaert, M. M.; Anderson, P. L.
2004-05-01
The generation of synthetic river flow samples that can reproduce the essential statistical features of historical river flows is essential to the planning, design and operation of water resource systems. Most river flow series are periodically stationary; that is, their mean and covariance functions are periodic with respect to time. We employ a periodic ARMA (PARMA) model. The innovation algorithm can be used to obtain parameter estimates for PARMA models with finite fourth moment as well as infinite fourth moment but finite variance. Anderson and Meerschaert (2003) provide a method for model identification when the time series has finite fourth moment. This article, an extension of the previous work by Anderson and Meerschaert, demonstrates the effectiveness of the technique using simulated data. An application to monthly flow data for the Frazier River in British Columbia is also included to illustrate the use of these methods.
Particle orbits in two-dimensional equilibrium models for the magnetotail
NASA Technical Reports Server (NTRS)
Karimabadi, H.; Pritchett, P. L.; Coroniti, F. V.
1990-01-01
Assuming that there exist an equilibrium state for the magnetotail, particle orbits are investigated in two-dimensional kinetic equilibrium models for the magnetotail. Particle orbits in the equilibrium field are compared with those calculated earlier with one-dimensional models, where the main component of the magnetic field (Bx) was approximated as either a hyperbolic tangent or a linear function of z with the normal field (Bz) assumed to be a constant. It was found that the particle orbits calculated with the two types of models are significantly different, mainly due to the neglect of the variation of Bx with x in the one-dimensional fields.
NASA Astrophysics Data System (ADS)
Lima, L. S.
2018-06-01
We study the effect of Dzyaloshisnkii-Moriya interaction on spin transport in the two and three-dimensional Heisenberg antiferromagnetic models in the square lattice and cubic lattice respectively. For the three-dimensional model, we obtain a large peak for the spin conductivity and therefore a finite AC conductivity. For the two-dimensional model, we have gotten the AC spin conductivity tending to the infinity at ω → 0 limit and a suave decreasing in the spin conductivity with increase of ω. We obtain a small influence of the Dzyaloshinskii-Moriya interaction on the spin conductivity in all cases analyzed.
Analysis Monthly Import of Palm Oil Products Using Box-Jenkins Model
NASA Astrophysics Data System (ADS)
Ahmad, Nurul F. Y.; Khalid, Kamil; Saifullah Rusiman, Mohd; Ghazali Kamardan, M.; Roslan, Rozaini; Che-Him, Norziha
2018-04-01
The palm oil industry has been an important component of the national economy especially the agriculture sector. The aim of this study is to identify the pattern of import of palm oil products, to model the time series using Box-Jenkins model and to forecast the monthly import of palm oil products. The method approach is included in the statistical test for verifying the equivalence model and statistical measurement of three models, namely Autoregressive (AR) model, Moving Average (MA) model and Autoregressive Moving Average (ARMA) model. The model identification of all product import palm oil is different in which the AR(1) was found to be the best model for product import palm oil while MA(3) was found to be the best model for products import palm kernel oil. For the palm kernel, MA(4) was found to be the best model. The results forecast for the next four months for products import palm oil, palm kernel oil and palm kernel showed the most significant decrease compared to the actual data.
Guo, Yi; Liu, Chen-Xi; Zhang, Li-Sheng; Wang, Meng-Qing; Chen, Hong-Yin
2017-12-01
Insects cannot synthesize sterols and must obtain them from plants. Therefore, reducing plant sterol content or changing sterol type might be an effective pest control strategy. However, the impacts of these changes on pests' natural predators remain unknown. Here, we fed artificial diets with reduced sterol content to Mythimna separata (Walker) (Lepidoptera: Noctuidae) and investigated the effects on its natural predator, Arma chinensis (Fallou) (Hemiptera: Pentatomidae). Reduced sterol content in M. separata (MS1, MS2, and MS5) was achieved by feeding them artificial diets prepared from a feed base subjected to one, two, or five cycles of sterol extractions, respectively. The content of most substances increased in A. chinensis (AC) groups feeding on MS2 and MS5. The content of eight substances (alanine, betaine, dimethylamine, fumarate, glutamine, glycine, methylamine, and sarcosine) differed significantly between the control (AC0) and treated (AC1, AC2, and AC5) groups. Metabolic profiling revealed that only AC5 was significantly distinct from AC0; the major substances contributing to this difference were maltose, glucose, tyrosine, proline, O-phosphocholine, glutamine, allantoin, lysine, valine, and glutamate. Furthermore, only two metabolic pathways, that is, nicotinate and nicotinamide metabolism and ubiquinone and other terpenoid-quinone biosynthesis, differed significantly between AC1 and AC5 and the control, albeit with an impact value of zero. Thus, the sterol content in the artificial diet fed to M. separata only minimally affected the metabolites and metabolic pathways of its predator A. chinensis, suggesting that A. chinensis has good metabolic self-regulation with high resistance to sterol content changes. © 2017 Wiley Periodicals, Inc.
Strongly magnetized classical plasma models
NASA Technical Reports Server (NTRS)
Montgomery, D. C.
1972-01-01
The class of plasma processes for which the so-called Vlasov approximation is inadequate is investigated. Results from the equilibrium statistical mechanics of two-dimensional plasmas are derived. These results are independent of the presence of an external dc magnetic field. The nonequilibrium statistical mechanics of the electrostatic guiding-center plasma, a two-dimensional plasma model, is discussed. This model is then generalized to three dimensions. The guiding-center model is relaxed to include finite Larmor radius effects for a two-dimensional plasma.
Two-Dimensional Versus Three-Dimensional Conceptualization in Astronomy Education
NASA Astrophysics Data System (ADS)
Reynolds, Michael David
Numerous science conceptual issues are naturally three-dimensional. Classroom presentations are often two -dimensional or at best multidimensional. Several astronomy topics are of this nature, e. g. mechanics of the phases of the moon. Textbooks present this three-dimensional topic in two-dimensions; such is often the case in the classroom. This study was conducted to examine conceptions exhibited by pairs of like-sex 11th grade standard physics students as they modeled the lunar phases. Student pairs, 13 male and 13 female, were randomly selected and assigned. Pairing comes closer to classroom emulation, minimizes needs for direct probes, and pair discussion is more likely to display variety and depth. Four hypotheses were addressed: (1) Participants who model three-dimensionally will more likely achieve a higher explanation score. (2) Students who experienced more earth or physical science exposure will more likely model three-dimensionally. (3) Pairs that exhibit a strong science or mathematics preference will more likely model three-dimensionally. (4) Males will model in three dimensions more than females. Students provided background information, including science course exposure and subject preference. Each pair laid out a 16-card set representing two complete lunar phase changes. The pair was asked to explain why the phases occur. Materials were provided for use, including disks, spheres, paper and pen, and flashlight. Activities were videotaped for later evaluation. Statistics of choice was a correlation determination between course preference and model type and ANOVA for the other hypotheses. It was determined that pairs who modeled three -dimensionally achieved a higher score on their phases mechanics explanation at p <.05 level. Pairs with earth science or physical science exposure, those who prefer science or mathematics, and male participants were not more likely to model three-dimensionally. Possible reasons for lack of significance was small sample size and in the case of course preferences, small differences in course preference means. Based on this study, instructors should be aware of dimensionality and student misconceptions. Whenever possible, three-dimensional concepts should be modeled as such. Authors and publishers should consider modeling suggestions and three-dimensional ancillaries.
NASA Astrophysics Data System (ADS)
Brenner, Konstantin; Hennicker, Julian; Masson, Roland; Samier, Pierre
2018-03-01
In this work, we extend, to two-phase flow, the single-phase Darcy flow model proposed in [26], [12] in which the (d - 1)-dimensional flow in the fractures is coupled with the d-dimensional flow in the matrix. Three types of so called hybrid-dimensional two-phase Darcy flow models are proposed. They all account for fractures acting either as drains or as barriers, since they allow pressure jumps at the matrix-fracture interfaces. The models also permit to treat gravity dominated flow as well as discontinuous capillary pressure at the material interfaces. The three models differ by their transmission conditions at matrix fracture interfaces: while the first model accounts for the nonlinear two-phase Darcy flux conservations, the second and third ones are based on the linear single phase Darcy flux conservations combined with different approximations of the mobilities. We adapt the Vertex Approximate Gradient (VAG) scheme to this problem, in order to account for anisotropy and heterogeneity aspects as well as for applicability on general meshes. Several test cases are presented to compare our hybrid-dimensional models to the generic equi-dimensional model, in which fractures have the same dimension as the matrix, leading to deep insight about the quality of the proposed reduced models.
Mixing Regimes in a Spatially Confined, Two-Dimensional, Supersonic Shear Layer
1992-07-31
MODEL ................................... 3 THE MODEL PROBLEMS .............................................. 6 THE ONE-DIMENSIONAL PROBLEM...the effects of the numerical diffusion on the spectrum. Guirguis et al.ś and Farouk et al."’ have studied spatially evolving mixing layers for equal...approximations. Physical and Numerical Model General Formulation We solve the time-dependent, two-dimensional, compressible, Navier-Stokes equations for a
Are Young Children's Drawings Canonically Biased?
ERIC Educational Resources Information Center
Picard, Delphine; Durand, Karine
2005-01-01
In a between-subjects design, 4-to 6-year-olds were asked to draw from three-dimensional (3D) models, two-and-a-half-dimensional (212D) models with or without depth cues, or two-dimensional (2D) models of a familiar object (a saucepan) in noncanonical orientations (handle at the back or at the front). Results showed that canonical errors were…
Thermal signature identification system (TheSIS): a spread spectrum temperature cycling method
NASA Astrophysics Data System (ADS)
Merritt, Scott
2015-03-01
NASA GSFC's Thermal Signature Identification System (TheSIS) 1) measures the high order dynamic responses of optoelectronic components to direct sequence spread-spectrum temperature cycling, 2) estimates the parameters of multiple autoregressive moving average (ARMA) or other models the of the responses, 3) and selects the most appropriate model using the Akaike Information Criterion (AIC). Using the AIC-tested model and parameter vectors from TheSIS, one can 1) select high-performing components on a multivariate basis, i.e., with multivariate Figures of Merit (FOMs), 2) detect subtle reversible shifts in performance, and 3) investigate irreversible changes in component or subsystem performance, e.g. aging. We show examples of the TheSIS methodology for passive and active components and systems, e.g. fiber Bragg gratings (FBGs) and DFB lasers with coupled temperature control loops, respectively.
Discrete-to-continuum modelling of weakly interacting incommensurate two-dimensional lattices.
Español, Malena I; Golovaty, Dmitry; Wilber, J Patrick
2018-01-01
In this paper, we derive a continuum variational model for a two-dimensional deformable lattice of atoms interacting with a two-dimensional rigid lattice. The starting point is a discrete atomistic model for the two lattices which are assumed to have slightly different lattice parameters and, possibly, a small relative rotation. This is a prototypical example of a three-dimensional system consisting of a graphene sheet suspended over a substrate. We use a discrete-to-continuum procedure to obtain the continuum model which recovers both qualitatively and quantitatively the behaviour observed in the corresponding discrete model. The continuum model predicts that the deformable lattice develops a network of domain walls characterized by large shearing, stretching and bending deformation that accommodates the misalignment and/or mismatch between the deformable and rigid lattices. Two integer-valued parameters, which can be identified with the components of a Burgers vector, describe the mismatch between the lattices and determine the geometry and the details of the deformation associated with the domain walls.
NASA Astrophysics Data System (ADS)
Golinski, M. R.
2006-07-01
Ecologists have observed that environmental noise affects population variance in the logistic equation for one-species growth. Interactions between deterministic and stochastic dynamics in a one-dimensional system result in increased variance in species population density over time. Since natural populations do not live in isolation, the present paper simulates a discrete-time two-species competition model with environmental noise to determine the type of colored population noise generated by extreme conditions in the long-term population dynamics of competing populations. Discrete Fourier analysis is applied to the simulation results and the calculated Hurst exponent ( H) is used to determine how the color of population noise for the two species corresponds to extreme conditions in population dynamics. To interpret the biological meaning of the color of noise generated by the two-species model, the paper determines the color of noise generated by three reference models: (1) A two-dimensional discrete-time white noise model (0⩽ H<1/2); (2) A two-dimensional fractional Brownian motion model (H=1/2); and (3) A two-dimensional discrete-time model with noise for unbounded growth of two uncoupled species (1/2< H⩽1).
Dynamic colloidal assembly pathways via low dimensional models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu; Thyagarajan, Raghuram
2016-05-28
Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterizedmore » by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.« less
Evaluation of a two-dimensional numerical model for air quality simulation in a street canyon
NASA Astrophysics Data System (ADS)
Okamoto, Shin `Ichi; Lin, Fu Chi; Yamada, Hiroaki; Shiozawa, Kiyoshige
For many urban areas, the most severe air pollution caused by automobile emissions appears along a road surrounded by tall buildings: the so=called street canyon. A practical two-dimensional numerical model has been developed to be applied to this kind of road structure. This model contains two submodels: a wind-field model and a diffusion model based on a Monte Carlo particle scheme. In order to evaluate the predictive performance of this model, an air quality simulation was carried out at three trunk roads in the Tokyo metropolitan area: Nishi-Shimbashi, Aoyama and Kanda-Nishikicho (using SF 6 as a tracer and NO x measurement). Since this model has two-dimensional properties and cannot be used for the parallel wind condition, the perpendicular wind condition was selected for the simulation. The correlation coefficients for the SF 6 and NO x data in Aoyama were 0.67 and 0.62, respectively. When predictive performance of this model is compared with other models, this model is comparable to the SRI model, and superior to the APPS three-dimensional numerical model.
Lee, Chen-Hsiang; Liu, Jien-Wei; Li, Chia-Chin; Chien, Chun-Chih; Tang, Ya-Fen; Su, Lin-Hui
2011-09-01
Increasing resistance to quinolones, aminoglycosides, and/or cephamycins in extended-spectrum-β-lactamase (ESBL)-producing Enterobacteriaceae exacerbates the already limited antibiotic treatment options for infections due to these microbes. In this study, the presence of resistance determinants for these antimicrobial agents was examined by PCR among ESBL-producing Klebsiella pneumoniae (ESBL-KP) isolates that caused bacteremia. Pulsed-field gel electrophoresis was used to differentiate the clonal relationship among the isolates studied. Transferability and the location of the resistance genes were analyzed by conjugation experiments, followed by DNA-DNA hybridization. Among the 94 ESBL-KP isolates studied, 20 isolates of flomoxef-resistant ESBL-KP were identified. They all carried a DHA-1 gene and were genetically diverse. CTX-M genes were found in 18 of the isolates. Among these DHA-1/CTX-M-producing K. pneumoniae isolates, ISCR1 was detected in 13 (72%) isolates, qnr genes (1 qnrA and 17 qnrB genes) were detected in 18 (100%), aac(6')-Ib-cr was detected in 11 (61%), and 16S rRNA methylase (all armA genes) was detected in 14 (78%). Four transconjugants were available for further analysis, and qnrB4, aac(6')-Ib-cr, armA, and bla(DHA-1) were all identified on these self-transferable bla(CTX-M)-carrying plasmids. The genetic environments of ISCR1 associated with armA, bla(DHA-1), and qnrB4 genes in the four transconjugants were identical. Replicon-type analysis revealed a FIIA plasmid among the four self-transferable plasmids, although the other three were nontypeable. The cotransfer of multiple resistance genes with the ISCR1 element-carrying plasmids has a clinical impact and warrants close monitoring and further study.
One-dimensional GIS-based model compared with a two-dimensional model in urban floods simulation.
Lhomme, J; Bouvier, C; Mignot, E; Paquier, A
2006-01-01
A GIS-based one-dimensional flood simulation model is presented and applied to the centre of the city of Nîmes (Gard, France), for mapping flow depths or velocities in the streets network. The geometry of the one-dimensional elements is derived from the Digital Elevation Model (DEM). The flow is routed from one element to the next using the kinematic wave approximation. At the crossroads, the flows in the downstream branches are computed using a conceptual scheme. This scheme was previously designed to fit Y-shaped pipes junctions, and has been modified here to fit X-shaped crossroads. The results were compared with the results of a two-dimensional hydrodynamic model based on the full shallow water equations. The comparison shows that good agreements can be found in the steepest streets of the study zone, but differences may be important in the other streets. Some reasons that can explain the differences between the two models are given and some research possibilities are proposed.
(2 + 1)-dimensional interacting model of two massless spin-2 fields as a bi-gravity model
NASA Astrophysics Data System (ADS)
Hoseinzadeh, S.; Rezaei-Aghdam, A.
2018-06-01
We propose a new group-theoretical (Chern-Simons) formulation for the bi-metric theory of gravity in (2 + 1)-dimensional spacetime which describe two interacting massless spin-2 fields. Our model has been formulated in terms of two dreibeins rather than two metrics. We obtain our Chern-Simons gravity model by gauging mixed AdS-AdS Lie algebra and show that it has a two dimensional conformal field theory (CFT) at the boundary of the anti de Sitter (AdS) solution. We show that the central charge of the dual CFT is proportional to the mass of the AdS solution. We also study cosmological implications of our massless bi-gravity model.
Hypersonic Combustor Model Inlet CFD Simulations and Experimental Comparisons
NASA Technical Reports Server (NTRS)
Venkatapathy, E.; TokarcikPolsky, S.; Deiwert, G. S.; Edwards, Thomas A. (Technical Monitor)
1995-01-01
Numerous two-and three-dimensional computational simulations were performed for the inlet associated with the combustor model for the hypersonic propulsion experiment in the NASA Ames 16-Inch Shock Tunnel. The inlet was designed to produce a combustor-inlet flow that is nearly two-dimensional and of sufficient mass flow rate for large scale combustor testing. The three-dimensional simulations demonstrated that the inlet design met all the design objectives and that the inlet produced a very nearly two-dimensional combustor inflow profile. Numerous two-dimensional simulations were performed with various levels of approximations such as in the choice of chemical and physical models, as well as numerical approximations. Parametric studies were conducted to better understand and to characterize the inlet flow. Results from the two-and three-dimensional simulations were used to predict the mass flux entering the combustor and a mass flux correlation as a function of facility stagnation pressure was developed. Surface heat flux and pressure measurements were compared with the computed results and good agreement was found. The computational simulations helped determine the inlet low characteristics in the high enthalpy environment, the important parameters that affect the combustor-inlet flow, and the sensitivity of the inlet flow to various modeling assumptions.
Westerman, Drew A.; Clark, Brian R.
2013-01-01
The results from the precipitation-runoff hydrologic model, the one-dimensional unsteady-state hydraulic model, and a separate two-dimensional model developed as part of a coincident study, each complement the other in terms of streamflow timing, water-surface elevations, and velocities propagated by the June 11, 2010, flood event. The simulated grids for water depth and stream velocity from each model were directly compared by subtracting the one-dimensional hydraulic model grid from the two-dimensional model grid. The absolute mean difference for the simulated water depth was 0.9 foot. Additionally, the absolute mean difference for the simulated stream velocity was 1.9 feet per second.
2013-04-30
resulting impact on residents and transportation infrastructure. The three-dimensional coastal ocean model FVCOM coupled with a two-dimensional...shallow water model is used to simulate hydrodynamic flooding from coastal ocean water with fine-resolution meshes, and a topography-based hydrologic... ocean model FVCOM coupled with a two-dimensional shallow water model is used to simulate hydrodynamic flooding from coastal ocean water with fine
Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models
NASA Astrophysics Data System (ADS)
Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini
2014-12-01
The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the choice of the wavelets in multiscale model evaluation. It was found that the proposed wavelet-based performance measures, namely the MNSC (Multiscale Nash-Sutcliffe Criteria) and MNRMSE (Multiscale Normalized Root Mean Square Error), are a more reliable measure than traditional performance measures such as the Nash-Sutcliffe Criteria (NSC), Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). Further, the proposed methodology can be used to: i) compare different hydrological models (both physical and statistical models), and ii) help in model calibration.
Teaching "Filing Rules"--Via Computer-Aided Instruction.
ERIC Educational Resources Information Center
Agneberg, Craig
A computer software package has been developed to teach and test students on the Rules for Alphabetical Filing of the Association of Records Managers and Administrators (ARMA). The following computer assisted instruction principles were used in developing the program: gaining attention, stating objectives, providing direction, reviewing…
37. Closeup of stairs in previous photo, leading up to ...
37. Close-up of stairs in previous photo, leading up to El Macho and down to Plaza de Armas, from Santa Barbara Bastion, viewed from northwest - Castillo de San Felipe del Morro, Northwest end of San Juan, San Juan, San Juan Municipio, PR
23. General view of the top gundeck looking northwest from ...
23. General view of the top gundeck looking northwest from Austria Bastion showing ramp down and parapet wall of the Plaza de Armas on lower level - Castillo de San Felipe del Morro, Northwest end of San Juan, San Juan, San Juan Municipio, PR
FireStem2D A two-dimensional heat transfer model for simulating tree stem injury in fires
Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson
2013-01-01
FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...
Topology of large-scale structure. IV - Topology in two dimensions
NASA Technical Reports Server (NTRS)
Melott, Adrian L.; Cohen, Alexander P.; Hamilton, Andrew J. S.; Gott, J. Richard, III; Weinberg, David H.
1989-01-01
In a recent series of papers, an algorithm was developed for quantitatively measuring the topology of the large-scale structure of the universe and this algorithm was applied to numerical models and to three-dimensional observational data sets. In this paper, it is shown that topological information can be derived from a two-dimensional cross section of a density field, and analytic expressions are given for a Gaussian random field. The application of a two-dimensional numerical algorithm for measuring topology to cross sections of three-dimensional models is demonstrated.
Model of a Negatively Curved Two-Dimensional Space.
ERIC Educational Resources Information Center
Eckroth, Charles A.
1995-01-01
Describes the construction of models of two-dimensional surfaces with negative curvature that are used to illustrate differences in the triangle sum rule for the various Big Bang Theories of the universe. (JRH)
Teaching Science: Eclipse Seasons.
ERIC Educational Resources Information Center
Leyden, Michael B.
1995-01-01
Demonstrates the need for a three-dimensional model as an aid for teaching students why eclipses do not occur every two weeks, as falsely indicated by two-dimensional models such as books, chalkboards, and computer screens. Describes procedure to construct the model. Indicates question related to seasons likely to arise from such a model and…
On the role of radiation and dimensionality in predicting flow opposed flame spread over thin fuels
NASA Astrophysics Data System (ADS)
Kumar, Chenthil; Kumar, Amit
2012-06-01
In this work a flame-spread model is formulated in three dimensions to simulate opposed flow flame spread over thin solid fuels. The flame-spread model is coupled to a three-dimensional gas radiation model. The experiments [1] on downward spread and zero gravity quiescent spread over finite width thin fuel are simulated by flame-spread models in both two and three dimensions to assess the role of radiation and effect of dimensionality on the prediction of the flame-spread phenomena. It is observed that while radiation plays only a minor role in normal gravity downward spread, in zero gravity quiescent spread surface radiation loss holds the key to correct prediction of low oxygen flame spread rate and quenching limit. The present three-dimensional simulations show that even in zero gravity gas radiation affects flame spread rate only moderately (as much as 20% at 100% oxygen) as the heat feedback effect exceeds the radiation loss effect only moderately. However, the two-dimensional model with the gas radiation model badly over-predicts the zero gravity flame spread rate due to under estimation of gas radiation loss to the ambient surrounding. The two-dimensional model was also found to be inadequate for predicting the zero gravity flame attributes, like the flame length and the flame width, correctly. The need for a three-dimensional model was found to be indispensable for consistently describing the zero gravity flame-spread experiments [1] (including flame spread rate and flame size) especially at high oxygen levels (>30%). On the other hand it was observed that for the normal gravity downward flame spread for oxygen levels up to 60%, the two-dimensional model was sufficient to predict flame spread rate and flame size reasonably well. Gas radiation is seen to increase the three-dimensional effect especially at elevated oxygen levels (>30% for zero gravity and >60% for normal gravity flames).
Two dimensional analytical model for a reconfigurable field effect transistor
NASA Astrophysics Data System (ADS)
Ranjith, R.; Jayachandran, Remya; Suja, K. J.; Komaragiri, Rama S.
2018-02-01
This paper presents two-dimensional potential and current models for a reconfigurable field effect transistor (RFET). Two potential models which describe subthreshold and above-threshold channel potentials are developed by solving two-dimensional (2D) Poisson's equation. In the first potential model, 2D Poisson's equation is solved by considering constant/zero charge density in the channel region of the device to get the subthreshold potential characteristics. In the second model, accumulation charge density is considered to get above-threshold potential characteristics of the device. The proposed models are applicable for the device having lightly doped or intrinsic channel. While obtaining the mathematical model, whole body area is divided into two regions: gated region and un-gated region. The analytical models are compared with technology computer-aided design (TCAD) simulation results and are in complete agreement for different lengths of the gated regions as well as at various supply voltage levels.
Lee, Jonathan K.; Froehlich, David C.
1987-01-01
Published literature on the application of the finite-element method to solving the equations of two-dimensional surface-water flow in the horizontal plane is reviewed in this report. The finite-element method is ideally suited to modeling two-dimensional flow over complex topography with spatially variable resistance. A two-dimensional finite-element surface-water flow model with depth and vertically averaged velocity components as dependent variables allows the user great flexibility in defining geometric features such as the boundaries of a water body, channels, islands, dikes, and embankments. The following topics are reviewed in this report: alternative formulations of the equations of two-dimensional surface-water flow in the horizontal plane; basic concepts of the finite-element method; discretization of the flow domain and representation of the dependent flow variables; treatment of boundary conditions; discretization of the time domain; methods for modeling bottom, surface, and lateral stresses; approaches to solving systems of nonlinear equations; techniques for solving systems of linear equations; finite-element alternatives to Galerkin's method of weighted residuals; techniques of model validation; and preparation of model input data. References are listed in the final chapter.
Deep learning architecture for air quality predictions.
Li, Xiang; Peng, Ling; Hu, Yuan; Shao, Jing; Chi, Tianhe
2016-11-01
With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.
Thermoelastic damping in thin microrings with two-dimensional heat conduction
NASA Astrophysics Data System (ADS)
Fang, Yuming; Li, Pu
2015-05-01
Accurate determination of thermoelastic damping (TED) is very challenging in the design of micro-resonators. Microrings are widely used in many micro-resonators. In the past, to model the TED effect on the microrings, some analytical models have been developed. However, in the previous works, the heat conduction within the microring is modeled by using the one-dimensional approach. The governing equation for heat conduction is solved only for the one-dimensional heat conduction along the radial thickness of the microring. This paper presents a simple analytical model for TED in microrings. The two-dimensional heat conduction over the thermoelastic temperature gradients along the radial thickness and the circumferential direction are considered in the present model. A two-dimensional heat conduction equation is developed. The solution of the equation is represented by the product of an assumed sine series along the radial thickness and an assumed trigonometric series along the circumferential direction. The analytical results obtained by the present 2-D model show a good agreement with the numerical (FEM) results. The limitations of the previous 1-D model are assessed.
USING TWO-DIMENSIONAL HYDRODYNAMIC MODELS AT SCALES OF ECOLOGICAL IMPORTANCE. (R825760)
Modeling of flow features that are important in assessing stream habitat conditions has been a long-standing interest of stream biologists. Recently, they have begun examining the usefulness of two-dimensional (2-D) hydrodynamic models in attaining this objective. Current modelin...
NASA Astrophysics Data System (ADS)
Andersen, L.; Jones, C. J. C.
2006-06-01
The analysis of vibration from railway tunnels is of growing interest as new and higher-speed railways are built under the ground to address the transport problems of growing modern urban areas. Such analysis can be carried out using numerical methods but models and therefore computing times can be large. There is a need to be able to apply very fast calculations that can be used in tunnel design and studies of environmental impacts. Taking advantage of the fact that tunnels often have a two-dimensional geometry in the sense that the cross section is constant along the tunnel axis, it is useful to evaluate the potential uses of two-dimensional models before committing to much more costly three-dimensional approaches. The vibration forces in the track due to the passage of a train are by nature three-dimensional and a complete analysis undoubtedly requires a model of three-dimensional wave propagation. The aim of this paper is to investigate the quality of the information that can be gained from a two-dimensional model of a railway tunnel. The vibration transmission from the tunnel floor to the ground surface is analysed for the frequency range relevant to the perception of whole body vibration (about 4-80 Hz). A coupled finite element and boundary element scheme is applied in both two and three dimensions. Two tunnel designs are considered: a cut-and-cover tunnel for a double track and a single-track tunnel dug with the New Austrian tunnelling method (NATM).
Cold spray nozzle mach number limitation
NASA Astrophysics Data System (ADS)
Jodoin, B.
2002-12-01
The classic one-dimensional isentropic flow approach is used along with a two-dimensional axisymmetric numerical model to show that the exit Mach number of a cold spray nozzle should be limited due to two factors. To show this, the two-dimensional model is validated with experimental data. Although both models show that the stagnation temperature is an important limiting factor, the one-dimensional approach fails to show how important the shock-particle interactions are at limiting the nozzle Mach number. It is concluded that for an air nozzle spraying solid powder particles, the nozzle Mach number should be set between 1.5 and 3 to limit the negative effects of the high stagnation temperature and of the shock-particle interactions.
NASA Technical Reports Server (NTRS)
Stone, Peter H.; Yao, Mao-Sung
1990-01-01
A number of perpetual January simulations are carried out with a two-dimensional zonally averaged model employing various parameterizations of the eddy fluxes of heat (potential temperature) and moisture. The parameterizations are evaluated by comparing these results with the eddy fluxes calculated in a parallel simulation using a three-dimensional general circulation model with zonally symmetric forcing. The three-dimensional model's performance in turn is evaluated by comparing its results using realistic (nonsymmetric) boundary conditions with observations. Branscome's parameterization of the meridional eddy flux of heat and Leovy's parameterization of the meridional eddy flux of moisture simulate the seasonal and latitudinal variations of these fluxes reasonably well, while somewhat underestimating their magnitudes. New parameterizations of the vertical eddy fluxes are developed that take into account the enhancement of the eddy mixing slope in a growing baroclinic wave due to condensation, and also the effect of eddy fluctuations in relative humidity. The new parameterizations, when tested in the two-dimensional model, simulate the seasonal, latitudinal, and vertical variations of the vertical eddy fluxes quite well, when compared with the three-dimensional model, and only underestimate the magnitude of the fluxes by 10 to 20 percent.
NASA Technical Reports Server (NTRS)
Krueger, Ronald; Paris, Isbelle L.; OBrien, T. Kevin; Minguet, Pierre J.
2004-01-01
The influence of two-dimensional finite element modeling assumptions on the debonding prediction for skin-stiffener specimens was investigated. Geometrically nonlinear finite element analyses using two-dimensional plane-stress and plane-strain elements as well as three different generalized plane strain type approaches were performed. The computed skin and flange strains, transverse tensile stresses and energy release rates were compared to results obtained from three-dimensional simulations. The study showed that for strains and energy release rate computations the generalized plane strain assumptions yielded results closest to the full three-dimensional analysis. For computed transverse tensile stresses the plane stress assumption gave the best agreement. Based on this study it is recommended that results from plane stress and plane strain models be used as upper and lower bounds. The results from generalized plane strain models fall between the results obtained from plane stress and plane strain models. Two-dimensional models may also be used to qualitatively evaluate the stress distribution in a ply and the variation of energy release rates and mixed mode ratios with delamination length. For more accurate predictions, however, a three-dimensional analysis is required.
NASA Technical Reports Server (NTRS)
Krueger, Ronald; Minguet, Pierre J.; Bushnell, Dennis M. (Technical Monitor)
2002-01-01
The influence of two-dimensional finite element modeling assumptions on the debonding prediction for skin-stiffener specimens was investigated. Geometrically nonlinear finite element analyses using two-dimensional plane-stress and plane strain elements as well as three different generalized plane strain type approaches were performed. The computed deflections, skin and flange strains, transverse tensile stresses and energy release rates were compared to results obtained from three-dimensional simulations. The study showed that for strains and energy release rate computations the generalized plane strain assumptions yielded results closest to the full three-dimensional analysis. For computed transverse tensile stresses the plane stress assumption gave the best agreement. Based on this study it is recommended that results from plane stress and plane strain models be used as upper and lower bounds. The results from generalized plane strain models fall between the results obtained from plane stress and plane strain models. Two-dimensional models may also be used to qualitatively evaluate the stress distribution in a ply and the variation of energy release rates and mixed mode ratios with lamination length. For more accurate predictions, however, a three-dimensional analysis is required.
Queda dos homicídios em São Paulo, Brasil: uma análise descritiva
Peres, Maria Fernanda Tourinho; Vicentin, Diego; Nery, Marcelo Batista; de Lima, Renato Sérgio; de Souza, Edinilsa Ramos; Cerda, Magdalena; Cardia, Nancy; Adorno, e Sérgio
2012-01-01
Objetivo Descrever a evolução da mortalidade por homicídios no Município de São Paulo segundo tipo de arma, sexo, raça ou cor, idade e áreas de exclusão/inclusão social entre 1996 e 2008. Métodos Estudo ecológico de série temporal. Os dados sobre óbitos ocorridos no Município foram coletados da base de dados do Programa de Aprimoramento das Informações sobre Mortalidade, seguindo a Classificação Internacional de Doenças, Décima Revisão (CID-10). Foram calculadas as taxas de mortalidade por homicídio (TMH) para a população total, por sexo, raça ou cor, faixa etária, tipo de arma e área de exclusão/inclusão social. As TMH foram padronizadas por idade pelo método direto. Foram calculados os percentuais de variação no período estudado. Para as áreas de exclusão/inclusão social foram calculados os riscos relativos de morte por homicídio. Resultados As TMH apresentaram queda de 73,7% entre 2001 e 2008. Foi observada redução da TMH em todos os grupos analisados, mais pronunciada em homens (−74,5%), jovens de 15 a 24 anos (−78,0%) e moradores de áreas de exclusão social extrema (−79,3%). A redução ocorreu, sobretudo, nos homicídios cometidos com armas de fogo (−74,1%). O risco relativo de morte por homicídio nas áreas de exclusão extrema (tendo como referência áreas com algum grau de exclusão social) foi de 2,77 em 1996, 3,9 em 2001 e 2,13 em 2008. Nas áreas de alta exclusão social, o risco relativo foi de 2,07 em 1996 e 1,96 em 2008. Conclusões Para compreender a redução dos homicídios no Município, é importante considerar macrodeterminantes que atingem todo o Município e todos os subgrupos populacionais e microdeterminantes que atuam localmente, influenciando de forma diferenciada os homicídios com armas de fogo e os homicídios na população jovem, no sexo masculino e em residentes em áreas de alta exclusão social. PMID:21390415
NASA Astrophysics Data System (ADS)
Kiani, Keivan
2014-06-01
Novel nonlocal discrete and continuous models are proposed for dynamic analysis of two- and three-dimensional ensembles of single-walled carbon nanotubes (SWCNTs). The generated extra van der Waals forces between adjacent SWCNTs due to their lateral motions are evaluated via Lennard-Jones potential function. Using a nonlocal Rayleigh beam model, the discrete and continuous models are developed for both two- and three-dimensional ensembles of SWCNTs acted upon by transverse dynamic loads. The capabilities of the proposed continuous models in capturing the vibration behavior of SWCNTs ensembles are then examined through various numerical simulations. A reasonably good agreement between the results of the continuous models and those of the discrete ones is also reported. The effects of the applied load frequency, intertube spaces, and small-scale parameter on the transverse dynamic responses of both two- and three-dimensional ensembles of SWCNTs are explained. The proposed continuous models would be very useful for dynamic analyses of large populated ensembles of SWCNTs whose discrete models suffer from both computational efforts and labor costs.
ERIC Educational Resources Information Center
Penny, Matthew R.; Cao, Zi Jing; Patel, Bhaven; dos Santos, Bruno Sil; Asquith, Christopher R. M.; Szulc, Blanka R.; Rao, Zenobia X.; Muwaffak, Zaid; Malkinson, John P.; Hilton, Stephen T.
2017-01-01
Three-dimensional (3D) chemical models are a well-established learning tool used to enhance the understanding of chemical structures by converting two-dimensional paper or screen outputs into realistic three-dimensional objects. While commercial atom model kits are readily available, there is a surprising lack of large molecular and orbital models…
ERIC Educational Resources Information Center
Ellison, Mark D.
2008-01-01
The one-dimensional particle-in-a-box model used to introduce quantum mechanics to students suffers from a tenuous connection to a real physical system. This article presents a two-dimensional model, the particle confined within a ring, that directly corresponds to observations of surface electrons in a metal trapped inside a circular barrier.…
A study of frontal dynamics with application to the Australian summertime 'cool change'
NASA Technical Reports Server (NTRS)
Reeder, Michael J.; Smith, Roger K.
1987-01-01
The dynamics of frontal evolution is examined in terms of the Australian summertime cool change using a two-dimensional numerical model. The model is synthesized from observational data on surface cold fronts obtained during the Australian Cold Fronts Research Program, and the model develops a quasi-steady surface cold front during the 24 hours of integration. The characteristics of this model are compared with those of a kinematic model; it is observed that the features of the two models correspond. The two-dimensional and kinematic models are also compared with a 24-hour prediction of the cold front of February 1983 using the three-dimensional nested-grid model of the Australian Numerical Meteorology Research Center, developed by Gauntlett et al. (1984). Good correlation between these models is detected.
The role of gap edge instabilities in setting the depth of planet gaps in protoplanetary discs
NASA Astrophysics Data System (ADS)
Hallam, P. D.; Paardekooper, S.-J.
2017-08-01
It is known that an embedded massive planet will open a gap in a protoplanetary disc via angular momentum exchange with the disc material. The resulting surface density profile of the disc is investigated for one-dimensional and two-dimensional disc models and, in agreement with previous work, it is found that one-dimensional gaps are significantly deeper than their two-dimensional counterparts for the same initial conditions. We find, by applying one-dimensional torque density distributions to two-dimensional discs containing no planet, that the excitement of the Rossby wave instability and the formation of Rossby vortices play a critical role in setting the equilibrium depth of the gap. Being a two-dimensional instability, this is absent from one-dimensional simulations and does not limit the equilibrium gap depth there. We find similar gap depths between two-dimensional gaps formed by torque density distributions, in which the Rossby wave instability is present, and two-dimensional planet gaps, in which no Rossby wave instability is present. This can be understood if the planet gap is maintained at marginal stability, even when there is no obvious Rossby wave instability present. Further investigation shows the final equilibrium gap depth is very sensitive to the form of the applied torque density distribution, and using improved one-dimensional approximations from three-dimensional simulations can go even further towards reducing the discrepancy between one- and two-dimensional models, especially for lower mass planets. This behaviour is found to be consistent across discs with varying parameters.
A Comparison of Simplified Two-dimensional Flow Models Exemplified by Water Flow in a Cavern
NASA Astrophysics Data System (ADS)
Prybytak, Dzmitry; Zima, Piotr
2017-12-01
The paper shows the results of a comparison of simplified models describing a two-dimensional water flow in the example of a water flow through a straight channel sector with a cavern. The following models were tested: the two-dimensional potential flow model, the Stokes model and the Navier-Stokes model. In order to solve the first two, the boundary element method was employed, whereas to solve the Navier-Stokes equations, the open-source code library OpenFOAM was applied. The results of numerical solutions were compared with the results of measurements carried out on a test stand in a hydraulic laboratory. The measurements were taken with an ADV probe (Acoustic Doppler Velocimeter). Finally, differences between the results obtained from the mathematical models and the results of laboratory measurements were analysed.
NASA Astrophysics Data System (ADS)
Sakaguchi, Hidetsugu; Ishibashi, Kazuya
2018-06-01
We study self-propelled particles by direct numerical simulation of the nonlinear Kramers equation for self-propelled particles. In our previous paper, we studied self-propelled particles with velocity variables in one dimension. In this paper, we consider another model in which each particle exhibits directional motion. The movement direction is expressed with a variable ϕ. We show that one-dimensional solitary wave states appear in direct numerical simulations of the nonlinear Kramers equation in one- and two-dimensional systems, which is a generalization of our previous result. Furthermore, we find two-dimensionally localized states in the case that each self-propelled particle exhibits rotational motion. The center of mass of the two-dimensionally localized state exhibits circular motion, which implies collective rotating motion. Finally, we consider a simple one-dimensional model equation to qualitatively understand the formation of the solitary wave state.
Analytical solutions of the two-dimensional Dirac equation for a topological channel intersection
NASA Astrophysics Data System (ADS)
Anglin, J. R.; Schulz, A.
2017-01-01
Numerical simulations in a tight-binding model have shown that an intersection of topologically protected one-dimensional chiral channels can function as a beam splitter for noninteracting fermions on a two-dimensional lattice [Qiao, Jung, and MacDonald, Nano Lett. 11, 3453 (2011), 10.1021/nl201941f; Qiao et al., Phys. Rev. Lett. 112, 206601 (2014), 10.1103/PhysRevLett.112.206601]. Here we confirm this result analytically in the corresponding continuum k .p model, by solving the associated two-dimensional Dirac equation, in the presence of a "checkerboard" potential that provides a right-angled intersection between two zero-line modes. The method by which we obtain our analytical solutions is systematic and potentially generalizable to similar problems involving intersections of one-dimensional systems.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model.
Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak
2015-01-01
This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels.
Estimating Risk of Natural Gas Portfolios by Using GARCH-EVT-Copula Model
Tang, Jiechen; Zhou, Chao; Yuan, Xinyu; Sriboonchitta, Songsak
2015-01-01
This paper concentrates on estimating the risk of Title Transfer Facility (TTF) Hub natural gas portfolios by using the GARCH-EVT-copula model. We first use the univariate ARMA-GARCH model to model each natural gas return series. Second, the extreme value distribution (EVT) is fitted to the tails of the residuals to model marginal residual distributions. Third, multivariate Gaussian copula and Student t-copula are employed to describe the natural gas portfolio risk dependence structure. Finally, we simulate N portfolios and estimate value at risk (VaR) and conditional value at risk (CVaR). Our empirical results show that, for an equally weighted portfolio of five natural gases, the VaR and CVaR values obtained from the Student t-copula are larger than those obtained from the Gaussian copula. Moreover, when minimizing the portfolio risk, the optimal natural gas portfolio weights are found to be similar across the multivariate Gaussian copula and Student t-copula and different confidence levels. PMID:26351652
ERIC Educational Resources Information Center
de Senillosa, Antonio
1979-01-01
Discusses the important role that language has in our society and compares human communication to animal group communication. Gives specific examples of corruption in the Spanish language today. (NCR)
2. Historic American Buildings Survey, Frederik C. Gjessing, Photographer January, ...
2. Historic American Buildings Survey, Frederik C. Gjessing, Photographer January, 1956 ELEVATION OF CHAPEL AND SALLY PORT TOWARDS THE COURTYARD PLAZA DE ARMAS, SAN FELIPE DEL MORRO. - Castillo de San Felipe del Morro Sally Port & Chapel, Northwest end of San Juan Island, San Juan, San Juan Municipio, PR
NASA Astrophysics Data System (ADS)
Brawn, A. D.; Wheal, H. V.
1986-07-01
A system is described which can be used to create a three-dimensional model of a neurone from the central nervous system. This model can then be used to obtain quantitative data on the physical and electrical pro, perties of the neurone. Living neurones are either raised in culture, or taken from in vitro preparations of brain tissue and optically sectioned. These two-dimensional sections are digitised, and input to a 68008-based microcomputer. The system reconstructs the three-dimensional structure of the neurone, both geanetrically and electrically. The user can a) View the structure fran any point at any angle b) "Move through" the structure along any given vector c) Nave through" the structure following a neurone process d) Fire the neurone at any point, and "watch" the action potentials propagate e) Vary the parameters of the electrical model of a process element. The system is targeted to a research programme on epilepsy, which makes frequent use of both geometric and electrical neurone modelling. Current techniques which may involve crude histology and two-dimensional drawings have considerable short camings.
Tan, S; Hu, A; Wilson, T; Ladak, H; Haase, P; Fung, K
2012-04-01
(1) To investigate the efficacy of a computer-generated three-dimensional laryngeal model for laryngeal anatomy teaching; (2) to explore the relationship between students' spatial ability and acquisition of anatomical knowledge; and (3) to assess participants' opinion of the computerised model. Forty junior doctors were randomised to undertake laryngeal anatomy study supplemented by either a three-dimensional computer model or two-dimensional images. Outcome measurements comprised a laryngeal anatomy test, the modified Vandenberg and Kuse mental rotation test, and an opinion survey. Mean scores ± standard deviations for the anatomy test were 15.7 ± 2.0 for the 'three dimensions' group and 15.5 ± 2.3 for the 'standard' group (p = 0.7222). Pearson's correlation between the rotation test scores and the scores for the spatial ability questions in the anatomy test was 0.4791 (p = 0.086, n = 29). Opinion survey answers revealed significant differences in respondents' perceptions of the clarity and 'user friendliness' of, and their preferences for, the three-dimensional model as regards anatomical study. The three-dimensional computer model was equivalent to standard two-dimensional images, for the purpose of laryngeal anatomy teaching. There was no association between students' spatial ability and functional anatomy learning. However, students preferred to use the three-dimensional model.
Duct flow nonuniformities: Effect of struts in SSME HGM II(+)
NASA Technical Reports Server (NTRS)
Burke, Roger
1988-01-01
A numerical study, using the INS3D flow solver, of laminar and turbulent flow around a two dimensional strut, and three dimensional flow around a strut in an annulus is presented. A multi-block procedure was used to calculate two dimensional laminar flow around two struts in parallel, with each strut represented by one computational block. Single block calculations were performed for turbulent flow around a two dimensional strut, using a Baldwin-Lomax turbulence model to parameterize the turbulent shear stresses. A modified Baldwin-Lomax model was applied to the case of a three dimensional strut in an annulus. The results displayed the essential features of wing-body flows, including the presence of a horseshoe vortex system at the junction of the strut and the lower annulus surface. A similar system was observed at the upper annulus surface. The test geometries discussed were useful in developing the capability to perform multiblock calculations, and to simulate turbulent flow around obstructions located between curved walls. Both of these skills will be necessary to model the three dimensional flow in the strut assembly of the SSME. Work is now in progress on performing a three dimensional two block turbulent calculation of the flow in the turnaround duct (TAD) and strut/fuel bowl juncture region.
Chimera patterns in two-dimensional networks of coupled neurons.
Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp
2017-03-01
We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.
Chimera patterns in two-dimensional networks of coupled neurons
NASA Astrophysics Data System (ADS)
Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp
2017-03-01
We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mittal, Gaurav; Raju, Mandhapati P.; Sung, Chih-Jen
2010-07-15
In modeling rapid compression machine (RCM) experiments, zero-dimensional approach is commonly used along with an associated heat loss model. The adequacy of such approach has not been validated for hydrocarbon fuels. The existence of multi-dimensional effects inside an RCM due to the boundary layer, roll-up vortex, non-uniform heat release, and piston crevice could result in deviation from the zero-dimensional assumption, particularly for hydrocarbons exhibiting two-stage ignition and strong thermokinetic interactions. The objective of this investigation is to assess the adequacy of zero-dimensional approach in modeling RCM experiments under conditions of two-stage ignition and negative temperature coefficient (NTC) response. Computational fluidmore » dynamics simulations are conducted for n-heptane ignition in an RCM and the validity of zero-dimensional approach is assessed through comparisons over the entire NTC region. Results show that the zero-dimensional model based on the approach of 'adiabatic volume expansion' performs very well in adequately predicting the first-stage ignition delays, although quantitative discrepancy for the prediction of the total ignition delays and pressure rise in the first-stage ignition is noted even when the roll-up vortex is suppressed and a well-defined homogeneous core is retained within an RCM. Furthermore, the discrepancy is pressure dependent and decreases as compressed pressure is increased. Also, as ignition response becomes single-stage at higher compressed temperatures, discrepancy from the zero-dimensional simulations reduces. Despite of some quantitative discrepancy, the zero-dimensional modeling approach is deemed satisfactory from the viewpoint of the ignition delay simulation. (author)« less
Wilson loops in supersymmetric gauge theories
NASA Astrophysics Data System (ADS)
Pestun, Vasily
This thesis is devoted to several exact computations in four-dimensional supersymmetric gauge field theories. In the first part of the thesis we prove conjecture due to Erickson-Semenoff-Zarembo and Drukker-Gross which relates supersymmetric circular Wilson loop operators in the N = 4 supersymmetric Yang-Mills theory with a Gaussian matrix model. We also compute the partition function and give a new matrix model formula for the expectation value of a supersymmetric circular Wilson loop operator for the pure N = 2 and the N* = 2 supersymmetric Yang-Mills theory on a four-sphere. Circular supersymmetric Wilson loops in four-dimensional N = 2 superconformal gauge theory are treated similarly. In the second part we consider supersymmetric Wilson loops of arbitrary shape restricted to a two-dimensional sphere in the four-dimensional N = 4 supersymmetric Yang-Mills theory. We show that expectation value for these Wilson loops can be exactly computed using a two-dimensional theory closely related to the topological two-dimensional Higgs-Yang-Mills theory, or two-dimensional Yang-Mills theory for the complexified gauge group.
The design and development of a two-dimensional adaptive truss structure
NASA Technical Reports Server (NTRS)
Kuwao, Fumihiro; Motohashi, Shoichi; Yoshihara, Makoto; Takahara, Kenichi; Natori, Michihiro
1987-01-01
The functional model of a two dimensional adaptive truss structure which can purposefully change its geometrical configuration is introduced. The details of design and fabrication such as kinematic analysis, dynamic characteristics analysis and some test results are presented for the demonstration of this two dimensional truss concept.
Mixing of gaseous reactants in chemical generation of atomic iodine for COIL: two-dimensional study
NASA Astrophysics Data System (ADS)
Jirasek, Vit; Spalek, Otomar; Kodymova, Jarmila; Censky, Miroslav
2003-11-01
Two-dimensional CFD model was applied for the study of mixing and reaction between gaseous chlorine dioxide and nitrogen monoxide diluted with nitrogen during atomic iodine generation. The influence of molecular diffusion on the production of atomic chlorine as a precursor of atomic iodine was predominantly studied. The results were compared with one-dimensional modeling of the system.
A system for extracting 3-dimensional measurements from a stereo pair of TV cameras
NASA Technical Reports Server (NTRS)
Yakimovsky, Y.; Cunningham, R.
1976-01-01
Obtaining accurate three-dimensional (3-D) measurement from a stereo pair of TV cameras is a task requiring camera modeling, calibration, and the matching of the two images of a real 3-D point on the two TV pictures. A system which models and calibrates the cameras and pairs the two images of a real-world point in the two pictures, either manually or automatically, was implemented. This system is operating and provides three-dimensional measurements resolution of + or - mm at distances of about 2 m.
NASA Astrophysics Data System (ADS)
Sushko, Iryna; Gardini, Laura; Matsuyama, Kiminori
2018-05-01
We consider a two-dimensional continuous noninvertible piecewise smooth map, which characterizes the dynamics of innovation activities in the two-country model of trade and product innovation proposed in [7]. This two-dimensional map can be viewed as a coupling of two one-dimensional skew tent maps, each of which characterizes the innovation dynamics in each country in the absence of trade, and the coupling parameter depends inversely on the trade cost between the two countries. Hence, this model offers a laboratory for studying how a decline in the trade cost, or globalization, might synchronize endogenous fluctuations of innovation activities in the two countries. In this paper, we focus on the bifurcation scenarios, how the phase portrait of the two-dimensional map changes with a gradual decline of the trade cost, leading to border collision, merging, expansion and final bifurcations of the coexisting chaotic attractors. An example of peculiar border collision bifurcation leading to an increase of dimension of the chaotic attractor is also presented.
Further two-dimensional code development for Stirling space engine components
NASA Technical Reports Server (NTRS)
Ibrahim, Mounir; Tew, Roy C.; Dudenhoefer, James E.
1990-01-01
The development of multidimensional models of Stirling engine components is described. Two-dimensional parallel plate models of an engine regenerator and a cooler were used to study heat transfer under conditions of laminar, incompressible oscillating flow. Substantial differences in the nature of the temperature variations in time over the cycle were observed for the cooler as contrasted with the regenerator. When the two-dimensional cooler model was used to calculate a heat transfer coefficient, it yields a very different result from that calculated using steady-flow correlations. Simulation results for the regenerator and the cooler are presented.
A multi scale multi-dimensional thermo electrochemical modelling of high capacity lithium-ion cells
NASA Astrophysics Data System (ADS)
Tourani, Abbas; White, Peter; Ivey, Paul
2014-06-01
Lithium iron phosphate (LFP) and lithium manganese oxide (LMO) are competitive and complementary to each other as cathode materials for lithium-ion batteries, especially for use in electric vehicles. A multi scale multi-dimensional physic-based model is proposed in this paper to study the thermal behaviour of the two lithium-ion chemistries. The model consists of two sub models, a one dimensional (1D) electrochemical sub model and a two dimensional (2D) thermo-electric sub model, which are coupled and solved concurrently. The 1D model predicts the heat generation rate (Qh) and voltage (V) of the battery cell through different load cycles. The 2D model of the battery cell accounts for temperature distribution and current distribution across the surface of the battery cell. The two cells are examined experimentally through 90 h load cycles including high/low charge/discharge rates. The experimental results are compared with the model results and they are in good agreement. The presented results in this paper verify the cells temperature behaviour at different operating conditions which will lead to the design of a cost effective thermal management system for the battery pack.
Barlow, Paul M.
1997-01-01
Steady-state, two- and three-dimensional, ground-water-flow models coupled with particle tracking were evaluated to determine their effectiveness in delineating contributing areas of wells pumping from stratified-drift aquifers of Cape Cod, Massachusetts. Several contributing areas delineated by use of the three-dimensional models do not conform to simple ellipsoidal shapes that are typically delineated by use of two-dimensional analytical and numerical modeling techniques and included discontinuous areas of the water table.
NASA Technical Reports Server (NTRS)
Herrmann, M.
2003-01-01
This paper is divided into four parts. First, the level set/vortex sheet method for three-dimensional two-phase interface dynamics is presented. Second, the LSS model for the primary breakup of turbulent liquid jets and sheets is outlined and all terms requiring subgrid modeling are identified. Then, preliminary three-dimensional results of the level set/vortex sheet method are presented and discussed. Finally, conclusions are drawn and an outlook to future work is given.
Multiexponential models of (1+1)-dimensional dilaton gravity and Toda-Liouville integrable models
NASA Astrophysics Data System (ADS)
de Alfaro, V.; Filippov, A. T.
2010-01-01
We study general properties of a class of two-dimensional dilaton gravity (DG) theories with potentials containing several exponential terms. We isolate and thoroughly study a subclass of such theories in which the equations of motion reduce to Toda and Liouville equations. We show that the equation parameters must satisfy a certain constraint, which we find and solve for the most general multiexponential model. It follows from the constraint that integrable Toda equations in DG theories generally cannot appear without accompanying Liouville equations. The most difficult problem in the two-dimensional Toda-Liouville (TL) DG is to solve the energy and momentum constraints. We discuss this problem using the simplest examples and identify the main obstacles to solving it analytically. We then consider a subclass of integrable two-dimensional theories where scalar matter fields satisfy the Toda equations and the two-dimensional metric is trivial. We consider the simplest case in some detail. In this example, we show how to obtain the general solution. We also show how to simply derive wavelike solutions of general TL systems. In the DG theory, these solutions describe nonlinear waves coupled to gravity and also static states and cosmologies. For static states and cosmologies, we propose and study a more general one-dimensional TL model typically emerging in one-dimensional reductions of higher-dimensional gravity and supergravity theories. We especially attend to making the analytic structure of the solutions of the Toda equations as simple and transparent as possible.
Spin-Imbalanced Quasi-Two-Dimensional Fermi Gases
NASA Astrophysics Data System (ADS)
Ong, W.; Cheng, Chingyun; Arakelyan, I.; Thomas, J. E.
2015-03-01
We measure the density profiles for a Fermi gas of
On some structure-turbulence interaction problems
NASA Technical Reports Server (NTRS)
Maekawa, S.; Lin, Y. K.
1976-01-01
The interactions between a turbulent flow structure; responding to its excitation were studied. The turbulence was typical of those associated with a boundary layer, having a cross-spectral density indicative of convection and statistical decay. A number of structural models were considered. Among the one-dimensional models were an unsupported infinite beam and a periodically supported infinite beam. The fuselage construction of an aircraft was then considered. For the two-dimensional case a simple membrane was used to illustrate the type of formulation applicable to most two-dimensional structures. Both the one-dimensional and two-dimensional structures studied were backed by a cavity filled with an initially quiescent fluid to simulate the acoustic environment when the structure forms one side of a cabin of a sea vessel or aircraft.
Vfold: a web server for RNA structure and folding thermodynamics prediction.
Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie
2014-01-01
The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".
Stereoscopic Projection in Organic Chemistry: Bridging the Gap between Two and Three Dimensions.
ERIC Educational Resources Information Center
Rozzelle, Arlene A.; Rosenfeld, Stuart M.
1985-01-01
Shows how to make stereo slides of three-dimensional molecular models. The slides have been used to teach chirality, conformational isomerism, how models and two-dimensional representations embody selected aspects of structure, and fundamentals of using the specific model set required in a particular organic chemistry course. (JN)
Two-dimensional analytic weighting functions for limb scattering
NASA Astrophysics Data System (ADS)
Zawada, D. J.; Bourassa, A. E.; Degenstein, D. A.
2017-10-01
Through the inversion of limb scatter measurements it is possible to obtain vertical profiles of trace species in the atmosphere. Many of these inversion methods require what is often referred to as weighting functions, or derivatives of the radiance with respect to concentrations of trace species in the atmosphere. Several radiative transfer models have implemented analytic methods to calculate weighting functions, alleviating the computational burden of traditional numerical perturbation methods. Here we describe the implementation of analytic two-dimensional weighting functions, where derivatives are calculated relative to atmospheric constituents in a two-dimensional grid of altitude and angle along the line of sight direction, in the SASKTRAN-HR radiative transfer model. Two-dimensional weighting functions are required for two-dimensional inversions of limb scatter measurements. Examples are presented where the analytic two-dimensional weighting functions are calculated with an underlying one-dimensional atmosphere. It is shown that the analytic weighting functions are more accurate than ones calculated with a single scatter approximation, and are orders of magnitude faster than a typical perturbation method. Evidence is presented that weighting functions for stratospheric aerosols calculated under a single scatter approximation may not be suitable for use in retrieval algorithms under solar backscatter conditions.
Wang, Yanhong; Shen, Min; Yang, Jingni; Dai, Min; Chang, Yaowen; Zhang, Chi; Luan, Guangxin; Ling, Baodong; Jia, Xu
2016-01-01
The prevalence of aminoglycoside resistant enzymes has previously been reported and extended-spectrum β-lactamase among Acinetobacter baumannii. To track the risk of multidrug-resistant A. baumannii, the present study aimed to determine the prevalence of carbapenemases in high-level aminoglycoside resistant A. baumannii over two years. A total of 118 strains of A. baumannii were consecutively collected in the First Affiliated Hospital of Chengdu Medical College, Chengdu, China. These isolates were investigated on the genetic basis of their resistance to aminoglycosides. The results showed that 75 (63.56%) isolates were high-level resistant to aminoglycosides, including gentamicin and amikacin (minimum inhibitory concentration, ≥256 µg/ml). Aminoglycoside-resistant genes ant(2″)-Ia, aac(6′)-Ib, aph(3′)-Ia, aac(3)-Ia, aac(3)-IIa, armA, rmtA, rmtB, rmtC, rmtD, rmtE, rmtF, rmtG, rmtH and npmA, and carbapenem-resistant genes blaOXA-23, blaOXA-24, blaOXA-51, blaOXA-58, blaSIM, blaIMP, blaNDM-1 and blaKPC, were analyzed using polymerase chain reaction. The positive rate of ant(2″)-Ia, aac(6′)-Ib, aph(3′)-Ia, aac(3)-Ia and aac(3)-IIa was 66.95, 69.49, 42.37, 39.83 and 14.41%, respectively. armA was present in 72.0% (54/75) of A. baumannii isolates with high-level resistance to aminoglycosides. The remaining nine 16S ribosomal RNA methlyase genes (rmtA, rmtB, rmtC, rmtD, rmtE, rmtF, rmtG, rmtH and npmA) and aminoglycoside-modifying enzyme gene aac(6′)-Ib-cr were not detected. Among the 54 armA-positive isolates, the prevalence of the carbapenem resistant blaOXA-23 and blaOXA-51 genes was 79.63 and 100%, respectively. armA, ant(2″)-Ia and aac(6′)-Ib were positive in 43 isolates. The results of multilocus sequence typing revealed 31 sequence types (STs) in all clinical strains. Among these STs, the high-level aminoglycoside-resistant A. baumannii ST92, which mostly harbored blaOXA-23, was the predominant clone (29/75). In conclusion, A. baumannii harboring carbapenemases and aminoglycoside-resistant enzymes are extremely prevalent in western China, emphasizing the need to adopt surveillance programs to solve the therapeutic challenges that this presents. PMID:28101158
Kernodle, John Michael
1981-01-01
A two-dimensional ground-water flow model of the Eutaw-McShan and Gordo aquifers in the area of Lee County, Miss., was successfully calibrated and verified using data from six long-term observation wells and two intensive studies of areal water levels. The water levels computed by the model were found to be most sensitive to changes in simulated aquifer hydraulic conductivity and to changes in head in the overlying Coffee Sand aquifer. The two-dimensional model performed reasonably well in simulating the aquifer system except possibly in southern Lee County and southward where a clay bed at the top of the Gordo Formation partially isolated the Gordo from the overlying Eutaw-McShan aquifer. The verified model was used to determine theoretical aquifer response to increased ground-water withdrawal to the year 2000. Two estimated rates of increase and five possible well field locations were examined. (USGS)
NASA Technical Reports Server (NTRS)
Tsai, H. C.; Arocho, A. M.
1992-01-01
A simple one-dimensional fiber-matrix interphase model has been developed and analytical results obtained correlated well with available experimental data. It was found that by including the interphase between the fiber and matrix in the model, much better local stress results were obtained than with the model without the interphase. A more sophisticated two-dimensional micromechanical model, which included the interphase properties was also developed. Both one-dimensional and two-dimensional models were used to study the effect of the interphase properties on the local stresses at the fiber, interphase and matrix. From this study, it was found that interphase modulus and thickness have significant influence on the transverse tensile strength and mode of failure in fiber reinforced composites.
Entropic manifestations of topological order in three dimensions
NASA Astrophysics Data System (ADS)
Bullivant, Alex; Pachos, Jiannis K.
2016-03-01
We evaluate the entanglement entropy of exactly solvable Hamiltonians corresponding to general families of three-dimensional topological models. We show that the modification to the entropic area law due to three-dimensional topological properties is richer than the two-dimensional case. In addition to the reduction of the entropy caused by a nonzero vacuum expectation value of contractible loop operators, a topological invariant emerges that increases the entropy if the model consists of nontrivially braiding anyons. As a result the three-dimensional topological entanglement entropy provides only partial information about the two entropic topological invariants.
Supersymmetric gauged matrix models from dimensional reduction on a sphere
NASA Astrophysics Data System (ADS)
Closset, Cyril; Ghim, Dongwook; Seong, Rak-Kyeong
2018-05-01
It was recently proposed that N = 1 supersymmetric gauged matrix models have a duality of order four — that is, a quadrality — reminiscent of infrared dualities of SQCD theories in higher dimensions. In this note, we show that the zero-dimensional quadrality proposal can be inferred from the two-dimensional Gadde-Gukov-Putrov triality. We consider two-dimensional N = (0, 2) SQCD compactified on a sphere with the half-topological twist. For a convenient choice of R-charge, the zero-mode sector on the sphere gives rise to a simple N = 1 gauged matrix model. Triality on the sphere then implies a triality relation for the supersymmetric matrix model, which can be completed to the full quadrality.
Exact results for quench dynamics and defect production in a two-dimensional model.
Sengupta, K; Sen, Diptiman; Mondal, Shreyoshi
2008-02-22
We show that for a d-dimensional model in which a quench with a rate tau(-1) takes the system across a (d-m)-dimensional critical surface, the defect density scales as n approximately 1/tau(mnu/(znu+1)), where nu and z are the correlation length and dynamical critical exponents characterizing the critical surface. We explicitly demonstrate that the Kitaev model provides an example of such a scaling with d = 2 and m = nu = z = 1. We also provide the first example of an exact calculation of some multispin correlation functions for a two-dimensional model that can be used to determine the correlation between the defects. We suggest possible experiments to test our theory.
The Fog of Peace: Planning and Executing The Restoration of Panama
1992-04-15
posean armas Ilegalus., CONSTITUCION Y LAS LEVES DE lO0limpleard Ia fuerza sdlo cuando sea necesarlo y cl mifnmtoPANAMA, ~~~ti ENDFNS ELA( ucrz.a...rcqucrldw, hacienda uso tic lit ftierm. mortal PANAM , ENDEFESA D LA nlcarriente coini ultima rcuurso. DEMOCRACIA Oath Commandments 99 APPENDIX G U.S
Soviet Negotiating Techniques in Arms Control Negotiations with the United States
1979-08-01
Arma - ments and the Prohibition of Atomic, Hydrogen and Other Weapons of Mass Destruction. The disarmament debate then centered in twenty- eight...example, on the problem of the Mideast and on other outstanding problems in which the United States and the Soviet Union, acting together, canJ serve the
Entanglement Area Law in Disordered Free Fermion Anderson Model in One, Two, and Three Dimensions
Pouranvari, Mohammad; Zhang, Yuhui; Yang, Kun
2015-01-01
We calculate numerically the entanglement entropy of free fermion ground states in one-, two-, and three-dimensional Anderson models and find that it obeys the area law as long as the linear size of the subsystem is sufficiently larger than the mean free path. This result holds in the metallic phase of the three-dimensional Anderson model, where the mean free path is finite although the localization length is infinite. Relation between the present results and earlier ones on area law violation in special one-dimensional models that support metallic phases is discussed.
Beta functions in Chirally deformed supersymmetric sigma models in two dimensions
NASA Astrophysics Data System (ADS)
Vainshtein, Arkady
2016-10-01
We study two-dimensional sigma models where the chiral deformation diminished the original 𝒩 = (2, 2) supersymmetry to the chiral one, 𝒩 = (0, 2). Such heterotic models were discovered previously on the world sheet of non-Abelian stringy solitons supported by certain four-dimensional 𝒩 = 1 theories. We study geometric aspects and holomorphic properties of these models, and derive a number of exact expressions for the β functions in terms of the anomalous dimensions analogous to the NSVZ β function in four-dimensional Yang-Mills. Instanton calculus provides a straightforward method for the derivation.
Beta Functions in Chirally Deformed Supersymmetric Sigma Models in Two Dimensions
NASA Astrophysics Data System (ADS)
Vainshtein, Arkady
We study two-dimensional sigma models where the chiral deformation diminished the original 𝒩 =(2, 2) supersymmetry to the chiral one, 𝒩 =(0, 2). Such heterotic models were discovered previously on the world sheet of non-Abelian stringy solitons supported by certain four-dimensional 𝒩 = 1 theories. We study geometric aspects and holomorphic properties of these models, and derive a number of exact expressions for the β functions in terms of the anomalous dimensions analogous to the NSVZ β function in four-dimensional Yang-Mills. Instanton calculus provides a straightforward method for the derivation.
Entanglement Area Law in Disordered Free Fermion Anderson Model in One, Two, and Three Dimensions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pouranvari, Mohammad; Zhang, Yuhui; Yang, Kun
We calculate numerically the entanglement entropy of free fermion ground states in one-, two-, and three-dimensional Anderson models and find that it obeys the area law as long as the linear size of the subsystem is sufficiently larger than the mean free path. This result holds in the metallic phase of the three-dimensional Anderson model, where the mean free path is finite although the localization length is infinite. Relation between the present results and earlier ones on area law violation in special one-dimensional models that support metallic phases is discussed.
The Ames two-dimensional stratosphere-mesospheric model. [chemistry and transport of SST pollution
NASA Technical Reports Server (NTRS)
Whitten, R. C.; Borucki, W. J.; Watson, V. R.; Capone, L. A.; Maples, A. L.; Riegel, C. A.
1974-01-01
A two-dimensional model of the stratosphere and mesosphere has recently been developed at Ames Research Center. The model contains chemistry based on 18 species that are solved for at each step and a seasonally-varying transport model based on both winds and eddy transport. The model is described and a preliminary assessment of the impact of supersonic aircraft flights on the ozone layer is given.
Addetia, Karima; Mor-Avi, Victor; Weinert, Lynn; Salgo, Ivan S; Lang, Roberto M
2014-01-01
Differentiating between mitral valve (MV) prolapse (MVP) and MV billowing (MVB) on two-dimensional echocardiography is challenging. The aim of this study was to test the hypothesis that color-coded models of maximal leaflet displacement from the annular plane into the atrium derived from three-dimensional transesophageal echocardiography would allow discrimination between these lesions. Three-dimensional transesophageal echocardiographic imaging of the MV was performed in 50 patients with (n = 38) and without (n = 12) degenerative MV disease. Definitive diagnosis of MVP versus MVB was made using inspection of dynamic three-dimensional renderings and multiple two-dimensional cut planes extracted from three-dimensional data sets. This was used as a reference standard to test an alternative approach, wherein the color-coded parametric models were inspected for integrity of the coaptation line and location of the maximally displaced portion of the leaflet. Diagnostic interpretations of these models by two independent readers were compared with the reference standard. In all cases of MVP, the color-coded models depicted loss of integrity of the coaptation line and maximal leaflet displacement extending to the coaptation line. MVB was depicted by preserved leaflet apposition with maximal displacement away from the coaptation line. Interpretation of the 50 color-coded models by novice readers took 5 to 10 min and resulted in good agreement with the reference technique (κ = 0.81 and κ = 0.73 for the two readers). Three-dimensional color-coded models provide a static display of MV leaflet displacement, allowing differentiation between MVP and MVB, without the need to inspect multiple planes and while taking into account the saddle shape of the mitral annulus. Copyright © 2014 American Society of Echocardiography. Published by Mosby, Inc. All rights reserved.
Moran, John L; Solomon, Patricia J
2013-05-24
Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.
Special Holonomy and Two-Dimensional Supersymmetric Sigma-Models
NASA Astrophysics Data System (ADS)
Stojevic, Vid
2006-11-01
Two-dimensional sigma-models describing superstrings propagating on manifolds of special holonomy are characterized by symmetries related to covariantly constant forms that these manifolds hold, which are generally non-linear and close in a field dependent sense. The thesis explores various aspects of the special holonomy symmetries.
Improved parameter inference in catchment models: 1. Evaluating parameter uncertainty
NASA Astrophysics Data System (ADS)
Kuczera, George
1983-10-01
A Bayesian methodology is developed to evaluate parameter uncertainty in catchment models fitted to a hydrologic response such as runoff, the goal being to improve the chance of successful regionalization. The catchment model is posed as a nonlinear regression model with stochastic errors possibly being both autocorrelated and heteroscedastic. The end result of this methodology, which may use Box-Cox power transformations and ARMA error models, is the posterior distribution, which summarizes what is known about the catchment model parameters. This can be simplified to a multivariate normal provided a linearization in parameter space is acceptable; means of checking and improving this assumption are discussed. The posterior standard deviations give a direct measure of parameter uncertainty, and study of the posterior correlation matrix can indicate what kinds of data are required to improve the precision of poorly determined parameters. Finally, a case study involving a nine-parameter catchment model fitted to monthly runoff and soil moisture data is presented. It is shown that use of ordinary least squares when its underlying error assumptions are violated gives an erroneous description of parameter uncertainty.
Pressure distribution under flexible polishing tools. II - Cylindrical (conical) optics
NASA Astrophysics Data System (ADS)
Mehta, Pravin K.
1990-10-01
A previously developed eigenvalue model is extended to determine polishing pressure distribution by rectangular tools with unequal stiffness in two directions on cylindrical optics. Tool misfit is divided into two simplified one-dimensional problems and one simplified two-dimensional problem. Tools with nonuniform cross-sections are treated with a new one-dimensional eigenvalue algorithm, permitting evaluation of tool designs where the edge is more flexible than the interior. This maintains edge pressure variations within acceptable parameters. Finite element modeling is employed to resolve upper bounds, which handle pressure changes in the two-dimensional misfit element. Paraboloids and hyperboloids from the NASA AXAF system are treated with the AXAFPOD software for this method, and are verified with NASTRAN finite element analyses. The maximum deviation from the one-dimensional azimuthal pressure variation is predicted to be 10 percent and 20 percent for paraboloids and hyperboloids, respectively.
Lubricant dynamics under sliding condition in disk drives
NASA Astrophysics Data System (ADS)
Wu, Lin
2006-07-01
In this paper, we develop a two-dimensional flow model for the lubricant flow dynamics under a sliding head in disk drives. Our two-dimensional model includes important physics such as viscous force, external air shearing stress, air bearing pressure, centrifugal force, disjoining pressure, and surface tension. Our analysis shows that the lubricant flow dynamics under the sliding condition is a fully two-dimensional phenomenon and the circumferential lubricant flow is strongly coupled to the radial flow. It is necessary to have a two-dimensional flow model that couples the circumferential and radial flows together and includes all important physics to achieve realistic predictions. Our results show that the external air shearing stress has a dominant effect on the lubricant flow dynamics. Both velocity slippage at wall and Poiseuille flow effects have to be considered in the evaluation of the air shearing stress under the head. The nonuniform air bearing pressure has a non-negligible effect on the lubricant film dynamics mostly through the Poiseuille flow effect on the air shearing stress but not from its direct pushing or sucking effect on the lubricant surface. Prediction of the formation of lubricant depletion tracks under a sliding head using the two-dimensional model agrees reasonably well with the existing experimental measurements.
An incompressible two-dimensional multiphase particle-in-cell model for dense particle flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Snider, D.M.; O`Rourke, P.J.; Andrews, M.J.
1997-06-01
A two-dimensional, incompressible, multiphase particle-in-cell (MP-PIC) method is presented for dense particle flows. The numerical technique solves the governing equations of the fluid phase using a continuum model and those of the particle phase using a Lagrangian model. Difficulties associated with calculating interparticle interactions for dense particle flows with volume fractions above 5% have been eliminated by mapping particle properties to a Eulerian grid and then mapping back computed stress tensors to particle positions. This approach utilizes the best of Eulerian/Eulerian continuum models and Eulerian/Lagrangian discrete models. The solution scheme allows for distributions of types, sizes, and density of particles,more » with no numerical diffusion from the Lagrangian particle calculations. The computational method is implicit with respect to pressure, velocity, and volume fraction in the continuum solution thus avoiding courant limits on computational time advancement. MP-PIC simulations are compared with one-dimensional problems that have analytical solutions and with two-dimensional problems for which there are experimental data.« less
Khennouchi, Nour Chems el Houda; Loucif, Lotfi; Boutefnouchet, Nafissa; Allag, Hamoudi
2015-01-01
Enterobacter cloacae is among the most important pathogens responsible for nosocomial infections and outbreaks. In this study, 77 Enterobacter isolates were collected: 27 isolates from Algerian hospitals (in Constantine, Annaba, and Skikda) and 50 isolates from Marseille, France. All strains were identified by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS). Antibiotic susceptibility testing was performed by the disk diffusion method. PCR was used to detect extended-spectrum-beta-lactamase (ESBL)-encoding, fluoroquinolone resistance-encoding, and aminoglycoside-modifying enzyme (AME) genes. Epidemiological typing was performed using MALDI-TOF MS with data mining approaches, along with multilocus sequence typing (MLST). Sixty-eight isolates (27 from Algeria, 41 from Marseille) were identified by MALDI-TOF MS as E. cloacae. Resistance to antibiotics in the Algerian isolates was significantly higher than that in the strains from Marseille, especially for beta-lactams and aminoglycosides. Eighteen of the 27 Algerian isolates and 11 of the 41 Marseille isolates possessed at least one ESBL-encoding gene: blaCTX-M and/or blaTEM. AME genes were detected in 20 of the 27 Algerian isolates and 8 of the 41 Marseille isolates [ant(2″)-Ia, aac(6′)-Ib-cr, aadA1, aadA2, and armA]. Conjugation experiments showed that armA was carried on a transferable plasmid. MALDI-TOF typing showed three separate clusters according to the geographical distribution and species level. An MLST-based phylogenetic tree showed a clade of 14 E. cloacae isolates from a urology unit clustering together in the MALDI-TOF dendrogram, suggesting the occurrence of an outbreak in this unit. In conclusion, the ability of MALDI-TOF to biotype strains was confirmed, and surveillance measures should be implemented, especially for Algerian patients hospitalized in France. PMID:26239991
Al Sheikh, Yazeed A.; Marie, Mohammed Ali M.; John, James; Krishnappa, Lakshmana Gowda; Dabwab, Khaled Homoud M.
2014-01-01
Background Co production of 16S rRNA methylases gene and β-Lactamase gene among Enterobacteriaceae isolates conferring resistance to both therapeutic options has serious implications for clinicians worldwide. Methods To study co existence of 16S rRNA methylases (armA, rmtA, rmtB, rmtC, rmtD, and npmA) and β-Lactamase (blaTEM-1, blaSHV-12, blaCTX-M-14) genes, we screened all phenotypic positive β-Lactamase producing enterobacteriaceae by polymerase chain reaction (PCR) targeting above genes. A total of 330 enterobacteriaceae strains were collected during study period out of that 218 isolates were identified phenotypically as β-Lactamase producers, which include 50 (22.9%) Escherichia coli; 92 (42.2%) Klebsiella pneumoniae, 44 (20.2%), Citrobactor freundii and 32 (14.7%) Enterobacter spp. Results Among this 218, only 188 isolates harbored the resistant gene for β-Lactamase production. Major β-Lactamase producing isolates were bla TEM-1 type. 122 (56 %) isolates were found to produce any one of the 16S rRNA methylase genes. A total of 116 isolates co produced β-Lactamase and at least one 16S rRNA methylases gene Co production of armA gene was found in 26 isolates with rmtB and in 4 isolates with rmtC. The rmtA and rmtD genes were not detected in any of the tested isolates. Six isolates were positive for a 16S rRNA methylase gene alone. Conclusion β-Lactamase producing isolates appears to coexist with 16S rRNA methylase predominantly armA and rmtB genes in the same isolate. We conclude the major β-Lactamase and 16S rRNA methylases co-producer was K. pneumoniae followed by E. coli. We suggest further work on evaluating other β-lactamases types and novel antibiotic resistance mechanisms among Enterobacteriaceae. PMID:25005152
Lee, Chen-Hsiang; Liu, Jien-Wei; Li, Chia-Chin; Chien, Chun-Chih; Tang, Ya-Fen; Su, Lin-Hui
2011-01-01
Increasing resistance to quinolones, aminoglycosides, and/or cephamycins in extended-spectrum-β-lactamase (ESBL)-producing Enterobacteriaceae exacerbates the already limited antibiotic treatment options for infections due to these microbes. In this study, the presence of resistance determinants for these antimicrobial agents was examined by PCR among ESBL-producing Klebsiella pneumoniae (ESBL-KP) isolates that caused bacteremia. Pulsed-field gel electrophoresis was used to differentiate the clonal relationship among the isolates studied. Transferability and the location of the resistance genes were analyzed by conjugation experiments, followed by DNA-DNA hybridization. Among the 94 ESBL-KP isolates studied, 20 isolates of flomoxef-resistant ESBL-KP were identified. They all carried a DHA-1 gene and were genetically diverse. CTX-M genes were found in 18 of the isolates. Among these DHA-1/CTX-M-producing K. pneumoniae isolates, ISCR1 was detected in 13 (72%) isolates, qnr genes (1 qnrA and 17 qnrB genes) were detected in 18 (100%), aac(6′)-Ib-cr was detected in 11 (61%), and 16S rRNA methylase (all armA genes) was detected in 14 (78%). Four transconjugants were available for further analysis, and qnrB4, aac(6′)-Ib-cr, armA, and blaDHA-1 were all identified on these self-transferable blaCTX-M-carrying plasmids. The genetic environments of ISCR1 associated with armA, blaDHA-1, and qnrB4 genes in the four transconjugants were identical. Replicon-type analysis revealed a FIIA plasmid among the four self-transferable plasmids, although the other three were nontypeable. The cotransfer of multiple resistance genes with the ISCR1 element-carrying plasmids has a clinical impact and warrants close monitoring and further study. PMID:21746945
Batah, Rima; Loucif, Lotfi; Olaitan, Abiola Olumuyiwa; Boutefnouchet, Nafissa; Allag, Hamoudi; Rolain, Jean-Marc
2015-08-01
Serratia marcescens is one of the most important pathogens responsible for nosocomial infections worldwide. Here, we have investigated the molecular support of antibiotic resistance and genetic relationships in a series of 54 S. marcescens clinical isolates collected from Eastern Algeria between December 2011 and July 2013. The 54 isolates were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). Antibiotic susceptibility testing was performed by disc diffusion and E-test methods. Antibiotic resistance genes were detected by polymerase chain reaction (PCR). The genetic transfer of antibiotic resistance was performed by conjugation using azide-resistant Escherichia coli J53 as the recipient strain, and plasmid analysis was done by PCR-based replicon typing. The relatedness of our isolates was determined by phylogenetic analysis based on partial sequences of four protein-encoding genes (gyrB, rpoB, infB, and atpD) and then compared to MALDI-TOF MS clustering. Thirty-five out of 54 isolates yielded an extended-spectrum β-lactamase (ESBL) phenotype and carried bla(CTX-M-15) (n=32), bla(TEM-1) (n=26), bla(TEM-71) (n=1), bla(SHV-1a) (n=1), and bla(PER-2) (n=12). Among these isolates, we identified a cluster of 15 isolates from a urology unit that coharbored ESBL and the 16S rRNA methyltransferase armA. Conjugation was successful for five selected strains, demonstrating the transferability of a conjugative plasmid of incompatibility group incL/M type. Phylogenetic analysis along with MALDI-TOF clustering likely suggested an outbreak of such isolates in the urology unit. In this study, we report for the first time the co-occurrence of armA methyltransferase with ESBL in S. marcescens clinical isolates in Eastern Algeria.
Coupling Processes Between Atmospheric Chemistry and Climate
NASA Technical Reports Server (NTRS)
Ko, M. K. W.; Weisenstein, Debra; Shia, Run-Li; Sze, N. D.
1997-01-01
This is the first semi-annual report for NAS5-97039 summarizing work performed for January 1997 through June 1997. Work in this project is related to NAS1-20666, also funded by NASA ACMAP. The work funded in this project also benefits from work at AER associated with the AER three-dimensional isentropic transport model funded by NASA AEAP and the AER two-dimensional climate-chemistry model (co-funded by Department of Energy). The overall objective of this project is to improve the understanding of coupling processes between atmospheric chemistry and climate. Model predictions of the future distributions of trace gases in the atmosphere constitute an important component of the input necessary for quantitative assessments of global change. We will concentrate on the changes in ozone and stratospheric sulfate aerosol, with emphasis on how ozone in the lower stratosphere would respond to natural or anthropogenic changes. The key modeling tools for this work are the AER two-dimensional chemistry-transport model, the AER two-dimensional stratospheric sulfate model, and the AER three-wave interactive model with full chemistry.
Fulford, Janice M.
2003-01-01
A numerical computer model, Transient Inundation Model for Rivers -- 2 Dimensional (TrimR2D), that solves the two-dimensional depth-averaged flow equations is documented and discussed. The model uses a semi-implicit, semi-Lagrangian finite-difference method. It is a variant of the Trim model and has been used successfully in estuarine environments such as San Francisco Bay. The abilities of the model are documented for three scenarios: uniform depth flows, laboratory dam-break flows, and large-scale riverine flows. The model can start computations from a ?dry? bed and converge to accurate solutions. Inflows are expressed as source terms, which limits the use of the model to sufficiently long reaches where the flow reaches equilibrium with the channel. The data sets used by the investigation demonstrate that the model accurately propagates flood waves through long river reaches and simulates dam breaks with abrupt water-surface changes.
Two-dimensional Ising model on random lattices with constant coordination number
NASA Astrophysics Data System (ADS)
Schrauth, Manuel; Richter, Julian A. J.; Portela, Jefferson S. E.
2018-02-01
We study the two-dimensional Ising model on networks with quenched topological (connectivity) disorder. In particular, we construct random lattices of constant coordination number and perform large-scale Monte Carlo simulations in order to obtain critical exponents using finite-size scaling relations. We find disorder-dependent effective critical exponents, similar to diluted models, showing thus no clear universal behavior. Considering the very recent results for the two-dimensional Ising model on proximity graphs and the coordination number correlation analysis suggested by Barghathi and Vojta [Phys. Rev. Lett. 113, 120602 (2014), 10.1103/PhysRevLett.113.120602], our results indicate that the planarity and connectedness of the lattice play an important role on deciding whether the phase transition is stable against quenched topological disorder.
PNS calculations for 3-D hypersonic corner flow with two turbulence models
NASA Technical Reports Server (NTRS)
Smith, Gregory E.; Liou, May-Fun; Benson, Thomas J.
1988-01-01
A three-dimensional parabolized Navier-Stokes code has been used as a testbed to investigate two turbulence models, the McDonald Camarata and Bushnell Beckwith model, in the hypersonic regime. The Bushnell Beckwith form factor correction to the McDonald Camarata mixing length model has been extended to three-dimensional flow by use of an inverse averaging of the resultant length scale contributions from each wall. Two-dimensional calculations are compared with experiment for Mach 18 helium flow over a 4-deg wedge. Corner flow calculations have been performed at Mach 11.8 for a Reynolds number of .67 x 10 to the 6th, based on the duct half-width, and a freestream stagnation temperature of 1750-deg Rankine.
Numerically exploring the 1D-2D dimensional crossover on spin dynamics in the doped Hubbard model
Kung, Y. F.; Bazin, C.; Wohlfeld, K.; ...
2017-11-02
Using determinant quantum Monte Carlo (DQMC) simulations, we systematically study the doping dependence of the crossover from one to two dimensions and its impact on the magnetic properties of the Hubbard model. A square lattice of chains is used, in which the dimensionality can be tuned by varying the interchain coupling t ⊥. The dynamical spin structure factor and static quantities, such as the static spin susceptibility and nearest-neighbor spin correlation function, are characterized in the one- and two-dimensional limits as a benchmark. When the dimensionality is tuned between these limits, the magnetic properties, while evolving smoothly from one tomore » two dimensions, drastically change regardless of the doping level. This suggests that the spin excitations in the two-dimensional Hubbard model, even in the heavily doped case, cannot be explained using the spinon picture known from one dimension. In conclusion, the DQMC calculations are complemented by cluster perturbation theory studies to form a more complete picture of how the crossover occurs as a function of doping and how doped holes impact magnetic order.« less
NASA Astrophysics Data System (ADS)
Tiguercha, Djlalli; Bennis, Anne-claire; Ezersky, Alexander
2015-04-01
The elliptical motion in surface waves causes an oscillating motion of the sand grains leading to the formation of ripple patterns on the bottom. Investigation how the grains with different properties are distributed inside the ripples is a difficult task because of the segration of particle. The work of Fernandez et al. (2003) was extended from one-dimensional to two-dimensional case. A new numerical model, based on these non-linear diffusion equations, was developed to simulate the grain distribution inside the marine sand ripples. The one and two-dimensional models are validated on several test cases where segregation appears. Starting from an homogeneous mixture of grains, the two-dimensional simulations demonstrate different segregation patterns: a) formation of zones with high concentration of light and heavy particles, b) formation of «cat's eye» patterns, c) appearance of inverse Brazil nut effect. Comparisons of numerical results with the new set of field data and wave flume experiments show that the two-dimensional non-linear diffusion equations allow us to reproduce qualitatively experimental results on particles segregation.
TWO-DIMENSIONAL MODELING OF CURRENT CIRCULATION AND CONTAMINANT TRANSPORT IN SURFACE WATERS
The main objectives of this paper are to briefly describe and evaluate three different applications of two-dimensional, depth-averaged, finite-element models for hydrodynamics (RMA2) and transport (RMA4) ([1] and [2], respectively), which were run using the FastTABS user interfac...
Measurement of air and VOC vapor fluxes during gas-driven soil remediation: bench-scale experiments.
Kim, Heonki; Kim, Taeyun; Shin, Seungyeop; Annable, Michael D
2012-09-04
In this laboratory study, an experimental method was developed for the quantitative analyses of gas fluxes in soil during advective air flow. One-dimensional column and two- and three-dimensional flow chamber models were used in this study. For the air flux measurement, n-octane vapor was used as a tracer, and it was introduced in the air flow entering the physical models. The tracer (n-octane) in the gas effluent from the models was captured for a finite period of time using a pack of activated carbon, which then was analyzed for the mass of n-octane. The air flux was calculated based on the mass of n-octane captured by the activated carbon and the inflow concentration. The measured air fluxes are in good agreement with the actual values for one- and two-dimensional model experiments. Using both the two- and three-dimensional models, the distribution of the air flux at the soil surface was measured. The distribution of the air flux was found to be affected by the depth of the saturated zone. The flux and flux distribution of a volatile contaminant (perchloroethene) was also measured by using the two-dimensional model. Quantitative information of both air and contaminant flux may be very beneficial for analyzing the performance of gas-driven subsurface remediation processes including soil vapor extraction and air sparging.
NASA Technical Reports Server (NTRS)
Shiau, Jyh-Jen; Wahba, Grace; Johnson, Donald R.
1986-01-01
A new method, based on partial spline models, is developed for including specified discontinuities in otherwise smooth two- and three-dimensional objective analyses. The method is appropriate for including tropopause height information in two- and three-dimensinal temperature analyses, using the O'Sullivan-Wahba physical variational method for analysis of satellite radiance data, and may in principle be used in a combined variational analysis of observed, forecast, and climate information. A numerical method for its implementation is described and a prototype two-dimensional analysis based on simulated radiosonde and tropopause height data is shown. The method may also be appropriate for other geophysical problems, such as modeling the ocean thermocline, fronts, discontinuities, etc.
NASA Astrophysics Data System (ADS)
Lei, Jie
2011-03-01
In order to understand the electronic and transport properties of organic field-effect transistor (FET) materials, we theoretically studied the polarons in two-dimensional systems using a tight-binding model with the Holstein type and Su--Schrieffer--Heeger type electron--lattice couplings. By numerical calculations, it was found that a carrier accepts four kinds of localization, which are named the point polaron, two-dimensional polaron, one-dimensional polaron, and the extended state. The degree of localization is sensitive to the following parameters in the model: the strength and type of electron--lattice couplings, and the signs and relative magnitudes of transfer integrals. When a parameter set for a single-crystal phase of pentacene is applied within the Holstein model, a considerably delocalized hole polaron is found, consistent with the bandlike transport mechanism.
Variational asymptotic modeling of composite dimensionally reducible structures
NASA Astrophysics Data System (ADS)
Yu, Wenbin
A general framework to construct accurate reduced models for composite dimensionally reducible structures (beams, plates and shells) was formulated based on two theoretical foundations: decomposition of the rotation tensor and the variational asymptotic method. Two engineering software systems, Variational Asymptotic Beam Sectional Analysis (VABS, new version) and Variational Asymptotic Plate and Shell Analysis (VAPAS), were developed. Several restrictions found in previous work on beam modeling were removed in the present effort. A general formulation of Timoshenko-like cross-sectional analysis was developed, through which the shear center coordinates and a consistent Vlasov model can be obtained. Recovery relations are given to recover the asymptotic approximations for the three-dimensional field variables. A new version of VABS has been developed, which is a much improved program in comparison to the old one. Numerous examples are given for validation. A Reissner-like model being as asymptotically correct as possible was obtained for composite plates and shells. After formulating the three-dimensional elasticity problem in intrinsic form, the variational asymptotic method was used to systematically reduce the dimensionality of the problem by taking advantage of the smallness of the thickness. The through-the-thickness analysis is solved by a one-dimensional finite element method to provide the stiffnesses as input for the two-dimensional nonlinear plate or shell analysis as well as recovery relations to approximately express the three-dimensional results. The known fact that there exists more than one theory that is asymptotically correct to a given order is adopted to cast the refined energy into a Reissner-like form. A two-dimensional nonlinear shell theory consistent with the present modeling process was developed. The engineering computer code VAPAS was developed and inserted into DYMORE to provide an efficient and accurate analysis of composite plates and shells. Numerical results are compared with the exact solutions, and the excellent agreement proves that one can use VAPAS to analyze composite plates and shells efficiently and accurately. In conclusion, rigorous modeling approaches were developed for composite beams, plates and shells within a general framework. No such consistent and general treatment is found in the literature. The associated computer programs VABS and VAPAS are envisioned to have many applications in industry.
An intermediate-scale model for thermal hydrology in low-relief permafrost-affected landscapes
Jan, Ahmad; Coon, Ethan T.; Painter, Scott L.; ...
2017-07-10
Integrated surface/subsurface models for simulating the thermal hydrology of permafrost-affected regions in a warming climate have recently become available, but computational demands of those new process-rich simu- lation tools have thus far limited their applications to one-dimensional or small two-dimensional simulations. We present a mixed-dimensional model structure for efficiently simulating surface/subsurface thermal hydrology in low-relief permafrost regions at watershed scales. The approach replaces a full three-dimensional system with a two-dimensional overland thermal hydrology system and a family of one-dimensional vertical columns, where each column represents a fully coupled surface/subsurface thermal hydrology system without lateral flow. The system is then operatormore » split, sequentially updating the overland flow system without sources and the one-dimensional columns without lateral flows. We show that the app- roach is highly scalable, supports subcycling of different processes, and compares well with the corresponding fully three-dimensional representation at significantly less computational cost. Those advances enable recently developed representations of freezing soil physics to be coupled with thermal overland flow and surface energy balance at scales of 100s of meters. Furthermore developed and demonstrated for permafrost thermal hydrology, the mixed-dimensional model structure is applicable to integrated surface/subsurface thermal hydrology in general.« less
Model of chiral spin liquids with Abelian and non-Abelian topological phases
NASA Astrophysics Data System (ADS)
Chen, Jyong-Hao; Mudry, Christopher; Chamon, Claudio; Tsvelik, A. M.
2017-12-01
We present a two-dimensional lattice model for quantum spin-1/2 for which the low-energy limit is governed by four flavors of strongly interacting Majorana fermions. We study this low-energy effective theory using two alternative approaches. The first consists of a mean-field approximation. The second consists of a random phase approximation (RPA) for the single-particle Green's functions of the Majorana fermions built from their exact forms in a certain one-dimensional limit. The resulting phase diagram consists of two competing chiral phases, one with Abelian and the other with non-Abelian topological order, separated by a continuous phase transition. Remarkably, the Majorana fermions propagate in the two-dimensional bulk, as in the Kitaev model for a spin liquid on the honeycomb lattice. We identify the vison fields, which are mobile (they are static in the Kitaev model) domain walls propagating along only one of the two space directions.
NASA Astrophysics Data System (ADS)
Di Nucci, Carmine
2018-05-01
This note examines the two-dimensional unsteady isothermal free surface flow of an incompressible fluid in a non-deformable, homogeneous, isotropic, and saturated porous medium (with zero recharge and neglecting capillary effects). Coupling a Boussinesq-type model for nonlinear water waves with Darcy's law, the two-dimensional flow problem is solved using one-dimensional model equations including vertical effects and seepage face. In order to take into account the seepage face development, the system equations (given by the continuity and momentum equations) are completed by an integral relation (deduced from the Cauchy theorem). After testing the model against data sets available in the literature, some numerical simulations, concerning the unsteady flow through a rectangular dam (with an impermeable horizontal bottom), are presented and discussed.
Numerical modelling techniques of soft soil improvement via stone columns: A brief review
NASA Astrophysics Data System (ADS)
Zukri, Azhani; Nazir, Ramli
2018-04-01
There are a number of numerical studies on stone column systems in the literature. Most of the studies found were involved with two-dimensional analysis of the stone column behaviour, while only a few studies used three-dimensional analysis. The most popular software utilised in those studies was Plaxis 2D and 3D. Other types of software that used for numerical analysis are DIANA, EXAMINE, ZSoil, ABAQUS, ANSYS, NISA, GEOSTUDIO, CRISP, TOCHNOG, CESAR, GEOFEM (2D & 3D), FLAC, and FLAC 3. This paper will review the methodological approaches to model stone column numerically, both in two-dimensional and three-dimensional analyses. The numerical techniques and suitable constitutive model used in the studies will also be discussed. In addition, the validation methods conducted were to verify the numerical analysis conducted will be presented. This review paper also serves as a guide for junior engineers through the applicable procedures and considerations when constructing and running a two or three-dimensional numerical analysis while also citing numerous relevant references.
Observed light yield of scintillation pixels: Extending the two-ray model
NASA Astrophysics Data System (ADS)
Kantorski, Igor; Jurkowski, Jacek; Drozdowski, Winicjusz
2016-09-01
In this paper we propose an extended, two dimensional model describing the propagation of scintillation photons inside a cuboid crystal until they reach a PMT window. In the simplest approach the model considers two main reasons for light losses: standard absorption obeying the classical Lambert-Beer law and non-ideal reflectivity of the "mummy" covering formed by several layers of Teflon tape wrapping the sample. Results of the model calculations are juxtaposed with experimental data as well as with predictions of an earlier, one dimensional model.
Efficient processing of two-dimensional arrays with C or C++
Donato, David I.
2017-07-20
Because fast and efficient serial processing of raster-graphic images and other two-dimensional arrays is a requirement in land-change modeling and other applications, the effects of 10 factors on the runtimes for processing two-dimensional arrays with C and C++ are evaluated in a comparative factorial study. This study’s factors include the choice among three C or C++ source-code techniques for array processing; the choice of Microsoft Windows 7 or a Linux operating system; the choice of 4-byte or 8-byte array elements and indexes; and the choice of 32-bit or 64-bit memory addressing. This study demonstrates how programmer choices can reduce runtimes by 75 percent or more, even after compiler optimizations. Ten points of practical advice for faster processing of two-dimensional arrays are offered to C and C++ programmers. Further study and the development of a C and C++ software test suite are recommended.Key words: array processing, C, C++, compiler, computational speed, land-change modeling, raster-graphic image, two-dimensional array, software efficiency
NASA Astrophysics Data System (ADS)
Soeryana, E.; Fadhlina, N.; Sukono; Rusyaman, E.; Supian, S.
2017-01-01
Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on logarithmic utility function. Non constant mean analysed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analysed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyse some Islamic stocks in Indonesia. The expected result is to get the proportion of investment in each Islamic stock analysed.
NASA Astrophysics Data System (ADS)
Soeryana, Endang; Halim, Nurfadhlina Bt Abdul; Sukono, Rusyaman, Endang; Supian, Sudradjat
2017-03-01
Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on the Negative Exponential Utility Function. Non constant mean analyzed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analyzed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyze some stocks in Indonesia. The expected result is to get the proportion of investment in each stock analyzed
Space Weather Services of Korea
NASA Astrophysics Data System (ADS)
Yoon, KiChang; Kim, Jae-Hun; Kim, Young Yun; Kwon, Yongki; Wi, Gwan-sik
2016-07-01
The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition. KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).
Space Weather Services of Korea
NASA Astrophysics Data System (ADS)
Yoon, K.; Hong, S.; Jangsuk, C.; Dong Kyu, K.; Jinyee, C.; Yeongoh, C.
2016-12-01
The Korean Space Weather Center (KSWC) of the National Radio Research Agency (RRA) is a government agency which is the official source of space weather information for Korean Government and the primary action agency of emergency measure to severe space weather condition. KSWC's main role is providing alerts, watches, and forecasts in order to minimize the space weather impacts on both of public and commercial sectors of satellites, aviation, communications, navigations, power grids, and etc. KSWC is also in charge of monitoring the space weather condition and conducting research and development for its main role of space weather operation in Korea. In this study, we will present KSWC's recent efforts on development of application-oriented space weather research products and services on user needs, and introduce new international collaborative projects, such as IPS-Driven Enlil model, DREAM model estimating electron in satellite orbit, global network of DSCOVR and STEREO satellites tracking, and ARMAS (Automated Radiation Measurement for Aviation Safety).
NASA Technical Reports Server (NTRS)
Lee, S. S.; Sengupta, S.; Nwadike, E. V.
1982-01-01
The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter.
Role of dimensionality in Axelrod's model for the dissemination of culture
NASA Astrophysics Data System (ADS)
Klemm, Konstantin; Eguíluz, Víctor M.; Toral, Raúl; Miguel, Maxi San
2003-09-01
We analyze a model of social interaction in one- and two-dimensional lattices for a moderate number of features. We introduce an order parameter as a function of the overlap between neighboring sites. In a one-dimensional chain, we observe that the dynamics is consistent with a second-order transition, where the order parameter changes continuously and the average domain diverges at the transition point. However, in a two-dimensional lattice the order parameter is discontinuous at the transition point characteristic of a first-order transition between an ordered and a disordered state.
Two-dimensional Anderson-Hubbard model in the DMFT + {Sigma} approximation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuchinskii, E. Z., E-mail: kuchinsk@iep.uran.ru; Kuleeva, N. A.; Nekrasov, I. A.
The density of states, the dynamic (optical) conductivity, and the phase diagram of the paramagnetic two-dimensional Anderson-Hubbard model with strong correlations and disorder are analyzed within the generalized dynamical mean field theory (DMFT + {Sigma} approximation). Strong correlations are accounted by the DMFT, while disorder is taken into account via the appropriate generalization of the self-consistent theory of localization. We consider the two-dimensional system with the rectangular 'bare' density of states (DOS). The DMFT effective single-impurity problem is solved by numerical renormalization group (NRG). The 'correlated metal,' Mott insulator, and correlated Anderson insulator phases are identified from the evolution ofmore » the density of states, optical conductivity, and localization length, demonstrating both Mott-Hubbard and Anderson metal-insulator transitions in two-dimensional systems of finite size, allowing us to construct the complete zero-temperature phase diagram of the paramagnetic Anderson-Hubbard model. The localization length in our approximation is practically independent of the strength of Hubbard correlations. But the divergence of the localization length in a finite-size two-dimensional system at small disorder signifies the existence of an effective Anderson transition.« less
Guo, Qi; Shen, Shu-Ting
2016-04-29
There are two major classes of cardiac tissue models: the ionic model and the FitzHugh-Nagumo model. During computer simulation, each model entails solving a system of complex ordinary differential equations and a partial differential equation with non-flux boundary conditions. The reproducing kernel method possesses significant applications in solving partial differential equations. The derivative of the reproducing kernel function is a wavelet function, which has local properties and sensitivities to singularity. Therefore, study on the application of reproducing kernel would be advantageous. Applying new mathematical theory to the numerical solution of the ventricular muscle model so as to improve its precision in comparison with other methods at present. A two-dimensional reproducing kernel function inspace is constructed and applied in computing the solution of two-dimensional cardiac tissue model by means of the difference method through time and the reproducing kernel method through space. Compared with other methods, this method holds several advantages such as high accuracy in computing solutions, insensitivity to different time steps and a slow propagation speed of error. It is suitable for disorderly scattered node systems without meshing, and can arbitrarily change the location and density of the solution on different time layers. The reproducing kernel method has higher solution accuracy and stability in the solutions of the two-dimensional cardiac tissue model.
A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.
2013-07-25
This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load valuesmore » to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.« less
Global isostatic geoid anomalies for plate and boundary layer models of the lithosphere
NASA Technical Reports Server (NTRS)
Hager, B. H.
1981-01-01
Commonly used one dimensional geoid models predict that the isostatic geoid anomaly over old ocean basins for the boundary layer thermal model of the lithosphere is a factor of two greater than that for the plate model. Calculations presented, using the spherical analogues of the plate and boundary layer thermal models, show that for the actual global distribution of plate ages, one dimensional models are not accurate and a spherical, fully three dimensional treatment is necessary. The maximum difference in geoid heights predicted for the two models is only about two meters. The thermal structure of old lithosphere is unlikely to be resolvable using global geoid anomalies. Stripping the effects of plate aging and a hypothetical uniform, 35 km, isostatically-compensated continental crust from the observed geoid emphasizes that the largest-amplitude geoid anomaly is the geoid low of almost 120 m over West Antarctica, a factor of two greater than the low of 60 m over Ceylon.
Laudyn, Urszula A; Jung, Paweł S; Zegadło, Krzysztof B; Karpierz, Miroslaw A; Assanto, Gaetano
2014-11-15
We demonstrate the evolution of higher order one-dimensional guided modes into two-dimensional solitary waves in a reorientational medium. The observations, carried out at two different wavelengths in chiral nematic liquid crystals, are in good agreement with a simple nonlocal nonlinear model.
NASA Technical Reports Server (NTRS)
Lee, S. S.; Nwadike, E. V.; Sinha, S. E.
1982-01-01
The theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model are described. Model verification at two sites, a separate user's manual for each model are included. The 3-D model has two forms: free surface and rigid lid. The former allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth, estuaries and coastal regions. The latter is suited for small surface wave heights compared to depth because surface elevation was removed as a parameter. These models allow computation of time dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free surface model also provides surface height variations with time.
Numerical two-dimensional calculations of the formation of the solar nebula
NASA Technical Reports Server (NTRS)
Bodenheimer, Peter H.
1991-01-01
Numerical two dimensional calculations of the formation of the solar nebula are presented. The following subject areas are covered: (1) observational constraints of the properties of the initial solar nebula; (2) the physical problem; (3) review if two dimensional calculations of the formation phase; (4) recent models with hydrodynamics and radiative transport; and (5) further evolution of the system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Cheng-Hsien; Department of Water Resources and Environmental Engineering, Tamkang University, New Taipei City 25137, Taiwan; Low, Ying Min, E-mail: ceelowym@nus.edu.sg
2016-05-15
Sediment transport is fundamentally a two-phase phenomenon involving fluid and sediments; however, many existing numerical models are one-phase approaches, which are unable to capture the complex fluid-particle and inter-particle interactions. In the last decade, two-phase models have gained traction; however, there are still many limitations in these models. For example, several existing two-phase models are confined to one-dimensional problems; in addition, the existing two-dimensional models simulate only the region outside the sand bed. This paper develops a new three-dimensional two-phase model for simulating sediment transport in the sheet flow condition, incorporating recently published rheological characteristics of sediments. The enduring-contact, inertial,more » and fluid viscosity effects are considered in determining sediment pressure and stresses, enabling the model to be applicable to a wide range of particle Reynolds number. A k − ε turbulence model is adopted to compute the Reynolds stresses. In addition, a novel numerical scheme is proposed, thus avoiding numerical instability caused by high sediment concentration and allowing the sediment dynamics to be computed both within and outside the sand bed. The present model is applied to two classical problems, namely, sheet flow and scour under a pipeline with favorable results. For sheet flow, the computed velocity is consistent with measured data reported in the literature. For pipeline scour, the computed scour rate beneath the pipeline agrees with previous experimental observations. However, the present model is unable to capture vortex shedding; consequently, the sediment deposition behind the pipeline is overestimated. Sensitivity analyses reveal that model parameters associated with turbulence have strong influence on the computed results.« less
Two-dimensional habitat modeling in the Yellowstone/Upper Missouri River system
Waddle, T. J.; Bovee, K.D.; Bowen, Z.H.
1997-01-01
This study is being conducted to provide the aquatic biology component of a decision support system being developed by the U.S. Bureau of Reclamation. In an attempt to capture the habitat needs of Great Plains fish communities we are looking beyond previous habitat modeling methods. Traditional habitat modeling approaches have relied on one-dimensional hydraulic models and lumped compositional habitat metrics to describe aquatic habitat. A broader range of habitat descriptors is available when both composition and configuration of habitats is considered. Habitat metrics that consider both composition and configuration can be adapted from terrestrial biology. These metrics are most conveniently accessed with spatially explicit descriptors of the physical variables driving habitat composition. Two-dimensional hydrodynamic models have advanced to the point that they may provide the spatially explicit description of physical parameters needed to address this problem. This paper reports progress to date on applying two-dimensional hydraulic and habitat models on the Yellowstone and Missouri Rivers and uses examples from the Yellowstone River to illustrate the configurational metrics as a new tool for assessing riverine habitats.
Gate-controlled-diodes in silicon-on-sapphire: A computer simulation
NASA Technical Reports Server (NTRS)
Gassaway, J. D.
1974-01-01
The computer simulation of the electrical behavior of a Gate-Controlled Diode (GCD) fabricated in Silicon-On-Sapphire (SOS) was described. A procedure for determining lifetime profiles from capacitance and reverse current measurements on the GCD was established. Chapter 1 discusses the SOS structure and points out the need of lifetime profiles to assist in device design for GCD's and bipolar transistors. Chapter 2 presents the one-dimensional analytical formula for electrostatic analysis of the SOS-GCD which are useful for data interpretation and setting boundary conditions on a simplified two-dimensional analysis. Chapter 3 gives the results of a two-dimensional analysis which treats the field as one-dimensional until the silicon film is depleted and the field penetrates the sapphire substrate. Chapter 4 describes a more complete two-dimensional model and gives results of programs implementing the model.
1978-01-20
adopting new short- range, visually aimed weapons as secondary arma - FOXBAT ment on many of their deployed interceptors. These weapons should enhance...i egrtedwit letal eapns. EW threat, and provide practice in tactics and:1weapon system, integrated with lethal weapons. equipment operations
1999-09-01
application, a complete specification will require one or more companion documents, as follows. 1. Profile Specification Documents A Profile...Rio de Janeiro - RJ - Brazil 21. Diretoria de Sistemas de Armas da Marinha Rua Primeiro de Marco, 118 Rio de Janeiro - RJ - Brazil CEP 20010 22
Fatone, Stefania; Johnson, William Brett; Tucker, Kerice
2016-04-01
Misalignment of an articulated ankle-foot orthosis joint axis with the anatomic joint axis may lead to discomfort, alterations in gait, and tissue damage. Theoretical, two-dimensional models describe the consequences of misalignments, but cannot capture the three-dimensional behavior of ankle-foot orthosis use. The purpose of this project was to develop a model to describe the effects of ankle-foot orthosis ankle joint misalignment in three dimensions. Computational simulation. Three-dimensional scans of a leg and ankle-foot orthosis were incorporated into a link segment model where the ankle-foot orthosis joint axis could be misaligned with the anatomic ankle joint axis. The leg/ankle-foot orthosis interface was modeled as a network of nodes connected by springs to estimate interface pressure. Motion between the leg and ankle-foot orthosis was calculated as the ankle joint moved through a gait cycle. While the three-dimensional model corroborated predictions of the previously published two-dimensional model that misalignments in the anterior -posterior direction would result in greater relative motion compared to misalignments in the proximal -distal direction, it provided greater insight showing that misalignments have asymmetrical effects. The three-dimensional model has been incorporated into a freely available computer program to assist others in understanding the consequences of joint misalignments. Models and simulations can be used to gain insight into functioning of systems of interest. We have developed a three-dimensional model to assess the effect of ankle joint axis misalignments in ankle-foot orthoses. The model has been incorporated into a freely available computer program to assist understanding of trainees and others interested in orthotics. © The International Society for Prosthetics and Orthotics 2014.
NASA Technical Reports Server (NTRS)
Lee, S. S.; Sengupta, S.; Tuann, S. Y.; Lee, C. R.
1982-01-01
The six-volume report: describes the theory of a three-dimensional (3-D) mathematical thermal discharge model and a related one-dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth. These models allow computation of time-dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions.
NASA Astrophysics Data System (ADS)
Fedors, R. W.; Painter, S. L.
2004-12-01
Temperature gradients along the thermally-perturbed drifts of the potential high-level waste repository at Yucca Mountain, Nevada, will drive natural convection and associated heat and mass transfer along drifts. A three-dimensional, dual-permeability, thermohydrological model of heat and mass transfer was used to estimate the magnitude of temperature gradients along a drift. Temperature conditions along heated drifts are needed to support estimates of repository-edge cooling and as input to computational fluid dynamics modeling of in-drift axial convection and the cold-trap process. Assumptions associated with abstracted heat transfer models and two-dimensional thermohydrological models weakly coupled to mountain-scale thermal models can readily be tested using the three-dimensional thermohydrological model. Although computationally expensive, the fully coupled three-dimensional thermohydrological model is able to incorporate lateral heat transfer, including host rock processes of conduction, convection in gas phase, advection in liquid phase, and latent-heat transfer. Results from the three-dimensional thermohydrological model showed that weakly coupling three-dimensional thermal and two-dimensional thermohydrological models lead to underestimates of temperatures and underestimates of temperature gradients over large portions of the drift. The representative host rock thermal conductivity needed for abstracted heat transfer models are overestimated using the weakly coupled models. If axial flow patterns over large portions of drifts are not impeded by the strong cross-sectional flow patterns imparted by the heat rising directly off the waste package, condensation from the cold-trap process will not be limited to the extreme ends of each drift. Based on the three-dimensional thermohydrological model, axial temperature gradients occur sooner over a larger portion of the drift, though high gradients nearest the edge of the potential repository are dampened. This abstract is an independent product of CNWRA and does not necessarily reflect the view or regulatory position of the Nuclear Regulatory Commission.
Wake Management Strategies for Reduction of Turbomachinery Fan Noise
NASA Technical Reports Server (NTRS)
Waitz, Ian A.
1998-01-01
The primary objective of our work was to evaluate and test several wake management schemes for the reduction of turbomachinery fan noise. Throughout the course of this work we relied on several tools. These include 1) Two-dimensional steady boundary-layer and wake analyses using MISES (a thin-shear layer Navier-Stokes code), 2) Two-dimensional unsteady wake-stator interaction simulations using UNSFLO, 3) Three-dimensional, steady Navier-Stokes rotor simulations using NEWT, 4) Internal blade passage design using quasi-one-dimensional passage flow models developed at MIT, 5) Acoustic modeling using LINSUB, 6) Acoustic modeling using VO72, 7) Experiments in a low-speed cascade wind-tunnel, and 8) ADP fan rig tests in the MIT Blowdown Compressor.
Modeling of two-dimensional overland flow in a vegetative filter
Matthew J. Helmers; Dean E. Eisenhauer; Thomas G. Franti; Michael G. Dosskey
2002-01-01
Water transports sediment and other pollutants through vegetative filters. It is often assumed that the overland flow is uniformly distributed across the vegetative filter, but this research indicates otherwise. The objective of this study was to model the two-dimensional overland water flow through a vegetative filter, accounting for variation in microtopography,...
Analysis of spatial thermal field in a magnetic bearing
NASA Astrophysics Data System (ADS)
Wajnert, Dawid; Tomczuk, Bronisław
2018-03-01
This paper presents two mathematical models for temperature field analysis in a new hybrid magnetic bearing. Temperature distributions have been calculated using a three dimensional simulation and a two dimensional one. A physical model for temperature testing in the magnetic bearing has been developed. Some results obtained from computer simulations were compared with measurements.
NASA Astrophysics Data System (ADS)
Turkin, Yaroslav V.; Kuptsov, Pavel V.
2018-04-01
A quantum model of spin dynamics of spin-orbit coupled two-dimensional electron gas in the presence of strong high- frequency electromagnetic field is suggested. Interaction of electrons with optical phonons is taken into account in the second order of perturbation theory.
Two-dimensional finite element heat transfer model of softwood. Part II, Macrostructural effects
Hongmei Gu; John F. Hunt
2006-01-01
A two-dimensional finite element model was used to study the effects of structural features on transient heat transfer in softwood lumber with various orientations. Transient core temperature was modeled for lumber samples âcutâ from various locations within a simulated log. The effects of ring orientation, earlywood to latewood (E/L) ratio, and ring density were...
Statistical Signal Models and Algorithms for Image Analysis
1984-10-25
In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vostokov, N. V., E-mail: vostokov@ipm.sci-nnov.ru; Shashkin, V. I.
2015-11-28
We consider the problem of non-resonant detection of terahertz signals in a short gate length field-effect transistor having a two-dimensional electron channel with zero external bias between the source and the drain. The channel resistance, gate-channel capacitance, and quadratic nonlinearity parameter of the transistor during detection as a function of the gate bias voltage are studied. Characteristics of detection of the transistor connected in an antenna with real impedance are analyzed. The consideration is based on both a simple one-dimensional model of the transistor and allowance for the two-dimensional distribution of the electric field in the transistor structure. The resultsmore » given by the different models are discussed.« less
Techniques for interpretation of geoid anomalies
NASA Technical Reports Server (NTRS)
Chapman, M. E.
1979-01-01
For purposes of geological interpretation, techniques are developed to compute directly the geoid anomaly over models of density within the earth. Ideal bodies such as line segments, vertical sheets, and rectangles are first used to calculate the geoid anomaly. Realistic bodies are modeled with formulas for two-dimensional polygons and three-dimensional polyhedra. By using Fourier transform methods the two-dimensional geoid is seen to be a filtered version of the gravity field, in which the long-wavelength components are magnified and the short-wavelength components diminished.
On the dynamics of the Ising model of cooperative phenomena
Montroll, Elliott W.
1981-01-01
A two-dimensional (and to some degree three-dimensional) version of Glauber's one-dimensional spin relaxation model is described. The model is constructed to yield the Ising model of cooperative phenomena at equilibrium. A complete hierarchy of differential equations for multispin correlation functions is constructed. Some remarks are made concerning the solution of them for the initial value problem of determining the relaxation of an initial set of spin distributions. PMID:16592955
NASA Technical Reports Server (NTRS)
Ukanwa, A. O.; Stermole, F. J.; Golden, J. O.
1972-01-01
Natural convection effects in phase change thermal control devices were studied. A mathematical model was developed to evaluate natural convection effects in a phase change test cell undergoing solidification. Although natural convection effects are minimized in flight spacecraft, all phase change devices are ground tested. The mathematical approach to the problem was to first develop a transient two-dimensional conduction heat transfer model for the solidification of a normal paraffin of finite geometry. Next, a transient two-dimensional model was developed for the solidification of the same paraffin by a combined conduction-natural-convection heat transfer model. Throughout the study, n-hexadecane (n-C16H34) was used as the phase-change material in both the theoretical and the experimental work. The models were based on the transient two-dimensional finite difference solutions of the energy, continuity, and momentum equations.
Studies for the 3-Dimensional Structure, Composition, and Dynamic of Io's Atmosphere
NASA Technical Reports Server (NTRS)
Smyth, William H.
2001-01-01
Research work is discussed for the following: (1) the exploration of new H and Cl chemistry in Io's atmosphere using the already developed two-dimensional multi-species hydrodynamic model of Wong and Smyth; and (2) for the development of a new three-dimensional multi-species hydrodynamic model for Io's atmosphere.
Model Prediction of Self-Rotating Excitons in Two-Dimensional Transition-Metal Dichalcogenides
NASA Astrophysics Data System (ADS)
Trushin, Maxim; Goerbig, Mark Oliver; Belzig, Wolfgang
2018-05-01
Using the quasiclassical concept of Berry curvature we demonstrate that a Dirac exciton—a pair of Dirac quasiparticles bound by Coulomb interactions—inevitably possesses an intrinsic angular momentum making the exciton effectively self-rotating. The model is applied to excitons in two-dimensional transition metal dichalcogenides, in which the charge carriers are known to be described by a Dirac-like Hamiltonian. We show that the topological self-rotation strongly modifies the exciton spectrum and, as a consequence, resolves the puzzle of the overestimated two-dimensional polarizability employed to fit earlier spectroscopic measurements.
A Two-Dimensional Linear Bicharacteristic Scheme for Electromagnetics
NASA Technical Reports Server (NTRS)
Beggs, John H.
2002-01-01
The upwind leapfrog or Linear Bicharacteristic Scheme (LBS) has previously been implemented and demonstrated on one-dimensional electromagnetic wave propagation problems. This memorandum extends the Linear Bicharacteristic Scheme for computational electromagnetics to model lossy dielectric and magnetic materials and perfect electrical conductors in two dimensions. This is accomplished by proper implementation of the LBS for homogeneous lossy dielectric and magnetic media and for perfect electrical conductors. Both the Transverse Electric and Transverse Magnetic polarizations are considered. Computational requirements and a Fourier analysis are also discussed. Heterogeneous media are modeled through implementation of surface boundary conditions and no special extrapolations or interpolations at dielectric material boundaries are required. Results are presented for two-dimensional model problems on uniform grids, and the Finite Difference Time Domain (FDTD) algorithm is chosen as a convenient reference algorithm for comparison. The results demonstrate that the two-dimensional explicit LBS is a dissipation-free, second-order accurate algorithm which uses a smaller stencil than the FDTD algorithm, yet it has less phase velocity error.
Nonclassical models of the theory of plates and shells
NASA Astrophysics Data System (ADS)
Annin, Boris D.; Volchkov, Yuri M.
2017-11-01
Publications dealing with the study of methods of reducing a three-dimensional problem of the elasticity theory to a two-dimensional problem of the theory of plates and shells are reviewed. Two approaches are considered: the use of kinematic and force hypotheses and expansion of solutions of the three-dimensional elasticity theory in terms of the complete system of functions. Papers where a three-dimensional problem is reduced to a two-dimensional problem with the use of several approximations of each of the unknown functions (stresses and displacements) by segments of the Legendre polynomials are also reviewed.
Columnar organization of orientation domains in V1
NASA Astrophysics Data System (ADS)
Liedtke, Joscha; Wolf, Fred
In the primary visual cortex (V1) of primates and carnivores, the functional architecture of basic stimulus selectivities appears similar across cortical layers (Hubel & Wiesel, 1962) justifying the use of two-dimensional cortical models and disregarding organization in the third dimension. Here we show theoretically that already small deviations from an exact columnar organization lead to non-trivial three-dimensional functional structures. We extend two-dimensional random field models (Schnabel et al., 2007) to a three-dimensional cortex by keeping a typical scale in each layer and introducing a correlation length in the third, columnar dimension. We examine in detail the three-dimensional functional architecture for different cortical geometries with different columnar correlation lengths. We find that (i) topological defect lines are generally curved and (ii) for large cortical curvatures closed loops and reconnecting topological defect lines appear. This theory extends the class of random field models by introducing a columnar dimension and provides a systematic statistical assessment of the three-dimensional functional architecture of V1 (see also (Tanaka et al., 2011)).
MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors.
Hedeker, D; Gibbons, R D
1996-05-01
MIXREG is a program that provides estimates for a mixed-effects regression model (MRM) for normally-distributed response data including autocorrelated errors. This model can be used for analysis of unbalanced longitudinal data, where individuals may be measured at a different number of timepoints, or even at different timepoints. Autocorrelated errors of a general form or following an AR(1), MA(1), or ARMA(1,1) form are allowable. This model can also be used for analysis of clustered data, where the mixed-effects model assumes data within clusters are dependent. The degree of dependency is estimated jointly with estimates of the usual model parameters, thus adjusting for clustering. MIXREG uses maximum marginal likelihood estimation, utilizing both the EM algorithm and a Fisher-scoring solution. For the scoring solution, the covariance matrix of the random effects is expressed in its Gaussian decomposition, and the diagonal matrix reparameterized using the exponential transformation. Estimation of the individual random effects is accomplished using an empirical Bayes approach. Examples illustrating usage and features of MIXREG are provided.
Atmospheric mold spore counts in relation to meteorological parameters
NASA Astrophysics Data System (ADS)
Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.
Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.
Extended frequency turbofan model
NASA Technical Reports Server (NTRS)
Mason, J. R.; Park, J. W.; Jaekel, R. F.
1980-01-01
The fan model was developed using two dimensional modeling techniques to add dynamic radial coupling between the core stream and the bypass stream of the fan. When incorporated into a complete TF-30 engine simulation, the fan model greatly improved compression system frequency response to planar inlet pressure disturbances up to 100 Hz. The improved simulation also matched engine stability limits at 15 Hz, whereas the one dimensional fan model required twice the inlet pressure amplitude to stall the simulation. With verification of the two dimensional fan model, this program formulated a high frequency F-100(3) engine simulation using row by row compression system characteristics. In addition to the F-100(3) remote splitter fan, the program modified the model fan characteristics to simulate a proximate splitter version of the F-100(3) engine.
NASA Technical Reports Server (NTRS)
Noor, A. K.; Malik, M.
2000-01-01
A study is made of the effects of variation in the lamination and geometric parameters, and boundary conditions of multi-layered composite panels on the accuracy of the detailed response characteristics obtained by five different modeling approaches. The modeling approaches considered include four two-dimensional models, each with five parameters to characterize the deformation in the thickness direction, and a predictor-corrector approach with twelve displacement parameters. The two-dimensional models are first-order shear deformation theory, third-order theory; a theory based on trigonometric variation of the transverse shear stresses through the thickness, and a discrete layer theory. The combination of the following four key elements distinguishes the present study from previous studies reported in the literature: (1) the standard of comparison is taken to be the solutions obtained by using three-dimensional continuum models for each of the individual layers; (2) both mechanical and thermal loadings are considered; (3) boundary conditions other than simply supported edges are considered; and (4) quantities compared include detailed through-the-thickness distributions of transverse shear and transverse normal stresses. Based on the numerical studies conducted, the predictor-corrector approach appears to be the most effective technique for obtaining accurate transverse stresses, and for thermal loading, none of the two-dimensional models is adequate for calculating transverse normal stresses, even when used in conjunction with three-dimensional equilibrium equations.
Capacity of Heterogeneous Mobile Wireless Networks with D-Delay Transmission Strategy.
Wu, Feng; Zhu, Jiang; Xi, Zhipeng; Gao, Kai
2016-03-25
This paper investigates the capacity problem of heterogeneous wireless networks in mobility scenarios. A heterogeneous network model which consists of n normal nodes and m helping nodes is proposed. Moreover, we propose a D-delay transmission strategy to ensure that every packet can be delivered to its destination nodes with limited delay. Different from most existing network schemes, our network model has a novel two-tier architecture. The existence of helping nodes greatly improves the network capacity. Four types of mobile networks are studied in this paper: i.i.d. fast mobility model and slow mobility model in two-dimensional space, i.i.d. fast mobility model and slow mobility model in three-dimensional space. Using the virtual channel model, we present an intuitive analysis of the capacity of two-dimensional mobile networks and three-dimensional mobile networks, respectively. Given a delay constraint D, we derive the asymptotic expressions for the capacity of the four types of mobile networks. Furthermore, the impact of D and m to the capacity of the whole network is analyzed. Our findings provide great guidance for the future design of the next generation of networks.
James, Andrew J. A.; Konik, Robert M.; Lecheminant, Philippe; ...
2018-02-26
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symme-tries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one andmore » two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1+1D quantum chro-modynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. Lastly, we describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
James, Andrew J. A.; Konik, Robert M.; Lecheminant, Philippe
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symme-tries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one andmore » two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1+1D quantum chro-modynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. Lastly, we describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.« less
NASA Astrophysics Data System (ADS)
James, Andrew J. A.; Konik, Robert M.; Lecheminant, Philippe; Robinson, Neil J.; Tsvelik, Alexei M.
2018-04-01
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symmetries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb–Liniger model, 1 + 1D quantum chromodynamics, as well as Landau–Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.
New developments in the theoretical treatment of low dimensional strongly correlated systems.
James, Andrew J A; Konik, Robert M; Lecheminant, Philippe; Robinson, Neil; Tsvelik, Alexei M
2017-10-09
We review two important non-perturbative approaches for extracting the physics of low- dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of confor- mal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symme- tries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1+1D quantum chro- modynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics. © 2017 IOP Publishing Ltd.
James, Andrew J A; Konik, Robert M; Lecheminant, Philippe; Robinson, Neil J; Tsvelik, Alexei M
2018-02-26
We review two important non-perturbative approaches for extracting the physics of low-dimensional strongly correlated quantum systems. Firstly, we start by providing a comprehensive review of non-Abelian bosonization. This includes an introduction to the basic elements of conformal field theory as applied to systems with a current algebra, and we orient the reader by presenting a number of applications of non-Abelian bosonization to models with large symmetries. We then tie this technique into recent advances in the ability of cold atomic systems to realize complex symmetries. Secondly, we discuss truncated spectrum methods for the numerical study of systems in one and two dimensions. For one-dimensional systems we provide the reader with considerable insight into the methodology by reviewing canonical applications of the technique to the Ising model (and its variants) and the sine-Gordon model. Following this we review recent work on the development of renormalization groups, both numerical and analytical, that alleviate the effects of truncating the spectrum. Using these technologies, we consider a number of applications to one-dimensional systems: properties of carbon nanotubes, quenches in the Lieb-Liniger model, 1 + 1D quantum chromodynamics, as well as Landau-Ginzburg theories. In the final part we move our attention to consider truncated spectrum methods applied to two-dimensional systems. This involves combining truncated spectrum methods with matrix product state algorithms. We describe applications of this method to two-dimensional systems of free fermions and the quantum Ising model, including their non-equilibrium dynamics.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaufman, Allan N.; Tracy, Eugene R.; Brizard, Alain J.
The process of resonant wave conversion (often called linear mode conversion) has traditionally been analyzed with a spatially one-dimensional slab model, for which the rays propagate in a two-dimensional phase space. However, it has recently been shown [E. R. Tracy and A. N. Kaufman, Phys. Rev. Lett. 91, 130402 (2003)] that multidimensional rays have a helical structure for conversion in two or more spatial dimensions (if their dispersion matrix is generic). In that case, a one-dimensional model is inadequate; a correct analysis requires two spatial dimensions and, thus, four-dimensional phase space. A cold-plasma model is introduced in this paper whichmore » exhibits ray helicity in conversion regions where the density and magnetic field gradients are significantly nonparallel. For illustration, such regions are identified in a model of the poloidal plane of a deuterium-tritium tokamak plasma. In each conversion region, characterized by a six-sector topology, rays in the sector for incident and reflected magnetosonic waves exhibit significant helicity. A detailed analytic and numerical study of helical rays in this sector is developed for a 'symmetric-wedge' model.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kaufman, Allan N.; Tracy, Eugene R.; Brizard, Alain J.
The process of resonant wave conversion (often called linear mode conversion) has traditionally been analyzed with a spatially one-dimensional slab model, for which the rays propagate in a two-dimensional phase space. However, it has recently been shown [E.R. Tracy and A.N. Kaufman, Phys. Rev. Lett. 91, 130402 (2003)] that multidimensional rays have a helical structure for conversion in two or more spatial dimensions (if their dispersion matrix is generic). In that case, a one-dimensional model is inadequate; a correct analysis requires two spatial dimensions and, thus, four-dimensional phase space. In this paper we show that a cold plasma model willmore » exhibit ray helicity in conversion regions where the density and magnetic field gradients are significantly non-parallel. For illustration, we examine a model of the poloidal plane of a deuterium-tritium tokamak plasma, and identify such a region. In this region, characterized by a six-sector topology, rays in the sector for incident and reflected magnetosonic waves exhibit significant helicity. We introduce a ''symmetric-wedge'' model, to develop a detailed analytic and numerical study of helical rays in this sector.« less
A VLSI implementation for synthetic aperture radar image processing
NASA Technical Reports Server (NTRS)
Premkumar, A.; Purviance, J.
1990-01-01
A simple physical model for the Synthetic Aperture Radar (SAR) is presented. This model explains the one dimensional and two dimensional nature of the received SAR signal in the range and azimuth directions. A time domain correlator, its algorithm, and features are explained. The correlator is ideally suited for VLSI implementation. A real time SAR architecture using these correlators is proposed. In the proposed architecture, the received SAR data is processed using one dimensional correlators for determining the range while two dimensional correlators are used to determine the azimuth of a target. The architecture uses only three different types of custom VLSI chips and a small amount of memory.
Two-dimensional airflow modeling underpredicts the wind velocity over dunes
Michelsen, Britt; Strobl, Severin; Parteli, Eric J. R.; Pöschel, Thorsten
2015-01-01
We investigate the average turbulent wind field over a barchan dune by means of Computational Fluid Dynamics. We find that the fractional speed-up ratio of the wind velocity over the three-dimensional barchan shape differs from the one obtained from two-dimensional calculations of the airflow over the longitudinal cut along the dune’s symmetry axis — that is, over the equivalent transverse dune of same size. This finding suggests that the modeling of the airflow over the central slice of barchan dunes is insufficient for the purpose of the quantitative description of barchan dune dynamics as three-dimensional flow effects cannot be neglected. PMID:26572966
Three-dimensional modeling of the plasma arc in arc welding
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, G.; Tsai, H. L.; Hu, J.
2008-11-15
Most previous three-dimensional modeling on gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) focuses on the weld pool dynamics and assumes the two-dimensional axisymmetric Gaussian distributions for plasma arc pressure and heat flux. In this article, a three-dimensional plasma arc model is developed, and the distributions of velocity, pressure, temperature, current density, and magnetic field of the plasma arc are calculated by solving the conservation equations of mass, momentum, and energy, as well as part of the Maxwell's equations. This three-dimensional model can be used to study the nonaxisymmetric plasma arc caused by external perturbations such asmore » an external magnetic field. It also provides more accurate boundary conditions when modeling the weld pool dynamics. The present work lays a foundation for true three-dimensional comprehensive modeling of GTAW and GMAW including the plasma arc, weld pool, and/or electrode.« less
NASA Astrophysics Data System (ADS)
Po, Hoi Chun; Zhou, Qi
2015-08-01
Bosons have a natural instinct to condense at zero temperature. It is a long-standing challenge to create a high-dimensional quantum liquid that does not exhibit long-range order at the ground state, as either extreme experimental parameters or sophisticated designs of microscopic Hamiltonians are required for suppressing the condensation. Here we show that synthetic gauge fields for ultracold atoms, using either the Raman scheme or shaken lattices, provide physicists a simple and practical scheme to produce a two-dimensional algebraic quantum liquid at the ground state. This quantum liquid arises at a critical Lifshitz point, where a two-dimensional quartic dispersion emerges in the momentum space, and many fundamental properties of two-dimensional bosons are changed in its proximity. Such an ideal simulator of the quantum Lifshitz model allows experimentalists to directly visualize and explore the deconfinement transition of topological excitations, an intriguing phenomenon that is difficult to access in other systems.
Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.
Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela
2016-12-01
Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.
Continued development and validation of the AER two-dimensional interactive model
NASA Technical Reports Server (NTRS)
Ko, M. K. W.; Sze, N. D.; Shia, R. L.; Mackay, M.; Weisenstein, D. K.; Zhou, S. T.
1996-01-01
Results from two-dimensional chemistry-transport models have been used to predict the future behavior of ozone in the stratosphere. Since the transport circulation, temperature, and aerosol surface area are fixed in these models, they cannot account for the effects of changes in these quantities, which could be modified because of ozone redistribution and/or other changes in the troposphere associated with climate changes. Interactive two-dimensional models, which calculate the transport circulation and temperature along with concentrations of the chemical species, could provide answers to complement the results from three-dimension model calculations. In this project, we performed the following tasks in pursuit of the respective goals: (1) We continued to refine the 2-D chemistry-transport model; (2) We developed a microphysics model to calculate the aerosol loading and its size distribution; (3) The treatment of physics in the AER 2-D interactive model were refined in the following areas--the heating rate in the troposphere, and wave-forcing from propagation of planetary waves.
NASA Astrophysics Data System (ADS)
Najafi, M. N.; Dashti-Naserabadi, H.
2018-03-01
In many situations we are interested in the propagation of energy in some portions of a three-dimensional system with dilute long-range links. In this paper, a sandpile model is defined on the three-dimensional small-world network with real dissipative boundaries and the energy propagation is studied in three dimensions as well as the two-dimensional cross-sections. Two types of cross-sections are defined in the system, one in the bulk and another in the system boundary. The motivation of this is to make clear how the statistics of the avalanches in the bulk cross-section tend to the statistics of the dissipative avalanches, defined in the boundaries as the concentration of long-range links (α ) increases. This trend is numerically shown to be a power law in a manner described in the paper. Two regimes of α are considered in this work. For sufficiently small α s the dominant behavior of the system is just like that of the regular BTW, whereas for the intermediate values the behavior is nontrivial with some exponents that are reported in the paper. It is shown that the spatial extent up to which the statistics is similar to the regular BTW model scales with α just like the dissipative BTW model with the dissipation factor (mass in the corresponding ghost model) m2˜α for the three-dimensional system as well as its two-dimensional cross-sections.
Barlow, P.M.
1994-01-01
Steady-state, two-and three-dimensional, ground-water flow models coupled with a particle- tracking program were evaluated to determine their effectiveness in delineating contributing areas of existing and hypothetical public-supply wells pumping from two contrasting stratified-drift aquifers of Cape Cod, Mass. Several of the contri- buting areas delineated by use of the three- dimensional models do not conform to simple ellipsoidal shapes that are typically delineated by use of a two-dimensional analytical and numerical modeling techniques, include dis- continuous areas of the water table, and do not surround the wells. Because two-dimensional areal models do not account for vertical flow, they cannot adequately represent many of the hydro- geologic and well-design variables that were shown to complicate the delineation of contributing areas in these flow systems, including the presence of discrete lenses of 1ow hydraulic conductivity, large ratios of horizontal to ver- tical hydraulic conductivity, shallow streams, partially penetrating supply wells, and 1ow pumping rates (less than 0.1 million gallons per day). Nevertheless, contributing areas delineated for two wells in the simpler of the two flow systems--a thin (less than 100 feet), single- layer, uniform aquifer with near-ideal boundary conditions--were not significantly different for the two- or three-dimensional models of the natural system, for a pumping rate of 0.5 million gallons per day. Use of particle tracking helped identify the source of water to simulated wells, which included precipitation recharge, wastewater return flow, and pond water. Pond water and wastewater return flow accounted for as much as 73 and 40 percent, respectively, of the water captured by simulated wells.
Equation of State of the Two-Dimensional Hubbard Model
NASA Astrophysics Data System (ADS)
Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael
2016-04-01
The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.
NASA Astrophysics Data System (ADS)
Inoue, Makoto
2017-12-01
Some new formulae of the canonical correlation functions for the one dimensional quantum transverse Ising model are found by the ST-transformation method using a Morita's sum rule and its extensions for the two dimensional classical Ising model. As a consequence we obtain a time-independent term of the dynamical correlation functions. Differences of quantum version and classical version of these formulae are also discussed.
Transient Stress Wave Propagation in One-Dimensional Micropolar Bodies
2009-02-01
based on Biot’s theory of poro- elasticity. Two compressional waves were then observed in the resulting one-dimensional model of a poroelastic column...Lisina, S., Potapov, A., Nesterenko, V., 2001. A nonlinear granular medium with particle rotation: a one-dimensional model . Acoustical Physics 47 (5...zones in failed ceramics, may be modeled using continuum theories incorporating additional kinematic degrees of freedom beyond the scope of classical
Conformal mapping in optical biosensor applications.
Zumbrum, Matthew E; Edwards, David A
2015-09-01
Optical biosensors are devices used to investigate surface-volume reaction kinetics. Current mathematical models for reaction dynamics rely on the assumption of unidirectional flow within these devices. However, new devices, such as the Flexchip, include a geometry that introduces two-dimensional flow, complicating the depletion of the volume reactant. To account for this, a previous mathematical model is extended to include two-dimensional flow, and the Schwarz-Christoffel mapping is used to relate the physical device geometry to that for a device with unidirectional flow. Mappings for several Flexchip dimensions are considered, and the ligand depletion effect is investigated for one of these mappings. Estimated rate constants are produced for simulated data to quantify the inclusion of two-dimensional flow in the mathematical model.
Statistical mechanics of shell models for two-dimensional turbulence
NASA Astrophysics Data System (ADS)
Aurell, E.; Boffetta, G.; Crisanti, A.; Frick, P.; Paladin, G.; Vulpiani, A.
1994-12-01
We study shell models that conserve the analogs of energy and enstrophy and hence are designed to mimic fluid turbulence in two-dimensions (2D). The main result is that the observed state is well described as a formal statistical equilibrium, closely analogous to the approach to two-dimensional ideal hydrodynamics of Onsager [Nuovo Cimento Suppl. 6, 279 (1949)], Hopf [J. Rat. Mech. Anal. 1, 87 (1952)], and Lee [Q. Appl. Math. 10, 69 (1952)]. In the presence of forcing and dissipation we observe a forward flux of enstrophy and a backward flux of energy. These fluxes can be understood as mean diffusive drifts from a source to two sinks in a system which is close to local equilibrium with Lagrange multipliers (``shell temperatures'') changing slowly with scale. This is clear evidence that the simplest shell models are not adequate to reproduce the main features of two-dimensional turbulence. The dimensional predictions on the power spectra from a supposed forward cascade of enstrophy and from one branch of the formal statistical equilibrium coincide in these shell models in contrast to the corresponding predictions for the Navier-Stokes and Euler equations in 2D. This coincidence has previously led to the mistaken conclusion that shell models exhibit a forward cascade of enstrophy. We also study the dynamical properties of the models and the growth of perturbations.
Gómez-Ortiz, Olga; Ortega-Ruiz, Rosario; Jolliffe, Darrick; Romera, Eva M.
2017-01-01
Objectives (1) To examine the psychometric properties of the Basic Empathy Scale (BES) with Spanish adolescents, comparing a two and a three-dimensional structure;(2) To analyse the relationship between the three-dimensional empathy and social and normative adjustment in school. Design Transversal and ex post facto retrospective study. Confirmatory factorial analysis, multifactorial invariance analysis and structural equations models were used. Participants 747 students (51.3% girls) from Cordoba, Spain, aged 12–17 years (M=13.8; SD=1.21). Results The original two-dimensional structure was confirmed (cognitive empathy, affective empathy), but a three-dimensional structure showed better psychometric properties, highlighting the good fit found in confirmatory factorial analysis and adequate internal consistent valued, measured with Cronbach’s alpha and McDonald’s omega. Composite reliability and average variance extracted showed better indices for a three-factor model. The research also showed evidence of measurement invariance across gender. All the factors of the final three-dimensional BES model were direct and significantly associated with social and normative adjustment, being most strongly related to cognitive empathy. Conclusions This research supports the advances in neuroscience, developmental psychology and psychopathology through a three-dimensional version of the BES, which represents an improvement in the original two-factorial model. The organisation of empathy in three factors benefits the understanding of social and normative adjustment in adolescents, in which emotional disengagement favours adjusted peer relationships. Psychoeducational interventions aimed at improving the quality of social life in schools should target these components of empathy. PMID:28951400
NASA Astrophysics Data System (ADS)
Cui, Tiangang; Marzouk, Youssef; Willcox, Karen
2016-06-01
Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.
NASA Technical Reports Server (NTRS)
Booth, E., Jr.; Yu, J. C.
1986-01-01
An experimental investigation of two dimensional blade vortex interaction was held at NASA Langley Research Center. The first phase was a flow visualization study to document the approach process of a two dimensional vortex as it encountered a loaded blade model. To accomplish the flow visualization study, a method for generating two dimensional vortex filaments was required. The numerical study used to define a new vortex generation process and the use of this process in the flow visualization study were documented. Additionally, photographic techniques and data analysis methods used in the flow visualization study are examined.
Learning control system design based on 2-D theory - An application to parallel link manipulator
NASA Technical Reports Server (NTRS)
Geng, Z.; Carroll, R. L.; Lee, J. D.; Haynes, L. H.
1990-01-01
An approach to iterative learning control system design based on two-dimensional system theory is presented. A two-dimensional model for the iterative learning control system which reveals the connections between learning control systems and two-dimensional system theory is established. A learning control algorithm is proposed, and the convergence of learning using this algorithm is guaranteed by two-dimensional stability. The learning algorithm is applied successfully to the trajectory tracking control problem for a parallel link robot manipulator. The excellent performance of this learning algorithm is demonstrated by the computer simulation results.
NASA Technical Reports Server (NTRS)
Zeng, Xiping; Tao, Wei-Kuo; Lang, Stephen; Hou, Arthur Y.; Zhang, Minghua; Simpson, Joanne
2008-01-01
Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.
State-of-charge estimation in lithium-ion batteries: A particle filter approach
NASA Astrophysics Data System (ADS)
Tulsyan, Aditya; Tsai, Yiting; Gopaluni, R. Bhushan; Braatz, Richard D.
2016-11-01
The dynamics of lithium-ion batteries are complex and are often approximated by models consisting of partial differential equations (PDEs) relating the internal ionic concentrations and potentials. The Pseudo two-dimensional model (P2D) is one model that performs sufficiently accurately under various operating conditions and battery chemistries. Despite its widespread use for prediction, this model is too complex for standard estimation and control applications. This article presents an original algorithm for state-of-charge estimation using the P2D model. Partial differential equations are discretized using implicit stable algorithms and reformulated into a nonlinear state-space model. This discrete, high-dimensional model (consisting of tens to hundreds of states) contains implicit, nonlinear algebraic equations. The uncertainty in the model is characterized by additive Gaussian noise. By exploiting the special structure of the pseudo two-dimensional model, a novel particle filter algorithm that sweeps in time and spatial coordinates independently is developed. This algorithm circumvents the degeneracy problems associated with high-dimensional state estimation and avoids the repetitive solution of implicit equations by defining a 'tether' particle. The approach is illustrated through extensive simulations.
Łącki, Mateusz; Damski, Bogdan; Zakrzewski, Jakub
2016-12-02
We show that the critical point of the two-dimensional Bose-Hubbard model can be easily found through studies of either on-site atom number fluctuations or the nearest-neighbor two-point correlation function (the expectation value of the tunnelling operator). Our strategy to locate the critical point is based on the observation that the derivatives of these observables with respect to the parameter that drives the superfluid-Mott insulator transition are singular at the critical point in the thermodynamic limit. Performing the quantum Monte Carlo simulations of the two-dimensional Bose-Hubbard model, we show that this technique leads to the accurate determination of the position of its critical point. Our results can be easily extended to the three-dimensional Bose-Hubbard model and different Hubbard-like models. They provide a simple experimentally-relevant way of locating critical points in various cold atomic lattice systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nekrasov, Nikita; ITEP, Moscow; Shatashvili, Samson
Supersymmetric vacua of two dimensional N = 4 gauge theories with matter, softly broken by the twisted masses down to N = 2, are shown to be in one-to-one correspondence with the eigenstates of integrable spin chain Hamiltonians. Examples include: the Heisenberg SU(2)XXX spin chain which is mapped to the two dimensional U(N) theory with fundamental hypermultiplets, the XXZ spin chain which is mapped to the analogous three dimensional super-Yang-Mills theory compactified on a circle, the XYZ spin chain and eight-vertex model which are related to the four dimensional theory compactified on T{sup 2}. A consequence of our correspondence ismore » the isomorphism of the quantum cohomology ring of various quiver varieties, such as cotangent bundles to (partial) flag varieties and the ring of quantum integrals of motion of various spin chains. The correspondence extends to any spin group, representations, boundary conditions, and inhomogeneity, it includes Sinh-Gordon and non-linear Schroedinger models as well as the dynamical spin chains like Hubbard model. Compactifications of four dimensional N = 2 theories on a two-sphere lead to the instanton-corrected Bethe equations.« less
Stress concentration investigations using NASTRAN
NASA Technical Reports Server (NTRS)
Gillcrist, M. C.; Parnell, L. A.
1986-01-01
Parametic investigations are performed using several two dimensional finite element formulations to determine their suitability for use in predicting extremum stresses in marine propellers. Comparisons are made of two NASTRAN elements (CTRIM6 and CTRAIA2) wherein elasticity properties have been modified to yield plane strain results. The accuracy of the elements is investigated by comparing finite element stress predictions with experimentally determined stresses in two classical cases: (1) tension in a flat plate with a circular hole; and (2) a filleted flat bar subjected to in-plane bending. The CTRIA2 element is found to provide good results. The displacement field from a three dimensional finite element model of a representative marine propeller is used as the boundary condition for the two dimensional plane strain investigations of stresses in the propeller blade and fillet. Stress predictions from the three dimensional analysis are compared with those from the two dimensional models. The validity of the plane strain modifications to the NASTRAN element is checked by comparing the modified CTRIA2 element stress predictions with those of the ABAQUS plane strain element, CPE4.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, R.
This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.
Model of chiral spin liquids with Abelian and non-Abelian topological phases
Chen, Jyong-Hao; Mudry, Christopher; Chamon, Claudio; ...
2017-12-15
In this article, we present a two-dimensional lattice model for quantum spin-1/2 for which the low-energy limit is governed by four flavors of strongly interacting Majorana fermions. We study this low-energy effective theory using two alternative approaches. The first consists of a mean-field approximation. The second consists of a random phase approximation (RPA) for the single-particle Green's functions of the Majorana fermions built from their exact forms in a certain one-dimensional limit. The resulting phase diagram consists of two competing chiral phases, one with Abelian and the other with non-Abelian topological order, separated by a continuous phase transition. Remarkably, themore » Majorana fermions propagate in the two-dimensional bulk, as in the Kitaev model for a spin liquid on the honeycomb lattice. We identify the vison fields, which are mobile (they are static in the Kitaev model) domain walls propagating along only one of the two space directions.« less
Model of chiral spin liquids with Abelian and non-Abelian topological phases
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Jyong-Hao; Mudry, Christopher; Chamon, Claudio
In this article, we present a two-dimensional lattice model for quantum spin-1/2 for which the low-energy limit is governed by four flavors of strongly interacting Majorana fermions. We study this low-energy effective theory using two alternative approaches. The first consists of a mean-field approximation. The second consists of a random phase approximation (RPA) for the single-particle Green's functions of the Majorana fermions built from their exact forms in a certain one-dimensional limit. The resulting phase diagram consists of two competing chiral phases, one with Abelian and the other with non-Abelian topological order, separated by a continuous phase transition. Remarkably, themore » Majorana fermions propagate in the two-dimensional bulk, as in the Kitaev model for a spin liquid on the honeycomb lattice. We identify the vison fields, which are mobile (they are static in the Kitaev model) domain walls propagating along only one of the two space directions.« less
A parameter estimation algorithm for spatial sine testing - Theory and evaluation
NASA Technical Reports Server (NTRS)
Rost, R. W.; Deblauwe, F.
1992-01-01
This paper presents the theory and an evaluation of a spatial sine testing parameter estimation algorithm that uses directly the measured forced mode of vibration and the measured force vector. The parameter estimation algorithm uses an ARMA model and a recursive QR algorithm is applied for data reduction. In this first evaluation, the algorithm has been applied to a frequency response matrix (which is a particular set of forced mode of vibration) using a sliding frequency window. The objective of the sliding frequency window is to execute the analysis simultaneously with the data acquisition. Since the pole values and the modal density are obtained from this analysis during the acquisition, the analysis information can be used to help determine the forcing vectors during the experimental data acquisition.
NASA Technical Reports Server (NTRS)
Harik, V. M.
2001-01-01
Limitations in the validity of the continuum beam model for carbon nanotubes (NTs) and nanorods are examined. Applicability of all assumptions used in the model is restricted by the two criteria for geometric parameters that characterize the structure of NTs. The key non-dimensional parameters that control the NT buckling behavior are derived via dimensional analysis of the nanomechanical problem. A mechanical law of geometric similitude for NT buckling is extended from continuum mechanics for different molecular structures. A model applicability map, where two classes of beam-like NTs are identified, is constructed for distinct ranges of non-dimensional parameters. Expressions for the critical buckling loads and strains are tailored for two classes of NTs and compared with the data provided by the molecular dynamics simulations. copyright 2001 Elsevier Science Ltd. All rights reserved.
Three-Dimensional Computer-Assisted Two-Layer Elastic Models of the Face.
Ueda, Koichi; Shigemura, Yuka; Otsuki, Yuki; Fuse, Asuka; Mitsuno, Daisuke
2017-11-01
To make three-dimensional computer-assisted elastic models for the face, we decided on five requirements: (1) an elastic texture like skin and subcutaneous tissue; (2) the ability to take pen marking for incisions; (3) the ability to be cut with a surgical knife; (4) the ability to keep stitches in place for a long time; and (5) a layered structure. After testing many elastic solvents, we have made realistic three-dimensional computer-assisted two-layer elastic models of the face and cleft lip from the computed tomographic and magnetic resonance imaging stereolithographic data. The surface layer is made of polyurethane and the inner layer is silicone. Using this elastic model, we taught residents and young doctors how to make several typical local flaps and to perform cheiloplasty. They could experience realistic simulated surgery and understand three-dimensional movement of the flaps.
A mechanism for hot-spot generation in a reactive two-dimensional sheared viscous layer
NASA Astrophysics Data System (ADS)
Timms, Robert; Purvis, Richard; Curtis, John P.
2018-05-01
A two-dimensional model for the non-uniform melting of a thin sheared viscous layer is developed. An asymptotic solution is presented for both a non-reactive and a reactive material. It is shown that the melt front is linearly stable to small perturbations in the non-reactive case, but becomes linearly unstable upon introduction of an Arrhenius source term to model the chemical reaction. Results demonstrate that non-uniform melting acts as a mechanism to generate hot spots that are found to be sufficient to reduce the time to ignition when compared with the corresponding one-dimensional model of melting.
Yuan, Fang; Wang, Guangyi; Wang, Xiaowei
2017-03-01
In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.
NASA Astrophysics Data System (ADS)
Barinov, I. O.; Alodzhants, A. P.; Arakelyan, Sergei M.
2009-07-01
We describe a new type of spatially periodic structure (lattice models): a polaritonic crystal formed by a two-dimensional lattice of trapped two-level atoms interacting with the electromagnetic field in a cavity (or in a one-dimensional array of tunnelling-coupled microcavities), which allows polaritons to be fully localised. Using a one-dimensional polaritonic crystal as an example, we analyse conditions for quantum degeneracy of a lower-polariton gas and those for quantum optical information recording and storage.
NASA Technical Reports Server (NTRS)
Stordal, Frode; Garcia, Rolando R.
1987-01-01
The 1-1/2-D model of Holton (1986), which is actually a highly truncated two-dimensional model, describes latitudinal variations of tracer mixing ratios in terms of their projections onto second-order Legendre polynomials. The present study extends the work of Holton by including tracers with photochemical production in the stratosphere (O3 and NOy). It also includes latitudinal variations in the photochemical sources and sinks, improving slightly the calculated global mean profiles for the long-lived tracers studied by Holton and improving substantially the latitudinal behavior of ozone. Sensitivity tests of the dynamical parameters in the model are performed, showing that the response of the model to changes in vertical residual meridional winds and horizontal diffusion coefficients is similar to that of a full two-dimensional model. A simple ozone perturbation experiment shows the model's ability to reproduce large-scale latitudinal variations in total ozone column depletions as well as ozone changes in the chemically controlled upper stratosphere.
Perceptual integration of kinematic components in the recognition of emotional facial expressions.
Chiovetto, Enrico; Curio, Cristóbal; Endres, Dominik; Giese, Martin
2018-04-01
According to a long-standing hypothesis in motor control, complex body motion is organized in terms of movement primitives, reducing massively the dimensionality of the underlying control problems. For body movements, this low-dimensional organization has been convincingly demonstrated by the learning of low-dimensional representations from kinematic and EMG data. In contrast, the effective dimensionality of dynamic facial expressions is unknown, and dominant analysis approaches have been based on heuristically defined facial "action units," which reflect contributions of individual face muscles. We determined the effective dimensionality of dynamic facial expressions by learning of a low-dimensional model from 11 facial expressions. We found an amazingly low dimensionality with only two movement primitives being sufficient to simulate these dynamic expressions with high accuracy. This low dimensionality is confirmed statistically, by Bayesian model comparison of models with different numbers of primitives, and by a psychophysical experiment that demonstrates that expressions, simulated with only two primitives, are indistinguishable from natural ones. In addition, we find statistically optimal integration of the emotion information specified by these primitives in visual perception. Taken together, our results indicate that facial expressions might be controlled by a very small number of independent control units, permitting very low-dimensional parametrization of the associated facial expression.
NASA Astrophysics Data System (ADS)
Fan, Qingju; Wu, Yonghong
2015-08-01
In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.
D'Archivio, Angelo Antonio; Incani, Angela; Ruggieri, Fabrizio
2011-01-01
In this paper, we use a quantitative structure-retention relationship (QSRR) method to predict the retention times of polychlorinated biphenyls (PCBs) in comprehensive two-dimensional gas chromatography (GC×GC). We analyse the GC×GC retention data taken from the literature by comparing predictive capability of different regression methods. The various models are generated using 70 out of 209 PCB congeners in the calibration stage, while their predictive performance is evaluated on the remaining 139 compounds. The two-dimensional chromatogram is initially estimated by separately modelling retention times of PCBs in the first and in the second column ((1) t (R) and (2) t (R), respectively). In particular, multilinear regression (MLR) combined with genetic algorithm (GA) variable selection is performed to extract two small subsets of predictors for (1) t (R) and (2) t (R) from a large set of theoretical molecular descriptors provided by the popular software Dragon, which after removal of highly correlated or almost constant variables consists of 237 structure-related quantities. Based on GA-MLR analysis, a four-dimensional and a five-dimensional relationship modelling (1) t (R) and (2) t (R), respectively, are identified. Single-response partial least square (PLS-1) regression is alternatively applied to independently model (1) t (R) and (2) t (R) without the need for preliminary GA variable selection. Further, we explore the possibility of predicting the two-dimensional chromatogram of PCBs in a single calibration procedure by using a two-response PLS (PLS-2) model or a feed-forward artificial neural network (ANN) with two output neurons. In the first case, regression is carried out on the full set of 237 descriptors, while the variables previously selected by GA-MLR are initially considered as ANN inputs and subjected to a sensitivity analysis to remove the redundant ones. Results show PLS-1 regression exhibits a noticeably better descriptive and predictive performance than the other investigated approaches. The observed values of determination coefficients for (1) t (R) and (2) t (R) in calibration (0.9999 and 0.9993, respectively) and prediction (0.9987 and 0.9793, respectively) provided by PLS-1 demonstrate that GC×GC behaviour of PCBs is properly modelled. In particular, the predicted two-dimensional GC×GC chromatogram of 139 PCBs not involved in the calibration stage closely resembles the experimental one. Based on the above lines of evidence, the proposed approach ensures accurate simulation of the whole GC×GC chromatogram of PCBs using experimental determination of only 1/3 retention data of representative congeners.
Soganci, Gokce; Cinar, Duygu; Caglar, Alper; Yagiz, Ayberk
2018-05-31
The aim of this study was to determine and compare the dimensional changes of polyether and vinyl polyether siloxane impression materials under immersion disinfection with two different disinfectants in three time periods. Impressions were obtained from an edentulous master model. Sodium hypochlorite (5.25%) and glutaraldehyde (2%) were used for disinfection and measurements were done 30 min later after making impression before disinfection, after required disinfection period (10 min), and after 24 h storage at room temperature. Impressions were scanned using 3D scanner with 10 microns accuracy and 3D software was used to evaluate the dimensional changes with superimpositioning. Positive and negative deviations were calculated and compared with master model. There was no significant difference between two elastomeric impression materials (p>0.05). It was concluded that dimensional accuracy and stability of two impression materials were excellent and similar.
Investigation of two-dimensional wedge exhaust nozzles for advanced aircraft
NASA Technical Reports Server (NTRS)
Maiden, D. L.; Petit, J. E.
1975-01-01
Two-dimensional wedge nozzle performance characteristics were investigated in a series of wind-tunnel tests. An isolated single-engine/nozzle model was used to study the effects of internal expansion area ratio, aftbody cowl boattail angle, and wedge length. An integrated twin-engine/nozzle model, tested with and without empenage surfaces, included cruise, acceleration, thrust vectoring and thrust reversing nozzle operating modes. Results indicate that the thrust-minus-aftbody drag performance of the twin two-dimensional nozzle integration is significantly higher, for speeds greater than Mach 0.8, than the performance achieved with twin axisymmetric nozzle installations. Significant jet-induced lift was obtained on an aft-mounted lifting surface using a cambered wedge center body to vector thrust. The thrust reversing capabilities of reverser panels installed on the two-dimensional wedge center body were very effective for static or in-flight operation.
Reilly, Thomas E.; Harbaugh, Arlen W.
1980-01-01
A three-dimensional electric-analog model of the Long Island, NY , groundwater system constructed by the U.S. Geological Survey in the early 1970 's was used as the basis for developing a digital, three-dimensional finite-difference model. The digital model was needed to provide faster modifications and more rapid solutions to water-management questions. Results generated by the two models are depicted as potentiometric-surface maps of the upper glacial and Magothy aquifers. Results compare favorably for all parts of Long Island except the northwestern part, where hydrologic discontinuities are most prevalent and which the two models represent somewhat differently. The mathematical and hydrologic principles used in development of ground-water models, and the procedures for calibration and acceptance, are presented in nontechnical terms. (USGS)
A thermal analysis of a spirally wound battery using a simple mathematical model
NASA Technical Reports Server (NTRS)
Evans, T. I.; White, R. E.
1989-01-01
A two-dimensional thermal model for spirally wound batteries has been developed. The governing equation of the model is the energy balance. Convective and insulated boundary conditions are used, and the equations are solved using a finite element code called TOPAZ2D. The finite element mesh is generated using a preprocessor to TOPAZ2D called MAZE. The model is used to estimate temperature profiles within a spirally wound D-size cell. The model is applied to the lithium/thionyl chloride cell because of the thermal management problems that this cell exhibits. Simplified one-dimensional models are presented that can be used to predict best and worst temperature profiles. The two-dimensional model is used to predict the regions of maximum temperature within the spirally wound cell. Normal discharge as well as thermal runaway conditions are investigated.
Spintronics: spin accumulation in mesoscopic systems.
Johnson, Mark
2002-04-25
In spintronics, in which use is made of the spin degree of freedom of the electron, issues concerning electrical spin injection and detection of electron spin diffusion are fundamentally important. Jedema et al. describe a magneto-resistance study in which they claim to have observed spin accumulation in a mesoscopic copper wire, but their one-dimensional model ignores two-dimensional spin-diffusion effects, which casts doubt on their analysis. A two-dimensional vector formalism of spin transport is called for to model spin-injection experiments, and the identification of spurious background resistance effects is crucial.
Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants
NASA Technical Reports Server (NTRS)
Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.
1996-01-01
Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.
NASA Technical Reports Server (NTRS)
Lee, S. S.; Sengupta, S.; Nwadike, E. V.; Sinha, S. K.
1982-01-01
The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorage (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter. These models allow computation of time-dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions. The free-surface model also provides surface height variations with time.
Yang, Jing; Ye, Shu-jun; Wu, Ji-chun
2011-05-01
This paper studied on the influence of bioclogging on permeability of saturated porous media. Laboratory hydraulic tests were conducted in a two-dimensional C190 sand-filled cell (55 cm wide x 45 cm high x 1.28 cm thick) to investigate growth of the mixed microorganisms (KB-1) and influence of biofilm on permeability of saturated porous media under condition of rich nutrition. Biomass distributions in the water and on the sand in the cell were measured by protein analysis. The biofilm distribution on the sand was observed by confocal laser scanning microscopy. Permeability was measured by hydraulic tests. The biomass levels measured in water and on the sand increased with time, and were highest at the bottom of the cell. The biofilm on the sand at the bottom of the cell was thicker. The results of the hydraulic tests demonstrated that the permeability due to biofilm growth was estimated to be average 12% of the initial value. To investigate the spatial distribution of permeability in the two dimensional cell, three models (Taylor, Seki, and Clement) were used to calculate permeability of porous media with biofilm growth. The results of Taylor's model showed reduction in permeability of 2-5 orders magnitude. The Clement's model predicted 3%-98% of the initial value. Seki's model could not be applied in this study. Conclusively, biofilm growth could obviously decrease the permeability of two dimensional saturated porous media, however, the reduction was much less than that estimated in one dimensional condition. Additionally, under condition of two dimensional saturated porous media with rich nutrition, Seki's model could not be applied, Taylor's model predicted bigger reductions, and the results of Clement's model were closest to the result of hydraulic test.
Limitations to the use of two-dimensional thermal modeling of a nuclear waste repository
DOE Office of Scientific and Technical Information (OSTI.GOV)
Davis, B.W.
1979-01-04
Thermal modeling of a nuclear waste repository is basic to most waste management predictive models. It is important that the modeling techniques accurately determine the time-dependent temperature distribution of the waste emplacement media. Recent modeling studies show that the time-dependent temperature distribution can be accurately modeled in the far-field using a 2-dimensional (2-D) planar numerical model; however, the near-field cannot be modeled accurately enough by either 2-D axisymmetric or 2-D planar numerical models for repositories in salt. The accuracy limits of 2-D modeling were defined by comparing results from 3-dimensional (3-D) TRUMP modeling with results from both 2-D axisymmetric andmore » 2-D planar. Both TRUMP and ADINAT were employed as modeling tools. Two-dimensional results from the finite element code, ADINAT were compared with 2-D results from the finite difference code, TRUMP; they showed almost perfect correspondence in the far-field. This result adds substantially to confidence in future use of ADINAT and its companion stress code ADINA for thermal stress analysis. ADINAT was found to be somewhat sensitive to time step and mesh aspect ratio. 13 figures, 4 tables.« less
The Airborne Optical Systems Testbed (AOSTB)
2017-05-31
appropriate color to each pixel in and displayed in a two -dimensional array. Another method is to render a 3D model from the data and display the model as if...USA Distribution A: Public Release ALBOTA@LL.MIT.EDU ABSTRACT Over the last two decades MIT Lincoln Laboratory (MITLL) has pioneered the development... two -dimensional (2D) grid of detectors. Rather than measuring intensity, as in a conventional camera, these detectors measure the photon time-of
Dynamics of an HIV-1 infection model with cell mediated immunity
NASA Astrophysics Data System (ADS)
Yu, Pei; Huang, Jianing; Jiang, Jiao
2014-10-01
In this paper, we study the dynamics of an improved mathematical model on HIV-1 virus with cell mediated immunity. This new 5-dimensional model is based on the combination of a basic 3-dimensional HIV-1 model and a 4-dimensional immunity response model, which more realistically describes dynamics between the uninfected cells, infected cells, virus, the CTL response cells and CTL effector cells. Our 5-dimensional model may be reduced to the 4-dimensional model by applying a quasi-steady state assumption on the variable of virus. However, it is shown in this paper that virus is necessary to be involved in the modeling, and that a quasi-steady state assumption should be applied carefully, which may miss some important dynamical behavior of the system. Detailed bifurcation analysis is given to show that the system has three equilibrium solutions, namely the infection-free equilibrium, the infectious equilibrium without CTL, and the infectious equilibrium with CTL, and a series of bifurcations including two transcritical bifurcations and one or two possible Hopf bifurcations occur from these three equilibria as the basic reproduction number is varied. The mathematical methods applied in this paper include characteristic equations, Routh-Hurwitz condition, fluctuation lemma, Lyapunov function and computation of normal forms. Numerical simulation is also presented to demonstrate the applicability of the theoretical predictions.
The Two- and Three-Dimensional Models of the HK-WISC: A Confirmatory Factor Analysis.
ERIC Educational Resources Information Center
Chan, David W.; Lin, Wen-Ying
1996-01-01
Confirmatory analyses on the Hong Kong Wechsler Intelligence Scale for Children (HK-WISC) provided support for composite score interpretation based on the two- and three-dimensional models across age levels. Test sample was comprised of 1,100 children, ranging in age from 5 to 15 years at all 11 age levels specified by the HK-WISC. (KW)
Alignment dynamics of diffusive scalar gradient in a two-dimensional model flow
NASA Astrophysics Data System (ADS)
Gonzalez, M.
2018-04-01
The Lagrangian two-dimensional approach of scalar gradient kinematics is revisited accounting for molecular diffusion. Numerical simulations are performed in an analytic, parameterized model flow, which enables considering different regimes of scalar gradient dynamics. Attention is especially focused on the influence of molecular diffusion on Lagrangian statistical orientations and on the dynamics of scalar gradient alignment.
Resonant Zener tunneling in two-dimensional periodic photonic lattices.
Desyatnikov, Anton S; Kivshar, Yuri S; Shchesnovich, Valery S; Cavalcanti, Solange B; Hickmann, Jandir M
2007-02-15
We study Zener tunneling in two-dimensional photonic lattices and derive, for the case of hexagonal symmetry, the generalized Landau-Zener-Majorana model describing resonant interaction between high-symmetry points of the photonic spectral bands. We demonstrate that this effect can be employed for the generation of Floquet-Bloch modes and verify the model by direct numerical simulations of the tunneling effect.
Suemitsu, Yoshikazu; Nara, Shigetoshi
2004-09-01
Chaotic dynamics introduced into a neural network model is applied to solving two-dimensional mazes, which are ill-posed problems. A moving object moves from the position at t to t + 1 by simply defined motion function calculated from firing patterns of the neural network model at each time step t. We have embedded several prototype attractors that correspond to the simple motion of the object orienting toward several directions in two-dimensional space in our neural network model. Introducing chaotic dynamics into the network gives outputs sampled from intermediate state points between embedded attractors in a state space, and these dynamics enable the object to move in various directions. System parameter switching between a chaotic and an attractor regime in the state space of the neural network enables the object to move to a set target in a two-dimensional maze. Results of computer simulations show that the success rate for this method over 300 trials is higher than that of random walk. To investigate why the proposed method gives better performance, we calculate and discuss statistical data with respect to dynamical structure.
Experimental, Theoretical, and Computational Investigation of Separated Nozzle Flows
NASA Technical Reports Server (NTRS)
Hunter, Craig A.
2004-01-01
A detailed experimental, theoretical, and computational study of separated nozzle flows has been conducted. Experimental testing was performed at the NASA Langley 16-Foot Transonic Tunnel Complex. As part of a comprehensive static performance investigation, force, moment, and pressure measurements were made and schlieren flow visualization was obtained for a sub-scale, non-axisymmetric, two-dimensional, convergent- divergent nozzle. In addition, two-dimensional numerical simulations were run using the computational fluid dynamics code PAB3D with two-equation turbulence closure and algebraic Reynolds stress modeling. For reference, experimental and computational results were compared with theoretical predictions based on one-dimensional gas dynamics and an approximate integral momentum boundary layer method. Experimental results from this study indicate that off-design overexpanded nozzle flow was dominated by shock induced boundary layer separation, which was divided into two distinct flow regimes; three- dimensional separation with partial reattachment, and fully detached two-dimensional separation. The test nozzle was observed to go through a marked transition in passing from one regime to the other. In all cases, separation provided a significant increase in static thrust efficiency compared to the ideal prediction. Results indicate that with controlled separation, the entire overexpanded range of nozzle performance would be within 10% of the peak thrust efficiency. By offering savings in weight and complexity over a conventional mechanical exhaust system, this may allow a fixed geometry nozzle to cover an entire flight envelope. The computational simulation was in excellent agreement with experimental data over most of the test range, and did a good job of modeling internal flow and thrust performance. An exception occurred at low nozzle pressure ratios, where the two-dimensional computational model was inconsistent with the three-dimensional separation observed in the experiment. In general, the computation captured the physics of the shock boundary layer interaction and shock induced boundary layer separation in the nozzle, though there were some differences in shock structure compared to experiment. Though minor, these differences could be important for studies involving flow control or thrust vectoring of separated nozzles. Combined with other observations, this indicates that more detailed, three-dimensional computational modeling needs to be conducted to more realistically simulate shock-separated nozzle flows.
Two-Dimensional Analysis of Conical Pulsed Inductive Plasma Thruster Performance
NASA Technical Reports Server (NTRS)
Hallock, A. K.; Polzin, K. A.; Emsellem, G. D.
2011-01-01
A model of the maximum achievable exhaust velocity of a conical theta pinch pulsed inductive thruster is presented. A semi-empirical formula relating coil inductance to both axial and radial current sheet location is developed and incorporated into a circuit model coupled to a momentum equation to evaluate the effect of coil geometry on the axial directed kinetic energy of the exhaust. Inductance measurements as a function of the axial and radial displacement of simulated current sheets from four coils of different geometries are t to a two-dimensional expression to allow the calculation of the Lorentz force at any relevant averaged current sheet location. This relation for two-dimensional inductance, along with an estimate of the maximum possible change in gas-dynamic pressure as the current sheet accelerates into downstream propellant, enables the expansion of a one-dimensional circuit model to two dimensions. The results of this two-dimensional model indicate that radial current sheet motion acts to rapidly decouple the current sheet from the driving coil, leading to losses in axial kinetic energy 10-50 times larger than estimations of the maximum available energy in the compressed propellant. The decreased available energy in the compressed propellant as compared to that of other inductive plasma propulsion concepts suggests that a recovery in the directed axial kinetic energy of the exhaust is unlikely, and that radial compression of the current sheet leads to a loss in exhaust velocity for the operating conditions considered here.
NASA Astrophysics Data System (ADS)
Jia, Bing
2014-03-01
A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh—Rose (HR) neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two-dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the deterministic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in different two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces.
Harris, C.K.; Wiberg, P.L.
2001-01-01
A two-dimensional, time-dependent solution to the transport equation is formulated to account for advection and diffusion of sediment suspended in the bottom boundary layer of continental shelves. This model utilizes a semi-implicit, upwind-differencing scheme to solve the advection-diffusion equation across a two-dimensional transect that is configured so that one dimension is the vertical, and the other is a horizontal dimension usually aligned perpendicular to shelf bathymetry. The model calculates suspended sediment concentration and flux; and requires as input wave properties, current velocities, sediment size distributions, and hydrodynamic sediment properties. From the calculated two-dimensional suspended sediment fluxes, we quantify the redistribution of shelf sediment, bed erosion, and deposition for several sediment sizes during resuspension events. The two-dimensional, time-dependent approach directly accounts for cross-shelf gradients in bed shear stress and sediment properties, as well as transport that occurs before steady-state suspended sediment concentrations have been attained. By including the vertical dimension in the calculations, we avoid depth-averaging suspended sediment concentrations and fluxes, and directly account for differences in transport rates and directions for fine and coarse sediment in the bottom boundary layer. A flux condition is used as the bottom boundary condition for the transport equation in order to capture time-dependence of the suspended sediment field. Model calculations demonstrate the significance of both time-dependent and spatial terms on transport and depositional patterns on continental shelves. ?? 2001 Elsevier Science Ltd. All rights reserved.
Crack Modelling for Radiography
NASA Astrophysics Data System (ADS)
Chady, T.; Napierała, L.
2010-02-01
In this paper, possibility of creation of three-dimensional crack models, both random type and based on real-life radiographic images is discussed. Method for storing cracks in a number of two-dimensional matrices, as well algorithm for their reconstruction into three-dimensional objects is presented. Also the possibility of using iterative algorithm for matching simulated images of cracks to real-life radiographic images is discussed.
Modelling volatility recurrence intervals in the Chinese commodity futures market
NASA Astrophysics Data System (ADS)
Zhou, Weijie; Wang, Zhengxin; Guo, Haiming
2016-09-01
The law of extreme event occurrence attracts much research. The volatility recurrence intervals of Chinese commodity futures market prices are studied: the results show that the probability distributions of the scaled volatility recurrence intervals have a uniform scaling curve for different thresholds q. So we can deduce the probability distribution of extreme events from normal events. The tail of a scaling curve can be well fitted by a Weibull form, which is significance-tested by KS measures. Both short-term and long-term memories are present in the recurrence intervals with different thresholds q, which denotes that the recurrence intervals can be predicted. In addition, similar to volatility, volatility recurrence intervals also have clustering features. Through Monte Carlo simulation, we artificially synthesise ARMA, GARCH-class sequences similar to the original data, and find out the reason behind the clustering. The larger the parameter d of the FIGARCH model, the stronger the clustering effect is. Finally, we use the Fractionally Integrated Autoregressive Conditional Duration model (FIACD) to analyse the recurrence interval characteristics. The results indicated that the FIACD model may provide a method to analyse volatility recurrence intervals.
Make a Halley's Comet Orbit Model.
ERIC Educational Resources Information Center
Podmore, Francis; Fleet, Richard W.
1985-01-01
Describes a simple three-dimensional model of Halley's Comet orbit (which is much more informative than a two-dimensional drawing) to illustrate spatial relationships and visualize how the comet moves relative to the earth. Instructions for model assembly are given along with a template which can be photocopied and glued to cardboard. (JN)
USDA-ARS?s Scientific Manuscript database
This chapter presents the development and application of a three-dimensional water quality model for predicting the distributions of nutrients, phytoplankton, dissolved oxygen, etc., in natural lakes. In this model, the computational domain was divided into two parts: the water column and the bed se...
A model for near-wall dynamics in turbulent Rayleigh Bénard convection
NASA Astrophysics Data System (ADS)
Theerthan, S. Ananda; Arakeri, Jaywant H.
1998-10-01
Experiments indicate that turbulent free convection over a horizontal surface (e.g. Rayleigh Bénard convection) consists of essentially line plumes near the walls, at least for moderately high Rayleigh numbers. Based on this evidence, we propose here a two-dimensional model for near-wall dynamics in Rayleigh Bénard convection and in general for convection over heated horizontal surfaces. The model proposes a periodic array of steady laminar two-dimensional plumes. A plume is fed on either side by boundary layers on the wall. The results from the model are obtained in two ways. One of the methods uses the similarity solution of Rotem & Classen (1969) for the boundary layer and the similarity solution of Fuji (1963) for the plume. We have derived expressions for mean temperature and temperature and velocity fluctuations near the wall. In the second approach, we compute the two-dimensional flow field in a two-dimensional rectangular open cavity. The number of plumes in the cavity depends on the length of the cavity. The plume spacing is determined from the critical length at which the number of plumes increases by one. The results for average plume spacing and the distribution of r.m.s. temperature and velocity fluctuations are shown to be in acceptable agreement with experimental results.
NASA Technical Reports Server (NTRS)
Lee, S. S.; Sengupta, S.; Nwadike, E. V.
1982-01-01
The six-volume report: describes the theory of a three dimensional (3-D) mathematical thermal discharge model and a related one dimensional (1-D) model, includes model verification at two sites, and provides a separate user's manual for each model. The 3-D model has two forms: free surface and rigid lid. The former, verified at Anclote Anchorate (FL), allows a free air/water interface and is suited for significant surface wave heights compared to mean water depth; e.g., estuaries and coastal regions. The latter, verified at Lake Keowee (SC), is suited for small surface wave heights compared to depth (e.g., natural or man-made inland lakes) because surface elevation has been removed as a parameter. These models allow computation of time dependent velocity and temperature fields for given initial conditions and time-varying boundary conditions.
Modeling of the financial market using the two-dimensional anisotropic Ising model
NASA Astrophysics Data System (ADS)
Lima, L. S.
2017-09-01
We have used the two-dimensional classical anisotropic Ising model in an external field and with an ion single anisotropy term as a mathematical model for the price dynamics of the financial market. The model presented allows us to test within the same framework the comparative explanatory power of rational agents versus irrational agents with respect to the facts of financial markets. We have obtained the mean price in terms of the strong of the site anisotropy term Δ which reinforces the sensitivity of the agent's sentiment to external news.
Above and beyond short-term mating, long-term mating is uniquely tied to human personality.
Holtzman, Nicholas S; Strube, Michael J
2013-12-16
To what extent are personality traits and sexual strategies linked? The literature does not provide a clear answer, as it is based on the Sociosexuality model, a one-dimensional model that fails to measure long-term mating (LTM). An improved two-dimensional model separately assesses long-term and short-term mating (STM; Jackson and Kirkpatrick, 2007). In this paper, we link this two-dimensional model to an array of personality traits (Big 5, Dark Triad, and Schizoid Personality). We collected data from different sources (targets and peers; Study 1), and from different nations (United States, Study 1; India, Study 2). We demonstrate for the first time that, above and beyond STM, LTM captures variation in personality.
Measurement of the Equation of State of the Two-Dimensional Hubbard Model
NASA Astrophysics Data System (ADS)
Miller, Luke; Cocchi, Eugenio; Drewes, Jan; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Koehl, Michael
2016-05-01
The subtle interplay between kinetic energy, interactions and dimensionality challenges our comprehension of strongly-correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions, 0 <= U / t <= 20 , and temperatures, down to kB T / t = 0 . 63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities and double occupancies over the whole doping range, and hence our results constitute benchmarks for state-of-the-art theoretical approaches.
Optimization of the lithium/thionyl chloride battery
NASA Technical Reports Server (NTRS)
White, Ralph E.
1987-01-01
The progress which has been made in modeling the lithium/thionyl chloride cell over the past year and proposed research for the coming year are discussed. A one-dimensional mathematical model for a lithium/thionyl chloride cell has been developed and used to investigate methods of improving cell performance. During the course of the work a problem was detected with the banded solver being used. It was replaced with one more reliable. Future work may take one of two directions. The one-dimensional model could be augmented to include additional features and to investigate in more detail the cell temperature behavior, or a simplified two-dimensional model for the spirally wound design of this battery could be developed to investigate the heat flow within the cell.
Testing approximate theories of first-order phase transitions on the two-dimensional Potts model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dasgupta, C.; Pandit, R.
The two-dimensional, q-state (q > 4) Potts model is used as a testing ground for approximate theories of first-order phase transitions. In particular, the predictions of a theory analogous to the Ramakrishnan-Yussouff theory of freezing are compared with those of ordinary mean-field (Curie-Wiess) theory. It is found that the Curie-Weiss theory is a better approximation than the Ramakrishnan-Yussouff theory, even though the former neglects all fluctuations. It is shown that the Ramakrishnan-Yussouff theory overestimates the effects of fluctuations in this system. The reasons behind the failure of the Ramakrishnan-Yussouff approximation and the suitability of using the two-dimensional Potts model asmore » a testing ground for these theories are discussed.« less
NASA Astrophysics Data System (ADS)
Octarina, Sisca; Radiana, Mutia; Bangun, Putra B. J.
2018-01-01
Two dimensional cutting stock problem (CSP) is a problem in determining the cutting pattern from a set of stock with standard length and width to fulfill the demand of items. Cutting patterns were determined in order to minimize the usage of stock. This research implemented pattern generation algorithm to formulate Gilmore and Gomory model of two dimensional CSP. The constraints of Gilmore and Gomory model was performed to assure the strips which cut in the first stage will be used in the second stage. Branch and Cut method was used to obtain the optimal solution. Based on the results, it found many patterns combination, if the optimal cutting patterns which correspond to the first stage were combined with the second stage.
NASA Astrophysics Data System (ADS)
Yang, Xiaochen; Zhang, Qinghe; Hao, Linnan
2015-03-01
A water-fluid mud coupling model is developed based on the unstructured grid finite volume coastal ocean model (FVCOM) to investigate the fluid mud motion. The hydrodynamics and sediment transport of the overlying water column are solved using the original three-dimensional ocean model. A horizontal two-dimensional fluid mud model is integrated into the FVCOM model to simulate the underlying fluid mud flow. The fluid mud interacts with the water column through the sediment flux, current, and shear stress. The friction factor between the fluid mud and the bed, which is traditionally determined empirically, is derived with the assumption that the vertical distribution of shear stress below the yield surface of fluid mud is identical to that of uniform laminar flow of Newtonian fluid in the open channel. The model is validated by experimental data and reasonable agreement is found. Compared with numerical cases with fixed friction factors, the results simulated with the derived friction factor exhibit the best agreement with the experiment, which demonstrates the necessity of the derivation of the friction factor.
NASA Technical Reports Server (NTRS)
Reddy, T. S. R.; Srivastava, R.; Mehmed, Oral
2002-01-01
An aeroelastic analysis system for flutter and forced response analysis of turbomachines based on a two-dimensional linearized unsteady Euler solver has been developed. The ASTROP2 code, an aeroelastic stability analysis program for turbomachinery, was used as a basis for this development. The ASTROP2 code uses strip theory to couple a two dimensional aerodynamic model with a three dimensional structural model. The code was modified to include forced response capability. The formulation was also modified to include aeroelastic analysis with mistuning. A linearized unsteady Euler solver, LINFLX2D is added to model the unsteady aerodynamics in ASTROP2. By calculating the unsteady aerodynamic loads using LINFLX2D, it is possible to include the effects of transonic flow on flutter and forced response in the analysis. The stability is inferred from an eigenvalue analysis. The revised code, ASTROP2-LE for ASTROP2 code using Linearized Euler aerodynamics, is validated by comparing the predictions with those obtained using linear unsteady aerodynamic solutions.
NASA Technical Reports Server (NTRS)
Scalapino, D. J.; Sugar, R. L.; White, S. R.; Bickers, N. E.; Scalettar, R. T.
1989-01-01
Numerical simulations on the half-filled three-dimensional Hubbard model clearly show the onset of Neel order. Simulations of the two-dimensional electron-phonon Holstein model show the competition between the formation of a Peierls-CDW state and a superconducting state. However, the behavior of the partly filled two-dimensional Hubbard model is more difficult to determine. At half-filling, the antiferromagnetic correlations grow as T is reduced. Doping away from half-filling suppresses these correlations, and it is found that there is a weak attractive pairing interaction in the d-wave channel. However, the strength of the pair field susceptibility is weak at the temperatures and lattice sizes that have been simulated, and the nature of the low-temperature state of the nearly half-filled Hubbard model remains open.
Exact solutions and conservation laws of the system of two-dimensional viscous Burgers equations
NASA Astrophysics Data System (ADS)
Abdulwahhab, Muhammad Alim
2016-10-01
Fluid turbulence is one of the phenomena that has been studied extensively for many decades. Due to its huge practical importance in fluid dynamics, various models have been developed to capture both the indispensable physical quality and the mathematical structure of turbulent fluid flow. Among the prominent equations used for gaining in-depth insight of fluid turbulence is the two-dimensional Burgers equations. Its solutions have been studied by researchers through various methods, most of which are numerical. Being a simplified form of the two-dimensional Navier-Stokes equations and its wide range of applicability in various fields of science and engineering, development of computationally efficient methods for the solution of the two-dimensional Burgers equations is still an active field of research. In this study, Lie symmetry method is used to perform detailed analysis on the system of two-dimensional Burgers equations. Optimal system of one-dimensional subalgebras up to conjugacy is derived and used to obtain distinct exact solutions. These solutions not only help in understanding the physical effects of the model problem but also, can serve as benchmarks for constructing algorithms and validation of numerical solutions of the system of Burgers equations under consideration at finite Reynolds numbers. Independent and nontrivial conserved vectors are also constructed.
Student Learning about Biomolecular Self-Assembly Using Two Different External Representations
ERIC Educational Resources Information Center
Host, Gunnar E.; Larsson, Caroline; Olson, Arthur; Tibell, Lena A. E.
2013-01-01
Self-assembly is the fundamental but counterintuitive principle that explains how ordered biomolecular complexes form spontaneously in the cell. This study investigated the impact of using two external representations of virus self-assembly, an interactive tangible three-dimensional model and a static two-dimensional image, on student learning…
Zheng, X; Xue, Q; Mittal, R; Beilamowicz, S
2010-11-01
A new flow-structure interaction method is presented, which couples a sharp-interface immersed boundary method flow solver with a finite-element method based solid dynamics solver. The coupled method provides robust and high-fidelity solution for complex flow-structure interaction (FSI) problems such as those involving three-dimensional flow and viscoelastic solids. The FSI solver is used to simulate flow-induced vibrations of the vocal folds during phonation. Both two- and three-dimensional models have been examined and qualitative, as well as quantitative comparisons, have been made with established results in order to validate the solver. The solver is used to study the onset of phonation in a two-dimensional laryngeal model and the dynamics of the glottal jet in a three-dimensional model and results from these studies are also presented.
Aeroacoustic theory for noncompact wing-gust interaction
NASA Technical Reports Server (NTRS)
Martinez, R.; Widnall, S. E.
1981-01-01
Three aeroacoustic models for noncompact wing-gust interaction were developed for subsonic flow. The first is that for a two dimensional (infinite span) wing passing through an oblique gust. The unsteady pressure field was obtained by the Wiener-Hopf technique; the airfoil loading and the associated acoustic field were calculated, respectively, by allowing the field point down on the airfoil surface, or by letting it go to infinity. The second model is a simple spanwise superposition of two dimensional solutions to account for three dimensional acoustic effects of wing rotation (for a helicopter blade, or some other rotating planform) and of finiteness of wing span. A three dimensional theory for a single gust was applied to calculate the acoustic signature in closed form due to blade vortex interaction in helicopters. The third model is that of a quarter infinite plate with side edge through a gust at high subsonic speed. An approximate solution for the three dimensional loading and the associated three dimensional acoustic field in closed form was obtained. The results reflected the acoustic effect of satisfying the correct loading condition at the side edge.
NASA Astrophysics Data System (ADS)
Vasilyev, V.; Ludwig, H.-G.; Freytag, B.; Lemasle, B.; Marconi, M.
2017-10-01
Context. Standard spectroscopic analyses of Cepheid variables are based on hydrostatic one-dimensional model atmospheres, with convection treated using various formulations of mixing-length theory. Aims: This paper aims to carry out an investigation of the validity of the quasi-static approximation in the context of pulsating stars. We check the adequacy of a two-dimensional time-dependent model of a Cepheid-like variable with focus on its spectroscopic properties. Methods: With the radiation-hydrodynamics code CO5BOLD, we construct a two-dimensional time-dependent envelope model of a Cepheid with Teff = 5600 K, log g = 2.0, solar metallicity, and a 2.8-day pulsation period. Subsequently, we perform extensive spectral syntheses of a set of artificial iron lines in local thermodynamic equilibrium. The set of lines allows us to systematically study effects of line strength, ionization stage, and excitation potential. Results: We evaluate the microturbulent velocity, line asymmetry, projection factor, and Doppler shifts. The microturbulent velocity, averaged over all lines, depends on the pulsational phase and varies between 1.5 and 2.7 km s-1. The derived projection factor lies between 1.23 and 1.27, which agrees with observational results. The mean Doppler shift is non-zero and negative, -1 km s-1, after averaging over several full periods and lines. This residual line-of-sight velocity (related to the "K-term") is primarily caused by horizontal inhomogeneities, and consequently we interpret it as the familiar convective blueshift ubiquitously present in non-pulsating late-type stars. Limited statistics prevent firm conclusions on the line asymmetries. Conclusions: Our two-dimensional model provides a reasonably accurate representation of the spectroscopic properties of a short-period Cepheid-like variable star. Some properties are primarily controlled by convective inhomogeneities rather than by the Cepheid-defining pulsations. Extended multi-dimensional modelling offers new insight into the nature of pulsating stars.
Herrera-López, Mauricio; Gómez-Ortiz, Olga; Ortega-Ruiz, Rosario; Jolliffe, Darrick; Romera, Eva M
2017-09-25
(1) To examine the psychometric properties of the Basic Empathy Scale (BES) with Spanish adolescents, comparing a two and a three-dimensional structure;(2) To analyse the relationship between the three-dimensional empathy and social and normative adjustment in school. Transversal and ex post facto retrospective study. Confirmatory factorial analysis, multifactorial invariance analysis and structural equations models were used. 747 students (51.3% girls) from Cordoba, Spain, aged 12-17 years (M=13.8; SD=1.21). The original two-dimensional structure was confirmed (cognitive empathy, affective empathy), but a three-dimensional structure showed better psychometric properties, highlighting the good fit found in confirmatory factorial analysis and adequate internal consistent valued, measured with Cronbach's alpha and McDonald's omega. Composite reliability and average variance extracted showed better indices for a three-factor model. The research also showed evidence of measurement invariance across gender. All the factors of the final three-dimensional BES model were direct and significantly associated with social and normative adjustment, being most strongly related to cognitive empathy. This research supports the advances in neuroscience, developmental psychology and psychopathology through a three-dimensional version of the BES, which represents an improvement in the original two-factorial model. The organisation of empathy in three factors benefits the understanding of social and normative adjustment in adolescents, in which emotional disengagement favours adjusted peer relationships. Psychoeducational interventions aimed at improving the quality of social life in schools should target these components of empathy. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
COMOC 2: Two-dimensional aerodynamics sequence, computer program user's guide
NASA Technical Reports Server (NTRS)
Manhardt, P. D.; Orzechowski, J. A.; Baker, A. J.
1977-01-01
The COMOC finite element fluid mechanics computer program system is applicable to diverse problem classes. The two dimensional aerodynamics sequence was established for solution of the potential and/or viscous and turbulent flowfields associated with subsonic flight of elementary two dimensional isolated airfoils. The sequence is constituted of three specific flowfield options in COMOC for two dimensional flows. These include the potential flow option, the boundary layer option, and the parabolic Navier-Stokes option. By sequencing through these options, it is possible to computationally construct a weak-interaction model of the aerodynamic flowfield. This report is the user's guide to operation of COMOC for the aerodynamics sequence.
Generalized Heisenberg Algebras, SUSYQM and Degeneracies: Infinite Well and Morse Potential
NASA Astrophysics Data System (ADS)
Hussin, Véronique; Marquette, Ian
2011-03-01
We consider classical and quantum one and two-dimensional systems with ladder operators that satisfy generalized Heisenberg algebras. In the classical case, this construction is related to the existence of closed trajectories. In particular, we apply these results to the infinite well and Morse potentials. We discuss how the degeneracies of the permutation symmetry of quantum two-dimensional systems can be explained using products of ladder operators. These products satisfy interesting commutation relations. The two-dimensional Morse quantum system is also related to a generalized two-dimensional Morse supersymmetric model. Arithmetical or accidental degeneracies of such system are shown to be associated to additional supersymmetry.
This technical report describes the new one-dimensional (1D) hydrodynamic and sediment transport model EFDC1D. This model that can be applied to stream networks. The model code and two sample data sets are included on the distribution CD. EFDC1D can simulate bi-directional unstea...
Bearing-Load Modeling and Analysis Study for Mechanically Connected Structures
NASA Technical Reports Server (NTRS)
Knight, Norman F., Jr.
2006-01-01
Bearing-load response for a pin-loaded hole is studied within the context of two-dimensional finite element analyses. Pin-loaded-hole configurations are representative of mechanically connected structures, such as a stiffener fastened to a rib of an isogrid panel, that are idealized as part of a larger structural component. Within this context, the larger structural component may be idealized as a two-dimensional shell finite element model to identify load paths and high stress regions. Finite element modeling and analysis aspects of a pin-loaded hole are considered in the present paper including the use of linear and nonlinear springs to simulate the pin-bearing contact condition. Simulating pin-connected structures within a two-dimensional finite element analysis model using nonlinear spring or gap elements provides an effective way for accurate prediction of the local effective stress state and peak forces.
Li, Meng; Shi, Jialin; Liu, Lianqing; Yu, Peng; Xi, Ning; Wang, Yuechao
2016-01-01
Physical properties of two-dimensional materials, such as graphene, black phosphorus, molybdenum disulfide (MoS 2 ) and tungsten disulfide, exhibit significant dependence on their lattice orientations, especially for zigzag and armchair lattice orientations. Understanding of the atomic probe motion on surfaces with different orientations helps in the study of anisotropic materials. Unfortunately, there is no comprehensive model that can describe the probe motion mechanism. In this paper, we report a tribological study of MoS 2 in zigzag and armchair orientations. We observed a characteristic power spectrum and friction force values. To explain our results, we developed a modified, two-dimensional, stick-slip Tomlinson model that allows simulation of the probe motion on MoS 2 surfaces by combining the motion in the Mo layer and S layer. Our model fits well with the experimental data and provides a theoretical basis for tribological studies of two-dimensional materials.
Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?
NASA Astrophysics Data System (ADS)
Troisi, Antonio
2017-03-01
Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f( R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R)=f_0R^n the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions.
Comparison between PVI2D and Abreu–Johnson’s Model for Petroleum Vapor Intrusion Assessment
Yao, Yijun; Wang, Yue; Verginelli, Iason; Suuberg, Eric M.; Ye, Jianfeng
2018-01-01
Recently, we have developed a two-dimensional analytical petroleum vapor intrusion model, PVI2D (petroleum vapor intrusion, two-dimensional), which can help users to easily visualize soil gas concentration profiles and indoor concentrations as a function of site-specific conditions such as source strength and depth, reaction rate constant, soil characteristics, and building features. In this study, we made a full comparison of the results returned by PVI2D and those obtained using Abreu and Johnson’s three-dimensional numerical model (AJM). These comparisons, examined as a function of the source strength, source depth, and reaction rate constant, show that PVI2D can provide similar soil gas concentration profiles and source-to-indoor air attenuation factors (within one order of magnitude difference) as those by the AJM. The differences between the two models can be ascribed to some simplifying assumptions used in PVI2D and to some numerical limitations of the AJM in simulating strictly piecewise aerobic biodegradation and no-flux boundary conditions. Overall, the obtained results show that for cases involving homogenous source and soil, PVI2D can represent a valid alternative to more rigorous three-dimensional numerical models. PMID:29398981
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiengarten, T.; Fichtner, H.; Kleimann, J.
2016-12-10
We extend a two-component model for the evolution of fluctuations in the solar wind plasma so that it is fully three-dimensional (3D) and also coupled self-consistently to the large-scale magnetohydrodynamic equations describing the background solar wind. The two classes of fluctuations considered are a high-frequency parallel-propagating wave-like piece and a low-frequency quasi-two-dimensional component. For both components, the nonlinear dynamics is dominanted by quasi-perpendicular spectral cascades of energy. Driving of the fluctuations by, for example, velocity shear and pickup ions is included. Numerical solutions to the new model are obtained using the Cronos framework, and validated against previous simpler models. Comparing results frommore » the new model with spacecraft measurements, we find improved agreement relative to earlier models that employ prescribed background solar wind fields. Finally, the new results for the wave-like and quasi-two-dimensional fluctuations are used to calculate ab initio diffusion mean-free paths and drift lengthscales for the transport of cosmic rays in the turbulent solar wind.« less
Two-Dimensional Simulation of Left-Handed Metamaterial Flat Lens Using Remcon XFDTD
NASA Technical Reports Server (NTRS)
Wilson, Jeffrey D.; Reinert, Jason M.
2006-01-01
Remcom's XFDTD software was used to model the properties of a two-dimensional left-handed metamaterial (LHM) flat lens. The focusing capability and attenuation of the material were examined. The results showed strong agreement with experimental results and theoretical predictions of focusing effects and focal length. The inherent attenuation in the model corresponds well with the experimental results and implies that the code does a reasonably accurate job of modeling the actual metamaterial.
NASA Technical Reports Server (NTRS)
Ryan, Deirdre A.; Luebbers, Raymond J.; Nguyen, Truong X.; Kunz, Karl S.; Steich, David J.
1992-01-01
Prediction of anechoic chamber performance is a difficult problem. Electromagnetic anechoic chambers exist for a wide range of frequencies but are typically very large when measured in wavelengths. Three dimensional finite difference time domain (FDTD) modeling of anechoic chambers is possible with current computers but at frequencies lower than most chamber design frequencies. However, two dimensional FDTD (2D-FTD) modeling enables much greater detail at higher frequencies and offers significant insight into compact anechoic chamber design and performance. A major subsystem of an anechoic chamber for which computational electromagnetic analyses exist is the reflector. First, an analysis of the quiet zone fields of a low frequency anechoic chamber produced by a uniform source and a reflector in two dimensions using the FDTD method is presented. The 2D-FDTD results are compared with results from a three dimensional corrected physical optics calculation and show good agreement. Next, a directional source is substituted for the uniform radiator. Finally, a two dimensional anechoic chamber geometry, including absorbing materials, is considered, and the 2D-FDTD results for these geometries appear reasonable.
NASA Astrophysics Data System (ADS)
Sun, HongGuang; Liu, Xiaoting; Zhang, Yong; Pang, Guofei; Garrard, Rhiannon
2017-09-01
Fractional-order diffusion equations (FDEs) extend classical diffusion equations by quantifying anomalous diffusion frequently observed in heterogeneous media. Real-world diffusion can be multi-dimensional, requiring efficient numerical solvers that can handle long-term memory embedded in mass transport. To address this challenge, a semi-discrete Kansa method is developed to approximate the two-dimensional spatiotemporal FDE, where the Kansa approach first discretizes the FDE, then the Gauss-Jacobi quadrature rule solves the corresponding matrix, and finally the Mittag-Leffler function provides an analytical solution for the resultant time-fractional ordinary differential equation. Numerical experiments are then conducted to check how the accuracy and convergence rate of the numerical solution are affected by the distribution mode and number of spatial discretization nodes. Applications further show that the numerical method can efficiently solve two-dimensional spatiotemporal FDE models with either a continuous or discrete mixing measure. Hence this study provides an efficient and fast computational method for modeling super-diffusive, sub-diffusive, and mixed diffusive processes in large, two-dimensional domains with irregular shapes.
Lateral tunneling through voltage-controlled barriers
NASA Technical Reports Server (NTRS)
Manion, S. J.; Bell, L. D.; Kaiser, W. J.; Maker, P. D.; Muller, R. E.
1991-01-01
The paper reports on a detailed experimental investigation of lateral tunneling between electrodes of a two-dimensional electron gas separated by the voltage-controlled barrier of a nanometer Schottky gate. The experimental data are modeled using the WKB method to calculate the tunneling probability of electrons through a barrier whose shape is determined from a solution of the two-dimensional Poisson equation. This model is in excellent agreement with the experimental data over a two order of magnitude range of current.
Effect of Shear Deformation and Continuity on Delamination Modelling with Plate Elements
NASA Technical Reports Server (NTRS)
Glaessgen, E. H.; Riddell, W. T.; Raju, I. S.
1998-01-01
The effects of several critical assumptions and parameters on the computation of strain energy release rates for delamination and debond configurations modeled with plate elements have been quantified. The method of calculation is based on the virtual crack closure technique (VCCT), and models that model the upper and lower surface of the delamination or debond with two-dimensional (2D) plate elements rather than three-dimensional (3D) solid elements. The major advantages of the plate element modeling technique are a smaller model size and simpler geometric modeling. Specific issues that are discussed include: constraint of translational degrees of freedom, rotational degrees of freedom or both in the neighborhood of the crack tip; element order and assumed shear deformation; and continuity of material properties and section stiffness in the vicinity of the debond front, Where appropriate, the plate element analyses are compared with corresponding two-dimensional plane strain analyses.
2013-01-01
Background Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Methods Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. Results The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. Conclusions The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues. PMID:23705957
Two-dimensional random surface model for asperity-contact in elastohydrodynamic lubrication
NASA Technical Reports Server (NTRS)
Coy, J. J.; Sidik, S. M.
1979-01-01
Relations for the asperity-contact time function during elastohydrodynamic lubrication of a ball bearing are presented. The analysis is based on a two-dimensional random surface model, and actual profile traces of the bearing surfaces are used as statistical sample records. The results of the analysis show that transition from 90 percent contact to 1 percent contact occurs within a dimensionless film thickness range of approximately four to five. This thickness ratio is several times large than reported in the literature where one-dimensional random surface models were used. It is shown that low pass filtering of the statistical records will bring agreement between the present results and those in the literature.
NASA Astrophysics Data System (ADS)
Ouyang, Chaojun; He, Siming; Xu, Qiang; Luo, Yu; Zhang, Wencheng
2013-03-01
A two-dimensional mountainous mass flow dynamic procedure solver (Massflow-2D) using the MacCormack-TVD finite difference scheme is proposed. The solver is implemented in Matlab on structured meshes with variable computational domain. To verify the model, a variety of numerical test scenarios, namely, the classical one-dimensional and two-dimensional dam break, the landslide in Hong Kong in 1993 and the Nora debris flow in the Italian Alps in 2000, are executed, and the model outputs are compared with published results. It is established that the model predictions agree well with both the analytical solution as well as the field observations.
Rohan Benjankar; Daniele Tonina; James McKean
2014-01-01
Studies of the effects of hydrodynamic model dimensionality on simulated flow properties and derived quantities such as aquatic habitat quality are limited. It is important to close this knowledge gap especially now that entire river networks can be mapped at the microhabitat scale due to the advent of point-cloud techniques. This study compares flow properties, such...
Computer modelling of grain microstructure in three dimensions
NASA Astrophysics Data System (ADS)
Narayan, K. Lakshmi
We present a program that generates the two-dimensional micrographs of a three dimensional grain microstructure. The code utilizes a novel scanning, pixel mapping technique to secure statistical distributions of surface areas, grain sizes, aspect ratios, perimeters, number of nearest neighbors and volumes of the randomly nucleated particles. The program can be used for comparing the existing theories of grain growth, and interpretation of two-dimensional microstructure of three-dimensional samples. Special features have been included to minimize the computation time and resource requirements.
An integrated approach to reservoir modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Donaldson, K.
1993-08-01
The purpose of this research is to evaluate the usefulness of the following procedural and analytical methods in investigating the heterogeneity of the oil reserve for the Mississipian Big Injun Sandstone of the Granny Creek field, Clay and Roane counties, West Virginia: (1) relational database, (2) two-dimensional cross sections, (3) true three-dimensional modeling, (4) geohistory analysis, (5) a rule-based expert system, and (6) geographical information systems. The large data set could not be effectively integrated and interpreted without this approach. A relational database was designed to fully integrate three- and four-dimensional data. The database provides an effective means for maintainingmore » and manipulating the data. A two-dimensional cross section program was designed to correlate stratigraphy, depositional environments, porosity, permeability, and petrographic data. This flexible design allows for additional four-dimensional data. Dynamic Graphics[sup [trademark
Two-Dimensional Computational Model for Wave Rotor Flow Dynamics
NASA Technical Reports Server (NTRS)
Welch, Gerard E.
1996-01-01
A two-dimensional (theta,z) Navier-Stokes solver for multi-port wave rotor flow simulation is described. The finite-volume form of the unsteady thin-layer Navier-Stokes equations are integrated in time on multi-block grids that represent the stationary inlet and outlet ports and the moving rotor passages of the wave rotor. Computed results are compared with three-port wave rotor experimental data. The model is applied to predict the performance of a planned four-port wave rotor experiment. Two-dimensional flow features that reduce machine performance and influence rotor blade and duct wall thermal loads are identified. The performance impact of rounding the inlet port wall, to inhibit separation during passage gradual opening, is assessed.
Two-dimensional electronic spectra of the photosynthetic apparatus of green sulfur bacteria
NASA Astrophysics Data System (ADS)
Kramer, Tobias; Rodriguez, Mirta
2017-03-01
Advances in time resolved spectroscopy have provided new insight into the energy transmission in natural photosynthetic complexes. Novel theoretical tools and models are being developed in order to explain the experimental results. We provide a model calculation for the two-dimensional electronic spectra of Cholorobaculum tepidum which correctly describes the main features and transfer time scales found in recent experiments. From our calculation one can infer the coupling of the antenna chlorosome with the environment and the coupling between the chlorosome and the Fenna-Matthews-Olson complex. We show that environment assisted transport between the subunits is the required mechanism to reproduce the experimental two-dimensional electronic spectra.
NASA Astrophysics Data System (ADS)
Guinot, Vincent
2017-11-01
The validity of flux and source term formulae used in shallow water models with porosity for urban flood simulations is assessed by solving the two-dimensional shallow water equations over computational domains representing periodic building layouts. The models under assessment are the Single Porosity (SP), the Integral Porosity (IP) and the Dual Integral Porosity (DIP) models. 9 different geometries are considered. 18 two-dimensional initial value problems and 6 two-dimensional boundary value problems are defined. This results in a set of 96 fine grid simulations. Analysing the simulation results leads to the following conclusions: (i) the DIP flux and source term models outperform those of the SP and IP models when the Riemann problem is aligned with the main street directions, (ii) all models give erroneous flux closures when is the Riemann problem is not aligned with one of the main street directions or when the main street directions are not orthogonal, (iii) the solution of the Riemann problem is self-similar in space-time when the street directions are orthogonal and the Riemann problem is aligned with one of them, (iv) a momentum balance confirms the existence of the transient momentum dissipation model presented in the DIP model, (v) none of the source term models presented so far in the literature allows all flow configurations to be accounted for(vi) future laboratory experiments aiming at the validation of flux and source term closures should focus on the high-resolution, two-dimensional monitoring of both water depth and flow velocity fields.
Field-scale and wellbore modeling of compaction-induced casing failures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hilbert, L.B. Jr.; Gwinn, R.L.; Moroney, T.A.
1999-06-01
Presented in this paper are the results and verification of field- and wellbore-scale large deformation, elasto-plastic, geomechanical finite element models of reservoir compaction and associated casing damage. The models were developed as part of a multidisciplinary team project to reduce the number of costly well failures in the diatomite reservoir of the South Belridge Field near Bakersfield, California. Reservoir compaction of high porosity diatomite rock induces localized shearing deformations on horizontal weak-rock layers and geologic unconformities. The localized shearing deformations result in casing damage or failure. Two-dimensional, field-scale finite element models were used to develop relationships between field operations, surfacemore » subsidence, and shear-induced casing damage. Pore pressures were computed for eighteen years of simulated production and water injection, using a three-dimensional reservoir simulator. The pore pressures were input to the two-dimensional geomechanical field-scale model. Frictional contact surfaces were used to model localized shear deformations. To capture the complex casing-cement-rock interaction that governs casing damage and failure, three-dimensional models of a wellbore were constructed, including a frictional sliding surface to model localized shear deformation. Calculations were compared to field data for verification of the models.« less
Li, Jia; Xia, Yunni; Luo, Xin
2014-01-01
OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy.
2008-01-01
the sensor is a data cloud in multi- dimensional space with each band generating an axis of dimension. When the data cloud is viewed in two or three...endmember of interest is not a true endmember in the data space . A ) B) Figure 8: Linear mixture models. A ) two- dimensional ...multi- dimensional space . A classifier is a computer algorithm that takes
Compactification on phase space
NASA Astrophysics Data System (ADS)
Lovelady, Benjamin; Wheeler, James
2016-03-01
A major challenge for string theory is to understand the dimensional reduction required for comparison with the standard model. We propose reducing the dimension of the compactification by interpreting some of the extra dimensions as the energy-momentum portion of a phase-space. Such models naturally arise as generalized quotients of the conformal group called biconformal spaces. By combining the standard Kaluza-Klein approach with such a conformal gauge theory, we may start from the conformal group of an n-dimensional Euclidean space to form a 2n-dimensional quotient manifold with symplectic structure. A pair of involutions leads naturally to two n-dimensional Lorentzian manifolds. For n = 5, this leaves only two extra dimensions, with a countable family of possible compactifications and an SO(5) Yang-Mills field on the fibers. Starting with n=6 leads to 4-dimensional compactification of the phase space. In the latter case, if the two dimensions each from spacetime and momentum space are compactified onto spheres, then there is an SU(2)xSU(2) (left-right symmetric electroweak) field between phase and configuration space and an SO(6) field on the fibers. Such a theory, with minor additional symmetry breaking, could contain all parts of the standard model.
Learning of Cross-Sectional Anatomy Using Clay Models
ERIC Educational Resources Information Center
Oh, Chang-Seok; Kim, Ji-Young; Choe, Yeon Hyeon
2009-01-01
We incorporated clay modeling into gross anatomy and neuro-anatomy courses to help students understand cross-sectional anatomy. By making clay models, cutting them and comparing cut surfaces to CT and MR images, students learned how cross-sectional two-dimensional images were created from three-dimensional structure of human organs. Most students…
NASA Astrophysics Data System (ADS)
Sharma, Neetika; Verma, Neha; Jogi, Jyotika
2017-11-01
This paper models the scattering limited electron transport in a nano-dimensional In0.52Al0.48As/In0.53Ga0.47As/InP heterostructure. An analytical model for temperature dependent sheet carrier concentration and carrier mobility in a two dimensional electron gas, confined in a triangular potential well has been developed. The model accounts for all the major scattering process including ionized impurity scattering and lattice scattering. Quantum mechanical variational technique is employed for studying the intrasubband scattering mechanism in the two dimensional electron gas. Results of various scattering limited structural parameters such as energy band-gap and functional parameters such as sheet carrier concentration, scattering rate and mobility are presented. The model corroborates the dominance of ionized impurity scattering mechanism at low temperatures and that of lattice scattering at high temperatures, both in turn limiting the carrier mobility. Net mobility obtained taking various scattering mechanisms into account has been found in agreement with earlier reported results, thus validating the model.
Music Signal Processing Using Vector Product Neural Networks
NASA Astrophysics Data System (ADS)
Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.
2017-05-01
We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.
Stationary Solutions of A One-dimensional Thermodynamic Radiative Sea Ice Model
NASA Astrophysics Data System (ADS)
Taylor, P. D.; Feltham, D. L.
A one-dimensional thermodynamic model of sea ice is coupled to a two-stream radi- ation model and the stationary (time-independent) solutions analysed. The stationary model represents the state of the sea ice subjected to persistent or slowly varying forc- ing. Two physically realisable stationary solutions (real and positive ice thickness) occur for a large range of positive oceanic heat flux ( 20,Wm-2). The two station- ary solutions are due to the two-stream radiation model, which allows radiation to be reflected at the ice-ocean interface. Thick ice ( 1,m) only absorbs radiation near its surface, whereas thin ice ( 0.1,m) absorbs radiation across its entire depth. The two stationary solutions are caused by these two different radiative regimes. The results of this analysis have relevance to the interpretation and implementation of thermody- namic models of sea ice and the interpretation of thickness data.
Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy
NASA Astrophysics Data System (ADS)
Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li
2018-03-01
In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
A new model for two-dimensional numerical simulation of pseudo-2D gas-solids fluidized beds
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Tingwen; Zhang, Yongmin
2013-10-11
Pseudo-two dimensional (pseudo-2D) fluidized beds, for which the thickness of the system is much smaller than the other two dimensions, is widely used to perform fundamental studies on bubble behavior, solids mixing, or clustering phenomenon in different gas-solids fluidization systems. The abundant data from such experimental systems are very useful for numerical model development and validation. However, it has been reported that two-dimensional (2D) computational fluid dynamic (CFD) simulations of pseudo-2D gas-solids fluidized beds usually predict poor quantitative agreement with the experimental data, especially for the solids velocity field. In this paper, a new model is proposed to improve themore » 2D numerical simulations of pseudo-2D gas-solids fluidized beds by properly accounting for the frictional effect of the front and back walls. Two previously reported pseudo-2D experimental systems were simulated with this model. Compared to the traditional 2D simulations, significant improvements in the numerical predictions have been observed and the predicted results are in better agreement with the available experimental data.« less
Scalar quantum chromodynamics in two dimensions and parton model. [Scalar quarks, SU(N) groups
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shei, S.S.; Tsao, H.S.
1977-05-01
The SU(N) scalar quantum chromodynamics in two space-time dimensions in the large N limit are studied. This is the model of color gauge fields interacting with scalar quarks. It is found that the consensual properties of the four dimensional QCD, i.e., the infrared slavery, quark confinement, the charmonium picture etc. are all realized. Moreover, the current in this model mimics nicely the behaviors of current in the four dimensional QCD, in contrast to the original model of 't Hooft.
Computer modeling of inversion layer MOS solar cells and arrays
NASA Technical Reports Server (NTRS)
Ho, Fat Duen
1991-01-01
A two dimensional numerical model of the inversion layer metal insulator semiconductor (IL/MIS) solar cell is proposed by using the finite element method. The two-dimensional current flow in the device is taken into account in this model. The electrostatic potential distribution, the electron concentration distribution, and the hole concentration distribution for different terminal voltages are simulated. The results of simple calculation are presented. The existing problems for this model are addressed. Future work is proposed. The MIS structures are studied and some of the results are reported.
A finite area scheme for shallow granular flows on three-dimensional surfaces
NASA Astrophysics Data System (ADS)
Rauter, Matthias
2017-04-01
Shallow granular flow models have become a popular tool for the estimation of natural hazards, such as landslides, debris flows and avalanches. The shallowness of the flow allows to reduce the three-dimensional governing equations to a quasi two-dimensional system. Three-dimensional flow fields are replaced by their depth-integrated two-dimensional counterparts, which yields a robust and fast method [1]. A solution for a simple shallow granular flow model, based on the so-called finite area method [3] is presented. The finite area method is an adaption of the finite volume method [4] to two-dimensional curved surfaces in three-dimensional space. This method handles the three dimensional basal topography in a simple way, making the model suitable for arbitrary (but mildly curved) topography, such as natural terrain. Furthermore, the implementation into the open source software OpenFOAM [4] is shown. OpenFOAM is a popular computational fluid dynamics application, designed so that the top-level code mimics the mathematical governing equations. This makes the code easy to read and extendable to more sophisticated models. Finally, some hints on how to get started with the code and how to extend the basic model will be given. I gratefully acknowledge the financial support by the OEAW project "beyond dense flow avalanches". Savage, S. B. & Hutter, K. 1989 The motion of a finite mass of granular material down a rough incline. Journal of Fluid Mechanics 199, 177-215. Ferziger, J. & Peric, M. 2002 Computational methods for fluid dynamics, 3rd edn. Springer. Tukovic, Z. & Jasak, H. 2012 A moving mesh finite volume interface tracking method for surface tension dominated interfacial fluid flow. Computers & fluids 55, 70-84. Weller, H. G., Tabor, G., Jasak, H. & Fureby, C. 1998 A tensorial approach to computational continuum mechanics using object-oriented techniques. Computers in physics 12(6), 620-631.
Modeling and control of flexible structures
NASA Technical Reports Server (NTRS)
Gibson, J. S.; Mingori, D. L.
1988-01-01
This monograph presents integrated modeling and controller design methods for flexible structures. The controllers, or compensators, developed are optimal in the linear-quadratic-Gaussian sense. The performance objectives, sensor and actuator locations and external disturbances influence both the construction of the model and the design of the finite dimensional compensator. The modeling and controller design procedures are carried out in parallel to ensure compatibility of these two aspects of the design problem. Model reduction techniques are introduced to keep both the model order and the controller order as small as possible. A linear distributed, or infinite dimensional, model is the theoretical basis for most of the text, but finite dimensional models arising from both lumped-mass and finite element approximations also play an important role. A central purpose of the approach here is to approximate an optimal infinite dimensional controller with an implementable finite dimensional compensator. Both convergence theory and numerical approximation methods are given. Simple examples are used to illustrate the theory.
Extreme value modelling of Ghana stock exchange index.
Nortey, Ezekiel N N; Asare, Kwabena; Mettle, Felix Okoe
2015-01-01
Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana stock exchange all-shares index (2000-2010) by applying the extreme value theory (EVT) to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before the EVT method was applied. The Peak Over Threshold approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model's goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the value at risk and expected shortfall risk measures at some high quantiles, based on the fitted GPD model.
Strong second harmonic generation in two-dimensional ferroelectric IV-monochalcogenides
NASA Astrophysics Data System (ADS)
Panday, Suman Raj; Fregoso, Benjamin M.
2017-11-01
The two-dimensional ferroelectrics GeS, GeSe, SnS and SnSe are expected to have large spontaneous in-plane electric polarization and enhanced shift-current response. Using density functional methods, we show that these materials also exhibit the largest effective second harmonic generation reported so far. It can reach magnitudes up to 10~nm~V-1 which is about an order of magnitude larger than that of prototypical GaAs. To rationalize this result we model the optical response with a simple one-dimensional two-band model along the spontaneous polarization direction. Within this model the second-harmonic generation tensor is proportional to the shift-current response tensor. The large shift current and second harmonic responses of GeS, GeSe, SnS and SnSe make them promising non-linear materials for optoelectronic applications.
A small-scale turbulence model
NASA Technical Reports Server (NTRS)
Lundgren, T. S.
1992-01-01
A model for the small-scale structure of turbulence is reformulated in such a way that it may be conveniently computed. The model is an ensemble of randomly oriented structured two dimensional vortices stretched by an axially symmetric strain flow. The energy spectrum of the resulting flow may be expressed as a time integral involving only the enstrophy spectrum of the time evolving two-dimensional cross section flow, which may be obtained numerically. Examples are given in which a k(exp -5/3) spectrum is obtained by this method without using large wave number asymptotic analysis. The k(exp -5/3) inertial range spectrum is shown to be related to the existence of a self-similar enstrophy preserving range in the two-dimensional enstrophy spectrum. The results are insensitive to time dependence of the strain-rate, including even intermittent on-or-off strains.
Regularity of Solutions of the Nonlinear Sigma Model with Gravitino
NASA Astrophysics Data System (ADS)
Jost, Jürgen; Keßler, Enno; Tolksdorf, Jürgen; Wu, Ruijun; Zhu, Miaomiao
2018-02-01
We propose a geometric setup to study analytic aspects of a variant of the super symmetric two-dimensional nonlinear sigma model. This functional extends the functional of Dirac-harmonic maps by gravitino fields. The system of Euler-Lagrange equations of the two-dimensional nonlinear sigma model with gravitino is calculated explicitly. The gravitino terms pose additional analytic difficulties to show smoothness of its weak solutions which are overcome using Rivière's regularity theory and Riesz potential theory.
Advantages of multigrid methods for certifying the accuracy of PDE modeling
NASA Technical Reports Server (NTRS)
Forester, C. K.
1981-01-01
Numerical techniques for assessing and certifying the accuracy of the modeling of partial differential equations (PDE) to the user's specifications are analyzed. Examples of the certification process with conventional techniques are summarized for the three dimensional steady state full potential and the two dimensional steady Navier-Stokes equations using fixed grid methods (FG). The advantages of the Full Approximation Storage (FAS) scheme of the multigrid technique of A. Brandt compared with the conventional certification process of modeling PDE are illustrated in one dimension with the transformed potential equation. Inferences are drawn for how MG will improve the certification process of the numerical modeling of two and three dimensional PDE systems. Elements of the error assessment process that are common to FG and MG are analyzed.
Two-dimensional models as testing ground for principles and concepts of local quantum physics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schroer, Bert
In the past two-dimensional models of QFT have served as theoretical laboratories for testing new concepts under mathematically controllable condition. In more recent times low-dimensional models (e.g., chiral models, factorizing models) often have been treated by special recipes in a way which sometimes led to a loss of unity of QFT. In the present work, I try to counteract this apartheid tendency by reviewing past results within the setting of the general principles of QFT. To this I add two new ideas: (1) a modular interpretation of the chiral model Diff(S)-covariance with a close connection to the recently formulated localmore » covariance principle for QFT in curved spacetime and (2) a derivation of the chiral model temperature duality from a suitable operator formulation of the angular Wick rotation (in analogy to the Nelson-Symanzik duality in the Ostertwalder-Schrader setting) for rational chiral theories. The SL (2, Z) modular Verlinde relation is a special case of this thermal duality and (within the family of rational models) the matrix S appearing in the thermal duality relation becomes identified with the statistics character matrix S. The relevant angular 'Euclideanization' is done in the setting of the Tomita-Takesaki modular formalism of operator algebras. I find it appropriate to dedicate this work to the memory of J.A. Swieca with whom I shared the interest in two-dimensional models as a testing ground for QFT for more than one decade. This is a significantly extended version of an 'Encyclopedia of Mathematical Physics' contribution hep-th/0502125.« less
Two-dimensional models as testing ground for principles and concepts of local quantum physics
NASA Astrophysics Data System (ADS)
Schroer, Bert
2006-02-01
In the past two-dimensional models of QFT have served as theoretical laboratories for testing new concepts under mathematically controllable condition. In more recent times low-dimensional models (e.g., chiral models, factorizing models) often have been treated by special recipes in a way which sometimes led to a loss of unity of QFT. In the present work, I try to counteract this apartheid tendency by reviewing past results within the setting of the general principles of QFT. To this I add two new ideas: (1) a modular interpretation of the chiral model Diff( S)-covariance with a close connection to the recently formulated local covariance principle for QFT in curved spacetime and (2) a derivation of the chiral model temperature duality from a suitable operator formulation of the angular Wick rotation (in analogy to the Nelson-Symanzik duality in the Ostertwalder-Schrader setting) for rational chiral theories. The SL (2, Z) modular Verlinde relation is a special case of this thermal duality and (within the family of rational models) the matrix S appearing in the thermal duality relation becomes identified with the statistics character matrix S. The relevant angular "Euclideanization" is done in the setting of the Tomita-Takesaki modular formalism of operator algebras. I find it appropriate to dedicate this work to the memory of J.A. Swieca with whom I shared the interest in two-dimensional models as a testing ground for QFT for more than one decade. This is a significantly extended version of an "Encyclopedia of Mathematical Physics" contribution hep-th/0502125.
Dynamics of a neuron model in different two-dimensional parameter-spaces
NASA Astrophysics Data System (ADS)
Rech, Paulo C.
2011-03-01
We report some two-dimensional parameter-space diagrams numerically obtained for the multi-parameter Hindmarsh-Rose neuron model. Several different parameter planes are considered, and we show that regardless of the combination of parameters, a typical scenario is preserved: for all choice of two parameters, the parameter-space presents a comb-shaped chaotic region immersed in a large periodic region. We also show that exist regions close these chaotic region, separated by the comb teeth, organized themselves in period-adding bifurcation cascades.
Two-dimensional heteroclinic attractor in the generalized Lotka-Volterra system
NASA Astrophysics Data System (ADS)
Afraimovich, Valentin S.; Moses, Gregory; Young, Todd
2016-05-01
We study a simple dynamical model exhibiting sequential dynamics. We show that in this model there exist sets of parameter values for which a cyclic chain of saddle equilibria, O k , k=1,\\ldots,p , have two-dimensional unstable manifolds that contain orbits connecting each O k to the next two equilibrium points O k+1 and O k+2 in the chain ({{O}p+1}={{O}1} ). We show that the union of these equilibria and their unstable manifolds form a two-dimensional surface with a boundary that is homeomorphic to a cylinder if p is even and a Möbius strip if p is odd. If, further, each equilibrium in the chain satisfies a condition called ‘dissipativity’, then this surface is asymptotically stable.
NASA Astrophysics Data System (ADS)
Benjankar, R. M.; Sohrabi, M.; Tonina, D.; McKean, J. A.
2013-12-01
Aquatic habitat models utilize flow variables which may be predicted with one-dimensional (1D) or two-dimensional (2D) hydrodynamic models to simulate aquatic habitat quality. Studies focusing on the effects of hydrodynamic model dimensionality on predicted aquatic habitat quality are limited. Here we present the analysis of the impact of flow variables predicted with 1D and 2D hydrodynamic models on simulated spatial distribution of habitat quality and Weighted Usable Area (WUA) for fall-spawning Chinook salmon. Our study focuses on three river systems located in central Idaho (USA), which are a straight and pool-riffle reach (South Fork Boise River), small pool-riffle sinuous streams in a large meadow (Bear Valley Creek) and a steep-confined plane-bed stream with occasional deep forced pools (Deadwood River). We consider low and high flows in simple and complex morphologic reaches. Results show that 1D and 2D modeling approaches have effects on both the spatial distribution of the habitat and WUA for both discharge scenarios, but we did not find noticeable differences between complex and simple reaches. In general, the differences in WUA were small, but depended on stream type. Nevertheless, spatially distributed habitat quality difference is considerable in all streams. The steep-confined plane bed stream had larger differences between aquatic habitat quality defined with 1D and 2D flow models compared to results for streams with well defined macro-topographies, such as pool-riffle bed forms. KEY WORDS: one- and two-dimensional hydrodynamic models, habitat modeling, weighted usable area (WUA), hydraulic habitat suitability, high and low discharges, simple and complex reaches
Numerical modeling of surface wave development under the action of wind
NASA Astrophysics Data System (ADS)
Chalikov, Dmitry
2018-06-01
The numerical modeling of two-dimensional surface wave development under the action of wind is performed. The model is based on three-dimensional equations of potential motion with a free surface written in a surface-following nonorthogonal curvilinear coordinate system in which depth is counted from a moving surface. A three-dimensional Poisson equation for the velocity potential is solved iteratively. A Fourier transform method, a second-order accuracy approximation of vertical derivatives on a stretched vertical grid and fourth-order Runge-Kutta time stepping are used. Both the input energy to waves and dissipation of wave energy are calculated on the basis of earlier developed and validated algorithms. A one-processor version of the model for PC allows us to simulate an evolution of the wave field with thousands of degrees of freedom over thousands of wave periods. A long-time evolution of a two-dimensional wave structure is illustrated by the spectra of wave surface and the input and output of energy.
NASA Astrophysics Data System (ADS)
Lamb, Richard L.
2016-02-01
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the form of three-dimensional serious educational games, two-dimensional online laboratories, and traditional lecture-based instruction in the context of student content learning in science. In particular, this study examines the impact of dimensionality, or the ability to move along the X-, Y-, and Z-axis in the games. Study subjects ( N = 551) were randomly selected using a stratified sampling technique. Independent strata subsamples were developed based upon the conditions of serious educational games, online laboratories, and lecture. The study also computationally models a potential mechanism of action and compares two- and three-dimensional learning environments. F test results suggest a significant difference for the main effect of condition across the factor of content gain score with large effect. Overall, comparisons using computational models suggest that three-dimensional serious educational games increase the level of success in learning as measured with content examinations through greater recruitment and attributional retraining of cognitive systems. The study supports assertions in the literature that the use of games in higher dimensions (i.e., three-dimensional versus two-dimensional) helps to increase student understanding of science concepts.
Jiang, Zhi-Shen; Wang, Fei; Xing, Da-Wei; Xu, Ting; Yan, Jian-Hua; Cen, Ke-Fa
2012-11-01
The experimental method by using the tunable diode laser absorption spectroscopy combined with the model and algo- rithm was studied to reconstruct the two-dimensional distribution of gas concentration The feasibility of the reconstruction program was verified by numerical simulation A diagnostic system consisting of 24 lasers was built for the measurement of H2O in the methane/air premixed flame. The two-dimensional distribution of H2O concentration in the flame was reconstructed, showing that the reconstruction results reflect the real two-dimensional distribution of H2O concentration in the flame. This diagnostic scheme provides a promising solution for combustion control.
Two Dimensional Mechanism for Insect Hovering
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jane Wang, Z.
2000-09-04
Resolved computation of two dimensional insect hovering shows for the first time that a two dimensional hovering motion can generate enough lift to support a typical insect weight. The computation reveals a two dimensional mechanism of creating a downward dipole jet of counterrotating vortices, which are formed from leading and trailing edge vortices. The vortex dynamics further elucidates the role of the phase relation between the wing translation and rotation in lift generation and explains why the instantaneous forces can reach a periodic state after only a few strokes. The model predicts the lower limits in Reynolds number and amplitudemore » above which the averaged forces are sufficient. (c) 2000 The American Physical Society.« less
A NetCDF version of the two-dimensional energy balance model based on the full multigrid algorithm
NASA Astrophysics Data System (ADS)
Zhuang, Kelin; North, Gerald R.; Stevens, Mark J.
A NetCDF version of the two-dimensional energy balance model based on the full multigrid method in Fortran is introduced for both pedagogical and research purposes. Based on the land-sea-ice distribution, orbital elements, greenhouse gases concentration, and albedo, the code calculates the global seasonal surface temperature. A step-by-step guide with examples is provided for practice.
Monte Carlo calculation of dynamical properties of the two-dimensional Hubbard model
NASA Technical Reports Server (NTRS)
White, S. R.; Scalapino, D. J.; Sugar, R. L.; Bickers, N. E.
1989-01-01
A new method is introduced for analytically continuing imaginary-time data from quantum Monte Carlo calculations to the real-frequency axis. The method is based on a least-squares-fitting procedure with constraints of positivity and smoothness on the real-frequency quantities. Results are shown for the single-particle spectral-weight function and density of states for the half-filled, two-dimensional Hubbard model.
Critical behavior of two-dimensional vesicles in the deflated regime
NASA Technical Reports Server (NTRS)
Banavar, Jayanth R.; Maritan, Amos; Stella, Attilio
1991-01-01
The critical behavior of two-dimensional vesicles in the deflated regime is studied analytically using a mapping onto a gauge model, scaling arguments, and exact inequalities. In agreement with the results of earlier studies the critical behavior is governed by a branched-polymer fixed point. The shape of the critical line in the gauge model is deduced in the weak and in the infinitely deflated regime.
NASA Astrophysics Data System (ADS)
Falvo, Cyril
2018-02-01
The theory of linear and non-linear infrared response of vibrational Holstein polarons in one-dimensional lattices is presented in order to identify the spectral signatures of self-trapping phenomena. Using a canonical transformation, the optical response is computed from the small polaron point of view which is valid in the anti-adiabatic limit. Two types of phonon baths are considered: optical phonons and acoustical phonons, and simple expressions are derived for the infrared response. It is shown that for the case of optical phonons, the linear response can directly probe the polaron density of states. The model is used to interpret the experimental spectrum of crystalline acetanilide in the C=O range. For the case of acoustical phonons, it is shown that two bound states can be observed in the two-dimensional infrared spectrum at low temperature. At high temperature, analysis of the time-dependence of the two-dimensional infrared spectrum indicates that bath mediated correlations slow down spectral diffusion. The model is used to interpret the experimental linear-spectroscopy of model α-helix and β-sheet polypeptides. This work shows that the Davydov Hamiltonian cannot explain the observations in the NH stretching range.
NASA Astrophysics Data System (ADS)
González, Angélica; Linares, Román; Maceda, Marco; Sánchez-Santos, Oscar
2018-04-01
We analyze noncommutative deformations of a higher dimensional anti-de Sitter-Einstein-Born-Infeld black hole. Two models based on noncommutative inspired distributions of mass and charge are discussed and their thermodynamical properties such as the equation of state are explicitly calculated. In the (3 + 1)-dimensional case the Gibbs energy function of each model is used to discuss the presence of phase transitions.
NASA Astrophysics Data System (ADS)
Dashti-Naserabadi, H.; Najafi, M. N.
2017-10-01
We present extensive numerical simulations of Bak-Tang-Wiesenfeld (BTW) sandpile model on the hypercubic lattice in the upper critical dimension Du=4 . After re-extracting the critical exponents of avalanches, we concentrate on the three- and two-dimensional (2D) cross sections seeking for the induced criticality which are reflected in the geometrical and local exponents. Various features of finite-size scaling (FSS) theory have been tested and confirmed for all dimensions. The hyperscaling relations between the exponents of the distribution functions and the fractal dimensions are shown to be valid for all dimensions. We found that the exponent of the distribution function of avalanche mass is the same for the d -dimensional cross sections and the d -dimensional BTW model for d =2 and 3. The geometrical quantities, however, have completely different behaviors with respect to the same-dimensional BTW model. By analyzing the FSS theory for the geometrical exponents of the two-dimensional cross sections, we propose that the 2D induced models have degrees of similarity with the Gaussian free field (GFF). Although some local exponents are slightly different, this similarity is excellent for the fractal dimensions. The most important one showing this feature is the fractal dimension of loops df, which is found to be 1.50 ±0.02 ≈3/2 =dfGFF .
Dashti-Naserabadi, H; Najafi, M N
2017-10-01
We present extensive numerical simulations of Bak-Tang-Wiesenfeld (BTW) sandpile model on the hypercubic lattice in the upper critical dimension D_{u}=4. After re-extracting the critical exponents of avalanches, we concentrate on the three- and two-dimensional (2D) cross sections seeking for the induced criticality which are reflected in the geometrical and local exponents. Various features of finite-size scaling (FSS) theory have been tested and confirmed for all dimensions. The hyperscaling relations between the exponents of the distribution functions and the fractal dimensions are shown to be valid for all dimensions. We found that the exponent of the distribution function of avalanche mass is the same for the d-dimensional cross sections and the d-dimensional BTW model for d=2 and 3. The geometrical quantities, however, have completely different behaviors with respect to the same-dimensional BTW model. By analyzing the FSS theory for the geometrical exponents of the two-dimensional cross sections, we propose that the 2D induced models have degrees of similarity with the Gaussian free field (GFF). Although some local exponents are slightly different, this similarity is excellent for the fractal dimensions. The most important one showing this feature is the fractal dimension of loops d_{f}, which is found to be 1.50±0.02≈3/2=d_{f}^{GFF}.
An initial investigation into methods of computing transonic aerodynamic sensitivity coefficients
NASA Technical Reports Server (NTRS)
Carlson, Leland A.
1988-01-01
The initial effort was concentrated on developing the quasi-analytical approach for two-dimensional transonic flow. To keep the problem computationally efficient and straightforward, only the two-dimensional flow was considered and the problem was modeled using the transonic small perturbation equation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kung, Y. F.; Bazin, C.; Wohlfeld, K.
Using determinant quantum Monte Carlo (DQMC) simulations, we systematically study the doping dependence of the crossover from one to two dimensions and its impact on the magnetic properties of the Hubbard model. A square lattice of chains is used, in which the dimensionality can be tuned by varying the interchain coupling t ⊥. The dynamical spin structure factor and static quantities, such as the static spin susceptibility and nearest-neighbor spin correlation function, are characterized in the one- and two-dimensional limits as a benchmark. When the dimensionality is tuned between these limits, the magnetic properties, while evolving smoothly from one tomore » two dimensions, drastically change regardless of the doping level. This suggests that the spin excitations in the two-dimensional Hubbard model, even in the heavily doped case, cannot be explained using the spinon picture known from one dimension. In conclusion, the DQMC calculations are complemented by cluster perturbation theory studies to form a more complete picture of how the crossover occurs as a function of doping and how doped holes impact magnetic order.« less
Kimizuka, Hajime; Kurokawa, Shu; Yamaguchi, Akihiro; Sakai, Akira; Ogata, Shigenobu
2014-01-01
Predicting the equilibrium ordered structures at internal interfaces, especially in the case of nanometer-scale chemical heterogeneities, is an ongoing challenge in materials science. In this study, we established an ab-initio coarse-grained modeling technique for describing the phase-like behavior of a close-packed stacking-fault-type interface containing solute nanoclusters, which undergo a two-dimensional disorder-order transition, depending on the temperature and composition. Notably, this approach can predict the two-dimensional medium-range ordering in the nanocluster arrays realized in Mg-based alloys, in a manner consistent with scanning tunneling microscopy-based measurements. We predicted that the repulsively interacting solute-cluster system undergoes a continuous evolution into a highly ordered densely packed morphology while maintaining a high degree of six-fold orientational order, which is attributable mainly to an entropic effect. The uncovered interaction-dependent ordering properties may be useful for the design of nanostructured materials utilizing the self-organization of two-dimensional nanocluster arrays in the close-packed interfaces. PMID:25471232
Dickinson, J.E.; James, S.C.; Mehl, S.; Hill, M.C.; Leake, S.A.; Zyvoloski, G.A.; Faunt, C.C.; Eddebbarh, A.-A.
2007-01-01
A flexible, robust method for linking parent (regional-scale) and child (local-scale) grids of locally refined models that use different numerical methods is developed based on a new, iterative ghost-node method. Tests are presented for two-dimensional and three-dimensional pumped systems that are homogeneous or that have simple heterogeneity. The parent and child grids are simulated using the block-centered finite-difference MODFLOW and control-volume finite-element FEHM models, respectively. The models are solved iteratively through head-dependent (child model) and specified-flow (parent model) boundary conditions. Boundary conditions for models with nonmatching grids or zones of different hydraulic conductivity are derived and tested against heads and flows from analytical or globally-refined models. Results indicate that for homogeneous two- and three-dimensional models with matched grids (integer number of child cells per parent cell), the new method is nearly as accurate as the coupling of two MODFLOW models using the shared-node method and, surprisingly, errors are slightly lower for nonmatching grids (noninteger number of child cells per parent cell). For heterogeneous three-dimensional systems, this paper compares two methods for each of the two sets of boundary conditions: external heads at head-dependent boundary conditions for the child model are calculated using bilinear interpolation or a Darcy-weighted interpolation; specified-flow boundary conditions for the parent model are calculated using model-grid or hydrogeologic-unit hydraulic conductivities. Results suggest that significantly more accurate heads and flows are produced when both Darcy-weighted interpolation and hydrogeologic-unit hydraulic conductivities are used, while the other methods produce larger errors at the boundary between the regional and local models. The tests suggest that, if posed correctly, the ghost-node method performs well. Additional testing is needed for highly heterogeneous systems. ?? 2007 Elsevier Ltd. All rights reserved.
Temperature maxima in stable two-dimensional shock waves
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kum, O.; Hoover, W.G.; Hoover, C.G.
1997-07-01
We use molecular dynamics to study the structure of moderately strong shock waves in dense two-dimensional fluids, using Lucy{close_quote}s pair potential. The stationary profiles show relatively broad temperature maxima, for both the longitudinal and the average kinetic temperatures, just as does Mott-Smith{close_quote}s model for strong shock waves in dilute three-dimensional gases. {copyright} {ital 1997} {ital The American Physical Society}
Do, D D; Do, H D
2004-12-07
Adsorption of ethylene and ethane on graphitized thermal carbon black and in slit pores whose walls are composed of graphene layers is studied in detail to investigate the packing efficiency, the two-dimensional critical temperature, and the variation of the isosteric heat of adsorption with loading and temperature. Here we used a Monte Carlo simulation method with a grand canonical Monte Carlo ensemble. A number of two-center Lennard-Jones (LJ) potential models are investigated to study the impact of the choice of potential models in the description of adsorption behavior. We chose two 2C-LJ potential models in our investigation of the (i) UA-TraPPE-LJ model of Martin and Siepmann for ethane and Wick et al. for ethylene and (ii) AUA4-LJ model of Ungerer et al. for ethane and Bourasseau et al. for ethylene. These models are used to study the adsorption of ethane and ethylene on graphitized thermal carbon black. It is found that the solid-fluid binary interaction parameter is a function of adsorbate and temperature, and the adsorption isotherms and heat of adsorption are well described by both the UA-TraPPE and AUA models, although the UA-TraPPE model performs slightly better. However, the local distributions predicted by these two models are slightly different. These two models are used to explore the two-dimensional condensation for the graphitized thermal carbon black, and these values are 110 K for ethylene and 120 K for ethane.
2-D to 3-D global/local finite element analysis of cross-ply composite laminates
NASA Technical Reports Server (NTRS)
Thompson, D. Muheim; Griffin, O. Hayden, Jr.
1990-01-01
An example of two-dimensional to three-dimensional global/local finite element analysis of a laminated composite plate with a hole is presented. The 'zoom' technique of global/local analysis is used, where displacements of the global/local interface from the two-dimensional global model are applied to the edges of the three-dimensional local model. Three different hole diameters, one, three, and six inches, are considered in order to compare the effect of hole size on the three-dimensional stress state around the hole. In addition, three different stacking sequences are analyzed for the six inch hole case in order to study the effect of stacking sequence. The existence of a 'critical' hole size, where the interlaminar stresses are maximum, is indicated. Dispersion of plies at the same angle, as opposed to clustering, is found to reduce the magnitude of some interlaminar stress components and increase others.
NASA Astrophysics Data System (ADS)
Hosseinzadeh-Nik, Zahra; Regele, Jonathan D.
2015-11-01
Dense compressible particle-laden flow, which has a complex nature, exists in various engineering applications. Shock waves impacting a particle cloud is a canonical problem to investigate this type of flow. It has been demonstrated that large flow unsteadiness is generated inside the particle cloud from the flow induced by the shock passage. It is desirable to develop models for the Reynolds stress to capture the energy contained in vortical structures so that volume-averaged models with point particles can be simulated accurately. However, the previous work used Euler equations, which makes the prediction of vorticity generation and propagation innacurate. In this work, a fully resolved two dimensional (2D) simulation using the compressible Navier-Stokes equations with a volume penalization method to model the particles has been performed with the parallel adaptive wavelet-collocation method. The results still show large unsteadiness inside and downstream of the particle cloud. A 1D model is created for the unclosed terms based upon these 2D results. The 1D model uses a two-phase simple low dissipation AUSM scheme (TSLAU) developed by coupled with the compressible two phase kinetic energy equation.
2d affine XY-spin model/4d gauge theory duality and deconfinement
NASA Astrophysics Data System (ADS)
Anber, Mohamed M.; Poppitz, Erich; Ünsal, Mithat
2012-04-01
We introduce a duality between two-dimensional XY-spin models with symmetry-breaking perturbations and certain four-dimensional SU(2) and SU(2)/ {{Z}_2} gauge theories, compactified on a small spatial circle {{R}^{{^{{{1},{2}}}}}} × {{S}^{{^{{1}}}}} , and considered at temperatures near the deconfinement transition. In a Euclidean set up, the theory is defined on {{R}^{{^{{2}}}}} × {{T}^{{^{{2}}}}} . Similarly, thermal gauge theories of higher rank are dual to new families of "affine" XY-spin models with perturbations. For rank two, these are related to models used to describe the melting of a 2d crystal with a triangular lattice. The connection is made through a multi-component electric-magnetic Coulomb gas representation for both systems. Perturbations in the spin system map to topological defects in the gauge theory, such as monopole-instantons or magnetic bions, and the vortices in the spin system map to the electrically charged W-bosons in field theory (or vice versa, depending on the duality frame). The duality permits one to use the two-dimensional technology of spin systems to study the thermal deconfinement and discrete chiral transitions in four-dimensional SU( N c ) gauge theories with n f ≥1 adjoint Weyl fermions.
NASA Technical Reports Server (NTRS)
Pan, Jianqiang
1992-01-01
Several important problems in the fields of signal processing and model identification, such as system structure identification, frequency response determination, high order model reduction, high resolution frequency analysis, deconvolution filtering, and etc. Each of these topics involves a wide range of applications and has received considerable attention. Using the Fourier based sinusoidal modulating signals, it is shown that a discrete autoregressive model can be constructed for the least squares identification of continuous systems. Some identification algorithms are presented for both SISO and MIMO systems frequency response determination using only transient data. Also, several new schemes for model reduction were developed. Based upon the complex sinusoidal modulating signals, a parametric least squares algorithm for high resolution frequency estimation is proposed. Numerical examples show that the proposed algorithm gives better performance than the usual. Also, the problem was studied of deconvolution and parameter identification of a general noncausal nonminimum phase ARMA system driven by non-Gaussian stationary random processes. Algorithms are introduced for inverse cumulant estimation, both in the frequency domain via the FFT algorithms and in the domain via the least squares algorithm.
Finite state modeling of aeroelastic systems
NASA Technical Reports Server (NTRS)
Vepa, R.
1977-01-01
A general theory of finite state modeling of aerodynamic loads on thin airfoils and lifting surfaces performing completely arbitrary, small, time-dependent motions in an airstream is developed and presented. The nature of the behavior of the unsteady airloads in the frequency domain is explained, using as raw materials any of the unsteady linearized theories that have been mechanized for simple harmonic oscillations. Each desired aerodynamic transfer function is approximated by means of an appropriate Pade approximant, that is, a rational function of finite degree polynomials in the Laplace transform variable. The modeling technique is applied to several two dimensional and three dimensional airfoils. Circular, elliptic, rectangular and tapered planforms are considered as examples. Identical functions are also obtained for control surfaces for two and three dimensional airfoils.
Structure of turbulence in three-dimensional boundary layers
NASA Technical Reports Server (NTRS)
Subramanian, Chelakara S.
1993-01-01
This report provides an overview of the three dimensional turbulent boundary layer concepts and of the currently available experimental information for their turbulence modeling. It is found that more reliable turbulence data, especially of the Reynolds stress transport terms, is needed to improve the existing modeling capabilities. An experiment is proposed to study the three dimensional boundary layer formed by a 'sink flow' in a fully developed two dimensional turbulent boundary layer. Also, the mean and turbulence field measurement procedure using a three component laser Doppler velocimeter is described.
1983-05-09
Ap-PDP, 2; UCD, 1. Santa Cruz de Tenerife. Voters: 438,618. Seats: 30 (Tenerife, 15; La Palma, 8; Gomera, 4 and Hierro , 3). Deputies 28 October 1982...Canaries, have aroused the interest of independent groups that normally operate on the peripheral islands, such as Gomera and Hierro . 113 During the...Independent Gomera Electoral Group: Esteban Bethencourt. Hierro : PSOE: Jose Francisco Armas. AP-PDP-UL: Manuel Fernandez Gonzalez. PCE: Aurelio Ayala
Ecology of the Scorpion, Microtityus jaumei in Sierra de Canasta, Cuba
Cala-Riquelme, Franklyn; Colombo, Marco
2011-01-01
An assessment of the population dynamics of Microtityus jaumei Armas (Scorpiones: Buthidae) on the slopes south of Sierra de Canasta, Guantánamo Province, Cuba show an increase in activity over the year (≤ 0.05). The activity peak is related to the reproductive period from June to November. The abundance of scorpions was significantly related to density of the canopy and thickness of the substrate. PMID:21870972
Ecology of the scorpion, Microtityus jaumei in Sierra de Canasta, Cuba.
Cala-Riquelme, Franklyn; Colombo, Marco
2011-01-01
An assessment of the population dynamics of Microtityus jaumei Armas (Scorpiones: Buthidae) on the slopes south of Sierra de Canasta, Guantánamo Province, Cuba show an increase in activity over the year (≤ 0.05). The activity peak is related to the reproductive period from June to November. The abundance of scorpions was significantly related to density of the canopy and thickness of the substrate.
Three-dimensional head anthropometric analysis
NASA Astrophysics Data System (ADS)
Enciso, Reyes; Shaw, Alex M.; Neumann, Ulrich; Mah, James
2003-05-01
Currently, two-dimensional photographs are most commonly used to facilitate visualization, assessment and treatment of facial abnormalities in craniofacial care but are subject to errors because of perspective, projection, lack metric and 3-dimensional information. One can find in the literature a variety of methods to generate 3-dimensional facial images such as laser scans, stereo-photogrammetry, infrared imaging and even CT however each of these methods contain inherent limitations and as such no systems are in common clinical use. In this paper we will focus on development of indirect 3-dimensional landmark location and measurement of facial soft-tissue with light-based techniques. In this paper we will statistically evaluate and validate a current three-dimensional image-based face modeling technique using a plaster head model. We will also develop computer graphics tools for indirect anthropometric measurements in a three-dimensional head model (or polygonal mesh) including linear distances currently used in anthropometry. The measurements will be tested against a validated 3-dimensional digitizer (MicroScribe 3DX).
Laser one-dimensional range profile and the laser two-dimensional range profile of cylinders
NASA Astrophysics Data System (ADS)
Gong, Yanjun; Wang, Mingjun; Gong, Lei
2015-10-01
Laser one-dimensional range profile, that is scattering power from pulse laser scattering of target, is a radar imaging technology. The laser two-dimensional range profile is two-dimensional scattering imaging of pulse laser of target. Laser one-dimensional range profile and laser two-dimensional range profile are called laser range profile(LRP). The laser range profile can reflect the characteristics of the target shape and surface material. These techniques were motivated by applications of laser radar to target discrimination in ballistic missile defense. The radar equation of pulse laser is given in this paper. This paper demonstrates the analytical model of laser range profile of cylinder based on the radar equation of the pulse laser. Simulations results of laser one-dimensional range profiles of some cylinders are given. Laser range profiles of cylinder, whose surface material with diffuse lambertian reflectance, is given in this paper. Laser range profiles of different pulse width of cylinder are given in this paper. The influences of geometric parameters, pulse width, attitude on the range profiles are analyzed.
Kontis, Angelo L.
1999-01-01
The seaward limit of the fresh ground-water system underlying Kings and Queens Counties on Long Island, N.Y., is at the freshwater-saltwater transition zone. This zone has been conceptualized in transient-state, three-dimensional models of the aquifer system as a sharp interface between freshwater and saltwater, and represented as a stationary, zero lateral-flow boundary. In this study, a pair of two-dimensional, four-layer ground-water flow models representing a generalized vertical section in Kings County and one in adjacent Queens County were developed to evaluate the validity of the boundary condition used in three-dimensional models of the aquifer system. The two-dimensional simulations used a model code that can simulate the movement of a sharp interface in response to transient stress. Sensitivity of interface movement to four factors was analyzed; these were (1) the method of simulating vertical leakage between freshwater and saltwater; (2) recharge at the normal rate, at 50-percent of the normal rate, and at zero for a prolonged (3-year) period; (3) high, medium, and low pumping rates; and (4) pumping from a hypothetical cluster of wells at two locations. Results indicate that the response of the interfaces to the magnitude and duration of pumping and the location of the hypothetical wells is probably sufficiently slow that the interfaces in three-dimensional models can reasonably be approximated as stationary, zero-lateral- flow boundaries.
Flow through three-dimensional arrangements of cylinders with alternating streamwise planar tilt
NASA Astrophysics Data System (ADS)
Sahraoui, M.; Marshall, H.; Kaviany, M.
1993-09-01
In this report, fluid flow through a three-dimensional model for the fibrous filters is examined. In this model, the three-dimensional Stokes equation with the appropriate periodic boundary conditions is solved using the finite volume method. In addition to the numerical solution, we attempt to model this flow analytically by using the two-dimensional extended analytic solution in each of the unit cells of the three-dimensional structure. Particle trajectories computed using the superimposed analytic solution of the flow field are closed to those computed using the numerical solution of the flow field. The numerical results show that the pressure drop is not affected significantly by the relative angle of rotation of the cylinders for the high porosity used in this study (epsilon = 0.8 and epsilon = 0.95). The numerical solution and the superimposed analytic solution are also compared in terms of the particle capture efficiency. The results show that the efficiency predictions using the two methods are within 10% for St = 0.01 and 5% for St = 100. As the the porosity decreases, the three-dimensional effect becomes more significant and a difference of 35% is obtained for epsilon = 0.8.
Source Term Model for Steady Micro Jets in a Navier-Stokes Computer Code
NASA Technical Reports Server (NTRS)
Waithe, Kenrick A.
2005-01-01
A source term model for steady micro jets was implemented into a non-proprietary Navier-Stokes computer code, OVERFLOW. The source term models the mass flow and momentum created by a steady blowing micro jet. The model is obtained by adding the momentum and mass flow created by the jet to the Navier-Stokes equations. The model was tested by comparing with data from numerical simulations of a single, steady micro jet on a flat plate in two and three dimensions. The source term model predicted the velocity distribution well compared to the two-dimensional plate using a steady mass flow boundary condition, which was used to simulate a steady micro jet. The model was also compared to two three-dimensional flat plate cases using a steady mass flow boundary condition to simulate a steady micro jet. The three-dimensional comparison included a case with a grid generated to capture the circular shape of the jet and a case without a grid generated for the micro jet. The case without the jet grid mimics the application of the source term. The source term model compared well with both of the three-dimensional cases. Comparisons of velocity distribution were made before and after the jet and Mach and vorticity contours were examined. The source term model allows a researcher to quickly investigate different locations of individual or several steady micro jets. The researcher is able to conduct a preliminary investigation with minimal grid generation and computational time.
NASA Astrophysics Data System (ADS)
Dănilă, B.; Harko, T.; Mocanu, G.
2015-11-01
We investigate the transition to self-organized criticality in a two-dimensional model of a flux tube with a background flow. The magnetic induction equation, represented by a partial differential equation with a stochastic source term, is discretized and implemented on a two-dimensional cellular automaton. The energy released by the automaton during one relaxation event is the magnetic energy. As a result of the simulations, we obtain the time evolution of the energy release, of the system control parameter, of the event lifetime distribution and of the event size distribution, respectively, and we establish that a self-organized critical state is indeed reached by the system. Moreover, energetic initial impulses in the magnetohydrodynamic flow can lead to one-dimensional signatures in the magnetic two-dimensional system, once the self-organized critical regime is established. The applications of the model for the study of gamma-ray bursts (GRBs) is briefly considered, and it is shown that some astrophysical parameters of the bursts, like the light curves, the maximum released energy and the number of peaks in the light curve can be reproduced and explained, at least on a qualitative level, by working in a framework in which the systems settles in a self-organized critical state via magnetic reconnection processes in the magnetized GRB fireball.
Generation Algorithm of Discrete Line in Multi-Dimensional Grids
NASA Astrophysics Data System (ADS)
Du, L.; Ben, J.; Li, Y.; Wang, R.
2017-09-01
Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.
Glimm, Tilmann; Zhang, Jianying; Shen, Yun-Qiu; Newman, Stuart A
2012-03-01
We investigate a reaction-diffusion system consisting of an activator and an inhibitor in a two-dimensional domain. There is a morphogen gradient in the domain. The production of the activator depends on the concentration of the morphogen. Mathematically, this leads to reaction-diffusion equations with explicitly space-dependent terms. It is well known that in the absence of an external morphogen, the system can produce either spots or stripes via the Turing bifurcation. We derive first-order expansions for the possible patterns in the presence of an external morphogen and show how both stripes and spots are affected. This work generalizes previous one-dimensional results to two dimensions. Specifically, we consider the quasi-one-dimensional case of a thin rectangular domain and the case of a square domain. We apply the results to a model of skeletal pattern formation in vertebrate limbs. In the framework of reaction-diffusion models, our results suggest a simple explanation for some recent experimental findings in the mouse limb which are much harder to explain in positional-information-type models.
Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.
Xiong, Chunbao; Lu, Huali; Zhu, Jinsong
2017-02-23
Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.
Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements
Xiong, Chunbao; Lu, Huali; Zhu, Jinsong
2017-01-01
Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472
Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data
Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian
2015-01-01
In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213
Modeling the effect of mood on dimensional attention during categorization.
Zivot, Matthew T; Cohen, Andrew L; Kapucu, Aycan
2013-08-01
Classification is a flexible process that can be affected by mood. The goal of this paper is to evaluate the idea that mood may modulate categorization behavior through an attentional weighting mechanism in which mood changes the attention afforded to different stimulus dimensions. In two experiments, participants learn and are tested on categories while in a calm or sad mood. In Experiment 1, sad participants are faster to learn one- and two-dimensional category structures, but show no advantage on a three-dimensional category structure. In Experiment 2, the generalized context model of categorization is used to measure dimensional weighting. The results suggest that sad participants have a narrower focus of attention, but that the narrowing tends to be on diagnostic dimensions. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Jacobs, Carly A; Lin, Alexander Y
2017-05-01
Three-dimensional printing technology has been advancing in surgical applications. This systematic review examines its patient-specific applications in craniomaxillofacial surgery. Terms related to "three-dimensional printing" and "surgery" were searched on PubMed on May 4, 2015; 313 unique articles were returned. Inclusion and exclusion criteria concentrated on patient-specific surgical applications, yielding 141 full-text articles, of which 33 craniomaxillofacial articles were analyzed. Thirty-three articles included 315 patients who underwent three-dimensional printing-assisted operations. The most common modeling software was Mimics, the most common printing software was 3D Systems, the average time to create a printed object was 18.9 hours (range, 1.5 to 96 hours), and the average cost of a printed object was $1353.31 (range, $69.75 to $5500). Surgical procedures were divided among 203 craniofacial patients (205 three-dimensional printing objects) and 112 maxillofacial patients (137 objects). Printing technologies could be classified as contour models, guides, splints, and implants. For craniofacial patients, 173 contour models (84 percent), 13 guides (6 percent), two splints (1 percent), and 17 implants (8 percent) were made. For maxillofacial patients, 41 contour models (30 percent), 48 guides (35 percent), 40 splints (29 percent), and eight implants (6 percent) were made. These distributions were significantly different (p < 0.0001). Four studies compared three-dimensional printing techniques to conventional techniques; two of them found that three-dimensional printing produced improved outcomes. Three-dimensional printing technology in craniomaxillofacial surgery can be classified into contour models (type I), guides (type II), splints (type III), and implants (type IV). These four methods vary in their use between craniofacial and maxillofacial surgery, reflecting their different goals. This understanding may help advance and predict three-dimensional printing applications for other types of plastic surgery and beyond.
NASA Technical Reports Server (NTRS)
Bathel, Brett F.; Danehy, Paul M.; Johansen, Craig T.; Ashcraft, Scott W.; Novak, Luke A.
2013-01-01
Numerical predictions of the Mars Science Laboratory reaction control system jets interacting with a Mach 10 hypersonic flow are compared to experimental nitric oxide planar laser-induced fluorescence data. The steady Reynolds Averaged Navier Stokes equations using the Baldwin-Barth one-equation turbulence model were solved using the OVERFLOW code. The experimental fluorescence data used for comparison consists of qualitative two-dimensional visualization images, qualitative reconstructed three-dimensional flow structures, and quantitative two-dimensional distributions of streamwise velocity. Through modeling of the fluorescence signal equation, computational flow images were produced and directly compared to the qualitative fluorescence data.
Stereo imaging with spaceborne radars
NASA Technical Reports Server (NTRS)
Leberl, F.; Kobrick, M.
1983-01-01
Stereo viewing is a valuable tool in photointerpretation and is used for the quantitative reconstruction of the three dimensional shape of a topographical surface. Stereo viewing refers to a visual perception of space by presenting an overlapping image pair to an observer so that a three dimensional model is formed in the brain. Some of the observer's function is performed by machine correlation of the overlapping images - so called automated stereo correlation. The direct perception of space with two eyes is often called natural binocular vision; techniques of generating three dimensional models of the surface from two sets of monocular image measurements is the topic of stereology.
NASA Technical Reports Server (NTRS)
Hunter, Craig A.
1995-01-01
An analytical/numerical method has been developed to predict the static thrust performance of non-axisymmetric, two-dimensional convergent-divergent exhaust nozzles. Thermodynamic nozzle performance effects due to over- and underexpansion are modeled using one-dimensional compressible flow theory. Boundary layer development and skin friction losses are calculated using an approximate integral momentum method based on the classic karman-Polhausen solution. Angularity effects are included with these two models in a computational Nozzle Performance Analysis Code, NPAC. In four different case studies, results from NPAC are compared to experimental data obtained from subscale nozzle testing to demonstrate the capabilities and limitations of the NPAC method. In several cases, the NPAC prediction matched experimental gross thrust efficiency data to within 0.1 percent at a design NPR, and to within 0.5 percent at off-design conditions.
Two-dimensional analytical modeling of a linear variable filter for spectral order sorting.
Ko, Cheng-Hao; Wu, Yueh-Hsun; Tsai, Jih-Run; Wang, Bang-Ji; Chakraborty, Symphony
2016-06-10
A two-dimensional thin film thickness model based on the geometry of a commercial coater which can calculate more effectively the profiles of linear variable filters (LVFs) has been developed. This is done by isolating the substrate plane as an independent coordinate (local coordinate), while the rotation and translation matrices are used to establish the coordinate transformation and combine the characteristic vector with the step function to build a borderline which can conclude whether the local mask will block the deposition or not. The height of the local mask has been increased up to 40 mm in the proposed model, and two-dimensional simulations are developed to obtain a thin film profile deposition on the substrate inside the evaporation chamber to achieve the specific request of producing a LVF zone width in a more economical way than previously reported [Opt. Express23, 5102 (2015)OPEXFF1094-408710.1364/OE.23.005102].
Two-Dimensional Mathematical Modeling of the Pack Carburizing Process
NASA Astrophysics Data System (ADS)
Sarkar, S.; Gupta, G. S.
2008-10-01
Pack carburization is the oldest method among the case-hardening treatments, and sufficient attempts have not been made to understand this process in terms of heat and mass transfer, effect of alloying elements, dimensions of the sample, etc. Thus, a two-dimensional mathematical model in cylindrical coordinate is developed for simulating the pack carburization process for chromium-bearing steel in this study. Heat and mass balance equations are solved simultaneously, where the surface temperature of the sample varies with time, but the carbon potential at the surface during the process remains constant. The fully implicit finite volume technique is used to solve the governing equations. Good agreement has been found between the predicted and published data. The effect of temperature, carburizing time, dimensions of the sample, etc. on the pack carburizing process shows some interesting results. It is found that the two-dimensional model gives better insight into understanding the carburizing process.
Diagnostic analysis of two-dimensional monthly average ozone balance with Chapman chemistry
NASA Technical Reports Server (NTRS)
Stolarski, Richard S.; Jackman, Charles H.; Kaye, Jack A.
1986-01-01
Chapman chemistry has been used in a two-dimensional model to simulate ozone balance phenomenology. The similarity between regions of ozone production and loss calculated using Chapman chemistry and those computed using LIMS and SAMS data with a photochemical equilibrium model indicate that such simplified chemistry is useful in studying gross features in stratospheric ozone balance. Net ozone production or loss rates are brought about by departures from the photochemical equilibrium (PCE) condition. If transport drives ozone above its PCE condition, then photochemical loss dominates production. If transport drives ozone below its PCE condition, then photochemical production dominates loss. Gross features of ozone loss/production (L/P) inferred for the real atmosphere from data are also simulated using only eddy diffusion. This indicates that one must be careful in assigning a transport scheme for a two-dimensional model that mimics only behavior of the observed ozone L/P.
Excitation basis for (3+1)d topological phases
NASA Astrophysics Data System (ADS)
Delcamp, Clement
2017-12-01
We consider an exactly solvable model in 3+1 dimensions, based on a finite group, which is a natural generalization of Kitaev's quantum double model. The corresponding lattice Hamiltonian yields excitations located at torus-boundaries. By cutting open the three-torus, we obtain a manifold bounded by two tori which supports states satisfying a higher-dimensional version of Ocneanu's tube algebra. This defines an algebraic structure extending the Drinfel'd double. Its irreducible representations, labeled by two fluxes and one charge, characterize the torus-excitations. The tensor product of such representations is introduced in order to construct a basis for (3+1)d gauge models which relies upon the fusion of the defect excitations. This basis is defined on manifolds of the form Σ × S_1 , with Σ a two-dimensional Riemann surface. As such, our construction is closely related to dimensional reduction from (3+1)d to (2+1)d topological orders.
Towards a voxel-based geographic automata for the simulation of geospatial processes
NASA Astrophysics Data System (ADS)
Jjumba, Anthony; Dragićević, Suzana
2016-07-01
Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.