Dynamic Modeling and Seasonal Performance Evaluation of Air-to-Water Heat Pump Systems

In this Thesis a series of numerical models for the evaluation of the seasonal performance of reversible air-to-water heat pump systems coupled to residential and non-residential buildings are presented. The exploitation of the energy saving potential linked to the adoption of heat pumps is a hard task for designers due to the influence on their energy performance of several factors, like the external climate variability, the heat pump modulation capacity, the system control strategy and the hydronic loop configuration. The aim of this work is to study in detail all these aspects. In the first part of this Thesis a series of models which use a temperature class approach for the prediction of the seasonal performance of reversible air source heat pumps are shown. An innovative methodology for the calculation of the seasonal performance of an air-to-water heat pump has been proposed as an extension of the procedure reported by the European standard EN 14825. This methodology can be applied not only to air-to-water single-stage heat pumps (On-off HPs) but also to multi-stage (MSHPs) and inverter-driven units (IDHPs). In the second part, dynamic simulation has been used with the aim to optimize the control systems of the heat pump and of the HVAC plant. A series of dynamic models, developed by means of TRNSYS, are presented to study the behavior of On-off HPs, MSHPs and IDHPs. The main goal of these dynamic simulations is to show the influence of the heat pump control strategies and of the lay-out of the hydronic loop used to couple the heat pump to the emitters on the seasonal performance of the system. A particular focus is given to the modeling of the energy losses linked to on-off cycling.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Numerical modeling and experimental validation of the recrystallization behaviour in the extrusion of 6XXX aluminum alloys

The microstructure of 6XXX aluminum alloys deeply affects mechanical, crash, corrosion and aesthetic properties of extruded profiles. Unfortunately, grain structure evolution during manufacturing processes is a complex phenomenon because several process and material parameters such as alloy chemical composition, temperature, extrusion speed, tools geometries, quenching and thermal treatment parameters affect the grain evolution during the manufacturing process. The aim of the present PhD thesis was the analysis of the recrystallization kinetics during the hot extrusion of 6XXX aluminum alloys and the development of reliable recrystallization models to be used in FEM codes for the microstructure prediction at a die design stage. Experimental activities have been carried out in order to acquire data for the recrystallization models development, validation and also to investigate the effect of process parameters and die design on the microstructure of the final component. The experimental campaign reported in this thesis involved the extrusion of AA6063, AA6060 and AA6082 profiles with different process parameters in order to provide a reliable amount of data for the models validation. A particular focus was made to investigate the PCG defect evolution during the extrusion of medium-strength alloys such as AA6082. Several die designs and process conditions were analysed in order to understand the influence of each of them on the recrystallization behaviour of the investigated alloy. From the numerical point of view, innovative models for the microstructure prediction were developed and validated over the extrusion of industrial-scale profiles with complex geometries, showing a good matching in terms of the grain size and surface recrystallization prediction. The achieved results suggest the reliability of the developed models and their application in the industrial field for process and material properties optimization at a die-design stage.

Data assimilation for advanced cross-scale unstructured-grid ocean modeling.

The coastal ocean is a complex environment with extremely dynamic processes that require a high-resolution and cross-scale modeling approach in which all hydrodynamic fields and scales are considered integral parts of the overall system. In the last decade, unstructured-grid models have been used to advance in seamless modeling between scales. On the other hand, the data assimilation methodologies to improve the unstructured-grid models in the coastal seas have been developed only recently and need significant advancements. Here, we link the unstructured-grid ocean modeling to the variational data assimilation methods. In particular, we show results from the modeling system SANIFS based on SHYFEM fully-baroclinic unstructured-grid model interfaced with OceanVar, a state-of-art variational data assimilation scheme adopted for several systems based on a structured grid. OceanVar implements a 3DVar DA scheme. The combination of three linear operators models the background error covariance matrix. The vertical part is represented using multivariate EOFs for temperature, salinity, and sea level anomaly. The horizontal part is assumed to be Gaussian isotropic and is modeled using a first-order recursive filter algorithm designed for structured and regular grids. Here we introduced a novel recursive filter algorithm for unstructured grids. A local hydrostatic adjustment scheme models the rapidly evolving part of the background error covariance. We designed two data assimilation experiments using SANIFS implementation interfaced with OceanVar over the period 2017-2018, one with only temperature and salinity assimilation by Argo profiles and the second also including sea level anomaly. The results showed a successful implementation of the approach and the added value of the assimilation for the active tracer fields. While looking at the broad basin, no significant improvements are highlighted for the sea level, requiring future investigations. Furthermore, a Machine Learning methodology based on an LSTM network has been used to predict the model SST increments.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

Kinetic modeling for the synthesis of ethyl levulinate

This work is focused on studying the kinetics of esterification of levulinic acid in an isothermal batch reactor using ethanol as a reactant and as a protic polar solvent at the same time and in the presence of an acid catalyst (sulfuric acid). The choice of solvent is important as it affects the kinetics and thermodynamics of the reaction system moreover, the knowledge of the reaction kinetics plays an important role in the design of the process. This work is divided into two stages; The first stage is the experimental part in which the experimental matrix was developed by changing the process variables one at a time (temperature, molar ratio between reactants, and catalyst concentration) in order to study their influence on the kinetics; the second stage is using the obtained data from the experiments to build the modeling part in order to estimate the thermodynamics parameters.

Lifetime Modeling of SiC Power Modules in Automotive Traction Inverters

This thesis presents a model-based software implementation for the estimation of the damage of a power module inside and automotive traction inverter with few hardware test setup performed to support the simulation with real-life data.

The Crystal-t Algorithm: A New Approach To Calculate The Sle Of Lipidic Mixtures Presenting Solid Solutions.

Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.

Graded Meshes In Bio-thermal Problems With Transmission-line Modeling Method.

In this study, the transmission-line modeling (TLM) applied to bio-thermal problems was improved by incorporating several novel computational techniques, which include application of graded meshes which resulted in 9 times faster in computational time and uses only a fraction (16%) of the computational resources used by regular meshes in analyzing heat flow through heterogeneous media. Graded meshes, unlike regular meshes, allow heat sources to be modeled in all segments of the mesh. A new boundary condition that considers thermal properties and thus resulting in a more realistic modeling of complex problems is introduced. Also, a new way of calculating an error parameter is introduced. The calculated temperatures between nodes were compared against the results obtained from the literature and agreed within less than 1% difference. It is reasonable, therefore, to conclude that the improved TLM model described herein has great potential in heat transfer of biological systems.

Variability Modeling Of Rainfall, Deforestation, And Incidence Of American Tegumentary Leishmaniasis In Orán, Argentina, 1985-2007.

American tegumentary leishmaniasis (ATL) is a disease transmitted to humans by the female sandflies of the genus Lutzomyia. Several factors are involved in the disease transmission cycle. In this work only rainfall and deforestation were considered to assess the variability in the incidence of ATL. In order to reach this goal, monthly recorded data of the incidence of ATL in Orán, Salta, Argentina, were used, in the period 1985-2007. The square root of the relative incidence of ATL and the corresponding variance were formulated as time series, and these data were smoothed by moving averages of 12 and 24 months, respectively. The same procedure was applied to the rainfall data. Typical months, which are April, August, and December, were found and allowed us to describe the dynamical behavior of ATL outbreaks. These results were tested at 95% confidence level. We concluded that the variability of rainfall would not be enough to justify the epidemic outbreaks of ATL in the period 1997-2000, but it consistently explains the situation observed in the years 2002 and 2004. Deforestation activities occurred in this region could explain epidemic peaks observed in both years and also during the entire time of observation except in 2005-2007.

Storage At Low Temperature Differentially Affects The Colour And Carotenoid Composition Of Two Cultivars Of Banana.

Different storage conditions can induce changes in the colour and carotenoid profiles and levels in some fruits. The goal of this work was to evaluate the influence of low temperature storage on the colour and carotenoid synthesis in two banana cultivars: Prata and Nanicão. For this purpose, the carotenoids from the banana pulp were determined by HPLC-DAD-MS/MS, and the colour of the banana skin was determined by a colorimeter method. Ten carotenoids were identified, of which the major carotenoids were all-trans-lutein, all-trans-α-carotene and all-trans-β-carotene in both cultivars. The effect of the low temperatures was subjected to linear regression analysis. In cv. Prata, all-trans-α-carotene and all-trans-β-carotene were significantly affected by low temperature (p<0.01), with negative estimated values (β coefficients) indicating that during cold storage conditions, the concentrations of these carotenoids tended to decrease. In cv. Nanicão, no carotenoid was significantly affected by cold storage (p>0.05). The accumulation of carotenoids in this group may be because the metabolic pathways using these carotenoids were affected by storage at low temperatures. The colour of the fruits was not negatively affected by the low temperatures (p>0.05).

Modelos estatísticos indicadores de comportamentos associados a bem-estar térmico para matrizes pesadas

The study of female broiler breeders is of great importance for the country as poultry production is one of the largest export items, and Brazil is the second largest broiler meat exporter. Animal behavior is known as a response to the effect of several interaction factors among them the environment. In this way the internal housing environment is an element that gives hints regarding to the bird s thermal comfort. Female broiler breeder behavior, expresses in form of specific pattern the bird s health and welfare. This research had the objective of applying predictive statistical models through the use of simulation, presenting animal comfort scenarios facing distinct environmental conditions. The research was developed with data collected in a controlled environment using Hybro - PG® breeding submitted to distinct levels of temperature, three distinct types of standard ration and age. Descriptive and exploratory analysis were proceeded, and afterwards the modeling process using the Generalized Estimation Equation (GEE). The research allowed the development of the thermal comfort indicators by statistical model equations of predicting female broiler breeder behavior under distinct studied scenarios.

Rootstocks induce contrasting photosynthetic responses of orange plants to low night temperature without affecting the antioxidant metabolism

Low temperatures negatively impact the metabolism of orange trees, and the extent of damage can be influenced by the rootstock. We evaluated the effects of low nocturnal temperatures on Valencia orange scions grafted on Rangpur lime or Swingle citrumelo rootstocks. We exposed six-month-old plants to night temperatures of 20ºC and 8ºC under controlled conditions. After decreasing the temperature to 8ºC, there were decreases in leaf CO2 assimilation, stomatal conductance, mesophyll conductance and CO2 concentration in the chloroplasts, in plant hydraulic conductivity and in the maximum electron transport rate driven ribulose-1,5-bisphosphate (RuBP) regeneration in plants grafted on both rootstocks. However, the effects of low night temperature were more severe in plants grafted on Rangpur rootstock, which also presented reduction in the maximum rate of RuBP carboxylation and in the maximum quantum efficiency of the PSII. In general, irreversible damage due to night chilling was found in the photosynthetic apparatus of plants grafted on Rangpur lime. Low night temperatures induced similar changes in the antioxidant metabolism, preventing oxidative damage in citrus leaves on both rootstocks. As photosynthesis is linked to plant growth, our findings indicate that the rootstock may improve the performance of citrus trees in environments with low night temperatures, with Swingle rootstock improving the photosynthetic acclimation in leaves of orange plants.

In vitro study of the pulp chamber temperature rise during light-activated bleaching

This study evaluated in vitro the pulp chamber temperature rise induced by the light-activated dental bleaching technique using different light sources. The root portions of 78 extracted sound human mandibular incisors were sectioned approximately 2 mm below the cementoenamel junction. The root cavities of the crowns were enlarged to facilitate the correct placing of the sensor into the pulp chamber. Half of specimens (n=39) was assigned to receive a 35% hydrogen peroxide gel on the buccal surface and the other halt (n=39) not to receive the bleaching agent. Three groups (n=13) were formed for each condition (bleach or no bleach) according to the use of 3 light sources recommended for dental bleaching: a light-emitting diode (LED)laser system, a LED unit and a conventional halogen light. The light sources were positioned perpendicular to the buccal surface at a distance of 5 mm and activated during 30 s. The differences between the initial and the highest temperature readings for each specimen were obtained, and, from the temperature changes, the means for each specimen and each group were calculated. The values of temperature rise were compared using Kruskal-Wallis test at 1% significance level. Temperature rise varied significantly depending on the light-curing unit, with statistically significant differences (p<0.01) among the groups. When the bleaching agent was not applied, the halogen light induced the highest temperature rise (2.38±0.66ºC). The LED unit produced the lowest temperature increase (0.29±0.13ºC); but there was no significant difference between LED unit and LED-laser system (0.35±0.15ºC) (p>0.01). When the bleaching agent was applied, there were significant differences among groups (p<0.01): halogen light induced the highest temperature rise (1.41±0.64ºC), and LED-laser system the lowest (0.33±0.12ºC); however, there was no difference between LED-laser system and LED unit (0.44±0.11ºC). LED and LED-laser system did not differ significantly from each other regardless the temperature rise occurred with or without bleaching agent application. It may be concluded that during light-activated tooth bleaching, with or without the bleaching agent, halogen light promoted higher pulp chamber temperature rise than LED unit and LED-laser system. The tested light-curing units provided increases in the pulp chamber temperature that were compatible with pulpal health.

Intrapupal temperature variation during Er,Cr: YSGG enamel irradiation on carries prevention

Studies have shown the cariostatic effect of Er,Cr:YSGG (2.78 mm) laser irradiation on human enamel and have suggested its use on caries prevention. However there are still no reports on the intrapulpal temperature increase during enamel irradiation using parameters for caries prevention. The aim of this in vitro study was to evaluate the temperature variation in the pulp chamber during human enamel irradiation with Er,Cr:YSGG laser at different energy densities. Fifteen enamel blocks obtained from third molars (3 x 3 x 3 mm) were randomly assigned to 3 groups (n=5): G1 - Er,Cr:YSGG laser 0.25 W, 20 Hz, 2.84 J/cm², G2 - Er,Cr:YSGG laser 0.50 W, 20 Hz, 5.68 J/cm², G3 - Er,Cr:YSGG laser 0.75 W, 20 Hz, 8.52 J/cm². During enamel irradiation, two thermocouples were fixed in the inner surface of the specimens and a thermal conducting paste was used. One-way ANOVA did not show statistically significant difference among the experimental groups (a=0.05). There was intrapulpal temperature variation <0.1ºC for all irradiation parameters. In conclusion, under the tested conditions, the use of Er,Cr:YSGG laser with parameters set for caries prevention lead to an acceptable temperature increase in the pulp chamber.