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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

System reliability analysis of granular filter for protection against piping in dams

NASA Astrophysics Data System (ADS)

Srivastava, A.; Sivakumar Babu, G. L.

2015-09-01

Granular filters are provided for the safety of water retaining structure for protection against piping failure. The phenomenon of piping triggers when the base soil to be protected starts migrating in the direction of seepage flow under the influence of seepage force. To protect base soil from migration, the voids in the filter media should be small enough but it should not also be too small to block smooth passage of seeping water. Fulfilling these two contradictory design requirements at the same time is a major concern for the successful performance of granular filter media. Since Terzaghi era, conventionally, particle size distribution (PSD) of granular filters is designed based on particle size distribution characteristics of the base soil to be protected. The design approach provides a range of D15f value in which the PSD of granular filter media should fall and there exist infinite possibilities. Further, safety against the two critical design requirements cannot be ensured. Although used successfully for many decades, the existing filter design guidelines are purely empirical in nature accompanied with experience and good engineering judgment. In the present study, analytical solutions for obtaining the factor of safety with respect to base soil particle migration and soil permeability consideration as proposed by the authors are first discussed. The solution takes into consideration the basic geotechnical properties of base soil and filter media as well as existing hydraulic conditions and provides a comprehensive solution to the granular filter design with ability to assess the stability in terms of factor of safety. Considering the fact that geotechnical properties are variable in nature, probabilistic analysis is further suggested to evaluate the system reliability of the filter media that may help in risk assessment and risk management for decision making.

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.

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

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.

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.

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.

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.

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.

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

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.

Collaborative emitter tracking using Rao-Blackwellized random exchange diffusion particle filtering

NASA Astrophysics Data System (ADS)

Bruno, Marcelo G. S.; Dias, Stiven S.

2014-12-01

We introduce in this paper the fully distributed, random exchange diffusion particle filter (ReDif-PF) to track a moving emitter using multiple received signal strength (RSS) sensors. We consider scenarios with both known and unknown sensor model parameters. In the unknown parameter case, a Rao-Blackwellized (RB) version of the random exchange diffusion particle filter, referred to as the RB ReDif-PF, is introduced. In a simulated scenario with a partially connected network, the proposed ReDif-PF outperformed a PF tracker that assimilates local neighboring measurements only and also outperformed a linearized random exchange distributed extended Kalman filter (ReDif-EKF). Furthermore, the novel ReDif-PF matched the tracking error performance of alternative suboptimal distributed PFs based respectively on iterative Markov chain move steps and selective average gossiping with an inter-node communication cost that is roughly two orders of magnitude lower than the corresponding cost for the Markov chain and selective gossip filters. Compared to a broadcast-based filter which exactly mimics the optimal centralized tracker or its equivalent (exact) consensus-based implementations, ReDif-PF showed a degradation in steady-state error performance. However, compared to the optimal consensus-based trackers, ReDif-PF is better suited for real-time applications since it does not require iterative inter-node communication between measurement arrivals.

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

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The new approach for infrared target tracking based on the particle filter algorithm

NASA Astrophysics Data System (ADS)

Sun, Hang; Han, Hong-xia

2011-08-01

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring, precision, and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection, the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure, but in order to capture the change of the state space, it need a certain amount of particles to ensure samples is enough, and this number will increase in accompany with dimension and increase exponentially, this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining", we expand the classic Mean Shift tracking framework .Based on the previous perspective, we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis, Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism, used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation, and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value .Last because of the gray and fusion target motion information, this approach also inhibit interference from the background, ultimately improve the stability and the real-time of the target track.

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

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.

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.

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.

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

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.

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

James K. Neathery; Gary Jacobs; Burtron H. Davis

In this reporting period, a fundamental filtration study was started to investigate the separation of Fischer-Tropsch Synthesis (FTS) liquids from iron-based catalyst particles. Slurry-phase FTS in slurry bubble column reactor systems is the preferred mode of production since the reaction is highly exothermic. Consequently, heavy wax products must be separated from catalyst particles before being removed from the reactor system. Achieving an efficient wax product separation from iron-based catalysts is one of the most challenging technical problems associated with slurry-phase FTS. The separation problem is further compounded by catalyst particle attrition and the formation of ultra-fine iron carbide and/or carbonmore » particles. Existing pilot-scale equipment was modified to include a filtration test apparatus. After undergoing an extensive plant shakedown period, filtration tests with cross-flow filter modules using simulant FTS wax slurry were conducted. The focus of these early tests was to find adequate mixtures of polyethylene wax to simulate FTS wax. Catalyst particle size analysis techniques were also developed. Initial analyses of the slurry and filter permeate particles will be used by the research team to design improved filter media and cleaning strategies.« less

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.

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

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

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

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.

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.

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.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

Particle rejuvenation of Rao-Blackwellized sequential Monte Carlo smoothers for conditionally linear and Gaussian models

NASA Astrophysics Data System (ADS)

Nguyen, Ngoc Minh; Corff, Sylvain Le; Moulines, Éric

2017-12-01

This paper focuses on sequential Monte Carlo approximations of smoothing distributions in conditionally linear and Gaussian state spaces. To reduce Monte Carlo variance of smoothers, it is typical in these models to use Rao-Blackwellization: particle approximation is used to sample sequences of hidden regimes while the Gaussian states are explicitly integrated conditional on the sequence of regimes and observations, using variants of the Kalman filter/smoother. The first successful attempt to use Rao-Blackwellization for smoothing extends the Bryson-Frazier smoother for Gaussian linear state space models using the generalized two-filter formula together with Kalman filters/smoothers. More recently, a forward-backward decomposition of smoothing distributions mimicking the Rauch-Tung-Striebel smoother for the regimes combined with backward Kalman updates has been introduced. This paper investigates the benefit of introducing additional rejuvenation steps in all these algorithms to sample at each time instant new regimes conditional on the forward and backward particles. This defines particle-based approximations of the smoothing distributions whose support is not restricted to the set of particles sampled in the forward or backward filter. These procedures are applied to commodity markets which are described using a two-factor model based on the spot price and a convenience yield for crude oil data.

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.

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.

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.

Derivation and use of simple relationships between aerodynamic and optical particle measurements

USDA-ARS?s Scientific Manuscript database

A simple relationship, referred to as a mass conversion factor (MCF), is presented to convert optically based particle measurements to mass concentration. It is calculated from filter-based samples and optical particle counter (OPC) data on a daily or sample period basis. The MCF allows for greater ...

The Improved Locating Algorithm of Particle Filter Based on ROS Robot

NASA Astrophysics Data System (ADS)

Fang, Xun; Fu, Xiaoyang; Sun, Ming

2018-03-01

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

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.

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.

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.

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.

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.

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.

Microscopy with spatial filtering for sorting particles and monitoring subcellular morphology

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

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.

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.

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.

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.

Gravimetric Measurements of Filtering Facepiece Respirators Challenged With Diesel Exhaust.

PubMed

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

2017-07-01

Elevated concentrations of diesel exhaust have been linked to adverse health effects. Filtering facepiece respirators (FFRs) are widely used as a form of respiratory protection against diesel particulate matter (DPM) in occupational settings. Previous results (Penconek A, Drążyk P, Moskal A. (2013) Penetration of diesel exhaust particles through commercially available dust half masks. Ann Occup Hyg; 57: 360-73.) have suggested that common FFRs are less efficient than would be expected for this purpose based on their certification approvals. The objective of this study was to measure the penetration of DPM through NIOSH-certified R95 and P95 electret respirators to verify this result. Gravimetric-based penetration measurements conducted using polytetrafluoroethylene (PTFE) and polypropylene (PP) filters were compared with penetration measurements made with a Scanning Mobility Particle Sizer (SMPS, TSI Inc.), which measures the particle size distribution. Gravimetric measurements using PP filters were variable compared to SMPS measurements and biased high due to adsorption of gas phase organic material. Relatively inert PTFE filters adsorbed less gas phase organic material resulting in measurements that were more accurate. To attempt to correct for artifacts associated with adsorption of gas phase organic material, primary and secondary filters were used in series upstream and downstream of the FFR. Correcting for adsorption by subtracting the secondary mass from the primary mass improved the result for both PTFE and PP filters but this correction is subject to 'equilibrium' conditions that depend on sampling time and the concentration of particles and gas phase hydrocarbons. Overall, the results demonstrate that the use of filters to determine filtration efficiency of FFRs challenged with diesel exhaust produces erroneous results due to the presence of gas phase hydrocarbons in diesel exhaust and the tendency of filters to adsorb organic material. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

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.

A survey of implicit particle filters for data assimilation [Implicit particle filters for data assimilation

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

Chorin, Alexandre J.; Morzfeld, Matthias; Tu, Xuemin

Implicit particle filters for data assimilation update the particles by first choosing probabilities and then looking for particle locations that assume them, guiding the particles one by one to the high probability domain. We provide a detailed description of these filters, with illustrative examples, together with new, more general, methods for solving the algebraic equations and with a new algorithm for parameter identification.

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.

Numerical and experimental approaches to study soil transport and clogging in granular filters

NASA Astrophysics Data System (ADS)

Kanarska, Y.; Smith, J. J.; Ezzedine, S. M.; Lomov, I.; Glascoe, L. G.

2012-12-01

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. Numerical modeling has proved to be a cost-effective tool for improving our understanding of physical processes. Traditionally, the consideration of flow and particle transport in porous media has focused on treating the media as continuum. Practical models typically address flow and transport based on the Darcy's law as a function of a pressure gradient and a medium-dependent permeability parameter. Additional macroscopic constitutes describe porosity, and permeability changes during the migration of a suspension through porous media. However, most of them rely on empirical correlations, which often need to be recalibrated for each application. Grain-scale modeling can be used to gain insight into scale dependence of continuum macroscale parameters. 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 in the filter layers of gravity dam. 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. It is believed that the agreement between simulations and experimental data demonstrates the applicability of the proposed approach for prediction of the soil transport and clogging in embankment dams. 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. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The Department of Homeland Security Science and Technology Directorate provided funding for this research.

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.

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.

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.

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.

Assisted Perception, Planning and Control for Remote Mobility and Dexterous Manipulation

DTIC Science & Technology

2017-04-01

on unmanned aerial vehicles (UAVs). The underlying algorithm is based on an Extended Kalman Filter (EKF) that simultaneously estimates robot state...and sensor biases. The filter developed provided a probabilistic fusion of sensor data from many modalities to produce a single consistent position...estimation for a walking humanoid. Given a prior map using a Gaussian particle filter , the LIDAR based system is able to provide a drift-free

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.

Particle Filter Based Tracking in a Detection Sparse Discrete Event Simulation Environment

DTIC Science & Technology

2007-03-01

obtained by disqualifying a large number of particles. 52 (a) (b) ( c ) Figure 31. Particle Disqualification via Sanitization b...1 B. RESEARCH APPROACH..............................................................................5 C . THESIS ORGANIZATION...38 b. Detection Distribution Sampling............................................43 c . Estimated Position Calculation

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).

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.

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

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.

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.

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

PubMed

Besseling, E; Foekema, E M; Van Franeker, J A; Leopold, M F; Kühn, S; Bravo Rebolledo, E L; Heße, E; Mielke, L; IJzer, J; Kamminga, P; Koelmans, A A

2015-06-15

Marine filter feeders are exposed to microplastic because of their selection of small particles as food source. Baleen whales feed by filtering small particles from large water volumes. Macroplastic was found in baleen whales before. This study is the first to show the presence of microplastic in intestines of a baleen whale (Megaptera novaeangliae). Contents of its gastrointestinal tract were sieved, dissolved in 10% potassium hydroxide and washed. From the remaining dried material, potential synthetic polymer particles were selected based on density and appearance, and analysed by Fourier transform infrared (FTIR) spectroscopy. Several polymer types (polyethylene, polypropylene, polyvinylchloride, polyethylene terephthalate, nylon) were found, in varying particle shapes: sheets, fragments and threads with a size of 1mm to 17cm. This diversity in polymer types and particle shapes, can be interpreted as a representation of the varying characteristics of marine plastic and the unselective way of ingestion by M. novaeangliae. Copyright © 2015 Elsevier Ltd. All rights reserved.

Recalibrated Equations for Determining Effect of Oil Filtration on Rolling Bearing Life

NASA Technical Reports Server (NTRS)

Needelman, William M.; Zaretsky, Erwin V.

2014-01-01

In 1991, Needelman and Zaretsky presented a set of empirically derived equations for bearing fatigue life (adjustment) factors (LFs) as a function of oil filter ratings. These equations for life factors were incorporated into the reference book, "STLE Life Factors for Rolling Bearings." These equations were normalized (LF = 1) to a 10-micrometer filter rating at Beta(sub x) = 200 (normal cleanliness) as it was then defined. Over the past 20 years, these life factors based on oil filtration have been used in conjunction with ANSI/ABMA standards and bearing computer codes to predict rolling bearing life. Also, additional experimental studies have been made by other investigators into the relationship between rolling bearing life and the size, number, and type of particle contamination. During this time period filter ratings have also been revised and improved, and they now use particle counting calibrated to a new National Institute of Standards and Technology (NIST) reference material, NIST SRM 2806, 1997. This paper reviews the relevant bearing life studies and describes the new filter ratings. New filter ratings, Beta(sub x(c)) = 200 and Beta(sub x(c)) = 1000, are benchmarked to old filter ratings, Beta(sub x) = 200, and vice versa. Two separate sets of filter LF values were derived based on the new filter ratings for roller bearings and ball bearings, respectively. Filter LFs can be calculated for the new filter ratings.

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...

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

[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

Ensemble Data Assimilation for Streamflow Forecasting: Experiments with Ensemble Kalman Filter and Particle Filter

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Gebremichael, M.; Hopson, T. M.; Wojick, R.

2011-12-01

We present results of data assimilation of ground discharge observation and remotely sensed soil moisture observations into Sacramento Soil Moisture Accounting (SACSMA) model in a small watershed (1593 km2) in Minnesota, the Unites States. Specifically, we perform assimilation experiments with Ensemble Kalman Filter (EnKF) and Particle Filter (PF) in order to improve streamflow forecast accuracy at six hourly time step. The EnKF updates the soil moisture states in the SACSMA from the relative errors of the model and observations, while the PF adjust the weights of the state ensemble members based on the likelihood of the forecast. Results of the improvements of each filter over the reference model (without data assimilation) will be presented. Finally, the EnKF and PF are coupled together to further improve the streamflow forecast accuracy.

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

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.

Al-Coated Conductive Fiber Filters for High-Efficiency Electrostatic Filtration: Effects of Electrical and Fiber Structural Properties.

PubMed

Choi, Dong Yun; An, Eun Jeong; Jung, Soo-Ho; Song, Dong Keun; Oh, Yong Suk; Lee, Hyung Woo; Lee, Hye Moon

2018-04-10

Through the direct decomposition of an Al precursor ink AlH 3 {O(C 4 H 9 ) 2 }, we fabricated an Al-coated conductive fiber filter for the efficient electrostatic removal of airborne particles (>99%) with a low pressure drop (~several Pascals). The effects of the electrical and structural properties of the filters were investigated in terms of collection efficiency, pressure drop, and particle deposition behavior. The collection efficiency did not show a significant correlation with the extent of electrical conductivity, as the filter is electrostatically charged by the metallic Al layers forming electrical networks throughout the fibers. Most of the charged particles were collected via surface filtration by Coulombic interactions; consequently, the filter thickness had little effect on the collection efficiency. Based on simulations of various fiber structures, we found that surface filtration can transition to depth filtration depending on the extent of interfiber distance. Therefore, the effects of structural characteristics on collection efficiency varied depending on the degree of the fiber packing density. This study will offer valuable information pertaining to the development of a conductive metal/polymer composite air filter for an energy-efficient and high-performance electrostatic filtration system.

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.

Method of and apparatus for testing the integrity of filters

DOEpatents

Herman, R.L.

1985-05-07

A method of and apparatus are disclosed for testing the integrity of individual filters or filter stages of a multistage filtering system including a diffuser permanently mounted upstream and/or downstream of the filter stage to be tested for generating pressure differentials to create sufficient turbulence for uniformly dispersing trace agent particles within the airstream upstream and downstream of such filter stage. Samples of the particle concentration are taken upstream and downstream of the filter stage for comparison to determine the extent of particle leakage past the filter stage. 5 figs.

Method of and apparatus for testing the integrity of filters

DOEpatents

Herman, Raymond L [Richland, WA

1985-01-01

A method of and apparatus for testing the integrity of individual filters or filter stages of a multistage filtering system including a diffuser permanently mounted upstream and/or downstream of the filter stage to be tested for generating pressure differentials to create sufficient turbulence for uniformly dispersing trace agent particles within the airstream upstream and downstream of such filter stage. Samples of the particle concentration are taken upstream and downstream of the filter stage for comparison to determine the extent of particle leakage past the filter stage.

Performance study for a set of BLUE based Filters applied to amplitude estimation using as a reference the single photoelectron signal of the ν-Angra Experiment

NASA Astrophysics Data System (ADS)

Souza, D. M.; Costa, I. A.; Nóbrega, R. A.

2017-10-01

This document presents a detailed study of the performance of a set of digital filters whose implementations are based on the best linear unbiased estimator theory interpreted as a constrained optimization problem that could be relaxed depending on the input signal characteristics. This approach has been employed by a number of recent particle physics experiments for measuring the energy of particle events interacting with their detectors. The considered filters have been designed to measure the peak amplitude of signals produced by their detectors based on the digitized version of such signals. This study provides a clear understanding of the characteristics of those filters in the context of particle physics and, additionally, it proposes a phase related constraint based on the second derivative of the Taylor expansion in order to make the estimator less sensitive to phase variation (phase between the analog signal shaping and its sampled version), which is stronger in asynchronous experiments. The asynchronous detector developed by the ν-Angra Collaboration is used as the basis for this work. Nevertheless, the proposed analysis goes beyond, considering a wide range of conditions related to signal parameters such as pedestal, phase, sampling rate, amplitude resolution, noise and pile-up; therefore crossing the bounds of the ν-Angra Experiment to make it interesting and useful for different asynchronous and even synchronous experiments.

Impact of the air filtration on indoor particle concentration by using combination filters in offices building

NASA Astrophysics Data System (ADS)

Kabrein, H.; Hariri, A.; Leman, A. M.; Noraini, N. M. R.; Yusof, M. Z. M.; Afandi, A.

2017-09-01

Heating ventilation and air conditioning system (HVAC) is very important for offices building and human health. The combining filter method was used to reduce the air pollution indoor such as that particulate matter and gases pollution that affected in health and productivity. Using particle filters in industrial HVAC systems (factories and manufacturing process) does not enough to remove all the indoor pollution. The main objective of this study is to investigate the impact of combination filters for particle and gases removal efficiency. The combining method is by using two filters (particulate filter pre-filter and carbon filter) to reduce particle matter and gases respectively. The purpose of this study is to use minimum efficiency reporting value (MERV filter) rating 13 and activated carbon filter (ACF) to remove indoor air pollution and controlling the air change rate to enhance the air quality and energy saving. It was concluded that the combination filter showed good removal efficiency of particle up to 90.76% and 89.25% for PM10 and PM2.5 respectively. The pressure drop across the filters was small compared with the high-efficiency filters. The filtration efficiency of combination filters after three months’ was better than efficiency by the new MERV filter alone.

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.

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

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.

A Weighted Measurement Fusion Particle Filter for Nonlinear Multisensory Systems Based on Gauss–Hermite Approximation

PubMed Central

Li, Yun

2017-01-01

We addressed the fusion estimation problem for nonlinear multisensory systems. Based on the Gauss–Hermite approximation and weighted least square criterion, an augmented high-dimension measurement from all sensors was compressed into a lower dimension. By combining the low-dimension measurement function with the particle filter (PF), a weighted measurement fusion PF (WMF-PF) is presented. The accuracy of WMF-PF appears good and has a lower computational cost when compared to centralized fusion PF (CF-PF). An example is given to show the effectiveness of the proposed algorithms. PMID:28956862

Design and burn-up analyses of new type holder for silicon neutron transmutation doping.

PubMed

Komeda, Masao; Arai, Masaji; Tamai, Kazuo; Kawasaki, Kozo

2016-07-01

We have developed a new silicon irradiation holder with a neutron filter to increase the irradiation efficiency. The neutron filter is made of an alloy of aluminum and B4C particles. We fabricated a new holder based on the results of design analyses. This filter has limited use in applications requiring prolonged use due to a decrease in the amount of (10)B in B4C particles. We investigated the influence of (10)B reduction on doping distribution in a silicon ingot by using the Monte Carlo Code MVP. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tracking multiple particles in fluorescence time-lapse microscopy images via probabilistic data association.

PubMed

Godinez, William J; Rohr, Karl

2015-02-01

Tracking subcellular structures as well as viral structures displayed as 'particles' in fluorescence microscopy images yields quantitative information on the underlying dynamical processes. We have developed an approach for tracking multiple fluorescent particles based on probabilistic data association. The approach combines a localization scheme that uses a bottom-up strategy based on the spot-enhancing filter as well as a top-down strategy based on an ellipsoidal sampling scheme that uses the Gaussian probability distributions computed by a Kalman filter. The localization scheme yields multiple measurements that are incorporated into the Kalman filter via a combined innovation, where the association probabilities are interpreted as weights calculated using an image likelihood. To track objects in close proximity, we compute the support of each image position relative to the neighboring objects of a tracked object and use this support to recalculate the weights. To cope with multiple motion models, we integrated the interacting multiple model algorithm. The approach has been successfully applied to synthetic 2-D and 3-D images as well as to real 2-D and 3-D microscopy images, and the performance has been quantified. In addition, the approach was successfully applied to the 2-D and 3-D image data of the recent Particle Tracking Challenge at the IEEE International Symposium on Biomedical Imaging (ISBI) 2012.

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.

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

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

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.

Method of treating contaminated HEPA filter media in pulp process

DOEpatents

Hu, Jian S.; Argyle, Mark D.; Demmer, Ricky L.; Mondok, Emilio P.

2003-07-29

A method for reducing contamination of HEPA filters with radioactive and/or hazardous materials is described. The method includes pre-processing of the filter for removing loose particles. Next, the filter medium is removed from the housing, and the housing is decontaminated. Finally, the filter medium is processed as pulp for removing contaminated particles by physical and/or chemical methods, including gravity, flotation, and dissolution of the particles. The decontaminated filter medium is then disposed of as non-RCRA waste; the particles are collected, stabilized, and disposed of according to well known methods of handling such materials; and the liquid medium in which the pulp was processed is recycled.

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.

Filtration device for rapid separation of biological particles from complex matrices

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

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

2018-01-09

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

Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

NASA Astrophysics Data System (ADS)

He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

2014-12-01

Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

A distributed, dynamic, parallel computational model: the role of noise in velocity storage

PubMed Central

Merfeld, Daniel M.

2012-01-01

Networks of neurons perform complex calculations using distributed, parallel computation, including dynamic “real-time” calculations required for motion control. The brain must combine sensory signals to estimate the motion of body parts using imperfect information from noisy neurons. Models and experiments suggest that the brain sometimes optimally minimizes the influence of noise, although it remains unclear when and precisely how neurons perform such optimal computations. To investigate, we created a model of velocity storage based on a relatively new technique–“particle filtering”–that is both distributed and parallel. It extends existing observer and Kalman filter models of vestibular processing by simulating the observer model many times in parallel with noise added. During simulation, the variance of the particles defining the estimator state is used to compute the particle filter gain. We applied our model to estimate one-dimensional angular velocity during yaw rotation, which yielded estimates for the velocity storage time constant, afferent noise, and perceptual noise that matched experimental data. We also found that the velocity storage time constant was Bayesian optimal by comparing the estimate of our particle filter with the estimate of the Kalman filter, which is optimal. The particle filter demonstrated a reduced velocity storage time constant when afferent noise increased, which mimics what is known about aminoglycoside ablation of semicircular canal hair cells. This model helps bridge the gap between parallel distributed neural computation and systems-level behavioral responses like the vestibuloocular response and perception. PMID:22514288

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.

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.

Calibration of micromechanical parameters for DEM simulations by using the particle filter

NASA Astrophysics Data System (ADS)

Cheng, Hongyang; Shuku, Takayuki; Thoeni, Klaus; Yamamoto, Haruyuki

2017-06-01

The calibration of DEM models is typically accomplished by trail and error. However, the procedure lacks of objectivity and has several uncertainties. To deal with these issues, the particle filter is employed as a novel approach to calibrate DEM models of granular soils. The posterior probability distribution of the microparameters that give numerical results in good agreement with the experimental response of a Toyoura sand specimen is approximated by independent model trajectories, referred as `particles', based on Monte Carlo sampling. The soil specimen is modeled by polydisperse packings with different numbers of spherical grains. Prepared in `stress-free' states, the packings are subjected to triaxial quasistatic loading. Given the experimental data, the posterior probability distribution is incrementally updated, until convergence is reached. The resulting `particles' with higher weights are identified as the calibration results. The evolutions of the weighted averages and posterior probability distribution of the micro-parameters are plotted to show the advantage of using a particle filter, i.e., multiple solutions are identified for each parameter with known probabilities of reproducing the experimental response.

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.

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.

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

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

Protein-Based Nanofabrics for Multifunctional Air Filtering

NASA Astrophysics Data System (ADS)

Souzandeh, Hamid

With the fast development of economics and population, air pollution is getting worse and becomes a great concern worldwide. The release of chemicals, particulates and biological materials into air can lead to various diseases or discomfort to humans and other living organisms, alongside other serious impacts on the environment. Therefore, improving indoor air quality using various air filters is in critical need because people stay inside buildings most time of the day. However, current air filters using traditional polymers can only remove particles from the polluted air and disposing the huge amount of used air filters can cause serious secondary environmental pollution. Therefore, development of multi-functional air filter materials with environmental friendliness is significant. For this purpose, we developed "green" protein-based multifunctional air-filtering materials. The outstanding performance of the green materials in removal of multiple species of pollutants, including particulate matter, toxic chemicals, and biological hazards, simultaneously, will greatly facilitate the development of the next-generation air-filtration systems. First and foremost, we developed high-performance protein-based nanofabric air-filter mats. It was found that the protein-nanofabrics possess high-efficiency multifunctional air-filtering properties for both particles and various species of chemical gases. Then, the high-performance natural protein-based nanofabrics were promoted both mechanically and functionally by a textured cellulose paper towel. It is interestingly discovered that the textured cellulose paper towel not only can act as a flexible mechanical support, but also a type of airflow regulator which can improve the pollutant-nanofilter interactions. Furthermore, the protein-based nanofabrics were crosslinked in order to enhance the environmental-stability of the filters. It was found that the crosslinked protein-nanofabrics can significantly improve the structure stability against different moisture levels and temperatures, while maintain the multifunctional filtration performance. Moreover, it was demonstrated that the crosslinked protein-nanomaterials also possess antibacterial properties against the selected gram-negative and gram-positive bacteria. This provides a cost-effective solution for advanced "green" nanomaterials with excellent performance in both filtration functions and structure stability under varying environment. This work indicates that protein-based air-filters are promising "green" air-filtering materials for next-generation air-filtration systems.

Compact cyclone filter train for radiological and hazardous environments

DOEpatents

Bench, T.R.

1998-04-28

A compact cyclone filter train is disclosed for the removal of hazardous and radiological particles from a gaseous fluid medium. This filter train permits a small cyclone separator to be used in a very small space envelope due to the arrangement of the filter housing adjacent to the separator with the cyclone separator and the filters mounted on a plate. The entire unit will have a hoist connection at the center of gravity so that the entire unit including the separator, the filters, and the base can be lifted and repositioned as desired. 3 figs.

Separation of nanoparticles: Filtration and scavenging from waste incineration plants.

PubMed

Förster, Henning; Thajudeen, Thaseem; Funk, Christine; Peukert, Wolfgang

2016-06-01

Increased amounts of nanoparticles are applied in products of everyday life and despite material recycling efforts, at the end of their life cycle they are fed into waste incineration plants. This raises the question on the fate of nanoparticles during incineration. In terms of environmental impact the key question is how well airborne nanoparticles are removed by separation processes on their way to the bag house filters and by the existing filtration process based on pulse-jet cleanable fibrous filter media. Therefore, we investigate the scavenging and the filtration of metal nanoparticles under typical conditions in waste incineration plants. The scavenging process is investigated by a population balance model while the nanoparticle filtration experiments are realized in a filter test rig. The results show that depending on the particle sizes, in some cases nearly 80% of the nanoparticles are scavenged by fly ash particles before they reach the bag house filter. For the filtration step dust cakes with a pressure drop of 500Pa or higher are found to be very effective in preventing nanoparticles from penetrating through the filter. Thus, regeneration of the filter must be undertaken with care in order to guarantee highly efficient collection of particles even in the lower nanometre size regime. Copyright © 2016 Elsevier Ltd. All rights reserved.

Compact cyclone filter train for radiological and hazardous environments

DOEpatents

Bench, Thomas R.

1998-01-01

A compact cyclone filter train for the removal of hazardous and radiologi particles from a gaseous fluid medium which permits a small cyclone separator to be used in a very small space envelope due to the arrangement of the filter housing adjacent to the separator with the cyclone separator and the filters mounted on a plate. The entire unit will have a hoist connection at the center of gravity so that the entire unit including the separator, the filters, and the base can be lifted and repositioned as desired.

A novel coupling of noise reduction algorithms for particle flow simulations

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

Zimoń, M.J., E-mail: malgorzata.zimon@stfc.ac.uk; James Weir Fluids Lab, Mechanical and Aerospace Engineering Department, The University of Strathclyde, Glasgow G1 1XJ; Reese, J.M.

2016-09-15

Proper orthogonal decomposition (POD) and its extension based on time-windows have been shown to greatly improve the effectiveness of recovering smooth ensemble solutions from noisy particle data. However, to successfully de-noise any molecular system, a large number of measurements still need to be provided. In order to achieve a better efficiency in processing time-dependent fields, we have combined POD with a well-established signal processing technique, wavelet-based thresholding. In this novel hybrid procedure, the wavelet filtering is applied within the POD domain and referred to as WAVinPOD. The algorithm exhibits promising results when applied to both synthetically generated signals and particlemore » data. In this work, the simulations compare the performance of our new approach with standard POD or wavelet analysis in extracting smooth profiles from noisy velocity and density fields. Numerical examples include molecular dynamics and dissipative particle dynamics simulations of unsteady force- and shear-driven liquid flows, as well as phase separation phenomenon. Simulation results confirm that WAVinPOD preserves the dimensionality reduction obtained using POD, while improving its filtering properties through the sparse representation of data in wavelet basis. This paper shows that WAVinPOD outperforms the other estimators for both synthetically generated signals and particle-based measurements, achieving a higher signal-to-noise ratio from a smaller number of samples. The new filtering methodology offers significant computational savings, particularly for multi-scale applications seeking to couple continuum informations with atomistic models. It is the first time that a rigorous analysis has compared de-noising techniques for particle-based fluid simulations.« less

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.

Bead mediated separation of microparticles in droplets.

PubMed

Wang, Sida; Sung, Ki-Joo; Lin, Xiaoxia Nina; Burns, Mark A

2017-01-01

Exchange of components such as particles and cells in droplets is important and highly desired in droplet microfluidic assays, and many current technologies use electrical or magnetic fields to accomplish this process. Bead-based microfluidic techniques offer an alternative approach that uses the bead's solid surface to immobilize targets like particles or biological material. In this paper, we demonstrate a bead-based technique for exchanging droplet content by separating fluorescent microparticles in a microfluidic device. The device uses posts to filter surface-functionalized beads from a droplet and re-capture the filtered beads in a new droplet. With post spacing of 7 μm, beads above 10 μm had 100% capture efficiency. We demonstrate the efficacy of this system using targeted particles that bind onto the functionalized beads and are, therefore, transferred from one solution to another in the device. Binding capacity tests performed in the bulk phase showed an average binding capacity of 5 particles to each bead. The microfluidic device successfully separated the targeted particles from the non-targeted particles with up to 98% purity and 100% yield.

Bead mediated separation of microparticles in droplets

PubMed Central

Sung, Ki-Joo; Lin, Xiaoxia Nina; Burns, Mark A.

2017-01-01

Exchange of components such as particles and cells in droplets is important and highly desired in droplet microfluidic assays, and many current technologies use electrical or magnetic fields to accomplish this process. Bead-based microfluidic techniques offer an alternative approach that uses the bead’s solid surface to immobilize targets like particles or biological material. In this paper, we demonstrate a bead-based technique for exchanging droplet content by separating fluorescent microparticles in a microfluidic device. The device uses posts to filter surface-functionalized beads from a droplet and re-capture the filtered beads in a new droplet. With post spacing of 7 μm, beads above 10 μm had 100% capture efficiency. We demonstrate the efficacy of this system using targeted particles that bind onto the functionalized beads and are, therefore, transferred from one solution to another in the device. Binding capacity tests performed in the bulk phase showed an average binding capacity of 5 particles to each bead. The microfluidic device successfully separated the targeted particles from the non-targeted particles with up to 98% purity and 100% yield. PMID:28282412

Special diatomite solves fiberglass particles filtration problem

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

Not Available

1979-07-01

Johns-Manville Corp. has developed a water treatment system which is based on the principle of zero-discharge of process water and which uses an alum-coated Celite diatomaceous earth filter for removing particles of carbon black and abrasive glass, tramp dirt, and oils and grease out of waste water from its fiberglass plants at Parkersburg, W. Va., and elsewhere. The resulting water is essentially free of suspended solids larger than 0.5j at Vertical Bar3; 5 mg/l. concentration, even when the solids concentration in the filter feed water ranges from 50 to 1000 mg/l. The system's core is the alum coating, which ismore » obtained by reacting the diatomite with aluminum sulfate and soda ash. Because it has a highly positive electrical charge, the coating attracts the negatively charged carbon particles and attaches them to the diatomite surface to be filtered out. Filtration cycles vary from 8 to 24 hr depending on the raw water and filter grade used; the terminal pressure is about 60 psig. At cycles' end, the filter cake is up to 2.5 in. thick; this is disposed of in sanitary landfills.« less

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).

Filter and method of fabricating

DOEpatents

Janney, Mark A.

2006-02-14

A method of making a filter includes the steps of: providing a substrate having a porous surface; applying to the porous surface a coating of dry powder comprising particles to form a filter preform; and heating the filter preform to bind the substrate and the particles together to form a filter.

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 ...

A regularized auxiliary particle filtering approach for system state estimation and battery life prediction

NASA Astrophysics Data System (ADS)

Liu, Jie; Wang, Wilson; Ma, Fai

2011-07-01

System current state estimation (or condition monitoring) and future state prediction (or failure prognostics) constitute the core elements of condition-based maintenance programs. For complex systems whose internal state variables are either inaccessible to sensors or hard to measure under normal operational conditions, inference has to be made from indirect measurements using approaches such as Bayesian learning. In recent years, the auxiliary particle filter (APF) has gained popularity in Bayesian state estimation; the APF technique, however, has some potential limitations in real-world applications. For example, the diversity of the particles may deteriorate when the process noise is small, and the variance of the importance weights could become extremely large when the likelihood varies dramatically over the prior. To tackle these problems, a regularized auxiliary particle filter (RAPF) is developed in this paper for system state estimation and forecasting. This RAPF aims to improve the performance of the APF through two innovative steps: (1) regularize the approximating empirical density and redraw samples from a continuous distribution so as to diversify the particles; and (2) smooth out the rather diffused proposals by a rejection/resampling approach so as to improve the robustness of particle filtering. The effectiveness of the proposed RAPF technique is evaluated through simulations of a nonlinear/non-Gaussian benchmark model for state estimation. It is also implemented for a real application in the remaining useful life (RUL) prediction of lithium-ion batteries.

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

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.

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.

Iridium emissions from Hawaiian volcanoes

NASA Technical Reports Server (NTRS)

Finnegan, D. L.; Zoller, W. H.; Miller, T. M.

1988-01-01

Particle and gas samples were collected at Mauna Loa volcano during and after its eruption in March and April, 1984 and at Kilauea volcano in 1983, 1984, and 1985 during various phases of its ongoing activity. In the last two Kilauea sampling missions, samples were collected during eruptive activity. The samples were collected using a filterpack system consisting of a Teflon particle filter followed by a series of 4 base-treated Whatman filters. The samples were analyzed by INAA for over 40 elements. As previously reported in the literature, Ir was first detected on particle filters at the Mauna Loa Observatory and later from non-erupting high temperature vents at Kilauea. Since that time Ir was found in samples collected at Kilauea and Mauna Loa during fountaining activity as well as after eruptive activity. Enrichment factors for Ir in the volcanic fumes range from 10,000 to 100,000 relative to BHVO. Charcoal impregnated filters following a particle filter were collected to see if a significant amount of the Ir was in the gas phase during sample collection. Iridium was found on charcoal filters collected close to the vent, no Ir was found on the charcoal filters. This indicates that all of the Ir is in particulate form very soon after its release. Ratios of Ir to F and Cl were calculated for the samples from Mauna Loa and Kilauea collected during fountaining activity. The implications for the KT Ir anomaly are still unclear though as Ir was not found at volcanoes other than those at Hawaii. Further investigations are needed at other volcanoes to ascertain if basaltic volcanoes other than hot spots have Ir enrichments in their fumes.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Electrospun Magnetic Nanoparticle-Decorated Nanofiber Filter and Its Applications to High-Efficiency Air Filtration.

PubMed

Kim, Juyoung; Chan Hong, Seung; Bae, Gwi Nam; Jung, Jae Hee

2017-10-17

Filtration technology has been widely studied due to concerns about exposure to airborne dust, including metal oxide nanoparticles, which cause serious health problems. The aim of these studies has been to develop mechanisms for the continuous and efficient removal of metal oxide dusts. In this study, we introduce a novel air filtration system based on the magnetic attraction force. The filtration system is composed of a magnetic nanoparticle (MNP)-decorated nanofiber (MNP-NF) filter. Using a simple electrospinning system, we fabricated continuous and smooth electrospun nanofibers with evenly distributed Fe 3 O 4 MNPs. Our electrospun MNP-NF filter exhibited high particle collection efficiency (∼97% at 300 nm particle size) compared to the control filter (w/o MNPs, ∼ 68%), with a ∼ 64% lower pressure drop (∼17 Pa) than the control filter (∼27 Pa). Finally, the filter quality factors of the MNP-NF filter were 4.7 and 11.9 times larger than those of the control filter and the conventional high-efficiency particulate air filters (>99% and ∼269 Pa), respectively. Furthermore, we successfully performed a field test of our MNP-NF filter using dust from a subway station tunnel. This work suggests that our novel MNP-NF filter can be used to facilitate effective protection against hazardous metal oxide dust in real environments.

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.

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. ...

Online particle detection with Neural Networks based on topological calorimetry information

NASA Astrophysics Data System (ADS)

Ciodaro, T.; Deva, D.; de Seixas, J. M.; Damazio, D.

2012-06-01

This paper presents the latest results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction using the ATLAS calorimetry information (energy measurements). The extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time by 59%. Also, the total memory necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount.

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...

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.

Freeing Water from Viruses and Bacteria

NASA Technical Reports Server (NTRS)

2004-01-01

Four years ago, Argonide Corporation, a company focused on the research, production, and marketing of specialty nano materials, was seeking to develop applications for its NanoCeram[R] fibers. Only 2 nanometers in diameter, these nano aluminum oxide fibers possessed unusual bio-adhesive properties. When formulated into a filter material, the electropositive fibers attracted and retained electro-negative particles such as bacteria and viruses in water-based solutions. This technology caught the interest of NASA as a possible solution for improved water filtration in space cabins. NASA's Johnson Space Center awarded Sanford, Florida-based Argonide a Phase I Small Business Innovation Research (SBIR) contract to determine the feasibility of using the company's filter for purifying recycled space cabin water. Since viruses and bacteria can be carried aboard space cabins by space crews, the ability to detect and remove these harmful substances is a concern for NASA. The Space Agency also desired an improved filter to polish the effluent from condensed and waste water, producing potable drinking water. During its Phase I partnership with NASA, Argonide developed a laboratory-size filter capable of removing greater than 99.9999 percent of bacteria and viruses from water at flow rates more than 200 times faster than virus-rated membranes that remove particles by sieving. Since the new filter s pore size is rather large compared to other membranes, it is also less susceptible to clogging by small particles. In September 2002, Argonide began a Phase II SBIR project with Johnson to develop a full-size cartridge capable of serving a full space crew. This effort, which is still ongoing, enabled the company to demonstrate that its filter media is an efficient absorbent for DNA and RNA.

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.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant.

PubMed

Camplani, M; Malizia, A; Gelfusa, M; Barbato, F; Antonelli, L; Poggi, L A; Ciparisse, J F; Salgado, L; Richetta, M; Gaudio, P

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant

NASA Astrophysics Data System (ADS)

Camplani, M.; Malizia, A.; Gelfusa, M.; Barbato, F.; Antonelli, L.; Poggi, L. A.; Ciparisse, J. F.; Salgado, L.; Richetta, M.; Gaudio, P.

2016-01-01

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

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

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.

Performance of biomorphic Silicon Carbide as particulate filter in diesel boilers.

PubMed

Orihuela, M Pilar; Gómez-Martín, Aurora; Becerra, José A; Chacartegui, Ricardo; Ramírez-Rico, Joaquín

2017-12-01

Biomorphic Silicon Carbide (bioSiC) is a novel porous ceramic material with excellent mechanical and thermal properties. Previous studies have demonstrated that it may be a good candidate for its use as particle filter media of exhaust gases at medium or high temperature. In order to determine the filtration efficiency of biomorphic Silicon Carbide, and its adequacy as substrate for diesel particulate filters, different bioSiC-samples have been tested in the flue gases of a diesel boiler. For this purpose, an experimental facility to extract a fraction of the boiler exhaust flow and filter it under controlled conditions has been designed and built. Several filter samples with different microstructures, obtained from different precursors, have been tested in this bench. The experimental campaign was focused on the measurement of the number and size of particles before and after placing the samples. Results show that the initial efficiency of filters made from natural precursors is severely determined by the cutting direction and associated microstructure. In biomorphic Silicon Carbide derived from radially cut wood, the initial efficiency of the filter is higher than 95%. Nevertheless, when the cut of the wood is axial, the efficiency depends on the pore size and the permeability, reaching in some cases values in the range 70-90%. In this case, the presence of macropores in some of the samples reduces their efficiency as particle traps. In continuous operation, the accumulation of particles within the porous media leads to the formation of a soot cake, which improves the efficiency except in the case when extra-large pores exist. For all the samples, after a few operation cycles, capture efficiency was higher than 95%. These experimental results show the potential for developing filters for diesel boilers based on biomorphic Silicon Carbide. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Filtered cathodic arc deposition apparatus and method

DOEpatents

Krauss, Alan R.

1999-01-01

A filtered cathodic arc deposition method and apparatus for the production of highly dense, wear resistant coatings which are free from macro particles. The filtered cathodic arc deposition apparatus includes a cross shaped vacuum chamber which houses a cathode target having an evaporable surface comprised of the coating material, means for generating a stream of plasma, means for generating a transverse magnetic field, and a macro particle deflector. The transverse magnetic field bends the generated stream of plasma in the direction of a substrate. Macro particles are effectively filtered from the stream of plasma by traveling, unaffected by the transverse magnetic field, along the initial path of the plasma stream to a macro particle deflector. The macro particle deflector has a preformed surface which deflects macro particles away from the substrate.

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

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.

Detection near 1-nm with a laminar-flow, water-based condensation particle counter

DOE PAGES

Hering, Susanne V.; Lewis, Gregory S.; Spielman, Steven R.; ...

2016-11-18

Presented is a laminar-flow, water-based condensation particle counter capable of particle detection near 1 nm. This instrument employs a three-stage, laminar-flow growth tube with a “moderator” stage that reduces the temperature and water content of the output flow without reducing the peak supersaturation, and makes feasible operation at the large temperature differences necessary for achieving high supersaturations. The instrument has an aerosol flow of 0.3 L/min, and does not use a filtered sheath flow. It is referred to as a “versatile” water condensation particle counter, or vWCPC, as operating temperatures can be adjusted in accordance with the cut-point desired. Whenmore » operated with wall temperatures of ~2°C, >90°C, and ~22°C for the three stages, respectively, the vWCPC detects particles generated from a heated nichrome wire with a 50% efficiency cut-point near 1.6 nm mobility diameter. At these operating temperatures, it also detects 10–20% of large molecular ions formed from passing filtered ambient air through a bipolar ion source. Decreasing the temperature difference between the first two stages, with the first and second stages operated at 10 and 90°C, respectively, essentially eliminates the response to charger ions, and raises the 50% efficiency cut-point for the nichrome wire particles to 1.9 nm mobility diameter. Here, the time response, as measured by rapid removal of an inlet filter, yields a characteristic time constant of 195 ms.« less

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.

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.

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.

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.

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.

Methods of and apparatus for testing the integrity of filters

DOEpatents

Herman, R.L.

1984-01-01

A method of and apparatus for testing the integrity of individual filters or filter stages of a multistage filtering system including a diffuser permanently mounted upstream and/or downstream of the filter stage to be tested for generating pressure differentials to create sufficient turbulence for uniformly dispersing trace agent particles within the airstram upstream and downstream of such filter stage. Samples of the particel concentration are taken upstream and downstream of the filter stage for comparison to determine the extent of particle leakage past the filter stage.

A sunblock based on bioadhesive nanoparticles

NASA Astrophysics Data System (ADS)

Deng, Yang; Ediriwickrema, Asiri; Yang, Fan; Lewis, Julia; Girardi, Michael; Saltzman, W. Mark

2015-12-01

The majority of commercial sunblock preparations use organic or inorganic ultraviolet (UV) filters. Despite protecting against cutaneous phototoxicity, direct cellular exposure to UV filters has raised a variety of health concerns. Here, we show that the encapsulation of padimate O (PO)--a model UV filter--in bioadhesive nanoparticles (BNPs) prevents epidermal cellular exposure to UV filters while enhancing UV protection. BNPs are readily suspended in water, facilitate adherence to the stratum corneum without subsequent intra-epidermal or follicular penetration, and their interaction with skin is water resistant yet the particles can be removed via active towel drying. Although the sunblock based on BNPs contained less than 5 wt% of the UV-filter concentration found in commercial standards, the anti-UV effect was comparable when tested in two murine models. Moreover, the BNP-based sunblock significantly reduced double-stranded DNA breaks when compared with a commercial sunscreen formulation.

Biological hydrogels as selective diffusion barriers.

PubMed

Lieleg, Oliver; Ribbeck, Katharina

2011-09-01

The controlled exchange of molecules between organelles, cells, or organisms and their environment is crucial for life. Biological gels such as mucus, the extracellular matrix (ECM), and the biopolymer barrier within the nuclear pore are well suited to achieve such a selective exchange, allowing passage of particular molecules while rejecting many others. Although hydrogel-based filters are integral parts of biology, clear concepts of how their barrier function is controlled at a microscopic level are still missing. We summarize here our current understanding of how selective filtering is established by different biopolymer-based hydrogels. We ask if the modulation of microscopic particle transport in biological hydrogels is based on a generic filtering principle which employs biochemical/biophysical interactions with the filtered molecules rather than size-exclusion effects. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Removing Pathogens Using Nano-Ceramic-Fiber Filters

NASA Technical Reports Server (NTRS)

Tepper, Frederick; Kaledin, Leonid

2005-01-01

A nano-aluminum-oxide fiber of only 2 nanometers in diameter was used to develop a ceramic-fiber filter. The fibers are electropositive and, when formulated into a filter material (NanoCeram(TradeMark)), would attract electro-negative particles such as bacteria and viruses. The ability to detect and then remove viruses as well as bacteria is of concern in space cabins since they may be carried onboard by space crews. Moreover, an improved filter was desired that would polish the effluent from condensed moisture and wastewater, producing potable drinking water. A laboratory- size filter was developed that was capable of removing greater than 99.9999 percent of bacteria and virus. Such a removal was achieved at flow rates hundreds of times greater than those through ultraporous membranes that remove particles by sieving. Because the pore size of the new filter was rather large as compared to ultraporous membranes, it was found to be more resistant to clogging. Additionally, a full-size cartridge is being developed that is capable of serving a full space crew. During this ongoing effort, research demonstrated that the filter media was a very efficient adsorbent for DNA (deoxyribonucleic acid), RNA (ribonucleic acid), and endotoxins. Since the adsorption is based on the charge of the macromolecules, there is also a potential for separating proteins and other particulates on the basis of their charge differences. The separation of specific proteins is a major new thrust of biotechnology. The principal application of NanoCeram filters is based on their ability to remove viruses from water. The removal of more than 99.9999 percent of viruses was achieved by a NanoCeram polishing filter added to the effluent of an existing filtration device. NanoCeram is commercially available in laboratory-size filter discs and in the form of a syringe filter. The unique characteristic of the filter can be demonstrated by its ability to remove particulate dyes such as Metanyl yellow. Its particle size is only 2 nanometers, about the size of a DNA molecule, yet the NanoCeram syringe filter is capable of retaining the dyes as the fluid is passed through the syringe, without much back-pressure. Endotoxins, which are contaminants that are part of the residue of destroyed bacteria, can cause toxic shock and are therefore of major concern in pharmaceutical products. The NanoCeram syringe filter is capable of removing greater than 99.96 percent of the endotoxins.

THE INFLUENCE OF HUMAN ACTIVITY PATTERNS ON PERSONAL PM EXPOSURE: A COMPARATIVE ANALYSIS OF FILTER-BASED AND CONTINUOUS PARTICLE MEASUREMENTS

EPA Science Inventory

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency sponsored 1998 Baltimore and 1999 Fresno PM Exposure Studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly ...

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.

Combining Particle Filters and Consistency-Based Approaches for Monitoring and Diagnosis of Stochastic Hybrid Systems

NASA Technical Reports Server (NTRS)

Narasimhan, Sriram; Dearden, Richard; Benazera, Emmanuel

2004-01-01

Fault detection and isolation are critical tasks to ensure correct operation of systems. When we consider stochastic hybrid systems, diagnosis algorithms need to track both the discrete mode and the continuous state of the system in the presence of noise. Deterministic techniques like Livingstone cannot deal with the stochasticity in the system and models. Conversely Bayesian belief update techniques such as particle filters may require many computational resources to get a good approximation of the true belief state. In this paper we propose a fault detection and isolation architecture for stochastic hybrid systems that combines look-ahead Rao-Blackwellized Particle Filters (RBPF) with the Livingstone 3 (L3) diagnosis engine. In this approach RBPF is used to track the nominal behavior, a novel n-step prediction scheme is used for fault detection and L3 is used to generate a set of candidates that are consistent with the discrepant observations which then continue to be tracked by the RBPF scheme.

One-dimensional soil temperature assimilation experiment based on unscented particle filter and Common Land Model

NASA Astrophysics Data System (ADS)

Fu, Xiao Lei; Jin, Bao Ming; Jiang, Xiao Lei; Chen, Cheng

2018-06-01

Data assimilation is an efficient way to improve the simulation/prediction accuracy in many fields of geosciences especially in meteorological and hydrological applications. This study takes unscented particle filter (UPF) as an example to test its performance at different two probability distribution, Gaussian and Uniform distributions with two different assimilation frequencies experiments (1) assimilating hourly in situ soil surface temperature, (2) assimilating the original Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) once per day. The numerical experiment results show that the filter performs better when increasing the assimilation frequency. In addition, UPF is efficient for improving the soil variables (e.g., soil temperature) simulation/prediction accuracy, though it is not sensitive to the probability distribution for observation error in soil temperature assimilation.

Applying Theory to Understand and Modify Nurse Intention to Adhere to Recommendations regarding the Use of Filter Needles: An Intervention Mapping Approach.

PubMed

Cassista, Julianne; Payne-Gagnon, Julie; Martel, Brigitte; Gagnon, Marie-Pierre

2014-01-01

The manipulation of glass ampoules involves risk of particle contamination of parenteral medication, and the use of filter needles has often been recommended in order to reduce the number of particles in these solutions. This study aims to develop a theory-based intervention to increase nurse intention to use filter needles according to clinical guideline recommendations produced by a large university medical centre in Quebec (Canada). Using the Intervention Mapping framework, we first identified the psychosocial determinants of nurse intention to use filter needles according to these recommendations. Second, we developed and implemented an intervention targeting nurses from five care units in order to increase their intention to adhere to recommendations on the use of filter needles. We also assessed nurse satisfaction with the intervention. In total, 270 nurses received the intervention and 169 completed the posttest questionnaire. The two determinants of intention, that is, attitude and perceived behavioral control, were significantly higher after the intervention, but only perceived behavioral control remained a predictor of intention. In general, nurses were highly satisfied with the intervention. This study provides support for the use of Intervention Mapping to develop, implement, and evaluate theory-based interventions in order to improve healthcare professional adherence to clinical recommendations.

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.

A Maximum Entropy Method for Particle Filtering

NASA Astrophysics Data System (ADS)

Eyink, Gregory L.; Kim, Sangil

2006-06-01

Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.

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.

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%.

Complete filter-based cerebral embolic protection with transcatheter aortic valve replacement.

PubMed

Van Gils, Lennart; Kroon, Herbert; Daemen, Joost; Ren, Claire; Maugenest, Anne-Marie; Schipper, Marguerite; De Jaegere, Peter P; Van Mieghem, Nicolas M

2018-03-01

To evaluate the value of left vertebral artery filter protection in addition to the current filter-based embolic protection technology to achieve complete cerebral protection during TAVR. The occurrence of cerebrovascular events after transcatheter aortic valve replacement (TAVR) has fueled concern for its potential application in younger patients with longer life expectancy. Transcatheter cerebral embolic protection (TCEP) devices may limit periprocedural cerebrovascular events by preventing macro and micro-embolization to the brain. Conventional filter-based TCEP devices cover three extracranial contributories to the brain, yet leave the left vertebral artery unprotected. Patients underwent TAVR with complete TCEP. A dual-filter system was deployed in the brachiocephalic trunk and left common carotid artery with an additional single filter in the left vertebral artery. After TAVR all filters were retrieved and sent for histopathological evaluation by an experienced pathologist. Eleven patients received a dual-filter system and nine of them received an additional left vertebral filter. In the remaining two patients, the left vertebral filter could not be deployed. No periprocedural strokes occurred. We found debris in all filters, consisting of thrombus, tissue derived debris, and foreign body material. The left vertebral filter contained debris in an equal amount of patients as the Sentinel filters. The size of the captured particles was similar between all filters. The left vertebral artery is an important entry route for embolic material to the brain during TAVR. Selective filter protection of the left vertebral artery revealed embolic debris in all patients. The clinical value of complete filter-based TCEP during TAVR warrants further research. © 2017 Wiley Periodicals, Inc.

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.

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.

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.

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.

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.

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.

A simple dynamic subgrid-scale model for LES of particle-laden turbulence

NASA Astrophysics Data System (ADS)

Park, George Ilhwan; Bassenne, Maxime; Urzay, Javier; Moin, Parviz

2017-04-01

In this study, a dynamic model for large-eddy simulations is proposed in order to describe the motion of small inertial particles in turbulent flows. The model is simple, involves no significant computational overhead, contains no adjustable parameters, and is flexible enough to be deployed in any type of flow solvers and grids, including unstructured setups. The approach is based on the use of elliptic differential filters to model the subgrid-scale velocity. The only model parameter, which is related to the nominal filter width, is determined dynamically by imposing consistency constraints on the estimated subgrid energetics. The performance of the model is tested in large-eddy simulations of homogeneous-isotropic turbulence laden with particles, where improved agreement with direct numerical simulation results is observed in the dispersed-phase statistics, including particle acceleration, local carrier-phase velocity, and preferential-concentration metrics.

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.

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

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 %.

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.

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

An occupational exposure assessment for engineered nanoparticles used in semiconductor fabrication.

PubMed

Shepard, Michele Noble; Brenner, Sara

2014-03-01

Engineered nanoparticles of alumina, amorphous silica, and ceria are used in semiconductor device fabrication during wafer polishing steps referred to as 'chemical mechanical planarization' (CMP). Some metal oxide nanoparticles can impact the biological response of cells and organ systems and may cause adverse health effects; additional research is necessary to better understand potential risks from nanomaterial applications and occupational exposure scenarios. This study was conducted to assess potential airborne exposures to nanoparticles and agglomerates using direct-reading instruments and filter-based samples to characterize workplace aerosols by particle number, mass, size, composition, and morphology. Sampling was repeated for tasks in three work areas (fab, subfab, wastewater treatment) at a facility using engineered nanoparticles for CMP. Real-time measurements were collected using a condensation particle counter (CPC), optical particle counter, and scanning mobility particle spectrometer (SMPS). Filter-based samples were analyzed for total mass or the respirable fraction, and for specific metals of interest. Additional air sample filters were analyzed by transmission electron microscopy with energy dispersive x-ray spectroscopy (TEM/EDX) for elemental identification and to provide data on particle size, morphology, and concentration. Peak concentrations measured on the CPC ranged from 1 to 16 particles per cubic centimeter (P cm(-3)) for background and from 4 to 74 P cm(-3) during tasks sampled in the fab; from 1 to 60 P cm(-3) for background and from 3 to 84 P cm(-3) for tasks sampled in the subfab; and from 1160 to 45 894 P cm(-3) for background and from 1710 to 45 519 P cm(-3) during wastewater treatment system filter change tasks. Significant variability was seen among the repeated task measurements and among background comparisons in each area. Several data analysis methods were used to compare each set of task and background measurements. Increased concentrations of respirable particles were identified for some tasks sampled in each work area, although of relatively low magnitude and inconsistently among repeated measurements for specific tasks. Measurements with a portable SMPS indicated that nanoparticle number concentrations (channels 11.5-115.5nm) increased above background levels by 3.2 P cm(-3) during CMP tool set-up in the fab area but were not elevated when changing filters for the CMP wastewater treatment system. All results from mass concentration analysis were below the limits of detection. Characterization by TEM/EDX identified structures containing the elements of interest (Al, Si), primarily as agglomerates or aggregates in the 100-1000nm size range. Although health-based occupational exposure limits have not been established for nanoscale alumina, silica, or ceria, the measured concentrations by number and mass were below currently proposed benchmarks or reference values for poorly soluble low-toxicity nanoparticles.

Morphology of Nano and Micro Fiber Structures in Ultrafine Particles Filtration

NASA Astrophysics Data System (ADS)

Kimmer, Dusan; Vincent, Ivo; Fenyk, Jan; Petras, David; Zatloukal, Martin; Sambaer, Wannes; Zdimal, Vladimir

2011-07-01

Selected procedures permitting to prepare homogeneous nanofibre structures of the desired morphology by employing a suitable combination of variables during the electrospinning process are presented. A comparison (at the same pressure drop) was made of filtration capabilities of planar polyurethane nanostructures formed exclusively by nanofibres, space polycarbonate nanostructures having bead spacers, structures formed by a combination of polymethyl methacrylate micro- and nanofibres and polypropylene meltblown microstructures, through which ultrafine particles of ammonium sulphate 20-400 nm in size were filtered. The structures studied were described using a new digital image analysis technique based on black and white images obtained by scanning electron microscopy. More voluminous structures modified with distance microspheres and having a greater thickness and mass per square area of the material, i.e. structures possessing better mechanical properties, demanded so much in nanostructures, enable preparation of filters having approximately the same free volume fraction as flat nanofibre filters but an increased effective fibre surface area, changed pore size morphology and, consequently, a higher filter quality.

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.

Filtered refocusing: a volumetric reconstruction algorithm for plenoptic-PIV

NASA Astrophysics Data System (ADS)

Fahringer, Timothy W.; Thurow, Brian S.

2016-09-01

A new algorithm for reconstruction of 3D particle fields from plenoptic image data is presented. The algorithm is based on the technique of computational refocusing with the addition of a post reconstruction filter to remove the out of focus particles. This new algorithm is tested in terms of reconstruction quality on synthetic particle fields as well as a synthetically generated 3D Gaussian ring vortex. Preliminary results indicate that the new algorithm performs as well as the MART algorithm (used in previous work) in terms of the reconstructed particle position accuracy, but produces more elongated particles. The major advantage to the new algorithm is the dramatic reduction in the computational cost required to reconstruct a volume. It is shown that the new algorithm takes 1/9th the time to reconstruct the same volume as MART while using minimal resources. Experimental results are presented in the form of the wake behind a cylinder at a Reynolds number of 185.

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

NASA Astrophysics Data System (ADS)

Abbaszadeh, Peyman; Moradkhani, Hamid; Yan, Hongxiang

2018-01-01

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

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.

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.

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.

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.

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.

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.

[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.

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).

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.

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.

Infiltration of forest fire and residential wood smoke: an evaluation of air cleaner effectiveness.

PubMed

Barn, Prabjit; Larson, Timothy; Noullett, Melanie; Kennedy, Susan; Copes, Ray; Brauer, Michael

2008-09-01

Communities impacted by fine-particle air pollution (particles with an aerodynamic diameter less than 2.5 microm; PM(2.5)) from forest fires and residential wood burning require effective, evidence-based exposure-reduction strategies. Public health recommendations during smoke episodes typically include advising community members to remain indoors and the use of air cleaners, yet little information is available on the effectiveness of these measures. Our study attempted to address the following objectives: to measure indoor infiltration factor (F(inf)) of PM(2.5) from forest fires/wood smoke, to determine the effectiveness of high-efficiency particulate air (HEPA) filter air cleaners in reducing indoor PM(2.5), and to analyze the home determinants of F(inf) and air cleaner effectiveness (ACE). We collected indoor/outdoor 1-min PM(2.5) averages and 48-h outdoor PM(2.5) filter samples for 21 winter and 17 summer homes impacted by wood burning and forest fire smoke, respectively, during 2004-2005. A portable HEPA filter air cleaner was operated indoors with the filter removed for one of two sampling days. Particle F(inf) and ACE were calculated for each home using a recursive model. We found mean F(inf)+/-SD was 0.27+/-0.18 and 0.61+/-0.27 in winter (n=19) and summer (n=13), respectively, for days when HEPA filters were not used. Lower F(inf)+/-SD values of 0.10+/-0.08 and 0.19+/-0.20 were found on corresponding days when HEPA filters were in place. Mean+/-SD ACE ([F(inf) without filter-F(inf) with filter]/F(inf) without filter) in winter and summer were 55+/-38% and 65+/-35%, respectively. Number of windows and season predicted F(inf) (P<0.001). No significant predictors of ACE were identified. Our findings show that remaining indoors combined with use of air cleaner can effectively reduce PM(2.5) exposure during forest fires and residential wood burning.

A Model-Based Prognostics Approach Applied to Pneumatic Valves

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Goebel, Kai

2011-01-01

Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its components, and how they fail by casting the underlying physical phenomena in a physics-based model that is derived from first principles. Uncertainty cannot be avoided in prediction, therefore, algorithms are employed that help in managing these uncertainties. The particle filtering algorithm has become a popular choice for model-based prognostics due to its wide applicability, ease of implementation, and support for uncertainty management. We develop a general model-based prognostics methodology within a robust probabilistic framework using particle filters. As a case study, we consider a pneumatic valve from the Space Shuttle cryogenic refueling system. We develop a detailed physics-based model of the pneumatic valve, and perform comprehensive simulation experiments to illustrate our prognostics approach and evaluate its effectiveness and robustness. The approach is demonstrated using historical pneumatic valve data from the refueling system.

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...

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.

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.

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.

A Survey of Recent Advances in Particle Filters and Remaining Challenges for Multitarget Tracking

PubMed Central

Wang, Xuedong; Sun, Shudong; Corchado, Juan M.

2017-01-01

We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal, computing efficiency, particle degeneracy/impoverishment and constrained/multi-modal systems. The second part of our review is on analyzing the intractable challenges raised within the general multitarget (multi-sensor) tracking due to random target birth and termination, false alarm, misdetection, measurement-to-track (M2T) uncertainty and track uncertainty. The mainstream multitarget PF approaches consist of two main classes, one based on M2T association approaches and the other not such as the finite set statistics-based PF. In either case, significant challenges remain due to unknown tracking scenarios and integrated tracking management. PMID:29168772

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.

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.

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.

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.

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.

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.

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.

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

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

PDF-based heterogeneous multiscale filtration model.

PubMed

Gong, Jian; Rutland, Christopher J

2015-04-21

Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.

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

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.

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

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.

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.

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.

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

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.

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.

Novel Hollow Fiber Air Filters for the Removal of Ultrafine Particles in PM2.5 with Repetitive Usage Capability.

PubMed

Li, Manqing; Feng, Yingnan; Wang, Kaiyu; Yong, Wai Fen; Yu, Liya; Chung, Tai-Shung

2017-09-05

Severe air pollution has become a global concern, and there is a pressing need to develop effective and efficient air filters for removing airborne particulate matters (PMs). In this work, a highly permeable poly(ether sulfone) (PES) based hollow fiber membrane was developed via a one-step dry-jet wet spinning. For the first time, a hollow fiber membrane was used in removing the ultrafine particles (PMs with aerodynamic equivalent diameters of less than 100 nm) in PM 2.5 . The novel air filter was designed to possess the synergistic advantages of porous filters and fibrous filters with a sievelike outer surface and a fibrouslike porous substrate. A filtration efficiency of higher than 99.995% could be easily achieved when the self-support hollow fiber was challenged with less than 300 nm particulates. Without losses of the structural advantages, we have demonstrated that the permeation properties of the hollow fiber membrane can be facilely tailored via manipulation of the dope and bore fluid formulations. Various cleaning strategies were explored to regenerate the membrane performance after fouling. Both water rinse and backwash showed effectiveness to restore the membrane permeance for repetitive usage.

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.

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

PubMed Central

Li, Tao; Yuan, Gannan; Li, Wang

2016-01-01

The derivation of a conventional error model for the miniature gyroscope-based measurement while drilling (MGWD) system is based on the assumption that the errors of attitude are small enough so that the direction cosine matrix (DCM) can be approximated or simplified by the errors of small-angle attitude. However, the simplification of the DCM would introduce errors to the navigation solutions of the MGWD system if the initial alignment cannot provide precise attitude, especially for the low-cost microelectromechanical system (MEMS) sensors operated in harsh multilateral horizontal downhole drilling environments. This paper proposes a novel nonlinear error model (NNEM) by the introduction of the error of DCM, and the NNEM can reduce the propagated errors under large-angle attitude error conditions. The zero velocity and zero position are the reference points and the innovations in the states estimation of particle filter (PF) and Kalman filter (KF). The experimental results illustrate that the performance of PF is better than KF and the PF with NNEM can effectively restrain the errors of system states, especially for the azimuth, velocity, and height in the quasi-stationary condition. PMID:26999130

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.

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

PubMed

Li, Tao; Yuan, Gannan; Li, Wang

2016-03-15

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

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.

Iterons, fractals and computations of automata

NASA Astrophysics Data System (ADS)

Siwak, Paweł

1999-03-01

Processing of strings by some automata, when viewed on space-time (ST) diagrams, reveals characteristic soliton-like coherent periodic objects. They are inherently associated with iterations of automata mappings thus we call them the iterons. In the paper we present two classes of one-dimensional iterons: particles and filtrons. The particles are typical for parallel (cellular) processing, while filtrons, introduced in (32) are specific for serial processing of strings. In general, the images of iterated automata mappings exhibit not only coherent entities but also the fractals, and quasi-periodic and chaotic dynamics. We show typical images of such computations: fractals, multiplication by a number, and addition of binary numbers defined by a Turing machine. Then, the particles are presented as iterons generated by cellular automata in three computations: B/U code conversion (13, 29), majority classification (9), and in discrete version of the FPU (Fermi-Pasta-Ulam) dynamics (7, 23). We disclose particles by a technique of combinational recoding of ST diagrams (as opposed to sequential recoding). Subsequently, we recall the recursive filters based on FCA (filter cellular automata) window operators, and considered by Park (26), Ablowitz (1), Fokas (11), Fuchssteiner (12), Bruschi (5) and Jiang (20). We present the automata equivalents to these filters (33). Some of them belong to the class of filter automata introduced in (30). We also define and illustrate some properties of filtrons. Contrary to particles, the filtrons interact nonlocally in the sense that distant symbols may influence one another. Thus their interactions are very unusual. Some examples have been given in (32). Here we show new examples of filtron phenomena: multifiltron solitonic collisions, attracting and repelling filtrons, trapped bouncing filtrons (which behave like a resonance cavity) and quasi filtrons.

A system for the rapid detection of bacterial contamination in cell-based therapeutica

NASA Astrophysics Data System (ADS)

Bolwien, Carsten; Erhardt, Christian; Sulz, Gerd; Thielecke, Hagen; Johann, Robert; Pudlas, Marieke; Mertsching, Heike; Koch, Steffen

2010-02-01

Monitoring the sterility of cell or tissue cultures is of major concern, particularly in the fields of regenerative medicine and tissue engineering when implanting cells into the human body. Our sterility-control system is based on a Raman micro-spectrometer and is able to perform fast sterility testing on microliters of liquid samples. In conventional sterility control, samples are incubated for weeks to proliferate the contaminants to concentrations above the detection limit of conventional analysis. By contrast, our system filters particles from the liquid sample. The filter chip fabricated in microsystem technology comprises a silicon nitride membrane with millions of sub-micrometer holes to retain particles of critical sizes and is embedded in a microfluidic cell specially suited for concomitant microscopic observation. After filtration, identification is carried out on the single particle level: image processing detects possible contaminants and prepares them for Raman spectroscopic analysis. A custom-built Raman-spectrometer-attachment coupled to the commercial microscope uses 532nm or 785nm Raman excitation and records spectra up to 3400cm-1. In the final step, the recorded spectrum of a single particle is compared to an extensive library of GMP-relevant organisms, and classification is carried out based on a support vector machine.

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.

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.

Filterable redox cycling activity: a comparison between diesel exhaust particles and secondary organic aerosol constituents.

PubMed

McWhinney, Robert D; Badali, Kaitlin; Liggio, John; Li, Shao-Meng; Abbatt, Jonathan P D

2013-04-02

The redox activity of diesel exhaust particles (DEP) collected from a light-duty diesel passenger car engine was examined using the dithiothreitol (DTT) assay. DEP was highly redox-active, causing DTT to decay at a rate of 23-61 pmol min(-1) μg(-1) of particle used in the assay, which was an order of magnitude higher than ambient coarse and fine particulate matter (PM) collected from downtown Toronto. Only 2-11% of the redox activity was in the water-soluble portion, while the remainder occurred at the black carbon surface. This is in contrast to redox-active secondary organic aerosol constituents, in which upward of 90% of the activity occurs in the water-soluble fraction. The redox activity of DEP is not extractable by moderately polar (methanol) and nonpolar (dichloromethane) organic solvents, and is hypothesized to arise from redox-active moieties contiguous with the black carbon portion of the particles. These measurements illustrate that "Filterable Redox Cycling Activity" may therefore be useful to distinguish black carbon-based oxidative capacity from water-soluble organic-based activity. The difference in chemical environment leading to redox activity highlights the need to further examine the relationship between activity in the DTT assay and toxicology measurements across particles of different origins and composition.

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.

Ground-Based Aerosol Measurements | Science Inventory ...

EPA Pesticide Factsheets

Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomon et al. 2014) as well as in research studies. In this approach, air, at a specified flow rate and time period, is typically drawn through an inlet, usually a size selective inlet, and then drawn through filters, 1 INTRODUCTION Atmospheric particulate matter (PM) is a complex chemical mixture of liquid and solid particles suspended in air (Seinfeld and Pandis 2016). Measurements of this complex mixture form the basis of our knowledge regarding particle formation, source-receptor relationships, data to test and verify complex air quality models, and how PM impacts human health, visibility, global warming, and ecological systems (EPA 2009). Historically, PM samples have been collected on filters or other substrates with subsequent chemical analysis in the laboratory and this is still the major approach for routine networks (Chow 2005; Solomo

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.

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.

Sampling Artifacts from Conductive Silicone Tubing

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

Timko, Michael T.; Yu, Zhenhong; Kroll, Jesse

2009-05-15

We report evidence that carbon impregnated conductive silicone tubing used in aerosol sampling systems can introduce two types of experimental artifacts: 1) silicon tubing dynamically absorbs carbon dioxide gas, requiring greater than 5 minutes to reach equilibrium and 2) silicone tubing emits organic contaminants containing siloxane that adsorb onto particles traveling through it and onto downstream quartz fiber filters. The consequence can be substantial for engine exhaust measurements as both artifacts directly impact calculations of particulate mass-based emission indices. The emission of contaminants from the silicone tubing can result in overestimation of organic particle mass concentrations based on real-time aerosolmore » mass spectrometry and the off-line thermal analysis of quartz filters. The adsorption of siloxane contaminants can affect the surface properties of aerosol particles; we observed a marked reduction in the water-affinity of soot particles passed through conductive silicone tubing. These combined observations suggest that the silicone tubing artifacts may have wide consequence for the aerosol community and should, therefore, be used with caution. Gentle heating, physical and chemical properties of the particle carriers, exposure to solvents, and tubing age may influence siloxane uptake. The amount of contamination is expected to increase as the tubing surface area increases and as the particle surface area increases. The effect is observed at ambient temperature and enhanced by mild heating (<100 oC). Further evaluation is warranted.« less

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.

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.

H-SLAM: Rao-Blackwellized Particle Filter SLAM Using Hilbert Maps.

PubMed

Vallicrosa, Guillem; Ridao, Pere

2018-05-01

Occupancy Grid maps provide a probabilistic representation of space which is important for a variety of robotic applications like path planning and autonomous manipulation. In this paper, a SLAM (Simultaneous Localization and Mapping) framework capable of obtaining this representation online is presented. The H-SLAM (Hilbert Maps SLAM) is based on Hilbert Map representation and uses a Particle Filter to represent the robot state. Hilbert Maps offer a continuous probabilistic representation with a small memory footprint. We present a series of experimental results carried both in simulation and with real AUVs (Autonomous Underwater Vehicles). These results demonstrate that our approach is able to represent the environment more consistently while capable of running online.

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...

Impacts of Aging Emission Control Systems on In-Use Heavy-Duty Diesel Truck Emission Rates

NASA Astrophysics Data System (ADS)

Preble, C.; Cados, T.; Harley, R.; Kirchstetter, T.

2017-12-01

Heavy-duty diesel trucks are a major source of nitrogen oxides (NOx) and black carbon (BC) in urban environments, contributing to persistent ozone and particulate matter air quality problems. Recently, diesel particle filter (DPF) and selective catalytic reduction (SCR) emission control systems have become standard equipment on new trucks. Particle filters can also be installed as a retrofit on older engines. Prior work has shown that exhaust filters and SCR systems effectively reduce BC and NOx emission rates by up to 90 and 80%, respectively (Preble et al., ES&T 2015). There is concern, however, that DPFs may promote the formation of ultrafine particles (UFP) and increase tailpipe emissions of nitrogen dioxide (NO2). Additionally, urea-based SCR systems for NOx control may form nitrous oxide (N2O), an important contributor to stratospheric ozone depletion. The effectiveness of these emission controls has been thoroughly evaluated in the laboratory, but the long-term durability of in-use systems and their impacts on co-emitted species have not been well characterized. To evaluate the in-use performance of DPF and SCR systems, pollutant emissions from thousands of diesel trucks were measured over several years at the Port of Oakland and the Caldecott Tunnel in the San Francisco Bay Area. Pollutants present in the exhaust plumes of individual trucks were measured at high time resolution (≥1 Hz) as trucks passed under a mobile lab stationed on an overpass. Fuel-based emission factors (g pollutant emitted per kg fuel burned) were calculated for individual trucks and linked via recorded license plates to vehicle attributes, including engine model year and installed emission control systems. Use of DPFs reduced the BC emission rate by up to 95% at both locations. SCR systems were more effective at reducing NOx emissions under the uphill, highway driving conditions at the Caldecott Tunnel. The emission rates of co-emitted species NO2, UFP, and N2O depended on driving mode. Some DPFs on trucks with 2007-2009 model year engines showed deterioration or failure in filter performance, leading to higher BC emission rates compared to the average for trucks without filters. Emission inventories may underestimate total on-road emissions from diesel trucks, especially if particle filter failure rates continue to increase over time.

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.

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.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

PubMed

Huang, Lvwen; Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-08-23

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields.

Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor

PubMed Central

Chen, Siyuan; Zhang, Jianfeng; Cheng, Bang; Liu, Mingqing

2017-01-01

Object tracking is a crucial research subfield in computer vision and it has wide applications in navigation, robotics and military applications and so on. In this paper, the real-time visualization of 3D point clouds data based on the VLP-16 3D Light Detection and Ranging (LiDAR) sensor is achieved, and on the basis of preprocessing, fast ground segmentation, Euclidean clustering segmentation for outliers, View Feature Histogram (VFH) feature extraction, establishing object models and searching matching a moving spherical target, the Kalman filter and adaptive particle filter are used to estimate in real-time the position of a moving spherical target. The experimental results show that the Kalman filter has the advantages of high efficiency while adaptive particle filter has the advantages of high robustness and high precision when tested and validated on three kinds of scenes under the condition of target partial occlusion and interference, different moving speed and different trajectories. The research can be applied in the natural environment of fruit identification and tracking, robot navigation and control and other fields. PMID:28832520

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

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.

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.

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

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

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

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.

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.

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.

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.

Absorption Filter Based Optical Diagnostics in High Speed Flows

NASA Technical Reports Server (NTRS)

Samimy, Mo; Elliott, Gregory; Arnette, Stephen

1996-01-01

Two major regimes where laser light scattered by molecules or particles in a flow contains significant information about the flow are Mie scattering and Rayleigh scattering. Mie scattering is used to obtain only velocity information, while Rayleigh scattering can be used to measure both the velocity and the thermodynamic properties of the flow. Now, recently introduced (1990, 1991) absorption filter based diagnostic techniques have started a new era in flow visualization, simultaneous velocity and thermodynamic measurements, and planar velocity measurements. Using a filtered planar velocimetry (FPV) technique, we have modified the optically thick iodine filter profile of Miles, et al., and used it in the pressure-broaden regime which accommodates measurements in a wide range of velocity applications. Measuring velocity and thermodynamic properties simultaneously, using absorption filtered based Rayleigh scattering, involves not only the measurement of the Doppler shift, but also the spectral profile of the Rayleigh scattering signal. Using multiple observation angles, simultaneous measurement of one component velocity and thermodynamic properties in a supersonic jet were measured. Presently, the technique is being extended for simultaneous measurements of all three components of velocity and thermodynamic properties.

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.

Characterizing Dust from Cutting Corian®, a Solid-Surface Composite Material, in a Laboratory Testing System.

PubMed

Qi, Chaolong; Echt, Alan; Murata, Taichi K

2016-06-01

We conducted a laboratory test to characterize dust from cutting Corian(®), a solid-surface composite material, with a circular saw. Air samples were collected using filters and direct-reading instruments in an automatic laboratory testing system. The average mass concentrations of the total and respirable dusts from the filter samples were 4.78±0.01 and 1.52±0.01mg cm(-3), respectively, suggesting about 31.8% mass of the airborne dust from cutting Corian(®) is respirable. Analysis of the metal elements on the filter samples reveals that aluminum hydroxide is likely the dominant component of the airborne dust from cutting Corian(®), with the total airborne and respirable dusts containing 86.0±6.6 and 82.2±4.1% aluminum hydroxide, respectively. The results from the direct-reading instruments confirm that the airborne dust generated from cutting Corian(®) were mainly from the cutting process with very few particles released from the running circular saw alone. The number-based size distribution of the dusts from cutting Corian(®) had a peak for fine particles at 1.05 µm with an average total concentration of 871.9 particles cm(-3), and another peak for ultrafine particles at 11.8nm with an average total concentration of 1.19×10(6) particles cm(-3) The small size and high concentration of the ultrafine particles suggest additional investigation is needed to study their chemical composition and possible contribution to pulmonary effect. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2016.

Characterizing Dust from Cutting Corian®, a Solid-Surface Composite Material, in a Laboratory Testing System

PubMed Central

Qi, Chaolong; Echt, Alan; Murata, Taichi K

2016-01-01

We conducted a laboratory test to characterize dust from cutting Corian®, a solid-surface composite material, with a circular saw. Air samples were collected using filters and direct-reading instruments in an automatic laboratory testing system. The average mass concentrations of the total and respirable dusts from the filter samples were 4.78±0.01 and 1.52±0.01 mg cm−3, respectively, suggesting about 31.8% mass of the airborne dust from cutting Corian® is respirable. Analysis of the metal elements on the filter samples reveals that aluminum hydroxide is likely the dominant component of the airborne dust from cutting Corian®, with the total airborne and respirable dusts containing 86.0%±6.6% and 82.2%±4.1% aluminum hydroxide, respectively. The results from the direct-reading instruments confirm that the airborne dust generated from cutting Corian® were mainly from the cutting process with very few particles released from the running circular saw alone. The number-based size distribution of the dusts from cutting Corian® had a peak for fine particles at 1.05 µm with an average total concentration of 871.9 particles cm−3, and another peak for ultrafine particles at 11.8 nm with an average total concentration of 1.19×106 particles cm−3. The small size and high concentration of the ultrafine particles suggest additional investigation is needed to study their chemical composition and possible contribution to pulmonary effect. PMID:26872962

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.

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.

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.

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

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

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

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

Preparation of Fiber Based Binder Materials to Enhance the Gas Adsorption Efficiency of Carbon Air Filter.

PubMed

Lim, Tae Hwan; Choi, Jeong Rak; Lim, Dae Young; Lee, So Hee; Yeo, Sang Young

2015-10-01

Fiber binder adapted carbon air filter is prepared to increase gas adsorption efficiency and environmental stability. The filter prevents harmful gases, as well as particle dusts in the air from entering the body when a human inhales. The basic structure of carbon air filter is composed of spunbond/meltblown/activated carbon/bottom substrate. Activated carbons and meltblown layer are adapted to increase gas adsorption and dust filtration efficiency, respectively. Liquid type adhesive is used in the conventional carbon air filter as a binder material between activated carbons and other layers. However, it is thought that the liquid binder is not an ideal material with respect to its bonding strength and liquid flow behavior that reduce gas adsorption efficiency. To overcome these disadvantages, fiber type binder is introduced in our study. It is confirmed that fiber type binder adapted air filter media show higher strip strength, and their gas adsorption efficiencies are measured over 42% during 60 sec. These values are higher than those of conventional filter. Although the differential pressure of fiber binder adapted air filter is relatively high compared to the conventional one, short fibers have a good potential as a binder materials of activated carbon based air filter.

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

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

Cerati, Giuseppe; Elmer, Peter; Krutelyov, Slava

2017-01-01

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower-power, multi-core processors such as Graphical Processing Units (GPU), ARM CPUs, and Intel MICs. Broad-based efforts from manufacturers and developers have been devoted to making these processors user-friendly enough to perform general computations. However, extracting performance from a larger number of cores, as well as specialized vector or SIMD units, requires special care in algorithm design and code optimization. One of the most computationally challenging problems in high-energy particle experiments is finding and fitting the charged-particlemore » 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.« less

Particulate Hot Gas Stream Cleanup Technical Issues: Quarterly report, July 1-September 30, 1996

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

Pontius, D.H.

1996-12-09

This is the eighth in a series of quarterly reports describing the activities performed under Contract No. DE-AC21-94MC31160. Analyses of Hot Gas Stream Cleanup (HGCU) ashes and descriptions of filter performance address aspects of filter operation that are apparently linked to the characteristics of the collected ash or the performance of the ceramic barrier filter elements. Task 1 is designed to generate a data base of the key characteristics of ashes collected from operating advanced particle filters (APFS) and to relate these ash properties to the operation and performance of these filters. Task 2 concerns testing and failure analysis ofmore » ceramic filter elements. Under Task I during the past quarter, additional analyses were performed on ashes from the Ahlstrom 10 MWt Pressurized Fluidized Circulating Fluid Bed (PCFB) facility located at Karhula, Finland. Work continued on the HGCU data base being constructed in Microsoft Access. A variety of information has been entered into the data base, including numerical values, short or long text entries, and photographs. Detailed design of a bench top device for high temperature measurement of ash permeability has also begun. In addition to these activities, a paper was prepared and a poster was presented summarizing recent work performed under this contract at the 1996 DOE/METC Contractor`s Conference. A presentation was also given corresponding to the manuscript entitled Particle Characteristics and High-Temperature Filtration that was prepared for publication in the Proceedings of the Thirteenth Annual International Pittsburgh Coal Conference held this September in Pittsburgh, PA. Arrangements have been made to be present at the DOE/METC Modular Gas Cleanup Rig (MGCR) at the conclusion of the next run of the DOE/METC air blown Fluid Bed Gasifier (FBG). This visit will include on-site sampling to collect and characterize the filter cakes collected during FGB operation. Task 2 efforts during the past quarter focused on hoop tensile testing of Schumacher FT20 and Refractron 326 candle filter elements removed from the Karhula APF after 540 hours of service.« less

Filter feeding mechanics of Hypophthalmichthys molitrix regarding porous gill rakers

NASA Astrophysics Data System (ADS)

Palumbo, David; Bulusu, Kartik V.; Cohen, Karly; Hernandez, Particia; Leftwich, Megan C.; Plesniak, Michael W.

2017-11-01

The silver carp (Hypophthalmichthys molitrix) is a filter-feeding fish known to feed upon algal-growth in lakes, rivers, and aquacultures. The filter-feeding process centers on sponge-like membranes located in the carp's pharynx supported by fused gill rakers (GRs), which can efficiently strain suspended food particles as small as 4 µm without clogging. Guided by the anatomy of the silver carp, scanning electron microscope (SEM) images of GRs, and video of the silver carp feeding, we have hypothesized that the filtration mechanism involves a pump-based biological function to capture food particles within the GRs. Dye visualization experiments were performed on a silver carp cadaver head, an excised GR sample, and on a scaled GR in vitro model - the Artificial Gill Raker (AGR). Measurements are performed for the AGR using laser Doppler velocimetry (LDV) and penetration pressure monitoring with a biologically-inspired pumping mechanism. The role of mucus in the retention and capture of food particles has also been explored through rheological measurements, and further experimentation is planned. Our motivation stems from the potential to develop bioinspired industrial-scale filtration technologies ranging from wastewater treatment to filtration in the food industry. supported by GW Center for Biomimetics and Bioinspired Engineering.

E-Textile Embroidered Metamaterial Transmission Line for Signal Propagation Control.

PubMed

Moradi, Bahareh; Fernández-García, Raul; Gil, Ignacio

2018-06-05

In this paper, the utilization of common fabrics for the manufacturing of e-textile metamaterial transmission lines is investigated. In order to filter and control the signal propagation in the ultra-high frequency (UHF) range along the e-textile, a conventional metamaterial transmission line was compared with embroidered metamaterial particles. The proposed design was based on a transmission line loaded with one or several split-ring resonators (SRR) on a felt substrate. To explore the relations between physical parameters and filter performance characteristics, theoretical models based on transmission matrices' description of the filter constituent components were proposed. Excellent agreement between theoretical prediction, electromagnetic simulations, and measurement were found. Experimental results showed stop-band levels higher than -30 dB for compact embroidered metamaterial e-textiles. The validated results confirmed embroidery as a useful technique to obtain customized electromagnetic properties, such as filtering, on wearable applications.

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.

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.

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.

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.

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.

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.

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.

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.

Novel Optical Diagnostic Techniques for Studying Particle Deposition Upon Large Cylinders in a Sheared Suspension

NASA Technical Reports Server (NTRS)

Yoda, M.; Bailey, B. C.

2000-01-01

On a twelve-month voyage to Mars, one astronaut will require at least two tons of potable water and two tons of pure oxygen. Efficient, reliable fluid reclamation is therefore necessary for manned space exploration. Space habitats require a compact, flexible, and robust apparatus capable of solid-fluid mechanical separation over a wide range of fluid and particle densities and particle sizes. In space, centrifugal filtration, where particles suspended in fluid are captured by rotating fixed-fiber mat filters, is a logical candidate for mechanical separation. Non-colloidal particles are deposited on the fibers due to inertial impaction or direct interception. Since rotation rates are easily adjustable, inertial effects are the most practical way to control separation rates for a wide variety of multiphase mixtures in variable gravity environments. Understanding how fluid inertia and differential fluid-particle inertia, characterized by the Reynolds and Stokes numbers, respectively, affect deposition is critical in optimizing filtration in a microgravity environment. This work will develop non-intrusive optical diagnostic techniques for directly visualizing where and when non-colloidal particles deposit upon, or contact, solid surfaces: 'particle proximity sensors'. To model particle deposition upon a single filter fiber, these sensors will be used in ground-based experiments to study particle dynamics as in the vicinity of a large (compared with the particles) cylinder in a simply sheared (i.e., linearly-varying, zero-mean velocity profile) neutrally-buoyant, refractive-index matched solid-liquid suspension.

Particle Filter-Based Recursive Data Fusion With Sensor Indexing for Large Core Neutron Flux Estimation

NASA Astrophysics Data System (ADS)

Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

2017-06-01

We introduce a sequential importance sampling particle filter (PF)-based multisensor multivariate nonlinear estimator for estimating the in-core neutron flux distribution for pressurized heavy water reactor core. Many critical applications such as reactor protection and control rely upon neutron flux information, and thus their reliability is of utmost importance. The point kinetic model based on neutron transport conveniently explains the dynamics of nuclear reactor. The neutron flux in the large core loosely coupled reactor is sensed by multiple sensors measuring point fluxes located at various locations inside the reactor core. The flux values are coupled to each other through diffusion equation. The coupling facilitates redundancy in the information. It is shown that multiple independent data about the localized flux can be fused together to enhance the estimation accuracy to a great extent. We also propose the sensor anomaly handling feature in multisensor PF to maintain the estimation process even when the sensor is faulty or generates data anomaly.

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

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.

An autoregressive model-based particle filtering algorithms for extraction of respiratory rates as high as 90 breaths per minute from pulse oximeter.

PubMed

Lee, Jinseok; Chon, Ki H

2010-09-01

We present particle filtering (PF) algorithms for an accurate respiratory rate extraction from pulse oximeter recordings over a broad range: 12-90 breaths/min. These methods are based on an autoregressive (AR) model, where the aim is to find the pole angle with the highest magnitude as it corresponds to the respiratory rate. However, when SNR is low, the pole angle with the highest magnitude may not always lead to accurate estimation of the respiratory rate. To circumvent this limitation, we propose a probabilistic approach, using a sequential Monte Carlo method, named PF, which is combined with the optimal parameter search (OPS) criterion for an accurate AR model-based respiratory rate extraction. The PF technique has been widely adopted in many tracking applications, especially for nonlinear and/or non-Gaussian problems. We examine the performances of five different likelihood functions of the PF algorithm: the strongest neighbor, nearest neighbor (NN), weighted nearest neighbor (WNN), probability data association (PDA), and weighted probability data association (WPDA). The performance of these five combined OPS-PF algorithms was measured against a solely OPS-based AR algorithm for respiratory rate extraction from pulse oximeter recordings. The pulse oximeter data were collected from 33 healthy subjects with breathing rates ranging from 12 to 90 breaths/ min. It was found that significant improvement in accuracy can be achieved by employing particle filters, and that the combined OPS-PF employing either the NN or WNN likelihood function achieved the best results for all respiratory rates considered in this paper. The main advantage of the combined OPS-PF with either the NN or WNN likelihood function is that for the first time, respiratory rates as high as 90 breaths/min can be accurately extracted from pulse oximeter recordings.

Continuous-Flow Detector for Rapid Pathogen Identification

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

Barrett, Louise M.; Skulan, Andrew J.; Singh, Anup K.

2006-09-01

This report describes the continued development of a low-power, portable detector for the rapid identification of pathogens such as B. anthracis and smallpox. Based on our successful demonstration of the continuous filter/concentrator inlet, we believe strongly that the inlet section will enable differentiation between viable and non-viable populations, between types of cells, and between pathogens and background contamination. Selective, continuous focusing of particles in a microstream enables highly selective and sensitive identification using fluorescently labeled antibodies and other receptors such as peptides, aptamers, or small ligands to minimize false positives. Processes such as mixing and lysing will also benefit frommore » the highly localized particle streams. The concentrator is based on faceted prisms to contract microfluidic flows while maintaining uniform flowfields. The resulting interfaces, capable of high throughput, serve as high-, low-, and band-pass filters to direct selected bioparticles to a rapid, affinity-based detection system. The proposed device is superior to existing array-based detectors as antibody-pathogen binding can be accomplished in seconds rather than tens of minutes or even hours. The system is being designed to interface with aerosol collectors under development by the National Laboratories or commercial systems. The focused stream is designed to be interrogated using diode lasers to differentiate pathogens by light scattering. Identification of particles is done using fluorescently labeled antibodies to tag the particles, followed by multiplexed laser-induced fluorescence (LIF) detection (achieved by labeling each antibody with a different dye).« less

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.

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.

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).

SAMPLING AND ANALYSIS OF SEMIVOLATILE AEROSOLS

EPA Science Inventory

Denuder based samplers can effectively separate semivolatile gases from particles and 'freeze' the partitioning in time. Conversely, samples collected on filters partition mass according to the conditions of the influent airstream, which may change over time. As a result thes...

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

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.

Adaptive Resampling Particle Filters for GPS Carrier-Phase Navigation and Collision Avoidance System

NASA Astrophysics Data System (ADS)

Hwang, Soon Sik

This dissertation addresses three problems: 1) adaptive resampling technique (ART) for Particle Filters, 2) precise relative positioning using Global Positioning System (GPS) Carrier-Phase (CP) measurements applied to nonlinear integer resolution problem for GPS CP navigation using Particle Filters, and 3) collision detection system based on GPS CP broadcasts. First, Monte Carlo filters, called Particle Filters (PF), are widely used where the system is non-linear and non-Gaussian. In real-time applications, their estimation accuracies and efficiencies are significantly affected by the number of particles and the scheduling of relocating weights and samples, the so-called resampling step. In this dissertation, the appropriate number of particles is estimated adaptively such that the error of the sample mean and variance stay in bounds. These bounds are given by the confidence interval of a normal probability distribution for a multi-variate state. Two required number of samples maintaining the mean and variance error within the bounds are derived. The time of resampling is determined when the required sample number for the variance error crosses the required sample number for the mean error. Second, the PF using GPS CP measurements with adaptive resampling is applied to precise relative navigation between two GPS antennas. In order to make use of CP measurements for navigation, the unknown number of cycles between GPS antennas, the so called integer ambiguity, should be resolved. The PF is applied to this integer ambiguity resolution problem where the relative navigation states estimation involves nonlinear observations and nonlinear dynamics equation. Using the PF, the probability density function of the states is estimated by sampling from the position and velocity space and the integer ambiguities are resolved without using the usual hypothesis tests to search for the integer ambiguity. The ART manages the number of position samples and the frequency of the resampling step for real-time kinematics GPS navigation. The experimental results demonstrate the performance of the ART and the insensitivity of the proposed approach to GPS CP cycle-slips. Third, the GPS has great potential for the development of new collision avoidance systems and is being considered for the next generation Traffic alert and Collision Avoidance System (TCAS). The current TCAS equipment, is capable of broadcasting GPS code information to nearby airplanes, and also, the collision avoidance system using the navigation information based on GPS code has been studied by researchers. In this dissertation, the aircraft collision detection system using GPS CP information is addressed. The PF with position samples is employed for the CP based relative position estimation problem and the same algorithm can be used to determine the vehicle attitude if multiple GPS antennas are used. For a reliable and enhanced collision avoidance system, three dimensional trajectories are projected using the estimates of the relative position, velocity, and the attitude. It is shown that the performance of GPS CP based collision detecting algorithm meets the accuracy requirements for a precise approach of flight for auto landing with significantly less unnecessary collision false alarms and no miss alarms.

Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network

NASA Astrophysics Data System (ADS)

He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang

2017-03-01

Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.

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.

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.

Model-Based Fatigue Prognosis of Fiber-Reinforced Laminates Exhibiting Concurrent Damage Mechanisms

NASA Technical Reports Server (NTRS)

Corbetta, M.; Sbarufatti, C.; Saxena, A.; Giglio, M.; Goebel, K.

2016-01-01

Prognostics of large composite structures is a topic of increasing interest in the field of structural health monitoring for aerospace, civil, and mechanical systems. Along with recent advancements in real-time structural health data acquisition and processing for damage detection and characterization, model-based stochastic methods for life prediction are showing promising results in the literature. Among various model-based approaches, particle-filtering algorithms are particularly capable in coping with uncertainties associated with the process. These include uncertainties about information on the damage extent and the inherent uncertainties of the damage propagation process. Some efforts have shown successful applications of particle filtering-based frameworks for predicting the matrix crack evolution and structural stiffness degradation caused by repetitive fatigue loads. Effects of other damage modes such as delamination, however, are not incorporated in these works. It is well established that delamination and matrix cracks not only co-exist in most laminate structures during the fatigue degradation process but also affect each other's progression. Furthermore, delamination significantly alters the stress-state in the laminates and accelerates the material degradation leading to catastrophic failure. Therefore, the work presented herein proposes a particle filtering-based framework for predicting a structure's remaining useful life with consideration of multiple co-existing damage-mechanisms. The framework uses an energy-based model from the composite modeling literature. The multiple damage-mode model has been shown to suitably estimate the energy release rate of cross-ply laminates as affected by matrix cracks and delamination modes. The model is also able to estimate the reduction in stiffness of the damaged laminate. This information is then used in the algorithms for life prediction capabilities. First, a brief summary of the energy-based damage model is provided. Then, the paper describes how the model is embedded within the prognostic framework and how the prognostics performance is assessed using observations from run-to-failure experiments

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

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.

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.

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.

Multi-object tracking of human spermatozoa

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; Østergaard, Jakob; Johansen, Peter; de Bruijne, Marleen

2008-03-01

We propose a system for tracking of human spermatozoa in phase-contrast microscopy image sequences. One of the main aims of a computer-aided sperm analysis (CASA) system is to automatically assess sperm quality based on spermatozoa motility variables. In our case, the problem of assessing sperm quality is cast as a multi-object tracking problem, where the objects being tracked are the spermatozoa. The system combines a particle filter and Kalman filters for robust motion estimation of the spermatozoa tracks. Further, the combinatorial aspect of assigning observations to labels in the particle filter is formulated as a linear assignment problem solved using the Hungarian algorithm on a rectangular cost matrix, making the algorithm capable of handling missing or spurious observations. The costs are calculated using hidden Markov models that express the plausibility of an observation being the next position in the track history of the particle labels. Observations are extracted using a scale-space blob detector utilizing the fact that the spermatozoa appear as bright blobs in a phase-contrast microscope. The output of the system is the complete motion track of each of the spermatozoa. Based on these tracks, different CASA motility variables can be computed, for example curvilinear velocity or straight-line velocity. The performance of the system is tested on three different phase-contrast image sequences of varying complexity, both by visual inspection of the estimated spermatozoa tracks and by measuring the mean squared error (MSE) between the estimated spermatozoa tracks and manually annotated tracks, showing good agreement.

Reconstructing East African rainfall and Indian Ocean sea surface temperatures over the last centuries using data assimilation

NASA Astrophysics Data System (ADS)

Klein, François; Goosse, Hugues

2018-06-01

The relationship between the East African rainfall and Indian Ocean sea-surface temperatures (SSTs) is well established. The potential interest of this covariance to improve reconstructions of both variables over the last centuries is examined here. This is achieved through an off-line method of data assimilation based on a particle filter, using hydroclimate-related records at four East African sites (Lake Naivasha, Lake Challa, Lake Malawi and Lake Masoko) and SSTs-related records at six oceanic sites spread over the Indian Ocean to constrain the Last Millennium Ensemble of simulations performed by CESM1. Skillful reconstructions of the Indian SSTs and East African rainfall can be obtained based on the assimilation of only one of these variables, when assimilating pseudo-proxy data deduced from the model CESM1. The skill of these reconstructions increases with the number of particles selected in the particle filter, although the improvement becomes modest beyond 99 particles. When considering a more realistic framework, the skill of the reconstructions is strongly deteriorated because of the model biases and the uncertainties of the real proxy-based reconstructions. However, it is still possible to obtain a skillful reconstruction of SSTs over most of the Indian Ocean only based on the assimilation of the six SST-related proxy records selected, as far as a local calibration is applied at all individual sites. This underlines once more the critical role of an adequate integration of the signal inferred from proxy records into the climate models for reconstructions based on data assimilation.

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.

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

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.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

NASA Astrophysics Data System (ADS)

Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

2017-02-01

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

A personal sampler for aircraft engine cold start particles: laboratory development and testing.

PubMed

Armendariz, Alfredo; Leith, David

2003-01-01

Industrial hygienists in the U.S. Air Force are concerned about exposure of their personnel to jet fuel. One potential source of exposure for flightline ground crews is the plume emitted during the start of aircraft engines in extremely cold weather. The purpose of this study was to investigate a personal sampler, a small tube-and-wire electrostatic precipitator (ESP), for assessing exposure to aircraft engine cold start particles. Tests were performed in the laboratory to characterize the sampler's collection efficiency and to determine the magnitude of adsorption and evaporation artifacts. A low-temperature chamber was developed for the artifact experiments so tests could be performed at temperatures similar to actual field conditions. The ESP collected particles from 0.5 to 20 micro m diameter with greater than 98% efficiency at particle concentrations up to 100 mg/m(3). Adsorption artifacts were less than 5 micro g/m(3) when sampling a high concentration vapor stream. Evaporation artifacts were significantly lower for the ESP than for PVC membrane filters across a range of sampling times and incoming vapor concentrations. These tests indicate that the ESP provides more accurate exposure assessment results than traditional filter-based particle samplers when sampling cold start particles produced by an aircraft engine.

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.

Ice nucleating particles in the high Arctic at the beginning of the melt season

NASA Astrophysics Data System (ADS)

Hartmann, M.; Gong, X.; Van Pinxteren, M.; Welti, A.; Zeppenfeld, S.; Herrmann, H.; Stratmann, F.

2017-12-01

Ice nucleating particles (INPs) initiate the ice crystal formation in persistent Arctic mixed-phase clouds and are important for the formation of precipitation, which affects the radiative properties of the Arctic pack ice as well as the radiative properties of clouds. Sources of Arctic INP have been suggested to be local emissions from the marine boundary and long-range transport. To what extent local marine sources contribute to the INP population or if the majority of INPs originate from long-range transport is not yet known. Ship-based INP measurements in the PASCAL framework are reported. The field campaign took place from May 24 to July 20 2017 around and north of Svalbard (up to 84°N, between 0° and 35°E) onboard the RV Polarstern. INP concentrations were determined applying in-situ measurements (DMT Spectrometer for Ice Nuclei, SPIN) and offline filter techniques (filter sampling on both quartz fiber and polycarbonate filters with subsequent analysis of filter pieces and water suspension from particles collected on filters by means of immersion freezing experiments on cold stage setups). Additionally the compartments sea-surface micro layer (SML), bulk sea water, snow, sea ice and fog water were sampled and their ice nucleation potential quantified, also utilizing cold stages. The measurements yield comprehensive picture of the spatial and temporal distribution of INPs around Svalbard for the different compartments. The dependence of the INP concentration on meteorological conditions (e.g. wind speed) and the geographical situation (sea ice cover, distance to the ice edge) are investigated. Potential sources of INP are identified by the comparison of INP concentrations in the compartments and by back trajectory analysis.

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

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

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.

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.

Quantum neural network-based EEG filtering for a brain-computer interface.

PubMed

Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

2014-02-01

A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

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.

Spin Filtering in Storage Rings

NASA Astrophysics Data System (ADS)

Nikolaev, N. N.; Pavlov, F. F.

The spin filtering in storage rings is based on a multiple passage of a stored beam through a polarized internal gas target. Apart from the polarization by the spin-dependent transmission, a unique geometrical feature of interaction with the target in such a filtering process, pointed out by H.O. Meyer,1 is a scattering of stored particles within the beam. A rotation of the spin in the scattering process affects the polarization buildup. We derive here a quantum-mechanical evolution equation for the spin-density matrix of a stored beam which incorporates the scattering within the beam. We show how the interplay of the transmission and scattering within the beam changes from polarized electrons to polarized protons in the atomic target. After discussions of the FILTEX results on the filtering of stored protons,2 we comment on the strategy of spin filtering of antiprotons for the PAX experiment at GSI FAIR.3.

Removal of xenotropic murine leukemia virus by nanocellulose based filter paper.

PubMed

Asper, M; Hanrieder, T; Quellmalz, A; Mihranyan, A

2015-11-01

The removal of xenotrpic murine leukemia virus (xMuLV) by size-exclusion filter paper composed of 100% naturally derived cellulose was validated. The filter paper was produced using cellulose nanofibers derived from Cladophora sp. algae. The filter paper was characterized using atomic force microscopy, scanning electron microscopy, helium pycnometry, and model tracer (100 nm latex beads and 50 nm gold nanoparticles) retention tests. Following the filtration of xMuLV spiked solutions, LRV ≥5.25 log10 TCID50 was observed, as limited by the virus titre in the feed solution and sensitivity of the tissue infectivity test. The results of the validation study suggest that the nanocellulose filter paper is useful for removal of endogenous rodent retroviruses and retrovirus-like particles during the production of recombinant proteins. Copyright © 2015 The International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

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.

Synthesis of Carbonate-Based Micro/Nanoscale Particles With Controlled Morphology and Mineralogy

DTIC Science & Technology

2013-04-01

patterns were obtained using a Panalytical X’Pert Pro diffractometer using iron-filtered cobalt radiation, and analyzed using Panalytical X’Pert...develop composites by hydrothermal recrystallization of metastable phases. 15. SUBJECT TERMS Aragonite Calcite Calcium carbonate Dopant Mineralogy

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...

Application of Pulsed Electrical Fields for Advanced Cooling and Water Recovery in Coal-Fired Power Plant

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

Young Cho; Alexander Fridman

2009-04-02

The overall objective of the present work was to develop technologies to reduce freshwater consumption in a cooling tower of coal-based power plant so that one could significantly reduce the need of make-up water. The specific goal was to develop a scale prevention technology based an integrated system of physical water treatment (PWT) and a novel filtration method so that one could reduce the need for the water blowdown, which accounts approximately 30% of water loss in a cooling tower. The present study investigated if a pulsed spark discharge in water could be used to remove deposits from the filtermore » membrane. The test setup included a circulating water loop and a pulsed power system. The present experiments used artificially hardened water with hardness of 1,000 mg/L of CaCO{sub 3} made from a mixture of calcium chloride (CaCl{sub 2}) and sodium carbonate (Na{sub 2}CO{sub 3}) in order to produce calcium carbonate deposits on the filter membrane. Spark discharge in water was found to produce strong shockwaves in water, and the efficiency of the spark discharge in cleaning filter surface was evaluated by measuring the pressure drop across the filter over time. Results showed that the pressure drop could be reduced to the value corresponding to the initial clean state and after that the filter could be maintained at the initial state almost indefinitely, confirming the validity of the present concept of pulsed spark discharge in water to clean dirty filter. The present study also investigated the effect of a plasma-assisted self-cleaning filter on the performance of physical water treatment (PWT) solenoid coil for the mitigation of mineral fouling in a concentric counterflow heat exchanger. The self-cleaning filter utilized shockwaves produced by pulse-spark discharges in water to continuously remove scale deposits from the surface of the filter, thus keeping the pressure drop across the filter at a relatively low value. Artificial hard water was used in the present fouling experiments for three different cases: no treatment, PWT coil only, and PWT coil plus self-cleaning filter. Fouling resistances decreased by 59-72% for the combined case of PWT coil plus filter compared with the values for no-treatment cases. SEM photographs showed much smaller particle sizes for the combined case of PWT coil plus filter as larger particles were continuously removed from circulating water by the filter. The x-ray diffraction data showed calcite crystal structures for all three cases.« less

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

Detection and tracking of a moving target using SAR images with the particle filter-based track-before-detect algorithm.

PubMed

Gao, Han; Li, Jingwen

2014-06-19

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.

Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

PubMed Central

Gao, Han; Li, Jingwen

2014-01-01

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB. PMID:24949640

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...

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.

An ultra-compact rejection filter based on spoof surface plasmon polaritons.

PubMed

Zhao, Shumin; Zhang, Hao Chi; Zhao, Jiahao; Tang, Wen Xuan

2017-09-05

In this paper, we propose a scheme to construct a new type of ultra-compact rejection filter by loading split-ring resonators (SRRs) on the transmission line of spoof surface plasmon polaritons (SPPs). From the dispersion analysis of the spoof SPP transmission line with and without the SRR loading, we clearly reveal the mechanism of the rejection characteristic for this compact filter. Meanwhile, we fabricate two spoof SPPs waveguides loaded with different amounts of metamaterials particles, and experimentally test them using an Agilent Vector Network Analyzer (VNA) and a homemade near-field scanning system. Both the simulated and measured results agree well with our theoretical analysis and demonstrate the excellent filtering characteristics of our design. The isolation of both filters can be less than -20 dB, and even reach -40 dB at rejection frequencies. The proposed rejection and stop-band filters show important potentials to develop integrated plasmonic functional devices and circuits at microwave and terahertz frequencies.

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

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.

NASA Tech Briefs, February 2014

NASA Technical Reports Server (NTRS)

2014-01-01

Topics include: JWST Integrated Simulation and Test (JIST) Core; Software for Non-Contact Measurement of an Individual's Heart Rate Using a Common Camera; Rapid Infrared Pixel Grating Response Testbed; Temperature Measurement and Stabilization in a Birefringent Whispering Gallery Resonator; JWST IV and V Simulation and Test (JIST) Solid State Recorder (SSR) Simulator; Development of a Precision Thermal Doubler for Deep Space; Improving Friction Stir Welds Using Laser Peening; Methodology of Evaluating Margins of Safety in Critical Brazed Joints; Interactive Inventory Monitoring; Sensor for Spatial Detection of Single-Event Effects in Semiconductor-Based Electronics; Reworked CCGA-624 Interconnect Package Reliability for Extreme Thermal Environments; Current-Controlled Output Driver for Directly Coupled Loads; Bulk Metallic Glasses and Matrix Composites as Spacecraft Shielding; Touch Temperature Coating for Electrical Equipment on Spacecraft; Li-Ion Electrolytes Containing Flame-Retardant Additives; Autonomous Robotic Manipulation (ARM); CARVE Log; Platform Perspective Toolkit; Convex Hull-Based Plume and Anomaly Detection; Pre-Filtration of GOSAT Data Using Only Level 1 Data and an Intelligent Filter to Remove Low Clouds; Affordability Comparison Tool - ACT; "Ascent - Commemorating Shuttle" for iPad; Cassini Mission App; Light-Weight Workflow Engine: A Server for Executing Generic Workflows; Model for System Engineering of the CheMin Instrument; Timeline Central Concepts; Parallel Particle Filter Toolkit; Particle Filter Simulation and Analysis Enabling Non-Traditional Navigation; Quasi-Terminator Orbits for Mapping Small Primitive Bodies; The Subgrid-Scale Scalar Variance Under Supercritical Pressure Conditions; Sliding Gait for ATHLETE Mobility; and Automated Generation of Adaptive Filter Using a Genetic Algorithm and Cyclic Rule Reduction.

Importance of nanoparticles and colloids from volcanic ash for riverine transport of trace elements to the ocean: evidence from glacial-fed rivers after the 2010 eruption of Eyjafjallajökull Volcano, Iceland.

PubMed

Tepe, Nathalie; Bau, Michael

2014-08-01

Volcanic ashes are often referenced as examples for natural nanoparticles, yet the particle size distribution <1000 nm is only rarely documented. We here report results of a geochemical study of glacial-fed rivers, glacial surface runoff, glacial base flow, and pure glacial meltwater from southern Iceland, that had been sampled 25 days after the explosive eruptions at Eyjafjallajökull in 2010. In addition to the dissolved concentrations of rare earth elements (REE), Zr, Hf, Nb, and Th in the 450 nm-filtered waters, we also studied the respective filter residues (river particulates >450 nm) and volcanic ash. In spite of the low solubilities and high particle-reactivities of the elements studied, most water samples show high dissolved concentrations, such as up to 971 ng/kg of Ce and 501 ng/kg of Zr. Except for the pure glacial meltwater and glacial base flow, all waters display the same shale-normalized REE patterns with pronounced light and heavy REE depletion and positive Eu anomalies. While such patterns are unusual for river waters, they are similar to those of the respective river particulates and the volcanic ash, though at different concentration levels. The distribution of dissolved Zr, Hf, Nb, and Th in the waters also matches that of filter residues and ash. This strongly suggests that in all 450 nm-filtered river waters, the elements studied are associated with solid ash particles smaller than 450 nm. This reveals that volcanic ash-derived nanoparticles and colloids are present in these glacial-fed rivers and that such ultrafine particles control the trace element distribution in the surface runoff. Subsequent to explosive volcanic eruptions, these waters provide terrigenous input from landmasses to estuaries, that is characterized by a unique trace element signature and that subsequent to modification by estuarine processes delivers a pulse of nutrients to coastal seawater in regions not affected by plume fall-out. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Zhu Zhaohuan; Dong Ruobing; Nelson, Richard P.

By carrying out two-dimensional two-fluid global simulations, we have studied the response of dust to gap formation by a single planet in the gaseous component of a protoplanetary disk-the so-called dust filtration mechanism. We have found that a gap opened by a giant planet at 20 AU in an {alpha} = 0.01, M-dot =10{sup -8} M{sub Sun} yr{sup -1} disk can effectively stop dust particles larger than 0.1 mm drifting inward, leaving a submillimeter (submm) dust cavity/hole. However, smaller particles are difficult to filter by a gap induced by a several M{sub J} planet due to (1) dust diffusion andmore » (2) a high gas accretion velocity at the gap edge. Based on these simulations, an analytic model is derived to understand what size particles can be filtered by the planet-induced gap edge. We show that a dimensionless parameter T{sub s} /{alpha}, which is the ratio between the dimensionless dust stopping time and the disk viscosity parameter, is important for the dust filtration process. Finally, with our updated understanding of dust filtration, we have computed Monte Carlo radiative transfer models with variable dust size distributions to generate the spectral energy distributions of disks with gaps. By comparing with transitional disk observations (e.g., GM Aur), we have found that dust filtration alone has difficulties depleting small particles sufficiently to explain the near-IR deficit of moderate M-dot transitional disks, except under some extreme circumstances. The scenario of gap opening by multiple planets studied previously suffers the same difficulty. One possible solution is to invoke both dust filtration and dust growth in the inner disk. In this scenario, a planet-induced gap filters large dust particles in the disk, and the remaining small dust particles passing to the inner disk can grow efficiently without replenishment from fragmentation of large grains. Predictions for ALMA have also been made based on all these scenarios. We conclude that dust filtration with planet(s) in the disk is a promising mechanism to explain submm observations of transitional disks but it may need to be combined with other processes (e.g., dust growth) to explain the near-IR deficit of some systems.« less

GPU Accelerated DG-FDF Large Eddy Simulator

NASA Astrophysics Data System (ADS)

Inkarbekov, Medet; Aitzhan, Aidyn; Sammak, Shervin; Givi, Peyman; Kaltayev, Aidarkhan

2017-11-01

A GPU accelerated simulator is developed and implemented for large eddy simulation (LES) of turbulent flows. The filtered density function (FDF) is utilized for modeling of the subgrid scale quantities. The filtered transport equations are solved via a discontinuous Galerkin (DG) and the FDF is simulated via particle based Lagrangian Monte-Carlo (MC) method. It is demonstrated that the GPUs simulations are of the order of 100 times faster than the CPU-based calculations. This brings LES of turbulent flows to a new level, facilitating efficient simulation of more complex problems. The work at Al-Faraby Kazakh National University is sponsored by MoES of RK under Grant 3298/GF-4.

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.

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.

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.

Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter.

PubMed

Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V

2015-04-30

In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.

Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter

PubMed Central

Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V.

2015-01-01

In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time. PMID:25942641

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system.

PubMed

Sun, Kangfeng; Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai; Yang, Shichun

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small.

The deposition of gold nanoparticles in MWCNT forests

NASA Astrophysics Data System (ADS)

de Jong, Franciscus; Buffet, Adeline; Schlueter, Michael

2015-11-01

The deposition, i.e. transport and attachment, of small-sized particles is a basic process, on which many applications are based. The innumerable applications range from biology and medicine to engineering. Due to their promising mechanical properties multi-walled carbon nanotubes (MWCNTs) have gained increasing popularity in the past decade. A large number of dense packed vertically aligned MWCNTs form a so-called MWCNT forest. In our study we functionalized the MWCNT forest to filter gold nanoparticles from a colloidal suspension. An experimental investigation was carried out in which the particle deposition kinetics was locally determined with small-angle X-ray scattering (SAXS). Furthermore, inductively coupled plasma atomic emission spectroscopy (ICP-AES) was used to verify the local observations. It was concluded that both, SAXS and ICP-AES investigations shows very good agreement. Furthermore, an analytical deposition model was developed based on the DLVO-theory. The experimental and theoretical investigation presented here give insight in the deposition kinetics within a MWCNT forest. The results open up pathways to optimize MWCNT forests for filtering purposes.

A particle filter for ammonia coverage ratio and input simultaneous estimations in Diesel-engine SCR system

PubMed Central

Ji, Fenzhu; Yan, Xiaoyu; Jiang, Kai

2018-01-01

As NOx emissions legislation for Diesel-engines is becoming more stringent than ever before, an aftertreatment system has been widely used in many countries. Specifically, to reduce the NOx emissions, a selective catalytic reduction(SCR) system has become one of the most promising techniques for Diesel-engine vehicle applications. In the SCR system, input ammonia concentration and ammonia coverage ratio are regarded as essential states in the control-oriental model. Currently, an ammonia sensor placed before the SCR Can is a good strategy for the input ammonia concentration value. However, physical sensor would increase the SCR system cost and the ammonia coverage ratio information cannot be directly measured by physical sensor. Aiming to tackle this problem, an observer based on particle filter(PF) is investigated to estimate the input ammonia concentration and ammonia coverage ratio. Simulation results through the experimentally-validated full vehicle simulator cX-Emission show that the performance of observer based on PF is outstanding, and the estimation error is very small. PMID:29408924

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.

Removal of nano and microparticles by granular filter media coated with nanoporous aluminium oxide.

PubMed

Lau, B L T; Harrington, G W; Anderson, M A; Tejedor, I

2004-01-01

Conventional filtration was designed to achieve high levels of particle and pathogen removal. Previous studies have examined the possibility of modifying filtration media to improve their ability to remove microorganisms and viruses. Although these studies have evaluated filter media coatings for this purpose, none have evaluated nanoscale particle suspensions as coating materials. The overall goal of this paper is to describe the preliminary test results of nanoporous aluminium oxide coated media that can be used to enhance filtration of nano and microparticles. Filtration tests were carried out using columns packed with uncoated and coated forms of granular anthracite or granular activated carbon. A positive correlation between isoelectric pH of filter media and particle removal was observed. The modified filter media with a higher isoelectric pH facilitated better removal of bacteriophage MS2 and 3 microm latex microspheres, possibly due to increased favorable electrostatic interactions.

Heating without heat: Thermodynamics of passive energy filters between finite systems

NASA Astrophysics Data System (ADS)

Muñoz-Tapia, R.; Brito, R.; Parrondo, J. M. R.

2017-09-01

Passive filters allowing the exchange of particles in a narrow band of energy are currently used in microrefrigerators and energy transducers. In this Rapid Communication, we analyze their thermal properties using linear irreversible thermodynamics and kinetic theory, and discuss a striking phenomenon: the possibility of simultaneously increasing or decreasing the temperatures of two systems without any supply of energy. This occurs when the filter induces a flow of particles whose energy is between the average energies of the two systems. Here we show that this selective transfer of particles does not need the action of any sort of Maxwell demon and can be carried out by passive filters without compromising the second law of thermodynamics. This phenomenon allows us to design cycles between two reservoirs at temperatures T1

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.

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.

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.

PARTICLE REMOVAL AND HEAD LOSS DEVELOPMENT IN BIOLOGICAL FILTERS

EPA Science Inventory

The physical performance of granular media filters was studied under pre-chlorinated, backwash-chlorinated, and nonchlorinated conditions. Overall, biological filteration produced a high-quality water. Although effluent turbidities showed littleer difference between the perform...

Penetration of Fiber Versus Spherical Particles Through Filter Media and Faceseal Leakage of N95 Filtering Facepiece Respirators with Cyclic Flow

PubMed Central

Cho, Kyungmin Jacob; Turkevich, Leonid; Miller, Matthew; McKay, Roy; Grinshpun, Sergey A.; Ha, KwonChul; Reponen, Tiina

2015-01-01

This study investigated differences in penetration between fibers and spherical particles through faceseal leakage of an N95 filtering facepiece respirator. Three cyclic breathing flows were generated corresponding to mean inspiratory flow rates (MIF) of 15, 30, and 85 L/min. Fibers had a mean diameter of 1 μm and a median length of 4.9 μm (calculated aerodynamic diameter, dae = 1.73 μm). Monodisperse polystyrene spheres with a mean physical diameter of 1.01 μm (PSI) and 1.54 μm (PSII) were used for comparison (calculated dae = 1.05 and 1.58 μm, respectively). Two optical particle counters simultaneously determined concentrations inside and outside the respirator. Geometric means (GMs) for filter penetration of the fibers were 0.06, 0.09, and 0.08% at MIF of 15, 30, and 85 L/min, respectively. Corresponding values for PSI were 0.07, 0.12, and 0.12%. GMs for faceseal penetration of fibers were 0.40, 0.14, and 0.09% at MIF of 15, 30, and 85 L/min, respectively. Corresponding values for PSI were 0.96, 0.41, and 0.17%. Faceseal penetration decreased with increased breathing rate for both types of particles (p ≤ 0.001). GMs of filter and faceseal penetration of PSII at an MIF of 30 L/min were 0.14% and 0.36%, respectively. Filter penetration and faceseal penetration of fibers were significantly lower than those of PSI (p < 0.001) and PSII (p < 0.003). This confirmed that higher penetration of PSI was not due to slightly smaller aerodynamic diameter, indicating that the shape of fibers rather than their calculated mean aerodynamic diameter is a prevailing factor on deposition mechanisms through the tested respirator. In conclusion, faceseal penetration of fibers and spherical particles decreased with increasing breathing rate, which can be explained by increased capture by impaction. Spherical particles had 2.0–2.8 times higher penetration through faceseal leaks and 1.1–1.5 higher penetration through filter media than fibers, which can be attributed to differences in interception losses. PMID:23339437

Penetration of fiber versus spherical particles through filter media and faceseal leakage of N95 filtering facepiece respirators with cyclic flow.

PubMed

Cho, Kyungmin Jacob; Turkevich, Leonid; Miller, Matthew; McKay, Roy; Grinshpun, Sergey A; Ha, KwonChul; Reponen, Tiina

2013-01-01

This study investigated differences in penetration between fibers and spherical particles through faceseal leakage of an N95 filtering facepiece respirator. Three cyclic breathing flows were generated corresponding to mean inspiratory flow rates (MIF) of 15, 30, and 85 L/min. Fibers had a mean diameter of 1 μm and a median length of 4.9 μm (calculated aerodynamic diameter, d(ae) = 1.73 μm). Monodisperse polystyrene spheres with a mean physical diameter of 1.01 μm (PSI) and 1.54 μm (PSII) were used for comparison (calculated d(ae) = 1.05 and 1.58 μm, respectively). Two optical particle counters simultaneously determined concentrations inside and outside the respirator. Geometric means (GMs) for filter penetration of the fibers were 0.06, 0.09, and 0.08% at MIF of 15, 30, and 85 L/min, respectively. Corresponding values for PSI were 0.07, 0.12, and 0.12%. GMs for faceseal penetration of fibers were 0.40, 0.14, and 0.09% at MIF of 15, 30, and 85 L/min, respectively. Corresponding values for PSI were 0.96, 0.41, and 0.17%. Faceseal penetration decreased with increased breathing rate for both types of particles (p ≤ 0.001). GMs of filter and faceseal penetration of PSII at an MIF of 30 L/min were 0.14% and 0.36%, respectively. Filter penetration and faceseal penetration of fibers were significantly lower than those of PSI (p < 0.001) and PSII (p < 0.003). This confirmed that higher penetration of PSI was not due to slightly smaller aerodynamic diameter, indicating that the shape of fibers rather than their calculated mean aerodynamic diameter is a prevailing factor on deposition mechanisms through the tested respirator. In conclusion, faceseal penetration of fibers and spherical particles decreased with increasing breathing rate, which can be explained by increased capture by impaction. Spherical particles had 2.0-2.8 times higher penetration through faceseal leaks and 1.1-1.5 higher penetration through filter media than fibers, which can be attributed to differences in interception losses.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2004-01-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

Joint passive radar tracking and target classification using radar cross section

NASA Astrophysics Data System (ADS)

Herman, Shawn M.

2003-12-01

We present a recursive Bayesian solution for the problem of joint tracking and classification of airborne targets. In our system, we allow for complications due to multiple targets, false alarms, and missed detections. More importantly, though, we utilize the full benefit of a joint approach by implementing our tracker using an aerodynamically valid flight model that requires aircraft-specific coefficients such as wing area and vehicle mass, which are provided by our classifier. A key feature that bridges the gap between tracking and classification is radar cross section (RCS). By modeling the true deterministic relationship that exists between RCS and target aspect, we are able to gain both valuable class information and an estimate of target orientation. However, the lack of a closed-form relationship between RCS and target aspect prevents us from using the Kalman filter or its variants. Instead, we rely upon a sequential Monte Carlo-based approach known as particle filtering. In addition to allowing us to include RCS as a measurement, the particle filter also simplifies the implementation of our nonlinear non-Gaussian flight model.

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.

A Robust Indoor Autonomous Positioning System Using Particle Filter Based on ISM Band Wireless Communications

NASA Astrophysics Data System (ADS)

Ikeda, Takeshi; Kawamoto, Mitsuru; Sashima, Akio; Suzuki, Keiji; Kurumatani, Koichi

In the field of the ubiquitous computing, positioning systems which can provide users' location information have paid attention as an important technical element which can be applied to various services, for example, indoor navigation services, evacuation services, market research services, guidance services, and so on. A lot of researchers have proposed various outdoor and indoor positioning systems. In this paper, we deal with indoor positioning systems. Many conventional indoor positioning systems use expensive infrastructures, because the propagated times of radio waves are used to measure users' positions with high accuracy. In this paper, we propose an indoor autonomous positioning system using radio signal strengths (RSSs) based on ISM band communications. In order to estimate users' positions, the proposed system utilizes a particle filter that is one of the Monte Carlo methods. Because the RSS information is used in the proposed system, the equipments configuring the system are not expensive compared with the conventional indoor positioning systems and it can be installed easily. Moreover, because the particle filter is used to estimate user's position, even if the RSS fluctuates due to, for example, multi-paths, the system can carry out position estimation robustly. We install the proposed system in one floor of a building and carry out some experiments in order to verify the validity of the proposed system. As a result, we confirmed that the average of the estimation errors of the proposed system was about 1.8 m, where the result is enough accuracy for achieving the services mentioned above.

The effectiveness of stand alone air cleaners for shelter-in-place.

PubMed

Ward, M; Siegel, J A; Corsi, R L

2005-04-01

Stand-alone air cleaners may be efficient for rapid removal of indoor fine particles and have potential use for shelter-in-place (SIP) strategies following acts of bioterrorism. A screening model was employed to ascertain the potential significance of size-resolved particle (0.1-2 microm) removal using portable high efficiency particle arresting (HEPA) air cleaners in residential buildings following an outdoor release of particles. The number of stand-alone air cleaners, air exchange rate, volumetric flow rate through the heating, ventilating and air-conditioning (HVAC) system, and size-resolved particle removal efficiency in the HVAC filter were varied. The effectiveness of air cleaners for SIP was evaluated in terms of the outdoor and the indoor particle concentration with air cleaner(s) relative to the indoor concentration without air cleaners. Through transient and steady-state analysis of the model it was determined that one to three portable HEPA air cleaners can be effective for SIP following outdoor bioaerosol releases, with maximum reductions in particle concentrations as high as 90% relative to conditions in which an air cleaner is not employed. The relative effectiveness of HEPA air cleaners vs. other removal mechanisms was predicted to decrease with increasing particle size, because of increasing competition by particle deposition with indoor surfaces and removal to HVAC filters. However, the effect of particle size was relatively small for most scenarios considered here. The results of a screening analysis suggest that stand-alone (portable) air cleaners that contain high efficiency particle arresting (HEPA) filters can be effective for reducing indoor fine particle concentrations in residential dwellings during outdoor releases of biological warfare agents. The relative effectiveness of stand-alone air cleaners for reducing occupants' exposure to particles of outdoor origin depends on several factors, including the type of heating, ventilating and air-conditioning (HVAC) filter, HVAC operation, building air exchange rate, particle size, and duration of elevated outdoor particle concentration. Maximum particle reductions, relative to no stand-alone air cleaners, of 90% are predicted when three stand-alone air cleaners are employed.

Bacteria associated with granular activated carbon particles in drinking water.

PubMed Central

Camper, A K; LeChevallier, M W; Broadaway, S C; McFeters, G A

1986-01-01

A sampling protocol was developed to examine particles released from granular activated carbon filter beds. A gauze filter/Swinnex procedure was used to collect carbon fines from 201 granular activated carbon-treated drinking water samples over 12 months. Application of a homogenization procedure (developed previously) indicated that 41.4% of the water samples had heterotrophic plate count bacteria attached to carbon particles. With the enumeration procedures described, heterotrophic plate count bacteria were recovered at an average rate of 8.6 times higher than by conventional analyses. Over 17% of the samples contained carbon particles colonized with coliform bacteria as enumerated with modified most-probable-number and membrane filter techniques. In some instances coliform recoveries were 122 to 1,194 times higher than by standard procedures. Nearly 28% of the coliforms attached to these particles in drinking water exhibited the fecal biotype. Scanning electron micrographs of carbon fines from treated drinking water showed microcolonies of bacteria on particle surfaces. These data indicate that bacteria attached to carbon fines may be an important mechanism by which microorganisms penetrate treatment barriers and enter potable water supplies. PMID:3767356

Plugin-docking system for autonomous charging using particle filter

NASA Astrophysics Data System (ADS)

Koyasu, Hiroshi; Wada, Masayoshi

2017-03-01

Autonomous charging of the robot battery is one of the key functions for the sake of expanding working areas of the robots. To realize it, most of existing systems use custom docking stations or artificial markers. By the other words, they can only charge on a few specific outlets. If the limit can be removed, working areas of the robots significantly expands. In this paper, we describe a plugin-docking system for the autonomous charging, which does not require any custom docking stations or artificial markers. A single camera is used for recognizing the 3D position of an outlet socket. A particle filter-based image tracking algorithm which is robust to the illumination change is applied. The algorithm is implemented on a robot with an omnidirectional moving system. The experimental results show the effectiveness of our system.

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.

Comparison among filter-based, impactor-based and continuous techniques for measuring atmospheric fine sulfate and nitrate

NASA Astrophysics Data System (ADS)

Nie, Wei; Wang, Tao; Gao, Xiaomei; Pathak, Ravi Kant; Wang, Xinfeng; Gao, Rui; Zhang, Qingzhu; Yang, Lingxiao; Wang, Wenxing

2010-11-01

Filter-based methods for sampling aerosols are subject to great uncertainty if the gas-particle interactions on filter substrates are not properly handled. Sampling artifacts depend on both meteorological conditions and the chemical mix of the atmosphere. Despite numerous of studies on the subject, very few have evaluated filter-based methods in the Asian environments. This paper reports the results of a comparison of the performances of two filter-based samplers, including a Thermo Anderson Chemical Speciation Monitor (RAAS) and a honeycomb denuder filter-pack system, a Micro Orifice Uniform Deposit Impactor (MOUDI) and a real-time ambient ion monitor (AIM, URG9000B) in measuring atmospheric concentrations of PM 2.5 sulfate and nitrate. Field studies were conducted at an urban site in Jinan, Shandong province, during the winter of 2007 and at a rural site near Beijing in the summer of 2008. The AIM was first compared with the honeycomb denuder filter-pack system which was considered to have minimal sampling artifacts. After some modifications made to it, the AIM showed good performance for both sulfate and nitrate measurement at the two sites and was then used to evaluate other instruments. For the un-denuded RAAS, the extent of sampling artifacts for nitrate on quartz filters was negligible, while that on Teflon filters was also minimal at high nitrate concentrations (>10 μgm -3); however, loss through evaporation was significant (˜75%) at low nitrate concentrations under hot summer conditions. The MOUDI using aluminum substrates suffered a significant loss of nitrate (50-70%) under summer conditions due to evaporation. Considering that the aluminum substrates are still being widely used to obtain size-resolved aerosol compositions because of their low cost and accurate mass weighed, caution should be taken about the potential significant under determination of semi-volatile components such as ammonium nitrate.

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.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

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...

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.

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

Scale-by-scale contributions to Lagrangian particle acceleration

NASA Astrophysics Data System (ADS)

Lalescu, Cristian C.; Wilczek, Michael

2017-11-01

Fluctuations on a wide range of scales in both space and time are characteristic of turbulence. Lagrangian particles, advected by the flow, probe these fluctuations along their trajectories. In an effort to isolate the influence of the different scales on Lagrangian statistics, we employ direct numerical simulations (DNS) combined with a filtering approach. Specifically, we study the acceleration statistics of tracers advected in filtered fields to characterize the smallest temporal scales of the flow. Emphasis is put on the acceleration variance as a function of filter scale, along with the scaling properties of the relevant terms of the Navier-Stokes equations. We furthermore discuss scaling ranges for higher-order moments of the tracer acceleration, as well as the influence of the choice of filter on the results. Starting from the Lagrangian tracer acceleration as the short time limit of the Lagrangian velocity increment, we also quantify the influence of filtering on Lagrangian intermittency. Our work complements existing experimental results on intermittency and accelerations of finite-sized, neutrally-buoyant particles: for the passive tracers used in our DNS, feedback effects are neglected such that the spatial averaging effect is cleanly isolated.

Effectiveness and cost of reducing particle-related mortality with particle filtration

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

Fisk, W. J.; Chan, W. R.

This study evaluates the mortality-related benefits and costs of improvements in particle filtration in U.S. homes and commercial buildings based on models with empirical inputs. The models account for time spent in various environments as well as activity levels and associated breathing rates. The scenarios evaluated include improvements in filter efficiencies in both forced-air heating and cooling systems of homes and heating, ventilating, and air conditioning systems of workplaces as well as use of portable air cleaners in homes. The predicted reductions in mortality range from approximately 0.25 to 2.4 per 10 000 population. The largest reductions in mortality were frommore » interventions with continuously operating portable air cleaners in homes because, given our scenarios, these portable air cleaners with HEPA filters most reduced particle exposures. For some interventions, predicted annual mortality-related economic benefits exceed $1000 per person. Economic benefits always exceed costs with benefit-to-cost ratios ranging from approximately 3.9 to 133. In conclusion, restricting interventions to homes of the elderly further increases the mortality reductions per unit population and the benefit-to-cost ratios.« less

Near-wall effects for momentum, heat and mass transport in gas-particle suspensions at moderate Reynolds numbers

NASA Astrophysics Data System (ADS)

Radl, Stefan; Municchi, Federico; Goniva, Christoph

2016-11-01

Understanding transport phenomena in fluid-particle systems is of primary importance for the design of large-scale equipment, e.g., in the chemical industry. Typically, the analysis of such systems is performed by numerically solving a set of partial differential equations modeling the particle phase and the fluid phase as interpenetrating continua. Such models require a number of closure models that are often constructed via spatial filtering of data obtained from particle-resolved direct numerical simulations (PR-DNS). In the present work we make use of PR-DNS to evaluate corrections to existing closure models. Specifically, we aim on accounting for wall effects on the fluid-particle drag force and the particle-individual Nusselt number. We then propose an improved closure model to be used in particle-unresolved Euler-Lagrange (PU-EL) simulations. We demonstrate that such an advanced closure should account for a dimensionless filter size, as well as a normalized distance from the wall. In addition, we make an attempt to model the filtered fluid velocity profile in wall-bounded suspension flows. The authors acknowledge funding from the European Commission through FP7 Grant Agreement No. 604656, as well as VSC-3 and dcluster.tugraz.at.

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.

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.

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.

Assessment of Iodine-treated Filter Media for Removal and Inactivation of MS2 Bacteriophase Aerosols

DTIC Science & Technology

2009-04-01

values measured for test filters. The PRE was measured for ultrafine particles (i.e., 9.82 to 162.5 nm), whereas the VRE was measured over the entire...than that of ultrafine particles . This effect was observed in a prior study (Hogan et al. 2005), which reported that the possibility of containing

Use of entanglement in quantum optics

NASA Technical Reports Server (NTRS)

Horne, Michael A.; Bernstein, Herbert J.; Greenberger, Daniel M.; Zeilinger, Anton

1992-01-01

Several recent demonstrations of two-particle interferometry are reviewed and shown to be examples of either color entanglement or beam entanglement. A device, called a number filter, is described and shown to be of value in preparing beam entanglements. Finally, we note that all three concepts (color and beam entaglement, and number filtering) may be extended to three or more particles.

Filter aids influence on pressure drop across a filtration system

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

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.

The influence of sub-grid scale motions on particle collision in homogeneous isotropic turbulence

NASA Astrophysics Data System (ADS)

Xiong, Yan; Li, Jing; Liu, Zhaohui; Zheng, Chuguang

2018-02-01

The absence of sub-grid scale (SGS) motions leads to severe errors in particle pair dynamics, which represents a great challenge to the large eddy simulation of particle-laden turbulent flow. In order to address this issue, data from direct numerical simulation (DNS) of homogenous isotropic turbulence coupled with Lagrangian particle tracking are used as a benchmark to evaluate the corresponding results of filtered DNS (FDNS). It is found that the filtering process in FDNS will lead to a non-monotonic variation of the particle collision statistics, including radial distribution function, radial relative velocity, and the collision kernel. The peak of radial distribution function shifts to the large-inertia region due to the lack of SGS motions, and the analysis of the local flowstructure characteristic variable at particle position indicates that the most effective interaction scale between particles and fluid eddies is increased in FDNS. Moreover, this scale shifting has an obvious effect on the odd-order moments of the probability density function of radial relative velocity, i.e. the skewness, which exhibits a strong correlation to the variance of radial distribution function in FDNS. As a whole, the radial distribution function, together with radial relative velocity, can compensate the SGS effects for the collision kernel in FDNS when the Stokes number based on the Kolmogorov time scale is greater than 3.0. However, it still leaves considerable errors for { St}_k <3.0.

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

Physico-Chemical Characterization of Fine and Ultrafine Particles Emitted during Diesel Particulate Filter Active Regeneration of Euro5 Diesel Vehicles.

PubMed

R'Mili, Badr; Boréave, Antoinette; Meme, Aurelie; Vernoux, Philippe; Leblanc, Mickael; Noël, Ludovic; Raux, Stephane; D'Anna, Barbara

2018-03-06

Diesel particulate filters (DPFs) are commonly employed in modern passenger cars to comply with current particulate matter (PM) emission standards. DPFs requires periodic regeneration to remove the accumulated matter. During the process, high-concentration particles, in both nucleation and accumulation modes, are emitted. Here, we report new information on particle morphology and chemical composition of fine (FPs) and ultrafine particles (UFPs) measured downstream of the DPF during active regeneration of two Euro 5 passenger cars. The first vehicle was equipped with a close-coupled diesel oxidation catalyst (DOC) and noncatalyzed DPF combined with fuel borne catalyst and the second one with DOC and a catalyzed-diesel particle filter (CDPF). Differences in PM emission profiles of the two vehicles were related to different after treatment design, regeneration strategies, and vehicle characteristics and mileage. Particles in the nucleation mode consisted of ammonium bisulfate, sulfate and sulfuric acid, suggesting that the catalyst desulfation is the key process in the formation of UFPs. Larger particles and agglomerates, ranging from 90 to 600 nm, consisted of carbonaceous material (soot and soot aggregates) coated by condensable material including organics, ammonium bisulfate and sulfuric acid. Particle emission in the accumulation mode was due to the reduced filtration efficiency (soot cake oxidation) throughout the regeneration process.

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.

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.

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

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

Alleman, T. L.; Eudy, L.; Miyasato, M.

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

Reversible Quantum Brownian Heat Engines for Electrons

NASA Astrophysics Data System (ADS)

Humphrey, T. E.; Newbury, R.; Taylor, R. P.; Linke, H.

2002-08-01

Brownian heat engines use local temperature gradients in asymmetric potentials to move particles against an external force. The energy efficiency of such machines is generally limited by irreversible heat flow carried by particles that make contact with different heat baths. Here we show that, by using a suitably chosen energy filter, electrons can be transferred reversibly between reservoirs that have different temperatures and electrochemical potentials. We apply this result to propose heat engines based on mesoscopic semiconductor ratchets, which can quasistatically operate arbitrarily close to Carnot efficiency.

Reversible quantum heat engines for electrons

NASA Astrophysics Data System (ADS)

Linke, Heiner; Humphrey, Tammy E.; Newbury, Richard; Taylor, Richard P.

2002-03-01

Brownian heat engines use local temperature gradients in asymmetric potentials to move particles against an external force. The energy efficiency of such machines is generally limited by irreversible heat flow carried by particles that make contact with different heat baths. Here we show that, by using a suitably chosen energy filter, electrons can be transferred reversibly between reservoirs that have different temperatures and electrochemical potentials. We apply this result to propose heat engines based on quantum ratchets, which can quasistatically operate at Carnot efficiency.

Analyzing the uncertainty of suspended sediment load prediction using sequential data assimilation

NASA Astrophysics Data System (ADS)

Leisenring, Marc; Moradkhani, Hamid

2012-10-01

SummaryA first step in understanding the impacts of sediment and controlling the sources of sediment is to quantify the mass loading. Since mass loading is the product of flow and concentration, the quantification of loads first requires the quantification of runoff volume. Using the National Weather Service's SNOW-17 and the Sacramento Soil Moisture Accounting (SAC-SMA) models, this study employed particle filter based Bayesian data assimilation methods to predict seasonal snow water equivalent (SWE) and runoff within a small watershed in the Lake Tahoe Basin located in California, USA. A procedure was developed to scale the variance multipliers (a.k.a hyperparameters) for model parameters and predictions based on the accuracy of the mean predictions relative to the ensemble spread. In addition, an online bias correction algorithm based on the lagged average bias was implemented to detect and correct for systematic bias in model forecasts prior to updating with the particle filter. Both of these methods significantly improved the performance of the particle filter without requiring excessively wide prediction bounds. The flow ensemble was linked to a non-linear regression model that was used to predict suspended sediment concentrations (SSCs) based on runoff rate and time of year. Runoff volumes and SSC were then combined to produce an ensemble of suspended sediment load estimates. Annual suspended sediment loads for the 5 years of simulation were finally computed along with 95% prediction intervals that account for uncertainty in both the SSC regression model and flow rate estimates. Understanding the uncertainty associated with annual suspended sediment load predictions is critical for making sound watershed management decisions aimed at maintaining the exceptional clarity of Lake Tahoe. The computational methods developed and applied in this research could assist with similar studies where it is important to quantify the predictive uncertainty of pollutant load estimates.

Practical implementation of a particle filter data assimilation approach to estimate initial hydrologic conditions and initialize medium-range streamflow forecasts

NASA Astrophysics Data System (ADS)

Clark, E.; Wood, A.; Nijssen, B.; Newman, A. J.; Mendoza, P. A.

2016-12-01

The System for Hydrometeorological Applications, Research and Prediction (SHARP), developed at the National Center for Atmospheric Research (NCAR), University of Washington, U.S. Army Corps of Engineers, and U.S. Bureau of Reclamation, is a fully automated ensemble prediction system for short-term to seasonal applications. It incorporates uncertainty in initial hydrologic conditions (IHCs) and in hydrometeorological predictions. In this implementation, IHC uncertainty is estimated by propagating an ensemble of 100 plausible temperature and precipitation time series through the Sacramento/Snow-17 model. The forcing ensemble explicitly accounts for measurement and interpolation uncertainties in the development of gridded meteorological forcing time series. The resulting ensemble of derived IHCs exhibits a broad range of possible soil moisture and snow water equivalent (SWE) states. To select the IHCs that are most consistent with the observations, we employ a particle filter (PF) that weights IHC ensemble members based on observations of streamflow and SWE. These particles are then used to initialize ensemble precipitation and temperature forecasts downscaled from the Global Ensemble Forecast System (GEFS), generating a streamflow forecast ensemble. We test this method in two basins in the Pacific Northwest that are important for water resources management: 1) the Green River upstream of Howard Hanson Dam, and 2) the South Fork Flathead River upstream of Hungry Horse Dam. The first of these is characterized by mixed snow and rain, while the second is snow-dominated. The PF-based forecasts are compared to forecasts based on a single IHC (corresponding to median streamflow) paired with the full GEFS ensemble, and 2) the full IHC ensemble, without filtering, paired with the full GEFS ensemble. In addition to assessing improvements in the spread of IHCs, we perform a hindcast experiment to evaluate the utility of PF-based data assimilation on streamflow forecasts at 1- to 7-day lead times.

Bacteriophage-like Particles Associated with the Gene Transfer Agent of Methanococcus Voltale PS

NASA Technical Reports Server (NTRS)

Bertani, G.; Eiserling, F.; Pushkin, A.; Gingery, M.

1999-01-01

The methanogenic archaebacterium Methanococus voltae (strain PS) is known to produce a filterable, DNase resistant agent (called VTA, for voltae transfer agent), which carries very small fragments (4,400 base pairs) of bacterial DNA and is able to transduce bacterial genes between derivatives of the strain.

Source Apportionment of the Summer Time Carbonaceous Aerosol at Nordic Rural Background Sites

EPA Science Inventory

In the present study, natural and anthropogenic sources of particulate organic carbon (OC_p) and elemental carbon (EC) have been quantified based on weekly filter samples of PM₁₀ (particles with aerodynamic diameter <10µ collected at four Nordic rural backgro...

Measurements of Nascent Soot Using a Cavity Attenauted Phase Shift (CAPS)-based Single Scattering Albedo Monitor

NASA Astrophysics Data System (ADS)

Freedman, A.; Onasch, T. B.; Renbaum-Wollf, L.; Lambe, A. T.; Davidovits, P.; Kebabian, P. L.

2015-12-01

Accurate, as compared to precise, measurement of aerosol absorption has always posed a significant problem for the particle radiative properties community. Filter-based instruments do not actually measure absorption but rather light transmission through the filter; absorption must be derived from this data using multiple corrections. The potential for matrix-induced effects is also great for organic-laden aerosols. The introduction of true in situ measurement instruments using photoacoustic or photothermal interferometric techniques represents a significant advance in the state-of-the-art. However, measurement artifacts caused by changes in humidity still represent a significant hurdle as does the lack of a good calibration standard at most measurement wavelengths. And, in the absence of any particle-based absorption standard, there is no way to demonstrate any real level of accuracy. We, along with others, have proposed that under the circumstance of low single scattering albedo (SSA), absorption is best determined by difference using measurement of total extinction and scattering. We discuss a robust, compact, field deployable instrument (the CAPS PMssa) that simultaneously measures airborne particle light extinction and scattering coefficients and thus the single scattering albedo (SSA) on the same sample volume. The extinction measurement is based on cavity attenuated phase shift (CAPS) techniques as employed in the CAPS PMex particle extinction monitor; scattering is measured using integrating nephelometry by incorporating a Lambertian integrating sphere within the sample cell. The scattering measurement is calibrated using the extinction measurement of non-absorbing particles. For small particles and low SSA, absorption can be measured with an accuracy of 6-8% at absorption levels as low as a few Mm-1. We present new results of the measurement of the mass absorption coefficient (MAC) of soot generated by an inverted methane diffusion flame at 630 nm. A value of 6.60 ±0.2 m2 g-1 was determined where the uncertainty refers to the precision of the measurement. The overall accuracy of the measurement, traceable to the properties of polystyrene latex particles, is estimated to be better than ±10%.

Initial Alignment of Large Azimuth Misalignment Angles in SINS Based on Adaptive UPF

PubMed Central

Sun, Jin; Xu, Xiao-Su; Liu, Yi-Ting; Zhang, Tao; Li, Yao

2015-01-01

The case of large azimuth misalignment angles in a strapdown inertial navigation system (SINS) is analyzed, and a method of using the adaptive UPF for the initial alignment is proposed. The filter is based on the idea of a strong tracking filter; through the introduction of the attenuation memory factor to effectively enhance the corrections of the current information residual error on the system, it reduces the influence on the system due to the system simplification, and the uncertainty of noise statistical properties to a certain extent; meanwhile, the UPF particle degradation phenomenon is better overcome. Finally, two kinds of non-linear filters, UPF and adaptive UPF, are adopted in the initial alignment of large azimuth misalignment angles in SINS, and the filtering effects of the two kinds of nonlinear filter on the initial alignment were compared by simulation and turntable experiments. The simulation and turntable experiment results show that the speed and precision of the initial alignment using adaptive UPF for a large azimuth misalignment angle in SINS under the circumstance that the statistical properties of the system noise are certain or not have been improved to some extent. PMID:26334277

Behaviour of radiocaesium in coastal rivers of the Fukushima Prefecture (Japan) during conditions of low flow and low turbidity--Insight on the possible role of small particles and detrital organic compounds.

PubMed

Eyrolle-Boyer, Frédérique; Boyer, Patrick; Garcia-Sanchez, Laurent; Métivier, Jean-Michel; Onda, Yuichi; De Vismes, Anne; Cagnat, Xavier; Boulet, Béatrice; Cossonnet, Catherine

2016-01-01

To investigate riverine transfers from contaminated soils of the Fukushima Prefecture in Japan to the marine environment, suspended sediments, filtered water, sediments and detrital organic macro debris deposited onto river beds were collected in November 2013 within small coastal rivers during conditions of low flow rates and low turbidity. River waters were directly filtered on the field and high efficiency well-type Ge detectors were used to analyse radiocaesium concentrations in very small quantities of suspended particles and filtered water (a few mg to a few g). For such base-flow conditions, our results show that the watersheds studied present similar hydro-sedimentary behaviours at their outlets and that the exports of dissolved and particulate radiocaesium are comparable. Moreover, the contribution of these rivers to the instantaneous export of radiocaesium to the ocean is similar to that of the Abukuma River. Our preliminary results indicate that, in the estuaries, radiocaesium concentrations in suspended sediments would be reduced by more than 80%, while radiocaesium concentration in filtered waters would be maintained. Significant correlations between radiocaesium concentrations and radiocaesium inventories in the soils of the catchments indicate that there was at that time little intra and inter-watershed variability in the transfer processes of radiocaesium from lands to rivers at this regional scale. The apparent liquid-solid partition coefficient (KD) values acquired for the lowest loads/finest particles complement the values acquired by using sediment traps and highlight the strong capacity of the smallest particles to transfer radiocaesium. Finally, but not least, our observations suggest that there could be a significant transfer of highly contaminated detrital biomass from forest litter to the downstream rivers in a rather conservative way. Copyright © 2015 Elsevier Ltd. All rights reserved.

Research on particulate filter simulation and regeneration control strategy

NASA Astrophysics Data System (ADS)

Dawei, Qu; Jun, Li; Yu, Liu

2017-03-01

This paper reports a DPF (Diesel Particulate Filter) collection mathematical model for a new regeneration control strategy. The new strategy is composed by main parts, such as regeneration time capturing, temperature rising strategy and regeneration control strategy. In the part of regeneration time capturing, a multi-level regeneration capturing method is put forward based on the combined effect of the PM (Particulate Matter) loading, pressure drop and fuel consumption. The temperature rising strategy proposes the global temperature for all operating conditions. The regeneration control process considers the particle loading density, temperature and oxygen respectively. Based on the analysis of the initial overheating, runaway temperature and local hot spot, the final control strategy is established.

Black Carbon Measurement Intercomparison during the 2017 Black Carbon Shootout

NASA Astrophysics Data System (ADS)

Shingler, T.; Moore, R.; Winstead, E.; Robinson, C. E.; Shook, M.; Crosbie, E.; Ziemba, L. D.; Thornhill, K. L., II; Sorooshian, A.; Anderson, B. E.

2017-12-01

The NASA Langley Aerosol Research Group (LARGE) provides multiple black carbon (BC) based aerosol particle measurements and engine emission factors for airborne and ground-based field campaigns and laboratory studies. These datasets are made available to the general public where accuracy is key to enable further use in environmental assessments, models, and validation studies. Studies are needed to establish the accuracy and precision of BC measurements of particles with varying physical properties using a variety of detection techniques. Work is also needed to develop calibration and correction schemes for new sensors and to link these measurements to heritage instruments on which our understanding of BC emissions and characteristics has been established. A BC measurement intercomparison was performed at Langley Research Center using particles generated from a mini-CAST (Jing) diffusion flame soot generator. The particles were passed to instruments measuring optical absorption, extinction, scattering and black carbon mass. Filter based measurements of optical absorption were performed using a PSAP (Radiance Research) and a TAP (BMI). Absorption was also measured using two photoacoustic based instruments: the MSS-plus (AVL) and PASS-3 (DMT). Measurements of aerosol extinction were performed using three CAPS PM-ex (Aerodyne Research) instruments at multiple wavelengths. Two Artium LII-300 units (standard and high-sensitivity) were used to measure black carbon mass via laser incandescence. Black carbon measurements were correlated to mass collected concurrently on a filter and analyzed by OC/EC analysis (Sunset Labs). Black carbon quantification measurements are analyzed between instruments to assess agreement between platforms using manufacturer's calibration settings as well as after calibrations performed to a single standard soot source (mini-CAST). Sampling was also performed from behind a Falcon aircraft at multiple thrust settings and downwind of runway at an international airport with commercial takeoffs and landings.

Removal of Inclusions from Molten Aluminum by Supergravity Filtration

NASA Astrophysics Data System (ADS)

Song, Gaoyang; Song, Bo; Yang, Zhanbing; Yang, Yuhou; Zhang, Jing

2016-12-01

A new approach to removing inclusions from aluminum melt by supergravity filtration was investigated. The molten aluminum containing MgAl2O4 spinel and coarse Al3Ti particles was isothermally filtered with different gravity coefficients, different filtering times, and various filtering temperatures under supergravity field. When the gravity coefficient G ≥ 50, the alloy samples were divided automatically into two parts: the upper residue and the lower filtered aluminum. All inclusions (MgAl2O4 and Al3Ti particles) were nearly intercepted in the upper residue by filter felt with average pore size of 44.78 μm. The removal efficiencies of oxide inclusions and Al3Ti particles exceeded 98 and 90 pct, respectively, at G ≥ 50, t = 2 minutes, T = 973 K (700 °C). Besides, the yield of purified aluminum was up to 92.1 pct at G = 600, t = 2 minutes, and T = 973 K (700 °C). The calculations of centrifugal pressure indicated that supergravity filtration could effectively overcome the pressure drop without meeting the rigorous requirement of height of molten metal, especially for using the fine-pore filter medium. Moreover, cake-mode filtration was the major mechanism of supergravity filtration of molten metal in this work.

Synthesis of Polyhydroxybutyrate Particles with Micro-to-Nanosized Structures and Application as Protective Coating for Packaging Papers

PubMed Central

Rastogi, Vibhore Kumar; Samyn, Pieter

2016-01-01

This study reports on the development of bio-based hydrophobic coatings for packaging papers through deposition of polyhydroxybutyrate (PHB) particles in combination with nanofibrillated cellulose (NFC) and plant wax. In the first approach, PHB particles in the micrometer range (PHB-MP) were prepared through a phase-separation technique providing internally-nanosized structures. The particles were transferred as a coating by dip-coating filter papers in the particle suspension, followed by sizing with a carnauba wax solution. This approach allowed partial to almost full surface coverage of PHB-MP over the paper surface, resulting in static water contact angles of 105°–122° and 129°–144° after additional wax coating. In the second approach, PHB particles with submicron sizes (PHB-SP) were synthesized by an oil-in-water emulsion (o/w) solvent evaporation method and mixed in aqueous suspensions with 0–7 wt % NFC. After dip-coating filter papers in PHB-SP/NFC suspensions and sizing with a carnauba wax solution, static water contact angles of 112°–152° were obtained. The intrinsic properties of the particles were analyzed by scanning electron microscopy, thermal analysis and infrared spectroscopy, indicating higher crystallinity for PHB-SP than PHB-MP. The chemical interactions between the more amorphous PHB-MP particles and paper fibers were identified as an esterification reaction, while the morphology of the NFC fibrillar network was playing a key role as the binding agent in the retention of more crystalline PHB-SP at the paper surface, hence contributing to higher hydrophobicity. PMID:28336839

Synthesis of Polyhydroxybutyrate Particles with Micro-to-Nanosized Structures and Application as Protective Coating for Packaging Papers.

PubMed

Rastogi, Vibhore Kumar; Samyn, Pieter

2016-12-30

This study reports on the development of bio-based hydrophobic coatings for packaging papers through deposition of polyhydroxybutyrate (PHB) particles in combination with nanofibrillated cellulose (NFC) and plant wax. In the first approach, PHB particles in the micrometer range (PHB-MP) were prepared through a phase-separation technique providing internally-nanosized structures. The particles were transferred as a coating by dip-coating filter papers in the particle suspension, followed by sizing with a carnauba wax solution. This approach allowed partial to almost full surface coverage of PHB-MP over the paper surface, resulting in static water contact angles of 105°-122° and 129°-144° after additional wax coating. In the second approach, PHB particles with submicron sizes (PHB-SP) were synthesized by an oil-in-water emulsion (o/w) solvent evaporation method and mixed in aqueous suspensions with 0-7 wt % NFC. After dip-coating filter papers in PHB-SP/NFC suspensions and sizing with a carnauba wax solution, static water contact angles of 112°-152° were obtained. The intrinsic properties of the particles were analyzed by scanning electron microscopy, thermal analysis and infrared spectroscopy, indicating higher crystallinity for PHB-SP than PHB-MP. The chemical interactions between the more amorphous PHB-MP particles and paper fibers were identified as an esterification reaction, while the morphology of the NFC fibrillar network was playing a key role as the binding agent in the retention of more crystalline PHB-SP at the paper surface, hence contributing to higher hydrophobicity.

Evaluating the capabilities of aerosol-to-liquid particle extraction system (ALPXS)/ICP-MS for monitoring trace metals in indoor air.

PubMed

Jayawardene, Innocent; Rasmussen, Pat E; Chenier, Marc; Gardner, H David

2014-09-01

This study investigates the application of the Aerosol-to-Liquid Particle Extraction System (ALPXS), which uses wet electrostatic precipitation to collect airborne particles, for multi-element indoor stationary monitoring. Optimum conditions are determined for capturing airborne particles for metal determination by inductively coupled plasma-mass spectrometry (ICP-MS), for measuring field blanks, and for calculating limits of detection (LOD) and quantification (LOQ). Due to the relatively high flow rate (300 L min(-1)), a sampling duration of 1 hr to 2 hr was adequate to capture airborne particle-bound metals under the investigated experimental conditions. The performance of the ALPXS during a building renovation demonstrated signal-to-noise ratios appropriate for sampling airborne particles in environments with elevated metal concentrations, such as workplace settings. The ALPXS shows promise as a research tool for providing useful information on short-term variations (transient signals) and for trapping particles into aqueous solutions where needed for subsequent characterization. As the ALPXS does not provide size-specific samples, and its efficiency at different flow rates has yet to be quantified, the ALPXS would not replace standard filter-based protocols accepted for regulatory applications (e.g., exposure measurements), but rather would provide additional information if used in conjunction with filter based methods. Implications: This study investigates the capability of the Aerosol-to-Liquid Particle Extraction System (ALPXS) for stationary sampling of airborne metals in indoor workplace environments, with subsequent analysis by ICP-MS. The high flow rate (300 L/min) permits a short sampling duration (< 2 hr). Results indicated that the ALPXS was capable of monitoring short-term changes in metal emissions during a renovation activity. This portable instrument may prove to be advantageous in occupational settings as a qualitative indicator of elevated concentrations of airborne metals at short time scales.

Particle formation above natural and simulated salt lakes

NASA Astrophysics Data System (ADS)

Kamilli, Katharina A.; Ofner, Johannes; Sattler, Tobias; Krause, Torsten; Held, Andreas

2014-05-01

Originally, Western Australia was covered with Eucalyptus trees. Large scale deforestation for agricultural purposes led to rising ground water levels and brought dissolved salts and minerals to the surface. Nowadays, Western Australia is known for a great plenty of salt lakes with pH levels reaching from 2.5 to 7.1. The land is mainly used for wheat farming and livestock and becomes drier due to the lack of rain periods. One possible reason could be the formation of ultrafine particles from salt lakes, which increases the number of cloud condensation nuclei, and thus potentially suppresses precipitation. Several field campaigns have been conducted between 2006 and 2011 with car-based and airborne measurements, where new particle formation has been observed and has been related to the Western Australian salt lakes (Junkermann et al., 2009). To identify particle formation directly above the salt lakes, a 2.35 m³ PTFE chamber was set up above several lakes in 2012 and 2013. Inside the chamber, photochemistry may take place whereas mixing through wind or advection of already existing particles is prevented. Salt lakes with a low pH level led to strongly increased aerosol formation. Also, the dependence on meteorological conditions has been examined. To obtain chemical information of the newly formed particles, during the chamber experiments also aerosol filter samples have been taken. The analysis of the anions by ion chromatography in 2012 showed an 8 to 17 times higher concentration of Cl- than SO42-, which led to the assumption that particle formation may have been influenced by halogens. As reference experiments, laboratory based aerosol smog-chamber runs were performed to examine halogen induced aerosol formation under atmospheric conditions using simulated sunlight and the simplified chemical composition of a salt lake. The mixture included FeSO4, NaCl and Na2SO4. After adding α-pinene to the simulated salt lake, a strong nucleation event began comparable to the observed events in Western Australia. Also, IR spectroscopy of filter samples of a simulated salt lake showed an aerosol with C=O/C=C vibrations and a significant C-Cl vibration, which underlined this assumption. In contrast, the filter analysis with FTIR microscopy of the aerosol collected in 2013 in Western Australia showed vibrations of organic and sulfate species. Further analyses are ongoing, which will allow a detailed analysis of the atmospheric aerosol based on high-resolution chemical imaging. The resulting elemental composition and vibrational information will help elucidating which compounds initiate the particle formation and which condense on already existing matter. Reference: Junkermann, W., Hacker, J., Lyons, T., and Nair, U.: Land use change suppresses precipitation, Atmos. Chem. Phys., 9, 6531-6539, 2009.

High-efficiency particulate air filter test stand and aerosol generator for particle loading studies

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Hogancamp, Kristina U.; Parsons, Michael S.; Rogers, Donna M.; Norton, Olin P.; Nagel, Brian A.; Alderman, Steven L.; Waggoner, Charles A.

2007-08-01

This manuscript describes the design, characterization, and operational range of a test stand and high-output aerosol generator developed to evaluate the performance of 30×30×29cm3 nuclear grade high-efficiency particulate air (HEPA) filters under variable, highly controlled conditions. The test stand system is operable at volumetric flow rates ranging from 1.5to12standardm3/min. Relative humidity levels are controllable from 5%-90% and the temperature of the aerosol stream is variable from ambient to 150°C. Test aerosols are produced through spray drying source material solutions that are introduced into a heated stainless steel evaporation chamber through an air-atomizing nozzle. Regulation of the particle size distribution of the aerosol challenge is achieved by varying source solution concentrations and through the use of a postgeneration cyclone. The aerosol generation system is unique in that it facilitates the testing of standard HEPA filters at and beyond rated media velocities by consistently providing, into a nominal flow of 7standardm3/min, high mass concentrations (˜25mg/m3) of dry aerosol streams having count mean diameters centered near the most penetrating particle size for HEPA filters (120-160nm). Aerosol streams that have been generated and characterized include those derived from various concentrations of KCl, NaCl, and sucrose solutions. Additionally, a water insoluble aerosol stream in which the solid component is predominantly iron (III) has been produced. Multiple ports are available on the test stand for making simultaneous aerosol measurements upstream and downstream of the test filter. Types of filter performance related studies that can be performed using this test stand system include filter lifetime studies, filtering efficiency testing, media velocity testing, evaluations under high mass loading and high humidity conditions, and determination of the downstream particle size distributions.

High-efficiency particulate air filter test stand and aerosol generator for particle loading studies.

PubMed

Arunkumar, R; Hogancamp, Kristina U; Parsons, Michael S; Rogers, Donna M; Norton, Olin P; Nagel, Brian A; Alderman, Steven L; Waggoner, Charles A

2007-08-01

This manuscript describes the design, characterization, and operational range of a test stand and high-output aerosol generator developed to evaluate the performance of 30 x 30 x 29 cm(3) nuclear grade high-efficiency particulate air (HEPA) filters under variable, highly controlled conditions. The test stand system is operable at volumetric flow rates ranging from 1.5 to 12 standard m(3)/min. Relative humidity levels are controllable from 5%-90% and the temperature of the aerosol stream is variable from ambient to 150 degrees C. Test aerosols are produced through spray drying source material solutions that are introduced into a heated stainless steel evaporation chamber through an air-atomizing nozzle. Regulation of the particle size distribution of the aerosol challenge is achieved by varying source solution concentrations and through the use of a postgeneration cyclone. The aerosol generation system is unique in that it facilitates the testing of standard HEPA filters at and beyond rated media velocities by consistently providing, into a nominal flow of 7 standard m(3)/min, high mass concentrations (approximately 25 mg/m(3)) of dry aerosol streams having count mean diameters centered near the most penetrating particle size for HEPA filters (120-160 nm). Aerosol streams that have been generated and characterized include those derived from various concentrations of KCl, NaCl, and sucrose solutions. Additionally, a water insoluble aerosol stream in which the solid component is predominantly iron (III) has been produced. Multiple ports are available on the test stand for making simultaneous aerosol measurements upstream and downstream of the test filter. Types of filter performance related studies that can be performed using this test stand system include filter lifetime studies, filtering efficiency testing, media velocity testing, evaluations under high mass loading and high humidity conditions, and determination of the downstream particle size distributions.

Wake-Driven Dynamics of Finite-Sized Buoyant Spheres in Turbulence

NASA Astrophysics Data System (ADS)

Mathai, Varghese; Prakash, Vivek N.; Brons, Jon; Sun, Chao; Lohse, Detlef

2015-09-01

Particles suspended in turbulent flows are affected by the turbulence and at the same time act back on the flow. The resulting coupling can give rise to rich variability in their dynamics. Here we report experimental results from an investigation of finite-sized buoyant spheres in turbulence. We find that even a marginal reduction in the particle's density from that of the fluid can result in strong modification of its dynamics. In contrast to classical spatial filtering arguments and predictions of particle models, we find that the particle acceleration variance increases with size. We trace this reversed trend back to the growing contribution from wake-induced forces, unaccounted for in current particle models in turbulence. Our findings highlight the need for improved multiphysics based models that account for particle wake effects for a faithful representation of buoyant-sphere dynamics in turbulence.

Uncertainty in particle number modal analysis during transient operation of compressed natural gas, diesel, and trap-equipped diesel transit buses.

PubMed

Holmén, Britt A; Qu, Yingge

2004-04-15

The relationships between transient vehicle operation and ultrafine particle emissions are not well-known, especially for low-emission alternative bus technologies such as compressed natural gas (CNG) and diesel buses equipped with particulate filters/traps (TRAP). In this study, real-time particle number concentrations measured on a nominal 5 s average basis using an electrical low pressure impactor (ELPI) for these two bus technologies are compared to that of a baseline catalyst-equipped diesel bus operated on ultralow sulfur fuel (BASE) using dynamometer testing. Particle emissions were consistently 2 orders of magnitude lower for the CNG and TRAP compared to BASE on all driving cycles. Time-resolved total particle numbers were examined in terms of sampling factors identified as affecting the ability of ELPI to quantify the particulate matter number emissions for low-emitting vehicles such as CNG and TRAP as a function of vehicle driving mode. Key factors were instrument sensitivity and dilution ratio, alignment of particle and vehicle operating data, sampling train background particles, and cycle-to-cycle variability due to vehicle, engine, after-treatment, or driver behavior. In-cycle variability on the central business district (CBD) cycle was highest for the TRAP configuration, but this could not be attributed to the ELPI sensitivity issues observed for TRAP-IDLE measurements. Elevated TRAP emissions coincided with low exhaust temperature, suggesting on-road real-world particulate filter performance can be evaluated by monitoring exhaust temperature. Nonunique particle emission maps indicate that measures other than vehicle speed and acceleration are necessary to model disaggregated real-time particle emissions. Further testing on a wide variety of test cycles is needed to evaluate the relative importance of the time history of vehicle operation and the hysteresis of the sampling train/dilution tunnel on ultrafine particle emissions. Future studies should monitor particle emissions with high-resolution real-time instruments and account for the operating regime of the vehicle using time-series analysis to develop predictive number emissions models.

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.

Strategies for Tailoring the Pore-Size Distribution of Virus Retention Filter Papers.

PubMed

Gustafsson, Simon; Mihranyan, Albert

2016-06-08

The goal of this work is to demonstrate how the pore-size distribution of the nanocellulose-based virus-retentive filter can be tailored. The filter paper was produced using cellulose nanofibers derived from Cladophora sp. green algae using the hot-press drying at varying drying temperatures. The produced filters were characterized using scanning electron microscopy, atomic force microscopy, and N2 gas sorption analysis. Further, hydraulic permeability and retention efficiency toward surrogate 20 nm model particles (fluorescent carboxylate-modified polystyrene spheres) were assessed. It was shown that by controlling the rate of water evaporation during hot-press drying the pore-size distribution can be precisely tailored in the region between 10 and 25 nm. The mechanism of pore formation and critical parameters are discussed in detail. The results are highly valuable for development of advanced separation media, especially for virus-retentive size-exclusion filtration.

Modification of ceramic microfilters with colloidal zirconia to promote the adsorption of viruses from water.

PubMed

Wegmann, Markus; Michen, Benjamin; Luxbacher, Thomas; Fritsch, Johannes; Graule, Thomas

2008-03-01

The purpose of this study was to test the feasibility of modifying commercial microporous ceramic bacteria filters to promote adsorption of viruses. The internal surface of the filter medium was coated with ZrO(2) nanopowder via dip-coating and heat-treatment in order to impart a filter surface charge opposite to that of the target viruses. Streaming potential measurements revealed a shift in the isoelectric point from pH <3 to between pH 5.5 and 9, respectively. While the base filter elements generally exhibited only 75% retention with respect to MS2 bacteriophages, the modified elements achieved a 7log removal (99.99999%) of these virus-like particles. The coating process also increased the specific surface area of the filters from approximately 2m(2)/g to between 12.5 and 25.5m(2)/g, thereby also potentially increasing their adsorption capacity. The results demonstrate that, given more development effort, the chosen manufacturing process has the potential to yield effective virus filters with throughputs superior to those of current virus filtration techniques.

Abrasive Particle Trajectories and Material Removal Non-Uniformity during CMP and Filtration Characteristics of CMP Slurries - A Simulation and Experimental Study

NASA Astrophysics Data System (ADS)

Rastegar, Vahid

Nanoscale finishing and planarization are integral process steps in multilevel metallization designs for integrated circuit (IC) manufacturing since it is necessary to ensure local and global surface planarization at each metal layer before depositing the next layer. Chemical mechanical planarization (CMP) has been widely recognized as the most promising technology to eliminate topographic variation and has allowed the construction of multilevel interconnection structures with a more regularly stacked sequence, resulting in better device performance [1]. Understanding fundamental of the CMP mechanisms can offer guidance to the control and optimization of the polishing processes. CMP kinematics based on slurry distribution and particle trajectories have a significant impact on MRR profiles. In this work a mathematical model to describe particle trajectories during chemical mechanical polishing was developed and extended to account for the effect of larger particles, particle location changes due to slurry dispensing and in-situ conditioning. Material removal rate (MRR) and within wafer non-uniformity (WIWNU) were determined based on the calculated particle trajectory densities. Rotary dynamics and reciprocating motion were optimized to obtain best MRR uniformity. Edge-fast MRR profile was discussed based on mechanical aspect of CMP. Using the model, we also investigated the effect of variable rotational speeds of wafer and pad, and of large particles on WIWNU and scratch growth. It was shown that the presence of even a small portion of large particles can deteriorate the WIWNU significantly and also lead to more scratches. Furthermore, it was shown that the in-situ conditioning improves the uniformity of the polished wafers. Furthermore, a combined experimental and computational study of fibrous filters for removal of larger abrasive particles from aqueous dispersions, essential to minimize defects during chemical mechanical polishing, was performed. Dilute aqueous suspensions of colloidal ceria particles, of known size distribution, were filtered at different flow rates and the filter efficiencies were measured for different particle sizes and pH, then converted to single fiber efficiencies. The particle size distributions were also measured for the influent and effluent streams. In a series of numerical simulations, the Navier-Stokes equation was solved for a single fiber using the ANSYS-FLUENT computational fluid dynamics commercial package. For dilute suspensions, the motion of the dispersed particles in the size range of 35-600 nm and zeta potential range of -50 to 50 mV was tracked in the Lagrangian reference frame including the effects of hydrodynamic drag, lift, gravity, hydrodynamic retardation, Brownian, van der Waals and electric double layer forces. The electric double layer and van der Waals forces were incorporated in the calculations by developing a user defined function. Particular attention was given to the effects of Brownian excitations, as well as the electric double layer and van der Waals forces that have been neglected in many of the previous models on the overall fiber collection efficiency for different particle sizes and charges. Moreover, the effect of flow velocity on the fiber capture efficiency and residence time was investigated. The effect of velocity on minimum collection efficiency and most penetrating particle size was investigated. It was also shown that the CFD results are in a good agreement with the experimental results.