Method for determining aerosol particle size device for determining aerosol particle size

DOEpatents

Novick, Vincent J.

1998-01-01

A method for determining the mass median diameter D of particles contained in a fluid is provided wherein the data of the mass of a pre-exposed and then a post-exposed filter is mathematically combined with data concerning the pressure differential across the same filter before and then after exposure to a particle-laden stream. A device for measuring particle size is also provided wherein the device utilizes the above-method for mathematically combining the easily quantifiable data.

Method for determining aerosol particle size, device for determining aerosol particle size

DOEpatents

Novick, V.J.

1998-10-06

A method for determining the mass median diameter D of particles contained in a fluid is provided wherein the data of the mass of a pre-exposed and then a post-exposed filter is mathematically combined with data concerning the pressure differential across the same filter before and then after exposure to a particle-laden stream. A device for measuring particle size is also provided wherein the device utilizes the above-method for mathematically combining the easily quantifiable data. 2 figs.

Assessment of exhaust emissions from carbon nanotube production and particle collection by sampling filters.

PubMed

Tsai, Candace Su-Jung; Hofmann, Mario; Hallock, Marilyn; Ellenbecker, Michael; Kong, Jing

2015-11-01

This study performed a workplace evaluation of emission control using available air sampling filters and characterized the emitted particles captured in filters. Characterized particles were contained in the exhaust gas released from carbon nanotube (CNT) synthesis using chemical vapor deposition (CVD). Emitted nanoparticles were collected on grids to be analyzed using transmission electron microscopy (TEM). CNT clusters in the exhaust gas were collected on filters for investigation. Three types of filters, including Nalgene surfactant-free cellulose acetate (SFCA), Pall A/E glass fiber, and Whatman QMA quartz filters, were evaluated as emission control measures, and particles deposited in the filters were characterized using scanning transmission electron microscopy (STEM) to further understand the nature of particles emitted from this CNT production. STEM analysis for collected particles on filters found that particles deposited on filter fibers had a similar morphology on all three filters, that is, hydrophobic agglomerates forming circular beaded clusters on hydrophilic filter fibers on the collecting side of the filter. CNT agglomerates were found trapped underneath the filter surface. The particle agglomerates consisted mostly of elemental carbon regardless of the shapes. Most particles were trapped in filters and no particles were found in the exhaust downstream from A/E and quartz filters, while a few nanometer-sized and submicrometer-sized individual particles and filament agglomerates were found downstream from the SFCA filter. The number concentration of particles with diameters from 5 nm to 20 µm was measured while collecting particles on grids at the exhaust piping. Total number concentration was reduced from an average of 88,500 to 700 particle/cm(3) for the lowest found for all filters used. Overall, the quartz filter showed the most consistent and highest particle reduction control, and exhaust particles containing nanotubes were successfully collected and trapped inside this filter. As concern for the toxicity of engineered nanoparticles grows, there is a need to characterize emission from carbon nanotube synthesis processes and to investigate methods to prevent their environmental release. At this time, the particles emitted from synthesis were not well characterized when collected on filters, and limited information was available about filter performance to such emission. This field study used readily available sampling filters to collect nanoparticles from the exhaust gas of a carbon nanotube furnace. New agglomerates were found on filters from such emitted particles, and the performance of using the filters studied was encouraging in terms of capturing emissions from carbon nanotube synthesis.

Resolving occlusion and segmentation errors in multiple video object tracking

NASA Astrophysics Data System (ADS)

Cheng, Hsu-Yung; Hwang, Jenq-Neng

2009-02-01

In this work, we propose a method to integrate the Kalman filter and adaptive particle sampling for multiple video object tracking. The proposed framework is able to detect occlusion and segmentation error cases and perform adaptive particle sampling for accurate measurement selection. Compared with traditional particle filter based tracking methods, the proposed method generates particles only when necessary. With the concept of adaptive particle sampling, we can avoid degeneracy problem because the sampling position and range are dynamically determined by parameters that are updated by Kalman filters. There is no need to spend time on processing particles with very small weights. The adaptive appearance for the occluded object refers to the prediction results of Kalman filters to determine the region that should be updated and avoids the problem of using inadequate information to update the appearance under occlusion cases. The experimental results have shown that a small number of particles are sufficient to achieve high positioning and scaling accuracy. Also, the employment of adaptive appearance substantially improves the positioning and scaling accuracy on the tracking results.

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

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

Viswanathan, Sandeep; Rothamer, David; Zelenyuk, Alla

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 obtainmore » 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 process. Particle mobility diameter and trapped mass within the filter appeared to be the dominant parameters that impacted filter performance.« less

Are consistent equal-weight particle filters possible?

NASA Astrophysics Data System (ADS)

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.

Tracking and people counting using Particle Filter Method

NASA Astrophysics Data System (ADS)

Sulistyaningrum, D. R.; Setiyono, B.; Rizky, M. S.

2018-03-01

In recent years, technology has developed quite rapidly, especially in the field of object tracking. Moreover, if the object under study is a person and the number of people a lot. The purpose of this research is to apply Particle Filter method for tracking and counting people in certain area. Tracking people will be rather difficult if there are some obstacles, one of which is occlusion. The stages of tracking and people counting scheme in this study include pre-processing, segmentation using Gaussian Mixture Model (GMM), tracking using particle filter, and counting based on centroid. The Particle Filter method uses the estimated motion included in the model used. The test results show that the tracking and people counting can be done well with an average accuracy of 89.33% and 77.33% respectively from six videos test data. In the process of tracking people, the results are good if there is partial occlusion and no occlusion

New color-based tracking algorithm for joints of the upper extremities

NASA Astrophysics Data System (ADS)

Wu, Xiangping; Chow, Daniel H. K.; Zheng, Xiaoxiang

2007-11-01

To track the joints of the upper limb of stroke sufferers for rehabilitation assessment, a new tracking algorithm which utilizes a developed color-based particle filter and a novel strategy for handling occlusions is proposed in this paper. Objects are represented by their color histogram models and particle filter is introduced to track the objects within a probability framework. Kalman filter, as a local optimizer, is integrated into the sampling stage of the particle filter that steers samples to a region with high likelihood and therefore fewer samples is required. A color clustering method and anatomic constraints are used in dealing with occlusion problem. Compared with the general basic particle filtering method, the experimental results show that the new algorithm has reduced the number of samples and hence the computational consumption, and has achieved better abilities of handling complete occlusion over a few frames.

Propagating probability distributions of stand variables using sequential Monte Carlo methods

Treesearch

Jeffrey H. Gove

2009-01-01

A general probabilistic approach to stand yield estimation is developed based on sequential Monte Carlo filters, also known as particle filters. The essential steps in the development of the sampling importance resampling (SIR) particle filter are presented. The SIR filter is then applied to simulated and observed data showing how the 'predictor - corrector'...

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

NASA Astrophysics Data System (ADS)

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.

An Integrated Approach for Gear Health Prognostics

NASA Technical Reports Server (NTRS)

He, David; Bechhoefer, Eric; Dempsey, Paula; Ma, Jinghua

2012-01-01

In this paper, an integrated approach for gear health prognostics using particle filters is presented. The presented method effectively addresses the issues in applying particle filters to gear health prognostics by integrating several new components into a particle filter: (1) data mining based techniques to effectively define the degradation state transition and measurement functions using a one-dimensional health index obtained by whitening transform; (2) an unbiased l-step ahead RUL estimator updated with measurement errors. The feasibility of the presented prognostics method is validated using data from a spiral bevel gear case study.

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

PubMed Central

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

Visual Tracking Using 3D Data and Region-Based Active Contours

DTIC Science & Technology

2016-09-28

adaptive control strategies which explicitly take uncertainty into account. Filtering methods ranging from the classical Kalman filters valid for...linear systems to the much more general particle filters also fit into this framework in a very natural manner. In particular, the particle filtering ...the number of samples required for accurate filtering increases with the dimension of the system noise. In our approach, we approximate curve

Advanced Filter Technology For Nuclear Thermal Propulsion

NASA Technical Reports Server (NTRS)

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.

Multi-Target State Extraction for the SMC-PHD Filter

PubMed Central

Si, Weijian; Wang, Liwei; Qu, Zhiyu

2016-01-01

The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been demonstrated to be a favorable method for multi-target tracking. However, the time-varying target states need to be extracted from the particle approximation of the posterior PHD, which is difficult to implement due to the unknown relations between the large amount of particles and the PHD peaks representing potential target locations. To address this problem, a novel multi-target state extraction algorithm is proposed in this paper. By exploiting the information of measurements and particle likelihoods in the filtering stage, we propose a validation mechanism which aims at selecting effective measurements and particles corresponding to detected targets. Subsequently, the state estimates of the detected and undetected targets are performed separately: the former are obtained from the particle clusters directed by effective measurements, while the latter are obtained from the particles corresponding to undetected targets via clustering method. Simulation results demonstrate that the proposed method yields better estimation accuracy and reliability compared to existing methods. PMID:27322274

Particle Filtering Methods for Incorporating Intelligence Updates

DTIC Science & Technology

2017-03-01

methodology for incorporating intelligence updates into a stochastic model for target tracking. Due to the non -parametric assumptions of the PF...samples are taken with replacement from the remaining non -zero weighted particles at each iteration. With this methodology , a zero-weighted particle is...incorporation of information updates. A common method for incorporating information updates is Kalman filtering. However, given the probable nonlinear and non

Rotational response of suspended particles to turbulent flow: laboratory and numerical synthesis

NASA Astrophysics Data System (ADS)

Variano, Evan; Zhao, Lihao; Byron, Margaret; Bellani, Gabriele; Tao, Yiheng; Andersson, Helge

2014-11-01

Using laboratory and DNS measurements, we consider how aspherical and inertial particles suspended in a turbulent flow act to ``filter'' the fluid-phase vorticity. We use three approaches to predict the magnitude and structure of this filter. The first approach is based on Buckingham's Pi theorem, which shows a clear result for the relationship between filter strength and particle aspect ratio. Results are less clear for the dependence of filter strength on Stokes number; we briefly discuss some issues in the proper definition of Stokes number for use in this context. The second approach to predicting filter strength is based on a consideration of vorticity and enstrophy spectra in the fluid phase. This method has a useful feature: it can be used to predict the filter a priori, without need for measurements as input. We compare the results of this approach to measurements as a method of validation. The third and final approach to predicting filter strength is from the consideration of torques experienced by particles, and how the ``angular slip'' or ``spin slip'' evolves in an unsteady flow. We show results from our DNS that indicate different flow conditions in which the spin slip is more or less important in setting the particle rotation dynamics. Collaboration made possible by the Peder Sather Center.

Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics

PubMed Central

Yang, Wan; Karspeck, Alicia; Shaman, Jeffrey

2014-01-01

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 the past. PMID:24762780

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

NASA Astrophysics Data System (ADS)

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.

Method of concurrently filtering particles and collecting gases

DOEpatents

Mitchell, Mark A; Meike, Annemarie; Anderson, Brian L

2015-04-28

A system for concurrently filtering particles and collecting gases. Materials are be added (e.g., via coating the ceramic substrate, use of loose powder(s), or other means) to a HEPA filter (ceramic, metal, or otherwise) to collect gases (e.g., radioactive gases such as iodine). The gases could be radioactive, hazardous, or valuable gases.

Smoothed particle hydrodynamics method from a large eddy simulation perspective

NASA Astrophysics Data System (ADS)

Di Mascio, A.; Antuono, M.; Colagrossi, A.; Marrone, S.

2017-03-01

The Smoothed Particle Hydrodynamics (SPH) method, often used for the modelling of the Navier-Stokes equations by a meshless Lagrangian approach, is revisited from the point of view of Large Eddy Simulation (LES). To this aim, the LES filtering procedure is recast in a Lagrangian framework by defining a filter that moves with the positions of the fluid particles at the filtered velocity. It is shown that the SPH smoothing procedure can be reinterpreted as a sort of LES Lagrangian filtering, and that, besides the terms coming from the LES convolution, additional contributions (never accounted for in the SPH literature) appear in the equations when formulated in a filtered fashion. Appropriate closure formulas are derived for the additional terms and a preliminary numerical test is provided to show the main features of the proposed LES-SPH model.

Particle emissions from diesel passenger cars equipped with a particle trap in comparison to other technologies.

PubMed

Mohr, Martin; Forss, Anna-Maria; Lehmann, Urs

2006-04-01

Tail pipe particle emissions of passenger cars, with different engine and aftertreatment technologies, were determined with special focus on diesel engines equipped with a particle filter. The particle number measurements were performed, during transient tests, using a condensation particle counter. The measurement procedure complied with the draft Swiss ordinance, which is based on the findings of the UN/ECE particulate measurement program. In addition, particle mass emissions were measured by the legislated and a modified filter method. The results demonstrate the high efficiency of diesel particle filters (DPFs) in curtailing nonvolatile particle emissions over the entire size range. Higher emissions were observed during short periods of DPF regeneration and immediately afterward, when a soot cake has not yet formed on the filter surface. The gasoline vehicles exhibited higher emissions than the DPF equipped diesel vehicles but with a large variation depending on the technology and driving conditions. Although particle measurements were carried out during DPF regeneration, it was impossible to quantify their contribution to the overall emissions, due to the wide variation in intensity and frequency of regeneration. The numbers counting method demonstrated its clear superiority in sensitivity to the mass measurement. The results strongly suggest the application of the particle number counting to quantify future low tailpipe emissions.

SU-F-J-200: An Improved Method for Event Selection in Compton Camera Imaging for Particle Therapy

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

Mackin, D; Beddar, S; Polf, J

2016-06-15

Purpose: The uncertainty in the beam range in particle therapy limits the conformality of the dose distributions. Compton scatter cameras (CC), which measure the prompt gamma rays produced by nuclear interactions in the patient tissue, can reduce this uncertainty by producing 3D images confirming the particle beam range and dose delivery. However, the high intensity and short time windows of the particle beams limit the number of gammas detected. We attempt to address this problem by developing a method for filtering gamma ray scattering events from the background by applying the known gamma ray spectrum. Methods: We used a 4more » stage Compton camera to record in list mode the energy deposition and scatter positions of gammas from a Co-60 source. Each CC stage contained a 4×4 array of CdZnTe crystal. To produce images, we used a back-projection algorithm and four filtering Methods: basic, energy windowing, delta energy (ΔE), or delta scattering angle (Δθ). Basic filtering requires events to be physically consistent. Energy windowing requires event energy to fall within a defined range. ΔE filtering selects events with the minimum difference between the measured and a known gamma energy (1.17 and 1.33 MeV for Co-60). Δθ filtering selects events with the minimum difference between the measured scattering angle and the angle corresponding to a known gamma energy. Results: Energy window filtering reduced the FWHM from 197.8 mm for basic filtering to 78.3 mm. ΔE and Δθ filtering achieved the best results, FWHMs of 64.3 and 55.6 mm, respectively. In general, Δθ filtering selected events with scattering angles < 40°, while ΔE filtering selected events with angles > 60°. Conclusion: Filtering CC events improved the quality and resolution of the corresponding images. ΔE and Δθ filtering produced similar results but each favored different events.« less

A Sequential Ensemble Prediction System at Convection Permitting Scales

NASA Astrophysics Data System (ADS)

Milan, M.; Simmer, C.

2012-04-01

A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.

Ultrasonic tracking of shear waves using a particle filter

PubMed Central

Ingle, Atul N.; Ma, Chi; Varghese, Tomy

2015-01-01

Purpose: This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Methods: Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Results: Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. Conclusions: The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques. PMID:26520761

Efficiency of automotive cabin air filters to reduce acute health effects of diesel exhaust in human subjects

PubMed Central

Rudell, B.; Wass, U.; Horstedt, P.; Levin, J. O.; Lindahl, R.; Rannug, U.; Sunesson, A. L.; Ostberg, Y.; Sandstrom, T.

1999-01-01

OBJECTIVES: To evaluate the efficiency of different automotive cabin air filters to prevent penetration of components of diesel exhaust and thereby reduce biomedical effects in human subjects. Filtered air and unfiltered diluted diesel exhaust (DDE) were used as negative and positive controls, respectively, and were compared with exposure to DDE filtered with four different filter systems. METHODS: 32 Healthy non- smoking subjects (age 21-53) participated in the study. Each subject was exposed six times for 1 hour in a specially designed exposure chamber: once to air, once to unfiltered DDE, and once to DDE filtered with the four different cabin air filters. Particle concentrations during exposure to unfiltered DDE were kept at 300 micrograms/m3. Two of the filters were particle filters. The other two were particle filters combined with active charcoal filters that might reduce certain gaseous components. Subjective symptoms were recorded and nasal airway lavage (NAL), acoustic rhinometry, and lung function measurements were performed. RESULTS: The two particle filters decreased the concentrations of diesel exhaust particles by about half, but did not reduce the intensity of symptoms induced by exhaust. The combination of active charcoal filters and a particle filter significantly reduced the symptoms and discomfort caused by the diesel exhaust. The most noticable differences in efficacy between the filters were found in the reduction of detection of an unpleasant smell from the diesel exhaust. In this respect even the two charcoal filter combinations differed significantly. The efficacy to reduce symptoms may depend on the abilities of the filters investigated to reduce certain hydrocarbons. No acute effects on NAL, rhinometry, and lung function variables were found. CONCLUSIONS: This study has shown that the use of active charcoal filters, and a particle filter, clearly reduced the intensity of symptoms induced by diesel exhaust. Complementary studies on vehicle cabin air filters may result in further diminishing the biomedical effects of diesel exhaust in subjects exposed in traffic and workplaces.   PMID:10450238

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

PubMed Central

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-01-01

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. PMID:27294931

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

PubMed

Zhang, Zutao; Li, Yanjun; Wang, Fubing; Meng, Guanjun; Salman, Waleed; Saleem, Layth; Zhang, Xiaoliang; Wang, Chunbai; Hu, Guangdi; Liu, Yugang

2016-06-09

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.

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

PubMed

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 algorithm had the lowest MSEPWRD for all noise types at low input SNRs. Therefore, the morphology and diagnostic information of ECG signals were much better conserved compared with EKF/EKS frameworks, especially in non-Gaussian nonstationary situations.

Fabrication of a multi-walled carbon nanotube-deposited glass fiber air filter for the enhancement of nano and submicron aerosol particle filtration and additional antibacterial efficacy.

PubMed

Park, Jae Hong; Yoon, Ki Young; Na, Hyungjoo; Kim, Yang Seon; Hwang, Jungho; Kim, Jongbaeg; Yoon, Young Hun

2011-09-01

We grew multi-walled carbon nanotubes (MWCNTs) on a glass fiber air filter using thermal chemical vapor deposition (CVD) after the filter was catalytically activated with a spark discharge. After the CNT deposition, filtration and antibacterial tests were performed with the filters. Potassium chloride (KCl) particles (<1 μm) were used as the test aerosol particles, and their number concentration was measured using a scanning mobility particle sizer. Antibacterial tests were performed using the colony counting method, and Escherichia coli (E. coli) was used as the test bacteria. The results showed that the CNT deposition increased the filtration efficiency of nano and submicron-sized particles, but did not increase the pressure drop across the filter. When a pristine glass fiber filter that had no CNTs was used, the particle filtration efficiencies at particle sizes under 30 nm and near 500 nm were 48.5% and 46.8%, respectively. However, the efficiencies increased to 64.3% and 60.2%, respectively, when the CNT-deposited filter was used. The reduction in the number of viable cells was determined by counting the colony forming units (CFU) of each test filter after contact with the cells. The pristine glass fiber filter was used as a control, and 83.7% of the E. coli were inactivated on the CNT-deposited filter. Copyright © 2011 Elsevier B.V. All rights reserved.

Sub-micron particle sampler apparatus and method for sampling sub-micron particles

DOEpatents

Gay, D.D.; McMillan, W.G.

1984-04-12

Apparatus and method steps for collecting sub-micron sized particles include a collection chamber and cryogenic cooling. The cooling is accomplished by coil tubing carrying nitrogen in liquid form, with the liquid nitrogen changing to the gas phase before exiting from the collection chamber in the tubing. Standard filters are used to filter out particles of diameter greater than or equal to 0.3 microns; however, the present invention is used to trap particles of less than 0.3 micron in diameter. A blower draws air to said collection chamber through a filter which filters particles with diameters greater than or equal to 0.3 micron. The air is then cryogenically cooled so that moisture and sub-micron sized particles in the air condense into ice on the coil. The coil is then heated so that the ice melts, and the liquid is then drawn off and passed through a Buchner funnel where the liquid is passed through a Nuclepore membrane. A vacuum draws the liquid through the Nuclepore membrane, with the Nuclepore membrane trapping sub-micron sized particles therein. The Nuclepore membrane is then covered on its top and bottom surfaces with sheets of Mylar and the assembly is then crushed into a pellet. This effectively traps the sub-micron sized particles for later analysis. 6 figures.

Kalman and particle filtering methods for full vehicle and tyre identification

NASA Astrophysics Data System (ADS)

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.

Filter quality of electret masks in filtering 14.6–594 nm aerosol particles: Effects of five decontamination methods

PubMed Central

Lin, Tzu-Hsien; Chen, Chih-Chieh; Kuo, Chung-Wen

2017-01-01

This study investigates the effects of five decontamination methods on the filter quality (qf) of three commercially available electret masks—N95, Gauze and Spunlace nonwoven masks. Newly developed evaluation methods, the overall filter quality (qf,o) and the qf ratio were applied to evaluate the effectiveness of decontamination methods for respirators. A scanning mobility particle sizer is utilized to measure the concentration of polydispersed particles with diameter 14.6–594 nm. The penetration of particles and pressure drop (Δp) through the mask are used to determine qf and qf,o. Experimental results reveal that the most penetrating particle size (MPS) for the pre-decontaminated N95, Gauze and Spunlace masks were 118 nm, 461 nm and 279 nm, respectively, and the respective penetration rates were 2.6%, 23.2% and 70.0%. The Δp through the pretreated N95 masks was 9.2 mm H2O at the breathing flow rate of heavy-duty workers, exceeding the Δp values obtained through Gauze and Spunlace masks. Decontamination increased the sizes of the most penetrating particles, changing the qf values of all of the masks: qf fell as particle size increased because the penetration increased. Bleach increased the Δp of N95, but destroyed the Gauze mask. However, the use of an autoclave reduces the Δp values of both the N95 and the Gauze mask. Neither the rice cooker nor ethanol altered the Δp of the Gauze mask. Chemical decontamination methods reduced the qf,o values for the three electret masks. The value of qf,o for PM0.1 exceeded that for PM0.1–0.6, because particles smaller than 100 nm had lower penetration, resulting in a better qf for a given pressure drop. The values of qf,o, particularly for PM0.1, reveal that for the tested treatments and masks, physical decontamination methods are less destructive to the filter than chemical methods. Nevertheless, when purchasing new or reusing FFRs, penetration should be regarded as the priority. PMID:29023492

Ultrasonic tracking of shear waves using a particle filter.

PubMed

Ingle, Atul N; Ma, Chi; Varghese, Tomy

2015-11-01

This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques.

Method for sampling sub-micron particles

DOEpatents

Gay, Don D.; McMillan, William G.

1985-01-01

Apparatus and method steps for collecting sub-micron sized particles include a collection chamber and cryogenic cooling. The cooling is accomplished by coil tubing carrying nitrogen in liquid form, with the liquid nitrogen changing to the gas phase before exiting from the collection chamber in the tubing. Standard filters are used to filter out particles of diameter greater than or equal to 0.3 microns; however the present invention is used to trap particles of less than 0.3 micron in diameter. A blower draws air to said collection chamber through a filter which filters particles with diameters greater than or equal to 0.3 micron. The air is then cryogenically cooled so that moisture and sub-micron sized particles in the air condense into ice on the coil. The coil is then heated so that the ice melts, and the liquid is then drawn off and passed through a Buchner funnel where the liquid is passed through a Nuclepore membrane. A vacuum draws the liquid through the Nuclepore membrane, with the Nuclepore membrane trapping sub-micron sized particles therein. The Nuclepore membrane is then covered on its top and bottom surfaces with sheets of Mylar.RTM. and the assembly is then crushed into a pellet. This effectively traps the sub-micron sized particles for later analysis.

Fiber Bragg grating filter using evaporated induced self assembly of silica nano particles

NASA Astrophysics Data System (ADS)

Hammarling, Krister; Zhang, Renyung; Manuilskiy, Anatoliy; Nilsson, Hans-Erik

2014-03-01

In the present work we conduct a study of fiber filters produced by evaporation of silica particles upon a MM-fiber core. A band filter was designed and theoretically verified using a 2D Comsol simulation model of a 3D problem, and calculated in the frequency domain in respect to refractive index. The fiber filters were fabricated by stripping and chemically etching the middle part of an MM-fiber until the core was exposed. A mono layer of silica nano particles were evaporated on the core using an Evaporation Induced Self-Assembly (EISA) method. The experimental results indicated a broader bandwidth than indicated by the simulations which can be explained by the mismatch in the particle size distributions, uneven particle packing and finally by effects from multiple mode angles. Thus, there are several closely connected Bragg wavelengths that build up the broader bandwidth. The experimental part shows that it is possible by narrowing the particle size distributing and better control of the particle packing, the filter effectiveness can be greatly improved.

Flight prototype regenerative particulate filter system development

NASA Technical Reports Server (NTRS)

Green, D. C.; Garber, P. J.

1974-01-01

The effort to design, fabricate, and test a flight prototype Filter Regeneration Unit used to regenerate (clean) fluid particulate filter elements is reported. The design of the filter regeneration unit and the results of tests performed in both one-gravity and zero-gravity are discussed. The filter regeneration unit uses a backflush/jet impingement method of regenerating fluid filter elements that is highly efficient. A vortex particle separator and particle trap were designed for zero-gravity use, and the zero-gravity test results are discussed. The filter regeneration unit was designed for both inflight maintenance and ground refurbishment use on space shuttle and future space missions.

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

PubMed

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

2016-03-03

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 length and uses a particle filter to deal with the crack evolution and monitoring uncertainties. The piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The state space model relating to crack propagation is established by the data-driven and finite element methods. Fatigue experiments performed on hole-edge crack specimens have validated the advantages of the proposed method.

Use of Nuclepore filters for ambient and workplace nanoparticle exposure assessment-Spherical particles

NASA Astrophysics Data System (ADS)

Chen, Sheng-Chieh; Wang, Jing; Fissan, Heinz; Pui, David Y. H.

2013-10-01

Nuclepore filter collection with subsequent electron microscopy analysis for nanoparticles was carried out to examine the feasibility of the method to assess the nanoparticle exposure. The number distribution of nanoparticles collected on the filter surface was counted visually and converted to the distribution in the air using existing filtration models for Nuclepore filters. To search for a proper model, this paper studied the overall penetrations of three different nanoparticles (PSL, Ag and NaCl), covering a wide range of particle sizes (20-800 nm) and densities (1.05-10.5 g cm-3), through Nuclepore filters with two different pore diameters (1 and 3 μm) and different face velocities (2-15 cm s-1). The data were compared with existing particle deposition models and modified models proposed by this study, which delivered different results because of different deposition processes considered. It was found that a parameter associated with flow condition and filter geometry (density of fluid medium, particle density, filtration face velocity, filter porosity and pore diameter) should be taken into account to verify the applicability of the models. The data of the overall penetration were in very good agreement with the properly applied models. A good agreement of filter surface collection between the validated model and the SEM analysis was obtained, indicating a correct nanoparticle number distribution in the air can be converted from the Nuclepore filter surface collection and this method can be applied for nanoparticle exposure assessment.

Assessing consumption of bioactive micro-particles by filter-feeding Asian carp

USGS Publications Warehouse

Jensen, Nathan R.; Amberg, Jon J.; Luoma, James A.; Walleser, Liza R.; Gaikowski, Mark P.

2012-01-01

Silver carp Hypophthalmichthys molitrix (SVC) and bighead carp H. nobilis (BHC) have impacted waters in the US since their escape. Current chemical controls for aquatic nuisance species are non-selective. Development of a bioactive micro-particle that exploits filter-feeding habits of SVC or BHC could result in a new control tool. It is not fully understood if SVC or BHC will consume bioactive micro-particles. Two discrete trials were performed to: 1) evaluate if SVC and BHC consume the candidate micro-particle formulation; 2) determine what size they consume; 3) establish methods to evaluate consumption of filter-feeders for future experiments. Both SVC and BHC were exposed to small (50-100 μm) and large (150-200 μm) micro-particles in two 24-h trials. Particles in water were counted electronically and manually (microscopy). Particles on gill rakers were counted manually and intestinal tracts inspected for the presence of micro-particles. In Trial 1, both manual and electronic count data confirmed reductions of both size particles; SVC appeared to remove more small particles than large; more BHC consumed particles; SVC had fewer overall particles in their gill rakers than BHC. In Trial 2, electronic counts confirmed reductions of both size particles; both SVC and BHC consumed particles, yet more SVC consumed micro-particles compared to BHC. Of the fish that ate micro-particles, SVC consumed more than BHC. It is recommended to use multiple metrics to assess consumption of candidate micro-particles by filter-feeders when attempting to distinguish differential particle consumption. This study has implications for developing micro-particles for species-specific delivery of bioactive controls to help fisheries, provides some methods for further experiments with bioactive micro-particles, and may also have applications in aquaculture.

Variable flexure-based fluid filter

DOEpatents

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.

An Unscented Kalman-Particle Hybrid Filter for Space Object Tracking

NASA Astrophysics Data System (ADS)

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.

Evaluation of filter media for particle number, surface area and mass penetrations.

PubMed

Li, Lin; Zuo, Zhili; Japuntich, Daniel A; Pui, David Y H

2012-07-01

The National Institute for Occupational Safety and Health (NIOSH) developed a standard for respirator certification under 42 CFR Part 84, using a TSI 8130 automated filter tester with photometers. A recent study showed that photometric detection methods may not be sensitive for measuring engineered nanoparticles. Present NIOSH standards for penetration measurement are mass-based; however, the threshold limit value/permissible exposure limit for an engineered nanoparticle worker exposure is not yet clear. There is lack of standardized filter test development for engineered nanoparticles, and development of a simple nanoparticle filter test is indicated. To better understand the filter performance against engineered nanoparticles and correlations among different tests, initial penetration levels of one fiberglass and two electret filter media were measured using a series of polydisperse and monodisperse aerosol test methods at two different laboratories (University of Minnesota Particle Technology Laboratory and 3M Company). Monodisperse aerosol penetrations were measured by a TSI 8160 using NaCl particles from 20 to 300 nm. Particle penetration curves and overall penetrations were measured by scanning mobility particle sizer (SMPS), condensation particle counter (CPC), nanoparticle surface area monitor (NSAM), and TSI 8130 at two face velocities and three layer thicknesses. Results showed that reproducible, comparable filtration data were achieved between two laboratories, with proper control of test conditions and calibration procedures. For particle penetration curves, the experimental results of monodisperse testing agreed well with polydisperse SMPS measurements. The most penetrating particle sizes (MPPSs) of electret and fiberglass filter media were ~50 and 160 nm, respectively. For overall penetrations, the CPC and NSAM results of polydisperse aerosols were close to the penetration at the corresponding median particle sizes. For each filter type, power-law correlations between the penetrations measured by different instruments show that the NIOSH TSI 8130 test may be used to predict penetrations at the MPPS as well as the CPC and NSAM results with polydisperse aerosols. It is recommended to use dry air (<20% RH) as makeup air in the test system to prevent sodium chloride particle deliquescing and minimizing the challenge particle dielectric constant and to use an adequate neutralizer to fully neutralize the polydisperse challenge aerosol. For a simple nanoparticle penetration test, it is recommended to use a polydisperse aerosol challenge with a geometric mean of ~50 nm with the CPC or the NSAM as detectors.

Ultrafine particle removal by residential heating, ventilating, and air-conditioning filters.

PubMed

Stephens, B; Siegel, J A

2013-12-01

This work uses an in situ filter test method to measure the size-resolved removal efficiency of indoor-generated ultrafine particles (approximately 7-100 nm) for six new commercially available filters installed in a recirculating heating, ventilating, and air-conditioning (HVAC) system in an unoccupied test house. The fibrous HVAC filters were previously rated by the manufacturers according to ASHRAE Standard 52.2 and ranged from shallow (2.5 cm) fiberglass panel filters (MERV 4) to deep-bed (12.7 cm) electrostatically charged synthetic media filters (MERV 16). Measured removal efficiency ranged from 0 to 10% for most ultrafine particles (UFP) sizes with the lowest rated filters (MERV 4 and 6) to 60-80% for most UFP sizes with the highest rated filter (MERV 16). The deeper bed filters generally achieved higher removal efficiencies than the panel filters, while maintaining a low pressure drop and higher airflow rate in the operating HVAC system. Assuming constant efficiency, a modeling effort using these measured values for new filters and other inputs from real buildings shows that MERV 13-16 filters could reduce the indoor proportion of outdoor UFPs (in the absence of indoor sources) by as much as a factor of 2-3 in a typical single-family residence relative to the lowest efficiency filters, depending in part on particle size. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

[Evaluation of the viability of BEAS-2B cells exposed to gasoline engine exhaust with different particle sizes by air-liquid interface].

PubMed

Yu, T; Zhang, X Y; Wang, Z X; Li, B; Zheng, Y X; Bin, P

2017-06-20

Objective: To evaluate the viability of gasoline engine exhaust (GEE) with different particle sizes on human lung cell line BEAS-2B in vitro by air-liquid interface (ALI) . Methods: GEE were collected with a Tedlar bag and their particulate matter (PM) number, surface and mass concentration in three kind of GEE (filtered automobile exhaust, non-filtered automobile exhaust and motorcycle exhaust without three-way catalytic converter) were measured by two type of particle size spectrometer including TSI-3321 and SMPS-3938. Five groups were included, which divided into blank control group, clean air group, filtered automobile exhaust group, non-filtered automobile exhaust group and motorcycle exhaust without three-way catalytic converter group. Except the blank control group, BEAS-2B cells, cultured on the surface of Transwells, were treated with clean air or GEE by ALI method at a flow rate of 25 ml/min, 37 ℃ for 60 min in vitro . CCK-8 cytotoxicity test kit was used to determine the cell relative viability of BEAS-2B cells. Results: In the filtered automobile exhaust, non-filtered automobile exhaust and motorcycle exhaust without three-way catalytic converter, high concentrations of fine particles can be detected, but the coarse particles only accounted for a small proportion, and the sequence of PM concentration was motorcycle exhaust without three-way catalytic converter group> non-filtered automobile exhaust group> filtered automobile exhaust group ( P <0.001) . Compared with the clean air group, the cell relative viability in the 3 GEE-exposed groups were significantly lower ( P <0.001) . Among the comparisons of GEE exposure groups with different particle size spectra, the sequence of the cell relative viability was filtered automobile exhaust group >non-filtered automobile exhaust group> motorcycle exhaust without three-way catalytic converter group ( P <0.001) . When took the clean air control group as a reference, the mean of the cell relative viability in the filtered automobile exhaust group, non-filtered automobile exhaust group and motorcycle exhaust without three-way catalytic converter group, was decreased by 26.34%, 36.00% and 49.59%, respectively. Conclusion: GEE with different particle size spectra could induce different levels of toxic effects to the human lung cells BEAS-2B by ALI. After lowering the concentration of particles in the GEE and using the three-way catalytic converter could obviously improve the survival rate of lung cells.

An ultrasensitive bio-surrogate for nanoporous filter membrane performance metrology directed towards contamination control in microlithography applications

NASA Astrophysics Data System (ADS)

Ahmad, Farhan; Mish, Barbara; Qiu, Jian; Singh, Amarnauth; Varanasi, Rao; Bedford, Eilidh; Smith, Martin

2016-03-01

Contamination tolerances in semiconductor manufacturing processes have changed dramatically in the past two decades, reaching below 20 nm according to the guidelines of the International Technology Roadmap for Semiconductors. The move to narrower line widths drives the need for innovative filtration technologies that can achieve higher particle/contaminant removal performance resulting in cleaner process fluids. Nanoporous filter membrane metrology tools that have been the workhorse over the past decade are also now reaching limits. For example, nanoparticle (NP) challenge testing is commonly applied for assessing particle retention performance of filter membranes. Factors such as high NP size dispersity, low NP detection sensitivity, and high NP particle-filter affinity impose challenges in characterizing the next generation of nanoporous filter membranes. We report a novel bio-surrogate, 5 nm DNA-dendrimer conjugate for evaluating particle retention performance of nanoporous filter membranes. A technique capable of single molecule detection is employed to detect sparse concentration of conjugate in filter permeate, providing >1000- fold higher detection sensitivity than any existing 5 nm-sized particle enumeration technique. This bio-surrogate also offers narrow size distribution, high stability and chemical tunability. This bio-surrogate can discriminate various sub-15 nm pore-rated nanoporous filter membranes based on their particle retention performance. Due to high bio-surrogate detection sensitivity, a lower challenge concentration of bio-surrogate (as compared to other NPs of this size) can be used for filter testing, providing a better representation of customer applications. This new method should provide better understanding of the next generation filter membranes for removing defect-causing contaminants from lithography processes.

Multisensor fusion for 3D target tracking using track-before-detect particle filter

NASA Astrophysics Data System (ADS)

Moshtagh, Nima; Romberg, Paul M.; Chan, Moses W.

2015-05-01

This work presents a novel fusion mechanism for estimating the three-dimensional trajectory of a moving target using images collected by multiple imaging sensors. The proposed projective particle filter avoids the explicit target detection prior to fusion. In projective particle filter, particles that represent the posterior density (of target state in a high-dimensional space) are projected onto the lower-dimensional observation space. Measurements are generated directly in the observation space (image plane) and a marginal (sensor) likelihood is computed. The particles states and their weights are updated using the joint likelihood computed from all the sensors. The 3D state estimate of target (system track) is then generated from the states of the particles. This approach is similar to track-before-detect particle filters that are known to perform well in tracking dim and stealthy targets in image collections. Our approach extends the track-before-detect approach to 3D tracking using the projective particle filter. The performance of this measurement-level fusion method is compared with that of a track-level fusion algorithm using the projective particle filter. In the track-level fusion algorithm, the 2D sensor tracks are generated separately and transmitted to a fusion center, where they are treated as measurements to the state estimator. The 2D sensor tracks are then fused to reconstruct the system track. A realistic synthetic scenario with a boosting target was generated, and used to study the performance of the fusion mechanisms.

Conditions for successful data assimilation

NASA Astrophysics Data System (ADS)

Morzfeld, M.; Chorin, A. J.

2013-12-01

Many applications in science and engineering require that the predictions of uncertain models be updated by information from a stream of noisy data. The model and the data jointly define a conditional probability density function (pdf), which contains all the information one has about the process of interest and various numerical methods can be used to study and approximate this pdf, e.g. the Kalman filter, variational methods or particle filters. Given a model and data, each of these algorithms will produce a result. We are interested in the conditions under which this result is reasonable, i.e. consistent with the real-life situation one is modeling. In particular, we show, using idealized models, that numerical data assimilation is feasible in principle only if a suitably defined effective dimension of the problem is not excessive. This effective dimension depends on the noise in the model and the data, and in physically reasonable problems it can be moderate even when the number of variables is huge. In particular, we find that the effective dimension being moderate induces a balance condition between the noises in the model and the data; this balance condition is often satisfied in realistic applications or else the noise levels are excessive and drown the underlying signal. We also study the effects of the effective dimension on particle filters in two instances, one in which the importance function is based on the model alone, and one in which it is based on both the model and the data. We have three main conclusions: (1) the stability (i.e., non-collapse of weights) in particle filtering depends on the effective dimension of the problem. Particle filters can work well if the effective dimension is moderate even if the true dimension is large (which we expect to happen often in practice). (2) A suitable choice of importance function is essential, or else particle filtering fails even when data assimilation is feasible in principle with a sequential algorithm. (3) There is a parameter range in which the model noise and the observation noise are roughly comparable, and in which even the optimal particle filter collapses, even under ideal circumstances. We further study the role of the effective dimension in variational data assimilation and particle smoothing, for both the weak and strong constraint problem. It was found that these methods too require a moderate effective dimension or else no accurate predictions can be expected. Moreover, variational data assimilation or particle smoothing may be applicable in the parameter range where particle filtering fails, because the use of more than one consecutive data set helps reduce the variance which is responsible for the collapse of the filters.

Magnetic filtration process, magnetic filtering material, and methods of forming magnetic filtering material

DOEpatents

Taboada-Serrano, Patricia; Tsouris, Constantino; Contescu, Cristian I; McFarlane, Joanna

2013-10-08

The present invention provides magnetically responsive activated carbon, and a method of forming magnetically responsive activated carbon. The method of forming magnetically responsive activated carbon typically includes providing activated carbon in a solution containing ions of ferrite forming elements, wherein at least one of the ferrite forming elements has an oxidation state of +3 and at least a second of the ferrite forming elements has an oxidation state of +2, and increasing pH of the solution to precipitate particles of ferrite that bond to the activated carbon, wherein the activated carbon having the ferrite particles bonded thereto have a positive magnetic susceptibility. The present invention also provides a method of filtering waste water using magnetic activated carbon.

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

NASA Astrophysics Data System (ADS)

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.

A baker's dozen of new particle flows for nonlinear filters, Bayesian decisions and transport

NASA Astrophysics Data System (ADS)

Daum, Fred; Huang, Jim

2015-05-01

We describe a baker's dozen of new particle flows to compute Bayes' rule for nonlinear filters, Bayesian decisions and learning as well as transport. Several of these new flows were inspired by transport theory, but others were inspired by physics or statistics or Markov chain Monte Carlo methods.

Characterization of a Regenerable Impactor Filter for Spacecraft Cabin Applications

NASA Technical Reports Server (NTRS)

Agui, Juan H.; Vijayakumar, R.

2015-01-01

Regenerable filters will play an important role in human exploration beyond low-Earth orbit. Life Support Systems aboard crewed spacecrafts will have to operate reliably and with little maintenance over periods of more than a year, even multiple years. Air filters are a key component of spacecraft life support systems, but they often require frequent routine maintenance. Bacterial filters aboard the International Space Station require almost weekly cleaning of the pre-filter screen to remove large lint debris captured in the microgravity environment. The source of the airborne matter which is collected on the filter screen is typically from clothing fibers, biological matter (hair, skin, nails, etc.) and material wear. Clearly a need for low maintenance filters requiring little to no crew intervention will be vital to the success of the mission. An impactor filter is being developed and tested to address this need. This filter captures large particle matter through inertial separation and impaction methods on collection surfaces, which can be automatically cleaned after they become heavily loaded. The impactor filter can serve as a pre-filter to augment the life of higher efficiency filters that capture fine and ultrafine particles. A prototype of the filter is being tested at the Particulate Filtration Laboratory at NASA Glenn Research Center to determine performance characteristics, including particle cut size and overall efficiency. Model results are presented for the flow characteristics near the orifice plate through which the particle-laden flow is accelerated as well as around the collection bands.

Sequential data assimilation for a distributed hydrologic model considering different time scale of internal processes

NASA Astrophysics Data System (ADS)

Noh, S.; Tachikawa, Y.; Shiiba, M.; Kim, S.

2011-12-01

Applications of the sequential data assimilation methods have been increasing in hydrology to reduce uncertainty in the model prediction. In a distributed hydrologic model, there are many types of state variables and each variable interacts with each other based on different time scales. However, the framework to deal with the delayed response, which originates from different time scale of hydrologic processes, has not been thoroughly addressed in the hydrologic data assimilation. In this study, we propose the lagged filtering scheme to consider the lagged response of internal states in a distributed hydrologic model using two filtering schemes; particle filtering (PF) and ensemble Kalman filtering (EnKF). The EnKF is one of the widely used sub-optimal filters implementing an efficient computation with limited number of ensemble members, however, still based on Gaussian approximation. PF can be an alternative in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions involved. In case of PF, advanced particle regularization scheme is implemented together to preserve the diversity of the particle system. In case of EnKF, the ensemble square root filter (EnSRF) are implemented. Each filtering method is parallelized and implemented in the high performance computing system. A distributed hydrologic model, the water and energy transfer processes (WEP) model, is applied for the Katsura River catchment, Japan to demonstrate the applicability of proposed approaches. Forecasted results via PF and EnKF are compared and analyzed in terms of the prediction accuracy and the probabilistic adequacy. Discussions are focused on the prospects and limitations of each data assimilation method.

QMRPF-UKF Master-Slave Filtering for the Attitude Determination of Micro-Nano Satellites Using Gyro and Magnetometer

PubMed Central

Cui, Peiling; Zhang, Huijuan

2010-01-01

In this paper, the problem of estimating the attitude of a micro-nano satellite, obtaining geomagnetic field measurements via a three-axis magnetometer and obtaining angle rate via gyro, is considered. For this application, a QMRPF-UKF master-slave filtering method is proposed, which uses the QMRPF and UKF algorithms to estimate the rotation quaternion and the gyro bias parameters, respectively. The computational complexicity related to the particle filtering technique is eliminated by introducing a multiresolution approach that permits a significant reduction in the number of particles. This renders QMRPF-UKF master-slave filter computationally efficient and enables its implementation with a remarkably small number of particles. Simulation results by using QMRPF-UKF are given, which demonstrate the validity of the QMRPF-UKF nonlinear filter. PMID:22163448

76 FR 15974 - Office of Research and Development; Ambient Air Monitoring Reference and Equivalent Methods...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-22

... on a particle filter. Because this new measurement approach is being approved for NAAQS compliance... Lead (Pb) on TSP High-Volume Filters.'' A sample of total suspended particulate matter (TSP) is collected on a glass fiber filter, using the sampler and procedure of the EPA Reference Method for the...

Phase Response Design of Recursive All-Pass Digital Filters Using a Modified PSO Algorithm

PubMed Central

2015-01-01

This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter. PMID:26366168

CH PLIF and PIV implementation using C-X (0,0) and intra-vibrational band filtered detection

NASA Astrophysics Data System (ADS)

Hammack, Stephen D.; Skiba, Aaron W.; Lee, Tonghun; Carter, Campbell D.

2018-02-01

This study demonstrates advancement in a low-pulse energy methylidyne (CH) planar laser-induced fluorescence (PLIF) method that facilitates its application alongside flows seeded for particle image velocimetry (PIV) or other particle scattering based methods, as well as in high scattering environments. The C-X (0,0) R-branch excitation and filtered detection are carefully selected such that the laser line frequency is heavily attenuated by an edge filter while allowing transmission of most of the (0,0) band fluorescence. There are strong OH A-X (0,0) lines in the vicinity, but they can be avoided or utilized through dye laser tuning. As a demonstration of efficacy, PIV is performed simultaneously with the PLIF imaging. Using the edge filter, particle scattering signal is reduced to sub-fluorescence levels, allowing for flame-front analysis. This achievement enables flame-front tracking at high repetition rates (due to the low-pulse energy required) in combination with a scattering method such as PIV or use in high scattering environments such as enclosed combustors or near burner surfaces.

Thin film production method and apparatus

DOEpatents

Loutfy, Raouf O.; Moravsky, Alexander P.; Hassen, Charles N.

2010-08-10

A method for forming a thin film material which comprises depositing solid particles from a flowing suspension or aerosol onto a filter and next adhering the solid particles to a second substrate using an adhesive.

Nonlinear data assimilation using synchronization in a particle filter

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

Simulation on Soot Oxidation with NO2 and O2 in a Diesel Particulate Filter

NASA Astrophysics Data System (ADS)

Yamamoto, Kazuhiro; Satake, Shingo; Yamashita, Hiroshi; Obuchi, Akira; Uchisawa, Junko

Although diesel engines have an advantage of low fuel consumption in comparison with gasoline engines, exhaust gas has more particulate matters (PM) including soot. As one of the key technologies, a diesel particulate filter (DPF) has been developed to reduce PM. When the exhaust gas passes its porous filter wall, the soot particles are trapped. However, the filter would readily be plugged with particles, and the accumulated particles must be removed to prevent filter clogging and a rise in backpressure, which is called filter regeneration process. In this study, we have simulated the flow in the wall-flow DPF using the lattice Boltzmann method. Filters of different length, porosity, and pore size are used. The soot oxidation for filter regeneration process is considered. Especially, the effect of NO2 on the soot oxidation is examined. The reaction rate has been determined by previous experimental data. Results show that, the flow along the filter monolith is roughly uniform, and the large pressure drop across the filter wall is observed. The soot oxidation rate becomes ten times larger when NO2 is added. These are useful information to construct the future regeneration system.

Adaptive Square-Root Cubature-Quadrature Kalman Particle Filter for satellite attitude determination using vector observations

NASA Astrophysics Data System (ADS)

Kiani, Maryam; Pourtakdoust, Seid H.

2014-12-01

A novel algorithm is presented in this study for estimation of spacecraft's attitudes and angular rates from vector observations. In this regard, a new cubature-quadrature particle filter (CQPF) is initially developed that uses the Square-Root Cubature-Quadrature Kalman Filter (SR-CQKF) to generate the importance proposal distribution. The developed CQPF scheme avoids the basic limitation of particle filter (PF) with regards to counting the new measurements. Subsequently, CQPF is enhanced to adjust the sample size at every time step utilizing the idea of confidence intervals, thus improving the efficiency and accuracy of the newly proposed adaptive CQPF (ACQPF). In addition, application of the q-method for filter initialization has intensified the computation burden as well. The current study also applies ACQPF to the problem of attitude estimation of a low Earth orbit (LEO) satellite. For this purpose, the undertaken satellite is equipped with a three-axis magnetometer (TAM) as well as a sun sensor pack that provide noisy geomagnetic field data and Sun direction measurements, respectively. The results and performance of the proposed filter are investigated and compared with those of the extended Kalman filter (EKF) and the standard particle filter (PF) utilizing a Monte Carlo simulation. The comparison demonstrates the viability and the accuracy of the proposed nonlinear estimator.

Optimization of the cleaning process on a pilot filtration setup for waste water treatment accompanied by flow visualization

NASA Astrophysics Data System (ADS)

Bílek, Petr; Hrůza, Jakub

2018-06-01

This paper deals with an optimization of the cleaning process on a liquid flat-sheet filter accompanied by visualization of the inlet side of a filter. The cleaning process has a crucial impact on the hydrodynamic properties of flat-sheet filters. Cleaning methods avoid depositing of particles on the filter surface and forming a filtration cake. Visualization significantly helps to optimize the cleaning methods, because it brings new overall view on the filtration process in time. The optical method, described in the article, enables to see flow behaviour in a thin laser sheet on the inlet side of a tested filter during the cleaning process. Visualization is a strong tool for investigation of the processes on filters in details and it is also possible to determine concentration of particles after an image analysis. The impact of air flow rate, inverse pressure drop and duration on the cleaning mechanism is investigated in the article. Images of the cleaning process are compared to the hydrodynamic data. The tests are carried out on a pilot filtration setup for waste water treatment.

Method for filtering solvent and tar sand mixtures

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

Kelterborn, J. C.; Stone, R. A.

1985-09-03

A method for filtering spent tar sands from a bitumen and organic solvent solution comprises separating the solution into two streams wherein the bulk of the coarser spent tar sand is in a first stream and has an average particle size of about 10 to about 100 mesh and the bulk of the finer spent tar sand is in a second stream; producing a filter cake by filtering the coarser spent tar sand from the first stream; and filtering the finer spent tar sand from the second stream with the filter cake. The method is particularly useful for filtering solutionsmore » of bitumen extracted from bitumen containing diatomite, spent diatomite and organic solvent.« less

Cryogenic filter method produces super-pure helium and helium isotopes

NASA Technical Reports Server (NTRS)

Hildebrandt, A. F.

1964-01-01

Helium is purified when cooled in a low pressure environment until it becomes superfluid. The liquid helium is then filtered through iron oxide particles. Heating, cooling and filtering processes continue until the purified liquid helium is heated to a gas.

Effect of central fans and in-duct filters on deposition rates of ultrafine and fine particles in an occupied townhouse

NASA Astrophysics Data System (ADS)

Wallace, Lance A.; Emmerich, Steven J.; Howard-Reed, Cynthia

Airborne particles are implicated in morbidity and mortality of certain high-risk subpopulations. Exposure to particles occurs mostly indoors, where a main removal mechanism is deposition to surfaces. Deposition can be affected by the use of forced-air circulation through ducts or by air filters. In this study, we calculate the deposition rates of particles in an occupied house due to forced-air circulation and the use of in-duct filters such as electrostatic precipitators (ESP) and fibrous mechanical filters (MECH). Deposition rates are calculated for 128 size categories ranging from 0.01 to 2.5 μm. More than 110 separate "events" (mostly cooking, candle burning, and pouring kitty litter) were used to calculate deposition rates for four conditions: fan off, fan on, MECH installed, ESP installed. For all cases, deposition rates varied in a "U"-shaped distribution with the minimum occurring near 0.1 μm, as predicted by theory. The use of the central fan with no filter or with a standard furnace filter increased deposition rates by amounts on the order of 0.1-0.5 h -1. The MECH increased deposition rates by up to 2 h -1 for ultrafine and fine particles but was ineffective for particles in the 0.1-0.5 μm range. The ESP increased deposition rates by 2-3 h -1 and was effective for all sizes. However, the ESP lost efficiency after several weeks and needed regular cleaning to maintain its effectiveness. A reduction of particle levels by 50% or more could be achieved by use of the ESP when operating properly. Since the use of fans and filters reduces particle concentrations from both indoor and outdoor sources, it is more effective than the alternative approach of reducing ventilation by closing windows or insulating homes more tightly. For persons at risk, use of an air filter may be an effective method of reducing exposure to particles.

External Aiding Methods for IMU-Based Navigation

DTIC Science & Technology

2016-11-26

Carlo simulation and particle filtering . This approach allows for the utilization of highly complex systems in a black box configuration with minimal...alternative method, which has the advantage of being less computationally demanding, is to use a Kalman filtering -based approach. The particular...Kalman filtering -based approach used here is known as linear covariance analysis. In linear covariance analysis, the nonlinear systems describing the

Improving particle filters in rainfall-runoff models: application of the resample-move step and development of the ensemble Gaussian particle filter

NASA Astrophysics Data System (ADS)

Plaza Guingla, D. A.; Pauwels, V. R.; De Lannoy, G. J.; Matgen, P.; Giustarini, L.; De Keyser, R.

2012-12-01

The objective of this work is to analyze the improvement in the performance of the particle filter by including a resample-move step or by using a modified Gaussian particle filter. Specifically, the standard particle filter structure is altered by the inclusion of the Markov chain Monte Carlo move step. The second choice adopted in this study uses the moments of an ensemble Kalman filter analysis to define the importance density function within the Gaussian particle filter structure. Both variants of the standard particle filter are used in the assimilation of densely sampled discharge records into a conceptual rainfall-runoff model. In order to quantify the obtained improvement, discharge root mean square errors are compared for different particle filters, as well as for the ensemble Kalman filter. First, a synthetic experiment is carried out. The results indicate that the performance of the standard particle filter can be improved by the inclusion of the resample-move step, but its effectiveness is limited to situations with limited particle impoverishment. The results also show that the modified Gaussian particle filter outperforms the rest of the filters. Second, a real experiment is carried out in order to validate the findings from the synthetic experiment. The addition of the resample-move step does not show a considerable improvement due to performance limitations in the standard particle filter with real data. On the other hand, when an optimal importance density function is used in the Gaussian particle filter, the results show a considerably improved performance of the particle filter.

FILTER PACK TECHNIQUE FOR CLASSIFYING RADIOACTIVE AEROSOLS BY PARTICLE SIZE. PART 1 PRELIMINARY EVALUATION.

DTIC Science & Technology

radon daughters is associated have greater ability to penetrate the variousfilter media than has the fission product debris in the atmosphere; therefore the former is associated with aerosols of smaller size. A preliminary evaluation of the techniques of employing packs of filters of different retentivity characteristics to determine the particle size and/or particle size distribution of radioactive aerosols has been made which indicates the feasibility of the method. It is recommended that a series of measurements be undertaken to determine the relative particle size

Screening system and method of using same

DOEpatents

Jones, David A; Gresham, Christopher A; Basiliere, Marc L; Spates, James J; Rodacy, Philip J

2014-04-15

An integrated apparatus and method for screening an object for a target material is provided. The integrated apparatus comprises a housing and an integrated screener. The housing is positionable adjacent the object, and has a channel therethrough. The integrated screener is positionable in the housing, and comprises a fan, at least one filter, a heater and an analyzer. The fan is for drawing air carrying particles and vapor through the channel of the housing. The filter(s) is/are positionable in the channel of the housing for passage of the air therethrough. The filter(s) comprise(s) at least one metal foam having a plurality of pores therein for collecting and adsorbing a sample from the particles and vapor passing therethrough. The heater is for applying heat to the at least one metal foam whereby the collected sample is desorbed from the metal foam. The analyzer detects the target material from the desorbed sample.

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

Lu, Liqiang; Gao, Xi; Li, Tingwen

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models tomore » predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.« less

On-line prognosis of fatigue crack propagation based on Gaussian weight-mixture proposal particle filter.

PubMed

Chen, Jian; Yuan, Shenfang; Qiu, Lei; Wang, Hui; Yang, Weibo

2018-01-01

Accurate on-line prognosis of fatigue crack propagation is of great meaning for prognostics and health management (PHM) technologies to ensure structural integrity, which is a challenging task because of uncertainties which arise from sources such as intrinsic material properties, loading, and environmental factors. The particle filter algorithm has been proved to be a powerful tool to deal with prognostic problems those are affected by uncertainties. However, most studies adopted the basic particle filter algorithm, which uses the transition probability density function as the importance density and may suffer from serious particle degeneracy problem. This paper proposes an on-line fatigue crack propagation prognosis method based on a novel Gaussian weight-mixture proposal particle filter and the active guided wave based on-line crack monitoring. Based on the on-line crack measurement, the mixture of the measurement probability density function and the transition probability density function is proposed to be the importance density. In addition, an on-line dynamic update procedure is proposed to adjust the parameter of the state equation. The proposed method is verified on the fatigue test of attachment lugs which are a kind of important joint components in aircraft structures. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint state and parameter estimation of the hemodynamic model by particle smoother expectation maximization method

NASA Astrophysics Data System (ADS)

Aslan, Serdar; Taylan Cemgil, Ali; Akın, Ata

2016-08-01

Objective. In this paper, we aimed for the robust estimation of the parameters and states of the hemodynamic model by using blood oxygen level dependent signal. Approach. In the fMRI literature, there are only a few successful methods that are able to make a joint estimation of the states and parameters of the hemodynamic model. In this paper, we implemented a maximum likelihood based method called the particle smoother expectation maximization (PSEM) algorithm for the joint state and parameter estimation. Main results. Former sequential Monte Carlo methods were only reliable in the hemodynamic state estimates. They were claimed to outperform the local linearization (LL) filter and the extended Kalman filter (EKF). The PSEM algorithm is compared with the most successful method called square-root cubature Kalman smoother (SCKS) for both state and parameter estimation. SCKS was found to be better than the dynamic expectation maximization (DEM) algorithm, which was shown to be a better estimator than EKF, LL and particle filters. Significance. PSEM was more accurate than SCKS for both the state and the parameter estimation. Hence, PSEM seems to be the most accurate method for the system identification and state estimation for the hemodynamic model inversion literature. This paper do not compare its results with Tikhonov-regularized Newton—CKF (TNF-CKF), a recent robust method which works in filtering sense.

In Vitro Evaluation of a Rheolytic Thrombectomy System for Clot Removal from Five Different Temporary Vena Cava Filters

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

Buecker, Arno; Neuerburg, Joerg; Schmitz-Rode, Thomas

1997-11-15

Purpose: To evaluate the feasibility of thrombus removal from temporary vena cava filters using a rheolytic thrombectomy device and to assess the embolization rate of this procedure. Methods: Five temporary vena cava filters together with porcine thrombi were placed in a vena cava flow model (semitranslucent silicone tube of 23 mm diameter, pulsatile flow at a mean flow rate of 4 L/min). A rheolytic thrombectomy system (Hydrolyser) was used with a 9 Fr guiding catheter to remove the clots. The effluent was passed through filters of different size and the amount of embolized particles as well as the remaining thrombusmore » were measured. Results: Thrombus removal rates ranged from 85% to 100%. Embolization rates between 47% and 60% were calculated for the different filters. Conclusion: The Hydrolyser is able to remove sufficiently high amounts of thrombus from temporary vena cava filters. However, the amount of embolized particles makes it impossible to utilize this method without special precautions against embolization.« less

Localization of a variational particle smoother

NASA Astrophysics Data System (ADS)

Morzfeld, M.; Hodyss, D.; Poterjoy, J.

2017-12-01

Given the success of 4D-variational methods (4D-Var) in numerical weather prediction,and recent efforts to merge ensemble Kalman filters with 4D-Var,we consider a method to merge particle methods and 4D-Var.This leads us to revisit variational particle smoothers (varPS).We study the collapse of varPS in high-dimensional problemsand show how it can be prevented by weight-localization.We test varPS on the Lorenz'96 model of dimensionsn=40, n=400, and n=2000.In our numerical experiments, weight localization prevents the collapse of the varPS,and we note that the varPS yields results comparable to ensemble formulations of 4D-variational methods,while it outperforms EnKF with tuned localization and inflation,and the localized standard particle filter.Additional numerical experiments suggest that using localized weights in varPS may not yield significant advantages over unweighted or linearizedsolutions in near-Gaussian problems.

Robust dead reckoning system for mobile robots based on particle filter and raw range scan.

PubMed

Duan, Zhuohua; Cai, Zixing; Min, Huaqing

2014-09-04

Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs), where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hybrid system estimation problems, and they have also been widely used in many WMRs applications, such as pose tracking, SLAM, video tracking, fault identification, etc. In this paper, the readings of a laser range finder, which may be also interfered with by noises, are used to reach accurate dead reckoning. The main contribution is that a systematic method to implement fault diagnosis and dead reckoning in a particle filter framework concurrently is proposed. Firstly, the perception model of a laser range finder is given, where the raw scan may be faulty. Secondly, the kinematics of the normal model and different fault models for WMRs are given. Thirdly, the particle filter for fault diagnosis and dead reckoning is discussed. At last, experiments and analyses are reported to show the accuracy and efficiency of the presented method.

Robust Dead Reckoning System for Mobile Robots Based on Particle Filter and Raw Range Scan

PubMed Central

Duan, Zhuohua; Cai, Zixing; Min, Huaqing

2014-01-01

Robust dead reckoning is a complicated problem for wheeled mobile robots (WMRs), where the robots are faulty, such as the sticking of sensors or the slippage of wheels, for the discrete fault models and the continuous states have to be estimated simultaneously to reach a reliable fault diagnosis and accurate dead reckoning. Particle filters are one of the most promising approaches to handle hybrid system estimation problems, and they have also been widely used in many WMRs applications, such as pose tracking, SLAM, video tracking, fault identification, etc. In this paper, the readings of a laser range finder, which may be also interfered with by noises, are used to reach accurate dead reckoning. The main contribution is that a systematic method to implement fault diagnosis and dead reckoning in a particle filter framework concurrently is proposed. Firstly, the perception model of a laser range finder is given, where the raw scan may be faulty. Secondly, the kinematics of the normal model and different fault models for WMRs are given. Thirdly, the particle filter for fault diagnosis and dead reckoning is discussed. At last, experiments and analyses are reported to show the accuracy and efficiency of the presented method. PMID:25192318

Distributed multi-sensor particle filter for bearings-only tracking

NASA Astrophysics Data System (ADS)

Zhang, Jungen; Ji, Hongbing

2012-02-01

In this article, the classical bearings-only tracking (BOT) problem for a single target is addressed, which belongs to the general class of non-linear filtering problems. Due to the fact that the radial distance observability of the target is poor, the algorithm-based sequential Monte-Carlo (particle filtering, PF) methods generally show instability and filter divergence. A new stable distributed multi-sensor PF method is proposed for BOT. The sensors process their measurements at their sites using a hierarchical PF approach, which transforms the BOT problem from Cartesian coordinate to the logarithmic polar coordinate and separates the observable components from the unobservable components of the target. In the fusion centre, the target state can be estimated by utilising the multi-sensor optimal information fusion rule. Furthermore, the computation of a theoretical Cramer-Rao lower bound is given for the multi-sensor BOT problem. Simulation results illustrate that the proposed tracking method can provide better performances than the traditional PF method.

Numerical Investigation of the Ability of Salt Tracers to Represent the Residence Time Distribution of Fluidized Catalytic Cracking Particles

DOE PAGES

Lu, Liqiang; Gao, Xi; Li, Tingwen; ...

2017-11-02

For a long time, salt tracers have been used to measure the residence time distribution (RTD) of fluidized catalytic cracking (FCC) particles. However, due to limitations in experimental measurements and simulation methods, the ability of salt tracers to faithfully represent RTDs has never been directly investigated. Our current simulation results using coarse-grained computational fluid dynamic coupled with discrete element method (CFD-DEM) with filtered drag models show that the residence time of salt tracers with the same terminal velocity as FCC particles is slightly larger than that of FCC particles. This research also demonstrates the ability of filtered drag models tomore » predict the correct RTD curve for FCC particles while the homogeneous drag model may only be used in the dilute riser flow of Geldart type B particles. The RTD of large-scale reactors can then be efficiently investigated with our proposed numerical method as well as by using the old-fashioned salt tracer technology.« less

Error Modelling for Multi-Sensor Measurements in Infrastructure-Free Indoor Navigation

PubMed Central

Ruotsalainen, Laura; Kirkko-Jaakkola, Martti; Rantanen, Jesperi; Mäkelä, Maija

2018-01-01

The long-term objective of our research is to develop a method for infrastructure-free simultaneous localization and mapping (SLAM) and context recognition for tactical situational awareness. Localization will be realized by propagating motion measurements obtained using a monocular camera, a foot-mounted Inertial Measurement Unit (IMU), sonar, and a barometer. Due to the size and weight requirements set by tactical applications, Micro-Electro-Mechanical (MEMS) sensors will be used. However, MEMS sensors suffer from biases and drift errors that may substantially decrease the position accuracy. Therefore, sophisticated error modelling and implementation of integration algorithms are key for providing a viable result. Algorithms used for multi-sensor fusion have traditionally been different versions of Kalman filters. However, Kalman filters are based on the assumptions that the state propagation and measurement models are linear with additive Gaussian noise. Neither of the assumptions is correct for tactical applications, especially for dismounted soldiers, or rescue personnel. Therefore, error modelling and implementation of advanced fusion algorithms are essential for providing a viable result. Our approach is to use particle filtering (PF), which is a sophisticated option for integrating measurements emerging from pedestrian motion having non-Gaussian error characteristics. This paper discusses the statistical modelling of the measurement errors from inertial sensors and vision based heading and translation measurements to include the correct error probability density functions (pdf) in the particle filter implementation. Then, model fitting is used to verify the pdfs of the measurement errors. Based on the deduced error models of the measurements, particle filtering method is developed to fuse all this information, where the weights of each particle are computed based on the specific models derived. The performance of the developed method is tested via two experiments, one at a university’s premises and another in realistic tactical conditions. The results show significant improvement on the horizontal localization when the measurement errors are carefully modelled and their inclusion into the particle filtering implementation correctly realized. PMID:29443918

Real time tracking by LOPF algorithm with mixture model

NASA Astrophysics Data System (ADS)

Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

2007-11-01

A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

Sub-micron particle sampler apparatus

DOEpatents

Gay, Don D.; McMillan, William G.

1987-01-01

Apparatus and method steps for collecting sub-micron sized particles include a collection chamber and cryogenic cooling. The cooling is accomplished by coil tubing carrying nitrogen in liquid form, with the liquid nitrogen changing to the gas phase before exiting from the collection chamber in the tubing. Standard filters are used to filter out particles of diameter greater than or equal to 0.3 microns; however the present invention is used to trap particles of less than 0.3 micron in diameter. A blower draws air to said collection chamber through a filter which filters particles with diameters greater than or equal to 0.3 micron. The air is then cryogenically cooled so that moisture and sub-micron sized particles in the air condense into ice on the coil. The coil is then heated so that the ice melts, and the liquid is then drawn off and passed through a Buchner funnel where the liquid is passed through a Nuclepore membrane. A vacuum draws the liquid through the Nuclepore membrane, with the Nuclepore membrane trapping sub-micron sized particles therein. The Nuclepore membrane is then covered on its top and bottom surfaces with sheets of Mylar.RTM. and the assembly is then crushed into a pellet. This effectively traps the sub-micron sized particles for later analysis.

Numerical investigation of adhesion effects on solid particles filtration efficiency

NASA Astrophysics Data System (ADS)

Shaffee, Amira; Luckham, Paul; Matar, Omar K.

2017-11-01

Our work investigate the effectiveness of particle filtration process, in particular using a fully-coupled Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) approach involving poly-dispersed, adhesive solid particles. We found that an increase in particle adhesion reduces solid production through the opening of a wire-wrap type filter. Over time, as particle agglomerates continuously deposit on top of the filter, layer upon layer of particles is built on top of the filter, forming a particle pack. It is observed that with increasing particle adhesion, the pack height build up also increases and hence decreases the average particle volume fraction of the pack. This trend suggests higher porosity and looser packing of solid particles within the pack with increased adhesion. Furthermore, we found that the pressure drop for adhesive case is lower compared to non-adhesive case. Our results suggest agglomerating solid particles has beneficial effects on particle filtration. One important application of these findings is towards designing and optimizing sand control process for a hydrocarbon well with excessive sand production which is major challenge in oil and gas industry. Funding from PETRONAS and RAEng UK for Research Chair (OKM) gratefully acknowledged.

a Generic Probabilistic Model and a Hierarchical Solution for Sensor Localization in Noisy and Restricted Conditions

NASA Astrophysics Data System (ADS)

Ji, S.; Yuan, X.

2016-06-01

A generic probabilistic model, under fundamental Bayes' rule and Markov assumption, is introduced to integrate the process of mobile platform localization with optical sensors. And based on it, three relative independent solutions, bundle adjustment, Kalman filtering and particle filtering are deduced under different and additional restrictions. We want to prove that first, Kalman filtering, may be a better initial-value supplier for bundle adjustment than traditional relative orientation in irregular strips and networks or failed tie-point extraction. Second, in high noisy conditions, particle filtering can act as a bridge for gap binding when a large number of gross errors fail a Kalman filtering or a bundle adjustment. Third, both filtering methods, which help reduce the error propagation and eliminate gross errors, guarantee a global and static bundle adjustment, who requires the strictest initial values and control conditions. The main innovation is about the integrated processing of stochastic errors and gross errors in sensor observations, and the integration of the three most used solutions, bundle adjustment, Kalman filtering and particle filtering into a generic probabilistic localization model. The tests in noisy and restricted situations are designed and examined to prove them.

Cross-flow electrofilter and method

DOEpatents

Gidaspow, Dimitri; Lee, Chang H.; Wasan, Darsh T.

1980-01-01

A filter for clarifying carbonaceous liquids containing finely divided solid particles of, for instance, unreacted coal, ash and other solids discharged from a coal liquefaction process is presented. The filter includes two passageways separated by a porous filter medium. In one preferred embodiment the filter medium is of tubular shape to form the first passageway and is enclosed within an outer housing to form the second passageway within the annulus. An electrode disposed in the first passageway, for instance along the tube axis, is connected to a source of high voltage for establishing an electric field between the electrode and the filter medium. Slurry feed flows through the first passageway tangentially to the surfaces of the filter medium and the electrode. Particles from the feed slurry are attracted to the electrode within the first passageway to prevent plugging of the porous filter medium while carbonaceous liquid filters into the second passageway for withdrawal. Concentrated slurry is discharged from the first passageway at an end opposite to the feed slurry inlet. Means are also provided for the addition of diluent and a surfactant into the slurry to control relative permittivity and the electrophoretic mobility of the particles.

Cross flow electrofilter and method

DOEpatents

Gidaspow, Dimitri; Lee, Chang H.; Wasan, Darsh T.

1981-01-01

A filter for clarifying carbonaceous liquids containing finely divided solid particles of, for instance, unreacted coal, ash and other solids discharged from a coal liquefaction process is presented. The filter includes two passageways separated by a porous filter medium. In one preferred embodiment the filter medium is of tubular shape to form the first passageway and is enclosed within an outer housing to form the second passageway within the annulus. An electrode disposed in the first passageway, for instance along the tube axis, is connected to a source of high voltage for establishing an electric field between the electrode and the filter medium. Slurry feed flows through the first passageway tangentially to the surfaces of the filter medium and the electrode. Particles from the feed slurry are attracted to the electrode within the first passageway to prevent plugging of the porous filter medium while carbonaceous liquid filters into the second passageway for withdrawal. Concentrated slurry is discharged from the first passageway at an end opposite to the feed slurry inlet. Means are also provided for the addition of diluent and a surfactant into the slurry to control relative permittivity and the electrophoretic mobility of the particles.

Filtering coal-derived oil through a filter media precoated with particles partially solubilized by said oil

DOEpatents

Rodgers, Billy R.; Edwards, Michael S.

1977-01-01

Solids such as char, ash, and refractory organic compounds are removed from coal-derived liquids from coal liquefaction processes by the pressure precoat filtration method using particles of 85-350 mesh material selected from the group of bituminous coal, anthracite coal, lignite, and devolatilized coals as precoat materials and as body feed to the unfiltered coal-derived liquid.

Field Assessment of Enclosed Cab Filtration System Performance Using Particle Counting Measurements

PubMed Central

Organiscak, John A.; Cecala, Andrew B.; Noll, James D.

2015-01-01

Enclosed cab filtration systems are typically used on mobile mining equipment to reduce miners’ exposure to airborne dust generated during mining operations. The National Institute for Occupational Safety and Health (NIOSH) Office of Mine Safety and Health Research (OMSHR) has recently worked with a mining equipment manufacturer to examine a new cab filtration system design for underground industrial minerals equipment. This cab filtration system uses a combination of three particulate filters to reduce equipment operators’ exposure to dust and diesel particulates present in underground industrial mineral mines. NIOSH initially examined this cab filtration system using a two-instrument particle counting method at the equipment company’s manufacturing shop facility to assess several alternative filters. This cab filtration system design was further studied on several pieces of equipment during a two- to seven-month period at two underground limestone mines. The two-instrument particle counting method was used outside the underground mine at the end of the production shifts to regularly test the cabs’ long-term protection factor performance with particulates present in the ambient air. This particle counting method showed that three of the four cabs achieved protection factors greater than 1,000 during the field studies. The fourth cab did not perform at this level because it had a damaged filter in the system. The particle counting measurements of submicron particles present in the ambient air were shown to be a timely and useful quantification method in assessing cab performance during these field studies. PMID:23915268

Correction of pathlength amplification in the filter-pad technique for measurements of particulate absorption coefficient in the visible spectral region.

PubMed

Stramski, Dariusz; Reynolds, Rick A; Kaczmarek, Sławomir; Uitz, Julia; Zheng, Guangming

2015-08-01

Spectrophotometric measurement of particulate matter retained on filters is the most common and practical method for routine determination of the spectral light absorption coefficient of aquatic particles, a_p(λ), at high spectral resolution over a broad spectral range. The use of differing geometrical measurement configurations and large variations in the reported correction for pathlength amplification induced by the particle/filter matrix have hindered adoption of an established measurement protocol. We describe results of dedicated laboratory experiments with a diversity of particulate sample types to examine variation in the pathlength amplification factor for three filter measurement geometries; the filter in the transmittance configuration (T), the filter in the transmittance-reflectance configuration (T-R), and the filter placed inside an integrating sphere (IS). Relationships between optical density measured on suspensions (OD_s) and filters (OD_f) within the visible portion of the spectrum were evaluated for the formulation of pathlength amplification correction, with power functions providing the best functional representation of the relationship for all three geometries. Whereas the largest uncertainties occur in the T method, the IS method provided the least sample-to-sample variability and the smallest uncertainties in the relationship between OD_s and OD_f. For six different samples measured with 1 nm resolution within the light wavelength range from 400 to 700 nm, a median error of 7.1% is observed for predicted values of OD_s using the IS method. The relationships established for the three filter-pad methods are applicable to historical and ongoing measurements; for future work, the use of the IS method is recommended whenever feasible.

Measurements of Light Absorbing Particles on Tropical South American Glaciers

NASA Astrophysics Data System (ADS)

Schmitt, C. G.; All, J.; Schwarz, J. P.; Arnott, W. P.; Warthon, J.; Andrade, M.; Celestian, A. J.; Hoffmann, D.; Cole, R. J.; Lapham, E.; Horodyskyj, U. N.; Froyd, K. D.; Liao, J.

2014-12-01

Glaciers in the tropical Andes have been losing mass rapidly in recent decades. In addition to the documented increase in temperature, increases in light absorbing particulates deposited on glaciers could be contributing to the observed glacier loss. Here we present results of measurements of light absorbing particles from glaciers in Peru and Bolivia. Samples have been collected by American Climber Science Program volunteers and scientists at altitudes up to 6770 meters. Collected snow samples were melted and filtered in the field. A new inexpensive technique, the Light Absorption Heating Method (LAHM) has been developed for analysis of light absorbing particles collected on filters. Results from LAHM analysis are calibrated using filters with known amounts of fullerene soot, a common industrial surrogate for black carbon (BC). For snow samples collected at the same field location LAHM analysis and measurements from the Single Particle Soot Photometer (SP2) instrument are well correlated (r2 = 0.92). Co-located SP2 and LAHM filter analysis suggest that BC could be the dominant absorbing component of the light absorbing particles in some areas.

Models of filter-based particle light absorption measurements

NASA Astrophysics Data System (ADS)

Hamasha, Khadeejeh M.

Light absorption by aerosol is very important in the visible, near UN, and near I.R region of the electromagnetic spectrum. Aerosol particles in the atmosphere have a great influence on the flux of solar energy, and also impact health in a negative sense when they are breathed into lungs. Aerosol absorption measurements are usually performed by filter-based methods that are derived from the change in light transmission through a filter where particles have been deposited. These methods suffer from interference between light-absorbing and light-scattering aerosol components. The Aethalometer is the most commonly used filter-based instrument for aerosol light absorption measurement. This dissertation describes new understanding of aerosol light absorption obtained by the filter method. The theory uses a multiple scattering model for the combination of filter and particle optics. The theory is evaluated using Aethalometer data from laboratory and ambient measurements in comparison with photoacoustic measurements of aerosol light absorption. Two models were developed to calculate aerosol light absorption coefficients from the Aethalometer data, and were compared to the in-situ aerosol light absorption coefficients. The first is an approximate model and the second is a "full" model. In the approximate model two extreme cases of aerosol optics were used to develop a model-based calibration scheme for the 7-wavelength Aethalometer. These cases include those of very strong scattering aerosols (Ammonium sulfate sample) and very absorbing aerosols (kerosene soot sample). The exponential behavior of light absorption in the strong multiple scattering limit is shown to be the square root of the total absorption optical depth rather than linear with optical depth as is commonly assumed with Beer's law. 2-stream radiative transfer theory was used to develop the full model to calculate the aerosol light absorption coefficients from the Aethalometer data. This comprehensive model allows for studying very general cases of particles of various sizes embedded on arbitrary filter media. Application of this model to the Reno Aerosol Optics Study (Laboratory data) shows that the aerosol light absorption coefficients are about half of the Aethalometer attenuation coefficients, and there is a reasonable agreement between the model calculated absorption coefficients at 521 nm and the measured photoacoustic absorption coefficients at 532 nm. For ambient data obtained during the Las Vegas study, it shows that the model absorption coefficients at 521 nm are larger than the photoacoustic coefficients at 532 nm. Use of the 2-stream model shows that particle penetration depth into the filter has a strong influence on the interpretation of filter-based aerosol light absorption measurements. This is likely explanation for the difference found between model results for filter-based aerosol light absorption and those from photoacoustic measurements for ambient and laboratory aerosol.

Testing particle filters on convective scale dynamics

NASA Astrophysics Data System (ADS)

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 fluid dynamics. - Computers and Fluids, doi:10,1016/j.compfluid.2010.11.011, 1096 2011. Würsch, M. and G. C. Craig, 2013: A simple dynamical model of cumulus convection for data assimilation research, submitted to Met. Zeitschrift.

Reducing patients’ exposures to asthma and allergy triggers in their homes: an evaluation of effectiveness of grades of forced air ventilation filters

PubMed Central

Minegishi, Taeko; Allen, Joseph G.; McCarthy, John F.; Spengler, John D.; MacIntosh, David L.

2014-01-01

Objective Many interventions to reduce allergen levels in the home are recommended to asthma and allergy patients. One that is readily available and can be highly effective is the use of high performing filters in forced air ventilation systems. Methods We conducted a modeling analysis of the effectiveness of filter-based interventions in the home to reduce airborne asthma and allergy triggers. This work used “each pass removal efficiency” applied to health-relevant size fractions of particles to assess filter performance. We assessed effectiveness for key allergy and asthma triggers based on applicable particle sizes for cat allergen, indoor and outdoor sources of particles <2.5 µm in diameter (PM2.5), and airborne influenza and rhinovirus. Results Our analysis finds that higher performing filters can have significant impacts on indoor particle pollutant levels. Filters with removal efficiencies of >70% for cat dander particles, fine particulate matter (PM2.5) and respiratory virus can lower concentrations of those asthma triggers and allergens in indoor air of the home by >50%. Very high removal efficiency filters, such as those rated a 16 on the nationally recognized Minimum Efficiency Removal Value (MERV) rating system, tend to be only marginally more effective than MERV12 or 13 rated filters. Conclusions The results of this analysis indicate that use of a MERV12 or higher performing air filter in home ventilation systems can effectively reduce indoor levels of these common asthma and allergy triggers. These reductions in airborne allergens in turn may help reduce allergy and asthma symptoms, especially if employed in conjunction with other environmental management measures recommended for allergy and asthma patients. PMID:24555523

Colloidal Bandpass and Bandgap Filters

NASA Astrophysics Data System (ADS)

Yellen, Benjamin; Tahir, Mukarram; Ouyang, Yuyu; Nori, Franco

2013-03-01

Thermally or deterministically-driven transport of objects through asymmetric potential energy landscapes (ratchet-based motion) is of considerable interest as models for biological transport and as methods for controlling the flow of information, material, and energy. Here, we provide a general framework for implementing a colloidal bandpass filter, in which particles of a specific size range can be selectively transported through a periodic lattice, whereas larger or smaller particles are dynamically trapped in closed-orbits. Our approach is based on quasi-static (adiabatic) transition in a tunable potential energy landscape composed of a multi-frequency magnetic field input signal with the static field of a spatially-periodic magnetization. By tuning the phase shifts between the input signal and the relative forcing coefficients, large-sized particles may experience no local energy barriers, medium-sized particles experience only one local energy barrier, and small-sized particles experience two local energy barriers. The odd symmetry present in this system can be used to nudge the medium-sized particles along an open pathway, whereas the large or small beads remain trapped in a closed-orbit, leading to a bandpass filter, and vice versa for a bandgap filter. NSF CMMI - 0800173, Youth 100 Scholars Fund

Chemical, dimensional and morphological ultrafine particle characterization from a waste-to-energy plant

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

Buonanno, Giorgio, E-mail: buonanno@unicas.it; Stabile, Luca; Avino, Pasquale

2011-11-15

Highlights: > Particle size distributions and total concentrations measurement at the stack and before the fabric filter of an incinerator. > Chemical characterization of UFPs in terms of heavy metal concentration through a nuclear method. > Mineralogical investigation through a Transmission Electron Microscope equipped with an Energy Dispersive Spectrometer. > Heavy metal concentrations on UFPs as function of the boiling temperature. > Different mineralogical and morphological composition amongst samples collected before the fabric filter and at the stack. - Abstract: Waste combustion processes are responsible of particles and gaseous emissions. Referring to the particle emission, in the last years specificmore » attention was paid to ultrafine particles (UFPs, diameter less than 0.1 {mu}m), mainly emitted by combustion processes. In fact, recent findings of toxicological and epidemiological studies indicate that fine and ultrafine particles could represent a risk for health and environment. Therefore, it is necessary to quantify particle emissions from incinerators also to perform an exposure assessment for the human populations living in their surrounding areas. To these purposes, in the present work an experimental campaign aimed to monitor UFPs was carried out at the incineration plant in San Vittore del Lazio (Italy). Particle size distributions and total concentrations were measured both at the stack and before the fabric filter inlet in order to evaluate the removal efficiency of the filter in terms of UFPs. A chemical characterization of UFPs in terms of heavy metal concentration was performed through a nuclear method, i.e. Instrumental Neutron Activation Analysis (INAA), as well as a mineralogical investigation was carried out through a Transmission Electron Microscope (TEM) equipped with an Energy Dispersive Spectrometer (EDS) in order to evaluate shape, crystalline state and mineral compound of sampled particles. Maximum values of 2.7 x 10{sup 7} part. cm{sup -3} and 2.0 x 10{sup 3} part. cm{sup -3} were found, respectively, for number concentration before and after the fabric filter showing a very high efficiency in particle removing by the fabric filter. With regard to heavy metal concentrations, the elements with higher boiling temperature present higher concentrations at lower diameters showing a not complete evaporation in the combustion section and the consequent condensation of semi-volatile compounds on solid nuclei. In terms of mineralogical and morphological analysis, the most abundant compounds found in samples collected before the fabric filter are Na-K-Pb oxides followed by phyllosilicates, otherwise, different oxides of comparable abundance were detected in the samples collected at the stack.« less

Collection of biological and non-biological particles by new and used filters made from glass and electrostatically charged synthetic fibers.

PubMed

Raynor, P C; Kim, B G; Ramachandran, G; Strommen, M R; Horns, J H; Streifel, A J

2008-02-01

Synthetic filters made from fibers carrying electrostatic charges and fiberglass filters that do not carry electrostatic charges are both utilized commonly in heating, ventilating, and air-conditioning (HVAC) systems. The pressure drop and efficiency of a bank of fiberglass filters and a bank of electrostatically charged synthetic filters were measured repeatedly for 13 weeks in operating HVAC systems at a hospital. Additionally, the efficiency with which new and used fiberglass and synthetic filters collected culturable biological particles was measured in a test apparatus. Pressure drop measurements adjusted to equivalent flows indicated that the synthetic filters operated with a pressure drop less than half that of the fiberglass filters throughout the test. When measured using total ambient particles, synthetic filter efficiency decreased during the test period for all particle diameters. For particles 0.7-1.0 mum in diameter, efficiency decreased from 92% to 44%. It is hypothesized that this reduction in collection efficiency may be due to charge shielding. Efficiency did not change significantly for the fiberglass filters during the test period. However, when measured using culturable biological particles in the ambient air, efficiency was essentially the same for new filters and filters used for 13 weeks in the hospital for both the synthetic and fiberglass filters. It is hypothesized that the lack of efficiency reduction for culturable particles may be due to their having higher charge than non-biological particles, allowing them to overcome the effects of charge shielding. The type of particles requiring capture may be an important consideration when comparing the relative performance of electrostatically charged synthetic and fiberglass filters. Electrostatically charged synthetic filters with high initial efficiency can frequently replace traditional fiberglass filters with lower efficiency in HVAC systems because properly designed synthetic filters offer less resistance to air flow. Although the efficiency of charged synthetic filters at collecting non-biological particles declined substantially with use, the efficiency of these filters at collecting biological particles remained steady. These findings suggest that the merits of electrostatically charged synthetic HVAC filters relative to fiberglass filters may be more pronounced if collection of biological particles is of primary concern.

Toward standardized test methods to determine the effectiveness of filtration media against airborne nanoparticles

NASA Astrophysics Data System (ADS)

Wang, Jing; Tronville, Paolo

2014-06-01

The filtration of airborne nanoparticles is an important control technique as the environmental, health, and safety impacts of nanomaterials grow. A review of the literature shows that significant progress has been made on airborne nanoparticle filtration in the academic field in the recent years. We summarize the filtration mechanisms of fibrous and membrane filters; the air flow resistance and filter media figure of merit are discussed. Our review focuses on the air filtration test methods and instrumentation necessary to implement them; recent experimental studies are summarized accordingly. Two methods using monodisperse and polydisperse challenging aerosols, respectively, are discussed in detail. Our survey shows that the commercial instruments are already available for generating a large amount of nanoparticles, sizing, and quantifying them accurately. The commercial self-contained filter test systems provide the possibility of measurement for particles down to 15 nm. Current international standards dealing with efficiency test for filters and filter media focus on measurement of the minimum efficiency at the most penetrating particle size. The available knowledge and instruments provide a solid base for development of test methods to determine the effectiveness of filtration media against airborne nanoparticles down to single-digit nanometer range.

Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.

PubMed

Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D

2017-09-26

While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting mechanisms may be more than paid back by improved planning capacity. The robustness of the results on particle filter configuration in this case study suggests that it may be possible to formulate effective standard guidelines and regularized approaches for such techniques in particular epidemiological contexts. Most importantly, the work tentatively suggests potential for health decision makers to secure strong guidance when anticipating outbreak evolution for emerging infectious diseases by combining even very rough models with particle filtering method.

Influence of ventilation and filtration on indoor particle concentrations in urban office buildings

NASA Astrophysics Data System (ADS)

Quang, Tran Ngoc; He, Congrong; Morawska, Lidia; Knibbs, Luke D.

2013-11-01

This study aimed to quantify the efficiency of deep bag and electrostatic filters, and assess the influence of ventilation systems using these filters on indoor fine (<2.5 μm) and ultrafine particle concentrations in commercial office buildings. Measurements and modelling were conducted for different indoor and outdoor particle source scenarios at three office buildings in Brisbane, Australia. Overall, the in-situ efficiency, measured for particles in size ranges 6-3000 nm, of the deep bag filters ranged from 26.3 to 46.9% for the three buildings, while the in-situ efficiency of the electrostatic filter in one building was 60.2%. The highest PN and PM2.5 concentrations in one of the office buildings (up to 131% and 31% higher than the other two buildings, respectively) were due to the proximity of the building's HVAC air intakes to a nearby bus-only roadway, as well as its higher outdoor ventilation rate. The lowest PN and PM2.5 concentrations (up to 57% and 24% lower than the other two buildings, respectively) were measured in a building that utilised both outdoor and mixing air filters in its HVAC system. Indoor PN concentrations were strongly influenced by outdoor levels and were significantly higher during rush-hours (up to 41%) and nucleation events (up to 57%), compared to working-hours, for all three buildings. This is the first time that the influence of new particle formation on indoor particle concentrations has been identified and quantified. A dynamic model for indoor PN concentration, which performed adequately in this study also revealed that using mixing/outdoor air filters can significantly reduce indoor particle concentration in buildings where indoor air was strongly influenced by outdoor particle levels. This work provides a scientific basis for the selection and location of appropriate filters and outdoor air intakes, during the design of new, or upgrade of existing, building HVAC systems. The results also serve to provide a better understanding of indoor particle dynamics and behaviours under different ventilation and particle source scenarios, and highlight effective methods to reduce exposure to particles in commercial office buildings.

Scintillation Method of Analysis for Determination of Properties of Wear Particles in Lubricating Oils,

DTIC Science & Technology

1998-01-01

Scintillation Method of Analysis for Determination of Properties of Wear Particles in Lubricating Oils Andrey B. Alkhimov Applied Physics Insitute...lubricating oils; metrological properties ; scintillation spectral analysis; spectrometer; unit-to-unit diagnostics; wear particles. Introduction: In...filter. The use of air reduces the metrological properties of the method, but it saves the operators the trouble and expense of using argon and

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

NASA Technical Reports Server (NTRS)

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.

Tunable Passive Vibration Suppressor

NASA Technical Reports Server (NTRS)

Boechler, Nicholas (Inventor); Dillon, Robert Peter (Inventor); Daraio, Chiara (Inventor); Davis, Gregory L. (Inventor); Shapiro, Andrew A. (Inventor); Borgonia, John Paul C. (Inventor); Kahn, Daniel Louis (Inventor)

2016-01-01

An apparatus and method for vibration suppression using a granular particle chain. The granular particle chain is statically compressed and the end particles of the chain are attached to a payload and vibration source. The properties of the granular particles along with the amount of static compression are chosen to provide desired filtering of vibrations.

Influence of solid-liquid separation method parameters employed in soil leaching tests on apparent metal concentration.

PubMed

Imoto, Yukari; Yasutaka, Tetsuo; Someya, Masayuki; Higashino, Kazuo

2018-05-15

Soil leaching tests are commonly used to evaluate the leachability of hazardous materials, such as heavy metals, from the soil. Batch leaching tests often enhance soil colloidal mobility and may require solid-liquid separation procedures to remove excess soil particles. However, batch leaching test results depend on particles that can pass through a 0.45μm membrane filter and are influenced by test parameters such as centrifugal intensity and filtration volume per filter. To evaluate these parameters, we conducted batch leaching experiments using metal-contaminated soils and focused on the centrifugal intensity and filtration volume per filter used in solid-liquid separation methods currently employed in standard leaching tests. Our experiments showed that both centrifugal intensity and filtration volume per filter affected the reproducibility of batch leaching tests for some soil types. The results demonstrated that metal concentrations in the filtrates significantly differed according to the centrifugal intensity when it was 3000 g for 2h or less. Increased filtration volume per filter led to significant decreases in filtrate metal concentrations when filter cakes formed during filtration. Comparison of the filtration tests using 0.10 and 0.45μm membrane filters showed statistically significant differences in turbidity and metal concentration. These findings suggest that colloidal particles were not adequately removed from the extract and contributed substantially to the apparent metal concentrations in the leaching test of soil containing colloidal metals. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Tracking and Control of a Neutral Particle Beam Using Multiple Model Adaptive Meer Filter.

DTIC Science & Technology

1987-12-01

34 method incorporated by Zicker in 1983 [32]. Once the beam estimation problem had been solved, the problem of beam control was examined. Zicker conducted a...filter. Then, the methods applied by Meer, and later Zicker , to reduce the computational load of a simple Meer filter, will be presented. 2.5.1 Basic...number of possible methods to prune the hypothesis tree and chose the "Best Half Method" as the most viable (21). Zicker [323, applied the work of Weiss

A simple novel device for air sampling by electrokinetic capture

DOE PAGES

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra; ...

2015-12-27

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrodemore » assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.« less

A simple novel device for air sampling by electrokinetic capture

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

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrodemore » assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87%, with the reference filter taken as “gold standard.” Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. In conclusion, the performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.« less

A simple novel device for air sampling by electrokinetic capture.

PubMed

Gordon, Julian; Gandhi, Prasanthi; Shekhawat, Gajendra; Frazier, Angel; Hampton-Marcell, Jarrad; Gilbert, Jack A

2015-12-27

A variety of different sampling devices are currently available to acquire air samples for the study of the microbiome of the air. All have a degree of technical complexity that limits deployment. Here, we evaluate the use of a novel device, which has no technical complexity and is easily deployable. An air-cleaning device powered by electrokinetic propulsion has been adapted to provide a universal method for collecting samples of the aerobiome. Plasma-induced charge in aerosol particles causes propulsion to and capture on a counter-electrode. The flow of ions creates net bulk airflow, with no moving parts. A device and electrode assembly have been re-designed from air-cleaning technology to provide an average air flow of 120 lpm. This compares favorably with current air sampling devices based on physical air pumping. Capture efficiency was determined by comparison with a 0.4 μm polycarbonate reference filter, using fluorescent latex particles in a controlled environment chamber. Performance was compared with the same reference filter method in field studies in three different environments. For 23 common fungal species by quantitative polymerase chain reaction (qPCR), there was 100 % sensitivity and apparent specificity of 87 %, with the reference filter taken as "gold standard." Further, bacterial analysis of 16S RNA by amplicon sequencing showed equivalent community structure captured by the electrokinetic device and the reference filter. Unlike other current air sampling methods, capture of particles is determined by charge and so is not controlled by particle mass. We analyzed particle sizes captured from air, without regard to specific analyte by atomic force microscopy: particles at least as low as 100 nM could be captured from ambient air. This work introduces a very simple plug-and-play device that can sample air at a high-volume flow rate with no moving parts and collect particles down to the sub-micron range. The performance of the device is substantially equivalent to capture by pumping through a filter for microbiome analysis by quantitative PCR and amplicon sequencing.

A novel concept of dielectrophoretic engine oil filter

NASA Astrophysics Data System (ADS)

Khusid, Boris; Shen, Yueyang; Elele, Ezinwa

2011-11-01

A novel concept of an alternating current (AC) dielectrophoretic filter with a three-dimensional electrode array is presented. A filter is constructed by winding into layers around the core tube two sheets of woven metal wire-mesh with several sheets of woven insulating wire-mesh sandwiched in between. Contrary to conventional dielectrophoretic devices, the proposed design of electrodes generates a high-gradient field over a large working volume by applying several hundred volts at a standard frequency of 60 Hz. The operating principle of filtration is based on our recently developed method of AC dielectrophoretic gating for microfluidics. The filtration efficiency is expressed in terms of two non-dimensional parameters which describe the combined influence of the particle polarizability and size, the oil viscosity and flow rate, and the field gradient on the particle captivity. The proof-of-concept is tested by measuring the single-pass performance of two filters on positively polarized particles dispersed in engine oil: spherical glass beads, fused aluminum oxide powder, and silicon metal powder, all smaller than the mesh opening. The results obtained provide critical design guidelines for the development of a filter based on the retention capability of challenge particles. The work was supported in part by ONR and NSF.

Whole house particle removal and clean air delivery rates for in-duct and portable ventilation systems.

PubMed

Macintosh, David L; Myatt, Theodore A; Ludwig, Jerry F; Baker, Brian J; Suh, Helen H; Spengler, John D

2008-11-01

A novel method for determining whole house particle removal and clean air delivery rates attributable to central and portable ventilation/air cleaning systems is described. The method is used to characterize total and air-cleaner-specific particle removal rates during operation of four in-duct air cleaners and two portable air-cleaning devices in a fully instrumented test home. Operation of in-duct and portable air cleaners typically increased particle removal rates over the baseline rates determined in the absence of operating a central fan or an indoor air cleaner. Removal rates of 0.3- to 0.5-microm particles ranged from 1.5 hr(-1) during operation of an in-duct, 5-in. pleated media filter to 7.2 hr(-1) for an in-duct electrostatic air cleaner in comparison to a baseline rate of 0 hr(-1) when the air handler was operating without a filter. Removal rates for total particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass concentrations were 0.5 hr(-1) under baseline conditions, 0.5 hr(-1) during operation of three portable ionic air cleaners, 1 hr(-1) for an in-duct 1-in. media filter, 2.4 hr(-1) for a single high-efficiency particle arrestance (HEPA) portable air cleaner, 4.6 hr(-1) for an in-duct 5-in. media filter, 4.7 hr(-1) during operation of five portable HEPA filters, 6.1 hr(-1) for a conventional in-duct electronic air cleaner, and 7.5 hr(-1) for a high efficiency in-duct electrostatic air cleaner. Corresponding whole house clean air delivery rates for PM2.5 attributable to the air cleaner independent of losses within the central ventilation system ranged from 2 m3/min for the conventional media filter to 32 m3/min for the high efficiency in-duct electrostatic device. Except for the portable ionic air cleaner, the devices considered here increased particle removal indoors over baseline deposition rates.

Visualization of flow during cleaning process on a liquid nanofibrous filter

NASA Astrophysics Data System (ADS)

Bílek, P.

2017-10-01

This paper deals with visualization of flow during cleaning process on a nanofibrous filter. Cleaning of a filter is very important part of the filtration process which extends lifetime of the filter and improve filtration properties. Cleaning is carried out on flat-sheet filters, where particles are deposited on the filter surface and form a filtration cake. The cleaning process dislodges the deposited filtration cake, which is loose from the membrane surface to the retentate flow. The blocked pores in the filter are opened again and hydrodynamic properties are restored. The presented optical method enables to see flow behaviour in a thin laser sheet on the inlet side of a tested filter during the cleaning process. The local concentration of solid particles is possible to estimate and achieve new information about the cleaning process. In the article is described the cleaning process on nanofibrous membranes for waste water treatment. The hydrodynamic data were compared to the images of the cleaning process.

Probabilistic learning of nonlinear dynamical systems using sequential Monte Carlo

NASA Astrophysics Data System (ADS)

Schön, Thomas B.; Svensson, Andreas; Murray, Lawrence; Lindsten, Fredrik

2018-05-01

Probabilistic modeling provides the capability to represent and manipulate uncertainty in data, models, predictions and decisions. We are concerned with the problem of learning probabilistic models of dynamical systems from measured data. Specifically, we consider learning of probabilistic nonlinear state-space models. There is no closed-form solution available for this problem, implying that we are forced to use approximations. In this tutorial we will provide a self-contained introduction to one of the state-of-the-art methods-the particle Metropolis-Hastings algorithm-which has proven to offer a practical approximation. This is a Monte Carlo based method, where the particle filter is used to guide a Markov chain Monte Carlo method through the parameter space. One of the key merits of the particle Metropolis-Hastings algorithm is that it is guaranteed to converge to the "true solution" under mild assumptions, despite being based on a particle filter with only a finite number of particles. We will also provide a motivating numerical example illustrating the method using a modeling language tailored for sequential Monte Carlo methods. The intention of modeling languages of this kind is to open up the power of sophisticated Monte Carlo methods-including particle Metropolis-Hastings-to a large group of users without requiring them to know all the underlying mathematical details.

Lithium-ion battery state of health monitoring and remaining useful life prediction based on support vector regression-particle filter

NASA Astrophysics Data System (ADS)

Dong, Hancheng; Jin, Xiaoning; Lou, Yangbing; Wang, Changhong

2014-12-01

Lithium-ion batteries are used as the main power source in many electronic and electrical devices. In particular, with the growth in battery-powered electric vehicle development, the lithium-ion battery plays a critical role in the reliability of vehicle systems. In order to provide timely maintenance and replacement of battery systems, it is necessary to develop a reliable and accurate battery health diagnostic that takes a prognostic approach. Therefore, this paper focuses on two main methods to determine a battery's health: (1) Battery State-of-Health (SOH) monitoring and (2) Remaining Useful Life (RUL) prediction. Both of these are calculated by using a filter algorithm known as the Support Vector Regression-Particle Filter (SVR-PF). Models for battery SOH monitoring based on SVR-PF are developed with novel capacity degradation parameters introduced to determine battery health in real time. Moreover, the RUL prediction model is proposed, which is able to provide the RUL value and update the RUL probability distribution to the End-of-Life cycle. Results for both methods are presented, showing that the proposed SOH monitoring and RUL prediction methods have good performance and that the SVR-PF has better monitoring and prediction capability than the standard particle filter (PF).

Quantum-behaved particle swarm optimization for the synthesis of fibre Bragg gratings filter

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Sun, Yunxu; Yao, Yong; Tian, Jiajun; Cong, Shan

2011-12-01

A method based on the quantum-behaved particle swarm optimization algorithm is presented to design a bandpass filter of the fibre Bragg gratings. In contrast to the other optimization algorithms such as the genetic algorithm and particle swarm optimization algorithm, this method is simpler and easier to implement. To demonstrate the effectiveness of the QPSO algorithm, we consider a bandpass filter. With the parameters the half the bandwidth of the filter 0.05 nm, the Bragg wavelength 1550 nm, the grating length with 2cm is divided into 40 uniform sections and its index modulation is what should be optimized and whole feasible solution space is searched for the index modulation. After the index modulation profile is known for all the sections, the transfer matrix method is used to verify the final optimal index modulation by calculating the refection spectrum. The results show the group delay is less than 12ps in band and the calculated dispersion is relatively flat inside the passband. It is further found that the reflective spectrum has sidelobes around -30dB and the worst in-band dispersion value is less than 200ps/nm . In addition, for this design, it takes approximately several minutes to find the acceptable index modulation values with a notebook computer.

Filtering in Hybrid Dynamic Bayesian Networks

NASA Technical Reports Server (NTRS)

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).

Method of decontaminating a contaminated fluid by using photocatalytic particles

NASA Technical Reports Server (NTRS)

Cooper, Gerald (Inventor); Ratcliff, Matthew A. (Inventor)

1994-01-01

A system for decontaminating the contaminated fluid by using photocatalytic particles. The system includes a reactor tank for holding the contaminated fluid and the photocatalytic particles suspended in the contaminated fluid to form a slurry. Light irradiates the surface of the slurry, thereby activating the photocatalytic properties of the particles. The system also includes stirring blades for continuously agitating the irradiated fluid surface and for maintaining the particles in a suspended state within the fluid. The system also includes a cross flow filter for segregating the fluid (after decomposition) from the semiconductor powder. The cross flow filter is occasionally back flushed to remove any semiconductor powder that might have caked on the filter. The semiconductor powder may be recirculated back to the tank for reuse, or may be stored for future use. A series of such systems may be used to gradually decompose a chemical in the fluid. Preferably, the fluid is pretreated to remove certain metal ions which interfere with the photocatalytic process. Such pretreatment may be accomplished by dispersing semiconductor particles within the fluid, which adsorb ions or photodeposit the metal as the free metal or its insoluble oxide or hydroxide, and then removing the semiconductor particles together with the adsorbed metal ions/oxides/hydroxide/free metal from the fluid. A method of decontaminating a contaminated fluid is also disclosed.

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

NASA Astrophysics Data System (ADS)

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.

3D SAPIV particle field reconstruction method based on adaptive threshold.

PubMed

Qu, Xiangju; Song, Yang; Jin, Ying; Li, Zhenhua; Wang, Xuezhen; Guo, ZhenYan; Ji, Yunjing; He, Anzhi

2018-03-01

Particle image velocimetry (PIV) is a necessary flow field diagnostic technique that provides instantaneous velocimetry information non-intrusively. Three-dimensional (3D) PIV methods can supply the full understanding of a 3D structure, the complete stress tensor, and the vorticity vector in the complex flows. In synthetic aperture particle image velocimetry (SAPIV), the flow field can be measured with large particle intensities from the same direction by different cameras. During SAPIV particle reconstruction, particles are commonly reconstructed by manually setting a threshold to filter out unfocused particles in the refocused images. In this paper, the particle intensity distribution in refocused images is analyzed, and a SAPIV particle field reconstruction method based on an adaptive threshold is presented. By using the adaptive threshold to filter the 3D measurement volume integrally, the three-dimensional location information of the focused particles can be reconstructed. The cross correlations between images captured from cameras and images projected by the reconstructed particle field are calculated for different threshold values. The optimal threshold is determined by cubic curve fitting and is defined as the threshold value that causes the correlation coefficient to reach its maximum. The numerical simulation of a 16-camera array and a particle field at two adjacent time events quantitatively evaluates the performance of the proposed method. An experimental system consisting of a camera array of 16 cameras was used to reconstruct the four adjacent frames in a vortex flow field. The results show that the proposed reconstruction method can effectively reconstruct the 3D particle fields.

Method of and apparatus for measuring the mean concentration of thoron and/or radon in a gas mixture

DOEpatents

Lucas, Henry

1990-01-01

A method of and an apparatus for detecting and accurately measuring the mean concentrations of .sup.222 Rn and .sup.220 Tn in a gas mixture, such as the ambient atmosphere in a mine, is provided. The apparatus includes an alpha target member which defines at least one operative target surface and which is preferably fabricated from a single piece of an alpha particle sensitive material. At least one portion of the operative target surface is covered with an alpha particle filter. The uncovered and filter covered operative surface is exposed to the gas mixture containing the .sup.222 Rn and .sup.220 Tn. In the radioactive decay series of these isotopes the maximum kinetic energy emitted by the alpha decay of .sup.222 Rn is about 1.1 MeV less than the maximum kinetic energy emitted by the alpha decay of a .sup.220 Tn. The alpha particle filter has a predetermined mass per unit area of the covered portion of the operative target surface that prevents penetration of alpha particles which originate from .sup.222 Rn decay, but which allows passage therethrough of the maximum kinetic energy alpha particles from .sup.220 Tn decay. Thus, a count of the alpha particle tracks in the uncovered portion of the target member is proportional to the mean concentration of sum of .sup.222 Rn and .sup.220 Tn in the gas mixture, while the count of alpha tracks in the target member under the filter is proportional to the concentration of only the .sup.220 Tn in the gas mixture.

Particle size distribution of airborne Aspergillus fumigatus spores emitted from compost using membrane filtration

NASA Astrophysics Data System (ADS)

Deacon, L. J.; Pankhurst, L. J.; Drew, G. H.; Hayes, E. T.; Jackson, S.; Longhurst, P. J.; Longhurst, J. W. S.; Liu, J.; Pollard, S. J. T.; Tyrrel, S. F.

Information on the particle size distribution of bioaerosols emitted from open air composting operations is valuable in evaluating potential health impacts and is a requirement for improved dispersion simulation modelling. The membrane filter method was used to study the particle size distribution of Aspergillus fumigatus spores in air 50 m downwind of a green waste compost screening operation at a commercial facility. The highest concentrations (approximately 8 × 10 4 CFU m -3) of culturable spores were found on filters with pore diameters in the range 1-2 μm which suggests that the majority of spores are emitted as single cells. The findings were compared to published data collected using an Andersen sampler. Results were significantly correlated ( p < 0.01) indicating that the two methods are directly comparable across all particles sizes for Aspergillus spores.

Stochastic Adaptive Particle Beam Tracker Using Meer Filter Feedback.

DTIC Science & Technology

1986-12-01

breakthrough required in controlling the beam location. In 1983, Zicker (27] conducted a feasibility study of a simple proportional gain controller... Zicker synthesized his stochastic controller designs from a deterministic optimal LQ controller assuming full state feedback. An LQ controller is a...34Merge" Method 2.5 Simlifying the eer Filter a Zicker ran a performance analysis on the Meer filter and found the Meer filter virtually insensitive to

Absorption/Transmission Measurements of PSAP Particle-Laden Filters from the Biomass Burning Observation Project (BBOP) Field Campaign

PubMed Central

Presser, Cary; Nazarian, Ashot; Conny, Joseph M.; Chand, Duli; Sedlacek, Arthur; Hubbe, John M.

2017-01-01

Absorptivity measurements with a laser-heating approach, referred to as the laser-driven thermal reactor (LDTR), were carried out in the infrared and applied at ambient (laboratory) non-reacting conditions to particle-laden filters from a three-wavelength (visible) particle/soot absorption photometer (PSAP). The particles were obtained during the Biomass Burning Observation Project (BBOP) field campaign. The focus of this study was to determine the particle absorption coefficient from field-campaign filter samples using the LDTR approach, and compare results with other commercially available instrumentation (in this case with the PSAP, which has been compared with numerous other optical techniques). Advantages of the LDTR approach include 1) direct estimation of material absorption from temperature measurements (as opposed to resolving the difference between the measured reflection/scattering and transmission), 2) information on the filter optical properties, and 3) identification of the filter material effects on particle absorption (e.g., leading to particle absorption enhancement or shadowing). For measurements carried out under ambient conditions, the particle absorptivity is obtained with a thermocouple placed flush with the filter back surface and the laser probe beam impinging normal to the filter particle-laden surface. Thus, in principle one can employ a simple experimental arrangement to measure simultaneously both the transmissivity and absorptivity (at different discrete wavelengths) and ascertain the particle absorption coefficient. For this investigation, LDTR measurements were carried out with PSAP filters (pairs with both blank and exposed filters) from eight different days during the campaign, having relatively light but different particle loadings. The observed particles coating the filters were found to be carbonaceous (having broadband absorption characteristics). The LDTR absorption coefficient compared well with results from the PSAP. The analysis was also expanded to account for the filter fiber scattering on particle absorption in assessing particle absorption enhancement and shadowing effects. The results indicated that absorption enhancement effects were significant, and diminished with increased filter particle loading. PMID:28690360

Absorption/Transmission Measurements of PSAP Particle-Laden Filters from the Biomass Burning Observation Project (BBOP) Field Campaign.

PubMed

Presser, Cary; Nazarian, Ashot; Conny, Joseph M; Chand, Duli; Sedlacek, Arthur; Hubbe, John M

2017-01-01

Absorptivity measurements with a laser-heating approach, referred to as the laser-driven thermal reactor (LDTR), were carried out in the infrared and applied at ambient (laboratory) non-reacting conditions to particle-laden filters from a three-wavelength (visible) particle/soot absorption photometer (PSAP). The particles were obtained during the Biomass Burning Observation Project (BBOP) field campaign. The focus of this study was to determine the particle absorption coefficient from field-campaign filter samples using the LDTR approach, and compare results with other commercially available instrumentation (in this case with the PSAP, which has been compared with numerous other optical techniques). Advantages of the LDTR approach include 1) direct estimation of material absorption from temperature measurements (as opposed to resolving the difference between the measured reflection/scattering and transmission), 2) information on the filter optical properties, and 3) identification of the filter material effects on particle absorption (e.g., leading to particle absorption enhancement or shadowing). For measurements carried out under ambient conditions, the particle absorptivity is obtained with a thermocouple placed flush with the filter back surface and the laser probe beam impinging normal to the filter particle-laden surface. Thus, in principle one can employ a simple experimental arrangement to measure simultaneously both the transmissivity and absorptivity (at different discrete wavelengths) and ascertain the particle absorption coefficient. For this investigation, LDTR measurements were carried out with PSAP filters (pairs with both blank and exposed filters) from eight different days during the campaign, having relatively light but different particle loadings. The observed particles coating the filters were found to be carbonaceous (having broadband absorption characteristics). The LDTR absorption coefficient compared well with results from the PSAP. The analysis was also expanded to account for the filter fiber scattering on particle absorption in assessing particle absorption enhancement and shadowing effects. The results indicated that absorption enhancement effects were significant, and diminished with increased filter particle loading.

40 CFR 53.64 - Test procedure: Static fractionator test.

Code of Federal Regulations, 2012 CFR

2012-07-01

... particles of a given size reaching the sampler filter to the mass concentration of particles of the same.... Methods for generating aerosols shall be identical to those prescribed in § 53.62(c)(2). (2) Particle... (with or without an in-line mixing chamber). Validation particle size and quality shall be conducted at...

40 CFR 53.64 - Test procedure: Static fractionator test.

Code of Federal Regulations, 2013 CFR

2013-07-01

... particles of a given size reaching the sampler filter to the mass concentration of particles of the same.... Methods for generating aerosols shall be identical to those prescribed in § 53.62(c)(2). (2) Particle... (with or without an in-line mixing chamber). Validation particle size and quality shall be conducted at...

40 CFR 53.64 - Test procedure: Static fractionator test.

Code of Federal Regulations, 2014 CFR

2014-07-01

... particles of a given size reaching the sampler filter to the mass concentration of particles of the same.... Methods for generating aerosols shall be identical to those prescribed in § 53.62(c)(2). (2) Particle... (with or without an in-line mixing chamber). Validation particle size and quality shall be conducted at...

Tracking Algorithm of Multiple Pedestrians Based on Particle Filters in Video Sequences

PubMed Central

Liu, Yun; Wang, Chuanxu; Zhang, Shujun; Cui, Xuehong

2016-01-01

Pedestrian tracking is a critical problem in the field of computer vision. Particle filters have been proven to be very useful in pedestrian tracking for nonlinear and non-Gaussian estimation problems. However, pedestrian tracking in complex environment is still facing many problems due to changes of pedestrian postures and scale, moving background, mutual occlusion, and presence of pedestrian. To surmount these difficulties, this paper presents tracking algorithm of multiple pedestrians based on particle filters in video sequences. The algorithm acquires confidence value of the object and the background through extracting a priori knowledge thus to achieve multipedestrian detection; it adopts color and texture features into particle filter to get better observation results and then automatically adjusts weight value of each feature according to current tracking environment. During the process of tracking, the algorithm processes severe occlusion condition to prevent drift and loss phenomena caused by object occlusion and associates detection results with particle state to propose discriminated method for object disappearance and emergence thus to achieve robust tracking of multiple pedestrians. Experimental verification and analysis in video sequences demonstrate that proposed algorithm improves the tracking performance and has better tracking results. PMID:27847514

Self absorption of alpha and beta particles in a fiberglass filter.

PubMed

Luetzelschwab, J W; Storey, C; Zraly, K; Dussinger, D

2000-10-01

Environmental air sampling uses fiberglass filters to collect particulate matter from the air and then a gas flow detector to measure the alpha and beta activity on the filter. When counted, the filter is located close to the detector so the alpha and beta particles emerging from the filter travel toward the detector at angles ranging from zero to nearly 90 degrees to the normal to the filter surface. The particles at small angles can readily pass through the filter, but particles at large angles pass through a significant amount of filter material and can be totally absorbed. As a result, counting losses can be great. For 4 MeV alpha particles, the filter used in this experiment absorbs 43% of the alpha particles; for 7.5 MeV alphas, the absorption is 13%. The measured beta activities also can have significant counting losses. Beta particles with maximum energies of 0.2 and 2.0 MeV have absorptions of 44 and 2%, respectively.

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

PubMed

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 < 0.05), raising a concern about applicability of the N95 filters performance obtained with the NaCl aerosol challenge to protection against combustion particles. Aerosol type, inhalation flow rate and particle size were significant (p < 0.05) factors affecting the performance of the N95 FFR filter. In contrast to N95 filters, the penetration of 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.

Description of gas/particle sorption kinetics with an intraparticle diffusion model: Desorption experiments

USGS Publications Warehouse

Rounds, S.A.; Tiffany, B.A.; Pankow, J.F.

1993-01-01

Aerosol particles from a highway tunnel were collected on a Teflon membrane filter (TMF) using standard techniques. Sorbed organic compounds were then desorbed for 28 days by passing clean nitrogen through the filter. Volatile n-alkanes and polycyclic aromatic hydrocarbons (PAHs) were liberated from the filter quickly; only a small fraction of the less volatile ra-alkanes and PAHs were desorbed. A nonlinear least-squares method was used to fit an intraparticle diffusion model to the experimental data. Two fitting parameters were used: the gas/particle partition coefficient (Kp and an effective intraparticle diffusion coefficient (Oeff). Optimized values of Kp are in agreement with previously reported values. The slope of a correlation between the fitted values of Deff and Kp agrees well with theory, but the absolute values of Deff are a factor of ???106 smaller than predicted for sorption-retarded, gaseous diffusion. Slow transport through an organic or solid phase within the particles or preferential flow through the bed of particulate matter on the filter might be the cause of these very small effective diffusion coefficients. ?? 1993 American Chemical Society.

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

NASA Astrophysics Data System (ADS)

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.

Particle Filtering with Region-based Matching for Tracking of Partially Occluded and Scaled Targets*

PubMed Central

Nakhmani, Arie; Tannenbaum, Allen

2012-01-01

Visual tracking of arbitrary targets in clutter is important for a wide range of military and civilian applications. We propose a general framework for the tracking of scaled and partially occluded targets, which do not necessarily have prominent features. The algorithm proposed in the present paper utilizes a modified normalized cross-correlation as the likelihood for a particle filter. The algorithm divides the template, selected by the user in the first video frame, into numerous patches. The matching process of these patches by particle filtering allows one to handle the target’s occlusions and scaling. Experimental results with fixed rectangular templates show that the method is reliable for videos with nonstationary, noisy, and cluttered background, and provides accurate trajectories in cases of target translation, scaling, and occlusion. PMID:22506088

Tracking of Ball and Players in Beach Volleyball Videos

PubMed Central

Gomez, Gabriel; Herrera López, Patricia; Link, Daniel; Eskofier, Bjoern

2014-01-01

This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points. PMID:25426936

Developing particulate thin filter using coconut fiber for motor vehicle emission

NASA Astrophysics Data System (ADS)

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.

A regularized vortex-particle mesh method for large eddy simulation

NASA Astrophysics Data System (ADS)

Spietz, H. J.; Walther, J. H.; Hejlesen, M. M.

2017-11-01

We present recent developments of the remeshed vortex particle-mesh method for simulating incompressible fluid flow. The presented method relies on a parallel higher-order FFT based solver for the Poisson equation. Arbitrary high order is achieved through regularization of singular Green's function solutions to the Poisson equation and recently we have derived novel high order solutions for a mixture of open and periodic domains. With this approach the simulated variables may formally be viewed as the approximate solution to the filtered Navier Stokes equations, hence we use the method for Large Eddy Simulation by including a dynamic subfilter-scale model based on test-filters compatible with the aforementioned regularization functions. Further the subfilter-scale model uses Lagrangian averaging, which is a natural candidate in light of the Lagrangian nature of vortex particle methods. A multiresolution variation of the method is applied to simulate the benchmark problem of the flow past a square cylinder at Re = 22000 and the obtained results are compared to results from the literature.

Assessment of the capacity of vehicle cabin air inlet filters to reduce diesel exhaust-induced symptoms in human volunteers

PubMed Central

2014-01-01

Background Exposure to particulate matter (PM) air pollution especially derived from traffic is associated with increases in cardiorespiratory morbidity and mortality. In this study, we evaluated the ability of novel vehicle cabin air inlet filters to reduce diesel exhaust (DE)-induced symptoms and markers of inflammation in human subjects. Methods Thirty healthy subjects participated in a randomized double-blind controlled crossover study where they were exposed to filtered air, unfiltered DE and DE filtered through two selected particle filters, one with and one without active charcoal. Exposures lasted for one hour. Symptoms were assessed before and during exposures and lung function was measured before and after each exposure, with inflammation assessed in peripheral blood five hours after exposures. In parallel, PM were collected from unfiltered and filtered DE and assessed for their capacity to drive damaging oxidation reactions in a cell-free model, or promote inflammation in A549 cells. Results The standard particle filter employed in this study reduced PM10 mass concentrations within the exposure chamber by 46%, further reduced to 74% by the inclusion of an active charcoal component. In addition use of the active charcoal filter was associated by a 75% and 50% reduction in NO2 and hydrocarbon concentrations, respectively. As expected, subjects reported more subjective symptoms after exposure to unfiltered DE compared to filtered air, which was significantly reduced by the filter with an active charcoal component. There were no significant changes in lung function after exposures. Similarly diesel exhaust did not elicit significant increases in any of the inflammatory markers examined in the peripheral blood samples 5 hour post-exposure. Whilst the filters reduced chamber particle concentrations, the oxidative activity of the particles themselves, did not change following filtration with either filter. In contrast, diesel exhaust PM passed through the active charcoal combination filter appeared less inflammatory to A549 cells. Conclusions A cabin air inlet particle filter including an active charcoal component was highly effective in reducing both DE particulate and gaseous components, with reduced exhaust-induced symptoms in healthy volunteers. These data demonstrate the effectiveness of cabin filters to protect subjects travelling in vehicles from diesel exhaust emissions. PMID:24621126

A comparison of two nano-sized particle air filtration tests in the diameter range of 10 to 400 nanometers

NASA Astrophysics Data System (ADS)

Japuntich, Daniel A.; Franklin, Luke M.; Pui, David Y.; Kuehn, Thomas H.; Kim, Seong Chan; Viner, Andrew S.

2007-01-01

Two different air filter test methodologies are discussed and compared for challenges in the nano-sized particle range of 10-400 nm. Included in the discussion are test procedure development, factors affecting variability and comparisons between results from the tests. One test system which gives a discrete penetration for a given particle size is the TSI 8160 Automated Filter tester (updated and commercially available now as the TSI 3160) manufactured by the TSI, Inc., Shoreview, MN. Another filter test system was developed utilizing a Scanning Mobility Particle Sizer (SMPS) to sample the particle size distributions downstream and upstream of an air filter to obtain a continuous percent filter penetration versus particle size curve. Filtration test results are shown for fiberglass filter paper of intermediate filtration efficiency. Test variables affecting the results of the TSI 8160 for NaCl and dioctyl phthalate (DOP) particles are discussed, including condensation particle counter stability and the sizing of the selected particle challenges. Filter testing using a TSI 3936 SMPS sampling upstream and downstream of a filter is also shown with a discussion of test variables and the need for proper SMPS volume purging and filter penetration correction procedure. For both tests, the penetration versus particle size curves for the filter media studied follow the theoretical Brownian capture model of decreasing penetration with decreasing particle diameter down to 10 nm with no deviation. From these findings, the authors can say with reasonable confidence that there is no evidence of particle thermal rebound in the size range.

Modeling water and sediment trapping by vegetated filters using vfsmod: comparing methods for estimating infiltration parameters

Treesearch

Amanda L. Fox; Dean E. Eisenhauer; Michael G. Dosskey

2005-01-01

Vegetated filters (buffers) are used to intercept overland runoff and reduce sediment and other contaminant loads to streams (Dosskey, 2001). Filters function by reducing runoff velocity and volume, thus enhancing sedimentation and infiltration. lnfiltration is the main mechanism for soluble contaminant removal, but it also plays a role in suspended particle removal....

Vapor purification with self-cleaning filter

DOEpatents

Josephson, Gary B.; Heath, William O.; Aardahl, Christopher L.

2003-12-09

A vapor filtration device including a first electrode, a second electrode, and a filter between the first and second electrodes is disclosed. The filter is formed of dielectric material and the device is operated by applying a first electric potential between the electrodes to polarize the dielectric material such that upon passing a vapor stream through the filter, particles from the vapor stream are deposited onto the filter. After depositing the particles a second higher voltage is applied between the electrodes to form a nonthermal plasma around the filter to vaporize the collected particles thereby cleaning the filter. The filter can be a packed bed or serpentine filter mat, and an optional upstream corona wire can be utilized to charge airborne particles prior to their deposition on the filter.

Evaluation of methods for measuring particulate matter emissions from gas turbines.

PubMed

Petzold, Andreas; Marsh, Richard; Johnson, Mark; Miller, Michael; Sevcenco, Yura; Delhaye, David; Ibrahim, Amir; Williams, Paul; Bauer, Heidi; Crayford, Andrew; Bachalo, William D; Raper, David

2011-04-15

The project SAMPLE evaluated methods for measuring particle properties in the exhaust of aircraft engines with respect to the development of standardized operation procedures for particulate matter measurement in aviation industry. Filter-based off-line mass methods included gravimetry and chemical analysis of carbonaceous species by combustion methods. Online mass methods were based on light absorption measurement or used size distribution measurements obtained from an electrical mobility analyzer approach. Number concentrations were determined using different condensation particle counters (CPC). Total mass from filter-based methods balanced gravimetric mass within 8% error. Carbonaceous matter accounted for 70% of gravimetric mass while the remaining 30% were attributed to hydrated sulfate and noncarbonaceous organic matter fractions. Online methods were closely correlated over the entire range of emission levels studied in the tests. Elemental carbon from combustion methods and black carbon from optical methods deviated by maximum 5% with respect to mass for low to medium emission levels, whereas for high emission levels a systematic deviation between online methods and filter based methods was found which is attributed to sampling effects. CPC based instruments proved highly reproducible for number concentration measurements with a maximum interinstrument standard deviation of 7.5%.

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

PubMed

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.

Blended particle filters for large-dimensional chaotic dynamical systems

PubMed Central

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

An improved design method based on polyphase components for digital FIR filters

NASA Astrophysics Data System (ADS)

Kumar, A.; Kuldeep, B.; Singh, G. K.; Lee, Heung No

2017-11-01

This paper presents an efficient design of digital finite impulse response (FIR) filter, based on polyphase components and swarm optimisation techniques (SOTs). For this purpose, the design problem is formulated as mean square error between the actual response and ideal response in frequency domain using polyphase components of a prototype filter. To achieve more precise frequency response at some specified frequency, fractional derivative constraints (FDCs) have been applied, and optimal FDCs are computed using SOTs such as cuckoo search and modified cuckoo search algorithms. A comparative study of well-proved swarm optimisation, called particle swarm optimisation and artificial bee colony algorithm is made. The excellence of proposed method is evaluated using several important attributes of a filter. Comparative study evidences the excellence of proposed method for effective design of FIR filter.

Method and apparatus for a combination moving bed thermal treatment reactor and moving bed filter

DOEpatents

Badger, Phillip C.; Dunn, Jr., Kenneth J.

2015-09-01

A moving bed gasification/thermal treatment reactor includes a geometry in which moving bed reactor particles serve as both a moving bed filter and a heat carrier to provide thermal energy for thermal treatment reactions, such that the moving bed filter and the heat carrier are one and the same to remove solid particulates or droplets generated by thermal treatment processes or injected into the moving bed filter from other sources.

Filter Media Tests Under Simulated Martian Atmospheric Conditions

NASA Technical Reports Server (NTRS)

Agui, Juan H.

2016-01-01

Human exploration of Mars will require the optimal utilization of planetary resources. One of its abundant resources is the Martian atmosphere that can be harvested through filtration and chemical processes that purify and separate it into its gaseous and elemental constituents. Effective filtration needs to be part of the suite of resource utilization technologies. A unique testing platform is being used which provides the relevant operational and instrumental capabilities to test articles under the proper simulated Martian conditions. A series of tests were conducted to assess the performance of filter media. Light sheet imaging of the particle flow provided a means of detecting and quantifying particle concentrations to determine capturing efficiencies. The media's efficiency was also evaluated by gravimetric means through a by-layer filter media configuration. These tests will help to establish techniques and methods for measuring capturing efficiency and arrestance of conventional fibrous filter media. This paper will describe initial test results on different filter media.

Identifying, counting, and characterizing superfine activated-carbon particles remaining after coagulation, sedimentation, and sand filtration.

PubMed

Nakazawa, Yoshifumi; Matsui, Yoshihiko; Hanamura, Yusuke; Shinno, Koki; Shirasaki, Nobutaka; Matsushita, Taku

2018-07-01

Superfine powdered activated carbon (SPAC; particle diameter ∼1 μm) has greater adsorptivity for organic molecules than conventionally sized powdered activated carbon (PAC). Although SPAC is currently used in the pretreatment to membrane filtration at drinking water purification plants, it is not used in conventional water treatment consisting of coagulation-flocculation, sedimentation, and rapid sand filtration (CSF), because it is unclear whether CSF can adequately remove SPAC from the water. In this study, we therefore investigated the residual SPAC particles in water after CSF treatment. First, we developed a method to detect and quantify trace concentration of carbon particles in the sand filtrate. This method consisted of 1) sampling particles with a membrane filter and then 2) using image analysis software to manipulate a photomicrograph of the filter so that black spots with a diameter >0.2 μm (considered to be carbon particles) could be visualized. Use of this method revealed that CSF removed a very high percentage of SPAC: approximately 5-log in terms of particle number concentrations and approximately 6-log in terms of particle volume concentrations. When waters containing 7.5-mg/L SPAC and 30-mg/L PAC, concentrations that achieved the same adsorption performance, were treated, the removal rate of SPAC was somewhat superior to that of PAC, and the residual particle number concentrations for SPAC and PAC were at the same low level (100-200 particles/mL). Together, these results suggest that SPAC can be used in place of PAC in CSF treatment without compromising the quality of the filtered water in terms of particulate matter contamination. However, it should be noted that the activated carbon particles after sand filtration were smaller in terms of particle size and were charge-neutralized to a lesser extent than the activated carbon particles before sand filtration. Therefore, the tendency of small particles to escape in the filtrate would appear to be related to the fact that their small size leads to a low destabilization rate during the coagulation process and a low collision rate during the flocculation and filtration processes. Copyright © 2018 Elsevier Ltd. All rights reserved.

COMPUTATIONS ON THE PERFORMANCE OF PARTICLE FILTERS AND ELECTRONIC AIR CLEANERS

EPA Science Inventory

The paper discusses computations on the performance of particle filters and electronic air cleaners (EACs). The collection efficiency of particle filters and ACs is calculable if certain factors can be assumed or calibrated. For fibrous particulate filters, measurement of colle...

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

NASA Astrophysics Data System (ADS)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

NASA Astrophysics Data System (ADS)

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-03-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy.

A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red

PubMed Central

Maes, Thomas; Jessop, Rebecca; Wellner, Nikolaus; Haupt, Karsten; Mayes, Andrew G.

2017-01-01

A new approach is presented for analysis of microplastics in environmental samples, based on selective fluorescent staining using Nile Red (NR), followed by density-based extraction and filtration. The dye adsorbs onto plastic surfaces and renders them fluorescent when irradiated with blue light. Fluorescence emission is detected using simple photography through an orange filter. Image-analysis allows fluorescent particles to be identified and counted. Magnified images can be recorded and tiled to cover the whole filter area, allowing particles down to a few micrometres to be detected. The solvatochromic nature of Nile Red also offers the possibility of plastic categorisation based on surface polarity characteristics of identified particles. This article details the development of this staining method and its initial cross-validation by comparison with infrared (IR) microscopy. Microplastics of different sizes could be detected and counted in marine sediment samples. The fluorescence staining identified the same particles as those found by scanning a filter area with IR-microscopy. PMID:28300146

Particles in a karstic spring, Swabian Alb: Physicochemical and hydraulic effects during a snow melt event.

NASA Astrophysics Data System (ADS)

Schiperski, Ferry; Zirlewagen, Johannes; Hillebrand, Olav; Scheytt, Traugott; Licha, Tobias

2013-04-01

The studied karst spring 'Gallusquelle' is located on the Swabian Alb in Southwest Germany. The catchment area of the 'Gallusquelle' measures about 45 km². An average annual discharge of 0.5 m³/s serves drinking water to about 40,000 people via a waterworks. The study is part of the research project 'AGRO' (www.projekt-agro.de). The main objective of the project 'AGRO' is to develop a tool for the process-based risk management of micropollutants and pathogens in rural karst aquifers on catchment scale. As particle related transport could play an important role for micropollutants and pathogens, the characterization of particles in the spring water is one focus of this work. Furthermore we will attempt to correlate physicochemical parameters with the characteristics of particles in the spring water in order to enhance the knowledge of the transport mechanisms within the karst aquifer. For the measurement of the particle concentration and the particle size distribution the CIS 1 (GALAI) was used. The system works in a range of 0.5 to 150 µm with a resolution of at least 0.5 µm. The measurement is based on time-of-transition method using a laser beam. The turbidity was measured with an ULTRATURB PLUS (DR.LANGE) and a Fluorometer (GGUN-FL30, ALBILLIA), both working with scattering light method. To verify these measurements we used a portable turbidimeter (2100P IS PORTABLE TURBIDIMETER, HACH) working with the ratio of the signals from the scattered and the transmitted light. Temperature and electrical conductivity where also measured with the GGUN-FL30, whereby the electrical conductivity was verified with a portable multimeter (HQ 40D, HACH). Discharge, pH, water hardness, anion- and cation concentration, total organic carbon (TOC) and dissolved organic carbon (DOC) were also determined. To characterize the particles, the spring water was filtered onsite and the filter cake was analyzed in the laboratory. For SEM (scanning electron microscopy) including EDAX (energy dispersive X-ray spectroscopy) the water was filtered through PC membrane filters (∅=25mm) using a polycarbonate syringe. For X-ray diffraction the water was filtered through CA membrane filters (∅=142 mm) using a stainless steel pressure holder and a peristaltic pump. Both filters had an average pore size of 0.45 µm. Also we have analyzed sediments that where collected downstream of the online measurements and in the raw water tank of a waterworks that is located about 250 m downstream of the spring. During an average discharge the turbidity and the number of particles are around the limit of detection. Both increase with increasing discharge while the average particle size does not increase until a considerably higher-than-average discharge is reached. Particles in the size range of 0.5 - 2.0 µm display the main numeric amount (70 - 100 %) of the measurable particles under present discharge conditions. Only under high discharge conditions particles sizes > 5 µm increase significantly. Particles > 20 µm are rare during the whole period of measurement. In contrast to other works we include mineralogical studies of the particles in the spring water. Thus we can examine the relevance of mineralogical properties of the particles for the transport of micropollutants. Actual results of XRD analyses indicate that calcite, quartz and clay minerals dominate the turbidity. EDAX analyses with SEM confirm these measurements.

Continuous flow dielectrophoretic particle concentrator

DOEpatents

Cummings, Eric B [Livermore, CA

2007-04-17

A continuous-flow filter/concentrator for separating and/or concentrating particles in a fluid is disclosed. The filter is a three-port device an inlet port, an filter port and a concentrate port. The filter separates particles into two streams by the ratio of their dielectrophoretic mobility to their electrokinetic, advective, or diffusive mobility if the dominant transport mechanism is electrokinesis, advection, or diffusion, respectively.Also disclosed is a device for separating and/or concentrating particles by dielectrophoretic trapping of the particles.

Assessment of sub-grid scale dispersion closure with regularized deconvolution method in a particle-laden turbulent jet

NASA Astrophysics Data System (ADS)

Wang, Qing; Zhao, Xinyu; Ihme, Matthias

2017-11-01

Particle-laden turbulent flows are important in numerous industrial applications, such as spray combustion engines, solar energy collectors etc. It is of interests to study this type of flows numerically, especially using large-eddy simulations (LES). However, capturing the turbulence-particle interaction in LES remains challenging due to the insufficient representation of the effect of sub-grid scale (SGS) dispersion. In the present work, a closure technique for the SGS dispersion using regularized deconvolution method (RDM) is assessed. RDM was proposed as the closure for the SGS dispersion in a counterflow spray that is studied numerically using finite difference method on a structured mesh. A presumed form of LES filter is used in the simulations. In the present study, this technique has been extended to finite volume method with an unstructured mesh, where no presumption on the filter form is required. The method is applied to a series of particle-laden turbulent jets. Parametric analyses of the model performance are conducted for flows with different Stokes numbers and Reynolds numbers. The results from LES will be compared against experiments and direct numerical simulations (DNS).

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

NASA Astrophysics Data System (ADS)

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.

System and Apparatus for Filtering Particles

NASA Technical Reports Server (NTRS)

Agui, Juan H. (Inventor); Vijayakumar, Rajagopal (Inventor)

2015-01-01

A modular pre-filtration apparatus may be beneficial to extend the life of a filter. The apparatus may include an impactor that can collect a first set of particles in the air, and a scroll filter that can collect a second set of particles in the air. A filter may follow the pre-filtration apparatus, thus causing the life of the filter to be increased.

Wet particle source identification and reduction using a new filter cleaning process

NASA Astrophysics Data System (ADS)

Umeda, Toru; Morita, Akihiko; Shimizu, Hideki; Tsuzuki, Shuichi

2014-03-01

Wet particle reduction during filter installation and start-up aligns closely with initiatives to reduce both chemical consumption and preventative maintenance time. The present study focuses on the effects of filter materials cleanliness on wet particle defectivity through evaluation of filters that have been treated with a new enhanced cleaning process focused on organic compounds reduction. Little difference in filter performance is observed between the two filter types at a size detection threshold of 60 nm, while clear differences are observed at that of 26 nm. It can be suggested that organic compounds can be identified as a potential source of wet particles. Pall recommends filters that have been treated with the special cleaning process for applications with a critical defect size of less than 60 nm. Standard filter products are capable to satisfy wet particle defect performance criteria in less critical lithography applications.

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

NASA Astrophysics Data System (ADS)

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.

Final Report for Geometric Observers and Particle Filtering for Controlled Active Vision

DTIC Science & Technology

2016-12-15

code) 15-12-2016 Final Report 01Sep06 - 09May11 Final Report for Geometric Observers & Particle Filtering for Controlled Active Vision 49414-NS.1Allen...Observers and Particle Filtering for Controlled Active Vision by Allen R. Tannenbaum School of Electrical and Computer Engineering Georgia Institute of...7 2.2.4 Conformal Area Minimizing Flows . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Particle Filters

Effects of Particle Filters and Accelerated Engine Replacement on Heavy-Duty Diesel Vehicle Emissions of Black Carbon, Nitrogen Oxides, and Ultrafine Particles

NASA Astrophysics Data System (ADS)

Kirchstetter, T.; Preble, C.; Dallmann, T. R.; DeMartini, S. J.; Tang, N. W.; Kreisberg, N. M.; Hering, S. V.; Harley, R. A.

2013-12-01

Diesel particle filters have become widely used in the United States since the introduction in 2007 of a more stringent exhaust particulate matter emission standard for new heavy-duty diesel vehicle engines. California has instituted additional regulations requiring retrofit or replacement of older in-use engines to accelerate emission reductions and air quality improvements. This presentation summarizes pollutant emission changes measured over several field campaigns at the Port of Oakland in the San Francisco Bay Area associated with diesel particulate filter use and accelerated modernization of the heavy-duty truck fleet. Pollutants in the exhaust plumes of hundreds of heavy-duty trucks en route to the Port were measured in 2009, 2010, 2011, and 2013. Ultrafine particle number, black carbon (BC), nitrogen oxides (NOx), and nitrogen dioxide (NO2) concentrations were measured at a frequency ≤ 1 Hz and normalized to measured carbon dioxide concentrations to quantify fuel-based emission factors (grams of pollutant emitted per kilogram of diesel consumed). The size distribution of particles in truck exhaust plumes was also measured at 1 Hz. In the two most recent campaigns, emissions were linked on a truck-by-truck basis to installed emission control equipment via the matching of transcribed license plates to a Port truck database. Accelerated replacement of older engines with newer engines and retrofit of trucks with diesel particle filters reduced fleet-average emissions of BC and NOx. Preliminary results from the two most recent field campaigns indicate that trucks without diesel particle filters emit 4 times more BC than filter-equipped trucks. Diesel particle filters increase emissions of NO2, however, and filter-equipped trucks have NO2/NOx ratios that are 4 to 7 times greater than trucks without filters. Preliminary findings related to particle size distribution indicate that (a) most trucks emitted particles characterized by a single mode of approximately 100 nm in diameter and (b) new trucks originally equipped with diesel particle filters were 5 to 6 times more likely than filter-retrofitted trucks and trucks without filters to emit particles characterized by a single mode in the range of 10 to 30 nm in diameter.

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

NASA Astrophysics Data System (ADS)

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.

Dynamic state estimation assisted power system monitoring and protection

NASA Astrophysics Data System (ADS)

Cui, Yinan

The advent of phasor measurement units (PMUs) has unlocked several novel methods to monitor, control, and protect bulk electric power systems. This thesis introduces the concept of "Dynamic State Estimation" (DSE), aided by PMUs, for wide-area monitoring and protection of power systems. Unlike traditional State Estimation where algebraic variables are estimated from system measurements, DSE refers to a process to estimate the dynamic states associated with synchronous generators. This thesis first establishes the viability of using particle filtering as a technique to perform DSE in power systems. The utility of DSE for protection and wide-area monitoring are then shown as potential novel applications. The work is presented as a collection of several journal and conference papers. In the first paper, we present a particle filtering approach to dynamically estimate the states of a synchronous generator in a multi-machine setting considering the excitation and prime mover control systems. The second paper proposes an improved out-of-step detection method for generators by means of angular difference. The generator's rotor angle is estimated with a particle filter-based dynamic state estimator and the angular separation is then calculated by combining the raw local phasor measurements with this estimate. The third paper introduces a particle filter-based dual estimation method for tracking the dynamic states of a synchronous generator. It considers the situation where the field voltage measurements are not readily available. The particle filter is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. The fourth paper proposes a novel framework for event detection based on energy functions. The key idea is that any event in the system will leave a signature in WAMS data-sets. It is shown that signatures for four broad classes of disturbance events are buried in the components that constitute the energy function for the system. This establishes a direct correspondence (or mapping) between an event and certain component(s) of the energy function. The last paper considers the dynamic latency effect when the measurements and estimated dynamics are transmitted from remote ends to a centralized location through the networks.

A method for monitoring mass concentration of black carbon particulate matter using photothermal interferometry.

PubMed

Li, Baosheng; Wang, Yicheng; Li, Zhengqiang

2016-03-01

A method for measurements of mass concentration of black carbon particulate matter (PM) is proposed based on photothermal interferometry (PTI). A folded Jamin photothermal interferometer was used with a laser irradiation of particles deposited on a filter paper. The black carbon PM deposited on the filter paper was regarded as a film while the quartz filter paper was regarded as a substrate to establish a mathematical model for measuring the mass concentration of PM using a photothermal method. The photothermal interferometry system was calibrated and used to measure the atmospheric PM concentration corresponding to different dust-treated filter paper. The measurements were compared to those obtained using β ray method and were found consistent. This method can be particularly relevant to polluted atmospheres where PM is dominated by black carbon.

40 CFR Appendix B to Part 50 - Reference Method for the Determination of Suspended Particulate Matter in the Atmosphere (High...

Code of Federal Regulations, 2012 CFR

2012-07-01

... site, draws a measured quantity of ambient air into a covered housing and through a filter during a 24... filters used are specified to have a minimum collection efficiency of 99 percent for 0.3 µm (DOP) particles (see Section 7.1.4). 2.2 The filter is weighed (after moisture equilibration) before and after use...

Characterization of ambient and extracted PM2.5 collected on filters for toxicology applications

PubMed Central

Roper, Courtney; Chubb, Lauren G.; Cambal, Leah; Tunno, Brett; Clougherty, Jane E.; Mischler, Steven E.

2016-01-01

Research on the health effects of fine particulate matter (PM2.5) frequently disregards the differences in particle composition between that measured on an ambient filter versus that measured in the corresponding extraction solution used for toxicological testing. This study presents a novel method for characterizing the differences, in metallic and organic species, between the ambient samples and the corresponding extracted solutions through characterization of extracted PM2.5 suspended on filters. Removal efficiency was found to be 98.0 ± 1.4% when measured using pre- and post-removal filter weights, however, this efficiency was significantly reduced to 80.2 ± 0.8% when measured based on particle mass in the extraction solution. Furthermore, only 47.2 ± 22.3% of metals and 24.8 ± 14.5% of organics measured on the ambient filter were found in the extraction solution. Individual metallic and organic components were extracted with varying efficiency, with many organics being lost entirely during extraction. Finally, extraction efficiencies of specific PM2.5 components were inversely correlated with total mass. This study details a method to assess compositional alterations resulting from extraction of PM2.5 from filters, emphasizing the need for standardized procedures that maintain compositional integrity of ambient samples for use in toxicology studies of PM2.5. PMID:26446919

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

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

PubMed Central

2013-01-01

Background 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. Results 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 and apply it to a mixed effects model of plasma-leucine kinetics with data from a clinical study which included 34 patients. Conclusions Comparisons of our MTU-PF with the standard PF and with an alternative Maximum Likelihood estimation method on the small artificial example clearly show that the MTU-PF obtains better estimations. Considering the application to the data from the clinical study, the MTU-PF shows a similar performance with respect to the quality of estimated parameters compared with the standard particle filter, but besides that, the MTU algorithm shows to be less prone to degeneration than the standard particle filter. PMID:23331521

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

PubMed

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.

Evolution of deep-bed filtration of engine exhaust particulates with trapped mass

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

Viswanathan, Sandeep; Rothamer, David A.; Foster, David E.

Micro-scale filtration experiments were performed on cordierite filter samples using particulate matter (PM) generated by a spark-ignition direct-injection (SIDI) engine fueled with tier II EEE certification gasoline. Size-resolved mass and number concentrations were obtained from several engine operating conditions. The resultant mass-mobility relationships showed weak dependence on the operating condition. An integrated particle size distribution (IPSD) method was used estimate the PM mass concentration in the exhaust stream from the SIDI engine and a heavy duty diesel (HDD) engine. The average estimated mass concentration between all conditions was ~77****** % of the gravimetric measurements performed on Teflon filters. Despite themore » relatively low elemental carbon fraction (~0.4 to 0.7), the IPSD mass for stoichiometric SIDI exhaust was ~83±38 % of the gravimetric measurement. Identical cordierite filter samples with properties representative of diesel particulate filters were sequentially loaded with PM from the different SIDI engine operating conditions, in order of increasing PM mass concentration. Simultaneous particle size distribution measurements upstream and downstream of the filter sample were used to evaluate filter performance evolution and the instantaneous trapped mass within the filter for two different filter face velocities. The evolution of filtration performance for the different samples was sensitive only to trapped mass, despite using PM from a wide range of operating conditions. Higher filtration velocity resulted in a more rapid shift in the most penetrating particle size towards smaller mobility diameters.« less

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

NASA Astrophysics Data System (ADS)

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.

Probing Subsurface and Stream Particle Composition Through Optical Analysis at the Eel River Critical Zone Observatory

NASA Astrophysics Data System (ADS)

Nghiem, A.; Thurnhoffer, B. M.; Bishop, J. K. B.; Kim, H.

2014-12-01

Particles constitute a significant portion of the flux weathered material from continents to ocean basins but little is understood about their seasonal dynamics particularly in subsurface and headwater stream environments. At the Eel River Critical Zone Observatory, located near the headwaters of the South Fork Eel River in the Angelo Coast Range Reserve (Northern California), groundwater from weathered bedrock and stream waters are sampled at a frequency of one to three days from three wells (Well 1 down-slope, Well 3 mid-slope, Well 10 upper-slope) and Elder Creek. Approximately one thousand samples collected by automated ISCO Gravity Filtration System (GFS; Kim et al. 2012, EST) since 2011 have been filtered through 0.45 μm 25 mm diameter Supor filters. Filters imaged under controlled lighting are analyzed for red, green, and blue optical density (OD) to enable rapid assessment of sample loading and color as a prelude to and selection aid for more labor-intensive ICP-MS and Scanning Electron Microscopic analysis. For example, samples with lower red OD relative to green and blue may correspond to samples high in Mn/Fe oxides. Optical imaging of the loaded filters provides a time-series over three years and color anomalies in these filters along with chemical analysis of dissolved and particulate filtrate is used to establish a method for calibrating optical data to interpret chemical composition of water and particles. Results are interpreted within a framework of environmental data such as rainfall, stream discharge and turbidity, and water table depth measured at the heavily monitored forested hillslope. Data from the four locations range up to 0.6 OD units with a typical detection limit of better than 0.01 OD units. At Well 10, wet season filter samples exhibit highest particle loading (OD ~ 0.3) with values rapidly decreasing during the dry season (OD < D.L.) water table recession. At Well 1, particle loads instantaneously reflect intense rain events. Applied at a larger scale, this method - if proven - may be used to estimate basin level particulate flux with an estimation of chemical composition in a highly efficient manner.

Glass Frit Filters for Collecting Metal Oxide Nanoparticles

NASA Technical Reports Server (NTRS)

Ackerman, John; Buttry, Dan; Irvine, Geoffrey; Pope, John

2005-01-01

Filter disks made of glass frit have been found to be effective as means of high-throughput collection of metal oxide particles, ranging in size from a few to a few hundred nanometers, produced in gas-phase condensation reactors. In a typical application, a filter is placed downstream of the reactor and a valve is used to regulate the flow of reactor exhaust through the filter. The exhaust stream includes a carrier gas, particles, byproducts, and unreacted particle-precursor gas. The filter selectively traps the particles while allowing the carrier gas, the byproducts, and, in some cases, the unreacted precursor, to flow through unaffected. Although the pores in the filters are much larger than the particles, the particles are nevertheless trapped to a high degree: Anecdotal information from an experiment indicates that 6-nm-diameter particles of MnO2 were trapped with greater than 99-percent effectiveness by a filtering device comprising a glass-frit disk having pores 70 to 100 micrometer wide immobilized in an 8-cm-diameter glass tube equipped with a simple twist valve at its downstream end.

Evaluation of sampling methods for measuring exposure to volatile inorganic acids in workplace air. Part 1: sampling hydrochloric acid (HCl) and nitric acid (HNO₃) from a test gas atmosphere.

PubMed

Howe, Alan; Musgrove, Darren; Breuer, Dietmar; Gusbeth, Krista; Moritz, Andreas; Demange, Martine; Oury, Véronique; Rousset, Davy; Dorotte, Michel

2011-08-01

Historically, workplace exposure to the volatile inorganic acids hydrochloric acid (HCl) and nitric acid (HNO(3)) has been determined mostly by collection on silica gel sorbent tubes and analysis of the corresponding anions by ion chromatography (IC). However, HCl and HNO(3) can be present in workplace air in the form of mist as well as vapor, so it is important to sample the inhalable fraction of airborne particles. As sorbent tubes exhibit a low sampling efficiency for inhalable particles, a more suitable method was required. This is the first of two articles on "Evaluation of Sampling Methods for Measuring Exposure to Volatile Inorganic Acids in Workplace Air" and describes collaborative sampling exercises carried out to evaluate an alternative method for sampling HCl and HNO(3) using sodium carbonate-impregnated filters. The second article describes sampling capacity and breakthrough tests. The method was found to perform well and a quartz fiber filter impregnated with 500 μL of 1 M Na(2)CO(3) (10% (m/v) Na(2)CO(3)) was found to have sufficient sampling capacity for use in workplace air measurement. A pre-filter is required to remove particulate chlorides and nitrates that when present would otherwise result in a positive interference. A GSP sampler fitted with a plastic cone, a closed face cassette, or a plastic IOM sampler were all found to be suitable for mounting the pre-filter and sampling filter(s), but care has to be taken with the IOM sampler to ensure that the sampler is tightly closed to avoid leaks. HCl and HNO(3) can react with co-sampled particulate matter on the pre-filter, e.g., zinc oxide, leading to low results, and stronger acids can react with particulate chlorides and nitrates removed by the pre-filter to liberate HCl and HNO(3), which are subsequently collected on the sampling filter, leading to high results. However, although there is this potential for both positive and negative interferences in the measurement, these are unavoidable. The method studied has now been published in ISO 21438-2:2009.

A Comparison of Filter-based Approaches for Model-based Prognostics

NASA Technical Reports Server (NTRS)

Daigle, Matthew John; Saha, Bhaskar; Goebel, Kai

2012-01-01

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

Spectral imaging and passive sampling to investigate particle sources in urban desert regions.

PubMed

Wagner, Jeff; Casuccio, Gary

2014-07-01

Two types of electron microscopy analyses were employed along with geographic information system (GIS) mapping to investigate potential sources of PM2.5 and PM10 (airborne particulate matter smaller than 2.5 and 10 μm, respectively) in two urbanized desert areas known to exhibit PM excursions. Integrated spectral imaging maps were obtained from scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDS) analyses of 13 filters collected in Imperial Valley, California. Seven were from 24 h PM10 Federal Reference Method (FRM) samplers and six were from PM2.5 FRM samplers. This technique enabled extraction of information from particles collected on complex filter matrices, and indicated that all samples exhibited substantial proportions of crustal particles. Six Imperial PM2.5 and PM10 filters selected from unusually high-PM days exhibited more large particles (2.5-15 and 10-30 μm, respectively) than did filters from low-PM days, and were more consistent with soils analyzed from the region. High winds were present on three of the six high-PM days. One of the high-PM2.5 filters also exhibited substantial fine carbonaceous soot PM, suggesting significant contributions from a combustion source. Computer-controlled SEM/EDS (CCSEM/EDS) was conducted on PM collected with UNC Passive samplers from Phoenix, Arizona. The passive samplers showed good agreement with co-located FRM PM10 and PM2.5 measurements (μg m(-3)), and also enabled detailed individual particle analysis. The CCSEM/EDS data revealed mostly crustal particles in both the Phoenix fine and coarse PM10 fractions. GIS maps of multiple dust-related parameters confirm that both Imperial Valley and Phoenix possess favorable conditions for airborne crustal PM from natural and anthropogenic sources.

Solid colloidal optical wavelength filter

DOEpatents

Alvarez, Joseph L.

1992-01-01

A solid colloidal optical wavelength filter includes a suspension of spheal particles dispersed in a coagulable medium such as a setting plastic. The filter is formed by suspending spherical particles in a coagulable medium; agitating the particles and coagulable medium to produce an emulsion of particles suspended in the coagulable medium; and allowing the coagulable medium and suspended emulsion of particles to cool.

Model-based flow rate control for an orfice-type low-volume air sampler

USDA-ARS?s Scientific Manuscript database

The standard method of measuring air suspended particulate matter concentration per volume of air consists of continuously drawing a defined volume of air across a filter over an extended period of time, then measuring the mass of the filtered particles and dividing it by the total volume sampled ov...

Segmentation of Nerve Bundles and Ganglia in Spine MRI Using Particle Filters

PubMed Central

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation. PMID:22003741

Segmentation of nerve bundles and ganglia in spine MRI using particle filters.

PubMed

Dalca, Adrian; Danagoulian, Giovanna; Kikinis, Ron; Schmidt, Ehud; Golland, Polina

2011-01-01

Automatic segmentation of spinal nerve bundles that originate within the dural sac and exit the spinal canal is important for diagnosis and surgical planning. The variability in intensity, contrast, shape and direction of nerves seen in high resolution myelographic MR images makes segmentation a challenging task. In this paper, we present an automatic tracking method for nerve segmentation based on particle filters. We develop a novel approach to particle representation and dynamics, based on Bézier splines. Moreover, we introduce a robust image likelihood model that enables delineation of nerve bundles and ganglia from the surrounding anatomical structures. We demonstrate accurate and fast nerve tracking and compare it to expert manual segmentation.

Toward particle-level filtering of individual collision events at the Large Hadron Collider and beyond

NASA Astrophysics Data System (ADS)

Colecchia, Federico

2014-03-01

Low-energy strong interactions are a major source of background at hadron colliders, and methods of subtracting the associated energy flow are well established in the field. Traditional approaches treat the contamination as diffuse, and estimate background energy levels either by averaging over large data sets or by restricting to given kinematic regions inside individual collision events. On the other hand, more recent techniques take into account the discrete nature of background, most notably by exploiting the presence of substructure inside hard jets, i.e. inside collections of particles originating from scattered hard quarks and gluons. However, none of the existing methods subtract background at the level of individual particles inside events. We illustrate the use of an algorithm that will allow particle-by-particle background discrimination at the Large Hadron Collider, and we envisage this as the basis for a novel event filtering procedure upstream of the official reconstruction chains. Our hope is that this new technique will improve physics analysis when used in combination with state-of-the-art algorithms in high-luminosity hadron collider environments.

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

PubMed

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

Test of precoat filtration technology for treatment of swimming pool water.

PubMed

Christensen, Morten Lykkegaard; Klausen, Morten Møller; Christensen, Peter Vittrup

2018-02-01

The technical performance of a precoat filter was compared with that of a traditional sand filter. Particle concentration and size distribution were measured before and after the filtration of swimming pool water. Both the sand and precoat filters could reduce the particle concentration in the effluent. However, higher particle removal efficiency was generally observed for the precoat filter, especially for particles smaller than 10 μm in diameter. Adding flocculant improved the removal efficiency of the sand filter, resulting in removal efficiencies comparable to those of the precoat filter. Three powders, i.e., two types of perlite (Harbolite ® and Aquatec perlite) and cellulose fibers (Arbocel ® ), were tested for the precoat filter, but no significant difference in particle removal efficiency was observed among them. The maximum efficiency was reached within 30-40 min of filtration. The energy required for the pumps increased by approximately 35% over a period of 14 days. The energy consumption could be reduced by replacing the powder on the filter cloth. The sand filter was backwashed once a week, while the powder on the precoat filter was replaced every two weeks. Under these conditions, it was possible to reduce the water used for cleaning by 88% if the precoat filter was used instead of the sand filter.

An Investigation into Solution Verification for CFD-DEM

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

Fullmer, William D.; Musser, Jordan

This report presents the study of the convergence behavior of the computational fluid dynamicsdiscrete element method (CFD-DEM) method, specifically National Energy Technology Laboratory’s (NETL) open source MFiX code (MFiX-DEM) with a diffusion based particle-tocontinuum filtering scheme. In particular, this study focused on determining if the numerical method had a solution in the high-resolution limit where the grid size is smaller than the particle size. To address this uncertainty, fixed particle beds of two primary configurations were studied: i) fictitious beds where the particles are seeded with a random particle generator, and ii) instantaneous snapshots from a transient simulation of anmore » experimentally relevant problem. Both problems considered a uniform inlet boundary and a pressure outflow. The CFD grid was refined from a few particle diameters down to 1/6 th of a particle diameter. The pressure drop between two vertical elevations, averaged across the bed cross-section was considered as the system response quantity of interest. A least-squares regression method was used to extrapolate the grid-dependent results to an approximate “grid-free” solution in the limit of infinite resolution. The results show that the diffusion based scheme does yield a converging solution. However, the convergence is more complicated than encountered in simpler, single-phase flow problems showing strong oscillations and, at times, oscillations superimposed on top of globally non-monotonic behavior. The challenging convergence behavior highlights the importance of using at least four grid resolutions in solution verification problems so that (over-determined) regression-based extrapolation methods may be applied to approximate the grid-free solution. The grid-free solution is very important in solution verification and VVUQ exercise in general as the difference between it and the reference solution largely determines the numerical uncertainty. By testing different randomized particle configurations of the same general problem (for the fictitious case) or different instances of freezing a transient simulation, the numerical uncertainties appeared to be on the same order of magnitude as ensemble or time averaging uncertainties. By testing different drag laws, almost all cases studied show that model form uncertainty in this one, very important closure relation was larger than the numerical uncertainty, at least with a reasonable CFD grid, roughly five particle diameters. In this study, the diffusion width (filtering length scale) was mostly set at a constant of six particle diameters. A few exploratory tests were performed to show that similar convergence behavior was observed for diffusion widths greater than approximately two particle diameters. However, this subject was not investigated in great detail because determining an appropriate filter size is really a validation question which must be determined by comparison to experimental or highly accurate numerical data. Future studies are being considered targeting solution verification of transient simulations as well as validation of the filter size with direct numerical simulation data.« less

Development of a copula-based particle filter (CopPF) approach for hydrologic data assimilation under consideration of parameter interdependence

NASA Astrophysics Data System (ADS)

Fan, Y. R.; Huang, G. H.; Baetz, B. W.; Li, Y. P.; Huang, K.

2017-06-01

In this study, a copula-based particle filter (CopPF) approach was developed for sequential hydrological data assimilation by considering parameter correlation structures. In CopPF, multivariate copulas are proposed to reflect parameter interdependence before the resampling procedure with new particles then being sampled from the obtained copulas. Such a process can overcome both particle degeneration and sample impoverishment. The applicability of CopPF is illustrated with three case studies using a two-parameter simplified model and two conceptual hydrologic models. The results for the simplified model indicate that model parameters are highly correlated in the data assimilation process, suggesting a demand for full description of their dependence structure. Synthetic experiments on hydrologic data assimilation indicate that CopPF can rejuvenate particle evolution in large spaces and thus achieve good performances with low sample size scenarios. The applicability of CopPF is further illustrated through two real-case studies. It is shown that, compared with traditional particle filter (PF) and particle Markov chain Monte Carlo (PMCMC) approaches, the proposed method can provide more accurate results for both deterministic and probabilistic prediction with a sample size of 100. Furthermore, the sample size would not significantly influence the performance of CopPF. Also, the copula resampling approach dominates parameter evolution in CopPF, with more than 50% of particles sampled by copulas in most sample size scenarios.

Experimental study on filtration and continuous regeneration of a particulate filter system for heavy-duty diesel engines.

PubMed

Tang, Tao; Zhang, Jun; Cao, Dongxiao; Shuai, Shijin; Zhao, Yanguang

2014-12-01

This study investigated the filtration and continuous regeneration of a particulate filter system on an engine test bench, consisting of a diesel oxidation catalyst (DOC) and a catalyzed diesel particulate filter (CDPF). Both the DOC and the CDPF led to a high conversion of NO to NO2 for continuous regeneration. The filtration efficiency on solid particle number (SPN) was close to 100%. The post-CDPF particles were mainly in accumulation mode. The downstream SPN was sensitively influenced by the variation of the soot loading. This phenomenon provides a method for determining the balance point temperature by measuring the trend of SPN concentration. Copyright © 2014. Published by Elsevier B.V.

COMPARISON OF METHODS FOR MEASURING CONCENTRATIONS OF SEMIVOLATILE PARTICULATE MATTER

EPA Science Inventory

The paper gives results of a comparison of methods for measuring concentrations of semivolatile particulate matter (PM) from indoor-environment, small, combustion sources. Particle concentration measurements were compared for methods using filters and a small electrostatic precip...

The impact of aerosol composition on the particle to gas partitioning of reactive mercury.

PubMed

Rutter, Andrew P; Schauer, James J

2007-06-01

A laboratory system was developed to study the gas-particle partitioning of reactive mercury (RM) as a function of aerosol composition in synthetic atmospheric particulate matter. The collection of RM was achieved by filter- and sorbent-based methods. Analyses of the RM collected on the filters and sorbents were performed using thermal extraction combined with cold vapor atomic fluorescence spectroscopy (CVAFS), allowing direct measurement of the RM load on the substrates. Laboratory measurements of the gas-particle partitioning coefficients of RM to atmospheric aerosol particles revealed a strong dependence on aerosol composition, with partitioning coefficients that varied by orders of magnitude depending on the composition of the particles. Particles of sodium nitrate and the chlorides of potassium and sodium had high partitioning coefficients, shifting the RM partitioning toward the particle phase, while ammonium sulfate, levoglucosan, and adipic acid caused the RM to partition toward the gas phase and, therefore, had partitioning coefficients that were lower by orders of magnitude.

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

PubMed

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.

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-10-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters.

Enhancing Data Assimilation by Evolutionary Particle Filter and Markov Chain Monte Carlo

NASA Astrophysics Data System (ADS)

Moradkhani, H.; Abbaszadeh, P.; Yan, H.

2016-12-01

Particle Filters (PFs) have received increasing attention by the researchers from different disciplines in hydro-geosciences as an effective method to improve model predictions in nonlinear and non-Gaussian dynamical systems. The implication of dual state and parameter estimation by means of data assimilation in hydrology and geoscience has evolved since 2005 from SIR-PF to PF-MCMC and now to the most effective and robust framework through evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC. In this framework, the posterior distribution undergoes an evolutionary process to update an ensemble of prior states that more closely resemble realistic posterior probability distribution. The premise of this approach is that the particles move to optimal position using the GA optimization coupled with MCMC increasing the number of effective particles, hence the particle degeneracy is avoided while the particle diversity is improved. The proposed algorithm is applied on a conceptual and highly nonlinear hydrologic model and the effectiveness, robustness and reliability of the method in jointly estimating the states and parameters and also reducing the uncertainty is demonstrated for few river basins across the United States.

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

PubMed Central

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

2013-01-01

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. PMID:25300451

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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 covariance matrix Σ is assumed to be non-singular. In the present work we consider the case where the covariance Σ is singular. This happens in particular when the noise is spatially smooth and can be represented by a small number of Fourier coefficients, as is often the case in geophysical applications. We derive an implicit filter for this problem and show that it is very efficient, because the filter operates in a space whose dimension is the rank of Σ, rather than the full model dimension. We compare the implicit filter to SIR, to the Ensemble Kalman Filter and to variational methods, and also study how information from data is propagated from observed to unobserved variables. We illustrate the theory on two coupled nonlinear PDE's in one space dimension that have been used as a test-bed for geomagnetic data assimilation. We observe that the implicit filter gives good results with few (2-10) particles, while SIR requires thousands of particles for similar accuracy. We also find lower limits to the accuracy of the filter's reconstruction as a function of data availability.

Method and apparatus for generating low energy nuclear particles

DOEpatents

Powell, J.R.; Reich, M.; Ludewig, H.; Todosow, M.

1999-02-09

A particle accelerator generates an input particle beam having an initial energy level above a threshold for generating secondary nuclear particles. A thin target is rotated in the path of the input beam for undergoing nuclear reactions to generate the secondary particles and correspondingly decrease energy of the input beam to about the threshold. The target produces low energy secondary particles and is effectively cooled by radiation and conduction. A neutron scatterer and a neutron filter are also used for preferentially degrading the secondary particles into a lower energy range if desired. 18 figs.

Numerical simulation of filtration of mine water from coal slurry particles

NASA Astrophysics Data System (ADS)

Dyachenko, E. N.; Dyachenko, N. N.

2017-11-01

The discrete element method is applied to model a technology for clarification of industrial waste water containing fine-dispersed solid impurities. The process is analyzed at the level of discrete particles and pores. The effect of filter porosity on the volume fraction of particles has been shown. The degree of clarification of mine water was also calculated depending on the coal slurry particle size, taking into account the adhesion force.

Direct filtration for recovery of Schistosoma mansoni cercariae in the field.

PubMed

Sandt, D G

1973-01-01

The recovery of schistosome cercariae from natural waters has been limited by variations in turbidity and in the accuracy of recovery with different techniques. A modification of the Rowan vacuum paper filtration method employing a battery-operated pumping system, a glass-silicone plate filter, and a specially designed filter holder is described and evaluated. Field tests on St Lucia indicate a mean filtration volume of 12.2 litres per filter at a mean turbidity of 20.3 Jackson turbidity units. Overall, 86% of the volumes filtered per filter were in excess of 6 litres. Particle size, rather than turbidity, was found to be the main factor influencing filter blockage, reading time, and accuracy. Recoveries of 0.01 cercaria (Schistosoma mansoni) per litre sampled were obtained, but the practical limit of the method is considered to be closer to 0.1 cercaria per litre sampled.

A Nonlinear Framework of Delayed Particle Smoothing Method for Vehicle Localization under Non-Gaussian Environment.

PubMed

Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-05-13

In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student's t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods.

Multiuser Transmit Beamforming for Maximum Sum Capacity in Tactical Wireless Multicast Networks

DTIC Science & Technology

2006-08-01

commonly used extended Kalman filter . See [2, 5, 6] for recent tutorial overviews. In particle filtering , continuous distributions are approximated by...signals (using and developing associated particle filtering tools). Our work on these topics has been reported in seven (IEEE, SIAM) journal papers and...multidimensional scaling, tracking, intercept, particle filters . 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT 18. SECURITY CLASSIFICATION OF

Guide to Air Cleaners in the Home

MedlinePlus

... In-duct Particle Removal Flat or panel air filters Pleated or extended surface filters In-duct Gaseous Pollutant Removal In-duct Pollutant ... can remove particles from the air — mechanical air filters and electronic air cleaners. Mechanical air filters remove ...

Indoor Pedestrian Localization Using iBeacon and Improved Kalman Filter.

PubMed

Sung, Kwangjae; Lee, Dong Kyu 'Roy'; Kim, Hwangnam

2018-05-26

The reliable and accurate indoor pedestrian positioning is one of the biggest challenges for location-based systems and applications. Most pedestrian positioning systems have drift error and large bias due to low-cost inertial sensors and random motions of human being, as well as unpredictable and time-varying radio-frequency (RF) signals used for position determination. To solve this problem, many indoor positioning approaches that integrate the user's motion estimated by dead reckoning (DR) method and the location data obtained by RSS fingerprinting through Bayesian filter, such as the Kalman filter (KF), unscented Kalman filter (UKF), and particle filter (PF), have recently been proposed to achieve higher positioning accuracy in indoor environments. Among Bayesian filtering methods, PF is the most popular integrating approach and can provide the best localization performance. However, since PF uses a large number of particles for the high performance, it can lead to considerable computational cost. This paper presents an indoor positioning system implemented on a smartphone, which uses simple dead reckoning (DR), RSS fingerprinting using iBeacon and machine learning scheme, and improved KF. The core of the system is the enhanced KF called a sigma-point Kalman particle filter (SKPF), which localize the user leveraging both the unscented transform of UKF and the weighting method of PF. The SKPF algorithm proposed in this study is used to provide the enhanced positioning accuracy by fusing positional data obtained from both DR and fingerprinting with uncertainty. The SKPF algorithm can achieve better positioning accuracy than KF and UKF and comparable performance compared to PF, and it can provide higher computational efficiency compared with PF. iBeacon in our positioning system is used for energy-efficient localization and RSS fingerprinting. We aim to design the localization scheme that can realize the high positioning accuracy, computational efficiency, and energy efficiency through the SKPF and iBeacon indoors. Empirical experiments in real environments show that the use of the SKPF algorithm and iBeacon in our indoor localization scheme can achieve very satisfactory performance in terms of localization accuracy, computational cost, and energy efficiency.

Air-to-Air Missile Vector Scoring

DTIC Science & Technology

2012-03-22

SIR sampling-importance resampling . . . . . . . . . . . . . . 53 EPF extended particle filter . . . . . . . . . . . . . . . . . . . . 54 UPF unscented...particle filter ( EPF ) or a unscented particle fil- ter (UPF) [20]. The basic concept is to apply a bank of N EKF or UKF filters to move particles from...Merwe, Doucet, Freitas and Wan provide a comprehensive discussion on the EPF and UPF, including algorithms for implementation [20]. 2Result based on

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

NASA Astrophysics Data System (ADS)

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 radiative forcing based on their effects can be assessed.

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

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

Stillo, Andrew; Ricketts, Craig I.

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 capacitymore » 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 Code sections FC and FK[1]. (authors)« less

Effect of open channel filter on particle emissions of modern diesel engine.

PubMed

Heikkilä, Juha; Rönkkö, Topi; Lähde, Tero; Lemmetty, Mikko; Arffman, Anssi; Virtanen, Annele; Keskinen, Jorma; Pirjola, Liisa; Rothe, Dieter

2009-10-01

Particle emissions of modern diesel engines are of a particular interest because of their negative health effects. The special interest is in nanosized solid particles. The effect of an open channel filter on particle emissions of a modern heavy-duty diesel engine (MAN D2066 LF31, model year 2006) was studied. Here, the authors show that the open channel filter made from metal screen efficiently reduced the number of the smallest particles and, notably, the number and mass concentration of soot particles. The filter used in this study reached 78% particle mass reduction over the European Steady Cycle. Considering the size-segregated number concentration reduction, the collection efficiency was over 95% for particles smaller than 10 nm. The diffusion is the dominant collection mechanism in small particle sizes, thus the collection efficiency decreased as particle size increased, attaining 50% at 100 nm. The overall particle number reduction was 66-99%, and for accumulation-mode particles the number concentration reduction was 62-69%, both depending on the engine load.

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

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

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava

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 ismore » 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.« less

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications

PubMed Central

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-01-01

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service. PMID:28574471

A Map/INS/Wi-Fi Integrated System for Indoor Location-Based Service Applications.

PubMed

Yu, Chunyang; Lan, Haiyu; Gu, Fuqiang; Yu, Fei; El-Sheimy, Naser

2017-06-02

In this research, a new Map/INS/Wi-Fi integrated system for indoor location-based service (LBS) applications based on a cascaded Particle/Kalman filter framework structure is proposed. Two-dimension indoor map information, together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value, are integrated for estimating positioning information. The main challenge of this research is how to make effective use of various measurements that complement each other in order to obtain an accurate, continuous, and low-cost position solution without increasing the computational burden of the system. Therefore, to eliminate the cumulative drift caused by low-cost IMU sensor errors, the ubiquitous Wi-Fi signal and non-holonomic constraints are rationally used to correct the IMU-derived navigation solution through the extended Kalman Filter (EKF). Moreover, the map-aiding method and map-matching method are innovatively combined to constrain the primary Wi-Fi/IMU-derived position through an Auxiliary Value Particle Filter (AVPF). Different sources of information are incorporated through a cascaded structure EKF/AVPF filter algorithm. Indoor tests show that the proposed method can effectively reduce the accumulation of positioning errors of a stand-alone Inertial Navigation System (INS), and provide a stable, continuous and reliable indoor location service.

Remaining useful life assessment of lithium-ion batteries in implantable medical devices

NASA Astrophysics Data System (ADS)

Hu, Chao; Ye, Hui; Jain, Gaurav; Schmidt, Craig

2018-01-01

This paper presents a prognostic study on lithium-ion batteries in implantable medical devices, in which a hybrid data-driven/model-based method is employed for remaining useful life assessment. The method is developed on and evaluated against data from two sets of lithium-ion prismatic cells used in implantable applications exhibiting distinct fade performance: 1) eight cells from Medtronic, PLC whose rates of capacity fade appear to be stable and gradually decrease over a 10-year test duration; and 2) eight cells from Manufacturer X whose rates appear to be greater and show sharp increase after some period over a 1.8-year test duration. The hybrid method enables online prediction of remaining useful life for predictive maintenance/control. It consists of two modules: 1) a sparse Bayesian learning module (data-driven) for inferring capacity from charge-related features; and 2) a recursive Bayesian filtering module (model-based) for updating empirical capacity fade models and predicting remaining useful life. A generic particle filter is adopted to implement recursive Bayesian filtering for the cells from the first set, whose capacity fade behavior can be represented by a single fade model; a multiple model particle filter with fixed-lag smoothing is proposed for the cells from the second data set, whose capacity fade behavior switches between multiple fade models.

Capability of GPGPU for Faster Thermal Analysis Used in Data Assimilation

NASA Astrophysics Data System (ADS)

Takaki, Ryoji; Akita, Takeshi; Shima, Eiji

A thermal mathematical model plays an important role in operations on orbit as well as spacecraft thermal designs. The thermal mathematical model has some uncertain thermal characteristic parameters, such as thermal contact resistances between components, effective emittances of multilayer insulation (MLI) blankets, discouraging make up efficiency and accuracy of the model. A particle filter which is one of successive data assimilation methods has been applied to construct spacecraft thermal mathematical models. This method conducts a lot of ensemble computations, which require large computational power. Recently, General Purpose computing in Graphics Processing Unit (GPGPU) has been attracted attention in high performance computing. Therefore GPGPU is applied to increase the computational speed of thermal analysis used in the particle filter. This paper shows the speed-up results by using GPGPU as well as the application method of GPGPU.

Design parameters for rotating cylindrical filtration

NASA Technical Reports Server (NTRS)

Schwille, John A.; Mitra, Deepanjan; Lueptow, Richard M.

2002-01-01

Rotating cylindrical filtration displays significantly reduced plugging of filter pores and build-up of a cake layer, but the number and range of parameters that can be adjusted complicates the design of these devices. Twelve individual parameters were investigated experimentally by measuring the build-up of particles on the rotating cylindrical filter after a fixed time of operation. The build-up of particles on the filter depends on the rotational speed, the radial filtrate flow, the particle size and the gap width. Other parameters, such as suspension concentration and total flow rate are less important. Of the four mechanisms present in rotating filters to reduce pore plugging and cake build-up, axial shear, rotational shear, centrifugal sedimentation and vortical motion, the evidence suggests rotational shear is the dominant mechanism, although the other mechanisms still play minor roles. The ratio of the shear force acting parallel to the filter surface on a particle to the Stokes drag acting normal to the filter surface on the particle due to the difference between particle motion and filtrate flow can be used as a non-dimensional parameter that predicts the degree of particle build-up on the filter surface for a wide variety of filtration conditions. c2002 Elsevier Science B.V. All rights reserved.

A Wide Field of View Plasma Spectrometer

DOE PAGES

Skoug, Ruth M.; Funsten, Herbert O.; Moebius, Eberhard; ...

2016-07-01

Here we present a fundamentally new type of space plasma spectrometer, the wide field of view plasma spectrometer, whose field of view is >1.25π ster using fewer resources than traditional methods. The enabling component is analogous to a pinhole camera with an electrostatic energy-angle filter at the image plane. Particle energy-per-charge is selected with a tunable bias voltage applied to the filter plate relative to the pinhole aperture plate. For a given bias voltage, charged particles from different directions are focused by different angles to different locations. Particles with appropriate locations and angles can transit the filter plate and aremore » measured using a microchannel plate detector with a position-sensitive anode. Full energy and angle coverage are obtained using a single high-voltage power supply, resulting in considerable resource savings and allowing measurements at fast timescales. Lastly, we present laboratory prototype measurements and simulations demonstrating the instrument concept and discuss optimizations of the instrument design for application to space measurements.« less

Quantification of the fungal fraction released from various preloaded fibrous filters during a simulated ventilation restart.

PubMed

Morisseau, K; Joubert, A; Le Coq, L; Andres, Y

2017-05-01

This study aimed to demonstrate that particles, especially those associated with fungi, could be released from fibrous filters used in the air-handling unit (AHU) of heating, ventilation and air-conditioning (HVAC) systems during ventilation restarts. Quantification of the water retention capacity and SEM pictures of the filters was used to show the potential for fungal proliferation in unused or preloaded filters. Five fibrous filters with various particle collection efficiencies were studied: classes G4, M5, M6, F7, and combined F7 according to European standard EN779:2012. Filters were clogged with micronized rice particles containing the fungus Penicillium chrysogenum and then incubated for three weeks at 25°C and 90% relative humidity. The results indicated that the five clogged tested filters had various fungal growth capacities depending on their water retention capacity. Preloaded filters were subjected to a simulated ventilation restart in a controlled filtration device to quantify that the fraction of particles released was around 1% for the G4, 0.1% for the M5 and the M6, and 0.001% for the F7 and the combined F7 filter. The results indicate that the likelihood of fungal particle release by low efficiency filters is significantly higher than by high efficiency filters. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Real time infrared aerosol analyzer

DOEpatents

Johnson, Stanley A.; Reedy, Gerald T.; Kumar, Romesh

1990-01-01

Apparatus for analyzing aerosols in essentially real time includes a virtual impactor which separates coarse particles from fine and ultrafine particles in an aerosol sample. The coarse and ultrafine particles are captured in PTFE filters, and the fine particles impact onto an internal light reflection element. The composition and quantity of the particles on the PTFE filter and on the internal reflection element are measured by alternately passing infrared light through the filter and the internal light reflection element, and analyzing the light through infrared spectrophotometry to identify the particles in the sample.

Uncertainty quantification of seabed parameters for large data volumes along survey tracks with a tempered particle filter

NASA Astrophysics Data System (ADS)

Dettmer, J.; Quijano, J. E.; Dosso, S. E.; Holland, C. W.; Mandolesi, E.

2016-12-01

Geophysical seabed properties are important for the detection and classification of unexploded ordnance. However, current surveying methods such as vertical seismic profiling, coring, or inversion are of limited use when surveying large areas with high spatial sampling density. We consider surveys based on a source and receiver array towed by an autonomous vehicle which produce large volumes of seabed reflectivity data that contain unprecedented and detailed seabed information. The data are analyzed with a particle filter, which requires efficient reflection-coefficient computation, efficient inversion algorithms and efficient use of computer resources. The filter quantifies information content of multiple sequential data sets by considering results from previous data along the survey track to inform the importance sampling at the current point. Challenges arise from environmental changes along the track where the number of sediment layers and their properties change. This is addressed by a trans-dimensional model in the filter which allows layering complexity to change along a track. Efficiency is improved by likelihood tempering of various particle subsets and including exchange moves (parallel tempering). The filter is implemented on a hybrid computer that combines central processing units (CPUs) and graphics processing units (GPUs) to exploit three levels of parallelism: (1) fine-grained parallel computation of spherical reflection coefficients with a GPU implementation of Levin integration; (2) updating particles by concurrent CPU processes which exchange information using automatic load balancing (coarse grained parallelism); (3) overlapping CPU-GPU communication (a major bottleneck) with GPU computation by staggering CPU access to the multiple GPUs. The algorithm is applied to spherical reflection coefficients for data sets along a 14-km track on the Malta Plateau, Mediterranean Sea. We demonstrate substantial efficiency gains over previous methods. [This research was supported in part by the U.S. Dept of Defense, thought the Strategic Environmental Research and Development Program (SERDP).

The particle valve: On-demand particle trapping, filtering, and release from a microfabricated polydimethylsiloxane membrane using surface acoustic waves

NASA Astrophysics Data System (ADS)

Collins, David J.; Alan, Tuncay; Neild, Adrian

2014-07-01

We introduce a surface acoustic wave (SAW) based method for acoustically controlled concentration, capture, release, and sorting of particles in a microfluidic system. This method is power efficient by the nature of its design: the vertical direction of a traveling acoustic wave, in which the majority of the energy at the SAW-water interface is directed, is used to concentrate particles behind a microfabricated polydimethylsiloxane membrane extending partially into a channel. Sorting is also demonstrated with this concentration shown to be size-dependent. Low-power, miniature SAW devices, using methods such as the one demonstrated here, are well placed for future integration into point-of-care diagnostic systems.

A Particle Smoother with Sequential Importance Resampling for soil hydraulic parameter estimation: A lysimeter experiment

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Hendricks Franssen, Harrie-Jan; Moradkhani, Hamid; Pütz, Thomas; Han, Xujun; Vereecken, Harry

2013-04-01

An adequate description of soil hydraulic properties is essential for a good performance of hydrological forecasts. So far, several studies showed that data assimilation could reduce the parameter uncertainty by considering soil moisture observations. However, these observations and also the model forcings were recorded with a specific measurement error. It seems a logical step to base state updating and parameter estimation on observations made at multiple time steps, in order to reduce the influence of outliers at single time steps given measurement errors and unknown model forcings. Such outliers could result in erroneous state estimation as well as inadequate parameters. This has been one of the reasons to use a smoothing technique as implemented for Bayesian data assimilation methods such as the Ensemble Kalman Filter (i.e. Ensemble Kalman Smoother). Recently, an ensemble-based smoother has been developed for state update with a SIR particle filter. However, this method has not been used for dual state-parameter estimation. In this contribution we present a Particle Smoother with sequentially smoothing of particle weights for state and parameter resampling within a time window as opposed to the single time step data assimilation used in filtering techniques. This can be seen as an intermediate variant between a parameter estimation technique using global optimization with estimation of single parameter sets valid for the whole period, and sequential Monte Carlo techniques with estimation of parameter sets evolving from one time step to another. The aims are i) to improve the forecast of evaporation and groundwater recharge by estimating hydraulic parameters, and ii) to reduce the impact of single erroneous model inputs/observations by a smoothing method. In order to validate the performance of the proposed method in a real world application, the experiment is conducted in a lysimeter environment.

Design and Implementation of Embedded Computer Vision Systems Based on Particle Filters

DTIC Science & Technology

2010-01-01

for hardware/software implementa- tion of multi-dimensional particle filter application and we explore this in the third application which is a 3D...methodology for hardware/software implementation of multi-dimensional particle filter application and we explore this in the third application which is a...and hence multiprocessor implementation of parti- cle filters is an important option to examine. A significant body of work exists on optimizing generic

Allergy-Proof Your House

MedlinePlus

... small-particle or high-efficiency particulate air (HEPA) filter. Shampoo the carpet frequently. Curtains and blinds. Use ... dander they shed. Air filtration. Choose an air filter that has a small-particle or HEPA filter. ...

Coaxial charged particle energy analyzer

NASA Technical Reports Server (NTRS)

Kelly, Michael A. (Inventor); Bryson, III, Charles E. (Inventor); Wu, Warren (Inventor)

2011-01-01

A non-dispersive electrostatic energy analyzer for electrons and other charged particles having a generally coaxial structure of a sequentially arranged sections of an electrostatic lens to focus the beam through an iris and preferably including an ellipsoidally shaped input grid for collimating a wide acceptance beam from a charged-particle source, an electrostatic high-pass filter including a planar exit grid, and an electrostatic low-pass filter. The low-pass filter is configured to reflect low-energy particles back towards a charged particle detector located within the low-pass filter. Each section comprises multiple tubular or conical electrodes arranged about the central axis. The voltages on the lens are scanned to place a selected energy band of the accepted beam at a selected energy at the iris. Voltages on the high-pass and low-pass filters remain substantially fixed during the scan.

Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Cheng, Yao; Zhou, Ning; Zhang, Weihua; Wang, Zhiwei

2018-07-01

Minimum entropy deconvolution is a widely-used tool in machinery fault diagnosis, because it enhances the impulse component of the signal. The filter coefficients that greatly influence the performance of the minimum entropy deconvolution are calculated by an iterative procedure. This paper proposes an improved deconvolution method for the fault detection of rolling element bearings. The proposed method solves the filter coefficients by the standard particle swarm optimization algorithm, assisted by a generalized spherical coordinate transformation. When optimizing the filters performance for enhancing the impulses in fault diagnosis (namely, faulty rolling element bearings), the proposed method outperformed the classical minimum entropy deconvolution method. The proposed method was validated in simulation and experimental signals from railway bearings. In both simulation and experimental studies, the proposed method delivered better deconvolution performance than the classical minimum entropy deconvolution method, especially in the case of low signal-to-noise ratio.

Removal of viable bioaerosol particles with a low-efficiency HVAC filter enhanced by continuous emission of unipolar air ions.

PubMed

Huang, R; Agranovski, I; Pyankov, O; Grinshpun, S

2008-04-01

Continuous emission of unipolar ions has been shown to improve the performance of respirators and stationary filters challenged with non-biological particles. In this study, we investigated the ion-induced enhancement effect while challenging a low-efficiency heating, ventilation and air-conditioning (HVAC) filter with viable bacterial cells, bacterial and fungal spores, and viruses. The aerosol concentration was measured in real time. Samples were also collected with a bioaerosol sampler for viable microbial analysis. The removal efficiency of the filter was determined, respectively, with and without an ion emitter. The ionization was found to significantly enhance the filter efficiency in removing viable biological particles from the airflow. For example, when challenged with viable bacteria, the filter efficiency increased as much as four- to fivefold. For viable fungal spores, the ion-induced enhancement improved the efficiency by a factor of approximately 2. When testing with virus-carrying liquid droplets, the original removal efficiency provided by the filter was rather low: 9.09 +/- 4.84%. While the ion emission increased collection about fourfold, the efficiency did not reach 75-100% observed with bacteria and fungi. These findings, together with our previously published results for non-biological particles, demonstrate the feasibility of a new approach for reducing aerosol particles in HVAC systems used for indoor air quality control. Recirculated air in HVAC systems used for indoor air quality control in buildings often contains considerable number of viable bioaerosol particles because of limited efficiency of the filters installed in these systems. In the present study, we investigated - using aerosolized bacterial cells, bacterial and fungal spores, and virus-carrying particles - a novel idea of enhancing the performance of a low-efficiency HVAC filter utilizing continuous emission of unipolar ions in the filter vicinity. The findings described in this paper, together with our previously published results for non-biological particles, demonstrate the feasibility of the newly developed approach.

Method and apparatus for generating low energy nuclear particles

DOEpatents

Powell, James R.; Reich, Morris; Ludewig, Hans; Todosow, Michael

1999-02-09

A particle accelerator (12) generates an input particle beam having an initial energy level above a threshold for generating secondary nuclear particles. A thin target (14) is rotated in the path of the input beam for undergoing nuclear reactions to generate the secondary particles and correspondingly decrease energy of the input beam to about the threshold. The target (14) produces low energy secondary particles and is effectively cooled by radiation and conduction. A neutron scatterer (44) and a neutron filter (42) are also used for preferentially degrading the secondary particles into a lower energy range if desired.

Centrifugal lyophobic separator

NASA Technical Reports Server (NTRS)

Booth, F. W.; Bruce, R. A. (Inventor)

1974-01-01

A centrifugal separator is described using a lyophobic filter for removing liquid particles from a mixed stream of gas and liquid under various negative or positive external acceleration conditions as well as zero g or weightless conditions. Rotating the lyophobic filter and inclining the filter to the entering flow improves the lyophobic properties of the filter, provides gross separation of larger liquid particles, and prevents prolonged contact of liquid droplets with the spinning filter which might change the filter properties or block the filter.

Sub-micron filter

DOEpatents

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.

Data assimilation in the low noise regime

NASA Astrophysics Data System (ADS)

Weare, J.; Vanden-Eijnden, E.

2012-12-01

On-line data assimilation techniques such as ensemble Kalman filters and particle filters tend to lose accuracy dramatically when presented with an unlikely observation. Such observation may be caused by an unusually large measurement error or reflect a rare fluctuation in the dynamics of the system. Over a long enough span of time it becomes likely that one or several of these events will occur. In some cases they are signatures of the most interesting features of the underlying system and their prediction becomes the primary focus of the data assimilation procedure. The Kuroshio or Black Current that runs along the eastern coast of Japan is an example of just such a system. It undergoes infrequent but dramatic changes of state between a small meander during which the current remains close to the coast of Japan, and a large meander during which the current bulges away from the coast. Because of the important role that the Kuroshio plays in distributing heat and salinity in the surrounding region, prediction of these transitions is of acute interest. { Here we focus on a regime in which both the stochastic forcing on the system and the observational noise are small. In this setting large deviation theory can be used to understand why standard filtering methods fail and guide the design of the more effective data assimilation techniques. Motivated by our large deviations analysis we propose several data assimilation strategies capable of efficiently handling rare events such as the transitions of the Kuroshio. These techniques are tested on a model of the Kuroshio and shown to perform much better than standard filtering methods.Here the sequence of observations (circles) are taken directly from one of our Kuroshio model's transition events from the small meander to the large meander. We tested two new algorithms (Algorithms 3 and 4 in the legend) motivated by our large deviations analysis as well as a standard particle filter and an ensemble Kalman filter. The parameters of each algorithm are chosen so that their costs are comparable. The particle filter and an ensemble Kalman filter fail to accurately track the transition. Algorithms 3 and 4 maintain accuracy (and smaller scale resolution) throughout the transition.

Laboratory and on-road evaluations of cabin air filters using number and surface area concentration monitors.

PubMed

Qi, Chaolong; Stanley, Nick; Pui, David Y H; Kuehn, Thomas H

2008-06-01

An automotive cabin air filter's effectiveness for removing airborne particles was determined both in a laboratory wind tunnel and in vehicle on-road tests. The most penetrating particle size for the test filter was approximately 350 nm, where the filtration efficiency was 22.9 and 17.4% at medium and high fan speeds, respectively. The filtration efficiency increased for smaller particles and was 43.9% for 100 nm and 72.0% for 20 nm particles at a medium fan speed. We determined the reduction in passenger exposure to particles while driving in freeway traffic caused by a vehicle ventilation system with a cabin air filter installed. Both particle number and surface area concentration measurements were made inside the cabin and in the surrounding air. At medium fan speed, the number and surface area concentration-based exposure reductions were 65.6 +/- 6.0% and 60.6 +/- 9.4%, respectively. To distinguish the exposure reduction contribution from the filter alone and the remainder of the ventilation system, we also performed tests with and without the filter in place using the surface area monitors. The ventilation system operating in the recirculation mode with the cabin air filter installed provided the maximum protection, reducing the cabin particle concentration exponentially over time and usually taking only 3 min to reach 10 microm2/cm3 (a typical office air condition) under medium fan speed.

Measuring the Acoustic Release of a Chemotherapeutic Agent from Folate-Targeted Polymeric Micelles.

PubMed

Abusara, Ayah; Abdel-Hafez, Mamoun; Husseini, Ghaleb

2018-08-01

In this paper, we compare the use of Bayesian filters for the estimation of release and re-encapsulation rates of a chemotherapeutic agent (namely Doxorubicin) from nanocarriers in an acoustically activated drug release system. The study is implemented using an advanced kinetic model that takes into account cavitation events causing the antineoplastic agent's release from polymeric micelles upon exposure to ultrasound. This model is an improvement over the previous representations of acoustic release that used simple zero-, first- and second-order release and re-encapsulation kinetics to study acoustically triggered drug release from polymeric micelles. The new model incorporates drug release and micellar reassembly events caused by cavitation allowing for the controlled release of chemotherapeutics specially and temporally. Different Bayesian estimators are tested for this purpose including Kalman filters (KF), Extended Kalman filters (EKF), Particle filters (PF), and multi-model KF and EKF. Simulated and experimental results are used to verify the performance of the above-mentioned estimators. The proposed methods demonstrate the utility and high-accuracy of using estimation methods in modeling this drug delivery technique. The results show that, in both cases (linear and non-linear dynamics), the modeling errors are expensive but can be minimized using a multi-model approach. In addition, particle filters are more flexible filters that perform reasonably well compared to the other two filters. The study improved the accuracy of the kinetic models used to capture acoustically activated drug release from polymeric micelles, which may in turn help in designing hardware and software capable of precisely controlling the delivered amount of chemotherapeutics to cancerous tissue.

Angle only tracking with particle flow filters

NASA Astrophysics Data System (ADS)

Daum, Fred; Huang, Jim

2011-09-01

We show the results of numerical experiments for tracking ballistic missiles using only angle measurements. We compare the performance of an extended Kalman filter with a new nonlinear filter using particle flow to compute Bayes' rule. For certain difficult geometries, the particle flow filter is an order of magnitude more accurate than the EKF. Angle only tracking is of interest in several different sensors; for example, passive optics and radars in which range and Doppler data are spoiled by jamming.

Feature aided Monte Carlo probabilistic data association filter for ballistic missile tracking

NASA Astrophysics Data System (ADS)

Ozdemir, Onur; Niu, Ruixin; Varshney, Pramod K.; Drozd, Andrew L.; Loe, Richard

2011-05-01

The problem of ballistic missile tracking in the presence of clutter is investigated. Probabilistic data association filter (PDAF) is utilized as the basic filtering algorithm. We propose to use sequential Monte Carlo methods, i.e., particle filters, aided with amplitude information (AI) in order to improve the tracking performance of a single target in clutter when severe nonlinearities exist in the system. We call this approach "Monte Carlo probabilistic data association filter with amplitude information (MCPDAF-AI)." Furthermore, we formulate a realistic problem in the sense that we use simulated radar cross section (RCS) data for a missile warhead and a cylinder chaff using Lucernhammer1, a state of the art electromagnetic signature prediction software, to model target and clutter amplitude returns as additional amplitude features which help to improve data association and tracking performance. A performance comparison is carried out between the extended Kalman filter (EKF) and the particle filter under various scenarios using single and multiple sensors. The results show that, when only one sensor is used, the MCPDAF performs significantly better than the EKF in terms of tracking accuracy under severe nonlinear conditions for ballistic missile tracking applications. However, when the number of sensors is increased, even under severe nonlinear conditions, the EKF performs as well as the MCPDAF.

A fully-automated multiscale kernel graph cuts based particle localization scheme for temporal focusing two-photon microscopy

NASA Astrophysics Data System (ADS)

Huang, Xia; Li, Chunqiang; Xiao, Chuan; Sun, Wenqing; Qian, Wei

2017-03-01

The temporal focusing two-photon microscope (TFM) is developed to perform depth resolved wide field fluorescence imaging by capturing frames sequentially. However, due to strong nonignorable noises and diffraction rings surrounding particles, further researches are extremely formidable without a precise particle localization technique. In this paper, we developed a fully-automated scheme to locate particles positions with high noise tolerance. Our scheme includes the following procedures: noise reduction using a hybrid Kalman filter method, particle segmentation based on a multiscale kernel graph cuts global and local segmentation algorithm, and a kinematic estimation based particle tracking method. Both isolated and partial-overlapped particles can be accurately identified with removal of unrelated pixels. Based on our quantitative analysis, 96.22% isolated particles and 84.19% partial-overlapped particles were successfully detected.

Nonlinear Attitude Filtering Methods

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Crassidis, John L.; Cheng, Yang

2005-01-01

This paper provides a survey of modern nonlinear filtering methods for attitude estimation. Early applications relied mostly on the extended Kalman filter for attitude estimation. Since these applications, several new approaches have been developed that have proven to be superior to the extended Kalman filter. Several of these approaches maintain the basic structure of the extended Kalman filter, but employ various modifications in order to provide better convergence or improve other performance characteristics. Examples of such approaches include: filter QUEST, extended QUEST, the super-iterated extended Kalman filter, the interlaced extended Kalman filter, and the second-order Kalman filter. Filters that propagate and update a discrete set of sigma points rather than using linearized equations for the mean and covariance are also reviewed. A two-step approach is discussed with a first-step state that linearizes the measurement model and an iterative second step to recover the desired attitude states. These approaches are all based on the Gaussian assumption that the probability density function is adequately specified by its mean and covariance. Other approaches that do not require this assumption are reviewed, including particle filters and a Bayesian filter based on a non-Gaussian, finite-parameter probability density function on SO(3). Finally, the predictive filter, nonlinear observers and adaptive approaches are shown. The strengths and weaknesses of the various approaches are discussed.

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

PubMed Central

Ma, Huan; Shen, Henggen; Shui, Tiantian; Li, Qing; Zhou, Liuke

2016-01-01

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 school office buildings. PMID:26742055

Preparation of lipid nanoemulsions by premix membrane emulsification with disposable materials.

PubMed

Gehrmann, Sandra; Bunjes, Heike

2016-09-25

The possibility to prepare nanoemulsions as drug carrier systems on small scale was investigated with disposable materials. For this purpose premix membrane emulsification (premix ME) as a preparation method for nanoemulsions with narrow particle size distributions on small scale was used. The basic principle of premix ME is that the droplets of a coarse pre-emulsion get disrupted by the extrusion through a porous membrane. In order to implement the common preparation setup for premix ME with disposable materials, the suitability of different syringe filters (made from polyethersulfone, cellulose acetate, cellulose ester and nylon) and different pharmaceutically relevant emulsifiers (phospholipids, polysorbate 80 and sucrose laurate) for the preparation of nanoemulsions was investigated. Already the preparation of the premix could be realized by emulsification with the help of two disposable syringes. As shown for a phospholipid-stabilized emulsion, the polyethersulfone filter was the most appropriate one and was used for the study with different emulsifiers. With this syringe filter, the median particle size of all investigated emulsions was below 500nm after 21 extrusion cycles through a 200nm filter and a subsequent extrusion cycle through a 100nm filter. Furthermore, the particle size distribution of the polysorbate 80- and sucrose laurate-stabilized emulsions prepared this way was very narrow (span value of 0.7). Copyright © 2016 Elsevier B.V. All rights reserved.

Wood dust particle and mass concentrations and filtration efficiency in sanding of wood materials.

PubMed

Welling, Irma; Lehtimäki, Matti; Rautio, Sari; Lähde, Tero; Enbom, Seppo; Hynynen, Pasi; Hämeri, Kaarle

2009-02-01

The importance of fine particles has become apparent as the knowledge of their effects on health has increased. Fine particle concentrations have been published for outside air, plasma arc cutting, welding, and grinding, but little data exists for the woodworking industry. Sanding was evaluated as the producer of the woodworking industry's finest particles, and was selected as the target study. The number of dust particles in different particle size classes and the mass concentrations were measured in the following environments: workplace air during sanding in plywood production and in the inlet and return air; in the dust emission chamber; and in filter testing. The numbers of fine particles were low, less than 10(4) particles/cm(3) (10(7) particles/L). They were much lower than typical number concentrations near 10(6) particles/cm(3) measured in plasma arc cutting, grinding, and welding. Ultrafine particles in the size class less than 100 nm were found during sanding of MDF (medium density fiberboard) sheets. When the cleaned air is returned to the working areas, the dust content in extraction systems must be monitored continuously. One way to monitor the dust content in the return air is to use an after-filter and measure pressure drop across the filter to indicate leaks in the air-cleaning system. The best after-filtration materials provided a clear increase in pressure drop across the filter in the loading of the filter. The best after-filtration materials proved to be quite effective also for fine particles. The best mass removal efficiencies for fine particles around 0.3 mum were over 80% for some filter materials loaded with sanding wood dust.

Particle Clogging in Filter Media of Embankment Dams: A Numerical and Experimental Study

NASA Astrophysics Data System (ADS)

Antoun, T.; Kanarska, Y.; Ezzedine, S. M.; Lomov, I.; Glascoe, L. G.; Smith, J.; Hall, R. L.; Woodson, S. C.

2013-12-01

The safety of dam structures requires the characterization of the granular filter ability to capture fine-soil particles and prevent erosion failure in the event of an interfacial dislocation. Granular filters are one of the most important protective design elements of large embankment dams. In case of cracking and erosion, if the filter is capable of retaining the eroded fine particles, then the crack will seal and the dam safety will be ensured. Here we develop and apply a numerical tool to thoroughly investigate the migration of fines in granular filters at the grain scale. The numerical code solves the incompressible Navier-Stokes equations and uses a Lagrange multiplier technique which enforces the correct in-domain computational boundary conditions inside and on the boundary of the particles. The numerical code is validated to experiments conducted at the US Army Corps of Engineering and Research Development Center (ERDC). These laboratory experiments on soil transport and trapping in granular media are performed in constant-head flow chamber filled with the filter media. Numerical solutions are compared to experimentally measured flow rates, pressure changes and base particle distributions in the filter layer and show good qualitative and quantitative agreement. To further the understanding of the soil transport in granular filters, we investigated the sensitivity of the particle clogging mechanism to various parameters such as particle size ratio, the magnitude of hydraulic gradient, particle concentration, and grain-to-grain contact properties. We found that for intermediate particle size ratios, the high flow rates and low friction lead to deeper intrusion (or erosion) depths. We also found that the damage tends to be shallower and less severe with decreasing flow rate, increasing friction and concentration of suspended particles. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was sponsored by the Department of Homeland Security (DHS), Science and Technology Directorate, Homeland Security Advanced Research Projects Agency (HSARPA).

Hybrid Filter Membrane

NASA Technical Reports Server (NTRS)

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 dust particles on the filter surface and to facilitate dust removal with pulse or back airflow.

Numerical studies on the performance of an aerosol respirator with faceseal leakage

NASA Astrophysics Data System (ADS)

Zaripov, S. K.; Mukhametzanov, I. T.; Grinshpun, S. A.

2016-11-01

We studied the efficiency of a facepiece filtering respirator (FFR) in presence of a measurable faceseal leakage using the previously developed model of a spherical sampler with porous layer. In our earlier study, the model was validated for a specific filter permeability value. In this follow-up study, we investigated the effect of permeability on the overall respirator performance accounting for the faceseal leakage. The Total Inward Leakage (TIL) was calculated as a function of the leakage-to-filter surface ratio and the particle diameter. A good correlation was found between the theoretical and experimental TIL values. The TIL value was shown to increase and the effect of particle size on TIL to decrease as the leakage-to- filter surface ratio grows. The model confirmed that within the most penetrating particle size range (∼50 nm) and at relatively low leakage-to-filter surface ratios, an FFR performs better (TIL is lower) when the filter has a lower permeability which should be anticipated as long as the flow through the filter represents the dominant particle penetration pathway. An increase in leak size causes the TIL to rise; furthermore, under certain leakage-to-filter surface ratios, TIL for ultrafine particles becomes essentially independent on the filter properties due to a greater contribution of the aerosol flow through the faceseal leakage. In contrast to the ultrafine fraction, the larger particles (e.g., 800 nm) entering a typical high- or medium-quality respirator filter are almost fully collected by the filter medium regardless of its permeability; at the same time, the fraction penetrated through the leakage appears to be permeability- dependent: higher permeability generally results in a lower pressure drop through the filter which increases the air flow through the filter at the expense of the leakage flow. The latter reduces the leakage effect thus improving the overall respiratory protection level. The findings of this study provide valuable information for developing new respirators with a predictable actual workplace protection factor.

Image processing enhancement of high-resolution TEM micrographs of nanometer-size metal particles

NASA Technical Reports Server (NTRS)

Artal, P.; Avalos-Borja, M.; Soria, F.; Poppa, H.; Heinemann, K.

1989-01-01

The high-resolution TEM detectability of lattice fringes from metal particles supported on substrates is impeded by the substrate itself. Single value decomposition (SVD) and Fourier filtering (FFT) methods were applied to standard high resolution micrographs to enhance lattice resolution from particles as well as from crystalline substrates. SVD produced good results for one direction of fringes, and it can be implemented as a real-time process. Fourier methods are independent of azimuthal directions and allow separation of particle lattice planes from those pertaining to the substrate, which makes it feasible to detect possible substrate distortions produced by the supported particle. This method, on the other hand, is more elaborate, requires more computer time than SVD and is, therefore, less likely to be used in real-time image processing applications.

An extended Kalman filter approach to non-stationary Bayesian estimation of reduced-order vocal fold model parameters.

PubMed

Hadwin, Paul J; Peterson, Sean D

2017-04-01

The Bayesian framework for parameter inference provides a basis from which subject-specific reduced-order vocal fold models can be generated. Previously, it has been shown that a particle filter technique is capable of producing estimates and associated credibility intervals of time-varying reduced-order vocal fold model parameters. However, the particle filter approach is difficult to implement and has a high computational cost, which can be barriers to clinical adoption. This work presents an alternative estimation strategy based upon Kalman filtering aimed at reducing the computational cost of subject-specific model development. The robustness of this approach to Gaussian and non-Gaussian noise is discussed. The extended Kalman filter (EKF) approach is found to perform very well in comparison with the particle filter technique at dramatically lower computational cost. Based upon the test cases explored, the EKF is comparable in terms of accuracy to the particle filter technique when greater than 6000 particles are employed; if less particles are employed, the EKF actually performs better. For comparable levels of accuracy, the solution time is reduced by 2 orders of magnitude when employing the EKF. By virtue of the approximations used in the EKF, however, the credibility intervals tend to be slightly underpredicted.

Comparison of methods for the measurement of mist and vapor from light mineral oil-based metalworking fluids.

PubMed

Simpson, Andrew T

2003-11-01

The measurement of oil mist derived from metalworking fluids formulated with light mineral oils can be highly inaccurate when using traditional filter sampling. This is due to evaporation of oil from the filter. In this work the practicability of an alternative approach measuring total oil mist and vapor was investigated. Combinations of inhalable particle samplers with backup sorbent vapor traps and standard vapor sampling on pumped and diffusive sorbent tubes were evaluated with gravimetric, infrared spectroscopic, and gas chromatographic analytical methods against the performance requirements of European Standard EN 482. An artificial aerosol was used to compare the methods against a reference method of filter sampler in series with three impingers. Multi-orifice samplers were used with standard 8-mm diameter charcoal tubes at 2 L/min without any signs of channelling or significant breakthrough, as were conical inhalable samplers with XAD-2 tubes at 1 L/min. Most combinations of samplers had a bias of less than 3 percent, but solitary pumped charcoal tubes underestimated total oil by 13 percent. Diffusive sampling was affected by impaction of mist particles and condensation of oil vapor. Gravimetric analysis of filters revealed significant potential sample loss during storage, with 4 percent being lost after one day when stored at room temperature and 2 percent when refrigerated. Samples left overnight in the balance room to equilibrate lost 24 percent. Infrared spectroscopy gave more precise results for vapor than gas chromatography (p = 0.002). Gas chromatography was less susceptible to bias from contaminating solvent vapors than infrared spectroscopy, but was still vulnerable to petroleum distillates. Under the specific test conditions (one oil type and mist particle size), all combinations of methods examined complied with the requirements of European Standard EN 484. Total airborne oil can be measured accurately; however, care must be taken to avoid contamination by hydrocarbon solvent vapors during sampling.

Performance evaluation of the active-flow personal DataRAM PM 2.5 mass monitor (Thermo Anderson pDR-1200) designed for continuous personal exposure measurements

NASA Astrophysics Data System (ADS)

Chakrabarti, Bhabesh; Fine, Philip M.; Delfino, Ralph; Sioutas, Constantinos

The need for continuous personal monitoring for exposure to particulate matter has been demonstrated by recent health studies showing effects of PM exposure on time scales of less than a few hours. Filter-based methods cannot measure this short-term variation of PM levels, which can be quite significant considering human activity patterns. The goal of this study was to evaluate the active-flow personal DataRAM for PM 2.5 (MIE pDR-1200; Thermo Electron Corp., Franklin, MA) designed as a wearable monitor to continuously measure particle exposure. The instrument precision was found to be good (2.1%) and significantly higher than the passive pDR configuration tested previously. A comparison to other proven continuous monitors resulted in good agreement at low relative humidities. Results at higher humidity followed predictable trends and provided a correction scheme that improved the accuracy of pDR readings. The pDR response to particle size also corresponded to previously observed and theoretical errors. The active flow feature of the pDR allows collection of the sampled particles on a back-up filter. The 24-h mass measured on this filter was found to compare very well with a Federal Reference Method for PM 2.5 mass.

Adaptive prognosis of lithium-ion batteries based on the combination of particle filters and radial basis function neural networks

NASA Astrophysics Data System (ADS)

Sbarufatti, Claudio; Corbetta, Matteo; Giglio, Marco; Cadini, Francesco

2017-03-01

Lithium-Ion rechargeable batteries are widespread power sources with applications to consumer electronics, electrical vehicles, unmanned aerial and spatial vehicles, etc. The failure to supply the required power levels may lead to severe safety and economical consequences. Thus, in view of the implementation of adequate maintenance strategies, the development of diagnostic and prognostic tools for monitoring the state of health of the batteries and predicting their remaining useful life is becoming a crucial task. Here, we propose a method for predicting the end of discharge of Li-Ion batteries, which stems from the combination of particle filters with radial basis function neural networks. The major innovation lies in the fact that the radial basis function model is adaptively trained on-line, i.e., its parameters are identified in real time by the particle filter as new observations of the battery terminal voltage become available. By doing so, the prognostic algorithm achieves the flexibility needed to provide sound end-of-discharge time predictions as the charge-discharge cycles progress, even in presence of anomalous behaviors due to failures or unforeseen operating conditions. The method is demonstrated with reference to actual Li-Ion battery discharge data contained in the prognostics data repository of the NASA Ames Research Center database.

Development of a high efficiency personal/environmental radon dosimeter using polycarbonate detectors.

PubMed

Taheri, M; Jafarizadeh, M; Baradaran, S; Zainali, Gh

2006-12-01

Passive radon dosimeters, based on alpha particle etched track detectors, are widely used for the assessment of radon exposure. These methods are often applied in radon dosimetry for long periods of time. In this research work, we have developed a highly efficient method of personal/environmental radon dosimetry that is based upon the detection of alpha particles from radon daughters, (218)Po and (214)Po, using a polycarbonate detector (PC). The radon daughters are collected on the filter surface by passing a fixed flow of air through it and the PC detector, placed at a specified distance from the filter, is simultaneously exposed to alpha particles. After exposure, the latent tracks on the detector are made to appear by means of an electrochemical etching process; these are proportional to the radon dose. The air flow rate and the detector-filter distance are the major factors that can affect the performance of the dosimeter. The results obtained in our experimental investigations have shown that a distance of 1.5 cm between the detector and the filter, an absorber layer of Al with a thickness of 12 microm and an air flow rate of 4 l min(-1) offer the best design parameters for a high efficiency radon dosimeter. Then, the designed dosimeter was calibrated against different values of radon exposures and the obtained sensitivity was found to be 2.1 (tracks cm(-2)) (kBq h m(-3))(-1). The most important advantages of this method are that it is reliable, fast and convenient when used for radon dose assessment. In this paper, the optimized parameters of the dosimeter structure and its calibration procedure are presented and discussed.

Real-time localization of mobile device by filtering method for sensor fusion

NASA Astrophysics Data System (ADS)

Fuse, Takashi; Nagara, Keita

2017-06-01

Most of the applications with mobile devices require self-localization of the devices. GPS cannot be used in indoor environment, the positions of mobile devices are estimated autonomously by using IMU. Since the self-localization is based on IMU of low accuracy, and then the self-localization in indoor environment is still challenging. The selflocalization method using images have been developed, and the accuracy of the method is increasing. This paper develops the self-localization method without GPS in indoor environment by integrating sensors, such as IMU and cameras, on mobile devices simultaneously. The proposed method consists of observations, forecasting and filtering. The position and velocity of the mobile device are defined as a state vector. In the self-localization, observations correspond to observation data from IMU and camera (observation vector), forecasting to mobile device moving model (system model) and filtering to tracking method by inertial surveying and coplanarity condition and inverse depth model (observation model). Positions of a mobile device being tracked are estimated by system model (forecasting step), which are assumed as linearly moving model. Then estimated positions are optimized referring to the new observation data based on likelihood (filtering step). The optimization at filtering step corresponds to estimation of the maximum a posterior probability. Particle filter are utilized for the calculation through forecasting and filtering steps. The proposed method is applied to data acquired by mobile devices in indoor environment. Through the experiments, the high performance of the method is confirmed.

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

PubMed Central

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. PMID:26734037

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

PubMed

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.

Making Carbon-Nanotube Arrays Using Block Copolymers: Part 2

NASA Technical Reports Server (NTRS)

Bronikowski, Michael

2004-01-01

Some changes have been incorporated into a proposed method of manufacturing regular arrays of precisely sized, shaped, positioned, and oriented carbon nanotubes. Such arrays could be useful as mechanical resonators for signal filters and oscillators, and as electrophoretic filters for use in biochemical assays. A prior version of the method was described in Block Copolymers as Templates for Arrays of Carbon Nanotubes, (NPO-30240), NASA Tech Briefs, Vol. 27, No. 4 (April 2003), page 56. To recapitulate from that article: As in other previously reported methods, carbon nanotubes would be formed by decomposition of carbon-containing gases over nanometer-sized catalytic metal particles that had been deposited on suitable substrates. Unlike in other previously reported methods, the catalytic metal particles would not be so randomly and densely distributed as to give rise to thick, irregular mats of nanotubes with a variety of lengths, diameters, and orientations. Instead, in order to obtain regular arrays of spaced-apart carbon nanotubes as nearly identical as possible, the catalytic metal particles would be formed in predetermined regular patterns with precise spacings. The regularity of the arrays would be ensured by the use of nanostructured templates made of block copolymers.

A Nonlinear Framework of Delayed Particle Smoothing Method for Vehicle Localization under Non-Gaussian Environment

PubMed Central

Xiao, Zhu; Havyarimana, Vincent; Li, Tong; Wang, Dong

2016-01-01

In this paper, a novel nonlinear framework of smoothing method, non-Gaussian delayed particle smoother (nGDPS), is proposed, which enables vehicle state estimation (VSE) with high accuracy taking into account the non-Gaussianity of the measurement and process noises. Within the proposed method, the multivariate Student’s t-distribution is adopted in order to compute the probability distribution function (PDF) related to the process and measurement noises, which are assumed to be non-Gaussian distributed. A computation approach based on Ensemble Kalman Filter (EnKF) is designed to cope with the mean and the covariance matrix of the proposal non-Gaussian distribution. A delayed Gibbs sampling algorithm, which incorporates smoothing of the sampled trajectories over a fixed-delay, is proposed to deal with the sample degeneracy of particles. The performance is investigated based on the real-world data, which is collected by low-cost on-board vehicle sensors. The comparison study based on the real-world experiments and the statistical analysis demonstrates that the proposed nGDPS has significant improvement on the vehicle state accuracy and outperforms the existing filtering and smoothing methods. PMID:27187405

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

The Amateur Scientist.

ERIC Educational Resources Information Center

Walker, Jearl

1981-01-01

Describes several methods by which an amateur might prepare a laser light display in the home or the classroom. Methods described include the use of particles in lasers, filters, reflecting laser beams, vibration's effects on laser beams, rotating mirrors, and the use of prisms with laser beams. (DS)

Particulate removal processes and hydraulics of porous gravel media filters

NASA Astrophysics Data System (ADS)

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 clogging processes of gravel filters and are a considerable improvement on the inflow/outflow data most often available to monitor removal efficiency and clogging. Sub-section of the MRI derived geometry showing gravel (grey), pore space (blue), deposited particles (red) for 1) prior to clogging and 2) after clogging. The pore network skeleton (green) provided a reference point for comparing pore diameter change with clogging.

Aerosol-chamber study of the α-pinene/O 3 reaction: influence of particle acidity on aerosol yields and products

NASA Astrophysics Data System (ADS)

Iinuma, Yoshiteru; Böge, Olaf; Gnauk, Thomas; Herrmann, Hartmut

α-Pinene ozonolysis was carried out in the presence of ammonium sulfate or sulfuric acid seed particles in a 9 m 3 Teflon chamber at the mixing ratios of 100 ppbv for α-pinene and about 70 ppbv for ozone. The evolution of size distribution was measured by means of a differential mobility particle sizer (DMPS). The resulting secondary organic aerosol (SOA) was sampled by a denuder/quartz fiber filter combination for the determination of the total organic carbon concentration (TOC) in the particle phase, using a thermographic method and by a denuder/PTFE filter combination for the analysis of individual chemical species in the particle phase using capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS). cis-Pinic acid ( m/ z 185) and another species tentatively identified at m/ z 171 and 199 were the major particle phase species for both seed particles although the product yields were different, indicating the influence of seed particle acidity. A thermographic method for the determination of TOC showed an increase of particle phase organics by 40% for the experiments with higher acidity. CE-ESI-MS analysis showed a large increase in the concentration of compounds with Mw>300 from the experiments with sulfuric acid seed particles. These results suggest that the seed particle acidity enhances the yield of SOA and plays an important role in the formation of larger molecules in the particle phase. Our results from direct particle phase chemical analysis suggest for the first time that condensation of smaller organics takes place by polymerization or aldol condensation following the formation of aldehydes, such as pinonaldehyde from the terpene ozonolysis.

On-line crack prognosis in attachment lug using Lamb wave-deterministic resampling particle filter-based method

NASA Astrophysics Data System (ADS)

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

2017-08-01

Fatigue crack growth prognosis is important for prolonging service time, improving safety, and reducing maintenance cost in many safety-critical systems, such as in aircraft, wind turbines, bridges, and nuclear plants. Combining fatigue crack growth models with the particle filter (PF) method has proved promising to deal with the uncertainties during fatigue crack growth and reach a more accurate prognosis. However, research on prognosis methods integrating on-line crack monitoring with the PF method is still lacking, as well as experimental verifications. Besides, the PF methods adopted so far are almost all sequential importance resampling-based PFs, which usually encounter sample impoverishment problems, and hence performs poorly. To solve these problems, in this paper, the piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The deterministic resampling PF (DRPF) is proposed to be used in fatigue crack growth prognosis, which can overcome the sample impoverishment problem. The proposed method is verified through fatigue tests of attachment lugs, which are a kind of important joint component in aerospace systems.

Robust Hydrological Forecasting for High-resolution Distributed Models Using a Unified Data Assimilation Approach

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

Reliable real-time hydrological forecasting, to predict important phenomena such as floods, is invaluable to the society. However, modern high-resolution distributed models have faced challenges when dealing with uncertainties that are caused by the large number of parameters and initial state estimations involved. Therefore, to rely on these high-resolution models for critical real-time forecast applications, considerable improvements on the parameter and initial state estimation techniques must be made. In this work we present a unified data assimilation algorithm called Optimized PareTo Inverse Modeling through Inverse STochastic Search (OPTIMISTS) to deal with the challenge of having robust flood forecasting for high-resolution distributed models. This new algorithm combines the advantages of particle filters and variational methods in a unique way to overcome their individual weaknesses. The analysis of candidate particles compares model results with observations in a flexible time frame, and a multi-objective approach is proposed which attempts to simultaneously minimize differences with the observations and departures from the background states by using both Bayesian sampling and non-convex evolutionary optimization. Moreover, the resulting Pareto front is given a probabilistic interpretation through kernel density estimation to create a non-Gaussian distribution of the states. OPTIMISTS was tested on a low-resolution distributed land surface model using VIC (Variable Infiltration Capacity) and on a high-resolution distributed hydrological model using the DHSVM (Distributed Hydrology Soil Vegetation Model). In the tests streamflow observations are assimilated. OPTIMISTS was also compared with a traditional particle filter and a variational method. Results show that our method can reliably produce adequate forecasts and that it is able to outperform those resulting from assimilating the observations using a particle filter or an evolutionary 4D variational method alone. In addition, our method is shown to be efficient in tackling high-resolution applications with robust results.

Guided filter and convolutional network based tracking for infrared dim moving target

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Qin, Hanlin; Rong, Shenghui; Zhao, Dong; Du, Juan

2017-09-01

The dim moving target usually submerges in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio. A tracking algorithm that integrates the Guided Image Filter (GIF) and the Convolutional neural network (CNN) into the particle filter framework is presented to cope with the uncertainty of dim targets. First, the initial target template is treated as a guidance to filter incoming templates depending on similarities between the guidance and candidate templates. The GIF algorithm utilizes the structure in the guidance and performs as an edge-preserving smoothing operator. Therefore, the guidance helps to preserve the detail of valuable templates and makes inaccurate ones blurry, alleviating the tracking deviation effectively. Besides, the two-layer CNN method is adopted to obtain a powerful appearance representation. Subsequently, a Bayesian classifier is trained with these discriminative yet strong features. Moreover, an adaptive learning factor is introduced to prevent the update of classifier's parameters when a target undergoes sever background. At last, classifier responses of particles are utilized to generate particle importance weights and a re-sample procedure preserves samples according to the weight. In the predication stage, a 2-order transition model considers the target velocity to estimate current position. Experimental results demonstrate that the presented algorithm outperforms several relative algorithms in the accuracy.

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

PubMed

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.

DUAL STATE-PARAMETER UPDATING SCHEME ON A CONCEPTUAL HYDROLOGIC MODEL USING SEQUENTIAL MONTE CARLO FILTERS

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Tachikawa, Yasuto; Shiiba, Michiharu; Kim, Sunmin

Applications of data assimilation techniques have been widely used to improve upon the predictability of hydrologic modeling. Among various data assimilation techniques, sequential Monte Carlo (SMC) filters, known as "particle filters" provide the capability to handle non-linear and non-Gaussian state-space models. This paper proposes a dual state-parameter updating scheme (DUS) based on SMC methods to estimate both state and parameter variables of a hydrologic model. We introduce a kernel smoothing method for the robust estimation of uncertain model parameters in the DUS. The applicability of the dual updating scheme is illustrated using the implementation of the storage function model on a middle-sized Japanese catchment. We also compare performance results of DUS combined with various SMC methods, such as SIR, ASIR and RPF.

Regenerative particulate filter development

NASA Technical Reports Server (NTRS)

Descamp, V. A.; Boex, M. W.; Hussey, M. W.; Larson, T. P.

1972-01-01

Development, design, and fabrication of a prototype filter regeneration unit for regenerating clean fluid particle filter elements by using a backflush/jet impingement technique are reported. Development tests were also conducted on a vortex particle separator designed for use in zero gravity environment. A maintainable filter was designed, fabricated and tested that allows filter element replacement without any leakage or spillage of system fluid. Also described are spacecraft fluid system design and filter maintenance techniques with respect to inflight maintenance for the space shuttle and space station.

Mechanistic failure mode investigation and resolution of parvovirus retentive filters.

PubMed

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.

Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

NASA Astrophysics Data System (ADS)

Closas, Pau; Guillamon, Antoni

2017-12-01

This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain's connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers) are at the core of our study. The sole observation available are noisy, sampled voltage traces obtained from intracellular recordings. We design algorithms and inference methods using the tools provided by stochastic filtering that allow a probabilistic interpretation and treatment of the problem. Using particle filtering, we are able to reconstruct traces of voltages and estimate the time course of auxiliary variables. By extending the algorithm, through PMCMC methodology, we are able to estimate hidden physiological parameters as well, like intrinsic conductances or reversal potentials. Last, but not least, the method is applied to estimate synaptic conductances arriving at a target cell, thus reconstructing the synaptic excitatory/inhibitory input traces. Notably, the performance of these estimations achieve the theoretical lower bounds even in spiking regimes.

Structured filtering

NASA Astrophysics Data System (ADS)

Granade, Christopher; Wiebe, Nathan

2017-08-01

A major challenge facing existing sequential Monte Carlo methods for parameter estimation in physics stems from the inability of existing approaches to robustly deal with experiments that have different mechanisms that yield the results with equivalent probability. We address this problem here by proposing a form of particle filtering that clusters the particles that comprise the sequential Monte Carlo approximation to the posterior before applying a resampler. Through a new graphical approach to thinking about such models, we are able to devise an artificial-intelligence based strategy that automatically learns the shape and number of the clusters in the support of the posterior. We demonstrate the power of our approach by applying it to randomized gap estimation and a form of low circuit-depth phase estimation where existing methods from the physics literature either exhibit much worse performance or even fail completely.

Fabrication and Characterization of Surrogate Fuel Particles Using the Spark Erosion Method

NASA Astrophysics Data System (ADS)

Metzger, Kathryn E.

In light of the disaster at the Fukushima Daiichi Nuclear Plant, the Department of Energy's Advanced Fuels Program has shifted its interest from enhanced performance fuels to enhanced accident tolerance fuels. Dispersion fuels possess higher thermal conductivities than traditional light water reactor fuel and as a result, offer improved safety margins. The benefits of a dispersion fuel are due to the presence of the secondary non-fissile phase (matrix), which serves as a barrier to fission products and improves the overall thermal performance of the fuel. However, the presence of a matrix material reduces the fuel volume, which lowers the fissile content of dispersion. This issue can be remedied through the development of higher density fuel phases or through an optimization of fuel particle size and volume loading. The latter requirement necessitates the development of fabrication methods to produce small, micron-order fuel particles. This research examines the capabilities of the spark erosion process to fabricate particles on the order of 10 μm. A custom-built spark erosion device by CT Electromechanica was used to produce stainless steel surrogate fuel particles in a deionized water dielectric. Three arc intensities were evaluated to determine the effect on particle size. Particles were filtered from the dielectric using a polycarbonate membrane filter and vacuum filtration system. Fabricated particles were characterized via field emission scanning electron microscopy (FESEM), laser light particle size analysis, energy-dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD), and gas pycnometry. FESEM images reveal that the spark erosion process produces highly spherical particles on the order of 10 microns. These findings are substantiated by the results of particle size analysis. Additionally, EDS and XRD results indicate the presence of oxide phases, which suggests the dielectric reacted with the molten debris during particle formation.

Don't Fear Optimality: Sampling for Probabilistic-Logic Sequence Models

NASA Astrophysics Data System (ADS)

Thon, Ingo

One of the current challenges in artificial intelligence is modeling dynamic environments that change due to the actions or activities undertaken by people or agents. The task of inferring hidden states, e.g. the activities or intentions of people, based on observations is called filtering. Standard probabilistic models such as Dynamic Bayesian Networks are able to solve this task efficiently using approximative methods such as particle filters. However, these models do not support logical or relational representations. The key contribution of this paper is the upgrade of a particle filter algorithm for use with a probabilistic logical representation through the definition of a proposal distribution. The performance of the algorithm depends largely on how well this distribution fits the target distribution. We adopt the idea of logical compilation into Binary Decision Diagrams for sampling. This allows us to use the optimal proposal distribution which is normally prohibitively slow.

Nanosize electropositive fibrous adsorbent

DOEpatents

Tepper, Frederick; Kaledin, Leonid

2005-01-04

Aluminum hydroxide fibers approximately 2 nanometers in diameter and with surface areas ranging from 200 to 650 m.sup.2 /g have been fount 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 mirobes 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. Macromolicules such as proteins may be separated from each other based on their electronegative charges.

Denuder/filter sampling of organic acids and organosulfates at urban and boreal forest sites: Gas/particle distribution and possible sampling artifacts

NASA Astrophysics Data System (ADS)

Kristensen, Kasper; Bilde, Merete; Aalto, Pasi P.; Petäjä, Tuukka; Glasius, Marianne

2016-04-01

Carboxylic acids and organosulfates comprise an important fraction of atmospheric secondary organic aerosols formed from both anthropogenic and biogenic precursors. The partitioning of these compounds between the gas and particle phase is still unclear and further research is warranted to better understand the abundance and effect of organic acids and organosulfates on the formation and properties of atmospheric aerosols. This work compares atmospheric aerosols collected at an urban and a boreal forest site using two side-by-side sampling systems; a high volume sampler (HVS) and a low volume (LVS) denuder/filter sampling system allowing for separate collection of gas- and particle-phase organics. All particle filters and denuder samples were collected at H.C. Andersen Boulevard (HCAB), Copenhagen, Denmark in the summer of 2010, and at the remote boreal forest site at Hyytiälä forestry field station in Finland in the summer of 2012. The chemical composition of gas- and particle-phase secondary organic aerosol was investigated by ultra-high performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC/ESI-Q-TOFMS), with a focus on carboxylic acids and organosulfates. Results show gas-phase concentrations higher than those observed in the particle phase by a factor of 5-6 in HCAB 2010 and 50-80 in Hyytiälä 2012. Although abundant in the particle phase, no organosulfates were detected in the gas phase at either site. Through a comparison of samples collected by the HVS and the LVS denuder/filter sampling system we evaluate the potential artifacts associated with sampling of atmospheric aerosols. Such comparison shows that particle phase concentrations of semi-volatile organic acids obtained from the filters collected by HVS are more than two times higher than concentrations obtained from filters collected using LVS denuder/filter system. In most cases, higher concentrations of organosulfates are observed in particles collected by HVS compared to samples collected by LVS denuder/filter sampling system. The present study shows that volatile organics may absorb onto filter materials in the HVS (and similar sampling systems without denuder) and furthermore undergo subsequent on-filter oxidation and sulfation resulting in formation of both organic acids and organosulfates.

Analysis of Cosmic Spherule Candidates from the Kwajalein Micrometeorite Collection

NASA Technical Reports Server (NTRS)

Wozniakiewicz, P. J.; Price, M. C.; Bradley, J. P.; Ishii, H. A.; Russell, S. S.; Zolensky, M. E.; Brownlee, D. E.

2015-01-01

The Kwajalein micrometeorite collection utilised high volume air samplers fitted with 5 micrometer laser-etched polycarbonate membrane filters to capture particles directly from the atmosphere. The filters were changed weekly over several months throughout 2011/12, providing the opportunity to investigate the contemporary flux of micrometeorites. We recently reported the results of our initial survey of cosmic spherule-like particles on several of these filters. We identified three main groups of particle based on bulk compositions: 1. Silicate spherules rich in Mg, Ca and Fe, 2. Silicate spherules rich in Al, Ca, K and/or Na and 3. Fe-rich spherules. Abundances appeared to change over time suggesting links with celestial activity (e.g. meteor showers), however, spherules similar to groups 2 and 3 can be produced by terrestrial and anthropogenic activity (e.g. volcanic microspherules exhibit similar compositions to group 2 spherules and metallic spherules similar to those of group 3 can be formed during fuel combustion). We are now studying the internal structures and chemistries of these spherules and comparing against cosmic spherules identified in other collections to confrim their origins and further contrain the contemporary micrometeorite flux. Particles are being picked, embedded in resin and polished through to reveal their interiors. Here we will describe our ongoing analyses of these particles via SEM. We will also introduce our new collection using this method that is currently being performed in the Antarctic.

Filter Bed of Packed Spheres

NASA Technical Reports Server (NTRS)

Elleman, D. D.; Wang, T. G.

1986-01-01

Spheres sized and treated for desired sieve properties. Filter constructed from densely packed spheres restrained by screens. Hollow gas-filled plastic or metal spheres normally used. Manufactured within one percent or better diameter tolerance. Normally, all spheres in filter of same nominal diameter. Filter used as sieve to pass only particles smaller than given size or to retain particles larger than that size. Options available under filter concept make it easy to design for specific applications.

Precise orbit determination using the batch filter based on particle filtering with genetic resampling approach

NASA Astrophysics Data System (ADS)

Kim, Young-Rok; Park, Eunseo; Choi, Eun-Jung; Park, Sang-Young; Park, Chandeok; Lim, Hyung-Chul

2014-09-01

In this study, genetic resampling (GRS) approach is utilized for precise orbit determination (POD) using the batch filter based on particle filtering (PF). Two genetic operations, which are arithmetic crossover and residual mutation, are used for GRS of the batch filter based on PF (PF batch filter). For POD, Laser-ranging Precise Orbit Determination System (LPODS) and satellite laser ranging (SLR) observations of the CHAMP satellite are used. Monte Carlo trials for POD are performed by one hundred times. The characteristics of the POD results by PF batch filter with GRS are compared with those of a PF batch filter with minimum residual resampling (MRRS). The post-fit residual, 3D error by external orbit comparison, and POD repeatability are analyzed for orbit quality assessments. The POD results are externally checked by NASA JPL’s orbits using totally different software, measurements, and techniques. For post-fit residuals and 3D errors, both MRRS and GRS give accurate estimation results whose mean root mean square (RMS) values are at a level of 5 cm and 10-13 cm, respectively. The mean radial orbit errors of both methods are at a level of 5 cm. For POD repeatability represented as the standard deviations of post-fit residuals and 3D errors by repetitive PODs, however, GRS yields 25% and 13% more robust estimation results than MRRS for post-fit residual and 3D error, respectively. This study shows that PF batch filter with GRS approach using genetic operations is superior to PF batch filter with MRRS in terms of robustness in POD with SLR observations.

Environmental scanning electron microscope imaging examples related to particle analysis.

PubMed

Wight, S A; Zeissler, C J

1993-08-01

This work provides examples of some of the imaging capabilities of environmental scanning electron microscopy applied to easily charged samples relevant to particle analysis. Environmental SEM (also referred to as high pressure or low vacuum SEM) can address uncoated samples that are known to be difficult to image. Most of these specimens are difficult to image by conventional SEM even when coated with a conductive layer. Another area where environmental SEM is particularly applicable is for specimens not compatible with high vacuum, such as volatile specimens. Samples from which images were obtained that otherwise may not have been possible by conventional methods included fly ash particles on an oiled plastic membrane impactor substrate, a one micrometer diameter fiber mounted on the end of a wire, uranium oxide particles embedded in oil-bearing cellulose nitrate, teflon and polycarbonate filter materials with collected air particulate matter, polystyrene latex spheres on cellulosic filter paper, polystyrene latex spheres "loosely" sitting on a glass slide, and subsurface tracks in an etched nuclear track-etch detector. Surface charging problems experienced in high vacuum SEMs are virtually eliminated in the low vacuum SEM, extending imaging capabilities to samples previously difficult to use or incompatible with conventional methods.

Development of magnetic separation system of magnetoliposomes

NASA Astrophysics Data System (ADS)

Nakao, R.; Matuo, Y.; Mishima, F.; Taguchi, T.; Maenosono, S.; Nishijima, S.

2009-10-01

The magnetic separation technology using sub-microsized ferromagnetic particle is indispensable in many areas of medical biosciences. For example, ferromagnetic particles (200-500 nm) are widely used for cell sorting in stem cell research with the use of cell surface-specific antigens. Nanosized ferromagnetic particles (10-20 nm) have been suggested as more suitable in drug delivery studies given their efficiency of tissue penetration, however, the magnetic separation method for them has not been established. One of the major reasons is that magnetic force acting on the object particles decreases drastically as a particle diameter becomes small. In this study, magnetic force acting on the targets was enhanced by the combination of superconducting magnet and the filter consisting of ferromagnetic particle. By doing so, we confirmed that Fe 3O 4 of 20 nm in diameter was trapped in the magnetic filter under an external magnetic field of 0.5 T. Fe 3O 4 encapsulated with phospholipid liposomes of 200 nm in diameter was also shown to be trapped as external magnetic field of 1.5 T, but not of 0.5 T. We also showed the result of particle trajectory calculation which emulated well the experimental data.

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

PubMed

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.

Model Adaptation for Prognostics in a Particle Filtering Framework

NASA Technical Reports Server (NTRS)

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.

Method to separate lignin-rich solid phase from acidic biomass suspension at an acidic pH

DOEpatents

Yasarla, Kumar Lakshmi Rakesh; Ramarao, Bandaru V; Amidon, Thomas

2017-09-05

A method of separating a lignin-rich solid phase from a solution suspension, by pretreating a lignocellulosic biomass with a pretreatment fluid having remove soluble components, colloidal material and primarily lignin containing particles; separating the pretreated lignocellulosic biomass from the pretreatment fluid with soluble components, colloidal material and primarily lignin containing particles; flocculating the separated pretreatment fluid with soluble components, colloidal material and primarily lignin containing particles using polyethylene oxide (i.e., PEO) or cationic Poly acrylamide (i.e., CPAM) as a flocculating agent; and filtering the flocculated separated pretreatment fluid with soluble components, colloidal material and primarily lignin containing particles to remove agglomerates.

METHODS OF CALCULATINAG LUNG DELIVERY AND DEPOSITION OF AEROSOL PARTICLES

EPA Science Inventory

Lung deposition of aerosol is measured by a variety of methods. Total lung deposition can be measured by monitoring inhaled and exhaled aerosols in situ by laser photometry or by collecting the aerosols on filters. The measurements can be performed accurately for stable monod...

Modeling of submicrometer aerosol penetration through sintered granular membrane filters.

PubMed

Marre, Sonia; Palmeri, John; Larbot, André; Bertrand, Marielle

2004-06-01

We present a deep-bed aerosol filtration model that can be used to estimate the efficiency of sintered granular membrane filters in the region of the most penetrating particle size. In this region the capture of submicrometer aerosols, much smaller than the filter pore size, takes place mainly via Brownian diffusion and direct interception acting in synergy. By modeling the disordered sintered grain packing of such filters as a simple cubic lattice, and mapping the corresponding 3D connected pore volume onto a discrete cylindrical pore network, the efficiency of a granular filter can be estimated, using new analytical results for the efficiency of cylindrical pores. This model for aerosol penetration in sintered granular filters includes flow slip and the kinetics of particle capture by the pore surface. With a unique choice for two parameters, namely the structural tortuosity and effective kinetic coefficient of particle adsorption, this semiempirical model can account for the experimental efficiency of a new class of "high-efficiency particulate air" ceramic membrane filters as a function of particle size over a wide range of filter thickness and texture (pore size and porosity) and operating conditions (face velocity).

Development of an Advanced Respirator Fit Test Headform (Postprint)

DTIC Science & Technology

2012-11-01

needed to measure the fit of N95 filtering facepiece respirators (FFRs) for protection studies against viable airborne particles. The objective of...N95 filtering facepiece respirators (FFRs) for pro- tection studies against viable airborne particles. A Static (i.e., non-moving, non-speaking...The N95 class of filtering facepiece respirators (FFRs) is commonly used to re- duce exposure to airborne particles, including oil-free aerosols (dusts

Department of Defense Enhanced Particulate Matter Surveillance Program (EPMSP)

DTIC Science & Technology

2008-02-01

on Teflon® membrane, 23,807 on quartz fiber, and several million single particle analyses on Nuclepore® filters. Analytical results were...Nuclepore® filters, the sampling period was two hours, so as to provide lightly loaded filters with dispersed single particles, as required for CCSEM...membrane, 23,807 on quartz fiber, and several million single particle analyses on Nuclepore®. All results, together with summary tables and more than

An Integrated Approach to Indoor and Outdoor Localization

DTIC Science & Technology

2017-04-17

localization estimate, followed by particle filter based tracking. Initial localization is performed using WiFi and image observations. For tracking we...source. A two-step process is proposed that performs an initial localization es-timate, followed by particle filter based t racking. Initial...mapped, it is possible to use them for localization [20, 21, 22]. Haverinen et al. show that these fields could be used with a particle filter to

Evaluation of environmental filtration control of engineered nanoparticles using the Harvard Versatile Engineered Nanomaterial Generation System (VENGES)

NASA Astrophysics Data System (ADS)

Tsai, Candace S.-J.; Echevarría-Vega, Manuel E.; Sotiriou, Georgios A.; Santeufemio, Christopher; Schmidt, Daniel; Demokritou, Philip; Ellenbecker, Michael

2012-05-01

Applying engineering controls to airborne engineered nanoparticles (ENPs) is critical to prevent environmental releases and worker exposure. This study evaluated the effectiveness of two air sampling and six air cleaning fabric filters at collecting ENPs using industrially relevant flame-made engineered nanoparticles generated using a versatile engineered nanomaterial generation system (VENGES), recently designed and constructed at Harvard University. VENGES has the ability to generate metal and metal oxide exposure atmospheres while controlling important particle properties such as primary particle size, aerosol size distribution, and agglomeration state. For this study, amorphous SiO2 ENPs with a 15.4 nm primary particle size were generated and diluted with HEPA-filtered air. The aerosol was passed through the filter samples at two different filtration face velocities (2.3 and 3.5 m/min). Particle concentrations as a function of particle size were measured upstream and downstream of the filters using a specially designed filter test system to evaluate filtration efficiency. Real time instruments (FMPS and APS) were used to measure particle concentration for diameters from 5 to 20,000 nm. Membrane-coated fabric filters were found to have enhanced nanoparticle collection efficiency by 20-46 % points compared to non-coated fabric and could provide collection efficiency above 95 %.

Evaluation of environmental filtration control of engineered nanoparticles using the Harvard Versatile Engineered Nanomaterial Generation System (VENGES)

PubMed Central

Echevarría-Vega, Manuel E.; Sotiriou, Georgios A.; Santeufemio, Christopher; Schmidt, Daniel; Demokritou, Philip; Ellenbecker, Michael

2013-01-01

Applying engineering controls to airborne engineered nanoparticles (ENPs) is critical to prevent environmental releases and worker exposure. This study evaluated the effectiveness of two air sampling and six air cleaning fabric filters at collecting ENPs using industrially relevant flame-made engineered nanoparticles generated using a versatile engineered nanomaterial generation system (VENGES), recently designed and constructed at Harvard University. VENGES has the ability to generate metal and metal oxide exposure atmospheres while controlling important particle properties such as primary particle size, aerosol size distribution, and agglomeration state. For this study, amorphous SiO2 ENPs with a 15.4 nm primary particle size were generated and diluted with HEPA-filtered air. The aerosol was passed through the filter samples at two different filtration face velocities (2.3 and 3.5 m/min). Particle concentrations as a function of particle size were measured upstream and downstream of the filters using a specially designed filter test system to evaluate filtration efficiency. Real time instruments (FMPS and APS) were used to measure particle concentration for diameters from 5 to 20,000 nm. Membrane-coated fabric filters were found to have enhanced nanoparticle collection efficiency by 20–46 % points compared to non-coated fabric and could provide collection efficiency above 95 %. PMID:23412707

Anti-clogging filter system

DOEpatents

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.

Anti-clogging filter system

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

Brown, Erik P.

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 thatmore » preferentially directs the larger particulates to one area of the filter material allowing the remainder of the filter material to remain more efficient.« less

Statistical Orbit Determination using the Particle Filter for Incorporating Non-Gaussian Uncertainties

NASA Technical Reports Server (NTRS)

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

2012-01-01

The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.

INS/GNSS Tightly-Coupled Integration Using Quaternion-Based AUPF for USV.

PubMed

Xia, Guoqing; Wang, Guoqing

2016-08-02

This paper addresses the problem of integration of Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) for the purpose of developing a low-cost, robust and highly accurate navigation system for unmanned surface vehicles (USVs). A tightly-coupled integration approach is one of the most promising architectures to fuse the GNSS data with INS measurements. However, the resulting system and measurement models turn out to be nonlinear, and the sensor stochastic measurement errors are non-Gaussian and distributed in a practical system. Particle filter (PF), one of the most theoretical attractive non-linear/non-Gaussian estimation methods, is becoming more and more attractive in navigation applications. However, the large computation burden limits its practical usage. For the purpose of reducing the computational burden without degrading the system estimation accuracy, a quaternion-based adaptive unscented particle filter (AUPF), which combines the adaptive unscented Kalman filter (AUKF) with PF, has been proposed in this paper. The unscented Kalman filter (UKF) is used in the algorithm to improve the proposal distribution and generate a posterior estimates, which specify the PF importance density function for generating particles more intelligently. In addition, the computational complexity of the filter is reduced with the avoidance of the re-sampling step. Furthermore, a residual-based covariance matching technique is used to adapt the measurement error covariance. A trajectory simulator based on a dynamic model of USV is used to test the proposed algorithm. Results show that quaternion-based AUPF can significantly improve the overall navigation accuracy and reliability.

Measurements of particle backscatter, extinction, and lidar ratio at 1064 nm with the rotational raman method in Polly-XT

NASA Astrophysics Data System (ADS)

Engelmann, Ronny; Haarig, Moritz; Baars, Holger; Ansmann, Albert; Kottas, Michael; Marinou, Eleni

2018-04-01

We replaced a 1064-nm interference filter of a Polly-XT lidar system by a 1058-nm filter to observe pure rotational Raman backscattering from atmospheric Nitrogen and Oxygen. Polly-XT is compact Raman lidar with a Nd:YAG laser (20 Hz, 200 mJ at 1064 nm) and a 30-cm telescope mirror which applies photomultipliers in photoncounting mode. We present the first measured signals at 1058 nm and the derived extinction profile from measurements aboard RV Polarstern and in Leipzig. In combination with another Polly-XT system we could also derive particle backscatter and lidar ratio profiles at 1064 nm.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Kalman-variant estimators for state of charge in lithium-sulfur batteries

NASA Astrophysics Data System (ADS)

Propp, Karsten; Auger, Daniel J.; Fotouhi, Abbas; Longo, Stefano; Knap, Vaclav

2017-03-01

Lithium-sulfur batteries are now commercially available, offering high specific energy density, low production costs and high safety. However, there is no commercially-available battery management system for them, and there are no published methods for determining state of charge in situ. This paper describes a study to address this gap. The properties and behaviours of lithium-sulfur are briefly introduced, and the applicability of 'standard' lithium-ion state-of-charge estimation methods is explored. Open-circuit voltage methods and 'Coulomb counting' are found to have a poor fit for lithium-sulfur, and model-based methods, particularly recursive Bayesian filters, are identified as showing strong promise. Three recursive Bayesian filters are implemented: an extended Kalman filter (EKF), an unscented Kalman filter (UKF) and a particle filter (PF). These estimators are tested through practical experimentation, considering both a pulse-discharge test and a test based on the New European Driving Cycle (NEDC). Experimentation is carried out at a constant temperature, mirroring the environment expected in the authors' target automotive application. It is shown that the estimators, which are based on a relatively simple equivalent-circuit-network model, can deliver useful results. If the three estimators implemented, the unscented Kalman filter gives the most robust and accurate performance, with an acceptable computational effort.

Methodology for modeling the microbial contamination of air filters.

PubMed

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.

Independent motion detection with a rival penalized adaptive particle filter

NASA Astrophysics Data System (ADS)

Becker, Stefan; Hübner, Wolfgang; Arens, Michael

2014-10-01

Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic filter for real-time detection and tracking of independently moving objects. The proposed approach introduces a competition scheme between particles in order to ensure an improved multi-modality. Further, the filter design helps to generate a particle distribution which is homogenous even in the presence of multiple targets showing non-rigid motion patterns. The effectiveness of the method is shown on exemplary outdoor sequences.

Absorption/transmission measurements of PSAP particle-laden filters from the Biomass Burning Observation Project (BBOP) field campaign

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

Presser, Cary; Nazarian, Ashot; Conny, Joseph M.

Absorptivity measurements with a laser-heating approach, referred to as the laser-driven thermal reactor (LDTR), were carried out in the infrared and applied at ambient (laboratory) nonreacting conditions to particle-laden filters from a three-wavelength (visible) particle/soot absorption photometer (PSAP). Here, the particles were obtained during the Biomass Burning Observation Project (BBOP) field campaign. The focus of this study was to determine the particle absorption coefficient from field-campaign filter samples using the LDTR approach, and compare results with other commercially available instrumentation (in this case with the PSAP, which has been compared with numerous other optical techniques).

Absorption/transmission measurements of PSAP particle-laden filters from the Biomass Burning Observation Project (BBOP) field campaign

DOE PAGES

Presser, Cary; Nazarian, Ashot; Conny, Joseph M.; ...

2016-12-02

Absorptivity measurements with a laser-heating approach, referred to as the laser-driven thermal reactor (LDTR), were carried out in the infrared and applied at ambient (laboratory) nonreacting conditions to particle-laden filters from a three-wavelength (visible) particle/soot absorption photometer (PSAP). Here, the particles were obtained during the Biomass Burning Observation Project (BBOP) field campaign. The focus of this study was to determine the particle absorption coefficient from field-campaign filter samples using the LDTR approach, and compare results with other commercially available instrumentation (in this case with the PSAP, which has been compared with numerous other optical techniques).

RB Particle Filter Time Synchronization Algorithm Based on the DPM Model.

PubMed

Guo, Chunsheng; Shen, Jia; Sun, Yao; Ying, Na

2015-09-03

Time synchronization is essential for node localization, target tracking, data fusion, and various other Wireless Sensor Network (WSN) applications. To improve the estimation accuracy of continuous clock offset and skew of mobile nodes in WSNs, we propose a novel time synchronization algorithm, the Rao-Blackwellised (RB) particle filter time synchronization algorithm based on the Dirichlet process mixture (DPM) model. In a state-space equation with a linear substructure, state variables are divided into linear and non-linear variables by the RB particle filter algorithm. These two variables can be estimated using Kalman filter and particle filter, respectively, which improves the computational efficiency more so than if only the particle filter was used. In addition, the DPM model is used to describe the distribution of non-deterministic delays and to automatically adjust the number of Gaussian mixture model components based on the observational data. This improves the estimation accuracy of clock offset and skew, which allows achieving the time synchronization. The time synchronization performance of this algorithm is also validated by computer simulations and experimental measurements. The results show that the proposed algorithm has a higher time synchronization precision than traditional time synchronization algorithms.

Sorption and degradation of petroleum hydrocarbons, polycyclic aromatic hydrocarbons, alkylphenols, bisphenol A and phthalates in landfill leachate using sand, activated carbon and peat filters.

PubMed

Kalmykova, Yuliya; Moona, Nashita; Strömvall, Ann-Margret; Björklund, Karin

2014-06-01

Landfill leachates are repeatedly found contaminated with organic pollutants, such as alkylphenols (APs), phthalates and polycyclic aromatic hydrocarbons (PAHs) at levels exceeding water quality standards. It has been shown that these pollutants may be present in the colloidal and truly dissolved phase in contaminated water, making particle separation an inefficient removal method. The aim of this study was to investigate sorption and degradation of petroleum hydrocarbons (PHCs), selected APs, bisphenol A (BPA), phthalates and PAHs from landfill leachate using sand, granulated activated carbon (GAC) and peat moss filters. A pilot plant was installed at an inactive landfill with mixed industrial and household waste and samples were collected before and after each filter during two years. Leachate pre-treated in oil separator and sedimentation pond failed to meet water quality standards in most samples and little improvement was seen after the sand filter. These techniques are based on particle removal, whereas the analysed pollutants are found, to varying degrees, bound to colloids or dissolved. However, even highly hydrophobic compounds expected to be particle-bound, such as the PHCs and high-molecular weight PAHs, were poorly removed in the sand filter. The APs and BPA were completely removed by the GAC filter, while mass balance calculations indicate that 50-80% of the investigated phenols were removed in the peat filter. Results suggest possible AP degradation in peat filters. No evidence of phthalate degradation in the landfill, pond or the filters was found. The PHCs were completely removed in 50% and 35% of the measured occasions in the GAC and peat filters, respectively. The opposite trend was seen for removal of PAHs in GAC (50%) and peat (63%). Oxygenated PAHs with high toxicity were found in the leachates but not in the pond sediment. These compounds are likely formed in the pond water, which is alarming because sedimentation ponds are commonly used treatment techniques. The oxy-PAHs were effectively removed in the GAC, and especially the peat filter. It was hypothesized that dissolved compounds would adsorb equally well to the peat and GAC filters. This was not completely supported as the GAC filter was in general more efficient than peat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method.

PubMed

Saito, Masatoshi

2009-08-01

Dual-energy computed tomography (DECT) has the potential for measuring electron density distribution in a human body to predict the range of particle beams for treatment planning in proton or heavy-ion radiotherapy. However, thus far, a practical dual-energy method that can be used to precisely determine electron density for treatment planning in particle radiotherapy has not been developed. In this article, another DECT technique involving a balanced filter method using a conventional x-ray tube is described. For the spectral optimization of DECT using balanced filters, the author calculates beam-hardening error and air kerma required to achieve a desired noise level in electron density and effective atomic number images of a cylindrical water phantom with 50 cm diameter. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimized parameters were applied to cases with different phantom diameters ranging from 5 to 50 cm for the calculations. The author predicts that the optimal combination of tube voltages would be 80 and 140 kV with Tb/Hf and Bi/Mo filter pairs for the 50-cm-diameter water phantom. When a single phantom calibration at a diameter of 25 cm was employed to cover all phantom sizes, maximum absolute beam-hardening errors were 0.3% and 0.03% for electron density and effective atomic number, respectively, over a range of diameters of the water phantom. The beam-hardening errors were 1/10 or less as compared to those obtained by conventional DECT, although the dose was twice that of the conventional DECT case. From the viewpoint of beam hardening and the tube-loading efficiency, the present DECT using balanced filters would be significantly more effective in measuring the electron density than the conventional DECT. Nevertheless, further developments of low-exposure imaging technology should be necessary as well as x-ray tubes with higher outputs to apply DECT coupled with the balanced filter method for clinical use.

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

PubMed

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.

Verification of Eulerian-Eulerian and Eulerian-Lagrangian simulations for fluid-particle flows

NASA Astrophysics Data System (ADS)

Kong, Bo; Patel, Ravi G.; Capecelatro, Jesse; Desjardins, Olivier; Fox, Rodney O.

2017-11-01

In this work, we study the performance of three simulation techniques for fluid-particle flows: (1) a volume-filtered Euler-Lagrange approach (EL), (2) a quadrature-based moment method using the anisotropic Gaussian closure (AG), and (3) a traditional two-fluid model. By simulating two problems: particles in frozen homogeneous isotropic turbulence (HIT), and cluster-induced turbulence (CIT), the convergence of the methods under grid refinement is found to depend on the simulation method and the specific problem, with CIT simulations facing fewer difficulties than HIT. Although EL converges under refinement for both HIT and CIT, its statistical results exhibit dependence on the techniques used to extract statistics for the particle phase. For HIT, converging both EE methods (TFM and AG) poses challenges, while for CIT, AG and EL produce similar results. Overall, all three methods face challenges when trying to extract converged, parameter-independent statistics due to the presence of shocks in the particle phase. National Science Foundation and National Energy Technology Laboratory.

Particle sorting in Filter Porous Media and in Sediment Transport: A Numerical and Experimental Study

NASA Astrophysics Data System (ADS)

Glascoe, L. G.; Ezzedine, S. M.; Kanarska, Y.; Lomov, I. N.; Antoun, T.; Smith, J.; Hall, R.; Woodson, S.

2014-12-01

Understanding the flow of fines, particulate sorting in porous media and fractured media during sediment transport is significant for industrial, environmental, geotechnical and petroleum technologies to name a few. For example, the safety of dam structures requires the characterization of the granular filter ability to capture fine-soil particles and prevent erosion failure in the event of an interfacial dislocation. Granular filters are one of the most important protective design elements of large embankment dams. In case of cracking and erosion, if the filter is capable of retaining the eroded fine particles, then the crack will seal and the dam safety will be ensured. Here we develop and apply a numerical tool to thoroughly investigate the migration of fines in granular filters at the grain scale. The numerical code solves the incompressible Navier-Stokes equations and uses a Lagrange multiplier technique. The numerical code is validated to experiments conducted at the USACE and ERDC. These laboratory experiments on soil transport and trapping in granular media are performed in constant-head flow chamber filled with the filter media. Numerical solutions are compared to experimentally measured flow rates, pressure changes and base particle distributions in the filter layer and show good qualitative and quantitative agreement. To further the understanding of the soil transport in granular filters, we investigated the sensitivity of the particle clogging mechanism to various parameters such as particle size ratio, the magnitude of hydraulic gradient, particle concentration, and grain-to-grain contact properties. We found that for intermediate particle size ratios, the high flow rates and low friction lead to deeper intrusion (or erosion) depths. We also found that the damage tends to be shallower and less severe with decreasing flow rate, increasing friction and concentration of suspended particles. We have extended these results to more realistic heterogeneous population particulates for sediment transport. This work performed under the auspices of the US DOE by LLNL under Contract DE-AC52-07NA27344 and was sponsored by the Department of Homeland Security, Science and Technology Directorate, Homeland Security Advanced Research Projects Agency.

MODELING REFLECTANCE AND TRANSMITTANCE OF QUARTZ-FIBER FILTER SAMPLES CONTAINING ELEMENTAL CARBON PARTICLES: IMPLICATIONS FOR THERMAL/OPTICAL ANALYSIS. (R831086)

EPA Science Inventory

A radiative transfer scheme that considers absorption, scattering, and distribution of light-absorbing elemental carbon (EC) particles collected on a quartz-fiber filter was developed to explain simultaneous filter reflectance and transmittance observations prior to and during...

Application of direct-reading and elemental carbon analysis methods to measure mass-based penetration of carbon nanotubes through elastomeric half-face and filtering facepiece respirators.

PubMed

Vo, Evanly; Zhuang, Ziqing; Birch, Eileen; Birch, Quinn

2016-01-01

The aim of this study was to apply a direct-reading aerosol instrument method and an elemental carbon (EC) analysis method to measure the mass-based penetration of single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) through elastomeric half-mask respirators (EHRs) and filtering facepiece respirators (FFRs). For the direct-reading aerosol instrument method, two scanning mobility particle sizer/aerodynamic particle sizer systems were used to simultaneously determine the upstream (outside respirator) and downstream (inside respirator) test aerosols. For the EC analysis method, upstream and downstream CNTs were collected on filter cassettes and then analyzed using a thermal-optical technique. CNT mass penetrations were found in both methods to be within the associated efficiency requirements for each type and class of the respirator models that were tested. Generally, the penetrations of SWCNTs and MWCNTs had a similar trend with penetration being the highest for the N95 EHRs, followed by N95 FFRs, P100 EHRs, and P100 FFRs. This trend held true for both methods; however, the CNT penetration determined by the direct-reading aerosol instrument method (0.009-1.09% for SWCNTs and 0.005-0.21% for MWCNTs) was greater relative to the penetration values found through EC analysis method (0.007-0.69% for SWCNTs and 0.004-0.13% for MWCNTs). The results of this study illustrate considerations for how the methods can be used to evaluate penetration of morphologically complex materials through FFRs and EHRs.

A new method for isolation of polyethylene wear debris from tissue and synovial fluid.

PubMed

Visentin, Manuela; Stea, Susanna; Squarzoni, Stefano; Antonietti, Barbara; Reggiani, Matteo; Toni, Aldo

2004-11-01

Sub-micron-sized ultrahigh molecular-weight polyethylene (PE) debris is generated in the joint space as a result of articulation and cyclic loading of an orthopaedic implant. Its characterization requires isolation and subsequent analysis by ultra-structural methods. An innovative method based on the digestion of paraffin-embedded tissue samples was proposed. Tissue slices were digested with sodium hypochlorite directly on polycarbonate filter. The same procedure could be applied also to fresh synovial fluid. Plastic particles were not lost or damaged during treatment. Chemical identification of particles was done by micro-Raman spectroscopy that confirmed purity of retrieved PE particles. Size and shape of PE particles were characterised using scanning electron microscopy and were comparable in number and morphology to the retrieval by other authors. Equivalent diameter ranged from 0.48 to 0.95microm and particle number ranged from 9 to 23x10(9)/cm(3).

Continuous particle separation using pressure-driven flow-induced miniaturizing free-flow electrophoresis (PDF-induced μ-FFE).

PubMed

Jeon, Hyungkook; Kim, Youngkyu; Lim, Geunbae

2016-01-28

In this paper, we introduce pressure-driven flow-induced miniaturizing free-flow electrophoresis (PDF-induced μ-FFE), a novel continuous separation method. In our separation system, the external flow and electric field are applied to particles, such that particle movement is affected by pressure-driven flow, electroosmosis, and electrophoresis. We then analyzed the hydrodynamic drag force and electrophoretic force applied to the particles in opposite directions. Based on this analysis, micro- and nano-sized particles were separated according to their electrophoretic mobilities with high separation efficiency. Because the separation can be achieved in a simple T-shaped microchannel, without the use of internal electrodes, it offers the advantages of low-cost, simple device fabrication and bubble-free operation, compared with conventional μ-FFE methods. Therefore, we expect the proposed separation method to have a wide range of filtering/separation applications in biochemical analysis.

Continuous particle separation using pressure-driven flow-induced miniaturizing free-flow electrophoresis (PDF-induced μ-FFE)

PubMed Central

Jeon, Hyungkook; Kim, Youngkyu; Lim, Geunbae

2016-01-01

In this paper, we introduce pressure-driven flow-induced miniaturizing free-flow electrophoresis (PDF-induced μ-FFE), a novel continuous separation method. In our separation system, the external flow and electric field are applied to particles, such that particle movement is affected by pressure-driven flow, electroosmosis, and electrophoresis. We then analyzed the hydrodynamic drag force and electrophoretic force applied to the particles in opposite directions. Based on this analysis, micro- and nano-sized particles were separated according to their electrophoretic mobilities with high separation efficiency. Because the separation can be achieved in a simple T-shaped microchannel, without the use of internal electrodes, it offers the advantages of low-cost, simple device fabrication and bubble-free operation, compared with conventional μ-FFE methods. Therefore, we expect the proposed separation method to have a wide range of filtering/separation applications in biochemical analysis. PMID:26819221

Pyrolysis-gas chromatography/mass spectrometry analyses of biological particulates collected during recent space shuttle missions

NASA Technical Reports Server (NTRS)

Matney, M. L.; Limero, T. F.; James, J. T.

1994-01-01

Biological particulates collected on air filters during shuttle missions (STS-40 and STS-42) were identified using pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). A method was developed for identifying the atmospheric particles and their sources through the analysis of standard materials and the selection of "marker" compounds specific to the particle type. Pyrolysis spectra of biological standards were compared with those of airborne particles collected during two space shuttle missions; marker compounds present in the shuttle particle spectra were matched with those of the standards to identify the source of particles. Particles of 0,5--1-mm diameter and weighing as little as 40 micrograms could be identified using this technique. The Py-GC/MS method identified rat food and soilless plant-growth media as two sources of particles collected from the shuttle atmosphere during flight.

Trace element geochemistry of volcanic gases and particles from 1983--1984 eruptive episodes of Kilauea volcano

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

Crowe, B.M.; Finnegan, D.L.; Zoller, W.H.

1987-12-10

Compositional data have been obtained for volcanic gases and particles collected from fume emitted at the Pu'u O'o vent on the east rift zone of Kilauea volcano. The samples were collected by pumping fume through a filter pack system consisting of a front stage particulate filter followed by four base-treated filters (/sup 7/LiOH). Particles and condensed phases are trapped on the particulate filter, and acidic gases are collected on the treated filters. The filters are analyzed for 30 elements by instrumental neutron activation analysis. Fume samples were collected from the Pu'u O'o vent for two eruptive episodes: (1) 7 daysmore » after episode 11 (cooling vent samples) and (2) the stage of episode 13 (active vent samples).« less

International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

NASA Astrophysics Data System (ADS)

Kikuchi, Ryota; Misaka, Takashi; Obayashi, Shigeru

2016-04-01

An integrated method consisting of a proper orthogonal decomposition (POD)-based reduced-order model (ROM) and a particle filter (PF) is proposed for real-time prediction of an unsteady flow field. The proposed method is validated using identical twin experiments of an unsteady flow field around a circular cylinder for Reynolds numbers of 100 and 1000. In this study, a PF is employed (ROM-PF) to modify the temporal coefficient of the ROM based on observation data because the prediction capability of the ROM alone is limited due to the stability issue. The proposed method reproduces the unsteady flow field several orders faster than a reference numerical simulation based on Navier-Stokes equations. Furthermore, the effects of parameters, related to observation and simulation, on the prediction accuracy are studied. Most of the energy modes of the unsteady flow field are captured, and it is possible to stably predict the long-term evolution with ROM-PF.

Dilution-based emissions sampling from stationary sources: Part 2--Gas-fired combustors compared with other fuel-fired systems.

PubMed

England, Glenn C; Watson, John G; Chow, Judith C; Zielinska, Barbara; Chang, M C Oliver; Loos, Karl R; Hidy, George M

2007-01-01

With the recent focus on fine particle matter (PM2.5), new, self-consistent data are needed to characterize emissions from combustion sources. Such data are necessary for health assessment and air quality modeling. To address this need, emissions data for gas-fired combustors are presented here, using dilution sampling as the reference. The dilution method allows for collection of emitted particles under conditions simulating cooling and dilution during entry from the stack into the air. The sampling and analysis of the collected particles in the presence of precursor gases, SO2 nitrogen oxide, volatile organic compound, and NH3 is discussed; the results include data from eight gas fired units, including a dual-fuel institutional boiler and a diesel engine powered electricity generator. These data are compared with results in the literature for heavy-duty diesel vehicles and stationary sources using coal or wood as fuels. The results show that the gas-fired combustors have very low PM2.5 mass emission rates in the range of approximately 10(-4) lb/million Btu (MMBTU) compared with the diesel backup generator with particle filter, with approximately 5 x 10(-3) lb/MMBTU. Even higher mass emission rates are found in coal-fired systems, with rates of approximately 0.07 lb/MMBTU for a bag-filter-controlled pilot unit burning eastern bituminous coal. The characterization of PM2.5 chemical composition from the gas-fired units indicates that much of the measured primary particle mass in PM2.5 samples is organic or elemental carbon and, to a much less extent, sulfate. Metal emissions are quite low compared with the diesel engines and the coal- or wood-fueled combustors. The metals found in the gas-fired combustor particles are low in concentration, similar in concentration to ambient particles. The interpretation of the particulate carbon emissions is complicated by the fact that an approximately equal amount of particulate carbon (mainly organic carbon) is found on the particle collector and a backup filter. It is likely that measurement artifacts, mostly adsorption of volatile organic compounds on quartz filters, are positively biasing "true" particulate carbon emission results.

Estimating snow depth of alpine snowpack via airborne multifrequency passive microwave radiance observations: Colorado, USA

NASA Astrophysics Data System (ADS)

Kim, R. S.; Durand, M. T.; Li, D.; Baldo, E.; Margulis, S. A.; Dumont, M.; Morin, S.

2017-12-01

This paper presents a newly-proposed snow depth retrieval approach for mountainous deep snow using airborne multifrequency passive microwave (PM) radiance observation. In contrast to previous snow depth estimations using satellite PM radiance assimilation, the newly-proposed method utilized single flight observation and deployed the snow hydrologic models. This method is promising since the satellite-based retrieval methods have difficulties to estimate snow depth due to their coarse resolution and computational effort. Indeed, this approach consists of particle filter using combinations of multiple PM frequencies and multi-layer snow physical model (i.e., Crocus) to resolve melt-refreeze crusts. The method was performed over NASA Cold Land Processes Experiment (CLPX) area in Colorado during 2002 and 2003. Results showed that there was a significant improvement over the prior snow depth estimates and the capability to reduce the prior snow depth biases. When applying our snow depth retrieval algorithm using a combination of four PM frequencies (10.7,18.7, 37.0 and 89.0 GHz), the RMSE values were reduced by 48 % at the snow depth transects sites where forest density was less than 5% despite deep snow conditions. This method displayed a sensitivity to different combinations of frequencies, model stratigraphy (i.e. different number of layering scheme for snow physical model) and estimation methods (particle filter and Kalman filter). The prior RMSE values at the forest-covered areas were reduced by 37 - 42 % even in the presence of forest cover.

Microwave Bandpass Filter Based on Mie-Resonance Extraordinary Transmission

PubMed Central

Pan, Xiaolong; Wang, Haiyan; Zhang, Dezhao; Xun, Shuang; Ouyang, Mengzhu; Fan, Wentao; Guo, Yunsheng; Wu, Ye; Huang, Shanguo; Bi, Ke; Lei, Ming

2016-01-01

Microwave bandpass filter structure has been designed and fabricated by filling the periodically metallic apertures with dielectric particles. The microwave cannot transmit through the metallic subwavelength apertures. By filling the metallic apertures with dielectric particles, a transmission passband with insertion loss 2 dB appears at the frequency of 10–12 GHz. Both simulated and experimental results show that the passband is induced by the Mie resonance of the dielectric particles. In addition, the passband frequency can be tuned by the size and the permittivity of the dielectric particles. This approach is suitable to fabricate the microwave bandpass filters. PMID:27992440

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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 soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

Measurements of light-absorbing particles on the glaciers in the Cordillera Blanca, Peru

NASA Astrophysics Data System (ADS)

Schmitt, C. G.; All, J. D.; Schwarz, J. P.; Arnott, W. P.; Cole, R. J.; Lapham, E.; Celestian, A.

2015-02-01

Glaciers in the tropical Andes have been rapidly losing mass since the 1970s. In addition to the documented increase in temperature, increases in light-absorbing particles deposited on glaciers could be contributing to the observed glacier loss. Here we report on measurements of light-absorbing particles sampled from glaciers during three surveys in the Cordillera Blanca Mountains in Peru. During three research expeditions in the dry seasons (May-August) of 2011, 2012 and 2013, 240 snow samples were collected from 15 mountain peaks over altitudes ranging from 4800 to nearly 6800 m. Several mountains were sampled each of the 3 years and some mountains were sampled multiple times during the same year. Collected snow samples were melted and filtered in the field then later analyzed using the Light Absorption Heating Method (LAHM), a new technique that measures the ability of particles on filters to absorb visible light. LAHM results have been calibrated using filters with known amounts of fullerene soot, a common industrial surrogate for black carbon (BC). As sample filters often contain dust in addition to BC, results are presented in terms of effective black carbon (eBC). During the 2013 survey, snow samples were collected and kept frozen for analysis with a Single Particle Soot Photometer (SP2). Calculated eBC mass from the LAHM analysis and the SP2 refractory black carbon (rBC) results were well correlated (r2 = 0.92). These results indicate that a substantial portion of the light-absorbing particles in the more polluted regions were likely BC. The 3 years of data show that glaciers in the Cordillera Blanca Mountains close to human population centers have substantially higher levels of eBC (as high as 70 ng g-1) than remote glaciers (as low as 2.0 ng g-1 eBC), indicating that population centers can influence local glaciers by sourcing BC.

Comparison of field portable measurements of ultrafine TiO2: X-ray fluorescence, laser-induced breakdown spectroscopy, and Fourier-transform infrared spectroscopy.

PubMed

LeBouf, Ryan F; Miller, Arthur L; Stipe, Christopher; Brown, Jonathan; Murphy, Nate; Stefaniak, Aleksandr B

2013-06-01

Laboratory measurements of ultrafine titanium dioxide (TiO2) particulate matter loaded on filters were made using three field portable methods (X-ray fluorescence (XRF), laser-induced breakdown spectroscopy (LIBS), and Fourier-transform infrared (FTIR) spectroscopy) to assess their potential for determining end-of-shift exposure. Ultrafine TiO2 particles were aerosolized and collected onto 37 mm polycarbonate track-etched (PCTE) filters in the range of 3 to 578 μg titanium (Ti). Limit of detection (LOD), limit of quantification (LOQ), and calibration fit were determined for each measurement method. The LOD's were 11.8, 0.032, and 108 μg Ti per filter, for XRF, LIBS, and FTIR, respectively and the LOQ's were 39.2, 0.11, and 361 μg Ti per filter, respectively. The XRF calibration curve was linear over the widest dynamic range, up to the maximum loading tested (578 μg Ti per filter). LIBS was more sensitive but, due to the sample preparation method, the highest loaded filter measurable was 252 μg Ti per filter. XRF and LIBS had good predictability measured by regressing the predicted mass to the gravimetric mass on the filter. XRF and LIBS produced overestimations of 4% and 2%, respectively, with coefficients of determination (R(2)) of 0.995 and 0.998. FTIR measurements were less dependable due to interference from the PCTE filter media and overestimated mass by 2% with an R(2) of 0.831.

Modeling Human Performance in Restless Bandits with Particle Filters (Preprint)

DTIC Science & Technology

2009-01-01

respond to changes ( Gallistel , 2001). Here, we use a particle filter approach to finding solutions to the restless bandit problem. Particle...Experimental Psychology: Learning, Memory, and Cognition, 10(2), 258-270. Gallistel , C. R., Mark, T., King, A., & Latham, P. E. (2001). The rat

Ultrafine particle and fiber production in microgravity

NASA Technical Reports Server (NTRS)

Webb, George W. (Inventor)

1988-01-01

In a system and method for producing ultrafine particles and ultrafine fibers of a given source material by evaporating and condensing the material in a gas atmosphere that includes inert gas. A smaller, more narrow size distribution is accomplished by producing the particles and fibers in a microgravity environment in order to reduce particle coalescence caused by convection currents. Particle coalescence also is reduced in an Earth gravity environment by controlling the convection currents. Condensed particles are collected either by providing an electrostatic field or a spatially varying magnetic field or by causing the gas to move through a filter which collects the particles. Nonferromagnetic material fibers are produced and collected by electrodes which produce an electro- static field. Ferromagnetic particles are collected by spatially varying magnetic fields.

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

DTIC Science & Technology

2014-08-24

Distributed Monte Carlo Information Fusion and Distributed Particle Filtering Isaac L. Manuel and Adrian N. Bishop Australian National University and...2 20 + vit , (21) where vit is Gaussian white noise with a random variance. We initialised the filters with the state xi0 = 0.1 for all i ∈ V . This

Fabrication of an anti-viral air filter with SiO₂-Ag nanoparticles and performance evaluation in a continuous airflow condition.

PubMed

Joe, Yun Haeng; Woo, Kyoungja; Hwang, Jungho

2014-09-15

In this study, SiO2 nanoparticles surface coated with Ag nanoparticles (SA particles) were fabricated to coat a medium air filter. The pressure drop, filtration efficiency, and anti-viral ability of the filter were evaluated against aerosolized bacteriophage MS2 in a continuous air flow condition. A mathematical approach was developed to measure the anti-viral ability of the filter with various virus deposition times. Moreover, two quality factors based on the anti-viral ability of the filter, and a traditional quality factor based on filtration efficiency, were calculated. The filtration efficiency and pressure drop increased with decreasing media velocity and with increasing SA particle coating level. The anti-viral efficiency also increased with increasing SA particle coating level, and decreased by with increasing virus deposition time. Consequently, SA particle coating on a filter does not have significant effects on filtration quality, and there is an optimal coating level to produce the highest anti-viral quality. Copyright © 2014 Elsevier B.V. All rights reserved.

Methodology for Modeling the Microbial Contamination of Air Filters

PubMed Central

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. PMID:24523908

Technical note: improved methodology for analyses of acid detergent fiber and acid detergent lignin.

PubMed

Raffrenato, E; Van Amburgh, M E

2011-07-01

The objective of this study was to evaluate the methodology of the acid detergent lignin (ADL) assay in an effort to evaluate particle loss, improve repeatability, and decrease variation within and among samples. The original ADL method relied on asbestos as a filtering aid, but that was removed in 1989 with the mandate from the Environmental Protection Agency to eliminate asbestos in the environment. Furthermore, recent work on fiber methodology indicated that pore size in the Gooch sintered glass crucible (40-60 μm) was too large to trap all of the small particles associated with neutral detergent fiber (NDF) and acid detergent fiber (ADF). Thus, any loss of ADF could potentially result in a loss of ADL. Sixty forages including conventional and brown midrib corn silages, alfalfa silages and hays, mature grasses, early vegetative grasses, and 9 feces samples, were analyzed sequentially for ADF and ADL as outlined in the 1973 procedure of Van Soest except for the use of the asbestos fiber. A glass microfiber filter with a 1.5-μm pore size was chosen as a filtering aid because it met the criteria required by the assay: glass, heat resistant, acid resistant, chemically inert, and hydrophobic. To compare with the current ADF and ADL assays, the assays were conducted with either no filter or the glass filter inserted into crucibles, rinsed with acetone, and then according to the 1973 procedure of Van Soest. The samples analyzed covered a range from 18.11 to 55.79% ADF and from 0.96 to 9.94% ADL on a dry matter (DM) basis. With the use of the filter, the mean ADF values increased 4.2% and mean ADL values increased 18.9%. Overall, both ADF and ADL values were greater with the use of the glass microfiber filter than without, indicating that as the type of sample analyzed changed, use of the Gooch crucible without the filtering aid results in particle loss. The adoption of the use of a small pore size (1.5 μm) glass microfiber filter to improve filtration and recovery of ADF and ADL and to reduce variation in the ADL assay is recommended, especially when sintered glass bottom crucibles are used. These differences in recovery and repeatability have implications for other fiber and lignin methods, as well as for estimating the potential changes in digestibility of fibrous feeds and feed quality. Copyright © 2011 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Sintered composite medium and filter

DOEpatents

Bergman, Werner

1987-01-01

A particulate filter medium is formed of a sintered composite of 0.5 micron diameter quartz fibers and 2 micron diameter stainless steel fibers. A preferred composition is about 40 vol. % quartz and about 60 vol. % stainless steel fibers. The media is sintered at about 1100.degree. C. to bond the stainless steel fibers into a cage network which holds the quartz fibers. High filter efficiency and low flow resistance are provided by the smaller quartz fibers. High strength is provided by the stainless steel fibers. The resulting media has a high efficiency and low pressure drop similar to the standard HEPA media, with tensile strength at least four times greater, and a maximum operating temperature of about 550.degree. C. The invention also includes methods to form the composite media and a HEPA filter utilizing the composite media. The filter media can be used to filter particles in both liquids and gases.

Sintered composite filter

DOEpatents

Bergman, W.

1986-05-02

A particulate filter medium formed of a sintered composite of 0.5 micron diameter quartz fibers and 2 micron diameter stainless steel fibers is described. Preferred composition is about 40 vol.% quartz and about 60 vol.% stainless steel fibers. The media is sintered at about 1100/sup 0/C to bond the stainless steel fibers into a cage network which holds the quartz fibers. High filter efficiency and low flow resistance are provided by the smaller quartz fibers. High strength is provided by the stainless steel fibers. The resulting media has a high efficiency and low pressure drop similar to the standard HEPA media, with tensile strength at least four times greater, and a maximum operating temperature of about 550/sup 0/C. The invention also includes methods to form the composite media and a HEPA filter utilizing the composite media. The filter media can be used to filter particles in both liquids and gases.

Particle preconcentrator

DOEpatents

Linker, Kevin L.; Conrad, Frank J.; Custer, Chad A.; Rhykerd, Jr., Charles L.

1998-01-01

An apparatus and method for preconcentrating particles and vapors. The preconcentrator apparatus permits detection of highly diluted amounts of particles in a main gas stream, such as a stream of ambient air. A main gas stream having airborne particles entrained therein is passed through a pervious screen. The particles accumulate upon the screen, as the screen acts as a sort of selective particle filter. The flow of the main gas stream is then interrupted by diaphragm shutter valves, whereupon a cross-flow of carrier gas stream is blown parallel past the faces of the screen to dislodge the accumulated particles and carry them to a particle or vapor detector, such as an ion mobility spectrometer. The screen may be heated, such as by passing an electrical current there through, to promote desorption of particles therefrom during the flow of the carrier gas. Various types of screens are disclosed. The apparatus and method of the invention may find particular utility in the fields of narcotics, explosives detection and chemical agents.

Particle preconcentrator

DOEpatents

Linker, Kevin L.; Conrad, Frank J.; Custer, Chad A.; Rhykerd, Jr., Charles L.

2005-09-20

An apparatus and method for preconcentrating particles and vapors. The preconcentrator apparatus permits detection of highly diluted amounts of particles in a main gas stream, such as a stream of ambient air. A main gas stream having airborne particles entrained therein is passed through a pervious screen. The particles accumulate upon the screen, as the screen acts as a sort of selective particle filter. The flow of the main gas stream is then interrupted by diaphragm shutter valves, whereupon a cross-flow of carrier gas stream is blown parallel past the faces of the screen to dislodge the accumulated particles and carry them to a particle or vapor detector, such as an ion mobility spectrometer. The screen may be heated, such as by passing an electrical current there through, to promote desorption of particles therefrom during the flow of the carrier gas. Various types of screens are disclosed. The apparatus and method of the invention may find particular utility in the fields of narcotics, explosives detection and chemical agents.

Particle preconcentrator

DOEpatents

Linker, Kevin L.; Conrad, Frank J.; Custer, Chad A.; Rhykerd, Jr., Charles L.

2000-01-01

An apparatus and method for preconcentrating particles and vapors. The preconcentrator apparatus permits detection of highly diluted amounts of particles in a main gas stream, such as a stream of ambient air. A main gas stream having airborne particles entrained therein is passed through a pervious screen. The particles accumulate upon the screen, as the screen acts as a sort of selective particle filter. The flow of the main gas stream is then interrupted by diaphragm shutter valves, whereupon a cross-flow of carrier gas stream is blown parallel past the faces of the screen to dislodge the accumulated particles and carry them to a particle or vapor detector, such as an ion mobility spectrometer. The screen may be heated, such as by passing an electrical current there through, to promote desorption of particles therefrom during the flow of the carrier gas. Various types of screens are disclosed. The apparatus and method of the invention may find particular utility in the fields of narcotics, explosives detection and chemical agents.

Particle preconcentrator

DOEpatents

Linker, K.L.; Conrad, F.J.; Custer, C.A.; Rhykerd, C.L. Jr.

1998-12-29

An apparatus and method are disclosed for preconcentrating particles and vapors. The preconcentrator apparatus permits detection of highly diluted amounts of particles in a main gas stream, such as a stream of ambient air. A main gas stream having airborne particles entrained therein is passed through a pervious screen. The particles accumulate upon the screen, as the screen acts as a sort of selective particle filter. The flow of the main gas stream is then interrupted by diaphragm shutter valves, whereupon a cross-flow of carrier gas stream is blown parallel past the faces of the screen to dislodge the accumulated particles and carry them to a particle or vapor detector, such as an ion mobility spectrometer. The screen may be heated, such as by passing an electrical current there through, to promote desorption of particles therefrom during the flow of the carrier gas. Various types of screens are disclosed. The apparatus and method of the invention may find particular utility in the fields of narcotics, explosives detection and chemical agents. 3 figs.

Ion beam-based studies for tribological phenomena

NASA Astrophysics Data System (ADS)

Racolta, P. M.; Popa-Simil, L.; Alexandreanu, B.

1996-06-01

Custom-designed experiments based on the Thin Layer Activation technique (TLA) were completed, providing information on the wear level of some engine components with additional data on transfer and adhesion of material between metallic friction couples using the RBS method. RBS experimental results concerning material transfer for a steel-brass friction couple are presented and discussed in the paper. Also, the types and concentrations of the wear products in used lubricant oils were determined by in-air PIXE. A sequential lubricant filtering-based procedure for determining the dimension distribution of the resulting radioactive wear particles by low level γ-spectrometry is presented. Experimental XRF spectra showing the non-homogeneous distribution of the retained waste particles on the filtering paper are shown.

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

Characterization of the relationship between ceramic pot filter water production and turbidity in source water.

PubMed

Salvinelli, Carlo; Elmore, A Curt; Reidmeyer, Mary R; Drake, K David; Ahmad, Khaldoun I

2016-11-01

Ceramic pot filters represent a common and effective household water treatment technology in developing countries, but factors impacting water production rate are not well-known. Turbidity of source water may be principal indicator in characterizing the filter's lifetime in terms of water production capacity. A flow rate study was conducted by creating four controlled scenarios with different turbidities, and influent and effluent water samples were tested for total suspended solids and particle size distribution. A relationship between average flow rate and turbidity was identified with a negative linear trend of 50 mLh -1 /NTU. Also, a positive linear relationship was found between the initial flow rate of the filters and average flow rate calculated over the 23 day life of the experiment. Therefore, it was possible to establish a method to estimate the average flow rate given the initial flow rate and the turbidity in the influent water source, and to back calculate the maximum average turbidity that would need to be maintained in order to achieve a specific average flow rate. However, long-term investigations should be conducted to assess how these relationships change over the expected CPF lifetime. CPFs rejected fine suspended particles (below 75 μm), especially particles with diameters between 0.375 μm and 10 μm. The results confirmed that ceramic pot filters are able to effectively reduce turbidity, but pretreatment of influent water should be performed to avoid premature failure. Copyright © 2016 Elsevier Ltd. All rights reserved.

40 CFR 799.6784 - TSCA water solubility: Column elution method; shake flask method.

Code of Federal Regulations, 2010 CFR

2010-07-01

... reaction quality should be used to apply the test substance to the carrier material. Double distilled water... this section. (i) With this apparatus, the microcolumn must be modified. A stopcock with 2-way action... particles invalidates the results, and the test should be repeated with improvements in the filtering action...

Reducing patients' exposures to asthma and allergy triggers in their homes: an evaluation of effectiveness of grades of forced air ventilation filters.

PubMed

Brown, Kathleen Ward; Minegishi, Taeko; Allen, Joseph G; McCarthy, John F; Spengler, John D; MacIntosh, David L

2014-08-01

Many interventions to reduce allergen levels in the home are recommended to asthma and allergy patients. One that is readily available and can be highly effective is the use of high performing filters in forced air ventilation systems. We conducted a modeling analysis of the effectiveness of filter-based interventions in the home to reduce airborne asthma and allergy triggers. This work used "each pass removal efficiency" applied to health-relevant size fractions of particles to assess filter performance. We assessed effectiveness for key allergy and asthma triggers based on applicable particle sizes for cat allergen, indoor and outdoor sources of particles <2.5 µm in diameter (PM2.5), and airborne influenza and rhinovirus. Our analysis finds that higher performing filters can have significant impacts on indoor particle pollutant levels. Filters with removal efficiencies of >70% for cat dander particles, fine particulate matter (PM2.5) and respiratory virus can lower concentrations of those asthma triggers and allergens in indoor air of the home by >50%. Very high removal efficiency filters, such as those rated a 16 on the nationally recognized Minimum Efficiency Removal Value (MERV) rating system, tend to be only marginally more effective than MERV12 or 13 rated filters. The results of this analysis indicate that use of a MERV12 or higher performing air filter in home ventilation systems can effectively reduce indoor levels of these common asthma and allergy triggers. These reductions in airborne allergens in turn may help reduce allergy and asthma symptoms, especially if employed in conjunction with other environmental management measures recommended for allergy and asthma patients.

Combined state and parameter identification of nonlinear structural dynamical systems based on Rao-Blackwellization and Markov chain Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Abhinav, S.; Manohar, C. S.

2018-03-01

The problem of combined state and parameter estimation in nonlinear state space models, based on Bayesian filtering methods, is considered. A novel approach, which combines Rao-Blackwellized particle filters for state estimation with Markov chain Monte Carlo (MCMC) simulations for parameter identification, is proposed. In order to ensure successful performance of the MCMC samplers, in situations involving large amount of dynamic measurement data and (or) low measurement noise, the study employs a modified measurement model combined with an importance sampling based correction. The parameters of the process noise covariance matrix are also included as quantities to be identified. The study employs the Rao-Blackwellization step at two stages: one, associated with the state estimation problem in the particle filtering step, and, secondly, in the evaluation of the ratio of likelihoods in the MCMC run. The satisfactory performance of the proposed method is illustrated on three dynamical systems: (a) a computational model of a nonlinear beam-moving oscillator system, (b) a laboratory scale beam traversed by a loaded trolley, and (c) an earthquake shake table study on a bending-torsion coupled nonlinear frame subjected to uniaxial support motion.

Measurement of the adhesion force between particles for high gradient magnetic separation of pneumatic conveyed powder products

NASA Astrophysics Data System (ADS)

Senkawa, K.; Nakai, Y.; Mishima, F.; Akiyama, Y.; Nishijima, S.

2011-11-01

In the industrial plants such as foods, medicines or industrial materials, there are big amount of issues on contamination by metallic wear debris originated from pipes of manufacturing lines. In this study, we developed a high gradient magnetic separation system (HGMS) under the dry process by using superconducting magnet to remove the ferromagnetic particles. One of the major problems of dry HGMS systems is, however, the blockage of magnetic filter caused by particle coagulation or deposition. In order to actualize the magnetic separation without blockage, we introduced pneumatic conveyance system as a new method to feed the powder. It is important to increase the drag force acting on the sufficiently dispersed particles, which require strong magnetic fields. To generate the strong magnetic fields, HGMS technique was examined which consists of a magnetic filter and a superconducting solenoid magnet. As a result of the magnetic separation experiment, it was shown that the separation efficiency changes due to the difference of the cohesive property of the particles. On the basis of the result, the adhesion force which acts between the ferromagnetic particles and the medium particles used for the magnetic separation was measured by Atomic Force Microscope (AFM), and cohesion of particles was studied from the aspect of interparticle interaction. We assessed a suitable flow velocity for magnetic separation according to the cohesive property of each particle based on the result.

Antibacterial performance of nano polypropylene filter media containing nano-TiO2 and clay particles

NASA Astrophysics Data System (ADS)

Shafiee, Sara; Zarrebini, Mohammad; Naghashzargar, Elham; Semnani, Dariush

2015-10-01

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-TiO2 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 TiO2 nanoparticles.

Standard filtration practices may significantly distort planktonic microbial diversity estimates.

PubMed

Padilla, Cory C; Ganesh, Sangita; Gantt, Shelby; Huhman, Alex; Parris, Darren J; Sarode, Neha; Stewart, Frank J

2015-01-01

Fractionation of biomass by filtration is a standard method for sampling planktonic microbes. It is unclear how the taxonomic composition of filtered biomass changes depending on sample volume. Using seawater from a marine oxygen minimum zone, we quantified the 16S rRNA gene composition of biomass on a prefilter (1.6 μm pore-size) and a downstream 0.2 μm filter over sample volumes from 0.05 to 5 L. Significant community shifts occurred in both filter fractions, and were most dramatic in the prefilter community. Sequences matching Vibrionales decreased from ~40 to 60% of prefilter datasets at low volumes (0.05-0.5 L) to less than 5% at higher volumes, while groups such at the Chromatiales and Thiohalorhabdales followed opposite trends, increasing from minor representation to become the dominant taxa at higher volumes. Groups often associated with marine particles, including members of the Deltaproteobacteria, Planctomycetes, and Bacteroidetes, were among those showing the greatest increase with volume (4 to 27-fold). Taxon richness (97% similarity clusters) also varied significantly with volume, and in opposing directions depending on filter fraction, highlighting potential biases in community complexity estimates. These data raise concerns for studies using filter fractionation for quantitative comparisons of aquatic microbial diversity, for example between free-living and particle-associated communities.

Collecting Protein Biomarkers in Breath Using Electret Filters: A Preliminary Method on New Technical Model and Human Study.

PubMed

Li, Wang; Pi, Xitian; Qiao, Panpan; Liu, Hongying

2016-01-01

Biomarkers in exhaled breath are useful for respiratory disease diagnosis in human volunteers. Conventional methods that collect non-volatile biomarkers, however, necessitate an extensive dilution and sanitation processes that lowers collection efficiencies and convenience of use. Electret filter emerged in recent decade to collect virus biomarkers in exhaled breath given its simplicity and effectiveness. To investigate the capability of electret filters to collect protein biomarkers, a model that consists of an atomizer that produces protein aerosol and an electret filter that collects albumin and carcinoembryonic antigen-a typical biomarker in lung cancer development- from the atomizer is developed. A device using electret filter as the collecting medium is designed to collect human albumin from exhaled breath of 6 volunteers. Comparison of the collecting ability between the electret filter method and other 2 reported methods is finally performed based on the amounts of albumin collected from human exhaled breath. In conclusion, a decreasing collection efficiency ranging from 17.6% to 2.3% for atomized albumin aerosol and 42% to 12.5% for atomized carcinoembryonic antigen particles is found; moreover, an optimum volume of sampling human exhaled breath ranging from 100 L to 200 L is also observed; finally, the self-designed collecting device shows a significantly better performance in collecting albumin from human exhaled breath than the exhaled breath condensate method (p<0.05) but is not significantly more effective than reported 3-stage impactor method (p>0.05). In summary, electret filters are potential in collecting non-volatile biomarkers in human exhaled breath not only because it was simpler, cheaper and easier to use than traditional methods but also for its better collecting performance.

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

PubMed

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.

Method to Remove Particulate Matter from Dusty Gases at Low Pressures

NASA Technical Reports Server (NTRS)

Calle, Carlos; Clements, J. Sid

2012-01-01

Future human exploration of Mars will rely on local Martian resources to reduce the mass, cost, and risk of space exploration launched from Earth. NASA's In Situ Resource Utilization (ISRU) Project seeks to produce mission consumables from local Martian resources, such as atmospheric gas. The Martian atmosphere, however, contains dust particles in the 2-to-10 -micrometer range. These dust particles must be removed before the Martian atmospheric gas can be processed. The low pressure of the Martian atmosphere, at 5 to 10 mbars, prevents the development of large voltages required for a standard electrostatic precipitator. If the voltage is increased too much, the corona transitions into a glow/streamer discharge unsuitable for the operation of a precipitator. If the voltage is not large enough, the dust particles are not sufficiently charged and the field is not strong enough to drive the particles to the collector. A method using electrostatic fields has been developed to collect dust from gaseous environments at low pressures, specifically carbon dioxide at pressures around 5 to 10 mbars. This method, commonly known as electrostatic precipitation, is a mature technology in air at one atmosphere. In this case, the high voltages required for the method to work can easily be achieved. However, in carbon dioxide at low pressures, such as those found on Mars, large voltages are not possible. The innovation reported here consists of two concentric cylindrical electrodes set at specific potential difference that generate an electric field that produces a corona capable of imparting an electrostatic charge to the incoming dust particles. The strength of the field is carefully balanced so as to produce a stable charging corona at 5 to 10 mbars, and is also capable of imparting a force to the particles that drives them to the collecting electrode. There are only two possible ways that dust can be removed from Martian atmospheric gas intakes: with this electrostatic precipitator design, and with the use of filters. However, filters require upstream compression of the gas to be treated because the atmospheric pressure on Mars is too close to vacuum to use a vacuum pump downstream to the filter to draw the gas through the filter. The electrostatic precipitator is the best and more efficient solution for this environment. No other precipitator designs have been developed for the environment of Mars due to the challenges of the low atmospheric pressure. Dust particles are charged using corona generation around the high-voltage discharge electrode, which ionizes gas molecules. Since the atmospheric gas intakes for the ISRU processing chambers will likely be cylindrical, cylindrical precipitator geometry was chosen. The electrostatic precipitator design presented here removes simulated Martian dust particles in the required range in a simulated Martian atmospheric environment. The current-voltage (I-V) characteristic curves taken for the nine precipitator configurations at 9 mbars of pressure showed that a cylindrical collecting electrode 7.0 cm in diameter with a concentric positive high voltage electrode 100 m thick provides the best range of voltage and charging corona current. This precipitator design is effective for the size of the dust particles expected in the Martian atmosphere. Mass determination, as well as microscopic images and particle size distributions of dust collected on a silicon wafer placed directly below the precipitator with the field on and off, showed excellent initial results.

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Measurement of subcellular texture by optical Gabor-like filtering with a digital micromirror device

PubMed Central

Pasternack, Robert M.; Qian, Zhen; Zheng, Jing-Yi; Metaxas, Dimitris N.; White, Eileen; Boustany, Nada N.

2010-01-01

We demonstrate an optical Fourier processing method to quantify object texture arising from subcellular feature orientation within unstained living cells. Using a digital micromirror device as a Fourier spatial filter, we measured cellular responses to two-dimensional optical Gabor-like filters optimized to sense orientation of nonspherical particles, such as mitochondria, with a width around 0.45 μm. Our method showed significantly rounder structures within apoptosis-defective cells lacking the proapoptotic mitochondrial effectors Bax and Bak, when compared with Bax/Bak expressing cells functional for apoptosis, consistent with reported differences in mitochondrial shape in these cells. By decoupling spatial frequency resolution from image resolution, this method enables rapid analysis of nonspherical submicrometer scatterers in an under-sampled large field of view and yields spatially localized morphometric parameters that improve the quantitative assessment of biological function. PMID:18830354

Particulate emissions from a mid-latitude prescribed chaparral fire

Treesearch

Wesley R. Cofer; Joel S. Levine; Daniel I. Sebacher; Edward L. Winstead; Philip J. Riggan; James A. Brass; Vincent G. Ambrosia

1988-01-01

Smoke aerosol was collected on filters from a helicopter during a 400-acre (1.62 km2) prescribed chaparral burn in the San Dimas Experimental Forest on December 12, 1986. Hi-Vol samplers were used to collect particles on both Teflon and glass fiber filters. Scanning electron microscopy of the filters revealed particles that ranged in size from...

Fish tracking by combining motion based segmentation and particle filtering

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

ASSAYING PARTICLE-BOUND POLYCYCLIC AROMATIC HYDROCARBONS (PAH) FROM ARCHIVED PM2.5 FILTERS

EPA Science Inventory

Airborne particulate matter contains numerous organic species, including several polycyclic aromatic hydrocarbons (PAHs) that are known or suspected carcinogens. Existing methods for measuring airborne PAHs are complex and costly, primarily because they are designed to collect...

The analysis and application of a new hybrid pollutants forecasting model using modified Kolmogorov-Zurbenko filter.

PubMed

Li, Peizhi; Wang, Yong; Dong, Qingli

2017-04-01

Cities in China suffer from severe smog and haze, and a forecasting system with high accuracy is of great importance to foresee the concentrations of the airborne particles. Compared with chemical transport models, the growing artificial intelligence models can simulate nonlinearities and interactive relationships and getting more accurate results. In this paper, the Kolmogorov-Zurbenko (KZ) filter is modified and firstly applied to construct the model using an artificial intelligence method. The concentration of inhalable particles and fine particulate matter in Dalian are used to analyze the filtered components and test the forecasting accuracy. Besides, an extended experiment is made by implementing a comprehensive comparison and a stability test using data in three other cities in China. Results testify the excellent performance of the developed hybrid models, which can be utilized to better understand the temporal features of pollutants and to perform a better air pollution control and management. Copyright © 2017 Elsevier B.V. All rights reserved.

Pneumatic System for Concentration of Micrometer-Size Lunar Soil

NASA Technical Reports Server (NTRS)

McKay, David; Cooper, Bonnie

2012-01-01

A report describes a size-sorting method to separate and concentrate micrometer- size dust from a broad size range of particles without using sieves, fluids, or other processes that may modify the composition or the surface properties of the dust. The system consists of four processing units connected in series by tubing. Samples of dry particulates such as lunar soil are introduced into the first unit, a fluidized bed. The flow of introduced nitrogen fluidizes the particulates and preferentially moves the finer grain sizes on to the next unit, a flat plate impactor, followed by a cyclone separator, followed by a Nuclepore polycarbonate filter to collect the dust. By varying the gas flow rate and the sizes of various orifices in the system, the size of the final and intermediate particles can be varied to provide the desired products. The dust can be collected from the filter. In addition, electron microscope grids can be placed on the Nuclepore filter for direct sampling followed by electron microscope characterization of the dust without further handling.

Comparison and evaluation of in situ and filter carbon measurements at the Fresno Supersite

NASA Astrophysics Data System (ADS)

Watson, John G.; Chow, Judith C.

2002-11-01

The Fresno Supersite in Fresno, California, USA, acquires in situ 5- to 60-min average PM2.5 organic carbon (OC), elemental carbon (EC), and total carbon (TC) measurements by the following methods: (1) thermal evolution carbon analyzer for organic, elemental, and total carbon; (2) single-wavelength and seven-color aethalometer for black carbon (BC); and (3) photoionization for particle-bound polycyclic aromatic hydrocarbons. Twenty-four-hour average PM2.5 filter-based measurements include (1) nondenuded quartz filters with no backup filter in a PM2.5 Federal Reference Method (FRM) sampler; (2) quartz filters behind an organic carbon denuder with a quartz backup filter in a Reference Ambient Aerosol Sampler (RAAS); (3) nondenuded quartz filters with backup filter in a RAAS; and (4) nondenuded quartz filters with no backup filter in a sequential filter sampler. Filter samples are analyzed after sampling by the Interagency Monitoring of Protected Visual Environments (IMPROVE) thermal/optical reflectance carbon analysis protocol. Collocated measurements are examined for year 2000. Measurement equivalence is found for PM2.5 mass, light transmission, and TC between the FRM and RAAS speciation samplers. The average ratios of front filter carbon between the denuded and nondenuded channels in the RAAS sampler are 0.83 ± 0.19 for TC, 0.81 ± 0.20 for OC, and 1.01 ± 0.33 for EC. The average differences for TC and OC are low (1.2 to 1.4 μg m-3) and are comparable to the measurement uncertainties. Continuous thermal evolution carbon measurements are not comparable to filter measurements. Aethalometer BC and filter EC are highly correlated, but filter EC is consistently 20-25% higher than continuous aethalometer BC. Pairwise comparisons show filter EC measurements acquired in this study are predictable from aethalometer BC measurements.

Faint Debris Detection by Particle Based Track-Before-Detect Method

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

This study proposes a particle method to detect faint debris, which is hardly seen in single frame, from an image sequence based on the concept of track-before-detect (TBD). The most widely used detection method is detect-before-track (DBT), which firstly detects signals of targets from single frame by distinguishing difference of intensity between foreground and background then associate the signals for each target between frames. DBT is capable of tracking bright targets but limited. DBT is necessary to consider presence of false signals and is difficult to recover from false association. On the other hand, TBD methods try to track targets without explicitly detecting the signals followed by evaluation of goodness of each track and obtaining detection results. TBD has an advantage over DBT in detecting weak signals around background level in single frame. However, conventional TBD methods for debris detection apply brute-force search over candidate tracks then manually select true one from the candidates. To reduce those significant drawbacks of brute-force search and not-fully automated process, this study proposes a faint debris detection algorithm by a particle based TBD method consisting of sequential update of target state and heuristic search of initial state. The state consists of position, velocity direction and magnitude, and size of debris over the image at a single frame. The sequential update process is implemented by a particle filter (PF). PF is an optimal filtering technique that requires initial distribution of target state as a prior knowledge. An evolutional algorithm (EA) is utilized to search the initial distribution. The EA iteratively applies propagation and likelihood evaluation of particles for the same image sequences and resulting set of particles is used as an initial distribution of PF. This paper describes the algorithm of the proposed faint debris detection method. The algorithm demonstrates performance on image sequences acquired during observation campaigns dedicated to GEO breakup fragments, which would contain a sufficient number of faint debris images. The results indicate the proposed method is capable of tracking faint debris with moderate computational costs at operational level.

Particle leakage in extracorporeal blood purification systems based on microparticle suspensions.

PubMed

Hartmann, Jens; Schildboeck, Claudia; Brandl, Martin; Falkenhagen, Dieter

2005-01-01

The newly developed 'Microspheres based Detoxification System' (MDS) designed for any extracorporeal adsorption therapy uses microparticles as adsorbents characterized by a size of 1-20 microm in diameter which are recirculated in the secondary (filtrate) circuit connected to a hollow fiber filter located in the primary (blood) circuit. In the case of a leakage or rupture in the hollow fiber filter, microspheres can enter patients' blood circuits and cause embolic episodes in different organs with varying degrees of clinical relevance. Aim of this study was to determine the amount of particles infused to a patient during a long-term treatment under different failure conditions of the filter. The filters were prepared by cutting single hollow fibers. Fresh-frozen plasma (FFP) and a mixture of glycerol and water were used as a medium together with microparticles potentially used in the MDS. The amounts of particles transferred from the filtrate into the primary circuit were measured. The analysis of particle transfer in the case of a single cut hollow fiber inside the membrane results in particle volumes of up to 26 ml calculated for 10 h. Particle leakage in microparticle suspension based detoxification systems can lead to considerable particle transfer to the patient. Therefore, a particle detection unit which is able to detect critical amounts of particles (<1 ml particle volume/treatment) in the extracorporeal blood line is necessary for patient safety. (c) 2005 S. Karger AG, Basel.

Optimization of nonlinear, non-Gaussian Bayesian filtering for diagnosis and prognosis of monotonic degradation processes

NASA Astrophysics Data System (ADS)

Corbetta, Matteo; Sbarufatti, Claudio; Giglio, Marco; Todd, Michael D.

2018-05-01

The present work critically analyzes the probabilistic definition of dynamic state-space models subject to Bayesian filters used for monitoring and predicting monotonic degradation processes. The study focuses on the selection of the random process, often called process noise, which is a key perturbation source in the evolution equation of particle filtering. Despite the large number of applications of particle filtering predicting structural degradation, the adequacy of the picked process noise has not been investigated. This paper reviews existing process noise models that are typically embedded in particle filters dedicated to monitoring and predicting structural damage caused by fatigue, which is monotonic in nature. The analysis emphasizes that existing formulations of the process noise can jeopardize the performance of the filter in terms of state estimation and remaining life prediction (i.e., damage prognosis). This paper subsequently proposes an optimal and unbiased process noise model and a list of requirements that the stochastic model must satisfy to guarantee high prognostic performance. These requirements are useful for future and further implementations of particle filtering for monotonic system dynamics. The validity of the new process noise formulation is assessed against experimental fatigue crack growth data from a full-scale aeronautical structure using dedicated performance metrics.

A comparison of linear and non-linear data assimilation methods using the NEMO ocean model

NASA Astrophysics Data System (ADS)

Kirchgessner, Paul; Tödter, Julian; Nerger, Lars

2015-04-01

The assimilation behavior of the widely used LETKF is compared with the Equivalent Weight Particle Filter (EWPF) in a data assimilation application with an idealized configuration of the NEMO ocean model. The experiments show how the different filter methods behave when they are applied to a realistic ocean test case. The LETKF is an ensemble-based Kalman filter, which assumes Gaussian error distributions and hence implicitly requires model linearity. In contrast, the EWPF is a fully nonlinear data assimilation method that does not rely on a particular error distribution. The EWPF has been demonstrated to work well in highly nonlinear situations, like in a model solving a barotropic vorticity equation, but it is still unknown how the assimilation performance compares to ensemble Kalman filters in realistic situations. For the experiments, twin assimilation experiments with a square basin configuration of the NEMO model are performed. The configuration simulates a double gyre, which exhibits significant nonlinearity. The LETKF and EWPF are both implemented in PDAF (Parallel Data Assimilation Framework, http://pdaf.awi.de), which ensures identical experimental conditions for both filters. To account for the nonlinearity, the assimilation skill of the two methods is assessed by using different statistical metrics, like CRPS and Histograms.

Adaptive particle filter for robust visual tracking

NASA Astrophysics Data System (ADS)

Dai, Jianghua; Yu, Shengsheng; Sun, Weiping; Chen, Xiaoping; Xiang, Jinhai

2009-10-01

Object tracking plays a key role in the field of computer vision. Particle filter has been widely used for visual tracking under nonlinear and/or non-Gaussian circumstances. In particle filter, the state transition model for predicting the next location of tracked object assumes the object motion is invariable, which cannot well approximate the varying dynamics of the motion changes. In addition, the state estimate calculated by the mean of all the weighted particles is coarse or inaccurate due to various noise disturbances. Both these two factors may degrade tracking performance greatly. In this work, an adaptive particle filter (APF) with a velocity-updating based transition model (VTM) and an adaptive state estimate approach (ASEA) is proposed to improve object tracking. In APF, the motion velocity embedded into the state transition model is updated continuously by a recursive equation, and the state estimate is obtained adaptively according to the state posterior distribution. The experiment results show that the APF can increase the tracking accuracy and efficiency in complex environments.

Investigating the Present Day Cosmic Dust Flux at the Earth's Surface: Initial Results from the Kwajalein Micrometeorite Collection

NASA Technical Reports Server (NTRS)

Wozniakiewicz, P. J.; Bradley, J. P.; Price, M. C.; Zolensky, M. E.; Ishii, H. A.; Brownlee, D. E.; Russell, S. S.

2014-01-01

Examination of impact craters on the Long Duration Exposure Facility satellite indicate a present day micrometeoroid flux of approx. 30,000 tonnes [1 after 2]. But what portion of this material arrives at the Earth's surface as micrometeorites? Studies of available micrometeorite collections from deep sea sediments [e.g. 3], Greenland blue ice [e.g. 4] and the South Pole water well [e.g. 1] may be complicated by terrestrial weathering and, in some cases, collection bias (magnetic separation for deep sea sediments) and poorly constrained ages. We have recently set up a micrometeorite collection station on Kwajalein Island in the Republic of the Marshall Islands in the Pacific Ocean, using high volume air samplers to collect particles directly from the atmosphere. By collecting in this way, the terrestrial age of the particles is known, the weathering they experience is minimal, and we are able to constrain particle arrival times. Collecting at this location also exploits the considerably reduced anthropogenic background [5]. Method: High volume air samplers were installed on top of the two-story airport building on Kwajalein. These were fitted with polycarbonate membrane filters with 5µm diameter perforations. The flow rates were set to 0.5m3/min, and filters were changed once a week. After collection, filters were washed to remove salt and concentrate particles [see 5] in preparation for analysis by SEM. Results and Discussion: A selection of filters have been prepared and surveyed. Due to their ease of identification our initial investigations have focused on particles resembling cosmic spherules. The spheres can be divided into three main groups: 1. Silicate spherules rich in Al, Ca, K and Na (to varying degrees), 2. Silicate spherules rich in Mg and Fe and 3. Fe-rich spherules. Group 1 spherules are often vesiculated and can occur as aggregates. They are similar in appearance and composition to volcanic microspheres [e.g. 6] and are thus likely terrestrial in origin (volcanic). Those of groups 2 and 3, however, typically exhibit quenched surface textures consistent with cosmic spherules. Initial results suggest there is significant variation in the abundance of these groups from filter to filter. Work is ongoing to fully characterize these spherules and to constrain their flux with time.

Magnetic and SEM-EDS analyses of Tilia cordata leaves and PM10 filters as a complementary source of information on polluted air: Results from the city of Parma (Northern Italy).

PubMed

Mantovani, Luciana; Tribaudino, Mario; Solzi, Massimo; Barraco, Vera; De Munari, Eriberto; Pironi, Claudia

2018-08-01

In this work, both PM 10 filters and leaves have been collected, on a daily basis, over a period of five months and compared systematically. Filters were taken from an air-quality monitoring station and leaves from two Tilia cordata trees, both located near the railway station of Parma. SEM-EDS analysis on the surface and across the leaves shows that magnetic particles are almost entirely made of magnetite, and that they are found invariably on the leaves surface. The saturation isothermal magnetic remanence (SIRM) shows that for both filters and leaves the magnetic fraction mainly consists of a low coercivity, magnetite-like phase. The magnetic signals of filter and leaves and atmospheric PM concentrations are compared. The correlation is better for filters, mostly with parameters related to vehicular pollution, and improved for both filters and leaves once data were averaged on a 10 days basis. Filters and leaves equally show an increase in magnetic signal during the fall-winter period together with PM 10 content. The comparison between leaves and filters shows that: 1) leaves give a qualitative picture, and in our case they could be used as environmental proxies after averaging the results over multiple days; 2) the correlation with PM 10 is weaker, indicating that there is a PM 10 contribution from non-magnetic particles, like calcite and clay minerals, pollen and spores; 3) multidomain particles contribution from filters indicates a strong relation with vehicular polluters, suggesting the important role of larger particles; 4) magnetization from leaves and filters are weakly related, due to the different sampling lapse. Copyright © 2018 Elsevier Ltd. All rights reserved.

Alternative Fuel Vehicle Publications | Transportation Research | NREL

Science.gov Websites

from a Fleet of Class 6 Trucks Operating on Gas-to-Liquid Fuel and Catalyzed Diesel Particle Filters Particle Filters. Teresa Alleman, Leslie Eudy, Matt Miyasato, Adewale Oshinuga, Scott Allison, Tom Corcoran

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

NASA Technical Reports Server (NTRS)

Semper, Sean R.; Crassidis, John L.; George, Jemin; Mukherjee, Siddharth; Singla, Puneet

2015-01-01

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

Evaluation of methods for the quantification of ether extract contents in forage and cattle feces.

PubMed

Barbosa, Marcília M; Detmann, Edenio; Valadares, Sebastião C; Detmann, Kelly S C; Franco, Marcia O; Batista, Erick D; Rocha, Gabriel C

2017-01-01

The objective of this study was to compare the estimates of ether extract (EE) contents obtained by the Randall method and by the high-temperature method of the American Oil Chemist's Society (AOCS; Am 5-04) in forages (n = 20) and cattle feces (n = 15). The EE contents were quantified by using the Randall extraction or AOCS method and XT4 filter bags or cartridges made of qualitative filter paper (80 g/m²) as containers for the samples. It was also evaluated the loss of particles, and concentration of residual chlorophyll after extraction and the recovery of protein and minerals in the material subjected to extraction. Significant interaction was observed between extraction method and material for EE contents. The EE estimates using the AOCS method were higher, mainly in forages. No loss of particles was observed with different containers. The chlorophyll contents in the residues of cattle feces were not affected by the extraction method; however, residual chlorophyll was lower using the AOCS method in forages. There was complete recovery of the protein and ash after extraction. The results suggest that AOCS method produces higher estimates of EE contents in forages and cattle feces, possibly by providing greater extraction of non-fatty EE.

Evaluation of the topological characteristics of the turbulent flow in a `box of turbulence' through 2D time-resolved particle image velocimetry

NASA Astrophysics Data System (ADS)

Lian, Huan; Soulopoulos, Nikolaos; Hardalupas, Yannis

2017-09-01

The experimental evaluation of the topological characteristics of the turbulent flow in a `box' of homogeneous and isotropic turbulence (HIT) with zero mean velocity is presented. This requires an initial evaluation of the effect of signal noise on measurement of velocity invariants. The joint probability distribution functions (pdfs) of experimentally evaluated, noise contaminated, velocity invariants have a different shape than the corresponding noise-free joint pdfs obtained from the DNS data of the Johns Hopkins University (JHU) open resource HIT database. A noise model, based on Gaussian and impulsive Salt and Pepper noise, is established and added artificially to the DNS velocity vector field of the JHU database. Digital filtering methods, based on Median and Wiener Filters, are chosen to eliminate the modeled noise source and their capacity to restore the joint pdfs of velocity invariants to that of the noise-free DNS data is examined. The remaining errors after filtering are quantified by evaluating the global mean velocity, turbulent kinetic energy and global turbulent homogeneity, assessed through the behavior of the ratio of the standard deviation of the velocity fluctuations in two directions, the energy spectrum of the velocity fluctuations and the eigenvalues of the rate-of-strain tensor. A method of data filtering, based on median filtered velocity using different median filter window size, is used to quantify the clustering of zero velocity points of the turbulent field using the radial distribution function (RDF) and Voronoï analysis to analyze the 2D time-resolved particle image velocimetry (TR-PIV) velocity measurements. It was found that a median filter with window size 3 × 3 vector spacing is the effective and efficient approach to eliminate the experimental noise from PIV measured velocity images to a satisfactory level and extract the statistical two-dimensional topological turbulent flow patterns.

System and method for measuring particles in a sample stream of a flow cytometer using a low power laser source

DOEpatents

Graves, Steven W; Habbersett, Robert C

2013-10-22

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

System and method for measuring particles in a sample stream of a flow cytometer using low-power laser source

DOEpatents

Graves, Steven W.; Habbersett, Robert C.

2014-07-01

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

System and method for measuring particles in a sample stream of a flow cytometer or the like

DOEpatents

Graves, Steven W.; Habberset, Robert C.

2010-11-16

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

System and method for measuring particles in a sample stream of a flow cytometer using low-power laser source

DOEpatents

Graves, Steven W.; Habbersett, Robert C.

2016-11-15

A system and method for analyzing a particle in a sample stream of a flow cytometer or the like. The system has a light source, such as a laser pointer module, for generating a low powered light beam and a fluidics apparatus which is configured to transport particles in the sample stream at substantially low velocity through the light beam for interrogation. Detectors, such as photomultiplier tubes, are configured to detect optical signals generated in response to the light beam impinging the particles. Signal conditioning circuitry is connected to each of the detectors to condition each detector output into electronic signals for processing and is designed to have a limited frequency response to filter high frequency noise from the detector output signals.

Filtered sub-grid constitutive models for fluidized gas-particle flows constructed from 3-D simulations

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

Sarkar, Avik; Milioli, Fernando E.; Ozarkar, Shailesh

2016-10-01

The accuracy of fluidized-bed CFD predictions using the two-fluid model can be improved significantly, even when using coarse grids, by replacing the microscopic kinetic-theory-based closures with coarse-grained constitutive models. These coarse-grained constitutive relationships, called filtered models, account for the unresolved gas-particle structures (clusters and bubbles) via sub-grid corrections. Following the previous 2-D approaches of Igci et al. [AIChE J., 54(6), 1431-1448, 2008] and Milioli et al. [AIChE J., 59(9), 3265-3275, 2013], new filtered models are constructed from highly-resolved 3-D simulations of gas-particle flows. Although qualitatively similar to the older 2-D models, the new 3-D relationships exhibit noticeable quantitative and functionalmore » differences. In particular, the filtered stresses are strongly dependent on the gas-particle slip velocity. Closures for the filtered inter-phase drag, gas- and solids-phase pressures and viscosities are reported. A new model for solids stress anisotropy is also presented. These new filtered 3-D constitutive relationships are better suited to practical coarse-grid 3-D simulations of large, commercial-scale devices.« less

[Particulate contamination associated with the manipulation of drugs in glass ampules: A literature review].

PubMed

Painchart, L; Odou, P; Bussières, J-F

2018-01-01

The manipulation of drugs from glass ampules can generate particles when the ampule is broken. Several authors recommend the use of filter needle to withdraw the drug content. The aim of this study is to make an assessment of the presence of particles during the manipulation of glass ampules and to discuss the current practices. Literature review based on a search strategy (Pubmed, Google Scholar) and a summary table of available data. Analysis to evaluate the efficacy of the filtration when data are available. Eighteen articles have been included. Most of study shows the presence of particles in glass ampules. Important discrepancies reported regarding the number of particles per ampule. Analysis of data from seven studies: decrease of 83% of the total number of particles (>10μm) identified when drugs are removed with filter needle. All studies but two confirm the efficacy of filter needles. Studies show the presence of particles when drugs are removed from glass ampules. They do not allow to make a conclusion on human clinical consequences associated with the presence of particles. It is necessary to evaluate in human the risks associated with particle contamination to determine the optimal use of filter needle. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Optical Scatter Imaging with a digital micromirror device.

PubMed

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

2009-10-26

We had developed Optical Scatter Imaging (OSI) as a method which combines light scattering spectroscopy with microscopic imaging to probe local particle size in situ. Using a variable diameter iris as a Fourier spatial filter, the technique consisted of collecting images that encoded the intensity ratio of wide-to-narrow angle scatter at each pixel in the full field of view. In this paper, we replace the variable diameter Fourier filter with a digital micromirror device (DMD) to extend our assessment of morphology to the characterization of particle shape and orientation. We describe our setup in detail and demonstrate how to eliminate aberrations associated with the placement of the DMD in a conjugate Fourier plane of our microscopic imaging system. Using bacteria and polystyrene spheres, we show how this system can be used to assess particle aspect ratio even when imaged at low resolution. We also show the feasibility of detecting alterations in organelle aspect ratio in situ within living cells. This improved OSI system could be further developed to automate morphological quantification and sorting of non-spherical particles in situ.

Low level determination of (226)Ra in water using a micro-precipitate track method for large-scale environmental monitoring.

PubMed

Taheri, M; Sohrabi, M; Jaleh, B; Hosseini, T; Montazer Rahmati, M M

2009-12-01

In the present paper a method has been developed for the determination of (226)Ra in water by the detection, using a solid-state nuclear track detector (SSNTD), of alpha particles from (226)Ra in equilibrium with (222)Rn in micro-precipitates collected on a filter. The micro-precipitates were prepared from environmental water samples by collection of radium with lead as Pb/RaSO(4). Several factors affect the (226)Ra precipitation on the filter and its recovery, in particular the filter pore size. Therefore in this experiment Whatman #42 and Millipore filters with different pore sizes were used. Using a 0.45 microm Millipore filter, the recovery efficiency was increased up to 96%, and the alpha self-absorption and scattering decreased remarkably. For efficient detection of alphas from (226)Ra/(222)Rn in equilibrium, three types of SSNTD were used-polycarbonate (PC) electrochemically etched (ECE), CR-39 and LR-115 chemically etched (CE). By preparing a standard micro-precipitate on a filter with known (226)Ra/(222)Rn characteristics, the calibration response of each detector and its minimum detection limit (MDL) were determined.

Bacterial contamination levels of autogenous bone particles collected by 3 different techniques for harvesting intraoral bone grafts.

PubMed

Manzano-Moreno, Francisco J; Herrera-Briones, Francisco J; Linares-Recatala, Macarena; Ocaña-Peinado, Francisco M; Reyes-Botella, Candela; Vallecillo-Capilla, Manuel F

2015-03-01

The aim of this study was to compare levels of bacterial contamination of autogenous bone collected when using low-speed drilling, a back-action chisel, and a bone filter. Bone tissue samples were taken from 31 patients who underwent surgical extraction of their third lower molars. Before surgical removal of the molar, bone particles were collected by a low-speed drill or a back-action chisel. Then, a stringent aspiration protocol was applied during the ostectomy to collect particulate bone by a bone filter. Processing of samples commenced immediately by incubation in an anaerobic or a CO2-rich atmosphere. The number of colony-forming units (CFUs) was determined at 48 hours of culture. No significant difference in the number of CFUs per milliliter was observed between the low-speed drilling group and the back-action chisel group in the anaerobic or CO2-rich condition (P = .34). However, significantly more micro-organisms were found in the bone filter group than in the low-speed drilling group or the back-action chisel group in the anaerobic and CO2-rich conditions (P < .001). Particulate bone harvested with low-speed drilling or a back-action chisel is safer for use as an autograft than are bone particles collected with a bone filter. These results suggest that bone obtained from low-speed drilling is safe and straightforward to harvest and could be the method of choice for collecting particulate bone. Further research is needed to lower the bacterial contamination levels of autogenous bone particles used as graft material. Copyright © 2015 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Are glass fiber particles released during the use of electronic cigarettes? Development of a semi-quantitative approach to detect glass particle emission due to vaping.

PubMed

Shin, Jae-Won; Jo, Sang-Hee; Kim, Ki-Hyun; Song, Hee-Nam; Kang, Chang-Hee; Bolan, Nanthi; Hong, Jongki

2018-05-04

This study investigated the emission characteristics of glass particles resulting from smoking electronic cigarettes (ECs). First, the most suitable filter for the collection of glass particles was explored by examining the performance (reliability) of various types of filters. A polycarbonate filter was determined as the optimum choice to collect glass particles in EC aerosol. A cartomizer was filled with EC refill solution composed of an equal volume of propylene glycol (PG) and vegetable glycol (VG). To simulate the potential conditions for glass particle emission, EC vaped aerosols were collected at three distinctive puffing intervals: (1) 0-10 puffs, (2) 101-110 puffs, and (3) 201-210 puffs (flow rate of 1 L min -1 , 2 s per puff, and 10 puffs per sample). Glass particles were observed as early as after 100 times puffing from certain products, while after 200 from others. Thus, glass particles were generated by increasing the number of puffs and usage of the EC cartomizer. The analysis of glass particles collected onto polycarbonate filters by scanning electron microscopy (SEM)/energy dispersive X-ray spectroscopy (EDS) confirmed the presence of glass particles in samples collected after puffing 100-200 times. The study demonstrated that the possibility of glass particle emissions from the EC device increased considerably with the increasing number of total puffs. Copyright © 2018 Elsevier Inc. All rights reserved.

Exploring synchronisation in nonlinear data assimilation

NASA Astrophysics Data System (ADS)

Rodrigues-Pinheiro, Flavia; van Leeuwen, Peter Jan

2016-04-01

Present-day data assimilation methods are based on linearizations and face serious problems in strongly nonlinear cases such as convection. A promising solution to this problem is a particle filter, which provides a representation of the model probability density function (pdf) by a discrete set of model states, or particles. The basic particle filter uses Bayes's theorem directly, but does not work in high-dimensional cases. The performance can be improved by considering the proposal density freedom. This allows one to change the model equations to bring the particles closer to the observations, resulting in very efficient update schemes at observation times, but extending these schemes between observation times is computationally expensive. Simple solutions like nudging have been shown to be not powerful enough. A potential solution might be synchronization, in which one tries to synchronise the model of a system with the true evolution of the system via the observations. In practice this means that an extra term is added to the model equations that hampers growth of instabilities on the synchronization manifold. Especially the delayed versions, where observations are allowed to influence the state in the past have shown some remarkable successes. Unfortunately, all efforts ignore errors in the observations, and as soon as these are introduced the performance degrades considerably. There is a close connection between time-delayed synchronization and a Kalman Smoother, which does allow for observational (and other) errors. In this presentation we will explore this connection to the full, with a view to extend synchronization to more realistic settings. Specifically performance of the spread of information from observed to unobserved variables is studied in detail. The results indicate that this extended synchronisation is a promising tool to steer the model states towards the observations efficiently. If time permits, we will show initial results of embedding the new synchronization method into a particle filter.

Ozone Air Purifiers: Can They Improve Asthma Symptoms?

MedlinePlus

... and cleaner. However, ozone generators don't actually filter out the small particles that trigger asthma. Inhaling ... air — but they may generate unwanted ozone. Air filters that remove small particles — such as high-efficiency ...

Micron-pore-sized metallic filter tube membranes for filtration of particulates and water purification.

PubMed

Phelps, T J; Palumbo, A V; Bischoff, B L; Miller, C J; Fagan, L A; McNeilly, M S; Judkins, R R

2008-07-01

Robust filtering techniques capable of efficiently removing particulates and biological agents from water or air suffer from plugging, poor rejuvenation, low permeance, and high backpressure. Operational characteristics of pressure-driven separations are in part controlled by the membrane pore size, charge of particulates, transmembrane pressure and the requirement for sufficient water flux to overcome fouling. With long term use filters decline in permeance due to filter-cake plugging of pores, fouling, or filter deterioration. Though metallic filter tube development at ORNL has focused almost exclusively on gas separations, a small study examined the applicability of these membranes for tangential filtering of aqueous suspensions of bacterial-sized particles. A mixture of fluorescent polystyrene microspheres ranging in size from 0.5 to 6 microm in diameter simulated microorganisms in filtration studies. Compared to a commercial filter, the ORNL 0.6 microm filter averaged approximately 10-fold greater filtration efficiency of the small particles, several-fold greater permeance after considerable use and it returned to approximately 85% of the initial flow upon backflushing versus 30% for the commercial filter. After filtering several liters of the particle-containing suspension, the ORNL composite filter still exhibited greater than 50% of its initial permeance while the commercial filter had decreased to less than 20%. When considering a greater filtration efficiency, greater permeance per unit mass, greater percentage of rejuvenation upon backflushing (up to 3-fold), and likely greater performance with extended use, the ORNL 0.6 microm filters can potentially outperform the commercial filter by factors of 100-1,000 fold.

Building Hybrid Rover Models for NASA: Lessons Learned

NASA Technical Reports Server (NTRS)

Willeke, Thomas; Dearden, Richard

2004-01-01

Particle filters have recently become popular for diagnosis and monitoring of hybrid systems. In this paper we describe our experiences using particle filters on a real diagnosis problem, the NASA Ames Research Center's K-9 rover. As well as the challenge of modelling the dynamics of the system, there are two major issues in applying a particle filter to such a model. The first is the asynchronous nature of the system-observations from different subsystems arrive at different rates, and occasionally out of order, leading to large amounts of uncertainty in the state of the system. The second issue is data interpretation. The particle filter produces a probability distribution over the state of the system, from which summary statistics that can be used for control or higher-level diagnosis must be extracted. We describe our approaches to both these problems, as well as other modelling issues that arose in this domain.

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

PubMed

Heredia Rivera, Birmania; Gerardo Rodriguez, Martín

2016-10-01

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.

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

PubMed Central

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

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

NASA Astrophysics Data System (ADS)

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.

A Reliability-Based Particle Filter for Humanoid Robot Self-Localization in RoboCup Standard Platform League

PubMed Central

Sánchez, Eduardo Munera; Alcobendas, Manuel Muñoz; Noguera, Juan Fco. Blanes; Gilabert, Ginés Benet; Simó Ten, José E.

2013-01-01

This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption. PMID:24193098

Pulse-shape discrimination with Cs2HfCl6 crystal scintillator

NASA Astrophysics Data System (ADS)

Cardenas, C.; Burger, A.; Goodwin, B.; Groza, M.; Laubenstein, M.; Nagorny, S.; Rowe, E.

2017-10-01

The results of investigation into cesium hafnium chloride (Cs2HfCl6) scintillating crystals as a promising detector to search for rare nuclear processes occurring in Hf isotopes is reported. The light output, quenching factor, and pulse-shape characteristics have been investigated at room temperature. The scintillation response of the crystal induced by α-particles and γ-quanta were studied to determine possibility of particle discrimination. Using the optimal filter method we obtained clear separation between signals with a factor of merit (FOM) = 9.3. This indicates that we are able to fully separate signals originating from α-particles and γ-quanta. Similar fruitful discrimination power was obtained by applying the mean time method (FOM = 7) and charge integration method (FOM = 7.5). The quenching factor for collimated 4 MeV α-particles is found to be 0.36, showing that α-particles generate more than a third of the light compared to γ-quanta at the same energy.

Effects of ultrafine particles on the allergic inflammation in the lung of asthmatics: results of a double-blinded randomized cross-over clinical pilot study

PubMed Central

2014-01-01

Background Epidemiological and experimental studies suggest that exposure to ultrafine particles (UFP) might aggravate the allergic inflammation of the lung in asthmatics. Methods We exposed 12 allergic asthmatics in two subgroups in a double-blinded randomized cross-over design, first to freshly generated ultrafine carbon particles (64 μg/m3; 6.1 ± 0.4 × 105 particles/cm3 for 2 h) and then to filtered air or vice versa with a 28-day recovery period in-between. Eighteen hours after each exposure, grass pollen was instilled into a lung lobe via bronchoscopy. Another 24 hours later, inflammatory cells were collected by means of bronchoalveolar lavage (BAL). (Trial registration: NCT00527462) Results For the entire study group, inhalation of UFP by itself had no significant effect on the allergen induced inflammatory response measured with total cell count as compared to exposure with filtered air (p = 0.188). However, the subgroup of subjects, which inhaled UFP during the first exposure, exhibited a significant increase in total BAL cells (p = 0.021), eosinophils (p = 0.031) and monocytes (p = 0.013) after filtered air exposure and subsequent allergen challenge 28 days later. Additionally, the potential of BAL cells to generate oxidant radicals was significantly elevated at that time point. The subgroup that was exposed first to filtered air and 28 days later to UFP did not reveal differences between sessions. Conclusions Our data demonstrate that pre-allergen exposure to UFP had no acute effect on the allergic inflammation. However, the subgroup analysis lead to the speculation that inhaled UFP particles might have a long-term effect on the inflammatory course in asthmatic patients. This should be reconfirmed in further studies with an appropriate study design and sufficient number of subjects. PMID:25204642

The impact of recirculation, ventilation and filters on secondary organic aerosols generated by indoor chemistry

NASA Astrophysics Data System (ADS)

Fadeyi, M. O.; Weschler, C. J.; Tham, K. W.

This study examined the impact of recirculation rates (7 and 14 h -1), ventilation rates (1 and 2 h -1), and filtration on secondary organic aerosols (SOAs) generated by ozone of outdoor origin reacting with limonene of indoor origin. Experiments were conducted within a recirculating air handling system that serviced an unoccupied, 236 m 3 environmental chamber configured to simulate an office; either no filter, a new filter or a used filter was located downstream of where outdoor air mixed with return air. For otherwise comparable conditions, the SOA number and mass concentrations at a recirculation rate of 14 h -1 were significantly smaller than at a recirculation rate of 7 h -1. This was due primarily to lower ozone concentrations, resulting from increased surface removal, at the higher recirculation rate. Increased ventilation increased outdoor-to-indoor transport of ozone, but this was more than offset by the increased dilution of SOA derived from ozone-initiated chemistry. The presence of a particle filter (new or used) strikingly lowered SOA number and mass concentrations compared with conditions when no filter was present. Even though the particle filter in this study had only 35% single-pass removal efficiency for 100 nm particles, filtration efficiency was greatly amplified by recirculation. SOA particle levels were reduced to an even greater extent when an activated carbon filter was in the system, due to ozone removal by the carbon filter. These findings improve our understanding of the influence of commonly employed energy saving procedures on occupant exposures to ozone and ozone-derived SOA.

Simultaneous separation and determination of 15 organic UV filters in sunscreen cosmetics by HPLC-ESI-MS/MS.

PubMed

Meng, X; Ma, Q; Bai, H; Wang, Z; Han, C; Wang, C

2017-08-01

A comprehensive methodology for the simultaneous determination of 15 multiclass organic UV filters in sunscreen cosmetics was developed using high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Sunscreen cosmetics of various matrices, such as toning lotion, emulsion, cream and lipstick, were analysed. Ultrasound-assisted extraction (UAE) was utilized as the extraction technique for sample preparation. The 15 UV filters were chromatographically separated by two groups of mobile phase system on an XBridge C 18 analytical column (150 × 2.1 mm I.D., 3.5 μm particle size) and quantified using HPLC-ESI-MS/MS. The quantitation was performed using the external calibration method. The established method was validated in terms of linearity, sensitivity, specificity, accuracy, stability, intraday and interday precisions, recovery and matrix effect. The method was also applied for the determination of UV filters in commercial sunscreen cosmetics. The experimental results demonstrated that the developed method was accurate, rapid and sensitive and can be used for the analytical control of sunscreen cosmetics. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Detection of 210Po on filter papers 16 years after use for the collection of short-lived radon progeny in a room.

PubMed

Abu-Jarad, F; Fazal-ur-Rehman

2003-01-01

Radon gas was allowed to accumulate in its radium source and then injected into a 36 m(3) test room, resulting in an initial radon concentration of 15 kBq m(-3). Filter papers were used to collect the short-lived radon progeny and thus to measure the Potential Alpha Energy Concentration (PAEC) in-situ in the year 1984 at different times and conditions according to the experimental design. The radon progeny collected on the filter papers were studied as a function of aerosol particle concentration ranging from 10(2)-10(5) particles cm(-3) in three different experiments. The highest aerosol particle concentration was generated by indoor cigarette smoking. Those filters were stored after the experiment, and were used after 16 years to study the activity of the radon long-lived alpha emitter progeny, (210)Po (T(1/2)=138 days). This isotope is separated from the short-lived progeny by (210)Pb beta emitter with 22.3 years half-life. After 16 years' storage of these filters, each filter paper was sandwiched and wrapped between two CR-39 nuclear track detectors, to put the detectors in contact with the surfaces of different filters, for 337 days. Correlation between the PAEC measured using filter papers in the year 1984 and the activity of long-lived alpha emitter (210)Po on the same filter papers measured in the year 2000 were studied. The results of the (210)Po activity showed a very good correlation of 0.92 with the PAEC 16 years ago. The results also depict that the PAEC and (210)Po activity in indoor air increased with the increase of aerosol particle concentration, which shows the attachment of short-lived radon progeny with the aerosol particles. The experiment proves that indoor cigarette smoking is a major source of aerosol particles carrying radon progeny and, thus, indoor cigarette smoking is an additional source of internal radiation hazard to the occupants whether smoker or non-smoker.

Air purification equipment combining a filter coated by silver nanoparticles with a nano-TiO2 photocatalyst for use in hospitals

NASA Astrophysics Data System (ADS)

Son Le, Thanh; Hien Dao, Trong; Nguyen, Dinh Cuong; Chau Nguyen, Hoai; Balikhin, I. L.

2015-03-01

X-ray diffraction, scanning electron microscopy and transmission electron microscopy showed that TiO2 particles synthesized by a sol-gel procedure exhibited uniform size about 16-20 nm. This nanopowder was deposited on a porous quartz tube (D = 74 mm, L = 418 mm, deposit density ˜16.4 mg cm-2) through an intermediate adhesive polymethylmethacrylate layer to manufacture a photocatalytic filter tube. A polypropylene pre-filter was coated with a nanosilver layer (particle size ˜20 nm) prepared by aqueous molecular solution method. An air cleaner of 250 m3 h-1 capacity equipped with this pre-filter, an electrostatic air filter, 4 photocatalytic filter tubes and 4 UV-A lamps (36 W) presented the high degradation ability for certain volatile organic compounds (VOCs), bacteria and fungi. The VOCs degradation performances of the equipment with respect to divers compounds are different: in a 10 m3 box, 91.6% of butanol was removed within 55 min, 80% of acetone within 100 min, 70.1% of diethyl ether within 120 min and only 43% of benzene was oxidized within 150 min. Over 99% of bacteria and fungi were killed after the air passage through the equipment. For application, it was placed in the intensive care room (volume of 125 m3) of E hospital in Hanoi; 69% of bacteria and 63% of fungi were killed within 6 h.

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.

PubMed

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.

Extraction of beryllium from refractory beryllium oxide with dilute ammonium bifluoride and determination by fluorescence: a multiparameter performance evaluation.

PubMed

Goldcamp, Michael J; Goldcamp, Diane M; Ashley, Kevin; Fernback, Joseph E; Agrawal, Anoop; Millson, Mark; Marlow, David; Harrison, Kenneth

2009-12-01

Beryllium exposure can cause a number of deleterious health effects, including beryllium sensitization and the potentially fatal chronic beryllium disease. Efficient methods for monitoring beryllium contamination in workplaces are valuable to help prevent dangerous exposures to this element. In this work, performance data on the extraction of beryllium from various size fractions of high-fired beryllium oxide (BeO) particles (from < 32 microm up to 212 microm) using dilute aqueous ammonium bifluoride (ABF) solution were obtained under various conditions. Beryllium concentrations were determined by fluorescence using a hydroxybenzoquinoline fluorophore. The effects of ABF concentration and volume, extraction temperature, sample tube types, and presence of filter or wipe media were examined. Three percent ABF extracts beryllium nearly twice as quickly as 1% ABF; extraction solution volume has minimal influence. Elevated temperatures increase the rate of extraction dramatically compared with room temperature extraction. Sample tubes with constricted tips yield poor extraction rates owing to the inability of the extraction medium to access the undissolved particles. The relative rates of extraction of Be from BeO of varying particle sizes were examined. Beryllium from BeO particles in fractions ranging from less than 32 microm up to 212 microm were subjected to various extraction schemes. The smallest BeO particles are extracted more quickly than the largest particles, although at 90 degrees C even the largest BeO particles reach nearly quantitative extraction within 4 hr in 3% ABF. Extraction from mixed cellulosic-ester filters, cellulosic surface-sampling filters, wetted cellulosic dust wipes, and cotton gloves yielded 90% or greater recoveries. Scanning electron microscopy of BeO particles, including partially dissolved particles, shows that dissolution in dilute ABF occurs not just on the exterior surface but also via accessing particles' interiors due to porosity of the BeO material. Comparison of dissolution kinetics data shows that as particle diameter approximately doubles, extraction time is increased by a factor of about 1.5, which is consistent with the influence of porosity on dissolution.

Design and evaluation of an inlet conditioner to dry particles for real-time particle sizers.

PubMed

Peters, Thomas M; Riss, Adam L; Holm, Ricky L; Singh, Manisha; Vanderpool, Robert W

2008-04-01

Real-time particle sizers provide rapid information about atmospheric particles, particularly peak exposures, which may be important in the development of adverse health outcomes. However, these instruments are subject to erroneous readings in high-humidity environments when compared with measurements from filter-based, federal reference method (FRM) samplers. Laboratory tests were conducted to evaluate the ability of three inlet conditioners to dry aerosol prior to entering a real-time particle sizer for measuring coarse aerosols (Model 3321 Aerodynamic Particle Sizer, APS) under simulated highly humid conditions. Two 30 day field studies in Birmingham, AL, USA were conducted to compare the response of two APSs operated with and without an inlet conditioner to that measured with FRM samplers. In field studies, the correlation of PM(10-2.5) derived from the APS and that measured with the FRM was substantially stronger with an inlet conditioner applied (r2 ranged from 0.91 to 0.99) than with no conditioner (r2 = 0.61). Laboratory experiments confirmed the ability of the heater and desiccant conditioner to remove particle-borne moisture. In field tests, water was found associated with particles across the sizing range of the APS (0.5 microm to 20 microm) when relative humidity was high in Birmingham. Certain types of inlet conditioners may substantially improve the correlation between particulate mass concentration derived from real-time particle sizers and filter-based samplers in humid conditions.

Analysis of Video-Based Microscopic Particle Trajectories Using Kalman Filtering

PubMed Central

Wu, Pei-Hsun; Agarwal, Ashutosh; Hess, Henry; Khargonekar, Pramod P.; Tseng, Yiider

2010-01-01

Abstract The fidelity of the trajectories obtained from video-based particle tracking determines the success of a variety of biophysical techniques, including in situ single cell particle tracking and in vitro motility assays. However, the image acquisition process is complicated by system noise, which causes positioning error in the trajectories derived from image analysis. Here, we explore the possibility of reducing the positioning error by the application of a Kalman filter, a powerful algorithm to estimate the state of a linear dynamic system from noisy measurements. We show that the optimal Kalman filter parameters can be determined in an appropriate experimental setting, and that the Kalman filter can markedly reduce the positioning error while retaining the intrinsic fluctuations of the dynamic process. We believe the Kalman filter can potentially serve as a powerful tool to infer a trajectory of ultra-high fidelity from noisy images, revealing the details of dynamic cellular processes. PMID:20550894

Fish mouths as engineering structures for vortical cross-step filtration

NASA Astrophysics Data System (ADS)

Sanderson, S. Laurie; Roberts, Erin; Lineburg, Jillian; Brooks, Hannah

2016-03-01

Suspension-feeding fishes such as goldfish and whale sharks retain prey without clogging their oral filters, whereas clogging is a major expense in industrial crossflow filtration of beer, dairy foods and biotechnology products. Fishes' abilities to retain particles that are smaller than the pore size of the gill-raker filter, including extraction of particles despite large holes in the filter, also remain unexplained. Here we show that unexplored combinations of engineering structures (backward-facing steps forming d-type ribs on the porous surface of a cone) cause fluid dynamic phenomena distinct from current biological and industrial filter operations. This vortical cross-step filtration model prevents clogging and explains the transport of tiny concentrated particles to the oesophagus using a hydrodynamic tongue. Mass transfer caused by vortices along d-type ribs in crossflow is applicable to filter-feeding duck beak lamellae and whale baleen plates, as well as the fluid mechanics of ventilation at fish gill filaments.

Designing a Wien Filter Model with General Particle Tracer

NASA Astrophysics Data System (ADS)

Mitchell, John; Hofler, Alicia

2017-09-01

The Continuous Electron Beam Accelerator Facility injector employs a beamline component called a Wien filter which is typically used to select charged particles of a certain velocity. The Wien filter is also used to rotate the polarization of a beam for parity violation experiments. The Wien filter consists of perpendicular electric and magnetic fields. The electric field changes the spin orientation, but also imposes a transverse kick which is compensated for by the magnetic field. The focus of this project was to create a simulation of the Wien filter using General Particle Tracer. The results from these simulations were vetted against machine data to analyze the accuracy of the Wien model. Due to the close agreement between simulation and experiment, the data suggest that the Wien filter model is accurate. The model allows a user to input either the desired electric or magnetic field of the Wien filter along with the beam energy as parameters, and is able to calculate the perpendicular field strength required to keep the beam on axis. The updated model will aid in future diagnostic tests of any beamline component downstream of the Wien filter, and allow users to easily calculate the electric and magnetic fields needed for the filter to function properly. Funding support provided by DOE Office of Science's Student Undergraduate Laboratory Internship program.

Development of a field test method for total suspended solids analysis.

DOT National Transportation Integrated Search

2013-11-01

Total suspended solids (TSS) are all particles in water that will not pass through a glass fiber filter with a pore size less : than 2 m, including sediments, algae, nutrients, and metals. TSS is an important water quality parameter because of its ...

DLVO Approximation Methods for Predicting the Attachment of Silver Nanoparticles to Ceramic Membranes.

PubMed

Mikelonis, Anne M; Youn, Sungmin; Lawler, Desmond F

2016-02-23

This article examines the influence of three common stabilizing agents (citrate, poly(vinylpyrrolidone) (PVP), and branched poly(ethylenimine) (BPEI)) on the attachment affinity of silver nanoparticles to ceramic water filters. Citrate-stabilized silver nanoparticles were found to have the highest attachment affinity (under conditions in which the surface potential was of opposite sign to the filter). This work demonstrates that the interaction between the electrical double layers plays a critical role in the attachment of nanoparticles to flat surfaces and, in particular, that predictions of double-layer interactions are sensitive to boundary condition assumptions (constant charge vs constant potential). The experimental deposition results can be explained when using different boundary condition assumptions for different stabilizing molecules but not when the same assumption was assumed for all three types of particles. The integration of steric interactions can also explain the experimental deposition results. Particle size was demonstrated to have an effect on the predicted deposition for BPEI-stabilized particles but not for PVP.

Sequential bearings-only-tracking initiation with particle filtering method.

PubMed

Liu, Bin; Hao, Chengpeng

2013-01-01

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.

Development of a hybrid image processing algorithm for automatic evaluation of intramuscular fat content in beef M. longissimus dorsi.

PubMed

Du, Cheng-Jin; Sun, Da-Wen; Jackman, Patrick; Allen, Paul

2008-12-01

An automatic method for estimating the content of intramuscular fat (IMF) in beef M. longissimus dorsi (LD) was developed using a sequence of image processing algorithm. To extract IMF particles within the LD muscle from structural features of intermuscular fat surrounding the muscle, three steps of image processing algorithm were developed, i.e. bilateral filter for noise removal, kernel fuzzy c-means clustering (KFCM) for segmentation, and vector confidence connected and flood fill for IMF extraction. The technique of bilateral filtering was firstly applied to reduce the noise and enhance the contrast of the beef image. KFCM was then used to segment the filtered beef image into lean, fat, and background. The IMF was finally extracted from the original beef image by using the techniques of vector confidence connected and flood filling. The performance of the algorithm developed was verified by correlation analysis between the IMF characteristics and the percentage of chemically extractable IMF content (P<0.05). Five IMF features are very significantly correlated with the fat content (P<0.001), including count densities of middle (CDMiddle) and large (CDLarge) fat particles, area densities of middle and large fat particles, and total fat area per unit LD area. The highest coefficient is 0.852 for CDLarge.

The role of aluminum in slow sand filtration.

PubMed

Weber-Shirk, Monroe L; Chan, Kwok Loon

2007-03-01

Engineering enhancement of slow sand filtration has been an enigma in large part because the mechanisms responsible for particle removal have not been well characterized. The presumed role of biological processes in the filter ripening process nearly precluded the possibility of enhancing filter performance since interventions to enhance biological activity would have required decreasing the quality of the influent water. In previous work, we documented that an acid soluble polymer controls filter performance. The new understanding that particle removal is controlled in large part by physical chemical mechanisms has expanded the possibilities of engineering slow sand filter performance. Herein, we explore the role of naturally occurring aluminum as a ripening agent for slow sand filters and the possibility of using a low dose of alum to improve filter performance or to ripen slow sand filters.

EFFECT OF VENTILATION SYSTEMS AND AIR FILTERS ON DECAY RATES OF PARTICLES PRODUCED BY INDOOR SOURCES IN AN OCCUPIED TOWNHOUSE

EPA Science Inventory

Several studies have shown the importance of particle losses in real homes due to deposition and filtration; however, none have quantitatively shown the impact of using a central forced air fan and in-duct filter on particle loss rates. In an attempt to provide such data, we me...

Characterization of outdoor air particles as source of impurities in supply air

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

Pasanen, P.; Kalliokoski, P.; Tuomainen, A.

1997-12-31

Odor emission of supply air filters has proved to be a major source of stuffy odor of supply air. In this study, the odor emission characteristics of outdoor air particles and odor emissions of coarse prefilters and fine filters were studied. The outdoor air samples were collected by the aid of high volume impactor. Odor emissions of the size fractions, < 2.1 {micro}m , 2.1--10 {micro}m and >10 {micro}m were studied separately in laboratory with a trained olf panel: The odor emissions of the ventilation filters in real use were evaluated five times during the 14 month study period. Aftermore » the field evaluation the emissions of carbonyl compounds and other volatile organic compounds. The odor emissions of outdoor air particles were the highest during the heating season and lowest in the summer. The particles in the coarsest fraction had the most abundant emissions (1,200 olf/g) while the emissions from fine particles were lowest (100 olf/g). The odor emissions evaluated from the coarse and fine ventilation filters supported the finding that particles collected on coarse prefilter had the most abundant odor emission.« less

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

PubMed

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.

Exploration of PM2.5 filtration property of filter bag for environment protection

NASA Astrophysics Data System (ADS)

Zhu, Ruitian; Zheng, Jinwei; Ni, Bingxuan; Zhang, Peng

2017-06-01

In this paper, filter bag of polyphenylene sulfide (PPS) needle punched nonwoven for environment protection was investigated. The results showed that air permeability of sample was linear rise with the increase of the pressure drop. During the testing process, the residual pressure drop rose with the increase of cycles because of test dust attaching on the surface of the filter. The PM2.5 filtration efficiency was obtained of 99.854%, which was smaller than the dust filtration efficiency of 99.971% because of the fine particles taking larger proportion of the dust through the sample. Results show that this method of evaluating the PM2.5 filtration property is feasible.

Effects of uniformities of deposition of respirable particles on filters on determining their quartz contents by using the direct on-filter X-ray diffraction (DOF XRD) method.

PubMed

Chen, Ching-Hwa; Tsaia, Perng-Jy; Lai, Chane-Yu; Peng, Ya-Lian; Soo, Jhy-Charm; Chen, Cheng-Yao; Shih, Tung-Sheng

2010-04-15

In this study, field samplings were conducted in three workplaces of a foundry plant, including the molding, demolding, and bead blasting, respectively. Three respirable aerosol samplers (including a 25-mm aluminum cyclone, nylon cyclone, and IOSH cyclone) were used side-by-side to collect samples from each selected workplace. For each collected sample, the uniformity of the deposition of respirable dusts on the filter was measured and its free silica content was determined by both the DOF XRD method and NIOSH 7500 XRD method (i.e., the reference method). A same trend in measured uniformities can be found in all selected workplaces: 25-mm aluminum cyclone>nylon cyclone>IOSH cyclone. Even for samples collected by the sampler with the highest uniformity (i.e., 25-mm aluminum cyclone), the use of the DOF XRD method would lead to the measured free silica concentrations 1.15-2.89 times in magnitude higher than that of the reference method. A new filter holder should be developed with the minimum uniformity comparable to that of NIOSH 7500 XRD method (=0.78) in the future. The use of conversion factors for correcting quartz concentrations obtained from the DOF XRD method based on the measured uniformities could be suitable for the foundry industry at this stage. 2009 Elsevier B.V. All rights reserved.

Development of a filter regeneration system for advanced spacecraft fluid systems

NASA Technical Reports Server (NTRS)

Behrend, A. F., Jr.; Descamp, V. A.

1974-01-01

The development of a filter regeneration system for efficiently cleaning fluid particulate filters is presented. Based on a backflush/jet impingement technique, the regeneration system demonstrated a cleaning efficiency of 98.7 to 100%. The operating principles and design features are discussed with emphasis on the primary system components that include a regenerable filter, vortex particle separator, and zero-g particle trap. Techniques and equipment used for ground and zero-g performance tests are described. Test results and conclusions, as well as possible areas for commercial application, are included.

Numerical and experimental approaches to simulate soil clogging in porous media

NASA Astrophysics Data System (ADS)

Kanarska, Yuliya; LLNL Team

2012-11-01

Failure of a dam by erosion ranks among the most serious accidents in civil engineering. The best way to prevent internal erosion is using adequate granular filters in the transition areas where important hydraulic gradients can appear. In case of cracking and erosion, if the filter is capable of retaining the eroded particles, the crack will seal and the dam safety will be ensured. A finite element numerical solution of the Navier-Stokes equations for fluid flow together with Lagrange multiplier technique for solid particles was applied to the simulation of soil filtration. The numerical approach was validated through comparison of numerical simulations with the experimental results of base soil particle clogging in the filter layers performed at ERDC. The numerical simulation correctly predicted flow and pressure decay due to particle clogging. The base soil particle distribution was almost identical to those measured in the laboratory experiment. To get more precise understanding of the soil transport in granular filters we investigated sensitivity of particle clogging mechanisms to various aspects such as particle size ration, the amplitude of hydraulic gradient, particle concentration and contact properties. By averaging the results derived from the grain-scale simulations, we investigated how those factors affect the semi-empirical multiphase model parameters in the large-scale simulation tool. The Department of Homeland Security Science and Technology Directorate provided funding for this research.

Black carbon, mass and elemental measurements of airborne particles in the village of Serowe, Botswana

NASA Astrophysics Data System (ADS)

Moloi, K.; Chimidza, S.; Lindgren, E. Selin; Viksna, A.; Standzenieks, P.

Absorption of sunlight by sub-micron particles is an important factor in calculations of the radiation balance of the earth and thus in climate modelling. Carbon-containing particles are generally considered as the most important in this respect. Major sources of these particles are generally considered to be bio-mass burning and vehicle exhaust. In order to characterise size fractionated particulate matter in a rural village in Botswana with respect to light absorption and elemental content experiments were performed, in which simultaneous sampling was made with a dichotomous impactor and a laboratory-made sampler, made compatible with black carbon analysis by reflectometry. The dichotomous impactor was equipped with Teflon filters and the other sampler with glass fibre filters. Energy dispersive X-ray fluorescence was used for elemental analysis of both kinds of filters. It appeared that Teflon filters were the most suitable for the combination of mass-, elemental- and black carbon measurements. The black carbon content in coarse (2.5-10 μm) and fine (<2.5 μm) particles was determined separately and related to elemental content and emission source. The results show that the fine particle fraction in the aerosol has a much higher contribution of black particles than the coarse particle fraction. This observation is valid for the village in Botswana as well as for a typical industrialised city in Sweden, used as a reference location.

Fabrication of TiO2/EP super-hydrophobic thin film on filter paper surface.

PubMed

Gao, Zhengxin; Zhai, Xianglin; Liu, Feng; Zhang, Ming; Zang, Deli; Wang, Chengyu

2015-09-05

A composite filter paper with super-hydrophobicity was obtained by adhering micro/nano structure of amorphous titanium dioxide on the filter paper surface with modifying low surface energy material. By virtue of the coupling agent, which plays an important part in bonding amorphous titanium dioxide and epoxy resin, the structure of super-hydrophobic thin film on the filter paper surface is extremely stable. The microstructure of super-hydrophobic filter paper was characterized by scanning electron microscopy (SEM), the images showed that the as-prepared filter paper was covered with uniform amorphous titanium dioxide particles, generating a roughness structure on the filter paper surface. The super-hydrophobic performance of the filter paper was characterized by water contact angle measurements. The observations showed that the wettability of filter paper samples transformed from super-hydrophilicity to super-hydrophobicity with the water contact angle of 153 ± 1°. Some experiments were also designed to test the effect of water-oil separation and UV-resistant by the super-hydrophobic filter paper. The prepared super-hydrophobic filter paper worked efficiently and simply in water-oil separation as well as enduringly in anti-UV property after the experiments. This method offers an opportunity to the practical applications of the super-hydrophobic filter paper. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling Interactions Among Turbulence, Gas-Phase Chemistry, Soot and Radiation Using Transported PDF Methods

NASA Astrophysics Data System (ADS)

Haworth, Daniel

2013-11-01

The importance of explicitly accounting for the effects of unresolved turbulent fluctuations in Reynolds-averaged and large-eddy simulations of chemically reacting turbulent flows is increasingly recognized. Transported probability density function (PDF) methods have emerged as one of the most promising modeling approaches for this purpose. In particular, PDF methods provide an elegant and effective resolution to the closure problems that arise from averaging or filtering terms that correspond to nonlinear point processes, including chemical reaction source terms and radiative emission. PDF methods traditionally have been associated with studies of turbulence-chemistry interactions in laboratory-scale, atmospheric-pressure, nonluminous, statistically stationary nonpremixed turbulent flames; and Lagrangian particle-based Monte Carlo numerical algorithms have been the predominant method for solving modeled PDF transport equations. Recent advances and trends in PDF methods are reviewed and discussed. These include advances in particle-based algorithms, alternatives to particle-based algorithms (e.g., Eulerian field methods), treatment of combustion regimes beyond low-to-moderate-Damköhler-number nonpremixed systems (e.g., premixed flamelets), extensions to include radiation heat transfer and multiphase systems (e.g., soot and fuel sprays), and the use of PDF methods as the basis for subfilter-scale modeling in large-eddy simulation. Examples are provided that illustrate the utility and effectiveness of PDF methods for physics discovery and for applications to practical combustion systems. These include comparisons of results obtained using the PDF method with those from models that neglect unresolved turbulent fluctuations in composition and temperature in the averaged or filtered chemical source terms and/or the radiation heat transfer source terms. In this way, the effects of turbulence-chemistry-radiation interactions can be isolated and quantified.

PDADMAC flocculation of Chinese hamster ovary cells: enabling a centrifuge-less harvest process for monoclonal antibodies.

PubMed

McNerney, Thomas; Thomas, Anne; Senczuk, Anna; Petty, Krista; Zhao, Xiaoyang; Piper, Rob; Carvalho, Juliane; Hammond, Matthew; Sawant, Satin; Bussiere, Jeanine

2015-01-01

High titer (>10 g/L) monoclonal antibody (mAb) cell culture processes are typically achieved by maintaining high viable cell densities over longer culture durations. A corresponding increase in the solids and sub-micron cellular debris particle levels are also observed. This higher burden of solids (≥15%) and sub-micron particles typically exceeds the capabilities of a continuous centrifuge to effectively remove the solids without a substantial loss of product and/or the capacity of the harvest filtration train (depth filter followed by membrane filter) used to clarify the centrate. We discuss here the use of a novel and simple two-polymer flocculation method used to harvest mAb from high cell mass cell culture processes. The addition of the polycationic polymer, poly diallyldimethylammonium chloride (PDADMAC) to the cell culture broth flocculates negatively-charged cells and cellular debris via an ionic interaction mechanism. Incorporation of a non-ionic polymer such as polyethylene glycol (PEG) into the PDADMAC flocculation results in larger flocculated particles with faster settling rate compared to PDADMAC-only flocculation. PDADMAC also flocculates the negatively-charged sub-micron particles to produce a feed stream with a significantly higher harvest filter train throughput compared to a typical centrifuged harvest feed stream. Cell culture process variability such as lactate production, cellular debris and cellular densities were investigated to determine the effect on flocculation. Since PDADMAC is cytotoxic, purification process clearance and toxicity assessment were performed.

PDADMAC flocculation of Chinese hamster ovary cells: Enabling a centrifuge-less harvest process for monoclonal antibodies

PubMed Central

McNerney, Thomas; Thomas, Anne; Senczuk, Anna; Petty, Krista; Zhao, Xiaoyang; Piper, Rob; Carvalho, Juliane; Hammond, Matthew; Sawant, Satin; Bussiere, Jeanine

2015-01-01

High titer (>10 g/L) monoclonal antibody (mAb) cell culture processes are typically achieved by maintaining high viable cell densities over longer culture durations. A corresponding increase in the solids and sub-micron cellular debris particle levels are also observed. This higher burden of solids (≥15%) and sub-micron particles typically exceeds the capabilities of a continuous centrifuge to effectively remove the solids without a substantial loss of product and/or the capacity of the harvest filtration train (depth filter followed by membrane filter) used to clarify the centrate. We discuss here the use of a novel and simple two-polymer flocculation method used to harvest mAb from high cell mass cell culture processes. The addition of the polycationic polymer, poly diallyldimethylammonium chloride (PDADMAC) to the cell culture broth flocculates negatively-charged cells and cellular debris via an ionic interaction mechanism. Incorporation of a non-ionic polymer such as polyethylene glycol (PEG) into the PDADMAC flocculation results in larger flocculated particles with faster settling rate compared to PDADMAC-only flocculation. PDADMAC also flocculates the negatively-charged sub-micron particles to produce a feed stream with a significantly higher harvest filter train throughput compared to a typical centrifuged harvest feed stream. Cell culture process variability such as lactate production, cellular debris and cellular densities were investigated to determine the effect on flocculation. Since PDADMAC is cytotoxic, purification process clearance and toxicity assessment were performed. PMID:25706650

Methods used to calculate doses resulting from inhalation of Capstone depleted uranium aerosols.

PubMed

Miller, Guthrie; Cheng, Yung Sung; Traub, Richard J; Little, Tom T; Guilmette, Raymond A

2009-03-01

The methods used to calculate radiological and toxicological doses to hypothetical persons inside either a U.S. Army Abrams tank or Bradley Fighting Vehicle that has been perforated by depleted uranium munitions are described. Data from time- and particle-size-resolved measurements of depleted uranium aerosol as well as particle-size-resolved measurements of aerosol solubility in lung fluids for aerosol produced in the breathing zones of the hypothetical occupants were used. The aerosol was approximated as a mixture of nine monodisperse (single particle size) components corresponding to particle size increments measured by the eight stages plus the backup filter of the cascade impactors used. A Markov Chain Monte Carlo Bayesian analysis technique was employed, which straightforwardly calculates the uncertainties in doses. Extensive quality control checking of the various computer codes used is described.

Capturing PM2.5 Emissions from 3D Printing via Nanofiber-based Air Filter.

PubMed

Rao, Chengchen; Gu, Fu; Zhao, Peng; Sharmin, Nusrat; Gu, Haibing; Fu, Jianzhong

2017-09-04

This study investigated the feasibility of using polycaprolactone (PCL) nanofiber-based air filters to capture PM2.5 particles emitted from fused deposition modeling (FDM) 3D printing. Generation and aggregation of emitted particles were investigated under different testing environments. The results show that: (1) the PCL nanofiber membranes are capable of capturing particle emissions from 3D printing, (2) relative humidity plays a signification role in aggregation of the captured particles, (3) generation and aggregation of particles from 3D printing can be divided into four stages: the PM2.5 concentration and particles size increase slowly (first stage), small particles are continuously generated and their concentration increases rapidly (second stage), small particles aggregate into more large particles and the growth of concentration slows down (third stage), the PM2.5 concentration and particle aggregation sizes increase rapidly (fourth stage), and (4) the ultrafine particles denoted as "building unit" act as the fundamentals of the aggregated particles. This work has tremendous implications in providing measures for controlling the particle emissions from 3D printing, which would facilitate the extensive application of 3D printing. In addition, this study provides a potential application scenario for nanofiber-based air filters other than laboratory theoretical investigation.

Radiological/biological/aerosol removal system

DOEpatents

Haslam, Jeffery J

2015-03-17

An air filter replacement system for existing buildings, vehicles, arenas, and other enclosed airspaces includes a replacement air filter for replacing a standard air filter. The replacement air filter has dimensions and air flow specifications that allow it to replace the standard air filter. The replacement air filter includes a filter material that removes radiological or biological or aerosol particles.

Instituting a filtration/pressurization system to reduce dust concentrations in a control room at a mineral processing plant

PubMed Central

Noll, J.; Cecala, A.; Hummer, J.

2016-01-01

The National Institute for Occupational Safety and Health has observed that many control rooms and operator compartments in the U.S. mining industry do not have filtration systems capable of maintaining low dust concentrations in these areas. In this study at a mineral processing plant, to reduce respirable dust concentrations in a control room that had no cleaning system for intake air, a filtration and pressurization system originally designed for enclosed cabs was modified and installed. This system was composed of two filtering units: one to filter outside air and one to filter and recirculate the air inside the control room. Eighty-seven percent of submicrometer particles were reduced by the system under static conditions. This means that greater than 87 percent of respirable dust particles should be reduced as the particle-size distribution of respirable dust particles is greater than that of submicrometer particles, and filtration systems usually are more efficient in capturing the larger particles. A positive pressure near 0.02 inches of water gauge was produced, which is an important component of an effective system and minimizes the entry of particles, such as dust, into the room. The intake airflow was around 118 cfm, greater than the airflow suggested by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) for acceptable indoor air quality. After one year, the loading of the filter caused the airflow to decrease to 80 cfm, which still produces acceptable indoor air quality. Due to the loading of the filters, the reduction efficiency for submicrometer particles under static conditions increased to 94 percent from 87 percent. PMID:26834293

Real-time explosive particle detection using a cyclone particle concentrator.

PubMed

Hashimoto, Yuichiro; Nagano, Hisashi; Takada, Yasuaki; Kashima, Hideo; Sugaya, Masakazu; Terada, Koichi; Sakairi, Minoru

2014-06-30

There is a need for more rapid methods for the detection of explosive particles. We have developed a novel real-time analysis technique for explosive particles that uses a cyclone particle concentrator. This technique can analyze sample surfaces for the presence of particles from explosives such as TNT and RDX within 3 s, which is much faster than is possible by conventional methods. Particles are detached from the sample surface with air jet pulses, and then introduced into a cyclone particle concentrator with a high pumping speed of about 80 L/min. A vaporizer placed at the bottom of the cyclone particle concentrator immediately converts the particles into a vapor. The vapor is then ionized in the atmospheric pressure chemical ionization (APCI) source of a linear ion trap mass spectrometer. An online connection between the vaporizer and a mass spectrometer enables high-speed detection within a few seconds, compared with the conventional off-line heating method that takes more than 10 s to raise the temperature of a sample filter unit. Since the configuration enriched the number density of explosive particles by about 80 times compared with that without the concentrator, a sub-ng amount of TNT particles on a surface was detectable. The detection limit of our technique is comparable with that of an explosives trace detector using ion mobility spectrometry. The technique will be beneficial for trace detection in security applications, because it detects explosive particles on the surface more speedily than conventional methods. Copyright © 2014 John Wiley & Sons, Ltd.

TECHNICAL NOTE: PERFORMANCE OF A PERSONAL ELECTROSTATIC PRECIPITATOR PARTICLE SAMPLER

EPA Science Inventory

Filter-based methods used to measure aerosols with semi-volatile constituents are subject to biases from adsorption and volatilization that may occur during sampling (McDow et al., 1990, Turpin et al., 1994, Volckens et al., 1999; Tolocka et al. 2001). The development and eval...

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

Incorporating advanced language models into the P300 speller using particle filtering

NASA Astrophysics Data System (ADS)

Speier, W.; Arnold, C. W.; Deshpande, A.; Knall, J.; Pouratian, N.

2015-08-01

Objective. The P300 speller is a common brain-computer interface (BCI) application designed to communicate language by detecting event related potentials in a subject’s electroencephalogram signal. Information about the structure of natural language can be valuable for BCI communication, but attempts to use this information have thus far been limited to rudimentary n-gram models. While more sophisticated language models are prevalent in natural language processing literature, current BCI analysis methods based on dynamic programming cannot handle their complexity. Approach. Sampling methods can overcome this complexity by estimating the posterior distribution without searching the entire state space of the model. In this study, we implement sequential importance resampling, a commonly used particle filtering (PF) algorithm, to integrate a probabilistic automaton language model. Main result. This method was first evaluated offline on a dataset of 15 healthy subjects, which showed significant increases in speed and accuracy when compared to standard classification methods as well as a recently published approach using a hidden Markov model (HMM). An online pilot study verified these results as the average speed and accuracy achieved using the PF method was significantly higher than that using the HMM method. Significance. These findings strongly support the integration of domain-specific knowledge into BCI classification to improve system performance.

Comment on "Irreversible sorption of trace concentrations of perfluorocarboxylic acids to fiber filters used for air sampling" by Arp and Goss (Atmospheric Environment 42, 6869-6872, 2008)

NASA Astrophysics Data System (ADS)

Barton, Catherine A.; Kaiser, Mary A.; Butler, Larry E.; Botelho, Miguel A.

This discussion paper reflects concerns as to the technical arguments set forth in the Arp and Goss paper. The authors of the paper, Arp and Goss, hypothesize that vapor phase perfluorocarboxylic acids (PFAs) are irreversibly sorbed to the surface of air sampling filters, and that this sorption erroneously biases vapor/particle speciation measurements toward the particle phase. These authors also suggest a surface treatment of the filters is necessary. As authors of some of the experimental data used in the Arp paper, we believe Arp and Goss have misstated the case for irreversible adsorption, and that untreated filters provide adequate vapor/particle speciation results for PFAs. Additional field data are offered to help prove the point.

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

PubMed

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.

Genetic particle filter application to land surface temperature downscaling

NASA Astrophysics Data System (ADS)

Mechri, Rihab; Ottlé, Catherine; Pannekoucke, Olivier; Kallel, Abdelaziz

2014-03-01

Thermal infrared data are widely used for surface flux estimation giving the possibility to assess water and energy budgets through land surface temperature (LST). Many applications require both high spatial resolution (HSR) and high temporal resolution (HTR), which are not presently available from space. It is therefore necessary to develop methodologies to use the coarse spatial/high temporal resolutions LST remote-sensing products for a better monitoring of fluxes at appropriate scales. For that purpose, a data assimilation method was developed to downscale LST based on particle filtering. The basic tenet of our approach is to constrain LST dynamics simulated at both HSR and HTR, through the optimization of aggregated temperatures at the coarse observation scale. Thus, a genetic particle filter (GPF) data assimilation scheme was implemented and applied to a land surface model which simulates prior subpixel temperatures. First, the GPF downscaling scheme was tested on pseudoobservations generated in the framework of the study area landscape (Crau-Camargue, France) and climate for the year 2006. The GPF performances were evaluated against observation errors and temporal sampling. Results show that GPF outperforms prior model estimations. Finally, the GPF method was applied on Spinning Enhanced Visible and InfraRed Imager time series and evaluated against HSR data provided by an Advanced Spaceborne Thermal Emission and Reflection Radiometer image acquired on 26 July 2006. The temperatures of seven land cover classes present in the study area were estimated with root-mean-square errors less than 2.4 K which is a very promising result for downscaling LST satellite products.

Generation of a large volume of clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles for cell culture studies

PubMed Central

Ingham, Eileen; Fisher, John; Tipper, Joanne L

2014-01-01

It has recently been shown that the wear of ultra-high-molecular-weight polyethylene in hip and knee prostheses leads to the generation of nanometre-sized particles, in addition to micron-sized particles. The biological activity of nanometre-sized ultra-high-molecular-weight polyethylene wear particles has not, however, previously been studied due to difficulties in generating sufficient volumes of nanometre-sized ultra-high-molecular-weight polyethylene wear particles suitable for cell culture studies. In this study, wear simulation methods were investigated to generate a large volume of endotoxin-free clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles. Both single-station and six-station multidirectional pin-on-plate wear simulators were used to generate ultra-high-molecular-weight polyethylene wear particles under sterile and non-sterile conditions. Microbial contamination and endotoxin levels in the lubricants were determined. The results indicated that microbial contamination was absent and endotoxin levels were low and within acceptable limits for the pharmaceutical industry, when a six-station pin-on-plate wear simulator was used to generate ultra-high-molecular-weight polyethylene wear particles in a non-sterile environment. Different pore-sized polycarbonate filters were investigated to isolate nanometre-sized ultra-high-molecular-weight polyethylene wear particles from the wear test lubricants. The use of the filter sequence of 10, 1, 0.1, 0.1 and 0.015 µm pore sizes allowed successful isolation of ultra-high-molecular-weight polyethylene wear particles with a size range of < 100 nm, which was suitable for cell culture studies. PMID:24658586

Generation of a large volume of clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles for cell culture studies.

PubMed

Liu, Aiqin; Ingham, Eileen; Fisher, John; Tipper, Joanne L

2014-04-01

It has recently been shown that the wear of ultra-high-molecular-weight polyethylene in hip and knee prostheses leads to the generation of nanometre-sized particles, in addition to micron-sized particles. The biological activity of nanometre-sized ultra-high-molecular-weight polyethylene wear particles has not, however, previously been studied due to difficulties in generating sufficient volumes of nanometre-sized ultra-high-molecular-weight polyethylene wear particles suitable for cell culture studies. In this study, wear simulation methods were investigated to generate a large volume of endotoxin-free clinically relevant nanometre-sized ultra-high-molecular-weight polyethylene wear particles. Both single-station and six-station multidirectional pin-on-plate wear simulators were used to generate ultra-high-molecular-weight polyethylene wear particles under sterile and non-sterile conditions. Microbial contamination and endotoxin levels in the lubricants were determined. The results indicated that microbial contamination was absent and endotoxin levels were low and within acceptable limits for the pharmaceutical industry, when a six-station pin-on-plate wear simulator was used to generate ultra-high-molecular-weight polyethylene wear particles in a non-sterile environment. Different pore-sized polycarbonate filters were investigated to isolate nanometre-sized ultra-high-molecular-weight polyethylene wear particles from the wear test lubricants. The use of the filter sequence of 10, 1, 0.1, 0.1 and 0.015 µm pore sizes allowed successful isolation of ultra-high-molecular-weight polyethylene wear particles with a size range of < 100 nm, which was suitable for cell culture studies.

Volatilization of PM2.5 Inorganic Ions in a Filter Pack System with Backup Filter and Denuders

NASA Astrophysics Data System (ADS)

Kim, C.; Choi, Y.; Ghim, Y.

2012-12-01

Concentrations of PM2.5 inorganic ions were measured at the rooftop of the 5-story building on the hill (37.02oN, 127.16oE, 167 m above sea level) in the Global Campus of Hankuk University of Foreign Studies, about 35 km southeast of downtown Seoul, Korea. The measurements were made four times during one-year span between 2011 and 2012 by considering the climate of Korea with distinct seasonal variations: July 29 to August 26 (summer); September 14 to October 13 (fall); November 28 to January 4 (winter); February 14 to May 31 (spring). A filter pack system was composed of PM2.5 cyclone, two annular denuders, Teflon filter, nylon filter, and an annular denuder, in series. Two annular denuders were to remove acidic and basic gases prior to collecting particles on the Teflon filter. Nylon filter and an annular denuder were to back up the Teflon filter by absorbing acidic and basic gases, respectively, which were volatilized from collected particles on the Teflon filter. Samplings were made for 24 hours every day. Extracts from filters and denuders were analyzed by ion chromatography to measure concentrations of anions (SO42-, NO3-, Cl-) and cations (Ca2+, Mg2+, NH4+, Na+, K+). The amounts of ionic species absorbed at the backup nylon filter and denuder were examined in terms of meteorological parameters, the amounts of gases removed in front of the Teflon filter, and the amounts of particulate ions collected on the Teflon filter. Major factors to affect the volatilization from particles collected on the Teflon filter were discussed.

Electromagnetic sunscreen model: design of experiments on particle specifications.

PubMed

Lécureux, Marie; Deumié, Carole; Enoch, Stefan; Sergent, Michelle

2015-10-01

We report a numerical study on sunscreen design and optimization. Thanks to the combined use of electromagnetic modeling and design of experiments, we are able to screen the most relevant parameters of mineral filters and to optimize sunscreens. Several electromagnetic modeling methods are used depending on the type of particles, density of particles, etc. Both the sun protection factor (SPF) and the UVB/UVA ratio are considered. We show that the design of experiments' model should include interactions between materials and other parameters. We conclude that the material of the particles is a key parameter for the SPF and the UVB/UVA ratio. Among the materials considered, none is optimal for both. The SPF is also highly dependent on the size of the particles.

Variation in aluminum, iron, and particle concentrations in oxic groundwater samples collected by use of tangential-flow ultrafiltration with low-flow sampling

NASA Astrophysics Data System (ADS)

Szabo, Zoltan; Oden, Jeannette H.; Gibs, Jacob; Rice, Donald E.; Ding, Yuan

2002-02-01

Particulates that move with ground water and those that are artificially mobilized during well purging could be incorporated into water samples during collection and could cause trace-element concentrations to vary in unfiltered samples, and possibly in filtered samples (typically 0.45-um (micron) pore size) as well, depending on the particle-size fractions present. Therefore, measured concentrations may not be representative of those in the aquifer. Ground water may contain particles of various sizes and shapes that are broadly classified as colloids, which do not settle from water, and particulates, which do. In order to investigate variations in trace-element concentrations in ground-water samples as a function of particle concentrations and particle-size fractions, the U.S. Geological Survey, in cooperation with the U.S. Air Force, collected samples from five wells completed in the unconfined, oxic Kirkwood-Cohansey aquifer system of the New Jersey Coastal Plain. Samples were collected by purging with a portable pump at low flow (0.2-0.5 liters per minute and minimal drawdown, ideally less than 0.5 foot). Unfiltered samples were collected in the following sequence: (1) within the first few minutes of pumping, (2) after initial turbidity declined and about one to two casing volumes of water had been purged, and (3) after turbidity values had stabilized at less than 1 to 5 Nephelometric Turbidity Units. Filtered samples were split concurrently through (1) a 0.45-um pore size capsule filter, (2) a 0.45-um pore size capsule filter and a 0.0029-um pore size tangential-flow filter in sequence, and (3), in selected cases, a 0.45-um and a 0.05-um pore size capsule filter in sequence. Filtered samples were collected concurrently with the unfiltered sample that was collected when turbidity values stabilized. Quality-assurance samples consisted of sequential duplicates (about 25 percent) and equipment blanks. Concentrations of particles were determined by light scattering.

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

PubMed

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.

Quantitative filter forensics for indoor particle sampling.

PubMed

Haaland, D; Siegel, J A

2017-03-01

Filter forensics is a promising indoor air investigation technique involving the analysis of dust which has collected on filters in central forced-air heating, ventilation, and air conditioning (HVAC) or portable systems to determine the presence of indoor particle-bound contaminants. In this study, we summarize past filter forensics research to explore what it reveals about the sampling technique and the indoor environment. There are 60 investigations in the literature that have used this sampling technique for a variety of biotic and abiotic contaminants. Many studies identified differences between contaminant concentrations in different buildings using this technique. Based on this literature review, we identified a lack of quantification as a gap in the past literature. Accordingly, we propose an approach to quantitatively link contaminants extracted from HVAC filter dust to time-averaged integrated air concentrations. This quantitative filter forensics approach has great potential to measure indoor air concentrations of a wide variety of particle-bound contaminants. Future studies directly comparing quantitative filter forensics to alternative sampling techniques are required to fully assess this approach, but analysis of past research suggests the enormous possibility of this approach. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

From prompt gamma distribution to dose: a novel approach combining an evolutionary algorithm and filtering based on Gaussian-powerlaw convolutions.

PubMed

Schumann, A; Priegnitz, M; Schoene, S; Enghardt, W; Rohling, H; Fiedler, F

2016-10-07

Range verification and dose monitoring in proton therapy is considered as highly desirable. Different methods have been developed worldwide, like particle therapy positron emission tomography (PT-PET) and prompt gamma imaging (PGI). In general, these methods allow for a verification of the proton range. However, quantification of the dose from these measurements remains challenging. For the first time, we present an approach for estimating the dose from prompt γ-ray emission profiles. It combines a filtering procedure based on Gaussian-powerlaw convolution with an evolutionary algorithm. By means of convolving depth dose profiles with an appropriate filter kernel, prompt γ-ray depth profiles are obtained. In order to reverse this step, the evolutionary algorithm is applied. The feasibility of this approach is demonstrated for a spread-out Bragg-peak in a water target.

Feasibility of granular bed filtration of an aerosol of ultrafine metallic particles including a pressure drop regeneration system.

PubMed

Bémer, D; Wingert, L; Morele, Y; Subra, I

2015-09-01

A process for filtering an aerosol of ultrafine metallic particles (UFP) has been designed and tested, based on the principle of a multistage granular bed. The filtration system comprised a succession of granular beds of varying thickness composed of glass beads of different diameters. This system allows the pressure drop to be regenerated during filtration ("on-line" mode) using a vibrating probe. Tests monitoring the pressure drop were conducted on a "10-L/min" low airflow rate device and on a "100-m(3)/hr" prototype. Granular bed unclogging is automated on the latter. The cyclic operation and filtration performances are similar to that of filter medium-based industrial dust collectors. Filtration of ultrafine metallic particles generated by different industrial processes such as arc welding, metal cutting, or spraying constitutes a difficult problem due to the high filter clogging properties of these particles and to the high temperatures generally encountered. Granular beds represent an advantageous means of filtering these aerosols with difficult properties.

Irreversible sorption of trace concentrations of perfluorocarboxylic acids to fiber filters used for air sampling

NASA Astrophysics Data System (ADS)

Arp, Hans Peter H.; Goss, Kai-Uwe

Due to the apparent environmental omnipresence of perfluorocarboxylic acids (PFAs), an increasing number of researchers are investigating their ambient particle- and gas-phase concentrations. Typically this is done using a high-volume air sampler equipped with Quartz Fiber Filters (QFFs) or Glass Fiber Filters (GFFs) to sample the particle-bound PFAs and downstream sorbents to sample the gas-phase PFAs. This study reports that at trace, ambient concentrations gas-phase PFAs sorb to QFFs and GFFs irreversibly and hardly pass through these filters to the downstream sorbents. As a consequence, it is not possible to distinguish between particle- and gas-phase concentrations, or to distinguish concentrations on different particle size fractions, unless precautions are taken. Failure to take such precautions could have already caused reported data to be misinterpreted. Here it is also reported that deactivating QFFs and GFFs with a silylating agent renders them suitable for sampling PFAs. Based on the presented study, a series of recommendations for air-sampling PFAs are provided.

Indoor Map Aided Wi-Fi Integrated Lbs on Smartphone Platforms

NASA Astrophysics Data System (ADS)

Yu, C.; El-Sheimy, N.

2017-09-01

In this research, an indoor map aided INS/Wi-Fi integrated location based services (LBS) applications is proposed and implemented on smartphone platforms. Indoor map information together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value from Wi-Fi are collected to obtain an accurate, continuous, and low-cost position solution. The main challenge of this research is to make effective use of various measurements that complement each other without increasing the computational burden of the system. The integrated system in this paper includes three modules: INS, Wi-Fi (if signal available) and indoor maps. A cascade structure Particle/Kalman filter framework is applied to combine the different modules. Firstly, INS position and Wi-Fi fingerprint position integrated through Kalman filter for estimating positioning information. Then, indoor map information is applied to correct the error of INS/Wi-Fi estimated position through particle filter. Indoor tests show that the proposed method can effectively reduce the accumulation positioning errors of stand-alone INS systems, and provide stable, continuous and reliable indoor location service.

Ground roll attenuation using polarization analysis in the t-f-k domain

NASA Astrophysics Data System (ADS)

Wang, C.; Wang, Y.

2017-07-01

S waves travel slower than P waves and have a lower dominant frequency. Therefore, applying common techniques such as time-frequency filtering and f-k filtering to separate S waves from ground roll is difficult because ground roll is also characterized by slow velocity and low frequency. In this study, we present a method for attenuating ground roll using a polarization filtering method based on the t-f-k transform. We describe the particle motion of the waves by complex vector signals. Each pair of frequency components, whose frequencies have the same absolute value but different signs, of the complex signal indicate an elliptical or linear motion. The polarization parameters of the elliptical or linear motion are explicitly related to the two Fourier coefficients. We then extend these concepts to the t-f-k domain and propose a polarization filtering method for ground roll attenuation based on the t-f-k transform. The proposed approach can define automatically the time-varying reject zones on the f-k panel at different times as a function of the reciprocal ellipticity. Four attributes, time, frequency, apparent velocity and polarization are used to identify and extract the ground roll simultaneously. Thus, the ground roll and body waves can be separated as long as they are dissimilar in one of these attributes. We compare our method with commonly used filtering techniques by applying the methods to synthetic and real seismic data. The results indicate that our method can attenuate ground roll while preserving body waves more effectively than the other methods.

An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation using real data from a multiphase producer

NASA Astrophysics Data System (ADS)

Lorentzen, Rolf J.; Stordal, Andreas S.; Hewitt, Neal

2017-05-01

Flowrate allocation in production wells is a complicated task, especially for multiphase flow combined with several reservoir zones and/or branches. The result depends heavily on the available production data, and the accuracy of these. In the application we show here, downhole pressure and temperature data are available, in addition to the total flowrates at the wellhead. The developed methodology inverts these observations to the fluid flowrates (oil, water and gas) that enters two production branches in a real full-scale producer. A major challenge is accurate estimation of flowrates during rapid variations in the well, e.g. due to choke adjustments. The Auxiliary Sequential Importance Resampling (ASIR) filter was developed to handle such challenges, by introducing an auxiliary step, where the particle weights are recomputed (second weighting step) based on how well the particles reproduce the observations. However, the ASIR filter suffers from large computational time when the number of unknown parameters increase. The Gaussian Mixture (GM) filter combines a linear update, with the particle filters ability to capture non-Gaussian behavior. This makes it possible to achieve good performance with fewer model evaluations. In this work we present a new filter which combines the ASIR filter and the Gaussian Mixture filter (denoted ASGM), and demonstrate improved estimation (compared to ASIR and GM filters) in cases with rapid parameter variations, while maintaining reasonable computational cost.

Two size-selective mechanisms specifically trap bacteria-sized food particles in Caenorhabditis elegans.

PubMed

Fang-Yen, Christopher; Avery, Leon; Samuel, Aravinthan D T

2009-11-24

Caenorhabditis elegans is a filter feeder: it draws bacteria suspended in liquid into its pharynx, traps the bacteria, and ejects the liquid. How pharyngeal pumping simultaneously transports and filters food particles has been poorly understood. Here, we use high-speed video microscopy to define the detailed workings of pharyngeal mechanics. The buccal cavity and metastomal flaps regulate the flow of dense bacterial suspensions and exclude excessively large particles from entering the pharynx. A complex sequence of contractions and relaxations transports food particles in two successive trap stages before passage into the terminal bulb and intestine. Filtering occurs at each trap as bacteria are concentrated in the central lumen while fluids are expelled radially through three apical channels. Experiments with microspheres show that the C. elegans pharynx, in combination with the buccal cavity, is tuned to specifically catch and transport particles of a size range corresponding to most soil bacteria.

Two size-selective mechanisms specifically trap bacteria-sized food particles in Caenorhabditis elegans

PubMed Central

Fang-Yen, Christopher; Avery, Leon; Samuel, Aravinthan D. T.

2009-01-01

Caenorhabditis elegans is a filter feeder: it draws bacteria suspended in liquid into its pharynx, traps the bacteria, and ejects the liquid. How pharyngeal pumping simultaneously transports and filters food particles has been poorly understood. Here, we use high-speed video microscopy to define the detailed workings of pharyngeal mechanics. The buccal cavity and metastomal flaps regulate the flow of dense bacterial suspensions and exclude excessively large particles from entering the pharynx. A complex sequence of contractions and relaxations transports food particles in two successive trap stages before passage into the terminal bulb and intestine. Filtering occurs at each trap as bacteria are concentrated in the central lumen while fluids are expelled radially through three apical channels. Experiments with microspheres show that the C. elegans pharynx, in combination with the buccal cavity, is tuned to specifically catch and transport particles of a size range corresponding to most soil bacteria. PMID:19903886

A CAM (continuous air monitor) sampler for collecting and assessing alpha-emitting aerosol particles

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

McFarland, A.R.; Bethel, E.L.; Ortiz, C.A.

1991-07-01

A new continuous air monitor (CAM) sampler for assessing alpha-emitting transuranic aerosol particles has been developed. The system has been designed to permit collection of particles that can potentially penetrate into the thoracic region of the human respiratory system. Wind tunnel testing of the sampler has been used to characterize the penetration of aerosol to the collection filter. Results show that greater than or equal to 50% of 10-micrograms aerodynamic equivalent diameter (AED) particles are collected by the filter at wind speeds of 0.3 to 2 m s-1 and at sampling flow rates of 28 to 113 L min-1 (1more » to 4 cfm). The deposition of 10-microns AED particles takes place primarily in the center of the filter, where the counting efficiency of the detector is highest.« less

40 CFR 420.21 - Specialized definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... control system that utilizes filters to remove iron-bearing particles (fines) from blast furnace or... level is 10 pg/L per EPA Method 1613B for water and wastewater samples. (d) The term pg/L means... pollution control system means an emission control system that utilizes water to clean process or furnace...

40 CFR 420.21 - Specialized definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... control system that utilizes filters to remove iron-bearing particles (fines) from blast furnace or... level is 10 pg/L per EPA Method 1613B for water and wastewater samples. (d) The term pg/L means... pollution control system means an emission control system that utilizes water to clean process or furnace...

40 CFR 420.21 - Specialized definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... emission control system that utilizes filters to remove iron-bearing particles (fines) from blast furnace...-tetrachlorodibenzofuran, the minimum level is 10 pg/L per EPA Method 1613B for water and wastewater samples. (d) The term... term wet air pollution control system means an emission control system that utilizes water to clean...

40 CFR 420.21 - Specialized definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... control system that utilizes filters to remove iron-bearing particles (fines) from blast furnace or... level is 10 pg/L per EPA Method 1613B for water and wastewater samples. (d) The term pg/L means... pollution control system means an emission control system that utilizes water to clean process or furnace...

Characterization of biological aerosol exposure risks from automobile air conditioning system.

PubMed

Li, Jing; Li, Mingzhen; Shen, Fangxia; Zou, Zhuanglei; Yao, Maosheng; Wu, Chang-yu

2013-09-17

Although use of automobile air conditioning (AC) was shown to reduce in-vehicle particle levels, the characterization of its microbial aerosol exposure risks is lacking. Here, both AC and engine filter dust samples were collected from 30 automobiles in four different geographical locations in China. Biological contents (bacteria, fungi, and endotoxin) were studied using culturing, high-throughput gene sequence, and Limulus amebocyte lysate (LAL) methods. In-vehicle viable bioaerosol concentrations were directly monitored using an ultraviolet aerodynamic particle sizer (UVAPS) before and after use of AC for 5, 10, and 15 min. Regardless of locations, the vehicle AC filter dusts were found to be laden with high levels of bacteria (up to 26,150 CFU/mg), fungi (up to 1287 CFU/mg), and endotoxin (up to 5527 EU/mg). More than 400 unique bacterial species, including human opportunistic pathogens, were detected in the filter dusts. In addition, allergenic fungal species were also found abundant. Surprisingly, unexpected fluorescent peaks around 2.5 μm were observed during the first 5 min use of AC, which was attributed to the reaerosolization of those filter-borne microbial agents. The information obtained here can assist in minimizing or preventing the respiratory allergy or infection risk from the use of automobile AC system.

Scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX) and aerosol time-of-flight mass spectrometry (ATOFMS) single particle analysis of metallurgy plant emissions.

PubMed

Arndt, J; Deboudt, K; Anderson, A; Blondel, A; Eliet, S; Flament, P; Fourmentin, M; Healy, R M; Savary, V; Setyan, A; Wenger, J C

2016-03-01

The chemical composition of single particles deposited on industrial filters located in three different chimneys of an iron-manganese (Fe-Mn) alloy manufacturing plant have been compared using aerosol time-of-flight mass spectrometry (ATOFMS) and scanning electron microscopy-energy dispersive X-ray spectrometry (SEM-EDX). Very similar types of particles were observed using both analytical techniques. Calcium-containing particles dominated in the firing area of the sintering unit, Mn and/or Al-bearing particles were observed at the cooling area of the sintering unit, while Mn-containing particles were dominant at the smelting unit. SEM-EDX analysis of particles collected downstream of the industrial filters showed that the composition of the particles emitted from the chimneys is very similar to those collected on the filters. ATOFMS analysis of ore samples was also performed to identify particulate emissions that could be generated by wind erosion and manual activities. Specific particle types have been identified for each emission source (chimneys and ore piles) and can be used as tracers for source apportionment of ambient PM measured in the vicinity of the industrial site. Copyright © 2015 Elsevier Ltd. All rights reserved.

Deposition Uniformity of Coal Dust on Filters and Its Effect on the Accuracy of FTIR Analyses for Silica.

PubMed

Miller, Arthur L; Drake, Pamela L; Murphy, Nathaniel C; Cauda, Emanuele G; LeBouf, Ryan F; Markevicius, Gediminas

Miners are exposed to silica-bearing dust which can lead to silicosis, a potentially fatal lung disease. Currently, airborne silica is measured by collecting filter samples and sending them to a laboratory for analysis. Since this may take weeks, a field method is needed to inform decisions aimed at reducing exposures. This study investigates a field-portable Fourier transform infrared (FTIR) method for end-of-shift (EOS) measurement of silica on filter samples. Since the method entails localized analyses, spatial uniformity of dust deposition can affect accuracy and repeatability. The study, therefore, assesses the influence of radial deposition uniformity on the accuracy of the method. Using laboratory-generated Minusil and coal dusts and three different types of sampling systems, multiple sets of filter samples were prepared. All samples were collected in pairs to create parallel sets for training and validation. Silica was measured by FTIR at nine locations across the face of each filter and the data analyzed using a multiple regression analysis technique that compared various models for predicting silica mass on the filters using different numbers of "analysis shots." It was shown that deposition uniformity is independent of particle type (kaolin vs. silica), which suggests the role of aerodynamic separation is negligible. Results also reflected the correlation between the location and number of shots versus the predictive accuracy of the models. The coefficient of variation (CV) for the models when predicting mass of validation samples was 4%-51% depending on the number of points analyzed and the type of sampler used, which affected the uniformity of radial deposition on the filters. It was shown that using a single shot at the center of the filter yielded predictivity adequate for a field method, (93% return, CV approximately 15%) for samples collected with 3-piece cassettes.

Wildfire Smoke

MedlinePlus

... keep the fresh-air intake closed and the filter clean to prevent outdoor smoke from getting inside. ... inside with the windows closed. Use an air filter . Use a freestanding indoor air filter with particle ...

Filtered cathodic arc source

DOEpatents

Falabella, S.; Sanders, D.M.

1994-01-18

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.

Filtered cathodic arc source

DOEpatents

Falabella, Steven; Sanders, David 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. 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.

Morphological classification of bioaerosols from composting using scanning electron microscopy

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

Tamer Vestlund, A.; FIRA International Ltd., Maxwell Road, Stevenage, Herts SG1 2EW; Al-Ashaab, R.

2014-07-15

Highlights: • Bioaerosols were captured using the filter method. • Bioaerosols were analysed using scanning electron microscope. • Bioaerosols were classified on the basis of morphology. • Single small cells were found more frequently than aggregates and larger cells. • Smaller cells may disperse further than heavier aggregate structures. - Abstract: This research classifies the physical morphology (form and structure) of bioaerosols emitted from open windrow composting. Aggregation state, shape and size of the particles captured are reported alongside the implications for bioaerosol dispersal after release. Bioaerosol sampling took place at a composting facility using personal air filter samplers. Samplesmore » were analysed using scanning electron microscopy. Particles were released mainly as small (<1 μm) single, spherical cells, followed by larger (>1 μm) single cells, with aggregates occurring in smaller proportions. Most aggregates consisted of clusters of 2–3 particles as opposed to chains, and were <10 μm in size. No cells were attached to soil debris or wood particles. These small single cells or small aggregates are more likely to disperse further downwind from source, and cell viability may be reduced due to increased exposure to environmental factors.« less

Concurrent measurements of size-segregated particulate sulfate, nitrate and ammonium using quartz fiber filters, glass fiber filters and cellulose membranes

NASA Astrophysics Data System (ADS)

Tian, Shili; Pan, Yuepeng; Wang, Jian; Wang, Yuesi

2016-11-01

Current science and policy requirements have focused attention on the need to expand and improve particulate matter (PM) sampling methods. To explore how sampling filter type affects artifacts in PM composition measurements, size-resolved particulate SO42-, NO3- and NH4+ (SNA) were measured on quartz fiber filters (QFF), glass fiber filters (GFF) and cellulose membranes (CM) concurrently in an urban area of Beijing on both clean and hazy days. The results showed that SNA concentrations in most of the size fractions exhibited the following patterns on different filters: CM > QFF > GFF for NH4+; GFF > QFF > CM for SO42-; and GFF > CM > QFF for NO3-. The different patterns in coarse particles were mainly affected by filter acidity, and that in fine particles were mainly affected by hygroscopicity of the filters (especially in size fraction of 0.65-2.1 μm). Filter acidity and hygroscopicity also shifted the peaks of the annual mean size distributions of SNA on QFF from 0.43-0.65 μm on clean days to 0.65-1.1 μm on hazy days. However, this size shift was not as distinct for samples measured with CM and GFF. In addition, relative humidity (RH) and pollution levels are important factors that can enhance particulate size mode shifts of SNA on clean and hazy days. Consequently, the annual mean size distributions of SNA had maxima at 0.65-1.1 μm for QFF samples and 0.43-0.65 μm for GFF and CM samples. Compared with NH4+ and SO42-, NO3- is more sensitive to RH and pollution levels, accordingly, the annual mean size distribution of NO3- exhibited peak at 0.65-1.1 μm for CM samples instead of 0.43-0.65 μm. These methodological uncertainties should be considered when quantifying the concentrations and size distributions of SNA under different RH and haze conditions.

Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach.

PubMed

Liu, Mengyun; Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng; Pan, Yuanjin

2017-12-08

After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to "see" which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas.

Scene Recognition for Indoor Localization Using a Multi-Sensor Fusion Approach

PubMed Central

Chen, Ruizhi; Li, Deren; Chen, Yujin; Guo, Guangyi; Cao, Zhipeng

2017-01-01

After decades of research, there is still no solution for indoor localization like the GNSS (Global Navigation Satellite System) solution for outdoor environments. The major reasons for this phenomenon are the complex spatial topology and RF transmission environment. To deal with these problems, an indoor scene constrained method for localization is proposed in this paper, which is inspired by the visual cognition ability of the human brain and the progress in the computer vision field regarding high-level image understanding. Furthermore, a multi-sensor fusion method is implemented on a commercial smartphone including cameras, WiFi and inertial sensors. Compared to former research, the camera on a smartphone is used to “see” which scene the user is in. With this information, a particle filter algorithm constrained by scene information is adopted to determine the final location. For indoor scene recognition, we take advantage of deep learning that has been proven to be highly effective in the computer vision community. For particle filter, both WiFi and magnetic field signals are used to update the weights of particles. Similar to other fingerprinting localization methods, there are two stages in the proposed system, offline training and online localization. In the offline stage, an indoor scene model is trained by Caffe (one of the most popular open source frameworks for deep learning) and a fingerprint database is constructed by user trajectories in different scenes. To reduce the volume requirement of training data for deep learning, a fine-tuned method is adopted for model training. In the online stage, a camera in a smartphone is used to recognize the initial scene. Then a particle filter algorithm is used to fuse the sensor data and determine the final location. To prove the effectiveness of the proposed method, an Android client and a web server are implemented. The Android client is used to collect data and locate a user. The web server is developed for indoor scene model training and communication with an Android client. To evaluate the performance, comparison experiments are conducted and the results demonstrate that a positioning accuracy of 1.32 m at 95% is achievable with the proposed solution. Both positioning accuracy and robustness are enhanced compared to approaches without scene constraint including commercial products such as IndoorAtlas. PMID:29292761

Low-dislocation-density epitatial layers grown by defect filtering by self-assembled layers of spheres

DOEpatents

Wang, George T.; Li, Qiming

2013-04-23

A method for growing low-dislocation-density material atop a layer of the material with an initially higher dislocation density using a monolayer of spheroidal particles to bend and redirect or directly block vertically propagating threading dislocations, thereby enabling growth and coalescence to form a very-low-dislocation-density surface of the material, and the structures made by this method.

Magnetic evaluation of TSP-filters for air quality monitoring

NASA Astrophysics Data System (ADS)

Castañeda-Miranda, Ana Gabriela; Böhnel, Harald N.; Molina-Garza, Roberto S.; Chaparro, Marcos A. E.

2014-10-01

We present the magnetic properties of the powders collected by high volume total suspended particle air samplers used to monitor atmospheric pollution in Santiago de Querétaro, a city of one million people in central Mexico. The magnetic measurements have been combined with scanning electron microscopy observations and analysis, in order to characterize the particles captured in the filters as natural and anthropogenic. The main goal of the study is to test if magnetic measurements on the sampled atmospheric dust can be effective, low-cost, proxy to qualitatively estimate the air quality, complementing the traditional analytical methods. The magnetic properties of the powder collected in the filters have been investigated measuring the low field magnetic susceptibility, hysteresis loops, thermomagnetic curves, and isothermal remanent magnetization. The rock magnetism data have been supplemented by energy-dispersive X-ray spectroscopy analysis and Raman spectroscopy. It was found that the main magnetic carrier is low-Ti magnetite in the PSD range with a contribution from SP particles, and small but significant contributions from hematite, maghemite and goethite particles. Total suspended particles in the atmosphere during the monitored days ranged between about 30 and 280 μg/m3. Magnetic susceptibility values are well correlated with the independently determined total suspended particles concentration (R = 0.93), but particle concentration does not correlate as well with IRM1T. This may be attributed to contributions from SP and paramagnetic particles to the susceptibility signal, but not to the remanence. The effects of climate in particle size, composition and concentration were considered in terms of precipitation and wind intensity, but they are actually minor. The main effect of climate appears to be the removal of SP particles during rainy days. There is a contribution to air pollution from natural mineral sources, which we attribute to low vegetation cover in the region's arid climate. The concentration of the magnetic particles and their grain-size vary according to the location of the monitoring station, with higher contributions to anthropogenic Fe-rich particles from vehicle emissions in the city center and other metals in the industrial parks. Metals of interest, usually diagnostic of atmospheric pollution (Fe, As, Sb, Cr, Mo, V, Zn, Ba, Pb, and Cu) were identified by means of electron microscopy.

Track-before-detect labeled multi-bernoulli particle filter with label switching

NASA Astrophysics Data System (ADS)

Garcia-Fernandez, Angel F.

2016-10-01

This paper presents a multitarget tracking particle filter (PF) for general track-before-detect measurement models. The PF is presented in the random finite set framework and uses a labelled multi-Bernoulli approximation. We also present a label switching improvement algorithm based on Markov chain Monte Carlo that is expected to increase filter performance if targets get in close proximity for a sufficiently long time. The PF is tested in two challenging numerical examples.

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size

PubMed Central

Richman, Julie D.; Livi, Kenneth J.T.; Geyh, Alison S.

2011-01-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was −0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected. PMID:21625364

A Scanning Transmission Electron Microscopy Method for Determining Manganese Composition in Welding Fume as a Function of Primary Particle Size.

PubMed

Richman, Julie D; Livi, Kenneth J T; Geyh, Alison S

2011-06-01

Increasing evidence suggests that the physicochemical properties of inhaled nanoparticles influence the resulting toxicokinetics and toxicodynamics. This report presents a method using scanning transmission electron microscopy (STEM) to measure the Mn content throughout the primary particle size distribution of welding fume particle samples collected on filters for application in exposure and health research. Dark field images were collected to assess the primary particle size distribution and energy-dispersive X-ray and electron energy loss spectroscopy were performed for measurement of Mn composition as a function of primary particle size. A manual method incorporating imaging software was used to measure the primary particle diameter and to select an integration region for compositional analysis within primary particles throughout the size range. To explore the variation in the developed metric, the method was applied to 10 gas metal arc welding (GMAW) fume particle samples of mild steel that were collected under a variety of conditions. The range of Mn composition by particle size was -0.10 to 0.19 %/nm, where a positive estimate indicates greater relative abundance of Mn increasing with primary particle size and a negative estimate conversely indicates decreasing Mn content with size. However, the estimate was only statistically significant (p<0.05) in half of the samples (n=5), which all had a positive estimate. In the remaining samples, no significant trend was measured. Our findings indicate that the method is reproducible and that differences in the abundance of Mn by primary particle size among welding fume samples can be detected.

Bottles as models: predicting the effects of varying swimming speed and morphology on size selectivity and filtering efficiency in fishes.

PubMed

Paig-Tran, E W Misty; Bizzarro, Joseph J; Strother, James A; Summers, Adam P

2011-05-15

We created physical models based on the morphology of ram suspension-feeding fishes to better understand the roles morphology and swimming speed play in particle retention, size selectivity and filtration efficiency during feeding events. We varied the buccal length, flow speed and architecture of the gills slits, including the number, size, orientation and pore size/permeability, in our models. Models were placed in a recirculating flow tank with slightly negatively buoyant plankton-like particles (~20-2000 μm) collected at the simulated esophagus and gill rakers to locate the highest density of particle accumulation. Particles were captured through sieve filtration, direct interception and inertial impaction. Changing the number of gill slits resulted in a change in the filtration mechanism of particles from a bimodal filter, with very small (≤ 50 μm) and very large (>1000 μm) particles collected, to a filter that captured medium-sized particles (101-1000 μm). The number of particles collected on the gill rakers increased with flow speed and skewed the size distribution towards smaller particles (51-500 μm). Small pore sizes (105 and 200 μm mesh size) had the highest filtration efficiencies, presumably because sieve filtration played a significant role. We used our model to make predictions about the filtering capacity and efficiency of neonatal whale sharks. These results suggest that the filtration mechanics of suspension feeding are closely linked to an animal's swimming speed and the structural design of the buccal cavity and gill slits.

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

NASA Astrophysics Data System (ADS)

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.

Demonstration Bulletin. Membrane Microfiltration. E. I. DuPont de Nemours and Company, Inc. Oberlin Filter Company

EPA Science Inventory

The DuPont/Oberlin microfiltration technology is a physical separation process that removes solid particles from liquid wastes. The process can filter particles that are submicron or larger in diameter. Pretreatment, such as chemical additions, will be required if dissolved con...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, BAGHOUSE FILTRATION PRODUCTS, BHA GROUP, INC., QP131 FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size of those particles equal to and smalle...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, BAGHOUSE FILTRATION PRODUCTS, W.L. GORE & ASSOCIATES, INC., L4427 FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size of those particles equal to and smalle...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, BAGHOUSE FILTRATION PRODUCTS, POLYMER GROUP, INC., DURAPEX PET FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size of those particles equal to and smalle...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT: BAGHOUSE FILTRATION PRODUCTS, W.L. GORE & ASSOCIATES, INC. LYSB3 FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size for particles equal to or smaller than...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, BAGHOUSE FILTRATION PRODUCTS, TETRATEC PTFE PRODUCTS, TETRATEX 6212 FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size of those particles equal to and smalle...

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT: BAGHOUSE FILTRATION PRODUCTS, BWF AMERICA, INC. GRADE 700 MPS POLYESTER FELT FILTER SAMPLE

EPA Science Inventory

Baghouse filtration products (BFPs) were evaluated by the Air Pollution Control Technology (APCT) Verification Center. The performance factor verified was the mean outlet particle concentration for the filter fabric as a function of the size for particles equal to or smaller than...

40 CFR 53.62 - Test procedure: Full wind tunnel test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... distributions to provide six estimates of measured mass concentration. Critical parameters for these idealized... (expressed as a percentage) of the mass concentration of particles of a specific size reaching the sampler filter or filters to the mass concentration of particles of the same size approaching the sampler. (c...

Motion-Blurred Particle Image Restoration for On-Line Wear Monitoring

PubMed Central

Peng, Yeping; Wu, Tonghai; Wang, Shuo; Kwok, Ngaiming; Peng, Zhongxiao

2015-01-01

On-line images of wear debris contain important information for real-time condition monitoring, and a dynamic imaging technique can eliminate particle overlaps commonly found in static images, for instance, acquired using ferrography. However, dynamic wear debris images captured in a running machine are unavoidably blurred because the particles in lubricant are in motion. Hence, it is difficult to acquire reliable images of wear debris with an adequate resolution for particle feature extraction. In order to obtain sharp wear particle images, an image processing approach is proposed. Blurred particles were firstly separated from the static background by utilizing a background subtraction method. Second, the point spread function was estimated using power cepstrum to determine the blur direction and length. Then, the Wiener filter algorithm was adopted to perform image restoration to improve the image quality. Finally, experiments were conducted with a large number of dynamic particle images to validate the effectiveness of the proposed method and the performance of the approach was also evaluated. This study provides a new practical approach to acquire clear images for on-line wear monitoring. PMID:25856328

Submicron and Nanoparticulate Matter Removal by HEPA-Rated Media Filters and Packed Beds of Granular Materials

NASA Technical Reports Server (NTRS)

Perry, J. L.; Agui, J. H.; Vijayakimar, R

2016-01-01

Contaminants generated aboard crewed spacecraft by diverse sources consist of both gaseous chemical contaminants and particulate matter. Both HEPA media filters and packed beds of granular material, such as activated carbon, which are both commonly employed for cabin atmosphere purification purposes have efficacy for removing nanoparticulate contaminants from the cabin atmosphere. The phenomena associated with particulate matter removal by HEPA media filters and packed beds of granular material are reviewed relative to their efficacy for removing fine (less than 2.5 micrometers) and ultrafine (less than 0.01 micrometers) sized particulate matter. Considerations are discussed for using these methods in an appropriate configuration to provide the most effective performance for a broad range of particle sizes including nanoparticulates.

An evaluation of noise reduction algorithms for particle-based fluid simulations in multi-scale applications

NASA Astrophysics Data System (ADS)

Zimoń, M. J.; Prosser, R.; Emerson, D. R.; Borg, M. K.; Bray, D. J.; Grinberg, L.; Reese, J. M.

2016-11-01

Filtering of particle-based simulation data can lead to reduced computational costs and enable more efficient information transfer in multi-scale modelling. This paper compares the effectiveness of various signal processing methods to reduce numerical noise and capture the structures of nano-flow systems. In addition, a novel combination of these algorithms is introduced, showing the potential of hybrid strategies to improve further the de-noising performance for time-dependent measurements. The methods were tested on velocity and density fields, obtained from simulations performed with molecular dynamics and dissipative particle dynamics. Comparisons between the algorithms are given in terms of performance, quality of the results and sensitivity to the choice of input parameters. The results provide useful insights on strategies for the analysis of particle-based data and the reduction of computational costs in obtaining ensemble solutions.

Method and system for detecting polygon boundaries of structures in images as particle tracks through fields of corners and pixel gradients

DOEpatents

Paglieroni, David W [Pleasanton, CA; Manay, Siddharth [Livermore, CA

2011-12-20

A stochastic method and system for detecting polygon structures in images, by detecting a set of best matching corners of predetermined acuteness .alpha. of a polygon model from a set of similarity scores based on GDM features of corners, and tracking polygon boundaries as particle tracks using a sequential Monte Carlo approach. The tracking involves initializing polygon boundary tracking by selecting pairs of corners from the set of best matching corners to define a first side of a corresponding polygon boundary; tracking all intermediate sides of the polygon boundaries using a particle filter, and terminating polygon boundary tracking by determining the last side of the tracked polygon boundaries to close the polygon boundaries. The particle tracks are then blended to determine polygon matches, which may be made available, such as to a user, for ranking and inspection.

14 CFR 23.1107 - Induction system filters.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Induction system filters. 23.1107 Section... § 23.1107 Induction system filters. If an air filter is used to protect the engine against foreign material particles in the induction air supply— (a) Each air filter must be capable of withstanding the...

14 CFR 23.1107 - Induction system filters.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Induction system filters. 23.1107 Section... § 23.1107 Induction system filters. If an air filter is used to protect the engine against foreign material particles in the induction air supply— (a) Each air filter must be capable of withstanding the...

14 CFR 23.1107 - Induction system filters.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Induction system filters. 23.1107 Section... § 23.1107 Induction system filters. If an air filter is used to protect the engine against foreign material particles in the induction air supply— (a) Each air filter must be capable of withstanding the...

14 CFR 23.1107 - Induction system filters.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Induction system filters. 23.1107 Section... § 23.1107 Induction system filters. If an air filter is used to protect the engine against foreign material particles in the induction air supply— (a) Each air filter must be capable of withstanding the...

14 CFR 23.1107 - Induction system filters.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Induction system filters. 23.1107 Section... § 23.1107 Induction system filters. If an air filter is used to protect the engine against foreign material particles in the induction air supply— (a) Each air filter must be capable of withstanding the...

A simple new filter for nonlinear high-dimensional data assimilation

NASA Astrophysics Data System (ADS)

Tödter, Julian; Kirchgessner, Paul; Ahrens, Bodo

2015-04-01

The ensemble Kalman filter (EnKF) and its deterministic variants, mostly square root filters such as the ensemble transform Kalman filter (ETKF), represent a popular alternative to variational data assimilation schemes and are applied in a wide range of operational and research activities. Their forecast step employs an ensemble integration that fully respects the nonlinear nature of the analyzed system. In the analysis step, they implicitly assume the prior state and observation errors to be Gaussian. Consequently, in nonlinear systems, the analysis mean and covariance are biased, and these filters remain suboptimal. In contrast, the fully nonlinear, non-Gaussian particle filter (PF) only relies on Bayes' theorem, which guarantees an exact asymptotic behavior, but because of the so-called curse of dimensionality it is exposed to weight collapse. This work shows how to obtain a new analysis ensemble whose mean and covariance exactly match the Bayesian estimates. This is achieved by a deterministic matrix square root transformation of the forecast ensemble, and subsequently a suitable random rotation that significantly contributes to filter stability while preserving the required second-order statistics. The forecast step remains as in the ETKF. The proposed algorithm, which is fairly easy to implement and computationally efficient, is referred to as the nonlinear ensemble transform filter (NETF). The properties and performance of the proposed algorithm are investigated via a set of Lorenz experiments. They indicate that such a filter formulation can increase the analysis quality, even for relatively small ensemble sizes, compared to other ensemble filters in nonlinear, non-Gaussian scenarios. Furthermore, localization enhances the potential applicability of this PF-inspired scheme in larger-dimensional systems. Finally, the novel algorithm is coupled to a large-scale ocean general circulation model. The NETF is stable, behaves reasonably and shows a good performance with a realistic ensemble size. The results confirm that, in principle, it can be applied successfully and as simple as the ETKF in high-dimensional problems without further modifications of the algorithm, even though it is only based on the particle weights. This proves that the suggested method constitutes a useful filter for nonlinear, high-dimensional data assimilation, and is able to overcome the curse of dimensionality even in deterministic systems.

Bayesian model averaging using particle filtering and Gaussian mixture modeling: Theory, concepts, and simulation experiments

NASA Astrophysics Data System (ADS)

Rings, Joerg; Vrugt, Jasper A.; Schoups, Gerrit; Huisman, Johan A.; Vereecken, Harry

2012-05-01

Bayesian model averaging (BMA) is a standard method for combining predictive distributions from different models. In recent years, this method has enjoyed widespread application and use in many fields of study to improve the spread-skill relationship of forecast ensembles. The BMA predictive probability density function (pdf) of any quantity of interest is a weighted average of pdfs centered around the individual (possibly bias-corrected) forecasts, where the weights are equal to posterior probabilities of the models generating the forecasts, and reflect the individual models skill over a training (calibration) period. The original BMA approach presented by Raftery et al. (2005) assumes that the conditional pdf of each individual model is adequately described with a rather standard Gaussian or Gamma statistical distribution, possibly with a heteroscedastic variance. Here we analyze the advantages of using BMA with a flexible representation of the conditional pdf. A joint particle filtering and Gaussian mixture modeling framework is presented to derive analytically, as closely and consistently as possible, the evolving forecast density (conditional pdf) of each constituent ensemble member. The median forecasts and evolving conditional pdfs of the constituent models are subsequently combined using BMA to derive one overall predictive distribution. This paper introduces the theory and concepts of this new ensemble postprocessing method, and demonstrates its usefulness and applicability by numerical simulation of the rainfall-runoff transformation using discharge data from three different catchments in the contiguous United States. The revised BMA method receives significantly lower-prediction errors than the original default BMA method (due to filtering) with predictive uncertainty intervals that are substantially smaller but still statistically coherent (due to the use of a time-variant conditional pdf).

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

Converting environmental wastes into valuable resources

NASA Technical Reports Server (NTRS)

Duval, Leonard A.

1993-01-01

This concept employs a viable energy saving method that uses a solvent to separate oil from particle matter; it can be used in metal forming industries to deoil sludges, oxides, and particle matter that is presently committed to landfill. If oily particles are used in their oily state, severe consequences to environmental control systems such as explosions or filter blinding, occur in the air handling equipment. This is due to the presence of hydrocarbons in the stack gasses resulting from the oily particles. After deoiling, the particles can be recycled and the separated oil can be used as a fuel. The process does not produce a waste of it's own and does not harm air or water. It demonstrates the dual benefits of it being commercially viable and in the national interest of conserving resources.

Converting environmental wastes into valuable resources

NASA Astrophysics Data System (ADS)

Duval, Leonard A.

1993-02-01

This concept employs a viable energy saving method that uses a solvent to separate oil from particle matter; it can be used in metal forming industries to deoil sludges, oxides, and particle matter that is presently committed to landfill. If oily particles are used in their oily state, severe consequences to environmental control systems such as explosions or filter blinding, occur in the air handling equipment. This is due to the presence of hydrocarbons in the stack gasses resulting from the oily particles. After deoiling, the particles can be recycled and the separated oil can be used as a fuel. The process does not produce a waste of it's own and does not harm air or water. It demonstrates the dual benefits of it being commercially viable and in the national interest of conserving resources.

Apparatus and method for concentrating and filtering particles suspended in a fluid

DOEpatents

Fiechtner, Gregory J [Bethesda, MD; Cummings, Eric B [Livermore, CA; Singh, Anup K [Danville, CA

2009-05-19

Disclosed is a device for separating and concentrating particles suspended in a fluid stream by using dielectrophoresis (DEP) to trap and/or deflect those particles as they migrate through a fluid channel. The method uses fluid channels designed to constrain a liquid flowing through it to uniform electrokinetic flow velocities. This behavior is achieved by connecting deep and shallow sections of channels, with the channel depth varying abruptly along an interface. By careful design of abrupt changes in specific permeability at the interface, an abrupt and spatially uniform change in electrokinetic force can be selected. Because these abrupt interfaces also cause a sharp gradient in applied electric fields, a DEP force also can be established along the interface. Depending on the complex conductivity of the suspended particles and the immersion liquid, the DEP force can controllably complement or oppose the local electrokinetic force transporting the fluid through the channel allowing for manipulation of particles suspended in the transporting liquid.

Effectiveness of in-room air filtration and dilution ventilation for tuberculosis infection control.

PubMed

Miller-Leiden, S; Lobascio, C; Nazaroff, W W; Macher, J M

1996-09-01

Tuberculosis (TB) is a public health problem that may pose substantial risks to health care workers and others. TB infection occurs by inhalation of airborne bacteria emitted by persons with active disease. We experimentally evaluated the effectiveness of in-room air filtration systems, specifically portable air filters (PAFs) and ceiling-mounted air filters (CMAFs), in conjunction with dilution ventilation, for controlling TB exposure in high-risk settings. For each experiment, a test aerosol was continuously generated and released into a full-sized room. With the in-room air filter and room ventilation system operating, time-averaged airborne particle concentrations were measured at several points. The effectiveness of in-room air filtration plus ventilation was determined by comparing particle concentrations with and without device operation. The four PAFs and three CMAFs we evaluated reduced room-average particle concentrations, typically by 30% to 90%, relative to a baseline scenario with two air-changes per hour of ventilation (outside air) only. Increasing the rate of air flow recirculating through the filter and/or air flow from the ventilation did not always increase effectiveness. Concentrations were generally higher near the emission source than elsewhere in the room. Both the air flow configuration of the filter and its placement within the room were important, influencing room air flow patterns and the spatial distribution of concentrations. Air filters containing efficient, but non-high efficiency particulate air (HEPA) filter media were as effective as air filters containing HEPA filter media.

Effectiveness of In-Room Air Filtration and Dilution Ventilation for Tuberculosis Infection Control.

PubMed

Miller-Leiden, S; Lohascio, C; Nazaroff, W W; Macher, J M

1996-09-01

Tuberculosis (TB) is a public health problem that may pose substantial risks to health care workers and others. TB infection occurs by inhalation of airborne bacteria emitted by persons with active disease. We experimentally evaluated the effectiveness of in-room air filtration systems, specifically portable air filters (PAFs) and ceiling-mounted air filters (CMAFs), in conjunction with dilution ventilation, for controlling TB exposure in high-risk settings. For each experiment, a test aerosol was continuously generated and released into a full-sized room. With the in-room air filter and room ventilation system operating, time-averaged airborne particle concentrations were measured at several points. The effectiveness of in-room air filtration plus ventilation was determined by comparing particle concentrations with and without device operation. The four PAFs and three CMAFs we evaluated reduced room-average particle concentrations, typically by 30% to 90%, relative to a baseline scenario with two air-changes per hour of ventilation (outside air) only. Increasing the rate of air flow recirculating through the filter and/or air flow from the ventilation did not always increase effectiveness. Concentrations were generally higher near the emission source than elsewhere in the room. Both the air flow configuration of the filter and its placement within the room were important, influencing room air flow patterns and the spatial distribution of concentrations. Air filters containing efficient, but non-high efficiency particulate air (HEPA) filter media were as effective as air filters containing HEPA filter media.

Particle Filters for Real-Time Fault Detection in Planetary Rovers

NASA Technical Reports Server (NTRS)

Dearden, Richard; Clancy, Dan; Koga, Dennis (Technical Monitor)

2001-01-01

Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not suitable for rovers due to the tight coupling between the vehicle's performance and its environment. Hybrid diagnosis using particle filters is presented as an alternative, and its strengths and weakeners are examined. We also present some extensions to particle filters that are designed to make them more suitable for use in diagnosis problems.

Room air monitor for radioactive aerosols

DOEpatents

Balmer, D.K.; Tyree, W.H.

1987-03-23

A housing assembly for use with a room air monitor for simultaneous collection and counting of suspended particles includes a casing containing a combination detector-preamplifier system at one end, a filter system at the other end, and an air flow system consisting of an air inlet formed in the casing between the detector-preamplifier system and the filter system and an air passageway extending from the air inlet through the casing and out the end opposite the detector-preamplifier combination. The filter system collects suspended particles transported directly through the housing by means of the air flow system, and these particles are detected and examined for radioactivity by the detector-preamplifier combination. 2 figs.

Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters

NASA Astrophysics Data System (ADS)

Lee, Da Young; Lee, Gi Wook; Yoon, Kyu; Chun, Byoungjin; Jung, Hyun Wook

2018-01-01

Flows through porous filter walls of wall-flow diesel particulate filter are investigated using the lattice Boltzmann method (LBM). The microscopic model of the realistic filter wall is represented by randomly overlapped arrays of solid spheres. The LB simulation results are first validated by comparison to those from previous hydrodynamic theories and constitutive models for flows in porous media with simple regular and random solid-wall configurations. We demonstrate that the newly designed randomly overlapped array structures of porous walls allow reliable and accurate simulations for the porous wall-flow dynamics in a wide range of solid volume fractions from 0.01 to about 0.8, which is beyond the maximum random packing limit of 0.625. The permeable performance of porous media is scrutinized by changing the solid volume fraction and particle Reynolds number using Darcy's law and Forchheimer's extension in the laminar flow region.

A multi-time-step noise reduction method for measuring velocity statistics from particle tracking velocimetry

NASA Astrophysics Data System (ADS)

Machicoane, Nathanaël; López-Caballero, Miguel; Bourgoin, Mickael; Aliseda, Alberto; Volk, Romain

2017-10-01

We present a method to improve the accuracy of velocity measurements for fluid flow or particles immersed in it, based on a multi-time-step approach that allows for cancellation of noise in the velocity measurements. Improved velocity statistics, a critical element in turbulent flow measurements, can be computed from the combination of the velocity moments computed using standard particle tracking velocimetry (PTV) or particle image velocimetry (PIV) techniques for data sets that have been collected over different values of time intervals between images. This method produces Eulerian velocity fields and Lagrangian velocity statistics with much lower noise levels compared to standard PIV or PTV measurements, without the need of filtering and/or windowing. Particle displacement between two frames is computed for multiple different time-step values between frames in a canonical experiment of homogeneous isotropic turbulence. The second order velocity structure function of the flow is computed with the new method and compared to results from traditional measurement techniques in the literature. Increased accuracy is also demonstrated by comparing the dissipation rate of turbulent kinetic energy measured from this function against previously validated measurements.