An Experimental Investigation of the Impact of Gas Phase Prepolymerization of Propylene

2020 ◽  
Vol 14 (3) ◽  
pp. 1900052
Author(s):  
Yue Yu ◽  
Timothy F. L. McKenna
Keyword(s):  
Experimental Investigation ◽  
Gas Phase ◽  
The Impact

Experimental Investigation of the Impact of Dual Time Periods on Crash Hazardous Location Identification

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Gilbert Leano ◽  
Wen Cheng ◽  
Xudong Jia ◽  
Lingqi Kong ◽  
Robert Brennan
Keyword(s):  
Experimental Investigation ◽  
Time Periods ◽  
Location Identification ◽  
The Impact

The Impact of the Aqueous Phase Chemistry of HNO4 on Gas Phase Tropospheric Chemistry

2001 ◽  
Vol 32 ◽  
pp. 269-270
Author(s):  
J.E. WILLIAMS ◽  
F.J. DENTENER ◽  
A.R. van den BERG
Keyword(s):  
Gas Phase ◽  
Aqueous Phase ◽  
Tropospheric Chemistry ◽  
Phase Chemistry ◽  
The Impact

scholarly journals Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10

2019 ◽  
Vol 12 (3) ◽  
pp. 1209-1225 ◽  
Author(s):  
Christoph A. Keller ◽  
Mat J. Evans
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Random Forest Regression ◽  
Data Set ◽  
Gas Phase Chemistry ◽  
Chemical Conditions ◽  
Phase Chemistry ◽  
The Impact

Abstract. Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models are numerically intense, and previous attempts to reduce the numerical cost of chemistry solvers have not delivered transformative change. We show here the potential of a machine learning (in this case random forest regression) replacement for the gas-phase chemistry in atmospheric chemistry transport models. Our training data consist of 1 month (July 2013) of output of chemical conditions together with the model physical state, produced from the GEOS-Chem chemistry model v10. From this data set we train random forest regression models to predict the concentration of each transported species after the integrator, based on the physical and chemical conditions before the integrator. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for long-lived species and the absolute concentration for short-lived species. We also find improvements from a simple implementation of chemical families (NOx = NO + NO2). We then implement the trained random forest predictors back into GEOS-Chem to replace the numerical integrator. The machine-learning-driven GEOS-Chem model compares well to the standard simulation. For ozone (O3), errors from using the random forests (compared to the reference simulation) grow slowly and after 5 days the normalized mean bias (NMB), root mean square error (RMSE) and R2 are 4.2 %, 35 % and 0.9, respectively; after 30 days the errors increase to 13 %, 67 % and 0.75, respectively. The biases become largest in remote areas such as the tropical Pacific where errors in the chemistry can accumulate with little balancing influence from emissions or deposition. Over polluted regions the model error is less than 10 % and has significant fidelity in following the time series of the full model. Modelled NOx shows similar features, with the most significant errors occurring in remote locations far from recent emissions. For other species such as inorganic bromine species and short-lived nitrogen species, errors become large, with NMB, RMSE and R2 reaching >2100 % >400 % and <0.1, respectively. This proof-of-concept implementation takes 1.8 times more time than the direct integration of the differential equations, but optimization and software engineering should allow substantial increases in speed. We discuss potential improvements in the implementation, some of its advantages from both a software and hardware perspective, its limitations, and its applicability to operational air quality activities.

Maximizing Recall of Gruesome Images for Health Effects Advertising: An Experimental Investigation

2010 ◽  
Vol 16 (4) ◽  
pp. 112-121 ◽  
Author(s):  
Brennen W. Mills ◽  
Owen B. J. Carter ◽  
Robert J. Donovan
Keyword(s):  
Experimental Investigation ◽  
Body Part ◽  
The Body ◽  
Advertising Effectiveness ◽  
Body Parts ◽  
Online Study ◽  
Video Clips ◽  
Video Images ◽  
The Impact

The objective of this case study was to experimentally manipulate the impact on arousal and recall of two characteristics frequently occurring in gruesome depictions of body parts in smoking cessation advertisements: the presence or absence of an external physical insult to the body part depicted; whether or not the image contains a clear figure/ground demarcation. Three hundred participants (46% male, 54% female; mean age 27.3 years, SD = 11.4) participated in a two-stage online study wherein they viewed and responded to a series of gruesome 4-s video images. Seventy-two video clips were created to provide a sample of images across the two conditions: physical insult versus no insult and clear figure/ground demarcation versus merged or no clear figure/ground demarcation. In stage one, participants viewed a randomly ordered series of 36 video clips and rated how “confronting” they considered each to be. Seven days later (stage two), to test recall of each video image, participants viewed all 72 clips and were asked to identify those they had seen previously. Images containing a physical insult were consistently rated more confronting and were remembered more accurately than images with no physical insult. Images with a clear figure/ground demarcation were rated as no more confronting but were consistently recalled with greater accuracy than those with unclear figure/ground demarcation. Makers of gruesome health warning television advertisements should incorporate some form of physical insult and use a clear figure/ground demarcation to maximize image recall and subsequent potential advertising effectiveness.

scholarly journals Gaseous chemistry and aerosol mechanism developments for version 3.5.1 of the online regional model, WRF-Chem

2014 ◽  
Vol 7 (6) ◽  
pp. 2557-2579 ◽  
Author(s):  
S. Archer-Nicholls ◽  
D. Lowe ◽  
S. Utembe ◽  
J. Allan ◽  
R. A. Zaveri ◽  
...  
Keyword(s):  
Gas Phase ◽  
Chemical Mechanism ◽  
Reduced Form ◽  
Sea Spray ◽  
Wind Fields ◽  
Aerosol Composition ◽  
Aerosol Emission ◽  
Sea Spray Aerosol ◽  
The Impact ◽  
Phase Chemical

Abstract. We have made a number of developments to the Weather, Research and Forecasting model coupled with Chemistry (WRF-Chem), with the aim of improving model prediction of trace atmospheric gas-phase chemical and aerosol composition, and of interactions between air quality and weather. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been added, using the Kinetic Pre-Processor (KPP) interface, to enable more explicit simulation of VOC degradation. N2O5 heterogeneous chemistry has been added to the existing sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas-phase schemes. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. We have worked on the European domain, with a particular focus on making the model suitable for the study of nighttime chemistry and oxidation by the nitrate radical in the UK atmosphere. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments are illustrated, using a modified version of WRF-Chem 3.4.1, in order to demonstrate the impact that these changes have in the Northwest European domain. These developments are publicly available in WRF-Chem from version 3.5.1 onwards.

Experimental investigation of isothermal and reacting flow characteristics downstream of axisymmetric bluff body stabilizers under stratified or fully premixed inlet mixture conditions

2020 ◽  
Author(s):  
Γεώργιος Πατεράκης
Keyword(s):  
Experimental Investigation ◽  
Turbulent Flow ◽  
Bluff Body ◽  
Operating Conditions ◽  
Reacting Flow ◽  
Wide Range ◽  
Flow Features ◽  
Air Mixing ◽  
The Impact ◽  
Stratified Flames

The current work describes an experimental investigation of isothermal and turbulent reacting flow field characteristics downstream of axisymmetric bluff body stabilizers under a variety of inlet mixture conditions. Fully premixed and stratified flames established downstream of this double cavity premixer/burner configuration were measured and assessed under lean and ultra-lean operating conditions. The aim of this thesis was to further comprehend the impact of stratifying the inlet fuelair mixture on the reacting wake characteristics for a range of practical stabilizers under a variety of inlet fuel-air settings. In the first part of this thesis, the isothermal mean and turbulent flow features downstream of a variety of axisymmetric baffles was initially examined. The effect of different shapes, (cone or disk), blockage ratios, (0.23 and 0.48), and rim thicknesses of these baffles was assessed. The variations of the recirculation zones, back flow velocity magnitude, annular jet ejection angles, wake development, entrainment efficiency, as well as several turbulent flow features were obtained, evaluated and appraised. Next, a comparative examination of the counterpart turbulent cold fuel-air mixing performance and characteristics of stratified against fully-premixed operation was performed for a wide range of baffle geometries and inlet mixture conditions. Scalar mixing and entrainment properties were investigated at the exit plane, at the bluff body annular shear layer, at the reattachment region and along the developing wake were investigated. These isothermal studies provided the necessary background information for clarifying the combustion properties and interpreting the trends in the counterpart turbulent reacting fields. Subsequently, for selected bluff bodies, flame structures and behavior for operation with a variety of reacting conditions were demonstrated. The effect of inlet fuel-air mixture settings, fuel type and bluff body geometry on wake development, flame shape, anchoring and structure, temperatures and combustion efficiencies, over lean and close to blow-off conditions, was presented and analyzed. For the obtained measurements infrared radiation, particle image velocimetry, laser doppler velocimetry, chemiluminescence imaging set-ups, together with Fouriertransform infrared spectroscopy, thermocouples and global emission analyzer instrumentation was employed. This helped to delineate a number of factors that affectcold flow fuel-air mixing, flame anchoring topologies, wake structure development and overall burner performance. The presented data will also significantly assist the validation of computational methodologies for combusting flows and the development of turbulence-chemistry interaction models.

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