Validation of a new automatic smoking machine to study the effects of cigarette smoke in newborn lambs

The aim of this study was to describe the characteristics and validate the use of a new, custom-built automatic smoking machine (ASM), primarily designed to study the effects of an environmental tobacco smoke surrogate (ETS surrogate) exposure in animals of various sizes, including large animals. The equipment includes a programmable ASM coupled to a vented whole body chamber, where animals can be exposed to both mainstream and sidestream smoke. The user-friendly interface allows for full programming of puff volume (1-60 mL), time interval between two puffs (1-60 s) and between two cigarettes (1-60 min). Eight newborn lambs were exposed to either 10 (4 lambs, C10 group) or 20 (4 lambs, C20 group) cigarettes, 8 h per day for 15 days. Four additional control, lambs were exposed to air (C0 group). Weight gain was identical in all three groups of lambs. Urinary cotinine/creatinine ratio increased with the number of cigarettes smoked (C0: 11 ± 7 ng/mg; C10: 961 ± 539 ng/mg; C20: 1821 ± 312 ng/mg), with levels in the C10 and C20 groups in keeping with values published in infants exposed to ETS. Overall, results show that our new ASM is especially well suited for ETS surrogate exposure in non-restrained, non-anaesthetized large animals such as sheep

Dynamic simulation of ground source heat pump systems with nonstationary convolutions

Advective processes related to groundwater motion and flow rates have a significant impact on the thermal performance of ground source heat pump systems. Including these elements during the design phase, however, remains a challenging task, as few computationally efficient modeling tools allow for their adequate and accurate representation. The present work addresses this issue by presenting the experimental validation of non-stationary convolutions for predicting the thermal response of a ground heat exchanger to both transient heat loads and advection. First, the method is outlined along with a simple demonstration case emulating the time-variation of groundwater velocity. Then, it is validated against experimental data retrieved from a 35-day multi-flow rate thermal response test conducted on a real standing column well. The results show a mean absolute error of 0.28 °C between the experimental and simulated results, which represents good accuracy considering the complexity of the thermo-hydro-processes at work. The high computing efficiency of the proposed technique is also demonstrated and suggests its potential for future implementation in common-use design tools

Outdoor classes in higher education during the context of COVID-19 in Canada: Guide to support management during the first phases of implementation

Ressources éducatives libresOpen educational resourcesAbstract: The goal of this document is to allow the management of higher education establishments to view the first steps that Sherbrooke University has taken during the implementation of outdoor classes in the context of the Covid-19 pandemic, and to benefit from this experience. A pedagogical guide will be developed before the beginning of the 2020-2021 school year in order to allow institutions to maximize the potential of these spaces

Hydrogeothermal characterization and modelling of a standing column well experimental installation

Standing column wells (SCW) are efficient ground heat exchangers that offer promising potential for integration in dense urban areas. Recent years have witnessed a growing interest in SCWs, resulting in the development of various simulation models incorporating heat transfer, groundwater flow and geochemical reactions within the well and the surrounding ground. However, these models commonly use a configuration that involves pumping at the bottom of the well and reinjection from its top, which can lead to installation and maintenance difficulties in deep wells. Furthermore, very few SCW models have been validated against reliable field data. This paper presents an original finite element model coupling advection-diffusion of heat and groundwater flow within a top pumped SCW and its surrounding ground as well as the experimental setup used for its validation. Within the scope of this study, experimental data obtained after an extensive field characterization campaign and a thermal response test performed with a large-scale geothermal laboratory were used directly as inputs in the numerical model. Experimental validation shows that without any calibration procedure, the model reproduces the experimental inlet and outlet groundwater temperatures with a mean absolute error of 0.14 °C. It is also shown that the placement of the pump at the top of the well offers a more practical design that has minor impact on the thermal performance of the system

Forecasting hydraulic head changes in injection wells using LSTM network

Monitoring of well's specific capacity is commonly used to plan maintenance of injection wells in open-loop GSHP and standing column well systems. However, this method does not consider the effect of temperature on hydraulic conductivity. A first step towards an alternative approach that does include the effect of temperature is proposed in this work. We present a long short-term memory network capable of predicting the water level in the injection well of an operating GSHP system. The methodology consists of building a training set using a numerical model. A total of 500 simulations were conducted to evaluate hydraulic head signals under various inlet temperatures and flow rates along with hydraulic and thermal parameters drawn from a uniform distribution. Predictive performance of the artificial neural network is tested on an operational data set. The resulting RMSE between the forecasted and operational data set is 14.8 cm

Stationary and non-stationary deconvolution to recover long-term transfer functions

To design a ground heat exchanger, simulations are frequently used. One way to perform simulations is to use the well-known g-functions to obtain the ground temperature. These functions are usually obtained by analytical or numerical models, which limits the precision or takes long simulation time. Recent advances show that the short-term g-functions can also be retrieved by a deconvolution algorithm. However, the known deconvolution algorithm is only validated for a set of operating parameters and duration of less than 10 days. A first objective of this article is to demonstrate that longer g-functions can be retrieved with such an algorithm. Then, a second objective is to extend the application of the deconvolution to consider time varying operating parameters throughout a ground heat exchanger's operation. To achieve those objectives, the deconvolution will be first applied to various numerical year-long simulations of a ground source heat pump system with stationary conditions. Then, an extended multi-signal deconvolution will be applied to a non-stationary thermal response test of 30 days. Both tests show adequate temperature reconstruction with RMSE of less than 0.05 °C and 0.2 °C for the first and second scenarios respectively

Classes extérieures dans l’enseignement supérieur en contexte de COVID-19 au Canada : guide pour appuyer les directions lors des premières étapes d’implantation

Ressources éducatives libresOpen educational resourcesCe guide vise à permettre aux directions d’établissements d’enseignement supérieur de prendre connaissance des premières étapes vécues à l’Université de Sherbrooke lors de l’implantation de classes extérieures dans le contexte de la COVID-19 et de bénéficier de cette expérience. Un guide pédagogique sera développé avant la rentrée scolaire 2020-2021 afin de permettre aux personnes formatrices de maximiser le potentiel de ces milieux