scholarly journals The Influence of Water on the Heat Loss of Hot Mix Asphalt

2019 ◽  
Vol 9 (9) ◽  
pp. 1747
Author(s):  
Paweł Mieczkowski ◽  
Bartosz Budziński
Keyword(s):  
Hot Mix Asphalt ◽  
Specific Property ◽  
External Factors ◽  
Model Parameters ◽  
Thermal Processes ◽  
Average Value ◽  
Influence Of Water ◽  
Boiling And Evaporation ◽  
The Heat Transfer Coefficient ◽  
Specimen Section

Compaction of hot mix asphalt (HMA) is a process of altering the internal structure of the material and, as a consequence, also its performance characteristics. The process should ensure the adequate viscosity of binder, a property depending on the temperature and the material-specific property (hardness) of the binder (in the case of HMA). One of the external factors that can affect the process of compaction is the presence of water quickly decreasing the HMA temperature. This paper presents a theoretical model for determining the HMA temperature variation under the effect of water. One of the model parameters is the heat transfer coefficient α for the outward flow of heat. Its value varies strongly in the interfacial zones of the HMA layer (i.e., near the top and bottom surfaces) due to the effect of external factors. The paper presents the attempt to estimate the average value for the whole paving process depending on the precipitation rate (amount of water involved in the process). The temperatures obtained from the model were verified experimentally on laboratory specimens cooled with water. The temperature was measured on the surface and across the specimen section. The drop of temperature of HMA was almost instantaneous on the surface—due to the thermal processes involving water (boiling and evaporation)—and much slower across the layer thickness.

Effects of asphalt concrete characteristics on cohesive zone model parameters of hot mix asphalt mixtures

2016 ◽  
Vol 43 (3) ◽  
pp. 226-232 ◽  
Author(s):  
S. Pirmohammad ◽  
H. Khoramishad ◽  
M.R. Ayatollahi
Keyword(s):  
Asphalt Concrete ◽  
Cohesive Energy ◽  
Cohesive Zone ◽  
Hot Mix Asphalt ◽  
Cohesive Zone Model ◽  
Experimental Tests ◽  
Model Parameters ◽  
Zone Model ◽  
Binder Type ◽  
Air Void

In this paper, the effects of the main asphalt concrete characteristics including the binder type and the air void percentage on the cohesive zone model (CZM) parameters were studied. Experimental tests were conducted on semi-circular bend (SCB) specimens made of asphalt concrete and the fracture behavior was simulated using a proper CZM. The CZM parameters of various hot mix asphalt (HMA) mixtures were determined using the SCB experimental results. Five types of HMA mixtures were tested and modeled to consider the effects of binder type and air void percentage on the CZM parameters. The results showed that as the binder in HMA mixture softened, the cohesive energy strength increased, whereas enhancing the air void percentage led to reduction of the cohesive energy and strength values. Among the studied HMA mixtures, the highest values of CZM parameters were found for the HMA mixture containing a copolymer called styrene-butadiene-styrene.

scholarly journals Coupled Land Surface-Subsurface Hydrogeophysical Inverse Modeling to Estimate Soil Organic Content and explore associated Hydrological and Thermal Dynamics in an Arctic Tundra

2017 ◽  
Author(s):  
Anh Phuong Tran ◽  
Baptiste Dafflon ◽  
Susan S. Hubbard
Keyword(s):  
Land Surface ◽  
Measurement Errors ◽  
Apparent Resistivity ◽  
High Reliability ◽  
Joint Inversion ◽  
Model Parameters ◽  
Thermal Processes ◽  
Thermal Dynamics ◽  
Microbial Decomposition ◽  
Community Land Model

Abstract. Quantitative characterization of soil organic carbon (OC) content is essential due to its significant impacts on surface–subsurface hydrological-thermal processes and microbial decomposition of OC, which both in turn are important for predicting carbon-climate feedbacks. While such quantification is particularly important in the vulnerable organic-rich Arctic region, it is challenging to achieve due to the general limitations of conventional core sampling and analysis methods, and to the extremely dynamic nature of hydrological-thermal processes associated with annual freeze-thaw events. In this study, we develop and test an inversion scheme that can flexibly use single or multiple datasets, including soil water liquid, temperature and electrical resistivity data (ERT), to estimate the vertical distribution of OC content. We subsequently explore the control of OC on hydrological-thermal behavior. We employ the Community Land Model to simulate nonisothermal surface-subsurface hydrological dynamics from the bedrock to the top of canopy, with consideration of land surface processes and ice/liquid water phase transitions. For inversion, we combine a deterministic and an adaptive Markov chain Monte Carlo (MCMC) optimization algorithm to estimate posterior distributions of desired model parameters. For hydrological-thermal to geophysical variable transformation, the simulated subsurface temperature, liquid and ice water content are explicitly linked to the soil apparent resistivity via petrophysical and geophysical models. We validate the developed scheme using different numerical experiments and evaluate the influence of measurement errors and benefit of joint inversion on the estimation of OC and other parameters. We also quantified the propagation of uncertainty from the estimated parameters to prediction of hydrological-thermal responses. We find that compared to inversion of single dataset (either temperature or liquid or apparent resistivity), joint inversion of these datasets significantly reduces parameter uncertainty. We find that the joint inversion approach is able to estimate OC and sand content within the shallow active layer (0.3 m) with high reliability. Due to the small variations of temperature and moisture within the shallow permafrost (0.6 m), the approach is unable to estimate OC with confidence. However, if the soil porosity is functionally related to the OC and mineral content, the uncertainty of OC estimate at this depth remarkably decreases. Our study documents the value of the new surface-subsurface, deterministic-stochastic inversion approach, as well as the benefit of including multiple types of data to estimate OC and associated hydrological-thermal dynamics.

scholarly journals Interaction of Nanodiamonds with Water: Impact of Surface Chemistry on Hydrophilicity, Aggregation and Electrical Properties

Nanomaterials ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 2740
Author(s):  
Pietro Aprà ◽  
Lorenzo Mino ◽  
Alfio Battiato ◽  
Paolo Olivero ◽  
Sofia Sturari ◽  
...  
Keyword(s):  
Electrical Properties ◽  
Surface Chemistry ◽  
Water Adsorption ◽  
Electrical Conductance ◽  
Depth Information ◽  
Thermal Processes ◽  
Water Impact ◽  
Temperature Dependent ◽  
Research Fields ◽  
Influence Of Water

In recent decades, nanodiamonds (NDs) have earned increasing interest in a wide variety of research fields, thanks to their excellent mechanical, chemical, and optical properties, together with the possibility of easily tuning their surface chemistry for the desired purpose. According to the application context, it is essential to acquire an extensive understanding of their interaction with water in terms of hydrophilicity, environmental adsorption, stability in solution, and impact on electrical properties. In this paper, we report on a systematic study of the effects of reducing and oxidizing thermal processes on ND surface water adsorption. Both detonation and milled NDs were analyzed by combining different techniques. Temperature-dependent infrared spectroscopy was employed to study ND surface chemistry and water adsorption, while dynamic light scattering allowed the evaluation of their behavior in solution. The influence of water adsorption on their electrical properties was also investigated and correlated with structural and optical information obtained via Raman/photoluminescence spectroscopy. In general, higher oxygen-containing surfaces exhibited higher hydrophilicity, better stability in solution, and higher electrical conduction, although for the latter the surface graphitic contribution was also crucial. Our results provide in-depth information on the hydrophilicity of NDs in relation to their surface chemical and physical properties, by also evaluating the impacts on their aggregation and electrical conductance.

Penanganan Overdispersi pada Regresi Poisson dengan Regresi Binomial Negatif pada Kasus Kemiskinan di Indonesia

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Lulu Mahdiyah Sandjadirja ◽  
Muhammad Nur Aidi ◽  
Akbar Rizki
Keyword(s):  
Regression Model ◽  
Poisson Regression ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
External Factors ◽  
Poor People ◽  
Negative Binomial Regression Model ◽  
Average Value ◽  
Binomial Regression ◽  
Working Age

Poisson regression can be used to model rare events that consist of count data. Poisson regression application is carried out to find out external factors that affect the number of poor people in Indonesia by the province in 2016. The assumptions that must be met in this analysis are equdispersion. However, in real cases there is often a problem of overdispersion, ie the value of the variance is greater than the average value. High diversity can be caused by outliers. Expenditures on outliers have not been able to deal with the problem of overdispersion in Poisson Regression. One way to overcome this problem is to replace the Poisson distribution assumption with the Negative Binomial distribution. The results of the analysis show that the Negative Binomial Regression model without outliers is better than the Poisson Regression without outliers model indicated by a smaller AIC value. Based on the Negative Binomial Regression model without this outlier the external factors that affect the number of poor people in Indonesia by the province in 2016 are the percentage of households with floor conditions of houses with soil by province, population by province, percentage of unemployment to the total workforce by province and the percentage of the workforce against the working age population.

Improving tree mortality models by accounting for environmental influences

2007 ◽  
Vol 37 (11) ◽  
pp. 2106-2114 ◽  
Author(s):  
Henrik Hartmann ◽  
Christian Messier ◽  
Marilou Beaudet
Keyword(s):  
Tree Mortality ◽  
External Validation ◽  
Growth Patterns ◽  
External Factors ◽  
Model Parameters ◽  
Similar Frequency ◽  
Growth Series ◽  
Recent Growth ◽  
Dead Trees ◽  
The Impact

Tree-ring chronologies have been widely used in studies of tree mortality where variables of recent growth act as an indicator of tree physiological vigour. Comparing recent radial growth of live and dead trees thus allows estimating probabilities of tree mortality. Sampling of mature dead trees usually provides death-year distributions that may span over years or decades. Recent growth of dead trees (prior to death) is then computed during a number of periods, whereas recent growth (prior to sampling) for live trees is computed for identical periods. Because recent growth of live and dead trees is then computed for different periods, external factors such as disturbance or climate may influence growth rates and, thus, mortality probability estimations. To counteract this problem, we propose the truncating of live-growth series to obtain similar frequency distributions of the “last year of growth” for the populations of live and dead trees. In this paper, we use different growth scenarios from several tree species, from several geographic sources, and from trees with different growth patterns to evaluate the impact of truncating on predictor variables and their selection in logistic regression analysis. Also, we assess the ability of the resulting models to accurately predict the status of trees through internal and external validation. Our results suggest that the truncating of live-growth series helps decrease the influence of external factors on growth comparisons. By doing so, it reinforces the growth–vigour link of the mortality model and enhances the model’s accuracy as well as its general applicability. Hence, if model parameters are to be integrated in simulation models of greater geographical extent, truncating may be used to increase model robustness.

scholarly journals Rutting Performance of Hot Mix Asphalt Using Bagasse Ash as Filler

2021 ◽  
Author(s):  
Naveed Khan
Keyword(s):  
Hot Mix Asphalt ◽  
Asphalt Pavement ◽  
Agricultural Waste ◽  
Filler Material ◽  
Strength Parameters ◽  
Average Value ◽  
Stone Dust ◽  
Maximum Stability ◽  
Sugarcane Bagasse Ash ◽  
Number Of Passes

Transportation plays an important role in the development of a country. Due to the increase in the population, the demand for good transportation and passengers increased. For this purpose, new highways are built up every year. The demand for material for the construction is increasing and the researchers are in the race to find out materials which not only used as a replacer but also increase the strength parameters and decrease destresses in Hot Mix Asphalt pavement. In the present study Sugarcane, Bagasse Ash which is an agricultural waste was used as a filler material. At Optimum Binder Content 4.55 maximum stability of 7.03 KN was achieved while for the samples having stone dust as a filler material give maximum stability at 4.33 percent of 7.37 KN. Bagasse ash used as a filler in Wheel tracker test has given the best result at temperature 300C and the average rut depth was recorded as 2.065mm while stone dust samples showed average rut depth 2.235mm at 30 0Cand the number of passes was recorded as 14000. On the other hand, the samples which are subjected to a temperature of 600C BA samples showed greater rut of the average value of 6.81mm whereas the average value of stone dust samples showed 6.615mm rut depth. From the above results, the author concluded that bagasse is the best modifier material for the areas having low temperature such as 30 0C or below. 

Experimental study of electrostatic fields influencing thermal processes in gaseous methane at its natural convection

2021 ◽  
Author(s):  
V.A. Altunin ◽  
K.V. Altunin ◽  
M.R. Abdullin ◽  
M.R. Chigarev ◽  
I.N. Aliev ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Natural Convection ◽  
Power Plants ◽  
Discharge Zone ◽  
Thermal Processes ◽  
Electrostatic Fields ◽  
Experimental Base ◽  
Gaseous Media ◽  
History Of ◽  
The Heat Transfer Coefficient

The paper shows the history of studying electrostatic fields in various gaseous media, including gaseous methane, and substantiates the necessity to experimentally study electrostatic fields influencing thermal processes in gaseous methane at its natural convection. We describe the experimental base and working areas with the use of electrostatic fields, as well as the method of conducting experimental research. The results of the influence of electrostatic fields on the coefficient of heat transfer to gaseous methane and on the negative process of sedimentation in it — during its natural convection are presented. In our research, we found zones of possible intensification of heat transfer to gaseous methane and zones of saturation with electrostatic fields, in which a further increase in the heat transfer coefficient is impossible. We experimentally established that the boundary of the zone of the beginning of saturation with electrostatic fields is also the beginning of the corona discharge zone. The research results formed the basis for the method of using electrostatic fields in aircraft engines and power plants.

scholarly journals Using Recurrent Procedures in Adaptive Control System for Identify the Model Parameters of the Moving Vessel on the Cross Slipway

Data ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 60
Author(s):  
Hanna Rudakova ◽  
Oksana Polyvoda ◽  
Anton Omelchuk
Keyword(s):  
External Factors ◽  
Automated System ◽  
Coherent Motion ◽  
Control Synthesis ◽  
Model Parameters ◽  
Adaptive Control System ◽  
Operational Control ◽  
Two Phase ◽  
Mode Of Operation ◽  
Linearized Model

The article analyses the problems connected with ensuring the coordinated operation of slipway drives that arise during the launch of a ship. The dynamic model of load of the electric drive of the ship’s cart is obtained taking into account the peculiarities of the construction of the ship-lifting complex, which allows us to analyse the influence of external factors and random influences during the entire process of launching the ship. A linearized mathematical model of the dynamics of a complex vessel movement in the process of descent in the space of states is developed, which allows us to identify the mode of operation of the multi-drive system, taking into account its structure. The analysis of application efficiency of recurrent methods for identification (stochastic approximation and least squares) of the linearized model parameters in the space of states is carried out. A decision support system has been developed in the automated system of operational control by the module for estimating the situation and the control synthesis to ensure a coherent motion of a complex ship-carts object in a two-phase environment.

scholarly journals Covid-19 disease dynamics with vaccination: The effect of uncertainty

2022 ◽  
Author(s):  
Nandadulal Bairagi ◽  
Abhijiit Majumder
Keyword(s):  
Mathematical Models ◽  
Vaccine Efficacy ◽  
Loss Rate ◽  
Vaccination Rate ◽  
Model Parameters ◽  
Extinction Time ◽  
Disease Eradication ◽  
Average Value ◽  
Force Of Infection ◽  
Induced Immunity

Rate parameters are critical in estimating the covid burden using mathematical models. In the Covid-19 mathematical models, these parameters are assumed to be constant. However, uncertainties in these rate parameters are almost inevitable. In this paper, we study a stochastic epidemic model of the SARS-CoV-2 virus infection in the presence of vaccination in which some parameters fluctuate around its average value. Our analysis shows that if the stochastic basic reproduction number (SBRN) of the system is greater than unity, then there is a stationary distribution, implying the long-time disease persistence. A sufficient condition for disease eradication is also prescribed for which the exposed class goes extinct, followed by the infected class. The disease eradication criterion may not hold if the rate of vaccine-induced immunity loss increases or/and the force of infection increases. Using the Indian Covid-19 data, we estimated the model parameters and showed the future disease progression in the presence of vaccination. The disease extinction time is estimated under various conditions. It is revealed that the mean extinction time is an increasing function of both the force of infection and immunity loss rate and shows the lognormal distribution. We point out that disease eradication might not be possible even at a higher vaccination rate if the vaccine-induced immunity loss rate is high. Our observation thus indicates the endemicity of the disease for the existing vaccine efficacy. The disease eradication is possible only with a higher vaccine efficacy or a reduced infection rate.

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