:  The structural state of sewer systems is often quantified using condition classes. The classes are based on the severity of structural defects observed on individual pipes within the system. Here, a survival analysis model was developed to predict the overall structural state of a sewer network based on camera inspection data from a sample of pipes in the system. The convolution product was used to define the survival functions for cumulative staying times in each condition class. An original calibration procedure for the sewer deterioration model was developed to overcome the censored nature of data (left censored and right censored) available for the calibration of sewer deterioration models. The exponential and Weibull functions were used to represent the distribution of waiting times in each deterioration state. Cross‐validation tests showed that the Weibull function led to greater uncertainty than the exponential function for the simulated proportion of pipes that are in a deteriorated state. Using various sample sizes for model calibration, these cross‐validation tests also showed that the model's results are robust to smaller calibration sample sizes. This confirms the model's potential for predicting the overall state of deterioration of a sewer network when only a small proportion of the pipes have been inspected.

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This paper aims to shed further light on the viscous reconnection phenomenon. To this end, we propose a robust and efficient method in order to quantify the degree of reconnection of two vortex tubes. This method is used to compare the evolutions of two simple initial vortex configurations: orthogonal and antiparallel. For the antiparallel configuration, the proposed method is compared with alternative estimators and it is found to improve accuracy since it can account properly for the formation of looping structures inside the domain. This observation being new, the physical mechanism for the formation of those looping structures is discussed. For the orthogonal configuration, we report results from simulations that were performed at a much higher vortex Reynolds number (ReΓ ≡ circulation/viscosity = 104) and finer resolution (N3 = 10243) than previously presented in the literature. The incompressible Navier-stokes equations are solved directly (Direct Numerical Simulation or DNS) using a Fourier pseudospectral algorithm with triply periodic boundary conditions. The associated zero-circulation constraint is circumvented by solving the governing equations in a proper rotating frame of reference. Using ideas similar to those behind our method to compute the degree of reconnection, we split the vorticity field into its reconnected and non-reconnected parts, which allows to create insightful visualizations of the evolving vortex topology. It also allows to detect regions in the vorticity field that are neither reconnected nor non-reconnected and thus must be associated to internal looping structures. Finally, the Reynolds number dependence of the reconnection time scale Trec is investigated in the range 500 ≤ ReΓ ≤ 10 000. For both initial configurations, the scaling is generally found to vary continuously as ReΓ is increased from Trec∼ReΓ−1 to Trec∼ReΓ−1/2, thus providing quantitative support for previous claims that the reconnection physics of two vortices should be similar regardless of their spatial arrangement.

Implementing multicomponent diffusion models in reacting-flow simulations is computationally expensive due to the challenges involved in calculating diffusion coefficients. Instead, mixture-averaged diffusion treatments are typically used to avoid these costs. However, to our knowledge, the accuracy and appropriateness of the mixture-averaged diffusion models has not been verified for three-dimensional turbulent premixed flames. In this study we propose a fast, efficient, low-memory algorithm and use that to evaluate the role of multicomponent mass diffusion in reacting-flow simulations. Direct numerical simulation of these flames is performed by implementing the Stefan-Maxwell equations in NGA. A semi-implicit algorithm decreases the computational expense of inverting the full multicomponent ordinary diffusion array while maintaining accuracy and fidelity. We demonstrate the algorithm to be stable, and its performance scales approximately with the number of species squared. We first verify the method by performing one-dimensional simulations of premixed hydrogen flames and compare with matching cases in Cantera. As an initial study of multicomponent diffusion, we simulate premixed, three-dimensional turbulent hydrogen flames, neglecting secondary Soret and Dufour effects. Simulation conditions are carefully selected to match previously published results and ensure valid comparison. Our results show that using the mixture-averaged diffusion assumption lead to a 15 % under-prediction of the normalized turbulent flame speed for premixed hydrogen air flames. This large difference in the turbulent flame speed raises questions on the appropriateness of using the mixture-averaged diffusion assumption for DNS of moderate to high Karlovitz number flames.

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