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.

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

Stochastic Adaptive Particle Beam Tracker Using Meer Filter Feedback.

DTIC Science & Technology

1986-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Electromagnetic sunscreen model: design of experiments on particle specifications.

PubMed

Lécureux, Marie; Deumié, Carole; Enoch, Stefan; Sergent, Michelle

2015-10-01

We report a numerical study on sunscreen design and optimization. Thanks to the combined use of electromagnetic modeling and design of experiments, we are able to screen the most relevant parameters of mineral filters and to optimize sunscreens. Several electromagnetic modeling methods are used depending on the type of particles, density of particles, etc. Both the sun protection factor (SPF) and the UVB/UVA ratio are considered. We show that the design of experiments' model should include interactions between materials and other parameters. We conclude that the material of the particles is a key parameter for the SPF and the UVB/UVA ratio. Among the materials considered, none is optimal for both. The SPF is also highly dependent on the size of the particles.

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.

Numerical investigation of adhesion effects on solid particles filtration efficiency

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

PubMed

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

2018-07-01

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

[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.

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.

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.

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.

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.

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.

Filter Media Tests Under Simulated Martian Atmospheric Conditions

NASA Technical Reports Server (NTRS)

Agui, Juan H.

2016-01-01

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

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

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.

Tailoring Mechanically Robust Poly(m-phenylene isophthalamide) Nanofiber/nets for Ultrathin High-Efficiency Air Filter

PubMed Central

Zhang, Shichao; Liu, Hui; Yin, Xia; Li, Zhaoling; Yu, Jianyong; Ding, Bin

2017-01-01

Effective promotion of air filtration applications proposed for fibers requires their real nanoscale diameter, optimized pore structure, and high service strength; however, creating such filter medium has proved to be a tremendous challenge. This study first establishes a strategy to design and fabricate novel poly(m-phenylene isophthalamide) nanofiber/nets (PMIA NF/N) air filter via electrospinning/netting. Our strategy results in generation of a bimodal structure including a scaffold of nanofibers and abundant two-dimensional ultrathin (~20 nm) nanonets to synchronously construct PMIA filters by combining solution optimization, humidity regulation, and additive inspiration. Benefiting from the structural features including the true nanoscale diameter, small pore size, high porosity, and nets bonding contributed by the widely distributed nanonets, our PMIA NF/N filter exhibits the integrated properties of superlight weight (0.365 g m−2), ultrathin thickness (~0.5 μm), and high tensile strength (72.8 MPa) for effective air filtration, achieving the ultra-low penetration air filter level of 99.999% and low pressure drop of 92 Pa for 300–500 nm particles by sieving mechanism. The successful synthesis of PMIA NF/N would not only provide a promising medium for particle filtration, but also develop a versatile platform for exploring the application of nanonets in structural enhancement, separation and purification. PMID:28074880

Tailoring Mechanically Robust Poly(m-phenylene isophthalamide) Nanofiber/nets for Ultrathin High-Efficiency Air Filter

NASA Astrophysics Data System (ADS)

Zhang, Shichao; Liu, Hui; Yin, Xia; Li, Zhaoling; Yu, Jianyong; Ding, Bin

2017-01-01

Effective promotion of air filtration applications proposed for fibers requires their real nanoscale diameter, optimized pore structure, and high service strength; however, creating such filter medium has proved to be a tremendous challenge. This study first establishes a strategy to design and fabricate novel poly(m-phenylene isophthalamide) nanofiber/nets (PMIA NF/N) air filter via electrospinning/netting. Our strategy results in generation of a bimodal structure including a scaffold of nanofibers and abundant two-dimensional ultrathin (~20 nm) nanonets to synchronously construct PMIA filters by combining solution optimization, humidity regulation, and additive inspiration. Benefiting from the structural features including the true nanoscale diameter, small pore size, high porosity, and nets bonding contributed by the widely distributed nanonets, our PMIA NF/N filter exhibits the integrated properties of superlight weight (0.365 g m-2), ultrathin thickness (~0.5 μm), and high tensile strength (72.8 MPa) for effective air filtration, achieving the ultra-low penetration air filter level of 99.999% and low pressure drop of 92 Pa for 300-500 nm particles by sieving mechanism. The successful synthesis of PMIA NF/N would not only provide a promising medium for particle filtration, but also develop a versatile platform for exploring the application of nanonets in structural enhancement, separation and purification.

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.

Charged particle tracking without magnetic field: Optimal measurement of track momentum by a Bayesian analysis of the multiple measurements of deflections due to multiple scattering

NASA Astrophysics Data System (ADS)

Frosini, Mikael; Bernard, Denis

2017-09-01

We revisit the precision of the measurement of track parameters (position, angle) with optimal methods in the presence of detector resolution, multiple scattering and zero magnetic field. We then obtain an optimal estimator of the track momentum by a Bayesian analysis of the filtering innovations of a series of Kalman filters applied to the track. This work could pave the way to the development of autonomous high-performance gas time-projection chambers (TPC) or silicon wafer γ-ray space telescopes and be a powerful guide in the optimization of the design of the multi-kilo-ton liquid argon TPCs that are under development for neutrino studies.

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

PubMed

Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

2015-01-01

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

Cat Swarm Optimization algorithm for optimal linear phase FIR filter design.

PubMed

Saha, Suman Kumar; Ghoshal, Sakti Prasad; Kar, Rajib; Mandal, Durbadal

2013-11-01

In this paper a new meta-heuristic search method, called Cat Swarm Optimization (CSO) algorithm is applied to determine the best optimal impulse response coefficients of FIR low pass, high pass, band pass and band stop filters, trying to meet the respective ideal frequency response characteristics. CSO is generated by observing the behaviour of cats and composed of two sub-models. In CSO, one can decide how many cats are used in the iteration. Every cat has its' own position composed of M dimensions, velocities for each dimension, a fitness value which represents the accommodation of the cat to the fitness function, and a flag to identify whether the cat is in seeking mode or tracing mode. The final solution would be the best position of one of the cats. CSO keeps the best solution until it reaches the end of the iteration. The results of the proposed CSO based approach have been compared to those of other well-known optimization methods such as Real Coded Genetic Algorithm (RGA), standard Particle Swarm Optimization (PSO) and Differential Evolution (DE). The CSO based results confirm the superiority of the proposed CSO for solving FIR filter design problems. The performances of the CSO based designed FIR filters have proven to be superior as compared to those obtained by RGA, conventional PSO and DE. The simulation results also demonstrate that the CSO is the best optimizer among other relevant techniques, not only in the convergence speed but also in the optimal performances of the designed filters. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

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

PubMed

Saito, Masatoshi

2009-08-01

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

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design

PubMed Central

Adesina, Simeon K.; Wight, Scott A.; Akala, Emmanuel O.

2015-01-01

Purpose Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize crosslinked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Methods Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Results and Conclusion Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the crosslinking agent and stabilizer indicate the important factors for minimizing particle size. PMID:24059281

Optimization of the fabrication of novel stealth PLA-based nanoparticles by dispersion polymerization using D-optimal mixture design.

PubMed

Adesina, Simeon K; Wight, Scott A; Akala, Emmanuel O

2014-11-01

Nanoparticle size is important in drug delivery. Clearance of nanoparticles by cells of the reticuloendothelial system has been reported to increase with increase in particle size. Further, nanoparticles should be small enough to avoid lung or spleen filtering effects. Endocytosis and accumulation in tumor tissue by the enhanced permeability and retention effect are also processes that are influenced by particle size. We present the results of studies designed to optimize cross-linked biodegradable stealth polymeric nanoparticles fabricated by dispersion polymerization. Nanoparticles were fabricated using different amounts of macromonomer, initiators, crosslinking agent and stabilizer in a dioxane/DMSO/water solvent system. Confirmation of nanoparticle formation was by scanning electron microscopy (SEM). Particle size was measured by dynamic light scattering (DLS). D-optimal mixture statistical experimental design was used for the experimental runs, followed by model generation (Scheffe polynomial) and optimization with the aid of a computer software. Model verification was done by comparing particle size data of some suggested solutions to the predicted particle sizes. Data showed that average particle sizes follow the same trend as predicted by the model. Negative terms in the model corresponding to the cross-linking agent and stabilizer indicate the important factors for minimizing particle size.

Toward the Application of the Implicit Particle Filter to Real Data in a Shallow Water Model of the Nearshore Ocean

NASA Astrophysics Data System (ADS)

Miller, R.

2015-12-01

Following the success of the implicit particle filter in twin experiments with a shallow water model of the nearshore environment, the planned next step is application to the intensive Sandy Duck data set, gathered at Duck, NC. Adaptation of the present system to the Sandy Duck data set will require construction and evaluation of error models for both the model and the data, as well as significant modification of the system to allow for the properties of the data set. Successful implementation of the particle filter promises to shed light on the details of the capabilities and limitations of shallow water models of the nearshore ocean relative to more detailed models. Since the shallow water model admits distinct dynamical regimes, reliable parameter estimation will be important. Previous work by other groups give cause for optimism. In this talk I will describe my progress toward implementation of the new system, including problems solved, pitfalls remaining and preliminary results

A Wide Field of View Plasma Spectrometer

DOE PAGES

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

2016-07-01

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

Ridge filter design and optimization for the broad-beam three-dimensional irradiation system for heavy-ion radiotherapy.

PubMed

Schaffner, B; Kanai, T; Futami, Y; Shimbo, M; Urakabe, E

2000-04-01

The broad-beam three-dimensional irradiation system under development at National Institute of Radiological Sciences (NIRS) requires a small ridge filter to spread the initially monoenergetic heavy-ion beam to a small spread-out Bragg peak (SOBP). A large SOBP covering the target volume is then achieved by a superposition of differently weighted and displaced small SOBPs. Two approaches were studied for the definition of a suitable ridge filter and experimental verifications were performed. Both approaches show a good agreement between the calculated and measured dose and lead to a good homogeneity of the biological dose in the target. However, the ridge filter design that produces a Gaussian-shaped spectrum of the particle ranges was found to be more robust to small errors and uncertainties in the beam application. Furthermore, an optimization procedure for two fields was applied to compensate for the missing dose from the fragmentation tail for the case of a simple-geometry target. The optimized biological dose distributions show that a very good homogeneity is achievable in the target.

Rational approximations to rational models: alternative algorithms for category learning.

PubMed

Sanborn, Adam N; Griffiths, Thomas L; Navarro, Daniel J

2010-10-01

Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models is thus explaining how optimal solutions can be approximated by psychological processes. We outline a general strategy for answering this question, namely to explore the psychological plausibility of approximation algorithms developed in computer science and statistics. In particular, we argue that Monte Carlo methods provide a source of rational process models that connect optimal solutions to psychological processes. We support this argument through a detailed example, applying this approach to Anderson's (1990, 1991) rational model of categorization (RMC), which involves a particularly challenging computational problem. Drawing on a connection between the RMC and ideas from nonparametric Bayesian statistics, we propose 2 alternative algorithms for approximate inference in this model. The algorithms we consider include Gibbs sampling, a procedure appropriate when all stimuli are presented simultaneously, and particle filters, which sequentially approximate the posterior distribution with a small number of samples that are updated as new data become available. Applying these algorithms to several existing datasets shows that a particle filter with a single particle provides a good description of human inferences.

Experimental study of acoustic agglomeration and fragmentation on coal-fired ash

NASA Astrophysics Data System (ADS)

Shen, Guoqing; Huang, Xiaoyu; He, Chunlong; Zhang, Shiping; An, Liansuo; Wang, Liang; Chen, Yanqiao; Li, Yongsheng

2018-02-01

As the major part of air pollution, inhalable particles, especially fine particles are doing great harm to human body due to smaller particle size and absorption of hazardous components. However, the removal efficiency of current particles filtering devices is low. Acoustic agglomeration is considered as a very effective pretreatment technique for removing particles. Fine particles collide, agglomerate and grow up in the sound field and the fine particles can be removed by conventional particles devices easily. In this paper, the agglomeration and fragmentation of 3 different kinds of particles with different size distributions are studied experimentally in the sound field. It is found that there exists an optimal frequency at 1200 Hz for different particles. The agglomeration efficiency of inhalable particles increases with SPL increasing for the unimodal particles with particle diameter less than 10 μm. For the bimodal particles, the optimal SPLs are 115 and 120 dB with the agglomeration efficiencies of 25% and 55%. A considerable effectiveness of agglomeration could only be obtained in a narrow SPL range and it decreases significantly over the range for the particles fragmentation.

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.

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.

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.

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.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

A photon source model based on particle transport in a parameterized accelerator structure for Monte Carlo dose calculations.

PubMed

Ishizawa, Yoshiki; Dobashi, Suguru; Kadoya, Noriyuki; Ito, Kengo; Chiba, Takahito; Takayama, Yoshiki; Sato, Kiyokazu; Takeda, Ken

2018-05-17

An accurate source model of a medical linear accelerator is essential for Monte Carlo (MC) dose calculations. This study aims to propose an analytical photon source model based on particle transport in parameterized accelerator structures, focusing on a more realistic determination of linac photon spectra compared to existing approaches. We designed the primary and secondary photon sources based on the photons attenuated and scattered by a parameterized flattening filter. The primary photons were derived by attenuating bremsstrahlung photons based on the path length in the filter. Conversely, the secondary photons were derived from the decrement of the primary photons in the attenuation process. This design facilitates these sources to share the free parameters of the filter shape and be related to each other through the photon interaction in the filter. We introduced two other parameters of the primary photon source to describe the particle fluence in penumbral regions. All the parameters are optimized based on calculated dose curves in water using the pencil-beam-based algorithm. To verify the modeling accuracy, we compared the proposed model with the phase space data (PSD) of the Varian TrueBeam 6 and 15 MV accelerators in terms of the beam characteristics and the dose distributions. The EGS5 Monte Carlo code was used to calculate the dose distributions associated with the optimized model and reference PSD in a homogeneous water phantom and a heterogeneous lung phantom. We calculated the percentage of points passing 1D and 2D gamma analysis with 1%/1 mm criteria for the dose curves and lateral dose distributions, respectively. The optimized model accurately reproduced the spectral curves of the reference PSD both on- and off-axis. The depth dose and lateral dose profiles of the optimized model also showed good agreement with those of the reference PSD. The passing rates of the 1D gamma analysis with 1%/1 mm criteria between the model and PSD were 100% for 4 × 4, 10 × 10, and 20 × 20 cm 2 fields at multiple depths. For the 2D dose distributions calculated in the heterogeneous lung phantom, the 2D gamma pass rate was 100% for 6 and 15 MV beams. The model optimization time was less than 4 min. The proposed source model optimization process accurately produces photon fluence spectra from a linac using valid physical properties, without detailed knowledge of the geometry of the linac head, and with minimal optimization time. © 2018 American Association of Physicists in Medicine.

[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

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

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.

Internal Structure and Morphology Profile in Optimizing Filter Membrane Performance

NASA Astrophysics Data System (ADS)

Sanaei, Pejman; Cummings, Linda J.

Membrane filters are in widespread use, and manufacturers have considerable interest in improving their performance, in terms of particle retention properties, and total throughput over the filter lifetime. A good question to ask is therefore: what is the optimal configuration of filter membranes, in terms of internal morphology (pore size and shape), to achieve the most efficient filtration? To answer this question, we must first propose a robust measure of filtration performance. As filtration occurs the membrane becomes blocked, or fouled, by the impurities in the feed solution, and any performance measure must take account of this. For example, one performance measure might be the total throughput (the volume of filtered feed solution) at the end of the filtration process, when the membrane is so badly blocked that it is deemed no longer functional. Here we present a simplified mathematical model, which (i) characterizes membrane internal pore structure via pore or permeability profiles in the depth of the membrane; (ii) accounts for various membrane fouling mechanisms (adsorption, blocking and cake formation); and (iv) predicts the optimum pore profile for our chosen performance measure. NSF DMS-1261596 and NSF DMS-1615719.

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

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

Viswanathan, Sandeep; Rothamer, David; Zelenyuk, Alla

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

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.

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.

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.

Development of an on-line exposure system to determine freshly produced diesel engine emission-induced cellular effects.

PubMed

Oostingh, Gertie J; Papaioannou, Eleni; Chasapidis, Leonidas; Akritidis, Theofylaktos; Konstandopoulos, Athanasios G; Duschl, Albert

2013-09-01

Diesel engine emission particle filters are often placed at exhaust outlets to remove particles from the exhaust. The use of filters results in the exposure to a reduced number of nanometer-sized particles, which might be more harmful than the exposure to a larger number of micrometer-sized particles. An in vitro exposure system was established to expose human alveolar epithelial cells to freshly generated exhaust. Computer simulations were used to determine the optimal flow characteristics and ensure equal exposure conditions for each well of a 6-well plate. A selective particle size sampler was used to continuously deliver diesel soot particles with different particle size distributions to cells in culture. To determine, whether the system could be used for cellular assays, alterations in cytokine production and cell viability of human alveolar A549 cells were determined after 3h on-line exposure followed by a 21-h conventional incubation period. Data indicated that complete diesel engine emission slightly affected pre-stimulated cells, but naive cells were not affected. The fractions containing large or small particles never affected the cells. The experimental set-up allowed a reliable exposure of the cells to the complete exhaust fraction or to the fractions containing either large or small diesel engine emission particles. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Design of minimum multiplier fractional order differentiator based on lattice wave digital filter.

PubMed

Barsainya, Richa; Rawat, Tarun Kumar; Kumar, Manjeet

2017-01-01

In this paper, a novel design of fractional order differentiator (FOD) based on lattice wave digital filter (LWDF) is proposed which requires minimum number of multiplier for its structural realization. Firstly, the FOD design problem is formulated as an optimization problem using the transfer function of lattice wave digital filter. Then, three optimization algorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO) and cuckoo search algorithm (CSA) are applied to determine the optimal LWDF coefficients. The realization of FOD using LWD structure increases the design accuracy, as only N number of coefficients are to be optimized for Nth order FOD. Finally, two design examples of 3rd and 5th order lattice wave digital fractional order differentiator (LWDFOD) are demonstrated to justify the design accuracy. The performance analysis of the proposed design is carried out based on magnitude response, absolute magnitude error (dB), root mean square (RMS) magnitude error, arithmetic complexity, convergence profile and computation time. Simulation results are attained to show the comparison of the proposed LWDFOD with the published works and it is observed that an improvement of 29% is obtained in the proposed design. The proposed LWDFOD approximates the ideal FOD and surpasses the existing ones reasonably well in mid and high frequency range, thereby making the proposed LWDFOD a promising technique for the design of digital FODs. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-01-01

Filtering facepiece respirators (FFRs) are commonly worn by first responders, first receivers, and other exposed groups to protect against exposure to airborne particles, including those originated by combustion. Most of these FFRs are NIOSH-certified (e.g., N95-type) based on the performance testing of their filters against charge-equilibrated aerosol challenges, e.g., NaCl. However, it has not been examined if the filtration data obtained with the NaCl-challenged FFR filters adequately represent the protection against real aerosol hazards such as combustion particles. A filter sample of N95 FFR mounted on a specially designed holder was challenged with NaCl particles and three combustion aerosols generated in a test chamber by burning wood, paper, and plastic. The concentrations upstream (Cup) and downstream (Cdown) of the filter were measured with a TSI P-Trak condensation particle counter and a Grimm Nanocheck particle spectrometer. Penetration was determined as (Cdown/Cup) ×100%. Four test conditions were chosen to represent inhalation flows of 15, 30, 55, and 85 L/min. Results showed that the penetration values of combustion particles were significantly higher than those of the "model" NaCl particles (p < 0.05), raising a concern about applicability of the N95 filters performance obtained with the NaCl aerosol challenge to protection against combustion particles. Aerosol type, inhalation flow rate and particle size were significant (p < 0.05) factors affecting the performance of the N95 FFR filter. In contrast to N95 filters, the penetration of combustion particles through R95 and P95 FFR filters (were tested in addition to N95) were not significantly higher than that obtained with NaCl particles. The findings were attributed to several effects, including the degradation of an N95 filter due to hydrophobic organic components generated into the air by combustion. Their interaction with fibers is anticipated to be similar to those involving "oily" particles. The findings of this study suggest that the efficiency of N95 respirator filters obtained with the NaCl aerosol challenge may not accurately predict (and rather overestimate) the filter efficiency against combustion particles.

Evolution of the cerebellum as a neuronal machine for Bayesian state estimation

NASA Astrophysics Data System (ADS)

Paulin, M. G.

2005-09-01

The cerebellum evolved in association with the electric sense and vestibular sense of the earliest vertebrates. Accurate information provided by these sensory systems would have been essential for precise control of orienting behavior in predation. A simple model shows that individual spikes in electrosensory primary afferent neurons can be interpreted as measurements of prey location. Using this result, I construct a computational neural model in which the spatial distribution of spikes in a secondary electrosensory map forms a Monte Carlo approximation to the Bayesian posterior distribution of prey locations given the sense data. The neural circuit that emerges naturally to perform this task resembles the cerebellar-like hindbrain electrosensory filtering circuitry of sharks and other electrosensory vertebrates. The optimal filtering mechanism can be extended to handle dynamical targets observed from a dynamical platform; that is, to construct an optimal dynamical state estimator using spiking neurons. This may provide a generic model of cerebellar computation. Vertebrate motion-sensing neurons have specific fractional-order dynamical characteristics that allow Bayesian state estimators to be implemented elegantly and efficiently, using simple operations with asynchronous pulses, i.e. spikes. The computational neural models described in this paper represent a novel kind of particle filter, using spikes as particles. The models are specific and make testable predictions about computational mechanisms in cerebellar circuitry, while providing a plausible explanation of cerebellar contributions to aspects of motor control, perception and cognition.

Comparison of PIXE and XRF analysis of airborne particulate matter samples collected on Teflon and quartz fibre filters

NASA Astrophysics Data System (ADS)

Chiari, M.; Yubero, E.; Calzolai, G.; Lucarelli, F.; Crespo, J.; Galindo, N.; Nicolás, J. F.; Giannoni, M.; Nava, S.

2018-02-01

Within the framework of research projects focusing on the sampling and analysis of airborne particulate matter, Particle Induced X-ray Emission (PIXE) and Energy Dispersive X-ray Fluorescence (ED-XRF) techniques are routinely used in many laboratories throughout the world to determine the elemental concentration of the particulate matter samples. In this work an inter-laboratory comparison of the results obtained from analysing several samples (collected on both Teflon and quartz fibre filters) using both techniques is presented. The samples were analysed by PIXE (in Florence, at the 3 MV Tandetron accelerator of INFN-LABEC laboratory) and by XRF (in Elche, using the ARL Quant'X EDXRF spectrometer with specific conditions optimized for specific groups of elements). The results from the two sets of measurements are in good agreement for all the analysed samples, thus validating the use of the ARL Quant'X EDXRF spectrometer and the selected measurement protocol for the analysis of aerosol samples. Moreover, thanks to the comparison of PIXE and XRF results on Teflon and quartz fibre filters, possible self-absorption effects due to the penetration of the aerosol particles inside the quartz fibre-filters were quantified.

Investigations into the fouling mechanism of parvovirus filters during filtration of freeze-thawed mAb drug substance solutions.

PubMed

Barnard, James G; Kahn, David; Cetlin, David; Randolph, Theodore W; Carpenter, John F

2014-03-01

Filtration to remove viruses is one of the single most expensive steps in the production of mAb drug products. Therefore, virus filtration steps should be fully optimized, and any decline in flow rates warrants investigation into the causes of such membrane fouling. In the current study, it was found that freezing and thawing of a mAb bulk drug solution caused a substantial decrease in viral filter membrane flow rate. Freezing and thawing also caused formation of aggregates and particles across a broad size range, including particles that could be detected by microflow imaging (≥1 μm in size). However, removal of these particles offered little protection against flow rate decline during viral filtration. Further investigation revealed that trace amounts of aggregates (ca. 10⁻⁶ of the total mass of protein in solution) approximately 20-40 nm in size were primarily responsible for the observed membrane fouling. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

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.

4-channels coherent perfect absorption (CPA)-type demultiplexer using plasmonic nano spheres

NASA Astrophysics Data System (ADS)

Soltani, Mohamadreza; Keshavarzi, Rasul

2017-10-01

The current research represents a nanoscale and compact 4-channels plasmonic demultiplexer. It includes eight coherent perfect absorption (CPA) - type filters. The operation principle is based on the absorbable formation of a conductive path in the dielectric layer of a plasmonic nano-spheres waveguide. Since the CPA efficiency depends strongly on the number of plasmonic nano-spheres and the nano spheres location, an efficient binary optimization method based on the Particle Swarm Optimization algorithm is used to design an optimized array of the plasmonic nano-sphere in order to achieve the maximum absorption coefficient in the 'off' state.

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.

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.

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.

Robust estimation of event-related potentials via particle filter.

PubMed

Fukami, Tadanori; Watanabe, Jun; Ishikawa, Fumito

2016-03-01

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

Packing Optimization of Sorbent Bed Containing Dissimilar and Irregular Shaped Media

NASA Technical Reports Server (NTRS)

Holland, Nathan; Guttromson, Jayleen; Piowaty, Hailey

2011-01-01

The Fire Cartridge is a packed bed air filter with two different and separate layers of media designed to provide respiratory protection from combustion products after a fire event on the International Space Station (ISS). The first layer of media is a carbon monoxide catalyst and the second layer of media is universal carbon. During development of Fire Cartridge prototypes, the two media beds were noticed to have shifted inside the cartridge. The movement of media within the cartridge can cause mixing of the bed layers, air voids, and channeling, which could cause preferential air flow and allow contaminants to pass through without removal. An optimally packed bed mitigates these risks and ensures effective removal of contaminants from the air. In order to optimally pack each layer, vertical, horizontal, and orbital agitations were investigated and a packed bulk density was calculated for each method. Packed bulk density must be calculated for each media type to accommodate variations in particle size, shape, and density. Additionally, the optimal vibration parameters must be re-evaluated for each batch of media due to variations in particle size distribution between batches. For this application it was determined that orbital vibrations achieve an optimal pack density and the two media layers can be packed by the same method. Another finding was media with a larger size distribution of particles achieve an optimal bed pack easier than media with a smaller size distribution of particles.

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.

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.

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

NASA Astrophysics Data System (ADS)

Fuse, Takashi; Nagara, Keita

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

Hernandez, F.; Liang, X.

2017-12-01

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

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

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.

Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing

PubMed Central

Huth, Jacob; Masquelier, Timothée; Arleo, Angelo

2018-01-01

We developed Convis, a Python simulation toolbox for large scale neural populations which offers arbitrary receptive fields by 3D convolutions executed on a graphics card. The resulting software proves to be flexible and easily extensible in Python, while building on the PyTorch library (The Pytorch Project, 2017), which was previously used successfully in deep learning applications, for just-in-time optimization and compilation of the model onto CPU or GPU architectures. An alternative implementation based on Theano (Theano Development Team, 2016) is also available, although not fully supported. Through automatic differentiation, any parameter of a specified model can be optimized to approach a desired output which is a significant improvement over e.g., Monte Carlo or particle optimizations without gradients. We show that a number of models including even complex non-linearities such as contrast gain control and spiking mechanisms can be implemented easily. We show in this paper that we can in particular recreate the simulation results of a popular retina simulation software VirtualRetina (Wohrer and Kornprobst, 2009), with the added benefit of providing (1) arbitrary linear filters instead of the product of Gaussian and exponential filters and (2) optimization routines utilizing the gradients of the model. We demonstrate the utility of 3d convolution filters with a simple direction selective filter. Also we show that it is possible to optimize the input for a certain goal, rather than the parameters, which can aid the design of experiments as well as closed-loop online stimulus generation. Yet, Convis is more than a retina simulator. For instance it can also predict the response of V1 orientation selective cells. Convis is open source under the GPL-3.0 license and available from https://github.com/jahuth/convis/ with documentation at https://jahuth.github.io/convis/. PMID:29563867

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.

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...

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

NASA Astrophysics Data System (ADS)

Closas, Pau; Guillamon, Antoni

2017-12-01

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

UV/TiO2 photocatalytic disinfection of carbon-bacteria complexes in activated carbon-filtered water: Laboratory and pilot-scale investigation.

PubMed

Zhao, Jin Hui; Chen, Wei; Zhao, Yaqian; Liu, Cuiyun; Liu, Ranbin

2015-01-01

The occurrence of carbon-bacteria complexes in activated carbon filtered water has posed a public health problem regarding the biological safety of drinking water. The application of combined process of ultraviolet radiation and nanostructure titanium dioxide (UV/TiO2) photocatalysis for the disinfection of carbon-bacteria complexes were assessed in this study. Results showed that a 1.07 Lg disinfection rate can be achieved using a UV dose of 20 mJ cm(-2), while the optimal UV intensity was 0.01 mW cm(-2). Particle sizes ≥8 μm decreased the disinfection efficiency, whereas variation in particle number in activated carbon-filtered water did not significantly affect the disinfection efficiency. Photoreactivation ratio was reduced from 12.07% to 1.69% when the UV dose was increased from 5 mJ cm(-2) to 20 mJ cm(-2). Laboratory and on-site pilot-scale experiments have demonstrated that UV/TiO2 photocatalytic disinfection technology is capable of controlling the risk posed by carbon-bacteria complexes and securing drinking water safety.

Development of an Indexing Media Filtration System for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Agui, Juan H.; Vijayakumar, R.

2013-01-01

The effective maintenance of air quality aboard spacecraft cabins will be vital to future human exploration missions. A key component will be the air cleaning filtration system which will need to remove a broad size range of particles derived from multiple biological and material sources. In addition, during surface missions any extraterrestrial planetary dust, including dust generated by near-by ISRU equipment, which is tracked into the habitat will also need to be managed by the filtration system inside the pressurized habitat compartments. An indexing media filter system is being developed to meet the demand for long-duration missions that will result in dramatic increases in filter service life and loading capacity, and will require minimal crew involvement. The filtration system consists of three stages: an inertial impactor stage, an indexing media stage, and a high-efficiency filter stage, packaged in a stacked modular cartridge configuration. Each stage will target a specific range of particle sizes that optimize the filtration and regeneration performance of the system. An 1/8th scale and full-scale prototype of the filter system have been fabricated and have been tested in the laboratory and reduced gravity environments that simulate conditions on spacecrafts, landers and habitats. Results from recent laboratory and reduce-gravity flight tests data will be presented. The features of the new filter system may also benefit other closed systems, such as submarines, and remote location terrestrial installations where servicing and replacement of filter units is not practical.

Particle Swarm Optimization Based Feature Enhancement and Feature Selection for Improved Emotion Recognition in Speech and Glottal Signals

PubMed Central

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature. PMID:25799141

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

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.

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.

Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

PubMed

Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

2013-07-01

Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

Lávička, David; Kovařík, Petr

2012-04-01

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

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

DTIC Science & Technology

2016-12-15

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

An Integrated approach to the Space Situational Awareness Problem

DTIC Science & Technology

2016-12-15

data coming from the sensors. We developed particle-based Gaussian Mixture Filters that are immune to the “curse of dimensionality”/ “particle...depletion” problem inherent in particle filtering . This method maps the data assimilation/ filtering problem into an unsupervised learning problem. Results...Gaussian Mixture Filters ; particle depletion; Finite Set Statistics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 1

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.

Effect of gamma-ray irradiation on the dewaterability of waste activated sludge

NASA Astrophysics Data System (ADS)

Wu, Yuqi; Jiang, Yinghe; Ke, Guojun; Liu, Yingjiu

2017-01-01

The effect of gamma-ray irradiation on waste activated sludge (WAS) dewaterability was investigated with irradiation doses of 0-15 kGy. Time to filter (TTF50), specific resistance of filtration (SRF) and water content of sludge cake were measured to evaluate sludge dewaterability. Soluble chemical oxygen demand (SCOD), soluble extracellular polymeric substances (EPS) concentration and sludge particle size were determined to explain changes in sludge dewaterability. The optimal irradiation dose to obtain the maximum dewaterability characteristics was 1-4 kGy, which generated sludge with optimal disintegration (1.5-4.0%), soluble EPS concentration (590-750 mg/L) and particle size distribution (100-115 μm diameter). The combination of irradiation and cationic polyacrylamide (CPAM) addition exhibited minimal synergistic effect on increasing sludge dewatering rate compared with CPAM conditioning alone.

An application of PSO algorithm for multi-criteria geometry optimization of printed low-pass filters based on conductive periodic structures

NASA Astrophysics Data System (ADS)

Steckiewicz, Adam; Butrylo, Boguslaw

2017-08-01

In this paper we discussed the results of a multi-criteria optimization scheme as well as numerical calculations of periodic conductive structures with selected geometry. Thin printed structures embedded on a flexible dielectric substrate may be applied as simple, cheap, passive low-pass filters with an adjustable cutoff frequency in low (up to 1 MHz) radio frequency range. The analysis of an electromagnetic phenomena in presented structures was realized on the basis of a three-dimensional numerical model of three proposed geometries of periodic elements. The finite element method (FEM) was used to obtain a solution of an electromagnetic harmonic field. Equivalent lumped electrical parameters of printed cells obtained in such manner determine the shape of an amplitude transmission characteristic of a low-pass filter. A nonlinear influence of a printed cell geometry on equivalent parameters of cells electric model, makes it difficult to find the desired optimal solution. Therefore an optimization problem of optimal cell geometry estimation with regard to an approximation of the determined amplitude transmission characteristic with an adjusted cutoff frequency, was obtained by the particle swarm optimization (PSO) algorithm. A dynamically suitable inertia factor was also introduced into the algorithm to improve a convergence to a global extremity of a multimodal objective function. Numerical results as well as PSO simulation results were characterized in terms of approximation accuracy of predefined amplitude characteristics in a pass-band, stop-band and cutoff frequency. Three geometries of varying degrees of complexity were considered and their use in signal processing systems was evaluated.

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.

Self adaptive multi-scale morphology AVG-Hat filter and its application to fault feature extraction for wheel bearing

NASA Astrophysics Data System (ADS)

Deng, Feiyue; Yang, Shaopu; Tang, Guiji; Hao, Rujiang; Zhang, Mingliang

2017-04-01

Wheel bearings are essential mechanical components of trains, and fault detection of the wheel bearing is of great significant to avoid economic loss and casualty effectively. However, considering the operating conditions, detection and extraction of the fault features hidden in the heavy noise of the vibration signal have become a challenging task. Therefore, a novel method called adaptive multi-scale AVG-Hat morphology filter (MF) is proposed to solve it. The morphology AVG-Hat operator not only can suppress the interference of the strong background noise greatly, but also enhance the ability of extracting fault features. The improved envelope spectrum sparsity (IESS), as a new evaluation index, is proposed to select the optimal filtering signal processed by the multi-scale AVG-Hat MF. It can present a comprehensive evaluation about the intensity of fault impulse to the background noise. The weighted coefficients of the different scale structural elements (SEs) in the multi-scale MF are adaptively determined by the particle swarm optimization (PSO) algorithm. The effectiveness of the method is validated by analyzing the real wheel bearing fault vibration signal (e.g. outer race fault, inner race fault and rolling element fault). The results show that the proposed method could improve the performance in the extraction of fault features effectively compared with the multi-scale combined morphological filter (CMF) and multi-scale morphology gradient filter (MGF) methods.

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.

Damage Detection in Flexible Plates through Reduced-Order Modeling and Hybrid Particle-Kalman Filtering

PubMed Central

Capellari, Giovanni; Eftekhar Azam, Saeed; Mariani, Stefano

2015-01-01

Health monitoring of lightweight structures, like thin flexible plates, is of interest in several engineering fields. In this paper, a recursive Bayesian procedure is proposed to monitor the health of such structures through data collected by a network of optimally placed inertial sensors. As a main drawback of standard monitoring procedures is linked to the computational costs, two remedies are jointly considered: first, an order-reduction of the numerical model used to track the structural dynamics, enforced with proper orthogonal decomposition; and, second, an improved particle filter, which features an extended Kalman updating of each evolving particle before the resampling stage. The former remedy can reduce the number of effective degrees-of-freedom of the structural model to a few only (depending on the excitation), whereas the latter one allows to track the evolution of damage and to locate it thanks to an intricate formulation. To assess the effectiveness of the proposed procedure, the case of a plate subject to bending is investigated; it is shown that, when the procedure is appropriately fed by measurements, damage is efficiently and accurately estimated. PMID:26703615

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.

On optimal infinite impulse response edge detection filters

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1991-01-01

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters operating in two orthogonal directions. The implementation is very simple and computationally efficient, has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.

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.

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

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.

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

NASA Astrophysics Data System (ADS)

Metzger, Kathryn E.

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

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.

Development of an Indexing Media Filtration System for Long Duration Space Missions

NASA Technical Reports Server (NTRS)

Agui, Juan H.; Vijayakumar, R.

2013-01-01

The effective maintenance of air quality aboard spacecraft cabins will be vital to future human exploration missions. A key component will be the air cleaning filtration system which will need to remove a broad size range of particles including skin flakes, hair and clothing fibers, other biological matter, and particulate matter derived from material and equipment wear. In addition, during surface missions any extraterrestrial planetary dust, including dust generated by near-by ISRU equipment, which is tracked into the habitat will also need to be managed by the filtration system inside the pressurized habitat compartments. An indexing media filter system is being developed to meet the demand for long-duration missions that will result in dramatic increases in filter service life and loading capacity, and will require minimal crew involvement. These features may also benefit other closed systems, such as submarines, and remote location terrestrial installations where servicing and replacement of filter units is not practical. The filtration system consists of three stages: an inertial impactor stage, an indexing media stage, and a high-efficiency filter stage, packaged in a stacked modular cartridge configuration. Each stage will target a specific range of particle sizes that optimize the filtration and regeneration performance of the system. An 1/8th scale and full-scale prototype of the filter system have been fabricated and have been tested in the laboratory and reduced gravity environments that simulate conditions on spacecrafts, landers and habitats. Results from recent laboratory and reducegravity flight tests data will be presented.

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.

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.

Detection and removal of impurities in nitric oxide generated from air by pulsed electrical discharge.

PubMed

Yu, Binglan; Blaesi, Aron H; Casey, Noel; Raykhtsaum, Grigory; Zazzeron, Luca; Jones, Rosemary; Morrese, Alexander; Dobrynin, Danil; Malhotra, Rajeev; Bloch, Donald B; Goldstein, Lee E; Zapol, Warren M

2016-11-30

Inhalation of nitric oxide (NO) produces selective pulmonary vasodilation without dilating the systemic circulation. However, the current NO/N 2 cylinder delivery system is cumbersome and expensive. We developed a lightweight, portable, and economical device to generate NO from air by pulsed electrical discharge. The objective of this study was to investigate and optimize the purity and safety of NO generated by this device. By using low temperature streamer discharges in the plasma generator, we produced therapeutic levels of NO with very low levels of nitrogen dioxide (NO 2 ) and ozone. Despite the low temperature, spark generation eroded the surface of the electrodes, contaminating the gas stream with metal particles. During prolonged NO generation there was gradual loss of the iridium high-voltage tip (-90 μg/day) and the platinum-nickel ground electrode (-55 μg/day). Metal particles released from the electrodes were trapped by a high-efficiency particulate air (HEPA) filter. Quadrupole mass spectroscopy measurements of effluent gas during plasma NO generation showed that a single HEPA filter removed all of the metal particles. Mice were exposed to breathing 50 parts per million of electrically generated NO in air for 28 days with only a scavenger and no HEPA filter; the mice did not develop pulmonary inflammation or structural changes and iridium and platinum particles were not detected in the lungs of these mice. In conclusion, an electric plasma generator produced therapeutic levels of NO from air; scavenging and filtration effectively eliminated metallic impurities from the effluent gas. Copyright © 2016 Elsevier Inc. All rights reserved.

Detection and Removal of Impurities in Nitric Oxide Generated from Air by Pulsed Electrical Discharge

PubMed Central

Yu, Binglan; Blaesi, Aron H.; Casey, Noel; Raykhtsaum, Grigory; Zazzeron, Luca; Jones, Rosemary; Morrese, Alexander; Dobrynin, Danil; Malhotra, Rajeev; Bloch, Donald B.; Goldstein, Lee E.; Zapol, Warren M.

2016-01-01

Inhalation of nitric oxide (NO) produces selective pulmonary vasodilation without dilating the systemic circulation. However, the current NO/N2 cylinder delivery system is cumbersome and expensive. We developed a lightweight, portable, and economical device to generate NO from air by pulsed electrical discharge. The objective of this study was to investigate and optimize the purity and safety of NO generated by this device. By using low temperature streamer discharges in the plasma generator, we produced therapeutic levels of NO with very low levels of nitrogen dioxide (NO2) and ozone. Despite the low temperature, spark generation eroded the surface of the electrodes, contaminating the gas stream with metal particles. During prolonged NO generation there was gradual loss of the iridium high-voltage tip (−90 µg/day) and the platinum-nickel ground electrode (−55 µg/day). Metal particles released from the electrodes were trapped by a high-efficiency particulate air (HEPA) filter. Quadrupole mass spectroscopy measurements of effluent gas during plasma NO generation showed that a single HEPA filter removed all of the metal particles. Mice were exposed to breathing 50 parts per million of electrically generated NO in air for 28 days with only a scavenger and no HEPA filter; the mice did not develop pulmonary inflammation or structural changes and iridium and platinum particles were not detected in the lungs of these mice. In conclusion, an electric plasma generator produced therapeutic levels of NO from air; scavenging and filtration effectively eliminated metallic impurities from the effluent gas. PMID:27592386

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 ...

Air-to-Air Missile Vector Scoring

DTIC Science & Technology

2012-03-22

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

Particle identification algorithms for the PANDA Endcap Disc DIRC

NASA Astrophysics Data System (ADS)

Schmidt, M.; Ali, A.; Belias, A.; Dzhygadlo, R.; Gerhardt, A.; Götzen, K.; Kalicy, G.; Krebs, M.; Lehmann, D.; Nerling, F.; Patsyuk, M.; Peters, K.; Schepers, G.; Schmitt, L.; Schwarz, C.; Schwiening, J.; Traxler, M.; Böhm, M.; Eyrich, W.; Lehmann, A.; Pfaffinger, M.; Uhlig, F.; Düren, M.; Etzelmüller, E.; Föhl, K.; Hayrapetyan, A.; Kreutzfeld, K.; Merle, O.; Rieke, J.; Wasem, T.; Achenbach, P.; Cardinali, M.; Hoek, M.; Lauth, W.; Schlimme, S.; Sfienti, C.; Thiel, M.

2017-12-01

The Endcap Disc DIRC has been developed to provide an excellent particle identification for the future PANDA experiment by separating pions and kaons up to a momentum of 4 GeV/c with a separation power of 3 standard deviations in the polar angle region from 5o to 22o. This goal will be achieved using dedicated particle identification algorithms based on likelihood methods and will be applied in an offline analysis and online event filtering. This paper evaluates the resulting PID performance using Monte-Carlo simulations to study basic single track PID as well as the analysis of complex physics channels. The online reconstruction algorithm has been tested with a Virtex4 FGPA card and optimized regarding the resulting constraints.

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

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

Stillo, Andrew; Ricketts, Craig I.

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

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

PubMed

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

2009-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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.

The effect of spectral filters on visual search in stroke patients.

PubMed

Beasley, Ian G; Davies, Leon N

2013-01-01

Visual search impairment can occur following stroke. The utility of optimal spectral filters on visual search in stroke patients has not been considered to date. The present study measured the effect of optimal spectral filters on visual search response time and accuracy, using a task requiring serial processing. A stroke and control cohort undertook the task three times: (i) using an optimally selected spectral filter; (ii) the subjects were randomly assigned to two groups with group 1 using an optimal filter for two weeks, whereas group 2 used a grey filter for two weeks; (iii) the groups were crossed over with group 1 using a grey filter for a further two weeks and group 2 given an optimal filter, before undertaking the task for the final time. Initial use of an optimal spectral filter improved visual search response time but not error scores in the stroke cohort. Prolonged use of neither an optimal nor a grey filter improved response time or reduced error scores. In fact, response times increased with the filter, regardless of its type, for stroke and control subjects; this outcome may be due to contrast reduction or a reflection of task design, given that significant practice effects were noted.

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.

Statistical model for speckle pattern optimization.

PubMed

Su, Yong; Zhang, Qingchuan; Gao, Zeren

2017-11-27

Image registration is the key technique of optical metrologies such as digital image correlation (DIC), particle image velocimetry (PIV), and speckle metrology. Its performance depends critically on the quality of image pattern, and thus pattern optimization attracts extensive attention. In this article, a statistical model is built to optimize speckle patterns that are composed of randomly positioned speckles. It is found that the process of speckle pattern generation is essentially a filtered Poisson process. The dependence of measurement errors (including systematic errors, random errors, and overall errors) upon speckle pattern generation parameters is characterized analytically. By minimizing the errors, formulas of the optimal speckle radius are presented. Although the primary motivation is from the field of DIC, we believed that scholars in other optical measurement communities, such as PIV and speckle metrology, will benefit from these discussions.

A Novel Segmentation Approach Combining Region- and Edge-Based Information for Ultrasound Images

PubMed Central

Luo, Yaozhong; Liu, Longzhong; Li, Xuelong

2017-01-01

Ultrasound imaging has become one of the most popular medical imaging modalities with numerous diagnostic applications. However, ultrasound (US) image segmentation, which is the essential process for further analysis, is a challenging task due to the poor image quality. In this paper, we propose a new segmentation scheme to combine both region- and edge-based information into the robust graph-based (RGB) segmentation method. The only interaction required is to select two diagonal points to determine a region of interest (ROI) on the original image. The ROI image is smoothed by a bilateral filter and then contrast-enhanced by histogram equalization. Then, the enhanced image is filtered by pyramid mean shift to improve homogeneity. With the optimization of particle swarm optimization (PSO) algorithm, the RGB segmentation method is performed to segment the filtered image. The segmentation results of our method have been compared with the corresponding results obtained by three existing approaches, and four metrics have been used to measure the segmentation performance. The experimental results show that the method achieves the best overall performance and gets the lowest ARE (10.77%), the second highest TPVF (85.34%), and the second lowest FPVF (4.48%). PMID:28536703

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.

Sequential bearings-only-tracking initiation with particle filtering method.

PubMed

Liu, Bin; Hao, Chengpeng

2013-01-01

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association problem). In addition, the nonlinear measurements lead to a non-Gaussian posterior probability density function (pdf) in the optimal Bayesian sequential estimation framework. The consequence of this nonlinear/non-Gaussian context is the absence of a closed-form solution. This paper models the linkage uncertainty and the nonlinear/non-Gaussian estimation problem jointly with solid Bayesian formalism. A particle filtering (PF) algorithm is derived for estimating the model's parameters in a sequential manner. Numerical results show that the proposed solution provides a significant benefit over the most commonly used methods, IPDA and IMMPDA. The posterior Cramér-Rao bounds are also involved for performance evaluation.

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.

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.

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.

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. ...

Particle swarm optimization algorithm based parameters estimation and control of epileptiform spikes in a neural mass model

NASA Astrophysics Data System (ADS)

Shan, Bonan; Wang, Jiang; Deng, Bin; Wei, Xile; Yu, Haitao; Zhang, Zhen; Li, Huiyan

2016-07-01

This paper proposes an epilepsy detection and closed-loop control strategy based on Particle Swarm Optimization (PSO) algorithm. The proposed strategy can effectively suppress the epileptic spikes in neural mass models, where the epileptiform spikes are recognized as the biomarkers of transitions from the normal (interictal) activity to the seizure (ictal) activity. In addition, the PSO algorithm shows capabilities of accurate estimation for the time evolution of key model parameters and practical detection for all the epileptic spikes. The estimation effects of unmeasurable parameters are improved significantly compared with unscented Kalman filter. When the estimated excitatory-inhibitory ratio exceeds a threshold value, the epileptiform spikes can be inhibited immediately by adopting the proportion-integration controller. Besides, numerical simulations are carried out to illustrate the effectiveness of the proposed method as well as the potential value for the model-based early seizure detection and closed-loop control treatment design.

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.

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.

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.

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

NASA Technical Reports Server (NTRS)

Wemet, Mark P.

2008-01-01

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

[Factors affecting biological removal of iron and manganese in groundwater].

PubMed

Xue, Gang; He, Sheng-Bing; Wang, Xin-Ze

2006-01-01

Factors affecting biological process for removing iron and manganese in groundwater were analyzed. When DO and pH in groundwater after aeration were 7.0 - 7.5 mg/L and 6.8 - 7.0 respectively, not only can the activation of Mn2+ oxidizing bacteria be maintained, but also the demand of iron and manganese removal can be satisfied. A novel inoculating approach of grafting mature filter material into filter bed, which is easier to handle than selective culture media, was employed in this research. However, this approach was only suitable to the filter material of high-quality manganese sand with strong Mn2+ adsorption capacity. For the filter material of quartz sand with weak adsorption capacity, only culturing and domesticating Mn2+ oxidizing bacteria by selective culture media can be adopted as inoculation in filter bed. The optimal backwashing rate of biological filter bed filled with manganese sand and quartz sand should be kept at a relatively low level of 6 - 9 L/(m2 x s) and 7 -11 L/( m2 x s), respectively. Then the stability of microbial phase in filter bed was not disturbed, and iron and manganese removal efficiency recovered in less than 5h. Moreover, by using filter material with uniform particle size of 1.0 - 1.2 mm in filter bed, the filtration cycle reached as long as 35 - 38h.

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

PubMed Central

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

2010-01-01

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

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.

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.

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.

Communication Optimizations for a Wireless Distributed Prognostic Framework

NASA Technical Reports Server (NTRS)

Saha, Sankalita; Saha, Bhaskar; Goebel, Kai

2009-01-01

Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication overhead is an important design problem for such systems. In this paper we focus on communication issues faced in the distributed implementation of an important class of algorithms for prognostics - particle filters. In spite of being computation and memory intensive, particle filters lend well to distributed implementation except for one significant step - resampling. We propose new resampling scheme called parameterized resampling that attempts to reduce communication between collaborating nodes in a distributed wireless sensor network. Analysis and comparison with relevant resampling schemes is also presented. A battery health management system is used as a target application. A new resampling scheme for distributed implementation of particle filters has been discussed in this paper. Analysis and comparison of this new scheme with existing resampling schemes in the context for minimizing communication overhead have also been discussed. Our proposed new resampling scheme performs significantly better compared to other schemes by attempting to reduce both the communication message length as well as number total communication messages exchanged while not compromising prediction accuracy and precision. Future work will explore the effects of the new resampling scheme in the overall computational performance of the whole system as well as full implementation of the new schemes on the Sun SPOT devices. Exploring different network architectures for efficient communication is an importance future research direction as well.

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.

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.

Inverse design of high-Q wave filters in two-dimensional phononic crystals by topology optimization.

PubMed

Dong, Hao-Wen; Wang, Yue-Sheng; Zhang, Chuanzeng

2017-04-01

Topology optimization of a waveguide-cavity structure in phononic crystals for designing narrow band filters under the given operating frequencies is presented in this paper. We show that it is possible to obtain an ultra-high-Q filter by only optimizing the cavity topology without introducing any other coupling medium. The optimized cavity with highly symmetric resonance can be utilized as the multi-channel filter, raising filter and T-splitter. In addition, most optimized high-Q filters have the Fano resonances near the resonant frequencies. Furthermore, our filter optimization based on the waveguide and cavity, and our simple illustration of a computational approach to wave control in phononic crystals can be extended and applied to design other acoustic devices or even opto-mechanical devices. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Hybrid Filter Membrane

NASA Technical Reports Server (NTRS)

Laicer, Castro; Rasimick, Brian; Green, Zachary

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Non-stationary component extraction in noisy multicomponent signal using polynomial chirping Fourier transform.

PubMed

Lu, Wenlong; Xie, Junwei; Wang, Heming; Sheng, Chuan

2016-01-01

Inspired by track-before-detection technology in radar, a novel time-frequency transform, namely polynomial chirping Fourier transform (PCFT), is exploited to extract components from noisy multicomponent signal. The PCFT combines advantages of Fourier transform and polynomial chirplet transform to accumulate component energy along a polynomial chirping curve in the time-frequency plane. The particle swarm optimization algorithm is employed to search optimal polynomial parameters with which the PCFT will achieve a most concentrated energy ridge in the time-frequency plane for the target component. The component can be well separated in the polynomial chirping Fourier domain with a narrow-band filter and then reconstructed by inverse PCFT. Furthermore, an iterative procedure, involving parameter estimation, PCFT, filtering and recovery, is introduced to extract components from a noisy multicomponent signal successively. The Simulations and experiments show that the proposed method has better performance in component extraction from noisy multicomponent signal as well as provides more time-frequency details about the analyzed signal than conventional methods.

Waveform Analysis Optimization for the 45Ca Beta Decay Experiment

NASA Astrophysics Data System (ADS)

Whitehead, Ryan; ⁴⁵Ca Collaboration

2017-09-01

The 45Ca experiment is searching for a non-zero Fierz interference term, which would imply a tensor type contribution to the low-energy weak interaction, possibly signaling Beyond-the-Standard-Model (BSM) physics. Beta spectrum measurements are being performed at LANL, using the segmented, large area, Si detectors developed for the Nab and UCNB experiments. 109 events have been recorded, with 38 of the 254 pixels instrumented, during the summers of 2016 and 2017. An important step to extracting the energy spectra is the correction of the waveform for pile-up events. A set of analysis tools has been developed to address this issue. A trapezoidal filter has been characterized and optimized for the experimental waveforms. This filter is primarily used for energy extraction, but, by adjusting certain parameters, it has been modified to identify pile-up events. The efficiency varies with the total energy of the particle and the amount deposited with each detector interaction. Preliminary results of this analysis will be presented.

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

PubMed

Hadwin, Paul J; Peterson, Sean D

2017-04-01

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

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.

Exploring the statistics of magnetic reconnection X-points in kinetic particle-in-cell turbulence

NASA Astrophysics Data System (ADS)

Haggerty, C. C.; Parashar, T. N.; Matthaeus, W. H.; Shay, M. A.; Yang, Y.; Wan, M.; Wu, P.; Servidio, S.

2017-10-01

Magnetic reconnection is a ubiquitous phenomenon in turbulent plasmas. It is an important part of the turbulent dynamics and heating of space and astrophysical plasmas. We examine the statistics of magnetic reconnection using a quantitative local analysis of the magnetic vector potential, previously used in magnetohydrodynamics simulations, and now employed to fully kinetic particle-in-cell (PIC) simulations. Different ways of reducing the particle noise for analysis purposes, including multiple smoothing techniques, are explored. We find that a Fourier filter applied at the Debye scale is an optimal choice for analyzing PIC data. Finally, we find a broader distribution of normalized reconnection rates compared to the MHD limit with rates as large as 0.5 but with an average of approximately 0.1.

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.

Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints.

PubMed

Kuldeep, B; Singh, V K; Kumar, A; Singh, G K

2015-01-01

In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Reducing bottom anti-reflective coating (BARC) defects: optimizing and decoupling the filtration and dispense process

NASA Astrophysics Data System (ADS)

Brakensiek, Nickolas L.; Martin, Gary; Simmons, Sean; Batchelder, Traci

2006-03-01

Semiconductor device manufacturing is one of the cleanest manufacturing operations that can be found in the world today. It has to be that way; a particle on a wafer today can kill an entire device, which raises the costs, and therefore reduces the profits, of the manufacturing company in two ways: it must produce extra wafers to make up for the lost die, and it has less product to sell. In today's state-of-the-art fab, everything is filtered to the lowest pore size available. This practice is fairly easy for gases because a gas molecule is very small compared to the pore size of the filter. Filtering liquids, especially photochemicals such as photoresists and BARCs, can be much harder because the molecules that form the polymers used to manufacture the photochemicals are approaching the filter pore size. As a result, filters may plug up, filtration rates may drop, pressure drops across the filter may increase, or a filter may degrade. These conditions can then cause polymer shearing, microbubble formation, gel particle formation, and BARC chemical changes to occur before the BARC reaches the wafer. To investigate these possible interactions, an Entegris(R) IntelliGen(R) pump was installed on a TEL Mk8 TM track to see if the filtration process would have an effect on the BARC chemistry and coating defects. Various BARC chemicals such as DUV112 and DUV42P were pumped through various filter media having a variety of pore sizes at different filtration rates to investigate the interaction between the dispense process and the filtration process. The IntelliGen2 pump has the capability to filter the BARC independent of the dispense process. By using a designed experiment to look at various parameters such as dispense rate, filtration rate, and dispense volume, the effects of the complete pump system can be learned, and appropriate conditions can be applied to yield the cleanest BARC coating process. Results indicate that filtration rate and filter pore size play a dramatic role in the defect density on a coated wafer with the actual dispense properties such as dispense wafer speed and dispense time playing a lesser role.

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.

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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.

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.

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.

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

PubMed

Rengasamy, Samy; Eimer, Benjamin C

2012-01-01

National Institute for Occupational Safety and Health (NIOSH) certification test methods employ charge neutralized NaCl or dioctyl phthalate (DOP) aerosols to measure filter penetration levels of air-purifying particulate respirators photometrically using a TSI 8130 automated filter tester at 85 L/min. A previous study in our laboratory found that widely different filter penetration levels were measured for nanoparticles depending on whether a particle number (count)-based detector or a photometric detector was used. The purpose of this study was to better understand the influence of key test parameters, including filter media type, challenge aerosol size range, and detector system. Initial penetration levels for 17 models of NIOSH-approved N-, R-, and P-series filtering facepiece respirators were measured using the TSI 8130 photometric method and compared with the particle number-based penetration (obtained using two ultrafine condensation particle counters) for the same challenge aerosols generated by the TSI 8130. In general, the penetration obtained by the photometric method was less than the penetration obtained with the number-based method. Filter penetration was also measured for ambient room aerosols. Penetration measured by the TSI 8130 photometric method was lower than the number-based ambient aerosol penetration values. Number-based monodisperse NaCl aerosol penetration measurements showed that the most penetrating particle size was in the 50 nm range for all respirator models tested, with the exception of one model at ~200 nm size. Respirator models containing electrostatic filter media also showed lower penetration values with the TSI 8130 photometric method than the number-based penetration obtained for the most penetrating monodisperse particles. Results suggest that to provide a more challenging respirator filter test method than what is currently used for respirators containing electrostatic media, the test method should utilize a sufficient number of particles <100 nm and a count (particle number)-based detector.

Generation of ultra-long pure magnetization needle and multiple spots by phase modulated doughnut Gaussian beam

NASA Astrophysics Data System (ADS)

Udhayakumar, M.; Prabakaran, K.; Rajesh, K. B.; Jaroszewicz, Z.; Belafhal, Abdelmajid; Velauthapillai, Dhayalan

2018-06-01

Based on vector diffraction theory and inverse Faraday effect (IFE), the light induced magnetization distribution of a tightly focused azimuthally polarized doughnut Gaussian beam superimposed with a helical phase and modulated by an optimized multi belt complex phase filter (MBCPF) is analysed numerically. It is noted that by adjusting the radii of different rings of the complex phase filter, one can achieve many novel magnetization focal distribution such as sub wavelength scale (0.29λ) and super long (52.2λ) longitudinal magnetic probe suitable for all optical magnetic recording and the formation of multiple magnetization chain with four, six and eight sub-wavelength spherical magnetization spots suitable for multiple trapping of magnetic particles are achieved.

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.

QCD for Postgraduates (5/5)

ScienceCinema

None

2018-05-14

We will introduce and discuss in some detail the two main classes of jets: cone type and sequential-recombination type. We will discuss their basic properties, as well as more advanced concepts such as jet substructure, jet filtering, ways of optimizing the jet radius, ways of defining the areas of jets, and of establishing the quality measure of the jet-algorithm in terms of discriminating power in specific searches. Finally we will discuss applications for Higgs searches involving boosted particles.

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.

Uninformative Prior Multiple Target Tracking Using Evidential Particle Filters

NASA Astrophysics Data System (ADS)

Worthy, J. L., III; Holzinger, M. J.

Space situational awareness requires the ability to initialize state estimation from short measurements and the reliable association of observations to support the characterization of the space environment. The electro-optical systems used to observe space objects cannot fully characterize the state of an object given a short, unobservable sequence of measurements. Further, it is difficult to associate these short-arc measurements if many such measurements are generated through the observation of a cluster of satellites, debris from a satellite break-up, or from spurious detections of an object. An optimization based, probabilistic short-arc observation association approach coupled with a Dempster-Shafer based evidential particle filter in a multiple target tracking framework is developed and proposed to address these problems. The optimization based approach is shown in literature to be computationally efficient and can produce probabilities of association, state estimates, and covariances while accounting for systemic errors. Rigorous application of Dempster-Shafer theory is shown to be effective at enabling ignorance to be properly accounted for in estimation by augmenting probability with belief and plausibility. The proposed multiple hypothesis framework will use a non-exclusive hypothesis formulation of Dempster-Shafer theory to assign belief mass to candidate association pairs and generate tracks based on the belief to plausibility ratio. The proposed algorithm is demonstrated using simulated observations of a GEO satellite breakup scenario.

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.

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

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

Propagating probability distributions of stand variables using sequential Monte Carlo methods

Treesearch

Jeffrey H. Gove

2009-01-01

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

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.

Regenerative particulate filter development

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Mechanistic failure mode investigation and resolution of parvovirus retentive filters.

PubMed

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

2016-07-08

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

Single-File Escape of Colloidal Particles from Microfluidic Channels

NASA Astrophysics Data System (ADS)

Locatelli, Emanuele; Pierno, Matteo; Baldovin, Fulvio; Orlandini, Enzo; Tan, Yizhou; Pagliara, Stefano

2016-07-01

Single-file diffusion is a ubiquitous physical process exploited by living and synthetic systems to exchange molecules with their environment. It is paramount to quantify the escape time needed for single files of particles to exit from constraining synthetic channels and biological pores. This quantity depends on complex cooperative effects, whose predominance can only be established through a strict comparison between theory and experiments. By using colloidal particles, optical manipulation, microfluidics, digital microscopy, and theoretical analysis we uncover the self-similar character of the escape process and provide closed-formula evaluations of the escape time. We find that the escape time scales inversely with the diffusion coefficient of the last particle to leave the channel. Importantly, we find that at the investigated microscale, bias forces as tiny as 10-15 N determine the magnitude of the escape time by drastically reducing interparticle collisions. Our findings provide crucial guidelines to optimize the design of micro- and nanodevices for a variety of applications including drug delivery, particle filtering, and transport in geometrical constrictions.

Pulse-shape discrimination with Cs2HfCl6 crystal scintillator

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Effects of filtration temperature, humic acid level and alum dose on cryptosporidium sized particle breakthrough.

PubMed

Xu, G R; Fitzpatrick, C S B; Deng, L Y

2006-01-01

Recent Cryptosporidium outbreaks have highlighted concerns about filter efficiency and especially particle breakthrough. Understanding the causes of breakthrough is essential, as the parasite cannot be destroyed by conventional disinfection with chlorine. Particle breakthrough depends on many factors. This research aims to investigate the influence of temperature, humic acid (HA) level and chemical dosing on particle breakthrough in filtration. A series of temperatures were set at 5 degrees C, 15 degrees C and 25 degrees C; humic acid level was 5 mg L(-1). Each was combined with a series of Al doses. A laser particle counter was used to assess the particle breakthrough online. Turbidity, zeta potential, and UV254 absorption were measured before and after filtration. The results showed that particle breakthrough was influenced significantly by temperature, humic acid and dosing. Particle breakthrough occurred earlier at lower temperature, while at higher temperature it was reduced at the same coagulant dose. With coagulants, even at low dose, particle breakthrough was significantly reduced. With HA 5 mg L(-1), particle breakthrough was earlier and the amount was much larger than without HA even at high temperature. There was an optimal dose in filtration and it was well correlated with zeta potential.

Nanosize electropositive fibrous adsorbent

DOEpatents

Tepper, Frederick; Kaledin, Leonid

2005-01-04

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Method for optimizing output in ultrashort-pulse multipass laser amplifiers with selective use of a spectral filter

DOEpatents

Backus, Sterling J [Erie, CO; Kapteyn, Henry C [Boulder, CO

2007-07-10

A method for optimizing multipass laser amplifier output utilizes a spectral filter in early passes but not in later passes. The pulses shift position slightly for each pass through the amplifier, and the filter is placed such that early passes intersect the filter while later passes bypass it. The filter position may be adjust offline in order to adjust the number of passes in each category. The filter may be optimized for use in a cryogenic amplifier.

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.

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.

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

An Integrated Approach to Indoor and Outdoor Localization

DTIC Science & Technology

2017-04-17

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

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

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

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

PubMed Central

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

2013-01-01

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

Anti-clogging filter system

DOEpatents

Brown, Erik P.

2015-05-19

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

Anti-clogging filter system

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

Brown, Erik P.

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

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.

Bayesian Regression with Network Prior: Optimal Bayesian Filtering Perspective

PubMed Central

Qian, Xiaoning; Dougherty, Edward R.

2017-01-01

The recently introduced intrinsically Bayesian robust filter (IBRF) provides fully optimal filtering relative to a prior distribution over an uncertainty class ofjoint random process models, whereas formerly the theory was limited to model-constrained Bayesian robust filters, for which optimization was limited to the filters that are optimal for models in the uncertainty class. This paper extends the IBRF theory to the situation where there are both a prior on the uncertainty class and sample data. The result is optimal Bayesian filtering (OBF), where optimality is relative to the posterior distribution derived from the prior and the data. The IBRF theories for effective characteristics and canonical expansions extend to the OBF setting. A salient focus of the present work is to demonstrate the advantages of Bayesian regression within the OBF setting over the classical Bayesian approach in the context otlinear Gaussian models. PMID:28824268

Genetic particle filter application to land surface temperature downscaling

NASA Astrophysics Data System (ADS)

Mechri, Rihab; Ottlé, Catherine; Pannekoucke, Olivier; Kallel, Abdelaziz

2014-03-01

Thermal infrared data are widely used for surface flux estimation giving the possibility to assess water and energy budgets through land surface temperature (LST). Many applications require both high spatial resolution (HSR) and high temporal resolution (HTR), which are not presently available from space. It is therefore necessary to develop methodologies to use the coarse spatial/high temporal resolutions LST remote-sensing products for a better monitoring of fluxes at appropriate scales. For that purpose, a data assimilation method was developed to downscale LST based on particle filtering. The basic tenet of our approach is to constrain LST dynamics simulated at both HSR and HTR, through the optimization of aggregated temperatures at the coarse observation scale. Thus, a genetic particle filter (GPF) data assimilation scheme was implemented and applied to a land surface model which simulates prior subpixel temperatures. First, the GPF downscaling scheme was tested on pseudoobservations generated in the framework of the study area landscape (Crau-Camargue, France) and climate for the year 2006. The GPF performances were evaluated against observation errors and temporal sampling. Results show that GPF outperforms prior model estimations. Finally, the GPF method was applied on Spinning Enhanced Visible and InfraRed Imager time series and evaluated against HSR data provided by an Advanced Spaceborne Thermal Emission and Reflection Radiometer image acquired on 26 July 2006. The temperatures of seven land cover classes present in the study area were estimated with root-mean-square errors less than 2.4 K which is a very promising result for downscaling LST satellite products.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

PubMed

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

2010-03-01

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

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.

The carbonaceous sorbent based on the secondary silica-containing material from oil extraction industry

NASA Astrophysics Data System (ADS)

Starostina, I. V.; Stolyarov, D. V.; Anichina, Ya N.; Porozhnyuk, E. V.

2018-01-01

The object of research in this work is the silica-containing waste of oil extraction industry - the waste kieselghur (diatomite) sludge from precoat filtering units, used for the purification of vegetable oils from organic impurities. As a result of the thermal modification of the sludge, which contains up to 70% of organic impurities, a finely-dispersed low-porous carbonaceous mineral sorption material is formed. The modification of the sludge particles surface causes the substantial alteration of its physical, chemical, adsorption and structural properties - the organic matter is charred, the particle size is reduced, and on the surface of diatomite particles a carbon layer is formed, which deposits in macropores and partially occludes them. The amount of mesopores is increased, along with the specific surface of the obtained product. The optimal temperature of sludge modification is 500°C. The synthesized carbonaceous material can be used as an adsorbing agent for the purification of wastewater from heavy metal ions. The sorption capacity of Cu2+ ions amounted to 14.2 mg·g-1 and for Ni2+ ions - 17.0 mg·g-1. The obtained values exceed the sorption capacity values of the initial kieselghur, used as a filtering charge, for the researched metal ions.

[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).

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.

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

PubMed

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

2015-09-03

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

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.

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.

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.

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.

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.

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.

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

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

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.

Optimization of OT-MACH Filter Generation for Target Recognition

NASA Technical Reports Server (NTRS)

Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

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.

Microwave Bandpass Filter Based on Mie-Resonance Extraordinary Transmission

PubMed Central

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

2016-01-01

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

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

PubMed

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

2014-04-01

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

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

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

PubMed Central

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-01

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

PubMed

Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

2016-01-08

A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

1-D DC Resistivity Modeling and Interpretation in Anisotropic Media Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Pekşen, Ertan; Yas, Türker; Kıyak, Alper

2014-09-01

We examine the one-dimensional direct current method in anisotropic earth formation. We derive an analytic expression of a simple, two-layered anisotropic earth model. Further, we also consider a horizontally layered anisotropic earth response with respect to the digital filter method, which yields a quasi-analytic solution over anisotropic media. These analytic and quasi-analytic solutions are useful tests for numerical codes. A two-dimensional finite difference earth model in anisotropic media is presented in order to generate a synthetic data set for a simple one-dimensional earth. Further, we propose a particle swarm optimization method for estimating the model parameters of a layered anisotropic earth model such as horizontal and vertical resistivities, and thickness. The particle swarm optimization is a naturally inspired meta-heuristic algorithm. The proposed method finds model parameters quite successfully based on synthetic and field data. However, adding 5 % Gaussian noise to the synthetic data increases the ambiguity of the value of the model parameters. For this reason, the results should be controlled by a number of statistical tests. In this study, we use probability density function within 95 % confidence interval, parameter variation of each iteration and frequency distribution of the model parameters to reduce the ambiguity. The result is promising and the proposed method can be used for evaluating one-dimensional direct current data in anisotropic media.

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

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

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.

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

Optimization of In-Cylinder Pressure Filter for Engine Research

DTIC Science & Technology

2017-06-01

ARL-TR-8034 ● JUN 2017 US Army Research Laboratory Optimization of In-Cylinder Pressure Filter for Engine Research by Kenneth...Laboratory Optimization of In-Cylinder Pressure Filter for Engine Research by Kenneth S Kim, Michael T Szedlmayer, Kurt M Kruger, and Chol-Bum M...

Evaluation of the filtration performance of NIOSH-approved N95 filtering facepiece respirators by photometric and number-based test methods.

PubMed

Rengasamy, Samy; Miller, Adam; Eimer, Benjamin C

2011-01-01

N95 particulate filtering facepiece respirators are certified by measuring penetration levels photometrically with a presumed severe case test method using charge neutralized NaCl aerosols at 85 L/min. However, penetration values obtained by photometric methods have not been compared with count-based methods using contemporary respirators composed of electrostatic filter media and challenged with both generated and ambient aerosols. To better understand the effects of key test parameters (e.g., particle charge, detection method), initial penetration levels for five N95 model filtering facepiece respirators were measured using NaCl aerosols with the aerosol challenge and test equipment employed in the NIOSH respirator certification method (photometric) and compared with an ultrafine condensation particle counter method (count based) for the same NaCl aerosols as well as for ambient room air particles. Penetrations using the NIOSH test method were several-fold less than the penetrations obtained by the ultrafine condensation particle counter for NaCl aerosols as well as for room particles indicating that penetration measurement based on particle counting offers a more difficult challenge than the photometric method, which lacks sensitivity for particles < 100 nm. All five N95 models showed the most penetrating particle size around 50 nm for room air particles with or without charge neutralization, and at 200 nm for singly charged NaCl monodisperse particles. Room air with fewer charged particles and an overwhelming number of neutral particles contributed to the most penetrating particle size in the 50 nm range, indicating that the charge state for the majority of test particles determines the MPPS. Data suggest that the NIOSH respirator certification protocol employing the photometric method may not be a more challenging aerosol test method. Filter penetrations can vary among workplaces with different particle size distributions, which suggests the need for the development of new or revised "more challenging" aerosol test methods for NIOSH certification of respirators.

Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

PubMed Central

Moccia, Antonio

2014-01-01

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

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

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.

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.

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.

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.

Generalized Optimal-State-Constraint Extended Kalman Filter (OSC-EKF)

DTIC Science & Technology

2017-02-01

ARL-TR-7948• FEB 2017 US Army Research Laboratory GeneralizedOptimal-State-Constraint ExtendedKalman Filter (OSC-EKF) by James M Maley, Kevin...originator. ARL-TR-7948• FEB 2017 US Army Research Laboratory GeneralizedOptimal-State-Constraint ExtendedKalman Filter (OSC-EKF) by James M Maley Weapons and...

A Low Cost Structurally Optimized Design for Diverse Filter Types

PubMed Central

Kazmi, Majida; Aziz, Arshad; Akhtar, Pervez; Ikram, Nassar

2016-01-01

A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image processing applications especially in a constraint environment. PMID:27832133

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.

Improvement of LOD in Fluorescence Detection with Spectrally Nonuniform Background by Optimization of Emission Filtering.

PubMed

Galievsky, Victor A; Stasheuski, Alexander S; Krylov, Sergey N

2017-10-17

The limit-of-detection (LOD) in analytical instruments with fluorescence detection can be improved by reducing noise of optical background. Efficiently reducing optical background noise in systems with spectrally nonuniform background requires complex optimization of an emission filter-the main element of spectral filtration. Here, we introduce a filter-optimization method, which utilizes an expression for the signal-to-noise ratio (SNR) as a function of (i) all noise components (dark, shot, and flicker), (ii) emission spectrum of the analyte, (iii) emission spectrum of the optical background, and (iv) transmittance spectrum of the emission filter. In essence, the noise components and the emission spectra are determined experimentally and substituted into the expression. This leaves a single variable-the transmittance spectrum of the filter-which is optimized numerically by maximizing SNR. Maximizing SNR provides an accurate way of filter optimization, while a previously used approach based on maximizing a signal-to-background ratio (SBR) is the approximation that can lead to much poorer LOD specifically in detection of fluorescently labeled biomolecules. The proposed filter-optimization method will be an indispensable tool for developing new and improving existing fluorescence-detection systems aiming at ultimately low LOD.

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.

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...

Nonlinear Estimation With Sparse Temporal Measurements

DTIC Science & Technology

2016-09-01

Kalman filter , the extended Kalman filter (EKF) and unscented Kalman filter (UKF) are commonly used in practical application. The Kalman filter is an...optimal estimator for linear systems; the EKF and UKF are sub-optimal approximations of the Kalman filter . The EKF uses a first-order Taylor series...propagated covariance is compared for similarity with a Monte Carlo propagation. The similarity of the covariance matrices is shown to predict filter

Fish tracking by combining motion based segmentation and particle filtering

NASA Astrophysics Data System (ADS)

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

2006-01-01

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

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

PubMed

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

2006-08-25

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

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.

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.

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

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.

Particle Collection Efficiency of a Lens-Liquid Filtration System

NASA Astrophysics Data System (ADS)

Wong, Ross Y. M.; Ng, Moses L. F.; Chao, Christopher Y. H.; Li, Z. G.

2011-09-01

Clinical and epidemiological studies have shown that indoor air quality has substantial impact on the health of building occupants [1]. Possible sources of indoor air contamination include hazardous gases as well as particulate matters (PMs) [2]. Experimental studies show that the size distribution of PMs in indoor air ranges from tens of nanometers to a few hundreds of micrometers [3]. Vacuum cleaners can be used as a major tool to collect PMs from floor/carpets, which are the main sources of indoor PMs. However, the particle collection efficiency of typical cyclonic filters in the vacuums drops significantly for particles of diameter below 10 μm. In this work, we propose a lens-liquid filtration system (see Figure 1), where the flow channel is formed by a liquid free surface and a planar plate with fin/lens structures. Computational fluid dynamics simulations are performed by using FLUENT to optimize the structure of the proposed system toward high particle collection efficiency and satisfactory pressure drop. Numerical simulations show that the system can collect 250 nm diameter particles with collection efficiency of 50%.

[Alcohol-purification technology and its particle sedimentation process in manufactory of Fufang Kushen injection].

PubMed

Liu, Xiaoqian; Tong, Yan; Wang, Jinyu; Wang, Ruizhen; Zhang, Yanxia; Wang, Zhimin

2011-11-01

Fufang Kushen injection was selected as the model drug, to optimize its alcohol-purification process and understand the characteristics of particle sedimentation process, and to investigate the feasibility of using process analytical technology (PAT) on traditional Chinese medicine (TCM) manufacturing. Total alkaloids (calculated by matrine, oxymatrine, sophoridine and oxysophoridine) and macrozamin were selected as quality evaluation markers to optimize the process of Fufang Kushen injection purification with alcohol. Process parameters of particulate formed in the alcohol-purification, such as the number, density and sedimentation velocity, were also determined to define the sedimentation time and well understand the process. The purification process was optimized as that alcohol is added to the concentrated extract solution (drug material) to certain concentration for 2 times and deposited the alcohol-solution containing drug-material to sediment for some time, i.e. 60% alcohol deposited for 36 hours, filter and then 80% -90% alcohol deposited for 6 hours in turn. The content of total alkaloids was decreased a little during the depositing process. The average settling time of particles with the diameters of 10, 25 microm were 157.7, 25.2 h in the first alcohol-purified process, and 84.2, 13.5 h in the second alcohol-purified process, respectively. The optimized alcohol-purification process remains the marker compositions better and compared with the initial process, it's time saving and much economy. The manufacturing quality of TCM-injection can be controlled by process. PAT pattern must be designed under the well understanding of process of TCM production.

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.

Improvement of the fringe analysis algorithm for wavelength scanning interferometry based on filter parameter optimization.

PubMed

Zhang, Tao; Gao, Feng; Muhamedsalih, Hussam; Lou, Shan; Martin, Haydn; Jiang, Xiangqian

2018-03-20

The phase slope method which estimates height through fringe pattern frequency and the algorithm which estimates height through the fringe phase are the fringe analysis algorithms widely used in interferometry. Generally they both extract the phase information by filtering the signal in frequency domain after Fourier transform. Among the numerous papers in the literature about these algorithms, it is found that the design of the filter, which plays an important role, has never been discussed in detail. This paper focuses on the filter design in these algorithms for wavelength scanning interferometry (WSI), trying to optimize the parameters to acquire the optimal results. The spectral characteristics of the interference signal are analyzed first. The effective signal is found to be narrow-band (near single frequency), and the central frequency is calculated theoretically. Therefore, the position of the filter pass-band is determined. The width of the filter window is optimized with the simulation to balance the elimination of the noise and the ringing of the filter. Experimental validation of the approach is provided, and the results agree very well with the simulation. The experiment shows that accuracy can be improved by optimizing the filter design, especially when the signal quality, i.e., the signal noise ratio (SNR), is low. The proposed method also shows the potential of improving the immunity to the environmental noise by adapting the signal to acquire the optimal results through designing an adaptive filter once the signal SNR can be estimated accurately.

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.

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

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.

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.

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.

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

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

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

A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)

NASA Astrophysics Data System (ADS)

Li, Minghui; Hayward, Gordon

2017-02-01

The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.

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

NASA Astrophysics Data System (ADS)

Ji, S.; Yuan, X.

2016-06-01

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

Cross-flow electrofilter and method

DOEpatents

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

1980-01-01

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

Cross flow electrofilter and method

DOEpatents

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

1981-01-01

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

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.

Preparation of Porous Stainless Steel Hollow-Fibers through Multi-Modal Particle Size Sintering towards Pore Engineering

PubMed Central

Allioux, Francois-Marie; Etxeberria Benavides, Miren

2017-01-01

The sintering of metal powders is an efficient and versatile technique to fabricate porous metal elements such as filters, diffusers, and membranes. Neck formation between particles is, however, critical to tune the porosity and optimize mass transfer in order to minimize the densification process. In this work, macro-porous stainless steel (SS) hollow-fibers (HFs) were fabricated by the extrusion and sintering of a dope comprised, for the first time, of a bimodal mixture of SS powders. The SS particles of different sizes and shapes were mixed to increase the neck formation between the particles and control the densification process of the structure during sintering. The sintered HFs from particles of two different sizes were shown to be more mechanically stable at lower sintering temperature due to the increased neck area of the small particles sintered to the large ones. In addition, the sintered HFs made from particles of 10 and 44 μm showed a smaller average pore size (<1 μm) as compared to the micron-size pores of sintered HFs made from particles of 10 μm only and those of 10 and 20 μm. The novel HFs could be used in a range of applications, from filtration modules to electrochemical membrane reactors. PMID:28777352

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.

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

DOE PAGES

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

2014-10-23

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

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

Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

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.

Filter Selection for Optimizing the Spectral Sensitivity of Broadband Multispectral Cameras Based on Maximum Linear Independence.

PubMed

Li, Sui-Xian

2018-05-07

Previous research has shown that the effectiveness of selecting filter sets from among a large set of commercial broadband filters by a vector analysis method based on maximum linear independence (MLI). However, the traditional MLI approach is suboptimal due to the need to predefine the first filter of the selected filter set to be the maximum ℓ₂ norm among all available filters. An exhaustive imaging simulation with every single filter serving as the first filter is conducted to investigate the features of the most competent filter set. From the simulation, the characteristics of the most competent filter set are discovered. Besides minimization of the condition number, the geometric features of the best-performed filter set comprise a distinct transmittance peak along the wavelength axis of the first filter, a generally uniform distribution for the peaks of the filters and substantial overlaps of the transmittance curves of the adjacent filters. Therefore, the best-performed filter sets can be recognized intuitively by simple vector analysis and just a few experimental verifications. A practical two-step framework for selecting optimal filter set is recommended, which guarantees a significant enhancement of the performance of the systems. This work should be useful for optimizing the spectral sensitivity of broadband multispectral imaging sensors.

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...

Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

PubMed

Xing, Haifeng; Hou, Bo; Lin, Zhihui; Guo, Meifeng

2017-10-13

MEMS (Micro Electro Mechanical System) gyroscopes have been widely applied to various fields, but MEMS gyroscope random drift has nonlinear and non-stationary characteristics. It has attracted much attention to model and compensate the random drift because it can improve the precision of inertial devices. This paper has proposed to use wavelet filtering to reduce noise in the original data of MEMS gyroscopes, then reconstruct the random drift data with PSR (phase space reconstruction), and establish the model for the reconstructed data by LSSVM (least squares support vector machine), of which the parameters were optimized using CPSO (chaotic particle swarm optimization). Comparing the effect of modeling the MEMS gyroscope random drift with BP-ANN (back propagation artificial neural network) and the proposed method, the results showed that the latter had a better prediction accuracy. Using the compensation of three groups of MEMS gyroscope random drift data, the standard deviation of three groups of experimental data dropped from 0.00354°/s, 0.00412°/s, and 0.00328°/s to 0.00065°/s, 0.00072°/s and 0.00061°/s, respectively, which demonstrated that the proposed method can reduce the influence of MEMS gyroscope random drift and verified the effectiveness of this method for modeling MEMS gyroscope random drift.

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

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.

Highly efficient spatial data filtering in parallel using the opensource library CPPPO

NASA Astrophysics Data System (ADS)

Municchi, Federico; Goniva, Christoph; Radl, Stefan

2016-10-01

CPPPO is a compilation of parallel data processing routines developed with the aim to create a library for "scale bridging" (i.e. connecting different scales by mean of closure models) in a multi-scale approach. CPPPO features a number of parallel filtering algorithms designed for use with structured and unstructured Eulerian meshes, as well as Lagrangian data sets. In addition, data can be processed on the fly, allowing the collection of relevant statistics without saving individual snapshots of the simulation state. Our library is provided with an interface to the widely-used CFD solver OpenFOAM®, and can be easily connected to any other software package via interface modules. Also, we introduce a novel, extremely efficient approach to parallel data filtering, and show that our algorithms scale super-linearly on multi-core clusters. Furthermore, we provide a guideline for choosing the optimal Eulerian cell selection algorithm depending on the number of CPU cores used. Finally, we demonstrate the accuracy and the parallel scalability of CPPPO in a showcase focusing on heat and mass transfer from a dense bed of particles.

Cambrian cinctan echinoderms shed light on feeding in the ancestral deuterostome

PubMed Central

Rahman, Imran A.; Zamora, Samuel; Falkingham, Peter L.; Phillips, Jeremy C.

2015-01-01

Reconstructing the feeding mode of the latest common ancestor of deuterostomes is key to elucidating the early evolution of feeding in chordates and allied phyla; however, it is debated whether the ancestral deuterostome was a tentaculate feeder or a pharyngeal filter feeder. To address this, we evaluated the hydrodynamics of feeding in a group of fossil stem-group echinoderms (cinctans) using computational fluid dynamics. We simulated water flow past three-dimensional digital models of a Cambrian fossil cinctan in a range of possible life positions, adopting both passive tentacular feeding and active pharyngeal filter feeding. The results demonstrate that an orientation with the mouth facing downstream of the current was optimal for drag and lift reduction. Moreover, they show that there was almost no flow to the mouth and associated marginal groove under simulations of passive feeding, whereas considerable flow towards the animal was observed for active feeding, which would have enhanced the transport of suspended particles to the mouth. This strongly suggests that cinctans were active pharyngeal filter feeders, like modern enteropneust hemichordates and urochordates, indicating that the ancestral deuterostome employed a similar feeding strategy. PMID:26511049

A novel method for the detection of R-peaks in ECG based on K-Nearest Neighbors and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

He, Runnan; Wang, Kuanquan; Li, Qince; Yuan, Yongfeng; Zhao, Na; Liu, Yang; Zhang, Henggui

2017-12-01

Cardiovascular diseases are associated with high morbidity and mortality. However, it is still a challenge to diagnose them accurately and efficiently. Electrocardiogram (ECG), a bioelectrical signal of the heart, provides crucial information about the dynamical functions of the heart, playing an important role in cardiac diagnosis. As the QRS complex in ECG is associated with ventricular depolarization, therefore, accurate QRS detection is vital for interpreting ECG features. In this paper, we proposed a real-time, accurate, and effective algorithm for QRS detection. In the algorithm, a proposed preprocessor with a band-pass filter was first applied to remove baseline wander and power-line interference from the signal. After denoising, a method combining K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) was used for accurate QRS detection in ECGs with different morphologies. The proposed algorithm was tested and validated using 48 ECG records from MIT-BIH arrhythmia database (MITDB), achieved a high averaged detection accuracy, sensitivity and positive predictivity of 99.43, 99.69, and 99.72%, respectively, indicating a notable improvement to extant algorithms as reported in literatures.

Automated Sperm Head Detection Using Intersecting Cortical Model Optimised by Particle Swarm Optimization.

PubMed

Tan, Weng Chun; Mat Isa, Nor Ashidi

2016-01-01

In human sperm motility analysis, sperm segmentation plays an important role to determine the location of multiple sperms. To ensure an improved segmentation result, the Laplacian of Gaussian filter is implemented as a kernel in a pre-processing step before applying the image segmentation process to automatically segment and detect human spermatozoa. This study proposes an intersecting cortical model (ICM), which was derived from several visual cortex models, to segment the sperm head region. However, the proposed method suffered from parameter selection; thus, the ICM network is optimised using particle swarm optimization where feature mutual information is introduced as the new fitness function. The final results showed that the proposed method is more accurate and robust than four state-of-the-art segmentation methods. The proposed method resulted in rates of 98.14%, 98.82%, 86.46% and 99.81% in accuracy, sensitivity, specificity and precision, respectively, after testing with 1200 sperms. The proposed algorithm is expected to be implemented in analysing sperm motility because of the robustness and capability of this algorithm.

Multi-Patches IRIS Based Person Authentication System Using Particle Swarm Optimization and Fuzzy C-Means Clustering

NASA Astrophysics Data System (ADS)

Shekar, B. H.; Bhat, S. S.

2017-05-01

Locating the boundary parameters of pupil and iris and segmenting the noise free iris portion are the most challenging phases of an automated iris recognition system. In this paper, we have presented person authentication frame work which uses particle swarm optimization (PSO) to locate iris region and circular hough transform (CHT) to device the boundary parameters. To undermine the effect of the noise presented in the segmented iris region we have divided the candidate region into N patches and used Fuzzy c-means clustering (FCM) to classify the patches into best iris region and not so best iris region (noisy region) based on the probability density function of each patch. Weighted mean Hammimng distance is adopted to find the dissimilarity score between the two candidate irises. We have used Log-Gabor, Riesz and Taylor's series expansion (TSE) filters and combinations of these three for iris feature extraction. To justify the feasibility of the proposed method, we experimented on the three publicly available data sets IITD, MMU v-2 and CASIA v-4 distance.

An optimal filter for short photoplethysmogram signals

PubMed Central

Liang, Yongbo; Elgendi, Mohamed; Chen, Zhencheng; Ward, Rabab

2018-01-01

A photoplethysmogram (PPG) contains a wealth of cardiovascular system information, and with the development of wearable technology, it has become the basic technique for evaluating cardiovascular health and detecting diseases. However, due to the varying environments in which wearable devices are used and, consequently, their varying susceptibility to noise interference, effective processing of PPG signals is challenging. Thus, the aim of this study was to determine the optimal filter and filter order to be used for PPG signal processing to make the systolic and diastolic waves more salient in the filtered PPG signal using the skewness quality index. Nine types of filters with 10 different orders were used to filter 219 (2.1s) short PPG signals. The signals were divided into three categories by PPG experts according to their noise levels: excellent, acceptable, or unfit. Results show that the Chebyshev II filter can improve the PPG signal quality more effectively than other types of filters and that the optimal order for the Chebyshev II filter is the 4th order. PMID:29714722

Development of a filter regeneration system for advanced spacecraft fluid systems

NASA Technical Reports Server (NTRS)

Behrend, A. F., Jr.; Descamp, V. A.

1974-01-01

The development of a filter regeneration system for efficiently cleaning fluid particulate filters is presented. Based on a backflush/jet impingement technique, the regeneration system demonstrated a cleaning efficiency of 98.7 to 100%. The operating principles and design features are discussed with emphasis on the primary system components that include a regenerable filter, vortex particle separator, and zero-g particle trap. Techniques and equipment used for ground and zero-g performance tests are described. Test results and conclusions, as well as possible areas for commercial application, are included.

Numerical and experimental approaches to simulate soil clogging in porous media

NASA Astrophysics Data System (ADS)

Kanarska, Yuliya; LLNL Team

2012-11-01

Failure of a dam by erosion ranks among the most serious accidents in civil engineering. The best way to prevent internal erosion is using adequate granular filters in the transition areas where important hydraulic gradients can appear. In case of cracking and erosion, if the filter is capable of retaining the eroded particles, the crack will seal and the dam safety will be ensured. A finite element numerical solution of the Navier-Stokes equations for fluid flow together with Lagrange multiplier technique for solid particles was applied to the simulation of soil filtration. The numerical approach was validated through comparison of numerical simulations with the experimental results of base soil particle clogging in the filter layers performed at ERDC. The numerical simulation correctly predicted flow and pressure decay due to particle clogging. The base soil particle distribution was almost identical to those measured in the laboratory experiment. To get more precise understanding of the soil transport in granular filters we investigated sensitivity of particle clogging mechanisms to various aspects such as particle size ration, the amplitude of hydraulic gradient, particle concentration and contact properties. By averaging the results derived from the grain-scale simulations, we investigated how those factors affect the semi-empirical multiphase model parameters in the large-scale simulation tool. The Department of Homeland Security Science and Technology Directorate provided funding for this research.

Black carbon, mass and elemental measurements of airborne particles in the village of Serowe, Botswana

NASA Astrophysics Data System (ADS)

Moloi, K.; Chimidza, S.; Lindgren, E. Selin; Viksna, A.; Standzenieks, P.

Absorption of sunlight by sub-micron particles is an important factor in calculations of the radiation balance of the earth and thus in climate modelling. Carbon-containing particles are generally considered as the most important in this respect. Major sources of these particles are generally considered to be bio-mass burning and vehicle exhaust. In order to characterise size fractionated particulate matter in a rural village in Botswana with respect to light absorption and elemental content experiments were performed, in which simultaneous sampling was made with a dichotomous impactor and a laboratory-made sampler, made compatible with black carbon analysis by reflectometry. The dichotomous impactor was equipped with Teflon filters and the other sampler with glass fibre filters. Energy dispersive X-ray fluorescence was used for elemental analysis of both kinds of filters. It appeared that Teflon filters were the most suitable for the combination of mass-, elemental- and black carbon measurements. The black carbon content in coarse (2.5-10 μm) and fine (<2.5 μm) particles was determined separately and related to elemental content and emission source. The results show that the fine particle fraction in the aerosol has a much higher contribution of black particles than the coarse particle fraction. This observation is valid for the village in Botswana as well as for a typical industrialised city in Sweden, used as a reference location.

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.

Progress in navigation filter estimate fusion and its application to spacecraft rendezvous

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

1994-01-01

A new derivation of an algorithm which fuses the outputs of two Kalman filters is presented within the context of previous research in this field. Unlike other works, this derivation clearly shows the combination of estimates to be optimal, minimizing the trace of the fused covariance matrix. The algorithm assumes that the filters use identical models, and are stable and operating optimally with respect to their own local measurements. Evidence is presented which indicates that the error ellipsoid derived from the covariance of the optimally fused estimate is contained within the intersections of the error ellipsoids of the two filters being fused. Modifications which reduce the algorithm's data transmission requirements are also presented, including a scalar gain approximation, a cross-covariance update formula which employs only the two contributing filters' autocovariances, and a form of the algorithm which can be used to reinitialize the two Kalman filters. A sufficient condition for using the optimally fused estimates to periodically reinitialize the Kalman filters in this fashion is presented and proved as a theorem. When these results are applied to an optimal spacecraft rendezvous problem, simulated performance results indicate that the use of optimally fused data leads to significantly improved robustness to initial target vehicle state errors. The following applications of estimate fusion methods to spacecraft rendezvous are also described: state vector differencing, and redundancy management.

Capturing PM2.5 Emissions from 3D Printing via Nanofiber-based Air Filter.

PubMed

Rao, Chengchen; Gu, Fu; Zhao, Peng; Sharmin, Nusrat; Gu, Haibing; Fu, Jianzhong

2017-09-04

This study investigated the feasibility of using polycaprolactone (PCL) nanofiber-based air filters to capture PM2.5 particles emitted from fused deposition modeling (FDM) 3D printing. Generation and aggregation of emitted particles were investigated under different testing environments. The results show that: (1) the PCL nanofiber membranes are capable of capturing particle emissions from 3D printing, (2) relative humidity plays a signification role in aggregation of the captured particles, (3) generation and aggregation of particles from 3D printing can be divided into four stages: the PM2.5 concentration and particles size increase slowly (first stage), small particles are continuously generated and their concentration increases rapidly (second stage), small particles aggregate into more large particles and the growth of concentration slows down (third stage), the PM2.5 concentration and particle aggregation sizes increase rapidly (fourth stage), and (4) the ultrafine particles denoted as "building unit" act as the fundamentals of the aggregated particles. This work has tremendous implications in providing measures for controlling the particle emissions from 3D printing, which would facilitate the extensive application of 3D printing. In addition, this study provides a potential application scenario for nanofiber-based air filters other than laboratory theoretical investigation.

Radiological/biological/aerosol removal system

DOEpatents

Haslam, Jeffery J

2015-03-17

An air filter replacement system for existing buildings, vehicles, arenas, and other enclosed airspaces includes a replacement air filter for replacing a standard air filter. The replacement air filter has dimensions and air flow specifications that allow it to replace the standard air filter. The replacement air filter includes a filter material that removes radiological or biological or aerosol particles.

Instituting a filtration/pressurization system to reduce dust concentrations in a control room at a mineral processing plant

PubMed Central

Noll, J.; Cecala, A.; Hummer, J.

2016-01-01

The National Institute for Occupational Safety and Health has observed that many control rooms and operator compartments in the U.S. mining industry do not have filtration systems capable of maintaining low dust concentrations in these areas. In this study at a mineral processing plant, to reduce respirable dust concentrations in a control room that had no cleaning system for intake air, a filtration and pressurization system originally designed for enclosed cabs was modified and installed. This system was composed of two filtering units: one to filter outside air and one to filter and recirculate the air inside the control room. Eighty-seven percent of submicrometer particles were reduced by the system under static conditions. This means that greater than 87 percent of respirable dust particles should be reduced as the particle-size distribution of respirable dust particles is greater than that of submicrometer particles, and filtration systems usually are more efficient in capturing the larger particles. A positive pressure near 0.02 inches of water gauge was produced, which is an important component of an effective system and minimizes the entry of particles, such as dust, into the room. The intake airflow was around 118 cfm, greater than the airflow suggested by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) for acceptable indoor air quality. After one year, the loading of the filter caused the airflow to decrease to 80 cfm, which still produces acceptable indoor air quality. Due to the loading of the filters, the reduction efficiency for submicrometer particles under static conditions increased to 94 percent from 87 percent. PMID:26834293

Spectral optimized asymmetric segmented phase-only correlation filter.

PubMed

Leonard, I; Alfalou, A; Brosseau, C

2012-05-10

We suggest a new type of optimized composite filter, i.e., the asymmetric segmented phase-only filter (ASPOF), for improving the effectiveness of a VanderLugt correlator (VLC) when used for face identification. Basically, it consists in merging several reference images after application of a specific spectral optimization method. After segmentation of the spectral filter plane to several areas, each area is assigned to a single winner reference according to a new optimized criterion. The point of the paper is to show that this method offers a significant performance improvement on standard composite filters for face identification. We first briefly revisit composite filters [adapted, phase-only, inverse, compromise optimal, segmented, minimum average correlation energy, optimal trade-off maximum average correlation, and amplitude-modulated phase-only (AMPOF)], which are tools of choice for face recognition based on correlation techniques, and compare their performances with those of the ASPOF. We illustrate some of the drawbacks of current filters for several binary and grayscale image identifications. Next, we describe the optimization steps and introduce the ASPOF that can overcome these technical issues to improve the quality and the reliability of the correlation-based decision. We derive performance measures, i.e., PCE values and receiver operating characteristic curves, to confirm consistency of the results. We numerically find that this filter increases the recognition rate and decreases the false alarm rate. The results show that the discrimination of the ASPOF is comparable to that of the AMPOF, but the ASPOF is more robust than the trade-off maximum average correlation height against rotation and various types of noise sources. Our method has several features that make it amenable to experimental implementation using a VLC.

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.

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

PubMed Central

Wang, Xue; Ma, Jun-Jie; Wang, Sheng; Bi, Dao-Wei

2007-01-01

Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.

Parallel filtering in global gyrokinetic simulations

NASA Astrophysics Data System (ADS)

Jolliet, S.; McMillan, B. F.; Villard, L.; Vernay, T.; Angelino, P.; Tran, T. M.; Brunner, S.; Bottino, A.; Idomura, Y.

2012-02-01

In this work, a Fourier solver [B.F. McMillan, S. Jolliet, A. Bottino, P. Angelino, T.M. Tran, L. Villard, Comp. Phys. Commun. 181 (2010) 715] is implemented in the global Eulerian gyrokinetic code GT5D [Y. Idomura, H. Urano, N. Aiba, S. Tokuda, Nucl. Fusion 49 (2009) 065029] and in the global Particle-In-Cell code ORB5 [S. Jolliet, A. Bottino, P. Angelino, R. Hatzky, T.M. Tran, B.F. McMillan, O. Sauter, K. Appert, Y. Idomura, L. Villard, Comp. Phys. Commun. 177 (2007) 409] in order to reduce the memory of the matrix associated with the field equation. This scheme is verified with linear and nonlinear simulations of turbulence. It is demonstrated that the straight-field-line angle is the coordinate that optimizes the Fourier solver, that both linear and nonlinear turbulent states are unaffected by the parallel filtering, and that the k∥ spectrum is independent of plasma size at fixed normalized poloidal wave number.

LC separation of calcipotriol from its photodegradation products and protection possibilities using adjuvants.

PubMed

Cirunay, J J; Vander Heyden, Y; Plaizier-Vercammen, J

2001-08-01

Mobile phase optimization and reversed-phase column characteristics were used to separate photodegradation products from the parent compound, 24-cyclopropyl-9-,10-secochola-5,7,10(19),22-tetraene-1alpha,3beta,24-triol (calcipotriol). Separation between calcipotriol and its degradation products was obtained with an acetonitrile/water (53:47, v/v) mobile phase on a C(18) Hypersil ODS column (250 mm length, 4.6 mm id, 5 microm particle size) and a flow rate of 1 ml/min. Using this system, the influence of commonly used solvents in dermatology on degradation was studied. The addition of a UV filter in two concentrations was also evaluated for its possible protective effect to light exposure. Propylene glycol and polyethylene glycol 400 decreased the speed of degradation. The sunscreen 2-hydroxy-4-methoxybenzophenone affords a protection proportional to the filter concentration used in the study.

Measurement of charm meson production in Au+Au collisions at √S NN =200 GEV

NASA Astrophysics Data System (ADS)

Quintero, Amilkar

The study and characterization of nuclear matter under extreme conditions of temperature and pressure, and a full understanding of deconfined partonic matter, the Quark Gluon Plasma (QGP), are major goals of modern high-energy nuclear physics. Heavy quarks (charm and bottom) are formed mainly in the early stages of the collision. Open heavy flavor measurements, e.g. D0, D+/-, DS, are excellent tools to probe and study the hot and dense medium formed in heavy ion collisions. Details of their interaction with the surrounding medium can be studied through energy loss and elliptic flow measurements thus providing valuable information about the nature of the medium and its degree of thermalization. Initial indirect reconstruction studies of heavy quark particles using the electrons from heavy flavor decays, showed a large magnitude of energy loss that was inconsistent with model predictions and assumptions, at the time. Precise measurements of fully reconstructed heavy mesons would provide better understanding of the energy loss mechanisms and the properties of the formed medium. In relativistic heavy ion collisions, the relatively low abundance of heavy quarks and their short lifetimes makes them difficult to distinguish from the event vertex and the combinatorial background; therefore the need for a high precision vertex detector to reconstruct their decay particles. In 2014 a new micro vertex detector was installed in the STAR experiment at Brookhaven National Lab. The Heavy Flavor Tracker (HFT) was designed to perform direct topological reconstruction of the weak decays of heavy flavor particles. The HFT improves STAR track pointing resolution from a few millimeters to ˜30 microns for 1 GeV/c pions, allowing direct reconstruction of short lifetime particles. Although the results of the open charm meson reconstruction using the HFT improved dramatically there is still a lot of room for optimization, especially for reconstructed particles with low transverse momentum (< 1 GeV/c). The standard reconstruction algorithm in the STAR experiment is based on a helix swimming of the reconstructed tracks. This method consists of finding the distance of closest approach between the two helices and defining the midpoint as the decay particle's vertex position. In this work we are using an algorithm based on the Kalman filter to perform full vertex reconstruction. Although the Kalman filter is the most common fitting and filtering method used in tracking, it is not commonly used for particle reconstruction. By using the Kalman filter, the full error matrix for each track is taken into account in the calculations, performing a more complete approach to vertex reconstruction of the charm mesons by providing error estimates on all reconstructed quantities. Also in the traditional analyses, rectangular cuts are made to the reconstructed parameters of the candidate particle decay in order to improve the signal to background ratio and get the cleanest signal possible. In this analysis we use multivariate techniques (i.e. machine learning) to maximize the efficiency of the acquired signal. Machine learning techniques are widely used in many data analysis problems and are also in wide use in high-energy physics experiments. Different optimization methods are tested like Likelihood, Neural Networks. The one with the better performance for reconstruction of D0 mesons was found to be the Binary Decision Trees (BDT). We have applied these analysis techniques on our Run-14 data sample (~1.2 billion Au+Au events at 200 GeV) and we present results for D0 meson pT spectra and nuclear modification factor (RAA) for different event centralities. We discuss the obtained results and compare with current theory models.

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.

Grayscale Optical Correlator Workbench

NASA Technical Reports Server (NTRS)

Hanan, Jay; Zhou, Hanying; Chao, Tien-Hsin

2006-01-01

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

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

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.

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

PubMed

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

2017-08-18

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

Quantitative filter forensics for indoor particle sampling.

PubMed

Haaland, D; Siegel, J A

2017-03-01

Filter forensics is a promising indoor air investigation technique involving the analysis of dust which has collected on filters in central forced-air heating, ventilation, and air conditioning (HVAC) or portable systems to determine the presence of indoor particle-bound contaminants. In this study, we summarize past filter forensics research to explore what it reveals about the sampling technique and the indoor environment. There are 60 investigations in the literature that have used this sampling technique for a variety of biotic and abiotic contaminants. Many studies identified differences between contaminant concentrations in different buildings using this technique. Based on this literature review, we identified a lack of quantification as a gap in the past literature. Accordingly, we propose an approach to quantitatively link contaminants extracted from HVAC filter dust to time-averaged integrated air concentrations. This quantitative filter forensics approach has great potential to measure indoor air concentrations of a wide variety of particle-bound contaminants. Future studies directly comparing quantitative filter forensics to alternative sampling techniques are required to fully assess this approach, but analysis of past research suggests the enormous possibility of this approach. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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).

Initial Ares I Bending Filter Design

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Bedrossian, Nazareth; Hall, Robert; Norris, H. Lee; Hall, Charles; Jackson, Mark

2007-01-01

The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output will be required to ensure control system stability and adequate performance. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The filter design methodology was based on a numerical constrained optimization approach to maximize stability margins while meeting performance requirements. The resulting bending filter designs achieved stability by adding lag to the first structural frequency and hence phase stabilizing the first Ares-I flex mode. To minimize rigid body performance impacts, a priority was placed via constraints in the optimization algorithm to minimize bandwidth decrease with the addition of the bending filters. The bending filters provided here have been demonstrated to provide a stable first stage control system in both the frequency domain and the MSFC MAVERIC time domain simulation.

Feasibility of granular bed filtration of an aerosol of ultrafine metallic particles including a pressure drop regeneration system.

PubMed

Bémer, D; Wingert, L; Morele, Y; Subra, I

2015-09-01

A process for filtering an aerosol of ultrafine metallic particles (UFP) has been designed and tested, based on the principle of a multistage granular bed. The filtration system comprised a succession of granular beds of varying thickness composed of glass beads of different diameters. This system allows the pressure drop to be regenerated during filtration ("on-line" mode) using a vibrating probe. Tests monitoring the pressure drop were conducted on a "10-L/min" low airflow rate device and on a "100-m(3)/hr" prototype. Granular bed unclogging is automated on the latter. The cyclic operation and filtration performances are similar to that of filter medium-based industrial dust collectors. Filtration of ultrafine metallic particles generated by different industrial processes such as arc welding, metal cutting, or spraying constitutes a difficult problem due to the high filter clogging properties of these particles and to the high temperatures generally encountered. Granular beds represent an advantageous means of filtering these aerosols with difficult properties.

Irreversible sorption of trace concentrations of perfluorocarboxylic acids to fiber filters used for air sampling

NASA Astrophysics Data System (ADS)

Arp, Hans Peter H.; Goss, Kai-Uwe

Due to the apparent environmental omnipresence of perfluorocarboxylic acids (PFAs), an increasing number of researchers are investigating their ambient particle- and gas-phase concentrations. Typically this is done using a high-volume air sampler equipped with Quartz Fiber Filters (QFFs) or Glass Fiber Filters (GFFs) to sample the particle-bound PFAs and downstream sorbents to sample the gas-phase PFAs. This study reports that at trace, ambient concentrations gas-phase PFAs sorb to QFFs and GFFs irreversibly and hardly pass through these filters to the downstream sorbents. As a consequence, it is not possible to distinguish between particle- and gas-phase concentrations, or to distinguish concentrations on different particle size fractions, unless precautions are taken. Failure to take such precautions could have already caused reported data to be misinterpreted. Here it is also reported that deactivating QFFs and GFFs with a silylating agent renders them suitable for sampling PFAs. Based on the presented study, a series of recommendations for air-sampling PFAs are provided.

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

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.

An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation using real data from a multiphase producer

NASA Astrophysics Data System (ADS)

Lorentzen, Rolf J.; Stordal, Andreas S.; Hewitt, Neal

2017-05-01

Flowrate allocation in production wells is a complicated task, especially for multiphase flow combined with several reservoir zones and/or branches. The result depends heavily on the available production data, and the accuracy of these. In the application we show here, downhole pressure and temperature data are available, in addition to the total flowrates at the wellhead. The developed methodology inverts these observations to the fluid flowrates (oil, water and gas) that enters two production branches in a real full-scale producer. A major challenge is accurate estimation of flowrates during rapid variations in the well, e.g. due to choke adjustments. The Auxiliary Sequential Importance Resampling (ASIR) filter was developed to handle such challenges, by introducing an auxiliary step, where the particle weights are recomputed (second weighting step) based on how well the particles reproduce the observations. However, the ASIR filter suffers from large computational time when the number of unknown parameters increase. The Gaussian Mixture (GM) filter combines a linear update, with the particle filters ability to capture non-Gaussian behavior. This makes it possible to achieve good performance with fewer model evaluations. In this work we present a new filter which combines the ASIR filter and the Gaussian Mixture filter (denoted ASGM), and demonstrate improved estimation (compared to ASIR and GM filters) in cases with rapid parameter variations, while maintaining reasonable computational cost.

Two size-selective mechanisms specifically trap bacteria-sized food particles in Caenorhabditis elegans.

PubMed

Fang-Yen, Christopher; Avery, Leon; Samuel, Aravinthan D T

2009-11-24

Caenorhabditis elegans is a filter feeder: it draws bacteria suspended in liquid into its pharynx, traps the bacteria, and ejects the liquid. How pharyngeal pumping simultaneously transports and filters food particles has been poorly understood. Here, we use high-speed video microscopy to define the detailed workings of pharyngeal mechanics. The buccal cavity and metastomal flaps regulate the flow of dense bacterial suspensions and exclude excessively large particles from entering the pharynx. A complex sequence of contractions and relaxations transports food particles in two successive trap stages before passage into the terminal bulb and intestine. Filtering occurs at each trap as bacteria are concentrated in the central lumen while fluids are expelled radially through three apical channels. Experiments with microspheres show that the C. elegans pharynx, in combination with the buccal cavity, is tuned to specifically catch and transport particles of a size range corresponding to most soil bacteria.

Two size-selective mechanisms specifically trap bacteria-sized food particles in Caenorhabditis elegans

PubMed Central

Fang-Yen, Christopher; Avery, Leon; Samuel, Aravinthan D. T.

2009-01-01

Caenorhabditis elegans is a filter feeder: it draws bacteria suspended in liquid into its pharynx, traps the bacteria, and ejects the liquid. How pharyngeal pumping simultaneously transports and filters food particles has been poorly understood. Here, we use high-speed video microscopy to define the detailed workings of pharyngeal mechanics. The buccal cavity and metastomal flaps regulate the flow of dense bacterial suspensions and exclude excessively large particles from entering the pharynx. A complex sequence of contractions and relaxations transports food particles in two successive trap stages before passage into the terminal bulb and intestine. Filtering occurs at each trap as bacteria are concentrated in the central lumen while fluids are expelled radially through three apical channels. Experiments with microspheres show that the C. elegans pharynx, in combination with the buccal cavity, is tuned to specifically catch and transport particles of a size range corresponding to most soil bacteria. PMID:19903886

A CAM (continuous air monitor) sampler for collecting and assessing alpha-emitting aerosol particles

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

McFarland, A.R.; Bethel, E.L.; Ortiz, C.A.

1991-07-01

A new continuous air monitor (CAM) sampler for assessing alpha-emitting transuranic aerosol particles has been developed. The system has been designed to permit collection of particles that can potentially penetrate into the thoracic region of the human respiratory system. Wind tunnel testing of the sampler has been used to characterize the penetration of aerosol to the collection filter. Results show that greater than or equal to 50% of 10-micrograms aerodynamic equivalent diameter (AED) particles are collected by the filter at wind speeds of 0.3 to 2 m s-1 and at sampling flow rates of 28 to 113 L min-1 (1more » to 4 cfm). The deposition of 10-microns AED particles takes place primarily in the center of the filter, where the counting efficiency of the detector is highest.« less

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.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

Advanced lithographic filtration and contamination control for 14nm node and beyond semiconductor processes

NASA Astrophysics Data System (ADS)

Varanasi, Rao; Mesawich, Michael; Connor, Patrick; Johnson, Lawrence

2017-03-01

Two versions of a specific 2nm rated filter containing filtration medium and all other components produced from high density polyethylene (HDPE), one subjected to standard cleaning, the other to specialized ultra-cleaning, were evaluated in terms of their cleanliness characteristics, and also defectivity of wafers processed with photoresist filtered through each. With respect to inherent cleanliness, the ultraclean version exhibited a 70% reduction in total metal extractables and 90% reduction in organics extractables compared to the standard clean version. In terms of particulate cleanliness, the ultraclean version achieved stability of effluent particles 30nm and larger in about half the time required by the standard clean version, also exhibiting effluent levels at stability almost 90% lower. In evaluating defectivity of blanket wafers processed with photoresist filtered through either version, initial defect density while using the ultraclean version was about half that observed when the standard clean version was in service, with defectivity also falling more rapidly during subsequent usage of the ultraclean version compared to the standard clean version. Similar behavior was observed for patterned wafers, where the enhanced defect reduction was primarily of bridging defects. The filter evaluation and actual process-oriented results demonstrate the extreme value in using filtration designed possessing the optimal intrinsic characteristics, but with further improvements possible through enhanced cleaning processes

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.

Optimal frequency domain textural edge detection filter

NASA Technical Reports Server (NTRS)

Townsend, J. K.; Shanmugan, K. S.; Frost, V. S.

1985-01-01

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

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.

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.

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...

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

Sci-Thur AM: YIS – 07: Optimizing dual-energy x-ray parameters using a single filter for both high and low-energy images to enhance soft-tissue imaging

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

Bowman, Wesley; Sattarivand, Mike

Objective: To optimize dual-energy parameters of ExacTrac stereoscopic x-ray imaging system for lung SBRT patients Methods: Simulated spectra and a lung phantom were used to optimize filter material, thickness, kVps, and weighting factors to obtain bone subtracted dual-energy images. Spektr simulations were used to identify material in the atomic number (Z) range [3–83] based on a metric defined to separate spectrums of high and low energies. Both energies used the same filter due to time constraints of image acquisition in lung SBRT imaging. A lung phantom containing bone, soft tissue, and a tumor mimicking material was imaged with filter thicknessesmore » range [0–1] mm and kVp range [60–140]. A cost function based on contrast-to-noise-ratio of bone, soft tissue, and tumor, as well as image noise content, was defined to optimize filter thickness and kVp. Using the optimized parameters, dual-energy images of anthropomorphic Rando phantom were acquired and evaluated for bone subtraction. Imaging dose was measured with dual-energy technique using tin filtering. Results: Tin was the material of choice providing the best energy separation, non-toxicity, and non-reactiveness. The best soft-tissue-only image in the lung phantom was obtained using 0.3 mm tin and [140, 80] kVp pair. Dual-energy images of the Rando phantom had noticeable bone elimination when compared to no filtration. Dose was lower with tin filtering compared to no filtration. Conclusions: Dual-energy soft-tissue imaging is feasible using ExacTrac stereoscopic imaging system utilizing a single tin filter for both high and low energies and optimized acquisition parameters.« less

Packing Optimization of an Intentionally Stratified Sorbent Bed Containing Dissimilar Media Types

NASA Technical Reports Server (NTRS)

Kidd, Jessica; Guttromson, Jayleen; Holland, Nathan

2010-01-01

The Fire Cartridge is a packed bed air filter with two different and separate layers of media designed to provide respiratory protection from combustion products after a fire event on the International Space Station (ISS). The first layer of media is a carbon monoxide catalyst made from gold nanoparticles dispersed on iron oxide. The second layer of media is universal carbon, commonly used in commercial respirator filters. Each layer must be optimally packed to effectively remove contaminants from the air. Optimal packing is achieved by vibratory agitations. However, if post-packing movement of the media within the cartridge occurs, mixing of the bed layers, air voids, and channeling could cause preferential air flow and allow contaminants to pass. Several iterations of prototype fire cartridges were developed to reduce post-packing movement of the media within each layer (settling), and to prevent mixing of the two media types. Both types of movement of the media contribute to decreased fire cartridge performance. Each iteration of the fire cartridge design was tested to demonstrate mechanical loads required to cause detrimental movement within the bed, and resulting level of functionality of the media beds after movement was detected. In order to optimally pack each layer, vertical, horizontal, and orbital agitations were tested and a final packed bulk density was calculated for each method. Packed bulk density must be calculated for each lot of catalyst to accommodate variations in particle size, shape, and density. In addition, a physical divider sheet between each type of media was added within the fire cartridge design to further inhibit intermixing of the bed layers.

Experimental Evaluation of UWB Indoor Positioning for Sport Postures

PubMed Central

Defraye, Jense; Steendam, Heidi; Gerlo, Joeri; De Clercq, Dirk; De Poorter, Eli

2018-01-01

Radio frequency (RF)-based indoor positioning systems (IPSs) use wireless technologies (including Wi-Fi, Zigbee, Bluetooth, and ultra-wide band (UWB)) to estimate the location of persons in areas where no Global Positioning System (GPS) reception is available, for example in indoor stadiums or sports halls. Of the above-mentioned forms of radio frequency (RF) technology, UWB is considered one of the most accurate approaches because it can provide positioning estimates with centimeter-level accuracy. However, it is not yet known whether UWB can also offer such accurate position estimates during strenuous dynamic activities in which moves are characterized by fast changes in direction and velocity. To answer this question, this paper investigates the capabilities of UWB indoor localization systems for tracking athletes during their complex (and most of the time unpredictable) movements. To this end, we analyze the impact of on-body tag placement locations and human movement patterns on localization accuracy and communication reliability. Moreover, two localization algorithms (particle filter and Kalman filter) with different optimizations (bias removal, non-line-of-sight (NLoS) detection, and path determination) are implemented. It is shown that although the optimal choice of optimization depends on the type of movement patterns, some of the improvements can reduce the localization error by up to 31%. Overall, depending on the selected optimization and on-body tag placement, our algorithms show good results in terms of positioning accuracy, with average errors in position estimates of 20 cm. This makes UWB a suitable approach for tracking dynamic athletic activities. PMID:29315267

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...

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

Joint Transmit and Receive Filter Optimization for Sub-Nyquist Delay-Doppler Estimation

NASA Astrophysics Data System (ADS)

Lenz, Andreas; Stein, Manuel S.; Swindlehurst, A. Lee

2018-05-01

In this article, a framework is presented for the joint optimization of the analog transmit and receive filter with respect to a parameter estimation problem. At the receiver, conventional signal processing systems restrict the two-sided bandwidth of the analog pre-filter $B$ to the rate of the analog-to-digital converter $f_s$ to comply with the well-known Nyquist-Shannon sampling theorem. In contrast, here we consider a transceiver that by design violates the common paradigm $B\\leq f_s$. To this end, at the receiver, we allow for a higher pre-filter bandwidth $B>f_s$ and study the achievable parameter estimation accuracy under a fixed sampling rate when the transmit and receive filter are jointly optimized with respect to the Bayesian Cram\\'{e}r-Rao lower bound. For the case of delay-Doppler estimation, we propose to approximate the required Fisher information matrix and solve the transceiver design problem by an alternating optimization algorithm. The presented approach allows us to explore the Pareto-optimal region spanned by transmit and receive filters which are favorable under a weighted mean squared error criterion. We also discuss the computational complexity of the obtained transceiver design by visualizing the resulting ambiguity function. Finally, we verify the performance of the optimized designs by Monte-Carlo simulations of a likelihood-based estimator.

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.

Rapid detection of bacterial contamination in cell or tissue cultures based on Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bolwien, Carsten; Sulz, Gerd; Becker, Sebastian; Thielecke, Hagen; Mertsching, Heike; Koch, Steffen

2008-02-01

Monitoring the sterility of cell or tissue cultures is an essential task, particularly in the fields of regenerative medicine and tissue engineering when implanting cells into the human body. We present a system based on a commercially available microscope equipped with a microfluidic cell that prepares the particles found in the solution for analysis, a Raman-spectrometer attachment optimized for non-destructive, rapid recording of Raman spectra, and a data acquisition and analysis tool for identification of the particles. In contrast to conventional sterility testing in which samples are incubated over weeks, our system is able to analyze milliliters of supernatant or cell suspension within hours by filtering relevant particles and placing them on a Raman-friendly substrate in the microfluidic cell. Identification of critical particles via microscopic imaging and subsequent image analysis is carried out before micro-Raman analysis of those particles is then carried out with an excitation wavelength of 785 nm. The potential of this setup is demonstrated by results of artificial contamination of samples with a pool of bacteria, fungi, and spores: single-channel spectra of the critical particles are automatically baseline-corrected without using background data and classified via hierarchical cluster analysis, showing great promise for accurate and rapid detection and identification of contaminants.

SU-F-T-149: Development of the Monte Carlo Simulation Platform Using Geant4 for Designing Heavy Ion Therapy Beam Nozzle

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

Shin, Jae-ik; Yoo, SeungHoon; Cho, Sungho

Purpose: The significant issue of particle therapy such as proton and carbon ion was a accurate dose delivery from beam line to patient. For designing the complex delivery system, Monte Carlo simulation can be used for the simulation of various physical interaction in scatters and filters. In this report, we present the development of Monte Carlo simulation platform to help design the prototype of particle therapy nozzle and performed the Monte Carlo simulation using Geant4. Also we show the prototype design of particle therapy beam nozzle for Korea Heavy Ion Medical Accelerator (KHIMA) project in Korea Institute of Radiological andmore » Medical Science(KIRAMS) at Republic of Korea. Methods: We developed a simulation platform for particle therapy beam nozzle using Geant4. In this platform, the prototype nozzle design of Scanning system for carbon was simply designed. For comparison with theoretic beam optics, the beam profile on lateral distribution at isocenter is compared with Mont Carlo simulation result. From the result of this analysis, we can expected the beam spot property of KHIMA system and implement the spot size optimization for our spot scanning system. Results: For characteristics study of scanning system, various combination of the spot size from accerlator with ridge filter and beam monitor was tested as simple design for KHIMA dose delivery system. Conclusion: In this report, we presented the part of simulation platform and the characteristics study. This study is now on-going in order to develop the simulation platform including the beam nozzle and the dose verification tool with treatment planning system. This will be presented as soon as it is become available.« less

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

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.

Particle Filters for Real-Time Fault Detection in Planetary Rovers

NASA Technical Reports Server (NTRS)

Dearden, Richard; Clancy, Dan; Koga, Dennis (Technical Monitor)

2001-01-01

Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not suitable for rovers due to the tight coupling between the vehicle's performance and its environment. Hybrid diagnosis using particle filters is presented as an alternative, and its strengths and weakeners are examined. We also present some extensions to particle filters that are designed to make them more suitable for use in diagnosis problems.

Room air monitor for radioactive aerosols

DOEpatents

Balmer, D.K.; Tyree, W.H.

1987-03-23

A housing assembly for use with a room air monitor for simultaneous collection and counting of suspended particles includes a casing containing a combination detector-preamplifier system at one end, a filter system at the other end, and an air flow system consisting of an air inlet formed in the casing between the detector-preamplifier system and the filter system and an air passageway extending from the air inlet through the casing and out the end opposite the detector-preamplifier combination. The filter system collects suspended particles transported directly through the housing by means of the air flow system, and these particles are detected and examined for radioactivity by the detector-preamplifier combination. 2 figs.

Robust Controller for Turbulent and Convective Boundary Layers

DTIC Science & Technology

2006-08-01

filter and an optimal regulator. The Kalman filter equation and the optimal regulator equation corresponding to the state-space equations, (2.20), are...separate steady-state algebraic Riccati equations. The Kalman filter is used here as a state observer rather than as an estimator since no noises are...2001) which will not be repeated here. For robustness, in the design, the Kalman filter input matrix G has been set equal to the control input

Adaptive torque estimation of robot joint with harmonic drive transmission

NASA Astrophysics Data System (ADS)

Shi, Zhiguo; Li, Yuankai; Liu, Guangjun

2017-11-01

Robot joint torque estimation using input and output position measurements is a promising technique, but the result may be affected by the load variation of the joint. In this paper, a torque estimation method with adaptive robustness and optimality adjustment according to load variation is proposed for robot joint with harmonic drive transmission. Based on a harmonic drive model and a redundant adaptive robust Kalman filter (RARKF), the proposed approach can adapt torque estimation filtering optimality and robustness to the load variation by self-tuning the filtering gain and self-switching the filtering mode between optimal and robust. The redundant factor of RARKF is designed as a function of the motor current for tolerating the modeling error and load-dependent filtering mode switching. The proposed joint torque estimation method has been experimentally studied in comparison with a commercial torque sensor and two representative filtering methods. The results have demonstrated the effectiveness of the proposed torque estimation technique.

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

Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement.

PubMed

Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon

2017-02-24

The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers.

Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement

PubMed Central

Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon

2017-01-01

The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers. PMID:28245584

Optical Correlation of Images With Signal-Dependent Noise Using Constrained-Modulation Filter Devices

NASA Technical Reports Server (NTRS)

Downie, John D.

1995-01-01

Images with signal-dependent noise present challenges beyond those of images with additive white or colored signal-independent noise in terms of designing the optimal 4-f correlation filter that maximizes correlation-peak signal-to-noise ratio, or combinations of correlation-peak metrics. Determining the proper design becomes more difficult when the filter is to be implemented on a constrained-modulation spatial light modulator device. The design issues involved for updatable optical filters for images with signal-dependent film-grain noise and speckle noise are examined. It is shown that although design of the optimal linear filter in the Fourier domain is impossible for images with signal-dependent noise, proper nonlinear preprocessing of the images allows the application of previously developed design rules for optimal filters to be implemented on constrained-modulation devices. Thus the nonlinear preprocessing becomes necessary for correlation in optical systems with current spatial light modulator technology. These results are illustrated with computer simulations of images with signal-dependent noise correlated with binary-phase-only filters and ternary-phase-amplitude filters.

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.

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.

New estimation architecture for multisensor data fusion

NASA Astrophysics Data System (ADS)

Covino, Joseph M.; Griffiths, Barry E.

1991-07-01

This paper describes a novel method of hierarchical asynchronous distributed filtering called the Net Information Approach (NIA). The NIA is a Kalman-filter-based estimation scheme for spatially distributed sensors which must retain their local optimality yet require a nearly optimal global estimate. The key idea of the NIA is that each local sensor-dedicated filter tells the global filter 'what I've learned since the last local-to-global transmission,' whereas in other estimation architectures the local-to-global transmission consists of 'what I think now.' An algorithm based on this idea has been demonstrated on a small-scale target-tracking problem with many encouraging results. Feasibility of this approach was demonstrated by comparing NIA performance to an optimal centralized Kalman filter (lower bound) via Monte Carlo simulations.

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.

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...

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

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.

Quaternion Averaging

NASA Technical Reports Server (NTRS)

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

2007-01-01

Many applications require an algorithm that averages quaternions in an optimal manner. For example, when combining the quaternion outputs of multiple star trackers having this output capability, it is desirable to properly average the quaternions without recomputing the attitude from the the raw star tracker data. Other applications requiring some sort of optimal quaternion averaging include particle filtering and multiple-model adaptive estimation, where weighted quaternions are used to determine the quaternion estimate. For spacecraft attitude estimation applications, derives an optimal averaging scheme to compute the average of a set of weighted attitude matrices using the singular value decomposition method. Focusing on a 4-dimensional quaternion Gaussian distribution on the unit hypersphere, provides an approach to computing the average quaternion by minimizing a quaternion cost function that is equivalent to the attitude matrix cost function Motivated by and extending its results, this Note derives an algorithm that deterniines an optimal average quaternion from a set of scalar- or matrix-weighted quaternions. Rirthermore, a sufficient condition for the uniqueness of the average quaternion, and the equivalence of the mininiization problem, stated herein, to maximum likelihood estimation, are shown.

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.

Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space.

PubMed

Huang, Jianyong; Qin, Lei; Peng, Xiaoling; Zhu, Tao; Xiong, Chunyang; Zhang, Youyi; Fang, Jing

2009-08-21

Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

GaN nanostructure design for optimal dislocation filtering

NASA Astrophysics Data System (ADS)

Liang, Zhiwen; Colby, Robert; Wildeson, Isaac H.; Ewoldt, David A.; Sands, Timothy D.; Stach, Eric A.; García, R. Edwin

2010-10-01

The effect of image forces in GaN pyramidal nanorod structures is investigated to develop dislocation-free light emitting diodes (LEDs). A model based on the eigenstrain method and nonlocal stress is developed to demonstrate that the pyramidal nanorod efficiently ejects dislocations out of the structure. Two possible regimes of filtering behavior are found: (1) cap-dominated and (2) base-dominated. The cap-dominated regime is shown to be the more effective filtering mechanism. Optimal ranges of fabrication parameters that favor a dislocation-free LED are predicted and corroborated by resorting to available experimental evidence. The filtering probability is summarized as a function of practical processing parameters: the nanorod radius and height. The results suggest an optimal nanorod geometry with a radius of ˜50b (26 nm) and a height of ˜125b (65 nm), in which b is the magnitude of the Burgers vector for the GaN system studied. A filtering probability of greater than 95% is predicted for the optimal geometry.

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.

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

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

Weighted finite impulse response filter for chromatic dispersion equalization in coherent optical fiber communication systems

NASA Astrophysics Data System (ADS)

Zeng, Ziyi; Yang, Aiying; Guo, Peng; Feng, Lihui

2018-01-01

Time-domain CD equalization using finite impulse response (FIR) filter is now a common approach for coherent optical fiber communication systems. The complex weights of FIR taps are calculated from a truncated impulse response of the CD transfer function, and the modulus of the complex weights is constant. In our work, we take the limited bandwidth of a single channel signal into account and propose weighted FIRs to improve the performance of CD equalization. The key in weighted FIR filters is the selection and optimization of weighted functions. In order to present the performance of different types of weighted FIR filters, a square-root raised cosine FIR (SRRC-FIR) and a Gaussian FIR (GS-FIR) are investigated. The optimization of square-root raised cosine FIR and Gaussian FIR are made in term of the bit rate error (BER) of QPSK and 16QAM coherent detection signal. The results demonstrate that the optimized parameters of the weighted filters are independent of the modulation format, symbol rate and the length of transmission fiber. With the optimized weighted FIRs, the BER of CD equalization signal is decreased significantly. Although this paper has investigated two types of weighted FIR filters, i.e. SRRC-FIR filter and GS-FIR filter, the principle of weighted FIR can also be extended to other symmetric functions super Gaussian function, hyperbolic secant function and etc.

Design of order statistics filters using feedforward neural networks

NASA Astrophysics Data System (ADS)

Maslennikova, Yu. S.; Bochkarev, V. V.

2016-08-01

In recent years significant progress have been made in the development of nonlinear data processing techniques. Such techniques are widely used in digital data filtering and image enhancement. Many of the most effective nonlinear filters based on order statistics. The widely used median filter is the best known order statistic filter. Generalized form of these filters could be presented based on Lloyd's statistics. Filters based on order statistics have excellent robustness properties in the presence of impulsive noise. In this paper, we present special approach for synthesis of order statistics filters using artificial neural networks. Optimal Lloyd's statistics are used for selecting of initial weights for the neural network. Adaptive properties of neural networks provide opportunities to optimize order statistics filters for data with asymmetric distribution function. Different examples demonstrate the properties and performance of presented approach.

The optimal digital filters of sine and cosine transforms for geophysical transient electromagnetic method

NASA Astrophysics Data System (ADS)

Zhao, Yun-wei; Zhu, Zi-qiang; Lu, Guang-yin; Han, Bo

2018-03-01

The sine and cosine transforms implemented with digital filters have been used in the Transient electromagnetic methods for a few decades. Kong (2007) proposed a method of obtaining filter coefficients, which are computed in the sample domain by Hankel transform pair. However, the curve shape of Hankel transform pair changes with a parameter, which usually is set to be 1 or 3 in the process of obtaining the digital filter coefficients of sine and cosine transforms. First, this study investigates the influence of the parameter on the digital filter algorithm of sine and cosine transforms based on the digital filter algorithm of Hankel transform and the relationship between the sine, cosine function and the ±1/2 order Bessel function of the first kind. The results show that the selection of the parameter highly influences the precision of digital filter algorithm. Second, upon the optimal selection of the parameter, it is found that an optimal sampling interval s also exists to achieve the best precision of digital filter algorithm. Finally, this study proposes four groups of sine and cosine transform digital filter coefficients with different length, which may help to develop the digital filter algorithm of sine and cosine transforms, and promote its application.

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.

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.

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.

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.

Optimal Resonant Band Demodulation Based on an Improved Correlated Kurtosis and Its Application in Bearing Fault Diagnosis

PubMed Central

Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng

2017-01-01

The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes. PMID:28208820

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.

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.

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.

A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

PubMed

Konkle, Justin J; Goodwill, Patrick W; Hensley, Daniel W; Orendorff, Ryan D; Lustig, Michael; Conolly, Steven M

2015-01-01

Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

A novel Bayesian framework for discriminative feature extraction in Brain-Computer Interfaces.

PubMed

Suk, Heung-Il; Lee, Seong-Whan

2013-02-01

As there has been a paradigm shift in the learning load from a human subject to a computer, machine learning has been considered as a useful tool for Brain-Computer Interfaces (BCIs). In this paper, we propose a novel Bayesian framework for discriminative feature extraction for motor imagery classification in an EEG-based BCI in which the class-discriminative frequency bands and the corresponding spatial filters are optimized by means of the probabilistic and information-theoretic approaches. In our framework, the problem of simultaneous spatiospectral filter optimization is formulated as the estimation of an unknown posterior probability density function (pdf) that represents the probability that a single-trial EEG of predefined mental tasks can be discriminated in a state. In order to estimate the posterior pdf, we propose a particle-based approximation method by extending a factored-sampling technique with a diffusion process. An information-theoretic observation model is also devised to measure discriminative power of features between classes. From the viewpoint of classifier design, the proposed method naturally allows us to construct a spectrally weighted label decision rule by linearly combining the outputs from multiple classifiers. We demonstrate the feasibility and effectiveness of the proposed method by analyzing the results and its success on three public databases.

Optimal nonlinear filtering using the finite-volume method

NASA Astrophysics Data System (ADS)

Fox, Colin; Morrison, Malcolm E. K.; Norton, Richard A.; Molteno, Timothy C. A.

2018-01-01

Optimal sequential inference, or filtering, for the state of a deterministic dynamical system requires simulation of the Frobenius-Perron operator, that can be formulated as the solution of a continuity equation. For low-dimensional, smooth systems, the finite-volume numerical method provides a solution that conserves probability and gives estimates that converge to the optimal continuous-time values, while a Courant-Friedrichs-Lewy-type condition assures that intermediate discretized solutions remain positive density functions. This method is demonstrated in an example of nonlinear filtering for the state of a simple pendulum, with comparison to results using the unscented Kalman filter, and for a case where rank-deficient observations lead to multimodal probability distributions.

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.

Modeling error analysis of stationary linear discrete-time filters

NASA Technical Reports Server (NTRS)

Patel, R.; Toda, M.

1977-01-01

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available.

SU-E-I-57: Evaluation and Optimization of Effective-Dose Using Different Beam-Hardening Filters in Clinical Pediatric Shunt CT Protocol

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

Gill, K; Aldoohan, S; Collier, J

Purpose: Study image optimization and radiation dose reduction in pediatric shunt CT scanning protocol through the use of different beam-hardening filters Methods: A 64-slice CT scanner at OU Childrens Hospital has been used to evaluate CT image contrast-to-noise ratio (CNR) and measure effective-doses based on the concept of CT dose index (CTDIvol) using the pediatric head shunt scanning protocol. The routine axial pediatric head shunt scanning protocol that has been optimized for the intrinsic x-ray tube filter has been used to evaluate CNR by acquiring images using the ACR approved CT-phantom and radiation dose CTphantom, which was used to measuremore » CTDIvol. These results were set as reference points to study and evaluate the effects of adding different filtering materials (i.e. Tungsten, Tantalum, Titanium, Nickel and Copper filters) to the existing filter on image quality and radiation dose. To ensure optimal image quality, the scanner routine air calibration was run for each added filter. The image CNR was evaluated for different kVps and wide range of mAs values using above mentioned beam-hardening filters. These scanning protocols were run under axial as well as under helical techniques. The CTDIvol and the effective-dose were measured and calculated for all scanning protocols and added filtration, including the intrinsic x-ray tube filter. Results: Beam-hardening filter shapes energy spectrum, which reduces the dose by 27%. No noticeable changes in image low contrast detectability Conclusion: Effective-dose is very much dependent on the CTDIVol, which is further very much dependent on beam-hardening filters. Substantial reduction in effective-dose is realized using beam-hardening filters as compare to the intrinsic filter. This phantom study showed that significant radiation dose reduction could be achieved in CT pediatric shunt scanning protocols without compromising in diagnostic value of image quality.« less

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

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.

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.

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.

Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

PubMed Central

Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390

Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

PubMed

Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

2013-01-01

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

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.

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.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.

PubMed

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M

2018-04-12

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.

Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes

PubMed Central

Li, Yuqi; Majumder, Aditi; Zhang, Hao; Gopi, M.

2018-01-01

Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. PMID:29649114

Optimizing of a high-order digital filter using PSO algorithm

NASA Astrophysics Data System (ADS)

Xu, Fuchun

2018-04-01

A self-adaptive high-order digital filter, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance, is presented in this paper. The parameters of traditional digital filter are mainly tuned by complex calculation, whereas this paper presents a 5th order digital filter to obtain outstanding performance and the parameters of the proposed filter are optimized by swarm intelligent algorithm. Simulation results with respect to the proposed 5th order digital filter, SNR>122dB and the noise floor under -170dB are obtained in frequency range of [5-150Hz]. In further simulation, the robustness of the proposed 5th order digital is analyzed.

Analysis of multidimensional difference-of-Gaussians filters in terms of directly observable parameters.

PubMed

Cope, Davis; Blakeslee, Barbara; McCourt, Mark E

2013-05-01

The difference-of-Gaussians (DOG) filter is a widely used model for the receptive field of neurons in the retina and lateral geniculate nucleus (LGN) and is a potential model in general for responses modulated by an excitatory center with an inhibitory surrounding region. A DOG filter is defined by three standard parameters: the center and surround sigmas (which define the variance of the radially symmetric Gaussians) and the balance (which defines the linear combination of the two Gaussians). These parameters are not directly observable and are typically determined by nonlinear parameter estimation methods applied to the frequency response function. DOG filters show both low-pass (optimal response at zero frequency) and bandpass (optimal response at a nonzero frequency) behavior. This paper reformulates the DOG filter in terms of a directly observable parameter, the zero-crossing radius, and two new (but not directly observable) parameters. In the two-dimensional parameter space, the exact region corresponding to bandpass behavior is determined. A detailed description of the frequency response characteristics of the DOG filter is obtained. It is also found that the directly observable optimal frequency and optimal gain (the ratio of the response at optimal frequency to the response at zero frequency) provide an alternate coordinate system for the bandpass region. Altogether, the DOG filter and its three standard implicit parameters can be determined by three directly observable values. The two-dimensional bandpass region is a potential tool for the analysis of populations of DOG filters (for example, populations of neurons in the retina or LGN), because the clustering of points in this parameter space may indicate an underlying organizational principle. This paper concentrates on circular Gaussians, but the results generalize to multidimensional radially symmetric Gaussians and are given as an appendix.

Information theoretic methods for image processing algorithm optimization

NASA Astrophysics Data System (ADS)

Prokushkin, Sergey F.; Galil, Erez

2015-01-01

Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

Accumulative Difference Image Protocol for Particle Tracking in Fluorescence Microscopy Tested in Mouse Lymphonodes

PubMed Central

Villa, Carlo E.; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-01-01

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done. PMID:20808918

Accumulative difference image protocol for particle tracking in fluorescence microscopy tested in mouse lymphonodes.

PubMed

Villa, Carlo E; Caccia, Michele; Sironi, Laura; D'Alfonso, Laura; Collini, Maddalena; Rivolta, Ilaria; Miserocchi, Giuseppe; Gorletta, Tatiana; Zanoni, Ivan; Granucci, Francesca; Chirico, Giuseppe

2010-08-17

The basic research in cell biology and in medical sciences makes large use of imaging tools mainly based on confocal fluorescence and, more recently, on non-linear excitation microscopy. Substantially the aim is the recognition of selected targets in the image and their tracking in time. We have developed a particle tracking algorithm optimized for low signal/noise images with a minimum set of requirements on the target size and with no a priori knowledge of the type of motion. The image segmentation, based on a combination of size sensitive filters, does not rely on edge detection and is tailored for targets acquired at low resolution as in most of the in-vivo studies. The particle tracking is performed by building, from a stack of Accumulative Difference Images, a single 2D image in which the motion of the whole set of the particles is coded in time by a color level. This algorithm, tested here on solid-lipid nanoparticles diffusing within cells and on lymphocytes diffusing in lymphonodes, appears to be particularly useful for the cellular and the in-vivo microscopy image processing in which few a priori assumption on the type, the extent and the variability of particle motions, can be done.

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.

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.

Optimally designed narrowband guided-mode resonance reflectance filters for mid-infrared spectroscopy

PubMed Central

Liu, Jui-Nung; Schulmerich, Matthew V.; Bhargava, Rohit; Cunningham, Brian T.

2011-01-01

An alternative to the well-established Fourier transform infrared (FT-IR) spectrometry, termed discrete frequency infrared (DFIR) spectrometry, has recently been proposed. This approach uses narrowband mid-infrared reflectance filters based on guided-mode resonance (GMR) in waveguide gratings, but filters designed and fabricated have not attained the spectral selectivity (≤ 32 cm−1) commonly employed for measurements of condensed matter using FT-IR spectroscopy. With the incorporation of dispersion and optical absorption of materials, we present here optimal design of double-layer surface-relief silicon nitride-based GMR filters in the mid-IR for various narrow bandwidths below 32 cm−1. Both shift of the filter resonance wavelengths arising from the dispersion effect and reduction of peak reflection efficiency and electric field enhancement due to the absorption effect show that the optical characteristics of materials must be taken into consideration rigorously for accurate design of narrowband GMR filters. By incorporating considerations for background reflections, the optimally designed GMR filters can have bandwidth narrower than the designed filter by the antireflection equivalence method based on the same index modulation magnitude, without sacrificing low sideband reflections near resonance. The reported work will enable use of GMR filters-based instrumentation for common measurements of condensed matter, including tissues and polymer samples. PMID:22109445

Optimization of confocal laser induced fluorescence for long focal length applications

NASA Astrophysics Data System (ADS)

Jemiolo, Andrew J.; Henriquez, Miguel F.; Thompson, Derek S.; Scime, Earl E.

2017-10-01

Laser induced fluorescence (LIF) is a non-perturbative diagnostic for measuring ion and neutral particle velocities and temperatures in a plasma. The conventional method for single-photon LIF requires intersecting optical paths for light injection and collection. The multiple vacuum windows needed for such measurements are unavailable in many plasma experiments. Confocal LIF eliminates the need for perpendicular intersecting optical paths by using concentric injection and collection paths through a single window. One of the main challenges with using confocal LIF is achieving high resolution measurements at the longer focal lengths needed for many plasma experiments. We present confocal LIF measurements in HELIX, a helicon plasma experiment at West Virginia University, demonstrating spatial resolution dependence on focal length and spatial filtering. By combining aberration mitigating optics with spatial filtering, our results show high resolution measurements at focal lengths of 0.5 m, long enough to access the interiors of many laboratory plasma experiments. This work was supported by U.S. National Science Foundation Grant No. PHY-1360278.

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.

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.

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.

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.

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.

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.

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

Optimization Algorithm for Kalman Filter Exploiting the Numerical Characteristics of SINS/GPS Integrated Navigation Systems.

PubMed

Hu, Shaoxing; Xu, Shike; Wang, Duhu; Zhang, Aiwu

2015-11-11

Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted "useful" data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency.

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.

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

Automated Counting of Particles To Quantify Cleanliness

NASA Technical Reports Server (NTRS)

Rhode, James

2005-01-01

A machine vision system, similar to systems used in microbiological laboratories to count cultured microbes, has been proposed for quantifying the cleanliness of nominally precisely cleaned hardware by counting residual contaminant particles. The system would include a microscope equipped with an electronic camera and circuitry to digitize the camera output, a personal computer programmed with machine-vision and interface software, and digital storage media. A filter pad, through which had been aspirated solvent from rinsing the hardware in question, would be placed on the microscope stage. A high-resolution image of the filter pad would be recorded. The computer would analyze the image and present a histogram of sizes of particles on the filter. On the basis of the histogram and a measure of the desired level of cleanliness, the hardware would be accepted or rejected. If the hardware were accepted, the image would be saved, along with other information, as a quality record. If the hardware were rejected, the histogram and ancillary information would be recorded for analysis of trends. The software would perceive particles that are too large or too numerous to meet a specified particle-distribution profile. Anomalous particles or fibrous material would be flagged for inspection.

Cryogenic filter method produces super-pure helium and helium isotopes

NASA Technical Reports Server (NTRS)

Hildebrandt, A. F.

1964-01-01

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

Assessment of intermittently loaded woodchip and sand filters to treat dairy soiled water.

PubMed

Murnane, J G; Brennan, R B; Healy, M G; Fenton, O

2016-10-15

Land application of dairy soiled water (DSW) is expensive relative to its nutrient replacement value. The use of aerobic filters is an effective alternative method of treatment and potentially allows the final effluent to be reused on the farm. Knowledge gaps exist concerning the optimal design and operation of filters for the treatment of DSW. To address this, 18 laboratory-scale filters, with depths of either 0.6 m or 1 m, were intermittently loaded with DSW over periods of up to 220 days to evaluate the impacts of depth (0.6 m versus 1 m), organic loading rates (OLRs) (50 versus 155 g COD m(-2) d(-1)), and media type (woodchip versus sand) on organic, nutrient and suspended solids (SS) removals. The study found that media depth was important in contaminant removal in woodchip filters. Reductions of 78% chemical oxygen demand (COD), 95% SS, 85% total nitrogen (TN), 82% ammonium-nitrogen (NH4N), 50% total phosphorus (TP), and 54% dissolved reactive phosphorus (DRP) were measured in 1 m deep woodchip filters, which was greater than the reductions in 0.6 m deep woodchip filters. Woodchip filters also performed optimally when loaded at a high OLR (155 g COD m(-2) d(-1)), although the removal mechanism was primarily physical (i.e. straining) as opposed to biological. When operated at the same OLR and when of the same depth, the sand filters had better COD removals (96%) than woodchip (74%), but there was no significant difference between them in the removal of SS and NH4N. However, the likelihood of clogging makes sand filters less desirable than woodchip filters. Using the optimal designs of both configurations, the filter area required per cow for a woodchip filter is more than four times less than for a sand filter. Therefore, this study found that woodchip filters are more economically and environmentally effective in the treatment of DSW than sand filters, and optimal performance may be achieved using woodchip filters with a depth of at least 1 m, operated at an OLR of 155 g COD m(-2) d(-1). Copyright © 2016 Elsevier Ltd. All rights reserved.

Bonded carbon or ceramic fiber composite filter vent for radioactive waste

DOEpatents

Brassell, Gilbert W.; Brugger, Ronald P.

1985-02-19

Carbon bonded carbon fiber composites as well as ceramic or carbon bonded ceramic fiber composites are very useful as filters which can separate particulate matter from gas streams entraining the same. These filters have particular application to the filtering of radioactive particles, e.g., they can act as vents for containers of radioactive waste material.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

A computer controlled signal preprocessor for laser fringe anemometer applications

NASA Technical Reports Server (NTRS)

Oberle, Lawrence G.

1987-01-01

The operation of most commercially available laser fringe anemometer (LFA) counter-processors assumes that adjustments are made to the signal processing independent of the computer used for reducing the data acquired. Not only does the researcher desire a record of these parameters attached to the data acquired, but changes in flow conditions generally require that these settings be changed to improve data quality. Because of this limitation, on-line modification of the data acquisition parameters can be difficult and time consuming. A computer-controlled signal preprocessor has been developed which makes possible this optimization of the photomultiplier signal as a normal part of the data acquisition process. It allows computer control of the filter selection, signal gain, and photo-multiplier voltage. The raw signal from the photomultiplier tube is input to the preprocessor which, under the control of a digital computer, filters the signal and amplifies it to an acceptable level. The counter-processor used at Lewis Research Center generates the particle interarrival times, as well as the time-of-flight of the particle through the probe volume. The signal preprocessor allows computer control of the acquisition of these data.Through the preprocessor, the computer also can control the hand shaking signals for the interface between itself and the counter-processor. Finally, the signal preprocessor splits the pedestal from the signal before filtering, and monitors the photo-multiplier dc current, sends a signal proportional to this current to the computer through an analog to digital converter, and provides an alarm if the current exceeds a predefined maximum. Complete drawings and explanations are provided in the text as well as a sample interface program for use with the data acquisition software.

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.

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

PubMed Central

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

2017-01-01

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

Properties of new diffusion filters for treatment of amblyopia with accurate occlusive effects.

PubMed

Sasaki, Makoto; Iwasaki, Tsuneto; Kondo, Hiroyuki; Tawara, Akihiko

2016-06-01

Our purpose is to present the characteristics of newly developed diffusion filters that can reduce the best-corrected visual acuity (BCVA) of the non-amblyopic eye to a specified value and that can be used to treat amblyopia. Silica sol is a colorless and transparent colloidal gel of different particle sizes. The silica was added to an emulsion adhesive, thoroughly mixed, and coated evenly on polyethylene terephthalate films. Twelve filters with 12 different concentrations of silica were constructed. The density of the silica particles on the films was determined by scanning electron microscopy, and the haze values and light transmittance were measured with a goniophotometer. The reduction of the BCVA by the filters was determined in 16 healthy young women (mean age, 22.0 ± 2.3 years) by attaching the filters to spectacles. Scanning electron microscopy showed a monolayer of evenly spaced silica particles. The haze values of the 12 filters were related to the concentration of silica. The total light transmittance of the 12 filters was not significantly correlated to the concentration of silica. The BCVAs measured with the 12 filters were significantly and inversely correlated with the concentration of silica for both eyes (right eye, y = 0.174x - 0.197, R(2) = 0.951; left eye, y = 0.173x - 0.212, R(2) = 0.983). These findings indicate that these diffusion filters can reduce the BCVA with no reduction of light transmittance. We conclude that they can be used to degrade the image of the dominant eye by known amounts in patients with amblyopia without affecting the overall light levels to the eye, i.e., form deprivation without light deprivation.

A filterable lytic agent obtained from a red tide bloom that caused lysis of Karenia brevis (Gymnodinum breve) cultures

USGS Publications Warehouse

2002-01-01

A filterable lytic agent (FLA) was obtained from seawater in the southeastern Gulf of Mexico during a red tide bloom that caused lysis of Karenia brevis (formerly Gymnodinium breve) Piney Island. This agent was obtained from <0.2µ  filtrates that were concentrated by ultrafiltration using a 100 kDa filter. The FLA was propagated by passage on K. brevis cultures, and the filtered supernatants of such cultures resulted in K. brevis lysis when added to such cultures. The lytic activity was lost upon heating to 65°C or by 0.02 µm filtration. Epifluorescence and transmission electron microscopy (TEM) of supernatants of K. brevis cultures treated with the lytic agent indicated a high abundance of viral particles (4 × 109 to 7 × 109 virus-like particles [VLPs] ml–1) compared to control cultures (~107 ml–1). However, viral particles were seldom found in TEM photomicrograph thin sections of lysing K. brevis cells. Although a virus specific for K. brevis may have been the FLA, other explanations such as filterable bacteria or bacteriophages specific for bacteria associated with the K. brevis cultures cannot be discounted.

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

Evaluation of a Shaker Dust Collector for Use in a Recirculating Ventilation System

PubMed Central

Sawvel, Russell A.; Park, Jae Hong; Anthony, T. Renée

2016-01-01

General ventilation with recirculated air may be cost-effective to control the concentration of low-toxicity, contaminants in workplaces with diffuse, dusty operations, such as in agriculture. Such systems are, however, rarely adopted with little evidence showing improved air quality and ability to operate under harsh conditions. The goal of this work was to examine the initial and long-term performance of a fabric-filter shaker dust collector (SDC) in laboratory tests and as deployed within a recirculating ventilation system in an agricultural building. In laboratory tests, collection efficiency and pressure drop were tracked over several filter loading cycles, and the recovery of filter capacity (pressure drop) from filter shaking was examined. Collection efficiencies of particles larger than 5 μm was high (>95%) even when the filter was pristine, showing effective collection of large particles that dominate inhalable concentrations typical of agricultural dusts. For respirable-sized particles, collection efficiencies were low when the filter was pristine (e.g., 27% for 1 μm) but much higher when a dust cake developed on the filter (>99% for all size particles), even after shaking (e.g., 90% for 1 μm). The first shake of a filter was observed to recovery a substantial fraction of filter capacity, with subsequent shakes providing little benefit. In field tests, the SDC performed effectively over a period of three months in winter when incorporated in a recirculating ventilation system of a swine farrowing room. Trends in collection efficiency and pressure drop with loading were similar to those observed in the laboratory with overall collection efficiencies high (>80%) when pressure drop exceeded 230 Pa, or 23% of the maximum loading recommended by the manufacturer. This work shows that the SDC can function effectively over the harsh winter in swine rearing operations. Together with findings of improved air quality in the farrowing room reported in a companion manuscript, this article provides evidence that an SDC represents a cost-effective solution to improve air quality in agricultural settings. PMID:25955507

Event-triggered resilient filtering with stochastic uncertainties and successive packet dropouts via variance-constrained approach

NASA Astrophysics Data System (ADS)

Jia, Chaoqing; Hu, Jun; Chen, Dongyan; Liu, Yurong; Alsaadi, Fuad E.

2018-07-01

In this paper, we discuss the event-triggered resilient filtering problem for a class of time-varying systems subject to stochastic uncertainties and successive packet dropouts. The event-triggered mechanism is employed with hope to reduce the communication burden and save network resources. The stochastic uncertainties are considered to describe the modelling errors and the phenomenon of successive packet dropouts is characterized by a random variable obeying the Bernoulli distribution. The aim of the paper is to provide a resilient event-based filtering approach for addressed time-varying systems such that, for all stochastic uncertainties, successive packet dropouts and filter gain perturbation, an optimized upper bound of the filtering error covariance is obtained by designing the filter gain. Finally, simulations are provided to demonstrate the effectiveness of the proposed robust optimal filtering strategy.

Optimal Sharpening of Compensated Comb Decimation Filters: Analysis and Design

PubMed Central

Troncoso Romero, David Ernesto

2014-01-01

Comb filters are a class of low-complexity filters especially useful for multistage decimation processes. However, the magnitude response of comb filters presents a droop in the passband region and low stopband attenuation, which is undesirable in many applications. In this work, it is shown that, for stringent magnitude specifications, sharpening compensated comb filters requires a lower-degree sharpening polynomial compared to sharpening comb filters without compensation, resulting in a solution with lower computational complexity. Using a simple three-addition compensator and an optimization-based derivation of sharpening polynomials, we introduce an effective low-complexity filtering scheme. Design examples are presented in order to show the performance improvement in terms of passband distortion and selectivity compared to other methods based on the traditional Kaiser-Hamming sharpening and the Chebyshev sharpening techniques recently introduced in the literature. PMID:24578674

Optimal sharpening of compensated comb decimation filters: analysis and design.

PubMed

Troncoso Romero, David Ernesto; Laddomada, Massimiliano; Jovanovic Dolecek, Gordana

2014-01-01

Comb filters are a class of low-complexity filters especially useful for multistage decimation processes. However, the magnitude response of comb filters presents a droop in the passband region and low stopband attenuation, which is undesirable in many applications. In this work, it is shown that, for stringent magnitude specifications, sharpening compensated comb filters requires a lower-degree sharpening polynomial compared to sharpening comb filters without compensation, resulting in a solution with lower computational complexity. Using a simple three-addition compensator and an optimization-based derivation of sharpening polynomials, we introduce an effective low-complexity filtering scheme. Design examples are presented in order to show the performance improvement in terms of passband distortion and selectivity compared to other methods based on the traditional Kaiser-Hamming sharpening and the Chebyshev sharpening techniques recently introduced in the literature.

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

PubMed

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

2018-05-15

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

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

PubMed

Liu, Xin; Niranjan, Mahesan

2012-06-01

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

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

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

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

1997-11-15

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

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.

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

DOEpatents

Rodgers, Billy R.; Edwards, Michael S.

1977-01-01

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

Sea Mines and Countermeasures: A Bibliography. Revision

DTIC Science & Technology

2007-07-01

days. " Vector polarization filtering" was employed to separate the reflected signal due to Rayleigh waves, for which the particle motion is...buried mines. Rayleigh waves are unique in that they have elliptical particle motion that allows one to use vector polarization filtering to separate...D. Vector Acoustic Mine Mechanism. Patent. Washington, DC: Department of the Navy, February 1980. 11p. ABSTRACT: This patent discloses a submarine

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

NASA Astrophysics Data System (ADS)

Uetsuhara, M.; Ikoma, N.

2014-09-01

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

Optimal filter parameters for low SNR seismograms as a function of station and event location

NASA Astrophysics Data System (ADS)

Leach, Richard R.; Dowla, Farid U.; Schultz, Craig A.

1999-06-01

Global seismic monitoring requires deployment of seismic sensors worldwide, in many areas that have not been studied or have few useable recordings. Using events with lower signal-to-noise ratios (SNR) would increase the amount of data from these regions. Lower SNR events can add significant numbers to data sets, but recordings of these events must be carefully filtered. For a given region, conventional methods of filter selection can be quite subjective and may require intensive analysis of many events. To reduce this laborious process, we have developed an automated method to provide optimal filters for low SNR regional or teleseismic events. As seismic signals are often localized in frequency and time with distinct time-frequency characteristics, our method is based on the decomposition of a time series into a set of subsignals, each representing a band with f/Δ f constant (constant Q). The SNR is calculated on the pre-event noise and signal window. The band pass signals with high SNR are used to indicate the cutoff filter limits for the optimized filter. Results indicate a significant improvement in SNR, particularly for low SNR events. The method provides an optimum filter which can be immediately applied to unknown regions. The filtered signals are used to map the seismic frequency response of a region and may provide improvements in travel-time picking, azimuth estimation, regional characterization, and event detection. For example, when an event is detected and a preliminary location is determined, the computer could automatically select optimal filter bands for data from non-reporting stations. Results are shown for a set of low SNR events as well as 379 regional and teleseismic events recorded at stations ABKT, KIV, and ANTO in the Middle East.

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

Workplace Exposure to Titanium Dioxide Nanopowder Released from a Bag Filter System

PubMed Central

Ji, Jun Ho; Kim, Jong Bum; Lee, Gwangjae; Noh, Jung-Hun; Yook, Se-Jin; Cho, So-Hye; Bae, Gwi-Nam

2015-01-01

Many researchers who use laboratory-scale synthesis systems to manufacture nanomaterials could be easily exposed to airborne nanomaterials during the research and development stage. This study used various real-time aerosol detectors to investigate the presence of nanoaerosols in a laboratory used to manufacture titanium dioxide (TiO2). The TiO2 nanopowders were produced via flame synthesis and collected by a bag filter system for subsequent harvesting. Highly concentrated nanopowders were released from the outlet of the bag filter system into the laboratory. The fractional particle collection efficiency of the bag filter system was only 20% at particle diameter of 100 nm, which is much lower than the performance of a high-efficiency particulate air (HEPA) filter. Furthermore, the laboratory hood system was inadequate to fully exhaust the air discharged from the bag filter system. Unbalanced air flow rates between bag filter and laboratory hood systems could result in high exposure to nanopowder in laboratory settings. Finally, we simulated behavior of nanopowders released in the laboratory using computational fluid dynamics (CFD). PMID:26125024

Optimal Recursive Digital Filters for Active Bending Stabilization

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2013-01-01

In the design of flight control systems for large flexible boosters, it is common practice to utilize active feedback control of the first lateral structural bending mode so as to suppress transients and reduce gust loading. Typically, active stabilization or phase stabilization is achieved by carefully shaping the loop transfer function in the frequency domain via the use of compensating filters combined with the frequency response characteristics of the nozzle/actuator system. In this paper we present a new approach for parameterizing and determining optimal low-order recursive linear digital filters so as to satisfy phase shaping constraints for bending and sloshing dynamics while simultaneously maximizing attenuation in other frequency bands of interest, e.g. near higher frequency parasitic structural modes. By parameterizing the filter directly in the z-plane with certain restrictions, the search space of candidate filter designs that satisfy the constraints is restricted to stable, minimum phase recursive low-pass filters with well-conditioned coefficients. Combined with optimal output feedback blending from multiple rate gyros, the present approach enables rapid and robust parametrization of autopilot bending filters to attain flight control performance objectives. Numerical results are presented that illustrate the application of the present technique to the development of rate gyro filters for an exploration-class multi-engined space launch vehicle.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Screening system and method of using same

DOEpatents

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

2014-04-15

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

Development of nitrocellulose membrane filters impregnated with different biosynthesized silver nanoparticles applied to water purification.

PubMed

Fernández, Jorge G; Almeida, César A; Fernández-Baldo, Martín A; Felici, Emiliano; Raba, Julio; Sanz, María I

2016-01-01

Bactericidal water filters were developed. For this purpose, nitrocellulose membrane filters were impregnated with different biosynthesized silver nanoparticles. Silver nanoparticles (AgNPs) from Aspergillus niger (AgNPs-Asp), Cryptococcus laurentii (AgNPs-Cry) and Rhodotorula glutinis (AgNPs-Rho) were used for impregnating nitrocellulose filters. The bactericidal properties of these nanoparticles against Escherichia coli, Enterococcus faecalis and Pseudomona aeruginosa were successfully demonstrated. The higher antimicrobial effect was observed for AgNPs-Rho. This fact would be related not only to the smallest particles, but also to polysaccharides groups that surrounding these particles. Moreover, in this study, complete inhibition of bacterial growth was observed on nitrocellulose membrane filters impregnated with 1 mg L(-1) of biosynthesized AgNPs. This concentration was able to reduce the bacteria colony count by over 5 orders of magnitude, doing suitable for a water purification device. Copyright © 2015 Elsevier B.V. All rights reserved.

Adapted all-numerical correlator for face recognition applications

NASA Astrophysics Data System (ADS)

Elbouz, M.; Bouzidi, F.; Alfalou, A.; Brosseau, C.; Leonard, I.; Benkelfat, B.-E.

2013-03-01

In this study, we suggest and validate an all-numerical implementation of a VanderLugt correlator which is optimized for face recognition applications. The main goal of this implementation is to take advantage of the benefits (detection, localization, and identification of a target object within a scene) of correlation methods and exploit the reconfigurability of numerical approaches. This technique requires a numerical implementation of the optical Fourier transform. We pay special attention to adapt the correlation filter to this numerical implementation. One main goal of this work is to reduce the size of the filter in order to decrease the memory space required for real time applications. To fulfil this requirement, we code the reference images with 8 bits and study the effect of this coding on the performances of several composite filters (phase-only filter, binary phase-only filter). The saturation effect has for effect to decrease the performances of the correlator for making a decision when filters contain up to nine references. Further, an optimization is proposed based for an optimized segmented composite filter. Based on this approach, we present tests with different faces demonstrating that the above mentioned saturation effect is significantly reduced while minimizing the size of the learning data base.

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

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.