Experimental and numerical investigations of chemical grouting in heterogeneous porous media.

The objective of the present study is to understand the processes influencing the colloidal silica grout injection into porous media through experimental and numerical investigations. Experimental studies include viscosity measurements, grout injection into columns and grouted sand testing. The grout viscosities are measured during gelation under shear. Colloidal silica grout injection experiments are performed on two different sizes of columns to understand the grouting processes as well as to generate data for numerical simulations. The larger diameter column experiments are performed by varying colloidal silica solution and the type of water. The smaller diameter column (slim tube) experiment was conducted to obtain the data in the absence of fingers. The use of dyes aided in visualizing the grout flow patterns and understanding the processes. A numerical model is developed by non-iteratively coupling a groundwater flow simulation model (MODFLOW) and a 3-D multi-species reactive transport model (RT3D) and adding modules for the gelling process to simulate the chemical grouting in porous media. A grout gelation model is developed to estimate gel viscosity as a function of reaction time, grout concentration and shear rate. The flow field is periodically updated by taking into account the changing effective hydraulic conductivity in each cell as a result of non-uniform gel viscosity. The numerical model is verified and validated against (i) an analytical solution developed in this study, and (ii) the available numerical model results from literature, respectively. The grout model is used to analyse the experimental data of sodium silicate grout injection into the sand column as reported in literature. The grout model is also used to analyse the observations made in the colloidal silica grout injection experiment performed as part of this study. Simulation of grout injection has shown that the shear is an important parameter not incorporated in previous grouting models. The model captured the viscous fingers observed in the column experiments. The model has been able to predict the experimentally observed injection pressures in the mild slope region. The difference between experimental observations and numerical results increased towards the end of the simulation when the pressures increased steeply. It is hypothesized that this is due to the absence of filtration component in the model. The macromolecules filtered out at the pore throats contribute to the need for higher grout injection pressures. The model provides valuable insights in identifying the complex processes such as viscosification, shear, viscous finger formation and filtration, occurring during grouting.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .B65. Source: Dissertation Abstracts International, Volume: 66-07, Section: B, page: 3841. Thesis (Ph.D.)--University of Windsor (Canada), 2005

Variational Quantum Neural Networks (VQNNS) in Image Classification

Quantum machine learning has established as an interdisciplinary field to overcome limitations of classical machine learning and neural networks. This is a field of research which can prove that quantum computers are able to solve problems with complex correlations between inputs that can be hard for classical computers. This suggests that learning models made on quantum computers may be more powerful for applications, potentially faster computation and better generalization on less data. The objective of this paper is to investigate how training of quantum neural network (QNNs) can be done using quantum optimization algorithms for improving the performance and time complexity of QNNs. A classical neural network can be partially quantized to create a hybrid quantum-classical neural network which is used mainly in classification and image recognition. In this paper, a QNN structure is made where a variational parameterized circuit is incorporated as an input layer named as Variational Quantum Neural Network (VQNNs). We encode the cost function of QNNs onto relative phases of a superposition state in the Hilbert space of the network parameters. The parameters are tuned with an iterative quantum approximate optimisation (QAOA) mixer and problem hamiltonians. VQNNs is experimented with MNIST digit recognition (less complex) and crack image classification datasets (more complex) which converges the computation in lesser time than QNN with decent training accuracy

Microbial Water Quality Modelling of the Detroit River to assess the source water quality in drinking water treatment plants of Windsor and Amherstburg

Detroit River is an important part of the Great Lakes system that connects Lake St. Clair with Lake Erie. Studying microbial water quality of the Detroit will certainly contribute to the improvement of Great Lakes water quality. So this study fits in the grand challenge “Safeguarding Healthy Great Lakes”. In this study, a coupled hydrodynamic and microbial water quality model of the Detroit River has been developed. The three-dimensional hydrodynamic simulation was performed with TUFLOW-FV tool by using bathymetry, flow, water level and forcing data. The simulated model output was compared with the field observed data and the performance parameters were also calculated. The coefficient of determination, R2 values for the water level, flow and temperature were calculated 0.91, 0.6 and 0.7 respectively which shows satisfactory functionality of the model. The microbial module named Aquatic-Eco-dynamics was then coupled with the verified hydrodynamic model for microbial simulation. The hydrodynamic model provides velocity distribution of the entire system that being used in microbial module to simulate the fate and transport of E. coli with the consideration of decay rates and other ecological factors. Results show that the loadings from Little River and bypass from Little River wastewater treatment plant affect the microbial water quality of the Windsor Water Treatment Plant (WWTP). This model also simulated the impact of Canard River loadings in the Amherstburg Water Treatment Plant (AWTP) microbial water quality. This functional model can be used for supporting drinking water treatment and implementing water resources management decisions

Uncertainty analysis of a spatially-distributed hydrological model with rainfall multipliers

This paper has developed an input error model to account for input uncertainty, and applied the rainfall multiplier approaches to the calibration and uncertainty analysis of Soil and Water Assessment Tool (SWAT), a spatially-distributed hydrological model. The developed input error model has introduced the season-dependent rainfall multipliers to the Bayesian framework and reduced the dimension of the posterior probability density function. The method is applied to a watershed located in Southwestern Ontario, Canada. The results of the developed method are compared with two other methods. The SWAT model parameters and the input error model parameters are jointly inferred by a Markov chain Monte Carlo sampler. The results show the measured precipitation data overestimates the true precipitation values for the study area. The uncertainty in model prediction is underestimated for high flows and overestimated for low flows. There is no significant change in the estimation of parameter uncertainty and streamflow prediction uncertainty in the developed method from those in the other methods. The study emphasizes that the rainfall multiplier approaches are applicable to spatially-distributed hydrological modelling for accounting of input uncertainty.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Examination of Blockage Effects on the Progression of Local Scour around a Circular Cylinder

An evaluation of scour estimation methods has indicated that the effects of blockage ratio are neglected in both scour modelling and development of new predictive methods. The role of channel blockage on the mechanism and progression of local scour is not well understood, and further analysis is required in order to incorporate this effect into scour estimation. In the present investigation, local scour experiments were carried out under varying blockage ratio. The results were compared with data from literature in order to explore the effects of blockage ratio (D/b, where D is the pier diameter, and b is the channel width) on equilibrium scour depth (dse/D, where dse is the depth of scour at equilibrium). It was determined that D/b had a small influence on both dse/D and the progression of scour depth (ds/D) when relative coarseness D/d50 < 100 (where d50 is the median diameter of sediment), and that the influence appeared to be amplified when D/d50 > 100. The efficacy of scour estimation methods used to predict the progression of local scour was also dependent on D/d50. A method of scour estimation used to predict dse/D was evaluated, and it was similarly found to be particularly effective when D/d50 < 100. In future work, further experiments and analysis in the range of D/d50 > 100 are required in order to establish the role of D/b under prototype conditions and to refine existing scour estimation methods

EVALUATION OF GOVERNING PARAMETERS ON PIER SCOUR GEOMETRY

Current scour estimation methods typically over-predict scour, resulting in uneconomical design. This tendency is partly due to the complexity of the scouring process, which indicates that some of its aspects are still not well understood, and can also be attributed to scale effects. Here, experiments are conducted to isolate the influence of relative coarseness (D/d50) and flow shallowness (h/D) on scour depth. For the range of D/d50 in the present study, equilibrium scour depth (dse/D) decreases with increasing D/d50 until a limiting value of D/d50 = 175, after which dse/D â 0.75. Furthermore, dse/D is found to depend on h/D when all other scour influencing parameters are held constant. A revised definition of the densimetric Froude number (Fd) using the velocity along the separating streamline (Us) is shown to have an influential role in scour. An improved scour estimation method employing these parameters is presented and compared with current methods.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Climate model bias correction for nonstationary conditions

In most of the climate change impacts assessment studies, climate model bias is considered to be stationary between the control and scenario periods. A Few methods are found in the literature that addresses the issue of nonstationarity in correcting the bias. To overcome the shortcomings reported in these approaches, three new methods of bias correction (NBC_μ, NBC_σ, and NBC_bs) are presented. The methods are improvised versions of previous techniques relying on distribution mapping. The methods are tested using split sample approach over 50-year historical period for nine climate stations in Ontario, using six regional climate models. The average bias reduction improvement (BRI) by new methods, in mean daily and monthly precipitation, was found to be 73.9%, 74.3%, and 77.4%, respectively, higher than that obtained by the previous methods (eQM 67.7% and CNCDFm_NP 64.1%). Thus, the methods are found to be more effective in accounting for nonstationarity in the model bias.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Experimental and analytical investigation on pipe sizes for a coaxial borehole heat exchanger

This paper investigates the use of a vertical coaxial borehole heat exchanger (BHE), focusing on those consisting of standard geothermal piping material, as a component in a ground-source heat pump system. The results of a lab-scale experiment are used to verify the trends exhibited by a recent semi-analytical model, referred to as the composite coaxial (CCx) model, considering short-term behavior when laminar flow is experienced in the annular space of a coaxial heat exchanger. The discussion on pipe sizes is then expanded upon using the suggested model along with a modified design procedure to compare the performances realized by an example heat pump. A comparison is made here between configurations having various nominal inner pipe diameters while maintaining the same outer pipe. The results of the analysis show that increasing the inner pipe diameter, within the verified limit of the composite coaxial model, will reduce the required length of heat exchanger and increase the overall coefficient of performance realized by the heat pump

Short-term fluid temperature variations in either a coaxial or U-tube borehole heat exchanger

This paper uses composite cylindrical heat-source (CCS) models and typical thermal response test procedures to investigate two full-scale borehole heat exchangers (BHE); where one is a U-tube BHE, and the other, a pipe-in-pipe (coaxial) BHE. A previously developed CCS model is compared to a simplified infinite line-source (ILS) model. A time-varying heat-flux term is verified for the U-tube case, noting the error found when using the CCS model. A model is developed using a similar approach accounting for a coaxial configuration showing a root mean square error (RMSE) of less than 0.1 °C over the duration of the test

Heat transfer in a U-Bend pipe: Dean number versus Reynolds number

The performance of ground source and surface water heat pumps relies greatly on the heat transfer efficiency throughout the ground loop configuration. Typically these are vertical loops and consist of two pipes connected by a U-Bend at the bottom end. The U-Bend section generates vortical structures and turbulence, enhancing the heat transfer process. Two parameters that affect the flow turbulence and vortical structures are the Reynolds number and the Dean number. The isolated effects of the Reynolds and the Dean number are studied. It was found that while the Reynolds number has the greater effect on the average heat flux of the system; the Dean number\u27s influence on the heat flux is greater in the curved section of the pipe. The large vortex structures can last for many diameters downstream of the U-Bend. For the high Reynolds number flow it was shown that increasing the Dean number significantly enhances the longevity of vortex structures. This indicates that enhancing the Dean number in an already turbulent flow will further augment the heat transfer process