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| 2. |
- Ivanov, Mikhail F., et al.
(author)
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Ignition of deflagration and detonation ahead of the flame due to radiative preheating of suspended micro particles
- 2015
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In: Combustion and Flame. - : Elsevier BV. - 0010-2180 .- 1556-2921. ; 162:10, s. 3612-3621
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Journal article (peer-reviewed)abstract
- We study a flame propagating in the gaseous combustible mixture with suspended inert solid micro particles. The gaseous mixture is assumed to be transparent for thermal radiation emitted by the hot combustion products, while particles absorb and reemit the radiation. Thermal radiation heats the particles, which in turn transfer the heat to the surrounding unburned gaseous mixture by means of thermal heat transfer, so that the gas phase temperature lags that of the particles. We consider different scenarios depending on the spatial distribution of the particles, their size and the number density. In the case of uniform spatial distribution of the particles the radiation causes a modest increase of the temperature ahead of the flame and corresponding modest increase of the combustion velocity. In the case of non-uniform distribution of the particles (layered dust cloud), such that the particles number density is relatively small in the region just ahead of the flame front and increases in the distant regions ahead of the flame, the preheating caused by the thermal radiation may trigger additional independent source of ignition. Far ahead of the flame, where number density of particles increases forming a dense cloud of particles, the radiative preheating results in the formation of a temperature gradient with the maximum temperature sufficient for ignition. Depending on the steepness of the temperature gradient formed in the unburned mixture, either deflagration or detonation can be initiated via the Zel'dovich's gradient mechanism. The ignition and the resulting combustion regimes depend on the number density profile and, correspondingly, on the temperature profile (temperature gradient), which is formed in effect of radiation absorption and gas-dynamic expansion. The effect of radiation preheating as stronger as smaller is the normal flame velocity. The effect of radiation heat transfer in the case of coal dust flames propagating in layered particle-gas deposits cloud can result in the spread of combustion wave with velocity up to 1000 m/s and it is a plausible explanation of the origin of dust explosion in coal mines.
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| 3. |
- Winikka, Henrik, et al.
(author)
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Particle formation during pressurized entrained flow gasification of wood powder : Effects of process conditions on chemical composition, nanostructure, and reactivity
- 2018
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In: Combustion and Flame. - : Elsevier BV. - 0010-2180 .- 1556-2921. ; 189, s. 1339-1351
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Journal article (peer-reviewed)abstract
- The influence of operating condition on particle formation during pressurized, oxygen blown gasification of wood powder with an ash content of 0.4 wt% was investigated. The investigation was performed with a pilot scale gasifier operated at 7 bar(a). Two loads, 400 and 600 kW were tested, with the oxygen equivalence ratio (λ) varied between 0.25 and 0.50. Particle concentration and mass size distribution was analyzed with a low pressure cascade impactor and the collected particles were characterized for morphology, elemental composition, nanostructure, and reactivity using scanning electron microscopy/high resolution transmission electron microscopy/energy dispersive spectroscopy, and thermogravimetric analysis. In order to quantify the nanostructure of the particles and identify prevalent sub-structures, a novel image analysis framework was used. It was found that the process temperature, affected both by λ and the load of the gasifier, had a significant influence on the particle formation processes. At low temperature (1060 °C), the formed soot particles seemed to be resistant to the oxidation process; however, when the oxidation process started at 1119 °C, the internal burning of the more reactive particle core began. A further increase in temperature (> 1313 °C) lead to the oxidation of the less reactive particle shell. When the shell finally collapsed due to severe oxidation, the original soot particle shape and nanostructure also disappeared and the resulting particle could not be considered as a soot anymore. Instead, the particle shape and nanostructure at the highest temperatures (> 1430 °C) were a function of the inorganic content and of the inorganic elements the individual particle consisted of. All of these effects together lead to the soot particles in the real gasifier environment having less and less ordered nanostructure and higher and higher reactivity as the temperature increased; i.e., they followed the opposite trend of what is observed during laboratory-scale studies with fuels not containing any ash-forming elements and where the temperature was not controlled by λ.
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| 4. |
- Ali, Sharafat, Associate Professor, 1976-, et al.
(author)
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Composition–structure–property relationships of transparent Ca–Al–Si–O–N oxynitride glasses : The roles of nitrogen and aluminum
- 2023
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In: Journal of The American Ceramic Society. - : John Wiley & Sons. - 0002-7820 .- 1551-2916. ; 106:3, s. 1748-1765
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Journal article (peer-reviewed)abstract
- We explore the formation and composition–structure–property correlations of transparent Ca–Al–Si–O–N glasses, which were prepared by a standard melt-quenching technique using AlN as the nitrogen source and incorporating up to 8 at.% of N. Their measured physical properties of density, molar volume, compactness, refractive index, and hardness—along with the Young, shear, and bulk elastic moduli—depended roughly linearly on the N content. These effects are attributed primarily to the improved glass-network cross-linking from N compared to O, rather than the formation of higher-coordination AlO5 and AlO6 groups, where 27Al magic-angle-spinning nuclear magnetic resonance experimentation revealed that aluminum is predominately present in tetrahedral coordination as AlO4 units. Yet, several physical properties, such as the refractive index along with the bulk, shear, and Young's elastic moduli, increase concomitantly with the Al content of the glass. We discuss the incompletely understood mechanical–property boosting role of Al as observed both herein and in previous reports on oxynitride glasses, moreover suggesting glass-composition domains that are likely to offer optimal mechanical properties.
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| 5. |
- Olenius, Tinja, et al.
(author)
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Modeling of exhaust gas cleaning by acid pollutant conversion to aerosol particles
- 2021
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In: Fuel. - : Elsevier BV. - 0016-2361 .- 1873-7153. ; 290
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Journal article (peer-reviewed)abstract
- Sulfur and nitrogen oxides (SOx and NOx) are harmful pollutants emitted into the atmosphere by industry and transport sectors. In addition to being hazardous gases, SOx and NOx form sulfuric and nitric acids which contribute to the formation of airborne particulate matter through nucleation and condensation, hence magnifying the environmental impact of these species. In this work, we build a modeling framework for utilizing this phenomenon for low-temperature exhaust gas cleaning. It has been reported that ammonia gas can be used to facilitate particle formation from the aforementioned acids, and thus remove these gaseous pollutants by converting them into ammonium sulfate and nitrate particles. Here we provide comprehensive modeling tools for applying this idea to exhaust gas cleaning by combining detailed models for nucleation, gas-particle mass exchange and particle population dynamics. We demonstrate how these models can be used to find advantageous operating conditions for a cleaning unit. In particular, the full model is computationally cheap and enables optimization of the particle formation efficiency and particle growth, hence ensuring sufficient conversion of gaseous pollutants into collectable particulate matter. This constitutes a ground for future engineering tools for designing next-generation sustainable exhaust gas cleaners.
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| 6. |
- Ekener, Elisabeth, 1963-, et al.
(author)
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Developing Life Cycle Sustainability Assessment methodology by applying values-based sustainability weighting - Tested on biomass based and fossil transportation fuels
- 2018
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In: Journal of Cleaner Production. - : Elsevier BV. - 0959-6526 .- 1879-1786. ; 181, s. 337-351
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Journal article (peer-reviewed)abstract
- The production and use of transportation fuels can lead to sustainability impacts. Assessing them simultaneously in a holistic way is a challenge. This paper examines methodology for assessing the sustainability performance of products in a more integrated way, including a broad range of social impacts. Life Cycle Sustainability Assessment (LCSA) methodology is applied for this assessment. LSCA often constitutes of the integration of results from social LCA (S-LCA), environmental life cycle assessment (E-LCA) and life cycle costing (LCC). In this study, an S-LCA from an earlier project is extended with a positive social aspect, as well as refined and detailed. E-LCA and LCC results are built from LCA database and literature. Multi Criteria Decision Analysis (MCDA) methodology is applied to integrate the results from the three different assessments into an LCSA. The weighting of key sustainability dimensions in the MCDA is performed in different ways, where the sustainability dimensions are prioritized differently priority based on the assumed values of different stakeholder profiles (Egalitarian, Hierarchist, and Individualist). The developed methodology is tested on selected biomass based and fossil transportation fuels - ethanol produced from Brazilian sugarcane and US corn/maize, and petrol produced from Russian and Nigerian crude oils, where it delineates differences in sustainability performance between products assessed. The outcome in terms of relative ranking of the transportation fuel chains based on sustain ability performance differs when applying different decision-maker profiles. This result highlights and supports views that there is no one single answer regarding which of the alternatives that is most sustainable. Rather, it depends strongly upon the worldview and values held by the decision maker. A key conclusion is that sustainability assessments should pay more attention to potential differences in underlying values held by key stakeholders in relevant societal contexts. The LCSA methodology still faces challenges regarding results integration but MCDA in combination with stakeholder profiles appears to be a useful approach to build on further.
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| 7. |
- Sandberg, David, 1980, et al.
(author)
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Detecting driver sleeepiness using optimized non-linear combinations of sleepiness indicators
- 2011
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In: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 12:1, s. 97-108
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Journal article (peer-reviewed)abstract
- This paper addresses the problem of detecting sleepiness in car drivers. First, a variety of sleepiness indicators (based on driving behavior) proposed in the literature were evaluated. These indicators were then subjected to parametric optimization using stochastic optimization methods. To improve performance, the functional form of some of the indicators was generalized before optimization. Next, using a neural network, the best performing sleepiness indicators were combined with a mathematical model of sleepiness, i.e., the sleep/wake predictor (SWP). The analyses were based on data obtained from a study that involved 12 test subjects at the moving-base driving simulator at the Swedish National Road and Transportation Research Institute (VTI), Linkping, Sweden. The data were derived from 12 1-h driving sessions for each test subject, with varying degrees of sleepiness. The performance measure (range [0,1]) for indicators was taken as the average of sensitivity and specificity. Starting with indicators proposed in the literature, the best such indicator, i.e., the standard deviation of the yaw angle, reached a performance score of 0.72 on previously unseen test data. It was found that indicators based on a given signal gave essentially equal performance after parametric optimization, but in no case was it better than 0.72. The best generalized indicator (the generic variability indicator) obtained a performance score of 0.74. SWP achieved a score of 0.78. However, by nonlinearly combining SWP with the generic variability indicator, a score of 0.83 was obtained. Thus, the results imply that a nonlinear combination of a measure based on driving behavior with a model of sleepiness significantly improves driver sleepiness detection.
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| 8. |
- Bakker, Bram, et al.
(author)
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A Multi-Stage, Multi-Feature Machine Learning Approach to Detect Driver Sleepiness in Naturalistic Road Driving Conditions
- 2022
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In: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:5, s. 4791-4800
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Journal article (peer-reviewed)abstract
- Driver fatigue is a contributing factor in about 20% of all fatal road crashes worldwide. Countermeasures are urgently needed and one of the most promising and currently available approaches for that are in-vehicle systems for driver fatigue detection. The main objective of this paper is to present a video-based driver sleepiness detection system set up as a two-stage model with (1) a generic deep feature extraction module combined with (2) a personalised sleepiness detection module. The approach was designed and evaluated using data from 13 drivers, collected during naturalistic driving conditions on a motorway in Sweden. Each driver performed one 90-minute driving session during daytime (low sleepiness condition) and one session during night-time (high sleepiness condition). The sleepiness detection model outputs a continuous output representing the Karolinska Sleepiness Scale (KSS) scale from 1-9 or a binary decision as alert (defined as KSS 1-6) or sleepy (defined as KSS 7-9). Continuous output modelling resulted in a mean absolute error (MAE) of 0.54 KSS units. Binary classification of alert or sleepy showed an accuracy of 92% (sensitivity = 91.7%, specificity = 92.3%, F1 score = 90.4%). Without personalisation, the corresponding accuracy was 72%, while a standard fatigue detection PERCLOS-based baseline method reached an accuracy of 68% on the same dataset. The developed real-time sleepiness detection model can be used in the management of sleepiness/fatigue by detecting precursors of severe fatigue, and ultimately reduce sleepiness-related road crashes by alerting drivers before high levels of fatigue are reached.
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| 9. |
- Enrico, Alessandro, et al.
(author)
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Cleanroom-Free Direct Laser Micropatterning of Polymers for Organic Electrochemical Transistors in Logic Circuits and Glucose Biosensors
- 2024
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In: Advanced Science. - : Wiley. - 2198-3844.
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Journal article (peer-reviewed)abstract
- Organic electrochemical transistors (OECTs) are promising devices for bioelectronics, such as biosensors. However, current cleanroom-based microfabrication of OECTs hinders fast prototyping and widespread adoption of this technology for low-volume, low-cost applications. To address this limitation, a versatile and scalable approach for ultrafast laser microfabrication of OECTs is herein reported, where a femtosecond laser to pattern insulating polymers (such as parylene C or polyimide) is first used, exposing the underlying metal electrodes serving as transistor terminals (source, drain, or gate). After the first patterning step, conducting polymers, such as poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), or semiconducting polymers, are spin-coated on the device surface. Another femtosecond laser patterning step subsequently defines the active polymer area contributing to the OECT performance by disconnecting the channel and gate from the surrounding spin-coated film. The effective OECT width can be defined with high resolution (down to 2 mu m) in less than a second of exposure. Micropatterning the OECT channel area significantly improved the transistor switching performance in the case of PEDOT:PSS-based transistors, speeding up the devices by two orders of magnitude. The utility of this OECT manufacturing approach is demonstrated by fabricating complementary logic (inverters) and glucose biosensors, thereby showing its potential to accelerate OECT research. Ultrafast focused femtosecond laser has been introduced for the direct micropatterning of organic electrochemical transistors (OECTs), providing high resolution (2 mu m), selective cleanroom-free patterning of insulating and conjugated polymer layers while preserving device operation, and high flexibility in device design. The approach has been validated in the fabrication of complementary inverters and glucose biosensors.image
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| 10. |
- Gren, Åsa, et al.
(author)
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How smart is smart growth? : Examining the environmental validation behind city compaction
- 2019
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In: Ambio. - : Springer Netherlands. - 0044-7447 .- 1654-7209. ; 48:6, s. 580-589
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Research review (peer-reviewed)abstract
- Smart growth (SG) is widely adopted by planners and policy makers as an environmentally friendly way of building cities. In this paper, we analyze the environmental validity of the SG-approach based on a review of the scientific literature. We found a lack of proof of environmental gains, in combination with a great inconsistency in the measurements of different SG attributes. We found that a surprisingly limited number of studies have actually examined the environmental rationales behind SG, with 34% of those studies displaying negative environmental outcomes of SG. Based on the insights from the review, we propose that research within this context must first be founded in more advanced and consistent knowledge of geographic and spatial analyses. Second, it needs to a greater degree be based on a system's understanding of urban processes. Third, it needs to aim at making cities more resilient, e.g., against climate-change effects.
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