Jyoti Rao

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. Jyoti Rao. Articles written in Resonance – Journal of Science Education. Volume 22 Issue 9 September 2017 pp 829-833 General Article. Nobel Prize in Physiology or Medicine 2016 · Shekhar C Mande Jyoti Rao · More Details Abstract Fulltext PDF. The Nobel ...

Box-particle intensity filter

OpenAIRE

Schikora, Marek; Gning, Amadou; Mihaylova, Lyudmila; Cremers, Daniel; Koch, Wofgang; Streit, Roy

2012-01-01

This paper develops a novel approach for multi-target tracking, called box-particle intensity filter (box-iFilter). The approach is able to cope with unknown clutter, false alarms and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. The box-iFilter reduces the number of particles significantly, which improves the runtime considerably. The low particle number enables thi...

R Vittal Rao

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. R Vittal Rao. Articles written in Resonance – Journal of Science Education. Volume 1 Issue 12 December 1996 pp 78-80 Book Review. A Mathematician's Apology Mathematics and Creativity · R Vittal Rao · More Details Fulltext PDF ...

J Raghava Rao

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education. J Raghava Rao. Articles written in Resonance – Journal of Science Education. Volume 19 Issue 10 October 2014 pp 887-899 General Article. Yelavarthy Nayudamma: Scientist, Leader, and Mentor Extraordinary · J Raghava Rao T Ramasami · More Details ...

K J Rao

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. K J Rao. Articles written in Bulletin of Materials Science. Volume 23 Issue 6 December 2000 pp 461-466 Material Synthesis. Microwave synthesis of electrode materials for lithium batteries · M Harish Bhat B P Chakravarthy P A Ramakrishnan A Levasseur K J RAO.

K Narasimha Rao

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science. K Narasimha Rao. Articles written in Bulletin of Materials Science. Volume 26 Issue 2 February 2003 pp 239-245 Thin Films. Studies on thin film materials on acrylics for optical applications · K Narasimha Rao · More Details Abstract Fulltext PDF. Deposition of durable thin film ...

Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters*

KAUST Repository

Hoteit, Ibrahim

2012-02-01

This paper investigates an approximation scheme of the optimal nonlinear Bayesian filter based on the Gaussian mixture representation of the state probability distribution function. The resulting filter is similar to the particle filter, but is different from it in that the standard weight-type correction in the particle filter is complemented by the Kalman-type correction with the associated covariance matrices in the Gaussian mixture. The authors show that this filter is an algorithm in between the Kalman filter and the particle filter, and therefore is referred to as the particle Kalman filter (PKF). In the PKF, the solution of a nonlinear filtering problem is expressed as the weighted average of an “ensemble of Kalman filters” operating in parallel. Running an ensemble of Kalman filters is, however, computationally prohibitive for realistic atmospheric and oceanic data assimilation problems. For this reason, the authors consider the construction of the PKF through an “ensemble” of ensemble Kalman filters (EnKFs) instead, and call the implementation the particle EnKF (PEnKF). It is shown that different types of the EnKFs can be considered as special cases of the PEnKF. Similar to the situation in the particle filter, the authors also introduce a resampling step to the PEnKF in order to reduce the risk of weights collapse and improve the performance of the filter. Numerical experiments with the strongly nonlinear Lorenz-96 model are presented and discussed.

Are consistent equal-weight particle filters possible?

Science.gov (United States)

van Leeuwen, P. J.

2017-12-01

Particle filters are fully nonlinear data-assimilation methods that could potentially change the way we do data-assimilation in highly nonlinear high-dimensional geophysical systems. However, the standard particle filter in which the observations come in by changing the relative weights of the particles is degenerate. This means that one particle obtains weight one, and all other particles obtain a very small weight, effectively meaning that the ensemble of particles reduces to that one particle. For over 10 years now scientists have searched for solutions to this problem. One obvious solution seems to be localisation, in which each part of the state only sees a limited number of observations. However, for a realistic localisation radius based on physical arguments, the number of observations is typically too large, and the filter is still degenerate. Another route taken is trying to find proposal densities that lead to more similar particle weights. There is a simple proof, however, that shows that there is an optimum, the so-called optimal proposal density, and that optimum will lead to a degenerate filter. On the other hand, it is easy to come up with a counter example of a particle filter that is not degenerate in high-dimensional systems. Furthermore, several particle filters have been developed recently that claim to have equal or equivalent weights. In this presentation I will show how to construct a particle filter that is never degenerate in high-dimensional systems, and how that is still consistent with the proof that one cannot do better than the optimal proposal density. Furthermore, it will be shown how equal- and equivalent-weights particle filters fit within this framework. This insight will then lead to new ways to generate particle filters that are non-degenerate, opening up the field of nonlinear filtering in high-dimensional systems.

Efficient particle filtering through residual nudging

KAUST Repository

Luo, Xiaodong

2013-05-15

We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases where it performs poorly. The main idea of residual nudging is to monitor and, if necessary, adjust the residual norm of a state estimate in the observation space so that it does not exceed a pre-specified threshold. We suggest a rule to choose the pre-specified threshold, and construct a state estimate accordingly to achieve this objective. Numerical experiments suggest that introducing residual nudging to a particle filter may (substantially) improve its performance, in terms of filter accuracy and/or stability against divergence, especially when the particle filter is implemented with a relatively small number of particles. © 2013 Royal Meteorological Society.

P R Vasudeva Rao

Indian Academy of Sciences (India)

Home; Journals; Sadhana. P R Vasudeva Rao. Articles written in Sadhana. Volume 27 Issue 5 October 2002 pp 527-558. Development of fuels and structural materials for fast breeder reactors · Baldev Raj S L Mannan P R Vasudeva Rao M D Mathew · More Details Abstract Fulltext PDF. Fast breeder reactors (FBRs) are ...

Introduction to the Box Particle Filtering

OpenAIRE

Gning, Amadou; Ristic, B; Mihaylova, Lyudmila; Abdallah, F.

2013-01-01

This paper presents a novel method for solving nonlinear filtering problems. This approach is particularly appealing in practical situations involving imprecise stochastic measurements, thus resulting in very broad posterior densities. It relies on the concept of a box particle, which occupies a small and controllable rectangular region having a non-zero volume in the state space. Key advantages of the box particle filter (Box-PF) against the standard particle filter (PF) are in its reduced c...

Filtering in Hybrid Dynamic Bayesian Networks

Science.gov (United States)

Andersen, Morten Nonboe; Andersen, Rasmus Orum; Wheeler, Kevin

2000-01-01

We implement a 2-time slice dynamic Bayesian network (2T-DBN) framework and make a 1-D state estimation simulation, an extension of the experiment in (v.d. Merwe et al., 2000) and compare different filtering techniques. Furthermore, we demonstrate experimentally that inference in a complex hybrid DBN is possible by simulating fault detection in a watertank system, an extension of the experiment in (Koller & Lerner, 2000) using a hybrid 2T-DBN. In both experiments, we perform approximate inference using standard filtering techniques, Monte Carlo methods and combinations of these. In the watertank simulation, we also demonstrate the use of 'non-strict' Rao-Blackwellisation. We show that the unscented Kalman filter (UKF) and UKF in a particle filtering framework outperform the generic particle filter, the extended Kalman filter (EKF) and EKF in a particle filtering framework with respect to accuracy in terms of estimation RMSE and sensitivity with respect to choice of network structure. Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. Furthermore, we investigate the influence of data noise in the watertank simulation using UKF and PFUKD and show that the algorithms are more sensitive to changes in the measurement noise level that the process noise level. Theory and implementation is based on (v.d. Merwe et al., 2000).

Bayesian target tracking based on particle filter

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

Passive target tracking using marginalized particle filter

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

A marginalized particle filtering(MPF)approach is proposed for target tracking under the background of passive measurement.Essentially,the MPF is a combination of particle filtering technique and Kalman filter.By making full use of marginalization,the distributions of the tractable linear part of the total state variables are updated analytically using Kalman filter,and only the lower-dimensional nonlinear state variable needs to be dealt with using particle filter.Simulation studies are performed on an illustrative example,and the results show that the MPF method leads to a significant reduction of the tracking errors when compared with the direct particle implementation.Real data test results also validate the effectiveness of the presented method.

Optimization-based particle filter for state and parameter estimation

Institute of Scientific and Technical Information of China (English)

Li Fu; Qi Fei; Shi Guangming; Zhang Li

2009-01-01

In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

Penetration of Combustion Aerosol Particles Through Filters of NIOSH-Certified Filtering Facepiece Respirators (FFRs).

Science.gov (United States)

Gao, Shuang; Kim, Jinyong; Yermakov, Michael; Elmashae, Yousef; He, Xinjian; Reponen, Tiina; Grinshpun, Sergey A

2015-01-01

Filtering facepiece respirators (FFRs) are commonly worn by first responders, first receivers, and other exposed groups to protect against exposure to airborne particles, including those originated by combustion. Most of these FFRs are NIOSH-certified (e.g., N95-type) based on the performance testing of their filters against charge-equilibrated aerosol challenges, e.g., NaCl. However, it has not been examined if the filtration data obtained with the NaCl-challenged FFR filters adequately represent the protection against real aerosol hazards such as combustion particles. A filter sample of N95 FFR mounted on a specially designed holder was challenged with NaCl particles and three combustion aerosols generated in a test chamber by burning wood, paper, and plastic. The concentrations upstream (Cup) and downstream (Cdown) of the filter were measured with a TSI P-Trak condensation particle counter and a Grimm Nanocheck particle spectrometer. Penetration was determined as (Cdown/Cup) ×100%. Four test conditions were chosen to represent inhalation flows of 15, 30, 55, and 85 L/min. Results showed that the penetration values of combustion particles were significantly higher than those of the "model" NaCl particles (p combustion particles. Aerosol type, inhalation flow rate and particle size were significant (p combustion particles through R95 and P95 FFR filters (were tested in addition to N95) were not significantly higher than that obtained with NaCl particles. The findings were attributed to several effects, including the degradation of an N95 filter due to hydrophobic organic components generated into the air by combustion. Their interaction with fibers is anticipated to be similar to those involving "oily" particles. The findings of this study suggest that the efficiency of N95 respirator filters obtained with the NaCl aerosol challenge may not accurately predict (and rather overestimate) the filter efficiency against combustion particles.

Particle Filtering Methods for Incorporating Intelligence Updates

Science.gov (United States)

2017-03-01

past time steps. 3.2.1 Particle Filtering through Bayesian Bootstrap Sampling Although SIS helps resolve the computational and complexity issues...variables. This insight was called the Bayesian bootstrap filter, or more commonly called the particle filter. Multiple particles are sampled from an...2012) 16 maps of drug flow into the United States. Business Insider Online, (July 8), http://www.businessinsider.com/16-maps-of-drug-flow-into-the

Particle filters for random set models

CERN Document Server

Ristic, Branko

2013-01-01

“Particle Filters for Random Set Models” presents coverage of state estimation of stochastic dynamic systems from noisy measurements, specifically sequential Bayesian estimation and nonlinear or stochastic filtering. The class of solutions presented in this book is based  on the Monte Carlo statistical method. The resulting  algorithms, known as particle filters, in the last decade have become one of the essential tools for stochastic filtering, with applications ranging from  navigation and autonomous vehicles to bio-informatics and finance. While particle filters have been around for more than a decade, the recent theoretical developments of sequential Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book. These recent developments have dramatically widened the scope of applications, from single to multiple appearing/disappearing objects, from precise to imprecise measurements and measurement models. This book...

Mixed labelling in multitarget particle filtering

NARCIS (Netherlands)

Boers, Y.; Sviestins, Egils; Driessen, Hans

2010-01-01

The so-called mixed labelling problem inherent to a joint state multitarget particle filter implementation is treated. The mixed labelling problem would be prohibitive for track extraction from a joint state multitarget particle filter. It is shown, using the theory of Markov chains, that the mixed

Box-particle probability hypothesis density filtering

OpenAIRE

Schikora, M.; Gning, A.; Mihaylova, L.; Cremers, D.; Koch, W.

2014-01-01

This paper develops a novel approach for multitarget tracking, called box-particle probability hypothesis density filter (box-PHD filter). The approach is able to track multiple targets and estimates the unknown number of targets. Furthermore, it is capable of dealing with three sources of uncertainty: stochastic, set-theoretic, and data association uncertainty. The box-PHD filter reduces the number of particles significantly, which improves the runtime considerably. The small number of box-p...

Deposition of Aerosol Particles in Electrically Charged Membrane Filters

Energy Technology Data Exchange (ETDEWEB)

Stroem, L

1972-05-15

A theory for the influence of electric charge on particle deposition on the surface of charged filters has been developed. It has been tested experimentally on ordinary membrane filters and Nuclepore filters of 8 mum pore size, with a bipolar monodisperse test aerosol of 1 mum particle diameter, and at a filter charge up to 20 muC/m2. Agreement with theory was obtained for the Coulomb force between filter and particle for both kinds of filters. The image force between charged filter and neutral particles did not result in the predicted deposition in the ordinary membrane filter, probably due to lacking correspondence between the filter model employed for the theory, and the real filter. For the Nuclepore filter a satisfactory agreement with theory was obtained, also at image interaction

V S C Manga Rao

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics. V S C Manga Rao. Articles written in Pramana – Journal of Physics. Volume 61 Issue 3 September 2003 pp 563-575 Research Articles. Phase conjugation of gap solitons: A numerical study · V S C Manga Rao S Dutta Gupta · More Details Abstract Fulltext PDF. We study the ...

Distributed SLAM Using Improved Particle Filter for Mobile Robot Localization

Directory of Open Access Journals (Sweden)

Fujun Pei

2014-01-01

Full Text Available The distributed SLAM system has a similar estimation performance and requires only one-fifth of the computation time compared with centralized particle filter. However, particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involves a large number of dimensions. In this paper, particle filter use in distributed SLAM was improved in two aspects. First, we improved the important function of the local filters in particle filter. The adaptive values were used to replace a set of constants in the computational process of importance function, which improved the robustness of the particle filter. Second, an information fusion method was proposed by mixing the innovation method and the number of effective particles method, which combined the advantages of these two methods. And this paper extends the previously known convergence results for particle filter to prove that improved particle filter converges to the optimal filter in mean square as the number of particles goes to infinity. The experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system to have a better tolerance and robustness.

Robust estimation of event-related potentials via particle filter.

Science.gov (United States)

Fukami, Tadanori; Watanabe, Jun; Ishikawa, Fumito

2016-03-01

In clinical examinations and brain-computer interface (BCI) research, a short electroencephalogram (EEG) measurement time is ideal. The use of event-related potentials (ERPs) relies on both estimation accuracy and processing time. We tested a particle filter that uses a large number of particles to construct a probability distribution. We constructed a simple model for recording EEG comprising three components: ERPs approximated via a trend model, background waves constructed via an autoregressive model, and noise. We evaluated the performance of the particle filter based on mean squared error (MSE), P300 peak amplitude, and latency. We then compared our filter with the Kalman filter and a conventional simple averaging method. To confirm the efficacy of the filter, we used it to estimate ERP elicited by a P300 BCI speller. A 400-particle filter produced the best MSE. We found that the merit of the filter increased when the original waveform already had a low signal-to-noise ratio (SNR) (i.e., the power ratio between ERP and background EEG). We calculated the amount of averaging necessary after applying a particle filter that produced a result equivalent to that associated with conventional averaging, and determined that the particle filter yielded a maximum 42.8% reduction in measurement time. The particle filter performed better than both the Kalman filter and conventional averaging for a low SNR in terms of both MSE and P300 peak amplitude and latency. For EEG data produced by the P300 speller, we were able to use our filter to obtain ERP waveforms that were stable compared with averages produced by a conventional averaging method, irrespective of the amount of averaging. We confirmed that particle filters are efficacious in reducing the measurement time required during simulations with a low SNR. Additionally, particle filters can perform robust ERP estimation for EEG data produced via a P300 speller. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Testing particle filters on convective scale dynamics

Science.gov (United States)

Haslehner, Mylene; Craig, George. C.; Janjic, Tijana

2014-05-01

Particle filters have been developed in recent years to deal with highly nonlinear dynamics and non Gaussian error statistics that also characterize data assimilation on convective scales. In this work we explore the use of the efficient particle filter (P.v. Leeuwen, 2011) for convective scale data assimilation application. The method is tested in idealized setting, on two stochastic models. The models were designed to reproduce some of the properties of convection, for example the rapid development and decay of convective clouds. The first model is a simple one-dimensional, discrete state birth-death model of clouds (Craig and Würsch, 2012). For this model, the efficient particle filter that includes nudging the variables shows significant improvement compared to Ensemble Kalman Filter and Sequential Importance Resampling (SIR) particle filter. The success of the combination of nudging and resampling, measured as RMS error with respect to the 'true state', is proportional to the nudging intensity. Significantly, even a very weak nudging intensity brings notable improvement over SIR. The second model is a modified version of a stochastic shallow water model (Würsch and Craig 2013), which contains more realistic dynamical characteristics of convective scale phenomena. Using the efficient particle filter and different combination of observations of the three field variables (wind, water 'height' and rain) allows the particle filter to be evaluated in comparison to a regime where only nudging is used. Sensitivity to the properties of the model error covariance is also considered. Finally, criteria are identified under which the efficient particle filter outperforms nudging alone. References: Craig, G. C. and M. Würsch, 2012: The impact of localization and observation averaging for convective-scale data assimilation in a simple stochastic model. Q. J. R. Meteorol. Soc.,139, 515-523. Van Leeuwen, P. J., 2011: Efficient non-linear data assimilation in geophysical

Particle filtering for passive fathometer tracking.

Science.gov (United States)

Michalopoulou, Zoi-Heleni; Yardim, Caglar; Gerstoft, Peter

2012-01-01

Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs. © 2012 Acoustical Society of America.

Particle Kalman Filtering: A Nonlinear Framework for Ensemble Kalman Filters

KAUST Repository

Hoteit, Ibrahim

2010-09-19

Optimal nonlinear filtering consists of sequentially determining the conditional probability distribution functions (pdf) of the system state, given the information of the dynamical and measurement processes and the previous measurements. Once the pdfs are obtained, one can determine different estimates, for instance, the minimum variance estimate, or the maximum a posteriori estimate, of the system state. It can be shown that, many filters, including the Kalman filter (KF) and the particle filter (PF), can be derived based on this sequential Bayesian estimation framework. In this contribution, we present a Gaussian mixture‐based framework, called the particle Kalman filter (PKF), and discuss how the different EnKF methods can be derived as simplified variants of the PKF. We also discuss approaches to reducing the computational burden of the PKF in order to make it suitable for complex geosciences applications. We use the strongly nonlinear Lorenz‐96 model to illustrate the performance of the PKF.

Blended particle filters for large-dimensional chaotic dynamical systems

Science.gov (United States)

Majda, Andrew J.; Qi, Di; Sapsis, Themistoklis P.

2014-01-01

A major challenge in contemporary data science is the development of statistically accurate particle filters to capture non-Gaussian features in large-dimensional chaotic dynamical systems. Blended particle filters that capture non-Gaussian features in an adaptively evolving low-dimensional subspace through particles interacting with evolving Gaussian statistics on the remaining portion of phase space are introduced here. These blended particle filters are constructed in this paper through a mathematical formalism involving conditional Gaussian mixtures combined with statistically nonlinear forecast models compatible with this structure developed recently with high skill for uncertainty quantification. Stringent test cases for filtering involving the 40-dimensional Lorenz 96 model with a 5-dimensional adaptive subspace for nonlinear blended filtering in various turbulent regimes with at least nine positive Lyapunov exponents are used here. These cases demonstrate the high skill of the blended particle filter algorithms in capturing both highly non-Gaussian dynamical features as well as crucial nonlinear statistics for accurate filtering in extreme filtering regimes with sparse infrequent high-quality observations. The formalism developed here is also useful for multiscale filtering of turbulent systems and a simple application is sketched below. PMID:24825886

Group-SMA Algorithm Based Joint Estimation of Train Parameter and State

Directory of Open Access Journals (Sweden)

Wei Zheng

2015-03-01

Full Text Available The braking rate and train arresting operation is important in the train braking performance. It is difficult to obtain the states of the train on time because of the measurement noise and a long calculation time. A type of Group Stochastic M-algorithm (GSMA based on Rao-Blackwellization Particle Filter (RBPF algorithm and Stochastic M-algorithm (SMA is proposed in this paper. Compared with RBPF, GSMA based estimation precisions for the train braking rate and the control accelerations were improved by 78% and 62%, respectively. The calculation time of the GSMA was decreased by 70% compared with SMA.

A nested sampling particle filter for nonlinear data assimilation

KAUST Repository

Elsheikh, Ahmed H.

2014-04-15

We present an efficient nonlinear data assimilation filter that combines particle filtering with the nested sampling algorithm. Particle filters (PF) utilize a set of weighted particles as a discrete representation of probability distribution functions (PDF). These particles are propagated through the system dynamics and their weights are sequentially updated based on the likelihood of the observed data. Nested sampling (NS) is an efficient sampling algorithm that iteratively builds a discrete representation of the posterior distributions by focusing a set of particles to high-likelihood regions. This would allow the representation of the posterior PDF with a smaller number of particles and reduce the effects of the curse of dimensionality. The proposed nested sampling particle filter (NSPF) iteratively builds the posterior distribution by applying a constrained sampling from the prior distribution to obtain particles in high-likelihood regions of the search space, resulting in a reduction of the number of particles required for an efficient behaviour of particle filters. Numerical experiments with the 3-dimensional Lorenz63 and the 40-dimensional Lorenz96 models show that NSPF outperforms PF in accuracy with a relatively smaller number of particles. © 2013 Royal Meteorological Society.

Photon Rao

Indian Academy of Sciences (India)

Volume 2 Issue 5 May 1997 pp 69-72 Feature Article. Molecule of the Month Molecular–Chameleon: Solvatochromism at its Iridescent Best! Photon Rao · More Details Fulltext PDF. Volume 16 Issue 12 December 2011 pp 1303-1306. Molecule of the Month - Molecular-Chameleon: Solvatochromism at its Iridescent Best!

Weierstrass semigroups and the Feng-Rao Distance

DEFF Research Database (Denmark)

Campillo, Antonio; Farran, Ignacio

2000-01-01

We detrmine the Feng-Rao distance for several claases of codes from algebraic geometry usingthe weierstrass semigroups......We detrmine the Feng-Rao distance for several claases of codes from algebraic geometry usingthe weierstrass semigroups...

Hartebeesthoek Radio Astronomy Observatory (HartRAO)

Science.gov (United States)

Nickola, Marisa; Gaylard, Mike; Quick, Jonathan; Combrinck, Ludwig

2013-01-01

HartRAO provides the only fiducial geodetic site in Africa, and it participates in global networks for VLBI, GNSS, SLR, and DORIS. This report provides an overview of geodetic VLBI activities at HartRAO during 2012, including the conversion of a 15-m alt-az radio telescope to an operational geodetic VLBI antenna.

MapReduce particle filtering with exact resampling and deterministic runtime

Science.gov (United States)

Thiyagalingam, Jeyarajan; Kekempanos, Lykourgos; Maskell, Simon

2017-12-01

Particle filtering is a numerical Bayesian technique that has great potential for solving sequential estimation problems involving non-linear and non-Gaussian models. Since the estimation accuracy achieved by particle filters improves as the number of particles increases, it is natural to consider as many particles as possible. MapReduce is a generic programming model that makes it possible to scale a wide variety of algorithms to Big data. However, despite the application of particle filters across many domains, little attention has been devoted to implementing particle filters using MapReduce. In this paper, we describe an implementation of a particle filter using MapReduce. We focus on a component that what would otherwise be a bottleneck to parallel execution, the resampling component. We devise a new implementation of this component, which requires no approximations, has O( N) spatial complexity and deterministic O((log N)2) time complexity. Results demonstrate the utility of this new component and culminate in consideration of a particle filter with 224 particles being distributed across 512 processor cores.

Micro-particle filter made in SU-8 for biomedical applications

DEFF Research Database (Denmark)

Noeth, Nadine-Nicole; Keller, Stephan Urs; Fetz, Stefanie

2009-01-01

We have integrated a micro-particle filter in a polymer cantilever to filter micro-particles from a fluid while simultaneously measuring the amount of filtered particles. In a 3,8 mum thick SU-8 cantilever a filter was integrated with pore sizes between 3 and 30 mum. The chip was inserted in a mi...

On the Feng-Rao bound for generalized hamming weights

DEFF Research Database (Denmark)

Geil, Hans Olav; Thommesen, Christian

2006-01-01

The Feng-Rao bound gives good estimates of the minimum distance of a large class of codes. In this work we are concerned with the problem of how to extend the Feng-Rao bound so that it deals with all the generalized Hamming weights. The problem was solved by Heijnen and Pellikaan in [7] for a large...... family of codes that includes the duals of one-point geometric Goppa codes and the q-ary Reed-Muller codes, but not the Feng-Rao improved such ones. We show that Heijnen and Pellikaan's results holds for the more general class of codes for which the traditional Feng-Rao bound can be applied. We also...... establish the connection to the Shibuya-Sakaniwa bound for generalized Hamming weights ([15], [16], [17], [18], [19] and [20]). More precisely we show that the Shibuya-Sakaniwa bound is a consequence of the extended Feng-Rao bound. In particular the extended Feng-Rao bound gives always at least as good...

On the Feng-Rao bound for generalized Hamming weights

DEFF Research Database (Denmark)

Geil, Olav; Thommesen, Christian

2005-01-01

The Feng-Rao bound gives good estimates of the minimum distance of a large class of codes. In this work we are concerned with the problem of how to extend the Feng-Rao bound so that it deals with all the generalized Hamming weights. The problem was solved by Heijnen and Pellikaan in [7] for a large...... family of codes that includes the duals of one-point geometric Goppa codes and the q-ary Reed-Muller codes, but not the Feng-Rao improved such ones. We show that Heijnen and Pellikaan’s results holds for the more general class of codes for which the traditional Feng-Rao bound can be applied. We also...... establish the connection to the Shibuya-Sakaniwa bound for generalized Hamming weights ([15], [16], [17], [18], [19] and [20]). More precisely we show that the Shibuya-Sakaniwa bound is a consequence of the extended Feng-Rao bound. In particular the extended Feng-Rao bound gives always at least as good...

Particle Filter Tracking without Dynamics

Directory of Open Access Journals (Sweden)

Jaime Ortegon-Aguilar

2007-01-01

Full Text Available People tracking is an interesting topic in computer vision. It has applications in industrial areas such as surveillance or human-machine interaction. Particle Filters is a common algorithm for people tracking; challenging situations occur when the target's motion is poorly modelled or with unexpected motions. In this paper, an alternative to address people tracking is presented. The proposed algorithm is based in particle filters, but instead of using a dynamical model, it uses background subtraction to predict future locations of particles. The algorithm is able to track people in omnidirectional sequences with a low frame rate (one or two frames per second. Our approach can tackle unexpected discontinuities and changes in the direction of the motion. The main goal of the paper is to track people from laboratories, but it has applications in surveillance, mainly in controlled environments.

Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter

DEFF Research Database (Denmark)

Andreasen, Martin Møller

This paper shows how non-linear DSGE models with potential non-normal shocks can be estimated by Quasi-Maximum Likelihood based on the Central Difference Kalman Filter (CDKF). The advantage of this estimator is that evaluating the quasi log-likelihood function only takes a fraction of a second....... The second contribution of this paper is to derive a new particle filter which we term the Mean Shifted Particle Filter (MSPFb). We show that the MSPFb outperforms the standard Particle Filter by delivering more precise state estimates, and in general the MSPFb has lower Monte Carlo variation in the reported...

Ballistic target tracking algorithm based on improved particle filtering

Science.gov (United States)

Ning, Xiao-lei; Chen, Zhan-qi; Li, Xiao-yang

2015-10-01

Tracking ballistic re-entry target is a typical nonlinear filtering problem. In order to track the ballistic re-entry target in the nonlinear and non-Gaussian complex environment, a novel chaos map particle filter (CMPF) is used to estimate the target state. CMPF has better performance in application to estimate the state and parameter of nonlinear and non-Gassuian system. The Monte Carlo simulation results show that, this method can effectively solve particle degeneracy and particle impoverishment problem by improving the efficiency of particle sampling to obtain the better particles to part in estimation. Meanwhile CMPF can improve the state estimation precision and convergence velocity compared with EKF, UKF and the ordinary particle filter.

PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

Directory of Open Access Journals (Sweden)

Wei Leong Khong

2014-02-01

Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

Box-Particle Cardinality Balanced Multi-Target Multi-Bernoulli Filter

OpenAIRE

L. Song; X. Zhao

2014-01-01

As a generalized particle filtering, the box-particle filter (Box-PF) has a potential to process the measurements affected by bounded error of unknown distributions and biases. Inspired by the Box-PF, a novel implementation for multi-target tracking, called box-particle cardinality balanced multi-target multi-Bernoulli (Box-CBMeMBer) filter is presented in this paper. More important, to eliminate the negative effect of clutters in the estimation of the numbers of targets, an improved generali...

Particle filter based MAP state estimation: A comparison

NARCIS (Netherlands)

Saha, S.; Boers, Y.; Driessen, J.N.; Mandal, Pranab K.; Bagchi, Arunabha

2009-01-01

MAP estimation is a good alternative to MMSE for certain applications involving nonlinear non Gaussian systems. Recently a new particle filter based MAP estimator has been derived. This new method extracts the MAP directly from the output of a running particle filter. In the recent past, a Viterbi

Nonlinear Statistical Signal Processing: A Particle Filtering Approach

International Nuclear Information System (INIS)

Candy, J.

2007-01-01

A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations

Rao, Prof. Sumathi

Indian Academy of Sciences (India)

Rao, Prof. Sumathi Ph.D. (SUNY, Stony Brook), FNASc. Date of birth: 5 December 1956. Specialization: Theoretical Condensed Matter Physics, Quantum field Theory Address: Harish Chandra Research Institute, Chhatnag Road, Jhusi, Allahabad 211 019, U.P.. Contact: Office: (0532) 227 4303. Residence: (0532) 227 4002

Rao, Prof. Kaza Kesava

Indian Academy of Sciences (India)

Elected: 1992 Section: Engineering & Technology. Rao, Prof. ... Address: Professor, Department of Chemical Engineering, Indian Institute of Science, Bengaluru 560 012, Karnataka Contact: ... Upcoming Refresher Courses. Topology 02 to 14 ...

An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis

Directory of Open Access Journals (Sweden)

Qihang Wang

2016-07-01

Full Text Available In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.

Performance of Magnetic Filter for Separation of Magnetic Gel Particles

OpenAIRE

栗延, 俊太郎; 尾崎, 博明; 渡辺, 恒雄; クリノブ, シュンタロウ; オザキ, ヒロアキ; ワタナベ, ツネオ; Shuntaro, KURINOBU; Hiroaki, OZAKI; Tuneo, WATANABE

2003-01-01

We have developed a new wastewater treatment process using magnetic gel particles containing immobilized microorganisms and magnetic particles. The performance of magnetic gel particles using a magnetic filter is very important to control the process. In this study, the performance of a magnetic filter was studied for magnetic gel, particles. Agar particles containing magnetite particles were used as gel particles. The recovery and the relative retention area of magnetic gel particles on the ...

Cantilever-based micro-particle filter with simultaneous single particle detection

DEFF Research Database (Denmark)

Noeth, Nadine-Nicole; Keller, Stephan Sylvest; Boisen, Anja

2011-01-01

Currently, separation of whole blood samples on lab-on-a-chip systems is achieved via filters followed by analysis of the filtered matter such as counting of blood cells. Here, a micro-chip based on cantilever technology is developed, which enables simultaneous filtration and counting of micro-particles...... from a liquid. A hole-array is integrated into a micro-cantilever, which is inserted into a microfluidic channel perpendicular to the flow. A metal pad at the apex of the cantilever enables an optical read-out of the deflection of the cantilever. When a micro-particle is too large to pass a hole...

Marginalized particle filter for spacecraft attitude estimation from vector measurements

Institute of Scientific and Technical Information of China (English)

Yaqiu LIU; Xueyuan JIANG; Guangfu MA

2007-01-01

An algorithm based on the marginalized particle filters(MPF)is given in details in this paper to solve the spacecraft attitude estimation problem:attitude and gyro bias estimation using the biased gyro and vector observations.In this algorithm,by marginalizing out the state appearing linearly in the spacecraft model,the Kalman filter is associated with each particle in order to reduce the size of the state space and computational burden.The distribution of attitude vector is approximated by a set of particles and estimated using particle filter,while the estimation of gyro bias is obtained for each one of the attitude particles by applying the Kalman filter.The efficiency of this modified MPF estimator is verified through numerical simulation of a fully actuated rigid body.For comparison,unscented Kalman filter(UKF)is also used to gauge the performance of MPF.The results presented in this paper clearly demonstrate that the MPF is superior to UKF in coping with the nonlinear model.

Adaptive particle filter for localization problem in service robotics

Directory of Open Access Journals (Sweden)

Heilig Alexander

2018-01-01

Full Text Available In this paper we present a statistical approach to the likelihood computation and adaptive resampling algorithm for particle filters using low cost ultrasonic sensors in the context of service robotics. This increases the efficiency of the particle filter in the Monte Carlo Localization problem by means of preventing sample impoverishment and ensuring it converges towards the most likely particle and simultaneously keeping less likely ones by systematic resampling. Proposed algorithms were developed in the ROS framework, simulation was done in Gazebo environment. Experiments using a differential drive mobile platform with 4 ultrasonic sensors in the office environment show that our approach provides strong improvement over particle filters with fixed sample sizes.

Depth Filters Containing Diatomite Achieve More Efficient Particle Retention than Filters Solely Containing Cellulose Fibers.

Science.gov (United States)

Buyel, Johannes F; Gruchow, Hannah M; Fischer, Rainer

2015-01-01

The clarification of biological feed stocks during the production of biopharmaceutical proteins is challenging when large quantities of particles must be removed, e.g., when processing crude plant extracts. Single-use depth filters are often preferred for clarification because they are simple to integrate and have a good safety profile. However, the combination of filter layers must be optimized in terms of nominal retention ratings to account for the unique particle size distribution in each feed stock. We have recently shown that predictive models can facilitate filter screening and the selection of appropriate filter layers. Here we expand our previous study by testing several filters with different retention ratings. The filters typically contain diatomite to facilitate the removal of fine particles. However, diatomite can interfere with the recovery of large biopharmaceutical molecules such as virus-like particles and aggregated proteins. Therefore, we also tested filtration devices composed solely of cellulose fibers and cohesive resin. The capacities of both filter types varied from 10 to 50 L m(-2) when challenged with tobacco leaf extracts, but the filtrate turbidity was ~500-fold lower (~3.5 NTU) when diatomite filters were used. We also tested pre-coat filtration with dispersed diatomite, which achieved capacities of up to 120 L m(-2) with turbidities of ~100 NTU using bulk plant extracts, and in contrast to the other depth filters did not require an upstream bag filter. Single pre-coat filtration devices can thus replace combinations of bag and depth filters to simplify the processing of plant extracts, potentially saving on time, labor and consumables. The protein concentrations of TSP, DsRed and antibody 2G12 were not affected by pre-coat filtration, indicating its general applicability during the manufacture of plant-derived biopharmaceutical proteins.

Depth filters containing diatomite achieve more efficient particle retention than filters solely containing cellulose fibers

Directory of Open Access Journals (Sweden)

Johannes Felix Buyel

2015-12-01

Full Text Available The clarification of biological feed stocks during the production of biopharmaceutical proteins is challenging when large quantities of particles must be removed, e.g. when processing crude plant extracts. Single-use depth filters are often preferred for clarification because they are simple to integrate and have a good safety profile. However, the combination of filter layers must be optimized in terms of nominal retention ratings to account for the unique particle size distribution in each feed stock. We have recently shown that predictive models can facilitate filter screening and the selection of appropriate filter layers. Here we expand our previous study by testing several filters with different retention ratings. The filters typically contain diatomite to facilitate the removal of fine particles. However, diatomite can interfere with the recovery of large biopharmaceutical molecules such as virus-like particles and aggregated proteins. Therefore, we also tested filtration devices composed solely of cellulose fibers and cohesive resin. The capacities of both filter types varied from 10 to 50 L m-2 when challenged with tobacco leaf extracts, but the filtrate turbidity was ~500-fold lower (~3.5 NTU when diatomite filters were used. We also tested pre coat filtration with dispersed diatomite, which achieved capacities of up to 120 L m-2 with turbidities of ~100 NTU using bulk plant extracts, and in contrast to the other depth filters did not require an upstream bag filter. Single pre-coat filtration devices can thus replace combinations of bag and depth filters to simplify the processing of plant extracts, potentially saving on time, labor and consumables. The protein concentrations of TSP, DsRed and antibody 2G12 were not affected by pre-coat filtration, indicating its general applicability during the manufacture of plant-derived biopharmaceutical proteins.

Nonlinear data assimilation using synchronization in a particle filter

Science.gov (United States)

Rodrigues-Pinheiro, Flavia; Van Leeuwen, Peter Jan

2017-04-01

Current data assimilation methods still face problems in strongly nonlinear cases. A promising solution is a particle filter, which provides a representation of the model probability density function by a discrete set of particles. However, the basic particle filter does not work in high-dimensional cases. The performance can be improved by considering the proposal density freedom. A potential choice of proposal density might come from the synchronisation theory, in which one tries to synchronise the model with the true evolution of a system using one-way coupling via the observations. In practice, an extra term is added to the model equations that damps growth of instabilities on the synchronisation manifold. When only part of the system is observed synchronization can be achieved via a time embedding, similar to smoothers in data assimilation. In this work, two new ideas are tested. First, ensemble-based time embedding, similar to an ensemble smoother or 4DEnsVar is used on each particle, avoiding the need for tangent-linear models and adjoint calculations. Tests were performed using Lorenz96 model for 20, 100 and 1000-dimension systems. Results show state-averaged synchronisation errors smaller than observation errors even in partly observed systems, suggesting that the scheme is a promising tool to steer model states to the truth. Next, we combine these efficient particles using an extension of the Implicit Equal-Weights Particle Filter, a particle filter that ensures equal weights for all particles, avoiding filter degeneracy by construction. Promising results will be shown on low- and high-dimensional Lorenz96 models, and the pros and cons of these new ideas will be discussed.

Full-field particle velocimetry with a photorefractive optical novelty filter

International Nuclear Information System (INIS)

Woerdemann, Mike; Holtmann, Frank; Denz, Cornelia

2008-01-01

We utilize the finite time constant of a photorefractive optical novelty filter microscope to access full-field velocity information of fluid flows on microscopic scales. In contrast to conventional methods such as particle image velocimetry and particle tracking velocimetry, not only image acquisition of the tracer particle field but also evaluation of tracer particle velocities is done all-optically by the novelty filter. We investigate the velocity dependent parameters of two-beam coupling based optical novelty filters and demonstrate calibration and application of a photorefractive velocimetry system. Theoretical and practical limits to the range of accessible velocities are discussed

The Hartshorne-Rao module of curves on rational normal scrolls

Directory of Open Access Journals (Sweden)

Roberta Di Gennaro

2000-09-01

Full Text Available We study the Hartshorne-Rao module of curves lying on a rational normal scroll S_e of invariant e ≥ 0 in P^{e+3} .We calculate the Rao function, we characterize the aCM curves on S_e .Finally, we give an algorithm to check if a curve is aC M or not and, inthe second case, to calculate the Rao function.

Jagirdar, Prof. Balaji Rao

Indian Academy of Sciences (India)

Fellow Profile. Elected: 2013 Section: Chemistry. Jagirdar, Prof. Balaji Rao Ph.D. (Kansas State). Date of birth: 9 September 1965. Specialization: Organometallic Chemistry, Materials Chemistry, Catalysis Address: Department of Inorganic & Physical Chemistry, Indian Institute of Science, Bengaluru 560 012, Karnataka

An efficient multiple particle filter based on the variational Bayesian approach

KAUST Repository

Ait-El-Fquih, Boujemaa

2015-12-07

This paper addresses the filtering problem in large-dimensional systems, in which conventional particle filters (PFs) remain computationally prohibitive owing to the large number of particles needed to obtain reasonable performances. To overcome this drawback, a class of multiple particle filters (MPFs) has been recently introduced in which the state-space is split into low-dimensional subspaces, and then a separate PF is applied to each subspace. In this paper, we adopt the variational Bayesian (VB) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs to be generated. In a numerical test, the proposed VBMPF behaves better than the PF and MPF.

Computer Vision Tracking Using Particle Filters for 3D Position Estimation

Science.gov (United States)

2014-03-27

List of Acronyms Acronym Definition AFIT Air Force Institute of Technology ASIR Auxiliary Sampling Importance Re-sampling BPF Bootstrap Particle Filter...Auxiliary Sampling Importance Re-sampling ( ASIR ) filter, and Regularized Particle Filter (RPF), also seek to eliminate weight collapse through a variety

Rao, Prof. Maddali Nageswara

Indian Academy of Sciences (India)

Rao, Prof. Maddali Nageswara Dr. rer. nat. (Cologne). Date of birth: 11 July 1931. Specialization: Solar System Physics, Mars Fundamental Research, Earth & Planetary Sciences and Lunar & Meteorite Sample Studies Address: 16931, Tower Ridge, Friendswood, Texas 77546, USA Contact: Residence: (+1-281) 993 9191

Rao, Prof. Valipe Ramgopal

Indian Academy of Sciences (India)

Home; Fellowship. Fellow Profile. Elected: 2009 Section: Engineering & Technology. Rao, Prof. Valipe Ramgopal FNAE, FNASc, FNA, FIEEE. Date of birth: 16 August 1965. Specialization: Nanoelectronics and Nanotechnology Address: Director, Indian Institute of Technology, Hauz Khas, New Delhi 110 016, U.T.. Contact:

Hollywood log-homotopy: movies of particle flow for nonlinear filters

Science.gov (United States)

Daum, Fred; Huang, Jim

2011-06-01

In this paper we show five movies of particle flow to provide insight and intuition about this new algorithm. The particles flow solves the well known and important problem of particle degeneracy. Bayes' rule is implemented by particle flow rather than as a pointwise multiplication. This theory is roughly seven orders of magnitude faster than standard particle filters, and it often beats the extended Kalman filter by two orders of magnitude in accuracy for difficult nonlinear problems.

Model Adaptation for Prognostics in a Particle Filtering Framework

Directory of Open Access Journals (Sweden)

Bhaskar Saha

2011-01-01

Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

Model Adaptation for Prognostics in a Particle Filtering Framework

Science.gov (United States)

Saha, Bhaskar; Goebel, Kai Frank

2011-01-01

One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

A variational Bayesian multiple particle filtering scheme for large-dimensional systems

KAUST Repository

Ait-El-Fquih, Boujemaa

2016-06-14

This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-space systems. In such systems, classical particle filters (PFs) are impractical due to the prohibitive number of required particles to obtain reasonable performances. One approach that has been introduced to overcome this problem is the concept of multiple PFs (MPFs), where the state-space is split into low-dimensional subspaces and then a separate PF is applied to each subspace. Remarkable performances of MPF-like filters motivated our investigation here into a new strategy that combines the variational Bayesian approach to split the state-space with random sampling techniques, to derive a new computationally efficient MPF. The propagation of each particle in the prediction step of the resulting filter requires generating only a single particle in contrast with standard MPFs, for which a set of (children) particles is required. We present simulation results to evaluate the behavior of the proposed filter and compare its performances against standard PF and a MPF.

A variational Bayesian multiple particle filtering scheme for large-dimensional systems

KAUST Repository

Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

2016-01-01

This paper considers the Bayesian filtering problem in high-dimensional nonlinear state-space systems. In such systems, classical particle filters (PFs) are impractical due to the prohibitive number of required particles to obtain reasonable performances. One approach that has been introduced to overcome this problem is the concept of multiple PFs (MPFs), where the state-space is split into low-dimensional subspaces and then a separate PF is applied to each subspace. Remarkable performances of MPF-like filters motivated our investigation here into a new strategy that combines the variational Bayesian approach to split the state-space with random sampling techniques, to derive a new computationally efficient MPF. The propagation of each particle in the prediction step of the resulting filter requires generating only a single particle in contrast with standard MPFs, for which a set of (children) particles is required. We present simulation results to evaluate the behavior of the proposed filter and compare its performances against standard PF and a MPF.

Online Nonparametric Bayesian Activity Mining and Analysis From Surveillance Video.

Science.gov (United States)

Bastani, Vahid; Marcenaro, Lucio; Regazzoni, Carlo S

2016-05-01

A method for online incremental mining of activity patterns from the surveillance video stream is presented in this paper. The framework consists of a learning block in which Dirichlet process mixture model is employed for the incremental clustering of trajectories. Stochastic trajectory pattern models are formed using the Gaussian process regression of the corresponding flow functions. Moreover, a sequential Monte Carlo method based on Rao-Blackwellized particle filter is proposed for tracking and online classification as well as the detection of abnormality during the observation of an object. Experimental results on real surveillance video data are provided to show the performance of the proposed algorithm in different tasks of trajectory clustering, classification, and abnormality detection.

Valluri, Dr Sitaram Rao

Indian Academy of Sciences (India)

Home; Fellowship. Fellow Profile. Elected: 1971 Section: Engineering & Technology. Valluri, Dr Sitaram Rao Ph.D. (Caltech). Date of birth: 25 June 1924. Specialization: Metal Fatigue Address: 'Prashanthi', 659, 100 Feet Road, Indiranagar, Bengaluru 560 038, Karnataka Contact: Residence: (080) 2525 8294. YouTube ...

ECG Denoising Using Marginalized Particle Extended Kalman Filter With an Automatic Particle Weighting Strategy.

Science.gov (United States)

Hesar, Hamed Danandeh; Mohebbi, Maryam

2017-05-01

In this paper, a model-based Bayesian filtering framework called the "marginalized particle-extended Kalman filter (MP-EKF) algorithm" is proposed for electrocardiogram (ECG) denoising. This algorithm does not have the extended Kalman filter (EKF) shortcoming in handling non-Gaussian nonstationary situations because of its nonlinear framework. In addition, it has less computational complexity compared with particle filter. This filter improves ECG denoising performance by implementing marginalized particle filter framework while reducing its computational complexity using EKF framework. An automatic particle weighting strategy is also proposed here that controls the reliance of our framework to the acquired measurements. We evaluated the proposed filter on several normal ECGs selected from MIT-BIH normal sinus rhythm database. To do so, artificial white Gaussian and colored noises as well as nonstationary real muscle artifact (MA) noise over a range of low SNRs from 10 to -5 dB were added to these normal ECG segments. The benchmark methods were the EKF and extended Kalman smoother (EKS) algorithms which are the first model-based Bayesian algorithms introduced in the field of ECG denoising. From SNR viewpoint, the experiments showed that in the presence of Gaussian white noise, the proposed framework outperforms the EKF and EKS algorithms in lower input SNRs where the measurements and state model are not reliable. Owing to its nonlinear framework and particle weighting strategy, the proposed algorithm attained better results at all input SNRs in non-Gaussian nonstationary situations (such as presence of pink noise, brown noise, and real MA). In addition, the impact of the proposed filtering method on the distortion of diagnostic features of the ECG was investigated and compared with EKF/EKS methods using an ECG diagnostic distortion measure called the "Multi-Scale Entropy Based Weighted Distortion Measure" or MSEWPRD. The results revealed that our proposed

Numerical simulation of DPF filter for selected regimes with deposited soot particles

Science.gov (United States)

Lávička, David; Kovařík, Petr

2012-04-01

For the purpose of accumulation of particulate matter from Diesel engine exhaust gas, particle filters are used (referred to as DPF or FAP filters in the automotive industry). However, the cost of these filters is quite high. As the emission limits become stricter, the requirements for PM collection are rising accordingly. Particulate matters are very dangerous for human health and these are not invisible for human eye. They can often cause various diseases of the respiratory tract, even what can cause lung cancer. Performed numerical simulations were used to analyze particle filter behavior under various operating modes. The simulations were especially focused on selected critical states of particle filter, when engine is switched to emergency regime. The aim was to prevent and avoid critical situations due the filter behavior understanding. The numerical simulations were based on experimental analysis of used diesel particle filters.

An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

Science.gov (United States)

Raihan A. V, Dilshad; Chakravorty, Suman

2018-03-01

Optimal and consistent estimation of the state of space objects is pivotal to surveillance and tracking applications. However, probabilistic estimation of space objects is made difficult by the non-Gaussianity and nonlinearity associated with orbital mechanics. In this paper, we present an unscented Kalman-particle hybrid filtering framework for recursive Bayesian estimation of space objects. The hybrid filtering scheme is designed to provide accurate and consistent estimates when measurements are sparse without incurring a large computational cost. It employs an unscented Kalman filter (UKF) for estimation when measurements are available. When the target is outside the field of view (FOV) of the sensor, it updates the state probability density function (PDF) via a sequential Monte Carlo method. The hybrid filter addresses the problem of particle depletion through a suitably designed filter transition scheme. To assess the performance of the hybrid filtering approach, we consider two test cases of space objects that are assumed to undergo full three dimensional orbital motion under the effects of J 2 and atmospheric drag perturbations. It is demonstrated that the hybrid filters can furnish fast, accurate and consistent estimates outperforming standard UKF and particle filter (PF) implementations.

A fast ellipse extended target PHD filter using box-particle implementation

Science.gov (United States)

Zhang, Yongquan; Ji, Hongbing; Hu, Qi

2018-01-01

This paper presents a box-particle implementation of the ellipse extended target probability hypothesis density (ET-PHD) filter, called the ellipse extended target box particle PHD (EET-BP-PHD) filter, where the extended targets are described as a Poisson model developed by Gilholm et al. and the term "box" is here equivalent to the term "interval" used in interval analysis. The proposed EET-BP-PHD filter is capable of dynamically tracking multiple ellipse extended targets and estimating the target states and the number of targets, in the presence of clutter measurements, false alarms and missed detections. To derive the PHD recursion of the EET-BP-PHD filter, a suitable measurement likelihood is defined for a given partitioning cell, and the main implementation steps are presented along with the necessary box approximations and manipulations. The limitations and capabilities of the proposed EET-BP-PHD filter are illustrated by simulation examples. The simulation results show that a box-particle implementation of the ET-PHD filter can avoid the high number of particles and reduce computational burden, compared to a particle implementation of that for extended target tracking.

Learning based particle filtering object tracking for visible-light systems.

Science.gov (United States)

Sun, Wei

2015-10-01

We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

Nageswara Rao, Dr Gullapalli

Indian Academy of Sciences (India)

Nageswara Rao, Dr Gullapalli M.D. (Opthal.) (AIIMS), FAMS, FACS, FRCS, FNASc. Date of birth: 1 September 1945. Specialization: Cornea, Community Eye Health and Eye Care Policy & Planning Address: Distinguished Chair of Eye Health, LV Prasad Eye Institute, LV Prasad Marg, Banjara Hills, Hyderabad 500 034, A.P.

Rao, Prof. Kalya Jagannatha

Indian Academy of Sciences (India)

Rao, Prof. Kalya Jagannatha Ph.D. (IIT, Kanpur), D.Sc. (IISc), FNA, FNASc, D.Sc. (h.c., Univ. Bordeaux, France) Council Service: 1998-2003. Date of birth: 7 December 1940. Specialization: Physical Chemistry of Amorphous Solids & Ceramics and Phase Transitions Address: 187/1, Tadvanam Estate, Halasinganahalli Road ...

Bayesian signal processing classical, modern, and particle filtering methods

CERN Document Server

Candy, James V

2016-01-01

This book aims to give readers a unified Bayesian treatment starting from the basics (Baye's rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on "Sequential Bayesian Detection," a new section on "Ensemble Kalman Filters" as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to "fill-in-the gaps" of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical "sanity testing" lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed an...

Rao Quan Feasibility Study - Phase 1: Toxic Substances and Contamination (Final Report)

Energy Technology Data Exchange (ETDEWEB)

Berge, Dag; Knutzen, Jon

1997-12-31

Due to wartime activity in the Khe Sanh area, it was expected that damming of the river Rao Quan could wash out diffuse pollutants from the ground and from possible military dump sites. As discussed in this report, the rivers Rao Quan, Khe Nghi and Quang Tri contain relatively soft water. The buffer capacity against acidification is good. The sulphate concentration is low. The water will not be aggressive against concrete. The maximum particulate content in the wet season is low. The nutrient content of the rivers is relatively low. The phosphorus content correlated well with the turbidity, which indicates that the phosphorus is bound to particles. Khe Nghi has significantly higher nitrogen content than the other rivers, which may indicate some slight impact from animal husbandry. However, there was no eutrophication. The content of heavy metals is low and indicates no pollution from the military activities in the area. The water is well suited for irrigation. There was no indication from the analysed fish , the river sediments from Rao Quan or the top soil of the rice fields of any significant dioxin contamination. The content was similar to normal back ground levels caused by diffuse atmospheric fallout. The herbicide Agent Orange in 1962-1975 was applied mostly in the southernmost part of the country and contamination from it in the Quang Tri Province is not expected. 13 refs., 4 figs., 4 tabs.

Particle filters on light diesel vehicles - a socio-economic analysis on the introduction of particle filters; Partikelfiltre pae lette dieselkoeretoejer - en samfundsoekonomisk analyse af fremskyndelse af partikelfiltre

Energy Technology Data Exchange (ETDEWEB)

Kohl, M.; Larsen, Thommy; Carlsen, Kirsten; Mulvad Jeppesen, L.

2006-09-15

Emission of particles into the atmosphere is one of the biggest air pollution problems of our times. The emission of particles causes severe health problems such as respiratory and circulatory diseases, lung cancer, asthma, bronchitis and even causes premature deaths. The emission of particles comes from a number of different sources, where traffic is a considerable contributor. The effects of particle emissions from the traffic on the population are substantial, as the emission comes from mobile sources which create a high local pollution in city areas and in consequence high exposure of the local population. Exhaust particle emissions come mainly from diesel engines, and the introduction of particle filters would have a considerable impact on particle emissions. Vehicle emissions regulation is controlled by the EU. The coming emission regulation, EURO 5, is expected to be put into effect by the beginning of 2010. The current suggestions for the EURO 5 restrictions on particles are set so strict that they will be impossible to fulfil without a particle filter. This report performs a socio-economic analysis on the introduction of particle filters on all light vehicles (<3,500 kg). The analysis assumes that all newly registered diesel powered cars and vans should have a factory installed particle filter from the beginning of 2007. This thereby gives a period of three years before implementation of the EURO 5. (au)

Nonlinear Vibration Signal Tracking of Large Offshore Bridge Stayed Cable Based on Particle Filter

Directory of Open Access Journals (Sweden)

Ye Qingwei

2015-12-01

Full Text Available The stayed cables are key stress components of large offshore bridge. The fault detection of stayed cable is very important for safe of large offshore bridge. A particle filter model and algorithm of nonlinear vibration signal are used in this paper. Firstly, the particle filter model of stayed cable of large offshore bridge is created. Nonlinear dynamic model of the stayed-cable and beam coupling system is dispersed in temporal dimension by using the finite difference method. The discrete nonlinear vibration equations of any cable element are worked out. Secondly, a state equation of particle filter is fitted by least square algorithm from the discrete nonlinear vibration equations. So the particle filter algorithm can use the accurate state equations. Finally, the particle filter algorithm is used to filter the vibration signal of bridge stayed cable. According to the particle filter, the de-noised vibration signal can be tracked and be predicted for a short time accurately. Many experiments are done at some actual bridges. The simulation experiments and the actual experiments on the bridge stayed cables are all indicating that the particle filter algorithm in this paper has good performance and works stably.

L V G Rao

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science. L V G Rao. Articles written in Journal of Earth System Science. Volume 109 Issue 2 June 2000 pp 255-265. Thermohaline structure and circulation in the upper layers of the southern Bay of Bengal during BOBMEX-Pilot (October — November 1998) · V Ramesh Babu V S N ...

Development of particle filters for ships; Udvikling af partikelfiltre til skibe

Energy Technology Data Exchange (ETDEWEB)

Jakobsen, O.; Norre Holm, J.; Koecks, M. [Teknologisk Institut, Aarhus (Denmark)

2013-04-01

The project has resulted in a solution with a well-functioning maritime particle filter which reduces the particle emission significantly. The visible smoke from the vessels funnel, which typically is seen while manoeuvring in the harbour, is also reduced to a minimum. The system is constructed in such a way that the exhaust gases can be bypassed around the filter unit, in this situation to ensure the engines operation in case of filter clogging. The system has been provided with safety functions to prevent an excessive exhaust gas back-pressure and there are fitted remote controlled exhaust valves. Some of the challenges in the project have been the requirement from the engine manufacturer of keeping a low turbocharger back-pressure, besides the space conditions aboard the test vessel and the achievement of sufficient temperatures for regeneration of the particle filter. To oppose the requirement of low exhaust gas back-pressure, the filter housing was designed with space for twice as many monoliths as originally planned. In the funnel casing the original installations were removed to make space for the filter housing, and the system was enlarged with electrically controlled exhaust valves to improve the daily operation of the crew. The regeneration issue was solved by mounting electric automatically controlled heating elements in the filter housing and by an ash exhaust system. Regeneration is carried out by the crew when the vessel lies in harbour in the evening after the last tour of the day. Before mounting the particle filter, measurements were carried out aboard, showing a compound of particle emissions with an expected high NO{sub x}-level of 8.33 g/kW, whereas the other emissions were lower than expected at first. Especially HC and CO were very low, but also the particle mass (PM) had a relatively low value of 0.22 g/kWh. After commissioning the particle filter, a significant reduction of 93% of the particle number (N) was observed. A reduction in N was

Non-Pilot-Aided Sequential Monte Carlo Method to Joint Signal, Phase Noise, and Frequency Offset Estimation in Multicarrier Systems

Directory of Open Access Journals (Sweden)

Christelle Garnier

2008-05-01

Full Text Available We address the problem of phase noise (PHN and carrier frequency offset (CFO mitigation in multicarrier receivers. In multicarrier systems, phase distortions cause two effects: the common phase error (CPE and the intercarrier interference (ICI which severely degrade the accuracy of the symbol detection stage. Here, we propose a non-pilot-aided scheme to jointly estimate PHN, CFO, and multicarrier signal in time domain. Unlike existing methods, non-pilot-based estimation is performed without any decision-directed scheme. Our approach to the problem is based on Bayesian estimation using sequential Monte Carlo filtering commonly referred to as particle filtering. The particle filter is efficiently implemented by combining the principles of the Rao-Blackwellization technique and an approximate optimal importance function for phase distortion sampling. Moreover, in order to fully benefit from time-domain processing, we propose a multicarrier signal model which includes the redundancy information induced by the cyclic prefix, thus leading to a significant performance improvement. Simulation results are provided in terms of bit error rate (BER and mean square error (MSE to illustrate the efficiency and the robustness of the proposed algorithm.

Prof. Bookinkere Channakeshavaiah Subba Rao

Indian Academy of Sciences (India)

Annual Meetings · Mid Year Meetings · Discussion Meetings · Public Lectures · Lecture Workshops · Refresher Courses · Symposia · Live Streaming. Home; Fellowship. Fellow Profile. Elected: 1975 Section: Chemistry. Subba Rao, Prof. Bookinkere Channakeshavaiah Ph.D. (Purdue). Date of birth: 8 December 1923

Analysis of sensor impulse response effects on Cramèr–Rao lower bounds for signal parameter estimators

Directory of Open Access Journals (Sweden)

Ephraim S. Gower

2014-12-01

Full Text Available In this study, a generic analysis of sensor impulse response effects on linearly filtered channel noise is presented to illustrate the resulting variations to the Cramèr–Rao lower bounds (CRLBs of signal parameter estimators in signal processing and communication applications. The authors start by deriving the density function of a filtered signal, which is shown to be a mixture density, and hence the exact expressions for the mean and variance. Simulation results are used to confirm the derivations, which are then used to investigate the effects of impulse response length and variance, as well as channel noise length and variance effects on the resulting CRLBs. Results indicate that for non-zero-mean channel noise and impulse responses, the resulting mean of filtered noise can be relatively large causing adverse deviations to parameter estimations. The filtered noise variance is shown to be proportional to the impulse response energy, where for long duration of signal capture the CRLB is significantly increased.

ASME AG-1 Section FC Qualified HEPA Filters; a Particle Loading Comparison - 13435

International Nuclear Information System (INIS)

Stillo, Andrew; Ricketts, Craig I.

2013-01-01

High Efficiency Particulate Air (HEPA) Filters used to protect personnel, the public and the environment from airborne radioactive materials are designed, manufactured and qualified in accordance with ASME AG-1 Code section FC (HEPA Filters) [1]. The qualification process requires that filters manufactured in accordance with this ASME AG-1 code section must meet several performance requirements. These requirements include performance specifications for resistance to airflow, aerosol penetration, resistance to rough handling, resistance to pressure (includes high humidity and water droplet exposure), resistance to heated air, spot flame resistance and a visual/dimensional inspection. None of these requirements evaluate the particle loading capacity of a HEPA filter design. Concerns, over the particle loading capacity, of the different designs included within the ASME AG-1 section FC code[1], have been voiced in the recent past. Additionally, the ability of a filter to maintain its integrity, if subjected to severe operating conditions such as elevated relative humidity, fog conditions or elevated temperature, after loading in use over long service intervals is also a major concern. Although currently qualified HEPA filter media are likely to have similar loading characteristics when evaluated independently, filter pleat geometry can have a significant impact on the in-situ particle loading capacity of filter packs. Aerosol particle characteristics, such as size and composition, may also have a significant impact on filter loading capacity. Test results comparing filter loading capacities for three different aerosol particles and three different filter pack configurations are reviewed. The information presented represents an empirical performance comparison among the filter designs tested. The results may serve as a basis for further discussion toward the possible development of a particle loading test to be included in the qualification requirements of ASME AG-1

ASME AG-1 Section FC Qualified HEPA Filters; a Particle Loading Comparison - 13435

Energy Technology Data Exchange (ETDEWEB)

Stillo, Andrew [Camfil Farr, 1 North Corporate Drive, Riverdale, NJ 07457 (United States); Ricketts, Craig I. [New Mexico State University, Department of Engineering Technology and Surveying Engineering, P.O. Box 30001 MSC 3566, Las Cruces, NM 88003-8001 (United States)

2013-07-01

High Efficiency Particulate Air (HEPA) Filters used to protect personnel, the public and the environment from airborne radioactive materials are designed, manufactured and qualified in accordance with ASME AG-1 Code section FC (HEPA Filters) [1]. The qualification process requires that filters manufactured in accordance with this ASME AG-1 code section must meet several performance requirements. These requirements include performance specifications for resistance to airflow, aerosol penetration, resistance to rough handling, resistance to pressure (includes high humidity and water droplet exposure), resistance to heated air, spot flame resistance and a visual/dimensional inspection. None of these requirements evaluate the particle loading capacity of a HEPA filter design. Concerns, over the particle loading capacity, of the different designs included within the ASME AG-1 section FC code[1], have been voiced in the recent past. Additionally, the ability of a filter to maintain its integrity, if subjected to severe operating conditions such as elevated relative humidity, fog conditions or elevated temperature, after loading in use over long service intervals is also a major concern. Although currently qualified HEPA filter media are likely to have similar loading characteristics when evaluated independently, filter pleat geometry can have a significant impact on the in-situ particle loading capacity of filter packs. Aerosol particle characteristics, such as size and composition, may also have a significant impact on filter loading capacity. Test results comparing filter loading capacities for three different aerosol particles and three different filter pack configurations are reviewed. The information presented represents an empirical performance comparison among the filter designs tested. The results may serve as a basis for further discussion toward the possible development of a particle loading test to be included in the qualification requirements of ASME AG-1

Marginalized Particle Filtering Framework for Tuning of Ensemble Filters

Czech Academy of Sciences Publication Activity Database

Šmídl, Václav; Hofman, Radek

2011-01-01

Roč. 139, č. 11 (2011), s. 3589-3599 ISSN 0027-0644 R&D Projects: GA MV VG20102013018; GA ČR GP102/08/P250 Institutional research plan: CEZ:AV0Z10750506 Keywords : ensemble finter * marginalized particle filter * data assimilation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.688, year: 2011 http://library.utia.cas.cz/separaty/2011/AS/smidl-0367533.pdf

Particle loading rates for HVAC filters, heat exchangers, and ducts.

Science.gov (United States)

Waring, M S; Siegel, J A

2008-06-01

The rate at which airborne particulate matter deposits onto heating, ventilation, and air-conditioning (HVAC) components is important from both indoor air quality (IAQ) and energy perspectives. This modeling study predicts size-resolved particle mass loading rates for residential and commercial filters, heat exchangers (i.e. coils), and supply and return ducts. A parametric analysis evaluated the impact of different outdoor particle distributions, indoor emission sources, HVAC airflows, filtration efficiencies, coils, and duct system complexities. The median predicted residential and commercial loading rates were 2.97 and 130 g/m(2) month for the filter loading rates, 0.756 and 4.35 g/m(2) month for the coil loading rates, 0.0051 and 1.00 g/month for the supply duct loading rates, and 0.262 g/month for the commercial return duct loading rates. Loading rates are more dependent on outdoor particle distributions, indoor sources, HVAC operation strategy, and filtration than other considered parameters. The results presented herein, once validated, can be used to estimate filter changing and coil cleaning schedules, energy implications of filter and coil loading, and IAQ impacts associated with deposited particles. The results in this paper suggest important factors that lead to particle deposition on HVAC components in residential and commercial buildings. This knowledge informs the development and comparison of control strategies to limit particle deposition. The predicted mass loading rates allow for the assessment of pressure drop and indoor air quality consequences that result from particle mass loading onto HVAC system components.

Dynamics of particle loading in deep-bed filter. Transport, deposition and reentrainment

Directory of Open Access Journals (Sweden)

Przekop Rafał

2016-09-01

Full Text Available Deep bed filtration is an effective method of submicron and micron particle removal from the fluid stream. There is an extensive body of literature regarding particle deposition in filters, often using the classical continuum approach. However, the approach is not convenient for studying the influence of particle deposition on filter performance (filtration efficiency, pressure drop when non-steady state boundary conditions have to be introduced. For the purposes of this work the lattice-Boltzmann model describes fluid dynamics, while the solid particle motion is modeled by the Brownian dynamics. For aggregates the effect of their structure on displacement is taken into account. The possibility of particles rebound from the surface of collector or reentrainment of deposits to fluid stream is calculated by energy balanced oscillatory model derived from adhesion theory. The results show the evolution of filtration efficiency and pressure drop of filters with different internal structure described by the size of pores. The size of resuspended aggregates and volume distribution of deposits in filter were also analyzed. The model enables prediction of dynamic filter behavior. It can be a very useful tool for designing filter structures which optimize maximum lifetime with the acceptable values of filtration efficiency and pressure drop.

Gaussian particle filter based pose and motion estimation

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

Fish tracking by combining motion based segmentation and particle filtering

Science.gov (United States)

Bichot, E.; Mascarilla, L.; Courtellemont, P.

2006-01-01

In this paper, we suggest a new importance sampling scheme to improve a particle filtering based tracking process. This scheme relies on exploitation of motion segmentation. More precisely, we propagate hypotheses from particle filtering to blobs of similar motion to target. Hence, search is driven toward regions of interest in the state space and prediction is more accurate. We also propose to exploit segmentation to update target model. Once the moving target has been identified, a representative model is learnt from its spatial support. We refer to this model in the correction step of the tracking process. The importance sampling scheme and the strategy to update target model improve the performance of particle filtering in complex situations of occlusions compared to a simple Bootstrap approach as shown by our experiments on real fish tank sequences.

A nested sampling particle filter for nonlinear data assimilation

KAUST Repository

Elsheikh, Ahmed H.; Hoteit, Ibrahim; Wheeler, Mary Fanett

2014-01-01

. The proposed nested sampling particle filter (NSPF) iteratively builds the posterior distribution by applying a constrained sampling from the prior distribution to obtain particles in high-likelihood regions of the search space, resulting in a reduction

A novel permanently magnetised high gradient magnetic filter using assisted capture for fine particles

Energy Technology Data Exchange (ETDEWEB)

Watson, J.H.P. [Univ. of Southampton (United Kingdom)

1995-02-01

This paper describes the structure and properties of a novel permanently magnetised magnetic filter for fine friable radioactive material. Previously a filter was described and tested. This filter was designed so that the holes in the filter are left open as capture proceeds which means the pressure drop builds up only slowly. This filter is not suitable for friable composite particles which can be broken by mechanical forces. The structure of magnetic part of the second filter has been changed so as to strongly capture particles composed of fine particles weakly bound together which tend to break when captured. This uses a principle of assisted-capture in which coarse particles aid the capture of the fine fragments. The technique has the unfortunate consequence that the pressure drop across the filter rises faster as capture capture proceeds than the filter described previously. These filters have the following characteristics: (1) No external magnet is required. (2) No external power is required. (3) Small is size and portable. (4) Easily interchangeable. (5) Can be cleaned without demagnetising.

Evaluation of the effect of media velocity on filter efficiency and most penetrating particle size of nuclear grade high-efficiency particulate air filters.

Science.gov (United States)

Alderman, Steven L; Parsons, Michael S; Hogancamp, Kristina U; Waggoner, Charles A

2008-11-01

High-efficiency particulate air (HEPA) filters are widely used to control particulate matter emissions from processes that involve management or treatment of radioactive materials. Section FC of the American Society of Mechanical Engineers AG-1 Code on Nuclear Air and Gas Treatment currently restricts media velocity to a maximum of 2.5 cm/sec in any application where this standard is invoked. There is some desire to eliminate or increase this media velocity limit. A concern is that increasing media velocity will result in higher emissions of ultrafine particles; thus, it is unlikely that higher media velocities will be allowed without data to demonstrate the effect of media velocity on removal of ultrafine particles. In this study, the performance of nuclear grade HEPA filters, with respect to filter efficiency and most penetrating particle size, was evaluated as a function of media velocity. Deep-pleat nuclear grade HEPA filters (31 cm x 31 cm x 29 cm) were evaluated at media velocities ranging from 2.0 to 4.5 cm/sec using a potassium chloride aerosol challenge having a particle size distribution centered near the HEPA filter most penetrating particle size. Filters were challenged under two distinct mass loading rate regimes through the use of or exclusion of a 3 microm aerodynamic diameter cut point cyclone. Filter efficiency and most penetrating particle size measurements were made throughout the duration of filter testing. Filter efficiency measured at the onset of aerosol challenge was noted to decrease with increasing media velocity, with values ranging from 99.999 to 99.977%. The filter most penetrating particle size recorded at the onset of testing was noted to decrease slightly as media velocity was increased and was typically in the range of 110-130 nm. Although additional testing is needed, these findings indicate that filters operating at media velocities up to 4.5 cm/sec will meet or exceed current filter efficiency requirements. Additionally

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

Science.gov (United States)

2014-08-24

gossip procedure to arrive at a consensus about the likelihoods of particles. The selective gossip procedure shares particles based upon weights. This...focuses commu- nication on the particles that contain the most informa- tion. Oreshkin and Coates (2010) also use a gossip con- sensus approach to...Applied Probability. Chapman and Hall. Üstebay, D., Coates, M., and Rabbat, M. (2011). Dis- tributed auxiliary particle filters using selective gossip . In

Particle filters for object tracking: enhanced algorithm and efficient implementations

International Nuclear Information System (INIS)

Abd El-Halym, H.A.

2010-01-01

Object tracking and recognition is a hot research topic. In spite of the extensive research efforts expended, the development of a robust and efficient object tracking algorithm remains unsolved due to the inherent difficulty of the tracking problem. Particle filters (PFs) were recently introduced as a powerful, post-Kalman filter, estimation tool that provides a general framework for estimation of nonlinear/ non-Gaussian dynamic systems. Particle filters were advanced for building robust object trackers capable of operation under severe conditions (small image size, noisy background, occlusions, fast object maneuvers ..etc.). The heavy computational load of the particle filter remains a major obstacle towards its wide use.In this thesis, an Excitation Particle Filter (EPF) is introduced for object tracking. A new likelihood model is proposed. It depends on multiple functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modified the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. This modification is based on re-exciting the particles if their weights fall below a memorized weight value. The proposed enhanced PF is implemented in software and evaluated. Its results are compared with a single likelihood function PF tracker, Particle Swarm Optimization (PSO) tracker, a correlation tracker, as well as, an edge tracker. The experimental results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness, and occlusion compared with other methods Efficient novel hardware architectures of the Sample Important Re sample Filter (SIRF) and the EPF are implemented. Three novel hardware architectures of the SIRF for object tracking are introduced. The first architecture is a two-step sequential PF machine, where particle generation, weight calculation and normalization are carried out in parallel during the first step followed by a sequential re

Particle filtering with path sampling and an application to a bimodal ocean current model

International Nuclear Information System (INIS)

Weare, Jonathan

2009-01-01

This paper introduces a recursive particle filtering algorithm designed to filter high dimensional systems with complicated non-linear and non-Gaussian effects. The method incorporates a parallel marginalization (PMMC) step in conjunction with the hybrid Monte Carlo (HMC) scheme to improve samples generated by standard particle filters. Parallel marginalization is an efficient Markov chain Monte Carlo (MCMC) strategy that uses lower dimensional approximate marginal distributions of the target distribution to accelerate equilibration. As a validation the algorithm is tested on a 2516 dimensional, bimodal, stochastic model motivated by the Kuroshio current that runs along the Japanese coast. The results of this test indicate that the method is an attractive alternative for problems that require the generality of a particle filter but have been inaccessible due to the limitations of standard particle filtering strategies.

Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

Directory of Open Access Journals (Sweden)

Jing Liu

2012-01-01

Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.

Science.gov (United States)

Florin, Charles; Paragios, Nikos; Williams, Jim

2005-01-01

In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.

A hand tracking algorithm with particle filter and improved GVF snake model

Science.gov (United States)

Sun, Yi-qi; Wu, Ai-guo; Dong, Na; Shao, Yi-zhe

2017-07-01

To solve the problem that the accurate information of hand cannot be obtained by particle filter, a hand tracking algorithm based on particle filter combined with skin-color adaptive gradient vector flow (GVF) snake model is proposed. Adaptive GVF and skin color adaptive external guidance force are introduced to the traditional GVF snake model, guiding the curve to quickly converge to the deep concave region of hand contour and obtaining the complex hand contour accurately. This algorithm realizes a real-time correction of the particle filter parameters, avoiding the particle drift phenomenon. Experimental results show that the proposed algorithm can reduce the root mean square error of the hand tracking by 53%, and improve the accuracy of hand tracking in the case of complex and moving background, even with a large range of occlusion.

A nowcasting technique based on application of the particle filter blending algorithm

Science.gov (United States)

Chen, Yuanzhao; Lan, Hongping; Chen, Xunlai; Zhang, Wenhai

2017-10-01

To improve the accuracy of nowcasting, a new extrapolation technique called particle filter blending was configured in this study and applied to experimental nowcasting. Radar echo extrapolation was performed by using the radar mosaic at an altitude of 2.5 km obtained from the radar images of 12 S-band radars in Guangdong Province, China. The first bilateral filter was applied in the quality control of the radar data; an optical flow method based on the Lucas-Kanade algorithm and the Harris corner detection algorithm were used to track radar echoes and retrieve the echo motion vectors; then, the motion vectors were blended with the particle filter blending algorithm to estimate the optimal motion vector of the true echo motions; finally, semi-Lagrangian extrapolation was used for radar echo extrapolation based on the obtained motion vector field. A comparative study of the extrapolated forecasts of four precipitation events in 2016 in Guangdong was conducted. The results indicate that the particle filter blending algorithm could realistically reproduce the spatial pattern, echo intensity, and echo location at 30- and 60-min forecast lead times. The forecasts agreed well with observations, and the results were of operational significance. Quantitative evaluation of the forecasts indicates that the particle filter blending algorithm performed better than the cross-correlation method and the optical flow method. Therefore, the particle filter blending method is proved to be superior to the traditional forecasting methods and it can be used to enhance the ability of nowcasting in operational weather forecasts.

Particle Kalman Filtering: A Nonlinear Framework for Ensemble Kalman Filters

KAUST Repository

Hoteit, Ibrahim; Luo, Xiaodong; Pham, Dinh-Tuan; Moroz, Irene M.

2010-01-01

In this contribution, we present a Gaussian mixture‐based framework, called the particle Kalman filter (PKF), and discuss how the different EnKF methods can be derived as simplified variants of the PKF. We also discuss approaches to reducing the computational burden of the PKF in order to make it suitable for complex geosciences applications. We use the strongly nonlinear Lorenz‐96 model to illustrate the performance of the PKF.

Efficacy of patient skin dose reduction by a compensating filter through of irradiation field overlaps on the area during percutaneous coronary intervention

International Nuclear Information System (INIS)

Yamasaki, Hiroyuki; Yamaguchi, Sadao; Yamamoto, Naomi; Miyagawa, Takashi; Hirose, Etsuko; Takenaka, Tatsuaki; Nakahara, Makoto

2011-01-01

Our study was involved with entrance surface dose reduction and irradiation field by the filter use of PCI, and insertion in place of an effective compensating filter to maximize entrance surface dose reduction, which we verified. The radiation dosimetry put a 6 cc ion chamber on the back side of the thorax phantom, and changed the filter of the four corners (a: upper left, b: upper right, c: lower right, d: lower left) of the monitor confirmed with fluoroscopy [(0) no filter, (1) one filter, (2) two filters]. The angle of C arm was assumed to be eight directions and 0 degrees adopted by this hospital. It was compared with a corrective rate of which one was no filter. Next, the presence of filter and irradiation field overlaps on the area in monitor in the angle of C arm was verified by this hospital's classic example. As for corrective rate, (1) becomes 0.41 and (2) become 0.25 at fluoroscopy, (1) becomes 0.26 and (2) become 0.16 at exposure. Irradiation field overlaps on the area (+) compensating filter (-) was many with d of right anterior oblique (RAO)/cranial (CAU), a of RAO and c of CAU at left coronary angiography (CAG), c of left anterior oblique (LAO) at right CAG, b of LAO/cranial (CRA) (left CAG), b of CRA (right CAG) and a and d of RAO (right CAG) at both CAG. Irradiation field overlaps on the area (+) compensating filter (+) was many with b of CRA at left CAG, a of LAO/CRA at right CAG, b of CRA (left CAG) and b of RAO (right CAG) at both CAG. When the compensating filter is used the entrance surface dose reduction effect was great. If automatic exposure control protects the part of irradiation field overlaps on the area in the range without operating excessively, the radiological risk can be reduced, and it is conceivable as useful clinical setting. (author)

Fast Erasure and Error decoding of Algebraic Geometry Codes up to the Feng-Rao Bound

DEFF Research Database (Denmark)

Jensen, Helge Elbrønd; Sakata, S.; Leonard, D.

1996-01-01

This paper gives an errata(that is erasure-and error-) decoding algorithm of one-point algebraic geometry codes up to the Feng-Rao designed minimum distance using Sakata's multidimensional generalization of the Berlekamp-massey algorithm and the votin procedure of Feng and Rao.......This paper gives an errata(that is erasure-and error-) decoding algorithm of one-point algebraic geometry codes up to the Feng-Rao designed minimum distance using Sakata's multidimensional generalization of the Berlekamp-massey algorithm and the votin procedure of Feng and Rao....

Particle size for greatest penetration of HEPA filters - and their true efficiency

International Nuclear Information System (INIS)

da Roza, R.A.

1982-01-01

The particle size that most greatly penetrates a filter is a function of filter media construction, aerosol density, and air velocity. In this paper the published results of several experiments are compared with a modern filtration theory that predicts single-fiber efficiency and the particle size of maximum penetration. For high-efficiency particulate air (HEPA) filters used under design conditions this size is calculated to be 0.21 μm diam. This is in good agreement with the experimental data. The penetration at 0.21 μm is calculated to be seven times greater than at the 0.3 μm used for testing HEPA filters. Several mechanisms by which filters may have a lower efficiency in use than when tested are discussed

Experimental investigation of the effect of inlet particle properties on the capture efficiency in an exhaust particulate filter

Energy Technology Data Exchange (ETDEWEB)

Viswanathan, Sandeep; Rothamer, David; Zelenyuk, Alla; Stewart, Mark; Bell, David

2017-11-01

The impact of inlet particle properties on the filtration performance of clean and particulate matter (PM) laden cordierite filter samples was evaluated using PM generated by a spark-ignition direct-injection (SIDI) engine fuelled with tier II EEE certification gasoline. Prior to the filtration experiments, a scanning mobility particle spectrometer (SMPS) was used to measure the electrical-mobility based particle size distribution (PSD) in the SIDI exhaust from distinct engine operating conditions. An advanced aerosol characterization system that comprised of a centrifugal particle mass analyser (CPMA), a differential mobility analyser (DMA), and a single particle mass spectrometer (SPLAT II) was used to obtain additional information on the SIDI particulate, including particle composition, mass, and dynamic shape factors (DSFs) in the transition () and free-molecular () flow regimes. During the filtration experiments, real-time measurements of PSDs upstream and downstream of the filter sample were used to estimate the filtration performance and the total trapped mass within the filter using an integrated particle size distribution method. The filter loading process was paused multiple times to evaluate the filtration performance in the partially loaded state. The change in vacuum aerodynamic diameter () distribution of mass-selected particles was examined for flow through the filter to identify whether preferential capture of particles of certain shapes occurred in the filter. The filter was also probed using different inlet PSDs to understand their impact on particle capture within the filter sample. Results from the filtration experiment suggest that pausing the filter loading process and subsequently performing the filter probing experiments did not impact the overall evolution of filtration performance. Within the present distribution of particle sizes, filter efficiency was independent of particle shape potentially due to the diffusion-dominant filtration

An efficient multiple particle filter based on the variational Bayesian approach

KAUST Repository

Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

2015-01-01

) approach to propose a new MPF, the VBMPF. The proposed filter is computationally more efficient since the propagation of each particle requires generating one (new) particle only, while in the standard MPFs a set of (children) particles needs

Noncommutative Blackwell-Ross martingale inequality

Science.gov (United States)

Talebi, Ali; Moslehian, Mohammad Sal; Sadeghi, Ghadir

We establish a noncommutative Blackwell-Ross inequality for supermartingales under a suitable condition which generalizes Khan’s work to the noncommutative setting. We then employ it to deduce an Azuma-type inequality.

Computing the Feng-Rao distances for codes from order domains

DEFF Research Database (Denmark)

Ruano Benito, Diego

2007-01-01

We compute the Feng–Rao distance of a code coming from an order domain with a simplicial value semigroup. The main tool is the Apéry set of a semigroup that can be computed using a Gröbner basis.......We compute the Feng–Rao distance of a code coming from an order domain with a simplicial value semigroup. The main tool is the Apéry set of a semigroup that can be computed using a Gröbner basis....

Hybrid three-dimensional variation and particle filtering for nonlinear systems

International Nuclear Information System (INIS)

Leng Hong-Ze; Song Jun-Qiang

2013-01-01

This work addresses the problem of estimating the states of nonlinear dynamic systems with sparse observations. We present a hybrid three-dimensional variation (3DVar) and particle piltering (PF) method, which combines the advantages of 3DVar and particle-based filters. By minimizing the cost function, this approach will produce a better proposal distribution of the state. Afterwards the stochastic resampling step in standard PF can be avoided through a deterministic scheme. The simulation results show that the performance of the new method is superior to the traditional ensemble Kalman filtering (EnKF) and the standard PF, especially in highly nonlinear systems

Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

Directory of Open Access Journals (Sweden)

Michael Rudzsky

2008-01-01

Full Text Available We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.

Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter

Science.gov (United States)

Sindelar, Charles V.; Grigorieff, Nikolaus

2012-01-01

The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the “single-particle Wiener filter”) to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation. PMID:22613568

An improved analytic solution for analysis of particle trajectories in fibrous, two-dimensional filters

International Nuclear Information System (INIS)

Marshall, H.; Sahraoui, M.; Kaviany, M.

1994-01-01

The Kuwabara solution for creeping fluid flow through periodic arrangement of cylinders is widely used in analytic and numerical studies of fibrous filters. Numerical solutions have shown that the Kuwabara solution has systematic errors, and when used for the particle trajectories in filters it results in some error in the predicted filter efficiency. The numerical solutions, although accurate, preclude further analytic treatments, and are not as compact and convenient to use as the Kuwabara solution. By reexamining the outer boundary conditions of the Kuwabara solution, a correction term to the Kuwabara solution has been derived to obtain an extended solution that is more accurate and improves prediction of the filter efficiency. By comparison with the numerical solutions, it is shown that the Kuwabara solution is the high porosity asymptote, and that the extended solution has an improved porosity dependence. A rectification is explained that can make particle collection less efficient for periodic, in-line arrangements of fibers with particle diffusion or body force. This rectification also results in the alignment of particles with inertia (i.e., high Stokes number particles)

Research on the method of information system risk state estimation based on clustering particle filter

Directory of Open Access Journals (Sweden)

Cui Jia

2017-05-01

Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

Research on the method of information system risk state estimation based on clustering particle filter

Science.gov (United States)

Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

2017-05-01

With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

Science.gov (United States)

Uzunoglu, B.; Hussaini, Y.

2017-12-01

Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa

2017-12-11

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters\\' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters\\' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters\\' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles\\' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

An Efficient State–Parameter Filtering Scheme Combining Ensemble Kalman and Particle Filters

KAUST Repository

Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim

2017-01-01

This work addresses the state-parameter filtering problem for dynamical systems with relatively large-dimensional state and low-dimensional parameters' vector. A Bayesian filtering algorithm combining the strengths of the particle filter (PF) and the ensemble Kalman filter (EnKF) is proposed. At each assimilation cycle of the proposed EnKF-PF, the PF is first used to sample the parameters' ensemble followed by the EnKF to compute the state ensemble conditional on the resulting parameters' ensemble. The proposed scheme is expected to be more efficient than the traditional state augmentation techniques, which suffer from the curse of dimensionality and inconsistency that is particularly pronounced when the state is a strongly nonlinear function of the parameters. In the new scheme, the EnKF and PF interact via their ensembles' members, in contrast with the recently introduced two-stage EnKF-PF (TS-EnKF-PF), which exchanges point estimates between EnKF and PF while requiring almost double the computational load. Numerical experiments are conducted with the Lorenz-96 model to assess the behavior of the proposed filter and to evaluate its performances against the joint PF, joint EnKF, and TS-EnKF-PF. Numerical results suggest that the EnKF-PF performs best in all tested scenarios. It was further found to be more robust, successfully estimating both state and parameters in different sensitivity experiments.

Particle Filter for Fault Diagnosis and Robust Navigation of Underwater Robot

DEFF Research Database (Denmark)

Zhao, Bo; Skjetne, Roger; Blanke, Mogens

2014-01-01

A particle filter based robust navigation with fault diagnosis is designed for an underwater robot, where 10 failure modes of sensors and thrusters are considered. The nominal underwater robot and its anomaly are described by a switchingmode hidden Markov model. By extensively running a particle...... filter on the model, the fault diagnosis and robust navigation are achieved. Closed-loop full-scale experimental results show that the proposed method is robust, can diagnose faults effectively, and can provide good state estimation even in cases where multiple faults occur. Comparing with other methods...

Model Adaptation for Prognostics in a Particle Filtering Framework

Data.gov (United States)

National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....

The Cramér-Rao Bounds and Sensor Selection for Nonlinear Systems with Uncertain Observations.

Science.gov (United States)

Wang, Zhiguo; Shen, Xiaojing; Wang, Ping; Zhu, Yunmin

2018-04-05

This paper considers the problems of the posterior Cramér-Rao bound and sensor selection for multi-sensor nonlinear systems with uncertain observations. In order to effectively overcome the difficulties caused by uncertainty, we investigate two methods to derive the posterior Cramér-Rao bound. The first method is based on the recursive formula of the Cramér-Rao bound and the Gaussian mixture model. Nevertheless, it needs to compute a complex integral based on the joint probability density function of the sensor measurements and the target state. The computation burden of this method is relatively high, especially in large sensor networks. Inspired by the idea of the expectation maximization algorithm, the second method is to introduce some 0-1 latent variables to deal with the Gaussian mixture model. Since the regular condition of the posterior Cramér-Rao bound is unsatisfied for the discrete uncertain system, we use some continuous variables to approximate the discrete latent variables. Then, a new Cramér-Rao bound can be achieved by a limiting process of the Cramér-Rao bound of the continuous system. It avoids the complex integral, which can reduce the computation burden. Based on the new posterior Cramér-Rao bound, the optimal solution of the sensor selection problem can be derived analytically. Thus, it can be used to deal with the sensor selection of a large-scale sensor networks. Two typical numerical examples verify the effectiveness of the proposed methods.

A New Class of Particle Filters for Random Dynamic Systems with Unknown Statistics

Directory of Open Access Journals (Sweden)

Joaquín Míguez

2004-11-01

Full Text Available In recent years, particle filtering has become a powerful tool for tracking signals and time-varying parameters of random dynamic systems. These methods require a mathematical representation of the dynamics of the system evolution, together with assumptions of probabilistic models. In this paper, we present a new class of particle filtering methods that do not assume explicit mathematical forms of the probability distributions of the noise in the system. As a consequence, the proposed techniques are simpler, more robust, and more flexible than standard particle filters. Apart from the theoretical development of specific methods in the new class, we provide computer simulation results that demonstrate the performance of the algorithms in the problem of autonomous positioning of a vehicle in a 2-dimensional space.

Signal reconstruction in wireless sensor networks based on a cubature Kalman particle filter

International Nuclear Information System (INIS)

Huang Jin-Wang; Feng Jiu-Chao

2014-01-01

For solving the issues of the signal reconstruction of nonlinear non-Gaussian signals in wireless sensor networks (WSNs), a new signal reconstruction algorithm based on a cubature Kalman particle filter (CKPF) is proposed in this paper. We model the reconstruction signal first and then use the CKPF to estimate the signal. The CKPF uses a cubature Kalman filter (CKF) to generate the importance proposal distribution of the particle filter and integrates the latest observation, which can approximate the true posterior distribution better. It can improve the estimation accuracy. CKPF uses fewer cubature points than the unscented Kalman particle filter (UKPF) and has less computational overheads. Meanwhile, CKPF uses the square root of the error covariance for iterating and is more stable and accurate than the UKPF counterpart. Simulation results show that the algorithm can reconstruct the observed signals quickly and effectively, at the same time consuming less computational time and with more accuracy than the method based on UKPF. (general)

Removal of virus to protozoan sized particles in point-of-use ceramic water filters.

Science.gov (United States)

Bielefeldt, Angela R; Kowalski, Kate; Schilling, Cherylynn; Schreier, Simon; Kohler, Amanda; Scott Summers, R

2010-03-01

The particle removal performance of point-of-use ceramic water filters (CWFs) was characterized in the size range of 0.02-100 microm using carboxylate-coated polystyrene fluorescent microspheres, natural particles and clay. Particles were spiked into dechlorinated tap water, and three successive water batches treated in each of six different CWFs. Particle removal generally increased with increasing size. The removal of virus-sized 0.02 and 0.1 microm spheres were highly variable between the six filters, ranging from 63 to 99.6%. For the 0.5 microm spheres removal was less variable and in the range of 95.1-99.6%, while for the 1, 2, 4.5, and 10 microm spheres removal was >99.6%. Recoating four of the CWFs with colloidal silver solution improved removal of the 0.02 microm spheres, but had no significant effects on the other particle sizes. Log removals of 1.8-3.2 were found for natural turbidity and spiked kaolin clay particles; however, particles as large as 95 microm were detected in filtered water. Copyright 2009 Elsevier Ltd. All rights reserved.

Bearings-Only Tracking of Manoeuvring Targets Using Particle Filters

Directory of Open Access Journals (Sweden)

M. Sanjeev Arulampalam

2004-11-01

Full Text Available We investigate the problem of bearings-only tracking of manoeuvring targets using particle filters (PFs. Three different (PFs are proposed for this problem which is formulated as a multiple model tracking problem in a jump Markov system (JMS framework. The proposed filters are (i multiple model PF (MMPF, (ii auxiliary MMPF (AUX-MMPF, and (iii jump Markov system PF (JMS-PF. The performance of these filters is compared with that of standard interacting multiple model (IMM-based trackers such as IMM-EKF and IMM-UKF for three separate cases: (i single-sensor case, (ii multisensor case, and (iii tracking with hard constraints. A conservative CRLB applicable for this problem is also derived and compared with the RMS error performance of the filters. The results confirm the superiority of the PFs for this difficult nonlinear tracking problem.

Quantitative cine-left ventriculography - Superiority of 45 .deg. RAO view to straight AB view -

International Nuclear Information System (INIS)

Lim, Tae Hwan; Han, Man Chung

1981-01-01

The volumetry by cineangiocardiography is known to have the most diagnostic and prognostic value in the evaluation of various valvular heart diseases and ischemic heart diseases. Although many authors favor the area-length method for the volumetry of left ventricle, 45 .deg. RAO projection seems to be more simple, inexpensive and accurate technique, considering the positional relationship of cardiac valves and obliquity of the long axis of left ventricle within the chest cage. Authors present the anatomical, geometrical and radiological basis for the superiority of 45 .deg. RAO protection by analyzing 20 normal heart specimen and 115 cineangiocardiograms of valvular heart diseases, and the results as follows: 1. Blood flow and motility of the mitral and aortic valves can be more clearly demonstrated by 45 .deg. RAO projection than by AP view. 2. The long diameter of left ventricular silhouette made 45 .deg. RAO projection reflects 90% or more of real diameter. 3. In RAO 45 .deg. position, patient's left nipple is optimal and convenient level for the ruler offering accurate magnification coefficient of left ventricle. 4. Ejection fraction after the extrasystole is exaggerated regardless of the left ventricular function, so it is desirable to exclude the 2 or 3 beats after extrasystole

Validation of Underwater Sensor Package Using Feature Based SLAM

Directory of Open Access Journals (Sweden)

Christopher Cain

2016-03-01

Full Text Available Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.

Validation of Underwater Sensor Package Using Feature Based SLAM

Science.gov (United States)

Cain, Christopher; Leonessa, Alexander

2016-01-01

Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package. PMID:26999142

Microscopy with spatial filtering for sorting particles and monitoring subcellular morphology

Science.gov (United States)

Zheng, Jing-Yi; Qian, Zhen; Pasternack, Robert M.; Boustany, Nada N.

2009-02-01

Optical scatter imaging (OSI) was developed to non-invasively track real-time changes in particle morphology with submicron sensitivity in situ without exogenous labeling, cell fixing, or organelle isolation. For spherical particles, the intensity ratio of wide-to-narrow angle scatter (OSIR, Optical Scatter Image Ratio) was shown to decrease monotonically with diameter and agree with Mie theory. In living cells, we recently reported this technique is able to detect mitochondrial morphological alterations, which were mediated by the Bcl-xL transmembrane domain, and could not be observed by fluorescence or differential interference contrast images. Here we further extend the ability of morphology assessment by adopting a digital micromirror device (DMD) for Fourier filtering. When placed in the Fourier plane the DMD can be used to select scattering intensities at desired combination of scattering angles. We designed an optical filter bank consisting of Gabor-like filters with various scales and rotations based on Gabor filters, which have been widely used for localization of spatial and frequency information in digital images and texture analysis. Using a model system consisting of mixtures of polystyrene spheres and bacteria, we show how this system can be used to sort particles on a microscopic slide based on their size, orientation and aspect ratio. We are currently applying this technique to characterize the morphology of subcellular organelles to help understand fundamental biological processes.

The Particle Number Emission Characteristics of the Diesel Engine with a Catalytic Diesel Particle Filter

Directory of Open Access Journals (Sweden)

Li Jia Qiang

2016-01-01

Full Text Available Due to their adverse health effects and their abundance in urban areas, diesel exhaust ultrafine particles caused by the aftertreatment devices have been of great concern in the past years. An experiment of particles number emissions was carried out on a high-pressure, common rail diesel engine with catalytic diesel particle filter (CDPF to investigate the impact of CDPF on the number emission characteristics of particles. The results indicated that the conversion rates of CDPF is over 97%. The size distributions of particles are bimodal lognormal distributions downstream CDPF at 1400 r/min and 2300 r/min. CDPF has a lower conversion rates on the nucleation mode particles. The geometric number mean diameters of particles downstream CDPF is smaller than that upstream CDPF.

Kalman and particle filtering methods for full vehicle and tyre identification

Science.gov (United States)

Bogdanski, Karol; Best, Matthew C.

2018-05-01

This paper considers identification of all significant vehicle handling dynamics of a test vehicle, including identification of a combined-slip tyre model, using only those sensors currently available on most vehicle controller area network buses. Using an appropriately simple but efficient model structure, all of the independent parameters are found from test vehicle data, with the resulting model accuracy demonstrated on independent validation data. The paper extends previous work on augmented Kalman Filter state estimators to concentrate wholly on parameter identification. It also serves as a review of three alternative filtering methods; identifying forms of the unscented Kalman filter, extended Kalman filter and particle filter are proposed and compared for effectiveness, complexity and computational efficiency. All three filters are suited to applications of system identification and the Kalman Filters can also operate in real-time in on-line model predictive controllers or estimators.

Particle size distribution in effluent of trickling filters and in humus tanks.

Science.gov (United States)

Schubert, W; Günthert, F W

2001-11-01

Particles and aggregates from trickling filters must be eliminated from wastewater. Usually this happens through sedimentation in humus tanks. Investigations to characterize these solids by way of particle size measurements, image analysis and particle charge measurements (zeta potential) are made within the scope of Research Center for Science and Technology "Fundamentals of Aerobic biological wastewater treatment" (SFB 411). The particle size measuring results given within this report were obtained at the Ingolstadt wastewater treatment plant, Germany, which served as an example. They have been confirmed by similar results from other facilities. Particles flushed out from trickling filters will be partially destroyed on their way to the humus tank. A large amount of small particles is to be found there. On average 90% of the particles are smaller than 30 microm. Particle size plays a decisive role in the sedimentation behaviour of solids. Small particles need sedimentation times that cannot be provided in settling tanks. As a result they cause turbidity in the final effluent. Therefore quality of sewage discharge suffers, and there are hardly advantages of the fixed film reactor treatment compared to the activated sludge process regarding sedimentation behaviour.

Random set particle filter for bearings-only multitarget tracking

Science.gov (United States)

Vihola, Matti

2005-05-01

The random set approach to multitarget tracking is a theoretically sound framework that covers joint estimation of the number of targets and the state of the targets. This paper describes a particle filter implementation of the random set multitarget filter. The contribution of this paper to the random set tracking framework is the formulation of a measurement model where each sensor report is assumed to contain at most one measurement. The implemented filter was tested in synthetic bearings-only tracking scenarios containing up to two targets in the presence of false alarms and missed measurements. The estimated target state consisted of 2D position and velocity components. The filter was capable to track the targets fairly well despite of the missing measurements and the relatively high false alarm rates. In addition, the filter showed robustness against wrong parameter values of false alarm rates. The results that were obtained during the limited tests of the filter show that the random set framework has potential for challenging tracking situations. On the other hand, the computational burden of the described implementation is quite high and increases approximately linearly with respect to the expected number of targets.

Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

Institute of Scientific and Technical Information of China (English)

LI Shuo; TAO Ran

2006-01-01

We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.

Science.gov (United States)

Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng

2016-05-16

The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.

Filtration efficiency of an electrostatic fibrous filter: Studying filtration dependency on ultrafine particle exposure and composition

DEFF Research Database (Denmark)

Ardkapan, Siamak Rahimi; Johnson, Matthew S.; Yazdi, Sadegh

2014-01-01

The objective of the present study is to investigate the relationship between ultrafine particle concentrations and removal efficiencies for an electrostatic fibrous filter in a laboratory environment. Electrostatic fibrous filters capture particles efficiently, with a low pressure drop. Therefor...

Particle Filter-Based Target Tracking Algorithm for Magnetic Resonance-Guided Respiratory Compensation : Robustness and Accuracy Assessment

NARCIS (Netherlands)

Bourque, Alexandra E; Bedwani, Stéphane; Carrier, Jean-François; Ménard, Cynthia; Borman, Pim; Bos, Clemens; Raaymakers, Bas W; Mickevicius, Nikolai; Paulson, Eric; Tijssen, Rob H N

PURPOSE: To assess overall robustness and accuracy of a modified particle filter-based tracking algorithm for magnetic resonance (MR)-guided radiation therapy treatments. METHODS AND MATERIALS: An improved particle filter-based tracking algorithm was implemented, which used a normalized

Fast Erasure-and error decoding of algebraic geometry codes up to the Feng-Rao bound

DEFF Research Database (Denmark)

Høholdt, Tom; Jensen, Helge Elbrønd; Sakata, Shojiro

1998-01-01

This correspondence gives an errata (that is erasure-and error-) decoding algorithm of one-point algebraic-geometry codes up to the Feng-Rao designed minimum distance using Sakata's multidimensional generalization of the Berlekamp-Massey algorithm and the voting procedure of Feng and Rao....

An assessment of particle filtering methods and nudging for climate state reconstructions

NARCIS (Netherlands)

S. Dubinkina (Svetlana); H. Goosse

2013-01-01

htmlabstractUsing the climate model of intermediate complexity LOVECLIM in an idealized framework, we assess three data-assimilation methods for reconstructing the climate state. The methods are a nudging, a particle filter with sequential importance resampling, and a nudging proposal particle

Modelling of air flows in pleated filters and of their clogging by solid particles

International Nuclear Information System (INIS)

Del Fabbro, L.

2002-01-01

The devices of air cleaning against particles are widely spread in various branches of industry: nuclear, motor, food, electronic,...; among these devices, numerous are constituted by pleated porous media to increase the surface of filtration and thus to reduce the pressure drop, for given air flow. The objective of our work is to compensate a lack evident of knowledge on the evolution of the pressure drop of pleated filter during the clogging and to deduct a modelling from it, on the basis of experiments concerning industrial filters of nuclear and car types. The obtained model is a function of characteristics of the filtering medium and pleats, of the characteristics of solid particles deposited on the filter, of the mass of particles and of the aeraulic conditions of air flow. It also depends on data on the clogging of flat filters of equivalent medium. To elaborate this model of pressure drop, an initial stage was carried out in order to characterize, experimentally and numerically, the pressure drop and the distribution of air flow in clean pleated filters of nuclear (high efficiency particulate air filter, in fiberglasses) and car (mean efficiency filter, in fibers of cellulose) types. The numerical model allowed to understand the fundamental role played by the aeraulic resistance of the filtering medium. From an non-dimensional approach, we established a semi-empirical model of pressure drop for a clean pleated filter valid for both studied types of medium; this model is used of first base for the development of the final model of clogging. The study of the clogging of the filters showed the complexity of the phenomenon dependent mainly on a reduction of the surface of filtration. This observation brings us to propose a clogging of pleated filters in three phases. Both first phases are similar in those observed for flat filters, while last phase corresponds to a reduction of the surface of filtration and leads a strong increase of the filter pressure drop

Medical and radiological aspects of emergency preparedness and response at SevRAO facilities.

Science.gov (United States)

Savkin, M N; Sneve, M K; Grachev, M I; Frolov, G P; Shinkarev, S M; Jaworska, A

2008-12-01

Regulatory cooperation between the Norwegian Radiation Protection Authority and the Federal Medical Biological Agency (FMBA) of the Russian Federation has the overall goal of promoting improvements in radiation protection in Northwest Russia. One of the projects in this programme has the objectives to review and improve the existing medical emergency preparedness capabilities at the sites for temporary storage of spent nuclear fuel and radioactive waste. These are operated by SevRAO at Andreeva Bay and in Gremikha village on the Kola Peninsula. The work is also intended to provide a better basis for regulation of emergency response and medical emergency preparedness at similar facilities elsewhere in Russia. The purpose of this paper is to present the main results of that project, implemented by the Burnasyan Federal Medical Biophysical Centre. The first task was an analysis of the regulatory requirements and the current state of preparedness for medical emergency response at the SevRAO facilities. Although Russian regulatory documents are mostly consistent with international recommendations, some distinctions lead to numerical differences in operational intervention criteria under otherwise similar conditions. Radiological threats relating to possible accidents, and related gaps in the regulation of SevRAO facilities, were also identified. As part of the project, a special exercise on emergency medical response on-site at Andreeva Bay was prepared and carried out, and recommendations were proposed after the exercise. Following fruitful dialogue among regulators, designers and operators, special regulatory guidance has been issued by FMBA to account for the specific and unusual features of the SevRAO facilities. Detailed sections relate to the prevention of accidents, and emergency preparedness and response, supplementing the basic Russian regulatory requirements. Overall it is concluded that (a) the provision of medical and sanitary components of emergency

Modelling and measurement of wear particle flow in a dual oil filter system for condition monitoring

DEFF Research Database (Denmark)

Henneberg, Morten; Eriksen, René Lynge; Fich, Jens

2016-01-01

. The quantity of wear particles in gear oil is analysed with respect to system running conditions. It is shown that the model fits the data in terms of startup “particle burst” phenomenon, quasi-stationary conditions during operation, and clean-up filtration when placed out of operation. In order to establish...... boundary condition for particle burst phenomenon, the release of wear particles from a pleated mesh filter is measured in a test rig and included in the model. The findings show that a dual filter model, with startup phenomenon included, can describe trends in the wear particle flow observed in the gear...... particle generation is made possible by model parameter estimation and identification of an unintended lack of filter change. The model may also be used to optimise system and filtration performance, and to enable continuous condition monitoring....

An improved particle filter and its application to an INS/GPS integrated navigation system in a serious noisy scenario

International Nuclear Information System (INIS)

Wang, Xuemei; Ni, Wenbo

2016-01-01

For loosely coupled INS/GPS integrated navigation systems with low-cost and low-accuracy microelectromechanical device inertial sensors, in order to obtain enough accuracy, a full-state nonlinear dynamic model rather than a linearized error model is much more preferable. Particle filters are particularly for nonlinear and non-Gaussian situations, but typical bootstrap particle filters (BPFs) and some improved particle filters (IPFs) such as auxiliary particle filters (APFs) and Gaussian particle filters (GPFs) cannot solve the mismatch between the importance function and the likelihood function very well. The predicted particles propagated through inertial navigation equations cannot be scattered with certainty within the effective range of current observation when there are large drift errors of the inertial sensors. Therefore, the current observation cannot play the correction role well and these particle filters are invalid to some extent. The proposed IPF firstly estimates the corresponding state bias errors according to the current observation and then corrects the bias errors of the predicted particles before determining the weights and resampling the particles. Simulations and practical experiments both show that the proposed IPF can effectively solve the mismatch between the importance function and the likelihood function of a BPF and compensate the accumulated errors of INSs very well. It has great robustness in a serious noisy scenario. (paper)

Proposed hardware architectures of particle filter for object tracking

Science.gov (United States)

Abd El-Halym, Howida A.; Mahmoud, Imbaby Ismail; Habib, SED

2012-12-01

In this article, efficient hardware architectures for particle filter (PF) are presented. We propose three different architectures for Sequential Importance Resampling Filter (SIRF) implementation. The first architecture is a two-step sequential PF machine, where particle sampling, weight, and output calculations are carried out in parallel during the first step followed by sequential resampling in the second step. For the weight computation step, a piecewise linear function is used instead of the classical exponential function. This decreases the complexity of the architecture without degrading the results. The second architecture speeds up the resampling step via a parallel, rather than a serial, architecture. This second architecture targets a balance between hardware resources and the speed of operation. The third architecture implements the SIRF as a distributed PF composed of several processing elements and central unit. All the proposed architectures are captured using VHDL synthesized using Xilinx environment, and verified using the ModelSim simulator. Synthesis results confirmed the resource reduction and speed up advantages of our architectures.

Implicit particle filtering for equations with partial noise and application to geomagnetic data assimilation

Science.gov (United States)

Morzfeld, M.; Atkins, E.; Chorin, A. J.

2011-12-01

The task in data assimilation is to identify the state of a system from an uncertain model supplemented by a stream of incomplete and noisy data. The model is typically given in form of a discretization of an Ito stochastic differential equation (SDE), x(n+1) = R(x(n))+ G W(n), where x is an m-dimensional vector and n=0,1,2,.... The m-dimensional vector function R and the m x m matrix G depend on the SDE as well as on the discretization scheme, and W is an m-dimensional vector whose elements are independent standard normal variates. The data are y(n) = h(x(n))+QV(n) where h is a k-dimensional vector function, Q is a k x k matrix and V is a vector whose components are independent standard normal variates. One can use statistics of the conditional probability density (pdf) of the state given the observations, p(n+1)=p(x(n+1)|y(1), ... , y(n+1)), to identify the state x(n+1). Particle filters approximate p(n+1) by sequential Monte Carlo and rely on the recursive formulation of the target pdf, p(n+1)∝p(x(n+1)|x(n)) p(y(n+1)|x(n+1)). The pdf p(x(n+1)|x(n)) can be read off of the model equations to be a Gaussian with mean R(x(n)) and covariance matrix Σ = GG^T, where the T denotes a transposed; the pdf p(y(n+1)|x(n+1)) is a Gaussian with mean h(x(n+1)) and covariance QQ^T. In a sampling-importance-resampling (SIR) filter one samples new values for the particles from a prior pdf and then one weighs these samples with weights determined by the observations, to yield an approximation to p(n+1). Such weighting schemes often yield small weights for many of the particles. Implicit particle filtering overcomes this problem by using the observations to generate the particles, thus focusing attention on regions of large probability. A suitable algebraic equation that depends on the model and the observations is constructed for each particle, and its solution yields high probability samples of p(n+1). In the current formulation of the implicit particle filter, the state

Stochastic processes and functional analysis a volume of recent advances in honor of M. M. Rao

CERN Document Server

Krinik, Alan C

2004-01-01

This extraordinary compilation is an expansion of the recent American Mathematical Society Special Session celebrating M. M. Rao's distinguished career and includes most of the presented papers as well as ancillary contributions from session invitees. This book shows the effectiveness of abstract analysis for solving fundamental problems of stochastic theory, specifically the use of functional analytic methods for elucidating stochastic processes, as made manifest in M. M. Rao's prolific research achievements. Featuring a biography of M. M. Rao, a complete bibliography of his published works,

The attitude inversion method of geostationary satellites based on unscented particle filter

Science.gov (United States)

Du, Xiaoping; Wang, Yang; Hu, Heng; Gou, Ruixin; Liu, Hao

2018-04-01

The attitude information of geostationary satellites is difficult to be obtained since they are presented in non-resolved images on the ground observation equipment in space object surveillance. In this paper, an attitude inversion method for geostationary satellite based on Unscented Particle Filter (UPF) and ground photometric data is presented. The inversion algorithm based on UPF is proposed aiming at the strong non-linear feature in the photometric data inversion for satellite attitude, which combines the advantage of Unscented Kalman Filter (UKF) and Particle Filter (PF). This update method improves the particle selection based on the idea of UKF to redesign the importance density function. Moreover, it uses the RMS-UKF to partially correct the prediction covariance matrix, which improves the applicability of the attitude inversion method in view of UKF and the particle degradation and dilution of the attitude inversion method based on PF. This paper describes the main principles and steps of algorithm in detail, correctness, accuracy, stability and applicability of the method are verified by simulation experiment and scaling experiment in the end. The results show that the proposed method can effectively solve the problem of particle degradation and depletion in the attitude inversion method on account of PF, and the problem that UKF is not suitable for the strong non-linear attitude inversion. However, the inversion accuracy is obviously superior to UKF and PF, in addition, in the case of the inversion with large attitude error that can inverse the attitude with small particles and high precision.

On Convergence of Kernel Density Estimates in Particle Filtering

Czech Academy of Sciences Publication Activity Database

Coufal, David

2016-01-01

Roč. 52, č. 5 (2016), s. 735-756 ISSN 0023-5954 Grant - others:GA ČR(CZ) GA16-03708S; SVV(CZ) 260334/2016 Institutional support: RVO:67985807 Keywords : Fourier analysis * kernel methods * particle filter Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.379, year: 2016

Data Assimilation in Air Contaminant Dispersion Using a Particle Filter and Expectation-Maximization Algorithm

Directory of Open Access Journals (Sweden)

Rongxiao Wang

2017-09-01

Full Text Available The accurate prediction of air contaminant dispersion is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in chemical industry parks. Conventional atmospheric dispersion models can seldom give accurate predictions due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion models, two data assimilation methods (i.e., the typical particle filter & the combination of a particle filter and expectation-maximization algorithm are proposed to assimilate the virtual Unmanned Aerial Vehicle (UAV observations with measurement error into the atmospheric dispersion model. Two emission cases with different dimensions of state parameters are considered. To test the performances of the proposed methods, two numerical experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model predictions when the dimension of state parameters is relatively low. In contrast, when the dimension of state parameters becomes higher, the method of particle filter combining the expectation-maximization algorithm performs better in terms of the parameter estimation accuracy. Therefore, the proposed data assimilation methods are able to effectively support air quality monitoring and emergency management in chemical industry parks.

Pseudobrookite-type MgTi2O5 water purification filter with controlled particle morphology

Directory of Open Access Journals (Sweden)

Yuta Nakagoshi

2015-09-01

Full Text Available Pseudobrookite-type oxide-based ceramics, such as Al2TiO5 and MgTi2O5, have recently been studied as porous ceramic membranes. Here, the effect of LiF doping on the morphology of MgTi2O5 particles is presented in detail. Water purification filters were produced using porous MgTi2O5, with different particle morphologies. MgCO3 (basic and TiO2 powders with various LiF contents were wet-ball milled, dried, and then, calcined in air at 1100 °C to obtain the MgTi2O5 powders. The powder compacts were sintered at 1000–1200 °C to produce the MgTi2O5 disk filters. The 0.5 wt.% LiF-doped MgTi2O5 disk filter, with elongated grains, showed well-balanced performance removing boehmite particles with diameter of 0.7 μm. Non-doped MgTi2O5 disk filter with equiaxed grains was suitable for precise filtration.

Development of an optimal filter substrate for the identification of small microplastic particles in food by micro-Raman spectroscopy.

Science.gov (United States)

Oßmann, Barbara E; Sarau, George; Schmitt, Sebastian W; Holtmannspötter, Heinrich; Christiansen, Silke H; Dicke, Wilhelm

2017-06-01

When analysing microplastics in food, due to toxicological reasons it is important to achieve clear identification of particles down to a size of at least 1 μm. One reliable, optical analytical technique allowing this is micro-Raman spectroscopy. After isolation of particles via filtration, analysis is typically performed directly on the filter surface. In order to obtain high qualitative Raman spectra, the material of the membrane filters should not show any interference in terms of background and Raman signals during spectrum acquisition. To facilitate the usage of automatic particle detection, membrane filters should also show specific optical properties. In this work, beside eight different, commercially available membrane filters, three newly designed metal-coated polycarbonate membrane filters were tested to fulfil these requirements. We found that aluminium-coated polycarbonate membrane filters had ideal characteristics as a substrate for micro-Raman spectroscopy. Its spectrum shows no or minimal interference with particle spectra, depending on the laser wavelength. Furthermore, automatic particle detection can be applied when analysing the filter surface under dark-field illumination. With this new membrane filter, analytics free of interference of microplastics down to a size of 1 μm becomes possible. Thus, an important size class of these contaminants can now be visualized and spectrally identified. Graphical abstract A newly developed aluminium coated polycarbonate membrane filter enables automatic particle detection and generation of high qualitative Raman spectra allowing identification of small microplastics.

Experimental Study on Ultrafine Particle Removal Performance of Portable Air Cleaners with Different Filters in an Office Room

Directory of Open Access Journals (Sweden)

Huan Ma

2016-01-01

Full Text Available Size- and time-dependent aerodynamic behaviors of indoor particles, including PM1.0, were evaluated in a school office in order to test the performance of air-cleaning devices using different filters. In-situ real-time measurements were taken using an optical particle counter. The filtration characteristics of filter media, including single-pass efficiency, volume and effectiveness, were evaluated and analyzed. The electret filter (EE medium shows better initial removal efficiency than the high efficiency (HE medium in the 0.3–3.5 μm particle size range, while under the same face velocity, the filtration resistance of the HE medium is several times higher than that of the EE medium. During service life testing, the efficiency of the EE medium decreased to 60% with a total purifying air flow of 25 × 104 m3/m2. The resistance curve rose slightly before the efficiency reached the bottom, and then increased almost exponentially. The single-pass efficiency of portable air cleaner (PAC with the pre-filter (PR or the active carbon granule filter (CF was relatively poor. While PAC with the pre-filter and the high efficiency filter (PR&HE showed maximum single-pass efficiency for PM1.0 (88.6%, PAC with the HE was the most effective at removing PM1.0. The enhancement of PR with HE and electret filters augmented the single-pass efficiency, but lessened the airflow rate and effectiveness. Combined with PR, the decay constant of large-sized particles could be greater than for PACs without PR. Without regard to the lifetime, the electret filters performed better with respect to resource saving and purification improvement. A most penetrating particle size range (MPPS: 0.4–0.65 μm exists in both HE and electret filters; the MPPS tends to become larger after HE and electret filters are combined with PR. These results serve to provide a better understanding of the indoor particle removal performance of PACs when combined with different kinds of filters in

Prognostics 101: A tutorial for particle filter-based prognostics algorithm using Matlab

International Nuclear Information System (INIS)

An, Dawn; Choi, Joo-Ho; Kim, Nam Ho

2013-01-01

This paper presents a Matlab-based tutorial for model-based prognostics, which combines a physical model with observed data to identify model parameters, from which the remaining useful life (RUL) can be predicted. Among many model-based prognostics algorithms, the particle filter is used in this tutorial for parameter estimation of damage or a degradation model. The tutorial is presented using a Matlab script with 62 lines, including detailed explanations. As examples, a battery degradation model and a crack growth model are used to explain the updating process of model parameters, damage progression, and RUL prediction. In order to illustrate the results, the RUL at an arbitrary cycle are predicted in the form of distribution along with the median and 90% prediction interval. This tutorial will be helpful for the beginners in prognostics to understand and use the prognostics method, and we hope it provides a standard of particle filter based prognostics. -- Highlights: ► Matlab-based tutorial for model-based prognostics is presented. ► A battery degradation model and a crack growth model are used as examples. ► The RUL at an arbitrary cycle are predicted using the particle filter

Hybrid extended particle filter (HEPF) for integrated inertial navigation and global positioning systems

International Nuclear Information System (INIS)

Aggarwal, Priyanka; Syed, Zainab; El-Sheimy, Naser

2009-01-01

Navigation includes the integration of methodologies and systems for estimating time-varying position, velocity and attitude of moving objects. Navigation incorporating the integrated inertial navigation system (INS) and global positioning system (GPS) generally requires extensive evaluations of nonlinear equations involving double integration. Currently, integrated navigation systems are commonly implemented using the extended Kalman filter (EKF). The EKF assumes a linearized process, measurement models and Gaussian noise distributions. These assumptions are unrealistic for highly nonlinear systems like land vehicle navigation and may cause filter divergence. A particle filter (PF) is developed to enhance integrated INS/GPS system performance as it can easily deal with nonlinearity and non-Gaussian noises. In this paper, a hybrid extended particle filter (HEPF) is developed as an alternative to the well-known EKF to achieve better navigation data accuracy for low-cost microelectromechanical system sensors. The results show that the HEPF performs better than the EKF during GPS outages, especially when simulated outages are located in periods with high vehicle dynamics

Particle analysis on concentrated particle suspensions by transmission fluctuation spectrometry with band-pass filters: part 2. Experimental results

International Nuclear Information System (INIS)

Xu, Yamin; Shen, Jianqi; Cai, Xiaoshu; Riebel, Ulrich

2010-01-01

Transmission fluctuation spectrometry (TFS), as a new method of online and real-time particle analysis developed in recent years, can measure the particle size distribution and particle concentration simultaneously. In the preceding paper, high concentration effects on the TFS using band-pass filters were investigated by numerical simulation, and empirical expressions to correct the effects were obtained. This paper presents a study on the TFS measurements in which the particle concentration varies in a very wide dynamic range. Finally, reasonable results on both the particle size distribution and particle concentration are obtained by introducing empirical corrections into the inversion algorithm

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

Science.gov (United States)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Analysis of commodity prices with the particle filter

International Nuclear Information System (INIS)

Aiube, Fernando Antonio Lucena; Baidya, Tara Keshar Nanda; Tito, Edison Americo Huarsaya

2008-01-01

The behavior of commodities prices is fundamental to real-asset investment decisions, hedging, and pricing financial derivatives. Schwartz and Smith [Schwartz, E.S., Smith, J.E. (2000). Short term-variations and long-term dynamics in commodity prices. Management Science, 46, 893-911.] proposed a two-factor model for describing the stochastic processes of commodity prices, in which the two factors are short-term variations and equilibrium prices. These are both unobserved state variables that are estimated using the Kalman filter. The estimation is based on the observation of future prices for different maturities. The authors have carried out this process without incorporating jumps in the short-term variation of prices. Here we aim to demonstrate that the inclusion of jumps better explains the behavior of oil prices, and in fact creates difficulties in the estimation of state variables. This is because the variables become non-Gaussian so the Kalman filter is not recommended. Another methodology, called the particle filter, is more suitable in this case, and we describe its application in this article

Filtration of Oil-furnace Carbon Black Dust Particles from the Tail Gases by Filter Bags With PTFE Membrane

Directory of Open Access Journals (Sweden)

Čuzela, D.

2010-01-01

Full Text Available During the industrial production of oil furnace carbon black, tail gases containing oil-furnace carbon black dust particles are emitted to the atmosphere. In the carbon black plant, Petrokemija d. d., there are six exhaust stacks for tail gases. Each of them has installed process equipment for cleaning tail gases. Efficiency of cleaning mainly depends on equipment construction and cleaning technology. The vicinity of the town, quality of the air in the region of Kutina, regarding floating particles PM10, and corporate responsibility for further enviromental improvement, imposes development of new methods that will decrease the emmision of oil-furnace carbon black dust particles in the air. Combining centrifugal percipitator and filter, special construction of cyclofilter for filtration of oil-furnace carbon black dust particles from tail gases by using PTFE (polytetrafluoroethylene membrane filter bags, was designed. Developed filtration technique provides η = 99.9 % efficiency of filtration. Construction part of the filter contains the newest generation of PTFE membrane filter bags with the ability of jet pulse cleaning. Using the PTFE membrane filter bags technology, filtration efficiency for oil-furnace carbon black dust particles in tail gases of maximum γ=5mgm-3can be achieved. The filtration efficiency was monitored continuously measuring the concentration of the oil-furnace carbon black dust particles in the tail gases with the help of in situ electronic probe. The accomplished filtration technology is the base for the installation of the PTFE membrane filter bags in the main operation filters which will provide better protection of the air in the town of Kutina against floating particles PM10.

A volume-filtered formulation to capture particle-shock interactions in multiphase compressible flows

Science.gov (United States)

Shallcross, Gregory; Capecelatro, Jesse

2017-11-01

Compressible particle-laden flows are common in engineering systems. Applications include but are not limited to water injection in high-speed jet flows for noise suppression, rocket-plume surface interactions during planetary landing, and explosions during coal mining operations. Numerically, it is challenging to capture these interactions due to the wide range of length and time scales. Additionally, there are many forms of the multiphase compressible flow equations with volume fraction effects, some of which are conflicting in nature. The purpose of this presentation is to develop the capability to accurately capture particle-shock interactions in systems with a large number of particles from dense to dilute regimes. A thorough derivation of the volume filtered equations is presented. The volume filtered equations are then implemented in a high-order, energy-stable Eulerian-Lagrangian framework. We show this framework is capable of decoupling the fluid mesh from the particle size, enabling arbitrary particle size distributions in the presence of shocks. The proposed method is then assessed against particle-laden shock tube data. Quantities of interest include fluid-phase pressure profiles and particle spreading rates. The effect of collisions in 2D and 3D are also evaluated.

Characterization of Airborne Particles Collected from Car Engine Air Filters Using SEM and EDX Techniques

Science.gov (United States)

Heredia Rivera, Birmania; Gerardo Rodriguez, Martín

2016-01-01

Particulate matter accumulated on car engine air-filters (CAFs) was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed to. The morphology, microstructure, and chemical composition of a variety of particles were studied using scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX). The particulate matter accumulated by the CAFs was studied in two categories; the first was of removed particles by friction, and the second consisted of particles retained on the filters. Larger particles with a diameter of 74–10 µm were observed in the first category. In the second one, the detected particles had a diameter between 16 and 0.7 µm. These particles exhibited different morphologies and composition, indicating mostly a soil origin. The elemental composition revealed the presence of three groups: mineral (clay and asphalt), metallic (mainly Fe), and biological particles (vegetal and animal debris). The palynological analysis showed the presence of pollen grains associated with urban plants. These results suggest that CAFs capture a mixture of atmospheric particles, which can be analyzed in order to monitor urban air. Thus, the continuous availability of large numbers of filters and the retroactivity associated to the car routes suggest that these CAFs are very useful for studying the high traffic zones within a city. PMID:27706087

Characterization of Airborne Particles Collected from Car Engine Air Filters Using SEM and EDX Techniques

Directory of Open Access Journals (Sweden)

Birmania Heredia Rivera

2016-10-01

Full Text Available Particulate matter accumulated on car engine air-filters (CAFs was examined in order to investigate the potential use of these devices as efficient samplers for collecting street level air that people are exposed to. The morphology, microstructure, and chemical composition of a variety of particles were studied using scanning electron microscopy (SEM and energy-dispersive X-ray (EDX. The particulate matter accumulated by the CAFs was studied in two categories; the first was of removed particles by friction, and the second consisted of particles retained on the filters. Larger particles with a diameter of 74–10 µm were observed in the first category. In the second one, the detected particles had a diameter between 16 and 0.7 µm. These particles exhibited different morphologies and composition, indicating mostly a soil origin. The elemental composition revealed the presence of three groups: mineral (clay and asphalt, metallic (mainly Fe, and biological particles (vegetal and animal debris. The palynological analysis showed the presence of pollen grains associated with urban plants. These results suggest that CAFs capture a mixture of atmospheric particles, which can be analyzed in order to monitor urban air. Thus, the continuous availability of large numbers of filters and the retroactivity associated to the car routes suggest that these CAFs are very useful for studying the high traffic zones within a city.

Dust collected in air filters - Possible source of volatile organic compounds and particles; Ger smutsiga luftfilter foersaemrad tilluft ? En studie av emissioner med ursprung i filter

Energy Technology Data Exchange (ETDEWEB)

Johansson, J.H.P.; Rosell, Lars

1998-06-01

Emissions from dust collected in air filters have been investigated using in situ measurements. Two air filters of different classes (F6 and F8/9) have been exposed to outdoor air for a preconditioning period of six months. After this period measurements have been carried out using two operating conditions, continuous and intermittent. Air samples were taken both up- and downstream of the filters. The air samples were analysed regarding volatile organic compounds (VOCs), including formaldehyde and microbial VOCs (mVOC) and the samples of airborne dust were examined regarding the contents of colony forming units, ergosterol (marker of fungi), and endotoxin (marker of gram negative bacteria). Furthermore, a visual inspection of the airborne dust was conducted using SEM. Particles released when the fan was turned on and a short period after, were monitored using an optical particle counter, slitsamplers (fungus spores) and membrane filters for SEM analysis. After finishing the in situ measurements, the filters were placed in climate chambers for emission sampling. Finally, samples were cut out for analysis of microbial contents in the filter material, both on the dusty and `clean` side of the filters. No consistent change of VOC, aldehyde or mVOC concentrations across the filters could be measured. A significant ozone reduction was seen in one of the in situ measurements. The chamber experiments showed that the filters were a source of various VOCs, e.g. aldehydes and mVOCs. The emission of mVOCs in the chambers was significantly higher for the F8/9 filter, probably due to more and finer dust in that filter. Only a few colonization units (fungi) penetrate filters when running continuously but an increase was noted at the moment the fans were started. The same phenomenon was observed with the optical particle counter, but both the intensity and length of the increase, for colonization units and other particles, were moderate. Mycological examination of the filter

Response of Peripheral Blood Lymphocytes from RAO-affected Horses to b2-Agonist Stimulation

OpenAIRE

Werner Becker, Marianne Patricia

2011-01-01

Recurrent airway obstruction (RAO) affects middle-age horses, inducing bronchoconstriction and airway inflammation. β2-agonists like salbutamol are used as treatment, promoting airway smooth muscle (ASM) relaxation and bronchodilation. In addition to ASM, inflammatory cells express the β2-adrenoreceptors (β2-AR). In other species, β2-agonists promote peripheral blood lymphocyte (PBL) cytokine expression towards a pro-inflammatory phenotype. RAO horses are a good model for evaluating chron...

Implicit particle filtering for models with partial noise, and an application to geomagnetic data assimilation

Directory of Open Access Journals (Sweden)

M. Morzfeld

2012-06-01

Full Text Available Implicit particle filtering is a sequential Monte Carlo method for data assimilation, designed to keep the number of particles manageable by focussing attention on regions of large probability. These regions are found by minimizing, for each particle, a scalar function F of the state variables. Some previous implementations of the implicit filter rely on finding the Hessians of these functions. The calculation of the Hessians can be cumbersome if the state dimension is large or if the underlying physics are such that derivatives of F are difficult to calculate, as happens in many geophysical applications, in particular in models with partial noise, i.e. with a singular state covariance matrix. Examples of models with partial noise include models where uncertain dynamic equations are supplemented by conservation laws with zero uncertainty, or with higher order (in time stochastic partial differential equations (PDE or with PDEs driven by spatially smooth noise processes. We make the implicit particle filter applicable to such situations by combining gradient descent minimization with random maps and show that the filter is efficient, accurate and reliable because it operates in a subspace of the state space. As an example, we consider a system of nonlinear stochastic PDEs that is of importance in geomagnetic data assimilation.

Loss of collected particles from the filter of the stack monitor, the Ringhals-1 power reactor

International Nuclear Information System (INIS)

Stroem, L.

1993-01-01

The function of the filter holder was examined in the laboratory and in the Ringhals measurement installation. It was concluded that a loss of sample could occur, if the filter has a heavy particle deposit. An approximate relation between deposits thickness and loss of sample could be determined. Particle concentration in the stack air is sometimes so high, that loss of sample can occur. The test have also revealed that the sample air stream can by-pass the filter, without proper indication of the defect. Control instrumentation is proposed

Marginalized adaptive particle filtering for nonlinear models with unknown time-varying noise parameters

Czech Academy of Sciences Publication Activity Database

Ökzan, E.; Šmídl, Václav; Saha, S.; Lundquist, C.; Gustafsson, F.

2013-01-01

Roč. 49, č. 6 (2013), s. 1566-1575 ISSN 0005-1098 R&D Projects: GA ČR(CZ) GAP102/11/0437 Keywords : Unknown Noise Statistics * Adaptive Filtering * Marginalized Particle Filter * Bayesian Conjugate prior Subject RIV: BC - Control Systems Theory Impact factor: 3.132, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/smidl-0393047.pdf

3D head pose estimation and tracking using particle filtering and ICP algorithm

KAUST Repository

Ben Ghorbel, Mahdi; Baklouti, Malek; Couvet, Serge

2010-01-01

This paper addresses the issue of 3D head pose estimation and tracking. Existing approaches generally need huge database, training procedure, manual initialization or use face feature extraction manually extracted. We propose a framework for estimating the 3D head pose in its fine level and tracking it continuously across multiple Degrees of Freedom (DOF) based on ICP and particle filtering. We propose to approach the problem, using 3D computational techniques, by aligning a face model to the 3D dense estimation computed by a stereo vision method, and propose a particle filter algorithm to refine and track the posteriori estimate of the position of the face. This work comes with two contributions: the first concerns the alignment part where we propose an extended ICP algorithm using an anisotropic scale transformation. The second contribution concerns the tracking part. We propose the use of the particle filtering algorithm and propose to constrain the search space using ICP algorithm in the propagation step. The results show that the system is able to fit and track the head properly, and keeps accurate the results on new individuals without a manual adaptation or training. © Springer-Verlag Berlin Heidelberg 2010.

Analysing Institutions Interdisciplinarity by Extensive Use of Rao-Stirling Diversity Index.

Science.gov (United States)

Cassi, Lorenzo; Champeimont, Raphaël; Mescheba, Wilfriedo; de Turckheim, Élisabeth

2017-01-01

This paper shows how the Rao-Stirling diversity index may be extensively used for positioning and comparing institutions interdisciplinary practices. Two decompositions of this index make it possible to explore different components of the diversity of the cited references in a corpus of publications. The paper aims at demonstrating how these bibliometric tools can be used for comparing institutions in a research field by highlighting collaboration orientations and institutions strategies. To make the method available and easy to use for indicator users, this paper first recalls a previous result on the decomposition of the Rao-Stirling index into multidisciplinarity and interdisciplinarity components, then proposes a new decomposition to further explore the profile of research collaborations and finally presents an application to Neuroscience research in French universities.

X-ray diffraction analysis of particles ingested by filter-feeding animals

International Nuclear Information System (INIS)

Merritt, R.W.; Gersabeck, E.F.; Ross, D.H.; Mortland, M.M.

1978-01-01

The size and relative abundance of mineral particles ingested by two filter-feeding aquatic insects, Simulium vittatum Zett. (Diptera: Simuliidae) and Aedes triseriatus (Say) (Diptera: Culicidae) were determined by X-ray diffraction methods. Different minerals representing different particle size categories were supplied larval black flies and mosquitoes. Since minerals possess characteristic diffraction properties, their presence and relative abundance can be determined. Early instars of the black fly ingested and retained particles of three different size ranges: however, more coarse particles relative to fine particles were retained by smaller instars as compared with the larger instars. With mosquito larvae, there was a proportional increase in coarser material ingested with increasing age and size of larvae. Other applications of this method are discussed. (Auth.)

Cross-cultural adaptation and validation of the French version of the Rheumatoid and Arthritis Outcome Score (RAOS)

DEFF Research Database (Denmark)

Duval, Aurelie; Maillefert, Jean Francis; Gossec, Laure

2010-01-01

The Rheumatoid and Arthritis Outcome Score (RAOS) was recently developed to evaluate functional disability and quality of life in rheumatoid arthritis (RA) patients suffering from lower limb symptoms. The aims of this study were to cross-culturally adapt the RAOS into French and to assess its...

Antibacterial performance of nano polypropylene filter media containing nano-TiO{sub 2} and clay particles

Energy Technology Data Exchange (ETDEWEB)

Shafiee, Sara; Zarrebini, Mohammad; Naghashzargar, Elham, E-mail: e.naghashzargar@tx.iut.ac.ir; Semnani, Dariush, E-mail: d-semnani@cc.iut.ac.ir [Isfahan University of Technology, Department of Textile Engineering (Iran, Islamic Republic of)

2015-10-15

Disinfection and elimination of pathogenic microorganisms from liquid can be achieved by filtration process using antibacterial filter media. The advent of nanotechnology has facilitated the introduction of membranes consisting of nano-fiber in filtration operations. The melt electro-spun fibers due to their extremely small diameters are used in the production of this particular filtration medium. In this work, antibacterial polypropylene filter medium containing clay particles and nano-TiO{sub 2} were made using melt electro-spun technology. Antibacterial performance of polypropylene nano-filters was evaluated using E. coli bacteria. Additionally, filtration efficiency of the samples in terms fiber diameter, filter porosity, and fiber distribution using image processing technique was determined. Air permeability and dust aerosol tests were conducted to establish the suitability of the samples as a filter medium. It was concluded that as far as antibacterial property is concerned, nano-fibers filter media containing clay particles are preferential to similar media containing TiO{sub 2} nanoparticles.

Experimental relationship between the specific resistance of a HEPA [High Efficiency Particulate Air] filter and particle diameters of different aerosol materials

International Nuclear Information System (INIS)

Novick, V.J.; Monson, P.R.; Ellison, P.E.

1990-01-01

The increase in pressure drop across a HEPA filter has been measured as a function of the particle mass loading using two materials with different particle morphologies. The HEPA filter media chosen, is identical to the filter media used in the Airborne Activity Confinement System (AACS) on the Savannah River Reactors. The velocity through the test filter media was the same as the velocity through the AACS media, under normal operating flow conditions. Sodium Chloride challenge particles were generated using an atomizer, resulting in regularly shaped crystalline forms. Ammonium chloride aerosols were formed from the gas phase reaction of HCl and NH 4 OH vapors resulting in irregular agglomerates. In both cases, the generation conditions were adjusted to provide several different particle size distributions. For each particle size distribution, the mass of material loaded per unit area of filter per unit pressure drop for a given filtration velocity (1/Specific resistance) was measured. Theoretical considerations in the most widely accepted filter cake model predict that the mass per unit area and per unit pressure drop should increase with the particle density times the particle diameter squared. However, these test results indicate that the increase in the mass loaded per unit area per unit pressure drop, for both materials, can be better described by plotting the specific resistance divided by the particle density as an inverse function of the particle density times the particle diameter squared. 9 refs., 7 figs

The Wiley Blackwell companion to political geography

NARCIS (Netherlands)

Agnew, J.; Mamadouh, V.; Secor, A.J.; Sharp, J.

2015-01-01

The Wiley Blackwell Companion to Political Geography aims to account for the intellectual and worldly developments that have taken place in and around political geography in the last 10 years. Bringing together established names in the field as well as new scholars, it highlights provocative

Quantum metrology in open systems: dissipative Cramér-Rao bound.

Science.gov (United States)

Alipour, S; Mehboudi, M; Rezakhani, A T

2014-03-28

Estimation of parameters is a pivotal task throughout science and technology. The quantum Cramér-Rao bound provides a fundamental limit of precision allowed to be achieved under quantum theory. For closed quantum systems, it has been shown how the estimation precision depends on the underlying dynamics. Here, we propose a general formulation for metrology scenarios in open quantum systems, aiming to relate the precision more directly to properties of the underlying dynamics. This feature may be employed to enhance an estimation precision, e.g., by quantum control techniques. Specifically, we derive a Cramér-Rao bound for a fairly large class of open system dynamics, which is governed by a (time-dependent) dynamical semigroup map. We illustrate the utility of this scenario through three examples.

Variation in penetration of submicrometric particles through electrostatic filtering facepieces during exposure to paraffin oil aerosol.

Science.gov (United States)

Plebani, Carmela; Listrani, Stefano; Tranfo, Giovanna; Tombolini, Francesca

2012-01-01

Several studies show the increase of penetration through electrostatic filters during exposure to an aerosol flow, because of particle deposition on filter fibers. We studied the effect of increasing loads of paraffin oil aerosol on the penetration of selected particle sizes through an electrostatic filtering facepiece. FFP2 facepieces were exposed for 8 hr to a flow rate of 95.0 ± 0.5 L/min of polydisperse paraffin aerosol at 20.0 ± 0.5 mg/m(3). The penetration of bis(2-ethylhexyl)sebacate (DEHS) monodisperse neutralized aerosols, with selected particle size in the 0.03-0.40 μm range, was measured immediately prior to the start of the paraffin aerosol loading and at 1, 4, and 8 hr after the start of paraffin aerosol loading. Penetration through isopropanol-treated facepieces not oil paraffin loaded was also measured to evaluate facepiece behavior when electrostatic capture mechanisms are practically absent. During exposure to paraffin aerosol, DEHS penetration gradually increased for all aerosol sizes, and the most penetrating particle size (0.05 μm at the beginning of exposure) shifted slightly to larger diameters. After the isopropanol treatment, the higher penetration value was 0.30 μm. In addition to an increased penetration during paraffin loading at a given particle size, the relative degree of increase was greater as the particle size increased. Penetration value measured after 8 hr for 0.03-μm particles was on average 1.6 times the initial value, whereas it was about 8 times for 0.40-μm particles. This behavior, as well evidenced in the measurements of isopropanol-treated facepieces, can be attributed to the increasing action in particle capture of the electrostatic forces (Coulomb and polarization), which depend strictly on the diameter and electrical charge of neutralized aerosol particles. With reference to electrostatic filtering facepieces as personal protective equipment, results suggest the importance of complying with the manufacturer

Investigations into the penetration and pressure drop of HEPA filter media during loading with submicron particle aerosols at high concentrations

International Nuclear Information System (INIS)

Leibold, H; Wilhelm, J.G.

1991-01-01

High Efficiency Particulate Air (HEPA) filters are typically employed in particle removal and retention within the air cleaning systems of clean rooms in the pharmaceutical, nuclear and semiconductor industries for dust concentrations of some μg/m 3 . Their extremely high removal efficiencies for submicron particles make them attractive candidates in complying with increasingly lower emission limits for industrial processes that involve dust concentrations of up to several g/m 3 . Cost-effective operation under such conditions requires the filter units to be recleanable. The recleanability of HEPA filter media depends not only on the operating conditions during the cleaning process but also on the filtration conditions during particle loading. The structure and location of the particles captured by the glass fiber matrix greatly affect the degree to which they can be subsequently dislodged and removed from the filter medium. Changes in filtration efficiency with service time for various particle diameters in the critical submicron size range, as well as the effects of filtration velocity on the increase in pressure drop, are important criteria with regard to recleaning HEPA filter units. Of special significance for the recleanability of HEPA filter media is knowledge of how operating conditions affect dust cake formation. (author)

Integration of GPS precise point positioning and MEMS-based INS using unscented particle filter.

Science.gov (United States)

Abd Rabbou, Mahmoud; El-Rabbany, Ahmed

2015-03-25

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF) is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS) inertial sensors are used. To enhance the navigation system performance, alternatives to the standard EKF should be considered. Particle filtering (PF) is commonly considered as a nonlinear estimation technique to accommodate severe MEMS inertial sensor biases and noise behavior. However, the computation burden of PF limits its use. In this study, an improved version of PF, the unscented particle filter (UPF), is utilized, which combines the unscented Kalman filter (UKF) and PF for the integration of GPS precise point positioning and MEMS-based inertial systems. The proposed filter is examined and compared with traditional estimation filters, namely EKF, UKF and PF. Tightly coupled mechanization is adopted, which is developed in the raw GPS and INS measurement domain. Un-differenced ionosphere-free linear combinations of pseudorange and carrier-phase measurements are used for PPP. The performance of the UPF is analyzed using a real test scenario in downtown Kingston, Ontario. It is shown that the use of UPF reduces the number of samples needed to produce an accurate solution, in comparison with the traditional PF, which in turn reduces the processing time. In addition, UPF enhances the positioning accuracy by up to 15% during GPS outages, in comparison with EKF. However, all filters produce comparable results when the GPS measurement updates are available.

The performance of biological anaerobic filters packed with sludge-fly ash ceramic particles (SFCP) and commercial ceramic particles (CCP) during the restart period: effect of the C/N ratios and filter media.

Science.gov (United States)

Yue, Qinyan; Han, Shuxin; Yue, Min; Gao, Baoyu; Li, Qian; Yu, Hui; Zhao, Yaqin; Qi, Yuanfeng

2009-11-01

Two lab-scale upflow biological anaerobic filters (BAF) packed with sludge-fly ash ceramic particles (SFCP) and commercial ceramic particles (CCP) were employed to investigate effects of the C/N ratios and filter media on the BAF performance during the restart period. The results indicated that BAF could be restarted normally after one-month cease. The C/N ratio of 4.0 was the thresholds of nitrate removal and nitrite accumulation. TN removal and phosphate uptake reached the maximum value at the same C/N ratio of 5.5. Ammonia formation was also found and excreted a negative influence on TN removal, especially when higher C/N ratios were applied. Nutrients were mainly degraded within the height of 25 cm from the bottom. In addition, SFCP, as novel filter media manufactured by wastes-dewatered sludge and fly ash, represented a better potential in inhibiting nitrite accumulation, TN removal and phosphate uptake due to their special characteristics in comparison with CCP.

Neutrophil and macrophage apoptosis in bronchoalveolar lavage fluid from healthy horses and horses with recurrent airway obstruction (RAO)

Science.gov (United States)

2014-01-01

Background Dysregulation of apoptosis has been implicated in a range of diseases including tumors, neurodegenerative and autoimmine diseases, as well as allergic asthma and chronic obstructive pulmonary disease (COPD) in humans. Although it has a different pathophysiology, delayed apoptosis of various inflammatory cells may play a pivotal role in the development of recurrent airway obstruction (RAO) in horses. Reduction of inflammatory cell apoptosis or a dysregulation of this process could lead to chronic inflammation and tissue injury. Therefore, the aim of this study was to investigate the rate of apoptosis and necrosis of neutrophils and macrophages in bronchoalveolar lavage fluid obtained from seven horses suffering from RAO (study group) and seven control horses. Results We demonstrated that neutrophil/macrophage apoptosis is altered in RAO-affected horses compared with the control group in the BAL fluid. We found a significant difference between the median percentage of early and late apoptosis of neutrophils between the study and control group of horses. Moreover, we found a positive correlation between the rate of apoptosis and the median percentage of macrophages in RAO-affected horses. Conclusion The findings suggest that apoptosis dysregulation may play a significant role in the pathogenesis of RAO. However, further studies are needed to clarify the role of altered apoptosis in the course of equine recurrent airway obstruction. PMID:24460911

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

Science.gov (United States)

Wang, Ershen; Jia, Chaoying; Tong, Gang; Qu, Pingping; Lan, Xiaoyu; Pang, Tao

2018-03-01

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.

The spatial filtering method for solid particle velocity measurement based on an electrostatic sensor

International Nuclear Information System (INIS)

Xu, Chuanlong; Tang, Guanghua; Zhou, Bin; Wang, Shimin

2009-01-01

The spatial filtering method for particle velocity measurement has the advantages of simplicity of the measurement system and convenience of data processing. In this paper, the relationship between solid particles mean velocity in a pneumatic pipeline and the power spectrum of the output signal of an electrostatic sensor was mathematically modeled. The effects of the length of the sensor, the thickness of the dielectric pipe and its length on the spatial filtering characteristics of the sensor were also investigated using the finite element method. As for the roughness of and the difficult determination of the peak frequency f max of the power spectrum characteristics of the output signal of the sensor, a wavelet analysis based filtering method was applied to smooth the curve, which can accurately determine the peak frequency f max . Finally, experiments were performed on a pilot dense phase pneumatic conveying rig at high pressure to test the performance of the velocity measurement system. The experimental results show that the system repeatability is within ±4% over a gas superficial velocity range of 8.63–18.62 m s −1 for a particle concentration range of 0.067–0.130 m 3 m −3

GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model

Directory of Open Access Journals (Sweden)

Jgouta Meriem

2017-06-01

Full Text Available Positioning solutions need to be more precise and available. The most frequent method used nowadays includes a GPS receiver, sometimes supported by other sensors. Generally, GPS and GNSS suffer from spreading perturbations that produce biases on pseudo-range measurements. With a view to optimize the use of the satellites received, we offer a positioning algorithm with pseudo range error modelling with the contribution of an appropriate filtering process. Extended Kalman Filter, The Rao- Blackwellized filter are among the most widely used algorithms to predict errors and to filter the high frequency noise. This paper describes a new method of estimating the pseudo-range errors based on the PSO-RBF model which achieves an optimal training criterion. This model is appropriate of its method to predict the GPS corrections for accurate positioning, it reduce the positioning errors at high velocities by more than 50% compared to the RLS or EKF methods.

Multilevel particle filter

KAUST Repository

Law, Kody

2016-01-06

This talk will pertain to the filtering of partially observed diffusions, with discrete-time observations. It is assumed that only biased approximations of the diffusion can be obtained, for choice of an accuracy parameter indexed by l. A multilevel estimator is proposed, consisting of a telescopic sum of increment estimators associated to the successive levels. The work associated to O( 2) mean-square error between the multilevel estimator and average with respect to the filtering distribution is shown to scale optimally, for example as O( 2) for optimal rates of convergence of the underlying diffusion approximation. The method is illustrated on some toy examples as well as estimation of interest rate based on real S&P 500 stock price data.

Improved Particle Filter for Passive Target Tracking%改进粒子滤波在被动目标跟踪中的应用

Institute of Scientific and Technical Information of China (English)

邓小龙; 谢剑英; 杨煜普

2005-01-01

As a new method for dealing with any nonlinear or non-Gaussian distributions, based on the Monte Carlo methods and Bayesian filtering, particle filters (PF) are favored by researchers and widely applied in many fields. Based on particle filtering, an improved extended Kalman filter (EKF) proposal distribution is presented. Evaluation of the weights is simplified and other improved techniques including the residual resampling step and Markov Chain Monte Carlo method are introduced for target tracking. Performances of the EKF, basic PF and the improved PF are compared in target tracking examples. The simulation results confirm that the improved particle filter outperforms the others.

Design of application specific long period waveguide grating filters using adaptive particle swarm optimization algorithms

International Nuclear Information System (INIS)

Semwal, Girish; Rastogi, Vipul

2014-01-01

We present design optimization of wavelength filters based on long period waveguide gratings (LPWGs) using the adaptive particle swarm optimization (APSO) technique. We demonstrate optimization of the LPWG parameters for single-band, wide-band and dual-band rejection filters for testing the convergence of APSO algorithms. After convergence tests on the algorithms, the optimization technique has been implemented to design more complicated application specific filters such as erbium doped fiber amplifier (EDFA) amplified spontaneous emission (ASE) flattening, erbium doped waveguide amplifier (EDWA) gain flattening and pre-defined broadband rejection filters. The technique is useful for designing and optimizing the parameters of LPWGs to achieve complicated application specific spectra. (paper)

Hybrid Filter Membrane

Science.gov (United States)

Laicer, Castro; Rasimick, Brian; Green, Zachary

2012-01-01

Cabin environmental control is an important issue for a successful Moon mission. Due to the unique environment of the Moon, lunar dust control is one of the main problems that significantly diminishes the air quality inside spacecraft cabins. Therefore, this innovation was motivated by NASA s need to minimize the negative health impact that air-suspended lunar dust particles have on astronauts in spacecraft cabins. It is based on fabrication of a hybrid filter comprising nanofiber nonwoven layers coated on porous polymer membranes with uniform cylindrical pores. This design results in a high-efficiency gas particulate filter with low pressure drop and the ability to be easily regenerated to restore filtration performance. A hybrid filter was developed consisting of a porous membrane with uniform, micron-sized, cylindrical pore channels coated with a thin nanofiber layer. Compared to conventional filter media such as a high-efficiency particulate air (HEPA) filter, this filter is designed to provide high particle efficiency, low pressure drop, and the ability to be regenerated. These membranes have well-defined micron-sized pores and can be used independently as air filters with discreet particle size cut-off, or coated with nanofiber layers for filtration of ultrafine nanoscale particles. The filter consists of a thin design intended to facilitate filter regeneration by localized air pulsing. The two main features of this invention are the concept of combining a micro-engineered straight-pore membrane with nanofibers. The micro-engineered straight pore membrane can be prepared with extremely high precision. Because the resulting membrane pores are straight and not tortuous like those found in conventional filters, the pressure drop across the filter is significantly reduced. The nanofiber layer is applied as a very thin coating to enhance filtration efficiency for fine nanoscale particles. Additionally, the thin nanofiber coating is designed to promote capture of

State and parameter estimation of the heat shock response system using Kalman and particle filters.

Science.gov (United States)

Liu, Xin; Niranjan, Mahesan

2012-06-01

Traditional models of systems biology describe dynamic biological phenomena as solutions to ordinary differential equations, which, when parameters in them are set to correct values, faithfully mimic observations. Often parameter values are tweaked by hand until desired results are achieved, or computed from biochemical experiments carried out in vitro. Of interest in this article, is the use of probabilistic modelling tools with which parameters and unobserved variables, modelled as hidden states, can be estimated from limited noisy observations of parts of a dynamical system. Here we focus on sequential filtering methods and take a detailed look at the capabilities of three members of this family: (i) extended Kalman filter (EKF), (ii) unscented Kalman filter (UKF) and (iii) the particle filter, in estimating parameters and unobserved states of cellular response to sudden temperature elevation of the bacterium Escherichia coli. While previous literature has studied this system with the EKF, we show that parameter estimation is only possible with this method when the initial guesses are sufficiently close to the true values. The same turns out to be true for the UKF. In this thorough empirical exploration, we show that the non-parametric method of particle filtering is able to reliably estimate parameters and states, converging from initial distributions relatively far away from the underlying true values. Software implementation of the three filters on this problem can be freely downloaded from http://users.ecs.soton.ac.uk/mn/HeatShock

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Science.gov (United States)

Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell

2012-01-01

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Sub-micron filter

Science.gov (United States)

Tepper, Frederick [Sanford, FL; Kaledin, Leonid [Port Orange, FL

2009-10-13

Aluminum hydroxide fibers approximately 2 nanometers in diameter and with surface areas ranging from 200 to 650 m.sup.2/g have been found to be highly electropositive. When dispersed in water they are able to attach to and retain electronegative particles. When combined into a composite filter with other fibers or particles they can filter bacteria and nano size particulates such as viruses and colloidal particles at high flux through the filter. Such filters can be used for purification and sterilization of water, biological, medical and pharmaceutical fluids, and as a collector/concentrator for detection and assay of microbes and viruses. The alumina fibers are also capable of filtering sub-micron inorganic and metallic particles to produce ultra pure water. The fibers are suitable as a substrate for growth of cells. Macromolecules such as proteins may be separated from each other based on their electronegative charges.

AGU and Wiley-Blackwell to partner on publication of journals and books

Science.gov (United States)

McEntee, Chris

2012-07-01

AGU has signed a memorandum of understanding (MOU) with Wiley-Blackwell to partner in journal and book publishing. The agreement, effective 1 January 2013, is a significant step forward in transforming AGU publishing consistent with our strategic plan goal of scientific leadership and collaboration. Wiley-Blackwell is the international scientific, technical, medical, and scholarly publishing business of John Wiley & Sons, Inc. Family-owned and publicly traded on the New York Stock Exchange, the company is strong in every major academic and professional field and partners with many of the world's leading societies. Wiley-Blackwell, a leader in developing models for open access and providing developing nations with access to science, publishes nearly 1500 peer-reviewed journals and more than 1500 new books annually. The company publishes approximately 700 society titles.

Effects of Na and Ca on particle size; Effect of filtering on UV absorbance

Data.gov (United States)

U.S. Environmental Protection Agency — Effects of Na and Ca on particle size; Effect of filtering on UV absorbance. This dataset is associated with the following publication: Bouchard, D., C. Knightes, X....

A Novel Multi-Sensor Environmental Perception Method Using Low-Rank Representation and a Particle Filter for Vehicle Reversing Safety

Directory of Open Access Journals (Sweden)

Zutao Zhang

2016-06-01

Full Text Available Environmental perception and information processing are two key steps of active safety for vehicle reversing. Single-sensor environmental perception cannot meet the need for vehicle reversing safety due to its low reliability. In this paper, we present a novel multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety. The proposed system consists of four main steps, namely multi-sensor environmental perception, information fusion, target recognition and tracking using low-rank representation and a particle filter, and vehicle reversing speed control modules. First of all, the multi-sensor environmental perception module, based on a binocular-camera system and ultrasonic range finders, obtains the distance data for obstacles behind the vehicle when the vehicle is reversing. Secondly, the information fusion algorithm using an adaptive Kalman filter is used to process the data obtained with the multi-sensor environmental perception module, which greatly improves the robustness of the sensors. Then the framework of a particle filter and low-rank representation is used to track the main obstacles. The low-rank representation is used to optimize an objective particle template that has the smallest L-1 norm. Finally, the electronic throttle opening and automatic braking is under control of the proposed vehicle reversing control strategy prior to any potential collisions, making the reversing control safer and more reliable. The final system simulation and practical testing results demonstrate the validity of the proposed multi-sensor environmental perception method using low-rank representation and a particle filter for vehicle reversing safety.

Nanoparticle filtration performance of NIOSH-certified particulate air-purifying filtering facepiece respirators: evaluation by light scattering photometric and particle number-based test methods.

Science.gov (United States)

Rengasamy, Samy; Eimer, Benjamin C

2012-01-01

National Institute for Occupational Safety and Health (NIOSH) certification test methods employ charge neutralized NaCl or dioctyl phthalate (DOP) aerosols to measure filter penetration levels of air-purifying particulate respirators photometrically using a TSI 8130 automated filter tester at 85 L/min. A previous study in our laboratory found that widely different filter penetration levels were measured for nanoparticles depending on whether a particle number (count)-based detector or a photometric detector was used. The purpose of this study was to better understand the influence of key test parameters, including filter media type, challenge aerosol size range, and detector system. Initial penetration levels for 17 models of NIOSH-approved N-, R-, and P-series filtering facepiece respirators were measured using the TSI 8130 photometric method and compared with the particle number-based penetration (obtained using two ultrafine condensation particle counters) for the same challenge aerosols generated by the TSI 8130. In general, the penetration obtained by the photometric method was less than the penetration obtained with the number-based method. Filter penetration was also measured for ambient room aerosols. Penetration measured by the TSI 8130 photometric method was lower than the number-based ambient aerosol penetration values. Number-based monodisperse NaCl aerosol penetration measurements showed that the most penetrating particle size was in the 50 nm range for all respirator models tested, with the exception of one model at ~200 nm size. Respirator models containing electrostatic filter media also showed lower penetration values with the TSI 8130 photometric method than the number-based penetration obtained for the most penetrating monodisperse particles. Results suggest that to provide a more challenging respirator filter test method than what is currently used for respirators containing electrostatic media, the test method should utilize a sufficient number

Influence of thermophoresis on particle removal in a moving granular bed filter and heat exchanger

International Nuclear Information System (INIS)

Rudnick, S.N.; First, M.W.; Price, J.M.

1981-01-01

Bench-scale investigations were made to determine the influence of thermophoresis on particle removal in a moving granular bed filter. A continuous flow of 2-mm diameter ceramic granules at ambient temperature entered the top of the filter and moved slowly downward under the influence of gravity countercurrent to the gas stream. At an inlet gas temperature of 240 0 C, gas mass velocity of 0.12 kg/(s.m 2 ), and granule velocities up to 0.015 cm/s, clean bed collection efficiency for a submicrometer sodium chloride aerosol was found to increase the more the gas was cooled, indicating that thermophoretic forces were playing a measurable role in particle collection

Filter-based Aerosol Measurement Experiments using Spherical Aerosol Particles under High Temperature and High Pressure

Energy Technology Data Exchange (ETDEWEB)

Lee, Jong Chan; Jung, Woo Young; Lee, Hyun Chul; Lee, Doo Young [FNC TECH., Yongin (Korea, Republic of)

2016-05-15

Optical Particle Counter (OPC) is used to provide real-time measurement of aerosol concentration and size distribution. Glass fiber membrane filter also be used to measure average mass concentration. Three tests (MTA-1, 2 and 3) have been conducted to study thermal-hydraulic effect, a filtering tendency at given SiO{sub 2} particles. Based on the experimental results, the experiment will be carried out further with a main carrier gas of steam and different aerosol size. The test results will provide representative behavior of the aerosols under various conditions. The aim of the tests, MTA 1, 2 and 3, are to be able to 1) establish the test manuals for aerosol generation, mixing, sampling and measurement system, which defines aerosol preparation, calibration, operating and evaluation method under high pressure and high temperature 2) develop commercial aerosol test modules applicable to the thermal power plant, environmental industry, automobile exhaust gas, chemical plant, HVAC system including nuclear power plant. Based on the test results, sampled aerosol particles in the filter indicate that important parameters affecting aerosol behavior aerosols are 1) system temperature to keep above a evaporation temperature of ethanol and 2) aerosol losses due to the settling by ethanol liquid droplet.

Reducing uncertainties associated with filter-based optical measurements of light absorbing carbon particles with chemical information

Science.gov (United States)

Engström, J. E.; Leck, C.

2011-08-01

The presented filter-based optical method for determination of soot (light absorbing carbon or Black Carbon, BC) can be implemented in the field under primitive conditions and at low cost. This enables researchers with small economical means to perform monitoring at remote locations, especially in the Asia where it is much needed. One concern when applying filter-based optical measurements of BC is that they suffer from systematic errors due to the light scattering of non-absorbing particles co-deposited on the filter, such as inorganic salts and mineral dust. In addition to an optical correction of the non-absorbing material this study provides a protocol for correction of light scattering based on the chemical quantification of the material, which is a novelty. A newly designed photometer was implemented to measure light transmission on particle accumulating filters, which includes an additional sensor recording backscattered light. The choice of polycarbonate membrane filters avoided high chemical blank values and reduced errors associated with length of the light path through the filter. Two protocols for corrections were applied to aerosol samples collected at the Maldives Climate Observatory Hanimaadhoo during episodes with either continentally influenced air from the Indian/Arabian subcontinents (winter season) or pristine air from the Southern Indian Ocean (summer monsoon). The two ways of correction (optical and chemical) lowered the particle light absorption of BC by 63 to 61 %, respectively, for data from the Arabian Sea sourced group, resulting in median BC absorption coefficients of 4.2 and 3.5 Mm-1. Corresponding values for the South Indian Ocean data were 69 and 97 % (0.38 and 0.02 Mm-1). A comparison with other studies in the area indicated an overestimation of their BC levels, by up to two orders of magnitude. This raises the necessity for chemical correction protocols on optical filter-based determinations of BC, before even the sign on the

Reducing uncertainties associated with filter-based optical measurements of light absorbing carbon particles with chemical information

Directory of Open Access Journals (Sweden)

J. E. Engström

2011-08-01

Full Text Available The presented filter-based optical method for determination of soot (light absorbing carbon or Black Carbon, BC can be implemented in the field under primitive conditions and at low cost. This enables researchers with small economical means to perform monitoring at remote locations, especially in the Asia where it is much needed.

One concern when applying filter-based optical measurements of BC is that they suffer from systematic errors due to the light scattering of non-absorbing particles co-deposited on the filter, such as inorganic salts and mineral dust. In addition to an optical correction of the non-absorbing material this study provides a protocol for correction of light scattering based on the chemical quantification of the material, which is a novelty. A newly designed photometer was implemented to measure light transmission on particle accumulating filters, which includes an additional sensor recording backscattered light. The choice of polycarbonate membrane filters avoided high chemical blank values and reduced errors associated with length of the light path through the filter.

Two protocols for corrections were applied to aerosol samples collected at the Maldives Climate Observatory Hanimaadhoo during episodes with either continentally influenced air from the Indian/Arabian subcontinents (winter season or pristine air from the Southern Indian Ocean (summer monsoon. The two ways of correction (optical and chemical lowered the particle light absorption of BC by 63 to 61 %, respectively, for data from the Arabian Sea sourced group, resulting in median BC absorption coefficients of 4.2 and 3.5 Mm⁻¹. Corresponding values for the South Indian Ocean data were 69 and 97 % (0.38 and 0.02 Mm⁻¹. A comparison with other studies in the area indicated an overestimation of their BC levels, by up to two orders of magnitude. This raises the necessity for chemical correction protocols on optical filter

Particle Size Distribution of E-Cigarette Aerosols and the Relationship to Cambridge Filter Pad Collection Efficiency

Directory of Open Access Journals (Sweden)

Alderman Steven L.

2015-01-01

Full Text Available The relatively volatile nature of the particulate matter fraction of e-cigarette aerosols presents an experimental challenge with regard to particle size distribution measure-ments. This is particularly true for instruments requiring a high degree of aerosol dilution. This was illustrated in a previous study, where average particle diameters in the 10-50 nm range were determined by a high-dilution, electrical mobility method. Total particulate matter (TPM masses calculated based on those diameters were orders of magnitude smaller than gravimetrically determined TPM. This discrepancy was believed to result from almost complete particle evaporation at the dilution levels of the electrical mobility analysis. The same study described a spectral transmission measurement of e-cigarette particle size in an undiluted state, and reported particles from 210-380 nm count median diameter. Observed particle number concentrations were in the 109 particles/cm3 range. Additional particle size measurements described here also found e-cigarette particle size to be in the 260-320 nm count median diameter range. Cambridge filter pads have been used for decades to determine TPM yields of tobacco burning cigarettes, and collection of e-cigarette TPM by fibrous filters is predicted to be a highly efficient process over a wide range of filtration flow rates. The results presented in this work provide support for this hypothesis.

Determination of permeability of ultra-fine cupric oxide aerosol through military filters and protective filters

Science.gov (United States)

Kellnerová, E.; Večeřa, Z.; Kellner, J.; Zeman, T.; Navrátil, J.

2018-03-01

The paper evaluates the filtration and sorption efficiency of selected types of military combined filters and protective filters. The testing was carried out with the use of ultra-fine aerosol containing cupric oxide nanoparticles ranging in size from 7.6 nm to 299.6 nm. The measurements of nanoparticles were carried out using a scanning mobility particle sizer before and after the passage through the filter and a developed sampling device at the level of particle number concentration approximately 750000 particles·cm-3. The basic parameters of permeability of ultra-fine aerosol passing through the tested material were evaluated, in particular particle size, efficiency of nanoparticle capture by filter, permeability coefficient and overall filtration efficiency. Results indicate that the military filter and particle filters exhibited the highest aerosol permeability especially in the nanoparticle size range between 100–200 nm, while the MOF filters had the highest permeability in the range of 200 to 300 nm. The Filter Nuclear and the Health and Safety filter had 100% nanoparticle capture efficiency and were therefore the most effective. The obtained measurement results have shown that the filtration efficiency over the entire measured range of nanoparticles was sufficient; however, it was different for particular particle sizes.

Audiovisual Head Orientation Estimation with Particle Filtering in Multisensor Scenarios

Directory of Open Access Journals (Sweden)

Javier Hernando

2007-07-01

Full Text Available This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (camera, microphone in communications or video surveillance systems. The use of particle filters as a unified framework for the estimation of the head orientation for both monomodal and multimodal cases is proposed. In video, we estimate head orientation from color information by exploiting spatial redundancy among cameras. Audio information is processed to estimate the direction of the voice produced by a speaker making use of the directivity characteristics of the head radiation pattern. Furthermore, two different particle filter multimodal information fusion schemes for combining the audio and video streams are analyzed in terms of accuracy and robustness. In the first one, fusion is performed at a decision level by combining each monomodal head pose estimation, while the second one uses a joint estimation system combining information at data level. Experimental results conducted over the CLEAR 2006 evaluation database are reported and the comparison of the proposed multimodal head pose estimation algorithms with the reference monomodal approaches proves the effectiveness of the proposed approach.

Filtering in hybrid dynamic Bayesian networks

DEFF Research Database (Denmark)

Andersen, Morten Nonboe; Andersen, Rasmus Ørum; Wheeler, Kevin

2004-01-01

for inference. We extend the experiment and perform approximate inference using The Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF). Furthermore, we combine these techniques in a 'non-strict' Rao-Blackwellisation framework and apply it to the watertank system. We show that UKF and UKF in a PF...... framework outperform the generic PF, EKF and EKF in a PF framework with respect to accuracy and robustness in terms of estimation RMSE (root-mean-square error). Especially we demonstrate the superiority of UKF in a PF framework when our beliefs of how data was generated are wrong. We also show...... that the choice of network structure is very important for the performance of the generic PF and the EKF algorithms, but not for the UKF algorithms. Furthermore, we investigate the influence of data noise in the watertank simulation. Theory and implementation is based on the theory presented in (v.d. Merwe et al...

LEADER WITH GOLDEN HEART - SRI CA. A. RAGHAVENDRA RAO

OpenAIRE

Aithal Sreeramana P.; Suresh Kumar P.M.; Shailashri V.T.; Prithi Jeevan

2015-01-01

Srinivas group of colleges has come into being from a humble beginning in1988, into a chain of institutions due to its visionary founder Sri CA A Raghavendra Rao. Today it spreads over 18 colleges with 70 courses and over 12000 students generating livelihood to 3500 employees and their families. His leadership qualities and values are distinct. He is wired like business people but bottom line oriented and extraordinarily committed to results. The steep ascend from humble person to an accompl...

A model-based adaptive state of charge estimator for a lithium-ion battery using an improved adaptive particle filter

International Nuclear Information System (INIS)

Ye, Min; Guo, Hui; Cao, Binggang

2017-01-01

Highlights: • Propose an improved adaptive particle swarm filter method. • The SoC estimation method for the battery based on the adaptive particle swarm filter is presented. • The algorithm is validated by the case study of different aged extent batteries. • The effectiveness and applicability of the algorithm are validated by the LiPB batteries. - Abstract: Obtaining accurate parameters, state of charge (SoC) and capacity of a lithium-ion battery is crucial for a battery management system, and establishing a battery model online is complex. In addition, the errors and perturbations of the battery model dramatically increase throughout the battery lifetime, making it more challenging to model the battery online. To overcome these difficulties, this paper provides three contributions: (1) To improve the robustness of the adaptive particle filter algorithm, an error analysis method is added to the traditional adaptive particle swarm algorithm. (2) An online adaptive SoC estimator based on the improved adaptive particle filter is presented; this estimator can eliminate the estimation error due to battery degradation and initial SoC errors. (3) The effectiveness of the proposed method is verified using various initial states of lithium nickel manganese cobalt oxide (NMC) cells and lithium-ion polymer (LiPB) batteries. The experimental analysis shows that the maximum errors are less than 1% for both the voltage and SoC estimations and that the convergence time of the SoC estimation decreased to 120 s.

Frequency Diverse Array Radar Cramér-Rao Lower Bounds for Estimating Direction, Range, and Velocity

Directory of Open Access Journals (Sweden)

Yongbing Wang

2014-01-01

Full Text Available Different from phased-array radar, frequency diverse array (FDA radar offers range-dependent beampattern and thus provides new application potentials. But there is a fundamental question: what estimation performance can achieve for an FDA radar? In this paper, we derive FDA radar Cramér-Rao lower bounds (CRLBs for estimating direction, range (time delay, and velocity (Doppler shift. Two different data models including pre- and postmatched filtering are investigated separately. As the FDA radar has range-angle coupling, we use a simple transmit subaperturing strategy which divides the whole array into two subarrays, each uses a distinct frequency increment. Assuming temporally white Gaussian noise and linear frequency modulated transmit signal, extensive simulation examples are performed. When compared to conventional phased-array radar, FDA can yield better CRLBs for estimating the direction, range, and velocity. Moreover, the impacts of the element number and frequency increment are also analyzed. Simulation results show that the CRLBs decrease with the increase of the elements number and frequency increment.

The impact of sensor errors and building structures on particle filter-based inertial positioning

DEFF Research Database (Denmark)

Toftkjær, Thomas; Kjærgaard, Mikkel Baun

2012-01-01

Positioning systems that do not depend on in-building infrastructures are critical for enabling a range of applications within pervasive computing. Particle filter-based inertial positioning promises infrastructure-less positioning, but previous research has not provided an understanding of how t...

Fingerprinting Localization Method Based on TOA and Particle Filtering for Mines

Directory of Open Access Journals (Sweden)

Boming Song

2017-01-01

Full Text Available Accurate target localization technology plays a very important role in ensuring mine safety production and higher production efficiency. The localization accuracy of a mine localization system is influenced by many factors. The most significant factor is the non-line of sight (NLOS propagation error of the localization signal between the access point (AP and the target node (Tag. In order to improve positioning accuracy, the NLOS error must be suppressed by an optimization algorithm. However, the traditional optimization algorithms are complex and exhibit poor optimization performance. To solve this problem, this paper proposes a new method for mine time of arrival (TOA localization based on the idea of comprehensive optimization. The proposed method utilizes particle filtering to reduce the TOA data error, and the positioning results are further optimized with fingerprinting based on the Manhattan distance. This proposed method combines the advantages of particle filtering and fingerprinting localization. It reduces algorithm complexity and has better error suppression performance. The experimental results demonstrate that, as compared to the symmetric double-sided two-way ranging (SDS-TWR method or received signal strength indication (RSSI based fingerprinting method, the proposed method has a significantly improved localization performance, and the environment adaptability is enhanced.

Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Supriya Dhabal

2014-01-01

Full Text Available We present a novel hybrid algorithm based on particle swarm optimization (PSO and simulated annealing (SA for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.

Channel Estimation for Filter Bank Multicarrier Systems in Low SNR Environments

Energy Technology Data Exchange (ETDEWEB)

Driggs, Jonathan; Sibbett, Taylor; Moradiy, Hussein; Farhang-Boroujeny, Behrouz

2017-05-01

Channel estimation techniques are crucial for reliable communications. This paper is concerned with channel estimation in a filter bank multicarrier spread spectrum (FBMCSS) system. We explore two channel estimator options: (i) a method that makes use of a periodic preamble and mimics the channel estimation techniques that are widely used in OFDM-based systems; and (ii) a method that stays within the traditional realm of filter bank signal processing. For the case where the channel noise is white, both methods are analyzed in detail and their performance is compared against their respective Cramer-Rao Lower Bounds (CRLB). Advantages and disadvantages of the two methods under different channel conditions are given to provide insight to the reader as to when one will outperform the other.

Anti-clogging filter system

Science.gov (United States)

Brown, Erik P.

2015-05-19

An anti-clogging filter system for filtering a fluid containing large particles and small particles includes an enclosure with at least one individual elongated tubular filter element in the enclosure. The individual elongated tubular filter element has an internal passage, a closed end, an open end, and a filtering material in or on the individual elongated tubular filter element. The fluid travels through the open end of the elongated tubular element and through the internal passage and through the filtering material. An anti-clogging element is positioned on or adjacent the individual elongated tubular filter element and provides a fluid curtain that preferentially directs the larger particulates to one area of the filter material allowing the remainder of the filter material to remain more efficient.

Particles in swimming pool filters – Does pH determine the DBP formation?

DEFF Research Database (Denmark)

Hansen, Kamilla Marie Speht; Willach, Sarah; Mosbæk, Hans

2012-01-01

The formation was investigated for different groups of disinfection byproducts (DBPs) during chlorination of filter particles from swimming pools at different pH-values and the toxicity was estimated. Specifically, the formation of the DBP group trihalomethanes (THMs), which is regulated in many...... or initial free chlorine concentrations the particles were chlorinated at different pH-values in the relevant range for swimming pools. THM and HAA formations were reduced by decreasing pH while HAN formation increased with decreasing pH. Based on the organic content the relative DBP formation from...

Aggregated wind power generation probabilistic forecasting based on particle filter

International Nuclear Information System (INIS)

Li, Pai; Guan, Xiaohong; Wu, Jiang

2015-01-01

Highlights: • A new method for probabilistic forecasting of aggregated wind power generation. • A dynamic system is established based on a numerical weather prediction model. • The new method handles the non-Gaussian and time-varying wind power uncertainties. • Particle filter is applied to forecast predictive densities of wind generation. - Abstract: Probability distribution of aggregated wind power generation in a region is one of important issues for power system daily operation. This paper presents a novel method to forecast the predictive densities of the aggregated wind power generation from several geographically distributed wind farms, considering the non-Gaussian and non-stationary characteristics in wind power uncertainties. Based on a mesoscale numerical weather prediction model, a dynamic system is established to formulate the relationship between the atmospheric and near-surface wind fields of geographically distributed wind farms. A recursively backtracking framework based on the particle filter is applied to estimate the atmospheric state with the near-surface wind power generation measurements, and to forecast the possible samples of the aggregated wind power generation. The predictive densities of the aggregated wind power generation are then estimated based on these predicted samples by a kernel density estimator. In case studies, the new method presented is tested on a 9 wind farms system in Midwestern United States. The testing results that the new method can provide competitive interval forecasts for the aggregated wind power generation with conventional statistical based models, which validates the effectiveness of the new method

Sensory Pollution from Bag Filters, Carbon Filters and Combinations

DEFF Research Database (Denmark)

Bekö, Gabriel; Clausen, Geo; Weschler, Charles J.

2008-01-01

by an upstream pre-filter (changed monthly), an EU7 filter protected by an upstream activated carbon (AC) filter, and EU7 filters with an AC filter either downstream or both upstream and downstream. In addition, two types of stand-alone combination filters were evaluated: a bag-type fiberglass filter...... that contained AC and a synthetic fiber cartridge filter that contained AC. Air that had passed through used filters was most acceptable for those sets in which an AC filter was used downstream of the particle filter. Comparable air quality was achieved with the stand-alone bag filter that contained AC...

Assimilation of microwave brightness temperatures for soil moisture estimation using particle filter

International Nuclear Information System (INIS)

Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y

2014-01-01

Soil moisture plays a significant role in global water cycles. Both model simulations and remote sensing observations have their limitations when estimating soil moisture on a large spatial scale. Data assimilation (DA) is a promising tool which can combine model dynamics and remote sensing observations to obtain more precise ground soil moisture distribution. Among various DA methods, the particle filter (PF) can be applied to non-linear and non-Gaussian systems, thus holding great potential for DA. In this study, a data assimilation scheme based on the residual resampling particle filter (RR-PF) was developed to assimilate microwave brightness temperatures into the macro-scale semi-distributed Variance Infiltration Capacity (VIC) Model to estimate surface soil moisture. A radiative transfer model (RTM) was used to link brightness temperatures with surface soil moisture. Finally, the data assimilation scheme was validated by experimental data obtained at Arizona during the Soil Moisture Experiment 2004 (SMEX04). The results show that the estimation accuracy of soil moisture can be improved significantly by RR-PF through assimilating microwave brightness temperatures into VIC model. Both the overall trends and specific values of the assimilation results are more consistent with ground observations compared with model simulation results

Estimation of the Dynamic States of Synchronous Machines Using an Extended Particle Filter

Energy Technology Data Exchange (ETDEWEB)

Zhou, Ning; Meng, Da; Lu, Shuai

2013-11-11

In this paper, an extended particle filter (PF) is proposed to estimate the dynamic states of a synchronous machine using phasor measurement unit (PMU) data. A PF propagates the mean and covariance of states via Monte Carlo simulation, is easy to implement, and can be directly applied to a non-linear system with non-Gaussian noise. The extended PF modifies a basic PF to improve robustness. Using Monte Carlo simulations with practical noise and model uncertainty considerations, the extended PF’s performance is evaluated and compared with the basic PF and an extended Kalman filter (EKF). The extended PF results showed high accuracy and robustness against measurement and model noise.

Kalman filter with a linear state model for PDR+WLAN positioning and its application to assisting a particle filter

Science.gov (United States)

Raitoharju, Matti; Nurminen, Henri; Piché, Robert

2015-12-01

Indoor positioning based on wireless local area network (WLAN) signals is often enhanced using pedestrian dead reckoning (PDR) based on an inertial measurement unit. The state evolution model in PDR is usually nonlinear. We present a new linear state evolution model for PDR. In simulated-data and real-data tests of tightly coupled WLAN-PDR positioning, the positioning accuracy with this linear model is better than with the traditional models when the initial heading is not known, which is a common situation. The proposed method is computationally light and is also suitable for smoothing. Furthermore, we present modifications to WLAN positioning based on Gaussian coverage areas and show how a Kalman filter using the proposed model can be used for integrity monitoring and (re)initialization of a particle filter.

Study of the effect of humidity, particle hygroscopicity and size on the mass loading capacity of HEPA filters

International Nuclear Information System (INIS)

Gupta, A.

1992-01-01

The effect of humidity, particle hygroscopicity and size on the mass loading capacity of glass fiber HEPA filters has been studied. At humidifies above the deliquescent point, the pressure drop across the HEPA filter increased non-linearly with the areal loading density (mass collected/filtration area) of NaCl aerosol, thus significantly reducing the mass loading capacity of the filter compared to dry hygroscopic or non-hygroscopic particle mass loadings. The specific cake resistance, K 2 , has been computed for different test conditions and used as a measure of the mass loading capacity. K. was found to decrease with increasing humidity for the non-hygroscopic aluminum oxide particles and the hygroscopic NaCl particles (at humidities below the deliquescent point). It is postulated that an increase in humidity leads to the formation of a more open particulate cake which lowers the pressure drop for a given mass loading. A formula for predicting K 2 for lognormally distributed aerosols (parameters obtained from impactor data) is derived. The resistance factor, R, calculated using this formula was compared to the theoretical R calculated using the Rudnick-Happel expression. For the non-hygroscopic aluminum oxide the agreement was good but for the hygroscopic sodium chloride, due to large variation in the cake porosity estimates, the agreement was poor

Effect of humidity and particle hygroscopicity on the mass loading capacity of high efficiency particulate air (HEPA) filters

International Nuclear Information System (INIS)

Gupta, A.; Biswas, P.; Monson, P.R.; Novick, V.J.

1993-01-01

The effect of humidity, particle hygroscopicity, and size on the mass loading capacity of glass fiber high efficiency particulate air filters was studied. Above the deliquescent point, the pressure drop across the filter increased nonlinearly with areal loading density (mass collected/filtration area) of a NaCl aerosol, thus significantly reducing the mass loading capacity of the filter compared to dry hygroscopic or nonhygroscopic particle mass loadings. The specific cake resistance K 2 was computed for different test conditions and used as a measure of the mass loading capacity. K 2 was found to decrease with increasing humidity for nonhygroscopic aluminum oxide particles and for hygroscopic NaCl particles (at humidities below the deliquescent point). It is postulated that an increase in humidity leads to the formation of a more open particulate cake which lowers the pressure drop for a given mass loading. A formula for predicting K 2 for lognormally distributed aerosols (parameters obtained from impactor data) was derived. The resistance factor, R, calculated using this formula was compared to the theoretical R calculated using the Rudnick-Happel expression. For the nonhygroscopic aluminum oxide, the agreement was good but for the hygroscopic sodium chloride, due to large variation in the cake porosity estimates, the agreement was poor. 17 refs., 6 figs., 3 tabs

Detection of image structures using the Fisher information and the Rao metric.

Science.gov (United States)

Maybank, Stephen J

2004-12-01

In many detection problems, the structures to be detected are parameterized by the points of a parameter space. If the conditional probability density function for the measurements is known, then detection can be achieved by sampling the parameter space at a finite number of points and checking each point to see if the corresponding structure is supported by the data. The number of samples and the distances between neighboring samples are calculated using the Rao metric on the parameter space. The Rao metric is obtained from the Fisher information which is, in turn, obtained from the conditional probability density function. An upper bound is obtained for the probability of a false detection. The calculations are simplified in the low noise case by making an asymptotic approximation to the Fisher information. An application to line detection is described. Expressions are obtained for the asymptotic approximation to the Fisher information, the volume of the parameter space, and the number of samples. The time complexity for line detection is estimated. An experimental comparison is made with a Hough transform-based method for detecting lines.

Autonomous Positioning Techniques Based on Cramér-Rao Lower Bound Analysis

Directory of Open Access Journals (Sweden)

Urruela Andreu

2006-01-01

Full Text Available We consider the problem of autonomously locating a number of asynchronous sensor nodes in a wireless network. A strong focus lies on reducing the processing resources needed to solve the relative positioning problem, an issue of great interest in resource-constrained wireless sensor networks. In the first part of the paper, based on a well-known derivation of the Cramér-Rao lower bound for the asynchronous sensor positioning problem, we are able to construct optimal preprocessing methods for sensor clock-offset cancellation. A cancellation of unknown clock-offsets from the asynchronous positioning problem reduces processing requirements, and, under certain reasonable assumptions, allows for statistically efficient distributed positioning algorithms. Cramér-Rao lower bound theory may also be used for estimating the performance of a positioning algorithm. In the second part of this paper, we exploit this property in developing a distributed algorithm, where the global positioning problem is solved suboptimally, using a divide-and-conquer approach of low complexity. The performance of this suboptimal algorithm is evaluated through computer simulation, and compared to previously published algorithms.

Estimating volatility and model parameters of stochastic volatility models with jumps using particle filter

NARCIS (Netherlands)

Aihara, ShinIchi; Bagchi, Arunabha; Saha, S.

Despite the success of particle filter, there are two factors which cause difficulties in its implementation. The first one is the choice of importance functions commonly used in the literature which are far from being optimal. The second one is the combined state and parameter estimation problem.

The Improved Locating Algorithm of Particle Filter Based on ROS Robot

Science.gov (United States)

Fang, Xun; Fu, Xiaoyang; Sun, Ming

2018-03-01

This paperanalyzes basic theory and primary algorithm of the real-time locating system and SLAM technology based on ROS system Robot. It proposes improved locating algorithm of particle filter effectively reduces the matching time of laser radar and map, additional ultra-wideband technology directly accelerates the global efficiency of FastSLAM algorithm, which no longer needs searching on the global map. Meanwhile, the re-sampling has been largely reduced about 5/6 that directly cancels the matching behavior on Roboticsalgorithm.

Estimating particle number size distributions from multi-instrument observations with Kalman Filtering

Energy Technology Data Exchange (ETDEWEB)

Viskari, T.

2012-07-01

Atmospheric aerosol particles have several important effects on the environment and human society. The exact impact of aerosol particles is largely determined by their particle size distributions. However, no single instrument is able to measure the whole range of the particle size distribution. Estimating a particle size distribution from multiple simultaneous measurements remains a challenge in aerosol physical research. Current methods to combine different measurements require assumptions concerning the overlapping measurement ranges and have difficulties in accounting for measurement uncertainties. In this thesis, Extended Kalman Filter (EKF) is presented as a promising method to estimate particle number size distributions from multiple simultaneous measurements. The particle number size distribution estimated by EKF includes information from prior particle number size distributions as propagated by a dynamical model and is based on the reliabilities of the applied information sources. Known physical processes and dynamically evolving error covariances constrain the estimate both over time and particle size. The method was tested with measurements from Differential Mobility Particle Sizer (DMPS), Aerodynamic Particle Sizer (APS) and nephelometer. The particle number concentration was chosen as the state of interest. The initial EKF implementation presented here includes simplifications, yet the results are positive and the estimate successfully incorporated information from the chosen instruments. For particle sizes smaller than 4 micrometers, the estimate fits the available measurements and smooths the particle number size distribution over both time and particle diameter. The estimate has difficulties with particles larger than 4 micrometers due to issues with both measurements and the dynamical model in that particle size range. The EKF implementation appears to reduce the impact of measurement noise on the estimate, but has a delayed reaction to sudden

Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

Directory of Open Access Journals (Sweden)

Ye Tian

2014-01-01

Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

Human-Manipulator Interface Using Particle Filter

Directory of Open Access Journals (Sweden)

Guanglong Du

2014-01-01

Full Text Available This paper utilizes a human-robot interface system which incorporates particle filter (PF and adaptive multispace transformation (AMT to track the pose of the human hand for controlling the robot manipulator. This system employs a 3D camera (Kinect to determine the orientation and the translation of the human hand. We use Camshift algorithm to track the hand. PF is used to estimate the translation of the human hand. Although a PF is used for estimating the translation, the translation error increases in a short period of time when the sensors fail to detect the hand motion. Therefore, a methodology to correct the translation error is required. What is more, to be subject to the perceptive limitations and the motor limitations, human operator is hard to carry out the high precision operation. This paper proposes an adaptive multispace transformation (AMT method to assist the operator to improve the accuracy and reliability in determining the pose of the robot. The human-robot interface system was experimentally tested in a lab environment, and the results indicate that such a system can successfully control a robot manipulator.

Cascaded Kalman and particle filters for photogrammetry based gyroscope drift and robot attitude estimation.

Science.gov (United States)

Sadaghzadeh N, Nargess; Poshtan, Javad; Wagner, Achim; Nordheimer, Eugen; Badreddin, Essameddin

2014-03-01

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model. Nonlinear attitude kinematics, drift and robot angular movement dynamics each in 3 dimensions result in a nonlinear high dimensional system. To reduce the complexity, we propose a decomposition of system to cascaded subsystems and then design separate cascaded observers. This design leads to an easier tuning and more precise debugging from the perspective of programming and such a setting is well suited for a cooperative modular system with noticeably reduced computation time. Kalman Filtering (KF) is employed for the linear and Gaussian subsystem consisting of angular velocity and drift dynamics together with gyroscope measurement. The estimated angular velocity is utilized as input of the second Particle Filtering (PF) based observer in two scenarios of stochastic and deterministic inputs. Simulation results are provided to show the efficiency of the proposed method. Moreover, the experimental results based on data from a 3D MEMS IMU and a 3D camera system are used to demonstrate the efficiency of the method. © 2013 ISA Published by ISA All rights reserved.

Fisher Information and the Quantum Cramér-Rao Sensitivity Limit of Continuous Measurements

DEFF Research Database (Denmark)

Gammelmark, Søren; Mølmer, Klaus

2014-01-01

Precision measurements with quantum systems rely on our ability to trace the differences between experimental signals to variations in unknown physical parameters. In this Letter we derive the Fisher information and the ensuing Cramér-Rao sensitivity limit for parameter estimation by continuous...

Real-Time and Accurate Indoor Localization with Fusion Model of Wi-Fi Fingerprint and Motion Particle Filter

Directory of Open Access Journals (Sweden)

Xinlong Jiang

2015-01-01

Full Text Available As the development of Indoor Location Based Service (Indoor LBS, a timely localization and smooth tracking with high accuracy are desperately needed. Unfortunately, any single method cannot meet the requirement of both high accuracy and real-time ability at the same time. In this paper, we propose a fusion location framework with Particle Filter using Wi-Fi signals and motion sensors. In this framework, we use Extreme Learning Machine (ELM regression algorithm to predict position based on motion sensors and use Wi-Fi fingerprint location result to solve the error accumulation of motion sensors based location occasionally with Particle Filter. The experiments show that the trajectory is smoother as the real one than the traditional Wi-Fi fingerprint method.

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering.

Science.gov (United States)

Savran, Arman; Cao, Houwei; Shah, Miraj; Nenkova, Ani; Verma, Ragini

2012-01-01

We present experiments on fusing facial video, audio and lexical indicators for affect estimation during dyadic conversations. We use temporal statistics of texture descriptors extracted from facial video, a combination of various acoustic features, and lexical features to create regression based affect estimators for each modality. The single modality regressors are then combined using particle filtering, by treating these independent regression outputs as measurements of the affect states in a Bayesian filtering framework, where previous observations provide prediction about the current state by means of learned affect dynamics. Tested on the Audio-visual Emotion Recognition Challenge dataset, our single modality estimators achieve substantially higher scores than the official baseline method for every dimension of affect. Our filtering-based multi-modality fusion achieves correlation performance of 0.344 (baseline: 0.136) and 0.280 (baseline: 0.096) for the fully continuous and word level sub challenges, respectively.

Enhanced Prognostic Model for Lithium Ion Batteries Based on Particle Filter State Transition Model Modification

Directory of Open Access Journals (Sweden)

Buddhi Arachchige

2017-11-01

Full Text Available This paper focuses on predicting the End of Life and End of Discharge of Lithium ion batteries using a battery capacity fade model and a battery discharge model. The proposed framework will be able to estimate the Remaining Useful Life (RUL and the Remaining charge through capacity fade and discharge models. A particle filter is implemented that estimates the battery’s State of Charge (SOC and State of Life (SOL by utilizing the battery’s physical data such as voltage, temperature, and current measurements. The accuracy of the prognostic framework has been improved by enhancing the particle filter state transition model to incorporate different environmental and loading conditions without retuning the model parameters. The effect of capacity fade in the reduction of the EOD (End of Discharge time with cycling has also been included, integrating both EOL (End of Life and EOD prediction models in order to get more accuracy in the estimations.

Perturbed soliton excitations of Rao-dust Alfvén waves in magnetized dusty plasmas

Energy Technology Data Exchange (ETDEWEB)

Kavitha, L., E-mail: louiskavitha@yahoo.co.in [Department of Physics, School of Basic and Applied Sciences, Central University of Tamil Nadu, Thiruvarur 610 101 (India); The Abdus Salam International Centre for Theoretical Physics, Trieste (Italy); Lavanya, C.; Senthil Kumar, V. [Department of Physics, Periyar University, Salem, Tamil Nadu 636 011 (India); Gopi, D. [Department of Chemistry, Periyar University, Salem 636 011 (India); Center for Nanoscience and Nanotechnology, Periyar University, Salem, Tamil Nadu 636 011 (India); Pasqua, A. [Department of Physics, University of Trieste, Trieste (Italy)

2016-04-15

We investigate the propagation dynamics of the perturbed soliton excitations in a three component fully ionized dusty magnetoplasma consisting of electrons, ions, and heavy charged dust particulates. We derive the governing equation of motion for the two dimensional Rao-dust magnetohydrodynamic (R-D-MHD) wave by employing the inertialess electron equation of motion, inertial ion equation of motion, the continuity equations in a plasma with immobile charged dust grains, together with the Maxwell's equations, by assuming quasi neutrality and neglecting the displacement current in Ampere's law. Furthermore, we assume the massive dust particles are practically immobile since we are interested in timescales much shorter than the dusty plasma period, thereby neglecting any damping of the modes due to the grain charge fluctuations. We invoke the reductive perturbation method to represent the governing dynamics by a perturbed cubic nonlinear Schrödinger (pCNLS) equation. We solve the pCNLS, along the lines of Kodama-Ablowitz multiple scale nonlinear perturbation technique and explored the R-D-MHD waves as solitary wave excitations in a magnetized dusty plasma. Since Alfvén waves play an important role in energy transport in driving field-aligned currents, particle acceleration and heating, solar flares, and the solar wind, this representation of R-D-MHD waves as soliton excitations may have extensive applications to study the lower part of the earth's ionosphere.

Optimal Nonlinear Filter for INS Alignment

Institute of Scientific and Technical Information of China (English)

赵瑞; 顾启泰

2002-01-01

All the methods to handle the inertial navigation system (INS) alignment were sub-optimal in the past. In this paper, particle filtering (PF) as an optimal method is used for solving the problem of INS alignment. A sub-optimal two-step filtering algorithm is presented to improve the real-time performance of PF. The approach combines particle filtering with Kalman filtering (KF). Simulation results illustrate the superior performance of these approaches when compared with extended Kalman filtering (EKF).

Estimation of aerosol particle number distribution with Kalman Filtering – Part 2: Simultaneous use of DMPS, APS and nephelometer measurements

Directory of Open Access Journals (Sweden)

T. Viskari

2012-12-01

Full Text Available Extended Kalman Filter (EKF is used to estimate particle size distributions from observations. The focus here is on the practical application of EKF to simultaneously merge information from different types of experimental instruments. Every 10 min, the prior state estimate is updated with size-segregating measurements from Differential Mobility Particle Sizer (DMPS and Aerodynamic Particle Sizer (APS as well as integrating measurements from a nephelometer. Error covariances are approximate in our EKF implementation. The observation operator assumes a constant particle density and refractive index. The state estimates are compared to particle size distributions that are a composite of DMPS and APS measurements. The impact of each instrument on the size distribution estimate is studied. Kalman Filtering of DMPS and APS yielded a temporally consistent state estimate. This state estimate is continuous over the overlapping size range of DMPS and APS. Inclusion of the integrating measurements further reduces the effect of measurement noise. Even with the present approximations, EKF is shown to be a very promising method to estimate particle size distribution with observations from different types of instruments.

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

Science.gov (United States)

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava; Lantz, Steven; Lefebvre, Matthieu; Masciovecchio, Mario; McDermott, Kevin; Riley, Daniel; Tadel, Matevž; Wittich, Peter; Würthwein, Frank; Yagil, Avi

2017-08-01

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

Directory of Open Access Journals (Sweden)

Cerati Giuseppe

2017-01-01

Full Text Available For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU, ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC, for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

Energy Technology Data Exchange (ETDEWEB)

Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U.; Riley, Daniel [Cornell U., LNS; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

2017-01-01

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particle tracks during event reconstruction. This is expected to become by far the dominant problem at the High-Luminosity Large Hadron Collider (HL-LHC), for example. Today the most common track finding methods are those based on the Kalman filter. Experience with Kalman techniques on real tracking detector systems has shown that they are robust and provide high physics performance. This is why they are currently in use at the LHC, both in the trigger and offine. Previously we reported on the significant parallel speedups that resulted from our investigations to adapt Kalman filters to track fitting and track building on Intel Xeon and Xeon Phi. Here, we discuss our progresses toward the understanding of these processors and the new developments to port the Kalman filter to NVIDIA GPUs.

Multi-parameter studies of environmental aerosols with cascade track filters

International Nuclear Information System (INIS)

Ensinger, W.; Guo, S.-L.; Vater, P.; Brandt, R.

2005-01-01

Aerosols in the air in a factory processing nuclear reactor fuel material were collected by using cascade Kapton track filters with outer pore sizes of 12.8, 4.0 and 1.0μm consecutively and a conventional filter of glass fiber being behind to collect all aerosol particles left-over. The volume of air passed through the filters was measured by a flow meter. The weight of aerosol particles on each filter was obtained by the weight difference of the filter before and after collection of aerosol particles. α-activity on each filter was measured with a methane gas flow proportional counter. The sizes and elemental compositions of aerosol particles on the filters were analyzed by using a scanning electron microscope and an electron microprobe. Special attention was given to uranium aerosol particles. The median sizes of uranium aerosol particles were obtained being 1.97, 1.33 and 0.72μm on the first, second and third filter, respectively. The median size of all the uranium aerosol particles on the three track filters was 1.25μm

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Haakon

2016-01-08

The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

Multilevel ensemble Kalman filtering

KAUST Repository

Hoel, Haakon; Chernov, Alexey; Law, Kody; Nobile, Fabio; Tempone, Raul

2016-01-01

The ensemble Kalman filter (EnKF) is a sequential filtering method that uses an ensemble of particle paths to estimate the means and covariances required by the Kalman filter by the use of sample moments, i.e., the Monte Carlo method. EnKF is often both robust and efficient, but its performance may suffer in settings where the computational cost of accurate simulations of particles is high. The multilevel Monte Carlo method (MLMC) is an extension of classical Monte Carlo methods which by sampling stochastic realizations on a hierarchy of resolutions may reduce the computational cost of moment approximations by orders of magnitude. In this work we have combined the ideas of MLMC and EnKF to construct the multilevel ensemble Kalman filter (MLEnKF) for the setting of finite dimensional state and observation spaces. The main ideas of this method is to compute particle paths on a hierarchy of resolutions and to apply multilevel estimators on the ensemble hierarchy of particles to compute Kalman filter means and covariances. Theoretical results and a numerical study of the performance gains of MLEnKF over EnKF will be presented. Some ideas on the extension of MLEnKF to settings with infinite dimensional state spaces will also be presented.

Log-Optimal Portfolio Selection Using the Blackwell Approachability Theorem

OpenAIRE

V'yugin, Vladimir

2014-01-01

We present a method for constructing the log-optimal portfolio using the well-calibrated forecasts of market values. Dawid's notion of calibration and the Blackwell approachability theorem are used for computing well-calibrated forecasts. We select a portfolio using this "artificial" probability distribution of market values. Our portfolio performs asymptotically at least as well as any stationary portfolio that redistributes the investment at each round using a continuous function of side in...

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures

Energy Technology Data Exchange (ETDEWEB)

Cerati, Giuseppe [Fermilab; Elmer, Peter [Princeton U.; Krutelyov, Slava [UC, San Diego; Lantz, Steven [Cornell U., Phys. Dept.; Lefebvre, Matthieu [Princeton U.; Masciovecchio, Mario [UC, San Diego; McDermott, Kevin [Cornell U., Phys. Dept.; Riley, Daniel [Cornell U., Phys. Dept.; Tadel, Matevž [UC, San Diego; Wittich, Peter [Cornell U., Phys. Dept.; Würthwein, Frank [UC, San Diego; Yagil, Avi [UC, San Diego

2017-11-16

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Examples include the Intel Xeon Phi, GPGPUs, and similar technologies. Algorithms should accordingly be designed with ample amounts of fine-grained parallelism if they are to realize the full performance of the hardware. This requirement can be challenging for algorithms that are naturally expressed as a sequence of small-matrix operations, such as the Kalman filter methods widely in use in high-energy physics experiments. In the High-Luminosity Large Hadron Collider (HL-LHC), for example, one of the dominant computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction; today, the most common track-finding methods are those based on the Kalman filter. Experience at the LHC, both in the trigger and offline, has shown that these methods are robust and provide high physics performance. Previously we reported the significant parallel speedups that resulted from our efforts to adapt Kalman-filter-based tracking to many-core architectures such as Intel Xeon Phi. Here we report on how effectively those techniques can be applied to more realistic detector configurations and event complexity.

PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

Science.gov (United States)

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

Hot-Gas Filter Ash Characterization Project

Energy Technology Data Exchange (ETDEWEB)

Swanson, M.L.; Hurley, J.P.; Dockter, B.A.; O`Keefe, C.A.

1997-07-01

Large-scale hot-gas filter testing over the past 10 years has revealed numerous cases of cake buildup on filter elements that has been difficult, if not impossible, to remove. At times, the cake can blind or bridge between candle filters, leading to filter failure. Physical factors, including particle-size distribution, particle shape, the aerodynamics of deposition, and system temperature, contribute to the difficulty in removing the cake, but chemical factors such as surface composition and gas-solid reactions also play roles in helping to bond the ash to the filters or to itself. This project is designed to perform the research necessary to determine the fuel-, sorbent-, and operations-related conditions that lead to blinding or bridging of hot-gas particle filters. The objectives of the project are threefold: (1) Determine the mechanisms by which a difficult-to-clean ash is formed and how it bridges hot-gas filters (2) Develop a method to determine the rate of bridging based on analyses of the feed coal and sorbent, filter properties, and system operating conditions and (3) Suggest and test ways to prevent filter bridging.

A spin filter polarimeter and an α-particle D-state study

International Nuclear Information System (INIS)

Lemieux, S.K.

1993-01-01

A Spin Filter Polarimeter (SFP) which reveals populations of individual hyperfine states of nuclear spin-polarized H ± (or D ± ) beams has been tested. the SFP is based on unique properties of a three-level interaction in the 2S 1/2 and 2P 1/2 states of the hydrogen (or deuterium) atoms, created when the polarized ion beams pick up electrons in cesium vapor. The SFP has potential for an absolute accuracy of better than 1.5%, thus it could be used for calibrating polarimeters absolutely for low energy experiments for which no nuclear polarization standard exists. Test results show that the SFP provides a quick and elegant measure of the relative hyperfine state populations in the beam. This α-particle study is a small part of a larger project studying the deuteron-deuteron configuration of the α-particle wave function. The differential cross section and tensor analyzing powers (TAP) were measured for the 50 Ti(bar d,α) 48 Sc reaction to the J π = 7 + state in 48 Sc at E x = 1.097 MeV and compared with exact finite-range distorted-wave Born approximation (DWBA) calculations. The DWBA calculations use realistic α-particle wave functions generated from variational Monte-Carlo calculations

Developing particulate thin filter using coconut fiber for motor vehicle emission

Science.gov (United States)

Wardoyo, A. Y. P.; Juswono, U. P.; Riyanto, S.

2016-03-01

Amounts of motor vehicles in Indonesia have been recognized a sharply increase from year to year with the increment reaching to 22 % per annum. Meanwhile motor vehicles produce particulate emissions in different sizes with high concentrations depending on type of vehicles, fuels, and engine capacity. Motor Particle emissions are not only to significantly contribute the atmosphric particles but also adverse to human health. In order to reduce the particle emission, it is needed a filter. This study was aimed to develop a thin filter using coconut fiber to reduce particulate emissions for motor vehicles. The filter was made of coconut fibers that were grinded into power and mixed with glues. The filter was tested by the measurements of particle concentrations coming out from the vehicle exhaust directly and the particle concentrations after passing through the filter. The efficiency of the filter was calculated by ratio of the particle concentrations before comming in the filter to the particle conentrations after passing through the filter. The results showed that the efficiency of the filter obtained more than 30 %. The efficiency increases sharply when a number of the filters are arranged paralelly.

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

Science.gov (United States)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of

Three dimensional indoor positioning based on visible light with Gaussian mixture sigma-point particle filter technique

Science.gov (United States)

Gu, Wenjun; Zhang, Weizhi; Wang, Jin; Amini Kashani, M. R.; Kavehrad, Mohsen

2015-01-01

Over the past decade, location based services (LBS) have found their wide applications in indoor environments, such as large shopping malls, hospitals, warehouses, airports, etc. Current technologies provide wide choices of available solutions, which include Radio-frequency identification (RFID), Ultra wideband (UWB), wireless local area network (WLAN) and Bluetooth. With the rapid development of light-emitting-diodes (LED) technology, visible light communications (VLC) also bring a practical approach to LBS. As visible light has a better immunity against multipath effect than radio waves, higher positioning accuracy is achieved. LEDs are utilized both for illumination and positioning purpose to realize relatively lower infrastructure cost. In this paper, an indoor positioning system using VLC is proposed, with LEDs as transmitters and photo diodes as receivers. The algorithm for estimation is based on received-signalstrength (RSS) information collected from photo diodes and trilateration technique. By appropriately making use of the characteristics of receiver movements and the property of trilateration, estimation on three-dimensional (3-D) coordinates is attained. Filtering technique is applied to enable tracking capability of the algorithm, and a higher accuracy is reached compare to raw estimates. Gaussian mixture Sigma-point particle filter (GM-SPPF) is proposed for this 3-D system, which introduces the notion of Gaussian Mixture Model (GMM). The number of particles in the filter is reduced by approximating the probability distribution with Gaussian components.

On the Cramér–Rao bound applicability and the role of Fisher information in computational neuroscience

Czech Academy of Sciences Publication Activity Database

Pilarski, Stevan; Pokora, O.

2015-01-01

Roč. 136, Oct 2015 (2015), s. 11-22 ISSN 0303-2647 Institutional support: RVO:67985823 Keywords : Fisher information * neuronal coding * Cramér–Rao admissibility Subject RIV: BA - General Mathematics Impact factor: 1.495, year: 2015

The Bayesian Cramér-Rao lower bound in Astrometry

Science.gov (United States)

Mendez, R. A.; Echeverria, A.; Silva, J.; Orchard, M.

2018-01-01

A determination of the highest precision that can be achieved in the measurement of the location of a stellar-like object has been a topic of permanent interest by the astrometric community. The so-called (parametric, or non-Bayesian) Cramér-Rao (CR hereafter) bound provides a lower bound for the variance with which one could estimate the position of a point source. This has been studied recently by Mendez et al. (2013, 2014, 2015). In this work we present a different approach to the same problem (Echeverria et al. 2016), using a Bayesian CR setting which has a number of advantages over the parametric scenario.

The application of particle filters in single trial event-related potential estimation

International Nuclear Information System (INIS)

Mohseni, Hamid R; Nazarpour, Kianoush; Sanei, Saeid; Wilding, Edward L

2009-01-01

In this paper, an approach for the estimation of single trial event-related potentials (ST-ERPs) using particle filters (PFs) is presented. The method is based on recursive Bayesian mean square estimation of ERP wavelet coefficients using their previous estimates as prior information. To enable a performance evaluation of the approach in the Gaussian and non-Gaussian distributed noise conditions, we added Gaussian white noise (GWN) and real electroencephalogram (EEG) signals recorded during rest to the simulated ERPs. The results were compared to that of the Kalman filtering (KF) approach demonstrating the robustness of the PF over the KF to the added GWN noise. The proposed method also outperforms the KF when the assumption about the Gaussianity of the noise is violated. We also applied this technique to real EEG potentials recorded in an odd-ball paradigm and investigated the correlation between the amplitude and the latency of the estimated ERP components. Unlike the KF method, for the PF there was a statistically significant negative correlation between amplitude and latency of the estimated ERPs, matching previous neurophysiological findings

Particle Filtering for Multiple Access DS/CDMA Systems DS/CDMA Channel Estimation

Directory of Open Access Journals (Sweden)

Rafael Oliveira Ribeiro

2013-09-01

Full Text Available This article discusses computational implementation aspects and performance of a Bayesian methodology, namely particle filter (PF. The PF channel estimation technique is directly applied to the channel coefficients estimation of DS/CDMA systems. Simulation results for non-line-of-sight (NLOS Rayleigh fading channel propagation have indicated that the bootstrap PF estimator is capable to provide RMSE in the range of [10-3 ; 10-2] for a wide range of multiple access interference (MAI levels and signal-noise ratio (SNR, and still be able to offer robustness to near-far ratio (NFR effect.

A dynamic particle filter-support vector regression method for reliability prediction

International Nuclear Information System (INIS)

Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

2013-01-01

Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

Separating particles from a liquid

International Nuclear Information System (INIS)

Leslie, C.M.; Watson, J.H.P.; Williams, J.A.

1980-01-01

An apparatus for separating particles suspended in a liquid from the liquid, is described, in which a flow of the liquid is passed through a filter bed of ferromagnetic bodies which acts as a coarse filter to trap the larger particles in the flow. The filter bed is arranged within a truncated core between the poles of an electromagnet. To cleanse the bed and flush out the trapped particles a wash liquid is passed through the bed and the electromagnet is energised to levitate the bed to allow the wash liquid to remove the particles. The liquid flow from the coarse filter can be passed to a high gradient magnetic separator at which remaining small particles in the flow are filtered magnetically. (U.K.)

Applying a particle filtering technique for canola crop growth stage estimation in Canada

Science.gov (United States)

Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi

2017-10-01

Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.

Enhancing hydrologic data assimilation by evolutionary Particle Filter and Markov Chain Monte Carlo

Science.gov (United States)

Abbaszadeh, Peyman; Moradkhani, Hamid; Yan, Hongxiang

2018-01-01

Particle Filters (PFs) have received increasing attention by researchers from different disciplines including the hydro-geosciences, as an effective tool to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation using the PFs in hydrology has evolved since 2005 from the PF-SIR (sampling importance resampling) to PF-MCMC (Markov Chain Monte Carlo), and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and MCMC, the so-called EPFM. In this framework, the prior distribution undergoes an evolutionary process based on the designed mutation and crossover operators of GA. The merit of this approach is that the particles move to an appropriate position by using the GA optimization and then the number of effective particles is increased by means of MCMC, whereby the particle degeneracy is avoided and the particle diversity is improved. In this study, the usefulness and effectiveness of the proposed EPFM is investigated by applying the technique on a conceptual and highly nonlinear hydrologic model over four river basins located in different climate and geographical regions of the United States. Both synthetic and real case studies demonstrate that the EPFM improves both the state and parameter estimation more effectively and reliably as compared with the PF-MCMC.

Indoor anti-occlusion visible light positioning systems based on particle filtering

Science.gov (United States)

Jiang, Meng; Huang, Zhitong; Li, Jianfeng; Zhang, Ruqi; Ji, Yuefeng

2015-04-01

As one of the most popular categories of mobile services, a rapid growth of indoor location-based services has been witnessed over the past decades. Indoor positioning methods based on Wi-Fi, radio-frequency identification or Bluetooth are widely commercialized; however, they have disadvantages such as low accuracy or high cost. An emerging method using visible light is under research recently. The existed visible light positioning (VLP) schemes using carrier allocation, time allocation and multiple receivers all have limitations. This paper presents a novel mechanism using particle filtering in VLP system. By this method no additional devices are needed and the occlusion problem in visible light would be alleviated which will effectively enhance the flexibility for indoor positioning.

Filtering suspension e.g. gas from nuclear reactor etc. by separating some of its solids, passing it through filter and recycling fraction rich in solids

International Nuclear Information System (INIS)

Pfertzel, R.; Quenault, M.

1987-01-01

Gas or liquid contaminated by radioactive particles are filtered for extraction of a part of the purified fluid, a part of particles in the fluid are extracted by a cyclone separator or an electrostatic filter; this fluid poor in particles or the fluid rich in particles from the filtration is recycled after addition of the initial fluid. The process avoid filter clogging [fr

Electrostatic air filters generated by electric fields

International Nuclear Information System (INIS)

Bergman, W.; Biermann, A.H.; Hebard, H.D.; Lum, B.Y.; Kuhl, W.D.

1981-01-01

This paper presents theoretical and experimental findings on fibrous filters converted to electrostatic operation by a nonionizing electric field. Compared to a conventional fibrous filter, the electrostatic filter has a higher efficiency and a longer, useful life. The increased efficiency is attributed to a time independent attraction between polarized fibers and charged, polarized particles and a time dependent attraction between charged fibers and charged, polarized particles. The charge on the fibers results from a dynamic process of charge accumulation due to the particle deposits and a charge dissipation due to the fiber conductivity

[Research on engine remaining useful life prediction based on oil spectrum analysis and particle filtering].

Science.gov (United States)

Sun, Lei; Jia, Yun-xian; Cai, Li-ying; Lin, Guo-yu; Zhao, Jin-song

2013-09-01

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

Comparison of testing methods for particulate filters

International Nuclear Information System (INIS)

Ullmann, W.; Przyborowski, S.

1983-01-01

Four testing methods for particulate filters were compared by using the test rigs of the National Board of Nuclear Safety and Radiation Protection: 1) Measurement of filter penetration P as a function of particle size d by using a polydisperse NaC1 test aerosol and a scintillation particle counter; 2) Modified sodium flame test for measurement of total filter penetration P for various polydisperse NaC1 test aerosols; 3) Measurement of total filter penetration P for a polydisperse NaC1 test aerosol labelled with short-lived radon daughter products; 4) Measurement of total filter penetration P for a special paraffin oil test aerosol (oil fog test used in FRG according DIN 24 184, test aerosol A). The investigations were carried out on sheets of glass fibre paper (five grades of paper). Detailed information about the four testing methods and the used particle size distributions is given. The different results of the various methods are the base for the discussion of the most important parameters which influence the filter penetration P. The course of the function P=f(d) shows the great influence of the particle size. As expected there was also found a great dependence both from the test aerosol as well as from the principle and the measuring range of the aerosol-measuring device. The differences between the results of the various test methods are greater the lower the penetration. The use of NaCl test aerosol with various particle size distributions gives great differences for the respective penetration values. On the basis of these results and the values given by Dorman conclusions are made about the investigation of particulate filters both for the determination of filter penetration P as well as for the leak test of installed filters

Outlier Detection in GNSS Pseudo-Range/Doppler Measurements for Robust Localization

Directory of Open Access Journals (Sweden)

Salim Zair

2016-04-01

Full Text Available In urban areas or space-constrained environments with obstacles, vehicle localization using Global Navigation Satellite System (GNSS data is hindered by Non-Line Of Sight (NLOS and multipath receptions. These phenomena induce faulty data that disrupt the precise localization of the GNSS receiver. In this study, we detect the outliers among the observations, Pseudo-Range (PR and/or Doppler measurements, and we evaluate how discarding them improves the localization. We specify a contrario modeling for GNSS raw data to derive an algorithm that partitions the dataset between inliers and outliers. Then, only the inlier data are considered in the localization process performed either through a classical Particle Filter (PF or a Rao-Blackwellization (RB approach. Both localization algorithms exclusively use GNSS data, but they differ by the way Doppler measurements are processed. An experiment has been performed with a GPS receiver aboard a vehicle. Results show that the proposed algorithms are able to detect the ‘outliers’ in the raw data while being robust to non-Gaussian noise and to intermittent satellite blockage. We compare the performance results achieved either estimating only PR outliers or estimating both PR and Doppler outliers. The best localization is achieved using the RB approach coupled with PR-Doppler outlier estimation.

Nonlinear Kalman filtering in affine term structure models

DEFF Research Database (Denmark)

Christoffersen, Peter; Dorion, Christian; Jacobs, Kris

2014-01-01

The extended Kalman filter, which linearizes the relationship between security prices and state variables, is widely used in fixed-income applications. We investigate whether the unscented Kalman filter should be used to capture nonlinearities and compare the performance of the Kalman filter...... with that of the particle filter. We analyze the cross section of swap rates, which are mildly nonlinear in the states, and cap prices, which are highly nonlinear. When caps are used to filter the states, the unscented Kalman filter significantly outperforms its extended counterpart. The unscented Kalman filter also...... performs well when compared with the much more computationally intensive particle filter. These findings suggest that the unscented Kalman filter may be a good approach for a variety of problems in fixed-income pricing....

Variable flexure-based fluid filter

Science.gov (United States)

Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

2007-03-13

An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

Preparation of Porcelanite Ceramic Filter by Slip Casting Technique

Directory of Open Access Journals (Sweden)

Majid Muhi Shukur

2016-09-01

Full Text Available This work is conducted to study producing solid block porcelanite filter from Iraqi porcelanite rocks and kaolin clay (as binder material by slip casting technique, and investigating its ability of removing contaminant (Pentachlorophenol from water via the adsorption mechanism. Four particle sizes (74, 88, 105 and 125 µm of porcelanite powder were used. Each batch of particle size was mixed with (30 wt. % kaolin as a binding material to improve the mechanical properties. After that, the mixtures were formed by slip casting to disk and cylindrical filter samples, and then fired at 500 and 700 °C to specify the effects of particle size of porcelanite, temperature and formation technique on porcelanite filter properties. Some physical, mechanical and chemical tests have been done on filter samples. Multi-experiments were carried out to evaluate the ability of porcelanite to form the filter. Porosity, permeability and maximum pore diameter were increased with increasing porcelanite particle size and decreased by increasing temperature, whereas the density shows the reverse behavior. In addition, bending, compressive and tensile strength of samples were increased by increasing temperature, and decreased with increasing porcelanite particle size. Efficiency of disk filter sample to remove pentachlorophenol was 95.41% at a temperature of 700°C using 74 µm particle size of porcelanite. While the efficiency of cylindrical filter sample was 97.57% at the same conditions.

Filter-adsorber aging assessment

Energy Technology Data Exchange (ETDEWEB)

Winegardner, W.K. [Pacific Northwest Laboratory, Richland, WA (United States)

1995-02-01

An aging assessment of high-efficiency particulate (HEPA) air filters and activated carbon gas adsorption units was performed by the Pacific Northwest Laboratory as part of the U.S. Nuclear Regulatory Commission`s (USNRC) Nuclear Plant Aging Research (NPAR) Program. This evaluation of the general process in which characteristics of these two components gradually change with time or use included the compilation of information concerning failure experience, stressors, aging mechanisms and effects, and inspection, surveillance, and monitoring methods (ISMM). Stressors, the agents or stimuli that can produce aging degradation, include heat, radiation, volatile contaminants, and even normal concentrations of aerosol particles and gasses. In an experimental evaluation of degradation in terms of the tensile breaking strength of aged filter media specimens, over forty percent of the samples did not meet specifications for new material. Chemical and physical reactions can gradually embrittle sealants and gaskets as well as filter media. Mechanisms that can lead to impaired adsorber performance are associated with the loss of potentially available active sites as a result of the exposure of the carbon to airborne moisture or volatile organic compounds. Inspection, surveillance, and monitoring methods have been established to observe filter pressure drop buildup, check HEPA filters and adsorbers for bypass, and determine the retention effectiveness of aged carbon. These evaluations of installed filters do not reveal degradation in terms of reduced media strength but that under normal conditions aged media can continue to effectively retain particles. However, this degradation may be important when considering the likelihood of moisture, steam, and higher particle loadings during severe accidents and the fact it is probable that the filters have been in use for an extended period.

A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue wireless sensor network.

Science.gov (United States)

Wu, Huafeng; Mei, Xiaojun; Chen, Xinqiang; Li, Junjun; Wang, Jun; Mohapatra, Prasant

2018-07-01

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method

OpenAIRE

Chen, Jian; Yuan, Shenfang; Qiu, Lei; Cai, Jian; Yang, Weibo

2016-01-01

Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF)-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack...

Apparatus for filtering radioactive fluids

International Nuclear Information System (INIS)

Gischel, E.H.

1975-01-01

Apparatus is provided for filtering radioactive particles from the cooling and/or auxiliary process water of a nuclear reactor, or nuclear fuel processing plant, or other installations wherein radioactive fluid systems are known to exist. The apparatus affords disposal of the captured particles in a manner which minimizes the exposure of operating personnel to radioactivity. The apparatus comprises a housing adapted to contain a removable filter cartridge assembly, a valve normally closing the lower end of the housing, an upwardly-open shipping cask located below the valve, and an elongated operating rod assembly projecting upwardly from the filter cartridge assembly and through the upper end of the housing to enable a workman to dismount the filter cartridge assembly from its housing and to lower the filter cartridge assembly through the valve and into the cask from a remote location above the housing. (U.S.)

Particle image velocimetry (PIV) study of rotating cylindrical filters for animal cell perfusion processes.

Science.gov (United States)

Figueredo-Cardero, Alvio; Chico, Ernesto; Castilho, Leda; de Andrade Medronho, Ricardo

2012-01-01

In the present work, the main fluid flow features inside a rotating cylindrical filtration (RCF) system used as external cell retention device for animal cell perfusion processes were investigated using particle image velocimetry (PIV). The motivation behind this work was to provide experimental fluid dynamic data for such turbulent flow using a high-permeability filter, given the lack of information about this system in the literature. The results shown herein gave evidence that, at the boundary between the filter mesh and the fluid, a slip velocity condition in the tangential direction does exist, which had not been reported in the literature so far. In the RCF system tested, this accounted for a fluid velocity 10% lower than that of the filter tip, which could be important for the cake formation kinetics during filtration. Evidence confirming the existence of Taylor vortices under conditions of turbulent flow and high permeability, typical of animal cell perfusion RCF systems, was obtained. Second-order turbulence statistics were successfully calculated. The radial behavior of the second-order turbulent moments revealed that turbulence in this system is highly anisotropic, which is relevant for performing numerical simulations of this system. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Permanently magnetized high gradient magnetic air filters for the nuclear industry

International Nuclear Information System (INIS)

Watson, J.H.P.

1995-01-01

This paper describes the structure and testing of two novel permanently magnetized magnetic filters for fine radioactive material. In the first filter the holes in the filter are left open as capture proceeds which means the pressure drop builds up only slowly. This filter is not suitable for composite particles which can be broken by mechanical forces. The second filter has been changed so as to strongly capture particles composed of fine particles weakly bound together which tend to break when captured. This uses a principle of assisted capture in which coarse particles aid the capture of the fine fragments. These filters have the following characteristics: (1) no external magnet is required, (2) no external power is required, (3) small in size and portable, (4) easily interchangeable, and (5) can be cleaned without demagnetizing by using a magnetic fluid which matches the susceptibility of the captured particles

A Brief Tutorial on the Ensemble Kalman Filter

OpenAIRE

Mandel, Jan

2009-01-01

The ensemble Kalman filter (EnKF) is a recursive filter suitable for problems with a large number of variables, such as discretizations of partial differential equations in geophysical models. The EnKF originated as a version of the Kalman filter for large problems (essentially, the covariance matrix is replaced by the sample covariance), and it is now an important data assimilation component of ensemble forecasting. EnKF is related to the particle filter (in this context, a particle is the s...

An Adaptive Particle Weighting Strategy for ECG Denoising Using Marginalized Particle Extended Kalman Filter: An Evaluation in Arrhythmia Contexts.

Science.gov (United States)

Hesar, Hamed Danandeh; Mohebbi, Maryam

2017-11-01

Model-based Bayesian frameworks have a common problem in processing electrocardiogram (ECG) signals with sudden morphological changes. This situation often happens in the case of arrhythmias where ECGs do not obey the predefined state models. To solve this problem, in this paper, a model-based Bayesian denoising framework is proposed using marginalized particle-extended Kalman filter (MP-EKF), variational mode decomposition, and a novel fuzzy-based adaptive particle weighting strategy. This strategy helps MP-EKF to perform well even when the morphology of signal does not comply with the predefined dynamic model. In addition, this strategy adapts MP-EKF's behavior to the acquired measurements in different input signal to noise ratios (SNRs). At low input SNRs, this strategy decreases the particles' trust level to the measurements while increasing their trust level to a synthetic ECG constructed with the feature parameters of ECG dynamic model. At high input SNRs, the particles' trust level to the measurements is increased and the trust level to synthetic ECG is decreased. The proposed method was evaluated on MIT-BIH normal sinus rhythm database and compared with EKF/EKS frameworks and previously proposed MP-EKF. It was also evaluated on ECG segments extracted from MIT-BIH arrhythmia database, which contained ventricular and atrial arrhythmia. The results showed that the proposed algorithm had a noticeable superiority over benchmark methods from both SNR improvement and multiscale entropy based weighted distortion (MSEWPRD) viewpoints at low input SNRs.

Preliminary study on filamentous particle distribution in septic tank effluent and their impact on filter cake development.

Science.gov (United States)

Spychała, Marcin; Nieć, Jakub; Pawlak, Maciej

2013-01-01

In this paper, the preliminary study on the impact of filamentous particles (FP) in the septic tank effluent (STE) on filter cake (FC) development was presented. The number, length and diameter (30 p./cm3, 451 and 121 microm, respectively, on average) of FPs were measured using microscope image analysis of STE samples condensed using a vacuum evaporation set. Results of this study showed, that 0.73% of volatile suspended solids (VSSs) mass from the STE occurs in the form of FPs. No correlation between FP total mass and VSS was found. An experiment with a layer of FPs simulated by ground toilet paper was conducted and showed the impact of this layer (4.89 mg/cm2) on wastewater hydraulic conductivity--for an FC with FPs (FC-FP), hydraulic conductivity was seven times lower than for the FC without the FP layer, and on outflow quality (lower concentration of organic matter expressed as chemical oxygen demand (COD) in effluent from the FC-FP filter than in the effluent from the FC filter: 618 and 732 gO2/m3, respectively). Despite a relatively small amount of FPs in STE solids (as volume fraction), they play an important role in FC development due to their relatively high length and low degradability. Probably relatively small pores of the FC containing FPs (FC-FP) caused a small particle blocking and a decrease in permeability.

An adaptive-order particle filter for remaining useful life prediction of aviation piston pumps

Directory of Open Access Journals (Sweden)

Tongyang LI

2018-05-01

Full Text Available An accurate estimation of the remaining useful life (RUL not only contributes to an effective application of an aviation piston pump, but also meets the necessity of condition based maintenance (CBM. For the current RUL evaluation methods, a model-based method is inappropriate for the degradation process of an aviation piston pump due to difficulties of modeling, while a data-based method rarely presents high-accuracy prediction in a long period of time. In this work, an adaptive-order particle filter (AOPF prognostic process is proposed aiming at improving long-term prediction accuracy of RUL by combining both kinds of methods. A dynamic model is initialized by a data-driven or empirical method. When a new observation comes, the prior state distribution is approximated by a current model. The order of the current model is updated adaptively by fusing the information of the observation. Monte Carlo simulation is employed for estimating the posterior probability density function of future states of the pump’s degradation. With updating the order number adaptively, the method presents a higher precision in contrast with those of traditional methods. In a case study, the proposed AOPF method is adopted to forecast the degradation status of an aviation piston pump with experimental return oil flow data, and the analytical results show the effectiveness of the proposed AOPF method. Keywords: Adaptive prognosis, Condition based maintenance (CBM, Particle filter (PF, Piston pump, Remaining useful life (RUL

Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar

Directory of Open Access Journals (Sweden)

Fei Cai

2014-01-01

Full Text Available A particle filter based track-before-detect (PF-TBD algorithm is proposed for the monopulse high pulse repetition frequency (PRF pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied.

Filtered cathodic arc source

International Nuclear Information System (INIS)

Falabella, S.; Sanders, D.M.

1994-01-01

A continuous, cathodic arc ion source coupled to a macro-particle filter capable of separation or elimination of macro-particles from the ion flux produced by cathodic arc discharge is described. The ion source employs an axial magnetic field on a cathode (target) having tapered sides to confine the arc, thereby providing high target material utilization. A bent magnetic field is used to guide the metal ions from the target to the part to be coated. The macro-particle filter consists of two straight solenoids, end to end, but placed at 45 degree to one another, which prevents line-of-sight from the arc spot on the target to the parts to be coated, yet provides a path for ions and electrons to flow, and includes a series of baffles for trapping the macro-particles. 3 figures

Evaluating the Sensitivity of the Mass-Based Particle Removal Calculations for HVAC Filters in ISO 16890 to Assumptions for Aerosol Distributions

Directory of Open Access Journals (Sweden)

Brent Stephens

2018-02-01

Full Text Available High efficiency particle air filters are increasingly being recommended for use in heating, ventilating, and air-conditioning (HVAC systems to improve indoor air quality (IAQ. ISO Standard 16890-2016 provides a methodology for approximating mass-based particle removal efficiencies for PM1, PM2.5, and PM10 using size-resolved removal efficiency measurements for 0.3 µm to 10 µm particles. Two historical volume distribution functions for ambient aerosol distributions are assumed to represent ambient air in urban and rural areas globally. The goals of this work are to: (i review the ambient aerosol distributions used in ISO 16890, (ii evaluate the sensitivity of the mass-based removal efficiency calculation procedures described in ISO 16890 to various assumptions that are related to indoor and outdoor aerosol distributions, and (iii recommend several modifications to the standard that can yield more realistic estimates of mass-based removal efficiencies for HVAC filters, and thus provide a more realistic representation of a greater number of building scenarios. The results demonstrate that knowing the PM mass removal efficiency estimated using ISO 16890 is not sufficient to predict the PM mass removal efficiency in all of the environments in which the filter might be used. The main reason for this insufficiency is that the assumptions for aerosol number and volume distributions can substantially impact the results, albeit with some exceptions.

THE EFFECT OF THE REYNOLDS NUMBER OF AIR FLOW TO THE PARTICLE COLLECTION EFFICIENCY OF A FIBROUS FILTER MEDIUM WITH CYLINDRICAL SECTION

Directory of Open Access Journals (Sweden)

George P. Kouropoulos

2014-01-01

Full Text Available At this study an attempt for the theoretical approach of the Re ynolds number effect of air flow to the particle collection efficiency of a fibrous fil ter with cylindrical section will be made. Initially, a report of the air filtration models to fibrous filter media will be presented along with an explanation of both the parameters and the physical quantities which govern the air filtration process. Furthermore, the resul ting equation from the mathematical model will be applied to a real filter medium and the characteristic curves of filter efficiency will be drawn. The change of a filter medi um efficiency with regard to the Reynolds number of air flow that passes through the filt er, derived from the curves, will be studied. The general conclusion that we have is that as the Reynolds number of filtered air increases, the collection efficiency of the filter decreases.

Particulate removal processes and hydraulics of porous gravel media filters

Science.gov (United States)

Minto, J. M.; Phoenix, V. R.; Dorea, C. C.; Haynes, H.; Sloan, W. T.

2013-12-01

Sustainable urban Drainage Systems (SuDS) are rapidly gaining acceptance as a low-cost tool for treating urban runoff pollutants close to source. Road runoff water in particular requires treatment due to the presence of high levels of suspended particles and heavy metals adsorbed to these particles. The aim of this research is to elucidate the particle removal processes that occur within gravel filters that have so far been considered as 'black-box' systems. Based on these findings, a better understanding will be attained on what influences gravel filter removal efficiency and how this changes throughout their design life; leading to a more rational design of this useful technology. This has been achieved by tying together three disparate research elements: tracer residence time distribution curves of filters during clogging; 3D magnetic resonance imaging (MRI) of clogging filters and computational fluid dynamics (CFD) modelling of complex filter pore networks. This research relates column average changes in particle removal efficiency and tracer residence time distributions (RTDs) due to clogging with non-invasive measurement of the spatial variability in particle deposition. The CFD modelling provides a link between observed deposition patterns, flow velocities and wall shear stresses as well as the explanations for the change in RTD with clogging and the effect on particle transport. Results show that, as a filter clogs, particles take a longer, more tortuous path through the filter. This is offset by a reduction in filter volume resulting in higher flow velocities and more rapid particle transport. Higher velocities result in higher shear stresses and the development of preferential pathways in which the velocity exceeds the deposition threshold and the overall efficiency of the filter decreases. Initial pore geometry is linked to the pattern of deposition and subsequent formation of preferential pathways. These results shed light on the 'black-box' internal

The AGILE on-board Kalman filter

International Nuclear Information System (INIS)

Giuliani, A.; Cocco, V.; Mereghetti, S.; Pittori, C.; Tavani, M.

2006-01-01

On-board reduction of particle background is one of the main challenges of space instruments dedicated to gamma-ray astrophysics. We present in this paper a discussion of the method and main simulation results of the on-board background filter of the Gamma-Ray Imaging Detector (GRID) of the AGILE mission. The GRID is capable of detecting and imaging with optimal point spread function gamma-ray photons in the range 30MeV-30GeV. The AGILE planned orbit is equatorial, with an altitude of 550km. This is an optimal orbit from the point of view of the expected particle background. For this orbit, electrons and positrons of kinetic energies between 20MeV and hundreds of MeV dominate the particle background, with significant contributions from high-energy (primary) and low-energy protons, and gamma-ray albedo-photons. We present here the main results obtained by extensive simulations of the on-board AGILE-GRID particle/photon background rejection algorithms based on a special application of Kalman filter techniques. This filter is applied (Level-2) sequentially after other data processing techniques characterizing the Level-1 processing. We show that, in conjunction with the Level-1 processing, the adopted Kalman filtering is expected to reduce the total particle/albedo-photon background rate to a value (=<10-30Hz) that is compatible with the AGILE telemetry. The AGILE on-board Kalman filter is also effective in reducing the Earth-albedo-photon background rate, and therefore contributes to substantially increase the AGILE exposure for celestial gamma-ray sources

Efficiency and mass loading characteristics of a typical HEPA filter media material

International Nuclear Information System (INIS)

Novick, V.J.; Higgins, P.J.; Dierkschiede, B.; Abrahamson, C.; Richardson, W.B.; Monson, P.R.; Ellison, P.G.

1991-01-01

The particle removal efficiency of the high-efficiency particulate air (HEPA) filter material used at the Savannah River Site was measured as a function of monodisperse particle diameter and two gas filtration velocities. the results indicate that the material meets or exceeds the minimum specified efficiency of 99.97% for all particle diameters at both normal and minimum operating flow conditions encountered at the Savannah River site. The pressure drop across the HEPA filter material used at the Savannah River site was measured as a function of particle mass loading for various aerosol size distributions. The pressure drop was found to increase linearly with the particle mass loaded onto the filters, as long as the particles were completely dry. The slope of the curve was found to be dependent on the particle diameter and velocity of the aerosol. The linear behavior between the initial pressure drop (clean filter) and the final pressure drop (loaded filter) implies that the filtration mechanism is dominated by the particle cake that rapidly forms on the front surface of the HEPA filter. This behavior is consistent with the high filtration efficiency of the material

Nanofiber Filters Eliminate Contaminants

Science.gov (United States)

2009-01-01

With support from Phase I and II SBIR funding from Johnson Space Center, Argonide Corporation of Sanford, Florida tested and developed its proprietary nanofiber water filter media. Capable of removing more than 99.99 percent of dangerous particles like bacteria, viruses, and parasites, the media was incorporated into the company's commercial NanoCeram water filter, an inductee into the Space Foundation's Space Technology Hall of Fame. In addition to its drinking water filters, Argonide now produces large-scale nanofiber filters used as part of the reverse osmosis process for industrial water purification.

Use of the Kalman filter in signal processing to reduce beam requirements for alpha-particle diagnostics

International Nuclear Information System (INIS)

Cooper, W.S.

1986-01-01

Several techniques proposed for diagnosing the velocity distribution of fast alpha-particles in a burning plasma require the injection of a beam of fast neutral atoms as probes. The author discusses how improving signal detection techniques is a high leverage factor in reducing the cost of the diagnostic beam. Optimal estimation theory provides a computational algorithm, the Kalman filter, that can optimally estimate the amplitude of a signal with arbitrary (but known) time dependence in the presence of noise. In one example presented, based on a square-wave signal and assumed noise levels, the Kalman filter achieves an enhancement of signal detection efficiency of about a factor of 10 (as compared with the straightforward observation of the signal superimposed on noise) with an observation time of 100 signal periods

Particle-filtering-based estimation of maximum available power state in Lithium-Ion batteries

International Nuclear Information System (INIS)

Burgos-Mellado, Claudio; Orchard, Marcos E.; Kazerani, Mehrdad; Cárdenas, Roberto; Sáez, Doris

2016-01-01

Highlights: • Approach to estimate the state of maximum power available in Lithium-Ion battery. • Optimisation problem is formulated on the basis of a non-linear dynamic model. • Solutions of the optimisation problem are functions of state of charge estimates. • State of charge estimates computed using particle filter algorithms. - Abstract: Battery Energy Storage Systems (BESS) are important for applications related to both microgrids and electric vehicles. If BESS are used as the main energy source, then it is required to include adequate procedures for the estimation of critical variables such as the State of Charge (SoC) and the State of Health (SoH) in the design of Battery Management Systems (BMS). Furthermore, in applications where batteries are exposed to high charge and discharge rates it is also desirable to estimate the State of Maximum Power Available (SoMPA). In this regard, this paper presents a novel approach to the estimation of SoMPA in Lithium-Ion batteries. This method formulates an optimisation problem for the battery power based on a non-linear dynamic model, where the resulting solutions are functions of the SoC. In the battery model, the polarisation resistance is modelled using fuzzy rules that are function of both SoC and the discharge (charge) current. Particle filtering algorithms are used as an online estimation technique, mainly because these algorithms allow approximating the probability density functions of the SoC and SoMPA even in the case of non-Gaussian sources of uncertainty. The proposed method for SoMPA estimation is validated using the experimental data obtained from an experimental setup designed for charging and discharging the Lithium-Ion batteries.

Development of a double-layered ceramic filter for aerosol filtration at high-temperatures: the filter collection efficiency.

Science.gov (United States)

de Freitas, Normanda L; Gonçalves, José A S; Innocentini, Murilo D M; Coury, José R

2006-08-25

The performance of double-layered ceramic filters for aerosol filtration at high temperatures was evaluated in this work. The filtering structure was composed of two layers: a thin granular membrane deposited on a reticulate ceramic support of high porosity. The goal was to minimize the high pressure drop inherent of granular structures, without decreasing their high collection efficiency for small particles. The reticulate support was developed using the technique of ceramic replication of polyurethane foam substrates of 45 and 75 pores per inch (ppi). The filtering membrane was prepared by depositing a thin layer of granular alumina-clay paste on one face of the support. Filters had their permeability and fractional collection efficiency analyzed for filtration of an airborne suspension of phosphatic rock in temperatures ranging from ambient to 700 degrees C. Results revealed that collection efficiency decreased with gas temperature and was enhanced with filtration time. Also, the support layer influenced the collection efficiency: the 75 ppi support was more effective than the 45 ppi. Particle collection efficiency dropped considerably for particles below 2 microm in diameter. The maximum collection occurred for particle diameters of approximately 3 microm, and decreased again for diameters between 4 and 8 microm. Such trend was successfully represented by the proposed correlation, which is based on the classical mechanisms acting on particle collection. Inertial impaction seems to be the predominant collection mechanism, with particle bouncing/re-entrainment acting as detachment mechanisms.

Robust and Adaptive Block Tracking Method Based on Particle Filter

Directory of Open Access Journals (Sweden)

Bin Sun

2015-10-01

Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

Methodology for modeling the microbial contamination of air filters.

Science.gov (United States)

Joe, Yun Haeng; Yoon, Ki Young; Hwang, Jungho

2014-01-01

In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

Methodology for modeling the microbial contamination of air filters.

Directory of Open Access Journals (Sweden)

Yun Haeng Joe

Full Text Available In this paper, we propose a theoretical model to simulate microbial growth on contaminated air filters and entrainment of bioaerosols from the filters to an indoor environment. Air filter filtration and antimicrobial efficiencies, and effects of dust particles on these efficiencies, were evaluated. The number of bioaerosols downstream of the filter could be characterized according to three phases: initial, transitional, and stationary. In the initial phase, the number was determined by filtration efficiency, the concentration of dust particles entering the filter, and the flow rate. During the transitional phase, the number of bioaerosols gradually increased up to the stationary phase, at which point no further increase was observed. The antimicrobial efficiency and flow rate were the dominant parameters affecting the number of bioaerosols downstream of the filter in the transitional and stationary phase, respectively. It was found that the nutrient fraction of dust particles entering the filter caused a significant change in the number of bioaerosols in both the transitional and stationary phases. The proposed model would be a solution for predicting the air filter life cycle in terms of microbiological activity by simulating the microbial contamination of the filter.

Modified Particle Swarm Optimization for Blind Deconvolution and Identification of Multichannel FIR Filters

Directory of Open Access Journals (Sweden)

Khanagha Ali

2010-01-01

Full Text Available Blind identification of MIMO FIR systems has widely received attentions in various fields of wireless data communications. Here, we use Particle Swarm Optimization (PSO as the update mechanism of the well-known inverse filtering approach and we show its good performance compared to original method. Specially, the proposed method is shown to be more robust against lower SNR scenarios or in cases with smaller lengths of available data records. Also, a modified version of PSO is presented which further improves the robustness and preciseness of PSO algorithm. However the most important promise of the modified version is its drastically faster convergence compared to standard implementation of PSO.

Particle Kalman Filtering: A Nonlinear Bayesian Framework for Ensemble Kalman Filters*

KAUST Repository

Hoteit, Ibrahim; Luo, Xiaodong; Pham, Dinh-Tuan

2012-01-01

introduce a resampling step to the PEnKF in order to reduce the risk of weights collapse and improve the performance of the filter. Numerical experiments with the strongly nonlinear Lorenz-96 model are presented and discussed.

Study of the stopping power of various filters

International Nuclear Information System (INIS)

Madelaine, G.

1964-01-01

The first part is devoted to a study of aerosols obtained from the combustion of various smoke-producing compounds. A trial aerosol of which the size distribution is the closest possible to that of atmospheric dusts has been defined. The efficiency of various filters has been determined for successive increments of the dimensions and not for the whole range of its diameter distribution. The variation in the efficiency of the filtering layers as a function of the filtering speed and particle size has been studied for aerosols having particle diameters of over 0.3 μ. The second part describes an original method for measuring the efficiency of filters for ultra-fine particles (under 0.1 μ) using the fixation properties of radioactive atoms resulting from the decay of thoron. (author) [fr

Method for Multiple Targets Tracking in Cognitive Radar Based on Compressed Sensing

Directory of Open Access Journals (Sweden)

Yang Jun

2016-02-01

Full Text Available A multiple targets cognitive radar tracking method based on Compressed Sensing (CS is proposed. In this method, the theory of CS is introduced to the case of cognitive radar tracking process in multiple targets scenario. The echo signal is sparsely expressed. The designs of sparse matrix and measurement matrix are accomplished by expressing the echo signal sparsely, and subsequently, the restruction of measurement signal under the down-sampling condition is realized. On the receiving end, after considering that the problems that traditional particle filter suffers from degeneracy, and require a large number of particles, the particle swarm optimization particle filter is used to track the targets. On the transmitting end, the Posterior Cramér-Rao Bounds (PCRB of the tracking accuracy is deduced, and the radar waveform parameters are further cognitively designed using PCRB. Simulation results show that the proposed method can not only reduce the data quantity, but also provide a better tracking performance compared with traditional method.

State-of-charge estimation in lithium-ion batteries: A particle filter approach

Science.gov (United States)

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.

A Cramer Rao analysis on receiver placement in a FM band commensal radar system based on doppler only measurements

CSIR Research Space (South Africa)

Maasdorp, FDV

2014-10-01

Full Text Available of receiver positions. Further, we show that time history information of a target can cumulatively be used together with FIM that will improve the Cramer-Rao bound. Lastly, we use the theory developed to evaluate receiver placement combinations by means of a...

In Situ Cleanable Alternative HEPA Filter Media

International Nuclear Information System (INIS)

Adamson, D. J.; Terry, M. T.

2002-01-01

The Westinghouse Savannah River Company, located at the Savannah River Site in Aiken, South Carolina, is currently testing two types of filter media for possible deployment as in situ regenerable/cleanable High Efficiency Particulate Air (HEPA) filters. The filters are being investigated to replace conventional, disposable, glass-fiber, HEPA filters that require frequent removal, replacement, and disposal. This is not only costly and subjects site personnel to radiation exposure, but adds to the ever-growing waste disposal problem. The types of filter media being tested, as part of a National Energy Technology Laboratory procurement, are sintered nickel metal and ceramic monolith membrane. These media were subjected to a hostile environment to simulate conditions that challenge the high-level waste tank ventilation systems. The environment promoted rapid filter plugging to maximize the number of filter loading/cleaning cycles that would occur in a specified period of time. The filters were challenged using nonradioactive simulated high-level waste materials and atmospheric dust; materials that cause filter pluggage in the field. The filters are cleaned in situ using an aqueous solution. The study found that both filter media were insensitive to high humidity or moisture conditions and were easily cleaned in situ. The filters regenerated to approximately clean filter status even after numerous plugging and in situ cleaning cycles. Air Techniques International is conducting particle retention testing on the filter media at the Oak Ridge Filter Test Facility. The filters are challenged using 0.3-mm di-octyl phthalate particles. Both the ceramic and sintered media have a particle retention efficiency > 99.97%. The sintered metal and ceramic filters not only can be cleaned in situ, but also hold great potential as a long life alternative to conventional HEPA filters. The Defense Nuclear Facility Safety Board Technical Report, ''HEPA Filters Used in the Department of

Advanced Filter Technology For Nuclear Thermal Propulsion

Science.gov (United States)

Castillon, Erick

2015-01-01

The Scrubber System focuses on using HEPA filters and carbon filtration to purify the exhaust of a Nuclear Thermal Propulsion engine of its aerosols and radioactive particles; however, new technology may lend itself to alternate filtration options, which may lead to reduction in cost while at the same time have the same filtering, if not greater, filtering capabilities, as its predecessors. Extensive research on various types of filtration methods was conducted with only four showing real promise: ionization, cyclonic separation, classic filtration, and host molecules. With the four methods defined, more research was needed to find the devices suitable for each method. Each filtration option was matched with a device: cyclonic separators for the method of the same name, electrostatic separators for ionization, HEGA filters, and carcerands for the host molecule method. Through many hours of research, the best alternative for aerosol filtration was determined to be the electrostatic precipitator because of its high durability against flow rate and its ability to cleanse up to 99.99% of contaminants as small as 0.001 micron. Carcerands, which are the only alternative to filtering radioactive particles, were found to be non-existent commercially because of their status as a "work in progress" at research institutions. Nevertheless, the conclusions after the research were that HEPA filters is recommended as the best option for filtering aerosols and carbon filtration is best for filtering radioactive particles.

Projects on filter testing in Sweden

International Nuclear Information System (INIS)

Normann, B.; Wiktorsson, C.

1985-01-01

The Swedish nuclear power program comprises twelve light water reactors. Nine are boiling water reactors of ASEA-ATOM design and three are pressurized water reactors of Westinghouse design. Of these, ten are in operation and two are under construction and planned to go into operation during late 1984 and early 1985, respectively. Frequent tests on the penetration of particles through HEPA filters, regular tests on the adsorption of methyl iodide in the stand-by carbon filter units by laboratory testing are discussed. The proposed new regulations are based on many years of experience of filter system operation and of tests in-situ and in the laboratory. Moisture and water are factors that affect the functioning of filters. In addition, high loading of dust can give rise to increased penetration through HEPA filters, however pinholes could have less influence on the total penetration. Laboratory tests show that DOP particles retain 30-40% in 90 mm carbon filters (8-12 mesh). However no effect on the ability of carbon to adsorb methyl iodide after DOP contamination in combined carbon/HEPA filters has been observed. Leakage from ventilation ducts can cause radioactive contamination problems during filter testing with radioiodine. In-situ testing of control-room filters has been performed using inactive methyl iodide. A type of carbon bed not previously used in Sweden has been introduced. Testing of this filter type is discussed

On a multiscale approach for filter efficiency simulations

KAUST Repository

Iliev, Oleg

2014-07-01

Filtration in general, and the dead end depth filtration of solid particles out of fluid in particular, is intrinsic multiscale problem. The deposition (capturing of particles) essentially depends on local velocity, on microgeometry (pore scale geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences the velocity field and pressure distribution inside the filter element. To close the loop, we mention that the velocity influences the transport and deposition of particles. In certain cases one can evaluate the filtration efficiency considering only microscale or only macroscale models, but in general an accurate prediction of the filtration efficiency requires multiscale models and algorithms. This paper discusses the single scale and the multiscale models, and presents a fractional time step discretization algorithm for the multiscale problem. The velocity within the filter element is computed at macroscale, and is used as input for the solution of microscale problems at selected locations of the porous medium. The microscale problem is solved with respect to transport and capturing of individual particles, and its solution is postprocessed to provide permeability values for macroscale computations. Results from computational experiments with an oil filter are presented and discussed.

Modelling of air flows in pleated filters and of their clogging by solid particles; Modelisation des ecoulements d'air et du colmatage des filtres plisses par des aerosols solides

Energy Technology Data Exchange (ETDEWEB)

Del Fabbro, L

2002-07-01

The devices of air cleaning against particles are widely spread in various branches of industry: nuclear, motor, food, electronic,...; among these devices, numerous are constituted by pleated porous media to increase the surface of filtration and thus to reduce the pressure drop, for given air flow. The objective of our work is to compensate a lack evident of knowledge on the evolution of the pressure drop of pleated filter during the clogging and to deduct a modelling from it, on the basis of experiments concerning industrial filters of nuclear and car types. The obtained model is a function of characteristics of the filtering medium and pleats, of the characteristics of solid particles deposited on the filter, of the mass of particles and of the aeraulic conditions of air flow. It also depends on data on the clogging of flat filters of equivalent medium. To elaborate this model of pressure drop, an initial stage was carried out in order to characterize, experimentally and numerically, the pressure drop and the distribution of air flow in clean pleated filters of nuclear (high efficiency particulate air filter, in fiberglasses) and car (mean efficiency filter, in fibers of cellulose) types. The numerical model allowed to understand the fundamental role played by the aeraulic resistance of the filtering medium. From an non-dimensional approach, we established a semi-empirical model of pressure drop for a clean pleated filter valid for both studied types of medium; this model is used of first base for the development of the final model of clogging. The study of the clogging of the filters showed the complexity of the phenomenon dependent mainly on a reduction of the surface of filtration. This observation brings us to propose a clogging of pleated filters in three phases. Both first phases are similar in those observed for flat filters, while last phase corresponds to a reduction of the surface of filtration and leads a strong increase of the filter pressure drop

In-place HEPA filter penetration test

International Nuclear Information System (INIS)

Bergman, W.; Wilson, K.; Elliott, J.; Bettencourt, B.; Slawski, J.W.

1997-01-01

We have demonstrated the feasibility of conducting penetration tests on high efficiency particulate air (HEPA) filters as installed in nuclear ventilation systems. The in-place penetration test, which is designed to yield equivalent penetration measurements as the standard DOP efficiency test, is based on measuring the aerosol penetration of the filter installation as a function of particle size using a portable laser particle counter. This in-place penetration test is compared to the current in-place leak test using light scattering photometers for single HEPA filter installations and for HEPA filter plenums using the shroud method. Test results show the in-place penetration test is more sensitive than the in-place leak test, has a similar operating procedure, but takes longer to conduct. Additional tests are required to confirm that the in-place penetration test yields identical results as the standard dioctyl phthalate (DOP) penetration test for HEPA filters with controlled leaks in the filter and gasket and duct by-pass leaks. Further development of the procedure is also required to reduce the test time before the in- place penetration test is practical

Stochastic global optimization as a filtering problem

International Nuclear Information System (INIS)

Stinis, Panos

2012-01-01

We present a reformulation of stochastic global optimization as a filtering problem. The motivation behind this reformulation comes from the fact that for many optimization problems we cannot evaluate exactly the objective function to be optimized. Similarly, we may not be able to evaluate exactly the functions involved in iterative optimization algorithms. For example, we may only have access to noisy measurements of the functions or statistical estimates provided through Monte Carlo sampling. This makes iterative optimization algorithms behave like stochastic maps. Naive global optimization amounts to evolving a collection of realizations of this stochastic map and picking the realization with the best properties. This motivates the use of filtering techniques to allow focusing on realizations that are more promising than others. In particular, we present a filtering reformulation of global optimization in terms of a special case of sequential importance sampling methods called particle filters. The increasing popularity of particle filters is based on the simplicity of their implementation and their flexibility. We utilize the flexibility of particle filters to construct a stochastic global optimization algorithm which can converge to the optimal solution appreciably faster than naive global optimization. Several examples of parametric exponential density estimation are provided to demonstrate the efficiency of the approach.

Visual SLAM Using Variance Grid Maps

Science.gov (United States)

Howard, Andrew B.; Marks, Tim K.

2011-01-01

An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

A continuous-time adaptive particle filter for estimations under measurement time uncertainties with an application to a plasma-leucine mixed effects model.

Science.gov (United States)

Krengel, Annette; Hauth, Jan; Taskinen, Marja-Riitta; Adiels, Martin; Jirstrand, Mats

2013-01-19

When mathematical modelling is applied to many different application areas, a common task is the estimation of states and parameters based on measurements. With this kind of inference making, uncertainties in the time when the measurements have been taken are often neglected, but especially in applications taken from the life sciences, this kind of errors can considerably influence the estimation results. As an example in the context of personalized medicine, the model-based assessment of the effectiveness of drugs is becoming to play an important role. Systems biology may help here by providing good pharmacokinetic and pharmacodynamic (PK/PD) models. Inference on these systems based on data gained from clinical studies with several patient groups becomes a major challenge. Particle filters are a promising approach to tackle these difficulties but are by itself not ready to handle uncertainties in measurement times. In this article, we describe a variant of the standard particle filter (PF) algorithm which allows state and parameter estimation with the inclusion of measurement time uncertainties (MTU). The modified particle filter, which we call MTU-PF, also allows the application of an adaptive stepsize choice in the time-continuous case to avoid degeneracy problems. The modification is based on the model assumption of uncertain measurement times. While the assumption of randomness in the measurements themselves is common, the corresponding measurement times are generally taken as deterministic and exactly known. Especially in cases where the data are gained from measurements on blood or tissue samples, a relatively high uncertainty in the true measurement time seems to be a natural assumption. Our method is appropriate in cases where relatively few data are used from a relatively large number of groups or individuals, which introduce mixed effects in the model. This is a typical setting of clinical studies. We demonstrate the method on a small artificial example

HEPA Filter Performance under Adverse Conditions

International Nuclear Information System (INIS)

Parsons, Michael; Hogancamp, Kristina; Alderman, Steven; Waggoner, Charles

2007-01-01

This study involved challenging nuclear grade high-efficiency particulate air (HEPA) filters under a variety of conditions that can arise in Department of Energy (DOE) applications such as: low or high RH, controlled and uncontrolled challenge, and filters with physically damaged media or seals (i.e., leaks). Reported findings correlate filter function as measured by traditional differential pressure techniques in comparison with simultaneous instrumental determination of up and down stream PM concentrations. Additionally, emission rates and failure signatures will be discussed for filters that have either failed or exceeded their usable lifetime. Significant findings from this effort include the use of thermocouples up and down stream of the filter housing to detect the presence of moisture. Also demonstrated in the moisture challenge series of tests is the effect of repeated wetting of the filter. This produces a phenomenon referred to as transient failure before the tensile strength of the media weakens to the point of physical failure. An evaluation of the effect of particle size distribution of the challenge aerosol on loading capacity of filters is also included. Results for soot and two size distributions of KCl are reported. Loading capacities for filters ranged from approximately 70 g of soot to nearly 900 g for the larger particle size distribution of KCl. (authors)

Design and construction of demineralized water production and maintenance system for RA-O nuclear reactor

International Nuclear Information System (INIS)

Rumis, D.; Martin, H.R.

1990-01-01

The normal operation of zero power RA-O Nuclear Reactor requires a production and maintenance of demineralized water system. This system was designed and built-up during the works for actualization, upgrading and new start up at Cordoba National University of this facility. This paper comments the relevant aspects about the didactical purpose of that system and the details considered for training and practices with it. Similarly, considerations about solids wastes and effluents treatment are discussed. (Author)

Radioactive liquid waste filtering device

International Nuclear Information System (INIS)

Inami, Ichiro; Tabata, Masayuki; Kubo, Koji.

1988-01-01

Purpose: To prevent clogging in filter materials and improve the filtration performance for radioactive liquid wastes without increasing the amount of radioactive wastes. Constitution: In a radioactive waste filtering device, a liquid waste recycling pipe and a liquid recycling pump are disposed for recycling the radioactive liquid wastes in a liquid wastes vessel. In this case, the recycling pipe and the recycling pump are properly selected so as to satisfy the conditions capable of making the radioactive liquid wastes flowing through the pipe to have the Reynolds number of 10 4 - 10 5 . By repeating the transportation of radioactive liquid wastes in the liquid waste vessel through the liquid waste recycling pipe by the liquid waste recycling pump and then returning them to the liquid waste vessel again, particles of fine grain size in the suspended liquids are coagulated with each other upon collision to increase the grain size of the suspended particles. In this way, clogging of the filter materials caused by the particles of fine grain size can be prevented, thereby enabling to prevent the increase in the rising rate of the filtration differential pressure, reduce the frequency for the occurrence of radioactive wastes such as filter sludges and improve the processing performance. (Kamimura, M.)

Evaluation of the flathead catfish population and fishery on Lake Carl Blackwell, Oklahoma, with emphasis on the effects of noodling

Science.gov (United States)

Winkelman, Dana L.; Michaletz, Paul H.; Travnichek, Vincent H.

2011-01-01

I conducted a 3-year study at Lake Carl Blackwell, Oklahoma to estimate effects of various fishing gears on the flathead catfish Pylodictis olivaris population. Managers were particularly interested in the effect of handfishing or noodling on this population. I used a phone survey to assess angler effort and electrofishing and gill nets to calculate standard population metrics to assess composition of the current population. Survey data indicated that fishing effort and harvest were highest for trotlines and juglines and lowest for noodling. Size distribution of fish harvested by noodlers was not different from sizes that were available in the fishery and was similar to those fish harvested with other gears. Flathead catfish Sampled in Lake Carl Blackwell ranged in size from 38 to 1,220 mm total length, and 77% of the population was less than 508 mm (minimum legal size). Estimated total annual mortality was about 11%. Proportional size distribution (PSD) of flathead catfish for Lake Carl Blackwell indicates that about 70% of legal-sized flathead catfish were over the preferred size of 710 mm. Overall, the Lake Carl Blackwell flathead catfish population appeared healthy. There were a wide range of sizes and ages in the population, and PSD indicated a well-balanced population with many preferred and memorable-sized fish. Due to its rarity, noodling is probably not adversely influencing the population. Additionally, noodling at Lake Carl Blackwell does not appear to be as size-selective as previously thought. 

Retention of radioactive particles and associated effects in the filter-feeding marine mollusc Mytilus edulis

Energy Technology Data Exchange (ETDEWEB)

Jaeschke, B.C., E-mail: Ben.Jaeschke@gmail.com [Department of Ecology Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm (Sweden); CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway); Lind, O.C. [CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway); Bradshaw, C. [Department of Ecology Environment and Plant Sciences, Stockholm University, SE-106 91 Stockholm (Sweden); Salbu, B. [CERAD CoE, Department of Environmental Sciences, Norwegian University of Life Sciences (NMBU), P.O. Box 5003, N-1432 Ås (Norway)

2015-01-01

Radioactive particles are aggregates of radioactive atoms that may contain significant activity concentrations. They have been released into the environment from nuclear weapons tests, and from accidents and effluents associated with the nuclear fuel cycle. Aquatic filter-feeders can capture and potentially retain radioactive particles, which could then provide concentrated doses to nearby tissues. This study experimentally investigated the retention and effects of radioactive particles in the blue mussel, Mytilus edulis. Spent fuel particles originating from the Dounreay nuclear establishment, and collected in the field, comprised a U and Al alloy containing fission products such as {sup 137}Cs and {sup 90}Sr/{sup 90}Y. Particles were introduced into mussels in suspension with plankton-food or through implantation in the extrapallial cavity. Of the particles introduced with food, 37% were retained for 70 h, and were found on the siphon or gills, with the notable exception of one particle that was ingested and found in the stomach. Particles not retained seemed to have been actively rejected and expelled by the mussels. The largest and most radioactive particle (estimated dose rate 3.18 ± 0.06 Gy h{sup −1}) induced a significant increase in Comet tail-DNA %. In one case this particle caused a large white mark (suggesting necrosis) in the mantle tissue with a simultaneous increase in micronucleus frequency observed in the haemolymph collected from the muscle, implying that non-targeted effects of radiation were induced by radiation from the retained particle. White marks found in the tissue were attributed to ionising radiation and physical irritation. The results indicate that current methods used for risk assessment, based upon the absorbed dose equivalent limit and estimating the “no-effect dose” are inadequate for radioactive particle exposures. Knowledge is lacking about the ecological implications of radioactive particles released into the environment

Retention of radioactive particles and associated effects in the filter-feeding marine mollusc Mytilus edulis

International Nuclear Information System (INIS)

Jaeschke, B.C.; Lind, O.C.; Bradshaw, C.; Salbu, B.

2015-01-01

Radioactive particles are aggregates of radioactive atoms that may contain significant activity concentrations. They have been released into the environment from nuclear weapons tests, and from accidents and effluents associated with the nuclear fuel cycle. Aquatic filter-feeders can capture and potentially retain radioactive particles, which could then provide concentrated doses to nearby tissues. This study experimentally investigated the retention and effects of radioactive particles in the blue mussel, Mytilus edulis. Spent fuel particles originating from the Dounreay nuclear establishment, and collected in the field, comprised a U and Al alloy containing fission products such as 137 Cs and 90 Sr/ 90 Y. Particles were introduced into mussels in suspension with plankton-food or through implantation in the extrapallial cavity. Of the particles introduced with food, 37% were retained for 70 h, and were found on the siphon or gills, with the notable exception of one particle that was ingested and found in the stomach. Particles not retained seemed to have been actively rejected and expelled by the mussels. The largest and most radioactive particle (estimated dose rate 3.18 ± 0.06 Gy h −1 ) induced a significant increase in Comet tail-DNA %. In one case this particle caused a large white mark (suggesting necrosis) in the mantle tissue with a simultaneous increase in micronucleus frequency observed in the haemolymph collected from the muscle, implying that non-targeted effects of radiation were induced by radiation from the retained particle. White marks found in the tissue were attributed to ionising radiation and physical irritation. The results indicate that current methods used for risk assessment, based upon the absorbed dose equivalent limit and estimating the “no-effect dose” are inadequate for radioactive particle exposures. Knowledge is lacking about the ecological implications of radioactive particles released into the environment, for example

Velocity measurements in a rigid ceramic filter in a parallel-flow arrangement

International Nuclear Information System (INIS)

Al-Hajeri, M.H.; Aroussi, A.; Witry, A.

2002-01-01

Rigid ceramic filters have been developed for cleaning the hot combustion gas streams upstream of the turbine in a combined cycle power plant. To obtain continues operation a periodic cleaning is necessary and the cleaning efficiency depends on the distribution of the filtration cake. Consequently uniform particle deposition on the filter element surface is desired. The flow around three filter elements in cross flow is investigated computationally using the commercial code FLUENT. Three filter elements are placed in a two-dimensional rectangle duct with fixed face velocity and varying the velocity ratio between the approach and face velocity. Particle trajectories are obtained for a number of particle diameters and different inlet (approach) velocity to face filtration velocity ratios to investigate the behavior of particles around the filter element. (author)

Energy-filtered TEM imaging and EELS study of ODS particles and argon-filled cavities in ferritic-martensitic steels.

Science.gov (United States)

Klimiankou, M; Lindau, R; Möslang, A

2005-01-01

Oxide-dispersion-strengthened (ODS) ferritic-martensitic steels with yttrium oxide (Y(2)O(3)) have been produced by mechanical alloying and hot isostatic pressing for use as advanced material in fusion power reactors. Argon gas, usually widely used as inert gas during mechanical alloying, was surprisingly detected in the nanodispersion-strengthened materials. Energy-filtered transmission electron microscopy (EFTEM) and electron energy loss spectroscopy (EELS) led to the following results: (i) chemical composition of ODS particles, (ii) voids with typical diameters of 1-6 nm are formed in the matrix, (iii) these voids are filled with Ar gas, and (iv) the high-density nanosized ODS particles serve as trapping centers for the Ar bubbles. The Ar L(3,2) energy loss edge at 245 eV as well as the absorption features of the ODS particle elements were identified in the EELS spectrum. The energy resolution in the EEL spectrum of about 1.0 eV allows to identify the electronic structure of the ODS particles.

Experimental study of filter cake formation on different filter media

International Nuclear Information System (INIS)

Saleem, M.

2009-01-01

Removal of particulate matter from gases generated in the process industry is important for product recovery as well as emission control. Dynamics of filtration plant depend on operating conditions. The models, that predict filter plant behaviour, involve empirical resistance parameters which are usually derived from limited experimental data and are characteristics of the filter media and filter cake (dust deposited on filter medium). Filter cake characteristics are affected by the nature of filter media, process parameters and mode of filter regeneration. Removal of dust particles from air is studied in a pilot scale jet pulsed bag filter facility resembling closely to the industrial filters. Limestone dust and ambient air are used in this study with two widely different filter media. All important parameters like pressure drop, gas flow rate, dust settling, are recorded continuously at 1s interval. The data is processed for estimation of the resistance parameters. The pressure drop rise on test filter media is compared. Results reveal that the surface of filter media has an influence on pressure drop rise (concave pressure drop rise). Similar effect is produced by partially jet pulsed filter surface. Filter behaviour is also simulated using estimated parameters and a simplified model and compared with the experimental results. Distribution of cake area load is therefore an important aspect of jet pulse cleaned bag filter modeling. Mean specific cake resistance remains nearly constant on thoroughly jet pulse cleaned membrane coated filter bags. However, the trend can not be confirmed without independent cake height and density measurements. Thus the results reveal the importance of independent measurements of cake resistance. (author)

Evaluation of the effect of media velocity on HEPA filter performance

International Nuclear Information System (INIS)

Alderman, Steven; Parsons, Michael; Hogancamp, Kristina; Norton, O. Perry; Waggoner, Charles

2007-01-01

Section FC of the ASME AG-1 Code addresses glass fiber HEPA filters and restricts the media velocity to a maximum of 2.54 cm/s (5 ft/min). Advances in filter media technology allow glass fiber HEPA filters to function at significantly higher velocities and still achieve HEPA performance. However, diffusional capture of particles < 100 nm is reduced at higher media velocities due to shorter residence times within the media matrix. Therefore, it is unlikely that higher media velocities for HEPA filters will be allowed without data to demonstrate the effect of media velocity on removal of particles in the smaller size classes. In order to address this issue, static testing has been conducted to generate performance related data and a range of dynamic testing has provided data regarding filter lifetimes, loading characteristics, changes in filter efficiency and the most penetrating particle size over time. Testing was conducted using 31 cm x 31 cm x 29 cm deep pleat HEPA filters supplied from two manufacturers. Testing was conducted at media velocities ranging from 2.0-4.5 cm/s with a solid aerosol challenge composed of potassium chloride. Two set of media velocity data were obtained for each filter type. In one set of evaluations, the maximum aerosol challenge particle size was limited to 3 μm, while particles above 3 μm were not constrained in the second set. This provided for considerable variability in the challenge mass mean diameter and overall mass loading rate. Results of this testing will be provided to the ASME AG-1 FC Committee for consideration in future versions of the HEPA standard. In general, the initial filter efficiency decreased with increasing media velocity. However, initial filter efficiencies were generally good in all cases. Filter efficiency values averaged over the first ten minute of the loading cycle ranged from 99.970 to 99.996 %. Additionally, the most penetrating particle size was observed to decrease with increasing media velocity

In-situ high efficiency filter testing at AEE Winfrith

International Nuclear Information System (INIS)

Fraser, D.C.

1977-01-01

This paper discusses experience in the testing of high efficiency filters in a variety of reactor and plant installations at AEE Winfrith. There is rarely any concern about the effectiveness of the filter as supplied by any reputable manufacturer. Experience has shown there is a need to check for defects in the installation of filters which could lead to by-passing of aerosols and it is desirable to perform periodical re-tests to ensure that no subsequent deterioration occurs. It is important to use simple, portable apparatus for such tests; methods based on the use of sodium chloride aerosols, although suitable for the testing of filters prior to installation, involve apparatus which is too bulky for in-situ testing. At Winfrith a double automatic Pollak counter has been developed and used routinely since 1970. The aerosol involved has a particle size far smaller than the size most likely to penetrate intact filters, but this is irrelevant when one is primarily interested in particles which by-pass the filter. Comparisons with other methods of testing filters will be described. There is remarkably good agreement between the efficiency of the filter installation as measured by a Pollak counter compared with techniques involving aerosols of sodium chloride and Dioctyl Phthalate (DOP), presumably because the leakage around the filter is independent of particle size

Estimation of visual maps with a robot network equipped with vision sensors.

Science.gov (United States)

Gil, Arturo; Reinoso, Óscar; Ballesta, Mónica; Juliá, Miguel; Payá, Luis

2010-01-01

In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM) problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

Estimation of Visual Maps with a Robot Network Equipped with Vision Sensors

Directory of Open Access Journals (Sweden)

Arturo Gil

2010-05-01

Full Text Available In this paper we present an approach to the Simultaneous Localization and Mapping (SLAM problem using a team of autonomous vehicles equipped with vision sensors. The SLAM problem considers the case in which a mobile robot is equipped with a particular sensor, moves along the environment, obtains measurements with its sensors and uses them to construct a model of the space where it evolves. In this paper we focus on the case where several robots, each equipped with its own sensor, are distributed in a network and view the space from different vantage points. In particular, each robot is equipped with a stereo camera that allow the robots to extract visual landmarks and obtain relative measurements to them. We propose an algorithm that uses the measurements obtained by the robots to build a single accurate map of the environment. The map is represented by the three-dimensional position of the visual landmarks. In addition, we consider that each landmark is accompanied by a visual descriptor that encodes its visual appearance. The solution is based on a Rao-Blackwellized particle filter that estimates the paths of the robots and the position of the visual landmarks. The validity of our proposal is demonstrated by means of experiments with a team of real robots in a office-like indoor environment.

Development and evaluation of hot filters

International Nuclear Information System (INIS)

Thexton, H.E.

1975-01-01

High temperature, high flow filtration removes radioactive particles from the primary coolant, as well as inactive particles before they can become activated. Canadian experience with edge, graphite, and magnetic filters is described. (Author)

Effect of Pore Structure on Soot Deposition in Diesel Particulate Filter

Directory of Open Access Journals (Sweden)

Kazuhiro Yamamoto

2016-12-01

Full Text Available Nowadays, in the after-treatment of diesel exhaust gas, a diesel particulate filter (DPF has been used to trap nano-particles of the diesel soot. However, as there are more particles inside the filter, the pressure which corresponds to the filter backpressure increases, which worsens the fuel consumption rate, together with the abatement of the available torque. Thus, a filter with lower backpressure would be needed. To achieve this, it is necessary to utilize the information on the phenomena including both the soot transport and its removal inside the DPF, and optimize the filter substrate structure. In this paper, to obtain useful information for optimization of the filter structure, we tested seven filters with different porosities and pore sizes. The porosity and pore size were changed systematically. To consider the soot filtration, the particle-laden flow was simulated by a lattice Boltzmann method (LBM. Then, the flow field and the pressure change were discussed during the filtration process.

In-place HEPA filter penetration test

Energy Technology Data Exchange (ETDEWEB)

Bergman, W.; Wilson, K.; Elliott, J. [Lawrence Livermore National Lab., CA (United States)] [and others

1997-08-01

We have demonstrated the feasibility of conducting penetration tests on high efficiency particulate air (HEPA) filters as installed in nuclear ventilation systems. The in-place penetration test, which is designed to yield equivalent penetration measurements as the standard DOP efficiency test, is based on measuring the aerosol penetration of the filter installation as a function of particle size using a portable laser particle counter. This in-place penetration test is compared to the current in-place leak test using light scattering photometers for single HEPA filter installations and for HEPA filter plenums using the shroud method. Test results show the in-place penetration test is more sensitive than the in-place leak test, has a similar operating procedure, but takes longer to conduct. Additional tests are required to confirm that the in-place penetration test yields identical results as the standard dioctyl phthalate (DOP) penetration test for HEPA filters with controlled leaks in the filter and gasket and duct by-pass leaks. Further development of the procedure is also required to reduce the test time before the in-place penetration test is practical. 14 refs., 14 figs., 3 tabs.

Large-scale generic test stand for testing of multiple configurations of air filters utilizing a range of particle size distributions

Science.gov (United States)

Giffin, Paxton K.; Parsons, Michael S.; Unz, Ronald J.; Waggoner, Charles A.

2012-05-01

The Institute for Clean Energy Technology (ICET) at Mississippi State University has developed a test stand capable of lifecycle testing of high efficiency particulate air filters and other filters specified in American Society of Mechanical Engineers Code on Nuclear Air and Gas Treatment (AG-1) filters. The test stand is currently equipped to test AG-1 Section FK radial flow filters, and expansion is currently underway to increase testing capabilities for other types of AG-1 filters. The test stand is capable of producing differential pressures of 12.45 kPa (50 in. w.c.) at volumetric air flow rates up to 113.3 m3/min (4000 CFM). Testing is performed at elevated and ambient conditions for temperature and relative humidity. Current testing utilizes three challenge aerosols: carbon black, alumina, and Arizona road dust (A1-Ultrafine). Each aerosol has a different mass median diameter to test loading over a wide range of particles sizes. The test stand is designed to monitor and maintain relative humidity and temperature to required specifications. Instrumentation is implemented on the upstream and downstream sections of the test stand as well as on the filter housing itself. Representative data are presented herein illustrating the test stand's capabilities. Digital images of the filter pack collected during and after testing is displayed after the representative data are discussed. In conclusion, the ICET test stand with AG-1 filter testing capabilities has been developed and hurdles such as test parameter stability and design flexibility overcome.

Guitarist Fingertip Tracking by Integrating a Bayesian Classifier into Particle Filters

Directory of Open Access Journals (Sweden)

Chutisant Kerdvibulvech

2008-01-01

Full Text Available We propose a vision-based method for tracking guitar fingerings made by guitar players. We present it as a new framework for tracking colored finger markers by integrating a Bayesian classifier into particle filters. This adds the useful abilities of automatic track initialization and recovery from tracking failures in a dynamic background. Furthermore, by using the online adaptation of color probabilities, this method is able to cope with illumination changes. Augmented Reality Tag (ARTag is then utilized to calculate the projection matrix as an online process which allows the guitar to be moved while being played. Representative experimental results are also included. The method presented can be used to develop the application of human-computer interaction (HCI to guitar playing by recognizing the chord being played by a guitarist in virtual spaces. The aforementioned application would assist guitar learners by allowing them to automatically identify if they are using the correct chords required by the musical piece.

Generalised Filtering

Directory of Open Access Journals (Sweden)

Karl Friston

2010-01-01

Full Text Available We describe a Bayesian filtering scheme for nonlinear state-space models in continuous time. This scheme is called Generalised Filtering and furnishes posterior (conditional densities on hidden states and unknown parameters generating observed data. Crucially, the scheme operates online, assimilating data to optimize the conditional density on time-varying states and time-invariant parameters. In contrast to Kalman and Particle smoothing, Generalised Filtering does not require a backwards pass. In contrast to variational schemes, it does not assume conditional independence between the states and parameters. Generalised Filtering optimises the conditional density with respect to a free-energy bound on the model's log-evidence. This optimisation uses the generalised motion of hidden states and parameters, under the prior assumption that the motion of the parameters is small. We describe the scheme, present comparative evaluations with a fixed-form variational version, and conclude with an illustrative application to a nonlinear state-space model of brain imaging time-series.

Mechanistic failure mode investigation and resolution of parvovirus retentive filters.

Science.gov (United States)

LaCasse, Daniel; Lute, Scott; Fiadeiro, Marcus; Basha, Jonida; Stork, Matthew; Brorson, Kurt; Godavarti, Ranga; Gallo, Chris

2016-07-08

Virus retentive filters are a key product safety measure for biopharmaceuticals. A simplistic perception is that they function solely based on a size-based particle removal mechanism of mechanical sieving and retention of particles based on their hydrodynamic size. Recent observations have revealed a more nuanced picture, indicating that changes in viral particle retention can result from process pressure and/or flow interruptions. In this study, a mechanistic investigation was performed to help identify a potential mechanism leading to the reported reduced particle retention in small virus filters. Permeate flow rate or permeate driving force were varied and analyzed for their impact on particle retention in three commercially available small virus retentive filters. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:959-970, 2016. © 2016 American Institute of Chemical Engineers.

Field test of radioactive high efficiency filter and filter exchange techniques of fuel cycle examination facility

International Nuclear Information System (INIS)

Hwang, Yong Hwa; Lee, Hyung Kwon; Chun, Young Bum; Park, Dae Gyu; Ahn, Sang Bok; Chu, Yong Sun; Kim, Eun Ka.

1997-12-01

The development of high efficiency filter was started to protect human beings from the contamination of radioactive particles, toxic gases and bacillus, and its gradual performance increment led to the fabrication of Ultra Low Penetration Air Filter (ULPA) today. The application field of ULPA has been spread not only to the air conditioning of nuclear power facilities, semiconductor industries, life science, optics, medical care and general facilities but also to the core of ultra-precision facilities. Periodic performance test on the filters is essential to extend its life-time through effective maintenance. Especially, the bank test on HEPA filter of nuclear facilities handling radioactive materials is required for environmental safety. Nowadays, the bank test technology has been reached to the utilization of a minimized portable detecting instruments and the evaluation techniques can provide high confidence in the area of particle distribution and leakage test efficiency. (author). 16 refs., 13 tabs., 14 figs

Filter cake breaker systems

Energy Technology Data Exchange (ETDEWEB)

Garcia, Marcelo H.F. [Poland Quimica Ltda., Duque de Caxias, RJ (Brazil)

2004-07-01

Drilling fluids filter cakes are based on a combination of properly graded dispersed particles and polysaccharide polymers. High efficiency filter cakes are formed by these combination , and their formation on wellbore walls during the drilling process has, among other roles, the task of protecting the formation from instantaneous or accumulative invasion of drilling fluid filtrate, granting stability to well and production zones. Filter cake minimizes contact between drilling fluid filtrate and water, hydrocarbons and clay existent in formations. The uniform removal of the filter cake from the entire interval is a critical factor of the completion process. The main methods used to breaking filter cake are classified into two groups, external or internal, according to their removal mechanism. The aim of this work is the presentation of these mechanisms as well their efficiency. (author)

Particle filtering based structural assessment with acoustic emission sensing

Science.gov (United States)

Yan, Wuzhao; Abdelrahman, Marwa; Zhang, Bin; Ziehl, Paul

2017-02-01

Nuclear structures are designed to withstand severe loading events under various stresses. Over time, aging of structural systems constructed with concrete and steel will occur. This deterioration may reduce service life of nuclear facilities and/or lead to unnecessary or untimely repairs. Therefore, online monitoring of structures in nuclear power plants and waste storage has drawn significant attention in recent years. Of many existing non-destructive evaluation and structural monitoring approaches, acoustic emission is promising for assessment of structural damage because it is non-intrusive and is sensitive to corrosion and crack growth in reinforced concrete elements. To provide a rapid, actionable, and graphical means for interpretation Intensity Analysis plots have been developed. This approach provides a means for classification of damage. Since the acoustic emission measurement is only an indirect indicator of structural damage, potentially corrupted by non-genuine data, it is more suitable to estimate the states of corrosion and cracking in a Bayesian estimation framework. In this paper, we will utilize the accelerated corrosion data from a specimen at the University of South Carolina to develop a particle filtering-based diagnosis and prognosis algorithm. Promising features of the proposed algorithm are described in terms of corrosion state estimation and prediction of degradation over time to a predefined threshold.

Diesel particles - a health hazard

Energy Technology Data Exchange (ETDEWEB)

Ege, C.

2004-08-15

To all appearances, small particles belong to the pollutants presenting the biggest health hazards. Particles come especially from diesel-powered vehicles. According to researchers, particles cause thousands of early deaths each year in the big cities in Denmark alone, and up to 1,250 of these deaths could be prevented by fitting particle filters on diesel-powered vehicles. That is more than deaths caused by traffic accidents. Especially the elderly are affected. In addition, the small particles seem to aggravate asthma incidences, including the many children with asthma. What makes the small particles so very dangerous is that they can enter the smallest of vessels of the lungs. There is a solution within sight to this grave health hazard. The solution is called particle filters, but they will not come automatically. It requires initiatives in the form of legislation, green taxes and subsidies. The EU is introducing stricter regulations regarding particle emission from heavy vehicles from 2006, though only for new vehicles. It will therefore take many years to abate the problem this way. In the present pamphlet, the Danish Ecological Council offers a number of specific proposals on how to further the introduction of filters on diesel vehicles. The Danish government has taken a small step in the right direction by establishing a subsidy scheme for particle filters. Yet the amount allocated is too small and, because it is not followed up by setting taxes on polluting vehicles, it will have little effect. (au)

Marginalized approximate filtering of state-space models

Czech Academy of Sciences Publication Activity Database

Dedecius, Kamil

2018-01-01

Roč. 32, č. 1 (2018), s. 1-12 ISSN 0890-6327 R&D Projects: GA ČR(CZ) GA16-09848S Institutional support: RVO:67985556 Keywords : approximate filtering * marginalized filters * particle filtering Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.708, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/dedecius-0478074.pdf

The characteristics and application of sludge-fly ash ceramic particles (SFCP) as novel filter media

International Nuclear Information System (INIS)

Han Shuxin; Yue Qinyan; Yue Min; Gao Baoyu; Li Qian; Yu Hui; Zhao Yaqin; Qi Yuanfeng

2009-01-01

Novel filter media-sludge-fly ash ceramic particles (SFCP) were prepared using dewatered sludge, fly ash and clay with a mass ratio of 1:1:1. Compared with commercial ceramic particles (CCP), SFCP had higher total porosity, larger total surface area and lower bulk and apparent density. Tests of heavy metal elements in lixivium proved that SFCP were safe for wastewater treatment. A lab-scale upflow anaerobic bioreactor was employed to ascertain the application of SFCP in denitrification process using acetate as carbon source. The results showed that SFCP reactor brought a relative superiority to CCP reactor in terms of total nitrogen (TN) removal at the optimum C/N ratio of 4.03 when volumetric loading rates (VLR) ranged from 0.33 to 3.69 kg TN (m 3 d) -1 . Therefore, SFCP application, as a novel process of treating wastes with wastes, provided a promising way in sludge and fly ash utilization.

Microplastic in a macro filter feeder: humpback whale Megaptera novaeangliae

NARCIS (Netherlands)

Besseling, E.; Foekema, E.M.; Franeker, van J.A.; Leopold, M.F.; Bravo Rebolledo, E.; Kuehn, S.; Mielke, L.; Heberle-Bors, E.; Ijzer, J.; Kamminga, P.; Koelmans, A.A.

2015-01-01

Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in

Microplastic in a macro filter feeder: Humpback whale Megaptera novaeangliae.

NARCIS (Netherlands)

E., Besseling,; E.M., Foekema,; J.A. van, Franeker; Leopold, Mardik F; Kuhn, S.; Bravo Rebolledo, E.L.; Hese, E.; Mielke, L.; IJzer, J.|info:eu-repo/dai/nl/304839663; Kamminga, P.; Koelmans, A.A.

2015-01-01

Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in

MST Filterability Tests

Energy Technology Data Exchange (ETDEWEB)

Poirier, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Burket, P. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Duignan, M. R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2015-03-12

The Savannah River Site (SRS) is currently treating radioactive liquid waste with the Actinide Removal Process (ARP) and the Modular Caustic Side Solvent Extraction Unit (MCU). The low filter flux through the ARP has limited the rate at which radioactive liquid waste can be treated. Recent filter flux has averaged approximately 5 gallons per minute (gpm). Salt Batch 6 has had a lower processing rate and required frequent filter cleaning. Savannah River Remediation (SRR) has a desire to understand the causes of the low filter flux and to increase ARP/MCU throughput. In addition, at the time the testing started, SRR was assessing the impact of replacing the 0.1 micron filter with a 0.5 micron filter. This report describes testing of MST filterability to investigate the impact of filter pore size and MST particle size on filter flux and testing of filter enhancers to attempt to increase filter flux. The authors constructed a laboratory-scale crossflow filter apparatus with two crossflow filters operating in parallel. One filter was a 0.1 micron Mott sintered SS filter and the other was a 0.5 micron Mott sintered SS filter. The authors also constructed a dead-end filtration apparatus to conduct screening tests with potential filter aids and body feeds, referred to as filter enhancers. The original baseline for ARP was 5.6 M sodium salt solution with a free hydroxide concentration of approximately 1.7 M.3 ARP has been operating with a sodium concentration of approximately 6.4 M and a free hydroxide concentration of approximately 2.5 M. SRNL conducted tests varying the concentration of sodium and free hydroxide to determine whether those changes had a significant effect on filter flux. The feed slurries for the MST filterability tests were composed of simple salts (NaOH, NaNO₂, and NaNO₃) and MST (0.2 – 4.8 g/L). The feed slurry for the filter enhancer tests contained simulated salt batch 6 supernate, MST, and filter enhancers.

Assessment of lumen degradation and remaining useful life of LEDs using particle filter

Energy Technology Data Exchange (ETDEWEB)

Lall, Pradeep [Auburn Univ., AL (United States); Zhang, Hao [Auburn Univ., AL (United States); Davis, Lynn [Auburn Univ., AL (United States)

2013-07-16

With the development of light-emitting diode (LED) technology, light emitting diodes system is becoming a popular light source in daily life and industry area. It has shown that Led from same factory and work under same working condition, may have significantly different behavior. Therefore, it is very important to learn the fail mechanisms, especially in the case of safety critical and harsh environment application. This paper focus on a prognostic health management (PHM) method based on the measurement of forward voltage and forward current of bare LED under harsh environment. In this paper, experiment has been done with ten samples. Ten pristine bare LEDs have been tested at 85°C while simultaneously being subjected to 85% humid environment. Pulse width modulation (PWM) control method has been employed to drive the bare LED in order to reduce the heat effect caused by forward current and high frequency (300HZ) data acquisition has been used to measure the peak forward voltage and forward current. Test to failure (lumen drops to 70 percent) data has been measured to study the effects of high temperature and humid environment loadings on the bare LED. Also, solid state cooling method with peltier cooler has been used to control the temperature of LED in the integrating sphere when take the measurement of lumen flux. The shift of forward voltage forward current curve and lumen degradation has been recorded to help build the fail model and predicted the remaining useful life. In this method, particle filter has been employed to predict the remaining useful life (RUL) of the bare LED and give us a whole picture how Led system fails. Result shows that predication of remaining useful life of Led, made by the particle filter model works under reasonable limit, and hence this method can be employed to predict the failure of Led caused by thermal and humid stress under harsh environment.

In-situ testing of high efficiency filters at AEE Winfrith

International Nuclear Information System (INIS)

Fraser, D.C.

1977-10-01

This paper discusses experience in the testing of high efficiency filters in a variety of reactor and plant installations at AEE Winfrith. There is rarely any concern about the effectiveness of the filter as supplied by any reputable manufacturer. Experience has shown there is a need to check for defects in the installation of filters which could lead to by-passing of aerosols and it is desirable to perform periodical re-tests to ensure that no subsequent deterioration occurs. It is important to use simple, portable apparatus for such tests; methods based on the use of sodium chloride aerosols, although suitable for the testing of filters prior to installation, involve apparatus which is too bulky for in-situ testing. At Winfrith a double automatic Pollak counter has been developed and used routinely since 1970. The aerosol involved has a particle size far smaller than the size most likely to penetrate intact filters, but this is irrelevant when one is primarily interested in particles which by-pass the filter. Comparisons with other methods of testing filters will be described. There is remarkably good agreement between the efficiency of the filter installation as measured by a Pollak counter compared with techniques involving aerosols of sodium chloride and di octyl phthalate (DOP), presumably because the leakage around the filter is independent of particle size. (author)

Factors Influencing HEPA Filter Performance

International Nuclear Information System (INIS)

Parsons, M.S.; Waggoner, Ch.A.

2009-01-01

Properly functioning HEPA air filtration systems depend on a variety of factors that start with the use of fully characterized challenge conditions for system design and then process control during operation. This paper addresses factors that should be considered during the design phase as well as operating parameters that can be monitored to ensure filter function and lifetime. HEPA filters used in nuclear applications are expected to meet design, fabrication, and performance requirements set forth in the ASME AG-1 standard. The DOE publication Nuclear Air Cleaning Handbook (NACH) is an additional guidance document for design and operation HEPA filter systems in DOE facilities. These two guidelines establish basic maximum operating parameters for temperature, maximum aerosol particle size, maximum particulate matter mass concentration, acceptable differential pressure range, and filter media velocity. Each of these parameters is discussed along with data linking variability of each parameter with filter function and lifetime. Temporal uncertainty associated with gas composition, temperature, and absolute pressure of the air flow can have a direct impact on the volumetric flow rate of the system with a corresponding impact on filter media velocity. Correlations between standard units of flow rate (standard meters per minute or cubic feet per minute) versus actual units of volumetric flow rate are shown for variations in relative humidity for a 70 deg. C to 200 deg. C temperature range as an example of gas composition that, uncorrected, will influence media velocity. The AG-1 standard establishes a 2.5 cm/s (5 feet per minute) ceiling for media velocities of nuclear grade HEPA filters. Data are presented that show the impact of media velocities from 2.0 to 4.0 cm/s media velocities (4 to 8 fpm) on differential pressure, filter efficiency, and filter lifetime. Data will also be presented correlating media velocity effects with two different particle size

Aerosol-phase Activity of Iodine Captured from a Triiodide Resin Filter on Fine Particles Containing an Infectious Virus

Science.gov (United States)

2015-01-01

filtration pro cess must be expected to experience attenuation at the point of aerosol contact with the mucosal surface. The effect of environmental...nebulizer were con nected using 79 mm ID, 127 mm OD conductive electrical tubing (TSI) to minimize particle attraction. Downstream of the filter holder...Na2CO3 (Gooch and Valker 1905; OSHA 1994). The negative control was bags filled with clean air and processed similarly immedi ately after filling. Iodine

Hydrodynamics of microbial filter feeding

DEFF Research Database (Denmark)

Nielsen, Lasse Tor; Asadzadeh, Seyed Saeed; Dölger, Julia

2017-01-01

Microbial filter feeders are an important group of grazers, significant to the microbial loop, aquatic food webs, and biogeochemical cycling. Our understanding of microbial filter feeding is poor, and, importantly, it is unknown what force microbial filter feeders must generate to process adequate......-feeding choanoflagellate Diaphanoeca grandis using particle tracking, and demonstrate that the current understanding of microbial filter feeding is inconsistent with computational fluid dynamics (CFD) and analytical estimates. Both approaches underestimate observed filtration rates by more than an order of magnitude......; the beating flagellum is simply unable to draw enough water through the fine filter. We find similar discrepancies for other choanoflagellate species, highlighting an apparent paradox. Our observations motivate us to suggest a radically different filtration mechanism that requires a flagellar vane (sheet...

Memories of Miles – Miles Blackwell and his contribution to South African librarianship

Directory of Open Access Journals (Sweden)

A.S.C. Hooper

2010-01-01

Full Text Available The contribution of BH Blackwell (BHB, and specifically of Miles Blackwell, to the development of libraries and librarians in South Africa is explored based on available literature sources and personal reminiscences. This article tells how Miles was true to his personal values and how he demonstrated his integrity in the exercise of his office. Miles integrated in his mind the history of the “firm” of BHB and the times that it lived though with his sense of his responsibility to his customers. He was prepared to stand up against enormous political pressure from his peers in Europe and North America, and perhaps his fellow board members in BHB, to make sure that the channels of published information flow remained open to his customers in South Africa. The value of books and information was what he believed in. His service to his customers in South Africa reflected the self-sacrificing service ethic that he understood to be the essence of the family firm of which he had the great privilege of leading. He contributed to the development of the new, post-apartheid South Africa by ensuring that the people who needed the enlightened word to become part of the global society, benefited by what he had done.

Fuel Property, Emission Test, and Operability Results from a Fleet of Class 6 Vehicles Operating on Gas-to-Liquid Fuel and Catalyzed Diesel Particle Filters

Energy Technology Data Exchange (ETDEWEB)

Alleman, T. L.; Eudy, L.; Miyasato, M.; Oshinuga, A.; Allison, S.; Corcoran, T.; Chatterjee, S.; Jacobs, T.; Cherrillo, R. A.; Clark, R.; Virrels, I.; Nine, R.; Wayne, S.; Lansing, R.

2005-11-01

A fleet of six 2001 International Class 6 trucks operating in southern California was selected for an operability and emissions study using gas-to-liquid (GTL) fuel and catalyzed diesel particle filters (CDPF). Three vehicles were fueled with CARB specification diesel fuel and no emission control devices (current technology), and three vehicles were fueled with GTL fuel and retrofit with Johnson Matthey's CCRT diesel particulate filter. No engine modifications were made.

Kaon Filtering For CLAS Data

International Nuclear Information System (INIS)

McNabb, J.

2001-01-01

The analysis of data from CLAS is a multi-step process. After the detectors for a given running period have been calibrated, the data is processed in the so called pass-1 cooking. During the pass-1 cooking each event is reconstructed by the program a1c which finds particle tracks and computes momenta from the raw data. The results are then passed on to several data monitoring and filtering utilities. In CLAS software, a filter is a parameterless function which returns an integer indicating whether an event should be kept by that filter or not. There is a main filter program called g1-filter which controls several specific filters and outputs several files, one for each filter. These files may then be analyzed separately, allowing individuals interested in one reaction channel to work from smaller files than using the whole data set would require. There are several constraints on what the filter functions should do. Obviously, the filtered files should be as small as possible, however the filter should also not reject any events that might be used in the later analysis for which the filter was intended

Hybrid unscented particle filter based state-of-charge determination for lead-acid batteries

International Nuclear Information System (INIS)

Shen, Yanqing

2014-01-01

Accurate prediction of cell SOC (state of charge) is important for the safety and functional capabilities of the battery energy storage application system. This paper presents a hybrid UPF (unscented particle filter) based SOC determination combined model for batteries. To simulate the entire dynamic electrical characteristics of batteries, a novel combined state space model, which takes current as a control input and let SOC and two constructed parameters as state variables, is advanced to represent cell behavior. Besides that, an improved UPF method is used to evaluate cell SOC. Taking lead-acid batteries for example, we apply the established model for test. Results show that the evolved combined state space cell model simulates battery dynamics robustly with high accuracy and the prediction value based on the improved UPF method converges to the real SOC very quickly within the error of±2%. - Highlights: • This paper introduces a hybrid UPF based SOC determination model for batteries. • The evolved model takes SOC and two constructed parameters as state variables. • The combined state space cell model simulates battery dynamics robustly. • NLMS based method is employed to lessen search space and fasten convergence process. • Novel model converges to the real SOC robustly and quickly with fewer particles

Comparative study of in-situ filter test methods

International Nuclear Information System (INIS)

Marshall, M.; Stevens, D.C.

1981-01-01

Available methods of testing high efficiency particulate aerosol (HEPA) filters in-situ have been reviewed. In order to understand the relationship between the results produced by different methods a selection has been compared. Various pieces of equipment for generating and detecting aerosols have been tested and their suitability assessed. Condensation-nuclei, DOP (di-octyl phthalate) and sodium-flame in-situ filter test methods have been studied, using the 500 cfm (9000 m 3 /h) filter test rig at Harwell and in the field. Both the sodium-flame and DOP methods measure the penetration through leaks and filter material. However the measured penetration through filtered leaks depends on the aerosol size distribution and the detection method. Condensation-nuclei test methods can only be used to measure unfiltered leaks since condensation nuclei have a very low penetration through filtered leaks. A combination of methods would enable filtered and unfiltered leaks to be measured. A condensation-nucleus counter using n-butyl alcohol as the working fluid has the advantage of being able to detect any particle up to 1 μm in diameter, including DOP, and so could be used for this purpose. A single-particle counter has not been satisfactory because of interference from particles leaking into systems under extract, particularly downstream of filters, and because the concentration of the input aerosol has to be severely limited. The sodium-flame method requires a skilled operator and may cause safety and corrosion problems. The DOP method using a total light scattering detector has so far been the most satisfactory. It is fairly easy to use, measures reasonably low values of penetration and gives rapid results. DOP has had no adverse effect on HEPA filters over a long series of tests

Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception.

Science.gov (United States)

Kutschireiter, Anna; Surace, Simone Carlo; Sprekeler, Henning; Pfister, Jean-Pascal

2017-08-18

The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical estimation can be rigorously formulated by nonlinear Bayesian filtering theory. Recent experimental and behavioral studies have shown that animals' performance in many tasks is consistent with such a Bayesian statistical interpretation. However, it is presently unclear how a nonlinear Bayesian filter can be efficiently implemented in a network of neurons that satisfies some minimum constraints of biological plausibility. Here, we propose the Neural Particle Filter (NPF), a sampling-based nonlinear Bayesian filter, which does not rely on importance weights. We show that this filter can be interpreted as the neuronal dynamics of a recurrently connected rate-based neural network receiving feed-forward input from sensory neurons. Further, it captures properties of temporal and multi-sensory integration that are crucial for perception, and it allows for online parameter learning with a maximum likelihood approach. The NPF holds the promise to avoid the 'curse of dimensionality', and we demonstrate numerically its capability to outperform weighted particle filters in higher dimensions and when the number of particles is limited.

Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation

Directory of Open Access Journals (Sweden)

Tao Li

2016-03-01

Full Text Available The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF and Kalman filter (KF. The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.

Particle Filter with Novel Nonlinear Error Model for Miniature Gyroscope-Based Measurement While Drilling Navigation.

Science.gov (United States)

Li, Tao; Yuan, Gannan; Li, Wang

2016-03-15

The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD) system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM) can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS) sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM) by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF) and Kalman filter (KF). The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition.

Removing Pathogens Using Nano-Ceramic-Fiber Filters

Science.gov (United States)

Tepper, Frederick; Kaledin, Leonid

2005-01-01

A nano-aluminum-oxide fiber of only 2 nanometers in diameter was used to develop a ceramic-fiber filter. The fibers are electropositive and, when formulated into a filter material (NanoCeram(TradeMark)), would attract electro-negative particles such as bacteria and viruses. The ability to detect and then remove viruses as well as bacteria is of concern in space cabins since they may be carried onboard by space crews. Moreover, an improved filter was desired that would polish the effluent from condensed moisture and wastewater, producing potable drinking water. A laboratory- size filter was developed that was capable of removing greater than 99.9999 percent of bacteria and virus. Such a removal was achieved at flow rates hundreds of times greater than those through ultraporous membranes that remove particles by sieving. Because the pore size of the new filter was rather large as compared to ultraporous membranes, it was found to be more resistant to clogging. Additionally, a full-size cartridge is being developed that is capable of serving a full space crew. During this ongoing effort, research demonstrated that the filter media was a very efficient adsorbent for DNA (deoxyribonucleic acid), RNA (ribonucleic acid), and endotoxins. Since the adsorption is based on the charge of the macromolecules, there is also a potential for separating proteins and other particulates on the basis of their charge differences. The separation of specific proteins is a major new thrust of biotechnology. The principal application of NanoCeram filters is based on their ability to remove viruses from water. The removal of more than 99.9999 percent of viruses was achieved by a NanoCeram polishing filter added to the effluent of an existing filtration device. NanoCeram is commercially available in laboratory-size filter discs and in the form of a syringe filter. The unique characteristic of the filter can be demonstrated by its ability to remove particulate dyes such as Metanyl yellow. Its

Adaptive estimation of a time-varying phase with coherent states: Smoothing can give an unbounded improvement over filtering

Science.gov (United States)

Laverick, Kiarn T.; Wiseman, Howard M.; Dinani, Hossein T.; Berry, Dominic W.

2018-04-01

The problem of measuring a time-varying phase, even when the statistics of the variation is known, is considerably harder than that of measuring a constant phase. In particular, the usual bounds on accuracy, such as the 1 /(4 n ¯) standard quantum limit with coherent states, do not apply. Here, by restricting to coherent states, we are able to analytically obtain the achievable accuracy, the equivalent of the standard quantum limit, for a wide class of phase variation. In particular, we consider the case where the phase has Gaussian statistics and a power-law spectrum equal to κp -1/|ω| p for large ω , for some p >1 . For coherent states with mean photon flux N , we give the quantum Cramér-Rao bound on the mean-square phase error as [psin(π /p ) ] -1(4N /κ ) -(p -1 )/p . Next, we consider whether the bound can be achieved by an adaptive homodyne measurement in the limit N /κ ≫1 , which allows the photocurrent to be linearized. Applying the optimal filtering for the resultant linear Gaussian system, we find the same scaling with N , but with a prefactor larger by a factor of p . By contrast, if we employ optimal smoothing we can exactly obtain the quantum Cramér-Rao bound. That is, contrary to previously considered (p =2 ) cases of phase estimation, here the improvement offered by smoothing over filtering is not limited to a factor of 2 but rather can be unbounded by a factor of p . We also study numerically the performance of these estimators for an adaptive measurement in the limit where N /κ is not large and find a more complicated picture.

Examination of quantitative accuracy of PIXE analysis for atmospheric aerosol particle samples. PIXE analysis of NIST air particulate on filter media

International Nuclear Information System (INIS)

Saitoh, Katsumi; Sera, Koichiro

2005-01-01

In order to confirm accuracy of the direct analysis of filter samples containing atmospheric aerosol particles collected on a polycarbonate membrane filter by PIXE, we carried out PIXE analysis on a National Institute of Standards and Technology (NIST, USA) air particulate on filter media (SRM 2783). For 16 elements with NIST certified values determined by PIXE analysis - Na, Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb - quantitative values were 80-110% relative to NIST certified values except for Na, Al, Si and Ni. Quantitative values of Na, Al and Si were 140-170% relative to NIST certified values, which were all high, and Ni was 64%. One possible reason why the quantitative values of Na, Al and Si were higher than the NIST certified values could be the difference in the X-ray spectrum analysis method used. (author)

Reservoir History Matching Using Ensemble Kalman Filters with Anamorphosis Transforms

KAUST Repository

Aman, Beshir M.

2012-01-01

Some History matching methods such as Kalman filter, particle filter and the ensemble Kalman filter are reviewed and applied to a test case in the reservoir application. The key idea is to apply the transformation before the update step

An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Kai Hu

2015-01-01

Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.

Application of the Engel, Kollat and Blackwell Model to Consumers of Automobile Insurance

OpenAIRE

Joseph C. Bonnice

1985-01-01

A significant stage of the analysis of consumer behavior was reached in the 1960s with the development of three models of consumer behavior in the following studies: Nicosia], Howard and Sheth, Engel Koolat, and Blackwell (EKB), all of which attempted to present a conceptual framework for the analysis of consumer behavior . This article focuses on the examination of these conceptual models of consumer behavior and the determination of whether these models accurately depict the behavior of con...

IIR Filter Modeling Using an Algorithm Inspired on Electromagnetism

Directory of Open Access Journals (Sweden)

Cuevas-Jiménez E.

2013-01-01

Full Text Available Infinite-impulse-response (IIR filtering provides a powerful approach for solving a variety of problems. However, its design represents a very complicated task, since the error surface of IIR filters is generally multimodal, global optimization techniques are required in order to avoid local minima. In this paper, a new method based on the Electromagnetism-Like Optimization Algorithm (EMO is proposed for IIR filter modeling. EMO originates from the electro-magnetism theory of physics by assuming potential solutions as electrically charged particles which spread around the solution space. The charge of each particle depends on its objective function value. This algorithm employs a collective attraction-repulsion mechanism to move the particles towards optimality. The experimental results confirm the high performance of the proposed method in solving various benchmark identification problems.

In-line Kevlar filters for microfiltration of transuranic-containing liquid streams.

Science.gov (United States)

Gonzales, G J; Beddingfield, D H; Lieberman, J L; Curtis, J M; Ficklin, A C

1992-06-01

The Department of Energy Rocky Flats Plant has numerous ongoing efforts to minimize the generation of residue and waste and to improve safety and health. Spent polypropylene liquid filters held for plutonium recovery, known as "residue," or as transuranic mixed waste contribute to storage capacity problems and create radiation safety and health considerations. An in-line process-liquid filter made of Kevlar polymer fiber has been evaluated for its potential to: (1) minimize filter residue, (2) recover economically viable quantities of plutonium, (3) minimize liquid storage tank and process-stream radioactivity, and (4) reduce potential personnel radiation exposure associated with these sources. Kevlar filters were rated to less than or equal to 1 mu nominal filtration and are capable of reducing undissolved plutonium particles to more than 10 times below the economic discard limit, however produced high back-pressures and are not yet acid resistant. Kevlar filters performed independent of loaded particles serving as a sieve. Polypropylene filters removed molybdenum particles at efficiencies equal to Kevlar filters only after loading molybdenum during recirculation events. Kevlars' high-efficiency microfiltration of process-liquid streams for the removal of actinides has the potential to reduce personnel radiation exposure by a factor of 6 or greater, while simultaneously achieving a reduction in the generation of filter residue and waste by a factor of 7. Insoluble plutonium may be recoverable from Kevlar filters by incineration.

Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics.

Directory of Open Access Journals (Sweden)

Wan Yang

2014-04-01

Full Text Available A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. These methods have found application in a range of disciplines and settings, including engineering design and forecasting, and, over the last two decades, have been applied to infectious disease epidemiology. For any system of interest, the ideal filter depends on the nonlinearity and complexity of the model to which it is applied, the quality and abundance of observations being entrained, and the ultimate application (e.g. forecast, parameter estimation, etc.. Here, we compare the performance of six state-of-the-art filter methods when used to model and forecast influenza activity. Three particle filters--a basic particle filter (PF with resampling and regularization, maximum likelihood estimation via iterated filtering (MIF, and particle Markov chain Monte Carlo (pMCMC--and three ensemble filters--the ensemble Kalman filter (EnKF, the ensemble adjustment Kalman filter (EAKF, and the rank histogram filter (RHF--were used in conjunction with a humidity-forced susceptible-infectious-recovered-susceptible (SIRS model and weekly estimates of influenza incidence. The modeling frameworks, first validated with synthetic influenza epidemic data, were then applied to fit and retrospectively forecast the historical incidence time series of seven influenza epidemics during 2003-2012, for 115 cities in the United States. Results suggest that when using the SIRS model the ensemble filters and the basic PF are more capable of faithfully recreating historical influenza incidence time series, while the MIF and pMCMC do not perform as well for multimodal outbreaks. For forecast of the week with the highest influenza activity, the accuracies of the six model-filter frameworks are comparable; the three particle filters perform slightly better predicting peaks 1-5 weeks in the future; the ensemble filters are more accurate predicting peaks in

Research and Application on Fractional-Order Darwinian PSO Based Adaptive Extended Kalman Filtering Algorithm

Directory of Open Access Journals (Sweden)

Qiguang Zhu

2014-05-01

Full Text Available To resolve the difficulty in establishing accurate priori noise model for the extended Kalman filtering algorithm, propose the fractional-order Darwinian particle swarm optimization (PSO algorithm has been proposed and introduced into the fuzzy adaptive extended Kalman filtering algorithm. The natural selection method has been adopted to improve the standard particle swarm optimization algorithm, which enhanced the diversity of particles and avoided the premature. In addition, the fractional calculus has been used to improve the evolution speed of particles. The PSO algorithm after improved has been applied to train fuzzy adaptive extended Kalman filter and achieve the simultaneous localization and mapping. The simulation results have shown that compared with the geese particle swarm optimization training of fuzzy adaptive extended Kalman filter localization and mapping algorithm, has been greatly improved in terms of localization and mapping.

Degradation of HEPA filters exposed to DMSO

International Nuclear Information System (INIS)

Bergman, W.; Wilson, K.; Larsen, G.; Lopez, R.; LeMay, J.

1994-01-01

Dimethyl sulfoxide (DMSO) sprays are being used to remove the high explosive (HE) from nuclear weapons in the process of their dismantlement. A boxed 50 cfm HEPA filter with an integral prefilter was exposed to DMSO vapor and aerosols that were generated by a spray nozzle to simulate conditions expected in the HE dissolution operation. After 198 hours of operation, the pressure drop of the filter had increased from 1.15 inches to 2.85 inches, and the efficiency for 0.3 μm dioctyl sebacate (DOS) aerosols decreased from 99.992% to 98.6%. Most of the DMSO aerosols had collected as a liquid pool inside the boxed HEPA. The liquid was blown out of the filter exit with 100 cfm air flow at the end of the test. Since the filter still met the minimum allowed efficiency of 99.97% after 166 hours of exposure, we recommend replacing the filter every 160 hours of operation or sooner if the pressure drop increases by 50%. Examination of the filter showed that visible cracks appeared at the joints of the wooden frame and a portion of the sealant had pulled away from the frame. Since all of the DMSO will be trapped in the first HEPA filter, the second HEPA filter should not suffer from DMSO degradation. Thus the combined efficiency for the first filter (98.6%) and the second filter (99.97%) is 99.99996% for 0.3μm particles. If the first filter is replaced prior to its degradation, each of the filters will have 99.97% efficiency, and the combined efficiency will be 99.999991%. The collection efficiency for DMSO/HE aerosols will be much higher because the particle size is much greater

Degradation of HEPA filters exposed to DMSO

Energy Technology Data Exchange (ETDEWEB)

Bergman, W.; Wilson, K.; Larsen, G. [Lawrence Livermore National Laboratory, CA (United States)] [and others

1995-02-01

Dimethyl sulfoxide (DMSO) sprays are being used to remove the high explosive (HE) from nuclear weapons in the process of their dismantlement. A boxed 50 cmf HEPA filter with an integral prefilter was exposed to DMSO vapor and aerosols that were generated by a spray nozzle to simulate conditions expected in the HE dissolution operation. After 198 hours of operation, the pressure drop of the filter had increased form 1.15 inches to 2,85 inches, and the efficiency for 0.3 {mu}m dioctyl sebacate (DOS) aerosols decreased form 99.992% to 98.6%. Most of the DMSO aerosols had collected as a liquid pool inside the boxed HEPA. The liquid was blown out of the filter exit with 100 cmf air flow at the end of the test. Since the filter still met the minimum allowed efficiency of 99.97% after 166 hours of exposure, we recommend replacing the filter every 160 hours of operation or sooner if the pressure drop increases by 50%. Examination of the filter showed that visible cracks appeared at the joints of the wooden frame and a portion of the sealant had pulled away from the frame. Since all of the DMSO will be trapped in the first HEPA filter, the second HEPA filter should not suffer from DMSO degradation. Thus the combined efficiency for the first filter (98.6%) and the second filter (99.97%) is 99.99996% for 0.3 {mu}m particles. If the first filter is replaced prior to its degradation, each of the filters will have 99.97% efficiency, and the combined efficiency will be 99.999991%. The collection efficiency for DMSO/HE aerosols will be much higher because the particle size is much greater.

Optical transmission through aerosol deposits on diffusely reflective filters: a method for measuring the absorbing component of aerosol particles

International Nuclear Information System (INIS)

Rosen, H.; Novakov, T.

1983-01-01

It is unclear why the backscattered radiation from nonabsorbing particles should not make a significant contribution to the optical attenuation measurement. This is especially true where the absorbing component represents only a very small fraction of the aerosol mass. In this Letter we present a simple theoretical model which accounts for all these observations and points out the critical role of the filter substrate as an almost perfect diffuse reflector in the technique

Gravimetric Measurements of Filtering Facepiece Respirators Challenged With Diesel Exhaust.

Science.gov (United States)

Satish, Swathi; Swanson, Jacob J; Xiao, Kai; Viner, Andrew S; Kittelson, David B; Pui, David Y H

2017-07-01

Elevated concentrations of diesel exhaust have been linked to adverse health effects. Filtering facepiece respirators (FFRs) are widely used as a form of respiratory protection against diesel particulate matter (DPM) in occupational settings. Previous results (Penconek A, Drążyk P, Moskal A. (2013) Penetration of diesel exhaust particles through commercially available dust half masks. Ann Occup Hyg; 57: 360-73.) have suggested that common FFRs are less efficient than would be expected for this purpose based on their certification approvals. The objective of this study was to measure the penetration of DPM through NIOSH-certified R95 and P95 electret respirators to verify this result. Gravimetric-based penetration measurements conducted using polytetrafluoroethylene (PTFE) and polypropylene (PP) filters were compared with penetration measurements made with a Scanning Mobility Particle Sizer (SMPS, TSI Inc.), which measures the particle size distribution. Gravimetric measurements using PP filters were variable compared to SMPS measurements and biased high due to adsorption of gas phase organic material. Relatively inert PTFE filters adsorbed less gas phase organic material resulting in measurements that were more accurate. To attempt to correct for artifacts associated with adsorption of gas phase organic material, primary and secondary filters were used in series upstream and downstream of the FFR. Correcting for adsorption by subtracting the secondary mass from the primary mass improved the result for both PTFE and PP filters but this correction is subject to 'equilibrium' conditions that depend on sampling time and the concentration of particles and gas phase hydrocarbons. Overall, the results demonstrate that the use of filters to determine filtration efficiency of FFRs challenged with diesel exhaust produces erroneous results due to the presence of gas phase hydrocarbons in diesel exhaust and the tendency of filters to adsorb organic material. Published by

Particle filter for the adsorption of radioactive impurities of a gas flow

International Nuclear Information System (INIS)

Bonn, J.W.

1978-01-01

The filter casing having several filter beds with e.g. activated carbon adsorbs iodine and methyl iodide from the off-gas of a safety room. The lid of the casing has numerous right-angled charging holes for the activated carbon filter beds which are closed during operation. The filter beds consist of perforated side walls opposite one another which form chambers for the activated carbon as well as limit the alternating gas inflow and outlet channels. Collector troughs for the used activated carbon are at the lower end of the filter beds; the former can be removed from the collector troughs by a suction blower without endangering the personal operating. (DG) [de

Results of Self-Absorption Study on the Versapor 3000 Filters for Radioactive Particulate Air Sampling

International Nuclear Information System (INIS)

Barnett, J.M.; Cullinan, Valerie I.; Barnett, Debra S.; Trang-Le, Truc LT; Bliss, Mary; Greenwood, Lawrence R.; Ballinger, Marcel Y.

2009-01-01

Since the mid-1980s, Pacific Northwest National Laboratory (PNNL) has used a value of 0.85 as the correction factor for self absorption of activity for particulate radioactive air samples collected from building exhaust for environmental monitoring. This value accounts for activity that cannot be detected by direct counting of alpha and beta particles. Emissions can be degraded or blocked by filter fibers for particles buried in the filter material or by inactive dust particles collected with the radioactive particles. These filters are used for monitoring air emissions from PNNL stacks for radioactive particles. This paper describes an effort to re-evaluate self-absorption effects in particulate radioactive air sample filters (Versapor(reg s ign) 3000, 47 mm diameter) used at PNNL. There were two methods used to characterize the samples. Sixty samples were selected from the archive for acid digestion to compare the radioactivity measured by direct gas-flow proportional counting of filters to the results obtained after acid digestion of the filter and counting again by gas-flow proportional detection. Thirty different sample filters were selected for visible light microscopy to evaluate filter loading and particulate characteristics. Mass-loading effects were also considered. Filter ratios were calculated by dividing the initial counts by the post-digestion counts with the expectation that post-digestion counts would be higher because digestion would expose radioactivity embedded in the filter in addition to that on top of the filter. Contrary to expectations, the post digestion readings were almost always lower than initial readings and averaged approximately half the initial readings for both alpha and beta activity. Before and after digestion readings appeared to be related to each other, but with a low coefficient of determination (R 2 ) value. The ratios had a wide range of values indicating that this method did not provide sufficient precision to quantify

Filter device for high density aerozol

International Nuclear Information System (INIS)

Karasawa, Hidetoshi; Endo, Masao; Utamura, Motoaki; Tozuka, Fumio; Tate, Hitoshi.

1991-01-01

In a reactor, filters for capturing aerozol particles at high concentration have such a structure that a great number of fine pores are formed. Aerozols are introduced to a filter portion from the place remote from a first inlet. Cloggings are caused successively from the places remote from the inlet. Even if the clogging should occur, since there are many pores, the performance of filters is not deteriorated. Further, the filter has a multi-layered structure. With such a constitution, if the filter at a first stage is clogged to increase the pressure, a partitioning plate is opened and fluids are introduced into a second filter. This is conducted successively to suppress the deterioration of the performance of the filter. In view of the above, even if cloggings should occur, the filter performance is not deteriorated and, accordingly, reactor container ventilation can be conducted at high reliability upon occurrence of accidents. (T.M.)

Prokaryotic communities in drinking water biofilters using alternative filter medium

DEFF Research Database (Denmark)

Breda, Inês Lousinha Ribeiro; Roslev, Peter; Ramsay, Loren

in an alternative filter medium during the start-up of manganese removal. Filter media properties were measured using gravimetric methods and a photometric particle analyzer. Physical, chemical and microbial analyses were used to follow the manganese ripening. Microbial analyses of both inlet water and filter...

Predicting mass loading as a function of pressure difference across prefilter/HEPA filter systems

International Nuclear Information System (INIS)

Novick, V.J.; Klassen, J.F.; Monson, P.R.

1992-01-01

The purpose of this work is to develop a methodology for predicting the mass loading and pressure drop effects on a prefilter/ HEPA filter system. The methodology relies on the use of empirical equations for the specific resistance of the aerosol loaded filter as a function of the particle diameter. These correlations relate the pressure difference across a filter to the mass loading on the filter and accounts for aerosol particle density effects. These predictions are necessary for the efficient design of new filtration systems and for risk assessment studies of existing filter systems. This work specifically addresses the prefilter/HEPA filter Airborne Activity Confinement Systems (AACS) at the Savannah River Plant. In order to determine the mass loading on the system, it is necessary to establish the efficiency characteristics for the prefilter, the mass loading characteristics of the prefilter measured as a function of pressure difference across the prefilter, and the mass loading characteristics of the HEPA filter as a function of pressure difference across the filter. Furthermore, the efficiency and mass loading characteristics need to be determined as a function of the aerosol particle diameter. A review of the literature revealed that no previous work had been performed to characterize the prefilter material of interest. In order to complete the foundation of information necessary to predict total mass loadings on prefilter/HEPA filter systems, it was necessary to determine the prefilter efficiency and mass loading characteristics. The measured prefilter characteristics combined with the previously determined HEPA filter characteristics allowed the resulting pressure difference across both filters to be predicted as a function of total particle mass for a given particle distribution. These predictions compare favorably to experimental measurements (±25%)

Water flow exchange characteristics in coarse granular filter media

DEFF Research Database (Denmark)

Andreasen, Rune Røjgaard; Pugliese, Lorenzo; Poulsen, Tjalfe

2013-01-01

Elution of inhibitory metabolites is a key parameter controlling the efficiency of air cleaning bio- and biotrickling filters. To the authors knowledge no studies have yet considered the relationship between specific surface area related elution velocity and physical media characteristics, which...... in this study are performed at a concurrent airflow of 0.3 m s−1, water irrigation rates of 1–21 cm h−1 in materials with particle diameters ranging from 2 to 14 mm to represent media and operation conditions relevant for low flow biotrickling filter design. Specific surface area related elution velocity...... distribution was closely related to the filter water content, water irrigation rate, media specific surface area and particle size distribution. A predictive model linking the specific surface area related elution velocity distribution to irrigation rate, specific surface area and particle size distribution...

Numerical simulation of Gaussian beam scattering by complex particles of arbitrary shape and structure

International Nuclear Information System (INIS)

Han, Y.P.; Cui, Z.W.; Gouesbet, G.

2012-01-01

An efficient numerical method based on the surface integral equations is introduced to simulate the scattering of Gaussian beam by complex particles that consist of an arbitrarily shaped host particle and multiple internal inclusions of arbitrary shape. In particular, the incident focused Gaussian beam is described by the Davis fifth-order approximate expressions in combination with rotation defined by Euler angles. The established surface integral equations are discretized with the method of moments, where the unknown equivalent electric and magnetic currents induced on the surfaces of the host particle and the internal inclusions are expanded using the Rao-Wilton-Glisson (RWG) basis functions. The resultant matrix equations are solved by using the parallel conjugate gradient method. The proposed numerical method is validated and its capability illustrated in several characteristic examples.

Filter aids influence on pressure drop across a filtration system

Science.gov (United States)

Hajar, S.; Rashid, M.; Nurnadia, A.; Ammar, M. R.; Hasfalina, C. M.

2017-06-01

Filter aids is commonly used to reduce pressure drop across air filtration system as it helps to increase the efficiency of filtration of accumulated filter cake. Filtration velocity is one of the main parameters that affect the performance of filter aids material. In this study, a formulated filter aids consisting of PreKot™ and activated carbon mixture (designated as PrekotAC) was tested on PTFE filter media under various filtration velocities of 5, 6, and 8 m/min at a constant material loading of 0.2 mg/mm2. Results showed that pressure drop is highly influenced by filtration velocity where higher filtration velocity leads to a higher pressure drop across the filter cake. It was found that PrekotAC performed better in terms of reducing the pressure drop across the filter cake even at the highest filtration velocity. The diversity in different particle size distribution of non-uniform particle size in the formulated PrekotAC mixture presents a higher permeability causes a lower pressure drop across the accumulated filter cake. The finding suggests that PrekotAC is a promising filter aids material that helps reducing the pressure drop across fabric filtration system.

Combination of ozone feed and wet electrostatic precipitator. Experimental study of an innovative system to filter gaseous iodine and iodine containing particles

International Nuclear Information System (INIS)

Gouëllo, Mélany; Hokkinen, Jouni; Kärkelä, Teemu; Auvinen, Ari

2017-01-01

Efficient mitigation systems capable of reducing as much as possible the radioactive discharge to the environment in a severe Nuclear Power Plant (NPP) accident are a necessity. Nuclear Power Plants are equipped with filtration systems which have been characterized for aerosol retention in a short term, but to a far lesser extent for the retention of volatile iodine or for the long-term behaviour of the system. After the Fukushima accident, one of the main concerns of the nuclear industry has been to verify the ability of filtration systems to mitigate the possible source term to the environment. Radiotoxic iodine has a significant contribution to a possible source term in a severe NPP accident. An innovative system has been developed at VTT Technical Research Centre of Finland Ltd. to filter gaseous iodine and iodine containing particles (e.g. I x O y ). The system consists of a combination of an ozone feed and a modern wet electrostatic precipitator (WESP). The electrostatic precipitation (ESP) technique is widely used in the industry to filter out impurities (i.e. particles) in gases. The advantage of a WESP is that the impurities are removed from the system with a solution. They can thus directly be transported to a water container, such as the sump in a nuclear power plant. The addition of ozone feed at the inlet of the WESP allows the oxidation of gaseous iodine into particles. The efficiency of the system for the filtration of gaseous molecular iodine and methyl iodine has been tested and the subsequent observations are further discussed in this paper. The results showed that the combination of WESP together with ozone feed results in a good filtering efficiency against molecular iodine under air atmosphere and air/steam atmosphere. (author)

Particle Filtering Equalization Method for a Satellite Communication Channel

Directory of Open Access Journals (Sweden)

Amblard Pierre-Olivier

2004-01-01

Full Text Available We propose the use of particle filtering techniques and Monte Carlo methods to tackle the in-line and blind equalization of a satellite communication channel. The main difficulties encountered are the nonlinear distortions caused by the amplifier stage in the satellite. Several processing methods manage to take into account these nonlinearities but they require the knowledge of a training input sequence for updating the equalizer parameters. Blind equalization methods also exist but they require a Volterra modelization of the system which is not suited for equalization purpose for the present model. The aim of the method proposed in the paper is also to blindly restore the emitted message. To reach this goal, a Bayesian point of view is adopted. Prior knowledge of the emitted symbols and of the nonlinear amplification model, as well as the information available from the received signal, is jointly used by considering the posterior distribution of the input sequence. Such a probability distribution is very difficult to study and thus motivates the implementation of Monte Carlo simulation methods. The presentation of the equalization method is cut into two parts. The first part solves the problem for a simplified model, focusing on the nonlinearities of the model. The second part deals with the complete model, using sampling approaches previously developed. The algorithms are illustrated and their performance is evaluated using bit error rate versus signal-to-noise ratio curves.

Further studies on the filtration of liquids using Kapton nuclear track micro filters

International Nuclear Information System (INIS)

Guo, S.L.; Ganz, M.; Fuest, M.; Vater, P.; Brandt, R.

1990-01-01

The flow rate of some liquids (water, heptane, toluene, xylene, dodecane) through Kapton nuclear track filters has been measured. The results can be interpreted with a modified Poiseuille formula. The influence of the viscosity of the liquids on their throughput through Kapton nuclear track filters has been determined. The purification of liquids with Kapton filters has been investigated. It is possible to measure the density of solid particles in deionized water by using Kapton filters. Consequently, nuclear track filters can remove solid particles from high-purity liquids. The soaking effect of some common liquid chemicals on Kapton filters has also been studied, no such soaking could be observed in most of the cases. Finally, these Kapton nuclear track filters are compared with a filter device from Hamamatsu (Japan). (orig.) [de

Fundamental study on recovery uranium oxide from HEPA filters

International Nuclear Information System (INIS)

Izumida, T.; Noguchi, Y.

1993-01-01

Large numbers of spent HEPA filters are produced at uranium fuel fabrication facilities. Uranium oxide particles have been collected on these filters. Then, a spent HEPA filter treatment system was developed from the viewpoint of recovering the UO 2 and minimizing the volume. The system consists of a mechanical separation process and a chemical dissolution process. This paper describes the results of fundamental experiments on recovering UO 2 from HEPA filters

Recleaning of HEPA filters by reverse flow - evaluation of the underlying processes and the cleaning technique

International Nuclear Information System (INIS)

Leibold, H.; Leiber, T.; Doeffert, I.; Wilhelm, J.G.

1993-08-01

HEPA filter operation at high concentrations of fine dusts requires the periodic recleaning of the filter units in their service locations. Due to the low mechanical stress induced during the recleaning process the regenration via low pressure reverse flow is a very suitable technique. Recleanability of HEPA filter had been attained for particle diameter >0,4 μm at air velocities up to 1 m/s, but filter clogging occurred in case of smaller particles. The recleaning forces are too weak for particles [de

Cost/benefit evaluation of electrofibrous air filters

International Nuclear Information System (INIS)

Bergman, W.; Kuhl, W.; Biermann, A.; Lum, B.

1986-01-01

Experimental electric air filters based on the principle of superimposing an electric field over conventional fibrous air filters have been developed. The different experimental electric filters described in this report include prefilters for use in glove boxes and in ventilation systems, re-circulating air filters, electric HEPA filters, and high efficiency, high temperature air filters. In each case the large improvement in filter efficiency that occurs when a mechanical filter is electrified is demonstrated. Also a significant increase in the particle loading capacity of filters in many of our evaluations is demonstrated. Both laboratory and field test results are presented. This paper also demonstrates that the performance of all of our electric filter designs, except one, can be matched by conventional mechanical air filters and usually at a lower cost. The one exception is the high temperature, high efficiency electric air filter. In that case there is no mechanical filter media that can match the performance of the electric air filter. Our findings show that electric air filters are only cost effective compared to mechanical air filters when the performance of the mechanical air filter cannot be further improved by mechanical means. (author)

On a multiscale approach for filter efficiency simulations

KAUST Repository

Iliev, Oleg; Lakdawala, Zahra; Printsypar, Galina

2014-01-01

geometry) of the filtering medium and on the diameter distribution of the particles. The deposited (captured) particles change the microstructure of the porous media what leads to change of permeability. The changed permeability directly influences

Effect of Drive Cycle and Gasoline Particulate Filter on the Size and Morphology of Soot Particles Emitted from a Gasoline-Direct-Injection Vehicle.

Science.gov (United States)

Saffaripour, Meghdad; Chan, Tak W; Liu, Fengshan; Thomson, Kevin A; Smallwood, Gregory J; Kubsh, Joseph; Brezny, Rasto

2015-10-06

The size and morphology of particulate matter emitted from a light-duty gasoline-direct-injection (GDI) vehicle, over the FTP-75 and US06 transient drive cycles, have been characterized by transmission-electron-microscope (TEM) image analysis. To investigate the impact of gasoline particulate filters on particulate-matter emission, the results for the stock-GDI vehicle, that is, the vehicle in its original configuration, have been compared to the results for the same vehicle equipped with a catalyzed gasoline particulate filter (GPF). The stock-GDI vehicle emits graphitized fractal-like aggregates over all driving conditions. The mean projected area-equivalent diameter of these aggregates is in the 78.4-88.4 nm range and the mean diameter of primary particles varies between 24.6 and 26.6 nm. Post-GPF particles emitted over the US06 cycle appear to have an amorphous structure, and a large number of nucleation-mode particles, depicted as low-contrast ultrafine droplets, are observed in TEM images. This indicates the emission of a substantial amount of semivolatile material during the US06 cycle, most likely generated by the incomplete combustion of accumulated soot in the GPF during regeneration. The size of primary particles and soot aggregates does not vary significantly by implementing the GPF over the FTP-75 cycle; however, particles emitted by the GPF-equipped vehicle over the US06 cycle are about 20% larger than those emitted by the stock-GDI vehicle. This may be attributed to condensation of large amounts of organic material on soot aggregates. High-contrast spots, most likely solid nonvolatile cores, are observed within many of the nucleation-mode particles emitted over the US06 cycle by the GPF-equipped vehicle. These cores are either generated inside the engine or depict incipient soot particles which are partially carbonized in the exhaust line. The effect of drive cycle and the GPF on the fractal parameters of particles, such as fractal dimension and

Filtration device for rapid separation of biological particles from complex matrices

Science.gov (United States)

Kim, Sangil; Naraghi-Arani, Pejman; Liou, Megan

2018-01-09

Methods and systems for filtering of biological particles are disclosed. Filtering membranes separate adjacent chambers. Through osmotic or electrokinetic processes, flow of particles is carried out through the filtering membranes. Cells, viruses and cell waste can be filtered depending on the size of the pores of the membrane. A polymer brush can be applied to a surface of the membrane to enhance filtering and prevent fouling.

IMPLICIT DUAL CONTROL BASED ON PARTICLE FILTERING AND FORWARD DYNAMIC PROGRAMMING.

Science.gov (United States)

Bayard, David S; Schumitzky, Alan

2010-03-01

This paper develops a sampling-based approach to implicit dual control. Implicit dual control methods synthesize stochastic control policies by systematically approximating the stochastic dynamic programming equations of Bellman, in contrast to explicit dual control methods that artificially induce probing into the control law by modifying the cost function to include a term that rewards learning. The proposed implicit dual control approach is novel in that it combines a particle filter with a policy-iteration method for forward dynamic programming. The integration of the two methods provides a complete sampling-based approach to the problem. Implementation of the approach is simplified by making use of a specific architecture denoted as an H-block. Practical suggestions are given for reducing computational loads within the H-block for real-time applications. As an example, the method is applied to the control of a stochastic pendulum model having unknown mass, length, initial position and velocity, and unknown sign of its dc gain. Simulation results indicate that active controllers based on the described method can systematically improve closed-loop performance with respect to other more common stochastic control approaches.

Numerical study of particle filtration in an induction crucible furnace

International Nuclear Information System (INIS)

Asad, Amjad; Kratzsch, Christoph; Dudczig, Steffen; Aneziris, Christos G.; Schwarze, Rüdiger

2016-01-01

Highlights: • Removing particles from a melt in an induction furnace by using a filter is introduced. • The effect of filter and its permeability on the melt flow is shown. • The impact of filter permeability and particle diameter on filter efficiency is studied. • The filter efficiency depends on filter position and number of the used filter. - Abstract: The present paper deals with a numerical investigation of the turbulent melt flow driven by the electromagnetic force in an induction furnace. The main scope of the paper is to present a new principle to remove non-metallic particles from steel melt in an induction furnace by immersing a porous filter in the melt. The magnetic field acting on the melt is calculated by using the open source software MaxFEM"®, while the turbulent flow is simulated by means of the open source computational fluid dynamics library OpenFOAM"®. The validation of the numerical model is accomplished by using experimental results for the flow without the immersed filter. Here it is shown that the time-averaged flow, obtained numerically is in a good quantitive agreement with the experimental data. Then, the validated numerical model is employed to simulate the melt flow with the immersed filter in the induction furnace of a new type of real steel casting simulator investigated at Technische Universität Bergakademie Freiberg. The considerable effect of the filter on the flow pattern is indicated in the present work. Moreover, it is shown that the filter permeability and its position have a significant influence on the melt flow in the induction furnace. Additionally, particles are injected in the flow domain and tracked by using Lagrangian framework. In this case, the efficiency of the used filter is determined in the present investigation depending on its permeability, its position and the particles diameter.

Comparison of the structure and composition of the branchial filters in suspension feeding elasmobranchs.

Science.gov (United States)

Misty Paig-Tran, E W; Summers, A P

2014-04-01

The four, evolutionarily independent, lineages of suspension feeding elasmobranchs have two types of branchial filters. The first is a robust, flattened filter pad akin to a colander (e.g., whale sharks, mantas and devil rays) while the second more closely resembles the comb-like gill raker structure found in bony fishes (e.g., basking and megamouth sharks). The structure and the presence of mucus on the filter elements will determine the mechanical function of the filter and subsequent particle transport. Using histology and scanning electron microscopy, we investigated the anatomy of the branchial filters in 12 of the 14 species of Chondrichthyian filter-feeding fishes. We hypothesized that mucus producing cells would be abundant along the filter epithelium and perform as a sticky mechanism to retain and transport particles; however, we found that only three species had mucus producing goblet cells. Two of these (Mobula kuhlii and Mobula tarapacana) also had branchial cilia, indicating sticky retention and transport. The remaining filter-feeding elasmobranchs did not have a sticky surface along the filter for particles to collect and instead must employ alternative mechanisms of filtration (e.g., direct sieving, inertial impaction or cross-flow). With the exception of basking sharks, the branchial filter is composed of a hyaline cartilage skeleton surrounded by a layer of highly organized connective tissue that may function as a support. Megamouth sharks and most of the mobulid rays have denticles along the surface of the filter, presumably to protect against damage from large particle impactions. Basking sharks have branchial filters that lack a cartilaginous core; instead they are composed entirely of smooth keratin. Copyright © 2014 Wiley Periodicals, Inc.

Human tracking in thermal images using adaptive particle filters with online random forest learning

Science.gov (United States)

Ko, Byoung Chul; Kwak, Joon-Young; Nam, Jae-Yeal

2013-11-01

This paper presents a fast and robust human tracking method to use in a moving long-wave infrared thermal camera under poor illumination with the existence of shadows and cluttered backgrounds. To improve the human tracking performance while minimizing the computation time, this study proposes an online learning of classifiers based on particle filters and combination of a local intensity distribution (LID) with oriented center-symmetric local binary patterns (OCS-LBP). Specifically, we design a real-time random forest (RF), which is the ensemble of decision trees for confidence estimation, and confidences of the RF are converted into a likelihood function of the target state. First, the target model is selected by the user and particles are sampled. Then, RFs are generated using the positive and negative examples with LID and OCS-LBP features by online learning. The learned RF classifiers are used to detect the most likely target position in the subsequent frame in the next stage. Then, the RFs are learned again by means of fast retraining with the tracked object and background appearance in the new frame. The proposed algorithm is successfully applied to various thermal videos as tests and its tracking performance is better than those of other methods.

Assessing clustering strategies for Gaussian mixture filtering a subsurface contaminant model

KAUST Repository

Liu, Bo

2016-02-03

An ensemble-based Gaussian mixture (GM) filtering framework is studied in this paper in term of its dependence on the choice of the clustering method to construct the GM. In this approach, a number of particles sampled from the posterior distribution are first integrated forward with the dynamical model for forecasting. A GM representation of the forecast distribution is then constructed from the forecast particles. Once an observation becomes available, the forecast GM is updated according to Bayes’ rule. This leads to (i) a Kalman filter-like update of the particles, and (ii) a Particle filter-like update of their weights, generalizing the ensemble Kalman filter update to non-Gaussian distributions. We focus on investigating the impact of the clustering strategy on the behavior of the filter. Three different clustering methods for constructing the prior GM are considered: (i) a standard kernel density estimation, (ii) clustering with a specified mixture component size, and (iii) adaptive clustering (with a variable GM size). Numerical experiments are performed using a two-dimensional reactive contaminant transport model in which the contaminant concentration and the heterogenous hydraulic conductivity fields are estimated within a confined aquifer using solute concentration data. The experimental results suggest that the performance of the GM filter is sensitive to the choice of the GM model. In particular, increasing the size of the GM does not necessarily result in improved performances. In this respect, the best results are obtained with the proposed adaptive clustering scheme.

Filter Feeding, Chaotic Filtration, and a Blinking Stokeslet

Science.gov (United States)

Blake, J. R.; Otto, S. R.; Blake, D. A.