Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Constructal Design of Energy Systems

This dissertation shows the use of Constructal law to find the relation between the morphing of the system configuration and the improvements in the global performance of the complex flow system. It shows that the better features of both flow and heat transfer architecture can be found and predicted by using the constructal law in energy systems. Chapter 2 shows the effect of flow configuration on the heat transfer performance of a spiral shaped pipe embedded in a cylindrical conducting volume. Several configurations were considered. The optimal spacings between the spiral turns and spire planes exist, such that the volumetric heat transfer rate is maximal. The optimized features of the heat transfer architecture are robust. Chapter 3 shows the heat transfer performance of a helically shaped pipe embedded in a cylindrical conducting volume. It shows that the optimized features of the heat transfer architecture are robust with respect to changes in several physical parameters. Chapter 4 reports analytically the formulas for effective permeability in several configurations of fissured systems, using the closed-form description of tree networks designed to provide flow access. The permeability formulas do not vary much from one tree design to the next, suggesting that similar formulas may apply to naturally fissured porous media with unknown precise details, which occur in natural reservoirs. Chapter 5 illustrates a counterflow heat exchanger consists of two plenums with a core. The results show that the overall flow and thermal resistance are lowest when the core is absent. Overall, the constructal design governs the evolution of flow configuration in nature and energy systems.

Design of Latent Thermal Energy Storage Systems

This dissertation documents the results of a theoretical and numerical study of time dependent storage of energy by melting a phase change material. The heating is provided along invading lines, which change from single-line invasion to tree-shaped invasion. Chapter 2 identifies the special design feature of distributing energy storage in time-dependent fashion on a territory, when the energy flows by fluid flow from a concentrated source to points (users) distributed equidistantly on the area. The challenge in this chapter is to determine the architecture of distributed energy storage. The chief conclusion is that the finite amount of storage material should be distributed proportionally with the distribution of the flow rate of heating agent arriving on the area. The total time needed by the source stream to ‘invade’ the area is cumulative (the sum of the storage times required at each storage site), and depends on the energy distribution paths and the sequence in which the users are served by the source stream. Chapter 3 shows theoretically that the melting process consists of two phases: “invasion” thermal diffusion along the invading line, which is followed by “consolidation” as heat diffuses perpendicularly to the invading line. This chapter also reports the duration of both phases and the evolution of the melt layer around the invading line during the two-dimensional and three-dimensional invasion. It also shows that the amount of melted material increases in time according to a curve shaped as an S. These theoretical predictions are validated by means of numerical simulations in chapter 4. This chapter also shows that the heat transfer rate density increases (i.e., the S curve becomes steeper) as the complexity and number of degrees of freedom of the structure are increased, in accord with the constructal law. The optimal geometric features of the tree structure are detailed in this chapter. Chapter 5 documents a numerical study of time-dependent melting where the heat transfer is convection dominated, unlike in chapter 3 and 4 where the melting is ruled by pure conduction. In accord with constructal design, the search is for effective heat-flow architectures. The volume-constrained improvement of the designs for heat flow begins with assuming the simplest structure, where a single line serves as heat source. Next, the heat source is endowed with freedom to change its shape as it grows. The objective of the numerical simulations is to discover the geometric features that lead to the fastest melting process. The results show that the heat transfer rate density increases as the complexity and number of degrees of freedom of the structure are increased. Furthermore, the angles between heat invasion lines have a minor effect on the global performance compared to other degrees of freedom: number of branching levels, stem length, and branch lengths. The effect of natural convection in the melt zone is documented.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.

Conditional moment closure for chemical reactions in laminar chaotic flows

We implement conditional moment closure (CMC) for simulation of chemical reactions in laminar chaotic flows. The CMC approach predicts the expected concentration of reactive species, conditional upon the concentration of a corresponding nonreactive scalar. Closure is obtained by neglecting the difference between the local concentration of the reactive scalar and its conditional average. We first use a Monte Carlo method to calculate the evolution of the moments of a conserved scalar; we then reconstruct the corresponding probability density function and dissipation rate. Finally, the concentrations of the reactive scalars are determined. The results are compared (and show excellent agreement) with full numerical simulations of the reaction processes in a chaotic laminar flow. This is a preprint of an article published in AlChE Journal copyright (2007) American Institute of Chemical Engineers: http://www3.interscience.wiley.com/

Thermal Tracking and Estimation for Microprocessors

Due to increasing integration density and operating frequency of today's high performance processors, the temperature of a typical chip can easily exceed 100 degrees Celsius. However, the runtime thermal state of a chip is very hard to predict and manage due to the random nature in computing workloads, as well as the process, voltage and ambient temperature variability (together called PVT variability). The uneven nature (both in time and space) of the heat dissipation of the chip could lead to severe reliability issues and error-prone chip behavior (e.g. timing errors). Many dynamic power/thermal management techniques have been proposed to address this issue such as dynamic voltage and frequency scaling (DVFS), clock gating and etc. However, most of such techniques require accurate knowledge of the runtime thermal state of the chip to make efficient and effective control decisions. In this work we address the problem of tracking and managing the temperature of microprocessors which include the following sub-problems: (1) how to design an efficient sensor-based thermal tracking system on a given design that could provide accurate real-time temperature feedback; (2) what statistical techniques could be used to estimate the full-chip thermal profile based on very limited (and possibly noise-corrupted) sensor observations; (3) how do we adapt to changes in the underlying system's behavior, since such changes could impact the accuracy of our thermal estimation. The thermal tracking methodology proposed in this work is enabled by on-chip sensors which are already implemented in many modern processors. We first investigate the underlying relationship between heat distribution and power consumption, then we introduce an accurate thermal model for the chip system. Based on this model, we characterize the temperature correlation that exists among different chip modules and explore statistical approaches (such as those based on Kalman filter) that could utilize such correlation to estimate the accurate chip-level thermal profiles in real time. Such estimation is performed based on limited sensor information because sensors are usually resource constrained and noise-corrupted. We also took a further step to extend the standard Kalman filter approach to account for (1) nonlinear effects such as leakage-temperature interdependency and (2) varying statistical characteristics in the underlying system model. The proposed thermal tracking infrastructure and estimation algorithms could consistently generate accurate thermal estimates even when the system is switching among workloads that have very distinct characteristics. Through experiments, our approaches have demonstrated promising results with much higher accuracy compared to existing approaches. Such results can be used to ensure thermal reliability and improve the effectiveness of dynamic thermal management techniques.

COMPREHENSIVE ELECTRICAL/OPTICAL/THERMAL CHARACTERIZATIONS OF HIGH POWER LIGHT EMITTING DIODES AND LASER DIODES

Thermal characterizations of high power light emitting diodes (LEDs) and laser diodes (LDs) are one of the most critical issues to achieve optimal performance such as center wavelength, spectrum, power efficiency, and reliability. Unique electrical/optical/thermal characterizations are proposed to analyze the complex thermal issues of high power LEDs and LDs. First, an advanced inverse approach, based on the transient junction temperature behavior, is proposed and implemented to quantify the resistance of the die-attach thermal interface (DTI) in high power LEDs. A hybrid analytical/numerical model is utilized to determine an approximate transient junction temperature behavior, which is governed predominantly by the resistance of the DTI. Then, an accurate value of the resistance of the DTI is determined inversely from the experimental data over the predetermined transient time domain using numerical modeling. Secondly, the effect of junction temperature on heat dissipation of high power LEDs is investigated. The theoretical aspect of junction temperature dependency of two major parameters – the forward voltage and the radiant flux – on heat dissipation is reviewed. Actual measurements of the heat dissipation over a wide range of junction temperatures are followed to quantify the effect of the parameters using commercially available LEDs. An empirical model of heat dissipation is proposed for applications in practice. Finally, a hybrid experimental/numerical method is proposed to predict the junction temperature distribution of a high power LD bar. A commercial water-cooled LD bar is used to present the proposed method. A unique experimental setup is developed and implemented to measure the average junction temperatures of the LD bar. After measuring the heat dissipation of the LD bar, the effective heat transfer coefficient of the cooling system is determined inversely. The characterized properties are used to predict the junction temperature distribution over the LD bar under high operating currents. The results are presented in conjunction with the wall-plug efficiency and the center wavelength shift.

Fire analysis of car park building structures

The thermal loading of an open car park building structure is going to be analysed, based on different fire scenarios that depend on the type of vehicle (different heat release rate). The compartment is going to be fixed and the thermal effect on beams is going to be analysed, depending on the vehicle position. The result of simple calculation method will be used to determine several temperature-time curves. The simple calculation method (Hasemi method) is also to be compared with the calculations of the Elefir-EN calculation program to analyse the thermal effect of the localized fire on beams.

Pesticide bioconcentration modelling for fruit trees.

The model presented allows simulating the pesticide concentration in fruit trees and estimating the pesticide bioconcentration factor in fruits of woody species. The model allows estimating the pesticide uptake by plants through the water transpiration stream and also the time in which maximum pesticide concentration occur in the fruits. The equation proposed presents the relationships between bioconcentration factor (BCF) and the following variables: plant water transpiration volume (Q), pesticide transpiration stream concentration factor (TSCF), pesticide stem-water partition coefficient (KWood,w), stem dry biomass (M) and pesticide dissipation rate in the soil-plant system (kEGS). The modeling started and was developed from a previous model ?Fruit Tree Model? (FTM), reported by Trapp and collaborators in 2003, to which was added the hypothesis that the pesticide degradation in the soil follows a first order kinetic equation. The model fitness was evaluated through the sensitivity analysis of the pesticide BCF values in fruits with respect to the model entry data variability.

Assessing canopy temperature patterns in two grapevine varieties subjected to deficit irrigation: a tool to optimize water management ?

A better understanding of grapevine responses to drought and high air temperatures can help to optimize vineyard management to improve water use efficiency, yield and berry quality. Faster and robust field phenotyping tools are needed in modern precision viticulture, in particular in dry and hot regions such as the Mediterranean. Canopy temperature (Tc) is commonly used to monitor water stress in plants/crops and to characterize stomatal physiology in different woody species including Vitis vinifera. Thermography permits remote determination of leaf surface or canopy temperature in the field and also to assess the range and spatial distribution of temperature from different parts of the canopies. Our hypothesis is that grapevine genotypes may show different Tc patterns along the day due to different stomatal behaviour and heat dissipation strategies. We have monitored the diurnal and seasonal course of Tc in two grapevine genotypes, Aragonez (syn. Tempranillo) and Touriga Nacional subjected to deficit irrigation under typical Mediterranean climate conditions. Temperature measurements were complemented by determination of the diurnal course of leaf water potential (ψleaf) and leaf gas exchange. Measurements were done in two seasons (2013 and 2014) at different phenological stages: i) mid-June (green berry stage), ii) mid-July (veraison), iii) early August (early ripening) and iv) before harvest (late ripening). Correlations between Tc and minimal stomatal conductance will be presented for the two genotypes along the day. Results are discussed over the use of thermal imagery to derive information on genotype physiology in response to changing environmental conditions and to mild water stress induced by deficit irrigation. Strategies to optimize the use of thermal imaging in field conditions are also proposed

MODELING OF TRANSFER PATH FOR DETERMINATION OF COMBUSTION AND NOISE METRICS ON DIESEL ENGINES

Determination of combustion metrics for a diesel engine has the potential of providing feedback for closed-loop combustion phasing control to meet current and upcoming emission and fuel consumption regulations. This thesis focused on the estimation of combustion metrics including start of combustion (SOC), crank angle location of 50% cumulative heat release (CA50), peak pressure crank angle location (PPCL), and peak pressure amplitude (PPA), peak apparent heat release rate crank angle location (PACL), mean absolute pressure error (MAPE), and peak apparent heat release rate amplitude (PAA). In-cylinder pressure has been used in the laboratory as the primary mechanism for characterization of combustion rates and more recently in-cylinder pressure has been used in series production vehicles for feedback control. However, the intrusive measurement with the in-cylinder pressure sensor is expensive and requires special mounting process and engine structure modification. As an alternative method, this work investigated block mounted accelerometers to estimate combustion metrics in a 9L I6 diesel engine. So the transfer path between the accelerometer signal and the in-cylinder pressure signal needs to be modeled. Depending on the transfer path, the in-cylinder pressure signal and the combustion metrics can be accurately estimated - recovered from accelerometer signals. The method and applicability for determining the transfer path is critical in utilizing an accelerometer(s) for feedback. Single-input single-output (SISO) frequency response function (FRF) is the most common transfer path model; however, it is shown here to have low robustness for varying engine operating conditions. This thesis examines mechanisms to improve the robustness of FRF for combustion metrics estimation. First, an adaptation process based on the particle swarm optimization algorithm was developed and added to the single-input single-output model. Second, a multiple-input single-output (MISO) FRF model coupled with principal component analysis and an offset compensation process was investigated and applied. Improvement of the FRF robustness was achieved based on these two approaches. Furthermore a neural network as a nonlinear model of the transfer path between the accelerometer signal and the apparent heat release rate was also investigated. Transfer path between the acoustical emissions and the in-cylinder pressure signal was also investigated in this dissertation on a high pressure common rail (HPCR) 1.9L TDI diesel engine. The acoustical emissions are an important factor in the powertrain development process. In this part of the research a transfer path was developed between the two and then used to predict the engine noise level with the measured in-cylinder pressure as the input. Three methods for transfer path modeling were applied and the method based on the cepstral smoothing technique led to the most accurate results with averaged estimation errors of 2 dBA and a root mean square error of 1.5dBA. Finally, a linear model for engine noise level estimation was proposed with the in-cylinder pressure signal and the engine speed as components.

The creation and evaluation of novel canine training aids for cocaine using molecularly encapsulated sol-gel polymers and an investigation of canine field accuracy

Biological detectors, such as canines, are valuable tools used for the rapid identification of illicit materials. However, recent increased scrutiny over the reliability, field accuracy, and the capabilities of each detection canine is currently being evaluated in the legal system. For example, the Supreme Court case, State of Florida v. Harris, discussed the need for continuous monitoring of canine abilities, thresholds, and search capabilities. As a result, the fallibility of canines for detection was brought to light, as well as a need for further research and understanding of canine detection. This study is two-fold, as it looks to not only create new training aids for canines that can be manipulated for dissipation control, but also investigates canine field accuracy to objects with similar odors to illicit materials. ^ It was the goal of this research to improve upon current canine training aid mimics. Sol-gel polymer training aids, imprinted with the active odor of cocaine, were developed. This novel training aid improved upon the longevity of currently existing training aids, while also provided a way to manipulate the polymer network to alter the dissipation rate of the imprinted active odors. The manipulation of the polymer network could allow handlers to control the abundance of odors presented to their canines, familiarizing themselves to their canine’s capabilities and thresholds, thereby increasing the canines’ strength in court.^ The field accuracy of detection canines was recently called into question during the Supreme Court case, State of Florida v. Jardines, where it was argued that if cocaine’s active odor, methyl benzoate, was found to be produced by the popular landscaping flower, snapdragons, canines will false alert to said flowers. Therefore, snapdragon flowers were grown and tested both in the laboratory and in the field to determine the odors produced by snapdragon flowers; the persistence of these odors once flowers have been cut; and whether detection canines will alert to both growing and cut flowers during a blind search scenario. Results revealed that although methyl benzoate is produced by snapdragon flowers, certified narcotics detection canines can distinguish cocaine’s odor profile from that of snapdragon flowers and will not alert.^

Mixing theory for culture and harvest in bioreactors of human mesenchymal stem cells on microcarriers

The use of human mesenchymal stem cells (hMSCs) in regenerative medicine is a potential major advance for the treatment of many medical conditions, especially with the use of allogeneic therapies where the cells from a single donor can be used to treat ailments in many patients. Such cells must be grown attached to surfaces and for large scale production, it is shown that stirred bioreactors containing ~200 μm particles (microcarriers) can provide such a surface. It is also shown that the just suspended condition, agitator speed NJS, provides a satisfactory condition for cell growth by minimizing the specific energy dissipation rate, εT, in the bioreactor whilst still meeting the oxygen demand of the cells. For the cells to be used for therapeutic purposes, they must be detached from the microcarriers before being cryopreserved. A strategy based on a short period (~7 min) of very high εT, based on theories of secondary nucleation, is effective at removing >99% cells. Once removed, the cells are smaller than the Kolmogorov scale of turbulence and hence not damaged. This approach is shown to be successful for culture and detachment in 4 types of stirred bioreactors from 15 mL to 5 L.