Abstract: In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.
Abstract: Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies. Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication. And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.
Abstract: Eddy viscosity models in turbulence modeling can be mainly classified as linear and nonlinear models. Linear formulations are simple and require less computational resources but have the disadvantage that they cannot predict actual flow pattern in complex geophysical flows where streamline curvature and swirling motion are predominant. A constitutive equation of Reynolds stress anisotropy is adopted for the formulation of eddy viscosity including all the possible higher order terms quadratic in the mean velocity gradients, and a simplified model is developed for actual oceanic flows where only the vertical velocity gradients are important. The new model is incorporated into the one dimensional General Ocean Turbulence Model (GOTM). Two realistic oceanic test cases (OWS Papa and FLEX' 76) have been investigated. The new model predictions match well with the observational data and are better in comparison to the predictions of the two equation k-epsilon model. The proposed model can be easily incorporated in the three dimensional Princeton Ocean Model (POM) to simulate a wide range of oceanic processes. Practically, this model can be implemented in the coastal regions where trasverse shear induces higher vorticity, and for prediction of flow in estuaries and lakes, where depth is comparatively less. The model predictions of marine turbulence and other related data (e.g. Sea surface temperature, Surface heat flux and vertical temperature profile) can be utilized in short term ocean and climate forecasting and warning systems.
Abstract: A facility exploiting only electronic gambling machines (EGMs) opened in 2007 in Quebec City, Canada under the name of Salons de Jeux du Québec (SdjQ). This facility is one of the first worldwide to rely on that business model. This paper models the performance of such EGMs. The interest from a managerial point of view is to identify the variables that can be controlled or influenced so that a comprehensive model can help improve the overall performance of the business. The EGM individual performance model contains eight different variables under study (Game Title, Progressive jackpot, Bonus Round, Minimum Coin-in, Maximum Coin-in, Denomination, Slant Top and Position). Using data from Quebec City’s SdjQ, a linear regression analysis explains 90.80% of the EGM performance. Moreover, results show a behavior slightly different than that of a casino. The addition of GameTitle as a factor to predict the EGM performance is one of the main contributions of this paper. The choice of the game (GameTitle) is very important. Games having better position do not have significantly better performance than games located elsewhere on the gaming floor. Progressive jackpots have a positive and significant effect on the individual performance of EGMs. The impact of BonusRound on the dependent variable is significant but negative. The effect of Denomination is significant but weakly negative. As expected, the Language of an EGMS does not impact its individual performance. This paper highlights some possible improvements by indicating which features are performing well. Recommendations are given to increase the performance of the EGMs performance.
Abstract: The Gravity Recovery and Climate Experiment (GRACE) has been a very successful project in determining math redistribution within the Earth system. Large deformations caused by earthquakes are in the high frequency band. Unfortunately, GRACE is only capable to provide reliable estimate at the low-to-medium frequency band for the gravitational changes. In this study, we computed the gravity changes after the 2012 Mw8.6 Indian Ocean earthquake off-Sumatra using the GRACE Level-2 monthly spherical harmonic (SH) solutions released by the University of Texas Center for Space Research (UTCSR). Moreover, we calculated gravity changes using different fault models derived from teleseismic data. The model predictions showed non-negligible discrepancies in gravity changes. However, after removing high-frequency signals, using Gaussian filtering 350 km commensurable GRACE spatial resolution, the discrepancies vanished, and the spatial patterns of total gravity changes predicted from all slip models became similar at the spatial resolution attainable by GRACE observations, and predicted-gravity changes were consistent with the GRACE-detected gravity changes. Nevertheless, the fault models, in which give different slip amplitudes, proportionally lead to different amplitude in the predicted gravity changes.
Abstract: Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).
Abstract: Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.
Abstract: Neutralisation of acid-mine drainage (AMD) using limestone is cost effective, and good results can be obtained. However, this process has its limitations; it cannot be used for highly acidic water which consists of Fe(III). When Fe(III) reacts with CaCO3, it results in armoring. Armoring slows the reaction, and additional alkalinity can no longer be generated. Limestone is easily accessible, so this problem can be easily dealt with. Experiments were carried out to evaluate the effect of PVC pipe length on ferric and ferrous ions. It was found that the shorter the pipe length the more these dissolved metals precipitate. The effect of the pipe length on the hydrogen ions was also studied, and it was found that these two have an inverse relationship. Experimental data were further compared with the model prediction data to see if they behave in a similar fashion. The model was able to predict the behaviour of 1.5m and 2 m pipes in ferric and ferrous ion precipitation.
Abstract: In this paper, a desiccant solar unit for air
conditioning and desalination is presented first. Secondly, a dynamic
modelling study of the desiccant wheel is developed. After that, a
simulation study and an experimental investigation of the behaviour
of desiccant wheel are developed. The experimental investigation is
done in the chamber of commerce in Freiburg-Germany. Indeed, the
variations of calculated and measured temperatures and specific
humidity of dehumidified and rejected air are presented where a good
agreement is found when comparing the model predictions with
experimental data under the considered range of operating conditions.
Finally, the study of the compartments of desalination and water
condensation shows that the unit can produce an acceptable quantity
of water at the same time of the air conditioning operation.
Abstract: Production fluids are transported from the platform to
tankers or process facilities through transfer pipelines. Water being
one of the heavier phases tends to settle at the bottom of pipelines
especially at low flow velocities and this has adverse consequences
for pipeline integrity. On restart after a shutdown, this could result in
corrosion and issues for process equipment, thus the need to have the
heavier liquid dispersed into the flowing lighter fluid. This study
looked at the flow regime of low water cut and low flow velocity oil
and water flow using conductive film thickness probes in a large
diameter 4-inch pipe to obtain oil and water interface height and the
interface structural velocity. A wide range of 0.1–1.0 m/s oil and
water mixture velocities was investigated for 0.5–5% water cut. Two
fluid model predictions were used to compare with the experimental
results.
Abstract: An industrial system for the production of white
liquor of a paper industry, Klabin Paraná Papéis, formed by ten
reactors was modeled, simulated, and analyzed. The developed model
considered possible water losses by evaporation and reaction, in
addition to variations in volumetric flow of lime mud across the
reactors due to composition variations. The model predictions agreed
well with the process measurements at the plant and the results
showed that the slaking reaction is nearly complete at the third
causticizing reactor, while causticizing ends by the seventh reactor.
Water loss due to slaking reaction and evaporation occurs more
pronouncedly in the slaking reaction than in the final causticizing
reactors; nevertheless, the lime mud flow remains nearly constant
across the reactors.
Abstract: We proposed a Hyperbolic Gompertz Growth Model
(HGGM), which was developed by introducing a shape parameter
(allometric). This was achieved by convoluting hyperbolic sine
function on the intrinsic rate of growth in the classical gompertz
growth equation. The resulting integral solution obtained
deterministically was reprogrammed into a statistical model and used
in modeling the height and diameter of Pines (Pinus caribaea). Its
ability in model prediction was compared with the classical gompertz
growth model, an approach which mimicked the natural variability of
height/diameter increment with respect to age and therefore provides
a more realistic height/diameter predictions using goodness of fit
tests and model selection criteria. The Kolmogorov Smirnov test and
Shapiro-Wilk test was also used to test the compliance of the error
term to normality assumptions while the independence of the error
term was confirmed using the runs test. The mean function of top
height/Dbh over age using the two models under study predicted
closely the observed values of top height/Dbh in the hyperbolic
gompertz growth models better than the source model (classical
gompertz growth model) while the results of R2, Adj. R2, MSE and
AIC confirmed the predictive power of the Hyperbolic Gompertz
growth models over its source model.
Abstract: Characterization of the engineering behavior of
unsaturated soil is dependent on the soil-water characteristic curve
(SWCC), a graphical representation of the relationship between water
content or degree of saturation and soil suction. A reasonable
description of the SWCC is thus important for the accurate prediction
of unsaturated soil parameters. The measurement procedures for
determining the SWCC, however, are difficult, expensive, and timeconsuming.
During the past few decades, researchers have laid a
major focus on developing empirical equations for predicting the
SWCC, with a large number of empirical models suggested. One of
the most crucial questions is how precisely existing equations can
represent the SWCC. As different models have different ranges of
capability, it is essential to evaluate the precision of the SWCC
models used for each particular soil type for better SWCC estimation.
It is expected that better estimation of SWCC would be achieved via
a thorough statistical analysis of its distribution within a particular
soil class. With this in view, a statistical analysis was conducted in
order to evaluate the reliability of the SWCC prediction models
against laboratory measurement. Optimization techniques were used
to obtain the best-fit of the model parameters in four forms of SWCC
equation, using laboratory data for relatively coarse-textured (i.e.,
sandy) soil. The four most prominent SWCCs were evaluated and
computed for each sample. The result shows that the Brooks and
Corey model is the most consistent in describing the SWCC for sand
soil type. The Brooks and Corey model prediction also exhibit
compatibility with samples ranging from low to high soil water
content in which subjected to the samples that evaluated in this study.
Abstract: Flood wave propagation in river channel flow can be enunciated by nonlinear equations of motion for unsteady flow. It is difficult to find analytical solution of these non-linear equations. Hence, in this paper verification of the finite element model has been carried out against available numerical predictions and field data. The results of the model indicate a good matching with both Preissmann scheme and HEC-RAS model for a river reach of 29km at both sites (15km from upstream and at downstream end) for discharge hydrographs. It also has an agreeable comparison with the Preissemann scheme for the flow depth (stage) hydrographs. The proposed model has also been applying to forecast daily discharges at 400km downstream in the Indus River from Sukkur barrage of Sindh, Pakistan, which demonstrates accurate model predictions with observed the daily discharges. Hence, this model may be utilized for flood warnings in advance.
Abstract: In the present study, two distinctly different approaches are followed for modeling of reactive distillation column, the equilibrium stage model and the nonequilibrium stage model. These models are simulated with a computer code developed in the present
study using MATLAB programming. In the equilibrium stage models, the vapor and liquid phases are assumed to be in equilibrium and allowance is made for finite reaction rates, where as in the nonequilibrium stage models simultaneous mass transfer and reaction rates are considered. These simulated model results are validated from the experimental data reported in the literature. The simulated results of equilibrium and nonequilibrium models are compared for concentration, temperature and reaction rate profiles in a reactive distillation column for Methyl Tert Butyle Ether (MTBE) production. Both the models show similar trend for the concentration, temperature and reaction rate profiles but the nonequilibrium model predictions are higher and closer to the experimental values reported in the literature.
Abstract: In the current work, a numerical parametric study was
performed in order to model the fluid mechanics in the riser of a
bubbling fluidized bed (BFB). The gas-solid flow was simulated by
mean of a multi-fluid Eulerian model incorporating the kinetic theory
for solid particles. The bubbling fluidized bed was simulated two
dimensionally by mean of a Computational Fluid Dynamic (CFD)
commercial software package, Fluent. The effects of using different
inter-phase drag function (the drag model of Gidaspow, Syamlal and
O-Brien and the EMMS drag model) on the model predictions were
evaluated and compared. The results showed that the drag models of
Gidaspow and Syamlal and O-Brien overestimated the drag force for
the FCC particles and predicted a greater bed expansion in
comparison to the EMMS drag model.
Abstract: This paper presents an alternate approach that uses
artificial neural network to simulate the flood level dynamics in a
river basin. The algorithm was developed in a decision support
system environment in order to enable users to process the data. The
decision support system is found to be useful due to its interactive
nature, flexibility in approach and evolving graphical feature and can
be adopted for any similar situation to predict the flood level. The
main data processing includes the gauging station selection, input
generation, lead-time selection/generation, and length of prediction.
This program enables users to process the flood level data, to
train/test the model using various inputs and to visualize results. The
program code consists of a set of files, which can as well be modified
to match other purposes. This program may also serve as a tool for
real-time flood monitoring and process control. The running results
indicate that the decision support system applied to the flood level
seems to have reached encouraging results for the river basin under
examination. The comparison of the model predictions with the
observed data was satisfactory, where the model is able to forecast
the flood level up to 5 hours in advance with reasonable prediction
accuracy. Finally, this program may also serve as a tool for real-time
flood monitoring and process control.
Abstract: A thin layer on the component surface can be found
with high tensile residual stresses, due to turning operations, which
can dangerously affect the fatigue performance of the component. In
this paper an analytical approach is presented to reconstruct the
residual stress field from a limited incomplete set of measurements.
Airy stress function is used as the primary unknown to directly solve
the equilibrium equations and satisfying the boundary conditions. In
this new method there exists the flexibility to impose the physical
conditions that govern the behavior of residual stress to achieve a
meaningful complete stress field. The analysis is also coupled to a
least squares approximation and a regularization method to provide
stability of the inverse problem. The power of this new method is
then demonstrated by analyzing some experimental measurements
and achieving a good agreement between the model prediction and
the results obtained from residual stress measurement.
Abstract: The Navier–Stokes equations for unsteady, incompressible, viscous fluids in the axisymmetric coordinate system are solved using a control volume method. The volume-of-fluid (VOF) technique is used to track the free-surface of the liquid. Model predictions are in good agreement with experimental measurements. It is found that the dynamic processes after impact are sensitive to the initial droplet velocity and the liquid pool depth. The time evolution of the crown height and diameter are obtained by numerical simulation. The critical We number for splashing (Wecr) is studied for Oh (Ohnesorge) numbers in the range of 0.01~0.1; the results compares well with those of the experiments.
Abstract: Droplet size distributions in the cold spray of a fuel
are important in observed combustion behavior. Specification of
droplet size and velocity distributions in the immediate downstream
of injectors is also essential as boundary conditions for advanced
computational fluid dynamics (CFD) and two-phase spray transport
calculations. This paper describes the development of a new model to
be incorporated into maximum entropy principle (MEP) formalism
for prediction of droplet size distribution in droplet formation region.
The MEP approach can predict the most likely droplet size and
velocity distributions under a set of constraints expressing the
available information related to the distribution.
In this article, by considering the mechanisms of turbulence
generation inside the nozzle and wave growth on jet surface, it is
attempted to provide a logical framework coupling the flow inside the
nozzle to the resulting atomization process. The purpose of this paper
is to describe the formulation of this new model and to incorporate it
into the maximum entropy principle (MEP) by coupling sub-models
together using source terms of momentum and energy. Comparison
between the model prediction and experimental data for a gas turbine
swirling nozzle and an annular spray indicate good agreement
between model and experiment.