scholarly journals Comparative Performance Evaluation of Commercial Packing Materials for Malodorants Abatement in Biofiltration

2021 ◽  
Vol 11 (7) ◽  
pp. 2966
Author(s):  
Raquel Lebrero ◽  
Elisa Rodríguez ◽  
María Collantes ◽  
Carlos De Juan ◽  
Geir Norden ◽  
...  
Keyword(s):  
Buffer Capacity ◽  
Superior Performance ◽  
Adsorption Potential ◽  
Proper Selection ◽  
Two Phase ◽  
Comparative Performance ◽  
Packing Materials ◽  
Abiotic Conditions ◽  
Biotrickling Filters ◽  
Materials Used

Packing materials used in biofiltration of gaseous pollutants represent a key design parameter, as a proper selection might not only determine the adequate performance of the system but also its cost-effectiveness. This study systematically assessed and compared the performance of a conventional plastic carrier with that of two novel clay-based materials from SAINT GOBAIN for the abatement of a model odorous stream composed of H2S, methylmercaptan and toluene. The packing materials were tested in biotrickling filters, biofilters and a two-phase biotrickling filter. SAINT GOBAIN materials exhibited a higher adsorption potential under abiotic conditions, a higher buffer capacity and a superior performance compared to conventional plastic rings when implemented in biotrickling filters operating at gas residence times as low as 7.5 s. Among the materials tested in biofilters, Filtralite Air AC supported almost complete H2S and toluene removals at a gas residence time of 20 s, while successfully eliminating methylmercaptan at values of ~80%. Interestingly, under most of the conditions tested, clay-based materials also showed comparable pressure drop values than those of plastic rings.

Aggregate Characteristics Governing Performance of Seal Coat Highway Overlays

1996 ◽  
Vol 1547 (1) ◽  
pp. 15-22 ◽  
Author(s):  
Mohamed-Asem U. Abdul-Malak ◽  
David W. Fowler ◽  
Cesar A. Constantino
Keyword(s):  
Statistical Models ◽  
Environmental Variables ◽  
Construction Projects ◽  
Performance Data ◽  
Engineering Properties ◽  
Proper Selection ◽  
Performance Variability ◽  
Frictional Performance ◽  
Materials Used ◽  
Selection Of

A study was undertaken to identify the engineering properties of aggregates that explain the variability in the frictional performance of seal coat highway overlays. The frictional performance data of 72 test sections and section replicates collected over a period of 8 years were used in the formulation of statistical models that incorporate the significant variables. The effects of traffic, construction, and environmental variables were also considered. Formulated models were of two types: general and individual. The former type attempts to describe frictional performance using the observations collected on all aggregate materials used. The latter describes the performance of individual aggregate groups. Laboratory properties found to be significant included the polish value, impact and abrasion, and soundness properties. The coating of aggregate particles, gradation, and construction placing rates of aggregate and asphalt were also shown to be significant in explaining performance variability. The influence of traffic and region was found to be interactive with the type and properties of aggregates. The formulated models can be used as a tool for predicting the frictional performance of seal coat aggregates, thus providing a better means for the proper selection of aggregates and for the planning of future seal coat construction projects.

scholarly journals Biological elimination of a high concentration of hydrogen sulfide from landfill biogas

2021 ◽  
Author(s):  
Rania Ibrahim ◽  
Abdessamad El Hassni ◽  
Shahram Navaee-Ardeh ◽  
Hubert Cabana
Keyword(s):  
Hydrogen Sulfide ◽  
Pilot Scale ◽  
Biotrickling Filter ◽  
High Concentration ◽  
Two Phase ◽  
Filter System ◽  
Biotrickling Filters ◽  
In Series ◽  
Maximum Elimination Capacity ◽  
Landfill Biogas

Abstract Hydrogen sulfide (H2S) is one of the main contaminants found in biogas which is one of the end products of the anaerobic biodegradation of proteins and other sulfur-containing compounds in solid waste. The presence of H2S is one of the factors limiting the valorization of biogas. To valorize biogas, H2S and other contaminants must be removed. This study evaluated the performance of a pilot-scale biotrickling filter system on H2S removal from landfill biogas. The biotrickling filter system, which was packed with stainless-steel pall rings and inoculated with an H2S-oxidizing consortium, was designed to process 1 to 10 SCFM of biogas and used to determine the removal efficiency of a high concentration of hydrogen sulfide from landfill biogas. The biofiltration system consisted of two biotrickling filters connected in series. Results indicate that the biofiltration system reduced H2S concentration by 94–97% without reduction of the methane concentration in the outlet biogas. The inlet concentration of hydrogen sulfide, supplied to the two-phase bioreactor, was in the range of 900 to 1500 ppmv. The hydraulic retention times (HRT) of the two biotrickling filters were 3.9 and 0.9 min, respectively. Approximately 50 ppmv of H2S gas was detected in the outlet gas. The maximum elimination capacity of the biotrickling filter system was found to be 272 g H2S.m− 3.h− 1. During the biological process, the performance of biotrickling filter was not affected when the pH of the recirculated liquid decreased to 2–3. The overall performance of the biotrickling filter system was described using a modified Michaelis–Menten equation, and the Ks and Vm values for the biosystem were 34.7 ppmv and 200 mg H2S/L.h− 1, respectively.

Empirical Correlations for Prediction Slug Liquid Holdup on Slug-Pseudo-Slug and Slug-Churn Transitions in Vertical and Inclined Two-Phase Flow

2021 ◽  
pp. 1-13
Author(s):  
Ghassan H. Abdul-Majeed ◽  
Abderraouf Arabi ◽  
Gabriel Soto-Cortes
Keyword(s):  
Two Phase Flow ◽  
Liquid Velocity ◽  
Superior Performance ◽  
Phase Flow ◽  
Liquid Viscosity ◽  
Empirical Correlations ◽  
Liquid Holdup ◽  
Two Phase ◽  
Experimental Database ◽  
Transition Models

Summary Most of the existing slug (SL) to churn (CH) or SL to pseudo-slug (PS) transition models (empirical and mechanistic) account for the effect of the SL liquid holdup (HLS). For simplicity, some of these models assume a constant value of HLS in SL/CH and SL/PS flow transitions, leading to a straightforward solution. Other models correlate HLS with different flow variables, resulting in an iterative solution for predicting these transitions. Using an experimental database collected from the open literature, two empirical correlations for prediction HLS at the SL/PS and SL/CH transitions (HLST) are proposed in this study. This database is composed of 1,029 data points collected in vertical, inclined, and horizontal configurations. The first correlation is developed for medium to high liquid viscosity two-phase flow (μL > 0.01 Pa·s), whereas the second one is developed for low liquid viscosity flow (μL ≤ 0.01 Pa·s). Both correlations are shown to be a function of superficial liquid velocity (VSL), liquid viscosity (μL), and pipe inclination angle (θ). The proposed correlations in a combination with the HLS model of Abdul-Majeed and Al-Mashat (2019) have been used to predict SL/PS and SL/CH transitions, and very satisfactory results were obtained. Furthermore, the SL/CH model of Brauner and Barnea (1986) is modified by using the proposed HLST correlations, instead of using a constant value. The modification results in a significant improvement in the prediction of SL/CH and SL/PS transitions and fixes the incorrect decrease of superficial gas velocity (VSG) with increasing VSL. The modified model follows the expected increase of VSG for high VSL, shown by the published observations. The proposed combinations are compared with the existing transition models and show superior performance among all models when tested against 357 measured data from independent studies.

THE COMPARATIVE PERFORMANCE EVALUATION OF WINDOW FUNCTIONS UNDER NOISY ENVIRONMENT FOR SPEECH RECOGNITION

2016 ◽  
Vol 78 (5-7) ◽  
Author(s):  
Syifaun Nafisah ◽  
Oyas Wahyunggoro ◽  
Lukito Edi Nugroho
Keyword(s):  
Feature Extraction ◽  
Speech Recognition ◽  
Back Propagation ◽  
Extraction Process ◽  
Superior Performance ◽  
Automated Identification ◽  
Comparative Performance ◽  
Rectangular Window ◽  
Window Functions ◽  
Optimal Accuracy

The accuracy and user acceptance of speech recognition systems is increasing in the last few years especially for automated identification and biomedical applications.  In implementation, it works based on the feature of utterance that will be recognized through a feature extraction process.  One process in feature extraction is windowing that is done for minimizing the disruptions at the first and last of the frame.  Basically, many window functions exist such as rectangular window, flat top window, hamming window, etc, but in the real application only hamming or Hanning function that are usually used as  a function in the windowing.  This article will analyzed the performance of all of window functions to prove the performance of those function.  The method that was used are mel-frequencies cepstral coefficients (MFCCs) as feature extractor technique and back propagation neural networks (BPNNs) as classifier.  The result shows that it can produce an accuracy at least 99%.  The optimal accuracy up to 99.86% is achieved using rectangle window with the duration of process is 15.47 msec.  This results show the superior performance of rectangle window as reference to recognize an isolated word based on speech.

An Analytical Model for Bubble Growth and Heat Transfer in Microchannels

2007 ◽  
Author(s):  
Martin Cerza ◽  
Sonia M. F. Garcia ◽  
Joshua L. Nickerson
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Bubble Growth ◽  
Leading Edge ◽  
Superior Performance ◽  
Transfer Model ◽  
Two Phase ◽  
Microchannel Cooling ◽  
Convection Schemes

Forced liquid convection microchannel cooling systems present an alternative to the forced air-convection schemes and offer higher thermal performance. With regard to forced liquid convection, two-phase convection offers superior performance to liquid only convection. This paper presents results developed from a bubble heat transfer growth model applied to microchannel geometry and incorporates these results into a model for the averaged bubble heat transfer coefficient. Results are shown for water and FC-72. The bubble heat transfer model shows that the bubble growth rates and subsequent averaged heat transfer coefficient are functions of the film thickness between the bubble and the microchannel wall, the slip velocity between the bubble and the fluid comprising the bubble base, the wall heat flux and the subsequent liquid superheat in the microchannel just upstream of the bubble leading edge.

Biological treatment of airstreams contaminated with VOCs: an overview

1996 ◽  
Vol 34 (3-4) ◽  
pp. 565-571 ◽  
Author(s):  
Findlay G. Edwards ◽  
N. Nirmalakhandan
Keyword(s):  
The Netherlands ◽  
Biological Treatment ◽  
Buffer Capacity ◽  
Pilot Studies ◽  
Volatile Chemicals ◽  
Biotrickling Filters ◽  
Different Types

Biological treatment of contaminated airstreams is a technology which has been used successfully in Germany and The Netherlands for twenty years. The technology can be utilized in a wide array of industries to treat numerous volatile chemicals. There are three categories of air phase bioreactors: biofilters, biotrickling filters, and bioscrubbers. Addition of nutrients and buffer capacity may be required. Many different types of support media can be used. Currently, design of airphase bioreactors is based upon guidelines, pilot studies, and experience gained from similar applications.

scholarly journals Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques

2021 ◽  
Vol 3 (2) ◽  
pp. 294-312
Author(s):  
Muhammad E. H. Chowdhury ◽  
Tawsifur Rahman ◽  
Amith Khandakar ◽  
Mohamed Arselene Ayari ◽  
Aftab Ullah Khan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Binary Classification ◽  
Experimental Studies ◽  
Plant Diseases ◽  
Superior Performance ◽  
World Population ◽  
Comparative Performance ◽  
Learning Techniques ◽  
Segmented Images ◽  
Segmentation Models

Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. Early detection of plant diseases using computer vision and artificial intelligence (AI) can help to reduce the adverse effects of diseases and also overcome the shortcomings of continuous human monitoring. In this work, we propose the use of a deep learning architecture based on a recent convolutional neural network called EfficientNet on 18,161 plain and segmented tomato leaf images to classify tomato diseases. The performance of two segmentation models i.e., U-net and Modified U-net, for the segmentation of leaves is reported. The comparative performance of the models for binary classification (healthy and unhealthy leaves), six-class classification (healthy and various groups of diseased leaves), and ten-class classification (healthy and various types of unhealthy leaves) are also reported. The modified U-net segmentation model showed accuracy, IoU, and Dice score of 98.66%, 98.5%, and 98.73%, respectively, for the segmentation of leaf images. EfficientNet-B7 showed superior performance for the binary classification and six-class classification using segmented images with an accuracy of 99.95% and 99.12%, respectively. Finally, EfficientNet-B4 achieved an accuracy of 99.89% for ten-class classification using segmented images. It can be concluded that all the architectures performed better in classifying the diseases when trained with deeper networks on segmented images. The performance of each of the experimental studies reported in this work outperforms the existing literature.

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